A systematic approach to vertebral hemangioma.

PubMed

Gaudino, Simona; Martucci, Matia; Colantonio, Raffaella; Lozupone, Emilio; Visconti, Emiliano; Leone, Antonio; Colosimo, Cesare

2015-01-01

Vertebral hemangiomas (VHs) are a frequent and often incidental finding on computed tomography (CT) and magnetic resonance (MR) imaging of the spine. When their imaging appearance is "typical" (coarsened vertical trabeculae on radiographic and CT images, hyperintensity on T1- and T2-weighted MR images), the radiological diagnosis is straightforward. Nonetheless, VHs might also display an "atypical" appearance on MR imaging because of their histological features (amount of fat, vessels, and interstitial edema). Although the majority of VHs are asymptomatic and quiescent lesions, they can exhibit active behaviors, including growing quickly, extending beyond the vertebral body, and invading the paravertebral and/or epidural space with possible compression of the spinal cord and/or nerve roots ("aggressive" VHs). These "atypical" and "aggressive" VHs are a radiological challenge since they can mimic primary bony malignancies or metastases. CT plays a central role in the workup of atypical VHs, being the most appropriate imaging modality to highlight the polka-dot appearance that is representative of them. When aggressive VHs are suspected, both CT and MR are needed. MR is the best imaging modality to characterize the epidural and/or soft-tissue component, helping in the differential diagnosis. Angiography is a useful imaging adjunct for evaluating and even treating aggressive VHs. The primary objectives of this review article are to summarize the clinical, pathological, and imaging features of VHs, as well as the treatment options, and to provide a practical guide for the differential diagnosis, focusing on the rationale assessment of the findings from radiography, CT, and MR imaging.

CT and MR imaging features in phosphaturic mesenchymal tumor-mixed connective tissue: A case report

PubMed Central

Shi, Zhenshan; Deng, Yiqiong; Li, Xiumei; Li, Yueming; Cao, Dairong; Coossa, Vikash Sahadeo

2018-01-01

Phosphaturic mesenchymal tumor-mixed connective tissue (PMT-MCT) is rare and usually benign and slow-growing. The majority of these tumors is associated with sporadic tumor-induced osteomalacia (TIO) or rickets, affect middle-aged individuals and are located in the extremities. Previous imaging studies often focused on seeking the causative tumors of TIO, not on the radiological features of these tumors, especially magnetic resonance imaging (MRI) features. PMT-MCT remains a largely misdiagnosed, ignored or unknown entity by most radiologists and clinicians. In the present case report, a review of the known literature of PMT-MCT was conducted and the CT and MRI findings from three patient cases were described for diagnosing the small subcutaneous tumor. Typical MRI appearances of PMT-MCT were isointense relative to the muscles on T1-weighted imaging, and markedly hyperintense on T2-weighted imaging containing variably flow voids, with markedly heterogeneous/homogenous enhancement on post contrast T1-weighted fat-suppression imaging. Short time inversion recovery was demonstrated to be the optimal sequence in localizing the tumor. PMID:29552133

CT and MR imaging features in phosphaturic mesenchymal tumor-mixed connective tissue: A case report.

PubMed

Shi, Zhenshan; Deng, Yiqiong; Li, Xiumei; Li, Yueming; Cao, Dairong; Coossa, Vikash Sahadeo

2018-04-01

Phosphaturic mesenchymal tumor-mixed connective tissue (PMT-MCT) is rare and usually benign and slow-growing. The majority of these tumors is associated with sporadic tumor-induced osteomalacia (TIO) or rickets, affect middle-aged individuals and are located in the extremities. Previous imaging studies often focused on seeking the causative tumors of TIO, not on the radiological features of these tumors, especially magnetic resonance imaging (MRI) features. PMT-MCT remains a largely misdiagnosed, ignored or unknown entity by most radiologists and clinicians. In the present case report, a review of the known literature of PMT-MCT was conducted and the CT and MRI findings from three patient cases were described for diagnosing the small subcutaneous tumor. Typical MRI appearances of PMT-MCT were isointense relative to the muscles on T1-weighted imaging, and markedly hyperintense on T2-weighted imaging containing variably flow voids, with markedly heterogeneous/homogenous enhancement on post contrast T1-weighted fat-suppression imaging. Short time inversion recovery was demonstrated to be the optimal sequence in localizing the tumor.

[Destructive mastoiditis with thrombosis of the sigmoid sinus in a 8 year-old child presenting with concomitant chicken pox].

PubMed

Bogomil'skiĭ, M R; Polunin, M M; Ivanenko, A M; Poliakov, A A

2014-01-01

The specific clinical feature of mastoidities that developed in a patient presenting with chicken pox was the rapid progress in temporal bone destruction with partial thrombosis of the sigmoid sinusis in the absence of typical manifestations of mastoiditis. The pronounced destructive changes found in a series of CT images were regarded as the indications for urgent antromastoidotomy with the puncture of the sigmoid sinusis.

Dual Tracer PET Imaging (68Ga-DOTATATE and 18F-FDG) Features in Pulmonary Carcinoid: Correlation with Tumor Proliferation Index.

PubMed

Bhatkar, Dhiraj; Utpat, Ketaki; Basu, Sandip; Joshi, Jyotsna M

2017-01-01

Pulmonary carcinoid tumors are rare group of lung neoplasms representing 1% of all the lung tumors. The typical bronchial carcinoids showed higher and more selective uptake of 68 Ga-DOTATATE than of 18 F-FDG on PET-CT. The Ki-67(MIB-1), a tumor proliferation index is a prognostic marker in neuroendocrine tumors for estimating tumor progression. Atypical carcinoids have higher Ki-67 index and have an increased propensity to metastasize as compared to typical ones. 68 Ga-DOTATATE PET imaging along with Ki-67 can be correlated for better management of patients with neuroendocrine tumors. We describe the dual tracer imaging features in a patient of pulmonary carcinoid with avid 68 Ga-DOTATATE and minimal 18 FDG ( 18 Flurodeoxyglucose) uptake diagnosed on the basis of imaging and bronchoscopic biopsy and its correlation with tumor proliferation index.

Comparison of CT enterography and MR enterography imaging features of active Crohn disease in children and adolescents.

PubMed

Gale, Heather I; Sharatz, Steven M; Taphey, Mayureewan; Bradley, William F; Nimkin, Katherine; Gee, Michael S

2017-09-01

Assessment for active Crohn disease by CT enterography and MR enterography relies on identifying mural and perienteric imaging features. To evaluate the performance of established imaging features of active Crohn disease in children and adolescents on CT and MR enterography compared with histological reference. We included patients ages 18 years and younger who underwent either CT or MR enterography from 2007 to 2014 and had endoscopic biopsy within 28 days of imaging. Two pediatric radiologists blinded to the histological results reviewed imaging studies and scored the bowel for the presence or absence of mural features (wall thickening >3 mm, mural hyperenhancement) and perienteric features (mesenteric hypervascularity, edema, fibrofatty proliferation and lymphadenopathy) of active disease. We performed univariate analysis and multivariate logistic regression to compare imaging features with histological reference. We evaluated 452 bowel segments (135 from CT enterography, 317 from MR enterography) from 84 patients. Mural imaging features had the highest association with active inflammation both for MR enterography (wall thickening had 80% accuracy, 69% sensitivity and 91% specificity; mural hyperenhancement had 78%, 53% and 96%, respectively) and CT enterography (wall thickening had 84% accuracy, 72% sensitivity and 91% specificity; mural hyperenhancement had 76%, 51% and 91%, respectively), with perienteric imaging features performing significantly worse on MR enterography relative to CT enterography (P < 0.001). Mural features are predictors of active inflammation for both CT and MR enterography, while perienteric features can be distinguished better on CT enterography compared with MR enterography. This likely reflects the increased conspicuity of the mesentery on CT enterography and suggests that mural features are the most reliable imaging features of active Crohn disease in children and adolescents.

Flexible wire-shaped strain sensor from cotton thread for human health and motion detection.

PubMed

Li, Yuan-Qing; Huang, Pei; Zhu, Wei-Bin; Fu, Shao-Yun; Hu, Ning; Liao, Kin

2017-03-21

In this work, a wire-shaped flexible strain sensor was fabricated by encapsulating conductive carbon thread (CT) with polydimethylsiloxane (PDMS) elastomer. The key strain sensitive material, CT, was prepared by pyrolysing cotton thread in N 2 atmosphere. The CT/PDMS composite wire shows a typical piezo-resistive behavior with high strain sensitivity. The gauge factors (GF) calculated at low strain of 0-4% and high strain of 8-10% are 8.7 and 18.5, respectively, which are much higher than that of the traditional metallic strain sensor (GF around 2). The wire-shaped CT/PDMS composite sensor shows excellent response to cyclic tensile loading within the strain range of 0-10%, the frequency range of 0.01-10 Hz, to up to 2000 cycles. The potential of the wire senor as wearable strain sensor is demonstrated by the finger motion and blood pulse monitoring. Featured by the low costs of cotton wire and PDMS resin, the simple structure and fabrication technique, as well as high performance with miniaturized size, the wire-shaped sensor based on CT/PDMS composite is believed to have a great potential for application in wearable electronics for human health and motion monitoring.

The use of postmortem computed tomography in the diagnosis of intentional medication overdose.

PubMed

Burke, Michael P; O'Donnell, Chris; Bassed, Richard

2012-09-01

The recognition of a well defined basal layer of radio dense material on the postmortem computed tomography (CT) images, in the setting of typical scene findings of an intentional medication overdose and unremarkable external examination of the deceased's body can, in certain circumstances, permit such cases to be managed without routine full autopsy examination. Preliminary toxicological analysis can be targeted to such cases to provide further supportive evidence of intentional medication overdose. In cases where the scene findings are ambiguous or have been contaminated the postmortem CT images may alert the pathologist of the possibility of overdose in an otherwise apparently natural death. We reviewed 61 cases of documented intentional therapeutic medication overdose and 61 control cases. In the majority of the cases of confirmed intentional therapeutic medication overdose the CT images showed no diagnostic features. However, in many cases a well defined basal layer of radio-opaque material was clearly seen to line the gastric mucosa. The postmortem CT pattern which we believe to be highly suggestive of intentional medication overdose must be differentiated from other causes of increased radio density in the stomach which include CT artefacts.

The MECP2 variant c.925C>T (p.Arg309Trp) causes intellectual disability in both males and females without classic features of Rett syndrome.

PubMed

Schönewolf-Greulich, B; Tejada, M-I; Stephens, K; Hadzsiev, K; Gauthier, J; Brøndum-Nielsen, K; Pfundt, R; Ravn, K; Maortua, H; Gener, B; Martínez-Bouzas, C; Piton, A; Rouleau, G; Clayton-Smith, J; Kleefstra, T; Bisgaard, A-M; Tümer, Z

2016-06-01

Missense MECP2 variants can have various phenotypic effects ranging from a normal phenotype to typical Rett syndrome (RTT). In females, the phenotype can also be influenced by the X-inactivation pattern. In this study, we present detailed clinical descriptions of six patients with a rare base-pair substitution affecting Arg309 at the C-terminal end of the transcriptional repression domain (TRD). All patients have intellectual disability and present with some RTT features, but they do not fulfill the clinical criteria for typical or atypical RTT. Most of the patients also have mild facial dysmorphism. Intriguingly, the mother of an affected male patient is an asymptomatic carrier of this variant. It is therefore likely that the p.(Arg309Trp) variation does not necessarily lead to male lethality, and it results in a wide range of clinical features in females, probably influenced by different X-inactivation patterns in target tissues. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Computed tomographic features of canine nonparenchymal hemangiosarcoma.

PubMed

Fukuda, Shoko; Kobayashi, Tetsuya; Robertson, Ian D; Oshima, Fukiko; Fukazawa, Eri; Nakano, Yuko; Ono, Shin; Thrall, Donald E

2014-01-01

The purpose of this retrospective study was to describe pre- and postcontrast computed tomographic (CT) characteristics of confirmed nonparenchymal hemangiosarcoma in a group of dogs. Medical records were searched during the period of July 2003 and October 2011 and dogs with histologically confirmed nonparenchymal hemangiosarcoma and pre- and postcontrast CT images were recruited. Two observers recorded a consensus opinion for the following CT characteristics for each dog: largest transverse tumor diameter, number of masses, general tumor shape, character of the tumor margin, precontrast appearance, presence of dystrophic calcification, presence of postcontrast enhancement, pattern of postcontrast enhancement, presence of regional lymphadenopathy, and presence of associated cavitary fluid. A total of 17 dogs met inclusion criteria. Tumors were located in the nasal cavity, muscle, mandible, mesentery, subcutaneous tissue, and retroperitoneal space. Computed tomographic features of nonparenchymal hemangiosarcoma were similar to those of other soft tissue sarcomas, with most tumors being heterogeneous in precontrast images, invasive into adjacent tissue, and heterogeneously contrast enhancing. One unexpected finding was the presence of intense foci of contrast enhancement in 13 of the 17 tumors (76%). This appearance, which is not typical of other soft tissue sarcomas, was consistent with contrast medium residing in vascular channels. Findings indicated that there were no unique distinguishing CT characteristics for nonparenchymal hemangiosarcoma in dogs; however, the presence of highly attenuating foci of contrast enhancement may warrant further investigation in prospective diagnostic sensitivity and treatment outcome studies. © 2014 American College of Veterinary Radiology.

CT texture features of liver parenchyma for predicting development of metastatic disease and overall survival in patients with colorectal cancer.

PubMed

Lee, Scott J; Zea, Ryan; Kim, David H; Lubner, Meghan G; Deming, Dustin A; Pickhardt, Perry J

2018-04-01

To determine if identifiable hepatic textural features are present at abdominal CT in patients with colorectal cancer (CRC) prior to the development of CT-detectable hepatic metastases. Four filtration-histogram texture features (standard deviation, skewness, entropy and kurtosis) were extracted from the liver parenchyma on portal venous phase CT images at staging and post-treatment surveillance. Surveillance scans corresponded to the last scan prior to the development of CT-detectable CRC liver metastases in 29 patients (median time interval, 6 months), and these were compared with interval-matched surveillance scans in 60 CRC patients who did not develop liver metastases. Predictive models of liver metastasis-free survival and overall survival were built using regularised Cox proportional hazards regression. Texture features did not significantly differ between cases and controls. For Cox models using all features as predictors, all coefficients were shrunk to zero, suggesting no association between any CT texture features and outcomes. Prognostic indices derived from entropy features at surveillance CT incorrectly classified patients into risk groups for future liver metastases (p < 0.001). On surveillance CT scans immediately prior to the development of CRC liver metastases, we found no evidence suggesting that changes in identifiable hepatic texture features were predictive of their development. • No correlation between liver texture features and metastasis-free survival was observed. • Liver texture features incorrectly classified patients into risk groups for liver metastases. • Standardised texture analysis workflows need to be developed to improve research reproducibility.

Systematic Review and Meta-Analysis of CT Features for Differentiating Complicated and Uncomplicated Appendicitis.

PubMed

Kim, Hae Young; Park, Ji Hoon; Lee, Yoon Jin; Lee, Sung Soo; Jeon, Jong-June; Lee, Kyoung Ho

2018-04-01

Purpose To perform a systematic review and meta-analysis to identify computed tomographic (CT) features for differentiating complicated appendicitis in patients suspected of having appendicitis and to summarize their diagnostic accuracy. Materials and Methods Studies on diagnostic accuracy of CT features for differentiating complicated appendicitis (perforated or gangrenous appendicitis) in patients suspected of having appendicitis were searched in Ovid-MEDLINE, EMBASE, and the Cochrane Library. Overlapping descriptors used in different studies to denote the same image finding were subsumed under a single CT feature. Pooled diagnostic accuracy of the CT features was calculated by using a bivariate random effects model. CT features with pooled diagnostic odds ratios with 95% confidence intervals not including 1 were considered as informative. Results Twenty-three studies were included, and 184 overlapping descriptors for various CT findings were subsumed under 14 features. Of these, 10 features were informative for complicated appendicitis. There was a general tendency for these features to show relatively high specificity but low sensitivity. Extraluminal appendicolith, abscess, appendiceal wall enhancement defect, extraluminal air, ileus, periappendiceal fluid collection, ascites, intraluminal air, and intraluminal appendicolith showed pooled specificity greater than 70% (range, 74%-100%), but sensitivity was limited (range, 14%-59%). Periappendiceal fat stranding was the only feature that showed high sensitivity (94%; 95% confidence interval: 86%, 98%) but low specificity (40%; 95% confidence interval, 23%, 60%). Conclusion Ten informative CT features for differentiating complicated appendicitis were identified in this study, nine of which showed high specificity, but low sensitivity. © RSNA, 2017 Online supplemental material is available for this article.

Testosterone-secreting adrenal adenoma in a peripubertal girl

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kamilaris, T.C.; DeBold, C.R.; Manolas, K.J.

1987-11-13

A 15-year-old girl who presented with primary amenorrhea and virilization had an adrenocortical adenoma that secreted predominantly testosterone. To the authors' knowledge, she is the first peripubertal and second youngest patient with a testosterone-secreting adrenal tumor described. Serum dehydroepiandrosterone sulfate and urinary 17-ketosteroid an 17-hydroxycorticosteroid levels were normal. A tumor was located by a computed tomographic (CT) scan and by uptake of 6-..beta..-(/sup 75/Se) selenomethylnorcholesterol. Microscopic examination of the tumor showed typical features of an adrenocortical adenoma with no histologic features characteristic of Leydig cells. Postoperatively, her hirsutism regressed, she rapidly went through puberty, and regular monthly menstruation started fourmore » months later. Finding the source of testosterone in a virilized patient can be difficult. Eleven of the 14 previously described patients with testosterone-secreting adrenal tumors initially underwent misdirected surgery on the ovaries. Review of these cases revealed that results of hormone stimulation and suppression tests are unreliable and that these tumors are usually large. Therefore, CT scanning of the adrenal glands is recommended in all patients suspected of having a testosterone-secreting tumor.« less

Mapping the stability of human brain asymmetry across five sex-chromosome aneuploidies.

PubMed

Lin, Amy; Clasen, Liv; Lee, Nancy Raitano; Wallace, Gregory L; Lalonde, Francois; Blumenthal, Jonathan; Giedd, Jay N; Raznahan, Armin

2015-01-07

The human brain displays stereotyped and early emerging patterns of cortical asymmetry in health. It is unclear if these asymmetries are highly sensitive to genetic and environmental variation or fundamental features of the brain that can survive severe developmental perturbations. To address this question, we mapped cortical thickness (CT) asymmetry in a group of genetically defined disorders known to impact CT development. Participants included 137 youth with one of five sex-chromosome aneuploidies [SCAs; XXX (n = 28), XXY (n = 58), XYY (n = 26), XXYY (n = 20), and XXXXY (n = 5)], and 169 age-matched typically developing controls (80 female). In controls, we replicated previously reported rightward inferior frontal and leftward lateral parietal CT asymmetry. These opposing frontoparietal CT asymmetries were broadly preserved in all five SCA groups. However, we also detected foci of shifting CT asymmetry with aneuploidy, which fell almost exclusively within regions of significant CT asymmetry in controls. Specifically, X-chromosome aneuploidy accentuated normative rightward inferior frontal asymmetries, while Y-chromosome aneuploidy reversed normative rightward medial prefrontal and lateral temporal asymmetries. These findings indicate that (1) the stereotyped normative pattern of opposing frontoparietal CT asymmetry arises from developmental mechanisms that can withstand gross chromosomal aneuploidy and (2) X and Y chromosomes can exert focal, nonoverlapping and directionally opposed influences on CT asymmetry within cortical regions of significant asymmetry in health. Our study attests to the resilience of developmental mechanisms that support the global patterning of CT asymmetry in humans, and motivates future research into the molecular bases and functional consequences of sex chromosome dosage effects on CT asymmetry. Copyright © 2015 the authors 0270-6474/15/350140-06$15.00/0.

Vertebral metastases from neuroendocrine tumours: How to avoid false positives on 68Ga-DOTA-TOC PET using CT pattern analysis?

PubMed

Gauthé, Mathieu; Testart Dardel, Nathalie; Ruiz Santiago, Fernando; Ohnona, Jessica; Nataf, Valérie; Montravers, Françoise; Talbot, Jean-Noël

2018-03-12

To develop criteria to improve discrimination between vertebral metastases from neuroendocrine tumours (NETs) and benign bone lesions on PET combined with CT using DOTA-D-Phe 1 -Tyr 3 -octreotide labelled with gallium-68 ( 68 Ga-DOTA-TOC). In 535 NET patients, 68 Ga-DOTA-TOC PET/CT examinations were reviewed retrospectively for vertebral CT lesions and/or PET foci. For each vertebral PET abnormality, appearance on CT, biological volume (BV), standardized uptake value (SUV max ) and ratios to those of reference organs were determined. All vertebral abnormalities were characterized as a metastasis, a typical vertebral haemangioma (VH) or other benign lesion. In 79 patients (14.8 %), we found 107 metastases, 34 VHs and 31 other benign lesions in the spine. The optimal cut-off values to differentiate metastases from benign lesions were BV ≥0.72 cm 3 , SUVmax ≥2, SUVmax ratio to a reference vertebra ≥2.1, to liver ≥0.28 and to spleen ≥0.14. They corresponded to lesion-based 68 Ga-DOTA-TOC PET/CT sensitivity of 87 %, 98 %, 97 %, 99 % and 94 %, and specificity of 55 %, 100 %, 90 %, 97 %, 100 %, respectively. The high sensitivity of 68 Ga-DOTA-TOC-PET/CT in detecting NET vertebral metastases was confirmed; this study showed that specificity could be improved by combining CT features and quantifying 68 Ga-DOTA-TOC uptake. • Bone metastases in neuroendocrine tumours correlate with prognosis. • Benign bone lesions may mimic metastases on 68 Ga-DOTA-TOC PET/CT imaging. • The specific polka-dot CT pattern may be missing in some vertebral haemangiomas. • Lesion atypical for haemangiomas can be better characterized by quantifying 68 Ga-DOTA-TOC uptake.

Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients

NASA Astrophysics Data System (ADS)

Mu, Wei; Qi, Jin; Lu, Hong; Schabath, Matthew; Balagurunathan, Yoganand; Tunali, Ilke; Gillies, Robert James

2018-02-01

Purpose: Investigate the ability of using complementary information provided by the fusion of PET/CT images to predict immunotherapy response in non-small cell lung cancer (NSCLC) patients. Materials and methods: We collected 64 patients diagnosed with primary NSCLC treated with anti PD-1 checkpoint blockade. Using PET/CT images, fused images were created following multiple methodologies, resulting in up to 7 different images for the tumor region. Quantitative image features were extracted from the primary image (PET/CT) and the fused images, which included 195 from primary images and 1235 features from the fusion images. Three clinical characteristics were also analyzed. We then used support vector machine (SVM) classification models to identify discriminant features that predict immunotherapy response at baseline. Results: A SVM built with 87 fusion features and 13 primary PET/CT features on validation dataset had an accuracy and area under the ROC curve (AUROC) of 87.5% and 0.82, respectively, compared to a model built with 113 original PET/CT features on validation dataset 78.12% and 0.68. Conclusion: The fusion features shows better ability to predict immunotherapy response prediction compared to individual image features.

SU-E-J-265: Feasibility Study of Texture Analysis for Prognosis of Local Tumor Recurrence Within 5-Years for Pharyngeal-Laryngeal Carcinoma Patients Received Radiotherapy Treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, W; Tu, S

Purpose: Pharyngeal and laryngeal carcinomas (PLC) are among the top leading cancers in Asian populations. Typically the tumor may recur and progress in a short period of time if radiotherapy fails to deliver a successful treatment. Here we used image texture features extracted from images of computed tomography (CT) planning and conducted a retrospective study to evaluate whether texture analysis is a feasible approach to predict local tumor recurrence for PLC patients received radiotherapy treatment. Methods: CT planning images of 100 patients with PLC treated by radiotherapy at our facility between 2001 and 2010 are collected. These patients were receivedmore » two separate CT scans, before and mid-course of the treatment delivery. Before the radiotherapy, a CT scanning was used for the first treatment planning. A total of 30 fractions were used in the treatment and patients were scanned with a second CT around the end of the fifteenth delivery for an adaptive treatment planning. Only patients who were treated with intensity modulated radiation therapy and RapidArc were selected. Treatment planning software of Eclipse was used. The changes of texture parameters between two CT acquisitions were computed to determine whether they were correlated to the local tumor recurrence. The following texture parameters were used in the preliminary assessment: mean, variance, standard deviation, skewness, kurtosis, energy, entropy, inverse difference moment, cluster shade, inertia, cluster prominence, gray-level co-occurrence matrix, and gray-level run-length matrix. The study was reviewed and approved by the committee of our institutional review board. Results: Our calculations suggested the following texture parameters were correlated with the local tumor recurrence: skewness, kurtosis, entropy, and inertia (p<0.0.05). Conclusion: The preliminary results were positive. However some works remain crucial to be completed, including addition of texture parameters for different image features, sensitivity of tumor segmentation variations, and effect of image filtering.« less

SU-E-J-270: Repeated 18F-FDG PET/CTs Based Feature Analysis for the Predication of Anal Cancer Recurrence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, J; Chuong, M; Choi, W

Purpose: To identify PET/CT based imaging predictors of anal cancer recurrence and evaluate baseline vs. mid-treatment vs. post-treatment PET/CT scans in the tumor recurrence prediction. Methods: FDG-PET/CT scans were obtained at baseline, during chemoradiotherapy (CRT, midtreatment), and after CRT (post-treatment) in 17 patients of anal cancer. Four patients had tumor recurrence. For each patient, the mid-treatment and post-treatment scans were respectively aligned to the baseline scan by a rigid registration followed by a deformable registration. PET/CT image features were computed within the manually delineated tumor volume of each scan to characterize the intensity histogram, spatial patterns (texture), and shape ofmore » the tumors, as well as the changes of these features resulting from CRT. A total of 335 image features were extracted. An Exact Logistic Regression model was employed to analyze these PET/CT image features in order to identify potential predictors for tumor recurrence. Results: Eleven potential predictors of cancer recurrence were identified with p < 0.10, including five shape features, five statistical texture features, and one CT intensity histogram feature. Six features were indentified from posttreatment scans, 3 from mid-treatment scans, and 2 from baseline scans. These features indicated that there were differences in shape, intensity, and spatial pattern between tumors with and without recurrence. Recurrent tumors tended to have more compact shape (higher roundness and lower elongation) and larger intensity difference between baseline and follow-up scans, compared to non-recurrent tumors. Conclusion: PET/CT based anal cancer recurrence predictors were identified. The post-CRT PET/CT is the most important scan for the prediction of cancer recurrence. The baseline and mid-CRT PET/CT also showed value in the prediction and would be more useful for the predication of tumor recurrence in early stage of CRT. This work was supported in part by the National Cancer Institute Grant R01CA172638.« less

Prognostic Value and Reproducibility of Pretreatment CT Texture Features in Stage III Non-Small Cell Lung Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fried, David V.; Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas; Tucker, Susan L.

2014-11-15

Purpose: To determine whether pretreatment CT texture features can improve patient risk stratification beyond conventional prognostic factors (CPFs) in stage III non-small cell lung cancer (NSCLC). Methods and Materials: We retrospectively reviewed 91 cases with stage III NSCLC treated with definitive chemoradiation therapy. All patients underwent pretreatment diagnostic contrast enhanced computed tomography (CE-CT) followed by 4-dimensional CT (4D-CT) for treatment simulation. We used the average-CT and expiratory (T50-CT) images from the 4D-CT along with the CE-CT for texture extraction. Histogram, gradient, co-occurrence, gray tone difference, and filtration-based techniques were used for texture feature extraction. Penalized Cox regression implementing cross-validation wasmore » used for covariate selection and modeling. Models incorporating texture features from the 33 image types and CPFs were compared to those with models incorporating CPFs alone for overall survival (OS), local-regional control (LRC), and freedom from distant metastases (FFDM). Predictive Kaplan-Meier curves were generated using leave-one-out cross-validation. Patients were stratified based on whether their predicted outcome was above or below the median. Reproducibility of texture features was evaluated using test-retest scans from independent patients and quantified using concordance correlation coefficients (CCC). We compared models incorporating the reproducibility seen on test-retest scans to our original models and determined the classification reproducibility. Results: Models incorporating both texture features and CPFs demonstrated a significant improvement in risk stratification compared to models using CPFs alone for OS (P=.046), LRC (P=.01), and FFDM (P=.005). The average CCCs were 0.89, 0.91, and 0.67 for texture features extracted from the average-CT, T50-CT, and CE-CT, respectively. Incorporating reproducibility within our models yielded 80.4% (±3.7% SD), 78.3% (±4.0% SD), and 78.8% (±3.9% SD) classification reproducibility in terms of OS, LRC, and FFDM, respectively. Conclusions: Pretreatment tumor texture may provide prognostic information beyond that obtained from CPFs. Models incorporating feature reproducibility achieved classification rates of ∼80%. External validation would be required to establish texture as a prognostic factor.« less

SU-E-J-242: Volume-Dependence of Quantitative Imaging Features From CT and CE-CT Images of NSCLC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fave, X; Fried, D; UT Health Science Center Graduate School of Biomedical Sciences, Houston, TX

Purpose: To determine whether tumor volume plays a significant role in the values obtained for texture features when they are extracted from computed tomography (CT) images of non-small cell lung cancer (NSCLC). We also sought to identify whether features can be reliably measured at all volumes or if a minimum volume threshold should be recommended. Methods: Eleven features were measured on 40 CT and 32 contrast-enhanced CT (CECT) patient images for this study. Features were selected for their prognostic/diagnostic value in previous publications. Direct correlations between these textures and volume were evaluated using the Spearman correlation coefficient. Any texture thatmore » the Wilcoxon rank-sum test was used to compare the variation above and below a volume cutoff. Four different volume thresholds (5, 10, 15, and 20 cm{sup 3}) were tested. Results: Four textures were found to be significantly correlated with volume in both the CT and CE-CT images. These were busyness, coarseness, gray-level nonuniformity, and run-length nonuniformity with correlation coefficients of 0.92, −0.96, 0.94, and 0.98 for the CT images and 0.95, −0.97, 0.98, and 0.98 for the CE-CT images. After volume normalization, the correlation coefficients decreased substantially. For the data obtained from the CT images, the results of the Wilcoxon rank-sum test were significant when volume thresholds of 5–15 cm3 were used. No volume threshold was shown to be significant for the CE-CT data. Conclusion: Equations for four features that have been used in several published studies were found to be volume-dependent. Future studies should consider implementing normalization factors or removing these features entirely to prevent this potential source of redundancy or bias. This work was supported in part by National Cancer Institute grant R03CA178495-01. Xenia Fave is a recipient of the American Association of Physicists in Medicine Graduate Fellowship.« less

SU-E-J-260: Quantitative Image Feature Analysis of Multiphase Liver CT for Hepatocellular Carcinoma (HCC) in Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choi, W; Wang, J; Lu, W

Purpose: To identify the effective quantitative image features (radiomics features) for prediction of response, survival, recurrence and metastasis of hepatocellular carcinoma (HCC) in radiotherapy. Methods: Multiphase contrast enhanced liver CT images were acquired in 16 patients with HCC on pre and post radiation therapy (RT). In this study, arterial phase CT images were selected to analyze the effectiveness of image features for the prediction of treatment outcome of HCC to RT. Response evaluated by RECIST criteria, survival, local recurrence (LR), distant metastasis (DM) and liver metastasis (LM) were examined. A radiation oncologist manually delineated the tumor and normal liver onmore » pre and post CT scans, respectively. Quantitative image features were extracted to characterize the intensity distribution (n=8), spatial patterns (texture, n=36), and shape (n=16) of the tumor and liver, respectively. Moreover, differences between pre and post image features were calculated (n=120). A total of 360 features were extracted and then analyzed by unpaired student’s t-test to rank the effectiveness of features for the prediction of response. Results: The five most effective features were selected for prediction of each outcome. Significant predictors for tumor response and survival are changes in tumor shape (Second Major Axes Length, p= 0.002; Eccentricity, p=0.0002), for LR, liver texture (Standard Deviation (SD) of High Grey Level Run Emphasis and SD of Entropy, both p=0.005) on pre and post CT images, for DM, tumor texture (SD of Entropy, p=0.01) on pre CT image and for LM, liver (Mean of Cluster Shade, p=0.004) and tumor texture (SD of Entropy, p=0.006) on pre CT image. Intensity distribution features were not significant (p>0.09). Conclusion: Quantitative CT image features were found to be potential predictors of the five endpoints of HCC in RT. This work was supported in part by the National Cancer Institute Grant R01CA172638.« less

A case report on bronchoalveolar carcinoma presenting as non-resolving consolidation.

PubMed

Shoib, Sheikh; Malik, Javid A; Arif, Tasleem; Bashir, Haamid

2012-08-01

Bronchoalveolar carcinoma presenting as non-resolving consolidation is an uncommon presentation. The typical presentation of bronchoalveolar carcinoma is asymptomatic (solitary nodule) and remains without symptoms even as disease disseminates. We report a case of bronchoalveolar carcinoma presenting as non-resolving consolidation in a young male with productive cough, exertional breathlessness and physical examination revealing the features of right lower consolidation on x-ray chest, with subsequent CT of the chest and bronchoscopic examination revealed bronchoalveolar carcinoma. Patient had a good score and was managed conservatively.

A novel canine model of portal vein stenosis plus thioacetamide administration-induced cirrhotic portal hypertension with hypersplenism.

PubMed

Lin, Dexin; Wu, Xianbin; Ji, Xiaoke; Zhang, Qiyu; Lin, YuanWei; Chen, WeiJian; Jin, Wangxun; Deng, Liming; Chen, Yunzhi; Chen, Bicheng; Li, Jianmin

2012-01-01

Current large animal models that could closely resemble the typical features of cirrhotic portal hypertension in human have not been well established. Thus, we aimed to develop and describe a reliable and reproducible canine cirrhosis model of portal hypertension. A total of 30 mongrel dogs were randomly divided into four groups: 1 (control; n = 5), 2 (portal vein stenosis [PVS]; n = 5], 3 (thioacetamide [TAA]; n = 5), and 4 (PVS plus TAA; n = 15). After 4-months modeling period, liver and spleen CT perfusion, abdominal CT scans, portal hemodynamics, gastroscopy, hepatic function, blood routine, the bone marrow, liver, and spleen histology were studied. The animals in group 2 (PVS) developed extrahepatic portosystemic collateral circulation, particularly esophageal varices, without hepatic cirrhosis and portal hypertension. Animals from group 3 (TAA) presented mild cirrhosis and portal hypertension without significant symptoms of esophageal varices and hypersplenism. In contrast, animals from group 4 (PVS + TAA) showed well-developed micronodular and macronodular cirrhosis, associated with significant portal hypertension and hypersplenism. The combination of PVS and TAA represents a novel, reliable, and reproducible canine cirrhosis model of portal hypertension, which is associated with the typical characteristics of portal hypertension, including hypersplenism.

Traumatic intracranial injury in intoxicated patients with minor head trauma.

PubMed

Easter, Joshua S; Haukoos, Jason S; Claud, Jonathan; Wilbur, Lee; Hagstrom, Michelle Tartalgia; Cantrill, Stephen; Mestek, Michael; Symonds, David; Bakes, Katherine

2013-08-01

Studies focusing on minor head injury in intoxicated patients report disparate prevalences of intracranial injury. It is unclear if the typical factors associated with intracranial injury in published clinical decision rules for computerized tomography (CT) acquisition are helpful in differentiating patients with and without intracranial injuries, as intoxication may obscure particular features of intracranial injury such as headache and mimic other signs of head injury such as altered mental status. This study aimed to estimate the prevalence of intracranial injury following minor head injury (Glasgow Coma Scale [GCS] score ≥14) in intoxicated patients and to assess the performance of established clinical decision rules in this population. This was a prospective cohort study of consecutive intoxicated adults presenting to the emergency department (ED) following minor head injury. Historical and physical examination features included those from the Canadian CT Head Rule, National Emergency X-Radiography Utilization Study (NEXUS), and New Orleans Criteria. All patients underwent head CT. A total of 283 patients were enrolled, with a median age of 40 years (interquartile range [IQR] = 28 to 48 years) and median alcohol concentration of 195 mmol/L (IQR = 154 to 256 mmol/L). A total of 238 of 283 (84%) were male, and 225 (80%) had GCS scores of 15. Clinically important injuries (injuries requiring admission to the hospital or neurosurgical follow-up) were identified in 23 patients (8%; 95% confidence interval [CI] = 5% to 12%); one required neurosurgical intervention (0.4%, 95% CI = 0% to 2%). Loss of consciousness and headache were associated with clinically important intracranial injury on CT. The Canadian CT Head Rule had a sensitivity of 70% (95% CI = 47% to 87%) and NEXUS criteria had a sensitivity of 83% (95% CI = 61% to 95%) for clinically important injury in intoxicated patients. In this study, the prevalence of clinically important injury in intoxicated patients with minor head injury was significant. While the presence of the common features associated with intracranial injury in nonintoxicated patients should raise clinical suspicion for intracranial injury in intoxicated patients, the Canadian CT Head Rule and NEXUS criteria do not have adequate sensitivity to be applied in intoxicated patients with minor head injury. © 2013 by the Society for Academic Emergency Medicine.

Pseudo CT estimation from MRI using patch-based random forest

NASA Astrophysics Data System (ADS)

Yang, Xiaofeng; Lei, Yang; Shu, Hui-Kuo; Rossi, Peter; Mao, Hui; Shim, Hyunsuk; Curran, Walter J.; Liu, Tian

2017-02-01

Recently, MR simulators gain popularity because of unnecessary radiation exposure of CT simulators being used in radiation therapy planning. We propose a method for pseudo CT estimation from MR images based on a patch-based random forest. Patient-specific anatomical features are extracted from the aligned training images and adopted as signatures for each voxel. The most robust and informative features are identified using feature selection to train the random forest. The well-trained random forest is used to predict the pseudo CT of a new patient. This prediction technique was tested with human brain images and the prediction accuracy was assessed using the original CT images. Peak signal-to-noise ratio (PSNR) and feature similarity (FSIM) indexes were used to quantify the differences between the pseudo and original CT images. The experimental results showed the proposed method could accurately generate pseudo CT images from MR images. In summary, we have developed a new pseudo CT prediction method based on patch-based random forest, demonstrated its clinical feasibility, and validated its prediction accuracy. This pseudo CT prediction technique could be a useful tool for MRI-based radiation treatment planning and attenuation correction in a PET/MRI scanner.

Discriminative feature representation: an effective postprocessing solution to low dose CT imaging

NASA Astrophysics Data System (ADS)

Chen, Yang; Liu, Jin; Hu, Yining; Yang, Jian; Shi, Luyao; Shu, Huazhong; Gui, Zhiguo; Coatrieux, Gouenou; Luo, Limin

2017-03-01

This paper proposes a concise and effective approach termed discriminative feature representation (DFR) for low dose computerized tomography (LDCT) image processing, which is currently a challenging problem in medical imaging field. This DFR method assumes LDCT images as the superposition of desirable high dose CT (HDCT) 3D features and undesirable noise-artifact 3D features (the combined term of noise and artifact features induced by low dose scan protocols), and the decomposed HDCT features are used to provide the processed LDCT images with higher quality. The target HDCT features are solved via the DFR algorithm using a featured dictionary composed by atoms representing HDCT features and noise-artifact features. In this study, the featured dictionary is efficiently built using physical phantom images collected from the same CT scanner as the target clinical LDCT images to process. The proposed DFR method also has good robustness in parameter setting for different CT scanner types. This DFR method can be directly applied to process DICOM formatted LDCT images, and has good applicability to current CT systems. Comparative experiments with abdomen LDCT data validate the good performance of the proposed approach. This research was supported by National Natural Science Foundation under grants (81370040, 81530060), the Fundamental Research Funds for the Central Universities, and the Qing Lan Project in Jiangsu Province.

[Tuberculous otomastoiditis: advantage of MRI in the treatment survey].

PubMed

Moya, Plana A; Malinvaud, D; Mimoun, M; Huart, J; Bonfils, P

2008-01-01

Mycobacterium tuberculosis is a rare cause of otomastoiditis, accounting for less than a percent of chronic otitis media. The diagnosis is difficult and typically delayed because most physicians are unfamiliar with its presenting features and special laboratory requirements. Such delayed diagnosis leads to delayed treatment onset, and thus, increases complications frequency as irreversible hearing loss, facial palsy or meningo-encephalitis complications. Moreover non specific CT findings do not allow any accurate evaluation of inner ear lesions initially and under treatment. We described the first case of MRI of tuberculous mastoiditis and the evolution over a 2-years follow-up period. A patient with a clinical history of chronic otorrhea, resistant to conventional therapy, was referred to our department. CT and MRI permitted to describe the initial lesions and to appreciate the medical treatment efficiency (in order to perform surgery in case of failure or complications). Under medical treatment, MRI showed abscess volume decrease at three months while CT was still unchanged. Remineralization only was observed on CT at 12 months. The patient's healing was obtained after 15 months of antituberculous medication. MRI has the advantage over CT to demonstrate directly abscess collections that superimposed to areas of bone destructions within the temporal bone. Initially, MRI allows an accurate evaluation of abscess collections and possible meningo-encephalitis complications. Moreover, MRI precises earlier than CT the improvement of lesions and the efficacy of medical treatment, and thus, permitting us to postpone surgery where it is unnecessary.

Accuracy of computed tomographic features in differentiating intestinal tuberculosis from Crohn's disease: a systematic review with meta-analysis.

PubMed

Kedia, Saurabh; Sharma, Raju; Sreenivas, Vishnubhatla; Madhusudhan, Kumble Seetharama; Sharma, Vishal; Bopanna, Sawan; Pratap Mouli, Venigalla; Dhingra, Rajan; Yadav, Dawesh Prakash; Makharia, Govind; Ahuja, Vineet

2017-04-01

Abdominal computed tomography (CT) can noninvasively image the entire gastrointestinal tract and assess extraintestinal features that are important in differentiating Crohn's disease (CD) and intestinal tuberculosis (ITB). The present meta-analysis pooled the results of all studies on the role of CT abdomen in differentiating between CD and ITB. We searched PubMed and Embase for all publications in English that analyzed the features differentiating between CD and ITB on abdominal CT. The features included comb sign, necrotic lymph nodes, asymmetric bowel wall thickening, skip lesions, fibrofatty proliferation, mural stratification, ileocaecal area, long segment, and left colonic involvements. Sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio (DOR) were calculated for all the features. Symmetric receiver operating characteristic curve was plotted for features present in >3 studies. Heterogeneity and publication bias was assessed and sensitivity analysis was performed by excluding studies that compared features on conventional abdominal CT instead of CT enterography (CTE). We included 6 studies (4 CTE, 1 conventional abdominal CT, and 1 CTE+conventional abdominal CT) involving 417 and 195 patients with CD and ITB, respectively. Necrotic lymph nodes had the highest diagnostic accuracy (sensitivity, 23%; specificity, 100%; DOR, 30.2) for ITB diagnosis, and comb sign (sensitivity, 82%; specificity, 81%; DOR, 21.5) followed by skip lesions (sensitivity, 86%; specificity, 74%; DOR, 16.5) had the highest diagnostic accuracy for CD diagnosis. On sensitivity analysis, the diagnostic accuracy of other features excluding asymmetric bowel wall thickening remained similar. Necrotic lymph nodes and comb sign on abdominal CT had the best diagnostic accuracy in differentiating CD and ITB.

Driving CT developments the last mile: case examples of successful and somewhat less successful translations into clinical practice

NASA Astrophysics Data System (ADS)

Sodickson, Aaron D.

2017-03-01

CT technology has advanced rapidly in recent years, yet not all innovations translate readily into clinical practice. Technology advances must meet certain key requirements to make it into routine use: They must provide a well-defined clinical benefit. They must be easy to use and integrate readily into existing workflows, or better still, further streamline these workflows. These requirements heavily favor fully integrated or automated solutions that remove the human factor and provide a reproducible output independent of operator skill level. Further, to achieve these aims, collaboration with the ultimate end users is needed as early as possible in the development cycle, not just at the point of product testing. Technology innovators are encouraged to engage such collaborators even at early stages of feature or product definition. This manuscript highlights these concepts through exploration of challenging areas in CT imaging in an Emergency Department setting. Technique optimization for pulmonary embolus CT is described as an example of successful integration of multiple advances in radiation dose reduction and imaging speed. The typical workflow of a trauma "pan-scan" (incorporating scans from head through pelvis) is described to highlight workflow challenges and opportunities for improvement. Finally, Dual Energy CT is discussed to highlight the undeniable clinical value of the material characterization it provides, yet also its surprisingly slow integration into routine use beyond early adopters.

SU-F-R-33: Can CT and CBCT Be Used Simultaneously for Radiomics Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, R; Wang, J; Zhong, H

2016-06-15

Purpose: To investigate whether CBCT and CT can be used in radiomics analysis simultaneously. To establish a batch correction method for radiomics in two similar image modalities. Methods: Four sites including rectum, bladder, femoral head and lung were considered as region of interest (ROI) in this study. For each site, 10 treatment planning CT images were collected. And 10 CBCT images which came from same site of same patient were acquired at first radiotherapy fraction. 253 radiomics features, which were selected by our test-retest study at rectum cancer CT (ICC>0.8), were calculated for both CBCT and CT images in MATLAB.more » Simple scaling (z-score) and nonlinear correction methods were applied to the CBCT radiomics features. The Pearson Correlation Coefficient was calculated to analyze the correlation between radiomics features of CT and CBCT images before and after correction. Cluster analysis of mixed data (for each site, 5 CT and 5 CBCT data are randomly selected) was implemented to validate the feasibility to merge radiomics data from CBCT and CT. The consistency of clustering result and site grouping was verified by a chi-square test for different datasets respectively. Results: For simple scaling, 234 of the 253 features have correlation coefficient ρ>0.8 among which 154 features haveρ>0.9 . For radiomics data after nonlinear correction, 240 of the 253 features have ρ>0.8 among which 220 features have ρ>0.9. Cluster analysis of mixed data shows that data of four sites was almost precisely separated for simple scaling(p=1.29 * 10{sup −7}, χ{sup 2} test) and nonlinear correction (p=5.98 * 10{sup −7}, χ{sup 2} test), which is similar to the cluster result of CT data (p=4.52 * 10{sup −8}, χ{sup 2} test). Conclusion: Radiomics data from CBCT can be merged with those from CT by simple scaling or nonlinear correction for radiomics analysis.« less

A New Approach to Automated Labeling of Internal Features of Hardwood Logs Using CT Images

Treesearch

Daniel L. Schmoldt; Pei Li; A. Lynn Abbott

1996-01-01

The feasibility of automatically identifying internal features of hardwood logs using CT imagery has been established previously. Features of primary interest are bark, knots, voids, decay, and clear wood. Our previous approach: filtered original CT images, applied histogram segmentation, grew volumes to extract 3-d regions, and applied a rule base, with Dempster-...

Evaluation of the BreastSimulator software platform for breast tomography

NASA Astrophysics Data System (ADS)

Mettivier, G.; Bliznakova, K.; Sechopoulos, I.; Boone, J. M.; Di Lillo, F.; Sarno, A.; Castriconi, R.; Russo, P.

2017-08-01

The aim of this work was the evaluation of the software BreastSimulator, a breast x-ray imaging simulation software, as a tool for the creation of 3D uncompressed breast digital models and for the simulation and the optimization of computed tomography (CT) scanners dedicated to the breast. Eight 3D digital breast phantoms were created with glandular fractions in the range 10%-35%. The models are characterised by different sizes and modelled realistic anatomical features. X-ray CT projections were simulated for a dedicated cone-beam CT scanner and reconstructed with the FDK algorithm. X-ray projection images were simulated for 5 mono-energetic (27, 32, 35, 43 and 51 keV) and 3 poly-energetic x-ray spectra typically employed in current CT scanners dedicated to the breast (49, 60, or 80 kVp). Clinical CT images acquired from two different clinical breast CT scanners were used for comparison purposes. The quantitative evaluation included calculation of the power-law exponent, β, from simulated and real breast tomograms, based on the power spectrum fitted with a function of the spatial frequency, f, of the form S(f)  =  α/f   β . The breast models were validated by comparison against clinical breast CT and published data. We found that the calculated β coefficients were close to that of clinical CT data from a dedicated breast CT scanner and reported data in the literature. In evaluating the software package BreastSimulator to generate breast models suitable for use with breast CT imaging, we found that the breast phantoms produced with the software tool can reproduce the anatomical structure of real breasts, as evaluated by calculating the β exponent from the power spectral analysis of simulated images. As such, this research tool might contribute considerably to the further development, testing and optimisation of breast CT imaging techniques.

Predicting tumor hypoxia in non-small cell lung cancer by combining CT, FDG PET and dynamic contrast-enhanced CT.

PubMed

Even, Aniek J G; Reymen, Bart; La Fontaine, Matthew D; Das, Marco; Jochems, Arthur; Mottaghy, Felix M; Belderbos, José S A; De Ruysscher, Dirk; Lambin, Philippe; van Elmpt, Wouter

2017-11-01

Most solid tumors contain inadequately oxygenated (i.e., hypoxic) regions, which tend to be more aggressive and treatment resistant. Hypoxia PET allows visualization of hypoxia and may enable treatment adaptation. However, hypoxia PET imaging is expensive, time-consuming and not widely available. We aimed to predict hypoxia levels in non-small cell lung cancer (NSCLC) using more easily available imaging modalities: FDG-PET/CT and dynamic contrast-enhanced CT (DCE-CT). For 34 NSCLC patients, included in two clinical trials, hypoxia HX4-PET/CT, planning FDG-PET/CT and DCE-CT scans were acquired before radiotherapy. Scans were non-rigidly registered to the planning CT. Tumor blood flow (BF) and blood volume (BV) were calculated by kinetic analysis of DCE-CT images. Within the gross tumor volume, independent clusters, i.e., supervoxels, were created based on FDG-PET/CT. For each supervoxel, tumor-to-background ratios (TBR) were calculated (median SUV/aorta SUV mean ) for HX4-PET/CT and supervoxel features (median, SD, entropy) for the other modalities. Two random forest models (cross-validated: 10 folds, five repeats) were trained to predict the hypoxia TBR; one based on CT, FDG, BF and BV, and one with only CT and FDG features. Patients were split in a training (trial NCT01024829) and independent test set (trial NCT01210378). For each patient, predicted, and observed hypoxic volumes (HV) (TBR > 1.2) were compared. Fifteen patients (3291 supervoxels) were used for training and 19 patients (1502 supervoxels) for testing. The model with all features (RMSE training: 0.19 ± 0.01, test: 0.27) outperformed the model with only CT and FDG-PET features (RMSE training: 0.20 ± 0.01, test: 0.29). All tumors of the test set were correctly classified as normoxic or hypoxic (HV > 1 cm 3 ) by the best performing model. We created a data-driven methodology to predict hypoxia levels and hypoxia spatial patterns using CT, FDG-PET and DCE-CT features in NSCLC. The model correctly classifies all tumors, and could therefore, aid tumor hypoxia classification and patient stratification.

Automatically pairing measured findings across narrative abdomen CT reports.

PubMed

Sevenster, Merlijn; Bozeman, Jeffrey; Cowhy, Andrea; Trost, William

2013-01-01

Radiological measurements are one of the key variables in widely adopted guidelines (WHO, RECIST) that standardize and objectivize response assessment in oncology care. Measurements are typically described in free-text, narrative radiology reports. We present a natural language processing pipeline that extracts measurements from radiology reports and pairs them with extracted measurements from prior reports of the same clinical finding, e.g., lymph node or mass. A ground truth was created by manually pairing measurements in the abdomen CT reports of 50 patients. A Random Forest classifier trained on 15 features achieved superior results in an end-to-end evaluation of the pipeline on the extraction and pairing task: precision 0.910, recall 0.878, F-measure 0.894, AUC 0.988. Representing the narrative content in terms of UMLS concepts did not improve results. Applications of the proposed technology include data mining, advanced search and workflow support for healthcare professionals managing radiological measurements.

TH-E-BRF-04: Characterizing the Response of Texture-Based CT Image Features for Quantification of Radiation-Induced Normal Lung Damage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krafft, S; Court, L; Briere, T

2014-06-15

Purpose: Radiation induced lung damage (RILD) is an important dose-limiting toxicity for patients treated with radiation therapy. Scoring systems for RILD are subjective and limit our ability to find robust predictors of toxicity. We investigate the dose and time-related response for texture-based lung CT image features that serve as potential quantitative measures of RILD. Methods: Pre- and post-RT diagnostic imaging studies were collected for retrospective analysis of 21 patients treated with photon or proton radiotherapy for NSCLC. Total lung and selected isodose contours (0–5, 5–15, 15–25Gy, etc.) were deformably registered from the treatment planning scan to the pre-RT and availablemore » follow-up CT studies for each patient. A CT image analysis framework was utilized to extract 3698 unique texture-based features (including co-occurrence and run length matrices) for each region of interest defined by the isodose contours and the total lung volume. Linear mixed models were fit to determine the relationship between feature change (relative to pre-RT), planned dose and time post-RT. Results: Seventy-three follow-up CT scans from 21 patients (median: 3 scans/patient) were analyzed to describe CT image feature change. At the p=0.05 level, dose affected feature change in 2706 (73.1%) of the available features. Similarly, time affected feature change in 408 (11.0%) of the available features. Both dose and time were significant predictors of feature change in a total of 231 (6.2%) of the extracted image features. Conclusion: Characterizing the dose and time-related response of a large number of texture-based CT image features is the first step toward identifying objective measures of lung toxicity necessary for assessment and prediction of RILD. There is evidence that numerous features are sensitive to both the radiation dose and time after RT. Beyond characterizing feature response, further investigation is warranted to determine the utility of these features as surrogates of clinically significant lung injury.« less

Hepatic CT image query using Gabor features

NASA Astrophysics Data System (ADS)

Zhao, Chenguang; Cheng, Hongyan; Zhuang, Tiange

2004-07-01

A retrieval scheme for liver computerize tomography (CT) images based on Gabor texture is presented. For each hepatic CT image, we manually delineate abnormal regions within liver area. Then, a continuous Gabor transform is utilized to analyze the texture of the pathology bearing region and extract the corresponding feature vectors. For a given sample image, we compare its feature vector with those of other images. Similar images with the highest rank are retrieved. In experiments, 45 liver CT images are collected, and the effectiveness of Gabor texture for content based retrieval is verified.

Role of multidetector computed tomography in evaluating incidentally detected breast lesions.

PubMed

Moschetta, Marco; Scardapane, Arnaldo; Lorusso, Valentina; Rella, Leonarda; Telegrafo, Michele; Serio, Gabriella; Angelelli, Giuseppe; Ianora, Amato Antonio Stabile

2015-01-01

Computed tomography (CT) does not represent the primary method for the evaluation of breast lesions; however, it can detect breast abnormalities, even when performed for other reasons related to thoracic structures. The aim of this study is to evaluate the potential benefits of 320-row multidetector CT (MDCT) in evaluating and differentiating incidentally detected breast lesions by using vessel probe and 3D analysis software with net enhancement value. Sixty-two breast lesions in 46 patients who underwent 320-row chest CT examination were retrospectively evaluated. CT scans were assessed searching for the presence, location, number, morphological features, and density of breast nodules. Net enhancement was calculated by subtracting precontrast density from the density obtained by postcontrast values. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of CT were calculated for morphological features and net enhancement. Thirty of 62 lesions were found to be malignant at histological examination and 32 were found to be benign. When morphological features were considered, the sensitivity, specificity, accuracy, PPV, and NPV of CT were 87%, 100%, 88%, 100%, and 50%, respectively. Based on net enhancement, CT reached a sensitivity, specificity, accuracy, PPV, and NPV of 100%, 94%, 97%, 94%, and 100%, respectively. MDCT allows to recognize and characterize breast lesions based on morphological features. Net enhancement can be proposed as an additional accurate feature of CT.

Assessment of the dose reduction potential of a model-based iterative reconstruction algorithm using a task-based performance metrology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Samei, Ehsan, E-mail: samei@duke.edu; Richard, Samuel

2015-01-15

Purpose: Different computed tomography (CT) reconstruction techniques offer different image quality attributes of resolution and noise, challenging the ability to compare their dose reduction potential against each other. The purpose of this study was to evaluate and compare the task-based imaging performance of CT systems to enable the assessment of the dose performance of a model-based iterative reconstruction (MBIR) to that of an adaptive statistical iterative reconstruction (ASIR) and a filtered back projection (FBP) technique. Methods: The ACR CT phantom (model 464) was imaged across a wide range of mA setting on a 64-slice CT scanner (GE Discovery CT750 HD,more » Waukesha, WI). Based on previous work, the resolution was evaluated in terms of a task-based modulation transfer function (MTF) using a circular-edge technique and images from the contrast inserts located in the ACR phantom. Noise performance was assessed in terms of the noise-power spectrum (NPS) measured from the uniform section of the phantom. The task-based MTF and NPS were combined with a task function to yield a task-based estimate of imaging performance, the detectability index (d′). The detectability index was computed as a function of dose for two imaging tasks corresponding to the detection of a relatively small and a relatively large feature (1.5 and 25 mm, respectively). The performance of MBIR in terms of the d′ was compared with that of ASIR and FBP to assess its dose reduction potential. Results: Results indicated that MBIR exhibits a variability spatial resolution with respect to object contrast and noise while significantly reducing image noise. The NPS measurements for MBIR indicated a noise texture with a low-pass quality compared to the typical midpass noise found in FBP-based CT images. At comparable dose, the d′ for MBIR was higher than those of FBP and ASIR by at least 61% and 19% for the small feature and the large feature tasks, respectively. Compared to FBP and ASIR, MBIR indicated a 46%–84% dose reduction potential, depending on task, without compromising the modeled detection performance. Conclusions: The presented methodology based on ACR phantom measurements extends current possibilities for the assessment of CT image quality under the complex resolution and noise characteristics exhibited with statistical and iterative reconstruction algorithms. The findings further suggest that MBIR can potentially make better use of the projections data to reduce CT dose by approximately a factor of 2. Alternatively, if the dose held unchanged, it can improve image quality by different levels for different tasks.« less

Computed tomographic features of apical infection of equine maxillary cheek teeth: a retrospective study of 49 horses.

PubMed

Bühler, M; Fürst, A; Lewis, F I; Kummer, M; Ohlerth, S

2014-07-01

Computed tomographic (CT) studies evaluating the relevance of individual CT features of apical infection in maxillary cheek teeth are lacking. To study the prevalence and relationship of single CT features in horses with and without clinical evidence of apical infection in maxillary cheek teeth. Retrospective case-control study. Multislice CT scans of the head of 49 horses were evaluated retrospectively. Changes of the infundibulum, pulp, root, lamina dura, periodontal space and alveolar bone in maxillary cheek teeth were recorded. Single CT changes were much more prevalent in the 28 horses with clinical signs. However, infundibular changes and a nondetectable lamina dura were also common in the 21 horses without clinical evidence of apical infection. Computed tomographic abnormalities of the pulp, root, periapical bone and periodontal space and the presence of a tooth fracture were significantly related. Infundibular changes were not associated with other CT signs of apical infection. Although nondetectable lamina dura was the most frequent CT change in all teeth in both studied groups, it was most commonly a solitary feature in otherwise normal teeth. Apical infections, defined as ≥3 CT changes, occurred mainly in the 108/208, 109/209 and 110/210 (Triadan numbers) and were found only in horses with clinical evidence of apical infection, except in one horse without clinical signs that had one affected root. Combined CT changes of the pulp, root, lamina dura, periapical bone and periodontal space and the presence of a tooth fracture appear to be reliable features to diagnose apical infection in maxillary cheek teeth. As a solitary feature, a nondetectable lamina dura should be interpreted cautiously and may even be considered normal due to its minor thickness and/or too low resolution of the imaging modality. © 2013 EVJ Ltd.

Full-Body CT Scans - What You Need to Know

MedlinePlus

... Medical Imaging Medical X-ray Imaging Full-Body CT Scans - What You Need to Know Share Tweet ... new service for health-conscious people: "Whole-body CT screening." This typically involves scanning the body from ...

WE-E-17A-05: Complementary Prognostic Value of CT and 18F-FDG PET Non-Small Cell Lung Cancer Tumor Heterogeneity Features Quantified Through Texture Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Desseroit, M; Cheze Le Rest, C; Tixier, F

2014-06-15

Purpose: Previous studies have shown that CT or 18F-FDG PET intratumor heterogeneity features computed using texture analysis may have prognostic value in Non-Small Cell Lung Cancer (NSCLC), but have been mostly investigated separately. The purpose of this study was to evaluate the potential added value with respect to prognosis regarding the combination of non-enhanced CT and 18F-FDG PET heterogeneity textural features on primary NSCLC tumors. Methods: One hundred patients with non-metastatic NSCLC (stage I–III), treated with surgery and/or (chemo)radiotherapy, that underwent staging 18F-FDG PET/CT images, were retrospectively included. Morphological tumor volumes were semi-automatically delineated on non-enhanced CT using 3D SlicerTM.more » Metabolically active tumor volumes (MATV) were automatically delineated on PET using the Fuzzy Locally Adaptive Bayesian (FLAB) method. Intratumoral tissue density and FDG uptake heterogeneities were quantified using texture parameters calculated from co-occurrence, difference, and run-length matrices. In addition to these textural features, first order histogram-derived metrics were computed on the whole morphological CT tumor volume, as well as on sub-volumes corresponding to fine, medium or coarse textures determined through various levels of LoG-filtering. Association with survival regarding all extracted features was assessed using Cox regression for both univariate and multivariate analysis. Results: Several PET and CT heterogeneity features were prognostic factors of overall survival in the univariate analysis. CT histogram-derived kurtosis and uniformity, as well as Low Grey-level High Run Emphasis (LGHRE), and PET local entropy were independent prognostic factors. Combined with stage and MATV, they led to a powerful prognostic model (p<0.0001), with median survival of 49 vs. 12.6 months and a hazard ratio of 3.5. Conclusion: Intratumoral heterogeneity quantified through textural features extracted from both CT and FDG PET images have complementary and independent prognostic value in NSCLC.« less

MO-DE-207B-10: Impact of Morphologic Characteristics On Radiomics Features From Contast-Enhanced CT for Primary Lung Tumors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fried, D; Zhang, L; Fave, X

Purpose: Determine the impact of morphologic characteristics (e.g. necrosis, vascular enhancement, and cavitation) on radiomic features from contrast enhanced CT (CE-CT) in primary lung tumors. Methods: We developed an auto-segmentation algorithm to separate lung tumors on contrast-enhanced CT into cavitation (air), necrosis, tissue, and enhancing vessels using a combination of thresholding and region-growing. An auto-segmentation algorithm was also designed to identify necrosis on FDG-PET scans. Wilcoxon rank-sum tests were used to determine if significant differences existed in radiomics features (histogram-uniformity and Laplacian-of-Gaussian average) from 249 patients, found to prognostic in previous work, based on the presence/absence of morphologic features. Featuremore » values were also compared between the original tumor contours and contours excluding a specific morphologic feature. Comparison of necrosis segmentation on CE-CT versus FDG-PET was performed in 78 patients to assess for agreement using the concordance correlation coefficient (CCC). Results: Tumors with cavitation and enhancing vasculature had lower uniformity values (p = 0.001 and p = 0.03, respectively). Tumors with enhancing vasculature and necrosis had higher Laplacian-of-Gaussian average values (measure of “edges” within the tumor) (p < 0.001). Removing these tissue types from regions-of-interest did not drastically alter either radiomic feature value (all scenarios had R{sup 2} > 0.8). This suggests there may be interactions between morphologic characteristics and the radiomic feature value of tumor tissue. Comparison of necrosis volume and percent necrosis volume of tumor were found to have CCC values of 0.85 and 0.76, respectively between CE-CT and FDG-PET segmentation methods. Conclusions: Tumors with enhancing vasculature, necrosis, and cavitation have higher radiomic feature values that are associated with poor prognosis than tumors without these features. Removing these tissue types from quantitative assessment did not drastically impact radiomic feature values. High reproducibility of CE-CT segmented necrosis compared to FDG-PET segmented necrosis provides a reasonable validation of segmentation accuracy on CE-CT.« less

TU-A-12A-07: CT-Based Biomarkers to Characterize Lung Lesion: Effects of CT Dose, Slice Thickness and Reconstruction Algorithm Based Upon a Phantom Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, B; Tan, Y; Tsai, W

2014-06-15

Purpose: Radiogenomics promises the ability to study cancer tumor genotype from the phenotype obtained through radiographic imaging. However, little attention has been paid to the sensitivity of image features, the image-based biomarkers, to imaging acquisition techniques. This study explores the impact of CT dose, slice thickness and reconstruction algorithm on measuring image features using a thorax phantom. Methods: Twentyfour phantom lesions of known volume (1 and 2mm), shape (spherical, elliptical, lobular and spicular) and density (-630, -10 and +100 HU) were scanned on a GE VCT at four doses (25, 50, 100, and 200 mAs). For each scan, six imagemore » series were reconstructed at three slice thicknesses of 5, 2.5 and 1.25mm with continuous intervals, using the lung and standard reconstruction algorithms. The lesions were segmented with an in-house 3D algorithm. Fifty (50) image features representing lesion size, shape, edge, and density distribution/texture were computed. Regression method was employed to analyze the effect of CT dose, slice of thickness and reconstruction algorithm on these features adjusting 3 confounding factors (size, density and shape of phantom lesions). Results: The coefficients of CT dose, slice thickness and reconstruction algorithm are presented in Table 1 in the supplementary material. No significant difference was found between the image features calculated on low dose CT scans (25mAs and 50mAs). About 50% texture features were found statistically different between low doses and high doses (100 and 200mAs). Significant differences were found for almost all features when calculated on 1.25mm, 2.5mm, and 5mm slice thickness images. Reconstruction algorithms significantly affected all density-based image features, but not morphological features. Conclusions: There is a great need to standardize the CT imaging protocols for radiogenomics study because CT dose, slice thickness and reconstruction algorithm impact quantitative image features to various degrees as our study has shown.« less

The effects of variations in parameters and algorithm choices on calculated radiomics feature values: initial investigations and comparisons to feature variability across CT image acquisition conditions

NASA Astrophysics Data System (ADS)

Emaminejad, Nastaran; Wahi-Anwar, Muhammad; Hoffman, John; Kim, Grace H.; Brown, Matthew S.; McNitt-Gray, Michael

2018-02-01

Translation of radiomics into clinical practice requires confidence in its interpretations. This may be obtained via understanding and overcoming the limitations in current radiomic approaches. Currently there is a lack of standardization in radiomic feature extraction. In this study we examined a few factors that are potential sources of inconsistency in characterizing lung nodules, such as 1)different choices of parameters and algorithms in feature calculation, 2)two CT image dose levels, 3)different CT reconstruction algorithms (WFBP, denoised WFBP, and Iterative). We investigated the effect of variation of these factors on entropy textural feature of lung nodules. CT images of 19 lung nodules identified from our lung cancer screening program were identified by a CAD tool and contours provided. The radiomics features were extracted by calculating 36 GLCM based and 4 histogram based entropy features in addition to 2 intensity based features. A robustness index was calculated across different image acquisition parameters to illustrate the reproducibility of features. Most GLCM based and all histogram based entropy features were robust across two CT image dose levels. Denoising of images slightly improved robustness of some entropy features at WFBP. Iterative reconstruction resulted in improvement of robustness in a fewer times and caused more variation in entropy feature values and their robustness. Within different choices of parameters and algorithms texture features showed a wide range of variation, as much as 75% for individual nodules. Results indicate the need for harmonization of feature calculations and identification of optimum parameters and algorithms in a radiomics study.

SU-F-R-40: Robustness Test of Computed Tomography Textures of Lung Tissues to Varying Scanning Protocols Using a Realistic Phantom Environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, S; Markel, D; Hegyi, G

2016-06-15

Purpose: The reliability of computed tomography (CT) textures is an important element of radiomics analysis. This study investigates the dependency of lung CT textures on different breathing phases and changes in CT image acquisition protocols in a realistic phantom setting. Methods: We investigated 11 CT texture features for radiation-induced lung disease from 3 categories (first-order, grey level co-ocurrence matrix (GLCM), and Law’s filter). A biomechanical swine lung phantom was scanned at two breathing phases (inhale/exhale) and two scanning protocols set for PET/CT and diagnostic CT scanning. Lung volumes acquired from the CT images were divided into 2-dimensional sub-regions with amore » grid spacing of 31 mm. The distribution of the evaluated texture features from these sub-regions were compared between the two scanning protocols and two breathing phases. The significance of each factor on feature values were tested at 95% significance level using analysis of covariance (ANCOVA) model with interaction terms included. Robustness of a feature to a scanning factor was defined as non-significant dependence on the factor. Results: Three GLCM textures (variance, sum entropy, difference entropy) were robust to breathing changes. Two GLCM (variance, sum entropy) and 3 Law’s filter textures (S5L5, E5L5, W5L5) were robust to scanner changes. Moreover, the two GLCM textures (variance, sum entropy) were consistent across all 4 scanning conditions. First-order features, especially Hounsfield unit intensity features, presented the most drastic variation up to 39%. Conclusion: Amongst the studied features, GLCM and Law’s filter texture features were more robust than first-order features. However, the majority of the features were modified by either breathing phase or scanner changes, suggesting a need for calibration when retrospectively comparing scans obtained at different conditions. Further investigation is necessary to identify the sensitivity of individual image acquisition parameters.« less

Selected PET radiomic features remain the same.

PubMed

Tsujikawa, Tetsuya; Tsuyoshi, Hideaki; Kanno, Masafumi; Yamada, Shizuka; Kobayashi, Masato; Narita, Norihiko; Kimura, Hirohiko; Fujieda, Shigeharu; Yoshida, Yoshio; Okazawa, Hidehiko

2018-04-17

We investigated whether PET radiomic features are affected by differences in the scanner, scan protocol, and lesion location using 18 F-FDG PET/CT and PET/MR scans. SUV, TMR, skewness, kurtosis, entropy, and homogeneity strongly correlated between PET/CT and PET/MR images. SUVs were significantly higher on PET/MR 0-2 min and PET/MR 0-10 min than on PET/CT in gynecological cancer ( p = 0.008 and 0.008, respectively), whereas no significant difference was observed between PET/CT, PET/MR 0-2 min , and PET/MR 0-10 min images in oral cavity/oropharyngeal cancer. TMRs on PET/CT, PET/MR 0-2 min , and PET/MR 0-10 min increased in this order in gynecological cancer and oral cavity/oropharyngeal cancer. In contrast to conventional and histogram indices, 4 textural features (entropy, homogeneity, SRE, and LRE) were not significantly different between PET/CT, PET/MR 0-2 min , and PET/MR 0-10 min images. 18 F-FDG PET radiomic features strongly correlated between PET/CT and PET/MR images. Dixon-based attenuation correction on PET/MR images underestimated tumor tracer uptake more significantly in oral cavity/oropharyngeal cancer than in gynecological cancer. 18 F-FDG PET textural features were affected less by differences in the scanner and scan protocol than conventional and histogram features, possibly due to the resampling process using a medium bin width. Eight patients with gynecological cancer and 7 with oral cavity/oropharyngeal cancer underwent a whole-body 18 F-FDG PET/CT scan and regional PET/MR scan in one day. PET/MR scans were performed for 10 minutes in the list mode, and PET/CT and 0-2 min and 0-10 min PET/MR images were reconstructed. The standardized uptake value (SUV), tumor-to-muscle SUV ratio (TMR), skewness, kurtosis, entropy, homogeneity, short-run emphasis (SRE), and long-run emphasis (LRE) were compared between PET/CT, PET/MR 0-2 min , and PET/MR 0-10 min images.

Pulmonary nodule characterization, including computer analysis and quantitative features.

PubMed

Bartholmai, Brian J; Koo, Chi Wan; Johnson, Geoffrey B; White, Darin B; Raghunath, Sushravya M; Rajagopalan, Srinivasan; Moynagh, Michael R; Lindell, Rebecca M; Hartman, Thomas E

2015-03-01

Pulmonary nodules are commonly detected in computed tomography (CT) chest screening of a high-risk population. The specific visual or quantitative features on CT or other modalities can be used to characterize the likelihood that a nodule is benign or malignant. Visual features on CT such as size, attenuation, location, morphology, edge characteristics, and other distinctive "signs" can be highly suggestive of a specific diagnosis and, in general, be used to determine the probability that a specific nodule is benign or malignant. Change in size, attenuation, and morphology on serial follow-up CT, or features on other modalities such as nuclear medicine studies or MRI, can also contribute to the characterization of lung nodules. Imaging analytics can objectively and reproducibly quantify nodule features on CT, nuclear medicine, and magnetic resonance imaging. Some quantitative techniques show great promise in helping to differentiate benign from malignant lesions or to stratify the risk of aggressive versus indolent neoplasm. In this article, we (1) summarize the visual characteristics, descriptors, and signs that may be helpful in management of nodules identified on screening CT, (2) discuss current quantitative and multimodality techniques that aid in the differentiation of nodules, and (3) highlight the power, pitfalls, and limitations of these various techniques.

Cortical thickness abnormalities associated with dyslexia, independent of remediation status.

PubMed

Ma, Yizhou; Koyama, Maki S; Milham, Michael P; Castellanos, F Xavier; Quinn, Brian T; Pardoe, Heath; Wang, Xiuyuan; Kuzniecky, Ruben; Devinsky, Orrin; Thesen, Thomas; Blackmon, Karen

2015-01-01

Abnormalities in cortical structure are commonly observed in children with dyslexia in key regions of the "reading network." Whether alteration in cortical features reflects pathology inherent to dyslexia or environmental influence (e.g., impoverished reading experience) remains unclear. To address this question, we compared MRI-derived metrics of cortical thickness (CT), surface area (SA), gray matter volume (GMV), and their lateralization across three different groups of children with a historical diagnosis of dyslexia, who varied in current reading level. We compared three dyslexia subgroups with: (1) persistent reading and spelling impairment; (2) remediated reading impairment (normal reading scores), and (3) remediated reading and spelling impairments (normal reading and spelling scores); and a control group of (4) typically developing children. All groups were matched for age, gender, handedness, and IQ. We hypothesized that the dyslexia group would show cortical abnormalities in regions of the reading network relative to controls, irrespective of remediation status. Such a finding would support that cortical abnormalities are inherent to dyslexia and are not a consequence of abnormal reading experience. Results revealed increased CT of the left fusiform gyrus in the dyslexia group relative to controls. Similarly, the dyslexia group showed CT increase of the right superior temporal gyrus, extending into the planum temporale, which resulted in a rightward CT asymmetry on lateralization indices. There were no group differences in SA, GMV, or their lateralization. These findings held true regardless of remediation status. Each reading level group showed the same "double hit" of atypically increased left fusiform CT and rightward superior temporal CT asymmetry. Thus, findings provide evidence that a developmental history of dyslexia is associated with CT abnormalities, independent of remediation status.

Cortical thickness abnormalities associated with dyslexia, independent of remediation status

PubMed Central

Ma, Yizhou; Koyama, Maki S.; Milham, Michael P.; Castellanos, F. Xavier; Quinn, Brian T.; Pardoe, Heath; Wang, Xiuyuan; Kuzniecky, Ruben; Devinsky, Orrin; Thesen, Thomas; Blackmon, Karen

2014-01-01

Abnormalities in cortical structure are commonly observed in children with dyslexia in key regions of the “reading network.” Whether alteration in cortical features reflects pathology inherent to dyslexia or environmental influence (e.g., impoverished reading experience) remains unclear. To address this question, we compared MRI-derived metrics of cortical thickness (CT), surface area (SA), gray matter volume (GMV), and their lateralization across three different groups of children with a historical diagnosis of dyslexia, who varied in current reading level. We compared three dyslexia subgroups with: (1) persistent reading and spelling impairment; (2) remediated reading impairment (normal reading scores), and (3) remediated reading and spelling impairments (normal reading and spelling scores); and a control group of (4) typically developing children. All groups were matched for age, gender, handedness, and IQ. We hypothesized that the dyslexia group would show cortical abnormalities in regions of the reading network relative to controls, irrespective of remediation status. Such a finding would support that cortical abnormalities are inherent to dyslexia and are not a consequence of abnormal reading experience. Results revealed increased CT of the left fusiform gyrus in the dyslexia group relative to controls. Similarly, the dyslexia group showed CT increase of the right superior temporal gyrus, extending into the planum temporale, which resulted in a rightward CT asymmetry on lateralization indices. There were no group differences in SA, GMV, or their lateralization. These findings held true regardless of remediation status. Each reading level group showed the same “double hit” of atypically increased left fusiform CT and rightward superior temporal CT asymmetry. Thus, findings provide evidence that a developmental history of dyslexia is associated with CT abnormalities, independent of remediation status. PMID:25610779

Knowledge of medical imaging radiation dose and risk among doctors.

PubMed

Brown, Nicholas; Jones, Lee

2013-02-01

The growth of computed tomography (CT) and nuclear medicine (NM) scans has revolutionised healthcare but also greatly increased population radiation doses. Overuse of diagnostic radiation is becoming a feature of medical practice, leading to possible unnecessary radiation exposures and lifetime-risks of developing cancer. Doctors across all medical specialties and experience levels were surveyed to determine their knowledge of radiation doses and potential risks associated with some diagnostic imaging. A survey relating to knowledge and understanding of medical imaging radiation was distributed to doctors at 14 major Queensland public hospitals, as well as fellows and trainees in radiology, emergency medicine and general practice. From 608 valid responses, only 17.3% correctly estimated the radiation dose from CT scans and almost 1 in 10 incorrectly believed that CT radiation is not associated with any increased lifetime risk of developing cancer. There is a strong inverse relationship between a clinician's experience and their knowledge of CT radiation dose and risks, even among radiologists. More than a third (35.7%) of doctors incorrectly believed that typical NM imaging either does not use ionising radiation or emits doses equal to or less than a standard chest radiograph. Knowledge of CT and NM radiation doses is poor across all specialties, and there is a significant inverse relationship between experience and awareness of CT dose and risk. Despite having a poor understanding of these concepts, most doctors claim to consider them prior to requesting scans and when discussing potential risks with patients. © 2012 The Authors. Journal of Medical Imaging and Radiation Oncology © 2012 The Royal Australian and New Zealand College of Radiologists.

19. Photocopy of drawing, typical floor beam and stringer, Bridge ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

19. Photocopy of drawing, typical floor beam and stringer, Bridge No. 79B, Main & Washington Sts., So. Norwalk, Ct., N. Y. Division, N.Y., N.H. and H.R.R., dated April 23, 1895. Original on file with Metro North Commuter Railroad. - South Norwalk Railroad Bridge, South Main & Washington Streets, Norwalk, Fairfield County, CT

Multi-layer cube sampling for liver boundary detection in PET-CT images.

PubMed

Liu, Xinxin; Yang, Jian; Song, Shuang; Song, Hong; Ai, Danni; Zhu, Jianjun; Jiang, Yurong; Wang, Yongtian

2018-06-01

Liver metabolic information is considered as a crucial diagnostic marker for the diagnosis of fever of unknown origin, and liver recognition is the basis of automatic diagnosis of metabolic information extraction. However, the poor quality of PET and CT images is a challenge for information extraction and target recognition in PET-CT images. The existing detection method cannot meet the requirement of liver recognition in PET-CT images, which is the key problem in the big data analysis of PET-CT images. A novel texture feature descriptor called multi-layer cube sampling (MLCS) is developed for liver boundary detection in low-dose CT and PET images. The cube sampling feature is proposed for extracting more texture information, which uses a bi-centric voxel strategy. Neighbour voxels are divided into three regions by the centre voxel and the reference voxel in the histogram, and the voxel distribution information is statistically classified as texture feature. Multi-layer texture features are also used to improve the ability and adaptability of target recognition in volume data. The proposed feature is tested on the PET and CT images for liver boundary detection. For the liver in the volume data, mean detection rate (DR) and mean error rate (ER) reached 95.15 and 7.81% in low-quality PET images, and 83.10 and 21.08% in low-contrast CT images. The experimental results demonstrated that the proposed method is effective and robust for liver boundary detection.

Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image.

PubMed

Xiang, Lei; Wang, Qian; Nie, Dong; Zhang, Lichi; Jin, Xiyao; Qiao, Yu; Shen, Dinggang

2018-07-01

Recently, more and more attention is drawn to the field of medical image synthesis across modalities. Among them, the synthesis of computed tomography (CT) image from T1-weighted magnetic resonance (MR) image is of great importance, although the mapping between them is highly complex due to large gaps of appearances of the two modalities. In this work, we aim to tackle this MR-to-CT synthesis task by a novel deep embedding convolutional neural network (DECNN). Specifically, we generate the feature maps from MR images, and then transform these feature maps forward through convolutional layers in the network. We can further compute a tentative CT synthesis from the midway of the flow of feature maps, and then embed this tentative CT synthesis result back to the feature maps. This embedding operation results in better feature maps, which are further transformed forward in DECNN. After repeating this embedding procedure for several times in the network, we can eventually synthesize a final CT image in the end of the DECNN. We have validated our proposed method on both brain and prostate imaging datasets, by also comparing with the state-of-the-art methods. Experimental results suggest that our DECNN (with repeated embedding operations) demonstrates its superior performances, in terms of both the perceptive quality of the synthesized CT image and the run-time cost for synthesizing a CT image. Copyright © 2018. Published by Elsevier B.V.

Deep 3D convolution neural network for CT brain hemorrhage classification

NASA Astrophysics Data System (ADS)

Jnawali, Kamal; Arbabshirani, Mohammad R.; Rao, Navalgund; Patel, Alpen A.

2018-02-01

Intracranial hemorrhage is a critical conditional with the high mortality rate that is typically diagnosed based on head computer tomography (CT) images. Deep learning algorithms, in particular, convolution neural networks (CNN), are becoming the methodology of choice in medical image analysis for a variety of applications such as computer-aided diagnosis, and segmentation. In this study, we propose a fully automated deep learning framework which learns to detect brain hemorrhage based on cross sectional CT images. The dataset for this work consists of 40,367 3D head CT studies (over 1.5 million 2D images) acquired retrospectively over a decade from multiple radiology facilities at Geisinger Health System. The proposed algorithm first extracts features using 3D CNN and then detects brain hemorrhage using the logistic function as the last layer of the network. Finally, we created an ensemble of three different 3D CNN architectures to improve the classification accuracy. The area under the curve (AUC) of the receiver operator characteristic (ROC) curve of the ensemble of three architectures was 0.87. Their results are very promising considering the fact that the head CT studies were not controlled for slice thickness, scanner type, study protocol or any other settings. Moreover, the proposed algorithm reliably detected various types of hemorrhage within the skull. This work is one of the first applications of 3D CNN trained on a large dataset of cross sectional medical images for detection of a critical radiological condition

Validating automatic semantic annotation of anatomy in DICOM CT images

NASA Astrophysics Data System (ADS)

Pathak, Sayan D.; Criminisi, Antonio; Shotton, Jamie; White, Steve; Robertson, Duncan; Sparks, Bobbi; Munasinghe, Indeera; Siddiqui, Khan

2011-03-01

In the current health-care environment, the time available for physicians to browse patients' scans is shrinking due to the rapid increase in the sheer number of images. This is further aggravated by mounting pressure to become more productive in the face of decreasing reimbursement. Hence, there is an urgent need to deliver technology which enables faster and effortless navigation through sub-volume image visualizations. Annotating image regions with semantic labels such as those derived from the RADLEX ontology can vastly enhance image navigation and sub-volume visualization. This paper uses random regression forests for efficient, automatic detection and localization of anatomical structures within DICOM 3D CT scans. A regression forest is a collection of decision trees which are trained to achieve direct mapping from voxels to organ location and size in a single pass. This paper focuses on comparing automated labeling with expert-annotated ground-truth results on a database of 50 highly variable CT scans. Initial investigations show that regression forest derived localization errors are smaller and more robust than those achieved by state-of-the-art global registration approaches. The simplicity of the algorithm's context-rich visual features yield typical runtimes of less than 10 seconds for a 5123 voxel DICOM CT series on a single-threaded, single-core machine running multiple trees; each tree taking less than a second. Furthermore, qualitative evaluation demonstrates that using the detected organs' locations as index into the image volume improves the efficiency of the navigational workflow in all the CT studies.

Accuracy of Dual-Energy Virtual Monochromatic CT Numbers: Comparison between the Single-Source Projection-Based and Dual-Source Image-Based Methods.

PubMed

Ueguchi, Takashi; Ogihara, Ryota; Yamada, Sachiko

2018-03-21

To investigate the accuracy of dual-energy virtual monochromatic computed tomography (CT) numbers obtained by two typical hardware and software implementations: the single-source projection-based method and the dual-source image-based method. A phantom with different tissue equivalent inserts was scanned with both single-source and dual-source scanners. A fast kVp-switching feature was used on the single-source scanner, whereas a tin filter was used on the dual-source scanner. Virtual monochromatic CT images of the phantom at energy levels of 60, 100, and 140 keV were obtained by both projection-based (on the single-source scanner) and image-based (on the dual-source scanner) methods. The accuracy of virtual monochromatic CT numbers for all inserts was assessed by comparing measured values to their corresponding true values. Linear regression analysis was performed to evaluate the dependency of measured CT numbers on tissue attenuation, method, and their interaction. Root mean square values of systematic error over all inserts at 60, 100, and 140 keV were approximately 53, 21, and 29 Hounsfield unit (HU) with the single-source projection-based method, and 46, 7, and 6 HU with the dual-source image-based method, respectively. Linear regression analysis revealed that the interaction between the attenuation and the method had a statistically significant effect on the measured CT numbers at 100 and 140 keV. There were attenuation-, method-, and energy level-dependent systematic errors in the measured virtual monochromatic CT numbers. CT number reproducibility was comparable between the two scanners, and CT numbers had better accuracy with the dual-source image-based method at 100 and 140 keV. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Translation initiation mediated by nuclear cap-binding protein complex.

PubMed

Ryu, Incheol; Kim, Yoon Ki

2017-04-01

In mammals, cap-dependent translation of mRNAs is initiated by two distinct mechanisms: cap-binding complex (CBC; a heterodimer of CBP80 and 20)-dependent translation (CT) and eIF4E-dependent translation (ET). Both translation initiation mechanisms share common features in driving cap- dependent translation; nevertheless, they can be distinguished from each other based on their molecular features and biological roles. CT is largely associated with mRNA surveillance such as nonsense-mediated mRNA decay (NMD), whereas ET is predominantly involved in the bulk of protein synthesis. However, several recent studies have demonstrated that CT and ET have similar roles in protein synthesis and mRNA surveillance. In a subset of mRNAs, CT preferentially drives the cap-dependent translation, as ET does, and ET is responsible for mRNA surveillance, as CT does. In this review, we summarize and compare the molecular features of CT and ET with a focus on the emerging roles of CT in translation. [BMB Reports 2017; 50(4): 186-193].

Evaluation of Shape and Textural Features from CT as Prognostic Biomarkers in Non-small Cell Lung Cancer.

PubMed

Bianconi, Francesco; Fravolini, Mario Luca; Bello-Cerezo, Raquel; Minestrini, Matteo; Scialpi, Michele; Palumbo, Barbara

2018-04-01

We retrospectively investigated the prognostic potential (correlation with overall survival) of 9 shape and 21 textural features from non-contrast-enhanced computed tomography (CT) in patients with non-small-cell lung cancer. We considered a public dataset of 203 individuals with inoperable, histologically- or cytologically-confirmed NSCLC. Three-dimensional shape and textural features from CT were computed using proprietary code and their prognostic potential evaluated through four different statistical protocols. Volume and grey-level run length matrix (GLRLM) run length non-uniformity were the only two features to pass all four protocols. Both features correlated negatively with overall survival. The results also showed a strong dependence on the evaluation protocol used. Tumour volume and GLRLM run-length non-uniformity from CT were the best predictor of survival in patients with non-small-cell lung cancer. We did not find enough evidence to claim a relationship with survival for the other features. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Diagnosis and management of traumatic cervical central spinal cord injury: A review.

PubMed

Epstein, Nancy E; Hollingsworth, Renee

2015-01-01

The classical clinical presentation, neuroradiographic features, and conservative vs. surgical management of traumatic cervical central spinal cord (CSS) injury remain controversial. CSS injuries, occurring in approximately 9.2% of all cord injuries, are usually attributed to significant hyperextension trauma combined with congenital/acquired cervical stenosis/spondylosis. Patients typically present with greater motor deficits in the upper vs. lower extremities accompanied by patchy sensory loss. T2-weighted magnetic resonance (MR) scans usually show hyperintense T2 intramedullary signals reflecting acute edema along with ligamentous injury, while noncontrast computed tomography (CT) studies typically show no attendant bony pathology (e.g. no fracture, dislocation). CSS constitute only a small percentage of all traumatic spinal cord injuries. Aarabi et al. found CSS patients averaged 58.3 years of age, 83% were male and 52.4% involved accidents/falls in patients with narrowed spinal canals (average 5.6 mm); their average American Spinal Injury Association (ASIA) motor score was 63.8, and most pathology was at the C3-C4 and C4-C5 levels (71%). Surgery was performed within 24 h (9 patients), 24-48 h (10 patients), or after 48 h (23 patients). In the Brodell et al. study of 16,134 patients with CSS, 39.7% had surgery. In the Gu et al. series, those with CSS and stenosis/ossification of the posterior longitudinal ligament (OPLL) exhibited better outcomes following laminoplasty. Recognizing the unique features of CSS is critical, as the clinical, neuroradiological, and management strategies (e.g. conservative vs. surgical management: early vs. late) differ from those utilized for other spinal cord trauma. Increased T2-weighted MR images best document CSS, while CT studies confirm the absence of fracture/dislocation.

CT Features of Ovarian Tumors: Defining Key Differences Between Serous Borderline Tumors and Low-Grade Serous Carcinomas.

PubMed

Nougaret, Stephanie; Lakhman, Yulia; Molinari, Nicolas; Feier, Diana; Scelzo, Chiara; Vargas, Hebert A; Sosa, Ramon E; Hricak, Hedvig; Soslow, Robert A; Grisham, Rachel N; Sala, Evis

2018-04-01

The objective of our study was to investigate whether the CT features of serous borderline tumors (SBTs) differ from those of low-grade serous carcinomas (LGSCs) and to evaluate if mutation status is associated with distinct CT phenotypes. This retrospective study included 59 women, 37 with SBT and 22 with LGSC, who underwent CT before primary surgical resection. Thirty of 59 patients were genetically profiled. Two radiologists (readers 1 and 2) independently and retrospectively reviewed CT examinations for qualitative features and quantified total tumor volumes (TTVs), solid tumor volumes (STVs), and solid proportion of ovarian masses. Univariate and multivariate associations of the CT features with histopathologic diagnoses and mutations were evaluated, and interreader agreement was determined. At multivariate analysis, the presence of bilateral ovarian masses (p = 0.03), the presence of peritoneal disease (PD) (p = 0.002), and higher STV of ovarian masses (p = 0.002) were associated with LGSC. The presence of nodular PD pattern (p < 0.001 each reader) and the presence of PD calcifications (reader 1, p = 0.02; reader 2, p = 0.003) were associated with invasive peritoneal lesions (i.e., LGSC). The presence of bilateral ovarian masses (p = 0.04 each reader), PD (reader 1, p = 0.01; reader 2, p = 0.004), and higher STV (p = 0.03 for each reader) were associated with the absence of BRAF mutation (i.e., wild type [wt]-BRAF). The CT features of LGSCs were distinct from those of SBTs. The CT manifestations of LGSC and the wt-BRAF phenotype were similar.

CT versus MR Techniques in the Detection of Cervical Artery Dissection.

PubMed

Hanning, Uta; Sporns, Peter B; Schmiedel, Meilin; Ringelstein, Erich B; Heindel, Walter; Wiendl, Heinz; Niederstadt, Thomas; Dittrich, Ralf

2017-11-01

Spontaneous cervical artery dissection (sCAD) is an important etiology of juvenile stroke. The gold standard for the diagnosis of sCAD is convential angiography. However, magnetic resonance imaging (MRI)/MR angiography (MRA) and computed tomography (CT)/CT angiography (CTA) are frequently used alternatives. New developments such as multislice CT/CTA have enabled routine acquisition of thinner sections with rapid imaging times. The goal of this study was to compare the capability of recent developed 128-slice CT/CTA to MRI/MRA to detect radiologic features of sCAD. Retrospective review of patients with suspected sCAD (n = 188) in a database of our Stroke center (2008-2014), who underwent CT/CTA and MRI/MRA on initial clinical work-up. A control group of 26 patients was added. All Images were evaluated concerning specific and sensitive radiological features for dissection by two experienced neuroradiologists. Imaging features were compared between the two modalities. Forty patients with 43 dissected arteries received both modalities (29 internal carotid arteries [ICAs] and 14 vertebral arteries [VAs]). All CADs were identified in CT/CTA and MRI/MRA. The features intimal flap, stenosis, and lumen irregularity appeared in both modalities. One high-grade stenosis was identified by CT/CTA that was expected occluded on MRI/MRA. Two MRI/MRA-confirmed pseudoaneurysms were missed by CT/CTA. None of the controls evidenced specific imaging signs for dissection. CT/CTA is a reliable and better available alternative to MRI/MRA for diagnosis of sCAD. CT/CTA should be used to complement MRI/MRA in cases where MRI/MRA suggests occlusion. Copyright © 2017 by the American Society of Neuroimaging.

Neuroradiologic characteristics of astroblastoma and systematic review of the literature: 2 new cases and 125 cases reported in 59 publications.

PubMed

Cunningham, Danielle A; Lowe, Lisa H; Shao, Lei; Acosta, Natasha R

2016-08-01

Astroblastoma is a rare tumor of uncertain origin most commonly presenting in the cerebrum of children and young adults. The literature contains only case reports and small series regarding its radiologic features. This systematic review is the largest study of imaging findings of astroblastoma to date and serves to identify features that might differentiate it from other neoplasms. This study describes the imaging features of astroblastoma based on a systematic review of the literature and two new cases. We conducted a PubMed and Google Scholar database search that identified 59 publications containing 125 cases of pathology-confirmed astroblastoma, and we also added two new cases from our own institution. Data collected include patient age, gender, tumor location, morphology, calcifications and calvarial changes. We recorded findings on CT, MRI, diffusion-weighted imaging (DWI), MR spectroscopy, positron emission tomography (PET) and catheter angiography. Age at diagnosis ranged 0-70 years (mean 18 years; median 14 years). Female-to-male ratio was 8:1. Of 127 cases, 66 reported CT, 78 reported MRI and 47 reported both findings. Not all authors reported all features, but the tumor features reported included supratentorial in 96% (122/127), superficial in 72% (48/67), well-demarcated in 96% (79/82), mixed cystic-solid in 93% (79/85), and enhancing in 99% (78/79). On CT, 84% (26/31) of astroblastomas were hyperattenuated, 73% (27/37) had calcifications and 7 cases reported adjacent calvarial erosion. Astroblastomas were hypointense on T1-W in 58% (26/45) and on T2-W in 50% (23/46) of MRI sequences. Peritumoral edema was present in 80% (40/50) of cases but was typically described as slight. Six cases included DWI findings, with 100% showing restricted diffusion. On MR spectroscopy, 100% (5/5) showed nonspecific tumor spectra with elevated choline and decreased N-acetylaspartate (NAA). PET revealed nonspecific reduced uptake of [F-18] 2-fluoro-2-deoxyglucose ((18)F-FDG) and increased uptake of [11C]-Methionine in 100% (3/3) of cases. Catheter angiography findings (n=12) were variable, including hypervascularity in 67%, arteriovenous shunting in 33% and avascular areas in 25%. Astroblastomas occur most often in adolescent girls. Imaging often shows a supratentorial, superficial, well-defined, cystic-solid enhancing mass. On CT, most are hyperattenuated, have calcifications, and may remodel adjacent bone if superficial. MRI characteristically reveals a hypointense mass on T1-W and T2-W sequences with restricted diffusion. MR spectroscopy, PET and catheter angiography findings are nonspecific.

4D CT sorting based on patient internal anatomy

NASA Astrophysics Data System (ADS)

Li, Ruijiang; Lewis, John H.; Cerviño, Laura I.; Jiang, Steve B.

2009-08-01

Respiratory motion during free-breathing computed tomography (CT) scan may cause significant errors in target definition for tumors in the thorax and upper abdomen. A four-dimensional (4D) CT technique has been widely used for treatment simulation of thoracic and abdominal cancer radiotherapy. The current 4D CT techniques require retrospective sorting of the reconstructed CT slices oversampled at the same couch position. Most sorting methods depend on external surrogates of respiratory motion recorded by extra instruments. However, respiratory signals obtained from these external surrogates may not always accurately represent the internal target motion, especially when irregular breathing patterns occur. We have proposed a new sorting method based on multiple internal anatomical features for multi-slice CT scan acquired in the cine mode. Four features are analyzed in this study, including the air content, lung area, lung density and body area. We use a measure called spatial coherence to select the optimal internal feature at each couch position and to generate the respiratory signals for 4D CT sorting. The proposed method has been evaluated for ten cancer patients (eight with thoracic cancer and two with abdominal cancer). For nine patients, the respiratory signals generated from the combined internal features are well correlated to those from external surrogates recorded by the real-time position management (RPM) system (average correlation: 0.95 ± 0.02), which is better than any individual internal measures at 95% confidence level. For these nine patients, the 4D CT images sorted by the combined internal features are almost identical to those sorted by the RPM signal. For one patient with an irregular breathing pattern, the respiratory signals given by the combined internal features do not correlate well with those from RPM (correlation: 0.68 ± 0.42). In this case, the 4D CT image sorted by our method presents fewer artifacts than that from the RPM signal. Our 4D CT internal sorting method eliminates the need of externally recorded surrogates of respiratory motion. It is an automatic, accurate, robust, cost efficient and yet simple method and therefore can be readily implemented in clinical settings.

Iodine and freeze-drying enhanced high-resolution MicroCT imaging for reconstructing 3D intraneural topography of human peripheral nerve fascicles.

PubMed

Yan, Liwei; Guo, Yongze; Qi, Jian; Zhu, Qingtang; Gu, Liqiang; Zheng, Canbin; Lin, Tao; Lu, Yutong; Zeng, Zitao; Yu, Sha; Zhu, Shuang; Zhou, Xiang; Zhang, Xi; Du, Yunfei; Yao, Zhi; Lu, Yao; Liu, Xiaolin

2017-08-01

The precise annotation and accurate identification of the topography of fascicles to the end organs are prerequisites for studying human peripheral nerves. In this study, we present a feasible imaging method that acquires 3D high-resolution (HR) topography of peripheral nerve fascicles using an iodine and freeze-drying (IFD) micro-computed tomography (microCT) method to greatly increase the contrast of fascicle images. The enhanced microCT imaging method can facilitate the reconstruction of high-contrast HR fascicle images, fascicle segmentation and extraction, feature analysis, and the tracing of fascicle topography to end organs, which define fascicle functions. The complex intraneural aggregation and distribution of fascicles is typically assessed using histological techniques or MR imaging to acquire coarse axial three-dimensional (3D) maps. However, the disadvantages of histological techniques (static, axial manual registration, and data instability) and MR imaging (low-resolution) limit these applications in reconstructing the topography of nerve fascicles. Thus, enhanced microCT is a new technique for acquiring 3D intraneural topography of the human peripheral nerve fascicles both to improve our understanding of neurobiological principles and to guide accurate repair in the clinic. Additionally, 3D microstructure data can be used as a biofabrication model, which in turn can be used to fabricate scaffolds to repair long nerve gaps. Copyright © 2017 Elsevier B.V. All rights reserved.

Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma.

PubMed

Feng, Zhichao; Rong, Pengfei; Cao, Peng; Zhou, Qingyu; Zhu, Wenwei; Yan, Zhimin; Liu, Qianyun; Wang, Wei

2018-04-01

To evaluate the diagnostic performance of machine-learning based quantitative texture analysis of CT images to differentiate small (≤ 4 cm) angiomyolipoma without visible fat (AMLwvf) from renal cell carcinoma (RCC). This single-institutional retrospective study included 58 patients with pathologically proven small renal mass (17 in AMLwvf and 41 in RCC groups). Texture features were extracted from the largest possible tumorous regions of interest (ROIs) by manual segmentation in preoperative three-phase CT images. Interobserver reliability and the Mann-Whitney U test were applied to select features preliminarily. Then support vector machine with recursive feature elimination (SVM-RFE) and synthetic minority oversampling technique (SMOTE) were adopted to establish discriminative classifiers, and the performance of classifiers was assessed. Of the 42 extracted features, 16 candidate features showed significant intergroup differences (P < 0.05) and had good interobserver agreement. An optimal feature subset including 11 features was further selected by the SVM-RFE method. The SVM-RFE+SMOTE classifier achieved the best performance in discriminating between small AMLwvf and RCC, with the highest accuracy, sensitivity, specificity and AUC of 93.9 %, 87.8 %, 100 % and 0.955, respectively. Machine learning analysis of CT texture features can facilitate the accurate differentiation of small AMLwvf from RCC. • Although conventional CT is useful for diagnosis of SRMs, it has limitations. • Machine-learning based CT texture analysis facilitate differentiation of small AMLwvf from RCC. • The highest accuracy of SVM-RFE+SMOTE classifier reached 93.9 %. • Texture analysis combined with machine-learning methods might spare unnecessary surgery for AMLwvf.

CT angiography - abdomen and pelvis

MedlinePlus

... this page: //medlineplus.gov/ency/article/007674.htm CT angiography - abdomen and pelvis To use the sharing features on this page, please enable JavaScript. CT angiography combines a CT scan with the injection ...

CT angiography - arms and legs

MedlinePlus

... this page: //medlineplus.gov/ency/article/007675.htm CT angiography - arms and legs To use the sharing features on this page, please enable JavaScript. CT angiography combines a CT scan with the injection ...

CT angiography - head and neck

MedlinePlus

... this page: //medlineplus.gov/ency/article/007677.htm CT angiography - head and neck To use the sharing features on this page, please enable JavaScript. CT angiography (CTA) combines a CT scan with the ...

SU-E-J-256: Predicting Metastasis-Free Survival of Rectal Cancer Patients Treated with Neoadjuvant Chemo-Radiotherapy by Data-Mining of CT Texture Features of Primary Lesions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhong, H; Wang, J; Shen, L

Purpose: The purpose of this study is to investigate the relationship between computed tomographic (CT) texture features of primary lesions and metastasis-free survival for rectal cancer patients; and to develop a datamining prediction model using texture features. Methods: A total of 220 rectal cancer patients treated with neoadjuvant chemo-radiotherapy (CRT) were enrolled in this study. All patients underwent CT scans before CRT. The primary lesions on the CT images were delineated by two experienced oncologists. The CT images were filtered by Laplacian of Gaussian (LoG) filters with different filter values (1.0–2.5: from fine to coarse). Both filtered and unfiltered imagesmore » were analyzed using Gray-level Co-occurrence Matrix (GLCM) texture analysis with different directions (transversal, sagittal, and coronal). Totally, 270 texture features with different species, directions and filter values were extracted. Texture features were examined with Student’s t-test for selecting predictive features. Principal Component Analysis (PCA) was performed upon the selected features to reduce the feature collinearity. Artificial neural network (ANN) and logistic regression were applied to establish metastasis prediction models. Results: Forty-six of 220 patients developed metastasis with a follow-up time of more than 2 years. Sixtyseven texture features were significantly different in t-test (p<0.05) between patients with and without metastasis, and 12 of them were extremely significant (p<0.001). The Area-under-the-curve (AUC) of ANN was 0.72, and the concordance index (CI) of logistic regression was 0.71. The predictability of ANN was slightly better than logistic regression. Conclusion: CT texture features of primary lesions are related to metastasisfree survival of rectal cancer patients. Both ANN and logistic regression based models can be developed for prediction.« less

Classification of CT examinations for COPD visual severity analysis

NASA Astrophysics Data System (ADS)

Tan, Jun; Zheng, Bin; Wang, Xingwei; Pu, Jiantao; Gur, David; Sciurba, Frank C.; Leader, J. Ken

2012-03-01

In this study we present a computational method of CT examination classification into visual assessed emphysema severity. The visual severity categories ranged from 0 to 5 and were rated by an experienced radiologist. The six categories were none, trace, mild, moderate, severe and very severe. Lung segmentation was performed for every input image and all image features are extracted from the segmented lung only. We adopted a two-level feature representation method for the classification. Five gray level distribution statistics, six gray level co-occurrence matrix (GLCM), and eleven gray level run-length (GLRL) features were computed for each CT image depicted segment lung. Then we used wavelets decomposition to obtain the low- and high-frequency components of the input image, and again extract from the lung region six GLCM features and eleven GLRL features. Therefore our feature vector length is 56. The CT examinations were classified using the support vector machine (SVM) and k-nearest neighbors (KNN) and the traditional threshold (density mask) approach. The SVM classifier had the highest classification performance of all the methods with an overall sensitivity of 54.4% and a 69.6% sensitivity to discriminate "no" and "trace visually assessed emphysema. We believe this work may lead to an automated, objective method to categorically classify emphysema severity on CT exam.

Lung texture in serial thoracic CT scans: Assessment of change introduced by image registration1

PubMed Central

Cunliffe, Alexandra R.; Al-Hallaq, Hania A.; Labby, Zacariah E.; Pelizzari, Charles A.; Straus, Christopher; Sensakovic, William F.; Ludwig, Michelle; Armato, Samuel G.

2012-01-01

Purpose: The aim of this study was to quantify the effect of four image registration methods on lung texture features extracted from serial computed tomography (CT) scans obtained from healthy human subjects. Methods: Two chest CT scans acquired at different time points were collected retrospectively for each of 27 patients. Following automated lung segmentation, each follow-up CT scan was registered to the baseline scan using four algorithms: (1) rigid, (2) affine, (3) B-splines deformable, and (4) demons deformable. The registration accuracy for each scan pair was evaluated by measuring the Euclidean distance between 150 identified landmarks. On average, 1432 spatially matched 32 × 32-pixel region-of-interest (ROI) pairs were automatically extracted from each scan pair. First-order, fractal, Fourier, Laws’ filter, and gray-level co-occurrence matrix texture features were calculated in each ROI, for a total of 140 features. Agreement between baseline and follow-up scan ROI feature values was assessed by Bland–Altman analysis for each feature; the range spanned by the 95% limits of agreement of feature value differences was calculated and normalized by the average feature value to obtain the normalized range of agreement (nRoA). Features with small nRoA were considered “registration-stable.” The normalized bias for each feature was calculated from the feature value differences between baseline and follow-up scans averaged across all ROIs in every patient. Because patients had “normal” chest CT scans, minimal change in texture feature values between scan pairs was anticipated, with the expectation of small bias and narrow limits of agreement. Results: Registration with demons reduced the Euclidean distance between landmarks such that only 9% of landmarks were separated by ≥1 mm, compared with rigid (98%), affine (95%), and B-splines (90%). Ninety-nine of the 140 (71%) features analyzed yielded nRoA > 50% for all registration methods, indicating that the majority of feature values were perturbed following registration. Nineteen of the features (14%) had nRoA < 15% following demons registration, indicating relative feature value stability. Student's t-tests showed that the nRoA of these 19 features was significantly larger when rigid, affine, or B-splines registration methods were used compared with demons registration. Demons registration yielded greater normalized bias in feature value change than B-splines registration, though this difference was not significant (p = 0.15). Conclusions: Demons registration provided higher spatial accuracy between matched anatomic landmarks in serial CT scans than rigid, affine, or B-splines algorithms. Texture feature changes calculated in healthy lung tissue from serial CT scans were smaller following demons registration compared with all other algorithms. Though registration altered the values of the majority of texture features, 19 features remained relatively stable after demons registration, indicating their potential for detecting pathologic change in serial CT scans. Combined use of accurate deformable registration using demons and texture analysis may allow for quantitative evaluation of local changes in lung tissue due to disease progression or treatment response. PMID:22894392

Mazabraud's syndrome: case report and literature review

PubMed Central

Munksgaard, Peter Svenssen; Salkus, Giedrius; Iyer, Victor V; Fisker, Rune Vincents

2013-01-01

Mazabraud's syndrome is a rare disorder characterized by the association of single or multiple intramuscular myxomas with fibrous dysplasia. Here, we present the first case of Mazabraud's syndrome visualized on 18F-FDG PET/CT with histopathological confirmation of the myxoma. Our case demonstrates a slightly increased FDG uptake (SUVmax 2.1) within the myxomas and a moderately to highly increased tracer uptake (SUVmax 7.0) within the fibrous dysplastic lesions. The typical histological appearance of the intramuscular myxoma confirmed the radiological diagnosis. Further, we discuss the imaging findings and the histopathological features of this rare case with a review of the related literature. PMID:24198959

Radiological and Pathological Correlation in Anti-MDA5 Antibody-positive Interstitial Lung Disease: Rapidly Progressive Perilobular Opacities and Diffuse Alveolar Damage.

PubMed

Chino, Haruka; Sekine, Akimasa; Baba, Tomohisa; Iwasawa, Tae; Okudela, Koji; Takemura, Tamiko; Itoh, Harumi; Sato, Shinji; Suzuki, Yasuo; Ogura, Takashi

2016-01-01

We herein present the first case of rapidly progressive interstitial lung disease (RP-ILD) with anti-melanoma differentiation-associated protein 5 (MDA5) antibody evaluated by surgical lung biopsy (SLB). High-resolution CT scan revealed perilobular opacities, which rapidly became thicker and formed consolidation, resulting in remarkable loss of lung volume. Specimens taken from SLB revealed membranous organization with alveolar occlusion, dilation of alveolar ducts, and sacs with collapsed alveoli, which are typical features of diffuse alveolar damage (DAD). Rapidly progressive perilobular opacities may be characteristic of RP-ILD with anti-MDA5 antibody and DAD.

Radiomics of CT Features May Be Nonreproducible and Redundant: Influence of CT Acquisition Parameters.

PubMed

Berenguer, Roberto; Pastor-Juan, María Del Rosario; Canales-Vázquez, Jesús; Castro-García, Miguel; Villas, María Victoria; Legorburo, Francisco Mansilla; Sabater, Sebastià

2018-04-24

Purpose To identify the reproducible and nonredundant radiomics features (RFs) for computed tomography (CT). Materials and Methods Two phantoms were used to test RF reproducibility by using test-retest analysis, by changing the CT acquisition parameters (hereafter, intra-CT analysis), and by comparing five different scanners with the same CT parameters (hereafter, inter-CT analysis). Reproducible RFs were selected by using the concordance correlation coefficient (as a measure of the agreement between variables) and the coefficient of variation (defined as the ratio of the standard deviation to the mean). Redundant features were grouped by using hierarchical cluster analysis. Results A total of 177 RFs including intensity, shape, and texture features were evaluated. The test-retest analysis showed that 91% (161 of 177) of the RFs were reproducible according to concordance correlation coefficient. Reproducibility of intra-CT RFs, based on coefficient of variation, ranged from 89.3% (151 of 177) to 43.1% (76 of 177) where the pitch factor and the reconstruction kernel were modified, respectively. Reproducibility of inter-CT RFs, based on coefficient of variation, also showed large material differences, from 85.3% (151 of 177; wood) to only 15.8% (28 of 177; polyurethane). Ten clusters were identified after the hierarchical cluster analysis and one RF per cluster was chosen as representative. Conclusion Many RFs were redundant and nonreproducible. If all the CT parameters are fixed except field of view, tube voltage, and milliamperage, then the information provided by the analyzed RFs can be summarized in only 10 RFs (each representing a cluster) because of redundancy. © RSNA, 2018 Online supplemental material is available for this article.

TU-C-12A-12: Differentiating Bone Lesions and Degenerative Joint Disease in NaF PET/CT Scans Using Machine Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perk, T; Bradshaw, T; Muzahir, S

2014-06-15

Purpose: [F-18]NaF PET can be used to image bone metastases; however, tracer uptake in degenerative joint disease (DJD) often appears similar to metastases. This study aims to develop and compare different machine learning algorithms to automatically identify regions of [F-18]NaF scans that correspond to DJD. Methods: 10 metastatic prostate cancer patients received whole body [F-18]NaF PET/CT scans prior to treatment. Image segmentation resulted in 852 ROIs, 69 of which were identified by a nuclear medicine physician as DJD. For all ROIs, various PET and CT textural features were computed. ROIs were divided into training and testing sets used to trainmore » eight different machine learning classifiers. Classifiers were evaluated based on receiver operating characteristics area under the curve (AUC), sensitivity, specificity, and positive predictive value (PPV). We also assessed the added value of including CT features in addition to PET features for training classifiers. Results: The training set consisted of 37 DJD ROIs with 475 non-DJD ROIs, and the testing set consisted of 32 DJD ROIs with 308 non-DJD ROIs. Of all classifiers, generalized linear models (GLM), decision forests (DF), and support vector machines (SVM) had the best performance. AUCs of GLM (0.929), DF (0.921), and SVM (0.889) were significantly higher than the other models (p<0.001). GLM and DF, overall, had the best sensitivity, specificity, and PPV, and gave a significantly better performance (p<0.01) than all other models. PET/CT GLM classifiers had higher AUC than just PET or just CT. GLMs built using PET/CT information had superior or comparable sensitivities, specificities and PPVs to just PET or just CT. Conclusion: Machine learning algorithms trained with PET/CT features were able to identify some cases of DJD. GLM outperformed the other classification algorithms. Using PET and CT information together was shown to be superior to using PET or CT features alone. Research supported by the Prostate Cancer Foundation.« less

Classifying features in CT imagery: accuracy for some single- and multiple-species classifiers

Treesearch

Daniel L. Schmoldt; Jing He; A. Lynn Abbott

1998-01-01

Our current approach to automatically label features in CT images of hardwood logs classifies each pixel of an image individually. These feature classifiers use a back-propagation artificial neural network (ANN) and feature vectors that include a small, local neighborhood of pixels and the distance of the target pixel to the center of the log. Initially, this type of...

Ovarian torsion: diagnostic features on CT and MRI with pathologic correlation.

PubMed

Duigenan, Shauna; Oliva, Esther; Lee, Susanna I

2012-02-01

The CT and MRI features of ovarian torsion are illustrated with gross pathologic correlation. Ovarian enlargement with or without an underlying mass is the finding most frequently associated with torsion, but it is nonspecific. A twisted pedicle, although not often detected on imaging, is pathognomonic when seen. Subacute ovarian hemorrhage and abnormal enhancement is usually seen, and both features show characteristic patterns on CT and MRI. Ipsilateral uterine deviation can also be seen. Diagnostic pitfalls that may mimic ovarian torsion and observations for discriminating them are discussed.

CT of abdominal tuberculosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Epstein, B.M.; Mann, J.H.

1982-11-01

Intraabdominal tuberculosis (TB) presents with a wide variety of clinical and radiologic features. Besides the reported computed tomographic (CT) finding of high-density ascites in tuberculous peritonitis, this report describes additional CT features highly suggestive of abdominal tuberculosis in eight cases: (1) irregular soft-tissue densities in the omental area; (2) low-density masses surrounded by thick solid rims; (3) a disorganized appearance of soft-tissue densities, fluid, and bowel loops forming a poorly defined mass; (4) low-density lymph nodes with a multilocular appearance after intravenous contrast administration; and (5) possibly high-density ascites. The differential diagnosis of these features include lymphoma, various forms ofmore » peritonitis, peritoneal carcinomatosis, and peritoneal mesothelioma. It is important that the CT features of intraabdominal tuberculosis be recognized in order that laparotomy be avoided and less invasive procedures (e.g., laparoscopy, biopsy, or a trial of antituberculous therapy) be instituted.« less

MO-DE-207B-11: Reliability of PET/CT Radiomics Features in Functional and Morphological Components of NSCLC Lesions: A Repeatability Analysis in a Prospective Multicenter Cohort

DOE Office of Scientific and Technical Information (OSTI.GOV)

Desseroit, M; EE DACTIM, CHU de Poitiers, Poitiers; Tixier, F

2016-06-15

Purpose: The goal of this study was to evaluate the repeatability of radiomics features (intensity, shape and heterogeneity) in both PET and low-dose CT components of test-retest FDG-PET/CT images in a prospective multicenter cohort of 74 NSCLC patients from ACRIN 6678 and a similar Merck trial. Methods: Seventy-four patients with stage III-IV NCSLC were prospectively included. The primary tumor and up to 3 additional lesions per patient were analyzed. The Fuzzy Locally Adaptive Bayesian algorithm was used to automatically delineate metabolically active volume (MAV) in PET. The 3D SlicerTM software was exploited to delineate anatomical volumes (AV) in CT. Tenmore » intensity first-order features, as well as 26 textural features and four 3D shape descriptors were calculated from tumour volumes in both modalities. The repeatability of each metric was assessed by Bland-Altman analysis. Results: One hundred and five lesions (primary tumors and nodal or distant metastases) were delineated and characterized. The MAV and AV determination had a repeatability of −1.4±11.0% and −1.2±18.7% respectively. Several shape and heterogeneity features were found to be highly or moderately repeatable (e.g., sphericity, co-occurrence entropy or intensity size-zone matrix zone percentage), whereas others were confirmed as unreliable with much higher variability (more than twice that of the corresponding volume determination). Conclusion: Our results in this large multicenter cohort with more than 100 measurements confirm the PET findings in previous studies (with <30 lesions). In addition, our study is the first to explore the repeatability of radiomics features in the low-dose CT component of PET/CT acquisitions (previous studies considered dosimetry CT, CE-CT or CBCT). Several features were identified as reliable in both PET and CT components and could be used to build prognostic models. This work has received a French government support granted to the CominLabs excellence laboratory and managed by the National Research Agency in the “Investing for the Future” program under reference ANR-10-LABX-07-01, and support from the city of Brest.« less

High-Resolution X-Ray and Neutron Computed Tomography of an Engine Combustion Network Spray G Gasoline Injector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duke, Daniel J.; Finney, Charles E. A.; Kastengren, Alan

Given the importance of the fuel-injection process on the combustion and emissions performance of gasoline direct injected engines, there has been significant recent interest in understanding the fluid dynamics within the injector, particularly around the needle and through the nozzles. Furthermore, the pressure losses and transients that occur in the flow passages above the needle are also of interest. Simulations of these injectors typically use the nominal design geometry, which does not always match the production geometry. Computed tomography (CT) using x-ray and neutron sources can be used to obtain the real geometry from production injectors, but there are trade-offsmore » in using these techniques. X-ray CT provides high resolution, but cannot penetrate through the thicker parts of the injector. Neutron CT has excellent penetrating power but lower resolution. Here, we present results from a joint effort to characterize a gasoline direct injector representative of the Spray G injector as defined by the Engine Combustion Network. High-resolution (1.2 to 3 µm) x-ray CT measurements from the Advanced Photon Source at Argonne National Laboratory were combined with moderate-resolution (40 µm) neutron CT measurements from the High Flux Isotope Reactor at Oak Ridge National Laboratory to generate a complete internal geometry for the injector. This effort combined the strengths of both facilities’ capabilities, with extremely fine spatially resolved features in the nozzles and injector tips and fine resolution of internal features of the needle along the length of injector. Analysis of the resulting surface model of the internal fluid flow volumes of the injector reveals how the internal cross-sectional area and nozzle hole geometry differs slightly from the design dimensions. A simplified numerical simulation of the internal flow shows how deviations from the design geometry can alter the flow inside the sac and holes. Our results of this study will provide computational modelers with very accurate solid and surface models for use in computational fluid dynamics studies and experimentalists with increased insight into the operating characteristics of their injectors.« less

High-Resolution X-Ray and Neutron Computed Tomography of an Engine Combustion Network Spray G Gasoline Injector

DOE PAGES

Duke, Daniel J.; Finney, Charles E. A.; Kastengren, Alan; ...

2017-03-14

Given the importance of the fuel-injection process on the combustion and emissions performance of gasoline direct injected engines, there has been significant recent interest in understanding the fluid dynamics within the injector, particularly around the needle and through the nozzles. Furthermore, the pressure losses and transients that occur in the flow passages above the needle are also of interest. Simulations of these injectors typically use the nominal design geometry, which does not always match the production geometry. Computed tomography (CT) using x-ray and neutron sources can be used to obtain the real geometry from production injectors, but there are trade-offsmore » in using these techniques. X-ray CT provides high resolution, but cannot penetrate through the thicker parts of the injector. Neutron CT has excellent penetrating power but lower resolution. Here, we present results from a joint effort to characterize a gasoline direct injector representative of the Spray G injector as defined by the Engine Combustion Network. High-resolution (1.2 to 3 µm) x-ray CT measurements from the Advanced Photon Source at Argonne National Laboratory were combined with moderate-resolution (40 µm) neutron CT measurements from the High Flux Isotope Reactor at Oak Ridge National Laboratory to generate a complete internal geometry for the injector. This effort combined the strengths of both facilities’ capabilities, with extremely fine spatially resolved features in the nozzles and injector tips and fine resolution of internal features of the needle along the length of injector. Analysis of the resulting surface model of the internal fluid flow volumes of the injector reveals how the internal cross-sectional area and nozzle hole geometry differs slightly from the design dimensions. A simplified numerical simulation of the internal flow shows how deviations from the design geometry can alter the flow inside the sac and holes. Our results of this study will provide computational modelers with very accurate solid and surface models for use in computational fluid dynamics studies and experimentalists with increased insight into the operating characteristics of their injectors.« less

Prevalence of upper airway obstruction in patients with apparently asymptomatic euthyroid multi nodular goitre

PubMed Central

Menon, Sunil K.; Jagtap, Varsha S.; Sarathi, Vijaya; Lila, Anurag R.; Bandgar, Tushar R.; Menon, Padmavathy S; Shah, Nalini S.

2011-01-01

Aims: To study the prevalence of upper airway obstruction (UAO) in “apparently asymptomatic” patients with euthyroid multinodular goitre (MNG) and find correlation between clinical features, UAO on pulmonary function test (PFT) and tracheal narrowing on computerised tomography (CT). Materials and Methods: Consecutive patients with apparently asymptomatic euthyroid MNG attending thyroid clinic in a tertiary centre underwent clinical examination to elicit features of UAO, PFT, and CT of neck and chest. Statistical Analysis Used: Statistical analysis was done with SPSS version 11.5 using paired t-test, Chi square test, and Fisher's exact test. P value of <0.05 was considered to be significant. Results: Fifty-six patients (52 females and four males) were studied. The prevalence of UAO (PFT) and significant tracheal narrowing (CT) was 14.3%. and 9.3%, respectively. Clinical features failed to predict UAO or significant tracheal narrowing. Tracheal narrowing (CT) did not correlate with UAO (PFT). Volume of goitre significantly correlated with degree of tracheal narrowing. Conclusions: Clinical features do not predict UAO on PFT or tracheal narrowing on CT in apparently asymptomatic patients with euthyroid MNG. PMID:21966649

[Effect of X-ray micro-computed tomography on the metabolic activity and diversity of soil microbial communities in two Chinese soils].

PubMed

Zu, Qianhui; Fang, Huan; Zhou, Hu; Zhang, Jianwei; Peng, Xinhua; Lin, Xiangui; Feng, Youzhi

2016-01-04

X-ray micro-computed tomography (micro-CT) technology, as used in the in situ and nondestructive analysis of soil physical structure, provides the opportunity of associating soil physical and biological assays. Due to the high heterogeneity of the soil matrix, X-ray micro-CT scanning and soil microbial assays should be conducted on the same soil sample. This raises the question whether X-ray micro-CT influences microbial function and diversity of the sample soil to be analyzed. To address this question, we used plate counting, microcalorimetry and pyrosequencing approaches to evaluate the effect of X-ray--at doses typically used in micro-CT--on soil microorganisms in a typical soil of North China Plain, Fluvo-aquic soil and in a typical soil of subtropical China, Ultisol soil, respectively. In both soils radiation decreased the number of viable soil bacteria and disturbed their thermogenic profiles. At DNA level, pyrosequencing revealed that alpha diversities of two soils biota were influenced in opposite ways, while beta diversity was not affected although the relative abundances of some guilds were changed. These findings indicate that the metabolically active aspects of soil biota are not compatible with X-ray micro-CT; while the beta molecular diversity based on pyrosequencing could be compatible.

Reproducibility and Prognosis of Quantitative Features Extracted from CT Images12

PubMed Central

Balagurunathan, Yoganand; Gu, Yuhua; Wang, Hua; Kumar, Virendra; Grove, Olya; Hawkins, Sam; Kim, Jongphil; Goldgof, Dmitry B; Hall, Lawrence O; Gatenby, Robert A; Gillies, Robert J

2014-01-01

We study the reproducibility of quantitative imaging features that are used to describe tumor shape, size, and texture from computed tomography (CT) scans of non-small cell lung cancer (NSCLC). CT images are dependent on various scanning factors. We focus on characterizing image features that are reproducible in the presence of variations due to patient factors and segmentation methods. Thirty-two NSCLC nonenhanced lung CT scans were obtained from the Reference Image Database to Evaluate Response data set. The tumors were segmented using both manual (radiologist expert) and ensemble (software-automated) methods. A set of features (219 three-dimensional and 110 two-dimensional) was computed, and quantitative image features were statistically filtered to identify a subset of reproducible and nonredundant features. The variability in the repeated experiment was measured by the test-retest concordance correlation coefficient (CCCTreT). The natural range in the features, normalized to variance, was measured by the dynamic range (DR). In this study, there were 29 features across segmentation methods found with CCCTreT and DR ≥ 0.9 and R2Bet ≥ 0.95. These reproducible features were tested for predicting radiologist prognostic score; some texture features (run-length and Laws kernels) had an area under the curve of 0.9. The representative features were tested for their prognostic capabilities using an independent NSCLC data set (59 lung adenocarcinomas), where one of the texture features, run-length gray-level nonuniformity, was statistically significant in separating the samples into survival groups (P ≤ .046). PMID:24772210

Bilateral multifocal Warthin tumours.

PubMed

Deveer, Mehmet; Sahan, Murat; Sivrioglu, Ali Kemal; Celik, Ozgür Ilhan

2013-05-22

Warthin tumour, also known as papillary cystadenoma lymphomatosum, is the second most frequent benign tumour of the parotid gland after pleomorphic adenoma. A 57-year-old man was referred to our hospital with bilateral buccal masses without pain. He presented with a 1-year history of the condition and stated that growth of the mass has accelerated during the last 6 months. Ultrasonography examination showed two heterogeneous solid masses. Axial contrast-enhanced CT image revealed bilateral heterogeneous solid masses. The masses showed enhancement after contrast administration (95 HU). Fine needle aspiration cytology was recommended for further analysis and typical benign features of Warthin tumour was obtained. Right parotid gland including the masses was resected completely. 5 weeks later superficial parotidectomy was performed to the left parotid gland. Histological examination revealed cystic tumour in the parenchyma of parotid gland, composed of prominent lymphoid stroma and large epithelial cells with oncocytic features covering it consistent with Warthin tumour.

Bilateral multifocal Warthin tumours

PubMed Central

Deveer, Mehmet; Sahan, Murat; Sivrioglu, Ali Kemal; İlhan Celik, Özgür

2013-01-01

Warthin tumour, also known as papillary cystadenoma lymphomatosum, is the second most frequent benign tumour of the parotid gland after pleomorphic adenoma. A 57-year-old man was referred to our hospital with bilateral buccal masses without pain. He presented with a 1-year history of the condition and stated that growth of the mass has accelerated during the last 6 months. Ultrasonography examination showed two heterogeneous solid masses. Axial contrast-enhanced CT image revealed bilateral heterogeneous solid masses. The masses showed enhancement after contrast administration (95 HU). Fine needle aspiration cytology was recommended for further analysis and typical benign features of Warthin tumour was obtained. Right parotid gland including the masses was resected completely. 5 weeks later superficial parotidectomy was performed to the left parotid gland. Histological examination revealed cystic tumour in the parenchyma of parotid gland, composed of prominent lymphoid stroma and large epithelial cells with oncocytic features covering it consistent with Warthin tumour. PMID:23704438

Imaging of cerebellopontine angle lesions: an update. Part 1: enhancing extra-axial lesions.

PubMed

Bonneville, Fabrice; Savatovsky, Julien; Chiras, Jacques

2007-10-01

Computed tomography (CT) and magnetic resonance (MR) imaging reliably demonstrate typical features of vestibular schwannomas or meningiomas in the vast majority of mass lesions in the cerebellopontine angle (CPA). However, a large variety of unusual lesions can also be encountered in the CPA. Covering the entire spectrum of lesions potentially found in the CPA, these articles explain the pertinent neuroimaging features that radiologists need to know to make clinically relevant diagnoses in these cases, including data from diffusion and perfusion-weighted imaging or MR spectroscopy, when available. A diagnostic algorithm based on the lesion's site of origin, shape and margins, density, signal intensity and contrast material uptake is also proposed. Part 1 describes the different enhancing extra-axial CPA masses primarily arising from the cerebellopontine cistern and its contents, including vestibular and non-vestibular schwannomas, meningioma, metastasis, aneurysm, tuberculosis and other miscellaneous meningeal lesions.

Analytical fuel property effects: Small combustors, phase 2

NASA Technical Reports Server (NTRS)

Hill, T. G.; Monty, J. D.; Morton, H. L.

1985-01-01

The effects of non-standard aviation fuels on a typical small gas turbine combustor were studied and the effectiveness of design changes intended to counter the effects of these fuels was evaluated. The T700/CT7 turboprop engine family was chosen as being representative of the class of aircraft power plants desired for this study. Fuel properties, as specified by NASA, are characterized by low hydrogen content and high aromatics levels. No. 2 diesel fuel was also evaluated in this program. Results demonstrated the anticipated higher than normal smoke output and flame radiation intensity with resulting increased metal temperatures on the baseline T700 combustor. Three new designs were evaluated using the non standard fuels. The three designs incorporated enhanced cooling features and smoke reduction features. All three designs, when burning the broad specification fuels, exhibited metal temperatures at or below the baseline combustor temperatures on JP-5. Smoke levels were acceptable but higher than predicted.

TU-C-12A-09: Modeling Pathologic Response of Locally Advanced Esophageal Cancer to Chemo-Radiotherapy Using Quantitative PET/CT Features, Clinical Parameters and Demographics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, H; Chen, W; Kligerman, S

2014-06-15

Purpose: To develop predictive models using quantitative PET/CT features for the evaluation of tumor response to neoadjuvant chemo-radiotherapy (CRT) in patients with locally advanced esophageal cancer. Methods: This study included 20 patients who underwent tri-modality therapy (CRT + surgery) and had {sup 18}F-FDG PET/CT scans before initiation of CRT and 4-6 weeks after completion of CRT but prior to surgery. Four groups of tumor features were examined: (1) conventional PET/CT response measures (SUVmax, tumor diameter, etc.); (2) clinical parameters (TNM stage, histology, etc.) and demographics; (3) spatial-temporal PET features, which characterize tumor SUV intensity distribution, spatial patterns, geometry, and associatedmore » changes resulting from CRT; and (4) all features combined. An optimal feature set was identified with recursive feature selection and cross-validations. Support vector machine (SVM) and logistic regression (LR) models were constructed for prediction of pathologic tumor response to CRT, using cross-validations to avoid model over-fitting. Prediction accuracy was assessed via area under the receiver operating characteristic curve (AUC), and precision was evaluated via confidence intervals (CIs) of AUC. Results: When applied to the 4 groups of tumor features, the LR model achieved AUCs (95% CI) of 0.57 (0.10), 0.73 (0.07), 0.90 (0.06), and 0.90 (0.06). The SVM model achieved AUCs (95% CI) of 0.56 (0.07), 0.60 (0.06), 0.94 (0.02), and 1.00 (no misclassifications). Using spatial-temporal PET features combined with conventional PET/CT measures and clinical parameters, the SVM model achieved very high accuracy (AUC 1.00) and precision (no misclassifications), significantly better than using conventional PET/CT measures or clinical parameters and demographics alone. For groups with a large number of tumor features (groups 3 and 4), the SVM model achieved significantly higher accuracy than the LR model. Conclusion: The SVM model using all features including quantitative PET/CT features accurately and precisely predicted pathologic tumor response to CRT in esophageal cancer. This work was supported in part by National Cancer Institute Grant R21 CA131979 and R01 CA172638. Shan Tan was supported in part by the National Natural Science Foundation of China 60971112 and 61375018, and by Fundamental Research Funds for the Central Universities 2012QN086.« less

Prediction of Late Postoperative Hemorrhage after Whipple Procedure Using Computed Tomography Performed During Early Postoperative Period.

PubMed

Han, Ga Jin; Kim, Suk; Lee, Nam Kyung; Kim, Chang Won; Seo, Hyeong Il; Kim, Hyun Sung; Kim, Tae Un

2018-01-01

Postpancreatectomy hemorrhage (PPH) is an uncommon but serious complication of Whipple surgery. To evaluate the radiologic features associated with late PPH at the first postoperative follow up CT, before bleeding. To evaluate the radiological features associated with late PPH at the first follow-up CT, two radiologists retrospectively reviewed the initial postoperative follow-up CT images of 151 patients, who had undergone Whipple surgery. Twenty patients showed PPH due to vascular problem or anastomotic ulcer. The research compared CT and clinical findings of 20 patients with late PPH and 131 patients without late PPH, including presence of suggestive feature of pancreatic fistula (presence of air at fluid along pancreaticojejunostomy [PJ]), abscess (fluid collection with an enhancing rim or gas), fluid along hepaticojejunostomy or PJ, the density of ascites, and the size of visible gastroduodenal artery (GDA) stump. CT findings including pancreatic fistula, abscess, and large GDA stump were associated with PPH on univariate analysis ( p ≤ 0.009). On multivariate analysis, radiological features suggestive of a pancreatic fistula, abscess, and a GDA stump > 4.45 mm were associated with PPH ( p ≤ 0.031). Early postoperative CT findings including GDA stump size larger than 4.45 mm, fluid collection with an enhancing rim or gas, and air at fluid along PJ, could predict late PPH.

Three-dimensional texture analysis of contrast enhanced CT images for treatment response assessment in Hodgkin lymphoma: Comparison with F-18-FDG PET

DOE Office of Scientific and Technical Information (OSTI.GOV)

Knogler, Thomas; El-Rabadi, Karem; Weber, Michael

2014-12-15

Purpose: To determine the diagnostic performance of three-dimensional (3D) texture analysis (TA) of contrast-enhanced computed tomography (CE-CT) images for treatment response assessment in patients with Hodgkin lymphoma (HL), compared with F-18-fludeoxyglucose (FDG) positron emission tomography/CT. Methods: 3D TA of 48 lymph nodes in 29 patients was performed on venous-phase CE-CT images before and after chemotherapy. All lymph nodes showed pathologically elevated FDG uptake at baseline. A stepwise logistic regression with forward selection was performed to identify classic CT parameters and texture features (TF) that enable the separation of complete response (CR) and persistent disease. Results: The TF fraction of imagemore » in runs, calculated for the 45° direction, was able to correctly identify CR with an accuracy of 75%, a sensitivity of 79.3%, and a specificity of 68.4%. Classical CT features achieved an accuracy of 75%, a sensitivity of 86.2%, and a specificity of 57.9%, whereas the combination of TF and CT imaging achieved an accuracy of 83.3%, a sensitivity of 86.2%, and a specificity of 78.9%. Conclusions: 3D TA of CE-CT images is potentially useful to identify nodal residual disease in HL, with a performance comparable to that of classical CT parameters. Best results are achieved when TA and classical CT features are combined.« less

Diagnostic performance and useful findings of ultrasound re-evaluation for patients with equivocal CT features of acute appendicitis.

PubMed

Kim, Mi Sung; Kwon, Heon-Ju; Kang, Kyung A; Do, In-Gu; Park, Hee-Jin; Kim, Eun Young; Hong, Hyun Pyo; Choi, Yoon Jung; Kim, Young Hwan

2018-02-01

To evaluate the diagnostic performance of ultrasound and to determine which ultrasound findings are useful to differentiate appendicitis from non-appendicitis in patients who underwent ultrasound re-evaluation owing to equivocal CT features of acute appendicitis. 62 patients who underwent CT examinations for suspected appendicitis followed by ultrasound re-evaluation owing to equivocal CT findings were included. Equivocal CT findings were considered based on the presence of only one or two findings among the CT criteria, and ultrasound re-evaluation was done based on a predefined structured report form. The diagnostic performance of ultrasound and independent variables to discriminate appendicitis from non-appendicitis were assessed. There were 27 patients in the appendicitis group. The overall diagnostic performance of ultrasound re-evaluation was sensitivity of 96.3%, specificity of 91.2% and accuracy of 91.9%. In terms of the performance of individual ultrasound findings, probe-induced tenderness showed the highest accuracy (86.7%) with sensitivity of 74% and specificity of 97%, followed by non-compressibility (accuracy 71.7%, sensitivity 85.2% and specificity 60.6%). The independent ultrasound findings for discriminating appendicitis were non-compressibility (p = 0.002) and increased flow on the appendiceal wall (p = 0.001). Ultrasound re-evaluation can be used to improve diagnostic accuracy in cases with equivocal CT features for diagnosing appendicitis. The presence of non-compressibility and increased vascular flow on the appendix wall are useful ultrasound findings to discriminate appendicitis from non-appendicitis. Advances in knowledge: Ultrasound re-evaluation is useful to discriminate appendicitis from non-appendicitis when CT features are inconclusive.

SU-F-R-46: Predicting Distant Failure in Lung SBRT Using Multi-Objective Radiomics Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Z; Folkert, M; Iyengar, P

2016-06-15

Purpose: To predict distant failure in lung stereotactic body radiation therapy (SBRT) in early stage non-small cell lung cancer (NSCLC) by using a new multi-objective radiomics model. Methods: Currently, most available radiomics models use the overall accuracy as the objective function. However, due to data imbalance, a single object may not reflect the performance of a predictive model. Therefore, we developed a multi-objective radiomics model which considers both sensitivity and specificity as the objective functions simultaneously. The new model is used to predict distant failure in lung SBRT using 52 patients treated at our institute. Quantitative imaging features of PETmore » and CT as well as clinical parameters are utilized to build the predictive model. Image features include intensity features (9), textural features (12) and geometric features (8). Clinical parameters for each patient include demographic parameters (4), tumor characteristics (8), treatment faction schemes (4) and pretreatment medicines (6). The modelling procedure consists of two steps: extracting features from segmented tumors in PET and CT; and selecting features and training model parameters based on multi-objective. Support Vector Machine (SVM) is used as the predictive model, while a nondominated sorting-based multi-objective evolutionary computation algorithm II (NSGA-II) is used for solving the multi-objective optimization. Results: The accuracy for PET, clinical, CT, PET+clinical, PET+CT, CT+clinical, PET+CT+clinical are 71.15%, 84.62%, 84.62%, 85.54%, 82.69%, 84.62%, 86.54%, respectively. The sensitivities for the above seven combinations are 41.76%, 58.33%, 50.00%, 50.00%, 41.67%, 41.67%, 58.33%, while the specificities are 80.00%, 92.50%, 90.00%, 97.50%, 92.50%, 97.50%, 97.50%. Conclusion: A new multi-objective radiomics model for predicting distant failure in NSCLC treated with SBRT was developed. The experimental results show that the best performance can be obtained by combining all features.« less

CT scan

MedlinePlus

... this page: //medlineplus.gov/ency/article/003330.htm CT scan To use the sharing features on this page, please enable JavaScript. A computed tomography (CT) scan is an imaging method that uses x- ...

SU-G-IeP4-10: Microimaging for Different Degrees of Human Cavernous Hemangioma of Liver by Using In-Line Phase-Contrast Imaging CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duan, J

2016-06-15

Purpose: Cavernous hemangioma of the liver (CHL) is the most common benign solid tumor of the liver. In this study, we quantitative assessment the different degrees of CHL from microscopic viewpoint by using in-line phase-contrast imaging CT (ILPCI-CT). Methods: The experiments were performed at x-ray imaging and biomedical application beamline (BL13W1) of Shanghai Synchrotron Radiation Facility (SSRF) in China. Three typical specimens at different stages, i.e., mild, moderate and severe human CHL were imaged using ILPCI-CT at 16keV without contrast agents. The 3D visualization of different degrees of CHL samples were presented using ILPCI-CT. Additionally, quantitative evaluation of the CHLmore » features, such as the range of hepatic sinusoid equivalent diameters in different degrees of CHL samples, the ratio of the hepatic sinusoid to the CHL tissue, were measured. Results: The planar image clearly displayed the dilated hepatic sinusoids in microns. There was no normal hepatic vascular found in the all CHL samples. Different stages of CHL samples were presented with vivid shapes and stereoscopic effects by using 3D visualization. The equivalent diameters of hepatic sinusoids in three degrees CHL were different. The equivalent diameters of the hepatic sinusoids in mild CHL, range from 60 to 120 µm. The equivalent diameters of the hepatic sinusoids in moderate CHL, range from 65 to 190 µm. The equivalent diameters of the hepatic sinusoids in severe CHL, range from 95 to 215 µm. The ratio of the hepatic sinusoid to the mild, moderate and severe CHL tissue were 3%, 16% and 21%, respectively. Conclusion: The results show that the high degree of sensitivity of the ILPCI-CT technique and demonstrate the feasibility of accurate visualization of different stage human CHL. ILPCI-CT may offers a potential use in non-invasive study and analysis of CHL.« less

CT in the diagnosis of interstitial lung disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bergin, C.J.; Mueller, N.L.

1985-09-01

The computed tomographic (CT) appearance of interstitial lung disease was assessed in 23 patients with known interstitial disease. These included seven patients with fibrosing alveolitis, six with silicosis, two with hypersensitivity pneumonitis, three with lymphangitic spread of tumor, two with sarcoidosis, one with rheumatoid lung disease, and two with neurofibromatosis. The CT appearance of the interstitial changes in the different disease entities was assessed. Nodules were a prominent CT feature in silicosis, sarcoidosis, and lymphangitic spread of malignancy. Distribution of nodules and associated interlobular septal thickening provided further distinguishing features in these diseases. Reticular densities were the predominant CT changemore » in fibrosing alveolitis, rheumatoid lung disease, and extrinsic allergic alveolitis. CT can be useful in the investigation of selected instances of interstitial pulmonary disease.« less

Texture feature extraction based on a uniformity estimation method for local brightness and structure in chest CT images.

PubMed

Peng, Shao-Hu; Kim, Deok-Hwan; Lee, Seok-Lyong; Lim, Myung-Kwan

2010-01-01

Texture feature is one of most important feature analysis methods in the computer-aided diagnosis (CAD) systems for disease diagnosis. In this paper, we propose a Uniformity Estimation Method (UEM) for local brightness and structure to detect the pathological change in the chest CT images. Based on the characteristics of the chest CT images, we extract texture features by proposing an extension of rotation invariant LBP (ELBP(riu4)) and the gradient orientation difference so as to represent a uniform pattern of the brightness and structure in the image. The utilization of the ELBP(riu4) and the gradient orientation difference allows us to extract rotation invariant texture features in multiple directions. Beyond this, we propose to employ the integral image technique to speed up the texture feature computation of the spatial gray level dependent method (SGLDM). Copyright © 2010 Elsevier Ltd. All rights reserved.

Higher-order scene statistics of breast images

NASA Astrophysics Data System (ADS)

Abbey, Craig K.; Sohl-Dickstein, Jascha N.; Olshausen, Bruno A.; Eckstein, Miguel P.; Boone, John M.

2009-02-01

Researchers studying human and computer vision have found description and construction of these systems greatly aided by analysis of the statistical properties of naturally occurring scenes. More specifically, it has been found that receptive fields with directional selectivity and bandwidth properties similar to mammalian visual systems are more closely matched to the statistics of natural scenes. It is argued that this allows for sparse representation of the independent components of natural images [Olshausen and Field, Nature, 1996]. These theories have important implications for medical image perception. For example, will a system that is designed to represent the independent components of natural scenes, where objects occlude one another and illumination is typically reflected, be appropriate for X-ray imaging, where features superimpose on one another and illumination is transmissive? In this research we begin to examine these issues by evaluating higher-order statistical properties of breast images from X-ray projection mammography (PM) and dedicated breast computed tomography (bCT). We evaluate kurtosis in responses of octave bandwidth Gabor filters applied to PM and to coronal slices of bCT scans. We find that kurtosis in PM rises and quickly saturates for filter center frequencies with an average value above 0.95. By contrast, kurtosis in bCT peaks near 0.20 cyc/mm with kurtosis of approximately 2. Our findings suggest that the human visual system may be tuned to represent breast tissue more effectively in bCT over a specific range of spatial frequencies.

Deep-learning derived features for lung nodule classification with limited datasets

NASA Astrophysics Data System (ADS)

Thammasorn, P.; Wu, W.; Pierce, L. A.; Pipavath, S. N.; Lampe, P. D.; Houghton, A. M.; Haynor, D. R.; Chaovalitwongse, W. A.; Kinahan, P. E.

2018-02-01

Only a few percent of indeterminate nodules found in lung CT images are cancer. However, enabling earlier diagnosis is important to avoid invasive procedures or long-time surveillance to those benign nodules. We are evaluating a classification framework using radiomics features derived with a machine learning approach from a small data set of indeterminate CT lung nodule images. We used a retrospective analysis of 194 cases with pulmonary nodules in the CT images with or without contrast enhancement from lung cancer screening clinics. The nodules were contoured by a radiologist and texture features of the lesion were calculated. In addition, sematic features describing shape were categorized. We also explored a Multiband network, a feature derivation path that uses a modified convolutional neural network (CNN) with a Triplet Network. This was trained to create discriminative feature representations useful for variable-sized nodule classification. The diagnostic accuracy was evaluated for multiple machine learning algorithms using texture, shape, and CNN features. In the CT contrast-enhanced group, the texture or semantic shape features yielded an overall diagnostic accuracy of 80%. Use of a standard deep learning network in the framework for feature derivation yielded features that substantially underperformed compared to texture and/or semantic features. However, the proposed Multiband approach of feature derivation produced results similar in diagnostic accuracy to the texture and semantic features. While the Multiband feature derivation approach did not outperform the texture and/or semantic features, its equivalent performance indicates promise for future improvements to increase diagnostic accuracy. Importantly, the Multiband approach adapts readily to different size lesions without interpolation, and performed well with relatively small amount of training data.

TU-CD-BRB-01: Normal Lung CT Texture Features Improve Predictive Models for Radiation Pneumonitis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krafft, S; The University of Texas Graduate School of Biomedical Sciences, Houston, TX; Briere, T

2015-06-15

Purpose: Existing normal tissue complication probability (NTCP) models for radiation pneumonitis (RP) traditionally rely on dosimetric and clinical data but are limited in terms of performance and generalizability. Extraction of pre-treatment image features provides a potential new category of data that can improve NTCP models for RP. We consider quantitative measures of total lung CT intensity and texture in a framework for prediction of RP. Methods: Available clinical and dosimetric data was collected for 198 NSCLC patients treated with definitive radiotherapy. Intensity- and texture-based image features were extracted from the T50 phase of the 4D-CT acquired for treatment planning. Amore » total of 3888 features (15 clinical, 175 dosimetric, and 3698 image features) were gathered and considered candidate predictors for modeling of RP grade≥3. A baseline logistic regression model with mean lung dose (MLD) was first considered. Additionally, a least absolute shrinkage and selection operator (LASSO) logistic regression was applied to the set of clinical and dosimetric features, and subsequently to the full set of clinical, dosimetric, and image features. Model performance was assessed by comparing area under the curve (AUC). Results: A simple logistic fit of MLD was an inadequate model of the data (AUC∼0.5). Including clinical and dosimetric parameters within the framework of the LASSO resulted in improved performance (AUC=0.648). Analysis of the full cohort of clinical, dosimetric, and image features provided further and significant improvement in model performance (AUC=0.727). Conclusions: To achieve significant gains in predictive modeling of RP, new categories of data should be considered in addition to clinical and dosimetric features. We have successfully incorporated CT image features into a framework for modeling RP and have demonstrated improved predictive performance. Validation and further investigation of CT image features in the context of RP NTCP modeling is warranted. This work was supported by the Rosalie B. Hite Fellowship in Cancer research awarded to SPK.« less

Imaging Characteristics of Pathologically Proven Thymic Hyperplasia: Identifying Features That Can Differentiate True From Lymphoid Hyperplasia

PubMed Central

Araki, Tetsuro; Sholl, Lynette M.; Gerbaudo, Victor H.; Hatabu, Hiroto; Nishino, Mizuki

2014-01-01

OBJECTIVE The purpose of this article is to investigate the imaging characteristics of pathologically proven thymic hyperplasia and to identify features that can differentiate true hyperplasia from lymphoid hyperplasia. MATERIALS AND METHODS Thirty-one patients (nine men and 22 women; age range, 20–68 years) with pathologically confirmed thymic hyperplasia (18 true and 13 lymphoid) who underwent preoperative CT (n = 27), PET/CT (n = 5), or MRI (n = 6) were studied. The length and thickness of each thymic lobe and the transverse and anterior-posterior diameters and attenuation of the thymus were measured on CT. Thymic morphologic features and heterogeneity on CT and chemical shift on MRI were evaluated. Maximum standardized uptake values were measured on PET. Imaging features between true and lymphoid hyperplasia were compared. RESULTS No significant differences were observed between true and lymphoid hyperplasia in terms of thymic length, thickness, diameters, morphologic features, and other qualitative features (p > 0.16). The length, thickness, and diameters of thymic hyperplasia were significantly larger than the mean values of normal glands in the corresponding age group (p < 0.001). CT attenuation of lymphoid hyperplasia was significantly higher than that of true hyperplasia among 15 patients with contrast-enhanced CT (median, 47.9 vs 31.4 HU; Wilcoxon p = 0.03). The receiver operating characteristic analysis yielded greater than 41.2 HU as the optimal threshold for differentiating lymphoid hyperplasia from true hyperplasia, with 83% sensitivity and 89% specificity. A decrease of signal intensity on opposed-phase images was present in all four cases with in- and opposed-phase imaging. The mean maximum standardized uptake value was 2.66. CONCLUSION CT attenuation of the thymus was significantly higher in lymphoid hyperplasia than in true hyperplasia, with an optimal threshold of greater than 41.2 HU in this cohort of patients with pathologically confirmed thymic hyperplasia. PMID:24555583

Localized thin-section CT with radiomics feature extraction and machine learning to classify early-detected pulmonary nodules from lung cancer screening

NASA Astrophysics Data System (ADS)

Tu, Shu-Ju; Wang, Chih-Wei; Pan, Kuang-Tse; Wu, Yi-Cheng; Wu, Chen-Te

2018-03-01

Lung cancer screening aims to detect small pulmonary nodules and decrease the mortality rate of those affected. However, studies from large-scale clinical trials of lung cancer screening have shown that the false-positive rate is high and positive predictive value is low. To address these problems, a technical approach is greatly needed for accurate malignancy differentiation among these early-detected nodules. We studied the clinical feasibility of an additional protocol of localized thin-section CT for further assessment on recalled patients from lung cancer screening tests. Our approach of localized thin-section CT was integrated with radiomics features extraction and machine learning classification which was supervised by pathological diagnosis. Localized thin-section CT images of 122 nodules were retrospectively reviewed and 374 radiomics features were extracted. In this study, 48 nodules were benign and 74 malignant. There were nine patients with multiple nodules and four with synchronous multiple malignant nodules. Different machine learning classifiers with a stratified ten-fold cross-validation were used and repeated 100 times to evaluate classification accuracy. Of the image features extracted from the thin-section CT images, 238 (64%) were useful in differentiating between benign and malignant nodules. These useful features include CT density (p  =  0.002 518), sigma (p  =  0.002 781), uniformity (p  =  0.032 41), and entropy (p  =  0.006 685). The highest classification accuracy was 79% by the logistic classifier. The performance metrics of this logistic classification model was 0.80 for the positive predictive value, 0.36 for the false-positive rate, and 0.80 for the area under the receiver operating characteristic curve. Our approach of direct risk classification supervised by the pathological diagnosis with localized thin-section CT and radiomics feature extraction may support clinical physicians in determining truly malignant nodules and therefore reduce problems in lung cancer screening.

Localized thin-section CT with radiomics feature extraction and machine learning to classify early-detected pulmonary nodules from lung cancer screening.

PubMed

Tu, Shu-Ju; Wang, Chih-Wei; Pan, Kuang-Tse; Wu, Yi-Cheng; Wu, Chen-Te

2018-03-14

Lung cancer screening aims to detect small pulmonary nodules and decrease the mortality rate of those affected. However, studies from large-scale clinical trials of lung cancer screening have shown that the false-positive rate is high and positive predictive value is low. To address these problems, a technical approach is greatly needed for accurate malignancy differentiation among these early-detected nodules. We studied the clinical feasibility of an additional protocol of localized thin-section CT for further assessment on recalled patients from lung cancer screening tests. Our approach of localized thin-section CT was integrated with radiomics features extraction and machine learning classification which was supervised by pathological diagnosis. Localized thin-section CT images of 122 nodules were retrospectively reviewed and 374 radiomics features were extracted. In this study, 48 nodules were benign and 74 malignant. There were nine patients with multiple nodules and four with synchronous multiple malignant nodules. Different machine learning classifiers with a stratified ten-fold cross-validation were used and repeated 100 times to evaluate classification accuracy. Of the image features extracted from the thin-section CT images, 238 (64%) were useful in differentiating between benign and malignant nodules. These useful features include CT density (p  =  0.002 518), sigma (p  =  0.002 781), uniformity (p  =  0.032 41), and entropy (p  =  0.006 685). The highest classification accuracy was 79% by the logistic classifier. The performance metrics of this logistic classification model was 0.80 for the positive predictive value, 0.36 for the false-positive rate, and 0.80 for the area under the receiver operating characteristic curve. Our approach of direct risk classification supervised by the pathological diagnosis with localized thin-section CT and radiomics feature extraction may support clinical physicians in determining truly malignant nodules and therefore reduce problems in lung cancer screening.

Can CT and MR Shape and Textural Features Differentiate Benign Versus Malignant Pleural Lesions?

PubMed

Pena, Elena; Ojiaku, MacArinze; Inacio, Joao R; Gupta, Ashish; Macdonald, D Blair; Shabana, Wael; Seely, Jean M; Rybicki, Frank J; Dennie, Carole; Thornhill, Rebecca E

2017-10-01

The study aimed to identify a radiomic approach based on CT and or magnetic resonance (MR) features (shape and texture) that may help differentiate benign versus malignant pleural lesions, and to assess if the radiomic model may improve confidence and accuracy of radiologists with different subspecialty backgrounds. Twenty-nine patients with pleural lesions studied on both contrast-enhanced CT and MR imaging were reviewed retrospectively. Three texture and three shape features were extracted. Combinations of features were used to generate logistic regression models using histopathology as outcome. Two thoracic and two abdominal radiologists evaluated their degree of confidence in malignancy. Diagnostic accuracy of radiologists was determined using contingency tables. Cohen's kappa coefficient was used to assess inter-reader agreement. Using optimal threshold criteria, sensitivity, specificity, and accuracy of each feature and combination of features were obtained and compared to the accuracy and confidence of radiologists. The CT model that best discriminated malignant from benign lesions revealed an AUC CT  = 0.92 ± 0.05 (P < 0.0001). The most discriminative MR model showed an AUC MR  = 0.87 ± 0.09 (P < 0.0001). The CT model was compared to the diagnostic confidence of all radiologists and the model outperformed both abdominal radiologists (P < 0.002), whereas the top discriminative MR model outperformed one of the abdominal radiologists (P = 0.02). The most discriminative MR model was more accurate than one abdominal (P = 0.04) and one thoracic radiologist (P = 0.02). Quantitative textural and shape analysis may help distinguish malignant from benign lesions. A radiomics-based approach may increase diagnostic confidence of abdominal radiologists on CT and MR and may potentially improve radiologists' accuracy in the assessment of pleural lesions characterized by MR. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Pulmonary tularaemia: all that looks like cancer is not necessarily cancer - case report of four consecutive cases.

PubMed

Fachinger, Patrick; Tini, Gabrielo Mauro; Grobholz, Rainer; Gambazzi, Franco; Fankhauser, Hans; Irani, Sarosh

2015-03-26

Pulmonary tularaemia is a very rare disease with only a small number of cases described in the literature. So far, to our knowledge, there exists no case report of pulmonary tularaemia where PET-CT scans and follow up CT scans are available. We present four consecutive cases of pulmonary tularaemia. All patients suffered from non-specific symptoms. All patients were referred to our institution with strong suspicions of malignancy, particularly lung cancer. Diagnosis of tularaemia was made by typical findings in the aspirate of EBUS guided fine needle aspiration (necrosis, epithelioid cell aggregation) and surgical biopsy respectively, and a positive serology. In three of the four cases, the diagnosis was confirmed by positive PCR results of the tissue. PET-CT scans obtained in all four cases were indistinguishable from lesions typically seen in patients suffering from lung cancer. One of the four patients suffered from recurrence of the disease after antibiotic treatment; also this patient finally recovered after initiation of a second antibiotic regimen. One case became asymptomatic spontaneously, but this patient still received an antibiotic treatment. In one case, a follow up CT scan was unchanged compared to the initial PET-CT scan; in all other cases, the lesions disappeared almost completely. Symptoms of patients suffering from pulmonary tularaemia are non-specific and can be of prolonged character. PET-CT scans in these cases are indistinguishable from lung cancer. The diagnosis can be established when typical findings in EBUS guided fine needle aspirates or surgical biopsies are found in combination with a positive serology. In most cases the lesions disappear in follow up CT scans after clinically successful treatment.

SU-E-J-275: Review - Computerized PET/CT Image Analysis in the Evaluation of Tumor Response to Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, W; Wang, J; Zhang, H

Purpose: To review the literature in using computerized PET/CT image analysis for the evaluation of tumor response to therapy. Methods: We reviewed and summarized more than 100 papers that used computerized image analysis techniques for the evaluation of tumor response with PET/CT. This review mainly covered four aspects: image registration, tumor segmentation, image feature extraction, and response evaluation. Results: Although rigid image registration is straightforward, it has been shown to achieve good alignment between baseline and evaluation scans. Deformable image registration has been shown to improve the alignment when complex deformable distortions occur due to tumor shrinkage, weight loss ormore » gain, and motion. Many semi-automatic tumor segmentation methods have been developed on PET. A comparative study revealed benefits of high levels of user interaction with simultaneous visualization of CT images and PET gradients. On CT, semi-automatic methods have been developed for only tumors that show marked difference in CT attenuation between the tumor and the surrounding normal tissues. Quite a few multi-modality segmentation methods have been shown to improve accuracy compared to single-modality algorithms. Advanced PET image features considering spatial information, such as tumor volume, tumor shape, total glycolytic volume, histogram distance, and texture features have been found more informative than the traditional SUVmax for the prediction of tumor response. Advanced CT features, including volumetric, attenuation, morphologic, structure, and texture descriptors, have also been found advantage over the traditional RECIST and WHO criteria in certain tumor types. Predictive models based on machine learning technique have been constructed for correlating selected image features to response. These models showed improved performance compared to current methods using cutoff value of a single measurement for tumor response. Conclusion: This review showed that computerized PET/CT image analysis holds great potential to improve the accuracy in evaluation of tumor response. This work was supported in part by the National Cancer Institute Grant R01CA172638.« less

Texture-based segmentation and analysis of emphysema depicted on CT images

NASA Astrophysics Data System (ADS)

Tan, Jun; Zheng, Bin; Wang, Xingwei; Lederman, Dror; Pu, Jiantao; Sciurba, Frank C.; Gur, David; Leader, J. Ken

2011-03-01

In this study we present a texture-based method of emphysema segmentation depicted on CT examination consisting of two steps. Step 1, a fractal dimension based texture feature extraction is used to initially detect base regions of emphysema. A threshold is applied to the texture result image to obtain initial base regions. Step 2, the base regions are evaluated pixel-by-pixel using a method that considers the variance change incurred by adding a pixel to the base in an effort to refine the boundary of the base regions. Visual inspection revealed a reasonable segmentation of the emphysema regions. There was a strong correlation between lung function (FEV1%, FEV1/FVC, and DLCO%) and fraction of emphysema computed using the texture based method, which were -0.433, -.629, and -0.527, respectively. The texture-based method produced more homogeneous emphysematous regions compared to simple thresholding, especially for large bulla, which can appear as speckled regions in the threshold approach. In the texture-based method, single isolated pixels may be considered as emphysema only if neighboring pixels meet certain criteria, which support the idea that single isolated pixels may not be sufficient evidence that emphysema is present. One of the strength of our complex texture-based approach to emphysema segmentation is that it goes beyond existing approaches that typically extract a single or groups texture features and individually analyze the features. We focus on first identifying potential regions of emphysema and then refining the boundary of the detected regions based on texture patterns.

Integrating dimension reduction and out-of-sample extension in automated classification of ex vivo human patellar cartilage on phase contrast X-ray computed tomography.

PubMed

Nagarajan, Mahesh B; Coan, Paola; Huber, Markus B; Diemoz, Paul C; Wismüller, Axel

2015-01-01

Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated as a novel imaging technique that can visualize human cartilage with high spatial resolution and soft tissue contrast. Different textural approaches have been previously investigated for characterizing chondrocyte organization on PCI-CT to enable classification of healthy and osteoarthritic cartilage. However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. For this purpose, geometrical feature sets derived from the scaling index method (SIM) were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. The extracted feature sets were subject to linear and non-linear dimension reduction techniques as well as feature selection based on evaluation of mutual information criteria. The reduced feature set was subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC). Our results show that the classification performance achieved by 9-D SIM-derived geometric feature sets (AUC: 0.96 ± 0.02) can be maintained with 2-D representations computed from both dimension reduction and feature selection (AUC values as high as 0.97 ± 0.02). Thus, such feature reduction techniques can offer a high degree of compaction to large feature sets extracted from PCI-CT images while maintaining their ability to characterize the underlying chondrocyte patterns.

Utility of Intermediate-Delay Washout CT Images for Differentiation of Malignant and Benign Adrenal Lesions: A Multivariate Analysis.

PubMed

Ng, Chaan S; Altinmakas, Emre; Wei, Wei; Ghosh, Payel; Li, Xiao; Grubbs, Elizabeth G; Perrier, Nancy D; Lee, Jeffrey E; Prieto, Victor G; Hobbs, Brian P

2018-06-27

The objective of this study was to identify features that impact the diagnostic performance of intermediate-delay washout CT for distinguishing malignant from benign adrenal lesions. This retrospective study evaluated 127 pathologically proven adrenal lesions (82 malignant, 45 benign) in 126 patients who had undergone portal venous phase and intermediate-delay washout CT (1-3 minutes after portal venous phase) with or without unenhanced images. Unenhanced images were available for 103 lesions. Quantitatively, lesion CT attenuation on unenhanced (UA) and delayed (DL) images, absolute and relative percentage of enhancement washout (APEW and RPEW, respectively), descriptive CT features (lesion size, margin characteristics, heterogeneity or homogeneity, fat, calcification), patient demographics, and medical history were evaluated for association with lesion status using multiple logistic regression with stepwise model selection. Area under the ROC curve (A z ) was calculated from both univariate and multivariate analyses. The predictive diagnostic performance of multivariate evaluations was ascertained through cross-validation. A z for DL, APEW, RPEW, and UA was 0.751, 0.795, 0.829, and 0.839, respectively. Multivariate analyses yielded the following significant CT quantitative features and associated A z when combined: RPEW and DL (A z = 0.861) when unenhanced images were not available and APEW and UA (A z = 0.889) when unenhanced images were available. Patient demographics and presence of a prior malignancy were additional significant factors, increasing A z to 0.903 and 0.927, respectively. The combined predictive classifier, without and with UA available, yielded 85.7% and 87.3% accuracies with cross-validation, respectively. When appropriately combined with other CT features, washout derived from intermediate-delay CT with or without additional clinical data has potential utility in differentiating malignant from benign adrenal lesions.

Deep neural networks for automatic detection of osteoporotic vertebral fractures on CT scans.

PubMed

Tomita, Naofumi; Cheung, Yvonne Y; Hassanpour, Saeed

2018-07-01

Osteoporotic vertebral fractures (OVFs) are prevalent in older adults and are associated with substantial personal suffering and socio-economic burden. Early diagnosis and treatment of OVFs are critical to prevent further fractures and morbidity. However, OVFs are often under-diagnosed and under-reported in computed tomography (CT) exams as they can be asymptomatic at an early stage. In this paper, we present and evaluate an automatic system that can detect incidental OVFs in chest, abdomen, and pelvis CT examinations at the level of practicing radiologists. Our OVF detection system leverages a deep convolutional neural network (CNN) to extract radiological features from each slice in a CT scan. These extracted features are processed through a feature aggregation module to make the final diagnosis for the full CT scan. In this work, we explored different methods for this feature aggregation, including the use of a long short-term memory (LSTM) network. We trained and evaluated our system on 1432 CT scans, comprised of 10,546 two-dimensional (2D) images in sagittal view. Our system achieved an accuracy of 89.2% and an F1 score of 90.8% based on our evaluation on a held-out test set of 129 CT scans, which were established as reference standards through standard semiquantitative and quantitative methods. The results of our system matched the performance of practicing radiologists on this test set in real-world clinical circumstances. We expect the proposed system will assist and improve OVF diagnosis in clinical settings by pre-screening routine CT examinations and flagging suspicious cases prior to review by radiologists. Copyright © 2018 Elsevier Ltd. All rights reserved.

CT AND MRI FEATURES OF CAROTID BODY PARAGANGLIOMAS IN 16 DOGS.

PubMed

Mai, Wilfried; Seiler, Gabriela S; Lindl-Bylicki, Britany J; Zwingenberger, Allison L

2015-01-01

Carotid body tumors (paragangliomas) arise from chemoreceptors located at the carotid bifurcation. In imaging studies, this neoplasm may be confused with other neck neoplasms such as thyroid carcinoma. The purpose of this retrospective, cross-sectional study was to describe computed tomographic (CT) and magnetic resonance imaging (MRI) characteristics of confirmed carotid body tumors in a multi-institutional sample of dogs. A total of 16 dogs met inclusion criteria (14 examined using CT and two with MRI). The most common reason for imaging was a palpable cervical mass or respiratory signs (i.e., dyspnea or increased respiratory noises). The most commonly affected breed was Boston terrier (n = 5). Dogs were predominantly male castrated (n = 10) and the median age was 9 years [range 3-14.5]. Most tumors appeared as a large mass centered at the carotid bifurcation, with poor margination in six dogs and discrete margins in ten dogs. Masses were iso- to hypoattenuating to adjacent muscles in CT images and hyperintense to muscles in T1- and T2-weighted MRI. For both CT and MRI, masses typically showed strong and heterogeneous contrast enhancement. There was invasion into the adjacent structures in 9/16 dogs. In six of these nine dogs, the basilar portion of the skull was affected. The external carotid artery was entrapped in seven dogs. There was invasion into the internal jugular vein in three dogs, and into the external jugular, maxillary, and linguo-facial veins in one dog. Imaging characteristics helped explain some clinical presentations such as breathing difficulties, Horner's syndrome, head tilt, or facial nerve paralysis. © 2015 American College of Veterinary Radiology.

Comparison of machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer from 18F-FDG PET/CT images.

PubMed

Wang, Hongkai; Zhou, Zongwei; Li, Yingci; Chen, Zhonghua; Lu, Peiou; Wang, Wenzhi; Liu, Wanyu; Yu, Lijuan

2017-12-01

This study aimed to compare one state-of-the-art deep learning method and four classical machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer (NSCLC) from 18 F-FDG PET/CT images. Another objective was to compare the discriminative power of the recently popular PET/CT texture features with the widely used diagnostic features such as tumor size, CT value, SUV, image contrast, and intensity standard deviation. The four classical machine learning methods included random forests, support vector machines, adaptive boosting, and artificial neural network. The deep learning method was the convolutional neural networks (CNN). The five methods were evaluated using 1397 lymph nodes collected from PET/CT images of 168 patients, with corresponding pathology analysis results as gold standard. The comparison was conducted using 10 times 10-fold cross-validation based on the criterion of sensitivity, specificity, accuracy (ACC), and area under the ROC curve (AUC). For each classical method, different input features were compared to select the optimal feature set. Based on the optimal feature set, the classical methods were compared with CNN, as well as with human doctors from our institute. For the classical methods, the diagnostic features resulted in 81~85% ACC and 0.87~0.92 AUC, which were significantly higher than the results of texture features. CNN's sensitivity, specificity, ACC, and AUC were 84, 88, 86, and 0.91, respectively. There was no significant difference between the results of CNN and the best classical method. The sensitivity, specificity, and ACC of human doctors were 73, 90, and 82, respectively. All the five machine learning methods had higher sensitivities but lower specificities than human doctors. The present study shows that the performance of CNN is not significantly different from the best classical methods and human doctors for classifying mediastinal lymph node metastasis of NSCLC from PET/CT images. Because CNN does not need tumor segmentation or feature calculation, it is more convenient and more objective than the classical methods. However, CNN does not make use of the import diagnostic features, which have been proved more discriminative than the texture features for classifying small-sized lymph nodes. Therefore, incorporating the diagnostic features into CNN is a promising direction for future research.

Acquiring 4D Thoracic CT Scans Using Ciné CT Acquisition

NASA Astrophysics Data System (ADS)

Low, Daniel

One method for acquiring 4D thoracic CT scans is to use ciné acquisition. Ciné acquisition is conducted by rotating the gantry and acquiring x-ray projections while keeping the couch stationary. After a complete rotation, a single set of CT slices, the number corresponding to the number of CT detector rows, is produced. The rotation period is typically sub second so each image set corresponds to a single point in time. The ciné image acquisition is repeated for at least one breathing cycle to acquire images throughout the breathing cycle. Once the images are acquired at a single couch position, the couch is moved to the abutting position and the acquisition is repeated. Post-processing of the images sets typically resorts the sets into breathing phases, stacking images from a specific phase to produce a thoracic CT scan at that phase. Benefits of the ciné acquisition protocol include, the ability to precisely identify the phase with respect to the acquired image, the ability to resort images after reconstruction, and the ability to acquire images over arbitrarily long times and for arbitrarily many images (within dose constraints).

SU-E-J-254: Evaluating the Role of Mid-Treatment and Post-Treatment FDG-PET/CT in Predicting Progression-Free Survival and Distant Metastasis of Anal Cancer Patients Treated with Chemoradiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, H; Wang, J; Chuong, M

2015-06-15

Purpose: To evaluate the role of mid-treatment and post-treatment FDG-PET/CT in predicting progression-free survival (PFS) and distant metastasis (DM) of anal cancer patients treated with chemoradiotherapy (CRT). Methods: 17 anal cancer patients treated with CRT were retrospectively studied. The median prescription dose was 56 Gy (range, 50–62.5 Gy). All patients underwent FDG-PET/CT scans before and after CRT. 16 of the 17 patients had an additional FDG-PET/CT image at 3–5 weeks into the treatment (denoted as mid-treatment FDG-PET/CT). 750 features were extracted from these three sets of scans, which included both traditional PET/CT measures (SUVmax, SUVpeak, tumor diameters, etc.) and spatialtemporalmore » PET/CT features (comprehensively quantify a tumor’s FDG uptake intensity and distribution, spatial variation (texture), geometric property and their temporal changes relative to baseline). 26 clinical parameters (age, gender, TNM stage, histology, GTV dose, etc.) were also analyzed. Advanced analytics including methods to select an optimal set of predictors and a model selection engine, which identifies the most accurate machine learning algorithm for predictive analysis was developed. Results: Comparing baseline + mid-treatment PET/CT set to baseline + posttreatment PET/CT set, 14 predictors were selected from each feature group. Same three clinical parameters (tumor size, T stage and whether 5-FU was held during any cycle of chemotherapy) and two traditional measures (pre- CRT SUVmin and SUVmedian) were selected by both predictor groups. Different mix of spatial-temporal PET/CT features was selected. Using the 14 predictors and Naive Bayes, mid-treatment PET/CT set achieved 87.5% accuracy (2 PFS patients misclassified, all local recurrence and DM patients correctly classified). Post-treatment PET/CT set achieved 94.0% accuracy (all PFS and DM patients correctly predicted, 1 local recurrence patient misclassified) with logistic regression, neural network or support vector machine model. Conclusion: Applying radiomics approach to either midtreatment or post-treatment PET/CT could achieve high accuracy in predicting anal cancer treatment outcomes. This work was supported in part by the National Cancer Institute Grant R01CA172638.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuo, J; Su, K; Department of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, Ohio

Purpose: Accurate and robust photon attenuation derived from MR is essential for PET/MR and MR-based radiation treatment planning applications. Although the fuzzy C-means (FCM) algorithm has been applied for pseudo-CT generation, the input feature combination and the number of clusters have not been optimized. This study aims to optimize both for clinically practical pseudo-CT generation. Methods: Nine volunteers were recruited. A 190-second, single-acquisition UTE-mDixon with 25% (angular) sampling and 3D radial readout was performed to acquire three primitive MR features at TEs of 0.1, 1.5, and 2.8 ms: the free-induction-decay (FID), the first and the second echo images. Three derivedmore » images, Dixon-fat and Dixon-water generated by two-point Dixon water/fat separation, and R2* (1/T2*) map, were also created. To identify informative inputs for generating a pseudo-CT image volume, all 63 combinations, choosing one to six of the feature images, were used as inputs to FCM for pseudo-CT generation. Further, the number of clusters was varied from four to seven to find the optimal approach. Mean prediction deviation (MPD), mean absolute prediction deviation (MAPD), and correlation coefficient (R) of different combinations were compared for feature selection. Results: Among the 63 feature combinations, the four that resulted in the best MAPD and R were further compared along with the set containing all six features. The results suggested that R2* and Dixon-water are the most informative features. Further, including FID also improved the performance of pseudo-CT generation. Consequently, the set containing FID, Dixon-water, and R2* resulted in the most accurate, robust pseudo-CT when the number of cluster equals to five (5C). The clusters were interpreted as air, fat, bone, brain, and fluid. The six-cluster Result additionally included bone marrow. Conclusion: The results suggested that FID, Dixon-water, R2* are the most important features. The findings can be used to facilitate pseudo-CT generation for unsupervised clustering. Please note that the project was completed with partial funding from the Ohio Department of Development grant TECH 11-063 and a sponsored research agreement with Philips Healthcare that is managed by Case Western Reserve University. As noted in the affiliations, some of the authors are Philips employees.« less

Cross Sectional Imaging of Solitary Lesions of the Neurocranium.

PubMed

Schäfer, Max-Ludwig; Koch, Arend; Streitparth, Florian; Wiener, Edzard

2017-12-01

Background  Although a wide range of processes along the neurocranium are of a benign nature, there are often difficulties in the differential diagnosis. Method  In the review CT/MRI scans of the head were evaluated retrospectively regarding solitary lesions along the neurocranium. The majority of the lesions were histologically proven. Results  The purpose of the review is to present typical pathologies of the neurocranium and provide a systematic overview based on 12 entities, their locations, prevalence and radiological characteristics. Conclusion  Processes, which primarily originate from the neurocranium have to be differentiated from secondary processes infiltrating the neurocranium. For this important diagnostic feature, MRI is typically essential, while the definitive diagnosis is often made on the basis of the medical history and the typical appearance on computer tomography. Key Points   · There are often difficulties in the precise differential diagnosis of solitary lesions along the neurocranium. Typical solitary pathologies of the neurocranium based on 12 entities were presented. Both magnetic resonance imaging and computed tomography are often essential for an exact differential diagnosis.. Citation Format · Schäfer M, Koch A, Streitparth F et al. Cross Sectional Diagnosis of Solitary Lesions of the Neurocranium. Fortschr Röntgenstr 2017; 189: 1135 - 1144. © Georg Thieme Verlag KG Stuttgart · New York.

Automatic segmentation of the prostate on CT images using deep learning and multi-atlas fusion

NASA Astrophysics Data System (ADS)

Ma, Ling; Guo, Rongrong; Zhang, Guoyi; Tade, Funmilayo; Schuster, David M.; Nieh, Peter; Master, Viraj; Fei, Baowei

2017-02-01

Automatic segmentation of the prostate on CT images has many applications in prostate cancer diagnosis and therapy. However, prostate CT image segmentation is challenging because of the low contrast of soft tissue on CT images. In this paper, we propose an automatic segmentation method by combining a deep learning method and multi-atlas refinement. First, instead of segmenting the whole image, we extract the region of interesting (ROI) to delete irrelevant regions. Then, we use the convolutional neural networks (CNN) to learn the deep features for distinguishing the prostate pixels from the non-prostate pixels in order to obtain the preliminary segmentation results. CNN can automatically learn the deep features adapting to the data, which are different from some handcrafted features. Finally, we select some similar atlases to refine the initial segmentation results. The proposed method has been evaluated on a dataset of 92 prostate CT images. Experimental results show that our method achieved a Dice similarity coefficient of 86.80% as compared to the manual segmentation. The deep learning based method can provide a useful tool for automatic segmentation of the prostate on CT images and thus can have a variety of clinical applications.

Cranio-orbital primary intraosseous haemangioma.

PubMed

Gupta, T; Rose, G E; Manisali, M; Minhas, P; Uddin, J M; Verity, D H

2013-11-01

Primary intraosseous haemangioma (IOH) is a rare benign neoplasm presenting in the fourth and fifth decades of life. The spine and skull are the most commonly involved, orbital involvement is extremely rare. We describe six patients with cranio-orbital IOH, the largest case series to date. Retrospective review of six patients with histologically confirmed primary IOH involving the orbit. Clinical characteristics, imaging features, approach to management, and histopathological findings are described. Five patients were male with a median age of 56. Pain and diplopia were the most common presenting features. A characteristic 'honeycomb' pattern on CT imaging was demonstrated in three of the cases. Complete surgical excision was performed in all cases with presurgical embolisation carried out in one case. In all the cases, histological studies identified cavernous vascular spaces within the bony tissue. These channels were lined by single layer of cytologically normal endothelial cells. IOCH of the cranio-orbital region is rare; in the absence of typical imaging features, the differential diagnosis includes chondroma, chondrosarcoma, bony metastasis, and lymphoma. Surgical excision may be necessary to exclude more sinister pathology. Intraoperative haemorrhage can be severe and may be reduced by preoperative embolisation.

Quantitative image feature variability amongst CT scanners with a controlled scan protocol

NASA Astrophysics Data System (ADS)

Ger, Rachel B.; Zhou, Shouhao; Chi, Pai-Chun Melinda; Goff, David L.; Zhang, Lifei; Lee, Hannah J.; Fuller, Clifton D.; Howell, Rebecca M.; Li, Heng; Stafford, R. Jason; Court, Laurence E.; Mackin, Dennis S.

2018-02-01

Radiomics studies often analyze patient computed tomography (CT) images acquired from different CT scanners. This may result in differences in imaging parameters, e.g. different manufacturers, different acquisition protocols, etc. However, quantifiable differences in radiomics features can occur based on acquisition parameters. A controlled protocol may allow for minimization of these effects, thus allowing for larger patient cohorts from many different CT scanners. In order to test radiomics feature variability across different CT scanners a radiomics phantom was developed with six different cartridges encased in high density polystyrene. A harmonized protocol was developed to control for tube voltage, tube current, scan type, pitch, CTDIvol, convolution kernel, display field of view, and slice thickness across different manufacturers. The radiomics phantom was imaged on 18 scanners using the control protocol. A linear mixed effects model was created to assess the impact of inter-scanner variability with decomposition of feature variation between scanners and cartridge materials. The inter-scanner variability was compared to the residual variability (the unexplained variability) and to the inter-patient variability using two different patient cohorts. The patient cohorts consisted of 20 non-small cell lung cancer (NSCLC) and 30 head and neck squamous cell carcinoma (HNSCC) patients. The inter-scanner standard deviation was at least half of the residual standard deviation for 36 of 49 quantitative image features. The ratio of inter-scanner to patient coefficient of variation was above 0.2 for 22 and 28 of the 49 features for NSCLC and HNSCC patients, respectively. Inter-scanner variability was a significant factor compared to patient variation in this small study for many of the features. Further analysis with a larger cohort will allow more thorough analysis with additional variables in the model to truly isolate the interscanner difference.

Identification of a novel mutation in a patient with pseudohypoparathyroidism type Ia

PubMed Central

Lee, Ye Seung; Kim, Hui Kwon; Kim, Hye Rim; Lee, Jong Yoon; Choi, Joong Wan; Bae, Eun Ju; Oh, Phil Soo; Park, Won Il; Ki, Chang Seok

2014-01-01

Pseudohypoparathyroidism type Ia (PHP Ia) is a disorder characterized by multiform hormonal resistance including parathyroid hormone (PTH) resistance and Albright hereditary osteodystrophy (AHO). It is caused by heterozygous inactivating mutations within the Gs alpha-encoding GNAS exons. A 9-year-old boy presented with clinical and laboratory abnormalities including hypocalcemia, hyperphosphatemia, PTH resistance, multihormone resistance and AHO (round face, short stature, obesity, brachydactyly and osteoma cutis) which were typical of PHP Ia. He had a history of repeated convulsive episodes that started from the age of 2 months. A cranial computed tomography scan showed bilateral calcifications in the basal ganglia and his intelligence quotient testing indicated mild mental retardation. Family history revealed that the patient's maternal relatives, including his grandmother and 2 of his mother's siblings, had features suggestive of AHO. Sequencing of the GNAS gene of the patient identified a heterozygous nonsense mutation within exon 11 (c.637 C>T). The C>T transversion results in an amino acid substitution from Gln to stop codon at codon 213 (p.Gln213*). To our knowledge, this is a novel mutation in GNAS. PMID:25045367

Acinar cell carcinoma of the pancreas presenting as diffuse pancreatic enlargement: Two case reports and literature review.

PubMed

Luo, Yaping; Hu, Guilan; Ma, Yanru; Guo, Ning; Li, Fang

2017-09-01

Pancreatic acinar cell carcinoma (ACC) is a rare malignant tumor of exocrine pancreas. It is typically a well-marginated large solid mass arising in a certain aspect of the pancreas. Diffuse involvement of ACC in the pancreas is very rare, and may simulate pancreatitis in radiological findings. We report 2 cases of ACC presenting as diffuse enlargement of the pancreas due to tumor involvement without formation of a distinct mass. The patients consisted of a 41-year-old man with weight loss and a 77-year-old man who was asymptomatic. Computed tomography (CT) and 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT showed diffuse enlargement of the pancreas forming a sausage-like shape with homogenously increased FDG activity. Endoscopic ultrasound (EUS)-guided fine needle aspiration (FNA) biopsy of the pancreatic lesion was performed. Histopathology results from the pancreas confirmed the diagnosis of pancreatic ACC. Because diffuse enlargement of the pancreas is a common imaging feature of pancreatitis, recognition of this rare morphologic pattern of ACC is important for radiological diagnosis of this tumor.

First installation of a dual-room IVR-CT system in the emergency room.

PubMed

Wada, Daiki; Nakamori, Yasushi; Kanayama, Shuji; Maruyama, Shuhei; Kawada, Masahiro; Iwamura, Hiromu; Hayakawa, Koichi; Saito, Fukuki; Kuwagata, Yasuyuki

2018-03-05

Computed tomography (CT) embedded in the emergency room has gained importance in the early diagnostic phase of trauma care. In 2011, we implemented a new trauma workflow concept with a sliding CT scanner system with interventional radiology features (IVR-CT) that allows CT examination and emergency therapeutic intervention without relocating the patient, which we call the Hybrid emergency room (Hybrid ER). In the Hybrid ER, all life-saving procedures, CT examination, damage control surgery, and transcatheter arterial embolisation can be performed on the same table. Although the trauma workflow realized in the Hybrid ER may improve mortality in severe trauma, the Hybrid ER can potentially affect the efficacy of other in/outpatient diagnostic workflow because one room is occupied by one severely injured patient undergoing both emergency trauma care and CT scanning for long periods. In July 2017, we implemented a new trauma workflow concept with a dual-room sliding CT scanner system with interventional radiology features (dual-room IVR-CT) to increase patient throughput. When we perform emergency surgery or interventional radiology for a severely injured or ill patient in the Hybrid ER, the sliding CT scanner moves to the adjacent CT suite, and we can perform CT scanning of another in/outpatient. We believe that dual-room IVR-CT can contribute to the improvement of both the survival of severely injured or ill patients and patient throughput.

Integrating Dimension Reduction and Out-of-Sample Extension in Automated Classification of Ex Vivo Human Patellar Cartilage on Phase Contrast X-Ray Computed Tomography

PubMed Central

Nagarajan, Mahesh B.; Coan, Paola; Huber, Markus B.; Diemoz, Paul C.; Wismüller, Axel

2015-01-01

Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated as a novel imaging technique that can visualize human cartilage with high spatial resolution and soft tissue contrast. Different textural approaches have been previously investigated for characterizing chondrocyte organization on PCI-CT to enable classification of healthy and osteoarthritic cartilage. However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. For this purpose, geometrical feature sets derived from the scaling index method (SIM) were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. The extracted feature sets were subject to linear and non-linear dimension reduction techniques as well as feature selection based on evaluation of mutual information criteria. The reduced feature set was subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC). Our results show that the classification performance achieved by 9-D SIM-derived geometric feature sets (AUC: 0.96 ± 0.02) can be maintained with 2-D representations computed from both dimension reduction and feature selection (AUC values as high as 0.97 ± 0.02). Thus, such feature reduction techniques can offer a high degree of compaction to large feature sets extracted from PCI-CT images while maintaining their ability to characterize the underlying chondrocyte patterns. PMID:25710875

More than one kind of inference: re-examining what's learned in feature inference and classification.

PubMed

Sweller, Naomi; Hayes, Brett K

2010-08-01

Three studies examined how task demands that impact on attention to typical or atypical category features shape the category representations formed through classification learning and inference learning. During training categories were learned via exemplar classification or by inferring missing exemplar features. In the latter condition inferences were made about missing typical features alone (typical feature inference) or about both missing typical and atypical features (mixed feature inference). Classification and mixed feature inference led to the incorporation of typical and atypical features into category representations, with both kinds of features influencing inferences about familiar (Experiments 1 and 2) and novel (Experiment 3) test items. Those in the typical inference condition focused primarily on typical features. Together with formal modelling, these results challenge previous accounts that have characterized inference learning as producing a focus on typical category features. The results show that two different kinds of inference learning are possible and that these are subserved by different kinds of category representations.

Dyspnea predicts mortality among patients undergoing coronary computed tomographic angiography.

PubMed

Nakanishi, Rine; Gransar, Heidi; Rozanski, Alan; Rana, Jamal S; Cheng, Victor Y; Thomson, Louise E J; Miranda-Peats, Romalisa; Dey, Damini; Hayes, Sean W; Friedman, John D; Min, James K; Berman, Daniel S

2016-02-01

The prognostic implications of dyspnea and typical angina in patients referred for coronary CT angiography have not been examined. We examined features associated with incident mortality risk among individuals undergoing coronary computed tomographic angiography (CCTA) presenting with dyspnea, typical angina, and neither of these symptoms. 1147 consecutive individuals without known CAD (mean 61 years, 61.6 %men) undergoing CCTA comprised the study population 132 with dyspnea, 218 with typical angina, and 797 without dyspnea or typical angina (reference group). Mortality risk in relation to dyspnea or typical angina was evaluated with multivariable Cox proportional hazards models compared to reference. In addition, the prognosis associated with dyspnea or typical angina was assessed among age matched subgroups. Patients with dyspnea had a greater prevalence of C70 % stenosis (p\\0.001) and coronary segments with plaque (p = 0.02) compared to the other two groups. During a follow-up of 3.1 years, 52 individuals died. By multivariable Cox models, compared to patients in reference group, dyspnea patients experienced higher mortality (HR 2.0, 95 % CI 1.0–4.0, p = 0.049) while typical angina patients did not (HR 1.1, 95 % CI 0.6–2.3, p = 0.76). In the matched group, the patients with dyspnea (HR 2.2, 95 % CI 1.1–4.3, p = 0.03) still had significantly reduced survival compared to the other two groups, while those with typical angina did not (HR 1.2, 95 % CI 0.6–2.6,p = 0.62). Dyspnea is associated with increased mortality ate compared to patients with typical angina and those with neither of these symptoms among patients undergoing CCTA.

Inflammatory Pseudotumor-Like Follicular Dendritic Cell Sarcoma of the Spleen: Computed Tomography Imaging Characteristics in 5 Patients.

PubMed

Li, Xiumei; Shi, Zhenshan; You, Ruixiong; Li, Yueming; Cao, Dairong; Lin, Renjie; Huang, Xinming

The purpose of this study was to retrospectively review the computed tomography (CT) and clinicopathological characteristics of inflammatory pseudotumor (IPT)-like follicular dendritic cell sarcoma (FDCS) of the spleen in 5 patients. Clinical, pathologic, and CT imaging findings of 5 patients with IPT-like FDCS of the spleen were reviewed and analyzed. Computed tomography imaging and pathologic features were compared. Abdominal unenhanced CT revealed a well-defined hypodense mass in the spleen with complex internal architecture with focal necrosis and/or speckle-strip calcification. On postcontrast CT, slightly delayed enhancement was observed in 5 cases. Four patients had a normalized spleen. The fourth patient had lung metastasis. The fifth patient had 2 relatively small lesions as well as metastases to the spine. Computed tomography imaging features of IPT-like FDCS of the spleen are distinctly different from other hypovascular splenic neoplasm; however, the definitive diagnosis requires further confirmation with needle biopsy or surgery. Inflammatory pseudotumor-like FDCS of the spleen should be suggested by using the CT imaging features of the splenic mass with evidence of metastatic disease.

Clinical and computed tomography features of adult abdominopelvic desmoplastic small round cell tumor.

PubMed

Shen, Xun-Ze; Zhao, Jian-Guo; Wu, Jian-Jun; Liu, Fang

2014-05-07

To investigate the clinical and computed tomography (CT) features of desmoplastic small round cell tumor (DSRCT), we retrospectively analyzed the clinical presentations, treatment and outcome, as well as CT manifestations of four cases of DSRCT confirmed by surgery and pathology. The CT manifestations of DSRCT were as follows: (1) multiple soft-tissue masses or diffuse peritoneal thickening in the abdomen and pelvis, with the dominant mass usually located in the pelvic cavity; (2) masses without an apparent organ-based primary site; (3) mild to moderate homogeneous or heterogeneous enhancement in solid area on enhanced CT; and (4) secondary manifestations, such as ascites, hepatic metastases, lymphadenopathy, hydronephrosis and hydroureter. The prognosis and overall survival rates were generally poor. Commonly used treatment strategies including aggressive tumor resection, polychemotherapy, and radiotherapy, showed various therapeutic effects. CT of DSRCT shows characteristic features that are helpful in diagnosis. Early discovery and complete resection, coupled with postoperative adjuvant chemotherapy, are important for prognosis of DSRCT. Whole abdominopelvic rather than locoregional radiotherapy is more effective for unresectable DSRCT.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsai, H; Hu, Y; Hwang, Y

Purpose: This study was to investigate size-specific dose estimates (SSDE) for routine adult abdominal CT examinations in Taiwan. Methods: A national survey was conducted in Taiwan in 2014 to investigate SSDEs for routine adult abdominal CT examinations. The hospitals involved in this study provided CT images of their typical patients. The CT image in the level of the middle liver was selected to record the corresponding tube current, slice mAs or effective mAs. The image was also used to estimate the dimensions of patient as measuring the lengths in the anterior to posterior (AP) and lateral (LAT) directions. The effectivemore » diameter was then calculated from AP and LAT, and used to look up conversion factors in the AAPM 204 report. The volume CTDI (CTDIvol) for each CT unit was measured on sites using a 32-cm cylindrical standard dose phantom and a calibrated pencil-type ionization chamber. Individual patient’s SSDEs were then calculated from the corresponding SSDE conversion factor and the CTDIvol. Results: The study cohort included 111 CT units. The ratio of turning on automatic tube current modulation (ATCM) or not is 88:23. Effective diameters are 258.7±25.1 mm (167–366 mm). 99.3% of typical patients selected by each hospital have smaller effective diameter than the 32-cm dosimetry phantom. Adult abdomenal SSDE is 17.5 ± 8.8 mGy (1.9-58 mGy). The SSDE seems to decrease as the effective diameter increases as the ATCM turns off, and independent with the effective diameter as the ATCM turns on. Conclusion: The SSDE for typical patients in Taiwan was investigated. We continue to complete this investigation in 2015 to include more valid data to establish SSDE reference level in Taiwan. This study was financially supported by the Atomic Energy Council in Taiwan.« less

Fixed, object-specific intensity compensation for cone beam optical CT radiation dosimetry

NASA Astrophysics Data System (ADS)

Dekker, Kurtis H.; Hazarika, Rubin; Silveira, Matheus A.; Jordan, Kevin J.

2018-03-01

Optical cone beam computed tomography (CT) scanning of radiochromic gel dosimeters, using a CCD camera and a low stray light convergent source, provides fast, truly 3D radiation dosimetry with high accuracy. However, a key limiting factor in radiochromic gel dosimetry at large (⩾10 cm diameter) volumes is the initial attenuation of the dosimeters. It is not unusual to observe a 5–10×  difference in signal intensity through the dosimeter center versus through the surrounding medium in pre-irradiation images. Thus, all dosimetric information in a typical experiment is measured within the lower 10%–20% of the camera sensor’s range, and re-use of gels is often not possible due to a lack of transmission. To counteract this, in this note we describe a simple method to create source compensators by printing on transparent films. This technique, which is easily implemented and inexpensive, is an optical analogue to the bowtie filter in x-ray CT. We present transmission images and solution phantom reconstructions to demonstrate that (1) placing compensators beyond the focal zone of the imaging lens prevents high spatial frequency features of the printed films from generating reconstruction artifacts, and (2) object-specific compensation considerably reduces the range of intensities measured in projection images. This will improve the measurable dose range in optical CT dosimetry, and will enable imaging of larger gel volumes (∼15 cm diameter). Additionally, it should enable re-use of dosimeters by printing a new compensator for a second experiment.

Renal carcinomas associated with Xp11.2 translocations/TFE3 gene fusions: findings on MRI and computed tomography imaging.

PubMed

Liu, Kefu; Xie, Ping; Peng, Weijun; Zhou, Zhengrong

2014-08-01

To retrospectively analyze MRI and computed tomographic (CT) findings from renal carcinomas associated with Xp11.2 translocations/TFE3 gene fusions (Xp11-RCC). Institutional review board permission was obtained to review patient medical records, and the requirement for informed consent was waved . The clinical and MRI/CT features of five cases with Xp11-RCC that were confirmed by pathology were analyzed retrospectively. The image characteristics included the lesion location and size, contribution of cystic and solid components, intratumoral necrosis or hemorrhage, invasion of perinephric tissue and renal sinus, lymphadenopathy, major venous or arterial vascular invasion, pattern of the tumor growth, intratumor calcification and lipids, homogeneity of SI on T2-weighted images, attenuation and SI of the mass with respect to the normal renal cortex on precontrast and contrasted CT/MRI images, tumor SIs, tumor attenuations and tumor-to-cortex indices, homogeneity of enhancement on the contrasted images. The mean age was 32 years (range, 15-47 years). Most patients (4/5) were women. All tumors showed a cortical location. The average tumor size was 9 cm (range, 4-18 cm). Four tumors comprised a predominantly solid lesion with focal necrosis, and one tumor comprised a solid lesion with significant necrosis. All tumors showed intertumor hemorrhage, infiltrative growth and invasion of the perirenal adipose/renal sinus. Four cases showed retroperitoneal lymphadenopathy, of which one case showed simultaneous mediastinal and supraclavicular lymphadenopathy. All tumors from four cases showed mild hyperintensity on T1-weighted MRI images, and three tumors showed hypointensity on T2-weighted MRI images relative to the renal cortex except for 1 tumor that showed significant hemorrhage and a relative hyperintensity. For 3 cases who were imaged with CT, two tumors imaged using nonenhanced CT images showed mild hyperdensity relative to the renal cortex. Calcification was noted in all three tumors. All tumors showed mild, persistent enhancement. Typical Xp11-RCC manifests as an advanced, solid renal mass with mild persistent enhancement, a prevalence of intertumor hemorrhage/calcification, and a cortical epicenter location. The predilection for children and young adults is a useful clinical feature when confirming a diagnosis of Xp11-RCC. © 2013 Wiley Periodicals, Inc.

MO-DE-207B-04: Impact of Reconstruction Field of View On Radiomics Features in Computed Tomography (CT) Using a Texture Phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shafiq ul Hassan, M; Zhang, G; Oliver, J

Purpose: To investigate the impact of reconstruction Field of View on Radiomics features in computed tomography (CT) using a texture phantom. Methods: A rectangular Credence Cartridge Radiomics (CCR) phantom, composed of 10 different cartridges, was scanned on four different CT scanners from two manufacturers. A pre-defined scanning protocol was adopted for consistency. The slice thickness and reconstruction interval of 1.5 mm was used on all scanners. The reconstruction FOV was varied to result a voxel size ranging from 0.38 to 0.98 mm. A spherical region of interest (ROI) was contoured on the shredded rubber cartridge from CCR phantom CT scans.more » Ninety three Radiomics features were extracted from ROI using an in-house program. These include 10 shape, 22 intensity, 26 GLCM, 11 GLZSM, 11 RLM, 5 NGTDM and 8 fractal dimensional features. To evaluate the Interscanner variability across three scanners, a coefficient of variation (COV) was calculated for each feature group. Each group was further classified according to the COV by calculating the percentage of features in each of the following categories: COV≤ 5%, between 5 and 10% and ≥ 10%. Results: Shape features were the most robust, as expected, because of the spherical contouring of ROI. Intensity features were the second most robust with 54.5 to 64% of features with COV < 5%. GLCM features ranged from 31 to 35% for the same category. RLM features were sensitive to specific scanner and 5% variability was 9 to 54%. Almost all GLZM and NGTDM features showed COV ≥10% among the scanners. The dependence of fractal dimensions features on FOV was not consistent across different scanners. Conclusion: We concluded that reconstruction FOV greatly influence Radiomics features. The GLZSM and NGTDM are highly sensitive to FOV. funded in part by Grant NIH/NCI R01CA190105-01.« less

Value of Ki-67 and computed tomography in the assessment of peripheral lung adenocarcinoma.

PubMed

Chen, Cheng; Zhu, Wei-Dong; Zhang, Xiao-Hui; Zhu, Ye-Han; Huang, Jian-An

2016-01-01

This study was designed to determine whether proliferation antigen Ki-67 and/or a computed tomography (CT) value could be used to evaluate the clinical-pathological features of peripheral lung adenocarcinoma. A total of 116 eligible lung cancer patients were enrolled. Nodule size, lymph node metastasis, differentiation, Ki-67 expression and CT findings were assessed. The relationship between clinic parameters and the CT feature was analysed statistically. The percentage of lesions that had ground-glass opacity or localised air bronchogram was significantly greater in low CT value group (<30, p < 0.05). No significant association was observed between CT value and size in the subgroup with CT value > 0 (p = 0.66). As a proliferative marker of lung cancer, Ki-67 was present in a total of 115 (99.9%) of the 116 evaluable primary lung cancers. There was a statistically significant correlation between the Ki-67 index and CT value (p < 0.05). Compared to CT value, Ki-67 index possessed higher sensitivity to predict the differentiation and lymph node metastasis of peripheral lung adenocarcinoma, adding of CT value would enhance its specificity. Combination of Ki-67 expression and CT value determination was useful for the classification of differentiation and metastatic or proliferative potential of peripheral lung adenocarcinoma.

SU-D-207B-03: A PET-CT Radiomics Comparison to Predict Distant Metastasis in Lung Adenocarcinoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coroller, T; Yip, S; Lee, S

2016-06-15

Purpose: Early prediction of distant metastasis may provide crucial information for adaptive therapy, subsequently improving patient survival. Radiomic features that extracted from PET and CT images have been used for assessing tumor phenotype and predicting clinical outcomes. This study investigates the values of radiomic features in predicting distant metastasis (DM) in non-small cell lung cancer (NSCLC). Methods: A total of 108 patients with stage II–III lung adenocarcinoma were included in this retrospective study. Twenty radiomic features were selected (10 from CT and 10 from PET). Conventional features (metabolic tumor volume, SUV, volume and diameter) were included for comparison. Concordance indexmore » (CI) was used to evaluate features prognostic value. Noether test was used to compute p-value to consider CI significance from random (CI = 0.5) and were adjusted for multiple testing using false rate discovery (FDR). Results: A total of 70 patients had DM (64.8%) with a median time to event of 8.8 months. The median delivered dose was 60 Gy (range 33–68 Gy). None of the conventional features from PET (CI ranged from 0.51 to 0.56) or CT (CI ranged from 0.57 to 0.58) were significant from random. Five radiomics features were significantly prognostic from random for DM (p-values < 0.05). Four were extracted from CT (CI = 0.61 to 0.63, p-value <0.01) and one from PET which was also the most prognostic (CI = 0.64, p-value <0.001). Conclusion: This study demonstrated significant association between radiomic features and DM for patients with locally advanced lung adenocarcinoma. Moreover, conventional (clinically utilized) metrics were not significantly associated with DM. Radiomics can potentially help classify patients at higher risk of DM, allowing clinicians to individualize treatment, such as intensification of chemotherapy) to reduce the risk of DM and improve survival. R.M. has consulting interests with Amgen.« less

A risk-adapted approach using US features and FNA results in the management of thyroid incidentalomas identified by 18F-FDG PET.

PubMed

Choi, J S; Choi, Y- J; Kim, E K; Yoon, J H; Youk, J H; Han, K H; Moon, H J; Kang, W J; Kwak, J Y

2014-02-01

To assess the risk of malignancy of thyroid incidentalomas found on 18F-FDG PET/CT by US features and cytologic results, and to evaluate the clinical usage of a combination of US features and cytology for post-FNA management of thyroid incidentalomas on 18F-FDG PET/CT. From September 2006 to December 2008, 132 patients with 134 thyroid incidentalomas detected on 18F-FDG PET/CT who had undergone US and US-FNA were included in this study. We evaluated the malignancy rate of thyroid incidentalomas in different subgroups subdivided by US features and US-FNA cytology results. Several variables were compared between the benign and malignant group. The risk of malignancy was 58.2 % (78/132) in thyroid incidentalomas on 18F-FDG PET/CT. Age, gender, and tumor size were not significantly different between the malignant and benign group.  Malignancy rate of thyroid incidentalomas was significantly higher in the suspicious malignant (88.9 %) than in the probably benign group (11.3 %) on US (p < 0.001). Malignancy rates were high in thyroid nodules with "malignancy", "suspicious for malignancy", or "follicular neoplasm" on cytologic results, regardless of US features. However, malignancy rates of thyroid incidentalomas with "unsatisfactory" or "benign" results on cytology were higher in the suspicious malignant (75 %, 12.5 %, respectively) than in the probably benign (0 %) group on US.  This study demonstrated that the risk of malignancy was high in thyroid incidentalomas on 18F-FDG PET/CT even without suspicious US features. However, there was no malignancy in nodules with no suspicious US features and benign cytology. Based on these results, we concluded that US may not replace FNA in the diagnosis of PET incidentalomas, and that a follow-up may be considered of thyroid incidentalomas with benign cytology and no suspicious US features. © Georg Thieme Verlag KG Stuttgart · New York.

Development of a database of organ doses for paediatric and young adult CT scans in the United Kingdom

PubMed Central

Kim, K. P.; Berrington de González, A.; Pearce, M. S.; Salotti, J. A.; Parker, L.; McHugh, K.; Craft, A. W.; Lee, C.

2012-01-01

Despite great potential benefits, there are concerns about the possible harm from medical imaging including the risk of radiation-related cancer. There are particular concerns about computed tomography (CT) scans in children because both radiation dose and sensitivity to radiation for children are typically higher than for adults undergoing equivalent procedures. As direct empirical data on the cancer risks from CT scans are lacking, the authors are conducting a retrospective cohort study of over 240 000 children in the UK who underwent CT scans. The main objective of the study is to quantify the magnitude of the cancer risk in relation to the radiation dose from CT scans. In this paper, the methods used to estimate typical organ-specific doses delivered by CT scans to children are described. An organ dose database from Monte Carlo radiation transport-based computer simulations using a series of computational human phantoms from newborn to adults for both male and female was established. Organ doses vary with patient size and sex, examination types and CT technical settings. Therefore, information on patient age, sex and examination type from electronic radiology information systems and technical settings obtained from two national surveys in the UK were used to estimate radiation dose. Absorbed doses to the brain, thyroid, breast and red bone marrow were calculated for reference male and female individuals with the ages of newborns, 1, 5, 10, 15 and 20 y for a total of 17 different scan types in the pre- and post-2001 time periods. In general, estimated organ doses were slightly higher for females than males which might be attributed to the smaller body size of the females. The younger children received higher doses in pre-2001 period when adult CT settings were typically used for children. Paediatric-specific adjustments were assumed to be used more frequently after 2001, since then radiation doses to children have often been smaller than those to adults. The database here is the first detailed organ-specific paediatric CT scan database for the UK. As well as forming the basis for the UK study, the results and description of the methods will also serve as a key resource for paediatric CT scan studies currently underway in other countries. PMID:22228685

Development of a database of organ doses for paediatric and young adult CT scans in the United Kingdom.

PubMed

Kim, K P; Berrington de González, A; Pearce, M S; Salotti, J A; Parker, L; McHugh, K; Craft, A W; Lee, C

2012-07-01

Despite great potential benefits, there are concerns about the possible harm from medical imaging including the risk of radiation-related cancer. There are particular concerns about computed tomography (CT) scans in children because both radiation dose and sensitivity to radiation for children are typically higher than for adults undergoing equivalent procedures. As direct empirical data on the cancer risks from CT scans are lacking, the authors are conducting a retrospective cohort study of over 240,000 children in the UK who underwent CT scans. The main objective of the study is to quantify the magnitude of the cancer risk in relation to the radiation dose from CT scans. In this paper, the methods used to estimate typical organ-specific doses delivered by CT scans to children are described. An organ dose database from Monte Carlo radiation transport-based computer simulations using a series of computational human phantoms from newborn to adults for both male and female was established. Organ doses vary with patient size and sex, examination types and CT technical settings. Therefore, information on patient age, sex and examination type from electronic radiology information systems and technical settings obtained from two national surveys in the UK were used to estimate radiation dose. Absorbed doses to the brain, thyroid, breast and red bone marrow were calculated for reference male and female individuals with the ages of newborns, 1, 5, 10, 15 and 20 y for a total of 17 different scan types in the pre- and post-2001 time periods. In general, estimated organ doses were slightly higher for females than males which might be attributed to the smaller body size of the females. The younger children received higher doses in pre-2001 period when adult CT settings were typically used for children. Paediatric-specific adjustments were assumed to be used more frequently after 2001, since then radiation doses to children have often been smaller than those to adults. The database here is the first detailed organ-specific paediatric CT scan database for the UK. As well as forming the basis for the UK study, the results and description of the methods will also serve as a key resource for paediatric CT scan studies currently underway in other countries.

18F-FDG PET/CT imaging of atypical subacute thyroiditis in thyrotoxicosis: A case report.

PubMed

Yoshida, Katsuya; Yokoh, Hidetaka; Toriihara, Akira; Fujii, Hayahiko; Harata, Naoki; Isogai, Jun; Tateishi, Ukihide

2017-07-01

In addition to its established role in oncologic imaging, F-fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET/CT) is useful for the assessment of inflammatory activity. However, subacute thyroiditis (SAT) in thyrotoxicosis is rarely detected during these scans. A 66-year-old man with SAT in thyrotoxicosis demonstrated symptoms of transient fatigue, headache, and fever, without typical neck pain. Using F-FDG PET/CT, we found increased F-FDG uptake in the thyroid gland, predominantly in the right side due to SAT. We also observed a coexisting decrease in F-FDG uptake in the liver and increased F-FDG uptake in skeletal muscle due to thyrotoxicosis. Using F-FDG PET/CT, the combined observations of increased F-FDG uptake in the thyroid and skeletal muscle, and decreased F-FDG uptake in the liver, even when the typical symptom of neck pain is subtle or absent, may be helpful for the differential diagnosis of SAT in thyrotoxicosis.

A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images

PubMed Central

Yang, Qiyao; Wang, Zhiguo; Zhang, Guoxu

2017-01-01

The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning. An effective registration of PET and CT images is the basis of image fusion. This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images. Firstly, a geometric feature-based segmentation (GFS) method and a dynamic threshold denoising (DTD) method are creatively proposed to preprocess CT and PET images, respectively. Next, a new automated trunk slices extraction method is presented for extracting feature point clouds. Finally, the multithread Iterative Closet Point is adopted to drive an affine transform. We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair) of 3D whole-body PET and CT data. Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933) on feature images and less Euclidean distance error (ED = 2.826) on landmark points, outperforming the source data (NC = −0.496, ED = 25.847) and the compared method (NC = −0.614, ED = 16.085). Moreover, our method is about ten times faster than the compared one. PMID:28316979

Understanding bone responses in B-mode ultrasound images and automatic bone surface extraction using a Bayesian probabilistic framework

NASA Astrophysics Data System (ADS)

Jain, Ameet K.; Taylor, Russell H.

2004-04-01

The registration of preoperative CT to intra-operative reality systems is a crucial step in Computer Assisted Orthopedic Surgery (CAOS). The intra-operative sensors include 3D digitizers, fiducials, X-rays and Ultrasound (US). Although US has many advantages over others, tracked US for Orthopedic Surgery has been researched by only a few authors. An important factor limiting the accuracy of tracked US to CT registration (1-3mm) has been the difficulty in determining the exact location of the bone surfaces in the US images (the response could range from 2-4mm). Thus it is crucial to localize the bone surface accurately from these images. Moreover conventional US imaging systems are known to have certain inherent inaccuracies, mainly due to the fact that the imaging model is assumed planar. This creates the need to develop a bone segmentation framework that can couple information from various post-processed spatially separated US images (of the bone) to enhance the localization of the bone surface. In this paper we discuss the various reasons that cause inherent uncertainties in the bone surface localization (in B-mode US images) and suggest methods to account for these. We also develop a method for automatic bone surface detection. To do so, we account objectively for the high-level understanding of the various bone surface features visible in typical US images. A combination of these features would finally decide the surface position. We use a Bayesian probabilistic framework, which strikes a fair balance between high level understanding from features in an image and the low level number crunching of standard image processing techniques. It also provides us with a mathematical approach that facilitates combining multiple images to augment the bone surface estimate.

SU-E-J-251: Incorporation of Pre-Therapy 18F-FDG Uptake with CT Texture Features in a Predictive Model for Radiation Pneumonitis Development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anthony, G; Cunliffe, A; Armato, S

2015-06-15

Purpose: To determine whether the addition of standardized uptake value (SUV) statistical variables to CT lung texture features can improve a predictive model of radiation pneumonitis (RP) development in patients undergoing radiation therapy. Methods: Anonymized data from 96 esophageal cancer patients (18 RP-positive cases of Grade ≥ 2) were retrospectively collected including pre-therapy PET/CT scans, pre-/posttherapy diagnostic CT scans and RP status. Twenty texture features (firstorder, fractal, Laws’ filter and gray-level co-occurrence matrix) were calculated from diagnostic CT scans and compared in anatomically matched regions of the lung. The mean, maximum, standard deviation, and 50th–95th percentiles of the SUV valuesmore » for all lung voxels in the corresponding PET scans were acquired. For each texture feature, a logistic regression-based classifier consisting of (1) the average change in that texture feature value between the pre- and post-therapy CT scans and (2) the pre-therapy SUV standard deviation (SUV{sub SD}) was created. The RP-classification performance of each logistic regression model was compared to the performance of its texture feature alone by computing areas under the receiver operating characteristic curves (AUCs). T-tests were performed to determine whether the mean AUC across texture features changed significantly when SUV{sub SD} was added to the classifier. Results: The AUC for single-texturefeature classifiers ranged from 0.58–0.81 in high-dose (≥ 30 Gy) regions of the lungs and from 0.53–0.71 in low-dose (< 10 Gy) regions. Adding SUVSD in a logistic regression model using a 50/50 data partition for training and testing significantly increased the mean AUC by 0.08, 0.06 and 0.04 in the low-, medium- and high-dose regions, respectively. Conclusion: Addition of SUVSD from a pre-therapy PET scan to a single CT-based texture feature improves RP-classification performance on average. These findings demonstrate the potential for more accurate prediction of RP using information from multiple imaging modalities. Supported, in part, by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under grant number T32 EB002103; SGA receives royalties and licensing fees through the University of Chicago for computer-aided diagnosis technology. HA receives royalties through the University of Chicago for computer-aided diagnosis technology.« less

Birt-Hogg-Dube syndrome prospectively detected by review of chest computed tomography scans.

PubMed

Park, Hye Jung; Park, Chul Hwan; Lee, Sang Eun; Lee, Geun Dong; Byun, Min Kwang; Lee, Sungsoo; Lee, Kyung-A; Kim, Tae Hoon; Kim, Seong Han; Yang, Seo Yeon; Kim, Hyung Jung; Ahn, Chul Min

2017-01-01

Birt-Hogg-Dube syndrome (BHD) is a rare disorder caused by mutations in the gene that encodes folliculin (FLCN) and is inherited in an autosomal dominant manner. BHD is commonly accompanied by fibrofolliculomas, renal tumors, multiple pulmonary cysts, and spontaneous pneumothorax. The aim of this study was to detect BHD prospectively in patients undergoing chest computed tomography (CT) scans and to evaluate further the characteristics of BHD in Korea. We prospectively checked and reviewed the chest CT scans obtained for 10,883 patients at Gangnam Severance Hospital, Seoul, Korea, from June 1, 2015 to May 31, 2016. Seventeen patients met the study inclusion criteria and underwent screening for FLCN mutation to confirm BHD. We analyzed the characteristics of the patients confirmed to have BHD and those for a further 6 patients who had previously been described in Korea. Six (0.06%) of the 10,883 patients reviewed were diagnosed with BHD. There was no difference in demographic or clinical features between the patients with BHD (n = 6) and those without BHD (n = 11). Pneumothorax was present in 50% of the patients with BHD but typical skin and renal lesions were absent. The maximum size of the cysts in the BHD group (median 39.4 mm; interquartile range [IQR] 11.4 mm) was significantly larger than that in the non-BHD group (median 15.8 mm; IQR 7.8 mm; P = 0.001). Variable morphology was seen in 100.0% of the cysts in the BHD group but in only 18.2% of the cysts in the non-BHD group (P = 0.002). Nine (95%) of the total of 12 Korean patients with BHD had experienced pneumothorax. Typical skin and renal lesions were present in 20.0% of patients with BHD. Our findings suggest that BHD can be detected if chest CT scans are read in detail.

Classification of ground glass opacity lesion characteristic based on texture feature using lung CT image

NASA Astrophysics Data System (ADS)

Sebatubun, M. M.; Haryawan, C.; Windarta, B.

2018-03-01

Lung cancer causes a high mortality rate in the world than any other cancers. That can be minimised if the symptoms and cancer cells have been detected early. One of the techniques used to detect lung cancer is by computed tomography (CT) scan. CT scan images have been used in this study to identify one of the lesion characteristics named ground glass opacity (GGO). It has been used to determine the level of malignancy of the lesion. There were three phases in identifying GGO: image cropping, feature extraction using grey level co-occurrence matrices (GLCM) and classification using Naïve Bayes Classifier. In order to improve the classification results, the most significant feature was sought by feature selection using gain ratio evaluation. Based on the results obtained, the most significant features could be identified by using feature selection method used in this research. The accuracy rate increased from 83.33% to 91.67%, the sensitivity from 82.35% to 94.11% and the specificity from 84.21% to 89.47%.

The prognostic value of CT radiomic features for patients with pulmonary adenocarcinoma treated with EGFR tyrosine kinase inhibitors

PubMed Central

Kim, Hyungjin; Park, Sang Joon; Kim, Miso; Kim, Tae Min; Kim, Dong-Wan; Heo, Dae Seog; Goo, Jin Mo

2017-01-01

Purpose To determine if the radiomic features on CT can predict progression-free survival (PFS) in epidermal growth factor receptor (EGFR) mutant adenocarcinoma patients treated with first-line EGFR tyrosine kinase inhibitors (TKIs) and to identify the incremental value of radiomic features over conventional clinical factors in PFS prediction. Methods In this institutional review board–approved retrospective study, pretreatment contrast-enhanced CT and first follow-up CT after initiation of TKIs were analyzed in 48 patients (M:F = 23:25; median age: 61 years). Radiomic features at baseline, at 1st first follow-up, and the percentage change between the two were determined. A Cox regression model was used to predict PFS with nonredundant radiomic features and clinical factors, respectively. The incremental value of radiomic features over the clinical factors in PFS prediction was also assessed by way of a concordance index. Results Roundness (HR: 3.91; 95% CI: 1.72, 8.90; P = 0.001) and grey-level nonuniformity (HR: 3.60; 95% CI: 1.80, 7.18; P<0.001) were independent predictors of PFS. For clinical factors, patient age (HR: 2.11; 95% CI: 1.01, 4.39; P = 0.046), baseline tumor diameter (HR: 1.03; 95% CI: 1.01, 1.05; P = 0.002), and treatment response (HR: 0.46; 95% CI: 0.24, 0.87; P = 0.017) were independent predictors. The addition of radiomic features to clinical factors significantly improved predictive performance (concordance index; combined model = 0.77, clinical-only model = 0.69, P<0.001). Conclusions Radiomic features enable PFS estimation in EGFR mutant adenocarcinoma patients treated with first-line EGFR TKIs. Radiomic features combined with clinical factors provide significant improvement in prognostic performance compared with using only clinical factors. PMID:29099855

Bowel obstruction complicated by ischemia: analysis of CT findings.

PubMed

Cox, Veronica L; Tahvildari, Ali M; Johnson, Benjamin; Wei, Wei; Jeffrey, R Brooke

2018-06-01

To analyze CT signs of bowel ischemia in patients with surgical bowel obstruction, and thereby improve CT diagnosis in this common clinical scenario. Surgical and histopathological findings were used as the reference standard. We retrospectively analyzed CT findings in patients brought to surgery for bowel obstruction over 13 years. Etiology of obstruction (adhesion, hernia, etc.) was recorded. Specific CT features of acute mesenteric ischemia (AMI) were analyzed, including bowel wall thickening, mucosal hypoenhancement, and others. 173 cases were eligible for analysis. 21% of cases were positive for bowel ischemia. Volvulus, internal hernia, and closed-loop obstructions showed ischemia rates of 60%, 43%, and 43%; ischemia rate in obstruction from simple adhesion was 21%. Patients with bowel obstruction related to malignancy were never ischemic. Sensitivities and specificities for CT features predicting ischemia were calculated, with wall thickening, hypoenhancement, and pneumatosis showing high specificity for ischemia (86%-100%). Wall thickening, hypoenhancement, and pneumatosis are highly specific CT signs of ischemia in the setting of obstruction. None of the evaluated CT signs were found to be highly sensitive. Overall frequency of ischemia in surgical bowel obstruction is 21%, and 2-3 times that for complex obstructions (volvulus, closed loop, etc.). Obstructions related to malignancy virtually never become ischemic.

Burned bodies: post-mortem computed tomography, an essential tool for modern forensic medicine.

PubMed

Coty, J-B; Nedelcu, C; Yahya, S; Dupont, V; Rougé-Maillart, C; Verschoore, M; Ridereau Zins, C; Aubé, C

2018-06-07

Currently, post-mortem computed tomography (PMCT) has become an accessible and contemporary tool for forensic investigations. In the case of burn victims, it provides specific semiologies requiring a prudent understanding to differentiate between the normal post-mortem changes from heat-related changes. The aim of this pictorial essay is to provide to the radiologist the keys to establish complete and focused reports in cases of PMCT of burn victims. Thus, the radiologist must discern all the contextual divergences with the forensic history, and must be able to report all the relevant elements to answer to the forensic pathologist the following questions: Are there tomographic features that could help to identify the victim? Is there evidence of remains of biological fluids in liquid form available for toxicological analysis and DNA sampling? Is there another obvious cause of death than heat-related lesions, especially metallic foreign bodies of ballistic origin? Finally, what are the characteristic burn-related injuries seen on the corpse that should be sought during the autopsy? • CT is highly useful to find features permitting the identification of a severely burned body. • PMCT is a major asset in gunshot injuries to depict ballistic foreign bodies in the burned cadavers. • CT is able to recognise accessible blood for tests versus heat clot (air-crescent sign). • Heat-related fractures are easily differentiated from traumatic fractures. • Epidural collections with a subdural appearance are typical heat-related head lesions.

EDI OCT evaluation of choroidal thickness in Stargardt disease

PubMed Central

Sodi, Andrea; Bacherini, Daniela; Caporossi, Orsola; Murro, Vittoria; Mucciolo, Dario Pasquale; Cipollini, Francesca; Passerini, Ilaria; Virgili, Gianni; Rizzo, Stanislao

2018-01-01

Purpose Choroidal thickness (CT) evaluation with EDI-OCT in Stargardt Disease (STGD), considering its possible association with some clinical features of the disease. Methods CT was evaluated in 41 STGD patients and in 70 controls. Measurements were performed in the subfoveal position and at 1000 μm nasally and temporally. CT average values in STGD and in the control group were first compared by means of Student’s T test. Then, the possible association between CT and some clinical features was evaluated by means of linear regression analysis. Considered clinical parameters were: age, age on onset, duration of the disease, visual acuity, foveal thickness, Fishman clinical phenotype, visual field loss and ERG response. Results Average CT was not significantly different between controls and STGD patients. In the STGD group the correlation between CT and age (r = 0.22, p = 0.033) and age of onset (r = 0.05, p = 0.424) was modest, while that of CT with disease duration (r = 0.30, p<0.001) was moderate. CT and foveal thickness were also significantly but modestly correlated (r = 0.15, p = 0.033). Conclusion In our series average CT is not significantly changed in STGD in comparison with the controls. Nevertheless a choroidal thinning may be identified in the more advanced stages of the disease. PMID:29304098

Textural features and SUV-based variables assessed by dual time point 18F-FDG PET/CT in locally advanced breast cancer.

PubMed

Garcia-Vicente, Ana María; Molina, David; Pérez-Beteta, Julián; Amo-Salas, Mariano; Martínez-González, Alicia; Bueno, Gloria; Tello-Galán, María Jesús; Soriano-Castrejón, Ángel

2017-12-01

To study the influence of dual time point 18F-FDG PET/CT in textural features and SUV-based variables and their relation among them. Fifty-six patients with locally advanced breast cancer (LABC) were prospectively included. All of them underwent a standard 18F-FDG PET/CT (PET-1) and a delayed acquisition (PET-2). After segmentation, SUV variables (SUVmax, SUVmean, and SUVpeak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were obtained. Eighteen three-dimensional (3D) textural measures were computed including: run-length matrices (RLM) features, co-occurrence matrices (CM) features, and energies. Differences between all PET-derived variables obtained in PET-1 and PET-2 were studied. Significant differences were found between the SUV-based parameters and MTV obtained in the dual time point PET/CT, with higher values of SUV-based variables and lower MTV in the PET-2 with respect to the PET-1. In relation with the textural parameters obtained in dual time point acquisition, significant differences were found for the short run emphasis, low gray-level run emphasis, short run high gray-level emphasis, run percentage, long run emphasis, gray-level non-uniformity, homogeneity, and dissimilarity. Textural variables showed relations with MTV and TLG. Significant differences of textural features were found in dual time point 18F-FDG PET/CT. Thus, a dynamic behavior of metabolic characteristics should be expected, with higher heterogeneity in delayed PET acquisition compared with the standard PET. A greater heterogeneity was found in bigger tumors.

Hybrid registration of PET/CT in thoracic region with pre-filtering PET sinogram

NASA Astrophysics Data System (ADS)

Mokri, S. S.; Saripan, M. I.; Marhaban, M. H.; Nordin, A. J.; Hashim, S.

2015-11-01

The integration of physiological (PET) and anatomical (CT) images in cancer delineation requires an accurate spatial registration technique. Although hybrid PET/CT scanner is used to co-register these images, significant misregistrations exist due to patient and respiratory/cardiac motions. This paper proposes a hybrid feature-intensity based registration technique for hybrid PET/CT scanner. First, simulated PET sinogram was filtered with a 3D hybrid mean-median before reconstructing the image. The features were then derived from the segmented structures (lung, heart and tumor) from both images. The registration was performed based on modified multi-modality demon registration with multiresolution scheme. Apart from visual observations improvements, the proposed registration technique increased the normalized mutual information index (NMI) between the PET/CT images after registration. All nine tested datasets show marked improvements in mutual information (MI) index than free form deformation (FFD) registration technique with the highest MI increase is 25%.

Nonlinear dimensionality reduction of CT histogram based feature space for predicting recurrence-free survival in non-small-cell lung cancer

NASA Astrophysics Data System (ADS)

Kawata, Y.; Niki, N.; Ohmatsu, H.; Aokage, K.; Kusumoto, M.; Tsuchida, T.; Eguchi, K.; Kaneko, M.

2015-03-01

Advantages of CT scanners with high resolution have allowed the improved detection of lung cancers. In the recent release of positive results from the National Lung Screening Trial (NLST) in the US showing that CT screening does in fact have a positive impact on the reduction of lung cancer related mortality. While this study does show the efficacy of CT based screening, physicians often face the problems of deciding appropriate management strategies for maximizing patient survival and for preserving lung function. Several key manifold-learning approaches efficiently reveal intrinsic low-dimensional structures latent in high-dimensional data spaces. This study was performed to investigate whether the dimensionality reduction can identify embedded structures from the CT histogram feature of non-small-cell lung cancer (NSCLC) space to improve the performance in predicting the likelihood of RFS for patients with NSCLC.

Comparing risk estimates following diagnostic CT radiation exposures employing different methodological approaches.

PubMed

Kashcheev, Valery V; Pryakhin, Evgeny A; Menyaylo, Alexander N; Chekin, Sergey Yu; Ivanov, Viktor K

2014-06-01

The current study has two aims: the first is to quantify the difference between radiation risks estimated with the use of organ or effective doses, particularly when planning pediatric and adult computed tomography (CT) examinations. The second aim is to determine the method of calculating organ doses and cancer risk using dose-length product (DLP) for typical routine CT examinations. In both cases, the radiation-induced cancer risks from medical CT examinations were evaluated as a function of gender and age. Lifetime attributable risk values from CT scanning were estimated with the use of ICRP (Publication 103) risk models and Russian national medical statistics data. For populations under the age of 50 y, the risk estimates based on organ doses usually are 30% higher than estimates based on effective doses. In older populations, the difference can be up to a factor of 2.5. The typical distributions of organ doses were defined for Chest Routine, Abdominal Routine, and Head Routine examinations. The distributions of organ doses were dependent on the anatomical region of scanning. The most exposed organs/tissues were thyroid, breast, esophagus, and lungs in cases of Chest Routine examination; liver, stomach, colon, ovaries, and bladder in cases of Abdominal Routine examination; and brain for Head Routine examinations. The conversion factors for calculation of typical organ doses or tissues at risk using DLP were determined. Lifetime attributable risk of cancer estimated with organ doses calculated from DLP was compared with the risk estimated on the basis of organ doses measured with the use of silicon photodiode dosimeters. The estimated difference in LAR is less than 29%.

Robust hepatic vessel segmentation using multi deep convolution network

NASA Astrophysics Data System (ADS)

Kitrungrotsakul, Titinunt; Han, Xian-Hua; Iwamoto, Yutaro; Foruzan, Amir Hossein; Lin, Lanfen; Chen, Yen-Wei

2017-03-01

Extraction of blood vessels of the organ is a challenging task in the area of medical image processing. It is really difficult to get accurate vessel segmentation results even with manually labeling by human being. The difficulty of vessels segmentation is the complicated structure of blood vessels and its large variations that make them hard to recognize. In this paper, we present deep artificial neural network architecture to automatically segment the hepatic vessels from computed tomography (CT) image. We proposed novel deep neural network (DNN) architecture for vessel segmentation from a medical CT volume, which consists of three deep convolution neural networks to extract features from difference planes of CT data. The three networks have share features at the first convolution layer but will separately learn their own features in the second layer. All three networks will join again at the top layer. To validate effectiveness and efficiency of our proposed method, we conduct experiments on 12 CT volumes which training data are randomly generate from 5 CT volumes and 7 using for test. Our network can yield an average dice coefficient 0.830, while 3D deep convolution neural network can yield around 0.7 and multi-scale can yield only 0.6.

Cardiopulmonary manifestations of isolated pulmonary valve infective endocarditis demonstrated with cardiac CT.

PubMed

Passen, Edward; Feng, Zekun

2015-01-01

Right-sided infective endocarditis involving the pulmonary valve is rare. This pictorial essay discusses the use and findings of cardiac CT combined with delayed chest CT and noncontrast chest CT of pulmonary valve endocarditis. Cardiac CT is able to show the full spectrum of right-sided endocarditis cardiopulmonary features including manifestations that cannot be demonstrated by echocardiography. Copyright © 2015 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Multicenter comparison of 18F-FDG and 68Ga-DOTA-peptide PET/CT for pulmonary carcinoid.

PubMed

Lococo, Filippo; Perotti, Germano; Cardillo, Giuseppe; De Waure, Chiara; Filice, Angelina; Graziano, Paolo; Rossi, Giulio; Sgarbi, Giorgio; Stefanelli, Antonella; Giordano, Alessandro; Granone, Pierluigi; Rindi, Guido; Versari, Annibale; Rufini, Vittoria

2015-03-01

The aims of this study were to retrospectively evaluate and compare the detection rate (DR) of 68Ga-DOTA-peptide and 18F-FDG PET/CT in the preoperative workup of patients with pulmonary carcinoid (PC) and to assess the utility of various functional indices obtained with the 2 tracers in predicting the histological characterization of PC, that is, typical versus atypical. Thirty-three consecutive patients with confirmed PC referred for 18F-FDG and 68Ga-DOTA-peptide PET/CT in 2 centers between January 2009 and April 2013 were included. The semiquantitative evaluation included the SUV max, the SUV of the tumor relative to the maximal liver uptake for 18F-FDG (SUV T/L) or the maximal spleen uptake for 68Ga-DOTA-peptides (SUV T/S), the ratio between SUV max of 68Ga-DOTA-peptides PET/CT, and the SUV max of 18F-FDG PET/CT (SUV max ratio). Histology was used as reference standard. Definitive diagnosis consisted of 23 typical carcinoids (TCs) and 10 atypical carcinoids. 18F-FDG PET/CT was positive in 18 cases and negative in 15 (55% DR). 68Ga-DOTA-peptide PET/CT was positive in 26 cases and negative in 7 (79% DR). In the subgroup analysis, 68Ga-DOTA-peptide PET/CT was superior in detecting TC (91% DR; P < 0.001), whereas 18F-FDG PET/CT was superior in detecting atypical carcinoid (100% DR; P = 0.04). The SUV max ratio was the most accurate semiquantitative index in identifying TC. Overall diagnostic performance of PET/CT in detecting PC is optimal when integrating 18F-FDG and 68Ga-DOTA-peptide PET/CT findings. In the subgroup analysis, the SUV max ratio seems to be the most accurate index in predicting TC. Both methods should be performed when PC is suspected or when the histological subtype is undefined.

CT imaging of malignant metastatic hemangiopericytoma of the parotid gland with histopathological correlation

PubMed Central

Khoo, James B.; Sittampalam, Kesavan; Chee, Soo K.

2008-01-01

Abstract We report an extremely rare case of malignant hemangiopericytoma (HPC) of the parotid gland and its metastatic spread to lung, liver, and skeletal muscle. Computed tomography (CT) imaging, histopathological and immunohistochemical methods were employed to study the features of malignant HPC and its metastases. CT imaging was helpful to determine the exact location, involvement of adjacent structures and vascularity, as well as evaluating pulmonary, hepatic, peritoneal, and muscular metastases. Immunohistochemical and histopatholgical features of the primary tumor as well as the metastases were consistent with the diagnosis of malignant HPC. PMID:18940737

Quantitative Features of Liver Lesions, Lung Nodules, and Renal Stones at Multi-Detector Row CT Examinations: Dependency on Radiation Dose and Reconstruction Algorithm.

PubMed

Solomon, Justin; Mileto, Achille; Nelson, Rendon C; Roy Choudhury, Kingshuk; Samei, Ehsan

2016-04-01

To determine if radiation dose and reconstruction algorithm affect the computer-based extraction and analysis of quantitative imaging features in lung nodules, liver lesions, and renal stones at multi-detector row computed tomography (CT). Retrospective analysis of data from a prospective, multicenter, HIPAA-compliant, institutional review board-approved clinical trial was performed by extracting 23 quantitative imaging features (size, shape, attenuation, edge sharpness, pixel value distribution, and texture) of lesions on multi-detector row CT images of 20 adult patients (14 men, six women; mean age, 63 years; range, 38-72 years) referred for known or suspected focal liver lesions, lung nodules, or kidney stones. Data were acquired between September 2011 and April 2012. All multi-detector row CT scans were performed at two different radiation dose levels; images were reconstructed with filtered back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction (MBIR) algorithms. A linear mixed-effects model was used to assess the effect of radiation dose and reconstruction algorithm on extracted features. Among the 23 imaging features assessed, radiation dose had a significant effect on five, three, and four of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). Adaptive statistical iterative reconstruction had a significant effect on three, one, and one of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). MBIR reconstruction had a significant effect on nine, 11, and 15 of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). Of note, the measured size of lung nodules and renal stones with MBIR was significantly different than those for the other two algorithms (P < .002 for all comparisons). Although lesion texture was significantly affected by the reconstruction algorithm used (average of 3.33 features affected by MBIR throughout lesion types; P < .002, for all comparisons), no significant effect of the radiation dose setting was observed for all but one of the texture features (P = .002-.998). Radiation dose settings and reconstruction algorithms affect the extraction and analysis of quantitative imaging features in lesions at multi-detector row CT.

Improved pulmonary nodule classification utilizing quantitative lung parenchyma features.

PubMed

Dilger, Samantha K N; Uthoff, Johanna; Judisch, Alexandra; Hammond, Emily; Mott, Sarah L; Smith, Brian J; Newell, John D; Hoffman, Eric A; Sieren, Jessica C

2015-10-01

Current computer-aided diagnosis (CAD) models for determining pulmonary nodule malignancy characterize nodule shape, density, and border in computed tomography (CT) data. Analyzing the lung parenchyma surrounding the nodule has been minimally explored. We hypothesize that improved nodule classification is achievable by including features quantified from the surrounding lung tissue. To explore this hypothesis, we have developed expanded quantitative CT feature extraction techniques, including volumetric Laws texture energy measures for the parenchyma and nodule, border descriptors using ray-casting and rubber-band straightening, histogram features characterizing densities, and global lung measurements. Using stepwise forward selection and leave-one-case-out cross-validation, a neural network was used for classification. When applied to 50 nodules (22 malignant and 28 benign) from high-resolution CT scans, 52 features (8 nodule, 39 parenchymal, and 5 global) were statistically significant. Nodule-only features yielded an area under the ROC curve of 0.918 (including nodule size) and 0.872 (excluding nodule size). Performance was improved through inclusion of parenchymal (0.938) and global features (0.932). These results show a trend toward increased performance when the parenchyma is included, coupled with the large number of significant parenchymal features that support our hypothesis: the pulmonary parenchyma is influenced differentially by malignant versus benign nodules, assisting CAD-based nodule characterizations.

The impact of personality disorder pathology on the effectiveness of Cognitive Therapy and Interpersonal Psychotherapy for Major Depressive Disorder.

PubMed

van Bronswijk, Suzanne C; Lemmens, Lotte H J M; Viechtbauer, Wolfgang; Huibers, Marcus J H; Arntz, Arnoud; Peeters, Frenk P M L

2018-01-01

Despite extensive research, there is no consensus how Personality Disorders (PD) and PD features affect outcome for Major Depressive Disorder (MDD). The present study evaluated the effects of PD (features) on treatment continuation and effectiveness in Cognitive Therapy (CT) and Interpersonal Psychotherapy (IPT) for MDD. Depressed outpatients were randomized to CT (n=72) and IPT (n=74). Primary outcome was depression severity measured repeatedly with the Beck Depression Inventory-II (BDI-II) at baseline, three months, at the start of each therapy session, at post-treatment and monthly during five months follow-up. Comorbid PD and PD features did not affect dropout. Multilevel and Cox regression models indicated no negative effect of PD on BDI-II change and remission rates during treatment and follow-up, irrespective of the treatment received. For both therapies, higher dependent PD features predicted overall lower BDI-II scores during treatment, however this effect did not sustain through follow-up. Cluster A PD features moderated treatment outcome during treatment and follow-up: individuals with high cluster A PD features had greater BDI-II reductions over time in CT as compared to IPT. Not all therapists and participants were blind to the assessment of PD (features), and assessments were performed by one rater. Further research must investigate the state and trait dependent changes of PD and MDD over time. We found no negative impact of PD on the effectiveness and treatment retention of CT and IPT for MDD during treatment and follow-up. If replicated, cluster A PD features can be used to optimize treatment selection. Copyright © 2017 Elsevier B.V. All rights reserved.

High-performance computer aided detection system for polyp detection in CT colonography with fluid and fecal tagging

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Wang, Shijun; Kabadi, Suraj; Summers, Ronald M.

2009-02-01

CT colonography (CTC) is a feasible and minimally invasive method for the detection of colorectal polyps and cancer screening. Computer-aided detection (CAD) of polyps has improved consistency and sensitivity of virtual colonoscopy interpretation and reduced interpretation burden. A CAD system typically consists of four stages: (1) image preprocessing including colon segmentation; (2) initial detection generation; (3) feature selection; and (4) detection classification. In our experience, three existing problems limit the performance of our current CAD system. First, highdensity orally administered contrast agents in fecal-tagging CTC have scatter effects on neighboring tissues. The scattering manifests itself as an artificial elevation in the observed CT attenuation values of the neighboring tissues. This pseudo-enhancement phenomenon presents a problem for the application of computer-aided polyp detection, especially when polyps are submerged in the contrast agents. Second, general kernel approach for surface curvature computation in the second stage of our CAD system could yield erroneous results for thin structures such as small (6-9 mm) polyps and for touching structures such as polyps that lie on haustral folds. Those erroneous curvatures will reduce the sensitivity of polyp detection. The third problem is that more than 150 features are selected from each polyp candidate in the third stage of our CAD system. These high dimensional features make it difficult to learn a good decision boundary for detection classification and reduce the accuracy of predictions. Therefore, an improved CAD system for polyp detection in CTC data is proposed by introducing three new techniques. First, a scale-based scatter correction algorithm is applied to reduce pseudo-enhancement effects in the image pre-processing stage. Second, a cubic spline interpolation method is utilized to accurately estimate curvatures for initial detection generation. Third, a new dimensionality reduction classifier, diffusion map and local linear embedding (DMLLE), is developed for classification and false positives (FP) reduction. Performance of the improved CAD system is evaluated and compared with our existing CAD system (without applying those techniques) using CT scans of 1186 patients. These scans are divided into a training set and a test set. The sensitivity of the improved CAD system increased 18% on training data at a rate of 5 FPs per patient and 15% on test data at a rate of 5 FPs per patient. Our results indicated that the improved CAD system achieved significantly better performance on medium-sized colonic adenomas with higher sensitivity and lower FP rate in CTC.

Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability.

PubMed

Kim, Hyungjin; Park, Chang Min; Lee, Myunghee; Park, Sang Joon; Song, Yong Sub; Lee, Jong Hyuk; Hwang, Eui Jin; Goo, Jin Mo

2016-01-01

To identify the impact of reconstruction algorithms on CT radiomic features of pulmonary tumors and to reveal and compare the intra- and inter-reader and inter-reconstruction algorithm variability of each feature. Forty-two patients (M:F = 19:23; mean age, 60.43±10.56 years) with 42 pulmonary tumors (22.56±8.51mm) underwent contrast-enhanced CT scans, which were reconstructed with filtered back projection and commercial iterative reconstruction algorithm (level 3 and 5). Two readers independently segmented the whole tumor volume. Fifteen radiomic features were extracted and compared among reconstruction algorithms. Intra- and inter-reader variability and inter-reconstruction algorithm variability were calculated using coefficients of variation (CVs) and then compared. Among the 15 features, 5 first-order tumor intensity features and 4 gray level co-occurrence matrix (GLCM)-based features showed significant differences (p<0.05) among reconstruction algorithms. As for the variability, effective diameter, sphericity, entropy, and GLCM entropy were the most robust features (CV≤5%). Inter-reader variability was larger than intra-reader or inter-reconstruction algorithm variability in 9 features. However, for entropy, homogeneity, and 4 GLCM-based features, inter-reconstruction algorithm variability was significantly greater than inter-reader variability (p<0.013). Most of the radiomic features were significantly affected by the reconstruction algorithms. Inter-reconstruction algorithm variability was greater than inter-reader variability for entropy, homogeneity, and GLCM-based features.

Effect of magnet/slot combination on triple-frequency magnetic force and vibration of permanent magnet motors

NASA Astrophysics Data System (ADS)

Huo, Mina; Wang, Shiyu; Xiu, Jie; Cao, Shuqian

2013-10-01

The relationship between magnet/slot combination and magnetic forces including unbalanced magnetic force (UMF) and cogging torque (CT) of permanent magnet (PM) motors is investigated by using superposition principle and mechanical and magnetic symmetries. The results show that magnetic force can be produced by all magnets passing a single slot, by all slots passing a single magnet, or by eccentricity, which respectively correspond to three frequency components. The results further show that net force/torque can be classified into three typical cases: UMF is suppressed and CT is excited, UMF excited and CT suppressed, and UMF and CT both suppressed, and consequently possible vibrations include three unique groups: rotational modes, translational modes, and balanced modes. The conclusion that combinations with the greatest common divisor (GCD) greater than unity can avoid UMF is mathematically verified, and at the same time lower CT harmonics are preliminarily addressed by the typical excitations. The above findings can create simple guidelines for the suppression of certain UMF and/or CT by using suitable combinations, which in turn can present approach to yield a more desirable response in high performance applications. The superposition effect and predicted relationship are verified by the transient magnetic Finite Element method. Since this work is motivated by symmetries, comparisons are made in order to give further insight into the inner force and vibration behaviors of general rotary power-transmission systems.

Post-infectious bronchiolitis obliterans in children: CT features that predict responsiveness to pulse methylprednisolone.

PubMed

Yoon, H M; Lee, J S; Hwang, J-Y; Cho, Y A; Yoon, H-K; Yu, J; Hong, S-J; Yoon, C H

2015-05-01

Intravenous pulse methylprednisolone therapy (IPMT) is an important treatment option for post-infectious obliterative bronchiolitis (OB), although it must be used carefully and only in selected patients because of its drawbacks. This study evaluated whether CT and clinical features of children with post-infectious OB can predict their responsiveness to IPMT. We searched the medical records for patients (less than 18 years of age) who were diagnosed with post-infectious OB between January 2000 and December 2011. 17 children who received IPMT were included in this study. All underwent chest CT before and after IPMT. The radiological features seen on pre-treatment CT were recorded. The air-trapping area percentages on pre- and post-treatment CT images were determined. The nine patients who exhibited decreased air trapping on post-treatment CT scans relative to pre-treatment scans were classed as responders. The patient ages and time from initial pneumonia to IPMT were recorded. All responders and only four non-responders had thickened bronchial walls before treatment (p = 0.029). The two groups did not differ significantly in terms of bronchiolitis, bronchiectasis or the extent of air trapping, although the responders had a significantly shorter median interval between initial pneumonia and IPMT (4 vs 50 months; p = 0.005) and were significantly younger (median, 2.0 vs 7.5 years; p = 0.048). Immediate IPMT may improve the degree of air trapping in children with post-infectious OB if they show a thickened bronchial wall on CT. Children with post-infectious OB may respond favourably to IPMT when pre-treatment CT indicates bronchial-wall thickening.

Validation of CBCT for the computation of textural biomarkers

NASA Astrophysics Data System (ADS)

Paniagua, Beatriz; Ruellas, Antonio C.; Benavides, Erika; Marron, Steve; Wolford, Larry; Cevidanes, Lucia

2015-03-01

Osteoarthritis (OA) is associated with significant pain and 42.6% of patients with TMJ disorders present with evidence of TMJ OA. However, OA diagnosis and treatment remain controversial, since there are no clear symptoms of the disease. The subchondral bone in the TMJ is believed to play a major role in the progression of OA. We hypothesize that the textural imaging biomarkers computed in high resolution Conebeam CT (hr- CBCT) and μCT scans are comparable. The purpose of this study is to test the feasibility of computing textural imaging biomarkers in-vivo using hr-CBCT, compared to those computed in μCT scans as our Gold Standard. Specimens of condylar bones obtained from condylectomies were scanned using μCT and hr- CBCT. Nine different textural imaging biomarkers (four co-occurrence features and five run-length features) from each pair of μCT and hr-CBCT were computed and compared. Pearson correlation coefficients were computed to compare textural biomarkers values of μCT and hr-CBCT. Four of the nine computed textural biomarkers showed a strong positive correlation between biomarkers computed in μCT and hr-CBCT. Higher correlations in Energy and Contrast, and in GLN (grey-level non-uniformity) and RLN (run length non-uniformity) indicate quantitative texture features can be computed reliably in hr-CBCT, when compared with μCT. The textural imaging biomarkers computed in-vivo hr-CBCT have captured the structure, patterns, contrast between neighboring regions and uniformity of healthy and/or pathologic subchondral bone. The ability to quantify bone texture non-invasively now makes it possible to evaluate the progression of subchondral bone alterations, in TMJ OA.

Validation of CBCT for the computation of textural biomarkers

PubMed Central

Paniagua, Beatriz; Ruellas, Antonio Carlos; Benavides, Erika; Marron, Steve; Woldford, Larry; Cevidanes, Lucia

2015-01-01

Osteoarthritis (OA) is associated with significant pain and 42.6% of patients with TMJ disorders present with evidence of TMJ OA. However, OA diagnosis and treatment remain controversial, since there are no clear symptoms of the disease. The subchondral bone in the TMJ is believed to play a major role in the progression of OA. We hypothesize that the textural imaging biomarkers computed in high resolution Conebeam CT (hr-CBCT) and μCT scans are comparable. The purpose of this study is to test the feasibility of computing textural imaging biomarkers in-vivo using hr-CBCT, compared to those computed in μCT scans as our Gold Standard. Specimens of condylar bones obtained from condylectomies were scanned using μCT and hr-CBCT. Nine different textural imaging biomarkers (four co-occurrence features and five run-length features) from each pair of μCT and hr-CBCT were computed and compared. Pearson correlation coefficients were computed to compare textural biomarkers values of μCT and hr-CBCT. Four of the nine computed textural biomarkers showed a strong positive correlation between biomarkers computed in μCT and hr-CBCT. Higher correlations in Energy and Contrast, and in GLN (grey-level non-uniformity) and RLN (run length non-uniformity) indicate quantitative texture features can be computed reliably in hr-CBCT, when compared with μCT. The textural imaging biomarkers computed in-vivo hr-CBCT have captured the structure, patterns, contrast between neighboring regions and uniformity of healthy and/or pathologic subchondral bone. The ability to quantify bone texture non-invasively now makes it possible to evaluate the progression of subchondral bone alterations, in TMJ OA. PMID:26085710

Validation of CBCT for the computation of textural biomarkers.

PubMed

Paniagua, Beatriz; Ruellas, Antonio Carlos; Benavides, Erika; Marron, Steve; Woldford, Larry; Cevidanes, Lucia

2015-03-17

Osteoarthritis (OA) is associated with significant pain and 42.6% of patients with TMJ disorders present with evidence of TMJ OA. However, OA diagnosis and treatment remain controversial, since there are no clear symptoms of the disease. The subchondral bone in the TMJ is believed to play a major role in the progression of OA. We hypothesize that the textural imaging biomarkers computed in high resolution Conebeam CT (hr-CBCT) and μCT scans are comparable. The purpose of this study is to test the feasibility of computing textural imaging biomarkers in-vivo using hr-CBCT, compared to those computed in μCT scans as our Gold Standard. Specimens of condylar bones obtained from condylectomies were scanned using μCT and hr-CBCT. Nine different textural imaging biomarkers (four co-occurrence features and five run-length features) from each pair of μCT and hr-CBCT were computed and compared. Pearson correlation coefficients were computed to compare textural biomarkers values of μCT and hr-CBCT. Four of the nine computed textural biomarkers showed a strong positive correlation between biomarkers computed in μCT and hr-CBCT. Higher correlations in Energy and Contrast, and in GLN (grey-level non-uniformity) and RLN (run length non-uniformity) indicate quantitative texture features can be computed reliably in hr-CBCT, when compared with μCT. The textural imaging biomarkers computed in-vivo hr-CBCT have captured the structure, patterns, contrast between neighboring regions and uniformity of healthy and/or pathologic subchondral bone. The ability to quantify bone texture non-invasively now makes it possible to evaluate the progression of subchondral bone alterations, in TMJ OA.

Multiple supervised residual network for osteosarcoma segmentation in CT images.

PubMed

Zhang, Rui; Huang, Lin; Xia, Wei; Zhang, Bo; Qiu, Bensheng; Gao, Xin

2018-01-01

Automatic and accurate segmentation of osteosarcoma region in CT images can help doctor make a reasonable treatment plan, thus improving cure rate. In this paper, a multiple supervised residual network (MSRN) was proposed for osteosarcoma image segmentation. Three supervised side output modules were added to the residual network. The shallow side output module could extract image shape features, such as edge features and texture features. The deep side output module could extract semantic features. The side output module could compute the loss value between output probability map and ground truth and back-propagate the loss information. Then, the parameters of residual network could be modified by gradient descent method. This could guide the multi-scale feature learning of the network. The final segmentation results were obtained by fusing the results output by the three side output modules. A total of 1900 CT images from 15 osteosarcoma patients were used to train the network and a total of 405 CT images from another 8 osteosarcoma patients were used to test the network. Results indicated that MSRN enabled a dice similarity coefficient (DSC) of 89.22%, a sensitivity of 88.74% and a F1-measure of 0.9305, which were larger than those obtained by fully convolutional network (FCN) and U-net. Thus, MSRN for osteosarcoma segmentation could give more accurate results than FCN and U-Net. Copyright © 2018 Elsevier Ltd. All rights reserved.

3D Riesz-wavelet based Covariance descriptors for texture classification of lung nodule tissue in CT.

PubMed

Cirujeda, Pol; Muller, Henning; Rubin, Daniel; Aguilera, Todd A; Loo, Billy W; Diehn, Maximilian; Binefa, Xavier; Depeursinge, Adrien

2015-01-01

In this paper we present a novel technique for characterizing and classifying 3D textured volumes belonging to different lung tissue types in 3D CT images. We build a volume-based 3D descriptor, robust to changes of size, rigid spatial transformations and texture variability, thanks to the integration of Riesz-wavelet features within a Covariance-based descriptor formulation. 3D Riesz features characterize the morphology of tissue density due to their response to changes in intensity in CT images. These features are encoded in a Covariance-based descriptor formulation: this provides a compact and flexible representation thanks to the use of feature variations rather than dense features themselves and adds robustness to spatial changes. Furthermore, the particular symmetric definite positive matrix form of these descriptors causes them to lay in a Riemannian manifold. Thus, descriptors can be compared with analytical measures, and accurate techniques from machine learning and clustering can be adapted to their spatial domain. Additionally we present a classification model following a "Bag of Covariance Descriptors" paradigm in order to distinguish three different nodule tissue types in CT: solid, ground-glass opacity, and healthy lung. The method is evaluated on top of an acquired dataset of 95 patients with manually delineated ground truth by radiation oncology specialists in 3D, and quantitative sensitivity and specificity values are presented.

Pulmonary embolism detection using localized vessel-based features in dual energy CT

NASA Astrophysics Data System (ADS)

Dicente Cid, Yashin; Depeursinge, Adrien; Foncubierta Rodríguez, Antonio; Platon, Alexandra; Poletti, Pierre-Alexandre; Müller, Henning

2015-03-01

Pulmonary embolism (PE) affects up to 600,000 patients and contributes to at least 100,000 deaths every year in the United States alone. Diagnosis of PE can be difficult as most symptoms are unspecific and early diagnosis is essential for successful treatment. Computed Tomography (CT) images can show morphological anomalies that suggest the existence of PE. Various image-based procedures have been proposed for improving computer-aided diagnosis of PE. We propose a novel method for detecting PE based on localized vessel-based features computed in Dual Energy CT (DECT) images. DECT provides 4D data indexed by the three spatial coordinates and the energy level. The proposed features encode the variation of the Hounsfield Units across the different levels and the CT attenuation related to the amount of iodine contrast in each vessel. A local classification of the vessels is obtained through the classification of these features. Moreover, the localization of the vessel in the lung provides better comparison between patients. Results show that the simple features designed are able to classify pulmonary embolism patients with an AUC (area under the receiver operating curve) of 0.71 on a lobe basis. Prior segmentation of the lung lobes is not necessary because an automatic atlas-based segmentation obtains similar AUC levels (0.65) for the same dataset. The automatic atlas reaches 0.80 AUC in a larger dataset with more control cases.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnan, Kalpagam; Liu, Jeff; Kohli, Kirpal

Purpose: Fusion of electrical impedance tomography (EIT) with computed tomography (CT) can be useful as a clinical tool for providing additional physiological information about tissues, but requires suitable fusion algorithms and validation procedures. This work explores the feasibility of fusing EIT and CT images using an algorithm for coregistration. The imaging performance is validated through feature space assessment on phantom contrast targets. Methods: EIT data were acquired by scanning a phantom using a circuit, configured for injecting current through 16 electrodes, placed around the phantom. A conductivity image of the phantom was obtained from the data using electrical impedance andmore » diffuse optical tomography reconstruction software (EIDORS). A CT image of the phantom was also acquired. The EIT and CT images were fused using a region of interest (ROI) coregistration fusion algorithm. Phantom imaging experiments were carried out on objects of different contrasts, sizes, and positions. The conductive medium of the phantoms was made of a tissue-mimicking bolus material that is routinely used in clinical radiation therapy settings. To validate the imaging performance in detecting different contrasts, the ROI of the phantom was filled with distilled water and normal saline. Spatially separated cylindrical objects of different sizes were used for validating the imaging performance in multiple target detection. Analyses of the CT, EIT and the EIT/CT phantom images were carried out based on the variations of contrast, correlation, energy, and homogeneity, using a gray level co-occurrence matrix (GLCM). A reference image of the phantom was simulated using EIDORS, and the performances of the CT and EIT imaging systems were evaluated and compared against the performance of the EIT/CT system using various feature metrics, detectability, and structural similarity index measures. Results: In detecting distilled and normal saline water in bolus medium, EIT as a stand-alone imaging system showed contrast discrimination of 47%, while the CT imaging system showed a discrimination of only 1.5%. The structural similarity index measure showed a drop of 24% with EIT imaging compared to CT imaging. The average detectability measure for CT imaging was found to be 2.375 ± 0.19 before fusion. After complementing with EIT information, the detectability measure increased to 11.06 ± 2.04. Based on the feature metrics, the functional imaging quality of CT and EIT were found to be 2.29% and 86%, respectively, before fusion. Structural imaging quality was found to be 66% for CT and 16% for EIT. After fusion, functional imaging quality improved in CT imaging from 2.29% to 42% and the structural imaging quality of EIT imaging changed from 16% to 66%. The improvement in image quality was also observed in detecting objects of different sizes. Conclusions: The authors found a significant improvement in the contrast detectability performance of CT imaging when complemented with functional imaging information from EIT. Along with the feature assessment metrics, the concept of complementing CT with EIT imaging can lead to an EIT/CT imaging modality which might fully utilize the functional imaging abilities of EIT imaging, thereby enhancing the quality of care in the areas of cancer diagnosis and radiotherapy treatment planning.« less

Cranio-orbital primary intraosseous haemangioma

PubMed Central

Gupta, T; Rose, G E; Manisali, M; Minhas, P; Uddin, J M; Verity, D H

2013-01-01

Purpose Primary intraosseous haemangioma (IOH) is a rare benign neoplasm presenting in the fourth and fifth decades of life. The spine and skull are the most commonly involved, orbital involvement is extremely rare. We describe six patients with cranio-orbital IOH, the largest case series to date. Patients and methods Retrospective review of six patients with histologically confirmed primary IOH involving the orbit. Clinical characteristics, imaging features, approach to management, and histopathological findings are described. Results Five patients were male with a median age of 56. Pain and diplopia were the most common presenting features. A characteristic ‘honeycomb' pattern on CT imaging was demonstrated in three of the cases. Complete surgical excision was performed in all cases with presurgical embolisation carried out in one case. In all the cases, histological studies identified cavernous vascular spaces within the bony tissue. These channels were lined by single layer of cytologically normal endothelial cells. Discussion IOCH of the cranio-orbital region is rare; in the absence of typical imaging features, the differential diagnosis includes chondroma, chondrosarcoma, bony metastasis, and lymphoma. Surgical excision may be necessary to exclude more sinister pathology. Intraoperative haemorrhage can be severe and may be reduced by preoperative embolisation. PMID:23989119

SU-D-207-01: Markerless Respiratory Motion Tracking with Contrast Enhanced Thoracic Cone Beam CT Projections

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chao, M; Yuan, Y; Rosenzweig, K

2015-06-15

Purpose: To develop a novel technique to enhance the image contrast of clinical cone beam CT projections and extract respiratory signals based on anatomical motion using the modified Amsterdam Shroud (AS) method to benefit image guided radiation therapy. Methods: Thoracic cone beam CT projections acquired prior to treatment were preprocessed to increase their contrast for better respiratory signal extraction. Air intensity on raw images was firstly estimated and then applied to correct the projections to generate new attenuation images that were subsequently improved with deeper anatomy feature enhancement through taking logarithm operation, derivative along superior-inferior direction, respectively. All pixels onmore » individual post-processed two dimensional images were horizontally summed to one column and all projections were combined side by side to create an AS image from which patient’s respiratory signal was extracted. The impact of gantry rotation on the breathing signal rendering was also investigated. Ten projection image sets from five lung cancer patients acquired with the Varian Onboard Imager on 21iX Clinac (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Results: Application of the air correction on raw projections showed that more than an order of magnitude of contrast enhancement was achievable. The typical contrast on the raw projections is around 0.02 while that on attenuation images could greater than 0.5. Clear and stable breathing signal can be reliably extracted from the new images while the uncorrected projection sets failed to yield clear signals most of the time. Conclusion: Anatomy feature plays a key role in yielding breathing signal from the projection images using the AS technique. The air correction process facilitated the contrast enhancement significantly and attenuation images thus obtained provides a practical solution to obtaining markerless breathing motion tracking.« less

Adenocarcinoma with BAC Features Presented as the Nonsolid Nodule Is Prone to Be False-Negative on 18F-FDG PET/CT

PubMed Central

Wu, Hu-bing; Wang, Lijuan; Wang, Quan-shi; Han, Yan-jian; Li, Hong-sheng; Zhou, Wen-lan; Tian, Ying

2015-01-01

Purpose. The present study investigated which type of adenocarcinoma with BAC features was prone to be false-negative on 18F-FDG PET/CT. Materials and Methods. A retrospective study was performed on 51 consecutive patients with localized adenocarcinoma with BAC features. CT and PET were assessed for lesion size, GGO percentage, and SUVmax. Lesions with FDG uptake the same as or more than mediastinal blood-pool activity were considered as PET-positive. Results. Of the 51 cases, 19.6% presented as pure GGO nodules, 31.4% as mixed nodules, and 49.0% as solid nodules. None of the pure GGO nodules was 18F-FDG avid, compared with 37.5% of mixed nodules and 96.0% of solid nodules (χ 2 = 31.55, P = 0.000). In the mixed nodule group, SUVmax was negatively correlated with GGO percentage (r = −0.588; P = 0.021). The positive detection rate of 18F-FDG PET/CT was 50.0%, 55.6%, and 100% in tumors 1.1–2.0 cm, 2.1–3.0 cm, and >3.0 cm in diameter, respectively (χ 2 = 5.815, P = 0.055). General linear model factor analysis showed that the GGO was an important factor contributing to false-negative PET/CT results (F = 23.992, P = 0.000), but lesion size was not (F = 0.602, P = 0.866). Conclusions. The present study indicated that the adenocarcinoma with BAC features presented as nonsolid nodule is prone to be false negative on 18F-FDG PET/CT. PMID:25879020

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mitera, Gunita, E-mail: Gunita.Mitera@Sunnybrook.ca; Probyn, Linda; Ford, Michael

Purpose: To correlate computed tomography (CT) imaging features of spinal metastases with pain relief after radiotherapy (RT). Methods and Materials: Thirty-three patients receiving computed tomography (CT)-simulated RT for spinal metastases in an outpatient palliative RT clinic from January 2007 to October 2008 were retrospectively reviewed. Forty spinal metastases were evaluated. Pain response was rated using the International Bone Metastases Consensus Working Party endpoints. Three musculoskeletal radiologists and two orthopaedic surgeons evaluated CT features, including osseous and soft tissue tumor extent, presence of a pathologic fracture, severity of vertebral height loss, and presence of kyphosis. Results: The mean patient age wasmore » 69 years; 24 were men and 9 were women. The mean worst pain score was 7/10, and the mean total daily oral morphine equivalent was 77.3 mg. Treatment doses included 8 Gy in one fraction (22/33), 20 Gy in five fractions (10/33), and 20 Gy in eight fractions (1/33). The CT imaging appearance of spinal metastases included vertebral body involvement (40/40), pedicle involvement (23/40), and lamina involvement (18/40). Soft tissue component (10/40) and nerve root compression (9/40) were less common. Pathologic fractures existed in 11/40 lesions, with resultant vertebral body height loss in 10/40 and kyphosis in 2/40 lesions. At months 1, 2, and 3 after RT, 18%, 69%, and 70% of patients experienced pain relief. Pain response was observed with various CT imaging features. Conclusions: Pain response after RT did not differ in patients with and without pathologic fracture, kyphosis, or any other CT features related to extent of tumor involvement. All patients with painful spinal metastases may benefit from palliative RT.« less

Optimization of CT image reconstruction algorithms for the lung tissue research consortium (LTRC)

NASA Astrophysics Data System (ADS)

McCollough, Cynthia; Zhang, Jie; Bruesewitz, Michael; Bartholmai, Brian

2006-03-01

To create a repository of clinical data, CT images and tissue samples and to more clearly understand the pathogenetic features of pulmonary fibrosis and emphysema, the National Heart, Lung, and Blood Institute (NHLBI) launched a cooperative effort known as the Lung Tissue Resource Consortium (LTRC). The CT images for the LTRC effort must contain accurate CT numbers in order to characterize tissues, and must have high-spatial resolution to show fine anatomic structures. This study was performed to optimize the CT image reconstruction algorithms to achieve these criteria. Quantitative analyses of phantom and clinical images were conducted. The ACR CT accreditation phantom containing five regions of distinct CT attenuations (CT numbers of approximately -1000 HU, -80 HU, 0 HU, 130 HU and 900 HU), and a high-contrast spatial resolution test pattern, was scanned using CT systems from two manufacturers (General Electric (GE) Healthcare and Siemens Medical Solutions). Phantom images were reconstructed using all relevant reconstruction algorithms. Mean CT numbers and image noise (standard deviation) were measured and compared for the five materials. Clinical high-resolution chest CT images acquired on a GE CT system for a patient with diffuse lung disease were reconstructed using BONE and STANDARD algorithms and evaluated by a thoracic radiologist in terms of image quality and disease extent. The clinical BONE images were processed with a 3 x 3 x 3 median filter to simulate a thicker slice reconstructed in smoother algorithms, which have traditionally been proven to provide an accurate estimation of emphysema extent in the lungs. Using a threshold technique, the volume of emphysema (defined as the percentage of lung voxels having a CT number lower than -950 HU) was computed for the STANDARD, BONE, and BONE filtered. The CT numbers measured in the ACR CT Phantom images were accurate for all reconstruction kernels for both manufacturers. As expected, visual evaluation of the spatial resolution bar patterns demonstrated that the BONE (GE) and B46f (Siemens) showed higher spatial resolution compared to the STANDARD (GE) or B30f (Siemens) reconstruction algorithms typically used for routine body CT imaging. Only the sharper images were deemed clinically acceptable for the evaluation of diffuse lung disease (e.g. emphysema). Quantitative analyses of the extent of emphysema in patient data showed the percent volumes above the -950 HU threshold as 9.4% for the BONE reconstruction, 5.9% for the STANDARD reconstruction, and 4.7% for the BONE filtered images. Contrary to the practice of using standard resolution CT images for the quantitation of diffuse lung disease, these data demonstrate that a single sharp reconstruction (BONE/B46f) should be used for both the qualitative and quantitative evaluation of diffuse lung disease. The sharper reconstruction images, which are required for diagnostic interpretation, provide accurate CT numbers over the range of -1000 to +900 HU and preserve the fidelity of small structures in the reconstructed images. A filtered version of the sharper images can be accurately substituted for images reconstructed with smoother kernels for comparison to previously published results.

Novel CT-based objective imaging biomarkers of long term radiation-induced lung damage.

PubMed

Veiga, Catarina; Landau, David; Devaraj, Anand; Doel, Tom; White, Jared; Ngai, Yenting; Hawkes, David J; McClelland, Jamie R

2018-06-14

and Purpose: Recent improvements in lung cancer survival have spurred an interest in understanding and minimizing long term radiation-induced lung damage (RILD). However, there is still no objective criteria to quantify RILD leading to variable reporting across centres and trials. We propose a set of objective imaging biomarkers to quantify common radiological findings observed 12-months after lung cancer radiotherapy (RT). Baseline and 12-month CT scans of 27 patients from a phase I/II clinical trial of isotoxic chemoradiation were included in this study. To detect and measure the severity of RILD, twelve quantitative imaging biomarkers were developed. These describe basic CT findings including parenchymal change, volume reduction and pleural change. The imaging biomarkers were implemented as semi-automated image analysis pipelines and assessed against visual assessment of the occurrence of each change. The majority of the biomarkers were measurable in each patient. Their continuous nature allows objective scoring of severity for each patient. For each imaging biomarker the cohort was split into two groups according to the presence or absence of the biomarker by visual assessment, testing the hypothesis that the imaging biomarkers were different in these two groups. All features were statistically significant except for rotation of the main bronchus and diaphragmatic curvature. The majority of the biomarkers were not strongly correlated with each other suggesting that each of the biomarkers is measuring a separate element of RILD pathology. We developed objective CT-based imaging biomarkers that quantify the severity of radiological lung damage after RT. These biomarkers are representative of typical radiological findings of RILD. Copyright © 2018. Published by Elsevier Inc.

Automatic segmentation of solitary pulmonary nodules based on local intensity structure analysis and 3D neighborhood features in 3D chest CT images

NASA Astrophysics Data System (ADS)

Chen, Bin; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

2012-03-01

This paper presents a solitary pulmonary nodule (SPN) segmentation method based on local intensity structure analysis and neighborhood feature analysis in chest CT images. Automated segmentation of SPNs is desirable for a chest computer-aided detection/diagnosis (CAS) system since a SPN may indicate early stage of lung cancer. Due to the similar intensities of SPNs and other chest structures such as blood vessels, many false positives (FPs) are generated by nodule detection methods. To reduce such FPs, we introduce two features that analyze the relation between each segmented nodule candidate and it neighborhood region. The proposed method utilizes a blob-like structure enhancement (BSE) filter based on Hessian analysis to augment the blob-like structures as initial nodule candidates. Then a fine segmentation is performed to segment much more accurate region of each nodule candidate. FP reduction is mainly addressed by investigating two neighborhood features based on volume ratio and eigenvector of Hessian that are calculates from the neighborhood region of each nodule candidate. We evaluated the proposed method by using 40 chest CT images, include 20 standard-dose CT images that we randomly chosen from a local database and 20 low-dose CT images that were randomly chosen from a public database: LIDC. The experimental results revealed that the average TP rate of proposed method was 93.6% with 12.3 FPs/case.

Unenhanced Computed Tomography to Visualize Hollow Viscera and/or Mesenteric Injury After Blunt Abdominal Trauma: A Single-Institution Experience.

PubMed

Yang, Xu-Yang; Wei, Ming-Tian; Jin, Cheng-Wu; Wang, Meng; Wang, Zi-Qiang

2016-03-01

To identify and describe the major features of unenhanced computed tomography (CT) images of blunt hollow viscera and/or mesenteric injury (BHVI/MI) and to determine the value of unenhanced CT in the diagnosis of BHVI/MI. This retrospective study included 151 patients who underwent unenhanced CT before laparotomy for blunt abdominal trauma between January 2011 and December 2013. According to surgical observations, patients were classified as having BHVI/MI (n = 73) or not (n = 78). Sensitivity, specificity, P values, and likelihood ratios were calculated by comparing CT findings between the 2 groups. Six significant CT findings (P < 0.05) for BHVI/MI were identified and their sensitivity and specificity values determined, as follows: bowel wall thickening (39.7%, 96.2%), mesentery thickening (46.6%, 88.5%), mesenteric fat infiltration (12.3%, 98.7%), peritoneal fat infiltration (31.5%, 87.1%), parietal peritoneum thickening (30.1%, 85.9%), and intra- or retro-peritoneal air (34.2%, 96.2%). Unenhanced CT scan was useful as an initial assessment tool for BHVI/MI after blunt abdominal trauma. Six key features on CT were correlated with BHVI/MI.

Prevalence of Imaging Biomarkers to Guide the Planning of Acute Stroke Reperfusion Trials.

PubMed

Jiang, Bin; Ball, Robyn L; Michel, Patrik; Jovin, Tudor; Desai, Manisha; Eskandari, Ashraf; Naqvi, Zack; Wintermark, Max

2017-06-01

Imaging biomarkers are increasingly used as selection criteria for stroke clinical trials. The goal of our study was to determine the prevalence of commonly studied imaging biomarkers in different time windows after acute ischemic stroke onset to better facilitate the design of stroke clinical trials using such biomarkers for patient selection. This retrospective study included 612 patients admitted with a clinical suspicion of acute ischemic stroke with symptom onset no more than 24 hours before completing baseline imaging. Patients with subacute/chronic/remote infarcts and hemorrhage were excluded from this study. Imaging biomarkers were extracted from baseline imaging, which included a noncontrast head computed tomography (CT), perfusion CT, and CT angiography. The prevalence of dichotomized versions of each of the imaging biomarkers in several time windows (time since symptom onset) was assessed and statistically modeled to assess time dependence (not lack thereof). We created tables showing the prevalence of the imaging biomarkers pertaining to the core, the penumbra and the arterial occlusion for different time windows. All continuous imaging features vary over time. The dichotomized imaging features that vary significantly over time include: noncontrast head computed tomography Alberta Stroke Program Early CT (ASPECT) score and dense artery sign, perfusion CT infarct volume, and CT angiography collateral score and visible clot. The dichotomized imaging features that did not vary significantly over time include the thresholded perfusion CT penumbra volumes. As part of the feasibility analysis in stroke clinical trials, this analysis and the resulting tables can help investigators determine sample size and the number needed to screen. © 2017 American Heart Association, Inc.

Clinical Importance of Temporal Bone Features for the Efficacy of Contrast-Enhanced Sonothrombolysis: a Retrospective Analysis of the NOR-SASS Trial.

PubMed

Novotny, Vojtech; Nacu, Aliona; Kvistad, Christopher E; Fromm, Annette; Neckelmann, Gesche F; Khanevski, Andrej N; Tobro, Haakon; Waje-Andreassen, Ulrike; Naess, Halvor; Thomassen, Lars; Logallo, Nicola

2017-11-08

Contrast-enhanced sonothrombolysis (CEST) seems to be a safe and promising treatment in acute ischemic stroke. It remains unknown if temporal bone features may influence the efficacy of CEST. We investigated the association between different temporal bone features on admission computed tomography (CT) scan and the outcome in acute ischemic stroke patients included in the randomized Norwegian Sonothrombolysis in Acute Stroke Study (NOR-SASS). Patients diagnosed as stroke mimics and those with infratentorial stroke or with incorrect insonation were excluded. We retrospectively assessed temporal bone heterogeneity (presence of diploë), diploë ratio, thickness, and density on admission CT scans. National institute of Health Stroke Scale (NIHSS) at 24 h and modified Rankin Scale (mRS) at 3 months were correlated with CT findings both in CEST and sham CEST patients. A total of 99 patients were included of which 52 were assigned to CEST and 47 to sham CEST. Approximately 20% patients had a heterogeneous temporal bone in both the CEST and sham CEST group. All temporal bone CT features studied were associated with female sex. In the CEST group, temporal bone heterogeneity (p = 0.006) and higher temporal bone diploë ratio (p = 0.002) were associated with higher NIHSS at 24 h. There was no association between temporal bone features and mRS at 3 months. Approximately 20% of acute ischemic stroke patients have heterogeneous temporal bone and may be resistant to standard 2-MHz transcranial Doppler ultrasound treatment. Sonothrombolysis resistance may easily be predicted by admission CT for better selection.

Septic thrombophlebitis of the portal venous system: clinical and imaging findings in thirty-three patients.

PubMed

Ames, Jennifer T; Federle, Michael P

2011-07-01

Our purpose was to review the clinical and imaging findings in a series of patients with septic thrombophlebitis of the portal venous system in order to define criteria that might allow more confident and timely diagnosis. This is a retrospective case series. The clinical and imaging features were analyzed in 33 subjects with septic thrombophlebitis of the portal venous system. All 33 patients with septic thrombophlebitis of the portal venous system had pre-disposing infectious or inflammatory processes. Contrast-enhanced CT studies of patients with septic thrombophlebitis typically demonstrate an infectious gastrointestinal source (82%), thrombosis (70%), and/or gas (21%) of the portal system or its branches, and intrahepatic abnormalities such as a transient hepatic attenuation difference (THAD) (42%) or abscess (61%). Septic thrombophlebitis of the portal system is often associated with an infectious source in the gastrointestinal tract and sepsis. Contrast-enhanced CT demonstrates an infectious gastrointestinal source, thrombosis or gas within the portal system or its branches, and intrahepatic abnormalities such as abscess in most cases. We report a THAD in several of our patients, an observation that was not made in prior reports of septic thrombophlebitis.

Computed tomography of a medium size Roman bronze statue of Cupid

NASA Astrophysics Data System (ADS)

Bettuzzi, M.; Casali, F.; Morigi, M. P.; Brancaccio, R.; Carson, D.; Chiari, G.; Maish, J.

2015-03-01

Diagnostics based on X-ray computed tomography (CT) are becoming increasingly important, not only in the medical field but in industry and cultural heritage. CT devices typical for medical applications, however, can seldom be used on art objects because both they are not easily transportable and they often present high X-ray absorption. It is therefore necessary to make use of portable instrumentation and/or to develop tomographic systems optimized to the characteristics of the objects under examination. This work describes the computed tomography of a first century A.D. Roman bronze statue of Cupid (96.AB.53) in the collection of the J. Paul Getty Museum, within the collaborative framework between the Getty Conservation Institute and the Department of Physics and Astronomy (DIFA) of the University of Bologna (Italy). The tomography performed at the Getty facilities employed a 450 kV X-ray tube and a detection system developed at DIFA. The study highlighted the casting and construction techniques used by Roman foundry workers and provided information on the status of conservation of the statue. A 3D virtual reconstruction allowed the user to define different cross-sections enabling the study of the internal features.

Acute fascioliasis--clinical and epidemiological features of four patients in Chile.

PubMed

Fica, A; Dabanch, J; Farias, C; Castro, M; Jercic, M I; Weitzel, T

2012-01-01

Because of its infrequent and protean presentation and the lack of clinical data, the management of acute infections with the foodborne trematode Fasciola hepatica is challenging. We report four serologically confirmed cases that illustrate our experience with this parasitic infection in Chile. All patients were adults presenting with upper abdominal pain. Other symptoms included fever, nausea/vomiting, and cutaneous manifestations. In all cases, marked eosinophilia was present. All patients lived in an urban environment, and three reported the consumption of raw watercress. Computed tomography (CT) scans showed hypodense hepatic lesions, whereas ultrasonography findings were unremarkable. One patient suffered portal vein thrombosis, which might be a rare complication of acute fascioliasis. All patients were successfully treated with triclabendazole. Our case series demonstrates that patients with acute fascioliasis typically present with a combination of upper abdominal pain, marked eosinophilia, and hypodense hepatic lesions on CT imaging. Diagnosis should be confirmed by serological investigation. A history of recent consumption of raw watercress is an important finding, but in some patients the source of infection remains obscure. © 2011 The Authors. Clinical Microbiology and Infection © 2011 European Society of Clinical Microbiology and Infectious Diseases.

[Features of Acquired Immunodeficiency Syndrome-related Lymphoma on (18)F-fluorodeoxyglucose Positron Emission Tomography/Computed Tomography].

PubMed

Niu, Na; Zhu, Zhao-hui; Ma, Yan-ru; Xing, Hai-qun; Li, Fang

2015-10-01

To analyze the imaging features of (18)F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography(PET)/computed tomography (CT) in acquired immune deficiency syndrome-related lymphoma (ARL) patients correlated with their clinical signs, symptoms, and treatments. Five ARL patients underwent ¹⁸F-FDG PET/CT at Peking Union Medical College Hospital from October 2008 to January 2013. Two patients received two additional follow-up studies 6 months later. Among these 5 patients, ¹⁸FDG-PET/CT helped in diagnosis of two patient and changed therapeutic strategy in other two patients. In two patients underwent ¹⁸F-FDG PET/CT brain scans, low-metabolism lesion was newly found in cerebral cortex. Of 4 patients receiving highly active antiretroviral therapy, PET/CT also demonstrated diffusely elevated ¹⁸F-FDG uptake in subcutaneous adipose tissue in two patients. ¹⁸F-FDG PET/CT is a highly useful tool in the diagnosis and treatment of ARL patients, in particular in the identification of associated encephalopathy and lipodystrophy.

Periosteal ganglia: CT and MR imaging features.

PubMed

Abdelwahab, I F; Kenan, S; Hermann, G; Klein, M J; Lewis, M M

1993-07-01

The imaging features of four cases of periosteal ganglia were studied. Three lesions were located over the proximal shaft of the tibia, in proximity to the pes anserinus. The fourth lesion involved the distal shaft of the ulna. Three lesions had different degrees of external cortical erosion, scalloping, and thick spicules of periosteal bone on plain radiographs. The bone adjacent to the fourth lesion was not involved. Computed tomography (CT) showed these lesions to be sharply defined soft-tissue masses abutting the periosteum. All of the lesions had the same attenuation as fluid. Magnetic resonance (MR) imaging revealed the ganglia to be sharply defined masses that were isointense compared with neighboring muscles on T1-weighted images. There was markedly increased signal intensity compared with that of fat on T2-weighted images. The signal intensity on both types of images was homogeneous. The MR imaging features were consistent with the fluid nature of the lesions. Under the appropriate clinical circumstances, the MR imaging and CT features of periosteal ganglia are diagnostic.

Computer aided diagnosis based on medical image processing and artificial intelligence methods

NASA Astrophysics Data System (ADS)

Stoitsis, John; Valavanis, Ioannis; Mougiakakou, Stavroula G.; Golemati, Spyretta; Nikita, Alexandra; Nikita, Konstantina S.

2006-12-01

Advances in imaging technology and computer science have greatly enhanced interpretation of medical images, and contributed to early diagnosis. The typical architecture of a Computer Aided Diagnosis (CAD) system includes image pre-processing, definition of region(s) of interest, features extraction and selection, and classification. In this paper, the principles of CAD systems design and development are demonstrated by means of two examples. The first one focuses on the differentiation between symptomatic and asymptomatic carotid atheromatous plaques. For each plaque, a vector of texture and motion features was estimated, which was then reduced to the most robust ones by means of ANalysis of VAriance (ANOVA). Using fuzzy c-means, the features were then clustered into two classes. Clustering performances of 74%, 79%, and 84% were achieved for texture only, motion only, and combinations of texture and motion features, respectively. The second CAD system presented in this paper supports the diagnosis of focal liver lesions and is able to characterize liver tissue from Computed Tomography (CT) images as normal, hepatic cyst, hemangioma, and hepatocellular carcinoma. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of neural network classifiers. The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.

Quantitative radiomics studies for tissue characterization: a review of technology and methodological procedures.

PubMed

Larue, Ruben T H M; Defraene, Gilles; De Ruysscher, Dirk; Lambin, Philippe; van Elmpt, Wouter

2017-02-01

Quantitative analysis of tumour characteristics based on medical imaging is an emerging field of research. In recent years, quantitative imaging features derived from CT, positron emission tomography and MR scans were shown to be of added value in the prediction of outcome parameters in oncology, in what is called the radiomics field. However, results might be difficult to compare owing to a lack of standardized methodologies to conduct quantitative image analyses. In this review, we aim to present an overview of the current challenges, technical routines and protocols that are involved in quantitative imaging studies. The first issue that should be overcome is the dependency of several features on the scan acquisition and image reconstruction parameters. Adopting consistent methods in the subsequent target segmentation step is evenly crucial. To further establish robust quantitative image analyses, standardization or at least calibration of imaging features based on different feature extraction settings is required, especially for texture- and filter-based features. Several open-source and commercial software packages to perform feature extraction are currently available, all with slightly different functionalities, which makes benchmarking quite challenging. The number of imaging features calculated is typically larger than the number of patients studied, which emphasizes the importance of proper feature selection and prediction model-building routines to prevent overfitting. Even though many of these challenges still need to be addressed before quantitative imaging can be brought into daily clinical practice, radiomics is expected to be a critical component for the integration of image-derived information to personalize treatment in the future.

Differential diagnosis of CT focal liver lesions using texture features, feature selection and ensemble driven classifiers.

PubMed

Mougiakakou, Stavroula G; Valavanis, Ioannis K; Nikita, Alexandra; Nikita, Konstantina S

2007-09-01

The aim of the present study is to define an optimally performing computer-aided diagnosis (CAD) architecture for the classification of liver tissue from non-enhanced computed tomography (CT) images into normal liver (C1), hepatic cyst (C2), hemangioma (C3), and hepatocellular carcinoma (C4). To this end, various CAD architectures, based on texture features and ensembles of classifiers (ECs), are comparatively assessed. Number of regions of interests (ROIs) corresponding to C1-C4 have been defined by experienced radiologists in non-enhanced liver CT images. For each ROI, five distinct sets of texture features were extracted using first order statistics, spatial gray level dependence matrix, gray level difference method, Laws' texture energy measures, and fractal dimension measurements. Two different ECs were constructed and compared. The first one consists of five multilayer perceptron neural networks (NNs), each using as input one of the computed texture feature sets or its reduced version after genetic algorithm-based feature selection. The second EC comprised five different primary classifiers, namely one multilayer perceptron NN, one probabilistic NN, and three k-nearest neighbor classifiers, each fed with the combination of the five texture feature sets or their reduced versions. The final decision of each EC was extracted by using appropriate voting schemes, while bootstrap re-sampling was utilized in order to estimate the generalization ability of the CAD architectures based on the available relatively small-sized data set. The best mean classification accuracy (84.96%) is achieved by the second EC using a fused feature set, and the weighted voting scheme. The fused feature set was obtained after appropriate feature selection applied to specific subsets of the original feature set. The comparative assessment of the various CAD architectures shows that combining three types of classifiers with a voting scheme, fed with identical feature sets obtained after appropriate feature selection and fusion, may result in an accurate system able to assist differential diagnosis of focal liver lesions from non-enhanced CT images.

Radiomic analysis in prediction of Human Papilloma Virus status.

PubMed

Yu, Kaixian; Zhang, Youyi; Yu, Yang; Huang, Chao; Liu, Rongjie; Li, Tengfei; Yang, Liuqing; Morris, Jeffrey S; Baladandayuthapani, Veerabhadran; Zhu, Hongtu

2017-12-01

Human Papilloma Virus (HPV) has been associated with oropharyngeal cancer prognosis. Traditionally the HPV status is tested through invasive lab test. Recently, the rapid development of statistical image analysis techniques has enabled precise quantitative analysis of medical images. The quantitative analysis of Computed Tomography (CT) provides a non-invasive way to assess HPV status for oropharynx cancer patients. We designed a statistical radiomics approach analyzing CT images to predict HPV status. Various radiomics features were extracted from CT scans, and analyzed using statistical feature selection and prediction methods. Our approach ranked the highest in the 2016 Medical Image Computing and Computer Assisted Intervention (MICCAI) grand challenge: Oropharynx Cancer (OPC) Radiomics Challenge, Human Papilloma Virus (HPV) Status Prediction. Further analysis on the most relevant radiomic features distinguishing HPV positive and negative subjects suggested that HPV positive patients usually have smaller and simpler tumors.

Concurrent segmentation of the prostate on MRI and CT via linked statistical shape models for radiotherapy planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chowdhury, Najeeb; Toth, Robert; Chappelow, Jonathan

2012-04-15

Purpose: Prostate gland segmentation is a critical step in prostate radiotherapy planning, where dose plans are typically formulated on CT. Pretreatment MRI is now beginning to be acquired at several medical centers. Delineation of the prostate on MRI is acknowledged as being significantly simpler to perform, compared to delineation on CT. In this work, the authors present a novel framework for building a linked statistical shape model (LSSM), a statistical shape model (SSM) that links the shape variation of a structure of interest (SOI) across multiple imaging modalities. This framework is particularly relevant in scenarios where accurate boundary delineations ofmore » the SOI on one of the modalities may not be readily available, or difficult to obtain, for training a SSM. In this work the authors apply the LSSM in the context of multimodal prostate segmentation for radiotherapy planning, where the prostate is concurrently segmented on MRI and CT. Methods: The framework comprises a number of logically connected steps. The first step utilizes multimodal registration of MRI and CT to map 2D boundary delineations of the prostate from MRI onto corresponding CT images, for a set of training studies. Hence, the scheme obviates the need for expert delineations of the gland on CT for explicitly constructing a SSM for prostate segmentation on CT. The delineations of the prostate gland on MRI and CT allows for 3D reconstruction of the prostate shape which facilitates the building of the LSSM. In order to perform concurrent prostate MRI and CT segmentation using the LSSM, the authors employ a region-based level set approach where the authors deform the evolving prostate boundary to simultaneously fit to MRI and CT images in which voxels are classified to be either part of the prostate or outside the prostate. The classification is facilitated by using a combination of MRI-CT probabilistic spatial atlases and a random forest classifier, driven by gradient and Haar features. Results: The authors acquire a total of 20 MRI-CT patient studies and use the leave-one-out strategy to train and evaluate four different LSSMs. First, a fusion-based LSSM (fLSSM) is built using expert ground truth delineations of the prostate on MRI alone, where the ground truth for the gland on CT is obtained via coregistration of the corresponding MRI and CT slices. The authors compare the fLSSM against another LSSM (xLSSM), where expert delineations of the gland on both MRI and CT are employed in the model building; xLSSM representing the idealized LSSM. The authors also compare the fLSSM against an exclusive CT-based SSM (ctSSM), built from expert delineations of the gland on CT alone. In addition, two LSSMs trained using trainee delineations (tLSSM) on CT are compared with the fLSSM. The results indicate that the xLSSM, tLSSMs, and the fLSSM perform equivalently, all of them out-performing the ctSSM. Conclusions: The fLSSM provides an accurate alternative to SSMs that require careful expert delineations of the SOI that may be difficult or laborious to obtain. Additionally, the fLSSM has the added benefit of providing concurrent segmentations of the SOI on multiple imaging modalities.« less

Non-squamous cell neoplasms of the larynx: radiologic-pathologic correlation.

PubMed

Becker, M; Moulin, G; Kurt, A M; Dulgerov, P; Vukanovic, S; Zbären, P; Marchal, F; Rüfenacht, D A; Terrier, F

1998-01-01

A variety of benign and malignant non-squamous cell neoplasms may affect the larynx. Most of these uncommon laryngeal neoplasms are located beneath an intact mucosa, making diagnosis difficult with endoscopy alone, and sampling errors may occur if only traditional superficial biopsies are performed. In some laryngeal neoplasms, radiologic evaluation allows the correct diagnosis. Hemangiomas have very high signal intensity at T2-weighted magnetic resonance (MR) imaging and strong enhancement at both computed tomography (CT) and MR imaging after administration of contrast material. Phleboliths, which are pathognomonic for hemangiomas, are easily identified at CT. Chondrogenic tumors typically manifest with coarse or stippled calcifications at CT. Because of their high water content, chondrogenic tumors have very high signal intensity on T2-weighted MR images, whereas only moderate enhancement is observed after administration of contrast material. Lipomas typically manifest at both CT and MR imaging as homogeneous nonenhancing lesions. They are isoattenuating to subcutaneous fat at CT and isointense relative to subcutaneous fat with all MR pulse sequences. Metastases from renal adenocarcinoma typically demonstrate strong contrast enhancement and flow voids at MR imaging, and metastases from melanotic melanoma usually have high signal intensity on T1-weighted MR images and low signal intensity on T2-weighted images owing to the paramagnetic properties of melanin. Although radiologic findings are nonspecific in most other non-squamous cell neoplasms of the larynx (eg, Kaposi sarcoma, hematopoietic tumors, tumors of the minor salivary glands, metastases from amelanotic melanoma), cross-sectional imaging can play an important role in the diagnostic work-up of these unusual tumors by delineating the extent of submucosal tumor spread and directing the endoscopist to the appropriate site for the deep, transmucosal biopsies needed to establish the diagnosis. In addition, CT and MR imaging are crucial for posttherapeutic monitoring and early detection of local recurrence.

CT findings of persistent pure ground glass opacity: can we predict the invasiveness?

PubMed

Liu, Li-Heng; Liu, Ming; Wei, Ran; Jin, Er-Hu; Liu, Yu-Hui; Xu, Liang; Li, Wen-Wu; Huang, Yong

2015-01-01

To investigate whether CT findings can predict the invasiveness of persistent cancerous pure ground glass opacity (pGGO) by correlating the CT imaging features of persistent pGGO with pathological changes. Ninety five patients with persistent pGGOs were included. Three radiologists evaluated the morphologic features of these pGGOs at high resolution CT (HRCT). Binary logistic regression was used to assess the association between CT findings and histopathological classification (pre-invasive and invasive groups). Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of diameters. A total of 105 pGGOs were identified. Between pre-invasive (atypical adenomatous hyperplasia, AAH, and adenocarcinoma in situ, AIS) and invasive group (minimally invasive adenocarcinoma, MIA and invasive lung adenocarcinomas, ILA), there were significant differences in diameter, spiculation and vessel dilatation (p<0.05). No difference was found in air-bronchogram, bubble- lucency, lobulated-margin, pleural indentation or vascular convergence (p>0.05). The optimal threshold value of the diameters to predict the invasiveness of pGGO was 12.50mm. HRCT features can predict the invasiveness of persistent pGGO. The pGGO with a diameter more than 12.50mm, presences of spiculation and vessel dilatation are important factors to differentiate invasive adenocarcinoma from pre-invasive cancerous lesions.

Extranasopharyngeal angiofibroma: clinical and radiological presentation.

PubMed

Szymańska, Anna; Szymański, Marcin; Morshed, Kamal; Czekajska-Chehab, Elżbieta; Szczerbo-Trojanowska, Małgorzata

2013-02-01

Nasopharyngeal angiofibroma (NA) is a rare, vascular tumor affecting adolescent males. Due to aggressive local growth, skull base location and risk of profound hemorrhage, NA is a challenge for surgeons. Angiofibromas have been sporadically described in extanasopharyngeal locations. We review ten cases of extranasopharyngeal angiofibroma (ENA) and discuss the incidence, clinical presentation and management of this pathology. The group consisted of 4 males and 5 females aged 8-49. There were 7 patients with nasal angiofibroma, 1 patient with laryngeal angiofibroma, 1 patient with oral angiofibroma and another patient with infratemporal fossa tumor. In patients with nasal angiofibroma most common presenting symptoms were nasal obstruction and epistaxis. Patients with laryngeal angiofibroma suffered from mild dysphagia and patients with the infratemporal fossa tumor had painless cheek swelling. In four patients with nasal tumor computed tomography (CT) demonstrated mass with strong to intermediate contrast enhancement. In one patient with nasal tumor carotid angiography demonstrated pathological vessels without intensive tumor blush. Infratemporal fossa tumor showed intensive contrast enhancement on CT and magnetic resonance imaging (MRI) scans, and abundant vascularity on angiography. Laryngeal and oral angiofibroma required no radiological imaging. Three nasal tumors were evaluated before introduction of CT to clinical practice. All patients underwent surgery. No recurrences developed. ENAs differ significantly from NAs regarding clinical and radiological presentations. They lack typical clinical and radiological features as they develop in all age groups and in females, may be less vascularised, arise from various sites and produce a variety of symptoms.

Radiologic Diagnosis of Spondylodiscitis, Role of Magnetic Resonance.

PubMed

Ramadani, Naser; Dedushi, Kreshnike; Kabashi, Serbeze; Mucaj, Sefedin

2017-03-01

Study aim is to report the Magnetic Resonance Imaging (MRI) features of acute and chronic spontaneous spondylodiscitis. 57 year old female, complaining of a fever and longstanding cervical pain worsened during physical therapy. MR images were acquired using superconductive magnet 1.5 T, with the following sequences: sagittal PD and T2 TSE, sagittal T1 SE, axial PD and T2 TSE (lumbar spine), axial T2 GRE (cervical spine). Axial and sagittal T1 SE after administration of (gadolinium DTPA). Examination was reviewed by three radiologists and compared to CT findings. Patient reported cervical pain associated with fever and minimal weight loss. Blood tests were normal except hyperglycemia (DM tip II). X Ray: vertebral destruction localized at C-4 and C-5: NECT: destruction of the C-4/C-5 vertebral bodies (ventral part). MRI: Low signal of the bone marrow on T1l images, which enhanced after Gd-DTPA administration and became intermediate or high on T2 images. The steady high signal intensity of the disk on T2 images and enhancement on T1 images is typical for an acute inflammatory process. Bone Scintigrafi results: Bone changes suspicious for metastasis. Whole body CT results: apart from spine, no other significant changes. MRI is the most sensitive technique for the diagnosis of spondylodiscitis in the acute phase and comparable to CT regarding chronial stage of the disease. The present imagining essay os aimed at showing the main magnetic resonance imaging findings of tuberculous discitis.

718F-FDG PET/CT metabolic tumor parameters and radiomics features in aggressive non-Hodgkin's lymphoma as predictors of treatment outcome and survival.

PubMed

Parvez, Aatif; Tau, Noam; Hussey, Douglas; Maganti, Manjula; Metser, Ur

2018-05-12

To determine whether metabolic tumor parameters and radiomic features extracted from 18 F-FDG PET/CT (PET) can predict response to therapy and outcome in patients with aggressive B-cell lymphoma. This institutional ethics board-approved retrospective study included 82 patients undergoing PET for aggressive B-cell lymphoma staging. Whole-body metabolic tumor volume (MTV) using various thresholds and tumor radiomic features were assessed on representative tumor sites. The extracted features were correlated with treatment response, disease-free survival (DFS) and overall survival (OS). At the end of therapy, 66 patients (80.5%) had shown complete response to therapy. The parameters correlating with response to therapy were bulky disease > 6 cm at baseline (p = 0.026), absence of a residual mass > 1.5 cm at the end of therapy CT (p = 0.028) and whole-body MTV with best performance using an SUV threshold of 3 and 6 (p = 0.015 and 0.009, respectively). None of the tumor texture features were predictive of first-line therapy response, while a few of them including GLNU correlated with disease-free survival (p = 0.013) and kurtosis correlated with overall survival (p = 0.035). Whole-body MTV correlates with response to therapy in patient with aggressive B-cell lymphoma. Tumor texture features could not predict therapy response, although several features correlated with the presence of a residual mass at the end of therapy CT and others correlated with disease-free and overall survival. These parameters should be prospectively validated in a larger cohort to confirm clinical prognostication.

SU-F-R-22: Malignancy Classification for Small Pulmonary Nodules with Radiomics and Logistic Regression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, W; Tu, S

Purpose: We conducted a retrospective study of Radiomics research for classifying malignancy of small pulmonary nodules. A machine learning algorithm of logistic regression and open research platform of Radiomics, IBEX (Imaging Biomarker Explorer), were used to evaluate the classification accuracy. Methods: The training set included 100 CT image series from cancer patients with small pulmonary nodules where the average diameter is 1.10 cm. These patients registered at Chang Gung Memorial Hospital and received a CT-guided operation of lung cancer lobectomy. The specimens were classified by experienced pathologists with a B (benign) or M (malignant). CT images with slice thickness ofmore » 0.625 mm were acquired from a GE BrightSpeed 16 scanner. The study was formally approved by our institutional internal review board. Nodules were delineated and 374 feature parameters were extracted from IBEX. We first used the t-test and p-value criteria to study which feature can differentiate between group B and M. Then we implemented a logistic regression algorithm to perform nodule malignancy classification. 10-fold cross-validation and the receiver operating characteristic curve (ROC) were used to evaluate the classification accuracy. Finally hierarchical clustering analysis, Spearman rank correlation coefficient, and clustering heat map were used to further study correlation characteristics among different features. Results: 238 features were found differentiable between group B and M based on whether their statistical p-values were less than 0.05. A forward search algorithm was used to select an optimal combination of features for the best classification and 9 features were identified. Our study found the best accuracy of classifying malignancy was 0.79±0.01 with the 10-fold cross-validation. The area under the ROC curve was 0.81±0.02. Conclusion: Benign nodules may be treated as a malignant tumor in low-dose CT and patients may undergo unnecessary surgeries or treatments. Our study may help radiologists to differentiate nodule malignancy for low-dose CT.« less

Quantitative analysis of adipose tissue on chest CT to predict primary graft dysfunction in lung transplant recipients: a novel optimal biomarker approach

NASA Astrophysics Data System (ADS)

Tong, Yubing; Udupa, Jayaram K.; Wang, Chuang; Wu, Caiyun; Pednekar, Gargi; Restivo, Michaela D.; Lederer, David J.; Christie, Jason D.; Torigian, Drew A.

2018-02-01

In this study, patients who underwent lung transplantation are categorized into two groups of successful (positive) or failed (negative) transplantations according to primary graft dysfunction (PGD), i.e., acute lung injury within 72 hours of lung transplantation. Obesity or being underweight is associated with an increased risk of PGD. Adipose quantification and characterization via computed tomography (CT) imaging is an evolving topic of interest. However, very little research of PGD prediction using adipose quantity or characteristics derived from medical images has been performed. The aim of this study is to explore image-based features of thoracic adipose tissue on pre-operative chest CT to distinguish between the above two groups of patients. 140 unenhanced chest CT images from three lung transplant centers (Columbia, Penn, and Duke) are included in this study. 124 patients are in the successful group and 16 in failure group. Chest CT slices at the T7 and T8 vertebral levels are captured to represent the thoracic fat burden by using a standardized anatomic space (SAS) approach. Fat (subcutaneous adipose tissue (SAT)/ visceral adipose tissue (VAT)) intensity and texture properties (1142 in total) for each patient are collected, and then an optimal feature set is selected to maximize feature independence and separation between the two groups. Leave-one-out and leave-ten-out crossvalidation strategies are adopted to test the prediction ability based on those selected features all of which came from VAT texture properties. Accuracy of prediction (ACC), sensitivity (SEN), specificity (SPE), and area under the curve (AUC) of 0.87/0.97, 0.87/0.97, 0.88/1.00, and 0.88/0.99, respectively are achieved by the method. The optimal feature set includes only 5 features (also all from VAT), which might suggest that thoracic VAT plays a more important role than SAT in predicting PGD in lung transplant recipients.

Radiological Findings in a case of Advance staged Mesothelioma

PubMed Central

Aziz, Fahad

2009-01-01

Chest X Ray is the initial screening test for the mesothelioma like all other the chest diseases. But computed tomography (CT) is the imaging technique of choice for charactering pleural masses. CT also gives important information regarding invasion of the chest wall and surrounding structures. Certain CT features help differentiate benign from malignant processes. This short article highlights the salient CT appearance of mesothelioma; the most common pleural tumor. PMID:22263002

Scale-adaptive compressive tracking with feature integration

NASA Astrophysics Data System (ADS)

Liu, Wei; Li, Jicheng; Chen, Xiao; Li, Shuxin

2016-05-01

Numerous tracking-by-detection methods have been proposed for robust visual tracking, among which compressive tracking (CT) has obtained some promising results. A scale-adaptive CT method based on multifeature integration is presented to improve the robustness and accuracy of CT. We introduce a keypoint-based model to achieve the accurate scale estimation, which can additionally give a prior location of the target. Furthermore, by the high efficiency of data-independent random projection matrix, multiple features are integrated into an effective appearance model to construct the naïve Bayes classifier. At last, an adaptive update scheme is proposed to update the classifier conservatively. Experiments on various challenging sequences demonstrate substantial improvements by our proposed tracker over CT and other state-of-the-art trackers in terms of dealing with scale variation, abrupt motion, deformation, and illumination changes.

Further characterization of spectral features attributable to titanium on the moon

NASA Technical Reports Server (NTRS)

Burns, R. G.; Parkin, K. M.; Loeffler, B. M.; Leung, I. S.; Abu-Eid, R. M.

1976-01-01

The following transitions are observed in the electronic absorption spectra of lunar titanaugites: Fe(2+) spin-allowed and spin-forbidden crystal field; Ti(3+) spin allowed and Jahn-Teller split crystal field; Ti(3+)-Ti(4+) CT; Fe(2+)-Ti(4+) CT; and O(2-)-Fe(2+), Ti(3+), Ti(4+) CT. Of these, the transitions involving Ti(3+) are unique to lunar or nonferric-bearing titanaugites. All titanaugites have the Fe(2+) crystal field and Fe(2+)-Ti(4+) CT transitions in common. These features in the diffuse reflectance spectra of lunar materials give rise to the '1.0 band' and to the observed absorption around 0.5-0.6 micron, respectively. Since regolith contains a variety of phases with coexisting Fe(2+), Ti(3+), and Ti(4+) ions, several metal-metal charge transfer processes are possible.

Modeling Pathologic Response of Esophageal Cancer to Chemoradiation Therapy Using Spatial-Temporal {sup 18}F-FDG PET Features, Clinical Parameters, and Demographics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Hao; Tan, Shan; Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan

2014-01-01

Purpose: To construct predictive models using comprehensive tumor features for the evaluation of tumor response to neoadjuvant chemoradiation therapy (CRT) in patients with esophageal cancer. Methods and Materials: This study included 20 patients who underwent trimodality therapy (CRT + surgery) and underwent {sup 18}F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) both before and after CRT. Four groups of tumor features were examined: (1) conventional PET/CT response measures (eg, standardized uptake value [SUV]{sub max}, tumor diameter); (2) clinical parameters (eg, TNM stage, histology) and demographics; (3) spatial-temporal PET features, which characterize tumor SUV intensity distribution, spatial patterns, geometry, and associated changesmore » resulting from CRT; and (4) all features combined. An optimal feature set was identified with recursive feature selection and cross-validations. Support vector machine (SVM) and logistic regression (LR) models were constructed for prediction of pathologic tumor response to CRT, cross-validations being used to avoid model overfitting. Prediction accuracy was assessed by area under the receiver operating characteristic curve (AUC), and precision was evaluated by confidence intervals (CIs) of AUC. Results: When applied to the 4 groups of tumor features, the LR model achieved AUCs (95% CI) of 0.57 (0.10), 0.73 (0.07), 0.90 (0.06), and 0.90 (0.06). The SVM model achieved AUCs (95% CI) of 0.56 (0.07), 0.60 (0.06), 0.94 (0.02), and 1.00 (no misclassifications). With the use of spatial-temporal PET features combined with conventional PET/CT measures and clinical parameters, the SVM model achieved very high accuracy (AUC 1.00) and precision (no misclassifications)—results that were significantly better than when conventional PET/CT measures or clinical parameters and demographics alone were used. For groups with many tumor features (groups 3 and 4), the SVM model achieved significantly higher accuracy than did the LR model. Conclusions: The SVM model that used all features including spatial-temporal PET features accurately and precisely predicted pathologic tumor response to CRT in esophageal cancer.« less

Contourlet textual features: improving the diagnosis of solitary pulmonary nodules in two dimensional CT images.

PubMed

Wang, Jingjing; Sun, Tao; Gao, Ni; Menon, Desmond Dev; Luo, Yanxia; Gao, Qi; Li, Xia; Wang, Wei; Zhu, Huiping; Lv, Pingxin; Liang, Zhigang; Tao, Lixin; Liu, Xiangtong; Guo, Xiuhua

2014-01-01

To determine the value of contourlet textural features obtained from solitary pulmonary nodules in two dimensional CT images used in diagnoses of lung cancer. A total of 6,299 CT images were acquired from 336 patients, with 1,454 benign pulmonary nodule images from 84 patients (50 male, 34 female) and 4,845 malignant from 252 patients (150 male, 102 female). Further to this, nineteen patient information categories, which included seven demographic parameters and twelve morphological features, were also collected. A contourlet was used to extract fourteen types of textural features. These were then used to establish three support vector machine models. One comprised a database constructed of nineteen collected patient information categories, another included contourlet textural features and the third one contained both sets of information. Ten-fold cross-validation was used to evaluate the diagnosis results for the three databases, with sensitivity, specificity, accuracy, the area under the curve (AUC), precision, Youden index, and F-measure were used as the assessment criteria. In addition, the synthetic minority over-sampling technique (SMOTE) was used to preprocess the unbalanced data. Using a database containing textural features and patient information, sensitivity, specificity, accuracy, AUC, precision, Youden index, and F-measure were: 0.95, 0.71, 0.89, 0.89, 0.92, 0.66, and 0.93 respectively. These results were higher than results derived using the database without textural features (0.82, 0.47, 0.74, 0.67, 0.84, 0.29, and 0.83 respectively) as well as the database comprising only textural features (0.81, 0.64, 0.67, 0.72, 0.88, 0.44, and 0.85 respectively). Using the SMOTE as a pre-processing procedure, new balanced database generated, including observations of 5,816 benign ROIs and 5,815 malignant ROIs, and accuracy was 0.93. Our results indicate that the combined contourlet textural features of solitary pulmonary nodules in CT images with patient profile information could potentially improve the diagnosis of lung cancer.

WebCT: A Major Shift of Emphasis

ERIC Educational Resources Information Center

Morningstar, Barbara; Schubert, Jeremy; Thibeault, Kristine

2004-01-01

The evaluation reports in this series usually feature several products at once. The current review, however, comes at a time when one of the most widely used (and expensive) online learning management systems is undergoing a major change in its marketing strategy and corporate focus. "WebCT" is currently evolving to a new version ("WebCT Vista"),…

Quantifying the impact of respiratory-gated 4D CT acquisition on thoracic image quality: a digital phantom study.

PubMed

Bernatowicz, K; Keall, P; Mishra, P; Knopf, A; Lomax, A; Kipritidis, J

2015-01-01

Prospective respiratory-gated 4D CT has been shown to reduce tumor image artifacts by up to 50% compared to conventional 4D CT. However, to date no studies have quantified the impact of gated 4D CT on normal lung tissue imaging, which is important in performing dose calculations based on accurate estimates of lung volume and structure. To determine the impact of gated 4D CT on thoracic image quality, the authors developed a novel simulation framework incorporating a realistic deformable digital phantom driven by patient tumor motion patterns. Based on this framework, the authors test the hypothesis that respiratory-gated 4D CT can significantly reduce lung imaging artifacts. Our simulation framework synchronizes the 4D extended cardiac torso (XCAT) phantom with tumor motion data in a quasi real-time fashion, allowing simulation of three 4D CT acquisition modes featuring different levels of respiratory feedback: (i) "conventional" 4D CT that uses a constant imaging and couch-shift frequency, (ii) "beam paused" 4D CT that interrupts imaging to avoid oversampling at a given couch position and respiratory phase, and (iii) "respiratory-gated" 4D CT that triggers acquisition only when the respiratory motion fulfills phase-specific displacement gating windows based on prescan breathing data. Our framework generates a set of ground truth comparators, representing the average XCAT anatomy during beam-on for each of ten respiratory phase bins. Based on this framework, the authors simulated conventional, beam-paused, and respiratory-gated 4D CT images using tumor motion patterns from seven lung cancer patients across 13 treatment fractions, with a simulated 5.5 cm(3) spherical lesion. Normal lung tissue image quality was quantified by comparing simulated and ground truth images in terms of overall mean square error (MSE) intensity difference, threshold-based lung volume error, and fractional false positive/false negative rates. Averaged across all simulations and phase bins, respiratory-gating reduced overall thoracic MSE by 46% compared to conventional 4D CT (p ∼ 10(-19)). Gating leads to small but significant (p < 0.02) reductions in lung volume errors (1.8%-1.4%), false positives (4.0%-2.6%), and false negatives (2.7%-1.3%). These percentage reductions correspond to gating reducing image artifacts by 24-90 cm(3) of lung tissue. Similar to earlier studies, gating reduced patient image dose by up to 22%, but with scan time increased by up to 135%. Beam paused 4D CT did not significantly impact normal lung tissue image quality, but did yield similar dose reductions as for respiratory-gating, without the added cost in scanning time. For a typical 6 L lung, respiratory-gated 4D CT can reduce image artifacts affecting up to 90 cm(3) of normal lung tissue compared to conventional acquisition. This image improvement could have important implications for dose calculations based on 4D CT. Where image quality is less critical, beam paused 4D CT is a simple strategy to reduce imaging dose without sacrificing acquisition time.

Dissimilarity representations in lung parenchyma classification

NASA Astrophysics Data System (ADS)

Sørensen, Lauge; de Bruijne, Marleen

2009-02-01

A good problem representation is important for a pattern recognition system to be successful. The traditional approach to statistical pattern recognition is feature representation. More specifically, objects are represented by a number of features in a feature vector space, and classifiers are built in this representation. This is also the general trend in lung parenchyma classification in computed tomography (CT) images, where the features often are measures on feature histograms. Instead, we propose to build normal density based classifiers in dissimilarity representations for lung parenchyma classification. This allows for the classifiers to work on dissimilarities between objects, which might be a more natural way of representing lung parenchyma. In this context, dissimilarity is defined between CT regions of interest (ROI)s. ROIs are represented by their CT attenuation histogram and ROI dissimilarity is defined as a histogram dissimilarity measure between the attenuation histograms. In this setting, the full histograms are utilized according to the chosen histogram dissimilarity measure. We apply this idea to classification of different emphysema patterns as well as normal, healthy tissue. Two dissimilarity representation approaches as well as different histogram dissimilarity measures are considered. The approaches are evaluated on a set of 168 CT ROIs using normal density based classifiers all showing good performance. Compared to using histogram dissimilarity directly as distance in a emph{k} nearest neighbor classifier, which achieves a classification accuracy of 92.9%, the best dissimilarity representation based classifier is significantly better with a classification accuracy of 97.0% (text{emph{p" border="0" class="imgtopleft"> = 0.046).

Clinical Features and Outcomes of Gastric Ischemia.

PubMed

Sharma, Ayush; Mukewar, Saurabh; Chari, Suresh T; Wong Kee Song, Louis M

2017-12-01

Gastric ischemia is a rare condition associated with poor prognosis. Our study aim was to highlight the clinical features and outcomes of patients with gastric ischemia. A retrospective review of patients diagnosed with isolated gastric ischemia at our institution from January 1, 2000, to May 5, 2016, was performed. Demographic, clinical, endoscopic, radiologic, and outcome variables were abstracted for analysis. Seventeen patients (65% men) with mean age of 69.3 ± 11.3 years and body mass index of 28.8 ± 11.1 were identified. The etiologies for gastric ischemia included local vascular causes (n = 8), systemic hypoperfusion (n = 4), and mechanical obstruction (n = 5). The most common presenting symptoms were abdominal pain (65%), gastrointestinal bleeding (47%), and altered mental status (23%). The typical endoscopic appearance was mucosal congestion and erythema with or without ulceration. Gastric pneumatosis and portal venous air were more commonly seen on CT imaging. Radiologic and/or surgical intervention was needed in 9 patients, while the remaining 8 patients were managed conservatively with acid suppression, antibiotics, and nasogastric tube decompression. The median duration of hospital stay was 15 days (range 1-36 days). There were no cases of rebleeding and the mortality rate as a direct result of gastric ischemia was 24% within 6 months of diagnosis. Although uncommon, gastric ischemia is associated with significant mortality. Endoscopy and CT imaging play an important role in its diagnosis. The management of gastric ischemia is dictated by its severity and associated comorbidities.

Dictionary learning-based CT detection of pulmonary nodules

NASA Astrophysics Data System (ADS)

Wu, Panpan; Xia, Kewen; Zhang, Yanbo; Qian, Xiaohua; Wang, Ge; Yu, Hengyong

2016-10-01

Segmentation of lung features is one of the most important steps for computer-aided detection (CAD) of pulmonary nodules with computed tomography (CT). However, irregular shapes, complicated anatomical background and poor pulmonary nodule contrast make CAD a very challenging problem. Here, we propose a novel scheme for feature extraction and classification of pulmonary nodules through dictionary learning from training CT images, which does not require accurately segmented pulmonary nodules. Specifically, two classification-oriented dictionaries and one background dictionary are learnt to solve a two-category problem. In terms of the classification-oriented dictionaries, we calculate sparse coefficient matrices to extract intrinsic features for pulmonary nodule classification. The support vector machine (SVM) classifier is then designed to optimize the performance. Our proposed methodology is evaluated with the lung image database consortium and image database resource initiative (LIDC-IDRI) database, and the results demonstrate that the proposed strategy is promising.

Early Assessment of Treatment Responses During Radiation Therapy for Lung Cancer Using Quantitative Analysis of Daily Computed Tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paul, Jijo; Yang, Cungeng; Wu, Hui

Purpose: To investigate early tumor and normal tissue responses during the course of radiation therapy (RT) for lung cancer using quantitative analysis of daily computed tomography (CT) scans. Methods and Materials: Daily diagnostic-quality CT scans acquired using CT-on-rails during CT-guided RT for 20 lung cancer patients were quantitatively analyzed. On each daily CT set, the contours of the gross tumor volume (GTV) and lungs were generated and the radiation dose delivered was reconstructed. The changes in CT image intensity (Hounsfield unit [HU]) features in the GTV and the multiple normal lung tissue shells around the GTV were extracted from themore » daily CT scans. The associations between the changes in the mean HUs, GTV, accumulated dose during RT delivery, and patient survival rate were analyzed. Results: During the RT course, radiation can induce substantial changes in the HU histogram features on the daily CT scans, with reductions in the GTV mean HUs (dH) observed in the range of 11 to 48 HU (median 30). The dH is statistically related to the accumulated GTV dose (R{sup 2} > 0.99) and correlates weakly with the change in GTV (R{sup 2} = 0.3481). Statistically significant increases in patient survival rates (P=.038) were observed for patients with a higher dH in the GTV. In the normal lung, the 4 regions proximal to the GTV showed statistically significant (P<.001) HU reductions from the first to last fraction. Conclusion: Quantitative analysis of the daily CT scans indicated that the mean HUs in lung tumor and surrounding normal tissue were reduced during RT delivery. This reduction was observed in the early phase of the treatment, is patient specific, and correlated with the delivered dose. A larger HU reduction in the GTV correlated significantly with greater patient survival. The changes in daily CT features, such as the mean HU, can be used for early assessment of the radiation response during RT delivery for lung cancer.« less

Early Assessment of Treatment Responses During Radiation Therapy for Lung Cancer Using Quantitative Analysis of Daily Computed Tomography.

PubMed

Paul, Jijo; Yang, Cungeng; Wu, Hui; Tai, An; Dalah, Entesar; Zheng, Cheng; Johnstone, Candice; Kong, Feng-Ming; Gore, Elizabeth; Li, X Allen

2017-06-01

To investigate early tumor and normal tissue responses during the course of radiation therapy (RT) for lung cancer using quantitative analysis of daily computed tomography (CT) scans. Daily diagnostic-quality CT scans acquired using CT-on-rails during CT-guided RT for 20 lung cancer patients were quantitatively analyzed. On each daily CT set, the contours of the gross tumor volume (GTV) and lungs were generated and the radiation dose delivered was reconstructed. The changes in CT image intensity (Hounsfield unit [HU]) features in the GTV and the multiple normal lung tissue shells around the GTV were extracted from the daily CT scans. The associations between the changes in the mean HUs, GTV, accumulated dose during RT delivery, and patient survival rate were analyzed. During the RT course, radiation can induce substantial changes in the HU histogram features on the daily CT scans, with reductions in the GTV mean HUs (dH) observed in the range of 11 to 48 HU (median 30). The dH is statistically related to the accumulated GTV dose (R 2  > 0.99) and correlates weakly with the change in GTV (R 2  = 0.3481). Statistically significant increases in patient survival rates (P=.038) were observed for patients with a higher dH in the GTV. In the normal lung, the 4 regions proximal to the GTV showed statistically significant (P<.001) HU reductions from the first to last fraction. Quantitative analysis of the daily CT scans indicated that the mean HUs in lung tumor and surrounding normal tissue were reduced during RT delivery. This reduction was observed in the early phase of the treatment, is patient specific, and correlated with the delivered dose. A larger HU reduction in the GTV correlated significantly with greater patient survival. The changes in daily CT features, such as the mean HU, can be used for early assessment of the radiation response during RT delivery for lung cancer. Copyright © 2017 Elsevier Inc. All rights reserved.

Differential diagnosis of primary nasopharyngeal lymphoma and nasopharyngeal carcinoma focusing on CT, MRI, and PET/CT.

PubMed

Cho, Kyu-Sup; Kang, Dae-Woon; Kim, Hak-Jin; Lee, Jong-Kil; Roh, Hwan-Jung

2012-04-01

No study has done a comparative analysis of radiologic imaging findings between primary nasopharyngeal lymphoma (PNL) and nasopharyngeal carcinoma (NPC). The purpose of this study was to analyze computed tomography (CT) and magnetic resonance (MR) images and to evaluate the maximum standardized uptake value (SUV max) of positron emission tomography (PET)/CT between PNL and NPC, knowing the imaging features that distinguish PNL from NPC. Cross-sectional study. University tertiary care facility. The authors analyzed the features on CT, MR imaging, and PET/CT of 16 patients diagnosed with PNL and 32 patients diagnosed with NPC histopathologically. Patients with PNL had a larger tumor volume and showed symmetry of tumor shape than did patients with NPC. Patients with PNL also had higher tumor homogeneity than NPC patients on CT, T2-weighted, and postcontrast MR images. All PNL patients showed a high degree of enhancement without invasion to the adjacent deep structure. The involvement of the Waldeyer ring was significantly higher in PNL patients. Cervical and retropharyngeal lymphadenopathy and PET/CT SUV max showed no significant difference between PNL and NPC. If the images present a bulky, symmetric nasopharyngeal mass with marked homogeneity, a high degree of enhancement, and a higher Waldeyer ring involvement combined with no invasion into the deep structure, PNL should be considered over NPC.

Functional imaging in differentiating bronchial masses: an initial experience with a combination of (18)F-FDG PET-CT scan and (68)Ga DOTA-TOC PET-CT scan.

PubMed

Kumar, Arvind; Jindal, Tarun; Dutta, Roman; Kumar, Rakesh

2009-10-01

To evaluate the role of combination of (18)F-FDG PET-CT scan and (68)Ga DOTA-TOC PET-CT scan in differentiating bronchial tumors observed in contrast enhanced computed tomography scan of chest. Prospective observational study. Place of study: All India Institute of Medical Sciences, New Delhi, India. 7 patients with bronchial mass detected in computed tomography scan of the chest were included in this study. All patients underwent (18)F-FDG PET-CT scan, (68)Ga DOTA-TOC PET-CT scan and fiberoptic bronchoscope guided biopsy followed by definitive surgical excision. The results of functional imaging studies were analyzed and the results are correlated with the final histopathology of the tumor. Histopathological examination of 7 bronchial masses revealed carcinoid tumors (2 typical, 1 atypical), inflammatory myofibroblastic tumor (1), mucoepidermoid carcinoma (1), hamartoma (1), and synovial cell sarcoma (1). The typical carcinoids had mild (18)F-FDG uptake and high (68)Ga DOTA-TOC uptake. Atypical carcinoid had moderate uptake of (18)F-FDG and high (68)Ga DOTA-TOC uptake. Inflammatory myofibroblastic tumor showed high uptake of (18)F-FDG and no uptake of (68)Ga DOTA-TOC. Mucoepidermoid carcinoma showed mild (18)F-FDG uptake and no (68)Ga DOTA-TOC uptake. Hamartoma showed no uptake on either scans. Synovial cell sarcoma showed moderate (18)F-FDG uptake and mild focal (68)Ga DOTA-TOC uptake. This initial experience with the combined use of (18)F-FDG and (68)Ga DOTA-TOC PET-CT scan reveals different uptake patterns in various bronchial tumors. Bronchoscopic biopsy will continue to be the gold standard; however, the interesting observations made in this study merits further evaluation of the utility of the combination of (18)F-FDG PET-CT scan and (68)Ga DOTA-TOC PET-CT scan in larger number of patients with bronchial masses.

TU-F-CAMPUS-J-05: Effect of Uncorrelated Noise Texture On Computed Tomography Quantitative Image Features

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oliver, J; Budzevich, M; Moros, E

Purpose: To investigate the relationship between quantitative image features (i.e. radiomics) and statistical fluctuations (i.e. electronic noise) in clinical Computed Tomography (CT) using the standardized American College of Radiology (ACR) CT accreditation phantom and patient images. Methods: Three levels of uncorrelated Gaussian noise were added to CT images of phantom and patients (20) acquired in static mode and respiratory tracking mode. We calculated the noise-power spectrum (NPS) of the original CT images of the phantom, and of the phantom images with added Gaussian noise with means of 50, 80, and 120 HU. Concurrently, on patient images (original and noise-added images),more » image features were calculated: 14 shape, 19 intensity (1st order statistics from intensity volume histograms), 18 GLCM features (2nd order statistics from grey level co-occurrence matrices) and 11 RLM features (2nd order statistics from run-length matrices). These features provide the underlying structural information of the images. GLCM (size 128x128) was calculated with a step size of 1 voxel in 13 directions and averaged. RLM feature calculation was performed in 13 directions with grey levels binning into 128 levels. Results: Adding the electronic noise to the images modified the quality of the NPS, shifting the noise from mostly correlated to mostly uncorrelated voxels. The dramatic increase in noise texture did not affect image structure/contours significantly for patient images. However, it did affect the image features and textures significantly as demonstrated by GLCM differences. Conclusion: Image features are sensitive to acquisition factors (simulated by adding uncorrelated Gaussian noise). We speculate that image features will be more difficult to detect in the presence of electronic noise (an uncorrelated noise contributor) or, for that matter, any other highly correlated image noise. This work focuses on the effect of electronic, uncorrelated, noise and future work shall examine the influence of changes in quantum noise on the features. J. Oliver was supported by NSF FGLSAMP BD award HRD #1139850 and the McKnight Doctoral Fellowship.« less

A digital model individual template and CT-guided 125I seed implants for malignant tumors of the head and neck.

PubMed

Huang, Ming-Wei; Liu, Shu-Ming; Zheng, Lei; Shi, Yan; Zhang, Jie; Li, Yan-Sheng; Yu, Guang-Yan; Zhang, Jian-Guo

2012-11-01

To enhance the accuracy of radioactive seed implants in the head and neck, a digital model individual template, containing information simultaneously on needle pathway and facial features, was designed to guide implantation with CT imaging. Thirty-one patients with recurrent and local advanced malignant tumors of head and neck after prior surgery and radiotherapy were involved in this study. Before (125)I implants, patients received CT scans based on 0.75mm thickness. And the brachytherapy treatment planning system (BTPS) software was used to make the implantation plan based on the CT images. Mimics software and Geomagic software were used to read the data containing CT images and implantation plan, and to design the individual template. Then the individual template containing the information of needle pathway and face features simultaneously was made through rapid prototyping (RP) technique. All patients received (125)I seeds interstitial implantation under the guide of the individual template and CT. The individual templates were positioned easily and accurately, and were stable. After implants, treatment quality evaluation was made by CT and TPS. The seeds and dosages distribution (D(90),V(100),V(150)) were well meet the treatment requirement. Clinical practice confirms that this approach can facilitate easier and more accurate implantation.

Relationship between solitary pulmonary nodule lung cancer and CT image features based on gradual clustering

NASA Astrophysics Data System (ADS)

Zhang, Weipeng

2017-06-01

The relationship between the medical characteristics of lung cancers and computer tomography (CT) images are explored so as to improve the early diagnosis rate of lung cancers. This research collected CT images of patients with solitary pulmonary nodule lung cancer, and used gradual clustering methodology to classify them. Preliminary classifications were made, followed by continuous modification and iteration to determine the optimal condensation point, until iteration stability was achieved. Reasonable classification results were obtained. the clustering results fell into 3 categories. The first type of patients was mostly female, with ages between 50 and 65 years. CT images of solitary pulmonary nodule lung cancer for this group contain complete lobulation and burr, with pleural indentation; The second type of patients was mostly male with ages between 50 and 80 years. CT images of solitary pulmonary nodule lung cancer for this group contain complete lobulation and burr, but with no pleural indentation; The third type of patients was also mostly male with ages between 50 and 80 years. CT images for this group showed no abnormalities. the application of gradual clustering methodology can scientifically classify CT image features of patients with lung cancer in the initial lesion stage. These findings provide the basis for early detection and treatment of malignant lesions in patients with lung cancer.

Dose assessment of digital tomosynthesis in pediatric imaging

NASA Astrophysics Data System (ADS)

Gislason, Amber; Elbakri, Idris A.; Reed, Martin

2009-02-01

We investigated the potential for digital tomosynthesis (DT) to reduce pediatric x-ray dose while maintaining image quality. We utilized the DT feature (VolumeRadTM) on the GE DefiniumTM 8000 flat panel system installed in the Winnipeg Children's Hospital. Facial bones, cervical spine, thoracic spine, and knee of children aged 5, 10, and 15 years were represented by acrylic phantoms for DT dose measurements. Effective dose was estimated for DT and for corresponding digital radiography (DR) and computed tomography (CT) patient image sets. Anthropomorphic phantoms of selected body parts were imaged by DR, DT, and CT. Pediatric radiologists rated visualization of selected anatomic features in these images. Dose and image quality comparisons between DR, DT, and CT determined the usefulness of tomosynthesis for pediatric imaging. CT effective dose was highest; total DR effective dose was not always lowest - depending how many projections were in the DR image set. For the cervical spine, DT dose was close to and occasionally lower than DR dose. Expert radiologists rated visibility of the central facial complex in a skull phantom as better than DR and comparable to CT. Digital tomosynthesis has a significantly lower dose than CT. This study has demonstrated DT shows promise to replace CT for some facial bones and spinal diagnoses. Other clinical applications will be evaluated in the future.

Lab-based x-ray nanoCT imaging

NASA Astrophysics Data System (ADS)

Müller, Mark; Allner, Sebastian; Ferstl, Simone; Dierolf, Martin; Tuohimaa, Tomi; Pfeiffer, Franz

2017-03-01

Due to the recent development of transmission X-ray tubes with very small focal spot sizes, laboratory-based CT imaging with sub-micron resolutions is nowadays possible. We recently developed a novel X-ray nanoCT setup featuring a prototype nanofocus X-ray source and a single-photon counting detector. The system is based on mere geometrical magnification and can reach resolutions of 200 nm. To demonstrate the potential of the nanoCT system for biomedical applications we show high resolution nanoCT data of a small piece of human tooth comprising coronal dentin. The reconstructed CT data clearly visualize the dentin tubules within the tooth piece.

Robustness of Radiomic Features in [11C]Choline and [18F]FDG PET/CT Imaging of Nasopharyngeal Carcinoma: Impact of Segmentation and Discretization.

PubMed

Lu, Lijun; Lv, Wenbing; Jiang, Jun; Ma, Jianhua; Feng, Qianjin; Rahmim, Arman; Chen, Wufan

2016-12-01

Radiomic features are increasingly utilized to evaluate tumor heterogeneity in PET imaging and to enable enhanced prediction of therapy response and outcome. An important ingredient to success in translation of radiomic features to clinical reality is to quantify and ascertain their robustness. In the present work, we studied the impact of segmentation and discretization on 88 radiomic features in 2-deoxy-2-[ 18 F]fluoro-D-glucose ([ 18 F]FDG) and [ 11 C]methyl-choline ([ 11 C]choline) positron emission tomography/X-ray computed tomography (PET/CT) imaging of nasopharyngeal carcinoma. Forty patients underwent [ 18 F]FDG PET/CT scans. Of these, nine patients were imaged on a different day utilizing [ 11 C]choline PET/CT. Tumors were delineated using reference manual segmentation by the consensus of three expert physicians, using 41, 50, and 70 % maximum standardized uptake value (SUV max ) threshold with background correction, Nestle's method, and watershed and region growing methods, and then discretized with fixed bin size (0.05, 0.1, 0.2, 0.5, and 1) in units of SUV. A total of 88 features, including 21 first-order intensity features, 10 shape features, and 57 second- and higher-order textural features, were extracted from the tumors. The robustness of the features was evaluated via the intraclass correlation coefficient (ICC) for seven kinds of segmentation methods (involving all 88 features) and five kinds of discretization bin size (involving the 57 second- and higher-order features). Forty-four (50 %) and 55 (63 %) features depicted ICC ≥0.8 with respect to segmentation as obtained from [ 18 F]FDG and [ 11 C]choline, respectively. Thirteen (23 %) and 12 (21 %) features showed ICC ≥0.8 with respect to discretization as obtained from [ 18 F]FDG and [ 11 C]choline, respectively. Six features were obtained from both [ 18 F]FDG and [ 11 C]choline having ICC ≥0.8 for both segmentation and discretization, five of which were gray-level co-occurrence matrix (GLCM) features (SumEntropy, Entropy, DifEntropy, Homogeneity1, and Homogeneity2) and one of which was an neighborhood gray-tone different matrix (NGTDM) feature (Coarseness). Discretization generated larger effects on features than segmentation in both tracers. Features extracted from [ 11 C]choline were more robust than [ 18 F]FDG for segmentation. Discretization had very similar effects on features extracted from both tracers.

Cold tuberculous abscess identified by FDG PET.

PubMed

Yago, Yuzo; Yukihiro, Masashi; Kuroki, Hirofumi; Katsuragawa, Yuzo; Kubota, Kazuo

2005-09-01

We report FDG PET of two cases of cold abscess due to Mycobacterium tuberculosis. Case 1 had colon cancer; FDG PET showed high FDG uptake in the colon lesion and low uptake in the inguinal lesion. The latter was a tuberculous cold abscess confirmed by CT/MRI and biopsy. Case 2 received radiotherapy for lung cancer and presented with suspected vertebral metastasis. Further studies revealed tuberculosis of the vertebra and a tuberculous cold abscess in the iliopsoas muscle. FDG PET showed moderate uptake in the third lumbar spine and low uptake in the abscess center of iliopsoas lesion. Both tuberculous cold abscesses showed moderate FDG uptake in the capsule and low uptake in the center. These features are unique compared with non-tuberculous abscess and typical tuberculosis lesions, which are characterized by high FDG uptake. Pathologically, tuberculous cold abscess is not accompanied by active inflammatory reaction. Our findings suggested that the FDG uptake by tuberculous lesion varies according to the grade of inflammatory activity. The new diagnostic features of tuberculous cold abscess may be useful in the evaluation of such lesions by FDG PET.

Lung texture in serial thoracic CT scans: correlation with radiologist-defined severity of acute changes following radiation therapy

NASA Astrophysics Data System (ADS)

Cunliffe, Alexandra R.; Armato, Samuel G., III; Straus, Christopher; Malik, Renuka; Al-Hallaq, Hania A.

2014-09-01

This study examines the correlation between the radiologist-defined severity of normal tissue damage following radiation therapy (RT) for lung cancer treatment and a set of mathematical descriptors of computed tomography (CT) scan texture (‘texture features’). A pre-therapy CT scan and a post-therapy CT scan were retrospectively collected under IRB approval for each of the 25 patients who underwent definitive RT (median dose: 66 Gy). Sixty regions of interest (ROIs) were automatically identified in the non-cancerous lung tissue of each post-therapy scan. A radiologist compared post-therapy scan ROIs with pre-therapy scans and categorized each as containing no abnormality, mild abnormality, moderate abnormality, or severe abnormality. Twenty texture features that characterize gray-level intensity, region morphology, and gray-level distribution were calculated in post-therapy scan ROIs and compared with anatomically matched ROIs in the pre-therapy scan. Linear regression and receiver operating characteristic (ROC) analysis were used to compare the percent feature value change (ΔFV) between ROIs at each category of visible radiation damage. Most ROIs contained no (65%) or mild abnormality (30%). ROIs with moderate (3%) or severe (2%) abnormalities were observed in 9 patients. For 19 of 20 features, ΔFV was significantly different among severity levels. For 12 features, significant differences were observed at every level. Compared with regions with no abnormalities, ΔFV for these 12 features increased, on average, by 1.5%, 12%, and 30%, respectively, for mild, moderate, and severe abnormalitites. Area under the ROC curve was largest when comparing ΔFV in the highest severity level with the remaining three categories (mean AUC across features: 0.84). In conclusion, 19 features that characterized the severity of radiologic changes from pre-therapy scans were identified. These features may be used in future studies to quantify acute normal lung tissue damage following RT. Presented, in part at the IASLC 15th World Conference on Lung Conference, Sydney, AUS (2013).

Automated labeling of log features in CT imagery of multiple hardwood species

Treesearch

Daniel L. Schmoldt; Jing He; A. Lynn Abbott

2000-01-01

Before noninvasive scanning, e.g., computed tomography (CT), becomes feasible in industrial saw-mill operations, we need a procedure that can automatically interpret scan information in order to provide the saw operator with information necessary to make proper sawing decisions. To this end, we have worked to develop an approach for automatic analysis of CT images of...

Feature-based US to CT registration of the aortic root

NASA Astrophysics Data System (ADS)

Lang, Pencilla; Chen, Elvis C. S.; Guiraudon, Gerard M.; Jones, Doug L.; Bainbridge, Daniel; Chu, Michael W.; Drangova, Maria; Hata, Noby; Jain, Ameet; Peters, Terry M.

2011-03-01

A feature-based registration was developed to align biplane and tracked ultrasound images of the aortic root with a preoperative CT volume. In transcatheter aortic valve replacement, a prosthetic valve is inserted into the aortic annulus via a catheter. Poor anatomical visualization of the aortic root region can result in incorrect positioning, leading to significant morbidity and mortality. Registration of pre-operative CT to transesophageal ultrasound and fluoroscopy images is a major step towards providing augmented image guidance for this procedure. The proposed registration approach uses an iterative closest point algorithm to register a surface mesh generated from CT to 3D US points reconstructed from a single biplane US acquisition, or multiple tracked US images. The use of a single simultaneous acquisition biplane image eliminates reconstruction error introduced by cardiac gating and TEE probe tracking, creating potential for real-time intra-operative registration. A simple initialization procedure is used to minimize changes to operating room workflow. The algorithm is tested on images acquired from excised porcine hearts. Results demonstrate a clinically acceptable accuracy of 2.6mm and 5mm for tracked US to CT and biplane US to CT registration respectively.

Computed Tomography Image Origin Identification Based on Original Sensor Pattern Noise and 3-D Image Reconstruction Algorithm Footprints.

PubMed

Duan, Yuping; Bouslimi, Dalel; Yang, Guanyu; Shu, Huazhong; Coatrieux, Gouenou

2017-07-01

In this paper, we focus on the "blind" identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT scanner based on an original sensor pattern noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its three-dimensional (3-D) image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train a support vector machine (SVM) based classifier to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than sensor pattern noise (SPN) based strategy proposed for general public camera devices.

[Gas-containing gallstones: value of the "Mercedes-Benz" sign at CT examination].

PubMed

Delabrousse, E; Bartholomot, B; Narboux, Y; Barrali, E; Chirouze, C; Kastler, B

2000-11-01

Gas-containing gallstones are well-known in vitro. The typical triradiate arrangement of fissures filled with gas, first described on abdominal plain films, was named by Meyers the "Mercedes-Benz" sign. This sign is absent of the recent literature. We report a case where gas was the only CT sign suggesting the presence of gallstones in the gallbladder.

Machine Learning Algorithms Utilizing Quantitative CT Features May Predict Eventual Onset of Bronchiolitis Obliterans Syndrome After Lung Transplantation.

PubMed

Barbosa, Eduardo J Mortani; Lanclus, Maarten; Vos, Wim; Van Holsbeke, Cedric; De Backer, William; De Backer, Jan; Lee, James

2018-02-19

Long-term survival after lung transplantation (LTx) is limited by bronchiolitis obliterans syndrome (BOS), defined as a sustained decline in forced expiratory volume in the first second (FEV 1 ) not explained by other causes. We assessed whether machine learning (ML) utilizing quantitative computed tomography (qCT) metrics can predict eventual development of BOS. Paired inspiratory-expiratory CT scans of 71 patients who underwent LTx were analyzed retrospectively (BOS [n = 41] versus non-BOS [n = 30]), using at least two different time points. The BOS cohort experienced a reduction in FEV 1 of >10% compared to baseline FEV 1 post LTx. Multifactor analysis correlated declining FEV 1 with qCT features linked to acute inflammation or BOS onset. Student t test and ML were applied on baseline qCT features to identify lung transplant patients at baseline that eventually developed BOS. The FEV 1 decline in the BOS cohort correlated with an increase in the lung volume (P = .027) and in the central airway volume at functional residual capacity (P = .018), not observed in non-BOS patients, whereas the non-BOS cohort experienced a decrease in the central airway volume at total lung capacity with declining FEV 1 (P = .039). Twenty-three baseline qCT parameters could significantly distinguish between non-BOS patients and eventual BOS developers (P < .05), whereas no pulmonary function testing parameters could. Using ML methods (support vector machine), we could identify BOS developers at baseline with an accuracy of 85%, using only three qCT parameters. ML utilizing qCT could discern distinct mechanisms driving FEV 1 decline in BOS and non-BOS LTx patients and predict eventual onset of BOS. This approach may become useful to optimize management of LTx patients. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

A fully automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations.

PubMed

Spanier, A B; Caplan, N; Sosna, J; Acar, B; Joskowicz, L

2018-01-01

The goal of medical content-based image retrieval (M-CBIR) is to assist radiologists in the decision-making process by retrieving medical cases similar to a given image. One of the key interests of radiologists is lesions and their annotations, since the patient treatment depends on the lesion diagnosis. Therefore, a key feature of M-CBIR systems is the retrieval of scans with the most similar lesion annotations. To be of value, M-CBIR systems should be fully automatic to handle large case databases. We present a fully automatic end-to-end method for the retrieval of CT scans with similar liver lesion annotations. The input is a database of abdominal CT scans labeled with liver lesions, a query CT scan, and optionally one radiologist-specified lesion annotation of interest. The output is an ordered list of the database CT scans with the most similar liver lesion annotations. The method starts by automatically segmenting the liver in the scan. It then extracts a histogram-based features vector from the segmented region, learns the features' relative importance, and ranks the database scans according to the relative importance measure. The main advantages of our method are that it fully automates the end-to-end querying process, that it uses simple and efficient techniques that are scalable to large datasets, and that it produces quality retrieval results using an unannotated CT scan. Our experimental results on 9 CT queries on a dataset of 41 volumetric CT scans from the 2014 Image CLEF Liver Annotation Task yield an average retrieval accuracy (Normalized Discounted Cumulative Gain index) of 0.77 and 0.84 without/with annotation, respectively. Fully automatic end-to-end retrieval of similar cases based on image information alone, rather that on disease diagnosis, may help radiologists to better diagnose liver lesions.

Human Epidermal Growth Factor Receptor 2 Expression in Unresectable Gastric Cancers: Relationship with CT Characteristics.

PubMed

Lee, Jeong Sub; Kim, Se Hyung; Im, Seock-Ah; Kim, Min A; Han, Joon Koo

2017-01-01

To retrospectively analyze the qualitative CT features that correlate with human epidermal growth factor receptor 2 (HER2)-expression in pathologically-proven gastric cancers. A total of 181 patients with pathologically-proven unresectable gastric cancers with HER2-expression (HER2-positive [n = 32] and negative [n = 149]) were included. CT features of primary gastric and metastatic tumors were reviewed. The prevalence of each CT finding was compared in both groups. Thereafter, binary logistic regression determined the most significant differential CT features. Clinical outcomes were compared using Kaplan-Meier method. HER2-postive cancers showed lower clinical T stage (21.9% vs. 8.1%; p = 0.015), hyperattenuation on portal phase (62.5% vs. 30.9%; p = 0.003), and was more frequently metastasized to the liver (62.5% vs. 32.2%; p = 0.001), than HER2-negative cancers. On binary regression analysis, hyperattenuation of the tumor (odds ratio [OR], 4.68; p < 0.001) and hepatic metastasis (OR, 4.43; p = 0.001) were significant independent factors that predict HER2-positive cancers. Median survival of HER2-positive cancers (13.7 months) was significantly longer than HER2-negative cancers (9.6 months) ( p = 0.035). HER2-positive gastric cancers show less-advanced T stage, hyperattenuation on the portal phase, and frequently metastasize to the liver, as compared to HER2-negative cancers.

CT diagnosis of a clinically unsuspected acute appendicitis complicating infectious mononucleosis.

PubMed

Zissin, R; Brautbar, O; Shapiro-Feinberg, M

2001-01-01

Acute appendicitis is a rare complication of infectious mononucleosis (IM). We describe a patient with IM and splenic rupture with a computerized tomography (CT) diagnosis of acute appendicitis during the acute phase of the infectious disease. Diagnostic imaging features of acute appendicitis were found on an abdominal CT performed for the evaluation of postoperative fever. Histologic examination confirmed the CT diagnosis of the clinically unsuspected acute appendicitis. Our case is unique both for the rarity of this complication and the lack of clinical symptoms.

Constitutional Trisomy 8 Mosaicism with Persistent Macrocytosis.

PubMed

Altıner, Şule; Kutlay, Nüket Y; İlhan, Osman

2016-01-01

Constitutional trisomy 8 mosaicism (CT8M) is a rare chromosomal abnormality. The phenotype varies from normal features to severe malformations. CT8M increases the risk of developing leukemia and myelodysplastic syndrome. As CT8M is very rare, its diagnosis can easily be overlooked, especially in cases with mild phenotypes. Here, we report the diagnostic process of a 40-year-old female patient with CT8M and discuss the importance of follow-up in monitoring for hematological malignancies. © 2016 S. Karger AG, Basel.

Radiotherapy volume delineation using dynamic [18F]-FDG PET/CT imaging in patients with oropharyngeal cancer: a pilot study.

PubMed

Silvoniemi, Antti; Din, Mueez U; Suilamo, Sami; Shepherd, Tony; Minn, Heikki

2016-11-01

Delineation of gross tumour volume in 3D is a critical step in the radiotherapy (RT) treatment planning for oropharyngeal cancer (OPC). Static [ 18 F]-FDG PET/CT imaging has been suggested as a method to improve the reproducibility of tumour delineation, but it suffers from low specificity. We undertook this pilot study in which dynamic features in time-activity curves (TACs) of [ 18 F]-FDG PET/CT images were applied to help the discrimination of tumour from inflammation and adjacent normal tissue. Five patients with OPC underwent dynamic [ 18 F]-FDG PET/CT imaging in treatment position. Voxel-by-voxel analysis was performed to evaluate seven dynamic features developed with the knowledge of differences in glucose metabolism in different tissue types and visual inspection of TACs. The Gaussian mixture model and K-means algorithms were used to evaluate the performance of the dynamic features in discriminating tumour voxels compared to the performance of standardized uptake values obtained from static imaging. Some dynamic features showed a trend towards discrimination of different metabolic areas but lack of consistency means that clinical application is not recommended based on these results alone. Impact of inflammatory tissue remains a problem for volume delineation in RT of OPC, but a simple dynamic imaging protocol proved practicable and enabled simple data analysis techniques that show promise for complementing the information in static uptake values.

SU-F-R-21: The Stability of Radiomics Features On 4D FDG-PET/CT Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, C

2016-06-15

Purpose: The aim of our study was to perform a stability analysis of 4D PET-derived features in non-small cell lung carcinoma (NSCLC) based on six different respiratory phases. Methods: The 4D FDG-PET/CT respiratory phases were labeled as T0%, T17%, T33%,T50%, T67%, T83% phases, with the T0% phase approximately corresponding to the normal end-inspiration. Lesions were manually delineated based on fused PET-CT, using a standardized clinical delineation protocol. Six texture parameters were analyzed. Results: Results showed that the majority of assessed features had a low stability such as Homogeneity (0.385–0.416), Dissimilarity (3.707–3.861), Angular two moments (0.013–0.019), Contrast (39.782–49.562), Entropy(4.683–5.002) and Inversemore » differential moment (0.317–0.362) on different respiratory phases. Conclusion: This study suggest that further research of quantitative PET imaging features is warranted with respect to respiratory motion.« less

FDG PET/CT findings in a case of myositis ossificans circumscripta of the forearm.

PubMed

Clarençon, Frédéric; Larousserie, Frédérique; Babinet, Antoine; Zylbersztein, Christophe; Talbot, Jean-Noël; Kerrou, Khaldoun

2011-01-01

Myositis ossificans circumscripta (MOC) is a rare benign neoplasm located in soft tissues that, most of the time, appears after a local trauma. The positive diagnosis of MOC may be challenging on CT or MRI findings. We report on an atypical case of a spontaneous nontraumatic MOC in a 54-year-old man, located in the longus supinatus muscle diagnosed with MRI and F-18 FDG PET/CT findings. Rarely described F-18 FDG PET/CT features in MOC are presented. Pattern of avid FDG focus on PET/CT, that may wrongly suggest osteosarcoma, is presented.

Combined texture feature analysis of segmentation and classification of benign and malignant tumour CT slices.

PubMed

Padma, A; Sukanesh, R

2013-01-01

A computer software system is designed for the segmentation and classification of benign from malignant tumour slices in brain computed tomography (CT) images. This paper presents a method to find and select both the dominant run length and co-occurrence texture features of region of interest (ROI) of the tumour region of each slice to be segmented by Fuzzy c means clustering (FCM) and evaluate the performance of support vector machine (SVM)-based classifiers in classifying benign and malignant tumour slices. Two hundred and six tumour confirmed CT slices are considered in this study. A total of 17 texture features are extracted by a feature extraction procedure, and six features are selected using Principal Component Analysis (PCA). This study constructed the SVM-based classifier with the selected features and by comparing the segmentation results with the experienced radiologist labelled ground truth (target). Quantitative analysis between ground truth and segmented tumour is presented in terms of segmentation accuracy, segmentation error and overlap similarity measures such as the Jaccard index. The classification performance of the SVM-based classifier with the same selected features is also evaluated using a 10-fold cross-validation method. The proposed system provides some newly found texture features have an important contribution in classifying benign and malignant tumour slices efficiently and accurately with less computational time. The experimental results showed that the proposed system is able to achieve the highest segmentation and classification accuracy effectiveness as measured by jaccard index and sensitivity and specificity.

Computer-aided diagnosis for phase-contrast X-ray computed tomography: quantitative characterization of human patellar cartilage with high-dimensional geometric features.

PubMed

Nagarajan, Mahesh B; Coan, Paola; Huber, Markus B; Diemoz, Paul C; Glaser, Christian; Wismüller, Axel

2014-02-01

Phase-contrast computed tomography (PCI-CT) has shown tremendous potential as an imaging modality for visualizing human cartilage with high spatial resolution. Previous studies have demonstrated the ability of PCI-CT to visualize (1) structural details of the human patellar cartilage matrix and (2) changes to chondrocyte organization induced by osteoarthritis. This study investigates the use of high-dimensional geometric features in characterizing such chondrocyte patterns in the presence or absence of osteoarthritic damage. Geometrical features derived from the scaling index method (SIM) and statistical features derived from gray-level co-occurrence matrices were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These features were subsequently used in a machine learning task with support vector regression to classify ROIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver-operating characteristic curve (AUC). SIM-derived geometrical features exhibited the best classification performance (AUC, 0.95 ± 0.06) and were most robust to changes in ROI size. These results suggest that such geometrical features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix in an automated and non-subjective manner, while also enabling classification of cartilage as healthy or osteoarthritic with high accuracy. Such features could potentially serve as imaging markers for evaluating osteoarthritis progression and its response to different therapeutic intervention strategies.

Acute gastrointestinal vaso-occlusive ischemia in sickle cell disease: CT imaging features and clinical outcome.

PubMed

Gardner, Carly S; Jaffe, Tracy A

2016-03-01

The purpose of this study was to determine the incidence, specific imaging features, and outcome of gastrointestinal vaso-occlusive ischemia (GVOI) in sickle cell patients undergoing CT for acute abdominal pain. This HIPAA-compliant, IRB-approved retrospective study evaluated sickle cell patients with an abdominal pain crisis and acute gastrointestinal abnormalities on CT from 1/2006 to 1/2014. CT findings were divided into those compatible and incompatible with bowel ischemia or clinical diagnosis of GVOI. Two abdominal radiologists (1, 13 years' experience) reviewed the CTs for specific imaging features of ischemia. Clinical laboratory values (lactate, WBC) and outcome were recorded. Descriptive statistics and Wilcoxon-Mann-Whitney two-sample rank-sum test were performed. Of 217 CTs, 33 had acute gastrointestinal abnormalities: 75% (25/33) consistent with ischemia and clinical GVOI. Complications of ischemia occurred in 16% (4/25): ileus (50%), perforation (25%), and pneumatosis (25%). In uncomplicated cases, all had bowel wall thickening: segmental 52% (11/21) or diffuse 48% (10/21). The colon was commonly involved (76%, 16/21), particularly the ascending (57%, 12/21). Most abnormalities (52%, 11/21) were in the superior mesenteric artery distribution. Average lactate (4.3 ± 4.0 mmol/L, p = 0.02) and WBC count (20.1 ± 10.4, ×1000 cells/μL, p = 0.01) were significantly higher in GVOI. Overall mortality in patients with GVOI was 17% (3/18). GVOI is an important feature of the acute abdominal crisis in patients with sickle cell disease and can be seen in up to 75% of patients with abnormal bowel findings on CT. The diagnosis should be strongly considered in sickle cell patients with CT findings of diffuse or segmental bowel wall thickening, particularly involving the colon.

Time-frequency analysis of pediatric murmurs

NASA Astrophysics Data System (ADS)

Lombardo, Joseph S.; Blodgett, Lisa A.; Rosen, Ron S.; Najmi, Amir-Homayoon; Thompson, W. Reid

1998-05-01

Technology has provided many new tools to assist in the diagnosis of pathologic conditions of the heart. Echocardiography, Ultrafast CT, and MRI are just a few. While these tools are a valuable resource, they are typically too expensive, large and complex in operation for use in rural, homecare, and physician's office settings. Recent advances in computer performance, miniaturization, and acoustic signal processing, have yielded new technologies that when applied to heart sounds can provide low cost screening for pathologic conditions. The short duration and transient nature of these signals requires processing techniques that provide high resolution in both time and frequency. Short-time Fourier transforms, Wigner distributions, and wavelet transforms have been applied to signals form hearts with various pathologic conditions. While no single technique provides the ideal solution, the combination of tools provides a good representation of the acoustic features of the pathologies selected.

An Eye-Tracking Study of Multiple Feature Value Category Structure Learning: The Role of Unique Features

PubMed Central

Liu, Zhiya; Song, Xiaohong; Seger, Carol A.

2015-01-01

We examined whether the degree to which a feature is uniquely characteristic of a category can affect categorization above and beyond the typicality of the feature. We developed a multiple feature value category structure with different dimensions within which feature uniqueness and typicality could be manipulated independently. Using eye tracking, we found that the highest attentional weighting (operationalized as number of fixations, mean fixation time, and the first fixation of the trial) was given to a dimension that included a feature that was both unique and highly typical of the category. Dimensions that included features that were highly typical but not unique, or were unique but not highly typical, received less attention. A dimension with neither a unique nor a highly typical feature received least attention. On the basis of these results we hypothesized that subjects categorized via a rule learning procedure in which they performed an ordered evaluation of dimensions, beginning with unique and strongly typical dimensions, and in which earlier dimensions received higher weighting in the decision. This hypothesis accounted for performance on transfer stimuli better than simple implementations of two other common theories of category learning, exemplar models and prototype models, in which all dimensions were evaluated in parallel and received equal weighting. PMID:26274332

An Eye-Tracking Study of Multiple Feature Value Category Structure Learning: The Role of Unique Features.

PubMed

Liu, Zhiya; Song, Xiaohong; Seger, Carol A

2015-01-01

We examined whether the degree to which a feature is uniquely characteristic of a category can affect categorization above and beyond the typicality of the feature. We developed a multiple feature value category structure with different dimensions within which feature uniqueness and typicality could be manipulated independently. Using eye tracking, we found that the highest attentional weighting (operationalized as number of fixations, mean fixation time, and the first fixation of the trial) was given to a dimension that included a feature that was both unique and highly typical of the category. Dimensions that included features that were highly typical but not unique, or were unique but not highly typical, received less attention. A dimension with neither a unique nor a highly typical feature received least attention. On the basis of these results we hypothesized that subjects categorized via a rule learning procedure in which they performed an ordered evaluation of dimensions, beginning with unique and strongly typical dimensions, and in which earlier dimensions received higher weighting in the decision. This hypothesis accounted for performance on transfer stimuli better than simple implementations of two other common theories of category learning, exemplar models and prototype models, in which all dimensions were evaluated in parallel and received equal weighting.

Hard x-ray micro-tomography of a human head post-mortem as a gold standard to compare x-ray modalities

NASA Astrophysics Data System (ADS)

Dalstra, M.; Schulz, G.; Dagassan-Berndt, D.; Verna, C.; Müller-Gerbl, M.; Müller, B.

2016-10-01

An entire human head obtained at autopsy was micro-CT scanned in a nano/micro-CT scanner in a 6-hour long session. Despite the size of the head, it could still be scanned with a pixel size of 70 μm. The aim of this study was to obtain an optimal quality 3D data-set to be used as baseline control in a larger study comparing the image quality of various cone beam CT systems currently used in dentistry. The image quality of the micro-CT scans was indeed better than the ones of the clinical imaging modalities, both with regard to noise and streak artifacts due to metal dental implants. Bony features in the jaws, like the trabecular architecture and the thin wall of the alveolar bone were clearly visible. Therefore, the 3D micro-CT data-set can be used as the gold standard for linear, angular, and volumetric measurements of anatomical features in and around the oral cavity when comparing clinical imaging modalities.

Tuberculous spondylodiscitis in a patient with a sickle-cell disease: CT findings.

PubMed

Krupniewski, Leszek; Palczewski, Piotr; Gołębiowski, Marek; Kosińska-Kaczyńska, Katarzyna

2012-01-01

Although sickle-cell anemia (SCA) is common in black Americans, Sub-Saharan Africa and in the Mediterranean area, the disease is rare in the temperate climate zone. The manifestations of the disease are related mainly to the production of abnormal hemoglobin that leads to organ ischemia and increased susceptibility to infection caused by functional asplenia. The authors present CT findings in a 39-year-old black woman diagnosed due to abdominal pain, lymphadenopathy and fever. CT of the thorax and abdomen demonstrated changes in the liver, spleen, and skeletal system suggestive of SCA complicated with spondylodiscitis in the thoracic spine. Hepatomegaly and small calcified spleen are typical findings in older homozygotic patients with SCA. The lesions in the skeleton may be related either to intramedullary hematopoiesis or osteonecrosis and osteomyelitis. In the latter case, diffuse osteosclerosis and H-shaped vertebrae are most typical. Tuberculous spondylodiscitis is characterized by the location in the thoracic region, preferential involvement of anterior elements, relative sparing of intervertebral discs, and cold abscesses.

Contrast-enhanced CT features of hepatoblastoma: Can we predict histopathology?

PubMed

Baheti, Akshay D; Luana Stanescu, A; Li, Ning; Chapman, Teresa

Hepatoblastoma is the most common hepatic malignancy occurring in the pediatric population. Intratumoral cellular behavior varies, and the small-cell undifferentiated histopathology carries a poorer prognosis than other tissue subtypes. Neoadjuvant chemotherapy is recommended for this tumor subtype prior to surgical resection in most cases. Early identification of tumors with poor prognosis could have a significant clinical impact. Objective The aim of this work was to identify imaging features of small-cell undifferentiated subtype hepatoblastoma that can help distinguish this subtype from more favorable tumors and potentially guide the clinical management. We also sought to characterize contrast-enhanced CT (CECT) features of hepatoblastoma that correlate with metastatic disease and patient outcome. Our study included 34 patients (24 males, 10 females) with a mean age of 16months (range: 0-46months) with surgically confirmed hepatoblastoma and available baseline abdominal imaging by CECT. Clinical data and CT abdominal images were retrospectively analyzed. Five tumors with small-cell undifferentiated components were identified. All of these tumors demonstrated irregular margins on CT imaging. Advanced PRETEXT stage, vascular invasion and irregular margins were associated with metastatic disease and decreased survival. Capsular retraction was also significantly associated with decreased survival. Irregular tumor margins demonstrated statistically significant association with the presence of small-cell undifferentiated components. No other imaging feature showed statistically significant association. Tumor margin irregularity, vascular invasion, capsular retraction, and PRETEXT stage correlate with worse patient outcomes. Irregular tumor margin was the only imaging feature significantly associated with more aggressive tumor subtype. Copyright © 2017 Elsevier Inc. All rights reserved.

Estimation of lung tumor position from multiple anatomical features on 4D-CT using multiple regression analysis.

PubMed

Ono, Tomohiro; Nakamura, Mitsuhiro; Hirose, Yoshinori; Kitsuda, Kenji; Ono, Yuka; Ishigaki, Takashi; Hiraoka, Masahiro

2017-09-01

To estimate the lung tumor position from multiple anatomical features on four-dimensional computed tomography (4D-CT) data sets using single regression analysis (SRA) and multiple regression analysis (MRA) approach and evaluate an impact of the approach on internal target volume (ITV) for stereotactic body radiotherapy (SBRT) of the lung. Eleven consecutive lung cancer patients (12 cases) underwent 4D-CT scanning. The three-dimensional (3D) lung tumor motion exceeded 5 mm. The 3D tumor position and anatomical features, including lung volume, diaphragm, abdominal wall, and chest wall positions, were measured on 4D-CT images. The tumor position was estimated by SRA using each anatomical feature and MRA using all anatomical features. The difference between the actual and estimated tumor positions was defined as the root-mean-square error (RMSE). A standard partial regression coefficient for the MRA was evaluated. The 3D lung tumor position showed a high correlation with the lung volume (R = 0.92 ± 0.10). Additionally, ITVs derived from SRA and MRA approaches were compared with ITV derived from contouring gross tumor volumes on all 10 phases of the 4D-CT (conventional ITV). The RMSE of the SRA was within 3.7 mm in all directions. Also, the RMSE of the MRA was within 1.6 mm in all directions. The standard partial regression coefficient for the lung volume was the largest and had the most influence on the estimated tumor position. Compared with conventional ITV, average percentage decrease of ITV were 31.9% and 38.3% using SRA and MRA approaches, respectively. The estimation accuracy of lung tumor position was improved by the MRA approach, which provided smaller ITV than conventional ITV. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Respiratory trace feature analysis for the prediction of respiratory-gated PET quantification.

PubMed

Wang, Shouyi; Bowen, Stephen R; Chaovalitwongse, W Art; Sandison, George A; Grabowski, Thomas J; Kinahan, Paul E

2014-02-21

The benefits of respiratory gating in quantitative PET/CT vary tremendously between individual patients. Respiratory pattern is among many patient-specific characteristics that are thought to play an important role in gating-induced imaging improvements. However, the quantitative relationship between patient-specific characteristics of respiratory pattern and improvements in quantitative accuracy from respiratory-gated PET/CT has not been well established. If such a relationship could be estimated, then patient-specific respiratory patterns could be used to prospectively select appropriate motion compensation during image acquisition on a per-patient basis. This study was undertaken to develop a novel statistical model that predicts quantitative changes in PET/CT imaging due to respiratory gating. Free-breathing static FDG-PET images without gating and respiratory-gated FDG-PET images were collected from 22 lung and liver cancer patients on a PET/CT scanner. PET imaging quality was quantified with peak standardized uptake value (SUV(peak)) over lesions of interest. Relative differences in SUV(peak) between static and gated PET images were calculated to indicate quantitative imaging changes due to gating. A comprehensive multidimensional extraction of the morphological and statistical characteristics of respiratory patterns was conducted, resulting in 16 features that characterize representative patterns of a single respiratory trace. The six most informative features were subsequently extracted using a stepwise feature selection approach. The multiple-regression model was trained and tested based on a leave-one-subject-out cross-validation. The predicted quantitative improvements in PET imaging achieved an accuracy higher than 90% using a criterion with a dynamic error-tolerance range for SUV(peak) values. The results of this study suggest that our prediction framework could be applied to determine which patients would likely benefit from respiratory motion compensation when clinicians quantitatively assess PET/CT for therapy target definition and response assessment.

A Bayesian framework for early risk prediction in traumatic brain injury

NASA Astrophysics Data System (ADS)

Chaganti, Shikha; Plassard, Andrew J.; Wilson, Laura; Smith, Miya A.; Patel, Mayur B.; Landman, Bennett A.

2016-03-01

Early detection of risk is critical in determining the course of treatment in traumatic brain injury (TBI). Computed tomography (CT) acquired at admission has shown latent prognostic value in prior studies; however, no robust clinical risk predictions have been achieved based on the imaging data in large-scale TBI analysis. The major challenge lies in the lack of consistent and complete medical records for patients, and an inherent bias associated with the limited number of patients samples with high-risk outcomes in available TBI datasets. Herein, we propose a Bayesian framework with mutual information-based forward feature selection to handle this type of data. Using multi-atlas segmentation, 154 image-based features (capturing intensity, volume and texture) were computed over 22 ROIs in 1791 CT scans. These features were combined with 14 clinical parameters and converted into risk likelihood scores using Bayes modeling. We explore the prediction power of the image features versus the clinical measures for various risk outcomes. The imaging data alone were more predictive of outcomes than the clinical data (including Marshall CT classification) for discharge disposition with an area under the curve of 0.81 vs. 0.67, but less predictive than clinical data for discharge Glasgow Coma Scale (GCS) score with an area under the curve of 0.65 vs. 0.85. However, in both cases, combining imaging and clinical data increased the combined area under the curve with 0.86 for discharge disposition and 0.88 for discharge GCS score. In conclusion, CT data have meaningful prognostic value for TBI patients beyond what is captured in clinical measures and the Marshall CT classification.

Mediastinal lymph node detection and station mapping on chest CT using spatial priors and random forest

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Jiamin; Hoffman, Joanne; Zhao, Jocelyn

2016-07-15

Purpose: To develop an automated system for mediastinal lymph node detection and station mapping for chest CT. Methods: The contextual organs, trachea, lungs, and spine are first automatically identified to locate the region of interest (ROI) (mediastinum). The authors employ shape features derived from Hessian analysis, local object scale, and circular transformation that are computed per voxel in the ROI. Eight more anatomical structures are simultaneously segmented by multiatlas label fusion. Spatial priors are defined as the relative multidimensional distance vectors corresponding to each structure. Intensity, shape, and spatial prior features are integrated and parsed by a random forest classifiermore » for lymph node detection. The detected candidates are then segmented by the following curve evolution process. Texture features are computed on the segmented lymph nodes and a support vector machine committee is used for final classification. For lymph node station labeling, based on the segmentation results of the above anatomical structures, the textual definitions of mediastinal lymph node map according to the International Association for the Study of Lung Cancer are converted into patient-specific color-coded CT image, where the lymph node station can be automatically assigned for each detected node. Results: The chest CT volumes from 70 patients with 316 enlarged mediastinal lymph nodes are used for validation. For lymph node detection, their system achieves 88% sensitivity at eight false positives per patient. For lymph node station labeling, 84.5% of lymph nodes are correctly assigned to their stations. Conclusions: Multiple-channel shape, intensity, and spatial prior features aggregated by a random forest classifier improve mediastinal lymph node detection on chest CT. Using the location information of segmented anatomic structures from the multiatlas formulation enables accurate identification of lymph node stations.« less

Respiratory trace feature analysis for the prediction of respiratory-gated PET quantification

NASA Astrophysics Data System (ADS)

Wang, Shouyi; Bowen, Stephen R.; Chaovalitwongse, W. Art; Sandison, George A.; Grabowski, Thomas J.; Kinahan, Paul E.

2014-02-01

The benefits of respiratory gating in quantitative PET/CT vary tremendously between individual patients. Respiratory pattern is among many patient-specific characteristics that are thought to play an important role in gating-induced imaging improvements. However, the quantitative relationship between patient-specific characteristics of respiratory pattern and improvements in quantitative accuracy from respiratory-gated PET/CT has not been well established. If such a relationship could be estimated, then patient-specific respiratory patterns could be used to prospectively select appropriate motion compensation during image acquisition on a per-patient basis. This study was undertaken to develop a novel statistical model that predicts quantitative changes in PET/CT imaging due to respiratory gating. Free-breathing static FDG-PET images without gating and respiratory-gated FDG-PET images were collected from 22 lung and liver cancer patients on a PET/CT scanner. PET imaging quality was quantified with peak standardized uptake value (SUVpeak) over lesions of interest. Relative differences in SUVpeak between static and gated PET images were calculated to indicate quantitative imaging changes due to gating. A comprehensive multidimensional extraction of the morphological and statistical characteristics of respiratory patterns was conducted, resulting in 16 features that characterize representative patterns of a single respiratory trace. The six most informative features were subsequently extracted using a stepwise feature selection approach. The multiple-regression model was trained and tested based on a leave-one-subject-out cross-validation. The predicted quantitative improvements in PET imaging achieved an accuracy higher than 90% using a criterion with a dynamic error-tolerance range for SUVpeak values. The results of this study suggest that our prediction framework could be applied to determine which patients would likely benefit from respiratory motion compensation when clinicians quantitatively assess PET/CT for therapy target definition and response assessment.

SEGMENTING CT PROSTATE IMAGES USING POPULATION AND PATIENT-SPECIFIC STATISTICS FOR RADIOTHERAPY.

PubMed

Feng, Qianjin; Foskey, Mark; Tang, Songyuan; Chen, Wufan; Shen, Dinggang

2009-08-07

This paper presents a new deformable model using both population and patient-specific statistics to segment the prostate from CT images. There are two novelties in the proposed method. First, a modified scale invariant feature transform (SIFT) local descriptor, which is more distinctive than general intensity and gradient features, is used to characterize the image features. Second, an online training approach is used to build the shape statistics for accurately capturing intra-patient variation, which is more important than inter-patient variation for prostate segmentation in clinical radiotherapy. Experimental results show that the proposed method is robust and accurate, suitable for clinical application.

SEGMENTING CT PROSTATE IMAGES USING POPULATION AND PATIENT-SPECIFIC STATISTICS FOR RADIOTHERAPY

PubMed Central

Feng, Qianjin; Foskey, Mark; Tang, Songyuan; Chen, Wufan; Shen, Dinggang

2010-01-01

This paper presents a new deformable model using both population and patient-specific statistics to segment the prostate from CT images. There are two novelties in the proposed method. First, a modified scale invariant feature transform (SIFT) local descriptor, which is more distinctive than general intensity and gradient features, is used to characterize the image features. Second, an online training approach is used to build the shape statistics for accurately capturing intra-patient variation, which is more important than inter-patient variation for prostate segmentation in clinical radiotherapy. Experimental results show that the proposed method is robust and accurate, suitable for clinical application. PMID:21197416

Imaging of Spontaneous and Traumatic Cervical Artery Dissection : Comparison of Typical CT Angiographic Features.

PubMed

Sporns, Peter B; Niederstadt, Thomas; Heindel, Walter; Raschke, Michael J; Hartensuer, René; Dittrich, Ralf; Hanning, Uta

2018-01-26

Cervical artery dissection (CAD) is an important etiology of ischemic stroke and early recognition is vital to protect patients from the major complication of cerebral embolization by administration of anticoagulants. The etiology of arterial dissections differ and can be either spontaneous or traumatic. Even though the historical gold standard is still catheter angiography, recent studies suggest a good performance of computed tomography angiography (CTA) for detection of CAD. We conducted this research to evaluate the variety and frequency of possible imaging signs of spontaneous and traumatic CAD and to guide neuroradiologists' decision making. Retrospective review of the database of our multiple injured patients admitted to the Department of Trauma, Hand, and Reconstructive Surgery of the University Hospital Münster in Germany (a level 1 trauma center) for patients with traumatic CAD (tCAD) and of our stroke database (2008-2015) for patients with spontaneous CAD (sCAD) and CT/CTA on initial clinical work-up. All images were evaluated concerning specific and sensitive radiological features for dissection by two experienced neuroradiologists. Imaging features were compared between the two etiologies. This study included 145 patients (99 male, 46 female; 45 ± 18.8 years of age), consisting of 126 dissected arteries with a traumatic and 43 with spontaneous etiology. Intimal flaps were more frequently observed after traumatic etiology (58.1% tCADs, 6.9% sCADs; p < 0.001); additionally, multivessel dissections were much more frequent in trauma patients (3 sCADs, 21 tCADs) and only less than half (42%) of the patients with traumatic dissections showed cervical spine fractures. Neuroradiologists should be aware that intimal flaps and multivessel dissections are more common after a traumatic etiology. In addition, it seems important to conduct a CTA in a trauma setting, even if no cervical spine fracture is detected.

Computed tomographic features of idiopathic fibrosing interstitial pneumonia: comparison with pulmonary fibrosis related to collagen vascular disease.

PubMed

Hwang, Jeong-Hwa; Misumi, Shigeki; Sahin, Hakan; Brown, Kevin K; Newell, John D; Lynch, David A

2009-01-01

To compare the computed tomographic (CT) features of idiopathic fibrosing interstitial pneumonia with those of pulmonary fibrosis related to collagen vascular disease (CVD). We reviewed the CT scans of 177 patients with diffuse interstitial pulmonary fibrosis, of which 97 had idiopathic fibrosing interstitial pneumonia and 80 had CVD. The CT images were systematically scored for the presence and extent of pulmonary and extrapulmonary abnormalities. Computed tomographic diagnosis of usual interstitial pneumonia (UIP) or nonspecific interstitial pneumonia (NSIP) was assigned. A CT pattern of UIP was identified in 59 (60.8%) of patients with idiopathic fibrosing interstitial pneumonia compared with 15 (18.7%) of those patients with CVD; conversely, the CT diagnosis of NSIP was made in 51 (64%) of patients with CVD compared with 36 (37%) of patients with idiopathic disease (P < 0.01). In 113 patients who had lung biopsy, the CT diagnoses of UIP and NSIP were concordant with the histologic diagnoses in 36 of 50 patients and 34 of 41 patients, respectively. Pleural effusions, esophageal dilation, and pericardial abnormalities were more frequent in patients with CVD than in patients with idiopathic fibrosing interstitial pneumonia. Compared with patients with CVD, those patients with an idiopathic fibrosing interstitial pneumonia showed a higher prevalence of a UIP pattern and lower prevalence of an NSIP pattern as determined by CT. Identification of coexisting extrapulmonary abnormalities on CT can support a diagnosis of CVD.

Radiomics in Oncological PET/CT: Clinical Applications.

PubMed

Lee, Jeong Won; Lee, Sang Mi

2018-06-01

18 F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is widely used for staging, evaluating treatment response, and predicting prognosis in malignant diseases. FDG uptake and volumetric PET parameters such as metabolic tumor volume have been used and are still used as conventional PET parameters to assess biological characteristics of tumors. However, in recent years, additional features derived from PET images by computational processing have been found to reflect intratumoral heterogeneity, which is related to biological tumor features, and to provide additional predictive and prognostic information, which leads to the concept of radiomics. In this review, we focus on recent clinical studies of malignant diseases that investigated intratumoral heterogeneity on PET/CT, and we discuss its clinical role in various cancers.

Ossicles of lumbar articular facets: normal variant or spondylolytic variant?

PubMed

Kumar, Dalavaye S; Fotiadou, Anastasia; Lalam, Radhesh; Ginder, Laurence M; Eisenstein, Stephen M; Tins, Bernard J; Tyrrell, Prudencia N M; Delieu, John M; McCall, Iain W; Rees, Dai A; Cassar-Pullicino, Victor N

2012-12-01

The objective of this study was to establish the prevalence and significance of ossicles of lumbar articular facets (OLAF) in young athletes with backache diagnosed by multi-detector computed tomography (MDCT). The MDCT examinations of the lumbar spine carried out for suspected spondylolysis on 46 consecutive symptomatic young athletes presenting to a sports injury clinic over a 1-year period were retrospectively reviewed. OLAF study included detailed correlation with the structural and morphological stress features of the posterior neural arches. This was then compared with a control group composed of 39 patients. Twenty-three OLAF were identified in 15 patients. Eleven of the 15 patients with ossicles had posterior element stress changes (PEST)/pars defects. In the control group, two OLAF were identified in two patients, one demonstrating PEST changes. The high prevalence of OLAF in young symptomatic athletes compared with the asymptomatic control group is indicative of stress fractures. The non-united articular process fractures should be regarded as part of the spectrum of stress-induced changes in the posterior neural arch in the same way as spondylolysis. MDCT with volumetric acquisition and multi-planar reformation is the most reliable investigation in the diagnosis of OLAF. 1) This CT study supports a traumatic aetiology for lumbar articular facets ossicles. 2) OLAF represent part of a spectrum of stress-induced changes in the posterior neural arch. 3) OLAF are associated with typical spondylolysis. 4) OLAF can be overlooked on reverse gantry angle computed tomography (RG-CT). 5) OLAF may account for some of the discrepancy between radionuclide and RG-CT studies.

Radiologic Diagnosis of Spondylodiscitis, Role of Magnetic Resonance

PubMed Central

Ramadani, Naser; Dedushi, Kreshnike; Kabashi, Serbeze; Mucaj, Sefedin

2017-01-01

Introduction: Study aim is to report the Magnetic Resonance Imaging (MRI) features of acute and chronic spontaneous spondylodiscitis. Case report: 57 year old female, complaining of a fever and longstanding cervical pain worsened during physical therapy. Methods: MR images were acquired using superconductive magnet 1.5 T, with the following sequences: sagittal PD and T2 TSE, sagittal T1 SE, axial PD and T2 TSE (lumbar spine), axial T2 GRE (cervical spine). Axial and sagittal T1 SE after administration of (gadolinium DTPA). Examination was reviewed by three radiologists and compared to CT findings. Results: Patient reported cervical pain associated with fever and minimal weight loss. Blood tests were normal except hyperglycemia (DM tip II). X Ray: vertebral destruction localized at C-4 and C-5: NECT: destruction of the C-4/C-5 vertebral bodies (ventral part). MRI: Low signal of the bone marrow on T1l images, which enhanced after Gd-DTPA administration and became intermediate or high on T2 images. The steady high signal intensity of the disk on T2 images and enhancement on T1 images is typical for an acute inflammatory process. Bone Scintigrafi results: Bone changes suspicious for metastasis. Whole body CT results: apart from spine, no other significant changes. Conclusion: MRI is the most sensitive technique for the diagnosis of spondylodiscitis in the acute phase and comparable to CT regarding chronial stage of the disease. The present imagining essay os aimed at showing the main magnetic resonance imaging findings of tuberculous discitis. PMID:28484299

Shading correction for cone-beam CT in radiotherapy: validation of dose calculation accuracy using clinical images

NASA Astrophysics Data System (ADS)

Marchant, T. E.; Joshi, K. D.; Moore, C. J.

2017-03-01

Cone-beam CT (CBCT) images are routinely acquired to verify patient position in radiotherapy (RT), but are typically not calibrated in Hounsfield Units (HU) and feature non-uniformity due to X-ray scatter and detector persistence effects. This prevents direct use of CBCT for re-calculation of RT delivered dose. We previously developed a prior-image based correction method to restore HU values and improve uniformity of CBCT images. Here we validate the accuracy with which corrected CBCT can be used for dosimetric assessment of RT delivery, using CBCT images and RT plans for 45 patients including pelvis, lung and head sites. Dose distributions were calculated based on each patient's original RT plan and using CBCT image values for tissue heterogeneity correction. Clinically relevant dose metrics were calculated (e.g. median and minimum target dose, maximum organ at risk dose). Accuracy of CBCT based dose metrics was determined using an "override ratio" method where the ratio of the dose metric to that calculated on a bulk-density assigned version of the image is assumed to be constant for each patient, allowing comparison to "gold standard" CT. For pelvis and head images the proportion of dose errors >2% was reduced from 40% to 1.3% after applying shading correction. For lung images the proportion of dose errors >3% was reduced from 66% to 2.2%. Application of shading correction to CBCT images greatly improves their utility for dosimetric assessment of RT delivery, allowing high confidence that CBCT dose calculations are accurate within 2-3%.

A reference dataset for deformable image registration spatial accuracy evaluation using the COPDgene study archive

NASA Astrophysics Data System (ADS)

Castillo, Richard; Castillo, Edward; Fuentes, David; Ahmad, Moiz; Wood, Abbie M.; Ludwig, Michelle S.; Guerrero, Thomas

2013-05-01

Landmark point-pairs provide a strategy to assess deformable image registration (DIR) accuracy in terms of the spatial registration of the underlying anatomy depicted in medical images. In this study, we propose to augment a publicly available database (www.dir-lab.com) of medical images with large sets of manually identified anatomic feature pairs between breath-hold computed tomography (BH-CT) images for DIR spatial accuracy evaluation. Ten BH-CT image pairs were randomly selected from the COPDgene study cases. Each patient had received CT imaging of the entire thorax in the supine position at one-fourth dose normal expiration and maximum effort full dose inspiration. Using dedicated in-house software, an imaging expert manually identified large sets of anatomic feature pairs between images. Estimates of inter- and intra-observer spatial variation in feature localization were determined by repeat measurements of multiple observers over subsets of randomly selected features. 7298 anatomic landmark features were manually paired between the 10 sets of images. Quantity of feature pairs per case ranged from 447 to 1172. Average 3D Euclidean landmark displacements varied substantially among cases, ranging from 12.29 (SD: 6.39) to 30.90 (SD: 14.05) mm. Repeat registration of uniformly sampled subsets of 150 landmarks for each case yielded estimates of observer localization error, which ranged in average from 0.58 (SD: 0.87) to 1.06 (SD: 2.38) mm for each case. The additions to the online web database (www.dir-lab.com) described in this work will broaden the applicability of the reference data, providing a freely available common dataset for targeted critical evaluation of DIR spatial accuracy performance in multiple clinical settings. Estimates of observer variance in feature localization suggest consistent spatial accuracy for all observers across both four-dimensional CT and COPDgene patient cohorts.

Contourlet Textual Features: Improving the Diagnosis of Solitary Pulmonary Nodules in Two Dimensional CT Images

PubMed Central

Wang, Jingjing; Sun, Tao; Gao, Ni; Menon, Desmond Dev; Luo, Yanxia; Gao, Qi; Li, Xia; Wang, Wei; Zhu, Huiping; Lv, Pingxin; Liang, Zhigang; Tao, Lixin; Liu, Xiangtong; Guo, Xiuhua

2014-01-01

Objective To determine the value of contourlet textural features obtained from solitary pulmonary nodules in two dimensional CT images used in diagnoses of lung cancer. Materials and Methods A total of 6,299 CT images were acquired from 336 patients, with 1,454 benign pulmonary nodule images from 84 patients (50 male, 34 female) and 4,845 malignant from 252 patients (150 male, 102 female). Further to this, nineteen patient information categories, which included seven demographic parameters and twelve morphological features, were also collected. A contourlet was used to extract fourteen types of textural features. These were then used to establish three support vector machine models. One comprised a database constructed of nineteen collected patient information categories, another included contourlet textural features and the third one contained both sets of information. Ten-fold cross-validation was used to evaluate the diagnosis results for the three databases, with sensitivity, specificity, accuracy, the area under the curve (AUC), precision, Youden index, and F-measure were used as the assessment criteria. In addition, the synthetic minority over-sampling technique (SMOTE) was used to preprocess the unbalanced data. Results Using a database containing textural features and patient information, sensitivity, specificity, accuracy, AUC, precision, Youden index, and F-measure were: 0.95, 0.71, 0.89, 0.89, 0.92, 0.66, and 0.93 respectively. These results were higher than results derived using the database without textural features (0.82, 0.47, 0.74, 0.67, 0.84, 0.29, and 0.83 respectively) as well as the database comprising only textural features (0.81, 0.64, 0.67, 0.72, 0.88, 0.44, and 0.85 respectively). Using the SMOTE as a pre-processing procedure, new balanced database generated, including observations of 5,816 benign ROIs and 5,815 malignant ROIs, and accuracy was 0.93. Conclusion Our results indicate that the combined contourlet textural features of solitary pulmonary nodules in CT images with patient profile information could potentially improve the diagnosis of lung cancer. PMID:25250576

Radiation exposure in whole body CT screening.

PubMed

Suresh, Pamidighantam; Ratnam, S V; Rao, K V J

2011-04-01

Using a technology that "takes a look" at people's insides and promises early warnings of cancer, cardiac disease, and other abnormalities, clinics and medical imaging facilities nationwide are touting a new service for health conscious people: "Whole body CT screening" this typically involves scanning the body from the chin to below the hips with a form of x-ray imaging that produces cross-sectional images. In USA direct-to-consumer marketing of whole body CT is occurring today in many metropolitan areas. Free standing CT screening centres are being sited in shopping malls and other high density public areas, and these centres are being advertised in the electronic and print media. In this context the present article discussed the pros and cons of having such centres in India with the advent of multislice CT leading to fast scan times.

TU-G-201-01: What Therapy Physicists Need to Know About CT and PET/CT: Terminology and Latest Developments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hua, C.

This session will update therapeutic physicists on technological advancements and radiation oncology features of commercial CT, MRI, and PET/CT imaging systems. Also described are physicists’ roles in every stage of equipment selection, purchasing, and operation, including defining specifications, evaluating vendors, making recommendations, and optimal and safe use of imaging equipment in radiation oncology environment. The first presentation defines important terminology of CT and PET/CT followed by a review of latest innovations, such as metal artifact reduction, statistical iterative reconstruction, radiation dose management, tissue classification by dual energy CT and spectral CT, improvement in spatial resolution and sensitivity in PET, andmore » potentials of PET/MR. We will also discuss important technical specifications and items in CT and PET/CT purchasing quotes and their impacts. The second presentation will focus on key components in the request for proposal for a MRI simulator and how to evaluate vendor proposals. MRI safety issues in radiation Oncology, including MRI scanner Zones (4-zone design), will be discussed. Basic MR terminologies, important functionalities, and advanced features, which are relevant to radiation therapy, will be discussed. In the third presentation, justification of imaging systems for radiation oncology, considerations in room design and construction in a RO department, shared use with diagnostic radiology, staffing needs and training, clinical/research use cases and implementation, will be discussed. The emphasis will be on understanding and bridging the differences between diagnostic and radiation oncology installations, building consensus amongst stakeholders for purchase and use, and integrating imaging technologies into the radiation oncology environment. Learning Objectives: Learn the latest innovations of major imaging systems relevant to radiation therapy Be able to describe important technical specifications of CT, MRI, and PET/CT Understand the process of budget request, equipment justification, comparisons of technical specifications, site visits, vendor selection, and contract development.« less

Volumetric characterization of human patellar cartilage matrix on phase contrast x-ray computed tomography

NASA Astrophysics Data System (ADS)

Abidin, Anas Z.; Nagarajan, Mahesh B.; Checefsky, Walter A.; Coan, Paola; Diemoz, Paul C.; Hobbs, Susan K.; Huber, Markus B.; Wismüller, Axel

2015-03-01

Phase contrast X-ray computed tomography (PCI-CT) has recently emerged as a novel imaging technique that allows visualization of cartilage soft tissue, subsequent examination of chondrocyte patterns, and their correlation to osteoarthritis. Previous studies have shown that 2D texture features are effective at distinguishing between healthy and osteoarthritic regions of interest annotated in the radial zone of cartilage matrix on PCI-CT images. In this study, we further extend the texture analysis to 3D and investigate the ability of volumetric texture features at characterizing chondrocyte patterns in the cartilage matrix for purposes of classification. Here, we extracted volumetric texture features derived from Minkowski Functionals and gray-level co-occurrence matrices (GLCM) from 496 volumes of interest (VOI) annotated on PCI-CT images of human patellar cartilage specimens. The extracted features were then used in a machine-learning task involving support vector regression to classify ROIs as healthy or osteoarthritic. Classification performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). The best classification performance was observed with GLCM features correlation (AUC = 0.83 +/- 0.06) and homogeneity (AUC = 0.82 +/- 0.07), which significantly outperformed all Minkowski Functionals (p < 0.05). These results suggest that such quantitative analysis of chondrocyte patterns in human patellar cartilage matrix involving GLCM-derived statistical features can distinguish between healthy and osteoarthritic tissue with high accuracy.

Radiomics-based features for pattern recognition of lung cancer histopathology and metastases.

PubMed

Ferreira Junior, José Raniery; Koenigkam-Santos, Marcel; Cipriano, Federico Enrique Garcia; Fabro, Alexandre Todorovic; Azevedo-Marques, Paulo Mazzoncini de

2018-06-01

lung cancer is the leading cause of cancer-related deaths in the world, and its poor prognosis varies markedly according to tumor staging. Computed tomography (CT) is the imaging modality of choice for lung cancer evaluation, being used for diagnosis and clinical staging. Besides tumor stage, other features, like histopathological subtype, can also add prognostic information. In this work, radiomics-based CT features were used to predict lung cancer histopathology and metastases using machine learning models. local image datasets of confirmed primary malignant pulmonary tumors were retrospectively evaluated for testing and validation. CT images acquired with same protocol were semiautomatically segmented. Tumors were characterized by clinical features and computer attributes of intensity, histogram, texture, shape, and volume. Three machine learning classifiers used up to 100 selected features to perform the analysis. radiomics-based features yielded areas under the receiver operating characteristic curve of 0.89, 0.97, and 0.92 at testing and 0.75, 0.71, and 0.81 at validation for lymph nodal metastasis, distant metastasis, and histopathology pattern recognition, respectively. the radiomics characterization approach presented great potential to be used in a computational model to aid lung cancer histopathological subtype diagnosis as a "virtual biopsy" and metastatic prediction for therapy decision support without the necessity of a whole-body imaging scanning. Copyright © 2018 Elsevier B.V. All rights reserved.

Application of molecular imaging combined with genetic screening in diagnosing MELAS, diabetes and recurrent pancreatitis.

PubMed

Zhiping, W; Quwen, L; Hai, Z; Jian, Z; Peiyi, G

2016-01-01

We report molecular imaging combined with gene diagnosis in a family with 7 members who carried an A3243G mutation in mitochondrial tRNA and p.Thr 137 Met in cationic trypsinogen (PRSS1) gene presented with mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS), diabetes, and recurrent pancreatitis. DNA sequencing was used to detect and validate mitochondrial DNA and PRSS1. We also verified that mitochondrial heterozygous mutations and c.410 C>T mutation causing p.Thr 137 Met could be detected in oral epithelial cells or in urine sediment cells. In addition, molecular imaging was carried out in the affected family members. In this pedigree, MELAS syndrome accompanied by pancreatitis was an important clinical feature, followed by diabetes. Heteroplasmy of the mtDNA A3243G and c.410 C>T mutation of PRSS1 was found in all tissue samples of these patients, but no mutations were found in 520 normal control and normal individuals of the family. However, based on molecular imaging observations, patients with relatively higher lactate/pyruvate levels had more typical and more severe symptoms, particularly those of pancreatic disease (diabetes or pancreatitis). MELAS syndrome may be associated with pancreatitis. For the diagnosis, it is more reasonable to perform molecular imaging combined with gene diagnosis.

WE-AB-204-06: Pseudo-CT Generation Using Undersampled, Single-Acquisition UTE-MDixon and Direct-Mapping Artificial Neural Networks for MR-Based Attenuation Correction and Radiation Therapy Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Su, K; Kuo, J; Department of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, Ohio

Purpose: Emerging technologies such as dedicated PET/MRI and MR-therapy systems require robust and clinically practical methods for determining photon attenuation. Herein, we propose using novel MR acquisition methods and processing for the generation of pseudo-CTs. Methods: A single acquisition, 190-second UTE-mDixon sequence with 25% (angular) sampling density and 3D radial readout was performed on nine volunteers. Three water-filled tubes were placed in the FOV for trajectory-delay correction. The MR data were reconstructed to generate three primitive images acquired at TEs of 0.1, 1.5 and 2.8 ms. In addition, three derived MR images were generated, i.e. two-point Dixon water/fat separation andmore » R2* (1/T2*) map. Furthermore, two spatial features, i.e. local binary pattern (S-1) and relative spatial coordinates (S-2), were incorporated. A direct-mapping operator was generated using Artificial Neural Networks (ANNs) for transforming the MR features to a pseudo-CT. CT images served as the training data and, using a leave-one-out method, for performance evaluation using mean prediction deviation (MPD), mean absolute prediction deviation (MAPD), and correlation coefficient (R). Results: The errors between measured CT and pseudo-CT declined dramatically when the spatial features, i.e. S-1 and S-2, were included. The MPD, MAPD, and R were, respectively, 5±57 HU, 141±41 HU, and 0.815±0.066 for results generated by the ANN trained without the spatial features and were 32±26 HU, 115±18 HU, and 0.869±0.035 with the spatial features. The estimation errors of the pseudo-CT were smaller when both the S-1 and S-2 were used together than when either the S-1 or the S-2 was used. Pseudo-CT generation (256×256×256 voxels) by ANN took < 0.5 s using a computer having an Intel i7 3.4GHz CPU and 16 GB RAM. Conclusion: The proposed direct-mapping ANN approach is a technically accurate, clinically practical method for pseudo-CT generation and can potentially help improve the accuracy of MR-AC and MR-RTP applications. Please note that the project was completed with partial funding from the Ohio Department of Development grant TECH 11-063 and a sponsored research agreement with Philips Healthcare that is managed by Case Western Reserve University. As noted in the affiliations, some of the authors are Philips employees.« less

Change descriptors for determining nodule malignancy in national lung screening trial CT screening images

NASA Astrophysics Data System (ADS)

Geiger, Benjamin; Hawkins, Samuel; Hall, Lawrence O.; Goldgof, Dmitry B.; Balagurunathan, Yoganand; Gatenby, Robert A.; Gillies, Robert J.

2016-03-01

Pulmonary nodules are effectively diagnosed in CT scans, but determining their malignancy has been a challenge. The rate of change of the volume of a pulmonary nodule is known to be a prognostic factor for cancer development. In this study, we propose that other changes in imaging characteristics are similarly informative. We examined the combination of image features across multiple CT scans, taken from the National Lung Screening Trial, with individual scans of the same patient separated by approximately one year. By subtracting the values of existing features in multiple scans for the same patient, we were able to improve the ability of existing classification algorithms to determine whether a nodule will become malignant. We trained each classifier on 83 nodules determined to be malignant by biopsy and 172 nodules determined to be benign by their clinical stability through two years of no change; classifiers were tested on 77 malignant and 144 benign nodules, using a set of features that in a test-retest experiment were shown to be stable. An accuracy of 83.71% and AUC of 0.814 were achieved with the Random Forests classifier on a subset of features determined to be stable via test-retest reproducibility analysis, further reduced with the Correlation-based Feature Selection algorithm.

A Method for Extracting Suspected Parotid Lesions in CT Images using Feature-based Segmentation and Active Contours based on Stationary Wavelet Transform

NASA Astrophysics Data System (ADS)

Wu, T. Y.; Lin, S. F.

2013-10-01

Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.

Feature-based Alignment of Volumetric Multi-modal Images

PubMed Central

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

Developing a radiomics framework for classifying non-small cell lung carcinoma subtypes

NASA Astrophysics Data System (ADS)

Yu, Dongdong; Zang, Yali; Dong, Di; Zhou, Mu; Gevaert, Olivier; Fang, Mengjie; Shi, Jingyun; Tian, Jie

2017-03-01

Patient-targeted treatment of non-small cell lung carcinoma (NSCLC) has been well documented according to the histologic subtypes over the past decade. In parallel, recent development of quantitative image biomarkers has recently been highlighted as important diagnostic tools to facilitate histological subtype classification. In this study, we present a radiomics analysis that classifies the adenocarcinoma (ADC) and squamous cell carcinoma (SqCC). We extract 52-dimensional, CT-based features (7 statistical features and 45 image texture features) to represent each nodule. We evaluate our approach on a clinical dataset including 324 ADCs and 110 SqCCs patients with CT image scans. Classification of these features is performed with four different machine-learning classifiers including Support Vector Machines with Radial Basis Function kernel (RBF-SVM), Random forest (RF), K-nearest neighbor (KNN), and RUSBoost algorithms. To improve the classifiers' performance, optimal feature subset is selected from the original feature set by using an iterative forward inclusion and backward eliminating algorithm. Extensive experimental results demonstrate that radiomics features achieve encouraging classification results on both complete feature set (AUC=0.89) and optimal feature subset (AUC=0.91).

Acute intracranial hemorrhage secondary to thrombocytopenia: CT appearances unaffected by absence of clot retraction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pierce, J.N.; Taber, K.H.; Hayman, L.A.

To describe the in vivo CT appearance of acute intracerebral blood clots formed from anemic platelet-depleted blood. Three patients with intracerebral hemorrhage secondary only to thrombocytopenia were examined with CT within 2 1/2 hours after the onset of clinical symptoms. There were no unusual CT features found in the intracerebral hemorrhages of patients with only thrombocytopenia. Specifically, a hyperdense zone(s) surrounded by areas of decreased density was identified. Clot retraction (which cannot occur in patients with severe thrombocytopenia) is not necessary for the CT appearance of acute intracerebral hemorrhage. 22 refs., 3 figs., 1 tab.

Radial gradient and radial deviation radiomic features from pre-surgical CT scans are associated with survival among lung adenocarcinoma patients.

PubMed

Tunali, Ilke; Stringfield, Olya; Guvenis, Albert; Wang, Hua; Liu, Ying; Balagurunathan, Yoganand; Lambin, Philippe; Gillies, Robert J; Schabath, Matthew B

2017-11-10

The goal of this study was to extract features from radial deviation and radial gradient maps which were derived from thoracic CT scans of patients diagnosed with lung adenocarcinoma and assess whether these features are associated with overall survival. We used two independent cohorts from different institutions for training (n= 61) and test (n= 47) and focused our analyses on features that were non-redundant and highly reproducible. To reduce the number of features and covariates into a single parsimonious model, a backward elimination approach was applied. Out of 48 features that were extracted, 31 were eliminated because they were not reproducible or were redundant. We considered 17 features for statistical analysis and identified a final model containing the two most highly informative features that were associated with lung cancer survival. One of the two features, radial deviation outside-border separation standard deviation, was replicated in a test cohort exhibiting a statistically significant association with lung cancer survival (multivariable hazard ratio = 0.40; 95% confidence interval 0.17-0.97). Additionally, we explored the biological underpinnings of these features and found radial gradient and radial deviation image features were significantly associated with semantic radiological features.

Computed Tomography Inspection and Analysis for Additive Manufacturing Components

NASA Technical Reports Server (NTRS)

Beshears, Ronald D.

2017-01-01

Computed tomography (CT) inspection was performed on test articles additively manufactured from metallic materials. Metallic AM and machined wrought alloy test articles with programmed flaws and geometric features were inspected using a 2-megavolt linear accelerator based CT system. Performance of CT inspection on identically configured wrought and AM components and programmed flaws was assessed to determine the impact of additive manufacturing on inspectability of objects with complex geometries.

Postmortem computed tomography findings in suicide victims.

PubMed

Garetier, M; Deloire, L; Dédouit, F; Dumousset, E; Saccardy, C; Ben Salem, D

2017-02-01

Suicide is the eighth cause of mortality in France and the leading cause in people aged between 25 and 34 years. The most common methods of suicide are hanging, self-poisoning with medicines and firearms. Postmortem computed tomography (CT) is a useful adjunct to autopsy to confirm suicide and exclude other causes of death. At autopsy, fractures of the hyoid bone or thyroid cartilage, or both, are found in more than 50% of suicidal hangings. Cervical vertebra fractures are rare and only seen in suicide victims jumping from a great height. Three-dimensional reconstructions from CT data are useful to visualize the ligature mark on the neck. In suicides by firearm, postmortem CT shows entry and exit wounds, parenchymal lesions along the bullet path, as well as projectiles in case of penetrating trauma. However, in the chest and abdomen it is more difficult to identify the path of the projectile. Postmortem CT also shows specific features of suicide by drowning or stabbing, but its use is limited in cases of self-poisoning. The use of postmortem CT is also limited by decomposition and change of body position. This article presents the imaging features seen on postmortem CT according to the method of suicide. Copyright © 2016 Éditions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Recent micro-CT scanner developments at UGCT

NASA Astrophysics Data System (ADS)

Dierick, Manuel; Van Loo, Denis; Masschaele, Bert; Van den Bulcke, Jan; Van Acker, Joris; Cnudde, Veerle; Van Hoorebeke, Luc

2014-04-01

This paper describes two X-ray micro-CT scanners which were recently developed to extend the experimental possibilities of microtomography research at the Centre for X-ray Tomography (www.ugct.ugent.be) of the Ghent University (Belgium). The first scanner, called Nanowood, is a wide-range CT scanner with two X-ray sources (160 kVmax) and two detectors, resolving features down to 0.4 μm in small samples, but allowing samples up to 35 cm to be scanned. This is a sample size range of 3 orders of magnitude, making this scanner well suited for imaging multi-scale materials such as wood, stone, etc. Besides the traditional cone-beam acquisition, Nanowood supports helical acquisition, and it can generate images with significant phase-contrast contributions. The second scanner, known as the Environmental micro-CT scanner (EMCT), is a gantry based micro-CT scanner with variable magnification for scanning objects which are not easy to rotate in a standard micro-CT scanner, for example because they are physically connected to external experimental hardware such as sensor wiring, tubing or others. This scanner resolves 5 μm features, covers a field-of-view of about 12 cm wide with an 80 cm vertical travel range. Both scanners will be extensively described and characterized, and their potential will be demonstrated with some key application results.

SU-F-R-30: Interscanner Variability of Radiomics Features in Computed Tomography (CT) Using a Standard ACR Phantom

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shafiq ul Hassan, M; Zhang, G; Moros, E

2016-06-15

Purpose: A simple approach to investigate Interscanner variability of Radiomics features in computed tomography (CT) using a standard ACR phantom. Methods: The standard ACR phantom was scanned on CT scanners from three different manufacturers. Scanning parameters of 120 KVp, 200 mA were used while slice thickness of 3.0 mm on two scanners and 3.27 mm on third scanner was used. Three spherical regions of interest (ROI) from water, medium density and high density inserts were contoured. Ninety four Radiomics features were extracted using an in-house program. These features include shape (11), intensity (22), GLCM (26), GLZSM (11), RLM (11), andmore » NGTDM (5) and 8 fractal dimensions features. To evaluate the Interscanner variability across three scanners, a coefficient of variation (COV) is calculated for each feature group. Each group is further classified according to the COV- by calculating the percentage of features in each of the following categories: COV less than 2%, between 2 and 10% and greater than 10%. Results: For all feature groups, similar trend was observed for three different inserts. Shape features were the most robust for all scanners as expected. 70% of the shape features had COV <2%. For intensity feature group, 2% COV varied from 9 to 32% for three scanners. All features in four groups GLCM, GLZSM, RLM and NGTDM were found to have Interscanner variability ≥2%. The fractal dimensions dependence for medium and high density inserts were similar while it was different for water inserts. Conclusion: We concluded that even for similar scanning conditions, Interscanner variability across different scanners was significant. The texture features based on GLCM, GLZSM, RLM and NGTDM are highly scanner dependent. Since the inserts of the ACR Phantom are not heterogeneous in HU values suggests that matrix based 2nd order features are highly affected by variation in noise. Research partly funded by NIH/NCI R01CA190105-01.« less

Computed tomography of coxofemoral injury in five mute swans (Cygnus olor).

PubMed

Gumpenberger, Michaela; Scope, Alexandra

2012-10-01

Five mute swans (Cygnus olor) were presented with inability to stand or with abnormal positioning of a leg. Clinical examinations indicated the possibility of femoral fractures or coxofemoral luxations. The suspected diagnosis was proven by means of computed tomography (CT), while superimposition of gastrointestinal contents or other artefacts limited radiographic diagnosis in three birds. A typical CT sign for lesions of the coxofemoral joint apart from femoral displacement was haemorrhage within the pelvic bones (especially around the acetabulum), found in four of the five birds. Small femoral head avulsion fractures could be detected only with CT.

Can CT imaging features of ground-glass opacity predict invasiveness? A meta-analysis.

PubMed

Dai, Jian; Yu, Guoyou; Yu, Jianqiang

2018-04-01

A meta-analysis was conducted to investigate the diagnostic performance of computed tomography (CT) imaging features of ground-glass opacity (GGO) to predict invasiveness. Two reviewers independently searched PubMed, Medline, Web of Science, Cochrane Embase and CNKI for relevant studies. CT imaging signs of bubble lucency, speculation, lobulated margin, and pleural indentation were used as diagnostic references to discriminate pre-invasive and invasive disease. The sensitivity, specificity, diagnostic odds ratio (DOR), summary receiver operating characteristic (SROC) curves, and the area under the SROC curve (AUC) were calculated to evaluate diagnostic efficiency. Twelve studies were finally included. Diagnostic performance ranged from 0.41 to 0.52 for sensitivity and 0.56 to 0.63 for specificity. The diagnostic positive and negative likelihood ratios ranged from 1.03 to 2.13 and 0.52 to 1.05, respectively. The DORs of the GGO CT features for discriminating invasive disease ranged from 1.02 to 4.00. The area under the ROC curve was also low, with a range of 0.60 to 0.67 for discriminating pre-invasive and invasive disease. The diagnostic value of a single CT imaging sign of GGO, such as bubble lucency, speculation, lobulated margin, or pleural indentation is limited for discriminating pre-invasive and invasive disease because of low sensitivity, specificity, and AUC. © 2018 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.

Surficial geology of the sea floor in Long Island Sound offshore of Orient Point, New York

USGS Publications Warehouse

McMullen, K.Y.; Poppe, L.J.; Danforth, W.W.; Blackwood, D.S.; Schaer, J.D.; Guberski, M.R.; Wood, D.A.; Doran, E.F.

2011-01-01

The U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), and the Connecticut Department of Environmental Protection (CT DEP) are working cooperatively to map and interpret features of the sea floor along the northeastern coast of the United States. This report presents multibeam bathymetry and sidescan-sonar data obtained during NOAA survey H11446, which was conducted in a 12-km2 area in Long Island Sound offshore of Orient Point, NY. In addition, sediment and photographic data from 26 stations obtained during a USGS verification cruise are presented. Overall, the sea floor slopes gently seaward, but topography is more complex in sand-wave and boulder areas, which are evident in the multibeam and sidescan-sonar data from the study area. Sand waves generally have north-south-oriented crests with 10- to 20-m wavelengths. Sand-wave asymmetry indicates eastward net sediment transport in the east and westward net sediment transport in the northern and western parts of the study area. Areas with boulders on the sea floor are typically hummocky and are part of a glacial moraine system. Boulders are typically encrusted with seaweed, sponges, and anemones as shown in the bottom photography.

Hypomorphic NOTCH3 mutation in an Italian family with CADASIL features.

PubMed

Moccia, Marcello; Mosca, Lorena; Erro, Roberto; Cervasio, Mariarosaria; Allocca, Roberto; Vitale, Carmine; Leonardi, Antonio; Caranci, Ferdinando; Del Basso-De Caro, Maria Laura; Barone, Paolo; Penco, Silvana

2015-01-01

The cerebral autosomal dominant arteriopathy with subcortical infarcts and leucoencephalopathy (CADASIL) is because of NOTCH3 mutations affecting the number of cysteine residues. In this view, the role of atypical NOTCH3 mutations is still debated. Therefore, we investigated a family carrying a NOTCH3 nonsense mutation, with dominantly inherited recurrent cerebrovascular disorders. Among 7 family members, 4 received a clinical diagnosis of CADASIL. A heterozygous truncating mutation in exon 3 (c.307C>T, p.Arg103X) was found in the 4 clinically affected subjects and in one 27-year old lady, only complaining of migraine with aura. Magnetic resonance imaging scans found typical signs of small-vessel disease in the 4 affected subjects, supporting the clinical diagnosis. Skin biopsies did not show the typical granular osmiophilic material, but only nonspecific signs of vascular damage, resembling those previously described in Notch3 knockout mice. Interestingly, messenger RNA (mRNA) analysis supports the hypothesis of an atypical NOTCH3 mutation, suggesting a nonsense-mediated mRNA decay. In conclusion, the present study broadens the spectrum of CADASIL mutations, and, therefore, opens new insights about Notch3 signaling. Copyright © 2015 Elsevier Inc. All rights reserved.

Hepatic perivascular epithelioid cell tumor (PEComa): dynamic CT, MRI, ultrasonography, and pathologic features--analysis of 7 cases and review of the literature.

PubMed

Tan, Yan; Xiao, En-hua

2012-10-01

To evaluate the dynamic CT, MRI, ultrasonography, and pathologic features of hepatic perivascular epithelioid cell tumor (PEComa), improving the understanding and diagnosis of the tumor. A retrospective analysis of CT, MRI, ultrasonography, and pathologic features of 7 hepatic PEComas diagnosed by pathology during 1st January 2005 to 1st September 2011 in our hospital. The performance of dynamic CT, MRI, and ultrasonography revealed that lesions were regular masses with well-defined borders, the maximum diameters were 2.5-8.5 cm (mean = 4 cm), density was homogeneous, contrast-enhanced CT and MRI showed the lesions were significantly and heterogeneously enhanced on arterial phase, less enhanced on portal venous phase, and slightly hypodense on delayed phase. One patient had multiple hepatic lesions and had delayed enhancement. There were no backgrounds of hepatitis and cirrhosis, enlarged lymph nodes, or distant metastases. Pathology showed the gross appearance of the tumor was smooth. Tumor cells were round or polygonal, with clear boundaries and clear membranes, and had abundant translucent cytoplasm. Nuclei were round, with medium size. Tumor cells were epithelial-like cells and arranged in dense sheets. Immunohistochemistry showed that most of them were positive in HMB45 and MelanA, S-100, SMA, while negative in CgA, Syn, CK, CD117, CD10, and CD34. Dynamic CT, MRI, ultrasonography, and pathology of PEComa had some characteristics of benign tumor's performance. Enhanced scan showed PEComa quickly enhanced on arterial phase and enhanced less on portal venous phase. Knowing these characteristics could help to improve the understanding and diagnosis of hepatic PEComa.

Uric acid versus non-uric acid urinary stones: differentiation with single energy CT texture analysis.

PubMed

Zhang, G-M-Y; Sun, H; Shi, B; Xu, M; Xue, H-D; Jin, Z-Y

2018-05-21

To evaluate the accuracy of computed tomography (CT) texture analysis (TA) to differentiate uric acid (UA) stones from non-UA stones on unenhanced CT in patients with urinary calculi with ex vivo Fourier transform infrared spectroscopy (FTIR) as the reference standard. Fourteen patients with 18 UA stones and 31 patients with 32 non-UA stones were included. All the patients had preoperative CT evaluation and subsequent surgical removal of the stones. CTTA was performed on CT images using commercially available research software. Each texture feature was evaluated using the non-parametric Mann-Whitney test. Receiver operating characteristic (ROC) curves were created and the area under the ROC curve (AUC) was calculated for texture parameters that were significantly different. The features were used to train support vector machine (SVM) classifiers. Diagnostic accuracy was evaluated. Compared to non-UA stones, UA stones had significantly lower mean, standard deviation and mean of positive pixels but higher kurtosis (p<0.001) on both unfiltered and filtered texture scales. There were no significant differences in entropy or skewness between UA and non-UA stones. The average SVM accuracy of texture features for differentiating UA from non-UA stones ranged from 88% to 92% (after 10-fold cross validation). A model incorporating standard deviation, skewness, and kurtosis from unfiltered texture scale images resulted in an AUC of 0.965±00.029 with a sensitivity of 94.4% and specificity of 93.7%. CTTA can be used to accurately differentiate UA stones from non-UA stones in vivo using unenhanced CT images. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Genome-wide profiles of CtBP link metabolism with genome stability and epithelial reprogramming in breast cancer.

PubMed

Di, Li-Jun; Byun, Jung S; Wong, Madeline M; Wakano, Clay; Taylor, Tara; Bilke, Sven; Baek, Songjoon; Hunter, Kent; Yang, Howard; Lee, Maxwell; Zvosec, Cecilia; Khramtsova, Galina; Cheng, Fan; Perou, Charles M; Miller, C Ryan; Raab, Rachel; Olopade, Olufunmilayo I; Gardner, Kevin

2013-01-01

The C-terminal binding protein (CtBP) is a NADH-dependent transcriptional repressor that links carbohydrate metabolism to epigenetic regulation by recruiting diverse histone-modifying complexes to chromatin. Here global profiling of CtBP in breast cancer cells reveals that it drives epithelial-to-mesenchymal transition, stem cell pathways and genome instability. CtBP expression induces mesenchymal and stem cell-like features, whereas CtBP depletion or caloric restriction reverses gene repression and increases DNA repair. Multiple members of the CtBP-targeted gene network are selectively downregulated in aggressive breast cancer subtypes. Differential expression of CtBP-targeted genes predicts poor clinical outcome in breast cancer patients, and elevated levels of CtBP in patient tumours predict shorter median survival. Finally, both CtBP promoter targeting and gene repression can be reversed by small molecule inhibition. These findings define broad roles for CtBP in breast cancer biology and suggest novel chromatin-based strategies for pharmacologic and metabolic intervention in cancer.

Estimating the effective radiation dose imparted to patients by intraoperative cone-beam computed tomography in thoracolumbar spinal surgery.

PubMed

Lange, Jeffrey; Karellas, Andrew; Street, John; Eck, Jason C; Lapinsky, Anthony; Connolly, Patrick J; Dipaola, Christian P

2013-03-01

Observational. To estimate the radiation dose imparted to patients during typical thoracolumbar spinal surgical scenarios. Minimally invasive techniques continue to become more common in spine surgery. Computer-assisted navigation systems coupled with intraoperative cone-beam computed tomography (CT) represent one such method used to aid in instrumented spinal procedures. Some studies indicate that cone-beam CT technology delivers a relatively low dose of radiation to patients compared with other x-ray-based imaging modalities. The goal of this study was to estimate the radiation exposure to the patient imparted during typical posterior thoracolumbar instrumented spinal procedures, using intraoperative cone-beam CT and to place these values in the context of standard CT doses. Cone-beam CT scans were obtained using Medtronic O-arm (Medtronic, Minneapolis, MN). Thermoluminescence dosimeters were placed in a linear array on a foam-plastic thoracolumbar spine model centered above the radiation source for O-arm presets of lumbar scans for small or large patients. In-air dosimeter measurements were converted to skin surface measurements, using published conversion factors. Dose-length product was calculated from these values. Effective dose was estimated using published effective dose to dose-length product conversion factors. Calculated dosages for many full-length procedures using the small-patient setting fell within the range of published effective doses of abdominal CT scans (1-31 mSv). Calculated dosages for many full-length procedures using the large-patient setting fell within the range of published effective doses of abdominal CT scans when the number of scans did not exceed 3. We have demonstrated that single cone-beam CT scans and most full-length posterior instrumented spinal procedures using O-arm in standard mode would likely impart a radiation dose within the range of those imparted by a single standard CT scan of the abdomen. Radiation dose increases with patient size, and the radiation dose received by larger patients as a result of more than 3 O-arm scans in standard mode may exceed the dose received during standard CT of the abdomen. Understanding radiation imparted to patients by cone-beam CT is important for assessing risks and benefits of this technology, especially when spinal surgical procedures require multiple intraoperative scans.

Quantifying the impact of respiratory-gated 4D CT acquisition on thoracic image quality: A digital phantom study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernatowicz, K., E-mail: kingab@student.ethz.ch; Knopf, A.; Lomax, A.

Purpose: Prospective respiratory-gated 4D CT has been shown to reduce tumor image artifacts by up to 50% compared to conventional 4D CT. However, to date no studies have quantified the impact of gated 4D CT on normal lung tissue imaging, which is important in performing dose calculations based on accurate estimates of lung volume and structure. To determine the impact of gated 4D CT on thoracic image quality, the authors developed a novel simulation framework incorporating a realistic deformable digital phantom driven by patient tumor motion patterns. Based on this framework, the authors test the hypothesis that respiratory-gated 4D CTmore » can significantly reduce lung imaging artifacts. Methods: Our simulation framework synchronizes the 4D extended cardiac torso (XCAT) phantom with tumor motion data in a quasi real-time fashion, allowing simulation of three 4D CT acquisition modes featuring different levels of respiratory feedback: (i) “conventional” 4D CT that uses a constant imaging and couch-shift frequency, (ii) “beam paused” 4D CT that interrupts imaging to avoid oversampling at a given couch position and respiratory phase, and (iii) “respiratory-gated” 4D CT that triggers acquisition only when the respiratory motion fulfills phase-specific displacement gating windows based on prescan breathing data. Our framework generates a set of ground truth comparators, representing the average XCAT anatomy during beam-on for each of ten respiratory phase bins. Based on this framework, the authors simulated conventional, beam-paused, and respiratory-gated 4D CT images using tumor motion patterns from seven lung cancer patients across 13 treatment fractions, with a simulated 5.5 cm{sup 3} spherical lesion. Normal lung tissue image quality was quantified by comparing simulated and ground truth images in terms of overall mean square error (MSE) intensity difference, threshold-based lung volume error, and fractional false positive/false negative rates. Results: Averaged across all simulations and phase bins, respiratory-gating reduced overall thoracic MSE by 46% compared to conventional 4D CT (p ∼ 10{sup −19}). Gating leads to small but significant (p < 0.02) reductions in lung volume errors (1.8%–1.4%), false positives (4.0%–2.6%), and false negatives (2.7%–1.3%). These percentage reductions correspond to gating reducing image artifacts by 24–90 cm{sup 3} of lung tissue. Similar to earlier studies, gating reduced patient image dose by up to 22%, but with scan time increased by up to 135%. Beam paused 4D CT did not significantly impact normal lung tissue image quality, but did yield similar dose reductions as for respiratory-gating, without the added cost in scanning time. Conclusions: For a typical 6 L lung, respiratory-gated 4D CT can reduce image artifacts affecting up to 90 cm{sup 3} of normal lung tissue compared to conventional acquisition. This image improvement could have important implications for dose calculations based on 4D CT. Where image quality is less critical, beam paused 4D CT is a simple strategy to reduce imaging dose without sacrificing acquisition time.« less

A natural language processing pipeline for pairing measurements uniquely across free-text CT reports.

PubMed

Sevenster, Merlijn; Bozeman, Jeffrey; Cowhy, Andrea; Trost, William

2015-02-01

To standardize and objectivize treatment response assessment in oncology, guidelines have been proposed that are driven by radiological measurements, which are typically communicated in free-text reports defying automated processing. We study through inter-annotator agreement and natural language processing (NLP) algorithm development the task of pairing measurements that quantify the same finding across consecutive radiology reports, such that each measurement is paired with at most one other ("partial uniqueness"). Ground truth is created based on 283 abdomen and 311 chest CT reports of 50 patients each. A pre-processing engine segments reports and extracts measurements. Thirteen features are developed based on volumetric similarity between measurements, semantic similarity between their respective narrative contexts and structural properties of their report positions. A Random Forest classifier (RF) integrates all features. A "mutual best match" (MBM) post-processor ensures partial uniqueness. In an end-to-end evaluation, RF has precision 0.841, recall 0.807, F-measure 0.824 and AUC 0.971; with MBM, which performs above chance level (P<0.001), it has precision 0.899, recall 0.776, F-measure 0.833 and AUC 0.935. RF (RF+MBM) has error-free performance on 52.7% (57.4%) of report pairs. Inter-annotator agreement of three domain specialists with the ground truth (κ>0.960) indicates that the task is well defined. Domain properties and inter-section differences are discussed to explain superior performance in abdomen. Enforcing partial uniqueness has mixed but minor effects on performance. A combined machine learning-filtering approach is proposed for pairing measurements, which can support prospective (supporting treatment response assessment) and retrospective purposes (data mining). Copyright © 2014 Elsevier Inc. All rights reserved.

Trauma Imaging: A Literature Review.

PubMed

Vela, Jason Heath; Wertz, Christopher Ira; Onstott, Kimberly L; Wertz, Joss R

2017-01-01

To inform radiologic technologists about which imaging modalities and examinations are best suited for evaluating specific anatomical structures in patients who have sustained a traumatic injury. Two scholarly research databases were searched to identify articles focused on trauma imaging of the head, cervical spine, thorax, abdomen, and pelvis. Articles focused on trauma diagnosis were excluded. Thirty-two articles were selected for analysis. Physical examination and plain-film radiographs typically are used to assess nasal bone fracures. Computed tomography (CT) can be used to assess zygomaticomaxillary complex, mandibular, and temporal bone fractures. Traumatic brain injuries are difficult to assess, and broad classifications are used. Depending on the severity of cervical spine trauma, plain-film radiographs or CT imaging is adequate, with magnetic resonance imaging used as a means for further evaluation. Trauma to the thorax typically is assessed with radiography and CT, and CT is recommended for assesment of abdominal and pelvic trauma. The literature was consistent regarding which examinations to perform to best evaluate suspected injuries to the chest, abdomen, and pelvis. The need for, and correct use of, imaging in evaluating trauma to the head and cervical spine is more controversial. Despite the need for additional research, emergency department care providers should be familiar with the structures most commonly injured during trauma and the role of medical imaging for diagnosis.

Radiological features for the approach in trans-sphenoidal pituitary surgery.

PubMed

Twigg, Victoria; Carr, Simon D; Balakumar, Ramkishan; Sinha, Saurabh; Mirza, Showkat

2017-08-01

In order to perform trans-sphenoidal endoscopic pituitary surgery safely and efficiently it is important to identify anatomical and pituitary disease features on the pre-operative CT and MRI scans; thereby minimising the risk to surrounding structures and optimising outcomes. We aim to create a checklist to streamline pre-operative planning. We retrospectively reviewed pre-operative CT and MRI scans of 100 adults undergoing trans-sphenoidal endoscopic pituitary surgery. Radiological findings and their incidence included deviated nasal septum (62%), concha bullosa (32%), bony dehiscence of the carotid arteries (18%), sphenoid septation overlying the internal carotid artery (24% at the sella) and low lying CSF (32%). The mean distance of the sphenoid ostium to the skull base was 10 mm (range 2.7-17.6 mm). We also describe the 'teddy bear' sign which when present on an axial CT indicates the carotid arteries will be identifiable intra-operatively. There are significant variations in the anatomical and pituitary disease features between patients. We describe a number of features on pre-operative scans and have devised a checklist including a new 'teddy bear' sign to aid the surgeon in the anatomical assessment of patients undergoing trans-sphenoidal pituitary surgery.

MR to CT registration of brains using image synthesis

NASA Astrophysics Data System (ADS)

Roy, Snehashis; Carass, Aaron; Jog, Amod; Prince, Jerry L.; Lee, Junghoon

2014-03-01

Computed tomography (CT) is the preferred imaging modality for patient dose calculation for radiation therapy. Magnetic resonance (MR) imaging (MRI) is used along with CT to identify brain structures due to its superior soft tissue contrast. Registration of MR and CT is necessary for accurate delineation of the tumor and other structures, and is critical in radiotherapy planning. Mutual information (MI) or its variants are typically used as a similarity metric to register MRI to CT. However, unlike CT, MRI intensity does not have an accepted calibrated intensity scale. Therefore, MI-based MR-CT registration may vary from scan to scan as MI depends on the joint histogram of the images. In this paper, we propose a fully automatic framework for MR-CT registration by synthesizing a synthetic CT image from MRI using a co-registered pair of MR and CT images as an atlas. Patches of the subject MRI are matched to the atlas and the synthetic CT patches are estimated in a probabilistic framework. The synthetic CT is registered to the original CT using a deformable registration and the computed deformation is applied to the MRI. In contrast to most existing methods, we do not need any manual intervention such as picking landmarks or regions of interests. The proposed method was validated on ten brain cancer patient cases, showing 25% improvement in MI and correlation between MR and CT images after registration compared to state-of-the-art registration methods.

Can technical characteristics predict clinical performance in PET/CT imaging? A correlation study for thyroid cancer diagnosis

NASA Astrophysics Data System (ADS)

Kallergi, Maria; Menychtas, Dimitrios; Georgakopoulos, Alexandros; Pianou, Nikoletta; Metaxas, Marinos; Chatziioannou, Sofia

2013-03-01

The purpose of this study was to determine whether image characteristics could be used to predict the outcome of ROC studies in PET/CT imaging. Patients suspected for recurrent thyroid cancer underwent a standard whole body (WB) examination and an additional high-resolution head-and-neck (HN) F18-FDG PET/CT scan. The value of the latter was determined with an ROC study, the results of which showed that the WB+HN combination was better than WB alone for thyroid cancer detection and diagnosis. Following the ROC experiment, the WB and HN images of confirmed benign or malignant thyroid disease were analyzed and first and second order textural features were determined. Features included minimum, mean, and maximum intensity, as well as contrast in regions of interest encircling the thyroid lesions. Lesion size and standard uptake values (SUV) were also determined. Bivariate analysis was applied to determine relationships between WB and HN features and between observer ROC responses and the various feature values. The two sets showed significant associations in the values of SUV, contrast, and lesion size. They were completely different when the intensities were considered; no relationship was found between the WB minimum, maximum, and mean ROI values and their HN counterparts. SUV and contrast were the strongest predictors of ROC performance on PET/CT examinations of thyroid cancer. The high resolution HN images seem to enhance these relationships but without a single dramatic effect as was projected from the ROC results. A combination of features from both WB and HN datasets may possibly be a more robust predictor of ROC performance.

Survival Prediction in Pancreatic Ductal Adenocarcinoma by Quantitative Computed Tomography Image Analysis.

PubMed

Attiyeh, Marc A; Chakraborty, Jayasree; Doussot, Alexandre; Langdon-Embry, Liana; Mainarich, Shiana; Gönen, Mithat; Balachandran, Vinod P; D'Angelica, Michael I; DeMatteo, Ronald P; Jarnagin, William R; Kingham, T Peter; Allen, Peter J; Simpson, Amber L; Do, Richard K

2018-04-01

Pancreatic cancer is a highly lethal cancer with no established a priori markers of survival. Existing nomograms rely mainly on post-resection data and are of limited utility in directing surgical management. This study investigated the use of quantitative computed tomography (CT) features to preoperatively assess survival for pancreatic ductal adenocarcinoma (PDAC) patients. A prospectively maintained database identified consecutive chemotherapy-naive patients with CT angiography and resected PDAC between 2009 and 2012. Variation in CT enhancement patterns was extracted from the tumor region using texture analysis, a quantitative image analysis tool previously described in the literature. Two continuous survival models were constructed, with 70% of the data (training set) using Cox regression, first based only on preoperative serum cancer antigen (CA) 19-9 levels and image features (model A), and then on CA19-9, image features, and the Brennan score (composite pathology score; model B). The remaining 30% of the data (test set) were reserved for independent validation. A total of 161 patients were included in the analysis. Training and test sets contained 113 and 48 patients, respectively. Quantitative image features combined with CA19-9 achieved a c-index of 0.69 [integrated Brier score (IBS) 0.224] on the test data, while combining CA19-9, imaging, and the Brennan score achieved a c-index of 0.74 (IBS 0.200) on the test data. We present two continuous survival prediction models for resected PDAC patients. Quantitative analysis of CT texture features is associated with overall survival. Further work includes applying the model to an external dataset to increase the sample size for training and to determine its applicability.

NOTE: An innovative phantom for quantitative and qualitative investigation of advanced x-ray imaging technologies

NASA Astrophysics Data System (ADS)

Chiarot, C. B.; Siewerdsen, J. H.; Haycocks, T.; Moseley, D. J.; Jaffray, D. A.

2005-11-01

Development, characterization, and quality assurance of advanced x-ray imaging technologies require phantoms that are quantitative and well suited to such modalities. This note reports on the design, construction, and use of an innovative phantom developed for advanced imaging technologies (e.g., multi-detector CT and the numerous applications of flat-panel detectors in dual-energy imaging, tomosynthesis, and cone-beam CT) in diagnostic and image-guided procedures. The design addresses shortcomings of existing phantoms by incorporating criteria satisfied by no other single phantom: (1) inserts are fully 3D—spherically symmetric rather than cylindrical; (2) modules are quantitative, presenting objects of known size and contrast for quality assurance and image quality investigation; (3) features are incorporated in ideal and semi-realistic (anthropomorphic) contexts; and (4) the phantom allows devices to be inserted and manipulated in an accessible module (right lung). The phantom consists of five primary modules: (1) head, featuring contrast-detail spheres approximate to brain lesions; (2) left lung, featuring contrast-detail spheres approximate to lung modules; (3) right lung, an accessible hull in which devices may be placed and manipulated; (4) liver, featuring conrast-detail spheres approximate to metastases; and (5) abdomen/pelvis, featuring simulated kidneys, colon, rectum, bladder, and prostate. The phantom represents a two-fold evolution in design philosophy—from 2D (cylindrically symmetric) to fully 3D, and from exclusively qualitative or quantitative to a design accommodating quantitative study within an anatomical context. It has proven a valuable tool in investigations throughout our institution, including low-dose CT, dual-energy radiography, and cone-beam CT for image-guided radiation therapy and surgery.

A region-based segmentation of tumour from brain CT images using nonlinear support vector machine classifier.

PubMed

Nanthagopal, A Padma; Rajamony, R Sukanesh

2012-07-01

The proposed system provides new textural information for segmenting tumours, efficiently and accurately and with less computational time, from benign and malignant tumour images, especially in smaller dimensions of tumour regions of computed tomography (CT) images. Region-based segmentation of tumour from brain CT image data is an important but time-consuming task performed manually by medical experts. The objective of this work is to segment brain tumour from CT images using combined grey and texture features with new edge features and nonlinear support vector machine (SVM) classifier. The selected optimal features are used to model and train the nonlinear SVM classifier to segment the tumour from computed tomography images and the segmentation accuracies are evaluated for each slice of the tumour image. The method is applied on real data of 80 benign, malignant tumour images. The results are compared with the radiologist labelled ground truth. Quantitative analysis between ground truth and the segmented tumour is presented in terms of segmentation accuracy and the overlap similarity measure dice metric. From the analysis and performance measures such as segmentation accuracy and dice metric, it is inferred that better segmentation accuracy and higher dice metric are achieved with the normalized cut segmentation method than with the fuzzy c-means clustering method.

Thin-Section CT Features of Idiopathic Pulmonary Fibrosis Correlated with Micro-CT and Histologic Analysis.

PubMed

Mai, Cindy; Verleden, Stijn E; McDonough, John E; Willems, Stijn; De Wever, Walter; Coolen, Johan; Dubbeldam, Adriana; Van Raemdonck, Dirk E; Verbeken, Eric K; Verleden, Geert M; Hogg, James C; Vanaudenaerde, Bart M; Wuyts, Wim A; Verschakelen, Johny A

2017-04-01

Purpose To elucidate the underlying lung changes responsible for the computed tomographic (CT) features of idiopathic pulmonary fibrosis (IPF) and to gain insight into the way IPF proceeds through the lungs and progresses over time. Materials and Methods Micro-CT studies of tissue cores obtained from explant lungs were examined and were correlated 1:1 with a CT study obtained immediately before transplantation. Samples for histologic analysis were obtained from selected cores. Results In areas with no or minimal abnormalities on CT images, small areas of increased attenuation located in or near the interlobular septa can be seen on micro-CT studies. In more involved lung areas, the number of opacities increases and opacities enlarge and approach each other along the interlobular septa, causing a fine reticular pattern on CT images. Simultaneously, air-containing structures in and around these opacities arise, corresponding with small cysts on CT images. Honeycombing is caused by a progressive increase in the number and size of these cystic structures and tissue opacities that gradually extend toward the centrilobular region and finally replace the entire lobule. At histologic analysis, the small islands of increased attenuation very likely correspond with fibroblastic foci. Near these fibroblastic foci, an abnormal adjacency of alveolar walls was seen, suggesting alveolar collapse. In later stages, normal lung tissue is replaced by a large amount of young collagen, as seen in patients with advanced fibrosis. Conclusion Fibrosis and cyst formation in patients with IPF seem to start at the periphery of the pulmonary lobule and progressively extend toward the core of this anatomic lung unit. Evidence was found that alveolar collapse might already be present in an early stage when there is only little pulmonary fibrosis. © RSNA, 2016.

Colloid Adenocarcinoma of the Lung: CT and PET/CT Findings in Seven Patients.

PubMed

Kim, Han Kyul; Han, Joungho; Franks, Teri J; Lee, Kyung Soo; Kim, Tae Jung; Choi, Joon Young; Zo, Jaeil

2018-05-24

We aimed to assess CT and 18 F-FDG PET/CT findings of colloid adenocarcinoma of the lung in seven patients. From 2010 to 2017, seven patients with surgically proven colloid adenocarcinoma of the lung were identified. CT (both enhanced and unenhanced) and PET/CT findings were analyzed, and the imaging features were compared with histopathologic reports. Clinical and demographic features were also analyzed. In all cases except one, tumors showed low attenuation on unenhanced CT scans, ranging in attenuation from -16.5 to 20.7 HU (median, 9.2 HU). After contrast medium injection, enhancement was scant, so net enhancement ranged from 0.4 to 29.0 HU (median, 4.1 HU). All tumors had a lobulated contour. Stippled calcifications within the tumor were seen in one patient. The maximum standardized uptake value of tumors on PET/CT ranged from 1.5 to 4.5 (median, 3.5). In six of seven patients, FDG accumulation was seen in the tumor walls (n = 3, curvilinear uptake) or in both the tumor walls and tumor septa (n = 3, crisscross uptake). Six patients were alive without recurrence after a median follow-up period of 2.3 years (range, 2 months to 5 years). In one patient, who was alive at follow-up 4 years after imaging and had received adjuvant concurrent chemoradiation therapy after lobectomy, recurrent disease was detected 6 months after completion of the therapy. On CT, pulmonary colloid adenocarcinomas present as lobulated homogeneously low-attenuation tumors. At PET, curvilinear or crisscross FDG uptake is seen within the tumor where tumor cells are lining the walls or septal structures.

Thin-Section CT Features of Idiopathic Pulmonary Fibrosis Correlated with Micro-CT and Histologic Analysis

PubMed Central

Mai, Cindy; Verleden, Stijn E.; McDonough, John E.; Willems, Stijn; De Wever, Walter; Coolen, Johan; Dubbeldam, Adriana; Van Raemdonck, Dirk E.; Verbeken, Eric K.; Verleden, Geert M.; Hogg, James C.; Vanaudenaerde, Bart M.; Wuyts, Wim A.

2017-01-01

Purpose To elucidate the underlying lung changes responsible for the computed tomographic (CT) features of idiopathic pulmonary fibrosis (IPF) and to gain insight into the way IPF proceeds through the lungs and progresses over time. Materials and Methods Micro-CT studies of tissue cores obtained from explant lungs were examined and were correlated 1:1 with a CT study obtained immediately before transplantation. Samples for histologic analysis were obtained from selected cores. Results In areas with no or minimal abnormalities on CT images, small areas of increased attenuation located in or near the interlobular septa can be seen on micro-CT studies. In more involved lung areas, the number of opacities increases and opacities enlarge and approach each other along the interlobular septa, causing a fine reticular pattern on CT images. Simultaneously, air-containing structures in and around these opacities arise, corresponding with small cysts on CT images. Honeycombing is caused by a progressive increase in the number and size of these cystic structures and tissue opacities that gradually extend toward the centrilobular region and finally replace the entire lobule. At histologic analysis, the small islands of increased attenuation very likely correspond with fibroblastic foci. Near these fibroblastic foci, an abnormal adjacency of alveolar walls was seen, suggesting alveolar collapse. In later stages, normal lung tissue is replaced by a large amount of young collagen, as seen in patients with advanced fibrosis. Conclusion Fibrosis and cyst formation in patients with IPF seem to start at the periphery of the pulmonary lobule and progressively extend toward the core of this anatomic lung unit. Evidence was found that alveolar collapse might already be present in an early stage when there is only little pulmonary fibrosis. © RSNA, 2016 PMID:27715655

Behavior of Compact Toroid Injected into C-2U Confinement Vessel

NASA Astrophysics Data System (ADS)

Matsumoto, Tadafumi; Roche, T.; Allrey, I.; Sekiguchi, J.; Asai, T.; Conroy, M.; Gota, H.; Granstedt, E.; Hooper, C.; Kinley, J.; Valentine, T.; Waggoner, W.; Binderbauer, M.; Tajima, T.; the TAE Team

2016-10-01

The compact toroid (CT) injector system has been developed for particle refueling on the C-2U device. A CT is formed by a magnetized coaxial plasma gun (MCPG) and the typical ejected CT/plasmoid parameters are as follows: average velocity 100 km/s, average electron density 1.9 ×1015 cm-3, electron temperature 30-40 eV, mass 12 μg . To refuel particles into FC plasma the CT must penetrate the transverse magnetic field that surrounds the FRC. The kinetic energy density of the CT should be higher than magnetic energy density of the axial magnetic field, i.e., ρv2 / 2 >=B2 / 2μ0 , where ρ, v, and B are mass density, velocity, and surrounded magnetic field, respectively. Also, the penetrated CT's trajectory is deflected by the transverse magnetic field (Bz 1 kG). Thus, we have to estimate CT's energy and track the CT trajectory inside the magnetic field, for which we adopted a fast-framing camera on C-2U: framing rate is up to 1.25 MHz for 120 frames. By employing the camera we clearly captured the CT/plasmoid trajectory. Comparisons between the fast-framing camera and some other diagnostics as well as CT injection results on C-2U will be presented.

SedCT: MATLAB™ tools for standardized and quantitative processing of sediment core computed tomography (CT) data collected using a medical CT scanner

NASA Astrophysics Data System (ADS)

Reilly, B. T.; Stoner, J. S.; Wiest, J.

2017-08-01

Computed tomography (CT) of sediment cores allows for high-resolution images, three-dimensional volumes, and down core profiles. These quantitative data are generated through the attenuation of X-rays, which are sensitive to sediment density and atomic number, and are stored in pixels as relative gray scale values or Hounsfield units (HU). We present a suite of MATLAB™ tools specifically designed for routine sediment core analysis as a means to standardize and better quantify the products of CT data collected on medical CT scanners. SedCT uses a graphical interface to process Digital Imaging and Communications in Medicine (DICOM) files, stitch overlapping scanned intervals, and create down core HU profiles in a manner robust to normal coring imperfections. Utilizing a random sampling technique, SedCT reduces data size and allows for quick processing on typical laptop computers. SedCTimage uses a graphical interface to create quality tiff files of CT slices that are scaled to a user-defined HU range, preserving the quantitative nature of CT images and easily allowing for comparison between sediment cores with different HU means and variance. These tools are presented along with examples from lacustrine and marine sediment cores to highlight the robustness and quantitative nature of this method.

Predicting Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer with Textural Features Derived from Pretreatment 18F-FDG PET/CT Imaging.

PubMed

Beukinga, Roelof J; Hulshoff, Jan B; van Dijk, Lisanne V; Muijs, Christina T; Burgerhof, Johannes G M; Kats-Ugurlu, Gursah; Slart, Riemer H J A; Slump, Cornelis H; Mul, Véronique E M; Plukker, John Th M

2017-05-01

Adequate prediction of tumor response to neoadjuvant chemoradiotherapy (nCRT) in esophageal cancer (EC) patients is important in a more personalized treatment. The current best clinical method to predict pathologic complete response is SUV max in 18 F-FDG PET/CT imaging. To improve the prediction of response, we constructed a model to predict complete response to nCRT in EC based on pretreatment clinical parameters and 18 F-FDG PET/CT-derived textural features. Methods: From a prospectively maintained single-institution database, we reviewed 97 consecutive patients with locally advanced EC and a pretreatment 18 F-FDG PET/CT scan between 2009 and 2015. All patients were treated with nCRT (carboplatin/paclitaxel/41.4 Gy) followed by esophagectomy. We analyzed clinical, geometric, and pretreatment textural features extracted from both 18 F-FDG PET and CT. The current most accurate prediction model with SUV max as a predictor variable was compared with 6 different response prediction models constructed using least absolute shrinkage and selection operator regularized logistic regression. Internal validation was performed to estimate the model's performances. Pathologic response was defined as complete versus incomplete response (Mandard tumor regression grade system 1 vs. 2-5). Results: Pathologic examination revealed 19 (19.6%) complete and 78 (80.4%) incomplete responders. Least absolute shrinkage and selection operator regularization selected the clinical parameters: histologic type and clinical T stage, the 18 F-FDG PET-derived textural feature long run low gray level emphasis, and the CT-derived textural feature run percentage. Introducing these variables to a logistic regression analysis showed areas under the receiver-operating-characteristic curve (AUCs) of 0.78 compared with 0.58 in the SUV max model. The discrimination slopes were 0.17 compared with 0.01, respectively. After internal validation, the AUCs decreased to 0.74 and 0.54, respectively. Conclusion: The predictive values of the constructed models were superior to the standard method (SUV max ). These results can be considered as an initial step in predicting tumor response to nCRT in locally advanced EC. Further research in refining the predictive value of these models is needed to justify omission of surgery. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

[Quantitative Evaluation of Metal Artifacts on CT Images on the Basis of Statistics of Extremes].

PubMed

Kitaguchi, Shigetoshi; Imai, Kuniharu; Ueda, Suguru; Hashimoto, Naomi; Hattori, Shouta; Saika, Takahiro; Ono, Yoshifumi

2016-05-01

It is well-known that metal artifacts have a harmful effect on the image quality of computed tomography (CT) images. However, the physical property remains still unknown. In this study, we investigated the relationship between metal artifacts and tube currents using statistics of extremes. A commercially available phantom for measuring CT dose index 160 mm in diameter was prepared and a brass rod 13 mm in diameter was placed at the centerline of the phantom. This phantom was used as a target object to evaluate metal artifacts and was scanned using an area detector CT scanner with various tube currents under a constant tube voltage of 120 kV. Sixty parallel line segments with a length of 100 pixels were placed to cross metal artifacts on CT images and the largest difference between two adjacent CT values in each of 60 CT value profiles of these line segments was employed as a feature variable for measuring metal artifacts; these feature variables were analyzed on the basis of extreme value theory. The CT value variation induced by metal artifacts was statistically characterized by Gumbel distribution, which was one of the extreme value distributions; namely, metal artifacts have the same statistical characteristic as streak artifacts. Therefore, Gumbel evaluation method makes it possible to analyze not only streak artifacts but also metal artifacts. Furthermore, the location parameter in Gumbel distribution was shown to be in inverse proportion to the square root of a tube current. This result suggested that metal artifacts have the same dose dependence as image noises.

Efficient and robust model-to-image alignment using 3D scale-invariant features.

PubMed

Toews, Matthew; Wells, William M

2013-04-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. Copyright © 2012 Elsevier B.V. All rights reserved.

Efficient and Robust Model-to-Image Alignment using 3D Scale-Invariant Features

PubMed Central

Toews, Matthew; Wells, William M.

2013-01-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a-posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. PMID:23265799

SU-E-J-113: Effects of Deformable Registration On First-Order Texture Maps Calculated From Thoracic Lung CT Scans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, C; Cunliffe, A; Al-Hallaq, H

Purpose: To determine the stability of eight first-order texture features following the deformable registration of serial computed tomography (CT) scans. Methods: CT scans at two different time points from 10 patients deemed to have no lung abnormalities by a radiologist were collected. Following lung segmentation using an in-house program, texture maps were calculated from 32×32-pixel regions of interest centered at every pixel in the lungs. The texture feature value of the ROI was assigned to the center pixel of the ROI in the corresponding location of the texture map. Pixels in the square ROI not contained within the segmented lungmore » were not included in the calculation. To quantify the agreement between ROI texture features in corresponding pixels of the baseline and follow-up texture maps, the Fraunhofer MEVIS EMPIRE10 deformable registration algorithm was used to register the baseline and follow-up scans. Bland-Altman analysis was used to compare registered scan pairs by computing normalized bias (nBias), defined as the feature value change normalized to the mean feature value, and normalized range of agreement (nRoA), defined as the range spanned by the 95% limits of agreement normalized to the mean feature value. Results: Each patient’s scans contained between 6.8–15.4 million ROIs. All of the first-order features investigated were found to have an nBias value less than 0.04% and an nRoA less than 19%, indicating that the variability introduced by deformable registration was low. Conclusion: The eight first-order features investigated were found to be registration stable. Changes in CT texture maps could allow for temporal-spatial evaluation of the evolution of lung abnormalities relating to a variety of diseases on a patient-by-patient basis. SGA and HA receives royalties and licensing fees through the University of Chicago for computer-aided diagnosis technology. Research reported in this publication was supported by the National Institute Of General Medical Sciences of the National Institutes of Health under Award Number R25GM109439.« less

Knowledge discovery for Deep Phenotyping serious mental illness from Electronic Mental Health records.

PubMed

Jackson, Richard; Patel, Rashmi; Velupillai, Sumithra; Gkotsis, George; Hoyle, David; Stewart, Robert

2018-01-01

Background: Deep Phenotyping is the precise and comprehensive analysis of phenotypic features in which the individual components of the phenotype are observed and described. In UK mental health clinical practice, most clinically relevant information is recorded as free text in the Electronic Health Record, and offers a granularity of information beyond what is expressed in most medical knowledge bases. The SNOMED CT nomenclature potentially offers the means to model such information at scale, yet given a sufficiently large body of clinical text collected over many years, it is difficult to identify the language that clinicians favour to express concepts. Methods: By utilising a large corpus of healthcare data, we sought to make use of semantic modelling and clustering techniques to represent the relationship between the clinical vocabulary of internationally recognised SMI symptoms and the preferred language used by clinicians within a care setting. We explore how such models can be used for discovering novel vocabulary relevant to the task of phenotyping Serious Mental Illness (SMI) with only a small amount of prior knowledge.  Results: 20 403 terms were derived and curated via a two stage methodology. The list was reduced to 557 putative concepts based on eliminating redundant information content. These were then organised into 9 distinct categories pertaining to different aspects of psychiatric assessment. 235 concepts were found to be expressions of putative clinical significance. Of these, 53 were identified having novel synonymy with existing SNOMED CT concepts. 106 had no mapping to SNOMED CT. Conclusions: We demonstrate a scalable approach to discovering new concepts of SMI symptomatology based on real-world clinical observation. Such approaches may offer the opportunity to consider broader manifestations of SMI symptomatology than is typically assessed via current diagnostic frameworks, and create the potential for enhancing nomenclatures such as SNOMED CT based on real-world expressions.

Micro-CT features of intermediate gunshot wounds severely damaged by fire.

PubMed

Fais, Paolo; Giraudo, Chiara; Boscolo-Berto, Rafael; Amagliani, Alessandro; Miotto, Diego; Feltrin, Giampietro; Viel, Guido; Ferrara, S Davide; Cecchetto, Giovanni

2013-03-01

Incineration or extensive burning of the body, causing changes in the content and distribution of fluids, fixation and shrinking processes of tissues, can alter the typical macroscopic and microscopic characteristics of firearm wounds, hampering or at least complicating the reconstruction of gunshot fatalities. The present study aims at evaluating the potential role of micro-computed tomography (micro-CT) for detecting and quantifying gunshot residue (GSR) particles in experimentally produced intermediate-range gunshot wounds severely damaged by fire. Eighteen experimental shootings were performed on 18 sections of human calves surgically amputated for medical reasons at three different firing distances (5, 15 and 30 cm). Six stab wounds produced with an ice pick were used as controls. Each calf section underwent a charring cycle, being placed in a wood-burning stove for 4 min at a temperature of 400 °C. At visual inspection, the charred entrance wounds could not be differentiated from the exit lesions and the stab wounds. On the contrary, micro-CT analysis showed the presence of GSR particles in all burnt entrance gunshot wounds, while GSR was absent in the exit and stab wounds. The GSR deposits of the firearm lesions inflicted at very close distance (5 cm) were mainly constituted of huge particles (diameter >150 μm) with an irregular shape and well-delineated edges; at greater distances (15 and 30 cm), agglomerates of tiny radiopaque particles scattered in the epidermis and dermis layers were evident. Statistical analysis demonstrated that also in charred firearm wounds the amount of GSR roughly correlates with the distance from which the gun was fired. The obtained results suggest that micro-CT analysis can be a valid screening tool for identifying entrance gunshot wounds and for differentiating firearm wounds from sharp-force injuries in bodies severely damaged by fire.

Quantitative computed tomography measurements of emphysema for diagnosing asthma-chronic obstructive pulmonary disease overlap syndrome

PubMed Central

Xie, Mengshuang; Wang, Wei; Dou, Shuang; Cui, Liwei; Xiao, Wei

2016-01-01

Background The diagnostic criteria of asthma–COPD overlap syndrome (ACOS) are controversial. Emphysema is characteristic of COPD and usually does not exist in typical asthma patients. Emphysema in patients with asthma suggests the coexistence of COPD. Quantitative computed tomography (CT) allows repeated evaluation of emphysema noninvasively. We investigated the value of quantitative CT measurements of emphysema in the diagnosis of ACOS. Methods This study included 404 participants; 151 asthma patients, 125 COPD patients, and 128 normal control subjects. All the participants underwent pulmonary function tests and a high-resolution CT scan. Emphysema measurements were taken with an Airway Inspector software. The asthma patients were divided into high and low emphysema index (EI) groups based on the percentage of low attenuation areas less than −950 Hounsfield units. The characteristics of asthma patients with high EI were compared with those having low EI or COPD. Results The normal value of percentage of low attenuation areas less than −950 Hounsfield units in Chinese aged >40 years was 2.79%±2.37%. COPD patients indicated more severe emphysema and more upper-zone-predominant distribution of emphysema than asthma patients or controls. Thirty-two (21.2%) of the 151 asthma patients had high EI. Compared with asthma patients with low EI, those with high EI were significantly older, more likely to be male, had more pack-years of smoking, had more upper-zone-predominant distribution of emphysema, and had greater airflow limitation. There were no significant differences in sex ratios, pack-years of smoking, airflow limitation, or emphysema distribution between asthma patients with high EI and COPD patients. A greater number of acute exacerbations were seen in asthma patients with high EI compared with those with low EI or COPD. Conclusion Asthma patients with high EI fulfill the features of ACOS, as described in the Global Initiative for Asthma and Global Initiative for Chronic Obstructive Lung Disease guidelines. Quantitative CT measurements of emphysema may help in diagnosing ACOS. PMID:27226711

Knowledge discovery for Deep Phenotyping serious mental illness from Electronic Mental Health records

PubMed Central

Jackson, Richard; Patel, Rashmi; Velupillai, Sumithra; Gkotsis, George; Hoyle, David; Stewart, Robert

2018-01-01

Background: Deep Phenotyping is the precise and comprehensive analysis of phenotypic features in which the individual components of the phenotype are observed and described. In UK mental health clinical practice, most clinically relevant information is recorded as free text in the Electronic Health Record, and offers a granularity of information beyond what is expressed in most medical knowledge bases. The SNOMED CT nomenclature potentially offers the means to model such information at scale, yet given a sufficiently large body of clinical text collected over many years, it is difficult to identify the language that clinicians favour to express concepts. Methods: By utilising a large corpus of healthcare data, we sought to make use of semantic modelling and clustering techniques to represent the relationship between the clinical vocabulary of internationally recognised SMI symptoms and the preferred language used by clinicians within a care setting. We explore how such models can be used for discovering novel vocabulary relevant to the task of phenotyping Serious Mental Illness (SMI) with only a small amount of prior knowledge.  Results: 20 403 terms were derived and curated via a two stage methodology. The list was reduced to 557 putative concepts based on eliminating redundant information content. These were then organised into 9 distinct categories pertaining to different aspects of psychiatric assessment. 235 concepts were found to be expressions of putative clinical significance. Of these, 53 were identified having novel synonymy with existing SNOMED CT concepts. 106 had no mapping to SNOMED CT. Conclusions: We demonstrate a scalable approach to discovering new concepts of SMI symptomatology based on real-world clinical observation. Such approaches may offer the opportunity to consider broader manifestations of SMI symptomatology than is typically assessed via current diagnostic frameworks, and create the potential for enhancing nomenclatures such as SNOMED CT based on real-world expressions. PMID:29899974

Handwriting in children with ADHD.

PubMed

Langmaid, Rebecca A; Papadopoulos, Nicole; Johnson, Beth P; Phillips, James G; Rinehart, Nicole J

2014-08-01

Children with ADHD-combined type (ADHD-CT) display fine and gross motor problems, often expressed as handwriting difficulties. This study aimed to kinematically characterize the handwriting of children with ADHD using a cursive letter l's task. In all, 28 boys (7-12 years), 14 ADHD-CT and 14 typically developing (TD), without developmental coordination disorder (DCD) or comorbid autism, wrote a series of four cursive letter l's using a graphics tablet and stylus. Children with ADHD-CT had more inconsistent writing size than did TD controls. In addition, ADHD-CT symptom severity, specifically inattention, predicted poorer handwriting outcomes. In a sample of children with ADHD-CT who do not have DCD or autism, subtle handwriting differences were evident. It was concluded that handwriting might be impaired in children with ADHD in a manner dependent on symptom severity. This may reflect reports of underlying motor impairment in ADHD. © 2011 SAGE Publications.

Dosimetry in MARS spectral CT: TOPAS Monte Carlo simulations and ion chamber measurements.

PubMed

Lu, Gray; Marsh, Steven; Damet, Jerome; Carbonez, Pierre; Laban, John; Bateman, Christopher; Butler, Anthony; Butler, Phil

2017-06-01

Spectral computed tomography (CT) is an up and coming imaging modality which shows great promise in revealing unique diagnostic information. Because this imaging modality is based on X-ray CT, it is of utmost importance to study the radiation dose aspects of its use. This study reports on the implementation and evaluation of a Monte Carlo simulation tool using TOPAS for estimating dose in a pre-clinical spectral CT scanner known as the MARS scanner. Simulated estimates were compared with measurements from an ionization chamber. For a typical MARS scan, TOPAS estimated for a 30 mm diameter cylindrical phantom a CT dose index (CTDI) of 29.7 mGy; CTDI was measured by ion chamber to within 3% of TOPAS estimates. Although further development is required, our investigation of TOPAS for estimating MARS scan dosimetry has shown its potential for further study of spectral scanning protocols and dose to scanned objects.

Differential effects of anxiety and depressive symptoms on working memory components in children and adolescents with ADHD combined type and ADHD inattentive type.

PubMed

Ferrin, Maite; Vance, Alasdair

2014-12-01

Working memory (WM) deficits have been shown to be associated with core ADHD symptoms, worse academic achievement and peer-relationship problems. Internalizing symptoms, such as anxiety and depression, have also been associated with impaired WM performance. However, the association of anxiety and depression and WM performance remains unclear for children and adolescents with ADHD. Further, it is unknown how these comorbid conditions might affect WM performance in the two main ADHD subtypes. The association of anxiety and depression and the specific components of spatial (SWM) and verbal working memory (VWM) were examined in 303 children and adolescents with ADHD, combined type (ADHD-CT) and 77 ADHD, inattentive type (ADHD-IA) compared to 128 age- and gender-matched typically developing participants. The relationship between anxiety and depression and WM was assessed using multiple linear regression analyses and separate simple regression analyses. Higher levels of anxiety/depression were associated with (1) increased between-search errors in the typically developing participants alone, (2) a better strategy performance in the ADHD-CT group, and (3) a better spatial span performance in the ADHD-IA group. VWM was equally impaired in the ADHD-CT and ADHD-IA groups, independent of the levels of anxiety and depression. The results suggest that the effects of internalizing symptoms on WM differ in typically developing children and adolescents compared to those with ADHD. Further, high levels of anxiety and depression modified WM performance differently according to the specific ADHD subtypes. This might help explain contradictory findings observed in previous studies of mixed samples of participants with ADHD-CT and ADHD-IA.

A study on using texture analysis methods for identifying lobar fissure regions in isotropic CT images.

PubMed

Wei, Q; Hu, Y

2009-01-01

The major hurdle for segmenting lung lobes in computed tomographic (CT) images is to identify fissure regions, which encase lobar fissures. Accurate identification of these regions is difficult due to the variable shape and appearance of the fissures, along with the low contrast and high noise associated with CT images. This paper studies the effectiveness of two texture analysis methods - the gray level co-occurrence matrix (GLCM) and the gray level run length matrix (GLRLM) - in identifying fissure regions from isotropic CT image stacks. To classify GLCM and GLRLM texture features, we applied a feed-forward back-propagation neural network and achieved the best classification accuracy utilizing 16 quantized levels for computing the GLCM and GLRLM texture features and 64 neurons in the input/hidden layers of the neural network. Tested on isotropic CT image stacks of 24 patients with the pathologic lungs, we obtained accuracies of 86% and 87% for identifying fissure regions using the GLCM and GLRLM methods, respectively. These accuracies compare favorably with surgeons/radiologists' accuracy of 80% for identifying fissure regions in clinical settings. This shows promising potential for segmenting lung lobes using the GLCM and GLRLM methods.

Imaging diagnosis--temporomandibular joint dysplasia in a Basset Hound.

PubMed

Lerer, Assaf; Chalmers, Heather J; Moens, Noel M M; Mackenzie, Shawn D; Kry, Kristin

2014-01-01

A 5-month-old intact male Basset Hound presented for evaluation of pain and crepitation during manipulation of the temporomandibular joint, worse on the right side. A computed tomography (CT) scan of the head was performed. The CT images demonstrated the osseous features of temporomandibular joint dysplasia and facilitated a 3D reconstruction, which allowed better visualization of the dysplastic features. The patient responded to conservative management with a tape muzzle with no recurrence reported by the owner 6 months after presentation. © 2013 American College of Veterinary Radiology.

TBIdoc: 3D content-based CT image retrieval system for traumatic brain injury

NASA Astrophysics Data System (ADS)

Li, Shimiao; Gong, Tianxia; Wang, Jie; Liu, Ruizhe; Tan, Chew Lim; Leong, Tze Yun; Pang, Boon Chuan; Lim, C. C. Tchoyoson; Lee, Cheng Kiang; Tian, Qi; Zhang, Zhuo

2010-03-01

Traumatic brain injury (TBI) is a major cause of death and disability. Computed Tomography (CT) scan is widely used in the diagnosis of TBI. Nowadays, large amount of TBI CT data is stacked in the hospital radiology department. Such data and the associated patient information contain valuable information for clinical diagnosis and outcome prediction. However, current hospital database system does not provide an efficient and intuitive tool for doctors to search out cases relevant to the current study case. In this paper, we present the TBIdoc system: a content-based image retrieval (CBIR) system which works on the TBI CT images. In this web-based system, user can query by uploading CT image slices from one study, retrieval result is a list of TBI cases ranked according to their 3D visual similarity to the query case. Specifically, cases of TBI CT images often present diffuse or focal lesions. In TBIdoc system, these pathological image features are represented as bin-based binary feature vectors. We use the Jaccard-Needham measure as the similarity measurement. Based on these, we propose a 3D similarity measure for computing the similarity score between two series of CT slices. nDCG is used to evaluate the system performance, which shows the system produces satisfactory retrieval results. The system is expected to improve the current hospital data management in TBI and to give better support for the clinical decision-making process. It may also contribute to the computer-aided education in TBI.

Isolated Main Pancreatic Duct Dilatation: CT Differentiation Between Benign and Malignant Causes.

PubMed

Kim, Se Woo; Kim, Se Hyung; Lee, Dong Ho; Lee, Sang Min; Kim, Yeon Soo; Jang, Jin Young; Han, Joon Koo

2017-11-01

The purpose of this study is to retrospectively evaluate the differential CT features of isolated benign and malignant main pancreatic duct (MPD) dilatation and to investigate whether the diagnostic performance of radiologists can be improved with knowledge of these differential CT features. Forty-one patients who had isolated MPD dilatation without any visible mass on CT from January 2000 to October 2016 were retrospectively enrolled in the study. Two radiologists reviewed CT images in consensus for the location, shape (smooth vs abrupt), length of transition, dilated pancreatic duct (PD) diameter, presence of duct penetrating sign, parenchymal atrophy, attenuation difference, associated pancreatitis, calcification, PD or common bile duct (CBD) enhancement, and perilesional cyst. The chi-square test, Fisher exact test, and t test were used to find the differential CT features of benign and malignant MPD dilatation. Two successive review sessions for differentiation between the two disease entities were then independently performed by three other reviewers with differing expertise, with the use of a 5-point confidence scale. The first session provided no information for differentiation; however, reviewers were aware of the results of univariate analyses in the second session. The diagnostic performance of the radiologists was evaluated using a pairwise comparison of ROC curves. A total of 19 benign and 22 malignant MPD dilatations were identified. In patients with benign MPD dilatation, transition areas were frequently located in the head (57.9% [11/19] vs 13.6% [3/22], p = 0.003) and showed significantly shorter (< 6.1 mm) (78.9% [15/19] vs 9.1% [2/22], p < 0.0001) and smooth transition (89.5% [17/19] vs 9.1% [2/22], p < 0.0001). Duct penetrating sign was exclusively observed in patients with benign MPD dilatation (73.7% [14/19] vs 0% [0/22], p < 0.0001). In contrast, malignant MPD dilatation frequently was accompanied by attenuation difference (63.6% [14/22] vs 10.5% [2/19], p = 0.001) and associated PD or CBD enhancement (36.4% [8/22] vs 0% [0/19], p = 0.003). The AUC values of three reviewers significantly increased from 0.653, 0.587, and 0.884 to 0.864, 0.964, and 0.908, respectively, with knowledge of significant CT features (p = 0.013, p < 0.0001, and p = 0.701, respectively). Distal, long (≥ 6.1 mm), and abrupt transition, the absence of duct penetrating sign, and the presence of attenuation difference and PD or CBD enhancement were highly suggestive CT findings for differentiation of malignant from benign MPD dilatation. The diagnostic performance of radiologists with regard to differentiation was significantly improved with knowledge of these highly suggestive CT criteria.

SU-F-R-31: Identification of Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induced Lung Disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choi, W; Riyahi, S; Lu, W

Purpose: Normal lung CT texture features have been used for the prediction of radiation-induced lung disease (radiation pneumonitis and radiation fibrosis). For these features to be clinically useful, they need to be relatively invariant (robust) to tumor size and not correlated with normal lung volume. Methods: The free-breathing CTs of 14 lung SBRT patients were studied. Different sizes of GTVs were simulated with spheres placed at the upper lobe and lower lobe respectively in the normal lung (contralateral to tumor). 27 texture features (9 from intensity histogram, 8 from grey-level co-occurrence matrix [GLCM] and 10 from grey-level run-length matrix [GLRM])more » were extracted from [normal lung-GTV]. To measure the variability of a feature F, the relative difference D=|Fref -Fsim|/Fref*100% was calculated, where Fref was for the entire normal lung and Fsim was for [normal lung-GTV]. A feature was considered as robust if the largest non-outlier (Q3+1.5*IQR) D was less than 5%, and considered as not correlated with normal lung volume when their Pearson correlation was lower than 0.50. Results: Only 11 features were robust. All first-order intensity-histogram features (mean, max, etc.) were robust, while most higher-order features (skewness, kurtosis, etc.) were unrobust. Only two of the GLCM and four of the GLRM features were robust. Larger GTV resulted greater feature variation, this was particularly true for unrobust features. All robust features were not correlated with normal lung volume while three unrobust features showed high correlation. Excessive variations were observed in two low grey-level run features and were later identified to be from one patient with local lung diseases (atelectasis) in the normal lung. There was no dependence on GTV location. Conclusion: We identified 11 robust normal lung CT texture features that can be further examined for the prediction of radiation-induced lung disease. Interestingly, low grey-level run features identified normal lung diseases. This work was supported in part by the National Cancer Institute Grants R01CA172638.« less

Investigating CT to CBCT image registration for head and neck proton therapy as a tool for daily dose recalculation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Landry, Guillaume, E-mail: g.landry@lmu.de; Nijhuis, Reinoud; Thieke, Christian

2015-03-15

Purpose: Intensity modulated proton therapy (IMPT) of head and neck (H and N) cancer patients may be improved by plan adaptation. The decision to adapt the treatment plan based on a dose recalculation on the current anatomy requires a diagnostic quality computed tomography (CT) scan of the patient. As gantry-mounted cone beam CT (CBCT) scanners are currently being offered by vendors, they may offer daily or weekly updates of patient anatomy. CBCT image quality may not be sufficient for accurate proton dose calculation and it is likely necessary to perform CBCT CT number correction. In this work, the authors investigatedmore » deformable image registration (DIR) of the planning CT (pCT) to the CBCT to generate a virtual CT (vCT) to be used for proton dose recalculation. Methods: Datasets of six H and N cancer patients undergoing photon intensity modulated radiation therapy were used in this study to validate the vCT approach. Each dataset contained a CBCT acquired within 3 days of a replanning CT (rpCT), in addition to a pCT. The pCT and rpCT were delineated by a physician. A Morphons algorithm was employed in this work to perform DIR of the pCT to CBCT following a rigid registration of the two images. The contours from the pCT were deformed using the vector field resulting from DIR to yield a contoured vCT. The DIR accuracy was evaluated with a scale invariant feature transform (SIFT) algorithm comparing automatically identified matching features between vCT and CBCT. The rpCT was used as reference for evaluation of the vCT. The vCT and rpCT CT numbers were converted to stopping power ratio and the water equivalent thickness (WET) was calculated. IMPT dose distributions from treatment plans optimized on the pCT were recalculated with a Monte Carlo algorithm on the rpCT and vCT for comparison in terms of gamma index, dose volume histogram (DVH) statistics as well as proton range. The DIR generated contours on the vCT were compared to physician-drawn contours on the rpCT. Results: The DIR accuracy was better than 1.4 mm according to the SIFT evaluation. The mean WET differences between vCT (pCT) and rpCT were below 1 mm (2.6 mm). The amount of voxels passing 3%/3 mm gamma criteria were above 95% for the vCT vs rpCT. When using the rpCT contour set to derive DVH statistics from dose distributions calculated on the rpCT and vCT the differences, expressed in terms of 30 fractions of 2 Gy, were within [−4, 2 Gy] for parotid glands (D{sub mean}), spinal cord (D{sub 2%}), brainstem (D{sub 2%}), and CTV (D{sub 95%}). When using DIR generated contours for the vCT, those differences ranged within [−8, 11 Gy]. Conclusions: In this work, the authors generated CBCT based stopping power distributions using DIR of the pCT to a CBCT scan. DIR accuracy was below 1.4 mm as evaluated by the SIFT algorithm. Dose distributions calculated on the vCT agreed well to those calculated on the rpCT when using gamma index evaluation as well as DVH statistics based on the same contours. The use of DIR generated contours introduced variability in DVH statistics.« less

SU-F-R-07: Radiomics of CT Features and Associations and Correlation with Outcomes Following Lung SBRT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schreibmann, E; Iwinski Sutter, A; Whitaker, D

Objective: To investigate the prognostic significance of image gradients and in predicting clinical outcomes in a patients with non-small cell lung cancer treated with stereotactic body radiotherapy (SBRT) on 71 patients with 83 treated lesions. Methods: The records of patients treated with lung SBRT were retrospectively reviewed. When applicable, SBRT target volumes were modified to exclude any overlap with pleura, chestwall, or mediastinum. The ITK software package was utilized to generate quantitative measures of image intensity, inhomogeneity, shape morphology and first and second-order CT textures. Multivariate and univariate models containing CT features were generated to assess associations with clinicopathologic factors.more » Results: On univariate analysis, tumor size (HR 0.54, p=0.045) sumHU (HR 0.31, p=0.044) and short run grey level emphasis STD (HR 0.22, p=0.019) were associated with regional failure-free survival; meanHU (HR 0.30, p=0.035), long run emphasis (HR 0.21, p=0.011) and long run low grey level emphasis (HR 0.14, p=0.005) was associated with distant failure-free survival (DFFS). No features were significant on multivariate modeling however long run low grey level emphasis had a hazard ratio of 0.12 (p=0.061) for DFFS. Adenocarcinoma and squamous cell carcinoma differed with respect to long run emphasis STD (p=0.024), short run low grey level emphasis STD (p<0.001), and long run low grey level emphasis STD (p=0.024). Multivariate modeling of texture features associated with tumor histology was used to estimate histologies of 18 lesions treated without histologic confirmation. Of these, MVA suggested the same histology as a prior metachronous lung malignancy in 3/7 patients. Conclusion: Extracting radiomics features on clinical datasets was feasible with the ITK package with minimal effort to identify pre-treatment quantitative CT features with prognostic factors for distant control after lung SBRT.« less

Fast algorithm for probabilistic bone edge detection (FAPBED)

NASA Astrophysics Data System (ADS)

Scepanovic, Danilo; Kirshtein, Joshua; Jain, Ameet K.; Taylor, Russell H.

2005-04-01

The registration of preoperative CT to intra-operative reality systems is a crucial step in Computer Assisted Orthopedic Surgery (CAOS). The intra-operative sensors include 3D digitizers, fiducials, X-rays and Ultrasound (US). FAPBED is designed to process CT volumes for registration to tracked US data. Tracked US is advantageous because it is real time, noninvasive, and non-ionizing, but it is also known to have inherent inaccuracies which create the need to develop a framework that is robust to various uncertainties, and can be useful in US-CT registration. Furthermore, conventional registration methods depend on accurate and absolute segmentation. Our proposed probabilistic framework addresses the segmentation-registration duality, wherein exact segmentation is not a prerequisite to achieve accurate registration. In this paper, we develop a method for fast and automatic probabilistic bone surface (edge) detection in CT images. Various features that influence the likelihood of the surface at each spatial coordinate are combined using a simple probabilistic framework, which strikes a fair balance between a high-level understanding of features in an image and the low-level number crunching of standard image processing techniques. The algorithm evaluates different features for detecting the probability of a bone surface at each voxel, and compounds the results of these methods to yield a final, low-noise, probability map of bone surfaces in the volume. Such a probability map can then be used in conjunction with a similar map from tracked intra-operative US to achieve accurate registration. Eight sample pelvic CT scans were used to extract feature parameters and validate the final probability maps. An un-optimized fully automatic Matlab code runs in five minutes per CT volume on average, and was validated by comparison against hand-segmented gold standards. The mean probability assigned to nonzero surface points was 0.8, while nonzero non-surface points had a mean value of 0.38 indicating clear identification of surface points on average. The segmentation was also sufficiently crisp, with a full width at half maximum (FWHM) value of 1.51 voxels.

Phase contrast imaging X-ray computed tomography: quantitative characterization of human patellar cartilage matrix with topological and geometrical features

NASA Astrophysics Data System (ADS)

Nagarajan, Mahesh B.; Coan, Paola; Huber, Markus B.; Diemoz, Paul C.; Wismüller, Axel

2014-03-01

Current assessment of cartilage is primarily based on identification of indirect markers such as joint space narrowing and increased subchondral bone density on x-ray images. In this context, phase contrast CT imaging (PCI-CT) has recently emerged as a novel imaging technique that allows a direct examination of chondrocyte patterns and their correlation to osteoarthritis through visualization of cartilage soft tissue. This study investigates the use of topological and geometrical approaches for characterizing chondrocyte patterns in the radial zone of the knee cartilage matrix in the presence and absence of osteoarthritic damage. For this purpose, topological features derived from Minkowski Functionals and geometric features derived from the Scaling Index Method (SIM) were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of healthy and osteoarthritic specimens of human patellar cartilage. The extracted features were then used in a machine learning task involving support vector regression to classify ROIs as healthy or osteoarthritic. Classification performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). The best classification performance was observed with high-dimensional geometrical feature vectors derived from SIM (0.95 ± 0.06) which outperformed all Minkowski Functionals (p < 0.001). These results suggest that such quantitative analysis of chondrocyte patterns in human patellar cartilage matrix involving SIM-derived geometrical features can distinguish between healthy and osteoarthritic tissue with high accuracy.

Apply radiomics approach for early stage prognostic evaluation of ovarian cancer patients: a preliminary study

NASA Astrophysics Data System (ADS)

Danala, Gopichandh; Wang, Yunzhi; Thai, Theresa; Gunderson, Camille; Moxley, Katherine; Moore, Kathleen; Mannel, Robert; Liu, Hong; Zheng, Bin; Qiu, Yuchen

2017-03-01

Predicting metastatic tumor response to chemotherapy at early stage is critically important for improving efficacy of clinical trials of testing new chemotherapy drugs. However, using current response evaluation criteria in solid tumors (RECIST) guidelines only yields a limited accuracy to predict tumor response. In order to address this clinical challenge, we applied Radiomics approach to develop a new quantitative image analysis scheme, aiming to accurately assess the tumor response to new chemotherapy treatment, for the advanced ovarian cancer patients. During the experiment, a retrospective dataset containing 57 patients was assembled, each of which has two sets of CT images: pre-therapy and 4-6 week follow up CT images. A Radiomics based image analysis scheme was then applied on these images, which is composed of three steps. First, the tumors depicted on the CT images were segmented by a hybrid tumor segmentation scheme. Then, a total of 115 features were computed from the segmented tumors, which can be grouped as 1) volume based features; 2) density based features; and 3) wavelet features. Finally, an optimal feature cluster was selected based on the single feature performance and an equal-weighed fusion rule was applied to generate the final predicting score. The results demonstrated that the single feature achieved an area under the receiver operating characteristic curve (AUC) of 0.838+/-0.053. This investigation demonstrates that the Radiomic approach may have the potential in the development of high accuracy predicting model for early stage prognostic assessment of ovarian cancer patients.

Chromosome Territories

PubMed Central

Cremer, Thomas; Cremer, Marion

2010-01-01

Chromosome territories (CTs) constitute a major feature of nuclear architecture. In a brief statement, the possible contribution of nuclear architecture studies to the field of epigenomics is considered, followed by a historical account of the CT concept and the final compelling experimental evidence of a territorial organization of chromosomes in all eukaryotes studied to date. Present knowledge of nonrandom CT arrangements, of the internal CT architecture, and of structural interactions with other CTs is provided as well as the dynamics of CT arrangements during cell cycle and postmitotic terminal differentiation. The article concludes with a discussion of open questions and new experimental strategies to answer them. PMID:20300217

On the feasibility of automatically selecting similar patients in highly individualized radiotherapy dose reconstruction for historic data of pediatric cancer survivors.

PubMed

Virgolin, Marco; van Dijk, Irma W E M; Wiersma, Jan; Ronckers, Cécile M; Witteveen, Cees; Bel, Arjan; Alderliesten, Tanja; Bosman, Peter A N

2018-04-01

The aim of this study is to establish the first step toward a novel and highly individualized three-dimensional (3D) dose distribution reconstruction method, based on CT scans and organ delineations of recently treated patients. Specifically, the feasibility of automatically selecting the CT scan of a recently treated childhood cancer patient who is similar to a given historically treated child who suffered from Wilms' tumor is assessed. A cohort of 37 recently treated children between 2- and 6-yr old are considered. Five potential notions of ground-truth similarity are proposed, each focusing on different anatomical aspects. These notions are automatically computed from CT scans of the abdomen and 3D organ delineations (liver, spleen, spinal cord, external body contour). The first is based on deformable image registration, the second on the Dice similarity coefficient, the third on the Hausdorff distance, the fourth on pairwise organ distances, and the last is computed by means of the overlap volume histogram. The relationship between typically available features of historically treated patients and the proposed ground-truth notions of similarity is studied by adopting state-of-the-art machine learning techniques, including random forest. Also, the feasibility of automatically selecting the most similar patient is assessed by comparing ground-truth rankings of similarity with predicted rankings. Similarities (mainly) based on the external abdomen shape and on the pairwise organ distances are highly correlated (Pearson r p ≥ 0.70) and are successfully modeled with random forests based on historically recorded features (pseudo-R 2 ≥ 0.69). In contrast, similarities based on the shape of internal organs cannot be modeled. For the similarities that random forest can reliably model, an estimation of feature relevance indicates that abdominal diameters and weight are the most important. Experiments on automatically selecting similar patients lead to coarse, yet quite robust results: the most similar patient is retrieved only 22% of the times, however, the error in worst-case scenarios is limited, with the fourth most similar patient being retrieved. Results demonstrate that automatically selecting similar patients is feasible when focusing on the shape of the external abdomen and on the position of internal organs. Moreover, whereas the common practice in phantom-based dose reconstruction is to select a representative phantom using age, height, and weight as discriminant factors for any treatment scenario, our analysis on abdominal tumor treatment for children shows that the most relevant features are weight and the anterior-posterior and left-right abdominal diameters. © 2018 American Association of Physicists in Medicine.

Performance Improvement of a Magnetized Coaxial Plasma Gun by adopting Iron-core Bias Coil and New Pre-Ionization System

NASA Astrophysics Data System (ADS)

Edo, Takahiro; Asai, T.; Tanaka, F.; Yamada, S.; Hosozawa, A.; Gota, H.; Roche, T.; Allfrey, I.; Matsumoto, T.

2017-10-01

A magnetized coaxial plasma gun (MCPG) is a device used to generate a compact toroid (CT), which has a spheromak-like configuration. A typical MCPG consists of a set of axisymmetric cylindrical electrodes, bias coil, and gas-puff valves. In order to expand the CT operating range, the distributions of the bias magnetic field and neutral gas have been investigated. We have developed a new means of generating stuffing flux. By inserting an iron core into the bias coil, the magnetic field increases dramatically; even a small current of a few Amps produces a sufficient bias field. According to a simulation result, it was also suggested that the radial distribution of the bias field is easily controlled. The ejected CT and the target FRC are cooled by excess neutral gas that typical MCPGs require to initiate a breakdown; therefore, we have adopted a miniature gun as a new pre-ionization (PI) system. By introducing this PI system, the breakdown occurs at lower neutral gas density so that the amount of excess neutral gas can be reduced.

Deep feature classification of angiomyolipoma without visible fat and renal cell carcinoma in abdominal contrast-enhanced CT images with texture image patches and hand-crafted feature concatenation.

PubMed

Lee, Hansang; Hong, Helen; Kim, Junmo; Jung, Dae Chul

2018-04-01

To develop an automatic deep feature classification (DFC) method for distinguishing benign angiomyolipoma without visible fat (AMLwvf) from malignant clear cell renal cell carcinoma (ccRCC) from abdominal contrast-enhanced computer tomography (CE CT) images. A dataset including 80 abdominal CT images of 39 AMLwvf and 41 ccRCC patients was used. We proposed a DFC method for differentiating the small renal masses (SRM) into AMLwvf and ccRCC using the combination of hand-crafted and deep features, and machine learning classifiers. First, 71-dimensional hand-crafted features (HCF) of texture and shape were extracted from the SRM contours. Second, 1000-4000-dimensional deep features (DF) were extracted from the ImageNet pretrained deep learning model with the SRM image patches. In DF extraction, we proposed the texture image patches (TIP) to emphasize the texture information inside the mass in DFs and reduce the mass size variability. Finally, the two features were concatenated and the random forest (RF) classifier was trained on these concatenated features to classify the types of SRMs. The proposed method was tested on our dataset using leave-one-out cross-validation and evaluated using accuracy, sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), and area under receiver operating characteristics curve (AUC). In experiments, the combinations of four deep learning models, AlexNet, VGGNet, GoogleNet, and ResNet, and four input image patches, including original, masked, mass-size, and texture image patches, were compared and analyzed. In qualitative evaluation, we observed the change in feature distributions between the proposed and comparative methods using tSNE method. In quantitative evaluation, we evaluated and compared the classification results, and observed that (a) the proposed HCF + DF outperformed HCF-only and DF-only, (b) AlexNet showed generally the best performances among the CNN models, and (c) the proposed TIPs not only achieved the competitive performances among the input patches, but also steady performance regardless of CNN models. As a result, the proposed method achieved the accuracy of 76.6 ± 1.4% for the proposed HCF + DF with AlexNet and TIPs, which improved the accuracy by 6.6%p and 8.3%p compared to HCF-only and DF-only, respectively. The proposed shape features and TIPs improved the HCFs and DFs, respectively, and the feature concatenation further enhanced the quality of features for differentiating AMLwvf from ccRCC in abdominal CE CT images. © 2018 American Association of Physicists in Medicine.

32. TYPICAL BRYANT ITEMS FROM THE 1930S; TOP ROW LEFT ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

32. TYPICAL BRYANT ITEMS FROM THE 1930S; TOP ROW LEFT TO RIGHT: PORCELAIN CASED SWITCH, ROTARY SWITCH, SHORTING PLUG TO BYPASS FUSE; SECOND ROW: BRASS INCANDESCENT LAMP SURFACE RECEPTACLE, INCANDESCENT LAMPHOLDER WITH ADAPTER FOR GLASS GLOBE; THIRD ROW: PORCELAIN BASE ROTARY SWITCH, APPLIANCE BREAKER WITH COVER REMOVED, APPLIANCE BREAKER - Bryant Electric Company, 1421 State Street, Bridgeport, Fairfield County, CT

Evaluation of correlation between CT image features and ERCC1 protein expression in assessing lung cancer prognosis

NASA Astrophysics Data System (ADS)

Tan, Maxine; Emaminejad, Nastaran; Qian, Wei; Sun, Shenshen; Kang, Yan; Guan, Yubao; Lure, Fleming; Zheng, Bin

2014-03-01

Stage I non-small-cell lung cancers (NSCLC) usually have favorable prognosis. However, high percentage of NSCLC patients have cancer relapse after surgery. Accurately predicting cancer prognosis is important to optimally treat and manage the patients to minimize the risk of cancer relapse. Studies have shown that an excision repair crosscomplementing 1 (ERCC1) gene was a potentially useful genetic biomarker to predict prognosis of NSCLC patients. Meanwhile, studies also found that chronic obstructive pulmonary disease (COPD) was highly associated with lung cancer prognosis. In this study, we investigated and evaluated the correlations between COPD image features and ERCC1 gene expression. A database involving 106 NSCLC patients was used. Each patient had a thoracic CT examination and ERCC1 genetic test. We applied a computer-aided detection scheme to segment and quantify COPD image features. A logistic regression method and a multilayer perceptron network were applied to analyze the correlation between the computed COPD image features and ERCC1 protein expression. A multilayer perceptron network (MPN) was also developed to test performance of using COPD-related image features to predict ERCC1 protein expression. A nine feature based logistic regression analysis showed the average COPD feature values in the low and high ERCC1 protein expression groups are significantly different (p < 0.01). Using a five-fold cross validation method, the MPN yielded an area under ROC curve (AUC = 0.669±0.053) in classifying between the low and high ERCC1 expression cases. The study indicates that CT phenotype features are associated with the genetic tests, which may provide supplementary information to help improve accuracy in assessing prognosis of NSCLC patients.

Volumetric quantitative characterization of human patellar cartilage with topological and geometrical features on phase-contrast X-ray computed tomography.

PubMed

Nagarajan, Mahesh B; Coan, Paola; Huber, Markus B; Diemoz, Paul C; Wismüller, Axel

2015-11-01

Phase-contrast X-ray computed tomography (PCI-CT) has attracted significant interest in recent years for its ability to provide significantly improved image contrast in low absorbing materials such as soft biological tissue. In the research context of cartilage imaging, previous studies have demonstrated the ability of PCI-CT to visualize structural details of human patellar cartilage matrix and capture changes to chondrocyte organization induced by osteoarthritis. This study evaluates the use of geometrical and topological features for volumetric characterization of such chondrocyte patterns in the presence (or absence) of osteoarthritic damage. Geometrical features derived from the scaling index method (SIM) and topological features derived from Minkowski Functionals were extracted from 1392 volumes of interest (VOI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These features were subsequently used in a machine learning task with support vector regression to classify VOIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver operating characteristic curve (AUC). Our results show that the classification performance of SIM-derived geometrical features (AUC: 0.90 ± 0.09) is significantly better than Minkowski Functionals volume (AUC: 0.54 ± 0.02), surface (AUC: 0.72 ± 0.06), mean breadth (AUC: 0.74 ± 0.06) and Euler characteristic (AUC: 0.78 ± 0.04) (p < 10(-4)). These results suggest that such geometrical features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix in an automated manner, while also enabling classification of cartilage as healthy or osteoarthritic with high accuracy. Such features could potentially serve as diagnostic imaging markers for evaluating osteoarthritis progression and its response to different therapeutic intervention strategies.

WE-G-207-05: Relationship Between CT Image Quality, Segmentation Performance, and Quantitative Image Feature Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, J; Nishikawa, R; Reiser, I

Purpose: Segmentation quality can affect quantitative image feature analysis. The objective of this study is to examine the relationship between computed tomography (CT) image quality, segmentation performance, and quantitative image feature analysis. Methods: A total of 90 pathology proven breast lesions in 87 dedicated breast CT images were considered. An iterative image reconstruction (IIR) algorithm was used to obtain CT images with different quality. With different combinations of 4 variables in the algorithm, this study obtained a total of 28 different qualities of CT images. Two imaging tasks/objectives were considered: 1) segmentation and 2) classification of the lesion as benignmore » or malignant. Twenty-three image features were extracted after segmentation using a semi-automated algorithm and 5 of them were selected via a feature selection technique. Logistic regression was trained and tested using leave-one-out-cross-validation and its area under the ROC curve (AUC) was recorded. The standard deviation of a homogeneous portion and the gradient of a parenchymal portion of an example breast were used as an estimate of image noise and sharpness. The DICE coefficient was computed using a radiologist’s drawing on the lesion. Mean DICE and AUC were used as performance metrics for each of the 28 reconstructions. The relationship between segmentation and classification performance under different reconstructions were compared. Distributions (median, 95% confidence interval) of DICE and AUC for each reconstruction were also compared. Results: Moderate correlation (Pearson’s rho = 0.43, p-value = 0.02) between DICE and AUC values was found. However, the variation between DICE and AUC values for each reconstruction increased as the image sharpness increased. There was a combination of IIR parameters that resulted in the best segmentation with the worst classification performance. Conclusion: There are certain images that yield better segmentation or classification performance. The best segmentation Result does not necessarily lead to the best classification Result. This work has been supported in part by grants from the NIH R21-EB015053. R Nishikawa is receives royalties form Hologic, Inc.« less

Radial gradient and radial deviation radiomic features from pre-surgical CT scans are associated with survival among lung adenocarcinoma patients

PubMed Central

Tunali, Ilke; Stringfield, Olya; Guvenis, Albert; Wang, Hua; Liu, Ying; Balagurunathan, Yoganand; Lambin, Philippe; Gillies, Robert J.; Schabath, Matthew B.

2017-01-01

The goal of this study was to extract features from radial deviation and radial gradient maps which were derived from thoracic CT scans of patients diagnosed with lung adenocarcinoma and assess whether these features are associated with overall survival. We used two independent cohorts from different institutions for training (n= 61) and test (n= 47) and focused our analyses on features that were non-redundant and highly reproducible. To reduce the number of features and covariates into a single parsimonious model, a backward elimination approach was applied. Out of 48 features that were extracted, 31 were eliminated because they were not reproducible or were redundant. We considered 17 features for statistical analysis and identified a final model containing the two most highly informative features that were associated with lung cancer survival. One of the two features, radial deviation outside-border separation standard deviation, was replicated in a test cohort exhibiting a statistically significant association with lung cancer survival (multivariable hazard ratio = 0.40; 95% confidence interval 0.17-0.97). Additionally, we explored the biological underpinnings of these features and found radial gradient and radial deviation image features were significantly associated with semantic radiological features. PMID:29221183

The prevalence of osteoarthritis of the sternoclavicular joint on computed tomography.

PubMed

Lawrence, Christopher R; East, Benjamin; Rashid, Abbas; Tytherleigh-Strong, Graham M

2017-01-01

Symptomatic disorders around the sternoclavicular joint (SCJ) are relatively uncommon. Previous cadaveric and radiographic studies have suggested that asymptomatic osteoarthritic changes are relatively common, progressively increasing with age. The purpose of this study was to determine the prevalence of SCJ osteoarthritis in the general population using computed tomography (CT) scans. We assessed 464 SCJs in 232 patients undergoing a standardized axial CT scan of the thorax including both SCJs, across a range of ages from the second to tenth decade. The scans were undertaken for multiple clinical indications; however, none were obtained to investigate SCJ pathology. The predominant changes investigated were for the features associated with osteoarthritis including the presence of osteophytes, subchondral cysts, and subcortical sclerosis. The CT scans of 244 SCJs (53%) in 137 patients (59%) showed at least 1 sign of osteoarthritis. No patients younger than 35 years had any features of osteoarthritis. Osteoarthritic changes were present in 89.6% of patients older than 50 years compared with 9.1% younger than this age. All patients above the age of 61 had at least 1 feature of osteoarthritic changes on at least 1 side of the SCJ. Increasing prevalence was noted with increasing age both in the percentage of SCJs showing any positive signs of osteoarthritis and in the severity of osteoarthritis. SCJ osteoarthritis is a very common incidental finding on CT scans, particularly with increasing age. This should be taken into consideration when using a CT scan to assess a patient with symptomatic SCJ pathology. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Computed tomography as an aid in the diagnosis of chronic nasal disease in dogs.

PubMed

Lefebvre, J; Kuehn, N F; Wortinger, A

2005-06-01

To assess the use of computed tomography (CT) in the diagnosis of chronic nasal disease in dogs. A retrospective study of 85 dogs with chronic nasal discharge due to primary nasal disease, which had undergone nasal CT and biopsy, was carried out. Medical records were reviewed for signalment, clinical signs, CT findings, endoscopic findings and histopathology. The results obtained via CT were correlated with nasal histopathology and gross anatomical observations were recorded at the time of rhinoscopy. Neoplasia was diagnosed in 37 dogs for which CT typically revealed a soft tissue density associated with extensive turbinate destruction. Inflammatory rhinitis was diagnosed in 40 dogs. CT disclosed either normal turbinate structures or mild to moderate turbinate destruction, with or without the presence of soft tissue densities (mucopus) within the nasal passages. Fungal rhinitis was diagnosed in seven dogs for which CT disclosed extensive turbinate destruction with hyperlucency of the nasal passages. One dog had normal CT and histopathology findings. CT greatly enhanced the ability to diagnose chronic nasal disease in dogs, providing detailed Information regarding the extent of the disease, accurate discrimination of neoplastic versus non-neoplastic diseases, and identification of areas of the nose to examine rhinoscopically and suspicious regions to target for biopsy.

TU-G-201-00: Imaging Equipment Specification and Selection in Radiation Oncology Departments

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

This session will update therapeutic physicists on technological advancements and radiation oncology features of commercial CT, MRI, and PET/CT imaging systems. Also described are physicists’ roles in every stage of equipment selection, purchasing, and operation, including defining specifications, evaluating vendors, making recommendations, and optimal and safe use of imaging equipment in radiation oncology environment. The first presentation defines important terminology of CT and PET/CT followed by a review of latest innovations, such as metal artifact reduction, statistical iterative reconstruction, radiation dose management, tissue classification by dual energy CT and spectral CT, improvement in spatial resolution and sensitivity in PET, andmore » potentials of PET/MR. We will also discuss important technical specifications and items in CT and PET/CT purchasing quotes and their impacts. The second presentation will focus on key components in the request for proposal for a MRI simulator and how to evaluate vendor proposals. MRI safety issues in radiation Oncology, including MRI scanner Zones (4-zone design), will be discussed. Basic MR terminologies, important functionalities, and advanced features, which are relevant to radiation therapy, will be discussed. In the third presentation, justification of imaging systems for radiation oncology, considerations in room design and construction in a RO department, shared use with diagnostic radiology, staffing needs and training, clinical/research use cases and implementation, will be discussed. The emphasis will be on understanding and bridging the differences between diagnostic and radiation oncology installations, building consensus amongst stakeholders for purchase and use, and integrating imaging technologies into the radiation oncology environment. Learning Objectives: Learn the latest innovations of major imaging systems relevant to radiation therapy Be able to describe important technical specifications of CT, MRI, and PET/CT Understand the process of budget request, equipment justification, comparisons of technical specifications, site visits, vendor selection, and contract development.« less

Magnetic resonance imaging and computed tomography characteristics of renal cell carcinoma associated with Xp11.2 translocation/TFE3 gene fusion.

PubMed

Wang, Wei; Ding, Jianhui; Li, Yuan; Wang, Chaofu; Zhou, Liangping; Zhu, Hui; Peng, Weijun

2014-01-01

To characterize Xp11.2 translocation renal cell carcinoma (RCC) using magnetic resonance imaging (MRI) and computed tomography (CT). This study retrospectively collected the MRI and CT data of twelve patients with Xp11.2 translocation RCC confirmed by pathology. Nine cases underwent dynamic contrast-enhanced MRI (DCE-MRI) and 6 cases underwent CT, of which 3 cases underwent MRI and CT simultaneously. The MRI and CT findings were analyzed in regard to tumor position, size, hemorrhagic, cystic or necrotic components, calcification, tumor density, signal intensity and enhancement features. The age of the 12 patients ranged from 13 to 46 years (mean age: 23 years). T2WI revealed heterogeneous intensity, hyper-intensity, and slight hypo-intensity in 6 cases, 2 cases, and 1 case, respectively. On DCE-MR images, mild, moderate, and marked rim enhancement of the tumor in the corticomedullary phase (CMP) were observed in 1, 6, and 2 cases, respectively. The tumor parenchyma showed iso-attenuation (n = 4) or slight hyper-attenuation (n = 1) compared to the normal renal cortex on non-contrast CT images. Imaging findings were suggestive of hemorrhage (n = 4) or necrosis (n = 8) in the tumors, and there was evidence of calcification in 8 cases by CT (n = 3) and pathology (n = 8). On dynamic contrast-enhanced CT images, 3 cases and 1 case manifested moderate and strong CMP enhancement, respectively. Nine tumors by MRI and 4 tumors by CT showed prolonged enhancement. Three neoplasms presented at stage I, 2 at stage II, 3 at stage III, and 4 at stage IV according the 2010 AJCC staging criteria. XP11.2 translocation RCC should be considered when a child or young adult patient presents with a renal tumor with heterogeneous features such as hemorrhage, necrosis, cystic changes, and calcification on CT and MRI and/or is accompanied by metastatic evidence.

Magnetic Resonance Imaging and Computed Tomography Characteristics of Renal Cell Carcinoma Associated with Xp11.2 Translocation/TFE3 Gene Fusion

PubMed Central

Li, Yuan; Wang, Chaofu; Zhou, Liangping; Zhu, Hui; Peng, Weijun

2014-01-01

Purpose To characterize Xp11.2 translocation renal cell carcinoma (RCC) using magnetic resonance imaging (MRI) and computed tomography (CT). Methods This study retrospectively collected the MRI and CT data of twelve patients with Xp11.2 translocation RCC confirmed by pathology. Nine cases underwent dynamic contrast-enhanced MRI (DCE-MRI) and 6 cases underwent CT, of which 3 cases underwent MRI and CT simultaneously. The MRI and CT findings were analyzed in regard to tumor position, size, hemorrhagic, cystic or necrotic components, calcification, tumor density, signal intensity and enhancement features. Results The age of the 12 patients ranged from 13 to 46 years (mean age: 23 years). T2WI revealed heterogeneous intensity, hyper-intensity, and slight hypo-intensity in 6 cases, 2 cases, and 1 case, respectively. On DCE-MR images, mild, moderate, and marked rim enhancement of the tumor in the corticomedullary phase (CMP) were observed in 1, 6, and 2 cases, respectively. The tumor parenchyma showed iso-attenuation (n = 4) or slight hyper-attenuation (n = 1) compared to the normal renal cortex on non-contrast CT images. Imaging findings were suggestive of hemorrhage (n = 4) or necrosis (n = 8) in the tumors, and there was evidence of calcification in 8 cases by CT (n = 3) and pathology (n = 8). On dynamic contrast-enhanced CT images, 3 cases and 1 case manifested moderate and strong CMP enhancement, respectively. Nine tumors by MRI and 4 tumors by CT showed prolonged enhancement. Three neoplasms presented at stage I, 2 at stage II, 3 at stage III, and 4 at stage IV according the 2010 AJCC staging criteria. Conclusions XP11.2 translocation RCC should be considered when a child or young adult patient presents with a renal tumor with heterogeneous features such as hemorrhage, necrosis, cystic changes, and calcification on CT and MRI and/or is accompanied by metastatic evidence. PMID:24926688

TU-G-201-02: An MRI Simulator From Proposal to Operation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cao, Y.

2015-06-15

This session will update therapeutic physicists on technological advancements and radiation oncology features of commercial CT, MRI, and PET/CT imaging systems. Also described are physicists’ roles in every stage of equipment selection, purchasing, and operation, including defining specifications, evaluating vendors, making recommendations, and optimal and safe use of imaging equipment in radiation oncology environment. The first presentation defines important terminology of CT and PET/CT followed by a review of latest innovations, such as metal artifact reduction, statistical iterative reconstruction, radiation dose management, tissue classification by dual energy CT and spectral CT, improvement in spatial resolution and sensitivity in PET, andmore » potentials of PET/MR. We will also discuss important technical specifications and items in CT and PET/CT purchasing quotes and their impacts. The second presentation will focus on key components in the request for proposal for a MRI simulator and how to evaluate vendor proposals. MRI safety issues in radiation Oncology, including MRI scanner Zones (4-zone design), will be discussed. Basic MR terminologies, important functionalities, and advanced features, which are relevant to radiation therapy, will be discussed. In the third presentation, justification of imaging systems for radiation oncology, considerations in room design and construction in a RO department, shared use with diagnostic radiology, staffing needs and training, clinical/research use cases and implementation, will be discussed. The emphasis will be on understanding and bridging the differences between diagnostic and radiation oncology installations, building consensus amongst stakeholders for purchase and use, and integrating imaging technologies into the radiation oncology environment. Learning Objectives: Learn the latest innovations of major imaging systems relevant to radiation therapy Be able to describe important technical specifications of CT, MRI, and PET/CT Understand the process of budget request, equipment justification, comparisons of technical specifications, site visits, vendor selection, and contract development.« less

Inflammatory myofibroblastic tumor: an entity of CT and MR imaging to differentiate from malignant tumors of the sinonasal cavity.

PubMed

Yan, Zhongyu; Wang, Yongzhe; Zhang, Zhengyu

2014-01-01

Inflammatory myofibroblastic tumor (IMT) is chronic inflammatory lesions of unknown origins. The preoperative diagnosis for tumors in the sinonasal cavity is difficult to distinguish between IMT and aggressive malignancy in most cases. The purpose of this study was to evaluate the imaging features of IMT distinguishing the 2 types of tumors. Computed tomography and magnetic resonance imaging were identified retrospectively with IMT in 14 cases and with aggressive malignancy in 38 cases in the sinonasal cavity proven by pathology. Imaging findings were evaluated, including the configuration, extent, margin, calcification, bone involvement, T1WI and T2WI signal intensity, and degree of enhancement. There was a significant difference between IMT and aggressive malignancy regarding the configuration, extension, calcification, bone change, signal intensity and homogeneous on T2-weighted imaging, and degree of enhancement (P < 0.05). Inflammatory myofibroblastic tumor and aggressive malignancy have some different imaging features that could be helpful in the differentiation between the lesions. Bone erosion with sclerosis, calcification when present, typically homogenous and never hyperintense of T2 appearance, and mild enhancement played an important role in differentiating sinonasal IMT from malignancies.

Radiation dose in the thyroid and the thyroid cancer risk attributable to CT scans for pediatric patients in one general hospital of China.

PubMed

Su, Yin-Ping; Niu, Hao-Wei; Chen, Jun-Bo; Fu, Ying-Hua; Xiao, Guo-Bing; Sun, Quan-Fu

2014-03-07

To quantify the radiation dose in the thyroid attributable to different CT scans and to estimate the thyroid cancer risk in pediatric patients. The information about pediatric patients who underwent CT scans was abstracted from the radiology information system in one general hospital between 1 January 2012 and 31 December 2012. The radiation doses were calculated using the ImPACT Patient Dosimetry Calculator and the lifetime attributable risk (LAR) of thyroid cancer incidence was estimated based on the National Academies Biologic Effects of Ionizing Radiation VII model. The subjects comprised 922 children, 68% were males, and received 971 CT scans. The range of typical radiation dose to the thyroid was estimated to be 0.61-0.92 mGy for paranasal sinus CT scans, 1.10-2.45 mGy for head CT scans, and 2.63-5.76 mGy for chest CT scans. The LAR of thyroid cancer were as follows: for head CT, 1.1 per 100,000 for boys and 8.7 per 100,000 for girls; for paranasal sinus CT scans, 0.4 per 100,000 for boys and 2.7 per 100,000 for girls; for chest CT scans, 2.2 per 100,000 for boys and 14.2 per 100,000 for girls. The risk of thyroid cancer was substantially higher for girls than for the boys, and from chest CT scans was higher than that from head or paransal sinus CT scans. Chest CT scans caused higher thyroid dose and the LAR of thyroid cancer incidence, compared with paransal sinus or head CT scans. Therefore, physicians should pay more attention to protect the thyroid when children underwent CT scans, especially chest CT scans.

Relationship between trabecular texture features of CT images and an amount of bone cement volume injection in percutaneous vertebroplasty

NASA Astrophysics Data System (ADS)

Tack, Gye Rae; Choi, Hyung Guen; Shin, Kyu-Chul; Lee, Sung J.

2001-06-01

Percutaneous vertebroplasty is a surgical procedure that was introduced for the treatment of compression fracture of the vertebrae. This procedure includes puncturing vertebrae and filling with polymethylmethacrylate (PMMA). Recent studies have shown that the procedure could provide structural reinforcement for the osteoporotic vertebrae while being minimally invasive and safe with immediate pain relief. However, treatment failures due to disproportionate PMMA volume injection have been reported as one of complications in vertebroplasty. It is believed that control of PMMA volume is one of the most critical factors that can reduce the incidence of complications. In this study, appropriate amount of PMMA volume was assessed based on the imaging data of a given patient under the following hypotheses: (1) a relationship can be drawn between the volume of PMMA injection and textural features of the trabecular bone in preoperative CT images and (2) the volume of PMMA injection can be estimated based on 3D reconstruction of postoperative CT images. Gray-level run length analysis was used to determine the textural features of the trabecular bone. The width of trabecular (T-texture) and the width of intertrabecular spaces (I-texture) were calculated. The correlation between PMMA volume and textural features of patient's CT images was also examined to evaluate the appropriate PMMA amount. Results indicated that there was a strong correlation between the actual PMMA injection volume and the area of the intertrabecular space and that of trabecular bone calculated from the CT image (correlation coefficient, requals0.96 and requals-0.95, respectively). T- texture (requals-0.93) did correlate better with the actual PMMA volume more than the I-texture (requals0.57). Therefore, it was demonstrated that appropriate PMMA injection volume could be predicted based on the textural analysis for better clinical management of the osteoporotic spine.

TH-E-17A-01: Internal Respiratory Surrogate for 4D CT Using Fourier Transform and Anatomical Features

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hui, C; Suh, Y; Robertson, D

Purpose: To develop a novel algorithm to generate internal respiratory signals for sorting of four-dimensional (4D) computed tomography (CT) images. Methods: The proposed algorithm extracted multiple time resolved features as potential respiratory signals. These features were taken from the 4D CT images and its Fourier transformed space. Several low-frequency locations in the Fourier space and selected anatomical features from the images were used as potential respiratory signals. A clustering algorithm was then used to search for the group of appropriate potential respiratory signals. The chosen signals were then normalized and averaged to form the final internal respiratory signal. Performance ofmore » the algorithm was tested in 50 4D CT data sets and results were compared with external signals from the real-time position management (RPM) system. Results: In almost all cases, the proposed algorithm generated internal respiratory signals that visibly matched the external respiratory signals from the RPM system. On average, the end inspiration times calculated by the proposed algorithm were within 0.1 s of those given by the RPM system. Less than 3% of the calculated end inspiration times were more than one time frame away from those given by the RPM system. In 3 out of the 50 cases, the proposed algorithm generated internal respiratory signals that were significantly smoother than the RPM signals. In these cases, images sorted using the internal respiratory signals showed fewer artifacts in locations corresponding to the discrepancy in the internal and external respiratory signals. Conclusion: We developed a robust algorithm that generates internal respiratory signals from 4D CT images. In some cases, it even showed the potential to outperform the RPM system. The proposed algorithm is completely automatic and generally takes less than 2 min to process. It can be easily implemented into the clinic and can potentially replace the use of external surrogates.« less

Intra-tumour 18F-FDG uptake heterogeneity decreases the reliability on target volume definition with positron emission tomography/computed tomography imaging.

PubMed

Dong, Xinzhe; Wu, Peipei; Sun, Xiaorong; Li, Wenwu; Wan, Honglin; Yu, Jinming; Xing, Ligang

2015-06-01

This study aims to explore whether the intra-tumour (18) F-fluorodeoxyglucose (FDG) uptake heterogeneity affects the reliability of target volume definition with FDG positron emission tomography/computed tomography (PET/CT) imaging for nonsmall cell lung cancer (NSCLC) and squamous cell oesophageal cancer (SCEC). Patients with NSCLC (n = 50) or SCEC (n = 50) who received (18)F-FDG PET/CT scanning before treatments were included in this retrospective study. Intra-tumour FDG uptake heterogeneity was assessed by visual scoring, the coefficient of variation (COV) of the standardised uptake value (SUV) and the image texture feature (entropy). Tumour volumes (gross tumour volume (GTV)) were delineated on the CT images (GTV(CT)), the fused PET/CT images (GTV(PET-CT)) and the PET images, using a threshold at 40% SUV(max) (GTV(PET40%)) or the SUV cut-off value of 2.5 (GTV(PET2.5)). The correlation between the FDG uptake heterogeneity parameters and the differences in tumour volumes among GTV(CT), GTV(PET-CT), GTV(PET40%) and GTV(PET2.5) was analysed. For both NSCLC and SCEC, obvious correlations were found between uptake heterogeneity, SUV or tumour volumes. Three types of heterogeneity parameters were consistent and closely related to each other. Substantial differences between the four methods of GTV definition were found. The differences between the GTV correlated significantly with PET heterogeneity defined with the visual score, the COV or the textural feature-entropy for NSCLC and SCEC. In tumours with a high FDG uptake heterogeneity, a larger GTV delineation difference was found. Advance image segmentation algorithms dealing with tracer uptake heterogeneity should be incorporated into the treatment planning system. © 2015 The Royal Australian and New Zealand College of Radiologists.

Plaque imaging with CT—a comprehensive review on coronary CT angiography based risk assessment

PubMed Central

Kolossváry, Márton; Szilveszter, Bálint; Merkely, Béla

2017-01-01

CT based technologies have evolved considerably in recent years. Coronary CT angiography (CTA) provides robust assessment of coronary artery disease (CAD). Early coronary CTA imaging—as a gate-keeper of invasive angiography—has focused on the presence of obstructive stenosis. Coronary CTA is currently the only non-invasive imaging modality for the evaluation of non-obstructive CAD, which has been shown to contribute to adverse cardiac events. Importantly, improved spatial resolution of CT scanners and novel image reconstruction algorithms enable the quantification and characterization of atherosclerotic plaques. State-of-the-art CT imaging can therefore reliably assess the extent of CAD and differentiate between various plaque features. Recent studies have demonstrated the incremental prognostic value of adverse plaque features over luminal stenosis. Comprehensive coronary plaque assessment holds potential to significantly improve individual risk assessment incorporating adverse plaque characteristics, the extent and severity of atherosclerotic plaque burden. As a result, several coronary CTA based composite risk scores have been proposed recently to determine patients at high risk for adverse events. Coronary CTA became a promising modality for the evaluation of functional significance of coronary lesions using CT derived fractional flow reserve (FFR-CT) and/or rest/dynamic myocardial CT perfusion. This could lead to substantial reduction in unnecessary invasive catheterization procedures and provide information on ischemic burden of CAD. Discordance between the degree of stenosis and ischemia has been recognized in clinical landmark trials using invasive FFR. Both lesion stenosis and composition are possibly related to myocardial ischemia. The evaluation of lesion-specific ischemia using combined functional and morphological plaque information could ultimately improve the diagnostic performance of CTA and thus patient care. In this review we aimed to summarize current evidence on comprehensive coronary artery plaque assessment using coronary CTA. PMID:29255692

Cyst-based measurements for assessing lymphangioleiomyomatosis in computed tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lo, P., E-mail: pechinlo@mednet.edu.ucla; Brown, M. S.; Kim, H.

Purpose: To investigate the efficacy of a new family of measurements made on individual pulmonary cysts extracted from computed tomography (CT) for assessing the severity of lymphangioleiomyomatosis (LAM). Methods: CT images were analyzed using thresholding to identify a cystic region of interest from chest CT of LAM patients. Individual cysts were then extracted from the cystic region by the watershed algorithm, which separates individual cysts based on subtle edges within the cystic regions. A family of measurements were then computed, which quantify the amount, distribution, and boundary appearance of the cysts. Sequential floating feature selection was used to select amore » small subset of features for quantification of the severity of LAM. Adjusted R{sup 2} from multiple linear regression and R{sup 2} from linear regression against measurements from spirometry were used to compare the performance of our proposed measurements with currently used density based CT measurements in the literature, namely, the relative area measure and the D measure. Results: Volumetric CT data, performed at total lung capacity and residual volume, from a total of 49 subjects enrolled in the MILES trial were used in our study. Our proposed measures had adjusted R{sup 2} ranging from 0.42 to 0.59 when regressing against the spirometry measures, with p < 0.05. For previously used density based CT measurements in the literature, the best R{sup 2} was 0.46 (for only one instance), with the majority being lower than 0.3 or p > 0.05. Conclusions: The proposed family of CT-based cyst measurements have better correlation with spirometric measures than previously used density based CT measurements. They show potential as a sensitive tool for quantitatively assessing the severity of LAM.« less

Application of PET/CT in treatment response evaluation and recurrence prediction in patients with newly-diagnosed multiple myeloma

PubMed Central

Li, Ying; Liu, Junru; Huang, Beihui; Chen, Meilan; Diao, Xiangwen; Li, Juan

2017-01-01

Multiple myeloma (MM) causes osteolytic lesions which can be detected by 18F-fluorodeoxyglucose positron emission tomography/Computed tomography (18F-FDG PET/CT). We prospectively involve 96 Newly diagnosed MM to take PET/CT scan at scheduled treatment time (figure 1), and 18F-FDG uptake of lesion was measured by SUVmax and T/Mmax. All MM patients took bortezomib based chemotherapy as induction and received ASCT and maintenance. All clinical features were analyzed with the PET/CT image changes, and some relationships between treatment response and FDG uptakes changes were found: Osteolytic lesions of MM uptakes higher FDG than healthy volunteers, and this trend is more obvious in extramedullary lesions. Compared to X-ray, PET/CT was more sensitive both in discoering bone as well as extramedullary lesions. In newly diagnosed MM, several adverse clinical factors were related to high FDG uptakes of bone lesions. Bone lesion FDG uptakes of MM with P53 mutation or with hypodiploidy and complex karyotype were also higher than those without such changes. In treatment response, PET/CT showed higher sensitivity in detecting tumor residual disease than immunofixation electrophoresis. But in relapse prediction, it might show false positive disease recurrences and the imaging changes might be influenced by infections and hemoglobulin levels. Conclusion: PET/CT is sensitive in discovering meduallary and extrameduallary lesions of MM, and the 18F-FDG uptake of lesions are related with clinical indictors and biological features of plasma cells. In evaluating treatment response and survival, PET/CT showed its superiority. But in predicting relapse or refractory, it may show false positive results. PMID:27556189

Microcephalia with mandibular and dental dysplasia in adult Zmpste24-deficient mice

PubMed Central

de Carlos, F; Varela, I; Germanà, A; Montalbano, G; Freije, J M P; Vega, J A; López-Otin, C; Cobo, J M

2008-01-01

ZMPSTE24 (also called FACE-1) is a zinc-metalloprotease involved in the post-translational processing of prelamin A to mature lamin A, a major component of the nuclear envelope. Mutations in the ZMPSTE24 gene or in that encoding its substrate prelamin A (LMNA) result in a series of human inherited diseases known collectively as laminopathies and showing regional or systemic manifestations (i.e. the Hutchinson–Gilford progeria syndrome). Typically, patients suffering some laminopathies show craniofacial or mandible anomalies, aberrant dentition or facial features characteristic of aged persons. To analyse whether Zmpste24−/– mice reproduce the cranial phenotype observed in humans due to mutations in ZMPSTE24or LMNA, we conducted a craniometric study based on micro-computer tomography (µCT) images. Furthermore, using simple radiology, µCT, µCT-densitometry and scanning electron microscopy, we analysed the mandible and the teeth from Zmpste24−/– mice. Finally, the structure of the lower incisor was investigated using an H&E technique. The results demonstrate that Zmpste24−/– mice are microcephalic and show mandibular and dental dysplasia affecting only the mandible teeth. In all cases, the lower incisor of mice lacking Zmpste24 was smaller than in control animals, showed cylindrical morphology and a transverse fissure at the incisal edge, and the pulpal cavity was severely reduced. Structurally, the dental layers were normally arranged but cellular layers were disorganized. The inferior molars showed a reduced cusp size. Taken together, these data strongly suggest that Zmpste24−/– mice represent a good model to analyse the craniofacial and teeth malformations characteristic of lamin-related pathologies, and might contribute to a better understanding of the molecular events underlying these diseases. PMID:19014358

Large Scale Geomorphic Mapping of Cryoplanation Terraces in Central and Eastern Alaska

NASA Astrophysics Data System (ADS)

Queen, C.; Nyland, K. E.; Nelson, F. E.

2017-12-01

Cryoplanation terraces (CTs) are large periglacial landforms characterized by alternating treads and risers, giving the appearance of giant staircases ascending ridgecrests and hillsides. The risers (scarps) are typically covered with coarse clastic material, while the surfaces of the nearly planar treads are a mosaic of vegetation, rock debris, and surficial periglacial landforms. CTs are best developed in areas of moderate relief across Beringia, the largely unglaciated region between the Lena and Mackenzie rivers, including Bering Sea islands that were formerly highlands on the Bering Land Bridge. CTs are generally thought to develop through locally intensified weathering at the base of scarps by processes associated with late lying bodies of snow. This hypothesis has been the subject of much speculative literature, but until recently there have been few process-oriented field studies performed on them. The work reported here builds on foundational work by R. D. Reger, who inventoried and investigated a large number of CTs in central and western Alaska. The resultant large-scale (1:2000) maps of cryoplanation terraces at Eagle Summit and Mount Fairplay in east-central Alaska were created using traditional and GPS-based mapping methodologies. Pits were excavated at representative locations across treads to obtain information about subsurface characteristics. The resulting maps show the location and morphology of surficial geomorphic features on CT scarps, treads, and sideslopes, superimposed on high-resolution topographic maps and perspective diagrams. GIS-based analysis of the assembled map layers promotes three-dimensional understanding of the spatial relationships between CT morphology, material properties, and erosional processes, and provides key insights into intra- and inter- terrace relationships. In concert with relative and absolute dating of material on the landforms, this research is generally supportive of the "nivation hypothesis of CT development."

HECTOR: A 240kV micro-CT setup optimized for research

NASA Astrophysics Data System (ADS)

Masschaele, Bert; Dierick, Manuel; Van Loo, Denis; Boone, Matthieu N.; Brabant, Loes; Pauwels, Elin; Cnudde, Veerle; Van Hoorebeke, Luc

2013-10-01

X-ray micro-CT has become a very powerful and common tool for non-destructive three-dimensional (3D) visualization and analysis of objects. Many systems are commercially available, but they are typically limited in terms of operational freedom both from a mechanical point of view as well as for acquisition routines. HECTOR is the latest system developed by the Ghent University Centre for X-ray Tomography (http://www.ugct.ugent.be) in collaboration with X-Ray Engineering (XRE bvba, Ghent, Belgium). It consists of a mechanical setup with nine motorized axes and a modular acquisition software package and combines a microfocus directional target X-ray source up to 240 kV with a large flat-panel detector. Provisions are made to install a line-detector for a maximal operational range. The system can accommodate samples up to 80 kg, 1 m long and 80 cm in diameter while it is also suited for high resolution (down to 4 μm) tomography. The bi-directional detector tiling is suited for large samples while the variable source-detector distance optimizes the signal to noise ratio (SNR) for every type of sample, even with peripheral equipment such as compression stages or climate chambers. The large vertical travel of 1 m can be used for helical scanning and a vertical detector rotation axis allows laminography experiments. The setup is installed in a large concrete bunker to allow accommodation of peripheral equipment such as pumps, chillers, etc., which can be integrated in the modular acquisition software to obtain a maximal correlation between the environmental control and the CT data taken. The acquisition software does not only allow good coupling with the peripheral equipment but its scripting feature is also particularly interesting for testing new and exotic acquisition routines.

Multi-mode phase speed measurements with array-based analysis: Application to the North American continent

NASA Astrophysics Data System (ADS)

Matsuzawa, H.; Yoshizawa, K.

2017-12-01

Recent high-density broad-band seismic networks allow us to construct improved 3-D upper mantle models with unprecedented horizontal resolution using surface waves. Such dispersion measurements have been primarily based on the analysis of fundamental mode. Higher-mode information can be of help in enhancing vertical resolution of 3-D models, but their dispersion analysis is intrinsically difficult, since wave-packets of several modes are overlapped each other in an observed seismogram. In this study, we measure phase dispersion of multi-mode surface waves with an array-based analysis. Our method is modeled on a one-dimensional frequency-wavenumber method originally developed by Nolet (1975, GRL), which can be applied to a set of broadband seismic records observed in a linear array along a great circle path. Through this analysis, we can obtain a spectrogram in c-T (phase speed - period) domain, which is characterized by mode-branch dispersion curves and relative spectral powers for each mode. Synthetic experiments indicate that we can separate the modal contribution using a long linear array with typical array length of about 2000 to 4000 km. The method is applied to a large data set from USArray using nearly 400 seismic events in 2007 - 2014 with Mw 6.5 or greater. Our phase-speed maps for the fundamental-mode Love and Rayleigh waves and the first higher-mode Rayleigh waves match well with the earlier models. The phase speed maps reflect typical large-scale features of regional seismic structure in North America, but smaller-scale variations are less constrained in our model, since our measured phase speeds represent path-average features over a long path (about a few thousands kilometers). Our multi-mode dispersion measurements can also be used for the extraction of mode-branch waveforms for the first a few modes. This can be done by applying a narrow filter around the dispersion curves of a target mode in c-T spectrogram. The mode-branch waveforms can then be reconstructed based on a linear Radon transform (e.g., Luo et al., 2015, GJI). Synthetic experiments suggest that we can successfully retrieve the mode-branch waveforms for several mode branches, which can be used in the secondary analysis for constraining local-scale heterogeneity with enhanced depth resolution.

Pathologic and Radiologic Correlation of Adult Cystic Lung Disease: A Comprehensive Review

PubMed Central

Parimi, Vamsi; Taddonio, Michale; Kane, Joshua Robert; Yeldandi, Anjana

2017-01-01

The presence of pulmonary parenchymal cysts on computed tomography (CT) imaging presents a significant diagnostic challenge. The diverse range of possible etiologies can usually be differentiated based on the clinical setting and radiologic features. In fact, the advent of high-resolution CT has facilitated making a diagnosis solely on analysis of CT image patterns, thus averting the need for a biopsy. While it is possible to make a fairly specific diagnosis during early stages of disease evolution by its characteristic radiological presentation, distinct features may progress to temporally converge into relatively nonspecific radiologic presentations sometimes necessitating histological examination to make a diagnosis. The aim of this review study is to provide both the pathologist and the radiologist with an overview of the diseases most commonly associated with cystic lung lesions primarily in adults by illustration and description of pathologic and radiologic features of each entity. Brief descriptions and characteristic radiologic features of the various disease entities are included and illustrative examples are provided for the common majority of them. In this article, we also classify pulmonary cystic disease with an emphasis on the pathophysiology behind cyst formation in an attempt to elucidate the characteristics of similar cystic appearances seen in various disease entities. PMID:28270943

Interstitial Features at Chest CT Enhance the Deleterious Effects of Emphysema in the COPDGene Cohort.

PubMed

Ash, Samuel Y; Harmouche, Rola; Ross, James C; Diaz, Alejandro A; Rahaghi, Farbod N; Sanchez-Ferrero, Gonzalo Vegas; Putman, Rachel K; Hunninghake, Gary M; Onieva, Jorge Onieva; Martinez, Fernando J; Choi, Augustine M; Bowler, Russell P; Lynch, David A; Hatabu, Hiroto; Bhatt, Surya P; Dransfield, Mark T; Wells, J Michael; Rosas, Ivan O; San Jose Estepar, Raul; Washko, George R

2018-06-05

Purpose To determine if interstitial features at chest CT enhance the effect of emphysema on clinical disease severity in smokers without clinical pulmonary fibrosis. Materials and Methods In this retrospective cohort study, an objective CT analysis tool was used to measure interstitial features (reticular changes, honeycombing, centrilobular nodules, linear scar, nodular changes, subpleural lines, and ground-glass opacities) and emphysema in 8266 participants in a study of chronic obstructive pulmonary disease (COPD) called COPDGene (recruited between October 2006 and January 2011). Additive differences in patients with emphysema with interstitial features and in those without interstitial features were analyzed by using t tests, multivariable linear regression, and Kaplan-Meier analysis. Multivariable linear and Cox regression were used to determine if interstitial features modified the effect of continuously measured emphysema on clinical measures of disease severity and mortality. Results Compared with individuals with emphysema alone, those with emphysema and interstitial features had a higher percentage predicted forced expiratory volume in 1 second (absolute difference, 6.4%; P < .001), a lower percentage predicted diffusing capacity of lung for carbon monoxide (DLCO) (absolute difference, 7.4%; P = .034), a 0.019 higher right ventricular-to-left ventricular (RVLV) volume ratio (P = .029), a 43.2-m shorter 6-minute walk distance (6MWD) (P < .001), a 5.9-point higher St George's Respiratory Questionnaire (SGRQ) score (P < .001), and 82% higher mortality (P < .001). In addition, interstitial features modified the effect of emphysema on percentage predicted DLCO, RVLV volume ratio, 6WMD, SGRQ score, and mortality (P for interaction < .05 for all). Conclusion In smokers, the combined presence of interstitial features and emphysema was associated with worse clinical disease severity and higher mortality than was emphysema alone. In addition, interstitial features enhanced the deleterious effects of emphysema on clinical disease severity and mortality. © RSNA, 2018 Online supplemental material is available for this article.

Primary Hepatic Malignant Fibrous Histiocytoma on PET/CT.

PubMed

Liu, Yachao; Xu, Baixuan

2018-06-01

Malignant fibrous histiocytoma is mainly presented in extremities, less commonly in posterior peritoneum, but primary presented in liver is very rare and often with a poor prognosis because of its high aggression. The features of clinical presentations and images are variable and the pre-operative diagnosis is difficult. Here, we report a primary hepatic malignant fibrous histiocytoma patient with no distant metastasis showed on pre-operative F-FDG PET/CT, however with many metastases showed on the post-operative F-FDG PET/CT.

[The computed tomographic semiotics of inflammatory diseases of the adnexa uteri].

PubMed

Todua, F I; Karmazanovskiĭ, G G; Podzolkova, N M

1990-01-01

The authors sum up the results of CT and clinical investigation of 46 women with inflammatory diseases of the uterine appendages: salpingo-oophoritis, pyosalpinx, pyoovarium, and 2 types of tuboovarian abscesses. They have shown CT potentialities in differential diagnosis of inflammations of the uterine appendages with cysts and true ovarian tumors on the basis of routine investigation and an iv contrast study of intensified images. Retrospective analysis of the most typical diagnostic errors is given.

Infrequent and low expression of cancer-testis antigens located on the X chromosome in colorectal cancer: implications for immunotherapy in South African populations.

PubMed

Dakshinamurthy, Amirtha Ganesh; Ramesar, Rajkumar; Goldberg, Paul; Blackburn, Jonathan M

2008-11-01

Cancer-testis (CT) antigens are a group of tumor antigens that are expressed in the testis and aberrantly in cancerous tissue but not in somatic tissues. The testis is an immune-privileged site because of the presence of a blood-testis barrier; as a result, CT antigens are considered to be essentially tumor specific and are attractive targets for immunotherapy. CT antigens are classified as the CT-X and the non-X CT antigens depending on the chromosomal location to which the genes are mapped. CT-X antigens are typically highly immunogenic and hence the first step towards tailored immunotherapy is to elucidate the expression profile of CT-X antigens in the respective tumors. In this study we investigated the expression profile of 16 CT-X antigen genes in 34 colorectal cancer (CRC) patients using reverse transcription-polymerase chain reaction. We observed that 12 of the 16 CT-X antigen genes studied did not show expression in any of the CRC samples analyzed. The other 4 CT-X antigen genes showed low frequency of expression and exhibited a highly variable expression profile when compared to other populations. Thus, our study forms the first report on the expression profile of CT-X antigen genes among CRC patients in the genetically diverse South African population. The results of our study suggest that genetic and ethnic variations in population might have a role in the expression of the CT-X antigen genes. Thus our results have significant implications for anti-CT antigen-based immunotherapy trials in this population.

Automated Analysis of CT Images for the Inspection of Hardwood Logs

Treesearch

Harbin Li; A. Lynn Abbott; Daniel L. Schmoldt

1996-01-01

This paper investigates several classifiers for labeling internal features of hardwood logs using computed tomography (CT) images. A primary motivation is to locate and classify internal defects so that an optimal cutting strategy can be chosen. Previous work has relied on combinations of low-level processing, image segmentation, autoregressive texture modeling, and...

Redesigning Instruction through Web-based Course Authoring Tools.

ERIC Educational Resources Information Center

Dabbagh, Nada H.; Schmitt, Jeff

1998-01-01

Examines the pedagogical implications of redesigning instruction for Web-based delivery through a case study of an undergraduate computer science course. Initially designed for a traditional learning environment, this course transformed to a Web-based course using WebCT, a Web-based course authoring tool. Discusses the specific features of WebCT.…

An application of Chan-Vese method used to determine the ROI area in CT lung screening

NASA Astrophysics Data System (ADS)

Prokop, Paweł; Surtel, Wojciech

2016-09-01

The article presents two approaches of determining the ROI area in CT lung screening. First approach is based on a classic method of framing the image in order to determine the ROI by using a MaZda tool. Second approach is based on segmentation of CT images of the lungs and reducing the redundant information from the image. Of the two approaches of an Active Contour, it was decided to choose the Chan-Vese method. In order to determine the effectiveness of the approach, it was performed an analysis of received ROI texture and extraction of textural features. In order to determine the effectiveness of the method, it was performed an analysis of the received ROI textures and extraction of the texture features, by using a Mazda tool. The results were compared and presented in the form of the radar graphs. The second approach proved to be effective and appropriate and consequently it is used for further analysis of CT images, in the computer-aided diagnosis of sarcoidosis.

Subsolid pulmonary nodules: imaging evaluation and strategic management.

PubMed

Godoy, Myrna C B; Sabloff, Bradley; Naidich, David P

2012-07-01

Given the higher rate of malignancy of subsolid pulmonary nodules and the considerably lower growth rate of ground-glass nodules (GGNs), dedicated standardized guidelines for management of these nodules have been proposed, including long-term low-dose computed tomography (CT) follow-up (≥3 years). Physicians must be familiar with the strategic management of subsolid pulmonary nodules, and should be able to identify imaging features that suggest invasive adenocarcinoma requiring a more aggressive management. Low-dose CT screening studies for early detection of lung cancer have increased our knowledge of pulmonary nodules, and in particular our understanding of the strong although imperfect correlation of the subsolid pulmonary nodules, including pure GGNs and part-solid nodules, with the spectrum of preinvasive to invasive lung adenocarcinoma. Serial CT imaging has shown stepwise progression in a subset of these nodules, characterized by increase in size and density of pure GGNs and development of a solid component, the latter usually indicating invasive adenocarcinoma. There is close correlation between the CT features of subsolid nodules (SSNs) and the spectrum of lung adenocarcinoma. Standardized guidelines are suggested for management of SSNs.

Augmenting atlas-based liver segmentation for radiotherapy treatment planning by incorporating image features proximal to the atlas contours

NASA Astrophysics Data System (ADS)

Li, Dengwang; Liu, Li; Chen, Jinhu; Li, Hongsheng; Yin, Yong; Ibragimov, Bulat; Xing, Lei

2017-01-01

Atlas-based segmentation utilizes a library of previously delineated contours of similar cases to facilitate automatic segmentation. The problem, however, remains challenging because of limited information carried by the contours in the library. In this studying, we developed a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. This study presented a new concept of atlas based segmentation method. Instead of using the complete volume of the target organs, only information along the organ contours from the atlas images was used for guiding segmentation of the new image. In setting up an atlas-based library, we included not only the coordinates of contour points, but also the image features adjacent to the contour. In this work, 139 CT images with normal appearing livers collected for radiotherapy treatment planning were used to construct the library. The CT images within the library were first registered to each other using affine registration. The nonlinear narrow shell was generated alongside the object contours of registered images. Matching voxels were selected inside common narrow shell image features of a library case and a new case using a speed-up robust features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the new image by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy optimization within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by physicians. A novel atlas-based segmentation technique with inclusion of neighborhood image features through the introduction of a narrow-shell surrounding the target objects was established. Application of the technique to 30 liver cases suggested that the technique was capable to reliably segment liver cases from CT, 4D-CT, and CBCT images with little human interaction. The accuracy and speed of the proposed method are quantitatively validated by comparing automatic segmentation results with the manual delineation results. The Jaccard similarity metric between the automatically generated liver contours obtained by the proposed method and the physician delineated results are on an average 90%-96% for planning images. Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically practical solution for auto-segmentation. The proposed mountainous narrow shell atlas based method can achieve efficient automatic liver propagation for CT, 4D-CT and CBCT images with following treatment planning and should find widespread application in future treatment planning systems.

Augmenting atlas-based liver segmentation for radiotherapy treatment planning by incorporating image features proximal to the atlas contours.

PubMed

Li, Dengwang; Liu, Li; Chen, Jinhu; Li, Hongsheng; Yin, Yong; Ibragimov, Bulat; Xing, Lei

2017-01-07

Atlas-based segmentation utilizes a library of previously delineated contours of similar cases to facilitate automatic segmentation. The problem, however, remains challenging because of limited information carried by the contours in the library. In this studying, we developed a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. This study presented a new concept of atlas based segmentation method. Instead of using the complete volume of the target organs, only information along the organ contours from the atlas images was used for guiding segmentation of the new image. In setting up an atlas-based library, we included not only the coordinates of contour points, but also the image features adjacent to the contour. In this work, 139 CT images with normal appearing livers collected for radiotherapy treatment planning were used to construct the library. The CT images within the library were first registered to each other using affine registration. The nonlinear narrow shell was generated alongside the object contours of registered images. Matching voxels were selected inside common narrow shell image features of a library case and a new case using a speed-up robust features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the new image by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy optimization within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by physicians. A novel atlas-based segmentation technique with inclusion of neighborhood image features through the introduction of a narrow-shell surrounding the target objects was established. Application of the technique to 30 liver cases suggested that the technique was capable to reliably segment liver cases from CT, 4D-CT, and CBCT images with little human interaction. The accuracy and speed of the proposed method are quantitatively validated by comparing automatic segmentation results with the manual delineation results. The Jaccard similarity metric between the automatically generated liver contours obtained by the proposed method and the physician delineated results are on an average 90%-96% for planning images. Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically practical solution for auto-segmentation. The proposed mountainous narrow shell atlas based method can achieve efficient automatic liver propagation for CT, 4D-CT and CBCT images with following treatment planning and should find widespread application in future treatment planning systems.

Intraosseous mucoepidermoid carcinoma: a review of the diagnostic imaging features of four jaw cases.

PubMed

Chan, K C; Pharoah, M; Lee, L; Weinreb, I; Perez-Ordonez, B

2013-01-01

The purpose of this case series is to present the common features of intraosseous mucoepidermoid carcinoma (IMC) of the jaws in plain film and CT imaging. Two oral and maxillofacial radiologists reviewed and characterized the common features of four biopsy-proven cases of IMC in the jaws in plain film and CT imaging obtained from the files of the Department of Oral Radiology, Faculty of Dentistry, University of Toronto, Toronto, Canada. The common features are a well-defined sclerotic periphery, the presence of internal amorphous sclerotic bone and numerous small loculations, lack of septae bordering many of the loculations, and expansion and perforation of the outer cortical plate with extension into surrounding soft tissue. Other characteristics include tooth displacement and root resorption. The four cases of IMC reviewed have common imaging characteristics. All cases share some diagnostic imaging features with other multilocular-appearing entities of the jaws. However, the presence of amorphous sclerotic bone and malignant characteristics can be useful in the differential diagnosis.

Solitary pulmonary nodule: A rare presentation of pulmonary mucormycosis in an immunocompetent adult

PubMed Central

Sarkar, Supriya; Jash, Debraj; Maji, Arnab; Maikap, Malay Kr

2014-01-01

Pulmonary mucormycosis is a rare opportunistic infection of immunocompromised individuals. Here, we report a case of 70-year-old male, smoker presenting with high-grade fever for 2 weeks and episodes of hemoptysis. Contrast-enhanced computed tomography (CT) thorax revealed a solitary pulmonary nodule measuring 2.3 × 1.6 cm in the right upper lobe. CT guided fine needle aspiration cytology and true cut biopsy showed plenty of typical fungal hyphae consistent with the diagnosis of mucormycosis. Fungal culture confirmed the organism as mucor. Positron emission tomography-CT scan showed a non- 18 fluorodeoxy glucose avid nodule ruling out possibility of malignancy. Investigation did not reveal any evidence of immunosuppression. Patient was treated with intravenous liposomal amphotericin B for 4 weeks. Follow-up chest X-ray and CT scan after 6 weeks were normal. PMID:24669089

3D printing from microfocus computed tomography (micro-CT) in human specimens: education and future implications.

PubMed

Shelmerdine, Susan C; Simcock, Ian C; Hutchinson, John Ciaran; Aughwane, Rosalind; Melbourne, Andrew; Nikitichev, Daniil I; Ong, Ju-Ling; Borghi, Alessandro; Cole, Garrard; Kingham, Emilia; Calder, Alistair D; Capelli, Claudio; Akhtar, Aadam; Cook, Andrew C; Schievano, Silvia; David, Anna; Ourselin, Sebastian; Sebire, Neil J; Arthurs, Owen J

2018-06-14

Microfocus CT (micro-CT) is an imaging method that provides three-dimensional digital data sets with comparable resolution to light microscopy. Although it has traditionally been used for non-destructive testing in engineering, aerospace industries and in preclinical animal studies, new applications are rapidly becoming available in the clinical setting including post-mortem fetal imaging and pathological specimen analysis. Printing three-dimensional models from imaging data sets for educational purposes is well established in the medical literature, but typically using low resolution (0.7 mm voxel size) data acquired from CT or MR examinations. With higher resolution imaging (voxel sizes below 1 micron, <0.001 mm) at micro-CT, smaller structures can be better characterised, and data sets post-processed to create accurate anatomical models for review and handling. In this review, we provide examples of how three-dimensional printing of micro-CT imaged specimens can provide insight into craniofacial surgical applications, developmental cardiac anatomy, placental imaging, archaeological remains and high-resolution bone imaging. We conclude with other potential future usages of this emerging technique.

Bone metastases in castration-resistant prostate cancer: associations between morphologic CT patterns, glycolytic activity, and androgen receptor expression on PET and overall survival.

PubMed

Vargas, Hebert Alberto; Wassberg, Cecilia; Fox, Josef J; Wibmer, Andreas; Goldman, Debra A; Kuk, Deborah; Gonen, Mithat; Larson, Steven M; Morris, Michael J; Scher, Howard I; Hricak, Hedvig

2014-04-01

To compare the features of bone metastases at computed tomography (CT) to tracer uptake at fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) and fluorine 18 16β-fluoro-5-dihydrotestosterone (FDHT) PET and to determine associations between these imaging features and overall survival in men with castration-resistant prostate cancer. This is a retrospective study of 38 patients with castration-resistant prostate cancer. Two readers independently evaluated CT, FDG PET, and FDHT PET features of bone metastases. Associations between imaging findings and overall survival were determined by using univariate Cox proportional hazards regression. In 38 patients, reader 1 detected 881 lesions and reader 2 detected 867 lesions. Attenuation coefficients at CT correlated inversely with FDG (reader 1: r = -0.3007; P < .001; reader 2: r = -0.3147; P < .001) and FDHT (reader 1: r = -0.2680; P = .001; reader 2: r = -0.3656; P < .001) uptake. The number of lesions on CT scans was significantly associated with overall survival (reader 1: hazard ratio [HR], 1.025; P = .05; reader 2: HR, 1.021; P = .04). The numbers of lesions on FDG and FDHT PET scans were significantly associated with overall survival for reader 1 (HR, 1.051-1.109; P < .001) and reader 2 (HR, 1.026-1.082; P ≤ .009). Patients with higher FDHT uptake (lesion with the highest maximum standardized uptake value) had significantly shorter overall survival (reader 1: HR, 1.078; P = .02; reader 2: HR, 1.092; P = .02). FDG uptake intensity was not associated with overall survival (reader 1, P = .65; reader 2, P = .38). In patients with castration-resistant prostate cancer, numbers of bone lesions on CT, FDG PET, and FDHT PET scans and the intensity of FDHT uptake are significantly associated with overall survival. RSNA, 2013

Bone Metastases in Castration-Resistant Prostate Cancer: Associations between Morphologic CT Patterns, Glycolytic Activity, and Androgen Receptor Expression on PET and Overall Survival

PubMed Central

Wassberg, Cecilia; Fox, Josef J.; Wibmer, Andreas; Goldman, Debra A.; Kuk, Deborah; Gonen, Mithat; Larson, Steven M.; Morris, Michael J.; Scher, Howard I.; Hricak, Hedvig

2014-01-01

Purpose To compare the features of bone metastases at computed tomography (CT) to tracer uptake at fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) and fluorine 18 16β-fluoro-5-dihydrotestosterone (FDHT) PET and to determine associations between these imaging features and overall survival in men with castration-resistant prostate cancer. Materials and Methods This is a retrospective study of 38 patients with castration-resistant prostate cancer. Two readers independently evaluated CT, FDG PET, and FDHT PET features of bone metastases. Associations between imaging findings and overall survival were determined by using univariate Cox proportional hazards regression. Results In 38 patients, reader 1 detected 881 lesions and reader 2 detected 867 lesions. Attenuation coefficients at CT correlated inversely with FDG (reader 1: r = −0.3007; P < .001; reader 2: r = −0.3147; P < .001) and FDHT (reader 1: r = −0.2680; P = .001; reader 2: r = −0.3656; P < .001) uptake. The number of lesions on CT scans was significantly associated with overall survival (reader 1: hazard ratio [HR], 1.025; P = .05; reader 2: HR, 1.021; P = .04). The numbers of lesions on FDG and FDHT PET scans were significantly associated with overall survival for reader 1 (HR, 1.051–1.109; P < .001) and reader 2 (HR, 1.026–1.082; P ≤ .009). Patients with higher FDHT uptake (lesion with the highest maximum standardized uptake value) had significantly shorter overall survival (reader 1: HR, 1.078; P = .02; reader 2: HR, 1.092; P = .02). FDG uptake intensity was not associated with overall survival (reader 1, P = .65; reader 2, P = .38). Conclusion In patients with castration-resistant prostate cancer, numbers of bone lesions on CT, FDG PET, and FDHT PET scans and the intensity of FDHT uptake are significantly associated with overall survival. © RSNA, 2013 PMID:24475817

Adult granulosa cell tumor of the ovary: fine-needle-aspiration cytology of 10 cases and review of literature.

PubMed

Ali, Sarfraz; Gattuso, Paolo; Howard, Allison; Mosunjac, Marina B; Siddiqui, Momin T

2008-05-01

Adult granulosa cell tumor (GCT) of the ovary is mostly diagnosed in postmenopausal women. They typically secrete estrogen, which stimulates the endometrium to proliferate and cause abnormal bleeding. This study reviews the cytologic features of adult GCT of the ovary diagnosed by fine-needle aspiration (FNA). We reviewed slides from ten cases diagnosed by CT guided FNA from 1995 to 2007 at our institutions. Smears were stained with Diff-Quik and Papanicolaou stains. Patient's history and histologic diagnosis were also available and reviewed for all cases. The patients ranged in age from 39 to 83 yr. All 10 cases were hypercellular with both large and small overlapping cell clusters and individual cells. The cytologic features identified included: naked nuclei (10/10 cases), Call-Exner bodies (7/10 cases), blood vessels with prominent perivascular tumor cell growth (4/10 cases), spindle-shaped hyperchromatic stromal cells within cellular clusters (6/10 cases), mixed inflammation (3/10 cases), tumor cell necrosis (1/10 cases), and prominent metachromatic stroma seen in association with blood vessels (1/10 cases). Moderate to scant delicate cytoplasm was also seen (10/10 cases). Small, punctuate cytoplasmic vacuoles were also noted (7/10 cases) and were occasionally prominent (3/10 cases). In general nuclear to cytoplasmic ratios were high although lower than those typically seen in a lymphoma or small-cell carcinoma. Nuclei were generally centrally located although eccentrically located nuclei were consistently seen in a minority of cells. Nuclei were monotonous in size showing slightly convoluted (occasional rentiform and fetiform nuclei) to polygonal outlines. Prominent, central nucleoli were also seen (4/10 cases). Nuclear grooves were also seen (9/10 cases). No atypical mitotic activity was identified in any of the 10 cases (0/10 cases). In summary, the above cytologic features can also help in the cytologic diagnosis of adult GCTs.

Dental stigmata and enamel thickness in a probable case of congenital syphilis from XVI century Croatia.

PubMed

Lauc, Tomislav; Fornai, Cinzia; Premužić, Zrinka; Vodanović, Marin; Weber, Gerhard W; Mašić, Boris; Rajić Šikanjić, Petra

2015-10-01

To analyse the dental remains of an individual with signs of congenital syphilis by using macroscopic observation, CBCT and micro-CT images, and the analysis of the enamel thickness. Anthropological analysis of human skeletal remains from the 16th century archaeological site Park Grič in Zagreb, Croatia discovered a female, 17-20 years old at the time of death, with dental signs supportive of congenital syphilis: mulberry molars and canine defects, as well as non-specific hypoplastic changes on incisors. The focus of the analysis was on three aspects: gross morphology, hypoplastic defects of the molars, canines and incisors, as well as enamel thickness of the upper first and second molars. The observed morphology of the first molars corresponds to the typical aspect of mulberry molars, while that of the canines is characterised by hypomineralisation. Hypoplastic grooves were observed on the incisal edges of all incisors. The enamel of the first molars is underdeveloped while in the second molars a thick-enamelled condition is observed. Our observations for the dental and skeletal evidence are supportive to a diagnosis of congenital syphilis for this specimen from XVI century Croatia. The use of CT imaging helped documenting the diagnostic features and quantifying the effect of the dental stigmata on first molars. Copyright © 2015 Elsevier Ltd. All rights reserved.

Three-dimensional stereotactic atlas of the adult human skull correlated with the brain, cranial nerves, and intracranial vasculature.

PubMed

Nowinski, Wieslaw L; Thaung, Thant Shoon Let; Chua, Beng Choon; Yi, Su Hnin Wut; Ngai, Vincent; Yang, Yili; Chrzan, Robert; Urbanik, Andrzej

2015-05-15

Although the adult human skull is a complex and multifunctional structure, its 3D, complete, realistic, and stereotactic atlas has not yet been created. This work addresses the construction of a 3D interactive atlas of the adult human skull spatially correlated with the brain, cranial nerves, and intracranial vasculature. The process of atlas construction included computed tomography (CT) high-resolution scan acquisition, skull extraction, skull parcellation, 3D disarticulated bone surface modeling, 3D model simplification, brain-skull registration, 3D surface editing, 3D surface naming and color-coding, integration of the CT-derived 3D bony models with the existing brain atlas, and validation. The virtual skull model created is complete with all 29 bones, including the auditory ossicles (being among the smallest bones). It contains all typical bony features and landmarks. The created skull model is superior to the existing skull models in terms of completeness, realism, and integration with the brain along with blood vessels and cranial nerves. This skull atlas is valuable for medical students and residents to easily get familiarized with the skull and surrounding anatomy with a few clicks. The atlas is also useful for educators to prepare teaching materials. It may potentially serve as a reference aid in the reading and operating rooms. Copyright © 2015 Elsevier B.V. All rights reserved.

18F-FDG PET radiomics approaches: comparing and clustering features in cervical cancer.

PubMed

Tsujikawa, Tetsuya; Rahman, Tasmiah; Yamamoto, Makoto; Yamada, Shizuka; Tsuyoshi, Hideaki; Kiyono, Yasushi; Kimura, Hirohiko; Yoshida, Yoshio; Okazawa, Hidehiko

2017-11-01

The aims of our study were to find the textural features on 18 F-FDG PET/CT which reflect the different histological architectures between cervical cancer subtypes and to make a visual assessment of the association between 18 F-FDG PET textural features in cervical cancer. Eighty-three cervical cancer patients [62 squamous cell carcinomas (SCCs) and 21 non-SCCs (NSCCs)] who had undergone pretreatment 18 F-FDG PET/CT were enrolled. A texture analysis was performed on PET/CT images, from which 18 PET radiomics features were extracted including first-order features such as standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), second- and high-order textural features using SUV histogram, normalized gray-level co-occurrence matrix (NGLCM), and neighborhood gray-tone difference matrix, respectively. These features were compared between SCC and NSCC using a Bonferroni adjusted P value threshold of 0.0028 (0.05/18). To assess the association between PET features, a heat map analysis with hierarchical clustering, one of the radiomics approaches, was performed. Among 18 PET features, correlation, a second-order textural feature derived from NGLCM, was a stable parameter and it was the only feature which showed a robust trend toward significant difference between SCC and NSCC. Cervical SCC showed a higher correlation (0.70 ± 0.07) than NSCC (0.64 ± 0.07, P = 0.0030). The other PET features did not show any significant differences between SCC and NSCC. A higher correlation in SCC might reflect higher structural integrity and stronger spatial/linear relationship of cancer cells compared with NSCC. A heat map with a PET feature dendrogram clearly showed 5 distinct clusters, where correlation belonged to a cluster including MTV and TLG. However, the association between correlation and MTV/TLG was not strong. Correlation was a relatively independent PET feature in cervical cancer. 18 F-FDG PET textural features might reflect the differences in histological architecture between cervical cancer subtypes. PET radiomics approaches reveal the association between PET features and will be useful for finding a single feature or a combination of features leading to precise diagnoses, potential prognostic models, and effective therapeutic strategies.

Quantitative micro-CT based coronary artery profiling using interactive local thresholding and cylindrical coordinates.

PubMed

Panetta, Daniele; Pelosi, Gualtiero; Viglione, Federica; Kusmic, Claudia; Terreni, Marianna; Belcari, Nicola; Guerra, Alberto Del; Athanasiou, Lambros; Exarchos, Themistoklis; Fotiadis, Dimitrios I; Filipovic, Nenad; Trivella, Maria Giovanna; Salvadori, Piero A; Parodi, Oberdan

2015-01-01

Micro-CT is an established imaging technique for high-resolution non-destructive assessment of vascular samples, which is gaining growing interest for investigations of atherosclerotic arteries both in humans and in animal models. However, there is still a lack in the definition of micro-CT image metrics suitable for comprehensive evaluation and quantification of features of interest in the field of experimental atherosclerosis (ATS). A novel approach to micro-CT image processing for profiling of coronary ATS is described, providing comprehensive visualization and quantification of contrast agent-free 3D high-resolution reconstruction of full-length artery walls. Accelerated coronary ATS has been induced by high fat cholesterol-enriched diet in swine and left coronary artery (LCA) harvested en bloc for micro-CT scanning and histologic processing. A cylindrical coordinate system has been defined on the image space after curved multiplanar reformation of the coronary vessel for the comprehensive visualization of the main vessel features such as wall thickening and calcium content. A novel semi-automatic segmentation procedure based on 2D histograms has been implemented and the quantitative results validated by histology. The potentiality of attenuation-based micro-CT at low kV to reliably separate arterial wall layers from adjacent tissue as well as identify wall and plaque contours and major tissue components has been validated by histology. Morphometric indexes from histological data corresponding to several micro-CT slices have been derived (double observer evaluation at different coronary ATS stages) and highly significant correlations (R2 > 0.90) evidenced. Semi-automatic morphometry has been validated by double observer manual morphometry of micro-CT slices and highly significant correlations were found (R2 > 0.92). The micro-CT methodology described represents a handy and reliable tool for quantitative high resolution and contrast agent free full length coronary wall profiling, able to assist atherosclerotic vessels morphometry in a preclinical experimental model of coronary ATS and providing a link between in vivo imaging and histology.

Generation of brain pseudo-CTs using an undersampled, single-acquisition UTE-mDixon pulse sequence and unsupervised clustering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Su, Kuan-Hao; Hu, Lingzhi; Traughber, Melanie

Purpose: MR-based pseudo-CT has an important role in MR-based radiation therapy planning and PET attenuation correction. The purpose of this study is to establish a clinically feasible approach, including image acquisition, correction, and CT formation, for pseudo-CT generation of the brain using a single-acquisition, undersampled ultrashort echo time (UTE)-mDixon pulse sequence. Methods: Nine patients were recruited for this study. For each patient, a 190-s, undersampled, single acquisition UTE-mDixon sequence of the brain was acquired (TE = 0.1, 1.5, and 2.8 ms). A novel method of retrospective trajectory correction of the free induction decay (FID) signal was performed based on point-spreadmore » functions of three external MR markers. Two-point Dixon images were reconstructed using the first and second echo data (TE = 1.5 and 2.8 ms). R2{sup ∗} images (1/T2{sup ∗}) were then estimated and were used to provide bone information. Three image features, i.e., Dixon-fat, Dixon-water, and R2{sup ∗}, were used for unsupervised clustering. Five tissue clusters, i.e., air, brain, fat, fluid, and bone, were estimated using the fuzzy c-means (FCM) algorithm. A two-step, automatic tissue-assignment approach was proposed and designed according to the prior information of the given feature space. Pseudo-CTs were generated by a voxelwise linear combination of the membership functions of the FCM. A low-dose CT was acquired for each patient and was used as the gold standard for comparison. Results: The contrast and sharpness of the FID images were improved after trajectory correction was applied. The mean of the estimated trajectory delay was 0.774 μs (max: 1.350 μs; min: 0.180 μs). The FCM-estimated centroids of different tissue types showed a distinguishable pattern for different tissues, and significant differences were found between the centroid locations of different tissue types. Pseudo-CT can provide additional skull detail and has low bias and absolute error of estimated CT numbers of voxels (−22 ± 29 HU and 130 ± 16 HU) when compared to low-dose CT. Conclusions: The MR features generated by the proposed acquisition, correction, and processing methods may provide representative clustering information and could thus be used for clinical pseudo-CT generation.« less

Myoanatomy of the velvet worm leg revealed by laboratory-based nanofocus X-ray source tomography.

PubMed

Müller, Mark; de Sena Oliveira, Ivo; Allner, Sebastian; Ferstl, Simone; Bidola, Pidassa; Mechlem, Korbinian; Fehringer, Andreas; Hehn, Lorenz; Dierolf, Martin; Achterhold, Klaus; Gleich, Bernhard; Hammel, Jörg U; Jahn, Henry; Mayer, Georg; Pfeiffer, Franz

2017-11-21

X-ray computed tomography (CT) is a powerful noninvasive technique for investigating the inner structure of objects and organisms. However, the resolution of laboratory CT systems is typically limited to the micrometer range. In this paper, we present a table-top nanoCT system in conjunction with standard processing tools that is able to routinely reach resolutions down to 100 nm without using X-ray optics. We demonstrate its potential for biological investigations by imaging a walking appendage of Euperipatoides rowelli , a representative of Onychophora-an invertebrate group pivotal for understanding animal evolution. Comparative analyses proved that the nanoCT can depict the external morphology of the limb with an image quality similar to scanning electron microscopy, while simultaneously visualizing internal muscular structures at higher resolutions than confocal laser scanning microscopy. The obtained nanoCT data revealed hitherto unknown aspects of the onychophoran limb musculature, enabling the 3D reconstruction of individual muscle fibers, which was previously impossible using any laboratory-based imaging technique.

(18)F-fluorodeoxyglucose positron emission tomography/computed tomography comparison of gastric lymphoma and gastric carcinoma.

PubMed

Li, Xiao-Feng; Fu, Qiang; Dong, You-Wen; Liu, Jian-Jing; Song, Xiu-Yu; Dai, Dong; Zuo, Cong; Xu, Wen-Gui

2016-09-14

To compare (18)F-fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-FDG PET/CT) features in gastric lymphoma and gastric carcinoma. Patients with newly diagnosed gastric lymphoma or gastric carcinoma who underwent (18)F-FDG PET/CT prior to treatment were included in this study. We reviewed and analyzed the PET/CT features of gastric wall lesions, including FDG avidity, pattern (focal/diffuse), and intensity [maximal standard uptake value: (SUVmax)]. The correlation of SUVmax with gastric clinicopathological variables was investigated by χ(2) test, and receiver-operating characteristic (ROC) curve analysis was performed to determine the differential diagnostic value of SUVmax-associated parameters in gastric lymphoma and gastric carcinoma. Fifty-two patients with gastric lymphoma and 73 with gastric carcinoma were included in this study. Abnormal gastric FDG accumulation was found in 49 patients (94.23%) with gastric lymphoma and 65 patients (89.04%) with gastric carcinoma. Gastric lymphoma patients predominantly presented with type I and type II lesions, whereas gastric carcinoma patients mainly had type III lesions. The SUVmax (13.39 ± 9.24 vs 8.35 ± 5.80, P < 0.001) and SUVmax/THKmax (maximal thickness) (7.96 ± 4.02 vs 4.88 ± 3.32, P < 0.001) were both higher in patients with gastric lymphoma compared with gastric carcinoma. ROC curve analysis suggested a better performance of SUVmax/THKmax in the evaluation of gastric lesions between gastric lymphoma and gastric carcinoma in comparison with that of SUVmax alone. PET/CT features differ between gastric lymphoma and carcinoma, which can improve PET/CT evaluation of gastric wall lesions and help differentiate gastric lymphoma from gastric carcinoma.

18F-fluorodeoxyglucose positron emission tomography/computed tomography comparison of gastric lymphoma and gastric carcinoma

PubMed Central

Li, Xiao-Feng; Fu, Qiang; Dong, You-Wen; Liu, Jian-Jing; Song, Xiu-Yu; Dai, Dong; Zuo, Cong; Xu, Wen-Gui

2016-01-01

AIM To compare 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) features in gastric lymphoma and gastric carcinoma. METHODS Patients with newly diagnosed gastric lymphoma or gastric carcinoma who underwent 18F-FDG PET/CT prior to treatment were included in this study. We reviewed and analyzed the PET/CT features of gastric wall lesions, including FDG avidity, pattern (focal/diffuse), and intensity [maximal standard uptake value: (SUVmax)]. The correlation of SUVmax with gastric clinicopathological variables was investigated by χ2 test, and receiver-operating characteristic (ROC) curve analysis was performed to determine the differential diagnostic value of SUVmax-associated parameters in gastric lymphoma and gastric carcinoma. RESULTS Fifty-two patients with gastric lymphoma and 73 with gastric carcinoma were included in this study. Abnormal gastric FDG accumulation was found in 49 patients (94.23%) with gastric lymphoma and 65 patients (89.04%) with gastric carcinoma. Gastric lymphoma patients predominantly presented with type I and type II lesions, whereas gastric carcinoma patients mainly had type III lesions. The SUVmax (13.39 ± 9.24 vs 8.35 ± 5.80, P < 0.001) and SUVmax/THKmax (maximal thickness) (7.96 ± 4.02 vs 4.88 ± 3.32, P < 0.001) were both higher in patients with gastric lymphoma compared with gastric carcinoma. ROC curve analysis suggested a better performance of SUVmax/THKmax in the evaluation of gastric lesions between gastric lymphoma and gastric carcinoma in comparison with that of SUVmax alone. CONCLUSION PET/CT features differ between gastric lymphoma and carcinoma, which can improve PET/CT evaluation of gastric wall lesions and help differentiate gastric lymphoma from gastric carcinoma. PMID:27678362

Quantitative computed tomography features and clinical manifestations associated with the extent of bronchiectasis in patients with moderate-to-severe COPD

PubMed Central

Bak, So Hyeon; Kim, Soohyun; Hong, Yoonki; Heo, Jeongwon; Lim, Myoung-Nam; Kim, Woo Jin

2018-01-01

Background Few studies have investigated the quantitative computed tomography (CT) features associated with the severity of bronchiectasis in COPD patients. The purpose of this study was to identify the quantitative CT features and clinical values to determine the extent of bronchiectasis in moderate-to-severe COPD patients. Methods A total of 127 moderate-to-severe COPD patients were selected from the cohort of COPD in Dusty Areas (CODA). The study subjects were classified into three groups according to the extent of bronchiectasis on CT: no bronchiectasis, mild bronchiectasis, and moderate-to-severe bronchiectasis. The three groups were compared with respect to demographic data, symptoms, medical history, serum inflammatory markers, pulmonary function, and quantitative CT values. Results Among 127 moderate-to-severe COPD subjects, 73 patients (57.5%) were detected to have bronchiectasis, 51 patients (40.2%) to have mild bronchiectasis, and 22 patients (17.3%) to have moderate-to-severe bronchiectasis. Compared with COPD patients without bronchiectasis, those with bronchiectasis were older and had higher frequency of prior tuberculosis, lower prevalence of bronchodilator reversibility (BDR), and more severe air trapping (P < 0.05). Moderate-to-severe bronchiectasis patients had lower body mass index (BMI), higher frequency of prior tuberculosis, lower prevalence of BDR, worse pulmonary function, and more severe air trapping (P < 0.05) than those in the mild bronchiectasis group. Conclusion Moderate-to-severe bronchiectasis was associated with a history of pulmonary tuberculosis, lower BMI, severe airflow obstruction, and lower BDR in moderate-to-severe COPD patients. Quantitative analysis of CT showed that severe air trapping was associated with the extent of bronchiectasis in these patients. PMID:29750028

Quantitative coronary plaque analysis predicts high-risk plaque morphology on coronary computed tomography angiography: results from the ROMICAT II trial.

PubMed

Liu, Ting; Maurovich-Horvat, Pál; Mayrhofer, Thomas; Puchner, Stefan B; Lu, Michael T; Ghemigian, Khristine; Kitslaar, Pieter H; Broersen, Alexander; Pursnani, Amit; Hoffmann, Udo; Ferencik, Maros

2018-02-01

Semi-automated software can provide quantitative assessment of atherosclerotic plaques on coronary CT angiography (CTA). The relationship between established qualitative high-risk plaque features and quantitative plaque measurements has not been studied. We analyzed the association between quantitative plaque measurements and qualitative high-risk plaque features on coronary CTA. We included 260 patients with plaque who underwent coronary CTA in the Rule Out Myocardial Infarction/Ischemia Using Computer Assisted Tomography (ROMICAT) II trial. Quantitative plaque assessment and qualitative plaque characterization were performed on a per coronary segment basis. Quantitative coronary plaque measurements included plaque volume, plaque burden, remodeling index, and diameter stenosis. In qualitative analysis, high-risk plaque was present if positive remodeling, low CT attenuation plaque, napkin-ring sign or spotty calcium were detected. Univariable and multivariable logistic regression analyses were performed to assess the association between quantitative and qualitative high-risk plaque assessment. Among 888 segments with coronary plaque, high-risk plaque was present in 391 (44.0%) segments by qualitative analysis. In quantitative analysis, segments with high-risk plaque had higher total plaque volume, low CT attenuation plaque volume, plaque burden and remodeling index. Quantitatively assessed low CT attenuation plaque volume (odds ratio 1.12 per 1 mm 3 , 95% CI 1.04-1.21), positive remodeling (odds ratio 1.25 per 0.1, 95% CI 1.10-1.41) and plaque burden (odds ratio 1.53 per 0.1, 95% CI 1.08-2.16) were associated with high-risk plaque. Quantitative coronary plaque characteristics (low CT attenuation plaque volume, positive remodeling and plaque burden) measured by semi-automated software correlated with qualitative assessment of high-risk plaque features.

COMPUTED TOMOGRAPHIC FEATURES OF INCISOR PSEUDO-ODONTOMAS IN PRAIRIE DOGS (CYNOMYS LUDOVICIANUS).

PubMed

Pelizzone, Igor; Di Ianni, Francesco; Volta, Antonella; Gnudi, Giacomo; Manfredi, Sabrina; Bertocchi, Mara; Parmigiani, Enrico

2017-05-01

Maxillary incisor pseudo-odontomas are common in pet prairie dogs and can cause progressive respiratory obstruction, while mandibular pseudo-odontomas are rarely clinically significant. The aim of this retrospective cross-sectional study was to describe CT features of maxillary and mandibular incisor pseudo-odontomas vs. normal incisors in a group of pet prairie dogs. All pet prairie dogs with head CT scans acquired during the period of 2013-2015 were included. A veterinary radiologist who was aware of final diagnosis reviewed CT scans and recorded qualitative features of affected and normal incisors. Mean density values for the pulp cavity and palatal and buccal dentin were also recorded. A total of 16 prairie dogs were sampled (12 normal maxillary incisors, 20 confirmed maxillary incisor pseudo-odontomas, 20 normal mandibular incisors, 12 presumed mandibular incisor pseudo-odontomas). Maxillary incisors with confirmed pseudo-odontomas had a significantly hyperattenuating pulp and dentin in the reserve crown and apical zone, when compared to normal maxillary incisors. Pseudo-odontomas appeared as enlargements of the apical zone with a globular/multilobular hyperattenuating mass formation haphazardly arranged, encroaching on midline and growing caudally and ventrally. Presumed mandibular incisor pseudo-odontomas had similar CT characteristics. In 60% of prairie dogs with maxillary incisor pseudo-odontomas, the hard palate was deformed and the mass bulged into the oral cavity causing loss of the palatine bone. The common nasal meatus was partially or totally obliterated in 81.8% of prairie dogs with maxillary pseudo-odontomas. Findings supported the use of CT for characterizing extent of involvement and surgical planning in prairie dogs with pseudo-odontomas. © 2017 American College of Veterinary Radiology.

Tissue segmentation of computed tomography images using a Random Forest algorithm: a feasibility study

NASA Astrophysics Data System (ADS)

Polan, Daniel F.; Brady, Samuel L.; Kaufman, Robert A.

2016-09-01

There is a need for robust, fully automated whole body organ segmentation for diagnostic CT. This study investigates and optimizes a Random Forest algorithm for automated organ segmentation; explores the limitations of a Random Forest algorithm applied to the CT environment; and demonstrates segmentation accuracy in a feasibility study of pediatric and adult patients. To the best of our knowledge, this is the first study to investigate a trainable Weka segmentation (TWS) implementation using Random Forest machine-learning as a means to develop a fully automated tissue segmentation tool developed specifically for pediatric and adult examinations in a diagnostic CT environment. Current innovation in computed tomography (CT) is focused on radiomics, patient-specific radiation dose calculation, and image quality improvement using iterative reconstruction, all of which require specific knowledge of tissue and organ systems within a CT image. The purpose of this study was to develop a fully automated Random Forest classifier algorithm for segmentation of neck-chest-abdomen-pelvis CT examinations based on pediatric and adult CT protocols. Seven materials were classified: background, lung/internal air or gas, fat, muscle, solid organ parenchyma, blood/contrast enhanced fluid, and bone tissue using Matlab and the TWS plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance evaluated over a voxel radius of 2 n , (n from 0 to 4), along with noise reduction and edge preserving filters: Gaussian, bilateral, Kuwahara, and anisotropic diffusion. The Random Forest algorithm used 200 trees with 2 features randomly selected per node. The optimized auto-segmentation algorithm resulted in 16 image features including features derived from maximum, mean, variance Gaussian and Kuwahara filters. Dice similarity coefficient (DSC) calculations between manually segmented and Random Forest algorithm segmented images from 21 patient image sections, were analyzed. The automated algorithm produced segmentation of seven material classes with a median DSC of 0.86  ±  0.03 for pediatric patient protocols, and 0.85  ±  0.04 for adult patient protocols. Additionally, 100 randomly selected patient examinations were segmented and analyzed, and a mean sensitivity of 0.91 (range: 0.82-0.98), specificity of 0.89 (range: 0.70-0.98), and accuracy of 0.90 (range: 0.76-0.98) were demonstrated. In this study, we demonstrate that this fully automated segmentation tool was able to produce fast and accurate segmentation of the neck and trunk of the body over a wide range of patient habitus and scan parameters.

Cross-sectional anatomy, computed tomography and magnetic resonance imaging of the head of common dolphin (Delphinus delphis) and striped dolphin (Stenella coeruleoalba).

PubMed

Alonso-Farré, J M; Gonzalo-Orden, M; Barreiro-Vázquez, J D; Barreiro-Lois, A; André, M; Morell, M; Llarena-Reino, M; Monreal-Pawlowsky, T; Degollada, E

2015-02-01

Computed tomography (CT) and low-field magnetic resonance imaging (MRI) were used to scan seven by-caught dolphin cadavers, belonging to two species: four common dolphins (Delphinus delphis) and three striped dolphins (Stenella coeruleoalba). CT and MRI were obtained with the animals in ventral recumbency. After the imaging procedures, six dolphins were frozen at -20°C and sliced in the same position they were examined. Not only CT and MRI scans, but also cross sections of the heads were obtained in three body planes: transverse (slices of 1 cm thickness) in three dolphins, sagittal (5 cm thickness) in two dolphins and dorsal (5 cm thickness) in two dolphins. Relevant anatomical structures were identified and labelled on each cross section, obtaining a comprehensive bi-dimensional topographical anatomy guide of the main features of the common and the striped dolphin head. Furthermore, the anatomical cross sections were compared with their corresponding CT and MRI images, allowing an imaging identification of most of the anatomical features. CT scans produced an excellent definition of the bony and air-filled structures, while MRI allowed us to successfully identify most of the soft tissue structures in the dolphin's head. This paper provides a detailed anatomical description of the head structures of common and striped dolphins and compares anatomical cross sections with CT and MRI scans, becoming a reference guide for the interpretation of imaging studies. © 2014 Blackwell Verlag GmbH.

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andrews, M; Abazeed, M; Woody, N

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported tomore » R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.« less

Retrospective data-driven respiratory gating for PET/CT

NASA Astrophysics Data System (ADS)

Schleyer, Paul J.; O'Doherty, Michael J.; Barrington, Sally F.; Marsden, Paul K.

2009-04-01

Respiratory motion can adversely affect both PET and CT acquisitions. Respiratory gating allows an acquisition to be divided into a series of motion-reduced bins according to the respiratory signal, which is typically hardware acquired. In order that the effects of motion can potentially be corrected for, we have developed a novel, automatic, data-driven gating method which retrospectively derives the respiratory signal from the acquired PET and CT data. PET data are acquired in listmode and analysed in sinogram space, and CT data are acquired in cine mode and analysed in image space. Spectral analysis is used to identify regions within the CT and PET data which are subject to respiratory motion, and the variation of counts within these regions is used to estimate the respiratory signal. Amplitude binning is then used to create motion-reduced PET and CT frames. The method was demonstrated with four patient datasets acquired on a 4-slice PET/CT system. To assess the accuracy of the data-derived respiratory signal, a hardware-based signal was acquired for comparison. Data-driven gating was successfully performed on PET and CT datasets for all four patients. Gated images demonstrated respiratory motion throughout the bin sequences for all PET and CT series, and image analysis and direct comparison of the traces derived from the data-driven method with the hardware-acquired traces indicated accurate recovery of the respiratory signal.

TU-AB-BRA-10: Prognostic Value of Intra-Radiation Treatment FDG-PET and CT Imaging Features in Locally Advanced Head and Neck Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, J; Pollom, E; Durkee, B

2015-06-15

Purpose: To predict response to radiation treatment using computational FDG-PET and CT images in locally advanced head and neck cancer (HNC). Methods: 68 patients with State III-IVB HNC treated with chemoradiation were included in this retrospective study. For each patient, we analyzed primary tumor and lymph nodes on PET and CT scans acquired both prior to and during radiation treatment, which led to 8 combinations of image datasets. From each image set, we extracted high-throughput, radiomic features of the following types: statistical, morphological, textural, histogram, and wavelet, resulting in a total of 437 features. We then performed unsupervised redundancy removalmore » and stability test on these features. To avoid over-fitting, we trained a logistic regression model with simultaneous feature selection based on least absolute shrinkage and selection operator (LASSO). To objectively evaluate the prediction ability, we performed 5-fold cross validation (CV) with 50 random repeats of stratified bootstrapping. Feature selection and model training was solely conducted on the training set and independently validated on the holdout test set. Receiver operating characteristic (ROC) curve of the pooled Result and the area under the ROC curve (AUC) was calculated as figure of merit. Results: For predicting local-regional recurrence, our model built on pre-treatment PET of lymph nodes achieved the best performance (AUC=0.762) on 5-fold CV, which compared favorably with node volume and SUVmax (AUC=0.704 and 0.449, p<0.001). Wavelet coefficients turned out to be the most predictive features. Prediction of distant recurrence showed a similar trend, in which pre-treatment PET features of lymph nodes had the highest AUC of 0.705. Conclusion: The radiomics approach identified novel imaging features that are predictive to radiation treatment response. If prospectively validated in larger cohorts, they could aid in risk-adaptive treatment of HNC.« less

Evaluation of chemotherapy response in ovarian cancer treatment using quantitative CT image biomarkers: a preliminary study

NASA Astrophysics Data System (ADS)

Qiu, Yuchen; Tan, Maxine; McMeekin, Scott; Thai, Theresa; Moore, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

2015-03-01

The purpose of this study is to identify and apply quantitative image biomarkers for early prediction of the tumor response to the chemotherapy among the ovarian cancer patients participated in the clinical trials of testing new drugs. In the experiment, we retrospectively selected 30 cases from the patients who participated in Phase I clinical trials of new drug or drug agents for ovarian cancer treatment. Each case is composed of two sets of CT images acquired pre- and post-treatment (4-6 weeks after starting treatment). A computer-aided detection (CAD) scheme was developed to extract and analyze the quantitative image features of the metastatic tumors previously tracked by the radiologists using the standard Response Evaluation Criteria in Solid Tumors (RECIST) guideline. The CAD scheme first segmented 3-D tumor volumes from the background using a hybrid tumor segmentation scheme. Then, for each segmented tumor, CAD computed three quantitative image features including the change of tumor volume, tumor CT number (density) and density variance. The feature changes were calculated between the matched tumors tracked on the CT images acquired pre- and post-treatments. Finally, CAD predicted patient's 6-month progression-free survival (PFS) using a decision-tree based classifier. The performance of the CAD scheme was compared with the RECIST category. The result shows that the CAD scheme achieved a prediction accuracy of 76.7% (23/30 cases) with a Kappa coefficient of 0.493, which is significantly higher than the performance of RECIST prediction with a prediction accuracy and Kappa coefficient of 60% (17/30) and 0.062, respectively. This study demonstrated the feasibility of analyzing quantitative image features to improve the early predicting accuracy of the tumor response to the new testing drugs or therapeutic methods for the ovarian cancer patients.

TU-F-CAMPUS-I-05: Investigation of An EMCCD Detector with Variable Gain in a Micro-CT System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnakumar, S Bysani; Ionita, C; Rudin, S

Purpose: To investigate the performance of a newly built Electron Multiplying Charged Coupled Device (EMCCD) based Micro-CT system, with variable detector gain, using a phantom containing contrast agent of different concentrations. Methods: We built a micro- CT system with an EMCCD having 8 microns pixels and on-chip variable gain. We tested the system using a phantom containing five tubes filled with different iodine contrast solutions (30% to 70%). First, we scanned the phantom using various x-ray exposures values at 40 kVp and constant detector gain. Next, for the same tube currents, the detector gain was increased to maintain the airmore » value of the projection image constant. A standard FDK algorithm was used to reconstruct the data. Performance was analyzed by comparing the signal-to-noise ratio (SNR) measurements for increased gain with those for the low constant gain at each exposure. Results: The high detector gain reconstructed data SNR was always greater than the low gain data SNR for all x-ray settings and for all iodine features. The largest increases were observed for low contrast features, 30% iodine concentration, where the SNR improvement approached 2. Conclusion: One of the first implementations of an EMCCD based micro- CT system was presented and used to image a phantom with various iodine solution concentrations. The analysis of the reconstructed volumes showed a significant improvement of the SNR especially for low contrast features. The unique on-chip gain feature is a substantial benefit allowing the use of the system at very low x-ray exposures per frame.Partial support: NIH grant R01EB002873 and Toshiba Medical Systems Corp. Partial support: NIH grant R01EB002873 and Toshiba Medical Systems Corp.« less

Clinical, pathological and thin-section CT features of persistent multiple ground-glass opacity nodules: comparison with solitary ground-glass opacity nodule.

PubMed

Kim, Tae Jung; Goo, Jin Mo; Lee, Kyung Won; Park, Chang Min; Lee, Hyun Ju

2009-05-01

To retrospectively compare the clinical, pathological, and thin-section CT features of persistent multiple ground-glass opacity (GGO) nodules with those of solitary GGO nodules. Histopathologic specimens were obtained from 193 GGO nodules in 136 patients (87 women, 49 men; mean age, 57; age range 33-81). The clinical data, pathologic findings, and thin-section CT features of multiple and solitary GGO nodules were compared by using t-test or Fisher's exact test. Multiple GGO nodules (n=105) included atypical adenomatous hyperplasia (AAH) (n=31), bronchioloalveolar carcinoma (BAC) (n=33), adenocarcinoma (n=34) and focal interstitial fibrosis (n=7). Solitary GGO nodules included AAH (n=8), BAC (n=15), adenocarcinoma (n=55) and focal interstitial fibrosis (n=10). AAH (P=.001) and BAC (P=.029) were more frequent in multiple GGO nodules, whereas adenocarcinoma (P<.001) was more frequent in solitary GGO nodules. Female sex (P<.001), nonsmoker (P=.012) and multiple primary lung cancers (P<.001) were more frequent for multiple GGO nodules, which were smaller (12 mm+/-7.9) than solitary GGO nodules (17 mm+/-8.1) (P<.001). Air-bronchogram (P=.019), bubble-lucency (P=.004), and pleural retraction (P<.001) were more frequent in solitary GGO nodules. There was no postoperative recurrence except for one patient with multiple GGO nodules and one with solitary GGO nodule. Clinical, pathological, and thin-section CT features of persistent multiple GGO nodules were found to differ from those of solitary GGO nodules. Nevertheless, the two nodule types can probably be followed up and managed in a similar manner because their prognoses were found to be similar.

Recurrent dermatofibrosarcoma protuberans with pulmonary metastases presenting twelve years after initial diagnosis: 18F-FDG PET/CT imaging findings.

PubMed

Suman, Sudhir; Sharma, Punit; Jain, Tarun Kumar; Sahoo, Manas Kumar; Bal, Chandrasekhar; Kumar, Rakesh

2014-01-01

Dermatofibrosarcoma protuberans is a rare cutaneous tumor that is locally aggressive and has a high rate of recurrence after surgical excision. The tumor grows slowly, typically over years. On rare occasions, metastasis to distant sites (especially the lung) or regional lymph nodes may occur. Here, we present F-FDG PET/CT imaging findings of a 52-year-old man with a local recurrence of dermatofibrosarcoma protuberans in the anterior abdominal wall with metastases to bilateral lungs.

Automated assessment of aortic and main pulmonary arterial diameters using model-based blood vessel segmentation for predicting chronic thromboembolic pulmonary hypertension in low-dose CT lung screening

NASA Astrophysics Data System (ADS)

Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Sugiura, Toshihiko; Tanabe, Nobuhiro; Kusumoto, Masahiko; Eguchi, Kenji; Kaneko, Masahiro

2018-02-01

Chronic thromboembolic pulmonary hypertension (CTEPH) is characterized by obstruction of the pulmonary vasculature by residual organized thrombi. A morphological abnormality inside mediastinum of CTEPH patient is enlargement of pulmonary artery. This paper presents an automated assessment of aortic and main pulmonary arterial diameters for predicting CTEPH in low-dose CT lung screening. The distinctive feature of our method is to segment aorta and main pulmonary artery using both of prior probability and vascular direction which were estimated from mediastinal vascular region using principal curvatures of four-dimensional hyper surface. The method was applied to two datasets, 64 lowdose CT scans of lung cancer screening and 19 normal-dose CT scans of CTEPH patients through the training phase with 121 low-dose CT scans. This paper demonstrates effectiveness of our method for predicting CTEPH in low-dose CT screening.

SU-D-BRA-07: A Phantom Study to Assess the Variability in Radiomics Features Extracted From Cone-Beam CT Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fave, X; Fried, D; UT Health Science Center Graduate School of Biomedical Sciences, Houston, TX

2015-06-15

Purpose: Several studies have demonstrated the prognostic potential for texture features extracted from CT images of non-small cell lung cancer (NSCLC) patients. The purpose of this study was to determine if these features could be extracted with high reproducibility from cone-beam CT (CBCT) images in order for features to be easily tracked throughout a patient’s treatment. Methods: Two materials in a radiomics phantom, designed to approximate NSCLC tumor texture, were used to assess the reproducibility of 26 features. This phantom was imaged on 9 CBCT scanners, including Elekta and Varian machines. Thoracic and head imaging protocols were acquired on eachmore » machine. CBCT images from 27 NSCLC patients imaged using the thoracic protocol on Varian machines were obtained for comparison. The variance for each texture measured from these patients was compared to the variance in phantom values for different manufacturer/protocol subsets. Levene’s test was used to identify features which had a significantly smaller variance in the phantom scans versus the patient data. Results: Approximately half of the features (13/26 for material1 and 15/26 for material2) had a significantly smaller variance (p<0.05) between Varian thoracic scans of the phantom compared to patient scans. Many of these same features remained significant for the head scans on Varian (12/26 and 8/26). However, when thoracic scans from Elekta and Varian were combined, only a few features were still significant (4/26 and 5/26). Three features (skewness, coarsely filtered mean and standard deviation) were significant in almost all manufacturer/protocol subsets. Conclusion: Texture features extracted from CBCT images of a radiomics phantom are reproducible and show significantly less variation than the same features measured from patient images when images from the same manufacturer or with similar parameters are used. Reproducibility between CBCT scanners may be high enough to allow the extraction of meaningful texture values for patients. This project was funded in part by the Cancer Prevention Research Institute of Texas (CPRIT). Xenia Fave is a recipient of the American Association of Physicists in Medicine Graduate Fellowship.« less

Teaching CSD Graduate Students to Think Critically, Apply Evidence, and Write Professionally

ERIC Educational Resources Information Center

Grillo, Elizabeth U.; Koenig, Mareile A.; Gunter, Cheryl D.; Kim, Sojung

2015-01-01

The purpose of this study was to assess the effectiveness of teaching modules designed to enhance the use of critical thinking (CT), evidence-based practice (EBP), and professional writing (PW) skills by graduate students in communication sciences and disorders. Three single-session teaching modules were developed to highlight key features of CT,…

Low-voltage chest CT: another way to reduce the radiation dose in asbestos-exposed patients.

PubMed

Macía-Suárez, D; Sánchez-Rodríguez, E; Lopez-Calviño, B; Diego, C; Pombar, M

2017-09-01

To assess whether low voltage chest computed tomography (CT) can be used to successfully diagnose disease in patients with asbestos exposure. Fifty-six former employees of the shipbuilding industry, who were candidates to receive a standard-dose chest CT due to their occupational exposure to asbestos, underwent a routine CT. Immediately after this initial CT, they underwent a second acquisition using low-dose chest CT parameters, based on a low potential (80 kV) and limited tube current. The findings of the two CT protocols were compared based on typical diseases associated with asbestos exposure. The kappa coefficient for each parameter and for an overall rating (grouping them based on mediastinal, pleural, and pulmonary findings) were calculated in order to test for correlations between the two protocols. A good correlation between routine and low-dose CT was demonstrated for most parameters with a mean radiation dose reduction of up to 83% of the effective dose based on the dose-length product between protocols. Low-dose chest CT, based on a limited tube potential, is useful for patients with an asbestos exposure background. Low-dose chest CT can be successfully used to minimise the radiation dose received by patients, as this protocol produced an estimated mean effective dose similar to that of an abdominal or pelvis plain film. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Stability of deep features across CT scanners and field of view using a physical phantom

NASA Astrophysics Data System (ADS)

Paul, Rahul; Shafiq-ul-Hassan, Muhammad; Moros, Eduardo G.; Gillies, Robert J.; Hall, Lawrence O.; Goldgof, Dmitry B.

2018-02-01

Radiomics is the process of analyzing radiological images by extracting quantitative features for monitoring and diagnosis of various cancers. Analyzing images acquired from different medical centers is confounded by many choices in acquisition, reconstruction parameters and differences among device manufacturers. Consequently, scanning the same patient or phantom using various acquisition/reconstruction parameters as well as different scanners may result in different feature values. To further evaluate this issue, in this study, CT images from a physical radiomic phantom were used. Recent studies showed that some quantitative features were dependent on voxel size and that this dependency could be reduced or removed by the appropriate normalization factor. Deep features extracted from a convolutional neural network, may also provide additional features for image analysis. Using a transfer learning approach, we obtained deep features from three convolutional neural networks pre-trained on color camera images. An we examination of the dependency of deep features on image pixel size was done. We found that some deep features were pixel size dependent, and to remove this dependency we proposed two effective normalization approaches. For analyzing the effects of normalization, a threshold has been used based on the calculated standard deviation and average distance from a best fit horizontal line among the features' underlying pixel size before and after normalization. The inter and intra scanner dependency of deep features has also been evaluated.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foster, R; Ding, C; Jiang, S

Purpose Spine SRS/SAbR treatment plans typically require very steep dose gradients to meet spinal cord constraints and it is crucial that the dose distribution be accurate. However, these plans are typically calculated on helical free-breathing CT scans, which often contain motion artifacts. While the spine itself doesn’t exhibit very much intra-fraction motion, tissues around the spine, particularly the liver, do move with respiration. We investigated the dosimetric effect of liver motion on dose distributions calculated on helical free-breathing CT scans for spine SAbR delivered to the T and L spine. Methods We took 5 spine SAbR plans and used densitymore » overrides to simulate an average reconstruction CT image set, which would more closely represent the patient anatomy during treatment. The value used for the density override was 0.66 g/cc. All patients were planned using our standard beam arrangement, which consists of 13 coplanar step and shoot IMRT beams. The original plan was recalculated with the same MU on the “average” scan and target coverage and spinal cord dose were compared to the original plan. Results The average changes in minimum PTV dose, PTV coverage, max cord dose and volume of cord receiving 10 Gy were 0.6%, 0.8%, 0.3% and 4.4% (0.012 cc), respectively. Conclusion SAbR spine plans are surprisingly robust relative to surrounding organ motion due to respiration. Motion artifacts in helical planning CT scans do not cause clinically significant differences when these plans are re-calculated on pseudo-average CT reconstructions. This is likely due to the beam arrangement used because only three beams pass through the liver and only one beam passes completely through the density override. The effect of the respiratory motion on VMAT plans for spine SAbR is being evaluated.« less

SU-F-SPS-03: Direct Measurement of Organ Doses Resulting From Head and Cervical Spine Trauma CT Protocols

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carranza, C; Lipnharski, I; Quails, N

Purpose: This retrospective study analyzes the exposure history of emergency department (ED) patients undergoing head and cervical spine trauma computed tomography (CT) studies. This study investigated dose levels received by trauma patients and addressed any potential concerns regarding radiation dose issues. Methods: Under proper IRB approval, a cohort of 300 trauma cases of head and cervical spine trauma CT scans received in the ED was studied. The radiological image viewing software of the hospital was used to view patient images and image data. The following parameters were extracted: the imaging history of patients, the reported dose metrics from the scannermore » including the volumetric CT Dose Index (CTDIvol) and Dose Length Product (DLP). A postmortem subject was scanned using the same scan techniques utilized in a standard clinical head and cervical spine trauma CT protocol with 120 kVp and 280 mAs. The CTDIvol was recorded for the subject and the organ doses were measured using optically stimulated luminescent (OSL) dosimeters. Typical organ doses to the brain, thyroid, lens, salivary glands, and skin, based on the cadaver studies, were then calculated and reported for the cohort. Results: The CTDIvol reported by the CT scanner was 25.5 mGy for the postmortem subject. The average CTDIvol from the patient cohort was 34.1 mGy. From these metrics, typical average organ doses in mGy were found to be: Brain (44.57), Thyroid (33.40), Lens (82.45), Salivary Glands (61.29), Skin (47.50). The imaging history of the cohort showed that on average trauma patients received 26.1 scans over a lifetime. Conclusion: The average number of scans received on average by trauma ED patients shows that radiation doses in trauma patients may be a concern. Available dose tracking software would be helpful to track doses in trauma ED patients, highlighting the importance of minimizing unnecessary scans and keeping doses ALARA.« less

Auditing SNOMED CT hierarchical relations based on lexical features of concepts in non-lattice subgraphs.

PubMed

Cui, Licong; Bodenreider, Olivier; Shi, Jay; Zhang, Guo-Qiang

2018-02-01

We introduce a structural-lexical approach for auditing SNOMED CT using a combination of non-lattice subgraphs of the underlying hierarchical relations and enriched lexical attributes of fully specified concept names. Our goal is to develop a scalable and effective approach that automatically identifies missing hierarchical IS-A relations. Our approach involves 3 stages. In stage 1, all non-lattice subgraphs of SNOMED CT's IS-A hierarchical relations are extracted. In stage 2, lexical attributes of fully-specified concept names in such non-lattice subgraphs are extracted. For each concept in a non-lattice subgraph, we enrich its set of attributes with attributes from its ancestor concepts within the non-lattice subgraph. In stage 3, subset inclusion relations between the lexical attribute sets of each pair of concepts in each non-lattice subgraph are compared to existing IS-A relations in SNOMED CT. For concept pairs within each non-lattice subgraph, if a subset relation is identified but an IS-A relation is not present in SNOMED CT IS-A transitive closure, then a missing IS-A relation is reported. The September 2017 release of SNOMED CT (US edition) was used in this investigation. A total of 14,380 non-lattice subgraphs were extracted, from which we suggested a total of 41,357 missing IS-A relations. For evaluation purposes, 200 non-lattice subgraphs were randomly selected from 996 smaller subgraphs (of size 4, 5, or 6) within the "Clinical Finding" and "Procedure" sub-hierarchies. Two domain experts confirmed 185 (among 223) suggested missing IS-A relations, a precision of 82.96%. Our results demonstrate that analyzing the lexical features of concepts in non-lattice subgraphs is an effective approach for auditing SNOMED CT. Copyright © 2017 Elsevier Inc. All rights reserved.

Computed Tomographic Distinction of Intimal and Medial Calcification in the Intracranial Internal Carotid Artery.

PubMed

Kockelkoren, Remko; Vos, Annelotte; Van Hecke, Wim; Vink, Aryan; Bleys, Ronald L A W; Verdoorn, Daphne; Mali, Willem P Th M; Hendrikse, Jeroen; Koek, Huiberdina L; de Jong, Pim A; De Vis, Jill B

2017-01-01

Intracranial internal carotid artery (iICA) calcification is associated with stroke and is often seen as a proxy of atherosclerosis of the intima. However, it was recently shown that these calcifications are predominantly located in the tunica media and internal elastic lamina (medial calcification). Intimal and medial calcifications are thought to have a different pathogenesis and clinical consequences and can only be distinguished through ex vivo histological analysis. Therefore, our aim was to develop CT scoring method to distinguish intimal and medial iICA calcification in vivo. First, in both iICAs of 16 cerebral autopsy patients the intimal and/or medial calcification area was histologically assessed (142 slides). Brain CT images of these patients were matched to the corresponding histological slides to develop a CT score that determines intimal or medial calcification dominance. Second, performance of the CT score was assessed in these 16 patients. Third, reproducibility was tested in a separate cohort. First, CT features of the score were circularity (absent, dot(s), <90°, 90-270° or 270-360°), thickness (absent, ≥1.5mm, or <1.5mm), and morphology (indistinguishable, irregular/patchy or continuous). A high sum of features represented medial and a lower sum intimal calcifications. Second, in the 16 patients the concordance between the CT score and the dominant calcification type was reasonable. Third, the score showed good reproducibility (kappa: 0.72 proportion of agreement: 0.82) between the categories intimal, medial or absent/indistinguishable. The developed CT score shows good reproducibility and can differentiate reasonably well between intimal and medial calcification dominance in the iICA, allowing for further (epidemiological) studies on iICA calcification.

Spatial clustering of high load ocular Chlamydia trachomatis infection in trachoma: a cross-sectional population-based study.

PubMed

Last, Anna; Burr, Sarah; Alexander, Neal; Harding-Esch, Emma; Roberts, Chrissy H; Nabicassa, Meno; Cassama, Eunice Teixeira da Silva; Mabey, David; Holland, Martin; Bailey, Robin

2017-07-31

Chlamydia trachomatis (Ct) is the most common cause of bacterial sexually transmitted infection and infectious cause of blindness (trachoma) worldwide. Understanding the spatial distribution of Ct infection may enable us to identify populations at risk and improve our understanding of Ct transmission. In this study, we sought to investigate the spatial distribution of Ct infection and the clinical features associated with high Ct load in trachoma-endemic communities on the Bijagós Archipelago (Guinea Bissau). We collected 1507 conjunctival samples and corresponding detailed clinical data during a cross-sectional population-based geospatially representative trachoma survey. We used droplet digital PCR to estimate Ct load on conjunctival swabs. Geostatistical tools were used to investigate clustering of ocular Ct infections. Spatial clusters (independent of age and gender) of individuals with high Ct loads were identified using local indicators of spatial association. We did not detect clustering of individuals with low load infections. These data suggest that infections with high bacterial load may be important in Ct transmission. These geospatial tools may be useful in the study of ocular Ct transmission dynamics and as part of trachoma surveillance post-treatment, to identify clusters of infection and thresholds of Ct load that may be important foci of re-emergent infection in communities. © FEMS 2017.

CT and PET-CT of a Dog with Multiple Pulmonary Adenocarcinoma

PubMed Central

KIM, Jisun; KWON, Seong Young; CENA, Rohani; PARK, Seungjo; OH, Juyeon; OUI, Heejin; CHO, Kyoung-Oh; MIN, Jung-Joon; CHOI, Jihye

2013-01-01

ABSTRACT A 10-year-old, intact female Yorkshire terrier had multiple pulmonary nodules on thoracic radiography and ultrasonography with no lesions elsewhere. Computed tomography (CT) and positron emission tomography and computed tomography (PET-CT) using 18F-fluorodeoxyglucose (FDG) were performed to identify metastasis and undetected primary tumors. On CT examination, pulmonary nodules had a hypoattenuating center with thin peripheral enhancement, suggesting ischemic or necrotizing lesion. In PET-CT at 47 min after intravenous injection of 11.1 MBq/kg of FDG, the maximum standardized uptake value of each pulmonary nodule was about from 3.8 to 6.4. There were no abnormal lesions except for four pulmonary nodules on the CT and PET-CT. Primary lung tumor was tentatively diagnosed, and palliative therapy using 2 mg/kg tramadol and 2.2 mg/kg carprofen twice per day was applied. After the dog’s euthanasia due to deteriorated clinical signs and poor prognosis, undifferentiated pulmonary adenocarcinoma was diagnosed through histopathologic and immunochemistry examination. To the best of the authors’ knowledge, this is the first study of CT and PET-CT features of canine pulmonary adenocarcinoma. In this case, multiple pulmonary adenocarcinoma could be determined on the basis of FDG PET-CT through screening the obvious distant metastasis and/or lymph node invasions and excluding unknown primary tumors. PMID:24389742

Pulsed excitation terahertz tomography - multiparametric approach

NASA Astrophysics Data System (ADS)

Lopato, Przemyslaw

2018-04-01

This article deals with pulsed excitation terahertz computed tomography (THz CT). Opposite to x-ray CT, where just a single value (pixel) is obtained, in case of pulsed THz CT the time signal is acquired for each position. Recorded waveform can be parametrized - many features carrying various information about examined structure can be calculated. Based on this, multiparametric reconstruction algorithm was proposed: inverse Radon transform based reconstruction is applied for each parameter and then fusion of results is utilized. Performance of the proposed imaging scheme was experimentally verified using dielectric phantoms.

Classification of pulmonary emphysema from chest CT scans using integral geometry descriptors

NASA Astrophysics Data System (ADS)

van Rikxoort, E. M.; Goldin, J. G.; Galperin-Aizenberg, M.; Brown, M. S.

2011-03-01

To gain insight into the underlying pathways of emphysema and monitor the effect of treatment, methods to quantify and phenotype the different types of emphysema from chest CT scans are of crucial importance. Current standard measures rely on density thresholds for individual voxels, which is influenced by inspiration level and does not take into account the spatial relationship between voxels. Measures based on texture analysis do take the interrelation between voxels into account and therefore might be useful for distinguishing different types of emphysema. In this study, we propose to use Minkowski functionals combined with rotation invariant Gaussian features to distinguish between healthy and emphysematous tissue and classify three different types of emphysema. Minkowski functionals characterize binary images in terms of geometry and topology. In 3D, four Minkowski functionals are defined. By varying the threshold and size of neighborhood around a voxel, a set of Minkowski functionals can be defined for each voxel. Ten chest CT scans with 1810 annotated regions were used to train the method. A set of 108 features was calculated for each training sample from which 10 features were selected to be most informative. A linear discriminant classifier was trained to classify each voxel in the lungs into a subtype of emphysema or normal lung. The method was applied to an independent test set of 30 chest CT scans with varying amounts and types of emphysema with 4347 annotated regions of interest. The method is shown to perform well, with an overall accuracy of 95%.

CT Radiogenomic Characterization of EGFR, K-RAS, and ALK Mutations in Non-Small Cell Lung Cancer.

PubMed

Rizzo, Stefania; Petrella, Francesco; Buscarino, Valentina; De Maria, Federica; Raimondi, Sara; Barberis, Massimo; Fumagalli, Caterina; Spitaleri, Gianluca; Rampinelli, Cristiano; De Marinis, Filippo; Spaggiari, Lorenzo; Bellomi, Massimo

2016-01-01

To assess the association between CT features and EGFR, ALK, KRAS mutations in non-small cell lung cancer. Patients undergoing chest CT and testing for the above gene mutations were included. Qualitative evaluation of CTs included: lobe; lesion diameter; shape; margins; ground-glass opacity; density; cavitation; air bronchogram; pleural thickening; intratumoral necrosis; nodules in tumour lobe; nodules in non-tumour lobes; pleural retraction; location; calcifications; emphysema; fibrosis; pleural contact; pleural effusion. Statistical analysis was performed to assess association of features with each gene mutation. ROC curves for gene mutations were drawn; the corresponding area under the curve was calculated. P-values <0.05 were considered significant. Of 285 patients, 60/280 (21.43 %) were positive for EGFR mutation; 31/270 (11.48 %) for ALK rearrangement; 64/240 (26.67 %) for KRAS mutation. EGFR mutation was associated with air bronchogram, pleural retraction, females, non-smokers, small lesion size, and absence of fibrosis. ALK rearrangements were associated with age and pleural effusion. KRAS mutation was associated with round shape, nodules in non-tumour lobes, and smoking. This study disclosed associations between CT features and alterations of EGFR (air bronchogram, pleural retraction, small lesion size, absence of fibrosis), ALK (pleural effusion) and KRAS (round lesion shape, nodules in non-tumour lobes). Air bronchogram, pleural retraction, small size relate to EGFR mutation in NSCLC. Pleural effusion and younger age relate to ALK mutation. Round lesion shape, nodules in non-tumour lobes relate to KRAS mutation.

Extraction of 3D Femur Neck Trabecular Bone Architecture from Clinical CT Images in Osteoporotic Evaluation: a Novel Framework.

PubMed

Sapthagirivasan, V; Anburajan, M; Janarthanam, S

2015-08-01

The early detection of osteoporosis risk enhances the lifespan and quality of life of an individual. A reasonable in-vivo assessment of trabecular bone strength at the proximal femur helps to evaluate the fracture risk and henceforth, to understand the associated structural dynamics on occurrence of osteoporosis. The main aim of our study was to develop a framework to automatically determine the trabecular bone strength from clinical femur CT images and thereby to estimate its correlation with BMD. All the 50 studied south Indian female subjects aged 30 to 80 years underwent CT and DXA measurements at right femur region. Initially, the original CT slices were intensified and active contour model was utilised for the extraction of the neck region. After processing through a novel process called trabecular enrichment approach (TEA), the three dimensional (3D) trabecular features were extracted. The extracted 3D trabecular features, such as volume fraction (VF), solidity of delta points (SDP) and boundness, demonstrated a significant correlation with femoral neck bone mineral density (r = 0.551, r = 0.432, r = 0.552 respectively) at p < 0.001. The higher area under the curve values of the extracted features (VF: 85.3 %; 95CI: 68.2-100 %, SDP: 82.1 %; 95CI: 65.1-98.9 % and boundness: 90.4 %; 95CI: 78.7-100 %) were observed. The findings suggest that the proposed framework with TEA method would be useful for spotting women vulnerable to osteoporotic risk.

The cheating liver: imaging of focal steatosis and fatty sparing.

PubMed

Dioguardi Burgio, Marco; Bruno, Onorina; Agnello, Francesco; Torrisi, Chiara; Vernuccio, Federica; Cabibbo, Giuseppe; Soresi, Maurizio; Petta, Salvatore; Calamia, Mauro; Papia, Giovanni; Gambino, Angelo; Ricceri, Viola; Midiri, Massimo; Lagalla, Roberto; Brancatelli, Giuseppe

2016-06-01

Focal steatosis and fatty sparing are a frequent finding in liver imaging, and can mimic solid lesions. Liver regional variations in the degree of fat accumulation can be related to vascular anomalies, metabolic disorders, use of certain drugs or coexistence of hepatic masses. CT and MRI are the modalities of choice for the noninvasive diagnosis of hepatic steatosis. Knowledge of CT and MRI appearance of focal steatosis and fatty sparing is crucial for an accurate diagnosis, and to rule-out other pathologic processes. This paper will review the CT and MRI techniques for the diagnosis of hepatic steatosis and the CT and MRI features of common and uncommon causes of focal steatosis and fatty sparing.

Temporal Dermoid Cyst with Unusual Imaging Appearance: Case Report.

PubMed

Abderrahmen, Khansa; Bouhoula, Asma; Aouidj, Lasaad; Jemel, Hafedh

2016-01-01

Intracranial dermoid cysts are benign, slow growing tumors derived from ectopic inclusions of epithelial cells during closure of neural tube. These lesions, accounting for less than 1% of intracranial tumors, have characteristic computed tomography (CT) and magnetic resonance imaging (MRI) appearances that generally permits preoperative diagnosis. However, the radiologic features are uncommon and the cyst can be easily misdiagnosed with other tumors in rare cases. Herein, we report a case of a left temporoparietal dermoid cyst in a 48-year-old woman that was peroperatively and histopathologically proven but not advocated on CT and MRI. Clinical, radiological and histopathological features of a dermoid cyst are reviewed.

Nano-Computed Tomography: Technique and Applications.

PubMed

Kampschulte, M; Langheinirch, A C; Sender, J; Litzlbauer, H D; Althöhn, U; Schwab, J D; Alejandre-Lafont, E; Martels, G; Krombach, G A

2016-02-01

Nano-computed tomography (nano-CT) is an emerging, high-resolution cross-sectional imaging technique and represents a technical advancement of the established micro-CT technology. Based on the application of a transmission target X-ray tube, the focal spot size can be decreased down to diameters less than 400 nanometers (nm). Together with specific detectors and examination protocols, a superior spatial resolution up to 400 nm (10 % MTF) can be achieved, thereby exceeding the resolution capacity of typical micro-CT systems. The technical concept of nano-CT imaging as well as the basics of specimen preparation are demonstrated exemplarily. Characteristics of atherosclerotic plaques (intraplaque hemorrhage and calcifications) in a murine model of atherosclerosis (ApoE (-/-)/LDLR(-/-) double knockout mouse) are demonstrated in the context of superior spatial resolution in comparison to micro-CT. Furthermore, this article presents the application of nano-CT for imaging cerebral microcirculation (murine), lung structures (porcine), and trabecular microstructure (ovine) in contrast to micro-CT imaging. This review shows the potential of nano-CT as a radiological method in biomedical basic research and discusses the application of experimental, high resolution CT techniques in consideration of other high resolution cross-sectional imaging techniques. Nano-computed tomography is a high resolution CT-technology for 3D imaging at sub-micrometer resolution. The technical concept bases on a further development of the established ex-vivo-micro-CT technology. By improvement of the spatial resolution, structures at a cellular level become visible (e.g. osteocyte lacunae). © Georg Thieme Verlag KG Stuttgart · New York.

The Reconstruction Toolkit (RTK), an open-source cone-beam CT reconstruction toolkit based on the Insight Toolkit (ITK)

NASA Astrophysics Data System (ADS)

Rit, S.; Vila Oliva, M.; Brousmiche, S.; Labarbe, R.; Sarrut, D.; Sharp, G. C.

2014-03-01

We propose the Reconstruction Toolkit (RTK, http://www.openrtk.org), an open-source toolkit for fast cone-beam CT reconstruction, based on the Insight Toolkit (ITK) and using GPU code extracted from Plastimatch. RTK is developed by an open consortium (see affiliations) under the non-contaminating Apache 2.0 license. The quality of the platform is daily checked with regression tests in partnership with Kitware, the company supporting ITK. Several features are already available: Elekta, Varian and IBA inputs, multi-threaded Feldkamp-David-Kress reconstruction on CPU and GPU, Parker short scan weighting, multi-threaded CPU and GPU forward projectors, etc. Each feature is either accessible through command line tools or C++ classes that can be included in independent software. A MIDAS community has been opened to share CatPhan datasets of several vendors (Elekta, Varian and IBA). RTK will be used in the upcoming cone-beam CT scanner developed by IBA for proton therapy rooms. Many features are under development: new input format support, iterative reconstruction, hybrid Monte Carlo / deterministic CBCT simulation, etc. RTK has been built to freely share tomographic reconstruction developments between researchers and is open for new contributions.

The prognostic impact of clinical and CT parameters in patients with pontine hemorrhage.

PubMed

Dziewas, Rainer; Kremer, Marion; Lüdemann, Peter; Nabavi, Darius G; Dräger, Bianca; Ringelstein, Bernd

2003-01-01

In patients with pontine hemorrhage (PH), an accurate prognostic assessment is critical for establishing a reasonable therapeutic approach. The initial clinical symptoms and computed tomography (CT) features were analyzed with multivariate regression analysis in 39 consecutive patients with PH. PHs were classified into three types: (1) large paramedian, (2) basal or basotegmental and (3) lateral tegmental, and the hematomas' diameters were measured. The patients' outcome was evaluated. Twenty-seven patients (69%) died and 12 (31%) survived for more than 1 year after PH. The symptom most predictive of death was coma on admission. The large paramedian type of PH predicted a poor prognosis, whereas the lateral tegmental type was associated with a favorable outcome. The transverse hematoma diameter was also related to outcome, with the threshold value found to be 20 mm. We conclude that PH outcome can be estimated best by combining the CT parameters 'large paramedian PH' and 'transverse diameter >/=20 mm' with the clinical variable 'coma on admission'. Survival is unlikely if all 3 features are present, whereas survival may be expected if only 1 or none of these features is found. Copyright 2003 S. Karger AG, Basel

Diagnostic imaging of solitary tumors of the spine: what to do and say.

PubMed

Rodallec, Mathieu H; Feydy, Antoine; Larousserie, Frédérique; Anract, Philippe; Campagna, Raphaël; Babinet, Antoine; Zins, Marc; Drapé, Jean-Luc

2008-01-01

Metastatic disease, myeloma, and lymphoma are the most common malignant spinal tumors. Hemangioma is the most common benign tumor of the spine. Other primary osseous lesions of the spine are more unusual but may exhibit characteristic imaging features that can help the radiologist develop a differential diagnosis. Radiologic evaluation of a patient who presents with osseous vertebral lesions often includes radiography, computed tomography (CT), and magnetic resonance (MR) imaging. Because of the complex anatomy of the vertebrae, CT is more useful than conventional radiography for evaluating lesion location and analyzing bone destruction and condensation. The diagnosis of spinal tumors is based on patient age, topographic features of the tumor, and lesion pattern as seen at CT and MR imaging. A systematic approach is useful for recognizing tumors of the spine with characteristic features such as bone island, osteoid osteoma, osteochondroma, chondrosarcoma, vertebral angioma, and aneurysmal bone cyst. In the remaining cases, the differential diagnosis may include other primary spinal tumors, vertebral metastases and major nontumoral lesions simulating a vertebral tumor, Paget disease, spondylitis, echinococcal infection, and aseptic osteitis. In many cases, vertebral biopsy is warranted to guide treatment.

TU-A-12A-04: Quantitative Texture Features Calculated in Lung Tissue From CT Scans Demonstrate Consistency Between Two Databases From Different Institutions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cunliffe, A; Armato, S; Castillo, R

Purpose: To evaluate the consistency of computed tomography (CT) scan texture features, previously identified as stable in a healthy patient cohort, in esophageal cancer patient CT scans. Methods: 116 patients receiving radiation therapy (median dose: 50.4Gy) for esophageal cancer were retrospectively identified. For each patient, diagnostic-quality pre-therapy (0-183 days) and post-therapy (5-120 days) scans (mean voxel size: 0.8mm×0.8mm×2.5mm) and a treatment planning scan and associated dose map were collected. An average of 501 32x32-pixel ROIs were placed randomly in the lungs of each pre-therapy scan. ROI centers were mapped to corresponding locations in post-therapy and planning scans using the displacementmore » vector field output by demons deformable registration. Only ROIs with mean dose <5Gy were analyzed, as these were expected to contain minimal post-treatment damage. 140 texture features were calculated in pre-therapy and post-therapy scan ROIs and compared using Bland-Altman analysis. For each feature, the mean feature value change and the distance spanned by the 95% limits of agreement were normalized to the mean feature value, yielding normalized range of agreement (nRoA) and normalized bias (nBias). Using Wilcoxon signed rank tests, nRoA and nBias were compared with values computed previously in 27 healthy patient scans (mean voxel size: 0.67mm×0.67mm×1mm) acquired at a different institution. Results: nRoA was significantly (p<0.001) larger in cancer patients than healthy patients. Differences in nBias were not significant (p=0.23). The 20 features identified previously as having nRoA<20% for healthy patients had the lowest nRoA values in the current database, with an average increase of 5.6%. Conclusion: Despite differences in CT scanner type, scan resolution, and patient health status, the same 20 features remained stable (i.e., low variability and bias) in the absence of disease changes for databases from two institutions. Identification of these features is the first step towards quantifying radiation-induced changes between preand post-therapy scans. Supported, in part, by NIH Grant Nos. S10 RR021039, and P30 CA14599, the Virginia and D. K. Ludwig Fund for Cancer Research, Imaging Research Institute, Biological Sciences Division, The University of Chicago, and The Institute for Translational Medicine Pilot Award, The University of Chicago.« less

Computational Confirmation of the Carrier for the ``XCN'' Interstellar Ice Band: OCN- Charge Transfer Complexes

NASA Astrophysics Data System (ADS)

Park, Jin-Young; Woon, David E.

2004-01-01

Recent experimental studies provide evidence that the carrier for the so-called XCN feature at 2165 cm-1 (4.62 μm) in young stellar objects is an OCN-/NH+4 charge transfer (CT) complex that forms in energetically processed interstellar icy grain mantles. Although other RCN nitriles and RNC isonitriles have been considered, Greenberg's conjecture that OCN- is associated with the XCN feature has persisted for over 15 years. In this work, we report a computational investigation that thoroughly confirms the hypothesis that the XCN feature observed in laboratory studies can result from OCN-/NH+4 CT complexes arising from HNCO and NH3 in a water ice environment. Density functional theory calculations with HNCO, NH3, and up to 12 waters reproduce seven spectroscopic measurements associated with XCN: the band origin of the asymmetric stretching mode of OCN-, shifts due to isotopic substitutions of C, N, O, and H, and two weak features. However, very similar values are also found for the OCN-/NH+4 CT complex arising from HOCN and NH3. In both cases, the complex forms by barrierless proton transfer from HNCO or HOCN to NH3 during the optimization of the solvated system. Scaled B3LYP/6-31+G** harmonic frequencies for the HNCO and HOCN cases are 2181 and 2202 cm-1, respectively.

Computational Confirmation of the Carrier for the "XCN" Interstellar Ice Bank: OCN(-) Charge Transfer Complexes

NASA Technical Reports Server (NTRS)

Park, J.-Y.; Woon, D. E.

2004-01-01

Recent experimental studies provide evidence that carrier for the so-called XCN feature at 2165 cm(exp -1) (4.62 micron) in young stellar objects is an OCN(-)/NH4(+) charge transfer (CT) complex that forms in energetically processed interstellar icy grain mantles. Although other RCN nitriles and RCN iosonitriles have been considered, Greenberg's conjecture that OCN(-) is associated with the XCN feature has persisted for over 15 years. In this work we report a computational investigation that thoroughly confirms the hypothesis that the XCN feature observed in laboratory studies can result from OCN(-)/NH4(+) CT complexes arising from HNCO and NH3, in a water ice environment. Density functional theory calculations with theory calculations with HNCO, NH3, and up to 12 waters reproduce seven spectroscopic measurements associated with XCN: the band origin of the asymmetric stretching mode of OCN(-), shifts due to isotopic substitutions of C, N, O, and H, and two weak features. However, very similar values are also found for the OCN(-)/NH4(+) CT complex arising from HOCN and NH3. In both cases, the complex forms by barrierless proton transfer from HNCO or HOCN to NH3 during the optimization of the solvated system. Scaled B3LYP/6-31+G** harmonic frequencies for HNCO and HOCN cases are 2181 and 2202 cm(exp -1), respectively.

Radiation Dose in the Thyroid and the Thyroid Cancer Risk Attributable to CT Scans for Pediatric Patients in One General Hospital of China

PubMed Central

Su, Yin-Ping; Niu, Hao-Wei; Chen, Jun-Bo; Fu, Ying-Hua; Xiao, Guo-Bing; Sun, Quan-Fu

2014-01-01

Objective: To quantify the radiation dose in the thyroid attributable to different CT scans and to estimate the thyroid cancer risk in pediatric patients. Methods: The information about pediatric patients who underwent CT scans was abstracted from the radiology information system in one general hospital between 1 January 2012 and 31 December 2012. The radiation doses were calculated using the ImPACT Patient Dosimetry Calculator and the lifetime attributable risk (LAR) of thyroid cancer incidence was estimated based on the National Academies Biologic Effects of Ionizing Radiation VII model. Results: The subjects comprised 922 children, 68% were males, and received 971 CT scans. The range of typical radiation dose to the thyroid was estimated to be 0.61–0.92 mGy for paranasal sinus CT scans, 1.10–2.45 mGy for head CT scans, and 2.63–5.76 mGy for chest CT scans. The LAR of thyroid cancer were as follows: for head CT, 1.1 per 100,000 for boys and 8.7 per 100,000 for girls; for paranasal sinus CT scans, 0.4 per 100,000 for boys and 2.7 per 100,000 for girls; for chest CT scans, 2.1 per 100,000 for boys and 14.1 per 100,000 for girls. The risk of thyroid cancer was substantially higher for girls than for the boys, and from chest CT scans was higher than that from head or paransal sinus CT scans. Conclusions: Chest CT scans caused higher thyroid dose and the LAR of thyroid cancer incidence, compared with paransal sinus or head CT scans. Therefore, physicians should pay more attention to protect the thyroid when children underwent CT scans, especially chest CT scans. PMID:24608902

Design, fabrication, and implementation of voxel-based 3D printed textured phantoms for task-based image quality assessment in CT

NASA Astrophysics Data System (ADS)

Solomon, Justin; Ba, Alexandre; Diao, Andrew; Lo, Joseph; Bier, Elianna; Bochud, François; Gehm, Michael; Samei, Ehsan

2016-03-01

In x-ray computed tomography (CT), task-based image quality studies are typically performed using uniform background phantoms with low-contrast signals. Such studies may have limited clinical relevancy for modern non-linear CT systems due to possible influence of background texture on image quality. The purpose of this study was to design and implement anatomically informed textured phantoms for task-based assessment of low-contrast detection. Liver volumes were segmented from 23 abdominal CT cases. The volumes were characterized in terms of texture features from gray-level co-occurrence and run-length matrices. Using a 3D clustered lumpy background (CLB) model, a fitting technique based on a genetic optimization algorithm was used to find the CLB parameters that were most reflective of the liver textures, accounting for CT system factors of spatial blurring and noise. With the modeled background texture as a guide, a cylinder phantom (165 mm in diameter and 30 mm height) was designed, containing 20 low-contrast spherical signals (6 mm in diameter at targeted contrast levels of ~3.2, 5.2, 7.2, 10, and 14 HU, 4 repeats per signal). The phantom was voxelized and input into a commercial multi-material 3D printer (Object Connex 350), with custom software for voxel-based printing. Using principles of digital half-toning and dithering, the 3D printer was programmed to distribute two base materials (VeroWhite and TangoPlus, nominal voxel size of 42x84x30 microns) to achieve the targeted spatial distribution of x-ray attenuation properties. The phantom was used for task-based image quality assessment of a clinically available iterative reconstruction algorithm (Sinogram Affirmed Iterative Reconstruction, SAFIRE) using a channelized Hotelling observer paradigm. Images of the textured phantom and a corresponding uniform phantom were acquired at six dose levels and observer model performance was estimated for each condition (5 contrasts x 6 doses x 2 reconstructions x 2 backgrounds = 120 total conditions). Based on the observer model results, the dose reduction potential of SAFIRE was computed and compared between the uniform and textured phantom. The dose reduction potential of SAFIRE was found to be 23% based on the uniform phantom and 17% based on the textured phantom. This discrepancy demonstrates the need to consider background texture when assessing non-linear reconstruction algorithms.

Bone lesions in Chinese POEMS syndrome patients: imaging characteristics and clinical implications.

PubMed

Wang, Fengdan; Huang, Xufei; Zhang, Yan; Li, Jian; Zhou, Daobin; Jin, Zhengyu

2016-01-01

Objective. Bone lesion is crucial for diagnosing and management of polyneuropathy, organomegaly, endocrinopathy, monoclonal protein, and skin change (POEMS) syndrome, a rare plasma cell disorder. This study is to compare the effectiveness of X-ray skeletal survey (SS) and computed tomography (CT) for detecting bone lesions in Chinese POEMS syndrome patients, and to investigate the relationship between bone lesion features and serum markers. Methods. SS and chest/abdomen/pelvic CT images of 38 Chinese patients (26 males, 12 females, aged 21-70 years) with POEMS syndrome recruited at our medical center between January 2013 and January 2015 were retrospectively analyzed. Bone lesions identified by CT were further categorized according to the size (<5 mm, 5-10 mm, >10 mm) and appearance (osteosclerotic, lytic, mixed). The percentage of plasma cells in bone marrow smears, type of immunoglobulin, platelet (Plt), and levels of serum bone metabolic markers and inflammatory factors including alkaline phosphatase (ALP), calcium, phosphate, parathyroid hormone (PTH), beta-isomerized C-telopeptide (β-CTx), vascular endothelial growth factor (VEGF), and interleukin (IL)-6 levels were also recorded. Results. Of the 38 POEMS syndrome patients, the immunoglobulin heavy chain isotypes were IgA in 25 patients (65.8%; 25/38) and IgG in 13 patients (34.2%; 13/38), and the light chain isotypes were λ in 35 patients (92.1%; 35/38) and κ in 3 patients (7.9%; 3/38). There were 23 patients with thrombocytosis. More patients with bone lesions were detected by CT than by SS (97.4% vs. 86.8%). The most commonly affected location was the pelvis (89.5%), followed by the spine, clavicle/scapula/sternum/ribs, skull, and long bones. Of the 38 POEMS syndrome patients, 35 (94.6%) had osteosclerotic and 32 (86.5%) had mixed lesions. Osteosclerotic lesions were typically scattered, variable in size, and plaque-like, whereas mixed lesions were pouch-shaped or soup bubble-like with a clear sclerotic margin and were generally larger. Although the majority of bone lesions were small in size, 23 (62.2%) had at least one lesion >10 mm. There was no correlation between serum marker levels and bone lesion patterns after Bonferroni correction (all P > 0.001). Conclusions. CT is more sensitive and accurate than SS in detecting bone lesions in POEMS syndrome.

Severity mapping of the proximal femur: a new method for assessing hip osteoarthritis with computed tomography.

PubMed

Turmezei, T D; Lomas, D J; Hopper, M A; Poole, K E S

2014-10-01

Plain radiography has been the mainstay of imaging assessment in osteoarthritis for over 50 years, but it does have limitations. Here we present the methodology and results of a new technique for identifying, grading, and mapping the severity and spatial distribution of osteoarthritic disease features at the hip in 3D with clinical computed tomography (CT). CT imaging of 456 hips from 230 adult female volunteers (mean age 66 ± 17 years) was reviewed using 3D multiplanar reformatting to identify bone-related radiological features of osteoarthritis, namely osteophytes, subchondral cysts and joint space narrowing. Scoresheets dividing up the femoral head, head-neck region and the joint space were used to register the location and severity of each feature (scored from 0 to 3). Novel 3D cumulative feature severity maps were then created to display where the most severe disease features from each individual were anatomically located across the cohort. Feature severity maps showed a propensity for osteophytes at the inferoposterior and superolateral femoral head-neck junction. Subchondral cysts were a less common and less localised phenomenon. Joint space narrowing <1.5 mm was recorded in at least one sector of 83% of hips, but most frequently in the posterolateral joint space. This is the first description of hip osteoarthritis using unenhanced clinical CT in which we describe the co-localisation of posterior osteophytes and joint space narrowing for the first time. We believe this technique can perform several important roles in future osteoarthritis research, including phenotyping and sensitive disease assessment in 3D. Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Radiological features of experimental staphylococcal septic arthritis by micro computed tomography scan

PubMed Central

Fatima, Farah; Fei, Ying; Ali, Abukar; Mohammad, Majd; Erlandsson, Malin C.; Bokarewa, Maria I.; Nawaz, Muhammad; Valadi, Hadi; Na, Manli

2017-01-01

Background Permanent joint dysfunction due to bone destruction occurs in up to 50% of patients with septic arthritis. Recently, imaging technologies such as micro computed tomography (μCT) scan have been widely used for preclinical models of autoimmune joint disorders. However, the radiological features of septic arthritis in mice are still largely unknown. Methods NMRI mice were intravenously or intra-articularly inoculated with S. aureus Newman or LS-1 strain. The radiological and clinical signs of septic arthritis were followed for 10 days using μCT. We assessed the correlations between joint radiological changes and clinical signs, histological changes, and serum levels of cytokines. Results On days 5–7 after intravenous infection, bone destruction verified by μCT became evident in most of the infected joints. Radiological signs of bone destruction were dependent on the bacterial dose. The site most commonly affected by septic arthritis was the distal femur in knees. The bone destruction detected by μCT was positively correlated with histological changes in both local and hematogenous septic arthritis. The serum levels of IL-6 were significantly correlated with the severity of joint destruction. Conclusion μCT is a sensitive method for monitoring disease progression and determining the severity of bone destruction in a mouse model of septic arthritis. IL-6 may be used as a biomarker for bone destruction in septic arthritis. PMID:28152087

An improved method for pancreas segmentation using SLIC and interactive region merging

NASA Astrophysics Data System (ADS)

Zhang, Liyuan; Yang, Huamin; Shi, Weili; Miao, Yu; Li, Qingliang; He, Fei; He, Wei; Li, Yanfang; Zhang, Huimao; Mori, Kensaku; Jiang, Zhengang

2017-03-01

Considering the weak edges in pancreas segmentation, this paper proposes a new solution which integrates more features of CT images by combining SLIC superpixels and interactive region merging. In the proposed method, Mahalanobis distance is first utilized in SLIC method to generate better superpixel images. By extracting five texture features and one gray feature, the similarity measure between two superpixels becomes more reliable in interactive region merging. Furthermore, object edge blocks are accurately addressed by re-segmentation merging process. Applying the proposed method to four cases of abdominal CT images, we segment pancreatic tissues to verify the feasibility and effectiveness. The experimental results show that the proposed method can make segmentation accuracy increase to 92% on average. This study will boost the application process of pancreas segmentation for computer-aided diagnosis system.

Assessment of an Optical Flow Field-Based Polyp Detector for CT Colonography

DTIC Science & Technology

2001-10-25

sort true polyps from false positives based on features extracted from the computed OFFs. II. METHODOLOGY A. Pre-processing The 3D CT data was...subvolume and scrolling direction, as follows:      = ∑ Z ZD y)x,( Smoothy )x,( vv (2) The smoothing filter used is a 3×3 rectangular

Calibration free beam hardening correction for cardiac CT perfusion imaging

NASA Astrophysics Data System (ADS)

Levi, Jacob; Fahmi, Rachid; Eck, Brendan L.; Fares, Anas; Wu, Hao; Vembar, Mani; Dhanantwari, Amar; Bezerra, Hiram G.; Wilson, David L.

2016-03-01

Myocardial perfusion imaging using CT (MPI-CT) and coronary CTA have the potential to make CT an ideal noninvasive gate-keeper for invasive coronary angiography. However, beam hardening artifacts (BHA) prevent accurate blood flow calculation in MPI-CT. BH Correction (BHC) methods require either energy-sensitive CT, not widely available, or typically a calibration-based method. We developed a calibration-free, automatic BHC (ABHC) method suitable for MPI-CT. The algorithm works with any BHC method and iteratively determines model parameters using proposed BHA-specific cost function. In this work, we use the polynomial BHC extended to three materials. The image is segmented into soft tissue, bone, and iodine images, based on mean HU and temporal enhancement. Forward projections of bone and iodine images are obtained, and in each iteration polynomial correction is applied. Corrections are then back projected and combined to obtain the current iteration's BHC image. This process is iterated until cost is minimized. We evaluate the algorithm on simulated and physical phantom images and on preclinical MPI-CT data. The scans were obtained on a prototype spectral detector CT (SDCT) scanner (Philips Healthcare). Mono-energetic reconstructed images were used as the reference. In the simulated phantom, BH streak artifacts were reduced from 12+/-2HU to 1+/-1HU and cupping was reduced by 81%. Similarly, in physical phantom, BH streak artifacts were reduced from 48+/-6HU to 1+/-5HU and cupping was reduced by 86%. In preclinical MPI-CT images, BHA was reduced from 28+/-6 HU to less than 4+/-4HU at peak enhancement. Results suggest that the algorithm can be used to reduce BHA in conventional CT and improve MPI-CT accuracy.

Three dimensional image correlation of CT, MR, and PET studies in radiotherapy treatment planning of brain tumors.

PubMed

Schad, L R; Boesecke, R; Schlegel, W; Hartmann, G H; Sturm, V; Strauss, L G; Lorenz, W J

1987-01-01

A treatment planning system for stereotactic convergent beam irradiation of deeply localized brain tumors is reported. The treatment technique consists of several moving field irradiations in noncoplanar planes at a linear accelerator facility. Using collimated narrow beams, a high concentration of dose within small volumes with a dose gradient of 10-15%/mm was obtained. The dose calculation was based on geometrical information of multiplanar CT or magnetic resonance (MR) imaging data. The patient's head was fixed in a stereotactic localization system, which is usable at CT, MR, and positron emission tomography (PET) installations. Special computer programs for correction of the geometrical MR distortions allowed a precise correlation of the different imaging modalities. The therapist can use combinations of CT, MR, and PET data for defining target volume. For instance, the superior soft tissue contrast of MR coupled with the metabolic features of PET may be a useful addition in the radiation treatment planning process. Furthermore, other features such as calculated dose distribution to critical structures can also be transferred from one set of imaging data to another and can be displayed as three-dimensional shaded structures.

Extraction and classification of 3D objects from volumetric CT data

NASA Astrophysics Data System (ADS)

Song, Samuel M.; Kwon, Junghyun; Ely, Austin; Enyeart, John; Johnson, Chad; Lee, Jongkyu; Kim, Namho; Boyd, Douglas P.

2016-05-01

We propose an Automatic Threat Detection (ATD) algorithm for Explosive Detection System (EDS) using our multistage Segmentation Carving (SC) followed by Support Vector Machine (SVM) classifier. The multi-stage Segmentation and Carving (SC) step extracts all suspect 3-D objects. The feature vector is then constructed for all extracted objects and the feature vector is classified by the Support Vector Machine (SVM) previously learned using a set of ground truth threat and benign objects. The learned SVM classifier has shown to be effective in classification of different types of threat materials. The proposed ATD algorithm robustly deals with CT data that are prone to artifacts due to scatter, beam hardening as well as other systematic idiosyncrasies of the CT data. Furthermore, the proposed ATD algorithm is amenable for including newly emerging threat materials as well as for accommodating data from newly developing sensor technologies. Efficacy of the proposed ATD algorithm with the SVM classifier is demonstrated by the Receiver Operating Characteristics (ROC) curve that relates Probability of Detection (PD) as a function of Probability of False Alarm (PFA). The tests performed using CT data of passenger bags shows excellent performance characteristics.

Colitis detection on abdominal CT scans by rich feature hierarchies

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Lay, Nathan; Wei, Zhuoshi; Lu, Le; Kim, Lauren; Turkbey, Evrim; Summers, Ronald M.

2016-03-01

Colitis is inflammation of the colon due to neutropenia, inflammatory bowel disease (such as Crohn disease), infection and immune compromise. Colitis is often associated with thickening of the colon wall. The wall of a colon afflicted with colitis is much thicker than normal. For example, the mean wall thickness in Crohn disease is 11-13 mm compared to the wall of the normal colon that should measure less than 3 mm. Colitis can be debilitating or life threatening, and early detection is essential to initiate proper treatment. In this work, we apply high-capacity convolutional neural networks (CNNs) to bottom-up region proposals to detect potential colitis on CT scans. Our method first generates around 3000 category-independent region proposals for each slice of the input CT scan using selective search. Then, a fixed-length feature vector is extracted from each region proposal using a CNN. Finally, each region proposal is classified and assigned a confidence score with linear SVMs. We applied the detection method to 260 images from 26 CT scans of patients with colitis for evaluation. The detection system can achieve 0.85 sensitivity at 1 false positive per image.

Inhibitory effects of magnolol and honokiol on human calcitonin aggregation

PubMed Central

Guo, Caiao; Ma, Liang; Zhao, Yudan; Peng, Anlin; Cheng, Biao; Zhou, Qiaoqiao; Zheng, Ling; Huang, Kun

2015-01-01

Amyloid formation is associated with multiple amyloidosis diseases. Human calcitonin (hCT) is a typical amyloidogenic peptide, its aggregation is associated with medullary carcinoma of the thyroid (MTC), and also limits its clinical application. Magnolia officinalis is a traditional Chinese herbal medicine; its two major polyphenol components, magnolol (Mag) and honokiol (Hon), have displayed multiple functions. Polyphenols like flavonoids and their derivatives have been extensively studied as amyloid inhibitors. However, the anti-amyloidogenic property of a biphenyl backbone containing polyphenols such as Mag and Hon has not been reported. In this study, these two compounds were tested for their effects on hCT aggregation. We found that Mag and Hon both inhibited the amyloid formation of hCT, whereas Mag showed a stronger inhibitory effect; moreover, they both dose-dependently disassembled preformed hCT aggregates. Further immuno-dot blot and dynamic light scattering studies suggested Mag and Hon suppressed the aggregation of hCT both at the oligomerization and the fibrillation stages, while MTT-based and dye-leakage assays demonstrated that Mag and Hon effectively reduced cytotoxicity caused by hCT aggregates. Furthermore, isothermal titration calorimetry indicated Mag and Hon both interact with hCT. Together, our study suggested a potential anti-amyloidogenic property of these two compounds and their structure related derivatives. PMID:26324190

Ultrasound, elastography, and fluorodeoxyglucose positron emission tomography/computed tomography imaging in Riedel's thyroiditis: report of two cases.

PubMed

Slman, Rouba; Monpeyssen, Hervé; Desarnaud, Serge; Haroche, Julien; Fediaevsky, Laurence Du Pasquier; Fabrice, Menegaux; Seret-Begue, Dominique; Amoura, Zahir; Aurengo, André; Leenhardt, Laurence

2011-07-01

Riedel's thyroiditis (RT) is a rare disease characterized by a chronic inflammatory lesion of the thyroid gland with invasion by a dense fibrosis. Publications of the imaging features of RT are scarce. To our knowledge, ultrasound elastography (USE) findings have not been previously reported. Therefore, we describe two patients with RT who were imaged with ultrasonography (US), USE, and fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT). Two women were referred for a large, hard goiter with compressive symptoms (dyspnea and dysphagia); in one patient, the goiter was associated with retroperitoneal fibrosis. In both cases, RT was confirmed by surgical biopsy with pathological examination. Thyroid US imaging was performed with a US scan and a 10-13 MHz linear transducer. The hardness of the tissues was analyzed using transient USE (ShearWave, Aixplorer-SuperSonic Imagine). PET/CT scanning was performed with a Philips Gemini GXL camera (GE Medical Systems). In the first patient, US examination revealed a compressive multinodular goiter with large solid hypoechoic and poorly vascularized areas adjacent to the nodules. The predominant right nodule was hypoechoic with irregular margins. The second patient had a hypoechoic goiter with large bilateral hypoechoic areas. In both cases, an unusual feature was observed: the presence of tissue surrounding the primitive carotid artery, associated with thrombi of the internal jugular vein. Further, USE showed heterogeneity in the stiffness values of the thyroid parenchyma varying between 21 kPa and 281 kPa. FDG-PET/CT imaging showed uptake foci in the thyroid gland. In both cases, US showed a decrease in the thyroid gland volume and the disappearance of encasement of the neck vasculature in response to corticosteroid treatment. In contrast, the FDG-PET/CT features remained unchanged. US features, such as vascular encasement and improvement under corticosteroid treatment, seem to be specific to this rare disease. For the first time, USE documents the hardness of RT tissues. Apart from the FDG-PET/CT findings that merit further investigation, US and USE prove useful tools in the assessment of such a rare disease.

SU-C-207B-06: Comparison of Registration Methods for Modeling Pathologic Response of Esophageal Cancer to Chemoradiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Riyahi, S; Choi, W; Bhooshan, N

2016-06-15

Purpose: To compare linear and deformable registration methods for evaluation of tumor response to Chemoradiation therapy (CRT) in patients with esophageal cancer. Methods: Linear and multi-resolution BSpline deformable registration were performed on Pre-Post-CRT CT/PET images of 20 patients with esophageal cancer. For both registration methods, we registered CT using Mean Square Error (MSE) metric, however to register PET we used transformation obtained using Mutual Information (MI) from the same CT due to being multi-modality. Similarity of Warped-CT/PET was quantitatively evaluated using Normalized Mutual Information and plausibility of DF was assessed using inverse consistency Error. To evaluate tumor response four groupsmore » of tumor features were examined: (1) Conventional PET/CT e.g. SUV, diameter (2) Clinical parameters e.g. TNM stage, histology (3)spatial-temporal PET features that describe intensity, texture and geometry of tumor (4)all features combined. Dominant features were identified using 10-fold cross-validation and Support Vector Machine (SVM) was deployed for tumor response prediction while the accuracy was evaluated by ROC Area Under Curve (AUC). Results: Average and standard deviation of Normalized mutual information for deformable registration using MSE was 0.2±0.054 and for linear registration was 0.1±0.026, showing higher NMI for deformable registration. Likewise for MI metric, deformable registration had 0.13±0.035 comparing to linear counterpart with 0.12±0.037. Inverse consistency error for deformable registration for MSE metric was 4.65±2.49 and for linear was 1.32±2.3 showing smaller value for linear registration. The same conclusion was obtained for MI in terms of inverse consistency error. AUC for both linear and deformable registration was 1 showing no absolute difference in terms of response evaluation. Conclusion: Deformable registration showed better NMI comparing to linear registration, however inverse consistency of transformation was lower in linear registration. We do not expect to see significant difference when warping PET images using deformable or linear registration. This work was supported in part by the National Cancer Institute Grants R01CA172638.« less

High resolution multidetector CT aided tissue analysis and quantification of lung fibrosis

NASA Astrophysics Data System (ADS)

Zavaletta, Vanessa A.; Karwoski, Ronald A.; Bartholmai, Brian; Robb, Richard A.

2006-03-01

Idiopathic pulmonary fibrosis (IPF, also known as Idiopathic Usual Interstitial Pneumontis, pathologically) is a progressive diffuse lung disease which has a median survival rate of less than four years with a prevalence of 15-20/100,000 in the United States. Global function changes are measured by pulmonary function tests and the diagnosis and extent of pulmonary structural changes are typically assessed by acquiring two-dimensional high resolution CT (HRCT) images. The acquisition and analysis of volumetric high resolution Multi-Detector CT (MDCT) images with nearly isotropic pixels offers the potential to measure both lung function and structure. This paper presents a new approach to three dimensional lung image analysis and classification of normal and abnormal structures in lungs with IPF.

[Effect of Charge-Transfer Complex on Ultraviolet-Visible (UV-Vis) Absorption Property of Chromophoric Dissolved Organic Matter (CDOM) in Waters of Typical Water-Level Fluctuation Zones of the Three Gorges Reservoir Areas].

PubMed

Jiang, Tao; Liang, Jian; Zhang, Mu-xue; Wang, Ding-yong; Wei, Shi-qiang; Lu, Song

2016-02-15

As an important fraction of dissolved organic matter (DOM), chromophoric dissolved organic matter (CDOM) plays a key role in decision of the optical properties and photogeochemistry of DOM, and further affects pollutant fate and global carbon cycle. These optical properties are ascribed to two chromophoric systems including superposition of individual chromophores and charge-transfer (CT) complexation between electron donor (e.g., phenols and indoles) and acceptor (e.g., quinones and other oxidized aromatics) in DOM structures. Thus in this study, based on the "double-chromophoric system" model, DOM samples from four typical water-level fluctuation zones of Three Gorges Reservoir (TGR) areas were selected, to investigate the effect and contribution of charge-transfer complex to ultraviolet-visible (UV-Vis) absorption property of CDOM. Using NaBH, reduction method, original featureless absorption curve was classified into two independent curves caused by individual chromophoric group, which were derived from a simple superposition of independent chromophore and charge-transfer complex, respectively. Also, the changes in curve properties and specific parameters before and after NaBH4 reduction were compared. The results showed that in all DOM samples from the four sites of TGR, more than 35% of absorption was attributed from CT complex. Shibaozhai of Zhongxian and Zhenxi of Fuling showed the highest proportion ( > 50%). It suggested that the role of CT complex in CDOM property could not be neglected. After removal of CT complex, absorption curve showed blue-shift and CDOM concentration [a (355)] decreased significantly. Meanwhile, because of deforming of bonds by reduction, DOM structures became more dispersive and the molecular size was decreased, resulting in the lower spectral slope (S) observed, which evidentially supported that the supermolecular association structure of DOM was self-assembled through CT complex. Meanwhile, deceasing hydrophobic components led to decreased apparent aromaticity (lower SUVA values), whereas specific parameters including SUVA, CDOM and SR still were applicable for comparison among different DOM samples instead of the same sample without consideration of "double-cbromopboric system" model involving tbe role of CT complex. Comparatively, S(275-295) was dynamic due to tbe impact of CT effect. Furtbermore, establisbing DOC estimation model by short-wavelength range of CDOM was recommended because of its stability despite of CT complex.

Learning about the internal structure of categories through classification and feature inference.

PubMed

Jee, Benjamin D; Wiley, Jennifer

2014-01-01

Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a "partial inference" condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.

An atypical sarcoidosis involvement in FDG PET/CT

PubMed Central

Robin, Philippe; Benigni, Paolo; Feger, Benoit; Salaun, Pierre-Yves; Abgral, Ronan

2016-01-01

Abstract Rationale: Sarcoidosis is an idiopathic systemic inflammatory granulomatous disorder comprised of epithelioid and multinucleated giant cells with little necrosis which involve various organs. Laryngeal involvement is extremely rare, with a prevalence of about 0.5 to 1%. Diagnoses: Here we present a case of laryngeal involvement of sarcoidosis demonstrated on 18F-Fluorodesoxyglucose Positron-Emission Tomography/Computed Tomography (FDG PET/CT). Patient concerns: A 63 year-old man suffering from dysphonia was referred to our department for characterization of laryngeal lesion suspicious for cancer with non-informative biopsy, the sample was not sufficient for diagnosis. Interventions: FDG PET/CT showed a pathological uptake on the right vocal cord, but also highlighted a bilateral uptake in intrathoracic hilar lymphadenopathy areas, typically found in several inflammatory diseases. Outcomes: New laryngeal targeted biopsies revealed non-caseating epithelioid granulomas suggesting sarcoidosis involvement. After 6 months of systemic steroid treatment, FDG PET/CT showed a significant decrease of the laryngeal uptake. Lessons: This case shows the usefulness of FDG PET/CT to accurately assess inflammatory activity in rare extra-pulmonary sarcoidosis involvement. Moreover, this case emphasizes that FDG PET/CT is an interesting tool for assessing therapeutic efficacy of inflammatory diseases such as sarcoidosis. PMID:28033265

Atlas and feature based 3D pathway visualization enhancement for skull base pre-operative fast planning from head CT

NASA Astrophysics Data System (ADS)

Aghdasi, Nava; Li, Yangming; Berens, Angelique; Moe, Kris S.; Bly, Randall A.; Hannaford, Blake

2015-03-01

Minimally invasive neuroendoscopic surgery provides an alternative to open craniotomy for many skull base lesions. These techniques provides a great benefit to the patient through shorter ICU stays, decreased post-operative pain and quicker return to baseline function. However, density of critical neurovascular structures at the skull base makes planning for these procedures highly complex. Furthermore, additional surgical portals are often used to improve visualization and instrument access, which adds to the complexity of pre-operative planning. Surgical approach planning is currently limited and typically involves review of 2D axial, coronal, and sagittal CT and MRI images. In addition, skull base surgeons manually change the visualization effect to review all possible approaches to the target lesion and achieve an optimal surgical plan. This cumbersome process relies heavily on surgeon experience and it does not allow for 3D visualization. In this paper, we describe a rapid pre-operative planning system for skull base surgery using the following two novel concepts: importance-based highlight and mobile portal. With this innovation, critical areas in the 3D CT model are highlighted based on segmentation results. Mobile portals allow surgeons to review multiple potential entry portals in real-time with improved visualization of critical structures located inside the pathway. To achieve this we used the following methods: (1) novel bone-only atlases were manually generated, (2) orbits and the center of the skull serve as features to quickly pre-align the patient's scan with the atlas, (3) deformable registration technique was used for fine alignment, (4) surgical importance was assigned to each voxel according to a surgical dictionary, and (5) pre-defined transfer function was applied to the processed data to highlight important structures. The proposed idea was fully implemented as independent planning software and additional data are used for verification and validation. The experimental results show: (1) the proposed methods provided greatly improved planning efficiency while optimal surgical plans were successfully achieved, (2) the proposed methods successfully highlighted important structures and facilitated planning, (3) the proposed methods require shorter processing time than classical segmentation algorithms, and (4) these methods can be used to improve surgical safety for surgical robots.

[Study on computed tomography features of nasal septum cellule and its clinical significance].

PubMed

Huang, Dingqiang; Li, Wanrong; Gao, Liming; Xu, Guanqiang; Ou, Xiaoyi; Tang, Guangcai

2008-03-01

To investigate the features of nasal septum cellule in computed tomographic (CT) images and its clinical significance. CT scans data of nasal septum in 173 patients were randomly obtained from January 2001 to June 2005. Prevalence and clinical features were summarized in the data of 19 patients with nasal septum cellule retrospectively. (1) Nineteen cases with nasal septum cellule were found in 173 patients. (2) All nasal septum cellule of 19 cases located in perpendicular plate of the ethmoid bone, in which 8 cases located in upper part of nasal septum and 11 located in middle. (3) There were totally seven patients with nasal diseases related to nasal septum cellule, in which 3 cases with inflammation, 2 cases with bone fracture, 1 case with cholesterol granuloma, 1 case with mucocele. Nasal septum cellule is an anatomic variation of nasal septum bone, and its features can provide further understanding of some diseases related to nasal septum cellule.

Chlamydia trachomatis CT771 (nudH) is an asymmetric Ap4A hydrolase.

PubMed

Barta, Michael L; Lovell, Scott; Sinclair, Amy N; Battaile, Kevin P; Hefty, P Scott

2014-01-14

Asymmetric diadenosine 5',5‴-P(1),P(4)-tetraphosphate (Ap4A) hydrolases are members of the Nudix superfamily that asymmetrically cleave the metabolite Ap4A into ATP and AMP while facilitating homeostasis. The obligate intracellular mammalian pathogen Chlamydia trachomatis possesses a single Nudix family protein, CT771. As pathogens that rely on a host for replication and dissemination typically have one or zero Nudix family proteins, this suggests that CT771 could be critical for chlamydial biology and pathogenesis. We identified orthologues to CT771 within environmental Chlamydiales that share active site residues suggesting a common function. Crystal structures of both apo- and ligand-bound CT771 were determined to 2.6 Å and 1.9 Å resolution, respectively. The structure of CT771 shows a αβα-sandwich motif with many conserved elements lining the putative Nudix active site. Numerous aspects of the ligand-bound CT771 structure mirror those observed in the ligand-bound structure of the Ap4A hydrolase from Caenorhabditis elegans. These structures represent only the second Ap4A hydrolase enzyme member determined from eubacteria and suggest that mammalian and bacterial Ap4A hydrolases might be more similar than previously thought. The aforementioned structural similarities, in tandem with molecular docking, guided the enzymatic characterization of CT771. Together, these studies provide the molecular details for substrate binding and specificity, supporting the analysis that CT771 is an Ap4A hydrolase (nudH).

Non-random Patterns in the Distribution of NOR-bearing Chromosome Territories in Human Fibroblasts: A Network Model of Interactions

PubMed Central

Pliss, Artem; Fritz, Andrew J.; Stojkovic, Branislav; Ding, Hu; Mukherjee, Lopamudra; Bhattacharya, Sambit; Xu, Jinhui; Berezney, Ronald

2017-01-01

We present a 3-D mapping in WI38 human diploid fibroblast cells of chromosome territories (CT) 13,14,15,21, and 22, which contain the nucleolar organizing regions (NOR) and participate in the formation of nucleoli. The nuclear radial positioning of NOR-CT correlated with the size of chromosomes with smaller CT more interior. A high frequency of pairwise associations between NOR-CT ranging from 52% (CT13-21) to 82% (CT15-21) was detected as well as a triplet arrangement of CT15-21-22 (72%). The associations of homologous CT were significantly lower (24–36%). The arrangements of each pairwise CT varied from CT13-14 and CT13-22, which had a majority of cells with single associations, to CT13-15 and CT13-21 where a majority of cells had multiple interactions. In cells with multiple nucleoli, one of the nucleoli (termed “dominant”) always associated with a higher number of CT. Moreover, certain CT pairs more frequently contributed to the same nucleolus than to others. This nonrandom pattern suggests that a large number of the NOR-chromsomes are poised in close proximity during the postmitotic nucleolar recovery and through their NORs may contribute to the formation of the same nucleolus. A global data mining program termed the chromatic median determined the most probable interchromosomal arrangement of the entire NOR-CT population. This interactive network model was significantly above randomized simulation and was composed of 13 connections among the NOR-CT. We conclude that the NOR-CT form a global interactive network in the cell nucleus that may be a fundamental feature for the regulation of nucleolar and other genomic functions. PMID:25077974

Nanoparticle Contrast Agents for Computed Tomography: A Focus on Micelles

PubMed Central

Cormode, David P.; Naha, Pratap C.; Fayad, Zahi A.

2014-01-01

Computed tomography (CT) is an X-ray based whole body imaging technique that is widely used in medicine. Clinically approved contrast agents for CT are iodinated small molecules or barium suspensions. Over the past seven years there has been a great increase in the development of nanoparticles as CT contrast agents. Nanoparticles have several advantages over small molecule CT contrast agents, such as long blood-pool residence times, and the potential for cell tracking and targeted imaging applications. Furthermore, there is a need for novel CT contrast agents, due to the growing population of renally impaired patients and patients hypersensitive to iodinated contrast. Micelles and lipoproteins, a micelle-related class of nanoparticle, have notably been adapted as CT contrast agents. In this review we discuss the principles of CT image formation and the generation of CT contrast. We discuss the progress in developing non-targeted, targeted and cell tracking nanoparticle CT contrast agents. We feature agents based on micelles and used in conjunction with spectral CT. The large contrast agent doses needed will necessitate careful toxicology studies prior to clinical translation. However, the field has seen tremendous advances in the past decade and we expect many more advances to come in the next decade. PMID:24470293

Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; More, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

2016-03-01

How to rationally identify epithelial ovarian cancer (EOC) patients who will benefit from bevacizumab or other antiangiogenic therapies is a critical issue in EOC treatments. The motivation of this study is to quantitatively measure adiposity features from CT images and investigate the feasibility of predicting potential benefit of EOC patients with or without receiving bevacizumab-based chemotherapy treatment using multivariate statistical models built based on quantitative adiposity image features. A dataset involving CT images from 59 advanced EOC patients were included. Among them, 32 patients received maintenance bevacizumab after primary chemotherapy and the remaining 27 patients did not. We developed a computer-aided detection (CAD) scheme to automatically segment subcutaneous fat areas (VFA) and visceral fat areas (SFA) and then extracted 7 adiposity-related quantitative features. Three multivariate data analysis models (linear regression, logistic regression and Cox proportional hazards regression) were performed respectively to investigate the potential association between the model-generated prediction results and the patients' progression-free survival (PFS) and overall survival (OS). The results show that using all 3 statistical models, a statistically significant association was detected between the model-generated results and both of the two clinical outcomes in the group of patients receiving maintenance bevacizumab (p<0.01), while there were no significant association for both PFS and OS in the group of patients without receiving maintenance bevacizumab. Therefore, this study demonstrated the feasibility of using quantitative adiposity-related CT image features based statistical prediction models to generate a new clinical marker and predict the clinical outcome of EOC patients receiving maintenance bevacizumab-based chemotherapy.

Characterization of healthy and osteoarthritic chondrocyte cell patterns on phase contrast CT images of the knee cartilage matrix

NASA Astrophysics Data System (ADS)

Nagarajan, Mahesh B.; Coan, Paola; Huber, Markus B.; Yang, Chien-Chun; Glaser, Christian; Reiser, Maximilian F.; Wismüller, Axel

2012-03-01

The current approach to evaluating cartilage degeneration at the knee joint requires visualization of the joint space on radiographic images where indirect cues such as joint space narrowing serve as markers for osteoarthritis. A recent novel approach to visualizing the knee cartilage matrix using phase contrast CT imaging (PCI-CT) was shown to allow direct examination of chondrocyte cell patterns and their subsequent correlation to osteoarthritis. This study aims to characterize chondrocyte cell patterns in the radial zone of the knee cartilage matrix in the presence and absence of osteoarthritic damage through both gray-level co-occurrence matrix (GLCM) derived texture features as well as Minkowski Functionals (MF). Thirteen GLCM and three MF texture features were extracted from 404 regions of interest (ROI) annotated on PCI images of healthy and osteoarthritic specimens of knee cartilage. These texture features were then used in a machine learning task to classify ROIs as healthy or osteoarthritic. A fuzzy k-nearest neighbor classifier was used and its performance was evaluated using the area under the ROC curve (AUC). The best classification performance was observed with the MF features 'perimeter' and 'Euler characteristic' and with GLCM correlation features (f3 and f13). With the experimental conditions used in this study, both Minkowski Functionals and GLCM achieved a high classification performance (AUC value of 0.97) in the task of distinguishing between health and osteoarthritic ROIs. These results show that such quantitative analysis of chondrocyte patterns in the knee cartilage matrix can distinguish between healthy and osteoarthritic tissue with high accuracy.

Contribution of postmortem multidetector CT scanning to identification of the deceased in a mass disaster: Experience gained from the 2009 Victorian bushfires.

PubMed

O'Donnell, C; Iino, M; Mansharan, K; Leditscke, J; Woodford, N

2011-02-25

CT scanning of the deceased is an established technique performed on all individuals admitted to VIFM over the last 5 years. It is used primarily to assist pathologists in determining cause and manner of death but is also invaluable for identification of unknown deceased individuals where traditional methods are not possible. Based on this experience, CT scanning was incorporated into phase 2 of the Institute's DVI process for the 2009 Victorian bushfires. All deceased individuals and fragmented remains admitted to the mortuary were CT scanned in their body bags using established protocols. Images were reviewed by 2 teams of 2 radiologists experienced in forensic imaging and the findings transcribed onto a data sheet constructed specifically for the DVI exercise. The contents of 255 body bags were examined in the 28 days following the fires. 164 missing persons were included in the DVI process with 163 deceased individuals eventually identified. CT contributed to this identification in 161 persons. In 2 cases, radiologists were unable to recognize commingled remains. CT was utilized in the initial triage of each bag's contents. If radiological evaluation determined that bodies were incomplete then this information was provided to search teams who revisited the scenes of death. CT was helpful in differentiation of human from non-human remains in 8 bags, recognition of human/animal commingling in 10 bags and human commingling in 6 bags. In 61% of cases gender was able to be determined on CT using a novel technique of genitalia detection and in all but 2 cases this was correct. Age range was able to be determined on CT in 94% with an accuracy of 76%. Specific identification features detected on CT included the presence of disease (14 disease entities in 13 cases), medical devices (26 devices in 19 cases) and 274 everyday metallic items associated with the remains of 135 individuals. CT scanning provided useful information prior to autopsy by flagging likely findings including the presence of non-human remains, at the time of autopsy by assisting in the localization of identifying features in heavily disfigured bodies, and after autopsy by retrospective review of images for clarification of issues that arose at the time of pathologist case review. In view of the success of CT scanning in this mass disaster, DVI administrators should explore the incorporation of CT services into their disaster plans. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

A new methodological approach for PET implementation in radiotherapy treatment planning.

PubMed

Bellan, Elena; Ferretti, Alice; Capirci, Carlo; Grassetto, Gaia; Gava, Marcello; Chondrogiannis, Sotirios; Virdis, Graziella; Marzola, Maria Cristina; Massaro, Arianna; Rubello, Domenico; Nibale, Otello

2012-05-01

In this paper, a new methodological approach to using PET information in radiotherapy treatment planning has been discussed. Computed tomography (CT) represents the primary modality to plan personalized radiation treatment, because it provides the basic electron density map for correct dose calculation. If PET scanning is also performed it is typically coregistered with the CT study. This operation can be executed automatically by a hybrid PET/CT scanner or, if the PET and CT imaging sets have been acquired through different equipment, by a dedicated module of the radiotherapy treatment planning system. Both approaches have some disadvantages: in the first case, the bore of a PET/CT system generally used in clinical practice often does not allow the use of certain bulky devices for patient immobilization in radiotherapy, whereas in the second case the result could be affected by limitations in window/level visualization of two different image modalities, and the displayed PET volumes can appear not to be related to the actual uptake into the patient. To overcome these problems, at our centre a specific procedure has been studied and tested in 30 patients, allowing good results of precision in the target contouring to be obtained. The process consists of segmentation of the biological target volume by a dedicated PET/CT console and its export to a dedicated radiotherapy system, where an image registration between the CT images acquired by the PET/CT scanner and a large-bore CT is performed. The planning target volume is contoured only on the large-bore CT and is used for virtual simulation, to individuate permanent skin markers on the patient.

Imaging of cerebellopontine angle lesions: an update. Part 2: intra-axial lesions, skull base lesions that may invade the CPA region, and non-enhancing extra-axial lesions.

PubMed

Bonneville, Fabrice; Savatovsky, Julien; Chiras, Jacques

2007-11-01

Computed tomography (CT) and magnetic resonance (MR) imaging reliably demonstrate typical features of vestibular schwannomas or meningiomas in the vast majority of mass lesions responsible for cerebellopontine angle (CPA) syndrome. However, a large variety of unusual lesions can also be encountered in the CPA. Covering the entire spectrum of lesions potentially found in the CPA, these articles explain the pertinent neuroimaging features that radiologists need to know to make clinically relevant diagnoses in these cases, including data from diffusion- and perfusion-weighted imaging or MR spectroscopy, when available. A diagnostic algorithm based on the lesion's site of origin, shape and margins, density, signal intensity and contrast material uptake is also proposed. Non-enhancing extra-axial CPA masses are cystic (epidermoid cyst, arachnoid cyst, neurenteric cyst) or contain fat (dermoid cyst, lipoma). Tumours can also extend into the CPA by extension from the skull base (paraganglioma, chondromatous tumours, chordoma, cholesterol granuloma, endolymphatic sac tumour). Finally, brain stem or ventricular tumours can present with a significant exophytic component in the CPA that may be difficult to differentiate from an extra-axial lesion (lymphoma, hemangioblastoma, choroid plexus papilloma, ependymoma, glioma, medulloblastoma, dysembryoplastic neuroepithelial tumour).

Face recognition using slow feature analysis and contourlet transform

NASA Astrophysics Data System (ADS)

Wang, Yuehao; Peng, Lingling; Zhe, Fuchuan

2018-04-01

In this paper we propose a novel face recognition approach based on slow feature analysis (SFA) in contourlet transform domain. This method firstly use contourlet transform to decompose the face image into low frequency and high frequency part, and then takes technological advantages of slow feature analysis for facial feature extraction. We named the new method combining the slow feature analysis and contourlet transform as CT-SFA. The experimental results on international standard face database demonstrate that the new face recognition method is effective and competitive.

Neuropathologic Characterization of Pontocerebellar Hypoplasia Type 6 Associated With Cardiomyopathy and Hydrops Fetalis and Severe Multisystem Respiratory Chain Deficiency due to Novel RARS2 Mutations.

PubMed

Lax, Nichola Z; Alston, Charlotte L; Schon, Katherine; Park, Soo-Mi; Krishnakumar, Deepa; He, Langping; Falkous, Gavin; Ogilvy-Stuart, Amanda; Lees, Christoph; King, Rosalind H; Hargreaves, Iain P; Brown, Garry K; McFarland, Robert; Dean, Andrew F; Taylor, Robert W

2015-07-01

Autosomal recessive mutations in the RARS2 gene encoding the mitochondrial arginyl-transfer RNA synthetase cause infantile-onset myoencephalopathy pontocerebellar hypoplasia type 6 (PCH6). We describe 2 sisters with novel compound heterozygous RARS2 mutations who presented perinatally with neurologic features typical of PCH6 but with additional features including cardiomyopathy, hydrops, and pulmonary hypoplasia and who died at 1 day and 14 days of age. Magnetic resonance imaging findings included marked cerebellar hypoplasia, gyral immaturity, punctate lesions in cerebral white matter, and unfused deep cerebral grey matter. Enzyme histochemistry of postmortem tissues revealed a near-global cytochrome c oxidase-deficiency; assessment of respiratory chain enzyme activities confirmed severe deficiencies involving complexes I, III, and IV. Molecular genetic studies revealed 2 RARS2 gene mutations: a c.1A>G, p.? variant predicted to abolish the initiator methionine, and a deep intronic c.613-3927C>T variant causing skipping of exons 6-8 in the mature RARS2 transcript. Neuropathologic investigation included low brain weights, small brainstem and cerebellum, deep cerebral white matter pathology, pontine nucleus neuron loss (in 1 sibling), and peripheral nerve pathology. Mitochondrial respiratory chain immunohistochemistry in brain tissues confirmed an absence of complexes I and IV immunoreactivity with sparing of mitochondrial numbers. These cases expand the clinical spectrum of RARS2 mutations, including antenatal features and widespread mitochondrial respiratory chain deficiencies in postmortem brain tissues.

Neuropathologic Characterization of Pontocerebellar Hypoplasia Type 6 Associated With Cardiomyopathy and Hydrops Fetalis and Severe Multisystem Respiratory Chain Deficiency due to Novel RARS2 Mutations

PubMed Central

Lax, Nichola Z.; Alston, Charlotte L.; Schon, Katherine; Park, Soo-Mi; Krishnakumar, Deepa; He, Langping; Falkous, Gavin; Ogilvy-Stuart, Amanda; Lees, Christoph; King, Rosalind H.; Hargreaves, Iain P.; Brown, Garry K.; McFarland, Robert; Dean, Andrew F.; Taylor, Robert W.

2015-01-01

Abstract Autosomal recessive mutations in the RARS2 gene encoding the mitochondrial arginyl-transfer RNA synthetase cause infantile-onset myoencephalopathy pontocerebellar hypoplasia type 6 (PCH6). We describe 2 sisters with novel compound heterozygous RARS2 mutations who presented perinatally with neurologic features typical of PCH6 but with additional features including cardiomyopathy, hydrops, and pulmonary hypoplasia and who died at 1 day and 14 days of age. Magnetic resonance imaging findings included marked cerebellar hypoplasia, gyral immaturity, punctate lesions in cerebral white matter, and unfused deep cerebral grey matter. Enzyme histochemistry of postmortem tissues revealed a near-global cytochrome c oxidase-deficiency; assessment of respiratory chain enzyme activities confirmed severe deficiencies involving complexes I, III, and IV. Molecular genetic studies revealed 2 RARS2 gene mutations: a c.1A>G, p.? variant predicted to abolish the initiator methionine, and a deep intronic c.613-3927C>T variant causing skipping of exons 6–8 in the mature RARS2 transcript. Neuropathologic investigation included low brain weights, small brainstem and cerebellum, deep cerebral white matter pathology, pontine nucleus neuron loss (in 1 sibling), and peripheral nerve pathology. Mitochondrial respiratory chain immunohistochemistry in brain tissues confirmed an absence of complexes I and IV immunoreactivity with sparing of mitochondrial numbers. These cases expand the clinical spectrum of RARS2 mutations, including antenatal features and widespread mitochondrial respiratory chain deficiencies in postmortem brain tissues. PMID:26083569

Expanding the spectrum of phenotypes associated with germline PIGA mutations: a child with developmental delay, accelerated linear growth, facial dysmorphisms, elevated alkaline phosphatase, and progressive CNS abnormalities.

PubMed

van der Crabben, Saskia N; Harakalova, Magdalena; Brilstra, Eva H; van Berkestijn, Frédérique M C; Hofstede, Floris C; van Vught, Adrianus J; Cuppen, Edwin; Kloosterman, Wigard; Ploos van Amstel, Hans Kristian; van Haaften, Gijs; van Haelst, Mieke M

2014-01-01

Phosphatidyl inositol glycan (PIG) enzyme subclasses are involved in distinct steps of glycosyl phosphatidyl inositol anchor protein biosynthesis. Glycolsyl phosphatidyl inositol-anchored proteins have heterogeneous functions; they can function as enzymes, adhesion molecules, complement regulators and co-receptors in signal transduction pathways. Germline mutations in genes encoding different members of the PIG family result in diverse conditions with (severe) developmental delay, (neonatal) seizures, hypotonia, CNS abnormalities, growth abnormalities, and congenital abnormalities as hallmark features. The variability of clinical features resembles the typical diversity of other glycosylation pathway deficiencies such as the congenital disorders of glycosylation. Here, we report the first germline missense mutation in the PIGA gene associated with accelerated linear growth, obesity, central hypotonia, severe refractory epilepsy, cardiac anomalies, mild facial dysmorphic features, mildly elevated alkaline phosphatase levels, and CNS anomalies consisting of progressive cerebral atrophy, insufficient myelinization, and cortical MRI signal abnormalities. X-exome sequencing in the proband identified a c.278C>T (p.Pro93Leu) mutation in the PIGA gene. The mother and maternal grandmother were unaffected carriers and the mother showed 100% skewing of the X-chromosome harboring the mutation. These results together with the clinical similarity of the patient reported here and the previously reported patients with a germline nonsense mutation in PIGA support the determination that this mutation caused the phenotype in this family. © 2013 Wiley Periodicals, Inc.

Scanning transmission ion micro-tomography (STIM-T) of biological specimens.

PubMed

Schwertner, Micheal; Sakellariou, Arthur; Reinert, Tilo; Butz, Tilman

2006-05-01

Computed tomography (CT) was applied to sets of Scanning Transmission Ion Microscopy (STIM) projections recorded at the LIPSION ion beam laboratory (Leipzig) in order to visualize the 3D-mass distribution in several specimens. Examples for a test structure (copper grid) and for biological specimens (cartilage cells, cygospore) are shown. Scanning Transmission Micro-Tomography (STIM-T) at a resolution of 260 nm was demonstrated for the first time. Sub-micron features of the Cu-grid specimen were verified by scanning electron microscopy. The ion energy loss measured during a STIM-T experiment is related to the mass density of the specimen. Typically, biological specimens can be analysed without staining. Only shock freezing and freeze-drying is required to preserve the ultra-structure of the specimen. The radiation damage to the specimen during the experiment can be neglected. This is an advantage compared to other techniques like X-ray micro-tomography. At present, the spatial resolution is limited by beam position fluctuations and specimen vibrations.

Atypical hereditary sensory and autonomic neuropathy type IV with neither mental retardation nor pain insensitivity.

PubMed

Jung, Chae Lim; Ki, Chang-Seok; Kim, Byoung Joon; Lee, Jong-Hyuck; Sung, Ki-Sun; Kim, Jong-Won; Park, Youn-Soo

2013-12-01

Hereditary sensory and autonomic neuropathy type IV is an autosomal recessive disorder characterized by severe mental retardation and self-mutilation-related complications. Recently, we investigated a 16-year-old Korean boy with normal intelligence. He had preserved pain sensation but was suspected of having hereditary sensory and autonomic neuropathy type IV because of the recurrent bone fractures and painless joint destruction in the absence of any predisposing medical conditions. Genetic analysis of the NTRK1 gene revealed compound heterozygous mutations including c.851-33T>A and c.2303C>T (p.Pro768Leu) in the NTRK1 gene. The p.Pro768Leu mutation has been identified in 2 Japanese patients with a mild phenotype. Therefore, although it is rare, hereditary sensory and autonomic neuropathy type IV should be considered in patients with recurrent bone fractures and painless joint destruction who do not have any predisposing conditions even when they do not have typical clinical features such as mental retardation or pain insensitivity.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ushizima, Daniela; Perciano, Talita; Krishnan, Harinarayan

Fibers provide exceptional strength-to-weight ratio capabilities when woven into ceramic composites, transforming them into materials with exceptional resistance to high temperature, and high strength combined with improved fracture toughness. Microcracks are inevitable when the material is under strain, which can be imaged using synchrotron X-ray computed micro-tomography (mu-CT) for assessment of material mechanical toughness variation. An important part of this analysis is to recognize fibrillar features. This paper presents algorithms for detecting and quantifying composite cracks and fiber breaks from high-resolution image stacks. First, we propose recognition algorithms to identify the different structures of the composite, including matrix cracks andmore » fibers breaks. Second, we introduce our package F3D for fast filtering of large 3D imagery, implemented in OpenCL to take advantage of graphic cards. Results show that our algorithms automatically identify micro-damage and that the GPU-based implementation introduced here takes minutes, being 17x faster than similar tools on a typical image file.« less

Unusual phenotypic expression of an XLRS1 mutation in X-linked juvenile retinoschisis.

PubMed

Dodds, Jodi A; Srivastava, Anand K; Holden, Kenton R

2006-04-01

X-linked juvenile retinoschisis is a rare progressive vitreoretinal degenerative process that appears in early childhood, results in decreased visual acuity and blindness (if severe), and is caused by various mutations within the XLRS1 gene at Xp22.2. We report an affected family of Western European ancestry with X-linked juvenile retinoschisis. The family was found to carry a 304C-->T substitution in exon 4 of the XLRS1 gene, resulting in an Arg102Trp amino acid substitution. Two of the four available clinical cases in this family were found to carry the mutation. All available mothers of affected males were found to be unaffected carriers of the mutation, a typical feature of X-linked diseases. Two new female carriers, sisters of affected males, were identified and counseled accordingly. Questionnaires on visual functioning were given to the affected family members to examine the psychologic and sociologic impact of X-linked juvenile retinoschisis, which documented an associated stigma even when affected with a "mild" phenotype.

Automatic identification of IASLC-defined mediastinal lymph node stations on CT scans using multi-atlas organ segmentation

NASA Astrophysics Data System (ADS)

Hoffman, Joanne; Liu, Jiamin; Turkbey, Evrim; Kim, Lauren; Summers, Ronald M.

2015-03-01

Station-labeling of mediastinal lymph nodes is typically performed to identify the location of enlarged nodes for cancer staging. Stations are usually assigned in clinical radiology practice manually by qualitative visual assessment on CT scans, which is time consuming and highly variable. In this paper, we developed a method that automatically recognizes the lymph node stations in thoracic CT scans based on the anatomical organs in the mediastinum. First, the trachea, lungs, and spines are automatically segmented to locate the mediastinum region. Then, eight more anatomical organs are simultaneously identified by multi-atlas segmentation. Finally, with the segmentation of those anatomical organs, we convert the text definitions of the International Association for the Study of Lung Cancer (IASLC) lymph node map into patient-specific color-coded CT image maps. Thus, a lymph node station is automatically assigned to each lymph node. We applied this system to CT scans of 86 patients with 336 mediastinal lymph nodes measuring equal or greater than 10 mm. 84.8% of mediastinal lymph nodes were correctly mapped to their stations.

Optimizing spectral CT parameters for material classification tasks

NASA Astrophysics Data System (ADS)

Rigie, D. S.; La Rivière, P. J.

2016-06-01

In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC’s) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC’s predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies.

Optimizing Spectral CT Parameters for Material Classification Tasks

PubMed Central

Rigie, D. S.; La Rivière, P. J.

2017-01-01

In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC’s) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC’s predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies. PMID:27227430

A rare adult renal neuroblastoma better imaged by 18F-FDG than by 68Ga-dotanoc in the PET/CT scan.

PubMed

Jain, Tarun Kumar; Singh, Sharwan Kumar; Sood, Ashwani; Ashwathanarayama, Abhiram Gj; Basher, Rajender Kumar; Shukla, Jaya; Mittal, Bhagwant Rai

2017-01-01

Primary renal neuroblastoma is an uncommon tumor in children and extremely rare in adults. We present a case of a middle aged female having a large retroperitoneal mass involving the right kidney with features of neuroblastoma on pre-operative histopathology. Whole-body fluorine-18-fluoro-deoxyglucose positron emission tomography ( 18 F-FDG PET/CT) and 68 Ga-dotanoc PET/CT scans performed for staging and therapeutic potential revealed a tracer avid mass replacing the right kidney and also pelvic lymph nodes. The 18 F-FDG PET/CT scan showed better both the primary lesion and the metastases in the pelvic lymph nodes than the 68 Ga-dotanoc scan supporting diagnosis and treatment planning.

An artificial neural networks approach for assessment treatment response in oncological patients using PET/CT images.

PubMed

Nogueira, Mariana A; Abreu, Pedro H; Martins, Pedro; Machado, Penousal; Duarte, Hugo; Santos, João

2017-02-13

Positron Emission Tomography - Computed Tomography (PET/CT) imaging is the basis for the evaluation of response-to-treatment of several oncological diseases. In practice, such evaluation is manually performed by specialists, which is rather complex and time-consuming. Evaluation measures have been proposed, but with questionable reliability. The usage of before and after-treatment image descriptors of the lesions for treatment response evaluation is still a territory to be explored. In this project, Artificial Neural Network approaches were implemented to automatically assess treatment response of patients suffering from neuroendocrine tumors and Hodgkyn lymphoma, based on image features extracted from PET/CT. The results show that the considered set of features allows for the achievement of very high classification performances, especially when data is properly balanced. After synthetic data generation and PCA-based dimensionality reduction to only two components, LVQNN assured classification accuracies of 100%, 100%, 96.3% and 100% regarding the 4 response-to-treatment classes.

Bladder Cancer Treatment Response Assessment in CT using Radiomics with Deep-Learning.

PubMed

Cha, Kenny H; Hadjiiski, Lubomir; Chan, Heang-Ping; Weizer, Alon Z; Alva, Ajjai; Cohan, Richard H; Caoili, Elaine M; Paramagul, Chintana; Samala, Ravi K

2017-08-18

Cross-sectional X-ray imaging has become the standard for staging most solid organ malignancies. However, for some malignancies such as urinary bladder cancer, the ability to accurately assess local extent of the disease and understand response to systemic chemotherapy is limited with current imaging approaches. In this study, we explored the feasibility that radiomics-based predictive models using pre- and post-treatment computed tomography (CT) images might be able to distinguish between bladder cancers with and without complete chemotherapy responses. We assessed three unique radiomics-based predictive models, each of which employed different fundamental design principles ranging from a pattern recognition method via deep-learning convolution neural network (DL-CNN), to a more deterministic radiomics feature-based approach and then a bridging method between the two, utilizing a system which extracts radiomics features from the image patterns. Our study indicates that the computerized assessment using radiomics information from the pre- and post-treatment CT of bladder cancer patients has the potential to assist in assessment of treatment response.

Multidetector CT of musculoskeletal disease in the pediatric patient: principles, techniques, and clinical applications.

PubMed

Fayad, Laura M; Johnson, Pamela; Fishman, Elliot K

2005-01-01

Computed tomography (CT) plays an important role in the evaluation of musculoskeletal disease in the pediatric patient. With the advent of high-performance 16-section multidetector CT, images can be produced with subsecond gantry rotation times and with submillimeter acquisition, which yields true isotropic high-resolution volume data sets; these features are not attainable with older spiral CT technology. Such capabilities are particularly helpful in the evaluation of pediatric patients by virtually eliminating the need for sedation and minimizing dependence on patient cooperation. The role of three-dimensional (3D) volume imaging in the evaluation of pediatric musculoskeletal disease continues to evolve, with this technique becoming increasingly important in detection and characterization of lesions as well as in decisions about patient care. Specific designs and protocols for multidetector CT studies can be selected to minimize radiation dose to the patient. Principal clinical applications of 3D CT in evaluation of the pediatric musculoskeletal system include developmental abnormalities, trauma, neoplasms, and postoperative imaging.

Detection of Local Cancer Recurrence After Stereotactic Ablative Radiation Therapy for Lung Cancer: Physician Performance Versus Radiomic Assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mattonen, Sarah A.; Baines Imaging Research Laboratory, London Regional Cancer Program, London, Ontario; Palma, David A., E-mail: david.palma@lhsc.on.ca

Purpose: Stereotactic ablative radiation therapy (SABR) is a guideline-specified treatment option for early-stage lung cancer. However, significant posttreatment fibrosis can occur and obfuscate the detection of local recurrence. The goal of this study was to assess physician ability to detect timely local recurrence and to compare physician performance with a radiomics tool. Methods and Materials: Posttreatment computed tomography (CT) scans (n=182) from 45 patients treated with SABR (15 with local recurrence matched to 30 with no local recurrence) were used to measure physician and radiomic performance in assessing response. Scans were individually scored by 3 thoracic radiation oncologists and 3more » thoracic radiologists, all of whom were blinded to clinical outcomes. Radiomic features were extracted from the same images. Performances of the physician assessors and the radiomics signature were compared. Results: When taking into account all CT scans during the whole follow-up period, median sensitivity for physician assessment of local recurrence was 83% (range, 67%-100%), and specificity was 75% (range, 67%-87%), with only moderate interobserver agreement (κ = 0.54) and a median time to detection of recurrence of 15.5 months. When determining the early prediction of recurrence within <6 months after SABR, physicians assessed the majority of images as benign injury/no recurrence, with a mean error of 35%, false positive rate (FPR) of 1%, and false negative rate (FNR) of 99%. At the same time point, a radiomic signature consisting of 5 image-appearance features demonstrated excellent discrimination, with an area under the receiver operating characteristic curve of 0.85, classification error of 24%, FPR of 24%, and FNR of 23%. Conclusions: These results suggest that radiomics can detect early changes associated with local recurrence that are not typically considered by physicians. This decision support system could potentially allow for early salvage therapy of patients with local recurrence after SABR.« less

Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teramoto, Atsushi, E-mail: teramoto@fujita-hu.ac.jp; Fujita, Hiroshi; Yamamuro, Osamu

Purpose: Automated detection of solitary pulmonary nodules using positron emission tomography (PET) and computed tomography (CT) images shows good sensitivity; however, it is difficult to detect nodules in contact with normal organs, and additional efforts are needed so that the number of false positives (FPs) can be further reduced. In this paper, the authors propose an improved FP-reduction method for the detection of pulmonary nodules in PET/CT images by means of convolutional neural networks (CNNs). Methods: The overall scheme detects pulmonary nodules using both CT and PET images. In the CT images, a massive region is first detected using anmore » active contour filter, which is a type of contrast enhancement filter that has a deformable kernel shape. Subsequently, high-uptake regions detected by the PET images are merged with the regions detected by the CT images. FP candidates are eliminated using an ensemble method; it consists of two feature extractions, one by shape/metabolic feature analysis and the other by a CNN, followed by a two-step classifier, one step being rule based and the other being based on support vector machines. Results: The authors evaluated the detection performance using 104 PET/CT images collected by a cancer-screening program. The sensitivity in detecting candidates at an initial stage was 97.2%, with 72.8 FPs/case. After performing the proposed FP-reduction method, the sensitivity of detection was 90.1%, with 4.9 FPs/case; the proposed method eliminated approximately half the FPs existing in the previous study. Conclusions: An improved FP-reduction scheme using CNN technique has been developed for the detection of pulmonary nodules in PET/CT images. The authors’ ensemble FP-reduction method eliminated 93% of the FPs; their proposed method using CNN technique eliminates approximately half the FPs existing in the previous study. These results indicate that their method may be useful in the computer-aided detection of pulmonary nodules using PET/CT images.« less

CT and MR Imaging Diagnosis and Staging of Hepatocellular Carcinoma: Part I. Development, Growth, and Spread: Key Pathologic and Imaging Aspects

PubMed Central

Choi, Jin-Young; Lee, Jeong-Min

2014-01-01

Computed tomography (CT) and magnetic resonance (MR) imaging play critical roles in the diagnosis and staging of hepatocellular carcinoma (HCC). The first article of this two-part review discusses key concepts of HCC development, growth, and spread, emphasizing those features with imaging correlates and hence most relevant to radiologists; state-of-the-art CT and MR imaging technique with extracellular and hepatobiliary contrast agents; and the imaging appearance of precursor nodules that eventually may transform into overt HCC. © RSNA, 2014 PMID:25153274

Body Imaging

NASA Technical Reports Server (NTRS)

1990-01-01

Magnetic Resonance Imaging (MRI) and Computer-aided Tomography (CT) images are often complementary. In most cases, MRI is good for viewing soft tissue but not bone, while CT images are good for bone but not always good for soft tissue discrimination. Physicians and engineers in the Department of Radiology at the University of Michigan Hospitals are developing a technique for combining the best features of MRI and CT scans to increase the accuracy of discriminating one type of body tissue from another. One of their research tools is a computer program called HICAP. The program can be used to distinguish between healthy and diseased tissue in body images.

Cauda equina syndrome complicating ankylosing spondylitis: use of electromyography and computerised tomography in diagnosis.

PubMed

Young, A; Dixon, A; Getty, J; Renton, P; Vacher, H

1981-06-01

A case of the cauda equina syndrome complicating ankylosing spondylitis (AS) is described. An unusual feature of this case was the relapsing and remitting nature of the condition, but there is sufficient evidence to explain the clinical picture on the basis of a recurrent intraspinal inflammatory process. The clinical and radiological features are similar to those of a further 28 reported in the literature. An electromyogram (EMG) proved important in defining the extent of neurological involvement. Computerised tomography (CT) showed marked laminar erosion and no bony exit foramen encroachment. We believe that the clinical diagnosis of this condition can be adequately confirmed with plain radiology, EMG, and CT scan.

Quantitative CT analysis for the preoperative prediction of pathologic grade in pancreatic neuroendocrine tumors

NASA Astrophysics Data System (ADS)

Chakraborty, Jayasree; Pulvirenti, Alessandra; Yamashita, Rikiya; Midya, Abhishek; Gönen, Mithat; Klimstra, David S.; Reidy, Diane L.; Allen, Peter J.; Do, Richard K. G.; Simpson, Amber L.

2018-02-01

Pancreatic neuroendocrine tumors (PanNETs) account for approximately 5% of all pancreatic tumors, affecting one individual per million each year.1 PanNETs are difficult to treat due to biological variability from benign to highly malignant, indolent to very aggressive. The World Health Organization classifies PanNETs into three categories based on cell proliferative rate, usually detected using the Ki67 index and cell morphology: low-grade (G1), intermediate-grade (G2) and high-grade (G3) tumors. Knowledge of grade prior to treatment would select patients for optimal therapy: G1/G2 tumors respond well to somatostatin analogs and targeted or cytotoxic drugs whereas G3 tumors would be targeted with platinum or alkylating agents.2, 3 Grade assessment is based on the pathologic examination of the surgical specimen, biopsy or ne-needle aspiration; however, heterogeneity in the proliferative index can lead to sampling errors.4 Based on studies relating qualitatively assessed shape and enhancement characteristics on CT imaging to tumor grade in PanNET,5 we propose objective classification of PanNET grade with quantitative analysis of CT images. Fifty-five patients were included in our retrospective analysis. A pathologist graded the tumors. Texture and shape-based features were extracted from CT. Random forest and naive Bayes classifiers were compared for the classification of G1/G2 and G3 PanNETs. The best area under the receiver operating characteristic curve (AUC) of 0:74 and accuracy of 71:64% was achieved with texture features. The shape-based features achieved an AUC of 0:70 and accuracy of 78:73%.

Intra-operative adjustment of standard planes in C-arm CT image data.

PubMed

Brehler, Michael; Görres, Joseph; Franke, Jochen; Barth, Karl; Vetter, Sven Y; Grützner, Paul A; Meinzer, Hans-Peter; Wolf, Ivo; Nabers, Diana

2016-03-01

With the help of an intra-operative mobile C-arm CT, medical interventions can be verified and corrected, avoiding the need for a post-operative CT and a second intervention. An exact adjustment of standard plane positions is necessary for the best possible assessment of the anatomical regions of interest but the mobility of the C-arm causes the need for a time-consuming manual adjustment. In this article, we present an automatic plane adjustment at the example of calcaneal fractures. We developed two feature detection methods (2D and pseudo-3D) based on SURF key points and also transferred the SURF approach to 3D. Combined with an atlas-based registration, our algorithm adjusts the standard planes of the calcaneal C-arm images automatically. The robustness of the algorithms is evaluated using a clinical data set. Additionally, we tested the algorithm's performance for two registration approaches, two resolutions of C-arm images and two methods for metal artifact reduction. For the feature extraction, the novel 3D-SURF approach performs best. As expected, a higher resolution ([Formula: see text] voxel) leads also to more robust feature points and is therefore slightly better than the [Formula: see text] voxel images (standard setting of device). Our comparison of two different artifact reduction methods and the complete removal of metal in the images shows that our approach is highly robust against artifacts and the number and position of metal implants. By introducing our fast algorithmic processing pipeline, we developed the first steps for a fully automatic assistance system for the assessment of C-arm CT images.

An approach for quantitative image quality analysis for CT

NASA Astrophysics Data System (ADS)

Rahimi, Amir; Cochran, Joe; Mooney, Doug; Regensburger, Joe

2016-03-01

An objective and standardized approach to assess image quality of Compute Tomography (CT) systems is required in a wide variety of imaging processes to identify CT systems appropriate for a given application. We present an overview of the framework we have developed to help standardize and to objectively assess CT image quality for different models of CT scanners used for security applications. Within this framework, we have developed methods to quantitatively measure metrics that should correlate with feature identification, detection accuracy and precision, and image registration capabilities of CT machines and to identify strengths and weaknesses in different CT imaging technologies in transportation security. To that end we have designed, developed and constructed phantoms that allow for systematic and repeatable measurements of roughly 88 image quality metrics, representing modulation transfer function, noise equivalent quanta, noise power spectra, slice sensitivity profiles, streak artifacts, CT number uniformity, CT number consistency, object length accuracy, CT number path length consistency, and object registration. Furthermore, we have developed a sophisticated MATLAB based image analysis tool kit to analyze CT generated images of phantoms and report these metrics in a format that is standardized across the considered models of CT scanners, allowing for comparative image quality analysis within a CT model or between different CT models. In addition, we have developed a modified sparse principal component analysis (SPCA) method to generate a modified set of PCA components as compared to the standard principal component analysis (PCA) with sparse loadings in conjunction with Hotelling T2 statistical analysis method to compare, qualify, and detect faults in the tested systems.

New auto-segment method of cerebral hemorrhage

NASA Astrophysics Data System (ADS)

Wang, Weijiang; Shen, Tingzhi; Dang, Hua

2007-12-01

A novel method for Computerized tomography (CT) cerebral hemorrhage (CH) image automatic segmentation is presented in the paper, which uses expert system that models human knowledge about the CH automatic segmentation problem. The algorithm adopts a series of special steps and extracts some easy ignored CH features which can be found by statistic results of mass real CH images, such as region area, region CT number, region smoothness and some statistic CH region relationship. And a seven steps' extracting mechanism will ensure these CH features can be got correctly and efficiently. By using these CH features, a decision tree which models the human knowledge about the CH automatic segmentation problem has been built and it will ensure the rationality and accuracy of the algorithm. Finally some experiments has been taken to verify the correctness and reasonable of the automatic segmentation, and the good correct ratio and fast speed make it possible to be widely applied into practice.

Role of computed tomography of abdomen in difficult to diagnose typhoid fever: a case series.

PubMed

Hafeez, Wajid; Rajalakshmi, S; Sripriya, S; Madhu Bashini, M

2018-04-01

Background and Aim Diagnosis of typhoid is challenging when blood cultures fail to isolate Salmonella species. We report our experience with interpreting computed tomography (CT) abdomen findings in a case series of typhoid fever. Methods The case series consisted of patients who had a CT abdomen done as part of their investigations and a final diagnosis of typhoid fever. The CT films were reviewed and findings evaluated for distinctive features. Results During 2011-2017, 11 patients met the inclusion criteria. Indication for CT was pyrexia of unknown origin in the majority of patients. Review of CT films revealed mesenteric lymphadenopathy (100%), terminal ileum thickening (85%), hepatosplenomegaly (45%), retroperitoneal lymphadenopathy (18%) and ascites (9%). Conclusions Enhancing discrete mesenteric lymphadenopathy and terminal ileum thickening are non-specific findings noted in typhoid fever. Absence of matted necrotic nodes and peritoneal thickening rule out tuberculosis and raise suspicion of typhoid fever in endemic regions.

Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates

NASA Astrophysics Data System (ADS)

Farace, Paolo

2014-11-01

A two-steps procedure is presented to convert dual-energy CT data to stopping power ratio (SPR), relative to water. In the first step the relative electron density (RED) is calculated from dual-energy CT-numbers by means of a bi-linear relationship: RED = a HUscH + b HUscL + c, where HUscH and HUscL are scaled units (HUsc = HU + 1000) acquired at high and low energy respectively, and the three parameters a, b and c has to be determined for each CT scanner. In the second step the RED values were converted into SPR by means of published poly-line functions, which are invariant as they do not depend on a specific CT scanner. The comparison with other methods provides encouraging results, with residual SPR error on human tissue within 1%. The distinctive features of the proposed method are its simplicity and the generality of the conversion functions.

Spectrum of the Breast Lesions With Increased 18F-FDG Uptake on PET/CT

PubMed Central

Dong, Aisheng; Wang, Yang; Lu, Jianping; Zuo, Changjing

2016-01-01

Abstract Interpretation of 18F-FDG PET/CT studies in breast is challenging owing to nonspecific FDG uptake in various benign and malignant conditions. Benign conditions include breast changes in pregnancy and lactation, gynecomastia, mastitis, fat necrosis, fibroadenoma, intraductal papilloma, and atypical ductal hyperplasia. Among malignancies, invasive ductal carcinoma and invasive lobular carcinoma are common histological types of breast carcinoma. Rarely, other unusual histological types of breast carcinomas (eg, intraductal papillary carcinoma, invasive micropapillary carcinoma, medullary carcinoma, mucinous carcinoma, and metaplastic carcinoma), lymphoma, and metastasis can be the causes. Knowledge of a wide spectrum of hypermetabolic breast lesions on FDG PET/CT is essential in accurate reading of FDG PET/CT. The purpose of this atlas article is to demonstrate features of various breast lesions encountered at our institution, both benign and malignant, which can result in hypermetabolism on FDG PET/CT imaging. PMID:26975010

Experimental verification of ion stopping power prediction from dual energy CT data in tissue surrogates.

PubMed

Farace, Paolo

2014-11-21

A two-steps procedure is presented to convert dual-energy CT data to stopping power ratio (SPR), relative to water. In the first step the relative electron density (RED) is calculated from dual-energy CT-numbers by means of a bi-linear relationship: RED=a HUscH+b HUscL+c, where HUscH and HUscL are scaled units (HUsc=HU+1000) acquired at high and low energy respectively, and the three parameters a, b and c has to be determined for each CT scanner. In the second step the RED values were converted into SPR by means of published poly-line functions, which are invariant as they do not depend on a specific CT scanner. The comparison with other methods provides encouraging results, with residual SPR error on human tissue within 1%. The distinctive features of the proposed method are its simplicity and the generality of the conversion functions.

Correlation Between Findings of Multislice Helical Computed Tomography (CT), Endoscopic Examinations, Endovascular Procedures, and Surgery in Patients with Symptoms of Acute Gastrointestinal Bleeding.

PubMed

Konecki, Dariusz; Grabowska-Derlatka, Laretta; Pacho, Ryszard; Rowiński, Olgierd

2017-01-01

Endoscopic methods (gastroscopy and colonoscopy) are considered fundamental for the diagnosis of gastrointestinal bleeding. In recent years, multidetector computed tomography (MDCT) has also gained importance in diagnosing gastrointestinal bleeding, particularly in hemodynamically unstable patients and in cases with suspected lower gastrointestinal tract bleeding. CT can detect both the source and the cause of active gastrointestinal bleeding, thereby expediting treatment initiation. The study group consisted of 16 patients with clinical symptoms of gastrointestinal bleeding in whom features of active bleeding were observed on CT. In all patients, bleeding was verified by means of other methods such as endoscopic examinations, endovascular procedures, or surgery. The bleeding source was identified on CT in all 16 patients. In 14 cases (87.5%), bleeding was confirmed by other methods. CT is an efficient, fast, and readily available tool for detecting the location of acute gastrointestinal bleeding.

Differential diagnosis of breast masses in South Korean premenopausal women using diffuse optical spectroscopic imaging

NASA Astrophysics Data System (ADS)

Leproux, Anaïs; Kim, You Me; Min, Jun Won; McLaren, Christine E.; Chen, Wen-Pin; O'Sullivan, Thomas D.; Lee, Seung-ha; Chung, Phil-Sang; Tromberg, Bruce J.

2016-07-01

Young patients with dense breasts have a relatively low-positive biopsy rate for breast cancer (˜1 in 7). South Korean women have higher breast density than Westerners. We investigated the benefit of using a functional and metabolic imaging technique, diffuse optical spectroscopic imaging (DOSI), to help the standard of care imaging tools to distinguish benign from malignant lesions in premenopausal Korean women. DOSI uses near-infrared light to measure breast tissue composition by quantifying tissue concentrations of water (ctH2O), bulk lipid (ctLipid), deoxygenated (ctHHb), and oxygenated (ctHbO2) hemoglobin. DOSI spectral signatures specific to abnormal tissue and absent in healthy tissue were also used to form a malignancy index. This study included 19 premenopausal subjects (average age 41±9), corresponding to 11 benign and 10 malignant lesions. Elevated lesion to normal ratio of ctH2O, ctHHb, ctHbO2, total hemoglobin (THb=ctHHb+ctHbO2), and tissue optical index (ctHHb×ctH2O/ctLipid) were observed in the malignant lesions compared to the benign lesions (p<0.02). THb and malignancy index were the two best single predictors of malignancy, with >90% sensitivity and specificity. Malignant lesions showed significantly higher metabolism and perfusion than benign lesions. DOSI spectral features showed high discriminatory power for distinguishing malignant and benign lesions in dense breasts of the Korean population.

SU-E-J-262: Variability in Texture Analysis of Gynecological Tumors in the Context of An 18F-FDG PET Adaptive Protocol

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nawrocki, J; Chino, J; Das, S

Purpose: This study examines the effect on texture analysis due to variable reconstruction of PET images in the context of an adaptive FDG PET protocol for node positive gynecologic cancer patients. By measuring variability in texture features from baseline and intra-treatment PET-CT, we can isolate unreliable texture features due to large variation. Methods: A subset of seven patients with node positive gynecological cancers visible on PET was selected for this study. Prescribed dose varied between 45–50.4Gy, with a 55–70Gy boost to the PET positive nodes. A baseline and intratreatment (between 30–36Gy) PET-CT were obtained on a Siemens Biograph mCT. Eachmore » clinical PET image set was reconstructed 6 times using a TrueX+TOF algorithm with varying iterations and Gaussian filter. Baseline and intra-treatment primary GTVs were segmented using PET Edge (MIM Software Inc., Cleveland, OH), a semi-automatic gradient-based algorithm, on the clinical PET and transferred to the other reconstructed sets. Using an in-house MATLAB program, four 3D texture matrices describing relationships between voxel intensities in the GTV were generated: co-occurrence, run length, size zone, and neighborhood difference. From these, 39 textural features characterizing texture were calculated in addition to SUV histogram features. The percent variability among parameters was first calculated. Each reconstructed texture feature from baseline and intra-treatment per patient was normalized to the clinical baseline scan and compared using the Wilcoxon signed-rank test in order to isolate variations due to reconstruction parameters. Results: For the baseline scans, 13 texture features showed a mean range greater than 10%. For the intra scans, 28 texture features showed a mean range greater than 10%. Comparing baseline to intra scans, 25 texture features showed p <0.05. Conclusion: Variability due to different reconstruction parameters increased with treatment, however, the majority of texture features showed significant changes during treatment independent of reconstruction effects.« less

Characterization of PET/CT images using texture analysis: the past, the present… any future?

PubMed

Hatt, Mathieu; Tixier, Florent; Pierce, Larry; Kinahan, Paul E; Le Rest, Catherine Cheze; Visvikis, Dimitris

2017-01-01

After seminal papers over the period 2009 - 2011, the use of texture analysis of PET/CT images for quantification of intratumour uptake heterogeneity has received increasing attention in the last 4 years. Results are difficult to compare due to the heterogeneity of studies and lack of standardization. There are also numerous challenges to address. In this review we provide critical insights into the recent development of texture analysis for quantifying the heterogeneity in PET/CT images, identify issues and challenges, and offer recommendations for the use of texture analysis in clinical research. Numerous potentially confounding issues have been identified, related to the complex workflow for the calculation of textural features, and the dependency of features on various factors such as acquisition, image reconstruction, preprocessing, functional volume segmentation, and methods of establishing and quantifying correspondences with genomic and clinical metrics of interest. A lack of understanding of what the features may represent in terms of the underlying pathophysiological processes and the variability of technical implementation practices makes comparing results in the literature challenging, if not impossible. Since progress as a field requires pooling results, there is an urgent need for standardization and recommendations/guidelines to enable the field to move forward. We provide a list of correct formulae for usual features and recommendations regarding implementation. Studies on larger cohorts with robust statistical analysis and machine learning approaches are promising directions to evaluate the potential of this approach.

Texture-preserved penalized weighted least-squares reconstruction of low-dose CT image via image segmentation and high-order MRF modeling

NASA Astrophysics Data System (ADS)

Han, Hao; Zhang, Hao; Wei, Xinzhou; Moore, William; Liang, Zhengrong

2016-03-01

In this paper, we proposed a low-dose computed tomography (LdCT) image reconstruction method with the help of prior knowledge learning from previous high-quality or normal-dose CT (NdCT) scans. The well-established statistical penalized weighted least squares (PWLS) algorithm was adopted for image reconstruction, where the penalty term was formulated by a texture-based Gaussian Markov random field (gMRF) model. The NdCT scan was firstly segmented into different tissue types by a feature vector quantization (FVQ) approach. Then for each tissue type, a set of tissue-specific coefficients for the gMRF penalty was statistically learnt from the NdCT image via multiple-linear regression analysis. We also proposed a scheme to adaptively select the order of gMRF model for coefficients prediction. The tissue-specific gMRF patterns learnt from the NdCT image were finally used to form an adaptive MRF penalty for the PWLS reconstruction of LdCT image. The proposed texture-adaptive PWLS image reconstruction algorithm was shown to be more effective to preserve image textures than the conventional PWLS image reconstruction algorithm, and we further demonstrated the gain of high-order MRF modeling for texture-preserved LdCT PWLS image reconstruction.

Early prediction of tumor recurrence based on CT texture changes after stereotactic ablative radiotherapy (SABR) for lung cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mattonen, Sarah A.; Palma, David A.; Department of Oncology, The University of Western Ontario, London, Ontario N6A 4L6

Purpose: Benign computed tomography (CT) changes due to radiation induced lung injury (RILI) are common following stereotactic ablative radiotherapy (SABR) and can be difficult to differentiate from tumor recurrence. The authors measured the ability of CT image texture analysis, compared to more traditional measures of response, to predict eventual cancer recurrence based on CT images acquired within 5 months of treatment. Methods: A total of 24 lesions from 22 patients treated with SABR were selected for this study: 13 with moderate to severe benign RILI, and 11 with recurrence. Three-dimensional (3D) consolidative and ground-glass opacity (GGO) changes were manually delineatedmore » on all follow-up CT scans. Two size measures of the consolidation regions (longest axial diameter and 3D volume) and nine appearance features of the GGO were calculated: 2 first-order features [mean density and standard deviation of density (first-order texture)], and 7 second-order texture features [energy, entropy, correlation, inverse difference moment (IDM), inertia, cluster shade, and cluster prominence]. For comparison, the corresponding response evaluation criteria in solid tumors measures were also taken for the consolidation regions. Prediction accuracy was determined using the area under the receiver operating characteristic curve (AUC) and two-fold cross validation (CV). Results: For this analysis, 46 diagnostic CT scans scheduled for approximately 3 and 6 months post-treatment were binned based on their recorded scan dates into 2–5 month and 5–8 month follow-up time ranges. At 2–5 months post-treatment, first-order texture, energy, and entropy provided AUCs of 0.79–0.81 using a linear classifier. On two-fold CV, first-order texture yielded 73% accuracy versus 76%–77% with the second-order features. The size measures of the consolidative region, longest axial diameter and 3D volume, gave two-fold CV accuracies of 60% and 57%, and AUCs of 0.72 and 0.65, respectively. Conclusions: Texture measures of the GGO appearance following SABR demonstrated the ability to predict recurrence in individual patients within 5 months of SABR treatment. Appearance changes were also shown to be more accurately predictive of recurrence, as compared to size measures within the same time period. With further validation, these results could form the substrate for a clinically useful computer-aided diagnosis tool which could provide earlier salvage of patients with recurrence.« less

Classification of micro-CT images using 3D characterization of bone canal patterns in human osteogenesis imperfecta

NASA Astrophysics Data System (ADS)

Abidin, Anas Z.; Jameson, John; Molthen, Robert; Wismüller, Axel

2017-03-01

Few studies have analyzed the microstructural properties of bone in cases of Osteogenenis Imperfecta (OI), or `brittle bone disease'. Current approaches mainly focus on bone mineral density measurements as an indirect indicator of bone strength and quality. It has been shown that bone strength would depend not only on composition but also structural organization. This study aims to characterize 3D structure of the cortical bone in high-resolution micro CT images. A total of 40 bone fragments from 28 subjects (13 with OI and 15 healthy controls) were imaged using micro tomography using a synchrotron light source (SRµCT). Minkowski functionals - volume, surface, curvature, and Euler characteristics - describing the topological organization of the bone were computed from the images. The features were used in a machine learning task to classify between healthy and OI bone. The best classification performance (mean AUC - 0.96) was achieved with a combined 4-dimensional feature of all Minkowski functionals. Individually, the best feature performance was seen using curvature (mean AUC - 0.85), which characterizes the edges within a binary object. These results show that quantitative analysis of cortical bone microstructure, in a computer-aided diagnostics framework, can be used to distinguish between healthy and OI bone with high accuracy.

Diagnosis of Richter transformation in chronic lymphocytic leukemia: histology tips the scales.

PubMed

Federmann, Birgit; Mueller, Martin R; Steinhilber, Julia; Horger, Marius S; Fend, Falko

2018-06-12

Development of diffuse large B-cell lymphoma in chronic lymphocytic leukemia, so-called Richter transformation (RT), occurs in 2-5% of patients and is associated with poor outcome. The clinical features of RT are fairly non-specific and unable to discriminate transformation from other mimics. In case of clinically suspected RT, a CT/MRT is recommended, and FDG-PET/CT may help to select the site of biopsy. Radiological features suggestive of RT have been defined, but there are only limited data about their predictive value, and histological confirmation is still considered the gold standard for RT diagnosis. We retrospectively analyzed 34 patients with clinically suspected RT and available radiological and histological data. A histopathological diagnosis of RT with concordant clinical and radiological findings was obtained in 13 patients. In 18 patients, CT did not show features of transformation, concordant with lack of RT in the biopsy. Of interest, a distinct lymphoma other than DLBCL was identified in two of these cases. A false-positive radiological diagnosis of RT was rendered in two patients, including a case of Herpes simplex virus lymphadenitis. In conclusion, our findings confirm the central role of tissue biopsy in the diagnostic work up in case of clinically suspected RT.

Imaging and Clinicopathologic Features of Esophageal Gastrointestinal Stromal Tumors

PubMed Central

Winant, Abbey J.; Gollub, Marc J.; Shia, Jinru; Antonescu, Christina; Bains, Manjit S.; Levine, Marc S.

2016-01-01

OBJECTIVE The purpose of this article is to describe the imaging and clinicopathologic characteristics of esophageal gastrointestinal stromal tumors (GISTs) and to emphasize the features that differentiate esophageal GISTs from esophageal leiomyomas. MATERIALS AND METHODS A pathology database search identified all surgically resected or biopsied esophageal GISTs, esophageal leiomyomas, and esophageal leiomyosarcomas from 1994 to 2012. Esophageal GISTs were included only if imaging studies (including CT, fluoroscopic, or 18F-FDG PET/CT scans) and clinical data were available. RESULTS Nineteen esophageal mesenchymal tumors were identified, including eight esophageal GISTs (42%), 10 esophageal leiomyomas (53%), and one esophageal leiomyosarcoma (5%). Four patients (50%) with esophageal GIST had symptoms, including dysphagia in three (38%), cough in one (13%), and chest pain in one (13%). One esophageal GIST appeared on barium study as a smooth submucosal mass. All esophageal GISTs appeared on CT as well-marginated predominantly distal lesions, isoattenuating to muscle, that moderately enhanced after IV contrast agent administration. Compared with esophageal leiomyomas, esophageal GISTs tended to be more distal, larger, and more heterogeneous and showed greater IV enhancement on CT. All esophageal GISTs showed marked avidity (mean maximum standardized uptake value, 16) on PET scans. All esophageal GISTs were positive for c-KIT (a cell-surface transmembrane tyrosine kinase also known as CD117) and CD34. On histopathology, six esophageal GISTs (75%) were of the spindle pattern and two (25%) were of a mixed spindle and epithelioid pattern. Five esophageal GISTs had exon 11 mutations (with imatinib sensitivity). Clinical outcome correlated with treatment strategy (resection plus adjuvant therapy or resection alone) rather than risk stratification. CONCLUSION Esophageal GISTs are unusual but clinically important mesenchymal neoplasms. Although esophageal GISTs and esophageal leiomyomas had overlapping imaging features, esophageal GISTs tended to be more distal, larger, more heterogeneous, and more enhancing on CT and were markedly FDG avid on PET. Given their malignant potential, esophageal GISTs should be included in the differential diagnosis of intramural esophageal neoplasms. PMID:25055264

An automatic approach for 3D registration of CT scans

NASA Astrophysics Data System (ADS)

Hu, Yang; Saber, Eli; Dianat, Sohail; Vantaram, Sreenath Rao; Abhyankar, Vishwas

2012-03-01

CT (Computed tomography) is a widely employed imaging modality in the medical field. Normally, a volume of CT scans is prescribed by a doctor when a specific region of the body (typically neck to groin) is suspected of being abnormal. The doctors are required to make professional diagnoses based upon the obtained datasets. In this paper, we propose an automatic registration algorithm that helps healthcare personnel to automatically align corresponding scans from 'Study' to 'Atlas'. The proposed algorithm is capable of aligning both 'Atlas' and 'Study' into the same resolution through 3D interpolation. After retrieving the scanned slice volume in the 'Study' and the corresponding volume in the original 'Atlas' dataset, a 3D cross correlation method is used to identify and register various body parts.

Computed tomography of calcaneal fractures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heger, L.; Wulff, K.; Seddiqi, M.S.A.

1985-07-01

Computed tomography (CT) of 25 fractured calcanei was performed to investigate the potential of CT in evaluating the pattern and biomechanics of these fractures. The characteristic findings of typical fractures are presented, including the number and type of principal fragments, size and dislocation of the sustentacular fragment, and involvement of the anterior and posterior facets of the subtalar joint. In 17 cases, the calcaneus consisted of four or more fragments. Furthermore, in 17 cases the sustentacular fragment included all or part of the posterior facet joint. In 18 of the 25 cases, the sustentacular fragment was displaced. It is concludedmore » that well performed CT is an invaluable adjunct in understanding the fracture mechanism and in detecting pain-provoking impingement between the fibular malleolus and the tuberosity fragment.« less

SU-C-BRA-04: Automated Segmentation of Head-And-Neck CT Images for Radiotherapy Treatment Planning Via Multi-Atlas Machine Learning (MAML)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, X; Gao, H; Sharp, G

Purpose: Accurate image segmentation is a crucial step during image guided radiation therapy. This work proposes multi-atlas machine learning (MAML) algorithm for automated segmentation of head-and-neck CT images. Methods: As the first step, the algorithm utilizes normalized mutual information as similarity metric, affine registration combined with multiresolution B-Spline registration, and then fuses together using the label fusion strategy via Plastimatch. As the second step, the following feature selection strategy is proposed to extract five feature components from reference or atlas images: intensity (I), distance map (D), box (B), center of gravity (C) and stable point (S). The box feature Bmore » is novel. It describes a relative position from each point to minimum inscribed rectangle of ROI. The center-of-gravity feature C is the 3D Euclidean distance from a sample point to the ROI center of gravity, and then S is the distance of the sample point to the landmarks. Then, we adopt random forest (RF) in Scikit-learn, a Python module integrating a wide range of state-of-the-art machine learning algorithms as classifier. Different feature and atlas strategies are used for different ROIs for improved performance, such as multi-atlas strategy with reference box for brainstem, and single-atlas strategy with reference landmark for optic chiasm. Results: The algorithm was validated on a set of 33 CT images with manual contours using a leave-one-out cross-validation strategy. Dice similarity coefficients between manual contours and automated contours were calculated: the proposed MAML method had an improvement from 0.79 to 0.83 for brainstem and 0.11 to 0.52 for optic chiasm with respect to multi-atlas segmentation method (MA). Conclusion: A MAML method has been proposed for automated segmentation of head-and-neck CT images with improved performance. It provides the comparable result in brainstem and the improved result in optic chiasm compared with MA. Xuhua Ren and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).« less

Statistical distributions of ultra-low dose CT sinograms and their fundamental limits

NASA Astrophysics Data System (ADS)

Lee, Tzu-Cheng; Zhang, Ruoqiao; Alessio, Adam M.; Fu, Lin; De Man, Bruno; Kinahan, Paul E.

2017-03-01

Low dose CT imaging is typically constrained to be diagnostic. However, there are applications for even lowerdose CT imaging, including image registration across multi-frame CT images and attenuation correction for PET/CT imaging. We define this as the ultra-low-dose (ULD) CT regime where the exposure level is a factor of 10 lower than current low-dose CT technique levels. In the ULD regime it is possible to use statistically-principled image reconstruction methods that make full use of the raw data information. Since most statistical based iterative reconstruction methods are based on the assumption of that post-log noise distribution is close to Poisson or Gaussian, our goal is to understand the statistical distribution of ULD CT data with different non-positivity correction methods, and to understand when iterative reconstruction methods may be effective in producing images that are useful for image registration or attenuation correction in PET/CT imaging. We first used phantom measurement and calibrated simulation to reveal how the noise distribution deviate from normal assumption under the ULD CT flux environment. In summary, our results indicate that there are three general regimes: (1) Diagnostic CT, where post-log data are well modeled by normal distribution. (2) Lowdose CT, where normal distribution remains a reasonable approximation and statistically-principled (post-log) methods that assume a normal distribution have an advantage. (3) An ULD regime that is photon-starved and the quadratic approximation is no longer effective. For instance, a total integral density of 4.8 (ideal pi for 24 cm of water) for 120kVp, 0.5mAs of radiation source is the maximum pi value where a definitive maximum likelihood value could be found. This leads to fundamental limits in the estimation of ULD CT data when using a standard data processing stream

Using Helical CT to Predict Stone Fragility in Shock Wave Lithotripsy (SWL)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, James C. Jr.; Zarse, Chad A.; Jackson, Molly E.

2007-04-05

Great variability exists in the response of urinary stones to SWL, and this is true even for stones composed of the same mineral. Efforts have been made to predict stone fragility to shock waves using computed tomography (CT) patient images, but most work to date has focused on the use of stone CT number (i.e., Hounsfield units). This is an easy number to measure on a patient stone, but its value depends on a number of factors, including the relationship of the size of the stone to me resolution (i.e., the slicewidth) of the CT scan. Studies that have shownmore » a relationship between stone CT number and failure in SWL are reviewed, and all are shown to suffer from error due to stone size, which was not accounted for in the use of Hounsfield unit values. Preliminary data are then presented for a study of calcium oxalate monohydrate (COM) stones, in which stone structure-rather than simple CT number values-is shown to correlate with fragility to shock waves. COM stones that were observed to have structure by micro CT (e.g., voids, apatite regions, unusual shapes) broke to completion in about half the number of shock waves required for COM stones that were observed to be homogeneous in structure by CT. This result suggests another direction for the use of CT in predicting success of SWL: the use of CT to view stone structure, rather than simply measuring stone CT number. Viewing stone structure by CT requires the use of different viewing windows than those typically used for examining patient scans, but much research to date indicates that stone structure can be observed in the clinical setting. Future clinical studies will need to be done to verify the relationship between stone structure observed by CT and stone fragility in SWL.« less

Automatic detection of axillary lymphadenopathy on CT scans of untreated chronic lymphocytic leukemia patients

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Hua, Jeremy; Chellappa, Vivek; Petrick, Nicholas; Sahiner, Berkman; Farooqui, Mohammed; Marti, Gerald; Wiestner, Adrian; Summers, Ronald M.

2012-03-01

Patients with chronic lymphocytic leukemia (CLL) have an increased frequency of axillary lymphadenopathy. Pretreatment CT scans can be used to upstage patients at the time of presentation and post-treatment CT scans can reduce the number of complete responses. In the current clinical workflow, the detection and diagnosis of lymph nodes is usually performed manually by examining all slices of CT images, which can be time consuming and highly dependent on the observer's experience. A system for automatic lymph node detection and measurement is desired. We propose a computer aided detection (CAD) system for axillary lymph nodes on CT scans in CLL patients. The lung is first automatically segmented and the patient's body in lung region is extracted to set the search region for lymph nodes. Multi-scale Hessian based blob detection is then applied to detect potential lymph nodes within the search region. Next, the detected potential candidates are segmented by fast level set method. Finally, features are calculated from the segmented candidates and support vector machine (SVM) classification is utilized for false positive reduction. Two blobness features, Frangi's and Li's, are tested and their free-response receiver operating characteristic (FROC) curves are generated to assess system performance. We applied our detection system to 12 patients with 168 axillary lymph nodes measuring greater than 10 mm. All lymph nodes are manually labeled as ground truth. The system achieved sensitivities of 81% and 85% at 2 false positives per patient for Frangi's and Li's blobness, respectively.

Functional dissection of the Hox protein Abdominal-B in Drosophila cell culture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhai, Zongzhao; CellNetworks - Cluster of Excellence, Centre for Organismal Studies; Graduate School of Chinese Academy of Sciences, Beijing 100039

2011-11-04

Highlights: Black-Right-Pointing-Pointer ct340 CRM was identified to be the posterior spiracle enhancer of gene cut. Black-Right-Pointing-Pointer ct340 is under the direct transcriptional control of Hox protein Abd-B. Black-Right-Pointing-Pointer An efficient cloning system was developed to assay protein-DNA interaction. Black-Right-Pointing-Pointer New features of Abd-B dependent target gene regulation were detected. -- Abstract: Hox transcription factors regulate the morphogenesis along the anterior-posterior (A/P) body axis through the interaction with small cis-regulatory modules (CRMs) of their target gene, however so far very few Hox CRMs are known and have been analyzed in detail. In this study we have identified a new Hox CRM,more » ct340, which guides the expression of the cell type specification gene cut (ct) in the posterior spiracle under the direct control of the Hox protein Abdominal-B (Abd-B). Using the ct340 enhancer activity as readout, an efficient cloning system to generate VP16 activation domain fusion protein was developed to unambiguously test protein-DNA interaction in Drosophila cell culture. By functionally dissecting the Abd-B protein, new features of Abd-B dependent target gene regulation were detected. Due to its easy adaptability, this system can be generally used to map functional domains within sequence-specific transcriptional factors in Drosophila cell culture, and thus provide preliminary knowledge of the protein functional domain structure for further in vivo analysis.« less

Symmetry-breaking charge transfer in a zinc chlorodipyrrin acceptor for high open circuit voltage organic photovoltaics.

PubMed

Bartynski, Andrew N; Gruber, Mark; Das, Saptaparna; Rangan, Sylvie; Mollinger, Sonya; Trinh, Cong; Bradforth, Stephen E; Vandewal, Koen; Salleo, Alberto; Bartynski, Robert A; Bruetting, Wolfgang; Thompson, Mark E

2015-04-29

Low open-circuit voltages significantly limit the power conversion efficiency of organic photovoltaic devices. Typical strategies to enhance the open-circuit voltage involve tuning the HOMO and LUMO positions of the donor (D) and acceptor (A), respectively, to increase the interfacial energy gap or to tailor the donor or acceptor structure at the D/A interface. Here, we present an alternative approach to improve the open-circuit voltage through the use of a zinc chlorodipyrrin, ZCl [bis(dodecachloro-5-mesityldipyrrinato)zinc], as an acceptor, which undergoes symmetry-breaking charge transfer (CT) at the donor/acceptor interface. DBP/ZCl cells exhibit open-circuit voltages of 1.33 V compared to 0.88 V for analogous tetraphenyldibenzoperyflanthrene (DBP)/C60-based devices. Charge transfer state energies measured by Fourier-transform photocurrent spectroscopy and electroluminescence show that C60 forms a CT state of 1.45 ± 0.05 eV in a DBP/C60-based organic photovoltaic device, while ZCl as acceptor gives a CT state energy of 1.70 ± 0.05 eV in the corresponding device structure. In the ZCl device this results in an energetic loss between E(CT) and qV(OC) of 0.37 eV, substantially less than the 0.6 eV typically observed for organic systems and equal to the recombination losses seen in high-efficiency Si and GaAs devices. The substantial increase in open-circuit voltage and reduction in recombination losses for devices utilizing ZCl demonstrate the great promise of symmetry-breaking charge transfer in organic photovoltaic devices.

Bladder cancer treatment response assessment with radiomic, clinical, and radiologist semantic features

NASA Astrophysics Data System (ADS)

Gordon, Marshall N.; Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Cohan, Richard H.; Caoili, Elaine M.; Paramagul, Chintana; Alva, Ajjai; Weizer, Alon Z.

2018-02-01

We are developing a decision support system for assisting clinicians in assessment of response to neoadjuvant chemotherapy for bladder cancer. Accurate treatment response assessment is crucial for identifying responders and improving quality of life for non-responders. An objective machine learning decision support system may help reduce variability and inaccuracy in treatment response assessment. We developed a predictive model to assess the likelihood that a patient will respond based on image and clinical features. With IRB approval, we retrospectively collected a data set of pre- and post- treatment CT scans along with clinical information from surgical pathology from 98 patients. A linear discriminant analysis (LDA) classifier was used to predict the likelihood that a patient would respond to treatment based on radiomic features extracted from CT urography (CTU), a radiologist's semantic feature, and a clinical feature extracted from surgical and pathology reports. The classification accuracy was evaluated using the area under the ROC curve (AUC) with a leave-one-case-out cross validation. The classification accuracy was compared for the systems based on radiomic features, clinical feature, and radiologist's semantic feature. For the system based on only radiomic features the AUC was 0.75. With the addition of clinical information from examination under anesthesia (EUA) the AUC was improved to 0.78. Our study demonstrated the potential of designing a decision support system to assist in treatment response assessment. The combination of clinical features, radiologist semantic features and CTU radiomic features improved the performance of the classifier and the accuracy of treatment response assessment.

Differentiation of deep venous thrombosis from femoral vein mixing artifact on routine abdominopelvic CT.

PubMed

Doshi, Ankur M; Hoffman, David; Kierans, Andrea S; Ream, Justin M; Rosenkrantz, Andrew B

2015-10-01

The objective of this study is to assess the performance of qualitative and quantitative imaging features for the differentiation of deep venous thrombosis (DVT) from mixing artifact on routine portal venous phase abdominopelvic CT. This retrospective study included 40 adult patients with a femoral vein filling defect on portal venous phase CT and a Duplex ultrasound (n = 36) or catheter venogram (n = 4) to confirm presence or absence of DVT. Two radiologists (R1, R2) assessed the femoral veins for various qualitative and quantitative features. 60% of patients were confirmed to have DVT and 40% had mixing artifact. Features with significantly greater frequency in DVT than mixing artifact (all p ≤ 0.006) were central location (R1 90% vs. 28%; R2 96% vs. 31%), sharp margin (R1 83% vs. 28%; R2 96% vs. 31%), venous expansion (R1 48% vs. 6%, R2 56% vs. 6%), and venous wall enhancement (R1 62% vs. 0%; R2 48% vs. 0%). DVT exhibited significantly lower mean attenuation than mixing artifact (R1 42.1 ± 20.2 vs. 57.1 ± 23.6 HU; R2 43.6 ± 19.4 vs. 58.8 ± 23.4 HU, p ≤ 0.031) and a significantly larger difference in vein diameter compared to the contralateral vein (R1 0.4 ± 0.4 vs. 0.1 ± 0.2 cm; R2 0.3 ± 0.4 vs. 0.0 ± 0.1 cm, p ≤ 0.026). At multivariable analysis, central location and sharp margin were significant independent predictors of DVT for both readers (p ≤ 0.013). Awareness of these qualitative and quantitative imaging features may improve radiologists' confidence for differentiating femoral vein DVT and mixing artifact on routine portal venous phase CT. However, given overlap with mixing artifact, larger studies remain warranted.

Quantitative imaging features of pretreatment CT predict volumetric response to chemotherapy in patients with colorectal liver metastases.

PubMed

Creasy, John M; Midya, Abhishek; Chakraborty, Jayasree; Adams, Lauryn B; Gomes, Camilla; Gonen, Mithat; Seastedt, Kenneth P; Sutton, Elizabeth J; Cercek, Andrea; Kemeny, Nancy E; Shia, Jinru; Balachandran, Vinod P; Kingham, T Peter; Allen, Peter J; DeMatteo, Ronald P; Jarnagin, William R; D'Angelica, Michael I; Do, Richard K G; Simpson, Amber L

2018-06-19

This study investigates whether quantitative image analysis of pretreatment CT scans can predict volumetric response to chemotherapy for patients with colorectal liver metastases (CRLM). Patients treated with chemotherapy for CRLM (hepatic artery infusion (HAI) combined with systemic or systemic alone) were included in the study. Patients were imaged at baseline and approximately 8 weeks after treatment. Response was measured as the percentage change in tumour volume from baseline. Quantitative imaging features were derived from the index hepatic tumour on pretreatment CT, and features statistically significant on univariate analysis were included in a linear regression model to predict volumetric response. The regression model was constructed from 70% of data, while 30% were reserved for testing. Test data were input into the trained model. Model performance was evaluated with mean absolute prediction error (MAPE) and R 2 . Clinicopatholologic factors were assessed for correlation with response. 157 patients were included, split into training (n = 110) and validation (n = 47) sets. MAPE from the multivariate linear regression model was 16.5% (R 2 = 0.774) and 21.5% in the training and validation sets, respectively. Stratified by HAI utilisation, MAPE in the validation set was 19.6% for HAI and 25.1% for systemic chemotherapy alone. Clinical factors associated with differences in median tumour response were treatment strategy, systemic chemotherapy regimen, age and KRAS mutation status (p < 0.05). Quantitative imaging features extracted from pretreatment CT are promising predictors of volumetric response to chemotherapy in patients with CRLM. Pretreatment predictors of response have the potential to better select patients for specific therapies. • Colorectal liver metastases (CRLM) are downsized with chemotherapy but predicting the patients that will respond to chemotherapy is currently not possible. • Heterogeneity and enhancement patterns of CRLM can be measured with quantitative imaging. • Prediction model constructed that predicts volumetric response with 20% error suggesting that quantitative imaging holds promise to better select patients for specific treatments.

Metabolic Bone Disease in the Context of Metastatic Neuroendocrine Tumor: Differentiation from Skeletal Metastasis, the Molecular PET-CT Imaging Features, and Exploring the Possible Etiopathologies Including Parathyroid Adenoma (MEN1) and Paraneoplastic Humoral Hypercalcemia of Malignancy Due to PTHrP Hypersecretion.

PubMed

Ranade, Rohit; Basu, Sandip

2017-01-01

Three cases of metabolic bone disease in the setting of metastatic neuroendocrine tumor (NET) are illustrated with associated etiopathologies.  One of these cases harbored mixed lesions in the form of vertebral metastasis (biopsy proven) while the other skeletal lesions were caused due to metabolic bone disease related to multiple parathyroid adenomas. While the metastatic lesion was positive on 68Ga-DOTATATE positron emission tomography-computed tomography (PET-CT), the lesions of metabolic bone disease were negative and the 18F-fluoride PET-CT demonstrated the features of metabolic bone scan. Similar picture of metabolic bone disease [18-sodium fluoride (18NaF)/68Ga-DOTATATE mismatch] was documented in the other two patients, while fluorodeoxyglucose (FDG)-PET-CT was variably positive, primarily showing tracer uptake in the metabolic skeletal lesions of the patient with hypersecretion of parathyroid hormone-related protein (PTHrP) by the underlying tumor. Discordance between 18NaF PET-CT and 68Ga-DOTATATE PET-CT serves as a good marker for identification of metabolic bone disease and diagnosing such a clinical entity. In a patient of NET with metabolic bone disease and hypercalcemia, thus, two causes need to be considered: (i) Coexisting parathyroid adenoma in multiple endocrine neoplasia type I (MEN-I) syndrome and (ii) humoral hypercalcemia of malignancy (HHM) related to hypersecretion of PTHrP by the tumor. The correct diagnosis of metabolic bone disease in metastatic NET can alter the management substantially. Interestingly, peptide receptor radionuclide therapy (PRRT) can emerge as a very promising treatment modality in patients of metabolic bone disease caused by HHM in the setting of NET.

Morphometric anatomical and CT study of the human adult sacroiliac region.

PubMed

Postacchini, Roberto; Trasimeni, Guido; Ripani, Francesca; Sessa, Pasquale; Perotti, Stefano; Postacchini, Franco

2017-01-01

To identify and describe the morphometry and CT features of the articular and extra-articular portions of the sacroiliac region. The resulting knowledge might help to avoid complications in sacroiliac joint (SIJ) fusion. We analyzed 102 dry hemi-sacra, 80 ilia, and 10 intact pelves and assessed the pelvic computerized tomography (CT) scans of 90 patients, who underwent the examination for conditions not involving the pelvis. We assessed both the posterior aspect of sacrum with regard to the depressions located externally to the lateral sacral crest at the level of the proximal three sacral vertebrae and the posteroinferior aspect of ilium. Coronal and axial CT scans of the SIJ of patients were obtained and the joint space was measured. On each side, the sacrum exhibits three bone depressions, not described in anatomic textbooks or studies, facing the medial aspect of the posteroinferior ilium, not yet described in detail. Both structures are extra-articular portions situated posteriorly to the SIJ. Coronal CT scans of patients showing the first three sacral foramens and the interval between sacrum and ilium as a continuous space display only the S1 and S3 portions of SIJ, the intermediate portion being extra-articular. The S2 portion is visible on the most anterior coronal scan. Axial scans show articular and extra-articular portions and features improperly described as anatomic variations. Extra-articular portions of the sacroiliac region, not yet described exhaustively, have often been confused with SIJ. Coronal CT scans through the middle part of sacrum, the most used to evaluate degenerative and inflammatory conditions of SIJ, show articular and extra-articular portions of the region.

Measurement of small lesions near metallic implants with mega-voltage cone beam CT

NASA Astrophysics Data System (ADS)

Grigorescu, Violeta; Prevrhal, Sven; Pouliot, Jean

2008-03-01

Metallic objects severely limit diagnostic CT imaging because of their high X-ray attenuation in the diagnostic energy range. In contrast, radiation therapy linear accelerators now offer CT imaging with X-ray energies in the megavolt range, where the attenuation coefficients of metals are significantly lower. We hypothesized that Mega electron-Voltage Cone-Beam CT (MVCT) implemented on a radiation therapy linear accelerator can detect and quantify small features in the vicinity of metallic implants with accuracy comparable to clinical Kilo electron-Voltage CT (KVCT) for imaging. Our test application was detection of osteolytic lesions formed near the metallic stem of a hip prosthesis, a condition of severe concern in hip replacement surgery. Both MVCT and KVCT were used to image a phantom containing simulated osteolytic bone lesions centered around a Chrome-Cobalt hip prosthesis stem with hemispherical lesions with sizes and densities ranging from 0.5 to 4 mm radius and 0 to 500 mg•cm -3, respectively. Images for both modalities were visually graded to establish lower limits of lesion visibility as a function of their size. Lesion volumes and mean density were determined and compared to reference values. Volume determination errors were reduced from 34%, on KVCT, to 20% for all lesions on MVCT, and density determination errors were reduced from 71% on KVCT to 10% on MVCT. Localization and quantification of lesions was improved with MVCT imaging. MVCT offers a viable alternative to clinical CT in cases where accurate 3D imaging of small features near metallic hardware is critical. These results need to be extended to other metallic objects of different composition and geometry.