An intelligent architecture based on Field Programmable Gate Arrays designed to detect moving objects by using Principal Component Analysis.

PubMed

Bravo, Ignacio; Mazo, Manuel; Lázaro, José L; Gardel, Alfredo; Jiménez, Pedro; Pizarro, Daniel

2010-01-01

This paper presents a complete implementation of the Principal Component Analysis (PCA) algorithm in Field Programmable Gate Array (FPGA) devices applied to high rate background segmentation of images. The classical sequential execution of different parts of the PCA algorithm has been parallelized. This parallelization has led to the specific development and implementation in hardware of the different stages of PCA, such as computation of the correlation matrix, matrix diagonalization using the Jacobi method and subspace projections of images. On the application side, the paper presents a motion detection algorithm, also entirely implemented on the FPGA, and based on the developed PCA core. This consists of dynamically thresholding the differences between the input image and the one obtained by expressing the input image using the PCA linear subspace previously obtained as a background model. The proposal achieves a high ratio of processed images (up to 120 frames per second) and high quality segmentation results, with a completely embedded and reliable hardware architecture based on commercial CMOS sensors and FPGA devices.

Diagnostic Pathway with Multiparametric Magnetic Resonance Imaging Versus Standard Pathway: Results from a Randomized Prospective Study in Biopsy-naïve Patients with Suspected Prostate Cancer.

PubMed

Porpiglia, Francesco; Manfredi, Matteo; Mele, Fabrizio; Cossu, Marco; Bollito, Enrico; Veltri, Andrea; Cirillo, Stefano; Regge, Daniele; Faletti, Riccardo; Passera, Roberto; Fiori, Cristian; De Luca, Stefano

2017-08-01

An approach based on multiparametric magnetic resonance imaging (mpMRI) might increase the detection rate (DR) of clinically significant prostate cancer (csPCa). To compare an mpMRI-based pathway with the standard approach for the detection of prostate cancer (PCa) and csPCa. Between November 2014 and April 2016, 212 biopsy-naïve patients with suspected PCa (prostate specific antigen level ≤15 ng/ml and negative digital rectal examination results) were included in this randomized clinical trial. Patients were randomized into a prebiopsy mpMRI group (arm A, n=107) or a standard biopsy (SB) group (arm B, n=105). In arm A, patients with mpMRI evidence of lesions suspected for PCa underwent mpMRI/transrectal ultrasound fusion software-guided targeted biopsy (TB) (n=81). The remaining patients in arm A (n=26) with negative mpMRI results and patients in arm B underwent 12-core SB. The primary end point was comparison of the DR of PCa and csPCa between the two arms of the study; the secondary end point was comparison of the DR between TB and SB. The overall DRs were higher in arm A versus arm B for PCa (50.5% vs 29.5%, respectively; p=0.002) and csPCa (43.9% vs 18.1%, respectively; p<0.001). Concerning the biopsy approach, that is, TB in arm A, SB in arm A, and SB in arm B, the overall DRs were significantly different for PCa (60.5% vs 19.2% vs 29.5%, respectively; p<0.001) and for csPCa (56.8% vs 3.8% vs 18.1%, respectively; p<0.001). The reproducibility of the study could have been affected by the single-center nature. A diagnostic pathway based on mpMRI had a higher DR than the standard pathway in both PCa and csPCa. In this randomized trial, a pathway for the diagnosis of prostate cancer based on multiparametric magnetic resonance imaging (mpMRI) was compared with the standard pathway based on random biopsy. The mpMRI-based pathway had better performance than the standard pathway. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Co-trained convolutional neural networks for automated detection of prostate cancer in multi-parametric MRI.

PubMed

Yang, Xin; Liu, Chaoyue; Wang, Zhiwei; Yang, Jun; Min, Hung Le; Wang, Liang; Cheng, Kwang-Ting Tim

2017-12-01

Multi-parameter magnetic resonance imaging (mp-MRI) is increasingly popular for prostate cancer (PCa) detection and diagnosis. However, interpreting mp-MRI data which typically contains multiple unregistered 3D sequences, e.g. apparent diffusion coefficient (ADC) and T2-weighted (T2w) images, is time-consuming and demands special expertise, limiting its usage for large-scale PCa screening. Therefore, solutions to computer-aided detection of PCa in mp-MRI images are highly desirable. Most recent advances in automated methods for PCa detection employ a handcrafted feature based two-stage classification flow, i.e. voxel-level classification followed by a region-level classification. This work presents an automated PCa detection system which can concurrently identify the presence of PCa in an image and localize lesions based on deep convolutional neural network (CNN) features and a single-stage SVM classifier. Specifically, the developed co-trained CNNs consist of two parallel convolutional networks for ADC and T2w images respectively. Each network is trained using images of a single modality in a weakly-supervised manner by providing a set of prostate images with image-level labels indicating only the presence of PCa without priors of lesions' locations. Discriminative visual patterns of lesions can be learned effectively from clutters of prostate and surrounding tissues. A cancer response map with each pixel indicating the likelihood to be cancerous is explicitly generated at the last convolutional layer of the network for each modality. A new back-propagated error E is defined to enforce both optimized classification results and consistent cancer response maps for different modalities, which help capture highly representative PCa-relevant features during the CNN feature learning process. The CNN features of each modality are concatenated and fed into a SVM classifier. For images which are classified to contain cancers, non-maximum suppression and adaptive thresholding are applied to the corresponding cancer response maps for PCa foci localization. Evaluation based on 160 patient data with 12-core systematic TRUS-guided prostate biopsy as the reference standard demonstrates that our system achieves a sensitivity of 0.46, 0.92 and 0.97 at 0.1, 1 and 10 false positives per normal/benign patient which is significantly superior to two state-of-the-art CNN-based methods (Oquab et al., 2015; Zhou et al., 2015) and 6-core systematic prostate biopsies. Copyright © 2017 Elsevier B.V. All rights reserved.

European Randomized Study of Screening for Prostate Cancer Risk Calculator: External Validation, Variability, and Clinical Significance.

PubMed

Gómez-Gómez, Enrique; Carrasco-Valiente, Julia; Blanca-Pedregosa, Ana; Barco-Sánchez, Beatriz; Fernandez-Rueda, Jose Luis; Molina-Abril, Helena; Valero-Rosa, Jose; Font-Ugalde, Pilar; Requena-Tapia, Maria José

2017-04-01

To externally validate the European Randomized Study of Screening for Prostate Cancer (ERSPC) risk calculator (RC) and to evaluate its variability between 2 consecutive prostate-specific antigen (PSA) values. We prospectively catalogued 1021 consecutive patients before prostate biopsy for suspicion of prostate cancer (PCa). The risk of PCa and significant PCa (Gleason score ≥7) from 749 patients was calculated according to ERSPC-RC (digital rectal examination-based version 3 of 4) for 2 consecutive PSA tests per patient. The calculators' predictions were analyzed using calibration plots and the area under the receiver operating characteristic curve (area under the curve). Cohen kappa coefficient was used to compare the ability and variability. Of 749 patients, PCa was detected in 251 (33.5%) and significant PCa was detected in 133 (17.8%). Calibration plots showed an acceptable parallelism and similar discrimination ability for both PSA levels with an area under the curve of 0.69 for PCa and 0.74 for significant PCa. The ERSPC showed 226 (30.2%) unnecessary biopsies with the loss of 10 significant PCa. The variability of the RC was 16% for PCa and 20% for significant PCa, and a higher variability was associated with a reduced risk of significant PCa. We can conclude that the performance of the ERSPC-RC in the present cohort shows a high similitude between the 2 PSA levels; however, the RC variability value is associated with a decreased risk of significant PCa. The use of the ERSPC in our cohort detects a high number of unnecessary biopsies. Thus, the incorporation of ERSPC-RC could help the clinical decision to carry out a prostate biopsy. Copyright © 2016 Elsevier Inc. All rights reserved.

External validation of urinary PCA3-based nomograms to individually predict prostate biopsy outcome.

PubMed

Auprich, Marco; Haese, Alexander; Walz, Jochen; Pummer, Karl; de la Taille, Alexandre; Graefen, Markus; de Reijke, Theo; Fisch, Margit; Kil, Paul; Gontero, Paolo; Irani, Jacques; Chun, Felix K-H

2010-11-01

Prior to safely adopting risk stratification tools, their performance must be tested in an external patient cohort. To assess accuracy and generalizability of previously reported, internally validated, prebiopsy prostate cancer antigen 3 (PCA3) gene-based nomograms when applied to a large, external, European cohort of men at risk of prostate cancer (PCa). Biopsy data, including urinary PCA3 score, were available for 621 men at risk of PCa who were participating in a European multi-institutional study. All patients underwent a ≥10-core prostate biopsy. Biopsy indication was based on suspicious digital rectal examination, persistently elevated prostate-specific antigen level (2.5-10 ng/ml) and/or suspicious histology (atypical small acinar proliferation of the prostate, >/= two cores affected by high-grade prostatic intraepithelial neoplasia in first set of biopsies). PCA3 scores were assessed using the Progensa assay (Gen-Probe Inc, San Diego, CA, USA). According to the previously reported nomograms, different PCA3 score codings were used. The probability of a positive biopsy was calculated using previously published logistic regression coefficients. Predicted outcomes were compared to the actual biopsy results. Accuracy was calculated using the area under the curve as a measure of discrimination; calibration was explored graphically. Biopsy-confirmed PCa was detected in 255 (41.1%) men. Median PCA3 score of biopsy-negative versus biopsy-positive men was 20 versus 48 in the total cohort, 17 versus 47 at initial biopsy, and 37 versus 53 at repeat biopsy (all p≤0.002). External validation of all four previously reported PCA3-based nomograms demonstrated equally high accuracy (0.73-0.75) and excellent calibration. The main limitations of the study reside in its early detection setting, referral scenario, and participation of only tertiary-care centers. In accordance with the original publication, previously developed PCA3-based nomograms achieved high accuracy and sufficient calibration. These novel nomograms represent robust tools and are thus generalizable to European men at risk of harboring PCa. Consequently, in presence of a PCA3 score, these nomograms may be safely used to assist clinicians when prostate biopsy is contemplated. Copyright © 2010 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection

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

Chen, Pin-Yu; Choudhury, Sutanay; Hero, Alfred

Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles ofmore » graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.« less

Evaluation of Vitronectin Expression in Prostate Cancer and the Clinical Significance of the Association of Vitronectin Expression with Prostate Specific Antigen in Detecting Prostate Cancer.

PubMed

Niu, Yue; Zhang, Ling; Bi, Xing; Yuan, Shuai; Chen, Peng

2016-03-05

To detect the expression of vitronectin (VTN) in the tissues and blood serum of prostate cancer (PCa) patients, and evaluate its clinical significance and to evaluate the significance of the combined assay of VTN and prostate specific antigens (PSA) in PCa diagnosis. To detect the expression of VTN as a potential marker for PCa diagnosis and prognosis, immunohistochemistry was performed on the tissues of 32 patients with metastatic PCa (PCaM), 34 patients with PCa without metastasis (PCa), and 41 patients with benign prostatic hyperplasia (BPH). The sera were then subjected to Western blot analysis. All cases were subsequently examined to determine the concentrations of PSA and VTN in the sera. The collected data were collated and analyzed. The positive expression rates of VTN in the tissues of the BPH and PCa groups (including PCa and PCaM groups) were 75.61% and 45.45%, respectively (P = .005). VTN was more highly expressed in the sera of the BPH patients (0.83 ± 0.07) than in the sera of the PCa patients (0.65 ± 0.06) (P < .05). It was also more highly expressed in the sera of the PCa patients than in the sera of the PCaM patients (0.35 ± 0.08) (P < .05). In the diagnosis of BPH and PCa, the Youden indexes of PSA detection, VTN detection, and combined detection were 0.2620, 0.3468, and 0.5635; the kappa values were 0.338, 0.304, and 0.448, respectively, and the areas under the receiver operating characteristic curve were 0.625, 0.673, and 0.703 (P < .05), respectively. VTN levels in sera may be used as a potential marker of PCa for the diagnosis and assessment of disease progression and metastasis. The combined detection of VTN and PSA in sera can be clinically applied in PCa diagnosis. .

Serum markers for prostate cancer: a rational approach to the literature.

PubMed

Steuber, Thomas; O'Brien, Matthew Frank; Lilja, Hans

2008-07-01

Due to its universal applicability for early detection and prediction of cancer stage and disease recurrence, widespread implementation of serum-based prostate-specific antigen (PSA) measurements has a significant influence on current treatment strategies for men with prostate cancer (PCa). However, over-detection and the resultant over-treatment of indolent cancers have been strongly implicated to occur. Using current recommended guidelines, the PSA test suffers from both limited sensitivity and specificity to enable efficacious population-based cancer detection. Therefore, novel biomarkers are much needed to complement PSA by enhancing its diagnostic and prognostic performance. The present literature on serum markers for PCa was reviewed. PSA derivatives, molecular PSA isoforms, and novel molecular targets in blood were summarized and weighted against their potential to improve decision-making of men with PCa. Current evidence suggests that no single analyte is likely to achieve the desired level of diagnostic and prognostic accuracy for PCa. However, the combination of biomarkers with clinical and demographic data, for example, using established standard nomograms, has produced progress toward the goal of both optimal screening and risk assessment. Furthermore, potential candidate molecular markers for PCa can be derived from high-throughput technologies. Current studies demonstrate that understanding dynamic PSA changes over time may offer diagnostic and prognostic information. Bridging the gap between basic science and clinical practice represents the main goal in the near future to enable physicians to tailor risk-adjusted screening and treatment strategies for current patients with PCa.

Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction.

PubMed

Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

2007-11-01

Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

Automatically detect and track infrared small targets with kernel Fukunaga-Koontz transform and Kalman prediction

NASA Astrophysics Data System (ADS)

Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan

2007-11-01

Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.

Clinical performance of serum [-2]proPSA derivatives, %p2PSA and PHI, in the detection and management of prostate cancer.

PubMed

Huang, Ya-Qiang; Sun, Tong; Zhong, Wei-De; Wu, Chin-Lee

2014-01-01

Prostate-specific antigen (PSA) has been widely used as a serum marker for prostate cancer (PCa) screening or progression monitoring, which dramatically increased rate of early detection while significantly reduced PCa-specific mortality. However, a number of limitations of PSA have been noticed. Low specificity of PSA may lead to overtreatment in men who presenting with a total PSA (tPSA) level of < 10 ng/mL. As a type of free PSA (fPSA), [-2]proPSA is differentially expressed in peripheral zone of prostate gland and found to be elevated in serum of men with PCa. Two p2PSA-based derivatives, prostate health index (PHI) and %p2PSA, which were defined as [(p2PSA/fPSA) × √ tPSA] and [(p2PSA/fPSA) × 100] respectively, have been suggested to be increased in PCa and can better distinguish PCa from benign prostatic diseases than tPSA or fPSA. We performed a systematic review of the available scientific evidences to evaluate the potentials of %p2PSA and PHI in clinical application. Mounting evidences suggested that both %p2PSA and PHI possess higher area under the ROC curve (AUC) and better specificity at a high sensitivity for PCa detection when compare with tPSA and %fPSA. It indicated that measurements of %p2PSA and PHI significantly improved the accuracy of PCa detection and diminished unnecessary biopsies. Furthermore, elevations of %p2PSA and PHI are related to more aggressive diseases. %p2PSA and PHI might be helpful in reducing overtreatment on indolent cases or assessing the progression of PCa in men who undergo active surveillance. Further studies are needed before being applied in routine clinical practice.

MiR-145 detection in urinary extracellular vesicles increase diagnostic efficiency of prostate cancer based on hydrostatic filtration dialysis method.

PubMed

Xu, Yong; Qin, Sihua; An, Taixue; Tang, Yueting; Huang, Yiyao; Zheng, Lei

2017-07-01

Extracellular vesicles (EVs) can be detected in body fluids and may serve as disease biomarkers. Increasing evidence suggests that circulating miRNAs in serum and urine may be potential non-invasive biomarkers for prostate cancer (PCa). In the present study, we aimed to investigate whether hydrostatic filtration dialysis (HFD) is suitable for urinary EVs (UEVs) isolation and whether such reported PCa-related miRNAs can be detected in UEVs as PCa biomarkers. To analyze EVs miRNAs, we searched for an easy and economic method to enrich EVs from urine samples. We compared the efficiency of HFD method and conventional ultracentrifugation (UC) in isolating UEVs. Subsequently, UEVs were isolated from patients with PCa, patients with benign prostate hyperplasia (BPH) and healthy individuals. Differential expression of four PCa-related miRNAs (miR-572, miR-1290, miR-141, and miR-145) were measured in UEVs and paired serum EVs using SYBR Green-based quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The overall performance of HFD was similar to UC. In miRNA yield, both HFD and UC can meet the needs of further analysis. The level of miR-145 in UEVs was significantly increased in patients with PCa compared with the patients with BPH (P = 0.018). In addition, significant increase was observed in miR-145 levels when patients with Gleason score ≥8 tumors compared with Gleason score ≤7 (P = 0.020). Receiver-operating characteristic curve (ROC) revealed that miR-145 in UEVs combined with serum PSA could differentiate PCa from BPH better than PSA alone (AUC 0.863 and AUC 0.805, respectively). In serum EVs, four miRNAs were significantly higher in patients with PCa than with BPH. HFD is appropriate for UEVs isolation and miRNA analysis when compared with conventional UC. miR-145 in UEVs is upregulated from PCa patients compared BPH patients and healthy controls. We suggest the potential use of UEVs miR-145 as a biomarker of PCa. © 2017 Wiley Periodicals, Inc.

Low-rank plus sparse decomposition for exoplanet detection in direct-imaging ADI sequences. The LLSG algorithm

NASA Astrophysics Data System (ADS)

Gomez Gonzalez, C. A.; Absil, O.; Absil, P.-A.; Van Droogenbroeck, M.; Mawet, D.; Surdej, J.

2016-05-01

Context. Data processing constitutes a critical component of high-contrast exoplanet imaging. Its role is almost as important as the choice of a coronagraph or a wavefront control system, and it is intertwined with the chosen observing strategy. Among the data processing techniques for angular differential imaging (ADI), the most recent is the family of principal component analysis (PCA) based algorithms. It is a widely used statistical tool developed during the first half of the past century. PCA serves, in this case, as a subspace projection technique for constructing a reference point spread function (PSF) that can be subtracted from the science data for boosting the detectability of potential companions present in the data. Unfortunately, when building this reference PSF from the science data itself, PCA comes with certain limitations such as the sensitivity of the lower dimensional orthogonal subspace to non-Gaussian noise. Aims: Inspired by recent advances in machine learning algorithms such as robust PCA, we aim to propose a localized subspace projection technique that surpasses current PCA-based post-processing algorithms in terms of the detectability of companions at near real-time speed, a quality that will be useful for future direct imaging surveys. Methods: We used randomized low-rank approximation methods recently proposed in the machine learning literature, coupled with entry-wise thresholding to decompose an ADI image sequence locally into low-rank, sparse, and Gaussian noise components (LLSG). This local three-term decomposition separates the starlight and the associated speckle noise from the planetary signal, which mostly remains in the sparse term. We tested the performance of our new algorithm on a long ADI sequence obtained on β Pictoris with VLT/NACO. Results: Compared to a standard PCA approach, LLSG decomposition reaches a higher signal-to-noise ratio and has an overall better performance in the receiver operating characteristic space. This three-term decomposition brings a detectability boost compared to the full-frame standard PCA approach, especially in the small inner working angle region where complex speckle noise prevents PCA from discerning true companions from noise.

Epileptic seizure detection in EEG signal using machine learning techniques.

PubMed

Jaiswal, Abeg Kumar; Banka, Haider

2018-03-01

Epilepsy is a well-known nervous system disorder characterized by seizures. Electroencephalograms (EEGs), which capture brain neural activity, can detect epilepsy. Traditional methods for analyzing an EEG signal for epileptic seizure detection are time-consuming. Recently, several automated seizure detection frameworks using machine learning technique have been proposed to replace these traditional methods. The two basic steps involved in machine learning are feature extraction and classification. Feature extraction reduces the input pattern space by keeping informative features and the classifier assigns the appropriate class label. In this paper, we propose two effective approaches involving subpattern based PCA (SpPCA) and cross-subpattern correlation-based PCA (SubXPCA) with Support Vector Machine (SVM) for automated seizure detection in EEG signals. Feature extraction was performed using SpPCA and SubXPCA. Both techniques explore the subpattern correlation of EEG signals, which helps in decision-making process. SVM is used for classification of seizure and non-seizure EEG signals. The SVM was trained with radial basis kernel. All the experiments have been carried out on the benchmark epilepsy EEG dataset. The entire dataset consists of 500 EEG signals recorded under different scenarios. Seven different experimental cases for classification have been conducted. The classification accuracy was evaluated using tenfold cross validation. The classification results of the proposed approaches have been compared with the results of some of existing techniques proposed in the literature to establish the claim.

External validation of a PCA-3-based nomogram for predicting prostate cancer and high-grade cancer on initial prostate biopsy.

PubMed

Greene, Daniel J; Elshafei, Ahmed; Nyame, Yaw A; Kara, Onder; Malkoc, Ercan; Gao, Tianming; Jones, J Stephen

2016-08-01

The aim of this study was to externally validate a previously developed PCA3-based nomogram for the prediction of prostate cancer (PCa) and high-grade (intermediate and/or high-grade) prostate cancer (HGPCa) at the time of initial prostate biopsy. A retrospective review was performed on a cohort of 336 men from a large urban academic medical center. All men had serum PSA <20 ng/ml and underwent initial transrectal ultrasound-guided prostate biopsy with at least 10 cores sampling for suspicious exam and/or elevated PSA. Covariates were collected for the nomogram and included age, ethnicity, family history (FH) of PCa, PSA at diagnosis, PCA3, total prostate volume (TPV), and abnormal finding on digital rectal exam (DRE). These variables were used to test the accuracy (concordance index) and calibration of a previously published PCA3 nomogram. Biopsy confirms PCa and HGPCa in 51.0% and 30.4% of validation patients, respectively. This differed from the original cohort in that it had significantly more PCa and HGPCA (51% vs. 44%, P = 0.019; and 30.4% vs. 19.1%, P < 0.001). Despite the differences in PCa detection the concordance index was 75% and 77% for overall PCa and HGPCa, respectively. Calibration for overall PCa was good. This represents the first external validation of a PCA3-based prostate cancer predictive nomogram in a North American population. Prostate 76:1019-1023, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Performance assessment of automated tissue characterization for prostate H and E stained histopathology

NASA Astrophysics Data System (ADS)

DiFranco, Matthew D.; Reynolds, Hayley M.; Mitchell, Catherine; Williams, Scott; Allan, Prue; Haworth, Annette

2015-03-01

Reliable automated prostate tumor detection and characterization in whole-mount histology images is sought in many applications, including post-resection tumor staging and as ground-truth data for multi-parametric MRI interpretation. In this study, an ensemble-based supervised classification algorithm for high-resolution histology images was trained on tile-based image features including histogram and gray-level co-occurrence statistics. The algorithm was assessed using different combinations of H and E prostate slides from two separate medical centers and at two different magnifications (400x and 200x), with the aim of applying tumor classification models to new data. Slides from both datasets were annotated by expert pathologists in order to identify homogeneous cancerous and non-cancerous tissue regions of interest, which were then categorized as (1) low-grade tumor (LG-PCa), including Gleason 3 and high-grade prostatic intraepithelial neoplasia (HG-PIN), (2) high-grade tumor (HG-PCa), including various Gleason 4 and 5 patterns, or (3) non-cancerous, including benign stroma and benign prostatic hyperplasia (BPH). Classification models for both LG-PCa and HG-PCa were separately trained using a support vector machine (SVM) approach, and per-tile tumor prediction maps were generated from the resulting ensembles. Results showed high sensitivity for predicting HG-PCa with an AUC up to 0.822 using training data from both medical centres, while LG-PCa showed a lower sensitivity of 0.763 with the same training data. Visual inspection of cancer probability heatmaps from 9 patients showed that 17/19 tumors were detected, and HG-PCa generally reported less false positives than LG-PCa.

Improvement of Prostate Cancer Diagnosis by Detecting PSA Glycosylation-Specific Changes.

PubMed

Llop, Esther; Ferrer-Batallé, Montserrat; Barrabés, Sílvia; Guerrero, Pedro Enrique; Ramírez, Manel; Saldova, Radka; Rudd, Pauline M; Aleixandre, Rosa N; Comet, Josep; de Llorens, Rafael; Peracaula, Rosa

2016-01-01

New markers based on PSA isoforms have recently been developed to improve prostate cancer (PCa) diagnosis. However, novel approaches are still required to differentiate aggressive from non-aggressive PCa to improve decision making for patients. PSA glycoforms have been shown to be differentially expressed in PCa. In particular, changes in the extent of core fucosylation and sialylation of PSA N-glycans in PCa patients compared to healthy controls or BPH patients have been reported. The objective of this study was to determine these specific glycan structures in serum PSA to analyze their potential value as markers for discriminating between BPH and PCa of different aggressiveness. In the present work, we have established two methodologies to analyze the core fucosylation and the sialic acid linkage of PSA N-glycans in serum samples from BPH (29) and PCa (44) patients with different degrees of aggressiveness. We detected a significant decrease in the core fucose and an increase in the α2,3-sialic acid percentage of PSA in high-risk PCa that differentiated BPH and low-risk PCa from high-risk PCa patients. In particular, a cut-off value of 0.86 of the PSA core fucose ratio, could distinguish high-risk PCa patients from BPH with 90% sensitivity and 95% specificity, with an AUC of 0.94. In the case of the α2,3-sialic acid percentage of PSA, the cut-off value of 30% discriminated between high-risk PCa and the group of BPH, low-, and intermediate-risk PCa with a sensitivity and specificity of 85.7% and 95.5%, respectively, with an AUC of 0.97. The latter marker exhibited high performance in differentiating between aggressive and non-aggressive PCa and has the potential for translational application in the clinic.

Improvement of Prostate Cancer Diagnosis by Detecting PSA Glycosylation-Specific Changes

PubMed Central

Llop, Esther; Ferrer-Batallé, Montserrat; Barrabés, Sílvia; Guerrero, Pedro Enrique; Ramírez, Manel; Saldova, Radka; Rudd, Pauline M.; Aleixandre, Rosa N.; Comet, Josep; de Llorens, Rafael; Peracaula, Rosa

2016-01-01

New markers based on PSA isoforms have recently been developed to improve prostate cancer (PCa) diagnosis. However, novel approaches are still required to differentiate aggressive from non-aggressive PCa to improve decision making for patients. PSA glycoforms have been shown to be differentially expressed in PCa. In particular, changes in the extent of core fucosylation and sialylation of PSA N-glycans in PCa patients compared to healthy controls or BPH patients have been reported. The objective of this study was to determine these specific glycan structures in serum PSA to analyze their potential value as markers for discriminating between BPH and PCa of different aggressiveness. In the present work, we have established two methodologies to analyze the core fucosylation and the sialic acid linkage of PSA N-glycans in serum samples from BPH (29) and PCa (44) patients with different degrees of aggressiveness. We detected a significant decrease in the core fucose and an increase in the α2,3-sialic acid percentage of PSA in high-risk PCa that differentiated BPH and low-risk PCa from high-risk PCa patients. In particular, a cut-off value of 0.86 of the PSA core fucose ratio, could distinguish high-risk PCa patients from BPH with 90% sensitivity and 95% specificity, with an AUC of 0.94. In the case of the α2,3-sialic acid percentage of PSA, the cut-off value of 30% discriminated between high-risk PCa and the group of BPH, low-, and intermediate-risk PCa with a sensitivity and specificity of 85.7% and 95.5%, respectively, with an AUC of 0.97. The latter marker exhibited high performance in differentiating between aggressive and non-aggressive PCa and has the potential for translational application in the clinic. PMID:27279911

A three-gene panel on urine increases PSA specificity in the detection of prostate cancer.

PubMed

Rigau, Marina; Ortega, Israel; Mir, Maria Carmen; Ballesteros, Carlos; Garcia, Marta; Llauradó, Marta; Colás, Eva; Pedrola, Núria; Montes, Melania; Sequeiros, Tamara; Ertekin, Tugce; Majem, Blanca; Planas, Jacques; Ruiz, Anna; Abal, Miguel; Sánchez, Alex; Morote, Juan; Reventós, Jaume; Doll, Andreas

2011-12-01

Several studies have demonstrated the usefulness of monitoring an RNA transcript, such as PCA3, in post-prostate massage (PM) urine for increasing the specificity of prostate-specific antigen (PSA) in the detection of prostate cancer (PCa). However, a single marker may not necessarily reflect the multifactorial nature of PCa. We analyzed post-PM urine samples from 154 consecutive patients, who presented for prostate biopsies because of elevated serum PSA (>4 ng/ml) and/or abnormal digital rectal exam. We tested whether the putative PCa biomarkers PSMA, PSGR, and PCA3 could be detected by quantitative real-time PCR in post-PM urine sediment. We combined these findings to test if a combination of these biomarkers could improve the specificity of actual diagnosis. Afterwards, we specifically tested our model for clinical usefulness in the PSA diagnostic "gray zone" (4-10 ng/ml) on a target subset of 82 men with no prior biopsy. By univariate analysis, we found that the PSMA, PSGR, and PCA3 scores were significant predictors of PCa. Using a multiplex model, the area under the multi receiver-operating characteristic curve was 0.74 versus 0.82 in the diagnostic "gray zone." Fixing the sensitivity at 96%, we obtained a specificity of 34% and 50% in the gray zone. Taken together, these results provide a strategy for the development of a more accurate model for PCa diagnosis. In the future, a multiplexed, urine-based diagnostic test for PCa with a higher specificity, but the same sensitivity as the serum-PSA test, could be used to determine better which patients should undergo biopsy. Copyright © 2011 Wiley Periodicals, Inc.

Performance analysis of robust road sign identification

NASA Astrophysics Data System (ADS)

Ali, Nursabillilah M.; Mustafah, Y. M.; Rashid, N. K. A. M.

2013-12-01

This study describes performance analysis of a robust system for road sign identification that incorporated two stages of different algorithms. The proposed algorithms consist of HSV color filtering and PCA techniques respectively in detection and recognition stages. The proposed algorithms are able to detect the three standard types of colored images namely Red, Yellow and Blue. The hypothesis of the study is that road sign images can be used to detect and identify signs that are involved with the existence of occlusions and rotational changes. PCA is known as feature extraction technique that reduces dimensional size. The sign image can be easily recognized and identified by the PCA method as is has been used in many application areas. Based on the experimental result, it shows that the HSV is robust in road sign detection with minimum of 88% and 77% successful rate for non-partial and partial occlusions images. For successful recognition rates using PCA can be achieved in the range of 94-98%. The occurrences of all classes are recognized successfully is between 5% and 10% level of occlusions.

Epileptic seizure detection in EEG signal with GModPCA and support vector machine.

PubMed

Jaiswal, Abeg Kumar; Banka, Haider

2017-01-01

Epilepsy is one of the most common neurological disorders caused by recurrent seizures. Electroencephalograms (EEGs) record neural activity and can detect epilepsy. Visual inspection of an EEG signal for epileptic seizure detection is a time-consuming process and may lead to human error; therefore, recently, a number of automated seizure detection frameworks were proposed to replace these traditional methods. Feature extraction and classification are two important steps in these procedures. Feature extraction focuses on finding the informative features that could be used for classification and correct decision-making. Therefore, proposing effective feature extraction techniques for seizure detection is of great significance. Principal Component Analysis (PCA) is a dimensionality reduction technique used in different fields of pattern recognition including EEG signal classification. Global modular PCA (GModPCA) is a variation of PCA. In this paper, an effective framework with GModPCA and Support Vector Machine (SVM) is presented for epileptic seizure detection in EEG signals. The feature extraction is performed with GModPCA, whereas SVM trained with radial basis function kernel performed the classification between seizure and nonseizure EEG signals. Seven different experimental cases were conducted on the benchmark epilepsy EEG dataset. The system performance was evaluated using 10-fold cross-validation. In addition, we prove analytically that GModPCA has less time and space complexities as compared to PCA. The experimental results show that EEG signals have strong inter-sub-pattern correlations. GModPCA and SVM have been able to achieve 100% accuracy for the classification between normal and epileptic signals. Along with this, seven different experimental cases were tested. The classification results of the proposed approach were better than were compared the results of some of the existing methods proposed in literature. It is also found that the time and space complexities of GModPCA are less as compared to PCA. This study suggests that GModPCA and SVM could be used for automated epileptic seizure detection in EEG signal.

Clinical Significance of Retinoic Acid Receptor Beta Promoter Methylation in Prostate Cancer: A Meta-Analysis.

PubMed

Dou, MengMeng; Zhou, XueLiang; Fan, ZhiRui; Ding, XianFei; Li, LiFeng; Wang, ShuLing; Xue, Wenhua; Wang, Hui; Suo, Zhenhe; Deng, XiaoMing

2018-01-01

Retinoic acid receptor beta (RAR beta) is a retinoic acid receptor gene that has been shown to play key roles during multiple cancer processes, including cell proliferation, apoptosis, migration and invasion. Numerous studies have found that methylation of the RAR beta promoter contributed to the occurrence and development of malignant tumors. However, the connection between RAR beta promoter methylation and prostate cancer (PCa) remains unknown. This meta-analysis evaluated the clinical significance of RAR beta promoter methylation in PCa. We searched all published records relevant to RAR beta and PCa in a series of databases, including PubMed, Embase, Cochrane Library, ISI Web of Science and CNKI. The rates of RAR beta promoter methylation in the PCa and control groups (including benign prostatic hyperplasia and normal prostate tissues) were summarized. In addition, we evaluated the source region of available samples and the methods used to detect methylation. To compare the incidence and variation in RAR beta promoter methylation in PCa and non-PCa tissues, the odds ratio (OR) and 95% confidence interval (CI) were calculated accordingly. All the data were analyzed with the statistical software STATA 12.0. Based on the inclusion and exclusion criteria, 15 articles assessing 1,339 samples were further analyzed. These data showed that the RAR beta promoter methylation rates in PCa tissues were significantly higher than the rates in the non-PCa group (OR=21.65, 95% CI: 9.27-50.57). Subgroup analysis according to the source region of samples showed that heterogeneity in Asia was small (I2=0.0%, P=0.430). Additional subgroup analysis based on the method used to detect RAR beta promoter methylation showed that the heterogeneity detected by MSP (methylation-specific PCR) was relatively small (I2=11.3%, P=0.343). Although studies reported different rates for RAR beta promoter methylation in PCa tissues, the total analysis demonstrated that RAR beta promoter methylation may be correlated with PCa carcinogenesis and that the RAR beta gene is particularly susceptible. Additional studies with sufficient data are essential to further evaluate the clinical features and prognostic utility of RAR beta promoter methylation in PCa. © 2018 The Author(s). Published by S. Karger AG, Basel.

Novel RNA hybridization method for the in situ detection of ETV1, ETV4, and ETV5 gene fusions in prostate cancer.

PubMed

Kunju, Lakshmi P; Carskadon, Shannon; Siddiqui, Javed; Tomlins, Scott A; Chinnaiyan, Arul M; Palanisamy, Nallasivam

2014-09-01

The genetic basis of 50% to 60% of prostate cancer (PCa) is attributable to rearrangements in E26 transformation-specific (ETS) (ERG, ETV1, ETV4, and ETV5), BRAF, and RAF1 genes and overexpression of SPINK1. The development and validation of reliable detection methods are warranted to classify various molecular subtypes of PCa for diagnostic and prognostic purposes. ETS gene rearrangements are typically detected by fluorescence in situ hybridization and reverse-transcription polymerase chain reaction methods. Recently, monoclonal antibodies against ERG have been developed that detect the truncated ERG protein in immunohistochemical assays where staining levels are strongly correlated with ERG rearrangement status by fluorescence in situ hybridization. However, specific antibodies for ETV1, ETV4, and ETV5 are unavailable, challenging their clinical use. We developed a novel RNA in situ hybridization-based assay for the in situ detection of ETV1, ETV4, and ETV5 in formalin-fixed paraffin-embedded tissues from prostate needle biopsies, prostatectomy, and metastatic PCa specimens using RNA probes. Further, with combined RNA in situ hybridization and immunohistochemistry we identified a rare subset of PCa with dual ETS gene rearrangements in collisions of independent tumor foci. The high specificity and sensitivity of RNA in situ hybridization provides an alternate method enabling bright-field in situ detection of ETS gene aberrations in routine clinically available PCa specimens.

The added value of percentage of free to total prostate-specific antigen, PCA3, and a kallikrein panel to the ERSPC risk calculator for prostate cancer in prescreened men.

PubMed

Vedder, Moniek M; de Bekker-Grob, Esther W; Lilja, Hans G; Vickers, Andrew J; van Leenders, Geert J L H; Steyerberg, Ewout W; Roobol, Monique J

2014-12-01

Prostate-specific antigen (PSA) testing has limited accuracy for the early detection of prostate cancer (PCa). To assess the value added by percentage of free to total PSA (%fPSA), prostate cancer antigen 3 (PCA3), and a kallikrein panel (4k-panel) to the European Randomised Study of Screening for Prostate Cancer (ERSPC) multivariable prediction models: risk calculator (RC) 4, including transrectal ultrasound, and RC 4 plus digital rectal examination (4+DRE) for prescreened men. Participants were invited for rescreening between October 2007 and February 2009 within the Dutch part of the ERSPC study. Biopsies were taken in men with a PSA level ≥3.0 ng/ml or a PCA3 score ≥10. Additional analyses of the 4k-panel were done on serum samples. Outcome was defined as PCa detectable by sextant biopsy. Receiver operating characteristic curve and decision curve analyses were performed to compare the predictive capabilities of %fPSA, PCA3, 4k-panel, the ERSPC RCs, and their combinations in logistic regression models. PCa was detected in 119 of 708 men. The %fPSA did not perform better univariately or added to the RCs compared with the RCs alone. In 202 men with an elevated PSA, the 4k-panel discriminated better than PCA3 when modelled univariately (area under the curve [AUC]: 0.78 vs. 0.62; p=0.01). The multivariable models with PCA3 or the 4k-panel were equivalent (AUC: 0.80 for RC 4+DRE). In the total population, PCA3 discriminated better than the 4k-panel (univariate AUC: 0.63 vs. 0.56; p=0.05). There was no statistically significant difference between the multivariable model with PCA3 (AUC: 0.73) versus the model with the 4k-panel (AUC: 0.71; p=0.18). The multivariable model with PCA3 performed better than the reference model (0.73 vs. 0.70; p=0.02). Decision curves confirmed these patterns, although numbers were small. Both PCA3 and, to a lesser extent, a 4k-panel have added value to the DRE-based ERSPC RC in detecting PCa in prescreened men. We studied the added value of novel biomarkers to previously developed risk prediction models for prostate cancer. We found that inclusion of these biomarkers resulted in an increase in predictive ability. Copyright © 2014. Published by Elsevier B.V.

Convolutional neural network based deep-learning architecture for prostate cancer detection on multiparametric magnetic resonance images

NASA Astrophysics Data System (ADS)

Tsehay, Yohannes K.; Lay, Nathan S.; Roth, Holger R.; Wang, Xiaosong; Kwak, Jin Tae; Turkbey, Baris I.; Pinto, Peter A.; Wood, Brad J.; Summers, Ronald M.

2017-03-01

Prostate cancer (PCa) is the second most common cause of cancer related deaths in men. Multiparametric MRI (mpMRI) is the most accurate imaging method for PCa detection; however, it requires the expertise of experienced radiologists leading to inconsistency across readers of varying experience. To increase inter-reader agreement and sensitivity, we developed a computer-aided detection (CAD) system that can automatically detect lesions on mpMRI that readers can use as a reference. We investigated a convolutional neural network based deep-learing (DCNN) architecture to find an improved solution for PCa detection on mpMRI. We adopted a network architecture from a state-of-the-art edge detector that takes an image as an input and produces an image probability map. Two-fold cross validation along with a receiver operating characteristic (ROC) analysis and free-response ROC (FROC) were used to determine our deep-learning based prostate-CAD's (CADDL) performance. The efficacy was compared to an existing prostate CAD system that is based on hand-crafted features, which was evaluated on the same test-set. CADDL had an 86% detection rate at 20% false-positive rate while the top-down learning CAD had 80% detection rate at the same false-positive rate, which translated to 94% and 85% detection rate at 10 false-positives per patient on the FROC. A CNN based CAD is able to detect cancerous lesions on mpMRI of the prostate with results comparable to an existing prostate-CAD showing potential for further development.

Echo-Planar Imaging-Based, J-Resolved Spectroscopic Imaging for Improved Metabolite Detection in Prostate Cancer

DTIC Science & Technology

2014-10-01

Imaging (EP-JRESI); Citrate, Choline, Creatine , Spermine, 3Tesla MRI scanner, Endo-rectal MR coil, WET Water Suppression, prostate cancer (PCa...spectroscopic imaging are due to the overlap of metabolite resonances, quantifying few metabolites only (citrate (Cit), choline (Ch), creatine (Cr...concentrations of citrate (Cit), creatine (Cr), choline (Ch) and polyamines that are used to detect and diagnose PCa (2). The challenging task in 1D MRS

Comparison between target magnetic resonance imaging (MRI) in-gantry and cognitively directed transperineal or transrectal-guided prostate biopsies for Prostate Imaging-Reporting and Data System (PI-RADS) 3-5 MRI lesions.

PubMed

Yaxley, Anna J; Yaxley, John W; Thangasamy, Isaac A; Ballard, Emma; Pokorny, Morgan R

2017-11-01

To compare the detection rates of prostate cancer (PCa) in men with Prostate Imaging-Reporting and Data System (PI-RADS) 3-5 abnormalities on 3-Tesla multiparametric (mp) magnetic resonance imaging (MRI) using in-bore MRI-guided biopsy compared with cognitively directed transperineal (cTP) biopsy and transrectal ultrasonography (cTRUS) biopsy. This was a retrospective single-centre study of consecutive men attending the private practice clinic of an experienced urologist performing MRI-guided biopsy and an experienced urologist performing cTP and cTRUS biopsy techniques for PI-RADS 3-5 lesions identified on 3-Tesla mpMRI. There were 595 target mpMRI lesions from 482 men with PI-RADS 3-5 regions of interest during 483 episodes of biopsy. The abnormal mpMRI target lesion was biopsied using the MRI-guided method for 298 biopsies, the cTP method for 248 biopsies and the cTRUS method for 49 biopsies. There were no significant differences in PCa detection among the three biopsy methods in PI-RADS 3 (48.9%, 40.0% and 44.4%, respectively), PI-RADS 4 (73.2%, 81.0% and 85.0%, respectively) or PI-RADS 5 (95.2, 92.0% and 95.0%, respectively) lesions, and there was no significant difference in detection of significant PCa among the biopsy methods in PI-RADS 3 (42.2%, 30.0% and 33.3%, respectively), PI-RADS 4 (66.8%, 66.0% and 80.0%, respectively) or PI-RADS 5 (90.5%, 89.8% and 90.0%, respectively) lesions. There were also no differences in PCa or significant PCa detection based on lesion location or size among the methods. We found no significant difference in the ability to detect PCa or significant PCa using targeted MRI-guided, cTP or cTRUS biopsy methods. Identification of an abnormal area on mpMRI appears to be more important in increasing the detection of PCa than the technique used to biopsy an MRI abnormality. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Performance of serum prostate-specific antigen isoform [-2]proPSA (p2PSA) and the prostate health index (PHI) in a Chinese hospital-based biopsy population.

PubMed

Na, Rong; Ye, Dingwei; Liu, Fang; Chen, Haitao; Qi, Jun; Wu, Yishuo; Zhang, Guiming; Wang, Meilin; Wang, Wenying; Sun, Jielin; Yu, Guopeng; Zhu, Yao; Ren, Shancheng; Zheng, S Lilly; Jiang, Haowen; Sun, Yinghao; Ding, Qiang; Xu, Jianfeng

2014-11-01

The use of serum [-2]proPSA (p2PSA) and its derivative, the prostate health index (PHI), in detecting prostate cancer (PCa) have been consistently shown to have better performance than total prostate-specific antigen (tPSA) in discriminating biopsy outcomes in western countries. However, little is known about their performance in Chinese men. Our objective is to test the performance of p2PSA and PHI and their added value to tPSA in discriminating biopsy outcomes in Chinese men. Consecutive patients who underwent prostate biopsy in three tertiary hospitals in Shanghai, China during 2012-2013 were recruited. Serum tPSA, free PSA (fPSA), and p2PSA were measured centrally using Beckman Coulter's DxI 800 Immunoassay System. The primary outcome is PCa and the secondary outcome is high-grade PCa (Gleason Score of 4 + 3 or worse). Discriminative performance was assessed using the area under the receiver operating characteristic curve (AUC), detection rate and Decision Curve Analysis (DCA). Among 636 patients who underwent prostate biopsy, PHI was a significant predictor of biopsy outcomes, independent of other clinical variables. The AUC in discriminating PCa from non-PCa was consistently higher for PHI than tPSA in the entire cohort (0.88 vs. 0.81) as well as in patients with tPSA at 2-10 ng/ml (0.73 vs. 0.53), at 10.1-20 ng/ml (0.81 vs. 0.58), and at tPSA >20 ng/ml (0.90 vs. 0.80). The differences were statistically significant in all comparisons, P < 0.01. To detect 90% of all PCa in the cohort, 362 and 457 patients would need to be biopsied based on PHI and tPSA cutoff, respectively, a 21% reduction for PHI. Similar results were found for discriminating high-grade PCa. PHI provides added value over tPSA in discriminating PCa and high-grade PCa in patients who underwent prostate biopsy in China. © 2014 Wiley Periodicals, Inc.

PCA-HOG symmetrical feature based diseased cell detection

NASA Astrophysics Data System (ADS)

Wan, Min-jie

2016-04-01

A histogram of oriented gradient (HOG) feature is applied to the field of diseased cell detection, which can detect diseased cells in high resolution tissue images rapidly, accurately and efficiently. Firstly, motivated by symmetrical cellular forms, a new HOG symmetrical feature based on the traditional HOG feature is proposed to meet the condition of cell detection. Secondly, considering the high feature dimension of traditional HOG feature leads to plenty of memory resources and long runtime in practical applications, a classical dimension reduction method called principal component analysis (PCA) is used to reduce the dimension of high-dimensional HOG descriptor. Because of that, computational speed is increased greatly, and the accuracy of detection can be controlled in a proper range at the same time. Thirdly, support vector machine (SVM) classifier is trained with PCA-HOG symmetrical features proposed above. At last, practical tissue images is detected and analyzed by SVM classifier. In order to verify the effectiveness of this new algorithm, it is practically applied to conduct diseased cell detection which takes 200 pieces of H&E (hematoxylin & eosin) high resolution staining histopathological images collected from 20 breast cancer patients as a sample. The experiment shows that the average processing rate can be 25 frames per second and the detection accuracy can be 92.1%.

Emory University: Prediction of Protein-Protein Interactions by NanoLuc-Based Protein-Fragment Complementation Assay | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory has developed a new NanoLuc®-based protein-fragment complementation assay (NanoPCA) which allows the detection of novel protein-protein interactions (PPI). NanoPCA allows the study of PPI dynamics with reversible interactions.  Read the abstract. Experimental Approaches Read the detailed Experimetnal Approaches. 

Prediction of Protein-Protein Interactions by NanoLuc-Based Protein-Fragment Complementation Assay | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory has developed a new NanoLuc®-based protein-fragment complementation assay (NanoPCA) which allows the detection of novel protein-protein interactions (PPI). NanoPCA allows the study of PPI dynamics with reversible interactions.  Read the abstract. Experimental Approaches Read the detailed Experimetnal Approaches. 

The Pseudomonas aeruginosa efflux pump MexGHI-OpmD transports a natural phenazine that controls gene expression and biofilm development

PubMed Central

Sakhtah, Hassan; Koyama, Leslie; Zhang, Yihan; Morales, Diana K.; Fields, Blanche L.; Price-Whelan, Alexa; Hogan, Deborah A.; Shepard, Kenneth; Dietrich, Lars E. P.

2016-01-01

Redox-cycling compounds, including endogenously produced phenazine antibiotics, induce expression of the efflux pump MexGHI-OpmD in the opportunistic pathogen Pseudomonas aeruginosa. Previous studies of P. aeruginosa virulence, physiology, and biofilm development have focused on the blue phenazine pyocyanin and the yellow phenazine-1-carboxylic acid (PCA). In P. aeruginosa phenazine biosynthesis, conversion of PCA to pyocyanin is presumed to proceed through the intermediate 5-methylphenazine-1-carboxylate (5-Me-PCA), a reactive compound that has eluded detection in most laboratory samples. Here, we apply electrochemical methods to directly detect 5-Me-PCA and find that it is transported by MexGHI-OpmD in P. aeruginosa strain PA14 planktonic and biofilm cells. We also show that 5-Me-PCA is sufficient to fully induce MexGHI-OpmD expression and that it is required for wild-type colony biofilm morphogenesis. These physiological effects are consistent with the high redox potential of 5-Me-PCA, which distinguishes it from other well-studied P. aeruginosa phenazines. Our observations highlight the importance of this compound, which was previously overlooked due to the challenges associated with its detection, in the context of P. aeruginosa gene expression and multicellular behavior. This study constitutes a unique demonstration of efflux-based self-resistance, controlled by a simple circuit, in a Gram-negative pathogen. PMID:27274079

Esophageal cancer detection based on tissue surface-enhanced Raman spectroscopy and multivariate analysis

NASA Astrophysics Data System (ADS)

Feng, Shangyuan; Lin, Juqiang; Huang, Zufang; Chen, Guannan; Chen, Weisheng; Wang, Yue; Chen, Rong; Zeng, Haishan

2013-01-01

The capability of using silver nanoparticle based near-infrared surface enhanced Raman scattering (SERS) spectroscopy combined with principal component analysis (PCA) and linear discriminate analysis (LDA) to differentiate esophageal cancer tissue from normal tissue was presented. Significant differences in Raman intensities of prominent SERS bands were observed between normal and cancer tissues. PCA-LDA multivariate analysis of the measured tissue SERS spectra achieved diagnostic sensitivity of 90.9% and specificity of 97.8%. This exploratory study demonstrated great potential for developing label-free tissue SERS analysis into a clinical tool for esophageal cancer detection.

Automated high-grade prostate cancer detection and ranking on whole slide images

NASA Astrophysics Data System (ADS)

Huang, Chao-Hui; Racoceanu, Daniel

2017-03-01

Recently, digital pathology (DP) has been largely improved due to the development of computer vision and machine learning. Automated detection of high-grade prostate carcinoma (HG-PCa) is an impactful medical use-case showing the paradigm of collaboration between DP and computer science: given a field of view (FOV) from a whole slide image (WSI), the computer-aided system is able to determine the grade by classifying the FOV. Various approaches have been reported based on this approach. However, there are two reasons supporting us to conduct this work: first, there is still room for improvement in terms of detection accuracy of HG-PCa; second, a clinical practice is more complex than the operation of simple image classification. FOV ranking is also an essential step. E.g., in clinical practice, a pathologist usually evaluates a case based on a few FOVs from the given WSI. Then, makes decision based on the most severe FOV. This important ranking scenario is not yet being well discussed. In this work, we introduce an automated detection and ranking system for PCa based on Gleason pattern discrimination. Our experiments suggested that the proposed system is able to perform high-accuracy detection ( 95:57% +/- 2:1%) and excellent performance of ranking. Hence, the proposed system has a great potential to support the daily tasks in the medical routine of clinical pathology.

Innovations in diagnostic imaging of localized prostate cancer.

PubMed

Pummer, Karl; Rieken, Malte; Augustin, Herbert; Gutschi, Thomas; Shariat, Shahrokh F

2014-08-01

In recent years, various imaging modalities have been developed to improve diagnosis, staging, and localization of early-stage prostate cancer (PCa). A MEDLINE literature search of the time frame between 01/2007 and 06/2013 was performed on imaging of localized PCa. Conventional transrectal ultrasound (TRUS) is mainly used to guide prostate biopsy. Contrast-enhanced ultrasound is based on the assumption that PCa tissue is hypervascularized and might be better identified after intravenous injection of a microbubble contrast agent. However, results on its additional value for cancer detection are controversial. Computer-based analysis of the transrectal ultrasound signal (C-TRUS) appears to detect cancer in a high rate of patients with previous biopsies. Real-time elastography seems to have higher sensitivity, specificity, and positive predictive value than conventional TRUS. However, the method still awaits prospective validation. The same is true for prostate histoscanning, an ultrasound-based method for tissue characterization. Currently, multiparametric MRI provides improved tissue visualization of the prostate, which may be helpful in the diagnosis and targeting of prostate lesions. However, most published series are small and suffer from variations in indication, methodology, quality, interpretation, and reporting. Among ultrasound-based techniques, real-time elastography and C-TRUS seem the most promising techniques. Multiparametric MRI appears to have advantages over conventional T2-weighted MRI in the detection of PCa. Despite these promising results, currently, no recommendation for the routine use of these novel imaging techniques can be made. Prospective studies defining the value of various imaging modalities are urgently needed.

Comparison of 68Ga-HBED-CC PSMA-PET/CT and multiparametric MRI for gross tumour volume detection in patients with primary prostate cancer based on slice by slice comparison with histopathology

PubMed Central

Zamboglou, Constantinos; Drendel, Vanessa; Jilg, Cordula A.; Rischke, Hans C.; Beck, Teresa I.; Schultze-Seemann, Wolfgang; Krauss, Tobias; Mix, Michael; Schiller, Florian; Wetterauer, Ulrich; Werner, Martin; Langer, Mathias; Bock, Michael; Meyer, Philipp T.; Grosu, Anca L.

2017-01-01

Purpose: The exact detection and delineation of the intraprostatic tumour burden is crucial for treatment planning in primary prostate cancer (PCa). We compared 68Ga-HBED-CC-PSMA PET/CT with multiparametric MRI (mpMRI) for diagnosis and tumour delineation in patients with primary PCa based on slice by slice correlation with histopathological reference material. Methodology: Seven patients with histopathologically proven primary PCa underwent 68Ga-HBED-CC-PSMA PET/CT and MRI followed by radical prostatectomy. Resected prostates were scanned by ex-vivo CT in a special localizer and prepared for histopathology. Invasive PCa was delineated on a HE stained histologic tissue slide and matched to ex-vivo CT to obtain gross tumor volume (GTV-)histo. Ex-vivo CT including GTV-histo and MRI data were matched to in-vivo CT(PET). Consensus contours based on MRI (GTV-MRI), PSMA PET (GTV-PET) or the combination of both (GTV-union/-intersection) were created. In each in-vivo CT slice the prostate was separated into 4 equal segments and sensitivity and specificity for PSMA PET and mpMRI were assessed by comparison with histological reference material. Furthermore, the spatial overlap between GTV-histo and GTV-PET/-MRI and the Sørensen-Dice coefficient (DSC) were calculated. In the case of multifocal PCa (4/7 patients), SUV values (PSMA PET) and ADC-values (diffusion weighted MRI) were obtained for each lesion. Results: PSMA PET and mpMRI detected PCa in all patients. GTV-histo was detected in 225 of 340 segments (66.2%). Sensitivity and specificity for GTV-PET, GTV-MRI, GTV-union and GTV-intersection were 75% and 87%, 70% and 82%, 82% and 67%, 55% and 99%, respectively. GTV-histo had on average the highest overlap with GTV-union (57±22%), which was significantly higher than overlap with GTV-MRI (p=0.016) and GTV-PET (p=0.016), respectively. The mean DSC for GTV-union, GTV-PET and GTV-MRI was 0.51 (±0.18), 0.45 (±0.17) and 0.48 (±0.19), respectively. In every patient with multifocal PCa there was one lesion which had both the highest SUV and the lowest ADC-value (mean and max). Conclusion: In a slice by slice analysis with histopathology, 68Ga-HBED-CC-PSMA PET/CT and mpMRI showed high sensitivity and specificity in detection of primary PCa. A combination of both methods performed even better in terms of sensitivity (GTV-union) and specificity (GTV-intersection). A moderate to good spatial overlap with GTV-histo was observed for PSMA PET/CT and mpMRI alone which was significantly improved by GTV-union. Further studies are warranted to analyse the impact of these preliminary findings for diagnostic (multimodal guided TRUS biopsy) and therapeutic (focal therapy) strategies in primary PCa. PMID:28042330

New aspects of molecular imaging in prostate cancer.

PubMed

Ceci, Francesco; Castellucci, Paolo; Cerci, Juliano J; Fanti, Stefano

2017-11-01

Nowadays several new imaging modalities are available for investigating prostate cancer (PCa) such as magnet resonance imaging (MRI) in the form of whole body MRI and pelvic multiparametric MRI and positron emission tomography (PET) using choline as radiotracers. Nevertheless, these modalities proved sub-optimal accuracy for detecting PCa metastases, particularly in the recurrence setting. A new molecular probe targeting the prostate specific membrane antigen (PSMA) has been recently developed for PET imaging. PSMA, the glutamate carboxypeptidase II, is a membrane bound metallo-peptidase over-expressed in PCa cells. It has been shown that PSMA based imaging offers higher tumor detection rate compared to choline PET/CT and radiological conventional imaging, especially at very low PSA levels during biochemical recurrence. In addition PSMA, as theranostics agent, allows both radiolabeling with diagnostic (e.g. 68Ga, 18F) or therapeutic nuclides (e.g. 177Lu, 225Ac). Initial results show that PSMA-targeted radioligand therapy can potentially delay disease progression in metastatic castrate-resistant PCa. Despite still investigational, the bombesin-based radiotracers and antagonist of gastrin releasing-peptide receptor (GRP) (RM2) and anti1-amino-3-18Ffluorocyclobutane-1-carboxylic acid (18F-FACBC) are emerging as possible alternatives for investigating PCa. Considering the wide diffusion of PCa in the Europe and the United States, the presence of these new diagnostic techniques able to detect the disease with high sensitivity and specificity might have a clinical impact on the management of patients. PET/CT imaging with new radiopharmaceuticals can implement the patient management identifying lesion(s) not detectable with conventional imaging procedures. In this review article will be discussed the most promising new PET radiopharmaceuticals (68Ga-PSMA-11, 18F-FACBC, 68Ga-RM2) available at the moment, focusing the attention on their accuracy and their impact on treatment strategy. Copyright © 2017 Elsevier Inc. All rights reserved.

Demonstration of protein-fragment complementation assay using purified firefly luciferase fragments

PubMed Central

2013-01-01

Background Human interactome is predicted to contain 150,000 to 300,000 protein-protein interactions, (PPIs). Protein-fragment complementation assay (PCA) is one of the most widely used methods to detect PPI, as well as Förster resonance energy transfer (FRET). To date, successful applications of firefly luciferase (Fluc)-based PCA have been reported in vivo, in cultured cells and in cell-free lysate, owing to its high sensitivity, high signal-to-background (S/B) ratio, and reversible response. Here we show the assay also works with purified proteins with unexpectedly rapid kinetics. Results Split Fluc fragments both fused with a rapamycin-dependently interacting protein pair were made and expressed in E. coli system, and purified to homogeneity. When the proteins were used for PCA to detect rapamycin-dependent PPI, they enabled a rapid detection (~1 s) of PPI with high S/B ratio. When Fn7-8 domains (7 nm in length) that was shown to abrogate GFP mutant-based FRET was inserted between split Fluc and FKBP12 as a rigid linker, it still showed some response, suggesting less limitation in interacting partner’s size. Finally, the stability of the probe was investigated. Preincubation of the probes at 37 degreeC up to 1 h showed marked decrease of the luminescent signal to 1.5%, showing the limited stability of this system. Conclusion Fluc PCA using purified components will enable a rapid and handy detection of PPIs with high S/B ratio, avoiding the effects of concomitant components. Although the system might not be suitable for large-scale screening due to its limited stability, it can detect an interaction over larger distance than by FRET. This would be the first demonstration of Fluc PCA in vitro, which has a distinct advantage over other PPI assays. Our system enables detection of direct PPIs without risk of perturbation by PPI mediators in the complex cellular milieu. PMID:23536995

Detection of urban expansion in an urban-rural landscape with multitemporal QuickBird images

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio; Li, Guiying

2011-01-01

Accurately detecting urban expansion with remote sensing techniques is a challenge due to the complexity of urban landscapes. This paper explored methods for detecting urban expansion with multitemporal QuickBird images in Lucas do Rio Verde, Mato Grosso, Brazil. Different techniques, including image differencing, principal component analysis (PCA), and comparison of classified impervious surface images with the matched filtering method, were used to examine urbanization detection. An impervious surface image classified with the hybrid method was used to modify the urbanization detection results. As a comparison, the original multispectral image and segmentation-based mean-spectral images were used during the detection of urbanization. This research indicates that the comparison of classified impervious surface images with matched filtering method provides the best change detection performance, followed by the image differencing method based on segmentation-based mean spectral images. The PCA is not a good method for urban change detection in this study. Shadows and high spectral variation within the impervious surfaces represent major challenges to the detection of urban expansion when high spatial resolution images are used. PMID:21799706

Predicting prostate biopsy outcome: prostate health index (phi) and prostate cancer antigen 3 (PCA3) are useful biomarkers.

PubMed

Ferro, Matteo; Bruzzese, Dario; Perdonà, Sisto; Mazzarella, Claudia; Marino, Ada; Sorrentino, Alessandra; Di Carlo, Angelina; Autorino, Riccardo; Di Lorenzo, Giuseppe; Buonerba, Carlo; Altieri, Vincenzo; Mariano, Angela; Macchia, Vincenzo; Terracciano, Daniela

2012-08-16

Indication for prostate biopsy is presently mainly based on prostate-specific antigen (PSA) serum levels and digital-rectal examination (DRE). In view of the unsatisfactory accuracy of these two diagnostic exams, research has focused on novel markers to improve pre-biopsy prostate cancer detection, such as phi and PCA3. The purpose of this prospective study was to assess the diagnostic accuracy of phi and PCA3 for prostate cancer using biopsy as gold standard. Phi index (Beckman coulter immunoassay), PCA3 score (Progensa PCA3 assay) and other established biomarkers (tPSA, fPSA and %fPSA) were assessed before a 18-core prostate biopsy in a group of 251 subjects at their first biopsy. Values of %p2PSA and phi were significantly higher in patients with PCa compared with PCa-negative group (p<0.001) and also compared with high grade prostatic intraepithelial neoplasia (HGPIN) (p<0.001). PCA3 score values were significantly higher in PCa compared with PCa-negative subjects (p<0.001) and in HGPIN vs PCa-negative patients (p<0.001). ROC curve analysis showed that %p2PSA, phi and PCA3 are predictive of malignancy. In conclusion, %p2PSA, phi and PCA3 may predict a diagnosis of PCa in men undergoing their first prostate biopsy. PCA3 score is more useful in discriminating between HGPIN and non-cancer. Copyright © 2012 Elsevier B.V. All rights reserved.

Contrast-Enhanced Ultrasound (CEUS) and Quantitative Perfusion Analysis in Patients with Suspicion for Prostate Cancer.

PubMed

Maxeiner, Andreas; Fischer, Thomas; Schwabe, Julia; Baur, Alexander Daniel Jacques; Stephan, Carsten; Peters, Robert; Slowinski, Torsten; von Laffert, Maximilian; Marticorena Garcia, Stephan Rodrigo; Hamm, Bernd; Jung, Ernst-Michael

2018-06-06

 The aim of this study was to investigate contrast-enhanced ultrasound (CEUS) parameters acquired by software during magnetic resonance imaging (MRI) US fusion-guided biopsy for prostate cancer (PCa) detection and discrimination.  From 2012 to 2015, 158 out of 165 men with suspicion for PCa and with at least 1 negative biopsy of the prostate were included and underwent a multi-parametric 3 Tesla MRI and an MRI/US fusion-guided biopsy, consecutively. CEUS was conducted during biopsy with intravenous bolus application of 2.4 mL of SonoVue ® (Bracco, Milan, Italy). In the latter CEUS clips were investigated using quantitative perfusion analysis software (VueBox, Bracco). The area of strongest enhancement within the MRI pre-located region was investigated and all available parameters from the quantification tool box were collected and analyzed for PCa and its further differentiation was based on the histopathological results.  The overall detection rate was 74 (47 %) PCa cases in 158 included patients. From these 74 PCa cases, 49 (66 %) were graded Gleason ≥ 3 + 4 = 7 (ISUP ≥ 2) PCa. The best results for cancer detection over all quantitative perfusion parameters were rise time (p = 0.026) and time to peak (p = 0.037). Within the subgroup analysis (> vs ≤ 3 + 4 = 7a (ISUP 2)), peak enhancement (p = 0.012), wash-in rate (p = 0.011), wash-out rate (p = 0.007) and wash-in perfusion index (p = 0.014) also showed statistical significance.  The quantification of CEUS parameters was able to discriminate PCa aggressiveness during MRI/US fusion-guided prostate biopsy. © Georg Thieme Verlag KG Stuttgart · New York.

[Analyzing and modeling methods of near infrared spectroscopy for in-situ prediction of oil yield from oil shale].

PubMed

Liu, Jie; Zhang, Fu-Dong; Teng, Fei; Li, Jun; Wang, Zhi-Hong

2014-10-01

In order to in-situ detect the oil yield of oil shale, based on portable near infrared spectroscopy analytical technology, with 66 rock core samples from No. 2 well drilling of Fuyu oil shale base in Jilin, the modeling and analyzing methods for in-situ detection were researched. By the developed portable spectrometer, 3 data formats (reflectance, absorbance and K-M function) spectra were acquired. With 4 different modeling data optimization methods: principal component-mahalanobis distance (PCA-MD) for eliminating abnormal samples, uninformative variables elimination (UVE) for wavelength selection and their combina- tions: PCA-MD + UVE and UVE + PCA-MD, 2 modeling methods: partial least square (PLS) and back propagation artificial neural network (BPANN), and the same data pre-processing, the modeling and analyzing experiment were performed to determine the optimum analysis model and method. The results show that the data format, modeling data optimization method and modeling method all affect the analysis precision of model. Results show that whether or not using the optimization method, reflectance or K-M function is the proper spectrum format of the modeling database for two modeling methods. Using two different modeling methods and four different data optimization methods, the model precisions of the same modeling database are different. For PLS modeling method, the PCA-MD and UVE + PCA-MD data optimization methods can improve the modeling precision of database using K-M function spectrum data format. For BPANN modeling method, UVE, UVE + PCA-MD and PCA- MD + UVE data optimization methods can improve the modeling precision of database using any of the 3 spectrum data formats. In addition to using the reflectance spectra and PCA-MD data optimization method, modeling precision by BPANN method is better than that by PLS method. And modeling with reflectance spectra, UVE optimization method and BPANN modeling method, the model gets the highest analysis precision, its correlation coefficient (Rp) is 0.92, and its standard error of prediction (SEP) is 0.69%.

Improved Statistical Fault Detection Technique and Application to Biological Phenomena Modeled by S-Systems.

PubMed

Mansouri, Majdi; Nounou, Mohamed N; Nounou, Hazem N

2017-09-01

In our previous work, we have demonstrated the effectiveness of the linear multiscale principal component analysis (PCA)-based moving window (MW)-generalized likelihood ratio test (GLRT) technique over the classical PCA and multiscale principal component analysis (MSPCA)-based GLRT methods. The developed fault detection algorithm provided optimal properties by maximizing the detection probability for a particular false alarm rate (FAR) with different values of windows, and however, most real systems are nonlinear, which make the linear PCA method not able to tackle the issue of non-linearity to a great extent. Thus, in this paper, first, we apply a nonlinear PCA to obtain an accurate principal component of a set of data and handle a wide range of nonlinearities using the kernel principal component analysis (KPCA) model. The KPCA is among the most popular nonlinear statistical methods. Second, we extend the MW-GLRT technique to one that utilizes exponential weights to residuals in the moving window (instead of equal weightage) as it might be able to further improve fault detection performance by reducing the FAR using exponentially weighed moving average (EWMA). The developed detection method, which is called EWMA-GLRT, provides improved properties, such as smaller missed detection and FARs and smaller average run length. The idea behind the developed EWMA-GLRT is to compute a new GLRT statistic that integrates current and previous data information in a decreasing exponential fashion giving more weight to the more recent data. This provides a more accurate estimation of the GLRT statistic and provides a stronger memory that will enable better decision making with respect to fault detection. Therefore, in this paper, a KPCA-based EWMA-GLRT method is developed and utilized in practice to improve fault detection in biological phenomena modeled by S-systems and to enhance monitoring process mean. The idea behind a KPCA-based EWMA-GLRT fault detection algorithm is to combine the advantages brought forward by the proposed EWMA-GLRT fault detection chart with the KPCA model. Thus, it is used to enhance fault detection of the Cad System in E. coli model through monitoring some of the key variables involved in this model such as enzymes, transport proteins, regulatory proteins, lysine, and cadaverine. The results demonstrate the effectiveness of the proposed KPCA-based EWMA-GLRT method over Q , GLRT, EWMA, Shewhart, and moving window-GLRT methods. The detection performance is assessed and evaluated in terms of FAR, missed detection rates, and average run length (ARL 1 ) values.

Systematic ultrasound-guided saturation and template biopsy of the prostate: indications and advantages of extended sampling.

PubMed

Isbarn, Hendrik; Briganti, Alberto; De Visschere, Pieter J L; Fütterer, Jurgen J; Ghadjar, Pirus; Giannarini, Gianluca; Ost, Piet; Ploussard, Guillaume; Sooriakumaran, Prasanna; Surcel, Christian I; van Oort, Inge M; Yossepowitch, Ofer; van den Bergh, Roderick C N

2015-04-01

Prostate biopsy (PB) is the gold standard for the diagnosis of prostate cancer (PCa). However, the optimal number of biopsy cores remains debatable. We sought to compare contemporary standard (10-12 cores) vs. saturation (=18 cores) schemes on initial as well as repeat PB. A non-systematic review of the literature was performed from 2000 through 2013. Studies of highest evidence (randomized controlled trials, prospective non-randomized studies, and retrospective reports of high quality) comparing standard vs saturation schemes on initial and repeat PB were evaluated. Outcome measures were overall PCa detection rate, detection rate of insignificant PCa, and procedure-associated morbidity. On initial PB, there is growing evidence that a saturation scheme is associated with a higher PCa detection rate compared to a standard one in men with lower PSA levels (<10 ng/ml), larger prostates (>40 cc), or lower PSA density values (<0.25 ng/ml/cc). However, these cut-offs are not uniform and differ among studies. Detection rates of insignificant PCa do not differ in a significant fashion between standard and saturation biopsies. On repeat PB, PCa detection rate is likewise higher with saturation protocols. Estimates of insignificant PCa vary widely due to differing definitions of insignificant disease. However, the rates of insignificant PCa appear to be comparable for the schemes in patients with only one prior negative biopsy, while saturation biopsy seems to detect more cases of insignificant PCa compared to standard biopsy in men with two or more prior negative biopsies. Very extensive sampling is associated with a high rate of acute urinary retention, whereas other severe adverse events, such as sepsis, appear not to occur more frequently with saturation schemes. Current evidence suggests that saturation schemes are associated with a higher PCa detection rate compared to standard ones on initial PB in men with lower PSA levels or larger prostates, and on repeat PB. Since most data are derived from retrospective studies, other endpoints such as detection rate of insignificant disease - especially on repeat PB - show broad variations throughout the literature and must, thus, be interpreted with caution. Future prospective controlled trials should be conducted to compare extended templates with newer techniques, such as image-guided sampling, in order to optimize PCa diagnostic strategy.

EFEMP1 as a novel DNA methylation marker for prostate cancer: array-based DNA methylation and expression profiling.

PubMed

Kim, Yong-June; Yoon, Hyung-Yoon; Kim, Seon-Kyu; Kim, Young-Won; Kim, Eun-Jung; Kim, Isaac Yi; Kim, Wun-Jae

2011-07-01

Abnormal DNA methylation is associated with many human cancers. The aim of the present study was to identify novel methylation markers in prostate cancer (PCa) by microarray analysis and to test whether these markers could discriminate normal and PCa cells. Microarray-based DNA methylation and gene expression profiling was carried out using a panel of PCa cell lines and a control normal prostate cell line. The methylation status of candidate genes in prostate cell lines was confirmed by real-time reverse transcriptase-PCR, bisulfite sequencing analysis, and treatment with a demethylation agent. DNA methylation and gene expression analysis in 203 human prostate specimens, including 106 PCa and 97 benign prostate hyperplasia (BPH), were carried out. Further validation using microarray gene expression data from the Gene Expression Omnibus (GEO) was carried out. Epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1) was identified as a lead candidate methylation marker for PCa. The gene expression level of EFEMP1 was significantly higher in tissue samples from patients with BPH than in those with PCa (P < 0.001). The sensitivity and specificity of EFEMP1 methylation status in discriminating between PCa and BPH reached 95.3% (101 of 106) and 86.6% (84 of 97), respectively. From the GEO data set, we confirmed that the expression level of EFEMP1 was significantly different between PCa and BPH. Genome-wide characterization of DNA methylation profiles enabled the identification of EFEMP1 aberrant methylation patterns in PCa. EFEMP1 might be a useful indicator for the detection of PCa.

An electrochemiluminescence-supramolecular approach to sarcosine detection for early diagnosis of prostate cancer.

PubMed

Valenti, Giovanni; Rampazzo, Enrico; Biavardi, Elisa; Villani, Elena; Fracasso, Giulio; Marcaccio, Massimo; Bertani, Federico; Ramarli, Dunia; Dalcanale, Enrico; Paolucci, Francesco; Prodi, Luca

2015-01-01

Monitoring Prostate Cancer (PCa) biomarkers is an efficient way to diagnosis this disease early, since it improves the therapeutic success rate and suppresses PCa patient mortality: for this reason a powerful analytical technique such as electrochemiluminescence (ECL) is already used for this application, but its widespread usability is still hampered by the high cost of commercial ECL equipment. We describe an innovative approach for the selective and sensitive detection of the PCa biomarker sarcosine, obtained by a synergistic ECL-supramolecular approach, in which the free base form of sarcosine acts as co-reagent in a Ru(bpy)3(2+)-ECL process. We used magnetic micro-beads decorated with a supramolecular tetraphosphonate cavitand (Tiiii) for the selective capture of sarcosine hydrochloride in a complex matrix like urine. Sarcosine determination was then obtained with ECL measurements thanks to the complexation properties of Tiiii, with a protocol involving simple pH changes - to drive the capture-release process of sarcosine from the receptor - and magnetic micro-bead technology. With this approach we were able to measure sarcosine in the μM to mM window, a concentration range that encompasses the diagnostic urinary value of sarcosine in healthy subjects and PCa patients, respectively. These results indicate how this ECL-supramolecular approach is extremely promising for the detection of sarcosine and for PCa diagnosis and monitoring, and for the development of portable and more affordable devices.

Non-invasive imaging of prostate cancer progression in nude mice using iRFP gene reporter

NASA Astrophysics Data System (ADS)

Zhu, Banghe; Wu, Grace; Robinson, Holly; Wilganowski, Nathaniel; Sevick-Muraca, Eva M.

2013-03-01

Prostate cancer (PCa) is the second most common cancer in US men. Metastasis is the final step of tumor progression and remains the primary cause of PCa death. Hence preclinical, orthotopic models of PCa metastasis are necessary to develop new therapeutics against metastatic disease. Yet unlike irrelevant subcutaneous tumor models, the deployment of orthotopic models of cancer metastasis in drug research and development is limited by the inability to longitudinally monitor cancer progression/regression in response to administration of experimental pharmaceuticals. Recently, a nearinfrared fluorescent protein (iRFP) was created for deeper imaging [1]. Imaging prostate tumor growth and lymph node metastasis in nude mice therefore becomes possible using this new fluorescent gene reporter. In this study, we first developed an intensified CCD (ICCD)-based iRFP fluorescence imaging device. Then human PCa PC3 cell lines expressing iRFP gene reporter were orthotopically implanted in male Nu/Nu mice at 8-10 weeks old. After 6-10 weeks, in vivo, in situ and ex vivo fluorescence imaging was performed. In vivo iRFP fluorescence imaging showed that the detected fluorescence concentrated at the prostate and became stronger over time, indicating the growth of implanted PCa. Fluorescence was non-invasively detected at locations of prostate-draining lymph nodes as early as 5 weeks post implantation, indicating the metastasis to lymph nodes. In situ and ex vivo fluorescence imaging demonstrated that the detected signals from PCa and lymph nodes were correlated with cancer positive status of tissues as assessed through standard pathology.

RXTE PCA Detection of a New Outburst of XTE J1728-295 (probably IGR J17285-2922)

NASA Astrophysics Data System (ADS)

Markwardt, Craig B.; Swank, Jean H.

2010-08-01

We report the detection of a new outburst of a source designated XTE J1728-295 in the RXTE PCA scans, which is probably the same as IGR J17285-2922. This source was first detected in August-October 2003 with PCA scans of the galactic center region, and is speculated to be a black hole candidate (Barlow et al. 2005, A&A, 437, L27). In PCA scans on 2010-08-28 near 09:35 UTC, the source rose to a flux of 6.5 mCrab (2-10 keV).

Predicting timing of foot strike during running, independent of striking technique, using principal component analysis of joint angles.

PubMed

Osis, Sean T; Hettinga, Blayne A; Leitch, Jessica; Ferber, Reed

2014-08-22

As 3-dimensional (3D) motion-capture for clinical gait analysis continues to evolve, new methods must be developed to improve the detection of gait cycle events based on kinematic data. Recently, the application of principal component analysis (PCA) to gait data has shown promise in detecting important biomechanical features. Therefore, the purpose of this study was to define a new foot strike detection method for a continuum of striking techniques, by applying PCA to joint angle waveforms. In accordance with Newtonian mechanics, it was hypothesized that transient features in the sagittal-plane accelerations of the lower extremity would be linked with the impulsive application of force to the foot at foot strike. Kinematic and kinetic data from treadmill running were selected for 154 subjects, from a database of gait biomechanics. Ankle, knee and hip sagittal plane angular acceleration kinematic curves were chained together to form a row input to a PCA matrix. A linear polynomial was calculated based on PCA scores, and a 10-fold cross-validation was performed to evaluate prediction accuracy against gold-standard foot strike as determined by a 10 N rise in the vertical ground reaction force. Results show 89-94% of all predicted foot strikes were within 4 frames (20 ms) of the gold standard with the largest error being 28 ms. It is concluded that this new foot strike detection is an improvement on existing methods and can be applied regardless of whether the runner exhibits a rearfoot, midfoot, or forefoot strike pattern. Copyright © 2014 Elsevier Ltd. All rights reserved.

Assessing the Clinical Role of Genetic Markers of Early-Onset Prostate Cancer Among High-Risk Men Enrolled in Prostate Cancer Early Detection

PubMed Central

Hughes, Lucinda; Zhu, Fang; Ross, Eric; Gross, Laura; Uzzo, Robert G.; Chen, David Y. T.; Viterbo, Rosalia; Rebbeck, Timothy R.; Giri, Veda N.

2011-01-01

Background Men with familial prostate cancer (PCA) and African American men are at risk for developing PCA at younger ages. Genetic markers predicting early-onset PCA may provide clinically useful information to guide screening strategies for high-risk men. We evaluated clinical information from six polymorphisms associated with early-onset PCA in a longitudinal cohort of high-risk men enrolled in PCA early detection with significant African American participation. Methods Eligibility criteria include ages 35–69 with a family history of PCA or African American race. Participants undergo screening and biopsy per study criteria. Six markers associated with early-onset PCA (rs2171492 (7q32), rs6983561 (8q24), rs10993994 (10q11), rs4430796 (17q12), rs1799950 (17q21), and rs266849 (19q13)) were genotyped. Cox models were used to evaluate time to PCA diagnosis and PSA prediction for PCA by genotype. Harrell’s concordance index was used to evaluate predictive accuracy for PCA by PSA and genetic markers. Results 460 participants with complete data and ≥1 follow-up visit were included. 56% were African American. Among African American men, rs6983561 genotype was significantly associated with earlier time to PCA diagnosis (p=0.005) and influenced prediction for PCA by the PSA (p<0.001). When combined with PSA, rs6983561 improved predictive accuracy for PCA compared to PSA alone among African American men (PSA= 0.57 vs. PSA+rs6983561=0.75, p=0.03). Conclusions Early-onset marker rs6983561 adds potentially useful clinical information for African American men undergoing PCA risk assessment. Further study is warranted to validate these findings. Impact Genetic markers of early-onset PCA have potential to refine and personalize PCA early detection for high-risk men. PMID:22144497

Power line identification of millimeter wave radar based on PCA-GS-SVM

NASA Astrophysics Data System (ADS)

Fang, Fang; Zhang, Guifeng; Cheng, Yansheng

2017-12-01

Aiming at the problem that the existing detection method can not effectively solve the security of UAV's ultra low altitude flight caused by power line, a power line recognition method based on grid search (GS) and the principal component analysis and support vector machine (PCA-SVM) is proposed. Firstly, the candidate line of Hough transform is reduced by PCA, and the main feature of candidate line is extracted. Then, upport vector machine (SVM is) optimized by grid search method (GS). Finally, using support vector machine classifier optimized parameters to classify the candidate line. MATLAB simulation results show that this method can effectively identify the power line and noise, and has high recognition accuracy and algorithm efficiency.

[The value of PHI/PCA3 in the early diagnosis of prostate cancer].

PubMed

Tan, S J; Xu, L W; Xu, Z; Wu, J P; Liang, K; Jia, R P

2016-01-12

To investigate the value of prostate health index (PHI) and prostate cancer gene 3 (PCA3) in the early diagnosis of prostate cancer (PCa). A total of 190 patients with abnormal serum prostate specific antigen (PSA) or abnormal digital rectal examination were enrolled. They were all underwent initial biopsy and 11 of them were also underwent repeated biopsy. In addition, 25 healthy cases (with normal digital rectal examination and PSA<4 ng/ml) were the control group.The PHI and PCA3 were detected by using immunofluorescence and Loop-Mediated Isothermal Amplification (LAMP). The sensitivity and specificity of diagnosis were determined by ROC curve.In addition, the relationship between PHI/PSA and the Gleason score and clinical stage were analyzed. A total of 89 patients were confirmed PCa by Pathological diagnosis. The other 101 patients were diagnosed as benign prostatic hyperplasia (BPH). The sensitivity and specificity of PCA3 test were 85.4% was 92.1%. Area under curve (AUC) of PHI is higher than AUC of PSA (0.727>0.699). The PHI in peripheral blood was positively correlated with Gleason score and clinical stage. The detection of PCA3 and PHI shows excellent detecting effectiveness. Compared with single PSA, the combined detection of PHI and PCA3 improved the diagnostic specificity. It can provide a new method for the early diagnosis in prostate cancer and avoid unnecessary biopsies.

Nanotechnology-Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer

DTIC Science & Technology

2017-08-01

AWARD NUMBER: W81XWH-15-1-0157 TITLE: Nanotechnology -Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer PRINCIPAL...TITLE AND SUBTITLE Nanotechnology -Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer 5a. CONTRACT NUMBER 5b. GRANT NUMBER...identify novel differentially expressed miRNAs in the body fluids (blood, urine, etc.) for an early detection of PCa. Advances in nanotechnology and

Ultra-sensitive high performance liquid chromatography-laser-induced fluorescence based proteomics for clinical applications.

PubMed

Patil, Ajeetkumar; Bhat, Sujatha; Pai, Keerthilatha M; Rai, Lavanya; Kartha, V B; Chidangil, Santhosh

2015-09-08

An ultra-sensitive high performance liquid chromatography-laser induced fluorescence (HPLC-LIF) based technique has been developed by our group at Manipal, for screening, early detection, and staging for various cancers, using protein profiling of clinical samples like, body fluids, cellular specimens, and biopsy-tissue. More than 300 protein profiles of different clinical samples (serum, saliva, cellular samples and tissue homogenates) from volunteers (normal, and different pre-malignant/malignant conditions) were recorded using this set-up. The protein profiles were analyzed using principal component analysis (PCA) to achieve objective detection and classification of malignant, premalignant and healthy conditions with high sensitivity and specificity. The HPLC-LIF protein profiling combined with PCA, as a routine method for screening, diagnosis, and staging of cervical cancer and oral cancer, is discussed in this paper. In recent years, proteomics techniques have advanced tremendously in life sciences and medical sciences for the detection and identification of proteins in body fluids, tissue homogenates and cellular samples to understand biochemical mechanisms leading to different diseases. Some of the methods include techniques like high performance liquid chromatography, 2D-gel electrophoresis, MALDI-TOF-MS, SELDI-TOF-MS, CE-MS and LC-MS techniques. We have developed an ultra-sensitive high performance liquid chromatography-laser induced fluorescence (HPLC-LIF) based technique, for screening, early detection, and staging for various cancers, using protein profiling of clinical samples like, body fluids, cellular specimens, and biopsy-tissue. More than 300 protein profiles of different clinical samples (serum, saliva, cellular samples and tissue homogenates) from healthy and volunteers with different malignant conditions were recorded by using this set-up. The protein profile data were analyzed using principal component analysis (PCA) for objective classification and detection of malignant, premalignant and healthy conditions. The method is extremely sensitive to detect proteins with limit of detection of the order of femto-moles. The HPLC-LIF combined with PCA as a potential proteomic method for the diagnosis of oral cancer and cervical cancer has been discussed in this paper. This article is part of a Special Issue entitled: Proteomics in India. Copyright © 2015 Elsevier B.V. All rights reserved.

EEG channels reduction using PCA to increase XGBoost's accuracy for stroke detection

NASA Astrophysics Data System (ADS)

Fitriah, N.; Wijaya, S. K.; Fanany, M. I.; Badri, C.; Rezal, M.

2017-07-01

In Indonesia, based on the result of Basic Health Research 2013, the number of stroke patients had increased from 8.3 ‰ (2007) to 12.1 ‰ (2013). These days, some researchers are using electroencephalography (EEG) result as another option to detect the stroke disease besides CT Scan image as the gold standard. A previous study on the data of stroke and healthy patients in National Brain Center Hospital (RS PON) used Brain Symmetry Index (BSI), Delta-Alpha Ratio (DAR), and Delta-Theta-Alpha-Beta Ratio (DTABR) as the features for classification by an Extreme Learning Machine (ELM). The study got 85% accuracy with sensitivity above 86 % for acute ischemic stroke detection. Using EEG data means dealing with many data dimensions, and it can reduce the accuracy of classifier (the curse of dimensionality). Principal Component Analysis (PCA) could reduce dimensionality and computation cost without decreasing classification accuracy. XGBoost, as the scalable tree boosting classifier, can solve real-world scale problems (Higgs Boson and Allstate dataset) with using a minimal amount of resources. This paper reuses the same data from RS PON and features from previous research, preprocessed with PCA and classified with XGBoost, to increase the accuracy with fewer electrodes. The specific fewer electrodes improved the accuracy of stroke detection. Our future work will examine the other algorithm besides PCA to get higher accuracy with less number of channels.

Transrectal real-time tissue elastography targeted biopsy coupled with peak strain index improves the detection of clinically important prostate cancer.

PubMed

Ma, Qi; Yang, Dong-Rong; Xue, Bo-Xin; Wang, Cheng; Chen, Han-Bin; Dong, Yun; Wang, Cai-Shan; Shan, Yu-Xi

2017-07-01

The focus of the present study was to evaluate transrectal real-time tissue elastography (RTE)-targeted two-core biopsy coupled with peak strain index for the detection of prostate cancer (PCa) and to compare this method with 10-core systematic biopsy. A total of 141 patients were enrolled for evaluation. The diagnostic value of peak strain index was assessed using a receiver operating characteristic curve. The cancer detection rates of the two approaches and corresponding positive cores and Gleason score were compared. The cancer detection rate per core in the RTE-targeted biopsy (44%) was higher compared with that in systematic biopsy (30%). The peak strain index value of PCa was higher compared with that of the benign lesion. PCa was detected with the highest sensitivity (87.5%) and specificity (85.5%) using the threshold value of a peak strain index of ≥5.97 with an area under the curve value of 0.95. When the Gleason score was ≥7, RTE-targeted biopsy coupled with peak strain index detected 95.6% of PCa cases, but 84.4% were detected using systematic biopsy. Peak strain index as a quantitative parameter may improve the differentiation of PCa from benign lesions in the prostate peripheral zone. Transrectal RTE-targeted biopsy coupled with peak strain index may enhance the detection of clinically significant PCa, particularly when combined with systematic biopsy.

Behavior of the PCA3 gene in the urine of men with high grade prostatic intraepithelial neoplasia.

PubMed

Morote, Juan; Rigau, Marina; Garcia, Marta; Mir, Carmen; Ballesteros, Carlos; Planas, Jacques; Raventós, Carles X; Placer, José; de Torres, Inés M; Reventós, Jaume; Doll, Andreas

2010-12-01

An ideal marker for the early detection of prostate cancer (PCa) should also differentiate between men with isolated high grade prostatic intraepithelial neoplasia (HGPIN) and those with PCa. Prostate Cancer Gene 3 (PCA3) is a highly specific PCa gene and its score, in relation to the PSA gene in post-prostate massage urine (PMU-PCA3), seems to be useful in ruling out PCa, especially after a negative prostate biopsy. Because PCA3 is also expressed in the HGPIN lesion, the aim of this study was to determine the efficacy of PMU-PCA3 scores for ruling out PCa in men with previous HGPIN. The PMU-PCA3 score was assessed by quantitative PCR (multiplex research assay) in 244 men subjected to prostate biopsy: 64 men with an isolated HGPIN (no cancer detected after two or more repeated biopsies), 83 men with PCa and 97 men with benign pathology findings (BP: no PCa, HGPIN or ASAP). The median PMU-PCA3 score was 1.56 in men with BP, 2.01 in men with HGPIN (p = 0.128) and 9.06 in men with PCa (p = 0.008). The AUC in the ROC analysis was 0.705 in the subset of men with BP and PCa, while it decreased to 0.629 when only men with isolated HGPIN and PCa were included in the analysis. Fixing the sensitivity of the PMU-PCA3 score at 90%, its specificity was 79% in men with BP and 69% in men with isolated HGPIN. The efficacy of the PMU-PCA3 score to rule out PCa in men with HGPIN is lower than in men with BP.

PCA feature extraction for change detection in multidimensional unlabeled data.

PubMed

Kuncheva, Ludmila I; Faithfull, William J

2014-01-01

When classifiers are deployed in real-world applications, it is assumed that the distribution of the incoming data matches the distribution of the data used to train the classifier. This assumption is often incorrect, which necessitates some form of change detection or adaptive classification. While there has been a lot of work on change detection based on the classification error monitored over the course of the operation of the classifier, finding changes in multidimensional unlabeled data is still a challenge. Here, we propose to apply principal component analysis (PCA) for feature extraction prior to the change detection. Supported by a theoretical example, we argue that the components with the lowest variance should be retained as the extracted features because they are more likely to be affected by a change. We chose a recently proposed semiparametric log-likelihood change detection criterion that is sensitive to changes in both mean and variance of the multidimensional distribution. An experiment with 35 datasets and an illustration with a simple video segmentation demonstrate the advantage of using extracted features compared to raw data. Further analysis shows that feature extraction through PCA is beneficial, specifically for data with multiple balanced classes.

PSMA PET and radionuclide therapy in prostate cancer

PubMed Central

Bouchelouche, Kirsten; Turkbey, Baris; Choyke, Peter L.

2016-01-01

Prostate cancer (Pca) is the most common malignancy in men and a major cause of cancer death. Accurate imaging plays an important role in diagnosis, staging, restaging, detection of biochemical recurrence, and for therapy of PCa patients. Since no effective treatment is available for advanced PCa, there is an urgent need to develop new and more effective therapeutic strategies. In order to optimize treatment outcome, especially in high risk PCa patients, therapy of PCa is moving rapidly towards personalization. Medical imaging, including positron emission tomography (PET)/computed tomography (CT), plays an important role in personalized medicine in oncology. In the recent years, much focus has been on prostate specific membrane antigen (PSMA) as a promising target for imaging and therapy with radionuclides, since it is upregulated in most PCa. In the prostate, one potential role for PSMA PET imaging is to help guiding focal therapy. Several studies have shown great potential of PSMA PET/CT for initial staging, lymph node staging, and detection of recurrence of PCa, even at very low PSA values after primary therapy. Furthermore, studies have shown that PSMA PET/CT has a higher detection rate than choline PET/CT. Radiolabeled PSMA ligands for therapy show promise in several studies with metastatic PCa, and is an area of active investigation. The “Image and treat” strategy, with radiolabeled PSMA ligands, has the potential to improve the treatment outcome of PCa patients, and is paving the way for precision medicine in PCa. The aim of this review is to give an overview of recent advancement in PSMA PET and radionuclide therapy of PCa. PMID:27825432

A deviation based assessment methodology for multiple machine health patterns classification and fault detection

NASA Astrophysics Data System (ADS)

Jia, Xiaodong; Jin, Chao; Buzza, Matt; Di, Yuan; Siegel, David; Lee, Jay

2018-01-01

Successful applications of Diffusion Map (DM) in machine failure detection and diagnosis have been reported in several recent studies. DM provides an efficient way to visualize the high-dimensional, complex and nonlinear machine data, and thus suggests more knowledge about the machine under monitoring. In this paper, a DM based methodology named as DM-EVD is proposed for machine degradation assessment, abnormality detection and diagnosis in an online fashion. Several limitations and challenges of using DM for machine health monitoring have been analyzed and addressed. Based on the proposed DM-EVD, a deviation based methodology is then proposed to include more dimension reduction methods. In this work, the incorporation of Laplacian Eigen-map and Principal Component Analysis (PCA) are explored, and the latter algorithm is named as PCA-Dev and is validated in the case study. To show the successful application of the proposed methodology, case studies from diverse fields are presented and investigated in this work. Improved results are reported by benchmarking with other machine learning algorithms.

Health status monitoring for ICU patients based on locally weighted principal component analysis.

PubMed

Ding, Yangyang; Ma, Xin; Wang, Youqing

2018-03-01

Intelligent status monitoring for critically ill patients can help medical stuff quickly discover and assess the changes of disease and then make appropriate treatment strategy. However, general-type monitoring model now widely used is difficult to adapt the changes of intensive care unit (ICU) patients' status due to its fixed pattern, and a more robust, efficient and fast monitoring model should be developed to the individual. A data-driven learning approach combining locally weighted projection regression (LWPR) and principal component analysis (PCA) is firstly proposed and applied to monitor the nonlinear process of patients' health status in ICU. LWPR is used to approximate the complex nonlinear process with local linear models, in which PCA could be further applied to status monitoring, and finally a global weighted statistic will be acquired for detecting the possible abnormalities. Moreover, some improved versions are developed, such as LWPR-MPCA and LWPR-JPCA, which also have superior performance. Eighteen subjects were selected from the Physiobank's Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) database, and two vital signs of each subject were chosen for online monitoring. The proposed method was compared with several existing methods including traditional PCA, Partial least squares (PLS), just in time learning combined with modified PCA (L-PCA), and Kernel PCA (KPCA). The experimental results demonstrated that the mean fault detection rate (FDR) of PCA can be improved by 41.7% after adding LWPR. The mean FDR of LWPR-MPCA was increased by 8.3%, compared with the latest reported method L-PCA. Meanwhile, LWPR spent less training time than others, especially KPCA. LWPR is first introduced into ICU patients monitoring and achieves the best monitoring performance including adaptability to changes in patient status, sensitivity for abnormality detection as well as its fast learning speed and low computational complexity. The algorithm is an excellent approach to establishing a personalized model for patients, which is the mainstream direction of modern medicine in the following development, as well as improving the global monitoring performance. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Quantitative assessment of the mechanical properties of prostate tissue with optical coherence elastography

NASA Astrophysics Data System (ADS)

Ling, Yuting; Li, Chunhui; Zhou, Kanheng; Guan, Guangying; Lang, Stephen; McGloin, David; Nabi, Ghulam; Huang, Zhihong

2018-02-01

Prostate cancer (PCa) is a heterogeneous disease with multifocal origin. In current clinical care, the Gleason scoring system is the well-established diagnosis by microscopic evaluation of the tissue from trans-rectal ultrasound (TRUS) guided biopsies. Nevertheless, the sensitivity and specificity in detecting PCa can range from 40 to 50% for conventional TRUS B-mode imaging. Tissue elasticity is associated with the disease progression and elastography technique has recently shown promise in aiding PCa diagnosis. However, many cancer foci in the prostate gland has very small size less than 1 mm and those detected by medical elastography were larger than 2 mm. Hereby, we introduce optical coherence elastography (OCE) to quantify the prostate stiffness with high resolution in the magnitude of 10 µm. Following our feasibility study of 10 patients reported previously, we recruited 60 more patients undergoing 12-core TRUS guided biopsies for suspected PCa with a total of 720 biopsies. The stiffness of cancer tissue was approximately 57.63% higher than that of benign ones. Using histology as reference standard and cut-off threshold of 600kPa, the data analysis showed sensitivity and specificity of 89.6% and 99.8% respectively. The method also demonstrated potential in characterising different grades of PCa based on the change of tissue morphology and quantitative mechanical properties. In conclusion, quantitative OCE can be a reliable technique to identify PCa lesion and differentiate indolent from aggressive cancer.

Prostatitis, other genitourinary infections and prostate cancer: results from a population-based case-control study.

PubMed

Boehm, Katharina; Valdivieso, Roger; Meskawi, Malek; Larcher, Alessandro; Schiffmann, Jonas; Sun, Maxine; Graefen, Markus; Saad, Fred; Parent, Marie-Élise; Karakiewicz, Pierre I

2016-03-01

We relied on a population-based case-control study (PROtEuS) to examine a potential association between the presence of histologically confirmed prostate cancer (PCa) and history of genitourinary infections, e.g., prostatitis, urethritis, orchitis and epididymitis. Cases were 1933 men with incident PCa, diagnosed across Montreal hospitals between 2005 and 2009. Population controls were 1994 men from the same residential area and age distribution. In-person interviews collected information about socio-demographic characteristics, lifestyle and medical history, e.g., self-reported history of several genitourinary infections, as well as on PCa screening. Logistic regression analyses tested overall and grade-specific associations, including subgroup analyses with frequent PSA testing. After multivariable adjustment, prostatitis was associated with an increased risk of any PCa (OR 1.81 [1.44-2.27]), but not urethritis (OR 1.05 [0.84-1.30]), orchitis (OR 1.28 [0.92-1.78]) or epididymitis (OR 0.98 [0.57-1.68]). The association between prostatitis and PCa was more pronounced for low-grade PCa (Gleason ≤ 6: OR 2.11 [1.61-2.77]; Gleason ≥ 7: OR 1.59 [1.22-2.07]). Adjusting for frequency of physician visits, PSA testing frequency or restricting analyses to frequently screened subjects did not affect these results. Prostatitis was associated with an increased probability for detecting PCa even after adjustment for frequency of PSA testing and physician visits, but not urethritis, orchitis or epididymitis. These considerations may be helpful in clinical risk stratification of individuals in whom the risk of PCa is pertinent.

Nanotechnology-Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer

DTIC Science & Technology

2016-08-01

1 AD _________________ AWARD NUMBER: W81XWH-15-1-0157 TITLE: Nanotechnology -Based Detection of Novel microRNAs for Early Diagnosis of Prostate...DATES COVERED 15 Jul 2015 - 14 Jul 2016 4. TITLE AND SUBTITLE Nanotechnology -Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer...the expression level of deregulated miRNAs in mouse and human PCa tissues as well as serum samples using an advanced nanotechnology -based sensing

Molecular profiling of ETS and non‐ETS aberrations in prostate cancer patients from northern India

PubMed Central

Kunju, Lakshmi P.; Carskadon, Shannon L.; Pandey, Swaroop K.; Singh, Geetika; Pradeep, Immanuel; Tandon, Vini; Singhai, Atin; Goel, Apul; Amit, Sonal; Agarwal, Asha; Dinda, Amit K.; Seth, Amlesh; Tsodikov, Alexander; Chinnaiyan, Arul M.; Palanisamy, Nallasivam

2015-01-01

Abstract BACKGROUND Molecular stratification of prostate cancer (PCa) based on genetic aberrations including ETS or RAF gene‐rearrangements, PTEN deletion, and SPINK1 over‐expression show clear prognostic and diagnostic utility. Gene rearrangements involving ETS transcription factors are frequent pathogenetic somatic events observed in PCa. Incidence of ETS rearrangements in Caucasian PCa patients has been reported, however, occurrence in Indian population is largely unknown. The aim of this study was to determine the prevalence of the ETS and RAF kinase gene rearrangements, SPINK1 over‐expression, and PTEN deletion in this cohort. METHODS In this multi‐center study, formalin‐fixed paraffin embedded (FFPE) PCa specimens (n = 121) were procured from four major medical institutions in India. The tissues were sectioned and molecular profiling was done using immunohistochemistry (IHC), RNA in situ hybridization (RNA‐ISH) and/or fluorescence in situ hybridization (FISH). RESULTS ERG over‐expression was detected in 48.9% (46/94) PCa specimens by IHC, which was confirmed in a subset of cases by FISH. Among other ETS family members, while ETV1 transcript was detected in one case by RNA‐ISH, no alteration in ETV4 was observed. SPINK1 over‐expression was observed in 12.5% (12/96) and PTEN deletion in 21.52% (17/79) of the total PCa cases. Interestingly, PTEN deletion was found in 30% of the ERG‐positive cases (P = 0.017) but in only one case with SPINK1 over‐expression (P = 0.67). BRAF and RAF1 gene rearrangements were detected in ∼1% and ∼4.5% of the PCa cases, respectively. CONCLUSIONS This is the first report on comprehensive molecular profiling of the major spectrum of the causal aberrations in Indian men with PCa. Our findings suggest that ETS gene rearrangement and SPINK1 over‐expression patterns in North Indian population largely resembled those observed in Caucasian population but differed from Japanese and Chinese PCa patients. The molecular profiling data presented in this study could help in clinical decision‐making for the pursuit of surgery, diagnosis, and in selection of therapeutic intervention. Prostate 75:1051–1062, 2015. © 2015 The Authors. The Prostate, published by Wiley Periodicals, Inc. PMID:25809148

Comparative Study of Blood-Based Biomarkers, α2,3-Sialic Acid PSA and PHI, for High-Risk Prostate Cancer Detection.

PubMed

Ferrer-Batallé, Montserrat; Llop, Esther; Ramírez, Manel; Aleixandre, Rosa Núria; Saez, Marc; Comet, Josep; de Llorens, Rafael; Peracaula, Rosa

2017-04-17

Prostate Specific Antigen (PSA) is the most commonly used serum marker for prostate cancer (PCa), although it is not specific and sensitive enough to allow the differential diagnosis of the more aggressive tumors. For that, new diagnostic methods are being developed, such as PCA-3, PSA isoforms that have resulted in the 4K score or the Prostate Health Index (PHI), and PSA glycoforms. In the present study, we have compared the PHI with our recently developed PSA glycoform assay, based on the determination of the α2,3-sialic acid percentage of serum PSA (% α2,3-SA), in a cohort of 79 patients, which include 50 PCa of different grades and 29 benign prostate hyperplasia (BPH) patients. The % α2,3-SA could distinguish high-risk PCa patients from the rest of patients better than the PHI (area under the curve (AUC) of 0.971 vs. 0.840), although the PHI correlated better with the Gleason score than the % α2,3-SA. The combination of both markers increased the AUC up to 0.985 resulting in 100% sensitivity and 94.7% specificity to differentiate high-risk PCa from the other low and intermediate-risk PCa and BPH patients. These results suggest that both serum markers complement each other and offer an improved diagnostic tool to identify high-risk PCa, which is an important requirement for guiding treatment decisions.

Characterizing the molecular features of ERG-positive tumors in primary and castration resistant prostate cancer

PubMed Central

Roudier, Martine P; Winters, Brian R; Coleman, Ilsa; Lam, Hung-Ming; Zhang, Xiaotun; Coleman, Roger; Chéry, Lisly; True, Lawrence D.; Higano, Celestia S.; Montgomery, Bruce; Lange, Paul H.; Snyder, Linda A.; Srivistava, Shiv; Corey, Eva; Vessella, Robert L.; Nelson, Peter S.; Üren, Aykut; Morrissey, Colm

2017-01-01

Background The TMPRSS2-ERG gene fusion is detected in approximately half of primary prostate cancers (PCa) yet the prognostic significance remains unclear. We hypothesized that ERG promotes the expression of common genes in primary PCa and metastatic castration-resistant PCa (CRPC), with the objective of identifying ERG-associated pathways, which may promote the transition from primary PCa to CRPC. Methods We constructed tissue microarrays (TMA) from 127 radical prostatectomy specimens, 20 LuCaP patient-derived xenografts (PDX), and 152 CRPC metastases obtained immediately at time of death. Nuclear ERG was assessed by immunohistochemistry (IHC). To characterize the molecular features of ERG-expressing PCa, a subset of IHC confirmed ERG+ or ERG-specimens including 11 radical prostatectomies, 20 LuCaP PDXs, and 45 CRPC metastases underwent gene expression analysis. Genes were ranked based on expression in primary PCa and CRPC. Common genes of interest were targeted for IHC analysis and expression compared with biochemical recurrence (BCR) status. Results IHC revealed that 43% of primary PCa, 35% of the LuCaP PDXs, and 18% of the CRPC metastases were ERG+ (12 of 48 patients [25%] had at least 1 ERG+ metastasis). Based on gene expression data and previous literature, two proteins involved in calcium signaling (NCALD, CACNA1D), a protein involved in inflammation (HLA-DMB), CD3 positive immune cells, and a novel ERG-associated protein, DCLK1 were evaluated in primary PCa and CRPC metastases. In ERG+ primary PCa, a weak association was seen with NCALD and CACNA1D protein expression. HLA-DMB expression and the presence of CD3 positive immune cells were decreased in CRPC metastases compared to primary PCa. DCLK1 was upregulated at the protein level in unpaired ERG+ primary PCa and CRPC metastases (p=0.0013 and p<0.0001, respectively). In primary PCa, ERG status or expression of targeted proteins was not associated with BCR-free survival. However for primary PCa, ERG+DCLK1+ patients exhibited shorter time to BCR (p=0.06) compared with ERG+DCLK1- patients. Conclusions This study examined ERG expression in primary PCa and CRPC. We have identified altered levels of inflammatory mediators associated with ERG expression. We determined expression of DCLK1 correlates with ERG expression and may play a role in primary PCa progression to metastatic CPRC. PMID:26990456

Potential of non-invasive esophagus cancer detection based on urine surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Huang, Shaohua; Wang, Lan; Chen, Weisheng; Feng, Shangyuan; Lin, Juqiang; Huang, Zufang; Chen, Guannan; Li, Buhong; Chen, Rong

2014-11-01

Non-invasive esophagus cancer detection based on urine surface-enhanced Raman spectroscopy (SERS) analysis was presented. Urine SERS spectra were measured on esophagus cancer patients (n = 56) and healthy volunteers (n = 36) for control analysis. Tentative assignments of the urine SERS spectra indicated some interesting esophagus cancer-specific biomolecular changes, including a decrease in the relative content of urea and an increase in the percentage of uric acid in the urine of esophagus cancer patients compared to that of healthy subjects. Principal component analysis (PCA) combined with linear discriminant analysis (LDA) was employed to analyze and differentiate the SERS spectra between normal and esophagus cancer urine. The diagnostic algorithms utilizing a multivariate analysis method achieved a diagnostic sensitivity of 89.3% and specificity of 83.3% for separating esophagus cancer samples from normal urine samples. These results from the explorative work suggested that silver nano particle-based urine SERS analysis coupled with PCA-LDA multivariate analysis has potential for non-invasive detection of esophagus cancer.

Incidental Prostate Adenocarcinoma in Cystoprostatectomy Specimens: Partial Versus Complete Prostate Sampling.

PubMed

Filter, Emily R; Gabril, Manal Y; Gomez, Jose A; Wang, Peter Z T; Chin, Joseph L; Izawa, Jonathan; Moussa, Madeleine

2017-08-01

The rate of incidental prostate adenocarcinoma (PCa) detection in radical cystoprostatectomy (RCP) varies widely, ranging from 15% to 54%. Such variability may be explained by institutional differences in prostate grossing protocols. Either partial or complete submission of the prostate gland in RCP may result in detection of clinically insignificant or significant incidental PCa. The aim of the study was to compare the clinical significance of PCa in RCP specimens in partial versus complete sampling. Seventy-two out of 158 RCP cases showed incidental PCa. The pathologic features, including Gleason score, margin status, extraprostatic extension (EPE), seminal vesicle invasion (SVI), PCa stage, and tumor volume, were assessed. The 72 cases were divided into partial (n = 21, 29.1%) and complete sampling (n = 51, 70.8%) groups. EPE was detected in 13/72 (18.1%) with 11/13 (84.6%) cases in the complete group. Positive margins were present in 11/72 (15.3%) with 9/11 (81.8%) in the complete group. SVI was detected in 4/72 (5.6%) with 3/4 (75.0%) in the complete group. Overall, 4/72 (5.6%) had a Gleason score >7, all of which were in the complete group. Our data suggest that complete sampling of the prostate may be the ideal approach to grossing RCP specimens, allowing for greater detection of clinically significant incidental PCa.

Neural-network-based state of health diagnostics for an automated radioxenon sampler/analyzer

NASA Astrophysics Data System (ADS)

Keller, Paul E.; Kangas, Lars J.; Hayes, James C.; Schrom, Brian T.; Suarez, Reynold; Hubbard, Charles W.; Heimbigner, Tom R.; McIntyre, Justin I.

2009-05-01

Artificial neural networks (ANNs) are used to determine the state-of-health (SOH) of the Automated Radioxenon Analyzer/Sampler (ARSA). ARSA is a gas collection and analysis system used for non-proliferation monitoring in detecting radioxenon released during nuclear tests. SOH diagnostics are important for automated, unmanned sensing systems so that remote detection and identification of problems can be made without onsite staff. Both recurrent and feed-forward ANNs are presented. The recurrent ANN is trained to predict sensor values based on current valve states, which control air flow, so that with only valve states the normal SOH sensor values can be predicted. Deviation between modeled value and actual is an indication of a potential problem. The feed-forward ANN acts as a nonlinear version of principal components analysis (PCA) and is trained to replicate the normal SOH sensor values. Because of ARSA's complexity, this nonlinear PCA is better able to capture the relationships among the sensors than standard linear PCA and is applicable to both sensor validation and recognizing off-normal operating conditions. Both models provide valuable information to detect impending malfunctions before they occur to avoid unscheduled shutdown. Finally, the ability of ANN methods to predict the system state is presented.

Diagnostic potential for gold nanoparticle-based surface-enhanced Raman spectroscopy to provide colorectal cancer screening using blood serum sample

NASA Astrophysics Data System (ADS)

Lin, Duo; Feng, Shangyuan; Pan, Jianji; Chen, Yanping; Lin, Juqiang; Sun, Liqing; Chen, Rong

2011-11-01

Surface-enhanced Raman spectroscopy (SERS) is a vibrational spectroscopic technique that is capable of probing the biomolecular changes associated with diseased transformation. The objective of our study was to explore gold nanoparticle based SERS to obtain blood serum biochemical information for non-invasive colorectal cancer detection. SERS measurements were performed on two groups of blood serum samples: one group from patients (n = 38) with pathologically confirmed colorectal cancer and the other group from healthy volunteers (control subjects, n = 45). Tentative assignments of the Raman bands in the measured SERS spectra suggested interesting cancer specific biomolecular changes, including an increase in the relative amounts of nucleic acid, a decrease in the percentage of saccharide and proteins contents in the blood serum of colorectal cancer patients as compared to that of healthy subjects. Principal component analysis (PCA) of the measured SERS spectra separated the spectral features of the two groups into two distinct clusters with little overlaps. Linear discriminate analysis (LDA) based on the PCA generated features differentiated the nasopharyngeal cancer SERS spectra from normal SERS spectra with high sensitivity (97.4%) and specificity (100%). The results from this exploratory study demonstrated that gold nanoparticle based SERS serum analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of colorectal cancers.

Diagnostic potential for gold nanoparticle-based surface-enhanced Raman spectroscopy to provide colorectal cancer screening using blood serum sample

NASA Astrophysics Data System (ADS)

Lin, Duo; Feng, Shangyuan; Pan, Jianji; Chen, Yanping; Lin, Juqiang; Sun, Liqing; Chen, Rong

2012-03-01

Surface-enhanced Raman spectroscopy (SERS) is a vibrational spectroscopic technique that is capable of probing the biomolecular changes associated with diseased transformation. The objective of our study was to explore gold nanoparticle based SERS to obtain blood serum biochemical information for non-invasive colorectal cancer detection. SERS measurements were performed on two groups of blood serum samples: one group from patients (n = 38) with pathologically confirmed colorectal cancer and the other group from healthy volunteers (control subjects, n = 45). Tentative assignments of the Raman bands in the measured SERS spectra suggested interesting cancer specific biomolecular changes, including an increase in the relative amounts of nucleic acid, a decrease in the percentage of saccharide and proteins contents in the blood serum of colorectal cancer patients as compared to that of healthy subjects. Principal component analysis (PCA) of the measured SERS spectra separated the spectral features of the two groups into two distinct clusters with little overlaps. Linear discriminate analysis (LDA) based on the PCA generated features differentiated the nasopharyngeal cancer SERS spectra from normal SERS spectra with high sensitivity (97.4%) and specificity (100%). The results from this exploratory study demonstrated that gold nanoparticle based SERS serum analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of colorectal cancers.

Are concurrent systematic cores needed at the time of targeted biopsy in patients with prior negative prostate biopsies?

PubMed

Albisinni, S; Aoun, F; Noel, A; El Rassy, E; Lemort, M; Paesmans, M; van Velthoven, R; Roumeguère, T; Peltier, A

2018-01-01

MRI-guided targeted biopsies are advised in patients who have undergone an initial series of negative systematic biopsies, in whom prostate cancer (PCa) suspicion remains elevated. The aim of the study was to evaluate whether, in men with prior negative prostate biopsies, systematic cores are also warranted at the time of an MRI-targeted repeat biopsy. We enrolled patients with prior negative biopsy undergoing real time MRI/TRUS fusion guided prostate biopsy at our institute between 2014 and 2016. Patients with at least one index lesion on multiparametric MRI were included. All eligible patients underwent both systematic random biopsies (12-14 cores) and targeted biopsies (2-4 cores). The study included 74 men with a median age of 65 years, PSA level of 9.27ng/mL, and prostatic volume of 45ml. The overall PCa detection rate and the clinically significant cancer detection rate were 56.7% and 39.2%, respectively. Targeted cores demonstrated similar clinically significant PCa detection rate compared to systematic cores (33.8% vs. 28.4%, P=0.38) with significantly less tissue sampling. Indeed, a combination approach was significantly superior to a targeted-only in overall PCa detection (+16.7% overall detection rate, P=0.007). Although differences in clinically significant PCa detection were statistically non-significant (P=0.13), a combination approach did allow detecting 7 extra clinically significant PCas (+13.8%). In patients with elevated PSA and prior negative biopsies, concurrent systematic sampling may be needed at the time of targeted biopsy in order to maximize PCa detection rate. Larger studies are needed to validate our findings. 4. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

PCA method for automated detection of mispronounced words

NASA Astrophysics Data System (ADS)

Ge, Zhenhao; Sharma, Sudhendu R.; Smith, Mark J. T.

2011-06-01

This paper presents a method for detecting mispronunciations with the aim of improving Computer Assisted Language Learning (CALL) tools used by foreign language learners. The algorithm is based on Principle Component Analysis (PCA). It is hierarchical with each successive step refining the estimate to classify the test word as being either mispronounced or correct. Preprocessing before detection, like normalization and time-scale modification, is implemented to guarantee uniformity of the feature vectors input to the detection system. The performance using various features including spectrograms and Mel-Frequency Cepstral Coefficients (MFCCs) are compared and evaluated. Best results were obtained using MFCCs, achieving up to 99% accuracy in word verification and 93% in native/non-native classification. Compared with Hidden Markov Models (HMMs) which are used pervasively in recognition application, this particular approach is computational efficient and effective when training data is limited.

Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model.

PubMed

Lin, Yuxin; Chen, Feifei; Shen, Li; Tang, Xiaoyu; Du, Cui; Sun, Zhandong; Ding, Huijie; Chen, Jiajia; Shen, Bairong

2018-05-21

Prostate cancer (PCa) is a fatal malignant tumor among males in the world and the metastasis is a leading cause for PCa death. Biomarkers are therefore urgently needed to detect PCa metastatic signature at the early time. MicroRNAs are small non-coding RNAs with the potential to be biomarkers for disease prediction. In addition, computer-aided biomarker discovery is now becoming an attractive paradigm for precision diagnosis and prognosis of complex diseases. In this study, we identified key microRNAs as biomarkers for predicting PCa metastasis based on network vulnerability analysis. We first extracted microRNAs and mRNAs that were differentially expressed between primary PCa and metastatic PCa (MPCa) samples. Then we constructed the MPCa-specific microRNA-mRNA network and screened microRNA biomarkers by a novel bioinformatics model. The model emphasized the characterization of systems stability changes and the network vulnerability with three measurements, i.e. the structurally single-line regulation, the functional importance of microRNA targets and the percentage of transcription factor genes in microRNA unique targets. With this model, we identified five microRNAs as putative biomarkers for PCa metastasis. Among them, miR-101-3p and miR-145-5p have been previously reported as biomarkers for PCa metastasis and the remaining three, i.e. miR-204-5p, miR-198 and miR-152, were screened as novel biomarkers for PCa metastasis. The results were further confirmed by the assessment of their predictive power and biological function analysis. Five microRNAs were identified as candidate biomarkers for predicting PCa metastasis based on our network vulnerability analysis model. The prediction performance, literature exploration and functional enrichment analysis convinced our findings. This novel bioinformatics model could be applied to biomarker discovery for other complex diseases.

Vision-based method for detecting driver drowsiness and distraction in driver monitoring system

NASA Astrophysics Data System (ADS)

Jo, Jaeik; Lee, Sung Joo; Jung, Ho Gi; Park, Kang Ryoung; Kim, Jaihie

2011-12-01

Most driver-monitoring systems have attempted to detect either driver drowsiness or distraction, although both factors should be considered for accident prevention. Therefore, we propose a new driver-monitoring method considering both factors. We make the following contributions. First, if the driver is looking ahead, drowsiness detection is performed; otherwise, distraction detection is performed. Thus, the computational cost and eye-detection error can be reduced. Second, we propose a new eye-detection algorithm that combines adaptive boosting, adaptive template matching, and blob detection with eye validation, thereby reducing the eye-detection error and processing time significantly, which is hardly achievable using a single method. Third, to enhance eye-detection accuracy, eye validation is applied after initial eye detection, using a support vector machine based on appearance features obtained by principal component analysis (PCA) and linear discriminant analysis (LDA). Fourth, we propose a novel eye state-detection algorithm that combines appearance features obtained using PCA and LDA, with statistical features such as the sparseness and kurtosis of the histogram from the horizontal edge image of the eye. Experimental results showed that the detection accuracies of the eye region and eye states were 99 and 97%, respectively. Both driver drowsiness and distraction were detected with a success rate of 98%.

Classification of clinical significance of MRI prostate findings using 3D convolutional neural networks

NASA Astrophysics Data System (ADS)

Mehrtash, Alireza; Sedghi, Alireza; Ghafoorian, Mohsen; Taghipour, Mehdi; Tempany, Clare M.; Wells, William M.; Kapur, Tina; Mousavi, Parvin; Abolmaesumi, Purang; Fedorov, Andriy

2017-03-01

Prostate cancer (PCa) remains a leading cause of cancer mortality among American men. Multi-parametric magnetic resonance imaging (mpMRI) is widely used to assist with detection of PCa and characterization of its aggressiveness. Computer-aided diagnosis (CADx) of PCa in MRI can be used as clinical decision support system to aid radiologists in interpretation and reporting of mpMRI. We report on the development of a convolution neural network (CNN) model to support CADx in PCa based on the appearance of prostate tissue in mpMRI, conducted as part of the SPIE-AAPM-NCI PROSTATEx challenge. The performance of different combinations of mpMRI inputs to CNN was assessed and the best result was achieved using DWI and DCE-MRI modalities together with the zonal information of the finding. On the test set, the model achieved an area under the receiver operating characteristic curve of 0.80.

A Systematic Review and Meta-analysis of the Diagnostic Accuracy of Prostate Health Index and 4-Kallikrein Panel Score in Predicting Overall and High-grade Prostate Cancer.

PubMed

Russo, Giorgio Ivan; Regis, Federica; Castelli, Tommaso; Favilla, Vincenzo; Privitera, Salvatore; Giardina, Raimondo; Cimino, Sebastiano; Morgia, Giuseppe

2017-08-01

Markers for prostate cancer (PCa) have progressed over recent years. In particular, the prostate health index (PHI) and the 4-kallikrein (4K) panel have been demonstrated to improve the diagnosis of PCa. We aimed to review the diagnostic accuracy of PHI and the 4K panel for PCa detection. We performed a systematic literature search of PubMed, EMBASE, Cochrane, and Academic One File databases until July 2016. We included diagnostic accuracy studies that used PHI or 4K panel for the diagnosis of PCa or high-grade PCa. The methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Twenty-eight studies including 16,762 patients have been included for the analysis. The pooled data showed a sensitivity of 0.89 and 0.74 for PHI and 4K panel, respectively, for PCa detection and a pooled specificity of 0.34 and 0.60 for PHI and 4K panel, respectively. The derived area under the curve (AUC) from the hierarchical summary receiver operating characteristic (HSROC) showed an accuracy of 0.76 and 0.72 for PHI and 4K panel respectively. For high-grade PCa detection, the pooled sensitivity was 0.93 and 0.87 for PHI and 4K panel, respectively, whereas the pooled specificity was 0.34 and 0.61 for PHI and 4K panel, respectively. The derived AUC from the HSROC showed an accuracy of 0.82 and 0.81 for PHI and 4K panel, respectively. Both PHI and the 4K panel provided good diagnostic accuracy in detecting overall and high-grade PCa. Copyright © 2016 Elsevier Inc. All rights reserved.

Prostate-specific membrane antigen targeted imaging and therapy of prostate cancer using a PSMA inhibitor as a homing ligand.

PubMed

Kularatne, Sumith A; Wang, Kevin; Santhapuram, Hari-Krishna R; Low, Philip S

2009-01-01

Prostate cancer (PCa) is a major cause of mortality and morbidity in Western society today. Current methods for detecting PCa are limited, leaving most early malignancies undiagnosed and sites of metastasis in advanced disease undetected. Major deficiencies also exist in the treatment of PCa, especially metastatic disease. In an effort to improve both detection and therapy of PCa, we have developed a PSMA-targeted ligand that delivers attached imaging and therapeutic agents selectively to PCa cells without targeting normal cells. The PSMA-targeted radioimaging agent (DUPA-(99m)Tc) was found to bind PSMA-positive human PCa cells (LNCaP cell line) with nanomolar affinity (K(D) = 14 nM). Imaging and biodistribution studies revealed that DUPA-(99m)Tc localizes primarily to LNCaP cell tumor xenografts in nu/nu mice (% injected dose/gram = 11.3 at 4 h postinjection; tumor-to-muscle ratio = 75:1). Two PSMA-targeted optical imaging agents (DUPA-FITC and DUPA-rhodamine B) were also shown to efficiently label PCa cells and to internalize and traffic to intracellular endosomes. A PSMA-targeted chemotherapeutic agent (DUPA-TubH) was demonstrated to kill PSMA-positive LNCaP cells in culture (IC(50) = 3 nM) and to eliminate established tumor xenografts in nu/nu mice with no detectable weight loss. Blockade of tumor targeting upon administration of excess PSMA inhibitor (PMPA) and the absence of targeting to PSMA-negative tumors confirmed the specificity of each of the above targeted reagents for PSMA. Tandem use of the imaging and therapeutic agents targeted to the same receptor could allow detection, staging, monitoring, and treatment of PCa with improved accuracy and efficacy.

Hetero-bivalent Imaging Agents for Simultaneous Targeting Prostate-Specific Membrane Antigen (PSMA) and Hepsin

DTIC Science & Technology

2013-09-01

Suzuki cross-coupling reaction. The effects of solvent and base on the synthesis of 3 were studied using Pd(PPh3)4 as catalyst . DMF, ethanol, and DMSO...PSMA/hepsin for in vitro cell uptake and in vivo imaging studies . Compound 13 showed a low but detectable increased cell uptake into the developed...have been comprehensive clinical studies whether PSA testing is an efficient biomarker in diagnosing PCa and reducing PCa deaths. Two European studies

Metformin effects on biochemical recurrence and metabolic signaling in the prostate.

PubMed

Winters, Brian; Plymate, Stephen; Zeliadt, Steven B; Holt, Sarah; Zhang, Xiaotun; Hu, Elaine; Lin, Daniel W; Morrissey, Colm; Wooldridge, Bryan; Gore, John L; Porter, Michael P; Wright, Jonathan L

2015-11-01

Metformin has received considerable attention as a potential anti-cancer agent. Animal and in-vitro prostate cancer (PCa) models have demonstrated decreased tumor growth with metformin, however the precise mechanisms are unknown. We examine the effects of metformin on PCa biochemical recurrence (BCR) in a large clinical database followed by evaluating metabolic signaling changes in a cohort of men undergoing prostate needle biopsy (PNB). Men treated for localized PCa were identified in a comprehensive clinical database between 2001 and 2010. Cox regression was performed to determine association with BCR relative to metformin use. We next identified a separate case-control cohort of men undergoing prostate needle biopsy (PNB) stratified by metformin use. Differences in mean IHC scores were compared with linear regression for phosphorylated IR, IGF-IR, AKT, and AMPK. One thousand seven hundred and thirty four men were evaluated for BCR with mean follow up of 41 months (range 1-121 months). "Ever" metformin use was not associated with BCR (HR 1.12, 0.77-1.65), however men reporting both pre/post-treatment metformin use had a 45% reduction in BCR (HR = 0.55 (0.31-0.96)). For the tissue-based study, 48 metformin users and 42 controls underwent PNB. Significantly greater staining in phosphorylated nuclear (p-IR, p-AKT) and cytoplasmic (p-IR, p-IGF-1R) insulin signaling proteins were seen in patients with PCa detected compared to those with negative PNB (P-values all <0.006). When stratified by metformin use, IGF-1R remained significantly elevated (P = 0.01) in men with PCa detected whereas p-AMPK (P = 0.05) was elevated only in those without PCa. Metformin use is associated with reduced BCR after treatment of localized PCa when considering pre-diagnostic and cumulative dosing. In men with cancer detected on PNB, insulin signaling markers were significantly elevated compared to negative PNB patients. The finding of IGF-1R elevation in positive PNBs versus p-AMPK elevation in negative PNBs suggests altered metabolic pathway activation precipitated by metformin use. © 2015 Wiley Periodicals, Inc.

Metformin Effects on Biochemical Recurrence and Metabolic Signaling in the Prostate

PubMed Central

Winters, Brian; Plymate, Stephen; Zeliadt, Steven B; Holt, Sarah; Zhang, Xiaotun; Hu, Elaine; Lin, Daniel W.; Morrissey, Colm; Wooldridge, Bryan; Gore, John L; Porter, Michael P; Wright, Jonathan L

2015-01-01

Background Metformin has received considerable attention as a potential anti-cancer agent. Animal and in-vitro prostate cancer (PCa) models have demonstrated decreased tumor growth with metformin, however the precise mechanisms are unknown. We examine the effects of metformin on PCa biochemical recurrence (BCR) in a large clinical database followed by evaluating metabolic signaling changes in a cohort of men undergoing prostate needle biopsy (PNB). Methods Men treated for localized PCa were identified in a comprehensive clinical database between 2001 and 2010. Cox regression was performed to determine association with BCR relative to metformin use. We next identified a separate case-control cohort of men undergoing prostate needle biopsy (PNB) stratified by metformin use. Differences in mean IHC scores were compared with linear regression for phosphorylated IR, IGF-IR, AKT, and AMPK. Results 1,734 men were evaluated for BCR with mean follow up of 41 months (range 1-121 months). ‘Ever’ metformin use was not associated with BCR (HR 1.12, 0.77-1.65), however men reporting both pre/post-treatment metformin use had a 45% reduction in BCR (HR=0.55 (0.31-0.96)). For the tissue-based study, 48 metformin users and 42 controls underwent PNB. Significantly greater staining in phosphorylated nuclear (p-IR, p-AKT) and cytoplasmic (p-IR, p-IGF-1R) insulin signaling proteins were seen in patients with PCa detected compared to those with negative PNB (p-values all < 0.006). When stratified by metformin use, IGF-1R remained significantly elevated (p=0.01) in men with PCa detected whereas p-AMPK (p=0.05) was elevated only in those without PCa. Conclusion Metformin use is associated with reduced BCR after treatment of localized PCa when considering pre-diagnostic and cumulative dosing. In men with cancer detected on PNB, insulin signaling markers were significantly elevated compared to negative PNB patients. The finding of IGF-1R elevation in positive PNBs versus p-AMPK elevation in negative PNBs suggests altered metabolic pathway activation precipitated by metformin use. PMID:26201966

Using the prostate imaging reporting and data system version 2 (PI-RIDS v2) to detect prostate cancer can prevent unnecessary biopsies and invasive treatment.

PubMed

Liu, Chang; Liu, Shi-Liang; Wang, Zhi-Xian; Yu, Kai; Feng, Chun-Xiang; Ke, Zan; Wang, Liang; Zeng, Xiao-Yong

2018-04-13

Prostate cancer (PCa) is one of the most common cancers among men globally. The authors aimed to evaluate the ability of the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) to classify men with PCa, clinically significant PCa (CSPCa), or no PCa, especially among those with serum total prostate-specific antigen (tPSA) levels in the "gray zone" (4-10 ng ml -1 ). A total of 308 patients (355 lesions) were enrolled in this study. Diagnostic efficiency was determined. Univariate and multivariate analyses, receiver operating characteristic curve analysis, and decision curve analysis were performed to determine and compare the predictors of PCa and CSPCa. The results suggested that PI-RADS v2, tPSA, and prostate-specific antigen density (PSAD) were independent predictors of PCa and CSPCa. A PI-RADS v2 score ≥4 provided high negative predictive values (91.39% for PCa and 95.69% for CSPCa). A model of PI-RADS combined with PSA and PSAD helped to define a high-risk group (PI-RADS score = 5 and PSAD ≥0.15 ng ml -1 cm -3 , with tPSA in the gray zone, or PI-RADS score ≥4 with high tPSA level) with a detection rate of 96.1% for PCa and 93.0% for CSPCa while a low-risk group with a detection rate of 6.1% for PCa and 2.2% for CSPCa. It was concluded that the PI-RADS v2 could be used as a reliable and independent predictor of PCa and CSPCa. The combination of PI-RADS v2 score with PSA and PSAD could be helpful in the prediction and diagnosis of PCa and CSPCa and, thus, may help in preventing unnecessary invasive procedures.

A new statistical PCA-ICA algorithm for location of R-peaks in ECG.

PubMed

Chawla, M P S; Verma, H K; Kumar, Vinod

2008-09-16

The success of ICA to separate the independent components from the mixture depends on the properties of the electrocardiogram (ECG) recordings. This paper discusses some of the conditions of independent component analysis (ICA) that could affect the reliability of the separation and evaluation of issues related to the properties of the signals and number of sources. Principal component analysis (PCA) scatter plots are plotted to indicate the diagnostic features in the presence and absence of base-line wander in interpreting the ECG signals. In this analysis, a newly developed statistical algorithm by authors, based on the use of combined PCA-ICA for two correlated channels of 12-channel ECG data is proposed. ICA technique has been successfully implemented in identifying and removal of noise and artifacts from ECG signals. Cleaned ECG signals are obtained using statistical measures like kurtosis and variance of variance after ICA processing. This analysis also paper deals with the detection of QRS complexes in electrocardiograms using combined PCA-ICA algorithm. The efficacy of the combined PCA-ICA algorithm lies in the fact that the location of the R-peaks is bounded from above and below by the location of the cross-over points, hence none of the peaks are ignored or missed.

Genome-wide copy number analysis reveals candidate gene loci that confer susceptibility to high-grade prostate cancer.

PubMed

Poniah, Prevathe; Mohd Zain, Shamsul; Abdul Razack, Azad Hassan; Kuppusamy, Shanggar; Karuppayah, Shankar; Sian Eng, Hooi; Mohamed, Zahurin

2017-09-01

Two key issues in prostate cancer (PCa) that demand attention currently are the need for a more precise and minimally invasive screening test owing to the inaccuracy of prostate-specific antigen and differential diagnosis to distinguish advanced vs. indolent cancers. This continues to pose a tremendous challenge in diagnosis and prognosis of PCa and could potentially lead to overdiagnosis and overtreatment complications. Copy number variations (CNVs) in the human genome have been linked to various carcinomas including PCa. Detection of these variants may improve clinical treatment as well as an understanding of the pathobiology underlying this complex disease. To this end, we undertook a pilot genome-wide CNV analysis approach in 36 subjects (18 patients with high-grade PCa and 18 controls that were matched by age and ethnicity) in search of more accurate biomarkers that could potentially explain susceptibility toward high-grade PCa. We conducted this study using the array comparative genomic hybridization technique. Array results were validated in 92 independent samples (46 high-grade PCa, 23 benign prostatic hyperplasia, and 23 healthy controls) using polymerase chain reaction-based copy number counting method. A total of 314 CNV regions were found to be unique to PCa subjects in this cohort (P<0.05). A log 2 ratio-based copy number analysis revealed 5 putative rare or novel CNV loci or both associated with susceptibility to PCa. The CNV gain regions were 1q21.3, 15q15, 7p12.1, and a novel CNV in PCa 12q23.1, harboring ARNT, THBS1, SLC5A8, and DDC genes that are crucial in the p53 and cancer pathways. A CNV loss and deletion event was observed at 8p11.21, which contains the SFRP1 gene from the Wnt signaling pathway. Cross-comparison analysis with genes associated to PCa revealed significant CNVs involved in biological processes that elicit cancer pathogenesis via cytokine production and endothelial cell proliferation. In conclusion, we postulated that the CNVs identified in this study could provide an insight into the development of advanced PCa. Copyright © 2017 Elsevier Inc. All rights reserved.

Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) Significantly Improve Prostate Cancer Detection at Initial Biopsy in a Total PSA Range of 2–10 ng/ml

PubMed Central

Perdonà, Sisto; Marino, Ada; Mazzarella, Claudia; Perruolo, Giuseppe; D’Esposito, Vittoria; Cosimato, Vincenzo; Buonerba, Carlo; Di Lorenzo, Giuseppe; Musi, Gennaro; De Cobelli, Ottavio; Chun, Felix K.; Terracciano, Daniela

2013-01-01

Many efforts to reduce prostate specific antigen (PSA) overdiagnosis and overtreatment have been made. To this aim, Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) have been proposed as new more specific biomarkers. We evaluated the ability of phi and PCA3 to identify prostate cancer (PCa) at initial prostate biopsy in men with total PSA range of 2–10 ng/ml. The performance of phi and PCA3 were evaluated in 300 patients undergoing first prostate biopsy. ROC curve analyses tested the accuracy (AUC) of phi and PCA3 in predicting PCa. Decision curve analyses (DCA) were used to compare the clinical benefit of the two biomarkers. We found that the AUC value of phi (0.77) was comparable to those of %p2PSA (0.76) and PCA3 (0.73) with no significant differences in pairwise comparison (%p2PSA vs phi p = 0.673, %p2PSA vs. PCA3 p = 0.417 and phi vs. PCA3 p = 0.247). These three biomarkers significantly outperformed fPSA (AUC = 0.60), % fPSA (AUC = 0.62) and p2PSA (AUC = 0.63). At DCA, phi and PCA3 exhibited a very close net benefit profile until the threshold probability of 25%, then phi index showed higher net benefit than PCA3. Multivariable analysis showed that the addition of phi and PCA3 to the base multivariable model (age, PSA, %fPSA, DRE, prostate volume) increased predictive accuracy, whereas no model improved single biomarker performance. Finally we showed that subjects with active surveillance (AS) compatible cancer had significantly lower phi and PCA3 values (p<0.001 and p = 0.01, respectively). In conclusion, both phi and PCA3 comparably increase the accuracy in predicting the presence of PCa in total PSA range 2–10 ng/ml at initial biopsy, outperforming currently used %fPSA. PMID:23861782

Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) significantly improve prostate cancer detection at initial biopsy in a total PSA range of 2-10 ng/ml.

PubMed

Ferro, Matteo; Bruzzese, Dario; Perdonà, Sisto; Marino, Ada; Mazzarella, Claudia; Perruolo, Giuseppe; D'Esposito, Vittoria; Cosimato, Vincenzo; Buonerba, Carlo; Di Lorenzo, Giuseppe; Musi, Gennaro; De Cobelli, Ottavio; Chun, Felix K; Terracciano, Daniela

2013-01-01

Many efforts to reduce prostate specific antigen (PSA) overdiagnosis and overtreatment have been made. To this aim, Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) have been proposed as new more specific biomarkers. We evaluated the ability of phi and PCA3 to identify prostate cancer (PCa) at initial prostate biopsy in men with total PSA range of 2-10 ng/ml. The performance of phi and PCA3 were evaluated in 300 patients undergoing first prostate biopsy. ROC curve analyses tested the accuracy (AUC) of phi and PCA3 in predicting PCa. Decision curve analyses (DCA) were used to compare the clinical benefit of the two biomarkers. We found that the AUC value of phi (0.77) was comparable to those of %p2PSA (0.76) and PCA3 (0.73) with no significant differences in pairwise comparison (%p2PSA vs phi p = 0.673, %p2PSA vs. PCA3 p = 0.417 and phi vs. PCA3 p = 0.247). These three biomarkers significantly outperformed fPSA (AUC = 0.60), % fPSA (AUC = 0.62) and p2PSA (AUC = 0.63). At DCA, phi and PCA3 exhibited a very close net benefit profile until the threshold probability of 25%, then phi index showed higher net benefit than PCA3. Multivariable analysis showed that the addition of phi and PCA3 to the base multivariable model (age, PSA, %fPSA, DRE, prostate volume) increased predictive accuracy, whereas no model improved single biomarker performance. Finally we showed that subjects with active surveillance (AS) compatible cancer had significantly lower phi and PCA3 values (p<0.001 and p = 0.01, respectively). In conclusion, both phi and PCA3 comparably increase the accuracy in predicting the presence of PCa in total PSA range 2-10 ng/ml at initial biopsy, outperforming currently used %fPSA.

Fault Detection of Bearing Systems through EEMD and Optimization Algorithm

PubMed Central

Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2017-01-01

This study proposes a fault detection and diagnosis method for bearing systems using ensemble empirical mode decomposition (EEMD) based feature extraction, in conjunction with particle swarm optimization (PSO), principal component analysis (PCA), and Isomap. First, a mathematical model is assumed to generate vibration signals from damaged bearing components, such as the inner-race, outer-race, and rolling elements. The process of decomposing vibration signals into intrinsic mode functions (IMFs) and extracting statistical features is introduced to develop a damage-sensitive parameter vector. Finally, PCA and Isomap algorithm are used to classify and visualize this parameter vector, to separate damage characteristics from healthy bearing components. Moreover, the PSO-based optimization algorithm improves the classification performance by selecting proper weightings for the parameter vector, to maximize the visualization effect of separating and grouping of parameter vectors in three-dimensional space. PMID:29143772

[Determination of the Plant Origin of Licorice Oil Extract, a Natural Food Additive, by Principal Component Analysis Based on Chemical Components].

PubMed

Tada, Atsuko; Ishizuki, Kyoko; Sugimoto, Naoki; Yoshimatsu, Kayo; Kawahara, Nobuo; Suematsu, Takako; Arifuku, Kazunori; Fukai, Toshio; Tamura, Yukiyoshi; Ohtsuki, Takashi; Tahara, Maiko; Yamazaki, Takeshi; Akiyama, Hiroshi

2015-01-01

"Licorice oil extract" (LOE) (antioxidant agent) is described in the notice of Japanese food additive regulations as a material obtained from the roots and/or rhizomes of Glycyrrhiza uralensis, G. inflata or G. glabra. In this study, we aimed to identify the original Glycyrrhiza species of eight food additive products using LC/MS. Glabridin, a characteristic compound in G. glabra, was specifically detected in seven products, and licochalcone A, a characteristic compound in G. inflata, was detected in one product. In addition, Principal Component Analysis (PCA) (a kind of multivariate analysis) using the data of LC/MS or (1)H-NMR analysis was performed. The data of thirty-one samples, including LOE products used as food additives, ethanol extracts of various Glycyrrhiza species and commercially available Glycyrrhiza species-derived products were assessed. Based on the PCA results, the majority of LOE products was confirmed to be derived from G. glabra. This study suggests that PCA using (1)H-NMR analysis data is a simple and useful method to identify the plant species of origin of natural food additive products.

Characterizing the molecular features of ERG-positive tumors in primary and castration resistant prostate cancer.

PubMed

Roudier, Martine P; Winters, Brian R; Coleman, Ilsa; Lam, Hung-Ming; Zhang, Xiaotun; Coleman, Roger; Chéry, Lisly; True, Lawrence D; Higano, Celestia S; Montgomery, Bruce; Lange, Paul H; Snyder, Linda A; Srivastava, Shiv; Corey, Eva; Vessella, Robert L; Nelson, Peter S; Üren, Aykut; Morrissey, Colm

2016-06-01

The TMPRSS2-ERG gene fusion is detected in approximately half of primary prostate cancers (PCa) yet the prognostic significance remains unclear. We hypothesized that ERG promotes the expression of common genes in primary PCa and metastatic castration-resistant PCa (CRPC), with the objective of identifying ERG-associated pathways, which may promote the transition from primary PCa to CRPC. We constructed tissue microarrays (TMA) from 127 radical prostatectomy specimens, 20 LuCaP patient-derived xenografts (PDX), and 152 CRPC metastases obtained immediately at time of death. Nuclear ERG was assessed by immunohistochemistry (IHC). To characterize the molecular features of ERG-expressing PCa, a subset of IHC confirmed ERG+ or ERG- specimens including 11 radical prostatectomies, 20 LuCaP PDXs, and 45 CRPC metastases underwent gene expression analysis. Genes were ranked based on expression in primary PCa and CRPC. Common genes of interest were targeted for IHC analysis and expression compared with biochemical recurrence (BCR) status. IHC revealed that 43% of primary PCa, 35% of the LuCaP PDXs, and 18% of the CRPC metastases were ERG+ (12 of 48 patients [25%] had at least one ERG+ metastasis). Based on gene expression data and previous literature, two proteins involved in calcium signaling (NCALD, CACNA1D), a protein involved in inflammation (HLA-DMB), CD3 positive immune cells, and a novel ERG-associated protein, DCLK1 were evaluated in primary PCa and CRPC metastases. In ERG+ primary PCa, a weak association was seen with NCALD and CACNA1D protein expression. HLA-DMB association with ERG was decreased and CD3 cell number association with ERG was changed from positive to negative in CRPC metastases compared to primary PCa. DCLK1 was upregulated at the protein level in unpaired ERG+ primary PCa and CRPC metastases (P = 0.0013 and P < 0.0001, respectively). In primary PCa, ERG status or expression of targeted proteins was not associated with BCR-free survival. However, for primary PCa, ERG+DCLK1+ patients exhibited shorter time to BCR (P = 0.06) compared with ERG+DCLK1- patients. This study examined ERG expression in primary PCa and CRPC. We have identified altered levels of inflammatory mediators associated with ERG expression. We determined expression of DCLK1 correlates with ERG expression and may play a role in primary PCa progression to metastatic CPRC. Prostate 76:810-822, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Accuracy of the prostate health index versus the urinary prostate cancer antigen 3 score to predict overall and significant prostate cancer at initial biopsy.

PubMed

Seisen, Thomas; Rouprêt, Morgan; Brault, Didier; Léon, Priscilla; Cancel-Tassin, Géraldine; Compérat, Eva; Renard-Penna, Raphaële; Mozer, Pierre; Guechot, Jérome; Cussenot, Olivier

2015-01-01

It remains unclear whether the Prostate Health Index (PHI) or the urinary Prostate-Cancer Antigen 3 (PCA-3) score is more accurate at screening for prostate cancer (PCa). The aim of this study was to prospectively compare the accuracy of PHI and PCA-3 scores to predict overall and significant PCa in men undergoing an initial prostate biopsy. Double-blind assessments of PHI and PCA-3 were conducted by referent physicians in 138 patients who subsequently underwent trans-rectal ultrasound-guided prostate biopsy according to a 12-core scheme. Predictive accuracies of PHI and PCA-3 were assessed using AUC and compared according to the DeLong method. Diagnostic performances with usual cut-off values for positivity (i.e., PHI >40 and PCA-3 >35) were calculated, and odds ratios associated with predicting PCa overall and significant PCa as defined by pathological updated Epstein criteria (i.e., Gleason score ≥7, more than three positive cores, or >50% cancer involvement in any core) were estimated using logistic regression. Prevalences of overall and significant PCa were 44.9% and 28.3%, respectively. PCA-3 (AUC = 0.71) was the most accurate predictor of PCa overall, and significantly outperformed PHI (AUC = 0.65; P = 0.03). However, PHI (AUC = 0.80) remained the most accurate predictor when screening exclusively for significant PCa and significantly outperformed PCA-3 (AUC = 0.55; P = 0.03). Furthermore, PCA-3 >35 had the best accuracy, and positive or negative predictive values when screening for PCa overall whereas these diagnostic performances were greater for PHI >40 when exclusively screening for significant PCa. PHI > 40 combined with PCA-3 > 35 was more specific in both cases. In multivariate analyses, PCA-3 >35 (OR = 5.68; 95%CI = [2.21-14.59]; P < 0.001) was significantly correlated with the presence of PCa overall, but PHI >40 (OR = 9.60; 95%CI = [1.72-91.32]; P = 0.001) was the only independent predictor for detecting significant PCa. Although PCA-3 score is the best predictor for PCa overall at initial biopsy, our findings strongly indicate that PHI should be used for population-based screening to avoid over-diagnosis of indolent tumors that are unlikely to cause death. © 2014 Wiley Periodicals, Inc.

Evaluation of redundancy analysis to identify signatures of local adaptation.

PubMed

Capblancq, Thibaut; Luu, Keurcien; Blum, Michael G B; Bazin, Eric

2018-05-26

Ordination is a common tool in ecology that aims at representing complex biological information in a reduced space. In landscape genetics, ordination methods such as principal component analysis (PCA) have been used to detect adaptive variation based on genomic data. Taking advantage of environmental data in addition to genotype data, redundancy analysis (RDA) is another ordination approach that is useful to detect adaptive variation. This paper aims at proposing a test statistic based on RDA to search for loci under selection. We compare redundancy analysis to pcadapt, which is a nonconstrained ordination method, and to a latent factor mixed model (LFMM), which is a univariate genotype-environment association method. Individual-based simulations identify evolutionary scenarios where RDA genome scans have a greater statistical power than genome scans based on PCA. By constraining the analysis with environmental variables, RDA performs better than PCA in identifying adaptive variation when selection gradients are weakly correlated with population structure. Additionally, we show that if RDA and LFMM have a similar power to identify genetic markers associated with environmental variables, the RDA-based procedure has the advantage to identify the main selective gradients as a combination of environmental variables. To give a concrete illustration of RDA in population genomics, we apply this method to the detection of outliers and selective gradients on an SNP data set of Populus trichocarpa (Geraldes et al., 2013). The RDA-based approach identifies the main selective gradient contrasting southern and coastal populations to northern and continental populations in the northwestern American coast. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Prostate cancer incidence and newly diagnosed patient profile in Spain in 2010.

PubMed

Cózar, José M; Miñana, Bernardino; Gómez-Veiga, Francisco; Rodríguez-Antolín, Alfredo; Villavicencio, Humberto; Cantalapiedra, Arancha; Pedrosa, Emilio

2012-12-01

What's known on the subject? and What does the study add? Prostate cancer (PCa) accounts for 12% of newly diagnosed cases of cancer in Europe. It is one of the most frequently diagnosed tumours in the developed world. Since the introduction of prostate specific antigen as a test for early detection of PCa, the rate of diagnosis has increased significantly and specific mortality has reduced in most western countries. Most of the data on the incidence of PCa are obtained from population-based cancer registries which frequently do not cover the whole population. This first national hospital-based PCa registry aims not only to estimate the incidence of the disease but to ascertain the clinical profile of newly diagnosed PCa patients, a useful tool for evaluating the impact of the disease and its socio-health management. • To estimate the 2010 incidence of prostate cancer (PCa) in Spain. • To describe the clinical profile of newly diagnosed cases using a nationwide hospital-based registry. • This was a national epidemiological observational study in 25 public hospitals with a specific reference population according to the National Health System. • Sociodemographic and clinical variables of all newly diagnosed, histopathologically confirmed PCa cases were collected in 2010, in the area of influence of each centre. Cases diagnosed in private practice were not collected (estimated nearly 10% in Spain). • Data monitoring was external to guarantee quality and homogeneity. • The age-standardized PCa incidence was determined based on the age distribution of the European standard population. • In all, 4087 new cases of PCa were diagnosed for a reference population of 4933940 men (21.8% of the Spanish male population). • The estimated age-standardized PCa incidence was 70.75 cases per 100000 men. • Mean age at diagnosis was 69 years; 11.6% of patients presented with tumour-related symptoms and 39.5% with LUTS. Median PSA was 8 ng/mL. Gleason score was ≤ 6 in 56.5%, 7 in 26.7% and >7 in 16.8% of patients. At diagnosis, 89.8% had localized, 6.4% locally advanced and 3.8% metastatic disease. • This study on PCa incidence in Spain, a western country with intensive opportunistic PSA screening, shows that PCa is a high incidence tumour, diagnosed close to 70 years, usually asymptomatic. • Almost 40% of cases have low risk disease with a risk of over-diagnosis and over-treatment. • Around 55% of patients with intermediate or high risk disease are candidates for active therapy which may result in a reduction of cancer-specific mortality. © 2012 ASOCIACIÓN ESPANOLA UROLOGÍA.

Epigenetics in prostate cancer: biologic and clinical relevance.

PubMed

Jerónimo, Carmen; Bastian, Patrick J; Bjartell, Anders; Carbone, Giuseppina M; Catto, James W F; Clark, Susan J; Henrique, Rui; Nelson, William G; Shariat, Shahrokh F

2011-10-01

Prostate cancer (PCa) is one of the most common human malignancies and arises through genetic and epigenetic alterations. Epigenetic modifications include DNA methylation, histone modifications, and microRNAs (miRNA) and produce heritable changes in gene expression without altering the DNA coding sequence. To review progress in the understanding of PCa epigenetics and to focus upon translational applications of this knowledge. PubMed was searched for publications regarding PCa and DNA methylation, histone modifications, and miRNAs. Reports were selected based on the detail of analysis, mechanistic support of data, novelty, and potential clinical applications. Aberrant DNA methylation (hypo- and hypermethylation) is the best-characterized alteration in PCa and leads to genomic instability and inappropriate gene expression. Global and locus-specific changes in chromatin remodeling are implicated in PCa, with evidence suggesting a causative dysfunction of histone-modifying enzymes. MicroRNA deregulation also contributes to prostate carcinogenesis, including interference with androgen receptor signaling and apoptosis. There are important connections between common genetic alterations (eg, E twenty-six fusion genes) and the altered epigenetic landscape. Owing to the ubiquitous nature of epigenetic alterations, they provide potential biomarkers for PCa detection, diagnosis, assessment of prognosis, and post-treatment surveillance. Altered epigenetic gene regulation is involved in the genesis and progression of PCa. Epigenetic alterations may provide valuable tools for the management of PCa patients and be targeted by pharmacologic compounds that reverse their nature. The potential for epigenetic changes in PCa requires further exploration and validation to enable translation to the clinic. Copyright © 2011 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Expression of spermidine/spermine N(1) -acetyl transferase (SSAT) in human prostate tissues is related to prostate cancer progression and metastasis.

PubMed

Huang, Wei; Eickhoff, Jens C; Mehraein-Ghomi, Farideh; Church, Dawn R; Wilding, George; Basu, Hirak S

2015-08-01

Prostate cancer (PCa) in many patients remains indolent for the rest of their lives, but in some patients, it progresses to lethal metastatic disease. Gleason score is the current clinical method for PCa prognosis. It cannot reliably identify aggressive PCa, when GS is ≤ 7. It is shown that oxidative stress plays a key role in PCa progression. We have shown that in cultured human PCa cells, an activation of spermidine/spermine N(1) -acetyl transferase (SSAT; EC 2.3.1.57) enzyme initiates a polyamine oxidation pathway and generates copious amounts of reactive oxygen species in polyamine-rich PCa cells. We used RNA in situ hybridization and immunohistochemistry methods to detect SSAT mRNA and protein expression in two tissue microarrays (TMA) created from patient's prostate tissues. We analyzed 423 patient's prostate tissues in the two TMAs. Our data show that there is a significant increase in both SSAT mRNA and the enzyme protein in the PCa cells as compared to their benign counterpart. This increase is even more pronounced in metastatic PCa tissues as compared to the PCa localized in the prostate. In the prostatectomy tissues from early-stage patients, the SSAT protein level is also high in the tissues obtained from the patients who ultimately progress to advanced metastatic disease. Based on these results combined with published data from our and other laboratories, we propose an activation of an autocrine feed-forward loop of PCa cell proliferation in the absence of androgen as a possible mechanism of castrate-resistant prostate cancer growth. © 2015 Wiley Periodicals, Inc.

Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment

PubMed Central

Camacho Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis

2018-01-01

This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks. PMID:29762505

Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment.

PubMed

Camacho Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis; Quiroga, Jabid

2018-05-15

This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks.

Optimizing the clinical utility of PCA3 to diagnose prostate cancer in initial prostate biopsy.

PubMed

Rubio-Briones, Jose; Borque, Angel; Esteban, Luis M; Casanova, Juan; Fernandez-Serra, Antonio; Rubio, Luis; Casanova-Salas, Irene; Sanz, Gerardo; Domínguez-Escrig, Jose; Collado, Argimiro; Gómez-Ferrer, Alvaro; Iborra, Inmaculada; Ramírez-Backhaus, Miguel; Martínez, Francisco; Calatrava, Ana; Lopez-Guerrero, Jose A

2015-09-11

PCA3 has been included in a nomogram outperforming previous clinical models for the prediction of any prostate cancer (PCa) and high grade PCa (HGPCa) at the initial prostate biopsy (IBx). Our objective is to validate such IBx-specific PCA3-based nomogram. We also aim to optimize the use of this nomogram in clinical practice through the definition of risk groups. Independent external validation. Clinical and biopsy data from a contemporary cohort of 401 men with the same inclusion criteria to those used to build up the reference's nomogram in IBx. The predictive value of the nomogram was assessed by means of calibration curves and discrimination ability through the area under the curve (AUC). Clinical utility of the nomogram was analyzed by choosing thresholds points that minimize the overlapping between probability density functions (PDF) in PCa and no PCa and HGPCa and no HGPCa groups, and net benefit was assessed by decision curves. We detect 28% of PCa and 11 % of HGPCa in IBx, contrasting to the 46 and 20% at the reference series. Due to this, there is an overestimation of the nomogram probabilities shown in the calibration curve for PCa. The AUC values are 0.736 for PCa (C.I.95%:0.68-0.79) and 0.786 for HGPCa (C.I.95%:0.71-0.87) showing an adequate discrimination ability. PDF show differences in the distributions of nomogram probabilities in PCa and not PCa patient groups. A minimization of the overlapping between these curves confirms the threshold probability of harboring PCa >30 % proposed by Hansen is useful to indicate a IBx, but a cut-off > 40% could be better in series of opportunistic screening like ours. Similar results appear in HGPCa analysis. The decision curve also shows a net benefit of 6.31% for the threshold probability of 40%. PCA3 is an useful tool to select patients for IBx. Patients with a calculated probability of having PCa over 40% should be counseled to undergo an IBx if opportunistic screening is required.

Fast detection of Piscirickettsia salmonis in Salmo salar serum through MALDI-TOF-MS profiling.

PubMed

Olate, Verónica R; Nachtigall, Fabiane M; Santos, Leonardo S; Soto, Alex; Araya, Macarena; Oyanedel, Sandra; Díaz, Verónica; Marchant, Vanessa; Rios-Momberg, Mauricio

2016-03-01

Piscirickettsia salmonis is a pathogenic bacteria known as the aetiological agent of the salmonid rickettsial syndrome and causes a high mortality in farmed salmonid fishes. Detection of P. salmonis in farmed fishes is based mainly on molecular biology and immunohistochemistry techniques. These techniques are in most of the cases expensive and time consuming. In the search of new alternatives to detect the presence of P. salmonis in salmonid fishes, this work proposed the use of MALDI-TOF-MS to compare serum protein profiles from Salmo salar fish, including experimentally infected and non-infected fishes using principal component analysis (PCA). Samples were obtained from a controlled bioassay where S. salar was challenged with P. salmonis in a cohabitation model and classified according to the presence or absence of the bacteria by real time PCR analysis. MALDI spectra of the fish serum samples showed differences in its serum protein composition. These differences were corroborated with PCA analysis. The results demonstrated that the use of both MALDI-TOF-MS and PCA represents a useful tool to discriminate the fish status through the analysis of salmonid serum samples. Copyright © 2016 John Wiley & Sons, Ltd.

Coarse-to-fine markerless gait analysis based on PCA and Gauss-Laguerre decomposition

NASA Astrophysics Data System (ADS)

Goffredo, Michela; Schmid, Maurizio; Conforto, Silvia; Carli, Marco; Neri, Alessandro; D'Alessio, Tommaso

2005-04-01

Human movement analysis is generally performed through the utilization of marker-based systems, which allow reconstructing, with high levels of accuracy, the trajectories of markers allocated on specific points of the human body. Marker based systems, however, show some drawbacks that can be overcome by the use of video systems applying markerless techniques. In this paper, a specifically designed computer vision technique for the detection and tracking of relevant body points is presented. It is based on the Gauss-Laguerre Decomposition, and a Principal Component Analysis Technique (PCA) is used to circumscribe the region of interest. Results obtained on both synthetic and experimental tests provide significant reduction of the computational costs, with no significant reduction of the tracking accuracy.

A Positive Family History as risk factor for Prostate Cancer in a Population-based Study with organized PSA-Screening: Results of the Swiss ERSPC (Aarau)

PubMed Central

Randazzo, Marco; Müller, Alexander; Carlsson, Sigrid; Eberli, Daniel; Huber, Andreas; Grobholz, Rainer; Manka, Lukas; Mortezavi, Ashkan; Sulser, Tullio; Recker, Franz; Kwiatkowski, Maciej

2016-01-01

Objective To assess the value of positive family history (FH) as a risk factor for prostate cancer (PCa) incidence and grade among men undergoing organized PSA-screening in a population-based study. Patients and Methods The study cohort comprised all attendees of the Swiss arm of the European Randomized Study of Screening for Prostate Cancer (ERSPC) with systematic PSA-tests every 4 years. Men reporting first-degree relative(s) diagnosed with PCa were considered to have a positive FH. Biopsy was exclusively PSA-triggered with a threshold of 3 ng/ml. Primary endpoint was PCa diagnosis. Kaplan-Meier and Cox regression analyses were used. Results Of 4,932 attendees with a median age of 60.9 (IQR 57.6–65.1) years, 334 (6.8%) reported a positive FH. Median follow-up duration was 11.6 years (IQR 10.3–13.3). Cumulative PCa incidence was 60/334 (18%, positive FH) and 550/4,598 (12%, negative FH) (OR 1.6, 95% CI 1.2–2.2, p=0.001), respectively. In both groups, most PCa diagnosed had a low grade. There were no significant differences in PSA at diagnosis, biopsy Gleason score or Gleason score on pathologic specimen among men who underwent radical prostatectomy between both groups, respectively. On multivariable analysis, age (HR 1.04, 95% CI 1.02–1.06), baseline PSA (HR 1.13 95% CI 1.12–1.14), and FH (HR 1.6, CI 1.24–2.14) were independent predictors for overall PCa incidence (p<0.0001 each). Only baseline PSA (HR 1.14, 95% CI 1.12–1.16, p<0.0001) was an independent predictor of Gleason score ≥7 PCa on prostate biopsy. The proportion of interval PCa diagnosed in between the screening rounds was non-significantly different. Conclusion Irrespective of the FH status, the current PSA-based screening setting detects the majority of aggressive PCa and missed only a minority of interval cancers with a 4-year screening algorithm. Our results suggest that men with a positive FH are at increased risk for low grade but not aggressive PCa. PMID:26332304

Collaborative Review: Risk-Based Prostate Cancer Screening

PubMed Central

Zhu, Xiaoye; Albertsen, Peter C.; Andriole, Gerald L.; Roobol, Monique J.; Schröder, Fritz H.; Vickers, Andrew J.

2016-01-01

Context Widespread mass screening of prostate cancer (PCa) is not recommended because the balance between benefits and harms is still not well established. The achieved mortality reduction comes with considerable harm such as unnecessary biopsies, overdiagnoses, and overtreatment. Therefore, patient stratification with regard to PCa risk and aggressiveness is necessary to identify those men who are at risk and may actually benefit from early detection. Objective This review critically examines the current evidence regarding risk-based PCa screening. Evidence acquisition A search of the literature was performed using the Medline database. Further studies were selected based on manual searches of reference lists and review articles. Evidence synthesis Prostate-specific antigen (PSA) has been shown to be the single most significant predictive factor for identifying men at increased risk of developing PCa. Especially in men with no additional risk factors, PSA alone provides an appropriate marker up to 30 yr into the future. After assessment of an early PSA test, the screening frequency may be determined based on individualized risk. A limited list of additional factors such as age, comorbidity, prostate volume, family history, ethnicity, and previous biopsy status have been identified to modify risk and are important for consideration in routine practice. In men with a known PSA, risk calculators may hold the promise of identifying those who are at increased risk of having PCa and are therefore candidates for biopsy. Conclusions PSA testing may serve as the foundation for a more risk-based assessment. However, the decision to undergo early PSA testing should be a shared one between the patient and his physician based on information balancing its advantages and disadvantages. PMID:22134009

68Ga-PSMA PET/MR-Positive, Histopathology-Proven Prostate Cancer in a Patient With Negative Multiparametric Prostate MRI.

PubMed

Muehlematter, Urs J; Rupp, Niels J; Mueller, Julian; Eberli, Daniel; Burger, Irene A

2018-05-25

Multiparametric MRI incorporating T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced sequences is currently used for detection and localization of clinically important prostate cancer (PCa). The Ga-labeled PET tracer targeting the prostate-specific membrane antigen (PSMA, Ga-PSMA-11) is a promising diagnostic approach for staging and restating PCa. Recent studies suggest that Ga-PSMA could also be used for primary PCa detection and localization. We report a case of a Ga-PSMA PET/MR-positive lesion of the peripheral zone in a 73-year-old man with a negative preceding multiparametric MRI. Radical prostatectomy and subsequent histopathologic examination confirmed a Gleason 4 + 4 PCa.

Degradation of 1,1,2,2-tetrachloroethane in a freshwater tidal wetland: Field and laboratory evidence

USGS Publications Warehouse

Lorah, M.M.; Olsen, L.D.

1999-01-01

Degradation reactions controlling the fate of 1,1,2,2-tetrachloroethane (PCA) in a freshwater tidal wetland that is a discharge area for a contaminated aquifer were investigated by a combined field and laboratory study. Samples from nested piezometers and porous-membrane sampling devices (peepers) showed that PCA concentrations decreased and that less chlorinated daughter products formed as the groundwater became increasingly reducing along upward flow paths through the wetland sediments. The cis and trans isomers of 1,2-dichloroethylene (12DCE) and vinyl chloride (VC) were the predominant daughter products detected from degradation of PCA in the field and in microcosms constructed under methanogenic conditions. Significantly lower ratios of cis-12DCE to trans-12DCE were produced by PCA degradation than by degradation of trichloroethylene, a common co-contaminant with PCA. 1,1,2-Trichloroethane (112TCA) and 1,2-dichloroethane (12DCA) occurred simultaneously with 12DCE, indicating simultaneous hydrogenolysis and dichloroelimination of PCA. From an initial PCA concentration of about 1.5 ??mol/L, concentrations of PCA and its daughter products decreased to below detection within a 1.0-m vertical distance in the wetland sediments and within 34 days in the microcosms. The results indicate that natural attenuation of PCA through complete anaerobic biodegradation can occur in wetlands before sensitive surface water receptors are reached.

The Potential of MicroRNAs as Prostate Cancer Biomarkers.

PubMed

Fabris, Linda; Ceder, Yvonne; Chinnaiyan, Arul M; Jenster, Guido W; Sorensen, Karina D; Tomlins, Scott; Visakorpi, Tapio; Calin, George A

2016-08-01

Short noncoding RNAs known as microRNAs (miRNAs) control protein expression through the degradation of RNA or the inhibition of protein translation. The miRNAs influence a wide range of biologic processes and are often deregulated in cancer. This family of small RNAs constitutes potentially valuable markers for the diagnosis, prognosis, and therapeutic choices in prostate cancer (PCa) patients, as well as potential drugs (miRNA mimics) or drug targets (anti-miRNAs) in PCa management. To review the currently available data on miRNAs as biomarkers in PCa and as possible tools for early detection and prognosis. A systematic review was performed searching the PubMed database for articles in English using a combination of the following terms: microRNA, miRNA, cancer, prostate cancer, miRNA profiling, diagnosis, prognosis, therapy response, and predictive marker. We summarize the existing literature regarding the profiling of miRNA in PCa detection, prognosis, and response to therapy. The articles were reviewed with the main goal of finding a common recommendation that could be translated from bench to bedside in future clinical practice. The miRNAs are important regulators of biologic processes in PCa progression. A common expression profile characterizing each tumor subtype and stage has still not been identified for PCa, probably due to molecular heterogeneity as well as differences in study design and patient selection. Large-scale studies that should provide additional important information are still missing. Further studies, based on common clinical parameters and guidelines, are necessary to validate the translational potential of miRNAs in PCa clinical management. Such common signatures are promising in the field and emerge as potential biomarkers. The literature shows that microRNAs hold potential as novel biomarkers that could aid prostate cancer management, but additional studies with larger patient cohorts and common guidelines are necessary before clinical implementation. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Advances in prostate-specific membrane antigen PET of prostate cancer.

PubMed

Bouchelouche, Kirsten; Choyke, Peter L

2018-05-01

In recent years, a large number of reports have been published on prostate-specific membrane antigen (PSMA)/PET in prostate cancer (PCa). This review highlights advances in PSMA PET in PCa during the past year. PSMA PET/computed tomography (CT) is useful in detection of biochemical recurrence, especially at low prostate-specific antigen (PSA) values. The detection rate of PSMA PET is influenced by PSA level. For primary PCa, PSMA PET/CT shows promise for tumour localization in the prostate, especially in combination with multiparametric MRI (mpMRI). For primary staging, PSMA PET/CT can be used in intermediate and high-risk PCa. Intraoperative PSMA radioligand guidance seems promising for detection of malignant lymph nodes. While the use of PSMA PET/MRI in primary localized disease is limited to high and intermediate-risk patients and localized staging, in the recurrence setting, PET/MRI can be particularly helpful when the lesions are subtle. PSMA PET/CT is superior to choline PET/CT and other conventional imaging modalities. Molecular imaging with PSMA PET continues to pave the way for personalized medicine in PCa.However, large prospective clinical studies are still needed to fully evaluate the role of PSMA PET/CT and PET/MRI in the clinical workflow of PCa.

XMRV: A New Virus in Prostate Cancer?

PubMed Central

Aloia, Amanda L.; Sfanos, Karen S.; Isaacs, William B.; Zheng, Qizhi; Maldarelli, Frank; De Marzo, Angelo M.; Rein, Alan

2010-01-01

Several recent papers have reported the presence of a gammaretrovirus, termed “XMRV” (xenotropic murine leukemia virus-related virus) in prostate cancers (PCa). If confirmed, this could have enormous implications for the detection, prevention, and treatment of PCa. However, other papers report failure to detect XMRV in PCa. We tested nearly 800 PCa samples, using a combination of real-time PCR and immunohistochemistry (IHC). The PCR reactions were simultaneously monitored for amplification of a single-copy human gene, in order to confirm the quality of the sample DNA and its suitability for PCR. Controls demonstrated that the PCR assay could detect the XMRV in a single infected cell, even in the presence of a 10,000-fold excess of uninfected human cells. The IHC used two rabbit polyclonal antisera, each prepared against a purified MLV protein. Both antisera always stained XMRV-infected or – transfected cells, but never stained control cells. No evidence for XMRV in PCa was obtained in these experiments. We discuss possible explanations for the discrepancies in the results from different laboratories. It is possible that XMRV is not actually circulating in the human population; even if it is, the data do not seem to support a causal role for this virus in PCa. PMID:20966126

PSMA PET in prostate cancer – a step towards personalized medicine

PubMed Central

Bouchelouche, Kirsten; Choyke, Peter L.

2017-01-01

Purpose of review Increasing attention is being given to personalized medicine in oncology, where therapies are tailored to the particular characteristics of the individual cancer patient. In recent years, there has been greater focus on PSMA in prostate cancer (PCa) as a target for imaging and therapy with radionuclides. This review highlights the recent advancements in PSMA PET in PCa during the past year. Recent findings Several reports on PSMA PET/CT in PCa patients are demonstrating promising results, especially for detection of biochemical recurrence. 18F-PSMA PET/CT may be superior to 68Ga-PSMA PET/CT. The detection rate of PSMA PET is influenced by PSA level. PSMA PET/CT may have a higher detection rate than choline PET/CT. Only a few reports have been published on PSMA PET/MRI, and this modality remains to be elucidated further. Conclusion Molecular imaging with PSMA PET is paving the way for personalized medicine in PCa. However, large prospective clinical studies are needed to further evaluate the role of PSMA PET/CT and PET/MRI in the clinical workflow of PCa. PSMA is an excellent target for imaging and therapy with radionuclides, and the “image and treat” strategy has the potential to become a milestone in the management of PCa patients. PMID:26967720

Identification of Sarcosine as a Target Molecule for the Canine Olfactory Detection of Prostate Carcinoma.

PubMed

Pacik, Dalibor; Plevova, Mariana; Urbanova, Lucie; Lackova, Zuzana; Strmiska, Vladislav; Necas, Alois; Heger, Zbynek; Adam, Vojtech

2018-03-21

The hypothesis that dogs can detect malignant tumours through the identification of specific molecules is nearly 30 years old. To date, several reports have described the successful detection of distinct types of cancer. However, is still a lack of data regarding the specific molecules that can be recognized by a dog's olfactory apparatus. Hence, we performed a study with artificially prepared, well-characterized urinary specimens that were enriched with sarcosine, a widely reported urinary biomarker for prostate cancer (PCa). For the purposes of the study, a German shepherd dog was utilized for analyses of 60 positive and 120 negative samples. Our study provides the first evidence that a sniffer dog specially trained for the olfactory detection of PCa can recognize sarcosine in artificial urine with a performance [sensitivity of 90%, specificity of 95%, and precision of 90% for the highest amount of sarcosine (10 µmol/L)] that is comparable to the identification of PCa-diagnosed subjects (sensitivity of 93.5% and specificity of 91.6%). This study casts light on the unrevealed phenomenon of PCa olfactory detection and opens the door for further studies with canine olfactory detection and cancer diagnostics.

PCA-LBG-based algorithms for VQ codebook generation

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Yang, Po-Yuan

2015-04-01

Vector quantisation (VQ) codebooks are generated by combining principal component analysis (PCA) algorithms with Linde-Buzo-Gray (LBG) algorithms. All training vectors are grouped according to the projected values of the principal components. The PCA-LBG-based algorithms include (1) PCA-LBG-Median, which selects the median vector of each group, (2) PCA-LBG-Centroid, which adopts the centroid vector of each group, and (3) PCA-LBG-Random, which randomly selects a vector of each group. The LBG algorithm finds a codebook based on the better vectors sent to an initial codebook by the PCA. The PCA performs an orthogonal transformation to convert a set of potentially correlated variables into a set of variables that are not linearly correlated. Because the orthogonal transformation efficiently distinguishes test image vectors, the proposed PCA-LBG-based algorithm is expected to outperform conventional algorithms in designing VQ codebooks. The experimental results confirm that the proposed PCA-LBG-based algorithms indeed obtain better results compared to existing methods reported in the literature.

Mapping brain activity in gradient-echo functional MRI using principal component analysis

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Singh, Manbir; Don, Manuel

1997-05-01

The detection of sites of brain activation in functional MRI has been a topic of immense research interest and many technique shave been proposed to this end. Recently, principal component analysis (PCA) has been applied to extract the activated regions and their time course of activation. This method is based on the assumption that the activation is orthogonal to other signal variations such as brain motion, physiological oscillations and other uncorrelated noises. A distinct advantage of this method is that it does not require any knowledge of the time course of the true stimulus paradigm. This technique is well suited to EPI image sequences where the sampling rate is high enough to capture the effects of physiological oscillations. In this work, we propose and apply tow methods that are based on PCA to conventional gradient-echo images and investigate their usefulness as tools to extract reliable information on brain activation. The first method is a conventional technique where a single image sequence with alternating on and off stages is subject to a principal component analysis. The second method is a PCA-based approach called the common spatial factor analysis technique (CSF). As the name suggests, this method relies on common spatial factors between the above fMRI image sequence and a background fMRI. We have applied these methods to identify active brain ares during visual stimulation and motor tasks. The results from these methods are compared to those obtained by using the standard cross-correlation technique. We found good agreement in the areas identified as active across all three techniques. The results suggest that PCA and CSF methods have good potential in detecting the true stimulus correlated changes in the presence of other interfering signals.

A Mass Spectrometric Analysis Method Based on PPCA and SVM for Early Detection of Ovarian Cancer.

PubMed

Wu, Jiang; Ji, Yanju; Zhao, Ling; Ji, Mengying; Ye, Zhuang; Li, Suyi

2016-01-01

Background. Surfaced-enhanced laser desorption-ionization-time of flight mass spectrometry (SELDI-TOF-MS) technology plays an important role in the early diagnosis of ovarian cancer. However, the raw MS data is highly dimensional and redundant. Therefore, it is necessary to study rapid and accurate detection methods from the massive MS data. Methods. The clinical data set used in the experiments for early cancer detection consisted of 216 SELDI-TOF-MS samples. An MS analysis method based on probabilistic principal components analysis (PPCA) and support vector machine (SVM) was proposed and applied to the ovarian cancer early classification in the data set. Additionally, by the same data set, we also established a traditional PCA-SVM model. Finally we compared the two models in detection accuracy, specificity, and sensitivity. Results. Using independent training and testing experiments 10 times to evaluate the ovarian cancer detection models, the average prediction accuracy, sensitivity, and specificity of the PCA-SVM model were 83.34%, 82.70%, and 83.88%, respectively. In contrast, those of the PPCA-SVM model were 90.80%, 92.98%, and 88.97%, respectively. Conclusions. The PPCA-SVM model had better detection performance. And the model combined with the SELDI-TOF-MS technology had a prospect in early clinical detection and diagnosis of ovarian cancer.

Mortality Among Men with Advanced Prostate Cancer Excluded from the ProtecT Trial.

PubMed

Johnston, Thomas J; Shaw, Greg L; Lamb, Alastair D; Parashar, Deepak; Greenberg, David; Xiong, Tengbin; Edwards, Alison L; Gnanapragasam, Vincent; Holding, Peter; Herbert, Phillipa; Davis, Michael; Mizielinsk, Elizabeth; Lane, J Athene; Oxley, Jon; Robinson, Mary; Mason, Malcolm; Staffurth, John; Bollina, Prasad; Catto, James; Doble, Andrew; Doherty, Alan; Gillatt, David; Kockelbergh, Roger; Kynaston, Howard; Prescott, Steve; Paul, Alan; Powell, Philip; Rosario, Derek; Rowe, Edward; Donovan, Jenny L; Hamdy, Freddie C; Neal, David E

2017-03-01

Early detection and treatment of asymptomatic men with advanced and high-risk prostate cancer (PCa) may improve survival rates. To determine outcomes for men diagnosed with advanced PCa following prostate-specific antigen (PSA) testing who were excluded from the ProtecT randomised trial. Mortality was compared for 492 men followed up for a median of 7.4 yr to a contemporaneous cohort of men from the UK Anglia Cancer Network (ACN) and with a matched subset from the ACN. PCa-specific and all-cause mortality were compared using Kaplan-Meier analysis and Cox's proportional hazards regression. Of the 492 men excluded from the ProtecT cohort, 37 (8%) had metastases (N1, M0=5, M1=32) and 305 had locally advanced disease (62%). The median PSA was 17μg/l. Treatments included radical prostatectomy (RP; n=54; 11%), radiotherapy (RT; n=245; 50%), androgen deprivation therapy (ADT; n=122; 25%), other treatments (n=11; 2%), and unknown (n=60; 12%). There were 49 PCa-specific deaths (10%), of whom 14 men had received radical treatment (5%); and 129 all-cause deaths (26%). In matched ProtecT and ACN cohorts, 37 (9%) and 64 (16%), respectively, died of PCa, while 89 (22%) and 103 (26%) died of all causes. ProtecT men had a 45% lower risk of death from PCa compared to matched cases (hazard ratio 0.55, 95% confidence interval 0.38-0.83; p=0.0037), but mortality was similar in those treated radically. The nonrandomised design is a limitation. Men with PSA-detected advanced PCa excluded from ProtecT and treated radically had low rates of PCa death at 7.4-yr follow-up. Among men who underwent nonradical treatment, the ProtecT group had a lower rate of PCa death. Early detection through PSA testing, leadtime bias, and group heterogeneity are possible factors in this finding. Prostate cancer that has spread outside the prostate gland without causing symptoms can be detected via prostate-specific antigen testing and treated, leading to low rates of death from this disease. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Analyzing brain networks with PCA and conditional Granger causality.

PubMed

Zhou, Zhenyu; Chen, Yonghong; Ding, Mingzhou; Wright, Paul; Lu, Zuhong; Liu, Yijun

2009-07-01

Identifying directional influences in anatomical and functional circuits presents one of the greatest challenges for understanding neural computations in the brain. Granger causality mapping (GCM) derived from vector autoregressive models of data has been employed for this purpose, revealing complex temporal and spatial dynamics underlying cognitive processes. However, the traditional GCM methods are computationally expensive, as signals from thousands of voxels within selected regions of interest (ROIs) are individually processed, and being based on pairwise Granger causality, they lack the ability to distinguish direct from indirect connectivity among brain regions. In this work a new algorithm called PCA based conditional GCM is proposed to overcome these problems. The algorithm implements the following two procedures: (i) dimensionality reduction in ROIs of interest with principle component analysis (PCA), and (ii) estimation of the direct causal influences in local brain networks, using conditional Granger causality. Our results show that the proposed method achieves greater accuracy in detecting network connectivity than the commonly used pairwise Granger causality method. Furthermore, the use of PCA components in conjunction with conditional GCM greatly reduces the computational cost relative to the use of individual voxel time series. Copyright 2009 Wiley-Liss, Inc

Prostate cancer gene 3 and multiparametric magnetic resonance can reduce unnecessary biopsies: decision curve analysis to evaluate predictive models.

PubMed

Busetto, Gian Maria; De Berardinis, Ettore; Sciarra, Alessandro; Panebianco, Valeria; Giovannone, Riccardo; Rosato, Stefano; D'Errigo, Paola; Di Silverio, Franco; Gentile, Vincenzo; Salciccia, Stefano

2013-12-01

To overcome the well-known prostate-specific antigen limits, several new biomarkers have been proposed. Since its introduction in clinical practice, the urinary prostate cancer gene 3 (PCA3) assay has shown promising results for prostate cancer (PC) detection. Furthermore, multiparametric magnetic resonance imaging (mMRI) has the ability to better describe several aspects of PC. A prospective study of 171 patients with negative prostate biopsy findings and a persistent high prostate-specific antigen level was conducted to assess the role of mMRI and PCA3 in identifying PC. All patients underwent the PCA3 test and mMRI before a second transrectal ultrasound-guided prostate biopsy. The accuracy and reliability of PCA3 (3 different cutoff points) and mMRI were evaluated. Four multivariate logistic regression models were analyzed, in terms of discrimination and the cost benefit, to assess the clinical role of PCA3 and mMRI in predicting the biopsy outcome. A decision curve analysis was also plotted. Repeated transrectal ultrasound-guided biopsy identified 68 new cases (41.7%) of PC. The sensitivity and specificity of the PCA3 test and mMRI was 68% and 49% and 74% and 90%, respectively. Evaluating the regression models, the best discrimination (area under the curve 0.808) was obtained using the full model (base clinical model plus mMRI and PCA3). The decision curve analysis, to evaluate the cost/benefit ratio, showed good performance in predicting PC with the model that included mMRI and PCA3. mMRI increased the accuracy and sensitivity of the PCA3 test, and the use of the full model significantly improved the cost/benefit ratio, avoiding unnecessary biopsies. Copyright © 2013 Elsevier Inc. All rights reserved.

An Improved Pathological Brain Detection System Based on Two-Dimensional PCA and Evolutionary Extreme Learning Machine.

PubMed

Nayak, Deepak Ranjan; Dash, Ratnakar; Majhi, Banshidhar

2017-12-07

Pathological brain detection has made notable stride in the past years, as a consequence many pathological brain detection systems (PBDSs) have been proposed. But, the accuracy of these systems still needs significant improvement in order to meet the necessity of real world diagnostic situations. In this paper, an efficient PBDS based on MR images is proposed that markedly improves the recent results. The proposed system makes use of contrast limited adaptive histogram equalization (CLAHE) to enhance the quality of the input MR images. Thereafter, two-dimensional PCA (2DPCA) strategy is employed to extract the features and subsequently, a PCA+LDA approach is used to generate a compact and discriminative feature set. Finally, a new learning algorithm called MDE-ELM is suggested that combines modified differential evolution (MDE) and extreme learning machine (ELM) for segregation of MR images as pathological or healthy. The MDE is utilized to optimize the input weights and hidden biases of single-hidden-layer feed-forward neural networks (SLFN), whereas an analytical method is used for determining the output weights. The proposed algorithm performs optimization based on both the root mean squared error (RMSE) and norm of the output weights of SLFNs. The suggested scheme is benchmarked on three standard datasets and the results are compared against other competent schemes. The experimental outcomes show that the proposed scheme offers superior results compared to its counterparts. Further, it has been noticed that the proposed MDE-ELM classifier obtains better accuracy with compact network architecture than conventional algorithms.

Noninvasive detection of nasopharyngeal carcinoma based on saliva proteins using surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Lin, Xueliang; Lin, Duo; Ge, Xiaosong; Qiu, Sufang; Feng, Shangyuan; Chen, Rong

2017-10-01

The present study evaluated the capability of saliva analysis combining membrane protein purification with surface-enhanced Raman spectroscopy (SERS) for noninvasive detection of nasopharyngeal carcinoma (NPC). A rapid and convenient protein purification method based on cellulose acetate membrane was developed. A total of 659 high-quality SERS spectra were acquired from purified proteins extracted from the saliva samples of 170 patients with pathologically confirmed NPC and 71 healthy volunteers. Spectral analysis of those saliva protein SERS spectra revealed specific changes in some biochemical compositions, which were possibly associated with NPC transformation. Furthermore, principal component analysis combined with linear discriminant analysis (PCA-LDA) was utilized to analyze and classify the saliva protein SERS spectra from NPC and healthy subjects. Diagnostic sensitivity of 70.7%, specificity of 70.3%, and diagnostic accuracy of 70.5% could be achieved by PCA-LDA for NPC identification. These results show that this assay based on saliva protein SERS analysis holds promising potential for developing a rapid, noninvasive, and convenient clinical tool for NPC screening.

Prostate calculi in cancer and BPH in a cohort of Korean men: presence of calculi did not correlate with cancer risk

PubMed Central

Hwang, Eu-Chang; Choi, Hyang-Sik; Im, Chang-Min; Jung, Seung-Il; Kim, Sun-Ouck; Kang, Taek-Won; Kwon, Dong-Deuk; Park, Kwang-Sung; Ryu, Soo-Bang

2010-01-01

Prostatic calculi are common and are associated with inflammation of the prostate. Recently, it has been suggested that this inflammation may be associated with prostate carcinogenesis. The aim of this study was to investigate the relationship between prostatic calculi and prostate cancer (PCa) in prostate biopsy specimens. We retrospectively analyzed 417 consecutive patients who underwent transrectal ultrasonography (TRUS) and prostate biopsies between January 2005 and January 2008. Based on the biopsy findings, patients were divided into benign prostatic hyperplasia and PCa groups. TRUS was used to detect prostatic calculi and to measure prostate volume. The correlations between PCa risk and age, serum total PSA levels, prostate volume, and prostatic calculi were analyzed. Patient age and PSA, as well as the frequency of prostatic calculi in the biopsy specimens, differed significantly between both the groups (P < 0.05). In the PCa group, the Gleason scores (GSs) were higher in patients with prostatic calculi than in patients without prostatic calculi (P = 0.023). Using multivariate logistic regression analysis, we found that patient age, serum total PSA and prostate volume were risk factors for PCa (P = 0.001), but that the presence of prostatic calculi was not associated with an increased risk of PCa (P = 0.13). In conclusion, although the presence of prostatic calculi was not shown to be a risk factor for PCa, prostatic calculi were more common in patients with PCa and were associated with a higher GS among these men. PMID:20037598

Prospective randomized trial comparing magnetic resonance imaging (MRI)-guided in-bore biopsy to MRI-ultrasound fusion and transrectal ultrasound-guided prostate biopsy in patients with prior negative biopsies.

PubMed

Arsov, Christian; Rabenalt, Robert; Blondin, Dirk; Quentin, Michael; Hiester, Andreas; Godehardt, Erhard; Gabbert, Helmut E; Becker, Nikolaus; Antoch, Gerald; Albers, Peter; Schimmöller, Lars

2015-10-01

A significant proportion of prostate cancers (PCas) are missed by conventional transrectal ultrasound-guided biopsy (TRUS-GB). It remains unclear whether the combined approach using targeted magnetic resonance imaging (MRI)-ultrasound fusion-guided biopsy (FUS-GB) and systematic TRUS-GB is superior to targeted MRI-guided in-bore biopsy (IB-GB) for PCa detection. To compare PCa detection between IB-GB alone and FUS-GB + TRUS-GB in patients with at least one negative TRUS-GB and prostate-specific antigen ≥4 ng/ml. Patients were prospectively randomized after multiparametric prostate MRI to IB-GB (arm A) or FUS-GB + TRUS-GB (arm B) from November 2011 to July 2014. The study was powered at 80% to demonstrate an overall PCa detection rate of ≥60% in arm B compared to 40% in arm A. Secondary endpoints were the distribution of highest Gleason scores, the rate of detection of significant PCa (Gleason ≥7), the number of biopsy cores to detect one (significant) PCa, the positivity rate for biopsy cores, and tumor involvement per biopsy core. The study was halted after interim analysis because the primary endpoint was not met. The trial enrolled 267 patients, of whom 210 were analyzed (106 randomized to arm A and 104 to arm B). PCa detection was 37% in arm A and 39% in arm B (95% confidence interval for difference, -16% to 11%; p=0.7). Detection rates for significant PCa (29% vs 32%; p=0.7) and the highest percentage tumor involvement per biopsy core (48% vs 42%; p=0.4) were similar between the arms. The mean number of cores was 5.6 versus 17 (p<0.001). A limitation is the limited number of patients because of early cessation of accrual. This trial failed to identify an important improvement in detection rate for the combined biopsy approach over MRI-targeted biopsy alone. A prospective comparison between MRI-targeted biopsy alone and systematic TRUS-GB is justified. Our randomized study showed similar prostate cancer detection rates between targeted prostate biopsy guided by magnetic resonance imaging and the combination of targeted biopsy and systematic transrectal ultrasound-guided prostate biopsy. An important improvement in detection rates using the combined biopsy approach can be excluded. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Adaptive online monitoring for ICU patients by combining just-in-time learning and principal component analysis.

PubMed

Li, Xuejian; Wang, Youqing

2016-12-01

Offline general-type models are widely used for patients' monitoring in intensive care units (ICUs), which are developed by using past collected datasets consisting of thousands of patients. However, these models may fail to adapt to the changing states of ICU patients. Thus, to be more robust and effective, the monitoring models should be adaptable to individual patients. A novel combination of just-in-time learning (JITL) and principal component analysis (PCA), referred to learning-type PCA (L-PCA), was proposed for adaptive online monitoring of patients in ICUs. JITL was used to gather the most relevant data samples for adaptive modeling of complex physiological processes. PCA was used to build an online individual-type model and calculate monitoring statistics, and then to judge whether the patient's status is normal or not. The adaptability of L-PCA lies in the usage of individual data and the continuous updating of the training dataset. Twelve subjects were selected from the Physiobank's Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) database, and five vital signs of each subject were chosen. The proposed method was compared with the traditional PCA and fast moving-window PCA (Fast MWPCA). The experimental results demonstrated that the fault detection rates respectively increased by 20 % and 47 % compared with PCA and Fast MWPCA. L-PCA is first introduced into ICU patients monitoring and achieves the best monitoring performance in terms of adaptability to changes in patient status and sensitivity for abnormality detection.

The addition of a sagittal image fusion improves the prostate cancer detection in a sensor-based MRI /ultrasound fusion guided targeted biopsy.

PubMed

Günzel, Karsten; Cash, Hannes; Buckendahl, John; Königbauer, Maximilian; Asbach, Patrick; Haas, Matthias; Neymeyer, Jörg; Hinz, Stefan; Miller, Kurt; Kempkensteffen, Carsten

2017-01-13

To explore the diagnostic benefit of an additional image fusion of the sagittal plane in addition to the standard axial image fusion, using a sensor-based MRI/US fusion platform. During July 2013 and September 2015, 251 patients with at least one suspicious lesion on mpMRI (rated by PI-RADS) were included into the analysis. All patients underwent MRI/US targeted biopsy (TB) in combination with a 10 core systematic prostate biopsy (SB). All biopsies were performed on a sensor-based fusion system. Group A included 162 men who received TB by an axial MRI/US image fusion. Group B comprised 89 men in whom the TB was performed with an additional sagittal image fusion. The median age in group A was 67 years (IQR 61-72) and in group B 68 years (IQR 60-71). The median PSA level in group A was 8.10 ng/ml (IQR 6.05-14) and in group B 8.59 ng/ml (IQR 5.65-12.32). In group A the proportion of patients with a suspicious digital rectal examination (DRE) (14 vs. 29%, p = 0.007) and the proportion of primary biopsies (33 vs 46%, p = 0.046) were significantly lower. The rate of PI-RADS 3 lesions were overrepresented in group A compared to group B (19 vs. 9%; p = 0.044). Classified according to PI-RADS 3, 4 and 5, the detection rates of TB were 42, 48, 75% in group A and 25, 74, 90% in group B. The rate of PCa with a Gleason score ≥7 missed by TB was 33% (18 cases) in group A and 9% (5 cases) in group B; p-value 0.072. An explorative multivariate binary logistic regression analysis revealed that PI-RADS, a suspicious DRE and performing an additional sagittal image fusion were significant predictors for PCa detection in TB. 9 PCa were only detected by TB with sagittal fusion (sTB) and sTB identified 10 additional clinically significant PCa (Gleason ≥7). Performing an additional sagittal image fusion besides the standard axial fusion appears to improve the accuracy of the sensor-based MRI/US fusion platform.

Detection of circulatory microRNAs in prostate cancer.

PubMed

Srivastava, Anvesha; Goldberger, Helle; Afzal, Zainab; Suy, Simeng; Collins, Sean P; Kumar, Deepak

2015-01-01

Prostate cancer (PCa) is one of the most common cancer worldwide and accounts for 14.4 % of all new cancer cases. The clinical outcome and management of PCa can be significantly improved by use of biomarker assays for early detection, prognosis and also for prediction and monitoring of treatment response. MiRNAs are short, endogenous, single-stranded RNA molecules that play important role in regulation of gene expression and can modulate a number of cellular processes. Discovery of miRNAs in circulation has not only facilitated understanding their role in various diseases but also paved new avenues for biomarker discovery due to their ease of access and stability. The fact that a minimally invasive test based on miRNAs profiles can distinguish the presence or absence of disease illustrates immense potential of these molecules as predictive biomarkers.In this chapter, we have summarized the presumed mechanisms of miRNA release into the circulation and systematically summarized the studies of circulatory miRNAs in PCa. Also, we have mainly focused on the methodology of identification of circulatory miRNAs from biofluids.

Radar fall detection using principal component analysis

NASA Astrophysics Data System (ADS)

Jokanovic, Branka; Amin, Moeness; Ahmad, Fauzia; Boashash, Boualem

2016-05-01

Falls are a major cause of fatal and nonfatal injuries in people aged 65 years and older. Radar has the potential to become one of the leading technologies for fall detection, thereby enabling the elderly to live independently. Existing techniques for fall detection using radar are based on manual feature extraction and require significant parameter tuning in order to provide successful detections. In this paper, we employ principal component analysis for fall detection, wherein eigen images of observed motions are employed for classification. Using real data, we demonstrate that the PCA based technique provides performance improvement over the conventional feature extraction methods.

ERS-2 SAR and IRS-1C LISS III data fusion: A PCA approach to improve remote sensing based geological interpretation

NASA Astrophysics Data System (ADS)

Pal, S. K.; Majumdar, T. J.; Bhattacharya, Amit K.

Fusion of optical and synthetic aperture radar data has been attempted in the present study for mapping of various lithologic units over a part of the Singhbhum Shear Zone (SSZ) and its surroundings. ERS-2 SAR data over the study area has been enhanced using Fast Fourier Transformation (FFT) based filtering approach, and also using Frost filtering technique. Both the enhanced SAR imagery have been then separately fused with histogram equalized IRS-1C LISS III image using Principal Component Analysis (PCA) technique. Later, Feature-oriented Principal Components Selection (FPCS) technique has been applied to generate False Color Composite (FCC) images, from which corresponding geological maps have been prepared. Finally, GIS techniques have been successfully used for change detection analysis in the lithological interpretation between the published geological map and the fusion based geological maps. In general, there is good agreement between these maps over a large portion of the study area. Based on the change detection studies, few areas could be identified which need attention for further detailed ground-based geological studies.

Network intrusion detection based on a general regression neural network optimized by an improved artificial immune algorithm.

PubMed

Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

2015-01-01

To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data.

Latino Men and Familial Risk Communication about Prostate Cancer

PubMed Central

Hicks, Elisabeth M.; Litwin, Mark S.; Maliski, Sally L.

2014-01-01

Purpose This study investigated how familial communication about prostate cancer risk and screening affects sons of men with prostate cancer. It is important to engage Latino families shared decision making toward early detection because first degree relatives of men with PCa are at heightened risk and Latino men are diagnosed at more advanced stages of disease than Non-Hispanic White men. Methods The team conducted semi-structured interviews with seventeen sons of PCa survivors. Eight participants completed a follow up interview an average of seven months later. Therefore, our sample includes twenty-five transcripts. The sons are Latinos living in Southern California. Data were analyzed with a mix of a priori topical codes and grounded theory techniques. Results Sons were under informed about both familial risk and screening options. They became sensitized to PCa, desired information, and held protective intentions. Hopeful intentions came up against cultural taboos around sex, reproductive health, and intimacy that limited discussions between fathers and sons. Fathers were a valued source of information, but play various roles, which affect sons’ screening intentions. Open communication between father and son promoted awareness of screening and familial risk. Discussion Uncertainty about familial risk and screening options, especially early detection strategies, was exacerbated by cultural taboos around PCa. Fathers could have been primary and credible advocates for shared decision making, but sons found it difficult to learn from their fathers’ experience. Nursing Implications Findings from our study can inform community based interventions with Latino families, help to culturally tailor health messaging, and sensitize clinicians to a group which needs concerted counseling about PCa risk and screening. PMID:25158656

An Automated Micro-Total Immunoassay System for Measuring Cancer-Associated α2,3-linked Sialyl N-Glycan-Carrying Prostate-Specific Antigen May Improve the Accuracy of Prostate Cancer Diagnosis

PubMed Central

Ishikawa, Tomokazu; Yoneyama, Tohru; Tobisawa, Yuki; Hatakeyama, Shingo; Kurosawa, Tatsuo; Nakamura, Kenji; Narita, Shintaro; Mitsuzuka, Koji; Duivenvoorden, Wilhelmina; Pinthus, Jehonathan H.; Hashimoto, Yasuhiro; Koie, Takuya; Habuchi, Tomonori; Arai, Yoichi; Ohyama, Chikara

2017-01-01

The low specificity of the prostate-specific antigen (PSA) for early detection of prostate cancer (PCa) is a major issue worldwide. The aim of this study to examine whether the serum PCa-associated α2,3-linked sialyl N-glycan-carrying PSA (S2,3PSA) ratio measured by automated micro-total immunoassay systems (μTAS system) can be applied as a diagnostic marker of PCa. The μTAS system can utilize affinity-based separation involving noncovalent interaction between the immunocomplex of S2,3PSA and Maackia amurensis lectin to simultaneously determine concentrations of free PSA and S2,3PSA. To validate quantitative performance, both recombinant S2,3PSA and benign-associated α2,6-linked sialyl N-glycan-carrying PSA (S2,6PSA) purified from culture supernatant of PSA cDNA transiently-transfected Chinese hamster ovary (CHO)-K1 cells were used as standard protein. Between 2007 and 2016, fifty patients with biopsy-proven PCa were pair-matched for age and PSA levels, with the same number of benign prostatic hyperplasia (BPH) patients used to validate the diagnostic performance of serum S2,3PSA ratio. A recombinant S2,3PSA- and S2,6PSA-spiked sample was clearly discriminated by μTAS system. Limit of detection of S2,3PSA was 0.05 ng/mL and coefficient variation was less than 3.1%. The area under the curve (AUC) for detection of PCa for the S2,3PSA ratio (%S2,3PSA) with cutoff value 43.85% (AUC; 0.8340) was much superior to total PSA (AUC; 0.5062) using validation sample set. Although the present results are preliminary, the newly developed μTAS platform for measuring %S2,3PSA can achieve the required assay performance specifications for use in the practical and clinical setting and may improve the accuracy of PCa diagnosis. Additional validation studies are warranted. PMID:28241428

Simultaneous Treatment with Statins and Aspirin Reduces the Risk of Prostate Cancer Detection and Tumorigenic Properties in Prostate Cancer Cell Lines

PubMed Central

Olivan, M.; Rigau, M.; Colás, E.; Garcia, M.; Montes, M.; Sequeiros, T.; Regis, L.; Celma, A.; Planas, J.; Placer, J.; Reventós, J.; de Torres, I.; Doll, A.; Morote, J.

2015-01-01

Nowadays prostate cancer is the most common solid tumor in men from industrialized countries and the second leading cause of death. At the ages when PCa is usually diagnosed, mortality related to cardiovascular morbidity is high; therefore, men at risk for PCa frequently receive chronic lipid-lowering and antiplatelet treatment. The aim of this study was to analyze how chronic treatment with statins, aspirin, and their combination influenced the risk of PCa detection. The tumorigenic properties of these treatments were evaluated by proliferation, colony formation, invasion, and migration assays using different PCa cell lines, in order to assess how these treatments act at molecular level. The results showed that a combination of statins and aspirin enhances the effect of individual treatments and seems to reduce the risk of PCa detection (OR: 0.616 (95% CI: 0.467–0.812), P < 0.001). However, if treatments are maintained, aspirin (OR: 1.835 (95% CI: 1.068–3.155), P = 0.028) or the combination of both drugs (OR: 3.059 (95% CI: 1.894–4.939), P < 0.001) represents an increased risk of HGPCa. As observed at clinical level, these beneficial effects in vitro are enhanced when both treatments are administered simultaneously, suggesting that chronic, concomitant treatment with statins and aspirin has a protective effect on PCa incidence. PMID:25649906

Protease Expression Levels in Prostate Cancer Tissue Can Explain Prostate Cancer-Associated Seminal Biomarkers-An Explorative Concept Study.

PubMed

Neuhaus, Jochen; Schiffer, Eric; Mannello, Ferdinando; Horn, Lars-Christian; Ganzer, Roman; Stolzenburg, Jens-Uwe

2017-05-04

Previously, we described prostate cancer (PCa) detection (83% sensitivity; 67% specificity) in seminal plasma by CE-MS/MS. Moreover, advanced disease was distinguished from organ-confined tumors with 80% sensitivity and 82% specificity. The discovered biomarkers were naturally occurring fragments of larger seminal proteins, predominantly semenogelin 1 and 2, representing endpoints of the ejaculate liquefaction. Here we identified proteases putatively involved in PCa specific protein cleavage, and examined gene expression and tissue protein levels, jointly with cell localization in normal prostate (nP), benign prostate hyperplasia (BPH), seminal vesicles and PCa using qPCR, Western blotting and confocal laser scanning microscopy. We found differential gene expression of chymase (CMA1), matrix metalloproteinases (MMP3, MMP7), and upregulation of MMP14 and tissue inhibitors (TIMP1 and TIMP2) in BPH. In contrast tissue protein levels of MMP14 were downregulated in PCa. MMP3/TIMP1 and MMP7/TIMP1 ratios were decreased in BPH. In seminal vesicles, we found low-level expression of most proteases and, interestingly, we also detected TIMP1 and low levels of TIMP2. We conclude that MMP3 and MMP7 activity is different in PCa compared to BPH due to fine regulation by their inhibitor TIMP1. Our findings support the concept of seminal plasma biomarkers as non-invasive tool for PCa detection and risk stratification.

Non-invasive optical detection of HBV based on serum surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Zheng, Zuci; Wang, Qiwen; Weng, Cuncheng; Lin, Xueliang; Lin, Yao; Feng, Shangyuan

2016-10-01

An optical method of surface-enhanced Raman spectroscopy (SERS) was developed for non-invasive detection of hepatitis B surface virus (HBV). Hepatitis B virus surface antigen (HBsAg) is an established serological marker that is routinely used for the diagnosis of acute or chronic hepatitis B virus(HBV) infection. Utilizing SERS to analyze blood serum for detecting HBV has not been reported in previous literature. SERS measurements were performed on two groups of serum samples: one group for 50 HBV patients and the other group for 50 healthy volunteers. Blood serum samples are collected from healthy control subjects and patients diagnosed with HBV. Furthermore, principal components analysis (PCA) combined with linear discriminant analysis (LDA) were employed to differentiate HBV patients from healthy volunteer and achieved sensitivity of 80.0% and specificity of 74.0%. This exploratory work demonstrates that SERS serum analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of HBV.

MRI Fusion-Targeted Transrectal Prostate Biopsy and the Role of Prostate-Specific Antigen Density and Prostate Health Index for the Detection of Clinically Significant Prostate Cancer in Southeast Asian Men.

PubMed

Tan, Teck Wei; Png, Keng Siang; Lee, Chau Hung; Yuwono, Arianto; Yeow, Yuyi; Chong, Kian Tai; Lee, Yee Mun; Tan, Cher Heng; Tan, Yung Khan

2017-11-01

To test the hypothesis that targeted biopsy has a higher detection rate for clinically significant prostate cancer (csPCa) than systematic biopsy. We defined csPCa as any Gleason sum ≥7 cancer. In patients with Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions, to determine if factors, such as prostate-specific antigen density (PSAD) and prostate health index (PHI), can predict csPCa and help select patients for biopsy. We report the first series of targeted biopsies in Southeast Asian men, with comparison against systematic biopsy. Consecutive patients were registered into a prospective institutional review board-approved database in our institution. We reviewed patients who underwent biopsy from May 2016 to June 2017. Inclusion criteria for our study were patients with at least one PI-RADS ≥3, and who underwent both targeted and systematic biopsies in the same sitting. There were 115 patients in the study, of whom 74 (64.3%) had a previous negative systematic biopsy. Targeted biopsies detected significantly less Gleason 6 cancers than systematic biopsies (p < 0.01), and demonstrated significantly higher sensitivity, specificity, positive predictive value, and negative predictive value (NPV) for the detection of csPCa. For patients with PI-RADS 3 lesions, PHI and PSAD were found to be the best predictors for csPCa. PSAD <0.10 ng/mL/mL had an NPV of 93% and sensitivity of 92%, while allowing 20% of patients to avoid biopsy. PHI cutoff of <27 would allow 34% of patients to avoid biopsy, with both sensitivity and NPV of 100%. Targeted prostate biopsies were found to be significantly superior to systematic biopsies for the detection of csPCa, while detecting less Gleason 6 cancer. Usage of PSAD and PHI cutoff levels in patients with PI-RADS 3 lesions may enable a number of patients to avoid unnecessary biopsy.

Detection of tumor markers in prostate cancer and comparison of sensitivity between real time and nested PCR.

PubMed

Matsuoka, Takayuki; Shigemura, Katsumi; Yamamichi, Fukashi; Fujisawa, Masato; Kawabata, Masato; Shirakawa, Toshiro

2012-06-27

The objective of this study is to investigate and compare the sensitivity in conventional PCR, quantitative real time PCR, nested PCR and western blots for detection of prostate cancer tumor markers using prostate cancer (PCa) cells. We performed conventional PCR, quantitative real time PCR, nested PCR, and western blots using 5 kinds of PCa cells. Prostate specific antigen (PSA), prostate specific membrane antigen (PSMA), and androgen receptor (AR) were compared for their detection sensitivity by real time PCR and nested PCR. In real time PCR, there was a significant correlation between cell number and the RNA concentration obtained (R(2)=0.9944) for PSA, PSMA, and AR. We found it possible to detect these markers from a single LNCaP cell in both real time and nested PCR. By comparison, nested PCR reached a linear curve in fewer PCR cycles than real time PCR, suggesting that nested PCR may offer PCR results more quickly than real time PCR. In conclusion, nested PCR may offer tumor maker detection in PCa cells more quickly (with fewer PCR cycles) with the same high sensitivity as real time PCR. Further study is necessary to establish and evaluate the best tool for PCa tumor marker detection.

The best prostate biopsy scheme is dictated by the gland volume: a monocentric study.

PubMed

Dell'Atti, L

2015-08-01

Accuracy of biopsy scheme depends on different parameters. Prostate-specific antigen (PSA) level and digital rectal examination (DRE) influenced the detection rate and suggested the biopsy scheme to approach each patient. Another parameter is the prostate volume. Sampling accuracy tends to decrease progressively with an increasing prostate volume. We prospectively observed detection cancer rate in suspicious prostate cancer (PCa) and improved by applying a protocol biopsy according to prostate volume (PV). Clinical data and pathological features of these 1356 patients were analysed and included in this study. This protocol is a combined scheme that includes transrectal (TR) 12-core PBx (TR12PBx) for PV ≤ 30 cc, TR 14-core PBx (TR14PBx) for PV > 30 cc but < 60 cc, TR 18-core PBx (TR18PBx) for PV ≥ 60 cc. Out of a total of 1356 patients, in 111 (8.2%) PCa was identified through TR12PBx scheme, in 198 (14.6%) through TR14PBx scheme and in 253 (18.6%) through TR18PBx scheme. The PCa detection rate was increased by 44% by adding two TZ cores (TR14PBx scheme). The TR18PBx scheme increased this rate by 21.7% vs. TR14PBx scheme. The diagnostic yield offered by TR18PBx was statistically significant compared to the detection rate offered by the TR14PBx scheme (p < 0.003). The biopsy Gleason score and the percentage of core involvement were comparable between PCa detected by the TR14PBx scheme diagnostic yield and those detected by the TR18PBx scheme (p = 0.362). The only PV parameter, in our opinion, can be significant in choosing the best biopsy scheme to approach in a first setting of biopsies increasing PCa detection rate.

Diagnostic accuracy of prostate health index to identify aggressive prostate cancer. An Institutional validation study.

PubMed

Morote, J; Celma, A; Planas, J; Placer, J; Ferrer, R; de Torres, I; Pacciuci, R; Olivan, M

2016-01-01

New generations of tumor markers used to detect prostate cancer (PCa) should be able to discriminate men with aggressive PCa of those without PCa or nonaggressive tumors. The objective of this study has been to validate Prostate Health Index (PHI) as a marker of aggressive PCa in one academic institution. PHI was assessed in 357 men scheduled to prostatic biopsy between June of 2013 and July 2014 in one academic institution. Thereafter a subset of 183 men younger than 75 years and total PSA (tPSA) between 3.0 and 10.0 ng/mL, scheduled to it first prostatic biopsy, was retrospectively selected for this study. Twelve cores TRUS guided biopsy, under local anaesthesia, was performed in all cases. Total PSA, free PSA (fPSA), and [-2] proPSA (p2PSA) and prostate volume were determined before the procedure and %fPSA, PSA density (PSAd) and PHI were calculated. Aggressive tumors were considered if any Gleason 4 pattern was found. PHI was compared to %fPSA and PSAd through their ROC curves. Thresholds to detect 90%, 95% of all tumors and 95% and 100% of aggressive tumors were estimated and rates of unnecessary avoided biopsies were calculated and compared. The rate of PCa detection was 37.2% (68) and the rate of aggressive tumors was 24.6% (45). The PHI area under the curve was higher than those of %fPSA and PSAd to detect any PCa (0.749 vs 0.606 and 0.668 respectively) or to detect only aggressive tumors (0.786 vs 0.677 and 0.708 respectively), however, significant differences were not found. The avoided biopsy rates to detect 95% of aggressive tumors were 20.2% for PHI, 14.8% for %fPSA, and 23.5% for PSAd. Even more, to detect all aggressive tumors these rates dropped to 4.9% for PHI, 9.3% for %fPSA, and 7.9% for PSAd. PHI seems a good marker to PCa diagnosis. However, PHI was not superior to %fPSA and PSAd to identify at least 95% of aggressive tumors. Copyright © 2016 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

A novel-type phosphatidylinositol phosphate-interactive, Ca-binding protein PCaP1 in Arabidopsis thaliana: stable association with plasma membrane and partial involvement in stomata closure.

PubMed

Nagata, Chisako; Miwa, Chika; Tanaka, Natsuki; Kato, Mariko; Suito, Momoe; Tsuchihira, Ayako; Sato, Yori; Segami, Shoji; Maeshima, Masayoshi

2016-05-01

The Ca(2+)-binding protein-1 (PCaP1) of Arabidopsis thaliana is a new type protein that binds to phosphatidylinositol phosphates and Ca(2+)-calmodulin complex as well as free Ca(2+). Although biochemical properties, such as binding to ligands and N-myristoylation, have been revealed, the intracellular localization, tissue and cell specificity, integrity of membrane association and physiological roles of PCaP1 are unknown. We investigated the tissue and intracellular distribution of PCaP1 by using transgenic lines expressing PCaP1 linked with a green fluorescence protein (GFP) at the carboxyl terminus of PCaP1. GFP fluorescence was obviously detected in most tissues including root, stem, leaf and flower. In these tissues, PCaP1-GFP signal was observed predominantly in the plasma membrane even under physiological stress conditions but not in other organelles. The fluorescence was detected in the cytosol when the 25-residue N-terminal sequence was deleted from PCaP1 indicating essential contribution of N-myristoylation to the plasma membrane anchoring. Fluorescence intensity of PCaP1-GFP in roots was slightly decreased in seedlings grown in medium supplemented with high concentrations of iron for 1 week and increased in those grown with copper. In stomatal guard cells, PCaP1-GFP was strictly, specifically localized to the plasma membrane at the epidermal-cell side but not at the pore side. A T-DNA insertion mutant line of PCaP1 did not show marked phenotype in a life cycle except for well growth under high CO2 conditions. However, stomata of the mutant line did not close entirely even in high osmolarity, which usually induces stomata closure. These results suggest that PCaP1 is involved in the stomatal movement, especially closure process, in leaves and response to excessive copper in root and leaf as a mineral nutrient as a physiological role.

Low-Rank Matrix Recovery Approach for Clutter Rejection in Real-Time IR-UWB Radar-Based Moving Target Detection

PubMed Central

Sabushimike, Donatien; Na, Seung You; Kim, Jin Young; Bui, Ngoc Nam; Seo, Kyung Sik; Kim, Gil Gyeom

2016-01-01

The detection of a moving target using an IR-UWB Radar involves the core task of separating the waves reflected by the static background and by the moving target. This paper investigates the capacity of the low-rank and sparse matrix decomposition approach to separate the background and the foreground in the trend of UWB Radar-based moving target detection. Robust PCA models are criticized for being batched-data-oriented, which makes them inconvenient in realistic environments where frames need to be processed as they are recorded in real time. In this paper, a novel method based on overlapping-windows processing is proposed to cope with online processing. The method consists of processing a small batch of frames which will be continually updated without changing its size as new frames are captured. We prove that RPCA (via its Inexact Augmented Lagrange Multiplier (IALM) model) can successfully separate the two subspaces, which enhances the accuracy of target detection. The overlapping-windows processing method converges on the optimal solution with its batch counterpart (i.e., processing batched data with RPCA), and both methods prove the robustness and efficiency of the RPCA over the classic PCA and the commonly used exponential averaging method. PMID:27598159

In Vivo Imaging of Experimental Melanoma Tumors using the Novel Radiotracer 68Ga-NODAGA-Procainamide (PCA).

PubMed

Kertész, István; Vida, András; Nagy, Gábor; Emri, Miklós; Farkas, Antal; Kis, Adrienn; Angyal, János; Dénes, Noémi; Szabó, Judit P; Kovács, Tünde; Bai, Péter; Trencsényi, György

2017-01-01

The most aggressive form of skin cancer is the malignant melanoma. Because of its high metastatic potential the early detection of primary melanoma tumors and metastases using non-invasive PET imaging determines the outcome of the disease. Previous studies have already shown that benzamide derivatives, such as procainamide (PCA) specifically bind to melanin pigment. The aim of this study was to synthesize and investigate the melanin specificity of the novel 68 Ga-labeled NODAGA-PCA molecule in vitro and in vivo using PET techniques. Procainamide (PCA) was conjugated with NODAGA chelator and was labeled with Ga-68 ( 68 Ga-NODAGA-PCA). The melanin specificity of 68 Ga-NODAGA-PCA was tested in vitro , ex vivo and in vivo using melanotic B16-F10 and amelanotic Melur melanoma cell lines. By subcutaneous and intravenous injection of melanoma cells tumor-bearing mice were prepared, on which biodistribution studies and small animal PET/CT scans were performed for 68 Ga-NODAGA-PCA and 18 FDG tracers. 68 Ga-NODAGA-PCA was produced with high specific activity (14.9±3.9 GBq/µmol) and with excellent radiochemical purity (98%<), at all cases. In vitro experiments showed that 68 Ga-NODAGA-PCA uptake of B16-F10 cells was significantly ( p ≤0.01) higher than Melur cells. Ex vivo biodistribution and in vivo PET/CT studies using subcutaneous and metastatic tumor models showed significantly ( p ≤0.01) higher 68 Ga-NODAGA-PCA uptake in B16-F10 primary tumors and lung metastases in comparison with amelanotic Melur tumors. In experiments where 18 FDG and 68 Ga-NODAGA-PCA uptake of B16-F10 tumors was compared, we found that the tumor-to-muscle (T/M) and tumor-to-lung (T/L) ratios were significantly ( p ≤0.05 and p ≤0.01) higher using 68 Ga-NODAGA-PCA than the 18 FDG accumulation. Our novel radiotracer 68 Ga-NODAGA-PCA showed specific binding to the melanin producing experimental melanoma tumors. Therefore, 68 Ga-NODAGA-PCA is a suitable diagnostic radiotracer for the detection of melanoma tumors and metastases in vivo .

In Vivo Imaging of Experimental Melanoma Tumors using the Novel Radiotracer 68Ga-NODAGA-Procainamide (PCA)

PubMed Central

Kertész, István; Vida, András; Nagy, Gábor; Emri, Miklós; Farkas, Antal; Kis, Adrienn; Angyal, János; Dénes, Noémi; Szabó, Judit P.; Kovács, Tünde; Bai, Péter; Trencsényi, György

2017-01-01

Purpose: The most aggressive form of skin cancer is the malignant melanoma. Because of its high metastatic potential the early detection of primary melanoma tumors and metastases using non-invasive PET imaging determines the outcome of the disease. Previous studies have already shown that benzamide derivatives, such as procainamide (PCA) specifically bind to melanin pigment. The aim of this study was to synthesize and investigate the melanin specificity of the novel 68Ga-labeled NODAGA-PCA molecule in vitro and in vivo using PET techniques. Methods: Procainamide (PCA) was conjugated with NODAGA chelator and was labeled with Ga-68 (68Ga-NODAGA-PCA). The melanin specificity of 68Ga-NODAGA-PCA was tested in vitro, ex vivo and in vivo using melanotic B16-F10 and amelanotic Melur melanoma cell lines. By subcutaneous and intravenous injection of melanoma cells tumor-bearing mice were prepared, on which biodistribution studies and small animal PET/CT scans were performed for 68Ga-NODAGA-PCA and 18FDG tracers. Results: 68Ga-NODAGA-PCA was produced with high specific activity (14.9±3.9 GBq/µmol) and with excellent radiochemical purity (98%<), at all cases. In vitro experiments showed that 68Ga-NODAGA-PCA uptake of B16-F10 cells was significantly (p≤0.01) higher than Melur cells. Ex vivo biodistribution and in vivo PET/CT studies using subcutaneous and metastatic tumor models showed significantly (p≤0.01) higher 68Ga-NODAGA-PCA uptake in B16-F10 primary tumors and lung metastases in comparison with amelanotic Melur tumors. In experiments where 18FDG and 68Ga-NODAGA-PCA uptake of B16-F10 tumors was compared, we found that the tumor-to-muscle (T/M) and tumor-to-lung (T/L) ratios were significantly (p≤0.05 and p≤0.01) higher using 68Ga-NODAGA-PCA than the 18FDG accumulation. Conclusion: Our novel radiotracer 68Ga-NODAGA-PCA showed specific binding to the melanin producing experimental melanoma tumors. Therefore, 68Ga-NODAGA-PCA is a suitable diagnostic radiotracer for the detection of melanoma tumors and metastases in vivo. PMID:28382139

Damages detection in cylindrical metallic specimens by means of statistical baseline models and updated daily temperature profiles

NASA Astrophysics Data System (ADS)

Villamizar-Mejia, Rodolfo; Mujica-Delgado, Luis-Eduardo; Ruiz-Ordóñez, Magda-Liliana; Camacho-Navarro, Jhonatan; Moreno-Beltrán, Gustavo

2017-05-01

In previous works, damage detection of metallic specimens exposed to temperature changes has been achieved by using a statistical baseline model based on Principal Component Analysis (PCA), piezodiagnostics principle and taking into account temperature effect by augmenting the baseline model or by using several baseline models according to the current temperature. In this paper a new approach is presented, where damage detection is based in a new index that combine Q and T2 statistical indices with current temperature measurements. Experimental tests were achieved in a carbon-steel pipe of 1m length and 1.5 inches diameter, instrumented with piezodevices acting as actuators or sensors. A PCA baseline model was obtained to a temperature of 21º and then T2 and Q statistical indices were obtained for a 24h temperature profile. Also, mass adding at different points of pipe between sensor and actuator was used as damage. By using the combined index the temperature contribution can be separated and a better differentiation of damages respect to undamaged cases can be graphically obtained.

Elevated hardness of peripheral gland on real-time elastography is an independent marker for high-risk prostate cancers.

PubMed

Zhang, Qi; Yao, Jing; Cai, Yehua; Zhang, Limin; Wu, Yishuo; Xiong, Jingyu; Shi, Jun; Wang, Yuanyuan; Wang, Yi

2017-12-01

To examine the role of quantitative real-time elastography (RTE) features on differentiation between high-risk prostate cancer (PCA) and non-high-risk prostatic diseases in the initial transperineal biopsy setting. We retrospectively included 103 patients with suspicious PCA who underwent both RTE and initial transperineal prostate biopsy. Patients were grouped into high-risk and non-high-risk categories according to the D'Amico's risk stratification. With computer assistance based on MATLAB programming, three features were extracted from RTE, i.e., the median hardness within peripheral gland (PG) (H med ), the ratio of the median hardness within PG to that outside PG (H ratio ), and the ratio of the hard area within PG to the total PG area (H ar ). A multiple regression model incorporating an RTE feature, age, transrectal ultrasound finding, and prostate volume was used to identify markers for high-risk PCA. Forty-seven patients (45.6%) were diagnosed with PCA and 34 (33.0%) were diagnosed with high-risk PCA. Three RTE features were all statistically higher in high-risk PCA than in non-high-risk diseases (p < 0.001), indicating that the PGs in high-risk PCA patients were harder than those in non-high-risk patients. A high H ratio , high age, and low prostate volume were found to be independent markers for PCAs (p < 0.05), among which the high H ratio was the only independent marker for high-risk PCAs (p = 0.012). When predicting high-risk PCAs, the multiple regression achieved an area under receiver operating characteristic curve of 0.755, sensitivity of 73.5%, and specificity of 71.0%. The elevated hardness of PG identified high-risk PCA and served as an independent marker of high-risk PCA. As a non-invasive imaging modality, the RTE could be potentially used in routine clinical practice for the detection of high-risk PCA to decrease unnecessary biopsies and reduce overtreatment.

7 to 10 years' follow-up of 573 patients with elevated prostate-specific antigen (>4 ng/mL) or/and suspected rectal examination: biopsies protocol and follow-up guides.

PubMed

Kravchick, Sergey; Cytron, Shmuel; Stepnov, Eugeny; Ben-Dor, David; Kravchenko, Yakov; Peled, Ronit

2009-06-01

In this study, we tried to design a scheme for performing transrectal ultrasonographic (TRUS)-biopsies that would be accurate and include the optimal number of cores. We included in this study 600 consecutive patients with suspicious findings on a per-rectum examination and/or an elevated prostate-specific antigen (PSA) (>4 ng/mL) level. Patients were followed for 7 to 10 years. In all patients, we took from 8 to 16 biopsy samples, according to the prostate volume, from the lateral aspects. In the second session, the biopsy samples were taken medially; in the third session, we included the transitional zone, while in consecutive sessions, we increased the number of cores from all areas. Only 573 of the patients remained in follow-up. TRUS-biopsy detected prostate cancer (PCa) in 257 patients (44.85% overall detection rate). The detection rate in the first and second sessions was 32.98% and 14.94%, respectively, reaching 13.2% and 2.17%, in the third and fourth sessions, respectively. Prostate volumes were significantly smaller (52.9 +/- 22.4 cc vs 58.9 +/- 23.8 cc, P < 0.002) and the PSA/adenoma/prostate volumes ratio (ad-pro) ratio was higher (18.3 +/- 9 vs 13.96, P < 0/001) in the patients with PCa. Patients with PCa underwent fewer biopsy procedures and biopsy sessions than patients without a diagnosis of PCa (14.9 +/- 8.9 vs 20.4 +/- 12, P < 0.001;1.3 +/- 0.6 vs 1.7 +/- 0.9, P < 0.001). Biopsy samples obtained from the base were positive for cancer only in larger prostates with a mean volume of 54.3 +/- 15.3 cc. Numbers of biopsy procedures and PSA/ad-pro ratio were the strongest predictive factors for PCa detection (P < 0.001). In patients with a prostate volume >or=53 cc and PSA/ad-pro ratio >or=18, the optimal biopsy cores should be >or=15. Using this scheme, the discontinuation of biopsy procedures might be considered after three consecutive sessions.

Using Serological Proteome Analysis to Identify Serum Anti-Nucleophosmin 1 Autoantibody as a Potential Biomarker in European-American and African-American Patients With Prostate Cancer.

PubMed

Dai, Liping; Li, Jitian; Xing, Mengtao; Sanchez, Tino W; Casiano, Carlos A; Zhang, Jian-Ying

2016-11-01

The prostate-specific antigen (PSA) testing has been widely implemented for the early detection and management of prostate cancer (PCa). However, the lack of specificity has led to overdiagnosis, resulting in many possibly unnecessary biopsies and overtreatment. Therefore, novel serological biomarkers with high sensitivity and specificity are of vital importance needed to complement PSA testing in the early diagnosis and effective management of PCa. This is particularly critical in the context of PCa health disparities, where early detection and management could help reduce the disproportionately high PCa mortality observed in African-American men. Previous studies have demonstrated that sera from patients with PCa contain autoantibodies that react with tumor-associated antigens (TAAs). The serological proteome analysis (SERPA) approach was used to identify tumor-associated antigens (TAAs) of PCa. In evaluation study, the level of anti-NPM1 antibody was examined in sera from test cohort, validation cohort, as well as European-American (EA) and African-American (AA) men with PCa by using immunoassay. Nucleophosmin 1 (NPM1) as a 33 kDa TAA in PCa was identified and characterized by SERPA approach. Anti-NPM1 antibody level in PCa was higher than in benign prostatic hyperplasia (BPH) patients and healthy individuals. Receiver operating characteristic (ROC) curve analysis showed similar high diagnostic value for PCa in the test cohort (area under the curve (AUC):0.860) and validation cohort (AUC: 0.822) to differentiate from normal individuals and BPH. Interestingly, AUC values were significantly higher for AA PCa patients. When considering concurrent serum measurements of anti-NPM1 antibody and PSA, 97.1% PCa patients at early stage were identified correctly, while 69.2% BPH patients who had elevated PSA levels were found to be anti-NPM1 negative. Additionally, anti-NPM1 antibody levels in PCa patients at early stage significantly increased after surgery treatment. This intriguing data suggested that NPM1 can elicit autoantibody response in PCa and might be a potential biomarker for the immunodiagnosis and prognosis of PCa, and for supplementing PSA testing in distinguishing PCa from BPH. Prostate 76:1375-1386, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A diffusion-matched principal component analysis (DM-PCA) based two-channel denoising procedure for high-resolution diffusion-weighted MRI

PubMed Central

Chang, Hing-Chiu; Bilgin, Ali; Bernstein, Adam; Trouard, Theodore P.

2018-01-01

Over the past several years, significant efforts have been made to improve the spatial resolution of diffusion-weighted imaging (DWI), aiming at better detecting subtle lesions and more reliably resolving white-matter fiber tracts. A major concern with high-resolution DWI is the limited signal-to-noise ratio (SNR), which may significantly offset the advantages of high spatial resolution. Although the SNR of DWI data can be improved by denoising in post-processing, existing denoising procedures may potentially reduce the anatomic resolvability of high-resolution imaging data. Additionally, non-Gaussian noise induced signal bias in low-SNR DWI data may not always be corrected with existing denoising approaches. Here we report an improved denoising procedure, termed diffusion-matched principal component analysis (DM-PCA), which comprises 1) identifying a group of (not necessarily neighboring) voxels that demonstrate very similar magnitude signal variation patterns along the diffusion dimension, 2) correcting low-frequency phase variations in complex-valued DWI data, 3) performing PCA along the diffusion dimension for real- and imaginary-components (in two separate channels) of phase-corrected DWI voxels with matched diffusion properties, 4) suppressing the noisy PCA components in real- and imaginary-components, separately, of phase-corrected DWI data, and 5) combining real- and imaginary-components of denoised DWI data. Our data show that the new two-channel (i.e., for real- and imaginary-components) DM-PCA denoising procedure performs reliably without noticeably compromising anatomic resolvability. Non-Gaussian noise induced signal bias could also be reduced with the new denoising method. The DM-PCA based denoising procedure should prove highly valuable for high-resolution DWI studies in research and clinical uses. PMID:29694400

Prebiopsy biparametric MRI: differences of PI-RADS version 2 in patients with different PSA levels.

PubMed

Choi, M H; Lee, Y J; Jung, S E; Rha, S E; Byun, J Y

2018-06-09

To validate the diagnostic accuracy of Prostate Imaging-Reporting and Data System (PI-RADS) version 2 in detecting clinically significant prostate cancer (csPCa, Gleason score ≥7) on prebiopsy biparametric MRI (bpMRI) in patients with different prostate-specific antigen (PSA) levels. This retrospective study included 184 patients who underwent prebiopsy bpMRI followed by transrectal ultrasonography-guided biopsy between June 2015 and February 2017. Reader 1 performed a combination of systematic and targeted biopsy with cognitive fusion after reviewing bpMRI and reader 2 reviewed the bpMRIs retrospectively. PI-RADS categories 4 and 5 were considered positive, and the results of the biopsy were considered the reference standard. Diagnostic performance of PI-RADS of bpMRI was evaluated in two PSA groups with a PSA cut-off level of 10 ng/ml and compared to PSA and the PSA density using receiver operating characteristics (ROC) curve analysis. csPCa was diagnosed in 24 of 123 patients (19.5%) and 26 of 61 patients (42.6%) in the low and high PSA groups, respectively. A PI-RADS v2 category by either readers 1 or 2 had a significantly better performance to detect csPCa than PSA in both PSA groups. In the high PSA group, only one csPCa was missed by reader 2, but none by reader 1. In the low PSA group, readers 1 and 2 were unable to detect seven and five of the 24 csPCas, respectively. Prebiopsy bpMRI has good performance for detecting csPCa in the high PSA group but may miss small-volume csPCa in the low PSA group. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Inflammation: an important parameter in the search of prostate cancer biomarkers

PubMed Central

2014-01-01

Background A more specific and early diagnostics for prostate cancer (PCa) is highly desirable. In this study, being inflammation the focus of our effort, serum protein profiles were analyzed in order to investigate if this parameter could interfere with the search of discriminating proteins between PCa and benign prostatic hyperplasia (BPH). Methods Patients with clinical suspect of PCa and candidates for trans-rectal ultrasound guided prostate biopsy (TRUS) were enrolled. Histological specimens were examined in order to grade and classify the tumor, identify BPH and detect inflammation. Surface Enhanced Laser Desorption/Ionization-Time of Flight-Mass Spectrometry (SELDI-ToF-MS) and two-dimensional gel electrophoresis (2-DE) coupled with Liquid Chromatography-MS/MS (LC-MS/MS) were used to analyze immuno-depleted serum samples from patients with PCa and BPH. Results The comparison between PCa (with and without inflammation) and BPH (with and without inflammation) serum samples by SELDI-ToF-MS analysis did not show differences in protein expression, while changes were only observed when the concomitant presence of inflammation was taken into consideration. In fact, when samples with histological sign of inflammation were excluded, 20 significantly different protein peaks were detected. Subsequent comparisons (PCa with inflammation vs PCa without inflammation, and BPH with inflammation vs BPH without inflammation) showed that 16 proteins appeared to be modified in the presence of inflammation, while 4 protein peaks were not modified. With 2-DE analysis, comparing PCa without inflammation vs PCa with inflammation, and BPH without inflammation vs the same condition in the presence of inflammation, were identified 29 and 25 differentially expressed protein spots, respectively. Excluding samples with inflammation the comparison between PCa vs BPH showed 9 unique PCa proteins, 4 of which overlapped with those previously identified in the presence of inflammation, while other 2 were new proteins, not identified in our previous comparisons. Conclusions The present study indicates that inflammation might be a confounding parameter during the proteomic research of candidate biomarkers of PCa. These results indicate that some possible biomarker-candidate proteins are strongly influenced by the presence of inflammation, hence only a well-selected protein pattern should be considered for potential marker of PCa. PMID:24944525

Is bladder tumor location associated with prostate cancer detection after intravesical bacillus Calmette-Guérin instillation?

PubMed

Hong, Sungwoo; Kim, Seong-Cheol; Kwon, Taekmin; Jeong, In Gab; Kim, Choung-Soo; Ahn, Hanjong; Hong, Jun Hyuk

2014-01-01

The aim of this study was to evaluate the effect of bladder tumor (BT) location on prostate cancer (PCa) detection in patients with elevated PSA levels after intravesical BCG instillation. Between February 2004 and January 2013 prostate biopsies were performed in 59 non-muscle invasive bladder cancer (NMIBC) patients whose PSA level were elevated (≥3 ng/ml) after a 6 week course of intravesical BCG (Oncotice, 12.5 mg in 50 ml normal saline). Differences in PCa detection according to the BT location [bladder neck and/or trigone (Group 1, n = 22) vs. other locations (Group 2, n = 37)] were evaluated. The Fisher's exact test and the Mann-Whitney U test were used to evaluate the association between categorical and continuous variables, respectively. A total of 14 patients (23.7%) were diagnosed with PCa. The mean ± standard deviation (SD) PSA before intravesical BCG instillation and prostate biopsy were 1.36±1.04 ng/ml in Group 1 and 1.09±1.12 ng/ml in Group 2 (P = 0.633), and 6.05±3.57 ng/ml in Group 1 and 5.13±3.88 ng/ml in Group 2 (P = 0.378), respectively. Interestingly, whereas PCa was detected upon biopsy in only one patient in Group 1 (4.5%), 13 cases were detected in Group 2 (35.1%) (P = 0.009). PCa detection after intravesical BCG was highly associated with BT location. Prostate biopsy should therefore be considered when PSA level is elevated after BCG instillation and his BT is located far from the bladder neck.

Biotic and abiotic degradation of 1,1,2,2-tetrachloroethane in wetland sediments: Geochemical and microbial community analyses

USGS Publications Warehouse

Lorah, M.M.; Voytek, M.A.; Kirshtein, J.

2000-01-01

Additional microcosm experiments with the wetland sediment and groundwater at the Aberdeen Proving Ground, MD, site was presented to assist in elucidating the conditions under which these potentially competing biotic and abiotic degradation reactions for 1,1,2,2-tetrachloroethane (PCA) occur in the environment and to evaluate potential seasonal changes in degradation reactions. PCA concentration decreased to below detection within 21 days in the March 1999 experiment, while PCA was still present at day 35 in the July 1999 experiment. Compared to March 1999 experiment, peak concentrations of all daughter products except trichloroethylene (TCE) were delayed in the July 1999 experiment. The relative intensity of the peaks was directly related to the biomass present for each fragment length (bp, base pair). The relative intensities were lower in sediment collected in August 1999 than in March 1999, especially in the bp size range of ??? 160??-240??. These microbial community analyses, along with the geochemical analyses of the microcosms, provide evidence that abiotic production of TCE from PCA degradation is more significant under conditions of low bacterial biomass in the wetland sediments.

Nuclear Medicine Imaging of Prostate Cancer.

PubMed

Schreiter, V; Reimann, C; Geisel, D; Schreiter, N F

2016-11-01

The new tracer Gallium-68 prostate-specific membrane antigen (Ga-68 PSMA) yields new promising options for the PET/CT diagnosis of prostate cancer (PCa) and its metastases. To overcome limitations of hybrid imaging, known from the use of choline derivatives, seems to be possible with the use of Ga-68 PSMA for PCa. The benefits of hybrid imaging with Ga-68 PSMA for PCa compared to choline derivatives shall be discussed in this article based on an overview of the current literature. Key Points: • Ga-68 PSMA PET/CT can achieve higher detection rates of PCa lesions than PET/CT performed with choline derivatives• The new tracer Ga-68 PSMA has the advantage of high specificity, independence of PSA-level and low nonspecific tracer uptake in surrounding tissue• The new tracer Ga-68 PSMA seems very suitable for MR-PET diagnostic Citation Format: • Schreiter V, Reimann C, Geisel D et al. Nuclear Medicine Imaging of Prostate Cancer. Fortschr Röntgenstr 2016; 188: 1037 - 1044. © Georg Thieme Verlag KG Stuttgart · New York.

The epigenetics of prostate cancer diagnosis and prognosis: update on clinical applications.

PubMed

Blute, Michael L; Damaschke, Nathan A; Jarrard, David F

2015-01-01

There is a major deficit in our ability to detect and predict the clinical behavior of prostate cancer (PCa). Epigenetic changes are associated with PCa development and progression. This review will focus on recent results in the clinical application of diagnostic and prognostic epigenetic markers. The development of high throughput technology has seen an enormous increase in the discovery of new markers that encompass epigenetic changes including those in DNA methylation and histone modifications. Application of these findings to urine and other biofluids, but also cancer and noncancerous prostate tissue, has resulted in new biomarkers. There has been a recent commercial development of a DNA methylation-based assay for identifying PCa risk from normal biopsy tissue. Other biomarkers are currently in the validation phase and encompass combinations of multiple genes. Epigenetic changes improve the specificity and sensitivity of PCa diagnosis and have the potential to help determine clinical prognosis. Additional studies will not only provide new and better biomarker candidates, but also have the potential to inform new therapeutic strategies given the reversibility of these processes.

Ketamine added to morphine or hydromorphone patient-controlled analgesia for acute postoperative pain in adults: a systematic review and meta-analysis of randomized trials.

PubMed

Wang, Li; Johnston, Bradley; Kaushal, Alka; Cheng, Davy; Zhu, Fang; Martin, Janet

2016-03-01

To determine whether ketamine added to morphine or hydromorphone patient-controlled analgesia (PCA) provides clinically relevant reductions in postoperative pain, opioid requirements, and adverse events when compared with morphine or hydromorphone PCA in adults undergoing surgery. We systematically searched six databases up to June 2, 2015 for randomized controlled trials (RCTs) comparing ketamine plus morphine/hydromorphone PCA vs morphine/hydromorphone PCA for postoperative pain in adults. Thirty-six RCTs including 2,502 patients proved eligible, and 22 of these were at low risk of bias. The addition of ketamine to morphine/hydromorphone PCA decreased postoperative pain intensity at six to 72 hr when measured at rest (weighted mean difference [WMD] on a 10-cm visual analogue scale ranged from -0.4 to -1.3 cm) and during mobilization (WMD ranged from -0.4 to -0.5 cm). Adjunctive ketamine also significantly reduced cumulative morphine consumption at 24-72 hr by approximately 5-20 mg. Predefined subgroup analyses and meta-regression did not detect significant differences across subgroups, including a dose-response relationship. There was no significant difference in patient satisfaction scores at 24 and 48 hr. Nevertheless, the addition of ketamine to morphine/hydromorphone PCA significantly reduced postoperative nausea and vomiting (relative risk, 0.71; 95% confidence interval [CI], 0.60 to 0.85; absolute risk reduction, 8.9%; 95% CI, 4.6 to 12.2). Significant effects on other adverse events (e.g., hallucinations, vivid dreams) were not detected, though only a few studies reported on them. Adding ketamine to morphine/hydromorphone PCA provides a small improvement in postoperative analgesia while reducing opioid requirements. Adjunctive ketamine also reduces postoperative nausea and vomiting without a detected increase in other adverse effects; however, adverse events were probably underreported.

Validation of PI-RADS version 2 for the detection of prostate cancer.

PubMed

Hofbauer, Sebastian L; Kittner, Beatrice; Maxeiner, Andreas; Heckmann, Robin; Reimann, Maximillian; Wiemer, Laura; Asbach, Patrick; Haas, Matthias; Penzkofer, Tobias; Stephan, Carsten; Friedersdorff, Frank; Fuller, Florian; Miller, Kurt; Cash, Hannes

2018-05-04

The second version of the Prostate Imaging Reporting and Data System (PI-RADSv2) was introduced in 2015 to standardize the interpretation and reporting of multiparametric prostate magnetic resonance imaging (mpMRI). Recently, low cancer detection rates (CDR) for PI-RADSv2 category 4 lesions were reported. Therefore the aim of the study was to evaluate the CDR of PI-RADSv2 in a large prospective cohort. The study included 704 consecutive men with primary or prior negative biopsies who underwent MRI/ultrasound fusion-guided targeted biopsy (TB) and 10-core systematic prostate biopsy (SB) between September 2015 and May 2017. All lesions were rated according to PI-RADSv2 and lesions with PI-RADSv2 category ≥ 3 were biopsied. An ISUP (International Society of Urological Pathology) score of 2 or greater (i.e. Gleason 3+4 or greater) was defined as clinically significant prostate cancer (csPCa). The overall CDR for PI-RADSv2 categories 3, 4, and 5 was 39%, 72%, and 91% for all PCa, and 23%, 49%, and 77% for all csPCa, respectively. Fifty-nine (16%) clinically significant tumors would have been missed if only TB was performed. The PI-RADSv2 score was significantly associated with the presence of PCa (p<0.001), the presence of csPCa (p<0.001), and the ISUP grading (p<0.001). PI-RADSv2 is significantly associated with the presence of csPCa. The CDR for PI-RADSv2 category 4 lesions was considerably higher than previously reported. When performing TB, the combination with a SB still warrants the highest detection of csPCa. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Testosterone therapy for men at risk for or with history of prostate cancer.

PubMed

Morgentaler, Abraham

2006-09-01

Since the early 1940s when Huggins showed that severe reductions in serum testosterone by castration or estrogen therapy caused regression of prostate cancer (PCa), it has been assumed that higher testosterone levels cause enhanced growth of PCa. For this reason, it has been considered taboo to offer testosterone replacement therapy (TRT) to any man with a prior history of PCa, even if all objective evidence suggests he has been cured. The fear has been that higher testosterone levels would "awaken" dormant cells and cause a recurrence. Thus, US Food and Drug Administration-mandated language in all testosterone package inserts states that testosterone is contraindicated in men with a history of, or suspected of having, PCa. Although there is little modern experience with administration of testosterone in men with known history of PCa, there is a varied and extensive literature indicating that TRT does not pose any increased risk of PCa growth in men with or without prior treatment. For instance, the cancer rate in TRT trials is only approximately 1%, similar to detection rates in screening programs, yet biopsy-detectable PCa is found in one of seven hypogonadal men. Moreover, PCa is almost never seen in the peak testosterone years of the early 20s, despite autopsy evidence that men in this age group already harbor microfoci of PCa in substantial numbers. The growing number of PCa survivors who happen to be hypogonadal and request treatment has spurred a change in attitude toward this topic, with increasing numbers of physicians now offering TRT to men who appear cured of their disease. Publications have now reported no prostate-specific antigen (PSA) recurrence with TRT in small numbers of men who had undetectable PSA values after radical prostatectomy. Although still controversial, there appears to be little reason to withhold TRT from men with favorable outcomes after definitive treatment for PCa. Monitoring with PSA and digital rectal examination at regular intervals is recommended.

Network Intrusion Detection Based on a General Regression Neural Network Optimized by an Improved Artificial Immune Algorithm

PubMed Central

Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

2015-01-01

To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data. PMID:25807466

Pilot study for supervised target detection applied to spatially registered multiparametric MRI in order to non-invasively score prostate cancer.

PubMed

Mayer, Rulon; Simone, Charles B; Skinner, William; Turkbey, Baris; Choykey, Peter

2018-03-01

Gleason Score (GS) is a validated predictor of prostate cancer (PCa) disease progression and outcomes. GS from invasive needle biopsies suffers from significant inter-observer variability and possible sampling error, leading to underestimating disease severity ("underscoring") and can result in possible complications. A robust non-invasive image-based approach is, therefore, needed. Use spatially registered multi-parametric MRI (MP-MRI), signatures, and supervised target detection algorithms (STDA) to non-invasively GS PCa at the voxel level. This study retrospectively analyzed 26 MP-MRI from The Cancer Imaging Archive. The MP-MRI (T2, Diffusion Weighted, Dynamic Contrast Enhanced) were spatially registered to each other, combined into stacks, and stitched together to form hypercubes. Multi-parametric (or multi-spectral) signatures derived from a training set of registered MP-MRI were transformed using statistics-based Whitening-Dewhitening (WD). Transformed signatures were inserted into STDA (having conical decision surfaces) applied to registered MP-MRI determined the tumor GS. The MRI-derived GS was quantitatively compared to the pathologist's assessment of the histology of sectioned whole mount prostates from patients who underwent radical prostatectomy. In addition, a meta-analysis of 17 studies of needle biopsy determined GS with confusion matrices and was compared to the MRI-determined GS. STDA and histology determined GS are highly correlated (R = 0.86, p < 0.02). STDA more accurately determined GS and reduced GS underscoring of PCa relative to needle biopsy as summarized by meta-analysis (p < 0.05). This pilot study found registered MP-MRI, STDA, and WD transforms of signatures shows promise in non-invasively GS PCa and reducing underscoring with high spatial resolution. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Role of tissue markers on diagnosis, prognosis and monitoring of prostate cancer].

PubMed

Mora, Miguel J

2015-04-01

Prostate specific antigen has maintained a key role as serum marker for prostate cancer (PCa) diagnosis and management since almost 25 years ago. However, suboptimal sensitivity and specificity, resulting in missed diagnoses, unnecessary prostate biopsies, as well as, detection of clinically indolent disease emphasize the need for new biomarkers. The purpose of this review is to examine the current status of tissue-based PCa markers, with special emphasis on recently marketed assays, and to evaluate their potential advantages to improve diagnosis, discriminate between indolent and aggressive disease, as well as, their role selecting therapeutic strategies. PubMed-based available literature provided primarily the core for this review. The more recent, larger size series, meta-analysis and frequently referred originals were prioritized. Advances in genomics, molecular technologies along with new immunohistochemical procedures have enabled the discovery and study of a growing number of PCA markers. In the past two years, these efforts have produced assays to more accurately detect and characterize the disease. We present the development and validation of tissue-based genetic tests, and discuss the challenge of incorporating the use of these new markers into clinical practice. Since prostate cancer is a heterogeneous disease, having a defined set of markers for early diagnosis, prognosis and follow-up, is clinically relevant. Some of these new markers can now be used to complement the conventional histopathologic diagnosis, as well as, to help already established parameters assessing prognosis.

[Vis-NIR spectroscopic pattern recognition combined with SG smoothing applied to breed screening of transgenic sugarcane].

PubMed

Liu, Gui-Song; Guo, Hao-Song; Pan, Tao; Wang, Ji-Hua; Cao, Gan

2014-10-01

Based on Savitzky-Golay (SG) smoothing screening, principal component analysis (PCA) combined with separately supervised linear discriminant analysis (LDA) and unsupervised hierarchical clustering analysis (HCA) were used for non-destructive visible and near-infrared (Vis-NIR) detection for breed screening of transgenic sugarcane. A random and stability-dependent framework of calibration, prediction, and validation was proposed. A total of 456 samples of sugarcane leaves planting in the elongating stage were collected from the field, which was composed of 306 transgenic (positive) samples containing Bt and Bar gene and 150 non-transgenic (negative) samples. A total of 156 samples (negative 50 and positive 106) were randomly selected as the validation set; the remaining samples (negative 100 and positive 200, a total of 300 samples) were used as the modeling set, and then the modeling set was subdivided into calibration (negative 50 and positive 100, a total of 150 samples) and prediction sets (negative 50 and positive 100, a total of 150 samples) for 50 times. The number of SG smoothing points was ex- panded, while some modes of higher derivative were removed because of small absolute value, and a total of 264 smoothing modes were used for screening. The pairwise combinations of first three principal components were used, and then the optimal combination of principal components was selected according to the model effect. Based on all divisions of calibration and prediction sets and all SG smoothing modes, the SG-PCA-LDA and SG-PCA-HCA models were established, the model parameters were optimized based on the average prediction effect for all divisions to produce modeling stability. Finally, the model validation was performed by validation set. With SG smoothing, the modeling accuracy and stability of PCA-LDA, PCA-HCA were signif- icantly improved. For the optimal SG-PCA-LDA model, the recognition rate of positive and negative validation samples were 94.3%, 96.0%; and were 92.5%, 98.0% for the optimal SG-PCA-LDA model, respectively. Vis-NIR spectro- scopic pattern recognition combined with SG smoothing could be used for accurate recognition of transgenic sugarcane leaves, and provided a convenient screening method for transgenic sugarcane breeding.

DWI-associated entire-tumor histogram analysis for the differentiation of low-grade prostate cancer from intermediate-high-grade prostate cancer.

PubMed

Wu, Chen-Jiang; Wang, Qing; Li, Hai; Wang, Xiao-Ning; Liu, Xi-Sheng; Shi, Hai-Bin; Zhang, Yu-Dong

2015-10-01

To investigate diagnostic efficiency of DWI using entire-tumor histogram analysis in differentiating the low-grade (LG) prostate cancer (PCa) from intermediate-high-grade (HG) PCa in comparison with conventional ROI-based measurement. DW images (b of 0-1400 s/mm(2)) from 126 pathology-confirmed PCa (diameter >0.5 cm) in 110 patients were retrospectively collected and processed by mono-exponential model. The measurement of tumor apparent diffusion coefficients (ADCs) was performed with using histogram-based and ROI-based approach, respectively. The diagnostic ability of ADCs from two methods for differentiating LG-PCa (Gleason score, GS ≤ 6) from HG-PCa (GS > 6) was determined by ROC regression, and compared by McNemar's test. There were 49 LG-tumor and 77 HG-tumor at pathologic findings. Histogram-based ADCs (mean, median, 10th and 90th) and ROI-based ADCs (mean) showed dominant relationships with ordinal GS of Pca (ρ = -0.225 to -0.406, p < 0.05). All above imaging indices reflected significant difference between LG-PCa and HG-PCa (all p values <0.01). Histogram 10th ADCs had dominantly high Az (0.738), Youden index (0.415), and positive likelihood ratio (LR+, 2.45) in stratifying tumor GS against mean, median and 90th ADCs, and ROI-based ADCs. Histogram mean, median, and 10th ADCs showed higher specificity (65.3%-74.1% vs. 44.9%, p < 0.01), but lower sensitivity (57.1%-71.3% vs. 84.4%, p < 0.05) than ROI-based ADCs in differentiating LG-PCa from HG-PCa. DWI-associated histogram analysis had higher specificity, Az, Youden index, and LR+ for differentiation of PCa Gleason grade than ROI-based approach.

The biometric-based module of smart grid system

NASA Astrophysics Data System (ADS)

Engel, E.; Kovalev, I. V.; Ermoshkina, A.

2015-10-01

Within Smart Grid concept the flexible biometric-based module base on Principal Component Analysis (PCA) and selective Neural Network is developed. The formation of the selective Neural Network the biometric-based module uses the method which includes three main stages: preliminary processing of the image, face localization and face recognition. Experiments on the Yale face database show that (i) selective Neural Network exhibits promising classification capability for face detection, recognition problems; and (ii) the proposed biometric-based module achieves near real-time face detection, recognition speed and the competitive performance, as compared to some existing subspaces-based methods.

Race, Genetic West African Ancestry, and Prostate Cancer Prediction by PSA in Prospectively Screened High-Risk Men

PubMed Central

Giri, Veda N.; Egleston, Brian; Ruth, Karen; Uzzo, Robert G.; Chen, David Y.T.; Buyyounouski, Mark; Raysor, Susan; Hooker, Stanley; Torres, Jada Benn; Ramike, Teniel; Mastalski, Kathleen; Kim, Taylor Y.; Kittles, Rick

2008-01-01

Introduction “Race-specific” PSA needs evaluation in men at high-risk for prostate cancer (PCA) for optimizing early detection. Baseline PSA and longitudinal prediction for PCA was examined by self-reported race and genetic West African (WA) ancestry in the Prostate Cancer Risk Assessment Program, a prospective high-risk cohort. Materials and Methods Eligibility criteria are age 35–69 years, FH of PCA, African American (AA) race, or BRCA1/2 mutations. Biopsies have been performed at low PSA values (<4.0 ng/mL). WA ancestry was discerned by genotyping 100 ancestry informative markers. Cox proportional hazards models evaluated baseline PSA, self-reported race, and genetic WA ancestry. Cox models were used for 3-year predictions for PCA. Results 646 men (63% AA) were analyzed. Individual WA ancestry estimates varied widely among self-reported AA men. “Race-specific” differences in baseline PSA were not found by self-reported race or genetic WA ancestry. Among men with ≥ 1 follow-up visit (405 total, 54% AA), three-year prediction for PCA with a PSA of 1.5–4.0 ng/mL was higher in AA men with age in the model (p=0.025) compared to EA men. Hazard ratios of PSA for PCA were also higher by self-reported race (1.59 for AA vs. 1.32 for EA, p=0.04). There was a trend for increasing prediction for PCA with increasing genetic WA ancestry. Conclusions “Race-specific” PSA may need to be redefined as higher prediction for PCA at any given PSA in AA men. Large-scale studies are needed to confirm if genetic WA ancestry explains these findings to make progress in personalizing PCA early detection. PMID:19240249

The function of oxytocin: a potential biomarker for prostate cancer diagnosis and promoter of prostate cancer.

PubMed

Xu, Huan; Fu, Shi; Chen, Qi; Gu, Meng; Zhou, Juan; Liu, Chong; Chen, Yanbo; Wang, Zhong

2017-05-09

To measure the level of oxytocin in serum and prostate cancer (PCa) tissue and study its effect on the proliferation of PCa cells. Oxytocin level in serum was significantly increased in PCa patients compared with the no-carcinoma individuals. Additionally, the levels of oxytocin and its receptor were also elevated in the PCa tissue. However, no significant difference existed among the PCa of various Gleason grades. Western blot analysis confirmed the previous results and revealed an increased expression level of APPL1. The level of oxytocin in serum was measured by ELISA analysis. The expression of oxytocin and its receptor in prostate was analyzed by immunohistochemistry. The proliferation and apoptosis of PCa cells were assessed by the Cell Counting Kit 8 (CCK8) assay, cell cycle analysis and caspase3 activity analysis, respectively. Western blot analysis was used for the detection of PCNA, Caspase3 and APPL1 protein levels. Serum and prostatic oxytocin levels are increased in the PCa subjects. Serum oxytocin level may be a biomarker for PCa in the future. Oxytocin increases PCa growth and APPL1 expression.

A pilot study assessing the association between paraoxonase 1 gene polymorphism and prostate cancer.

PubMed

Uluocak, Nihat; Atılgan, Doğan; Parlaktaş, Bekir Süha; Erdemir, Fikret; Ateş, Ömer

2017-09-01

We aimed to show the relationship between paraoxonase 1 (PON1) gene polymorphism and the development of prostate cancer (PCa). We investigated the association of single nuclotide polymorphisms of PON1 enzyme with the development of PCa risk. A total of 147 male patients were divided into PCa, and control groups. The control group was also divided into two subgroups according to serum prostate specific antigen (PSA) levels as non PCa-high PSA (>4 ng/mL) and non PCa-low PSA (≤4 ng/mL) groups. The mean ages of the patients were 64.81 years, 63.27 years and 64.22 years in PCa group, non PCa-low PSA and non PCa -high PSA groups, respectively. The mean PSA levels were 10.9 ng/mL, 1.16 ng/mL and 6.63 ng/mL for PCa group, non PCa -low PSA and non PCa -high PSA groups, respectively. In terms of PON1 polymorphisms and allele frequencies, there were no statistically significant differences between PCa and control groups. There was not a statistically significant difference between PCa and non PCa-high PSA groups as for genotypic and allelic frequencies. As a result of this small sample sized hypothetical study of polymorphism, a relationship could not be detected between PCa development and PON1 gene polymorphism. According to the results of this preliminary study, it is thought that more comprehensive future studies are necessary to clarify the possible role of PON1 gene polymorphism in the etiology of PCa.

A pilot study assessing the association between paraoxonase 1 gene polymorphism and prostate cancer

PubMed Central

Uluocak, Nihat; Atılgan, Doğan; Parlaktaş, Bekir Süha; Erdemir, Fikret; Ateş, Ömer

2017-01-01

Objective We aimed to show the relationship between paraoxonase 1 (PON1) gene polymorphism and the development of prostate cancer (PCa). Material and methods We investigated the association of single nuclotide polymorphisms of PON1 enzyme with the development of PCa risk. A total of 147 male patients were divided into PCa, and control groups. The control group was also divided into two subgroups according to serum prostate specific antigen (PSA) levels as non PCa-high PSA (>4 ng/mL) and non PCa-low PSA (≤4 ng/mL) groups. Results The mean ages of the patients were 64.81 years, 63.27 years and 64.22 years in PCa group, non PCa-low PSA and non PCa –high PSA groups, respectively. The mean PSA levels were 10.9 ng/mL, 1.16 ng/mL and 6.63 ng/mL for PCa group, non PCa –low PSA and non PCa –high PSA groups, respectively. In terms of PON1 polymorphisms and allele frequencies, there were no statistically significant differences between PCa and control groups. There was not a statistically significant difference between PCa and non PCa-high PSA groups as for genotypic and allelic frequencies. As a result of this small sample sized hypothetical study of polymorphism, a relationship could not be detected between PCa development and PON1 gene polymorphism. Conclusion According to the results of this preliminary study, it is thought that more comprehensive future studies are necessary to clarify the possible role of PON1 gene polymorphism in the etiology of PCa. PMID:28861298

Microfluidic-integrated patterned ITO immunosensor for rapid detection of prostate-specific membrane antigen biomarker in prostate cancer.

PubMed

Seenivasan, Rajesh; Singh, Chandra K; Warrick, Jay W; Ahmad, Nihal; Gunasekaran, Sundaram

2017-09-15

An optically transparent patterned indium tin oxide (ITO) three-electrode sensor integrated with a microfluidic channel was designed for label-free immunosensing of prostate-specific membrane antigen (PSMA), a prostate cancer (PCa) biomarker, expressed on prostate tissue and circulating tumor cells but also found in serum. The sensor relies on cysteamine capped gold nanoparticles (N-AuNPs) covalently linked with anti-PSMA antibody (Ab) for target specificity. A polydimethylsiloxane (PDMS) microfluidic channel is used to efficiently and reproducibly introduce sample containing soluble proteins/cells to the sensor. The PSMA is detected and quantified by measuring the change in differential pulse voltammetry signal of a redox probe ([Fe(CN) 6 ] 3- /[Fe(CN) 6 ] 4- ) that is altered upon binding of PSMA with PSMA-Ab immobilized on N-AuNPs/ITO. Detection of PSMA expressing cells and soluble PSMA was tested. The limit of detection (LOD) of the sensor for PSMA-based PCa cells is 6/40µL (i.e., 150 cells/mL) (n=3) with a linear range of 15-400 cells/40µL (i.e., 375-10,000 cells/mL), and for the soluble PSMA is 0.499ng/40µL (i.e., 12.5ng/mL) (n=3) with the linear range of 0.75-250ng/40µL (i.e., 19-6250ng/mL), both with an incubation time of 10min. The results indicate that the sensor has a suitable sensitivity and dynamic range for routine detection of PCa circulating tumor cells and can be adapted to detect other biomarkers/cancer cells. Copyright © 2017 Elsevier B.V. All rights reserved.

Gabor-based kernel PCA with fractional power polynomial models for face recognition.

PubMed

Liu, Chengjun

2004-05-01

This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition. Gabor wavelets first derive desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. The kernel PCA method is then extended to include fractional power polynomial models for enhanced face recognition performance. A fractional power polynomial, however, does not necessarily define a kernel function, as it might not define a positive semidefinite Gram matrix. Note that the sigmoid kernels, one of the three classes of widely used kernel functions (polynomial kernels, Gaussian kernels, and sigmoid kernels), do not actually define a positive semidefinite Gram matrix either. Nevertheless, the sigmoid kernels have been successfully used in practice, such as in building support vector machines. In order to derive real kernel PCA features, we apply only those kernel PCA eigenvectors that are associated with positive eigenvalues. The feasibility of the Gabor-based kernel PCA method with fractional power polynomial models has been successfully tested on both frontal and pose-angled face recognition, using two data sets from the FERET database and the CMU PIE database, respectively. The FERET data set contains 600 frontal face images of 200 subjects, while the PIE data set consists of 680 images across five poses (left and right profiles, left and right half profiles, and frontal view) with two different facial expressions (neutral and smiling) of 68 subjects. The effectiveness of the Gabor-based kernel PCA method with fractional power polynomial models is shown in terms of both absolute performance indices and comparative performance against the PCA method, the kernel PCA method with polynomial kernels, the kernel PCA method with fractional power polynomial models, the Gabor wavelet-based PCA method, and the Gabor wavelet-based kernel PCA method with polynomial kernels.

Percentage of free prostate-specific antigen (PSA) is a useful method in deciding to perform prostate biopsy with higher core numbers in patients with low PSA cut-off values.

PubMed

Yilmaz, Hasan; Ciftci, Seyfettin; Yavuz, Ufuk; Ustuner, Murat; Saribacak, Ali; Dillioglugil, Ozdal

2015-06-01

The aim of this study was to evaluate the predictive role of percentage of free prostate-specific antigen (%fPSA) cut-points in prostate cancer (PCa) detection in patients with total PSA (tPSA) levels between 2.5 ng/mL and 10.0 ng/mL. In total, 1321 consecutive initial transrectal ultrasound (TRUS)-guided 12-core biopsies performed between 2005 and 2011 were evaluated retrospectively. Benign pathologies, high-grade prostatic intraepithelial neoplasia, and atypical small acinary proliferations were categorized as noncancerous (benign), and prostate adenocarcinomas were categorized as cancerous (malignant). The patients were categorized according to: Catalona's published %fPSA categories (<10%, 10-15%, 15-20%, 20-25%, or > 25%); digital rectal examination (DRE) results [benign (negative) or suspicious of malignancy (positive)]. There was a significant relationship between the %fPSA cut-points and detection of PCa in DRE-negative patients. The presence of a 10% cut-point increased the probability of PCa threefold. The %fPSA was significantly more related to PCa than the tPSA value in receiver operating characteristic (ROC) curve analyses (p = 0.001). Based on our findings, a lower %fPSA, especially <10%, is an important parameter when deciding whether to perform a biopsy on patients with a tPSA between 2.5 ng/mL and 10 ng/mL. Copyright © 2015. Published by Elsevier Taiwan.

Detection of compatibility between baclofen and excipients with aid of infrared spectroscopy and chemometry

NASA Astrophysics Data System (ADS)

Rojek, Barbara; Wesolowski, Marek; Suchacz, Bogdan

2013-12-01

In the paper infrared (IR) spectroscopy and multivariate exploration techniques: principal component analysis (PCA) and cluster analysis (CA) were applied as supportive methods for the detection of physicochemical incompatibilities between baclofen and excipients. In the course of research, the most useful rotational strategy in PCA proved to be varimax normalized, while in CA Ward's hierarchical agglomeration with Euclidean distance measure enabled to yield the most interpretable results. Chemometrical calculations confirmed the suitability of PCA and CA as the auxiliary methods for interpretation of infrared spectra in order to recognize whether compatibilities or incompatibilities between active substance and excipients occur. On the basis of IR spectra and the results of PCA and CA it was possible to demonstrate that the presence of lactose, β-cyclodextrin and meglumine in binary mixtures produce interactions with baclofen. The results were verified using differential scanning calorimetry, differential thermal analysis, thermogravimetry/differential thermogravimetry and X-ray powder diffraction analyses.

Differential research of inflammatory and related mediators in BPH, histological prostatitis and PCa.

PubMed

Huang, T R; Wang, G C; Zhang, H M; Peng, B

2018-02-14

Prostate cancer (PCa) is one of the most common male malignancies in the world. It was aimed to investigate differential expression of inflammatory and related factors in benign prostatic hyperplasia (BPH), prostate cancer (PCa), histological prostatitis (HP) and explore the role of Inducible nitric oxide synthase (iNOS), (VEGF) Vascular endothelial growth factor, androgen receptor (AR) and IL-2, IL-8 and TNF-α in the occurrence and development of prostate cancer. RT-PCR was used to detect the mRNA expression level of iNOS, VEGF, AR and IL-2, IL-8 and TNF-α in BPH, PCa and BPH+HP. Western blotting and immunohistochemical staining were used to detect the protein levels of various proteins in three diseases. The results showed the mRNA and protein levels of iNOS, VEGF and IL-2, IL-8 and TNF-α were significantly increased in PCa and BPH+HP groups compared with BPH group (p < .05), while the AR was significantly lower than those in PCa and BPH+HP groups (p < .05). There was no significant difference in the mRNA and protein levels of iNOS, VEGF, AR and IL-2, IL-8 and TNF-α between PCa and BPH+HP groups (p > .05). iNOS, VEGF, AR and IL-2, IL-8 and TNF-α are involved in the malignant transformation of prostate tissue and play an important role in the development and progression of Prostate cancer (PCa). © 2018 Blackwell Verlag GmbH.

Study on the echinococcosis blood serum detection based on Raman spectroscopy combined with neural network

NASA Astrophysics Data System (ADS)

Cheng, Jin-ying; Xu, Liang; Lü, Guo-dong; Tang, Jun; Mo, Jia-qing; Lü, Xiao-yi; Gao, Zhi-xian

2017-01-01

A Raman spectroscopy method combined with neural network is used for the invasive and rapid detection of echinococcosis. The Raman spectroscopy measurements are performed on two groups of blood serum samples, which are from 28 echinococcosis patients and 38 healthy persons, respectively. The normalized Raman reflection spectra show that the reflectivity of the echinococcosis blood serum is higher than that of the normal human blood serum in the wavelength ranges of 101—175 nm and 1 801—2 701 nm. Then the principal component analysis (PCA) and back propagation neural network (BPNN) model are used to obtain the diagnosis results. The diagnosis rates for healthy persons and echinococcosis persons are 93.333 3% and 90.909 1%, respectively, so the average final diagnosis rate is 92.121 2%. The results demonstrate that the Raman spectroscopy analysis of blood serum combined with PCA-BPNN has considerable potential for the non-invasive and rapid detection of echinococcosis.

[Research on fast classification based on LIBS technology and principle component analyses].

PubMed

Yu, Qi; Ma, Xiao-Hong; Wang, Rui; Zhao, Hua-Feng

2014-11-01

Laser-induced breakdown spectroscopy (LIBS) and the principle component analysis (PCA) were combined to study aluminum alloy classification in the present article. Classification experiments were done on thirteen different kinds of standard samples of aluminum alloy which belong to 4 different types, and the results suggested that the LIBS-PCA method can be used to aluminum alloy fast classification. PCA was used to analyze the spectrum data from LIBS experiments, three principle components were figured out that contribute the most, the principle component scores of the spectrums were calculated, and the scores of the spectrums data in three-dimensional coordinates were plotted. It was found that the spectrum sample points show clear convergence phenomenon according to the type of aluminum alloy they belong to. This result ensured the three principle components and the preliminary aluminum alloy type zoning. In order to verify its accuracy, 20 different aluminum alloy samples were used to do the same experiments to verify the aluminum alloy type zoning. The experimental result showed that the spectrum sample points all located in their corresponding area of the aluminum alloy type, and this proved the correctness of the earlier aluminum alloy standard sample type zoning method. Based on this, the identification of unknown type of aluminum alloy can be done. All the experimental results showed that the accuracy of principle component analyses method based on laser-induced breakdown spectroscopy is more than 97.14%, and it can classify the different type effectively. Compared to commonly used chemical methods, laser-induced breakdown spectroscopy can do the detection of the sample in situ and fast with little sample preparation, therefore, using the method of the combination of LIBS and PCA in the areas such as quality testing and on-line industrial controlling can save a lot of time and cost, and improve the efficiency of detection greatly.

Prostate cancer antigen 3 gene expression in peripheral blood and urine sediments from prostate cancer and benign prostatic hyperplasia patients versus healthy individuals.

PubMed

Moradi Sardareh, Hemen; Goodarzi, Mohammad Taghi; Yadegar-Azari, Reza; Poorolajal, Jalal; Mousavi-Bahar, Seyed Habibollah; Saidijam, Massoud

2014-11-30

To determine the expression of prostate cancer antigen 3 (PCA3) gene in peripheral blood and urine sediments from patients with prostate cancer (PCa) and benign prostatic hyperplasia (BPH) and normal subjects. A total number of 48 patients [24 with biopsy proven prostate cancer (PCa) and 24 with benign prostate hyperplasia (BPH)] were studied. Twenty-four healthy individuals were also recruited as control group. After blood and urine sampling, total RNA was extracted and cDNA was synthesized. Expression of PCA3 gene was assessed by quantitative reverse transcription polymerase chain reaction. Comparison of PCA3 gene expression between control and BPH groups indicated no statistically significant differences in both urine and blood samples. Patients with PCa demonstrated an increased PCA3 gene expression rate compared to control and BPH groups (10.64 and 7.17 folds, respectively). The rate of fold increased PCA3 gene expression in urine was 20.90, 20.90, and 20.35 in patients with PCa, BPH and normal subjects, respectively. Evaluation of PCA3 gene expression can be considered as a reliable marker for detection of PCa. Increased level of this marker in urine sediments is more sensitive than blood for distinguishing between cancerous and non-cancerous groups. 

An adaptive confidence limit for periodic non-steady conditions fault detection

NASA Astrophysics Data System (ADS)

Wang, Tianzhen; Wu, Hao; Ni, Mengqi; Zhang, Milu; Dong, Jingjing; Benbouzid, Mohamed El Hachemi; Hu, Xiong

2016-05-01

System monitoring has become a major concern in batch process due to the fact that failure rate in non-steady conditions is much higher than in steady ones. A series of approaches based on PCA have already solved problems such as data dimensionality reduction, multivariable decorrelation, and processing non-changing signal. However, if the data follows non-Gaussian distribution or the variables contain some signal changes, the above approaches are not applicable. To deal with these concerns and to enhance performance in multiperiod data processing, this paper proposes a fault detection method using adaptive confidence limit (ACL) in periodic non-steady conditions. The proposed ACL method achieves four main enhancements: Longitudinal-Standardization could convert non-Gaussian sampling data to Gaussian ones; the multiperiod PCA algorithm could reduce dimensionality, remove correlation, and improve the monitoring accuracy; the adaptive confidence limit could detect faults under non-steady conditions; the fault sections determination procedure could select the appropriate parameter of the adaptive confidence limit. The achieved result analysis clearly shows that the proposed ACL method is superior to other fault detection approaches under periodic non-steady conditions.

Detection of Fungus Infection on Petals of Rapeseed (Brassica napus L.) Using NIR Hyperspectral Imaging

NASA Astrophysics Data System (ADS)

Zhao, Yan-Ru; Yu, Ke-Qiang; Li, Xiaoli; He, Yong

2016-12-01

Infected petals are often regarded as the source for the spread of fungi Sclerotinia sclerotiorum in all growing process of rapeseed (Brassica napus L.) plants. This research aimed to detect fungal infection of rapeseed petals by applying hyperspectral imaging in the spectral region of 874-1734 nm coupled with chemometrics. Reflectance was extracted from regions of interest (ROIs) in the hyperspectral image of each sample. Firstly, principal component analysis (PCA) was applied to conduct a cluster analysis with the first several principal components (PCs). Then, two methods including X-loadings of PCA and random frog (RF) algorithm were used and compared for optimizing wavebands selection. Least squares-support vector machine (LS-SVM) methodology was employed to establish discriminative models based on the optimal and full wavebands. Finally, area under the receiver operating characteristics curve (AUC) was utilized to evaluate classification performance of these LS-SVM models. It was found that LS-SVM based on the combination of all optimal wavebands had the best performance with AUC of 0.929. These results were promising and demonstrated the potential of applying hyperspectral imaging in fungus infection detection on rapeseed petals.

Incidental prostate cancer in radical cystoprostatectomy specimens.

PubMed

Jin, Xiao-Dong; Chen, Zhao-Dian; Wang, Bo; Cai, Song-Liang; Yao, Xiao-Lin; Jin, Bai-Ye

2008-09-01

To investigate the rates of prostate cancer (PCa) in radical cystoprostatectomy (RCP) specimens for bladder cancer in mainland China. To determine the follow-up outcome of patients with two concurrent cancers and identify whether prostate-specific antigen (PSA) is a useful tool for the detection of PCa prior to surgery. From January 2002 to January 2007, 264 male patients with bladder cancer underwent RCP at our center. All patients underwent digital rectal examination (DRE) and B ultrasound. Serum PSA levels were tested in 168 patients. None of the patients had any evidence of PCa before RCP. Entire prostates were embedded and sectioned at 5 mm intervals. Incidental PCa was observed in 37 of 264 (14.0%) RCP specimens. Of these, 12 (32.4%) were clinically significant according to an accepted definition. The PSA levels were not significantly different between patients with PCa and those without PCa, nor between patients with significant PCa and those with insignificant PCa. Thirty-four patients with incidental PCa were followed up. During a mean follow-up period of 26 months, two patients with PSA > 4 ng/mL underwent castration. None of the patients died of PCa. The incidence of PCa in RCP specimens in mainland China is lower than that in most developed countries. PSA cannot identify asymptomatic PCa prior to RCP. In line with published reports, incidental PCa does not impact the prognosis of bladder cancer patients undergoing RCP. (c) 2008, Asian Journal of Andrology, SIMM and SJTU. All rights reserved.

A Multiplex Cancer/Testis Antigen-Based Biomarker Panel to Predict the Aggressive Phenotype of Prostate Cancer

DTIC Science & Technology

2016-09-01

US (Siegel et al., 2014). The introduction of the prostate specific antigen ( PSA ) test has greatly aided to the early detection of PCa. Detectable...levels of PSA are the earliest sign of recurrent disease after radical prostatectomy (RP) (Pound et al., 1999). Besides its sensitiveness, it is...estimated that 23-44% of patients submitted to RP will progress with detectable PSA levels and will never present recurrence (Draisma et al., 2009). Thus

Genetic Progression of High Grade Prostatic Intraepithelial Neoplasia to Prostate Cancer.

PubMed

Jung, Seung-Hyun; Shin, Sun; Kim, Min Sung; Baek, In-Pyo; Lee, Ji Youl; Lee, Sung Hak; Kim, Tae-Min; Lee, Sug Hyung; Chung, Yeun-Jun

2016-05-01

Although high grade prostatic intraepithelial neoplasia (HGPIN) is considered a neoplastic lesion that precedes prostate cancer (PCA), the genomic structures of HGPIN remain unknown. Identification of the genomic landscape of HGPIN and the genomic differences between HGPIN and PCA that may drive the progression to PCA. We analyzed 20 regions of paired HGPIN and PCA from six patients using whole-exome sequencing and array-comparative genomic hybridization. Somatic mutation and copy number alteration (CNA) profiles of paired HGPIN and PCA were measured and compared. The number of total mutations and CNAs of HGPINs were significantly fewer than those of PCAs. Mutations in FOXA1 and CNAs (1q and 8q gains) were detected in both HGPIN and PCA ('common'), suggesting their roles in early PCA development. Mutations in SPOP, KDM6A, and KMT2D were 'PCA-specific', suggesting their roles in HGPIN progression to PCA. The 8p loss was either 'common' or 'PCA-specific'. In-silico estimation of evolutionary ages predicted that HGPIN genomes were much younger than PCA genomes. Our data show that PCAs are direct descendants of HGPINs in most cases that require more genomic alterations to progress to PCA. The nature of heterogeneous HGPIN population that might attenuate genomic signals should further be studied. HGPIN genomes harbor relatively fewer mutations and CNAs than PCA but require additional hits for the progression. In this study, we suggest a systemic diagram from high grade prostatic intraepithelial neoplasia (HGPIN) to prostate cancer (PCA). Our results provide a clue to explain the long latency from HGPIN to PCA and provide useful information for the genetic diagnosis of HGPIN and PCA. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Detecting phase separation of freeze-dried binary amorphous systems using pair-wise distribution function and multivariate data analysis.

PubMed

Chieng, Norman; Trnka, Hjalte; Boetker, Johan; Pikal, Michael; Rantanen, Jukka; Grohganz, Holger

2013-09-15

The purpose of this study is to investigate the use of multivariate data analysis for powder X-ray diffraction-pair-wise distribution function (PXRD-PDF) data to detect phase separation in freeze-dried binary amorphous systems. Polymer-polymer and polymer-sugar binary systems at various ratios were freeze-dried. All samples were analyzed by PXRD, transformed to PDF and analyzed by principal component analysis (PCA). These results were validated by differential scanning calorimetry (DSC) through characterization of glass transition of the maximally freeze-concentrate solute (Tg'). Analysis of PXRD-PDF data using PCA provides a more clear 'miscible' or 'phase separated' interpretation through the distribution pattern of samples on a score plot presentation compared to residual plot method. In a phase separated system, samples were found to be evenly distributed around the theoretical PDF profile. For systems that were miscible, a clear deviation of samples away from the theoretical PDF profile was observed. Moreover, PCA analysis allows simultaneous analysis of replicate samples. Comparatively, the phase behavior analysis from PXRD-PDF-PCA method was in agreement with the DSC results. Overall, the combined PXRD-PDF-PCA approach improves the clarity of the PXRD-PDF results and can be used as an alternative explorative data analytical tool in detecting phase separation in freeze-dried binary amorphous systems. Copyright © 2013 Elsevier B.V. All rights reserved.

An Android malware detection system based on machine learning

NASA Astrophysics Data System (ADS)

Wen, Long; Yu, Haiyang

2017-08-01

The Android smartphone, with its open source character and excellent performance, has attracted many users. However, the convenience of the Android platform also has motivated the development of malware. The traditional method which detects the malware based on the signature is unable to detect unknown applications. The article proposes a machine learning-based lightweight system that is capable of identifying malware on Android devices. In this system we extract features based on the static analysis and the dynamitic analysis, then a new feature selection approach based on principle component analysis (PCA) and relief are presented in the article to decrease the dimensions of the features. After that, a model will be constructed with support vector machine (SVM) for classification. Experimental results show that our system provides an effective method in Android malware detection.

Hsp70 and gama-Semino protein as possible prognostic marker of prostate cancer.

PubMed

Kumar, Sanjay; Gurshaney, Sanjeev; Adagunodo, Yori; Gage, Erica; Qadri, Shezreen; Sharma, Mahak; Malik, Shalie; Manne, Upender; Singh, Udai P; Singh, Rajesh; Mishra, Manoj K

2018-06-01

In the United States, Prostate Cancer (PCa) is the leading cause of cancer-related mortality in men. PCa resulted in abnormal growth and function of prostate gland such as secretion of high level of gamma-seminoprotein (gama-SM)/Prostate-Specific Antigen (PSA) which could be detected in the blood. Beside gama-SM protein, the levels of heat shock proteins (Hsp70) were also observed significantly high. Therefore, gama-SM and Hsp70 are unique proteins with high potential for PCa therapeutics and diagnostics. High level of Hsp70 suppresses apoptosis, thus allowing PCa cells to exist; however, depletion of Hsp70 induces apoptosis in PCa cells. Gama-SM is the most prominent biomarker for PCa screening; however, its accuracy is still questionable. Thus, a more suitable streamline biomarker for PCa screening is urgently needed. Hsp70 and gama-SM proteins could be used as a revolutionary biomarker for PCa, and could help to identify possible therapeutic target(s). In this review article we will discuss the relationship between the Hsp70 and gama-SM proteins with PCa, their potential as a dual biomarker, and the possibility for both proteins being used as therapeutic targets.

Circular RNA Myosin Light Chain Kinase (MYLK) Promotes Prostate Cancer Progression through Modulating Mir-29a Expression.

PubMed

Dai, Yuanqing; Li, Dongjie; Chen, Xiong; Tan, Xinji; Gu, Jie; Chen, Mingquan; Zhang, Xiaobo

2018-05-25

BACKGROUND In developed countries, prostate cancer (PCa) is a frequently diagnosed cancer with the second highest fatality rate. Circular RNAs (circRNAs) are a class of endogenous non-coding RNAs (ncRNAs) stably expressed in cells and involved in a series of carcinomas. However, few research studies have reported on the role of circRNAs in PCa. MATERIAL AND METHODS We used qRT-PCR to detect the expression of circMYLK (circRNA ID: hsa_circ_0141940) and miR-29a in PCa tissues and cell lines. MTT, colony formation, and TUNEL assays were performed to analysis the cell viability of PCa cells. Transwell and wound scratch assays were performed to investigate the cell invasion and migration of PCa cells. RESULTS In the present study, we confirmed that circMYLK expression level was significantly higher in PCa samples and PCa cells than in normal tissues and normal prostatic cells. The upregulated circRNA-MYLK promoted PCa cells proliferation, invasion, and migration; however, si-circRNA-MYLK significantly accelerated the PCa cell apoptosis. We also observed that the aforementioned function of circRNA-MYLK on PCa cells was affected through targeting miR-29a. CONCLUSIONS We confirmed circRNA-MYLK was an oncogene in PCa and revealed a novel mechanism underlying circRNA-MYLK in PC progression.

Longer biopsy cores do not increase prostate cancer detection rate: A large-scale cohort study refuting cut-off values indicated in the literature

PubMed Central

Yılmaz, Hasan; Yavuz, Ufuk; Üstüner, Murat; Çiftçi, Seyfettin; Yaşar, Hikmet; Müezzinoğlu, Bahar; Uslubaş, Ali Kemal; Dillioğlugil, Özdal

2017-01-01

Objective Only a few papers in the literature aimed to evaluate biopsy core lengths. Additionally, studies evaluated the core length with different approaches. We aimed to determine whether prostate cancer (PCa) detection is affected from core lengths according to three different approaches in a large standard cohort and compare our cut-off values with the published cut-offs. Material and methods We retrospectively analyzed 1,523 initial consecutive transrectal ultrasound-guided 12-core prostate biopsies. Biopsies were evaluated with respect to total core length (total length of each patients’ core) average core length (total core length divided by total number of cores in each patient), and mean core length (mean length of all cores pooled), and compared our cut-off values with the published cut-offs. The prostate volumes were categorized into four groups (<30, 30–59.99, 60–119.99, ≥120 cm3) and PCa detection rates in these categories were examined. Results PCa was found in 41.5% patients. There was no difference between benign and malignant mean core lengths of the pooled cores (p>0.05). Total core length and average core length were not significantly associated with PCa in multivariate logistic regression analyses (p>0.05). The core lengths (mean, average and total core lengths) increased (p<0.001) and PCa rates decreased (p<0.001) steadily with increasing prostate volume categories. PCa percentages decreased in all categories above the utilized cut-offs for mean (p>0.05), average (p<0.05), and total core lengths (p>0.05). Conclusion There was no difference between mean core lengths of benign and malignant cores. Total core length and average core length were not significantly associated with PCa. Contrary to the cut-offs used for mean and average core lengths in the published studies, PCa rates decrease as these core lengths increase. Larger studies are necessary for the determination and acceptance of accurate cut-offs. PMID:28861301

Value of Endorectal MRI in Romanian Men for High Risk of Prostate Cancer: MRI Findings Compared with Saturation Biopsy.

PubMed

Lebovici, A; Sfrangeu, S A; Caraiani, C; Lucan, C; Suciu, M; Elec, F; Iacob, Gh; Buruian, M

2015-01-01

To evaluate the potentials of T2 weighted (T2W)MRI and diffusion weighted (DW) MRI for prostate cancer(PCa) detection, local staging and treatment planning in high-risk group. Endorectal MRI was performed in 17 Romanian men (median age: 66 years; range: 58 75 years), prostate specific antigen (PSA) serum levels (median: 20 ng mL; range: 8.6 100 ng mL) with positive findings for PCa(median Gleason score: 8; range: 7 - 9). Imaging findings were compared to standarised 20-core transperineal saturation biopsy. The prostate was divided into 16 standart sectors(10 posterior and 6 anterior). Overall, prostate cancer was detected in 16 patients(94%) on DW-MRI alone and in all 17 patients (100%) on T2W-MRI alone, and on combined imaging. On T2W-MRI165 sectors out of 272 were suspicious for PCa and 124 (75%)were cancer positive. On DW-MRI 126 sectors out of 272 were suspicious for PCa and 118 (95%) were cancer positive. On the combined imaging approach 134 sectors out of 272 were suspicious for PCa and 126 (94%) were cancer positive. This resulted in diagnostic accuracies per sector of 76% for T2WMRI, 86% for DW-MRI and 89% for combined imaging. Multifocal PCa was confirmed both on MR imaging and by biopsy in 8 of the 17 men (47%) Extra capsular extension(ECE) or seminal vesicles invasion (SVI) was highly suspected in 8 (47%) respectively 7 (41%) of the 17 patients. 6 patients(35%) presented both ECE and SVI. MRI findings were taken into account for treatment planning and none of these patients underwent radical prostatectomy and instead was treated with palliative cryotherapy, radiotherapy and hormone therapy. Endorectal MRI is highly accurate in PCa detection in the high-risk group and seems to have an important role in local staging and treatment planning for Romanian population. Celsius.

Relationship Between Prebiopsy Multiparametric Magnetic Resonance Imaging (MRI), Biopsy Indication, and MRI-ultrasound Fusion-targeted Prostate Biopsy Outcomes.

PubMed

Meng, Xiaosong; Rosenkrantz, Andrew B; Mendhiratta, Neil; Fenstermaker, Michael; Huang, Richard; Wysock, James S; Bjurlin, Marc A; Marshall, Susan; Deng, Fang-Ming; Zhou, Ming; Melamed, Jonathan; Huang, William C; Lepor, Herbert; Taneja, Samir S

2016-03-01

Increasing evidence supports the use of magnetic resonance imaging (MRI)-ultrasound fusion-targeted prostate biopsy (MRF-TB) to improve the detection of clinically significant prostate cancer (PCa) while limiting detection of indolent disease compared to systematic 12-core biopsy (SB). To compare MRF-TB and SB results and investigate the relationship between biopsy outcomes and prebiopsy MRI. Retrospective analysis of a prospectively acquired cohort of men presenting for prostate biopsy over a 26-mo period. A total of 601 of 803 consecutively eligible men were included. All men were offered prebiopsy MRI and assigned a maximum MRI suspicion score (mSS). Men with an MRI abnormality underwent combined MRF-TB and SB. Detection rates for all PCa and high-grade PCa (Gleason score [GS] ≥7) were compared using the McNemar test. MRF-TB detected fewer GS 6 PCas (75 vs 121; p<0.001) and more GS ≥7 PCas (158 vs 117; p<0.001) than SB. Higher mSS was associated with higher detection of GS ≥7 PCa (p<0.001) but was not correlated with detection of GS 6 PCa. Prediction of GS ≥7 disease by mSS varied according to biopsy history. Compared to SB, MRF-TB identified more GS ≥7 PCas in men with no prior biopsy (88 vs 72; p=0.012), in men with a prior negative biopsy (28 vs 16; p=0.010), and in men with a prior cancer diagnosis (42 vs 29; p=0.043). MRF-TB detected fewer GS 6 PCas in men with no prior biopsy (32 vs 60; p<0.001) and men with prior cancer (30 vs 46; p=0.034). Limitations include the retrospective design and the potential for selection bias given a referral population. MRF-TB detects more high-grade PCas than SB while limiting detection of GS 6 PCa in men presenting for prostate biopsy. These findings suggest that prebiopsy multiparametric MRI and MRF-TB should be considered for all men undergoing prostate biopsy. In addition, mSS in conjunction with biopsy indications may ultimately help in identifying men at low risk of high-grade cancer for whom prostate biopsy may not be warranted. We examined how magnetic resonance imaging (MRI)-targeted prostate biopsy compares to traditional systematic biopsy in detecting prostate cancer among men with suspicion of prostate cancer. We found that MRI-targeted biopsy detected more high-grade cancers than systematic biopsy, and that MRI performed before biopsy can predict the risk of high-grade cancer. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Elevated levels of circulating IL-7 and IL-15 in patients with early stage prostate cancer

PubMed Central

2011-01-01

Background Chronic inflammation has been suggested to favour prostate cancer (PCA) development. Interleukins (IL) represent essential inflammation mediators. IL-2, IL-7, IL-15 and IL-21, sharing a common receptor γ chain (c-γ), control T lymphocyte homeostasis and proliferation and play major roles in regulating cancer-immune system interactions. We evaluated local IL-2, IL-7, IL-15 and IL-21 gene expression in prostate tissues from patients with early stage PCA or benign prostatic hyperplasia (BPH). As control, we used IL-6 gene, encoding an IL involved in PCA progression. IL-6, IL-7 and IL-15 titres were also measured in patients' sera. Methods Eighty patients with BPH and 79 with early (1 to 2c) stage PCA were enrolled. Gene expression in prostate tissues was analyzed by quantitative real-time PCR (qRT-PCR). Serum IL concentrations and acute phase protein titres were evaluated by ELISA. Mann-Whitney, Wilcoxon and χ2 tests were used to compare IL gene expression and serum titers in the two groups of patients. Receiver operating characteristic (ROC) curves were constructed to evaluate the possibility to distinguish sera from different groups of patients based on IL titers. Results IL-2 and IL-21 gene expression was comparably detectable, with low frequency and at low extents, in PCA and BPH tissues. In contrast, IL-6, IL-7 and IL-15 genes were expressed more frequently (p < 0.0001, p = 0.0047 and p = 0.0085, respectively) and to significantly higher extents (p = 0.0051, p = 0.0310 and p = 0.0205, respectively) in early stage PCA than in BPH tissues. Corresponding proteins could be detected to significantly higher amounts in sera from patients with localized PCA, than in those from patients with BPH (p = 0.0153, p = 0.0174 and p = 0.0064, respectively). Analysis of ROC curves indicates that IL-7 (p = 0.0039), but not IL-6 (p = 0.2938) or IL-15 (p = 0.1804) titres were able to distinguish sera from patients with malignancy from those from patients with benign disease. Serum titres of C reactive (CRP), high mobility group B1 (HMGB1) and serum amyloid A (SAA) acute phase proteins were similar in both groups of patients. Conclusions Expression IL-7 and IL-15 genes in prostate tissues and corresponding serum titres are significantly increased in patients with early stage PCA as compared with patients with BPH. PMID:21943235

In-vivo detection of binary PKA network interactions upon activation of endogenous GPCRs

PubMed Central

Röck, Ruth; Bachmann, Verena; Bhang, Hyo-eun C; Malleshaiah, Mohan; Raffeiner, Philipp; Mayrhofer, Johanna E; Tschaikner, Philipp M; Bister, Klaus; Aanstad, Pia; Pomper, Martin G; Michnick, Stephen W; Stefan, Eduard

2015-01-01

Membrane receptor-sensed input signals affect and modulate intracellular protein-protein interactions (PPIs). Consequent changes occur to the compositions of protein complexes, protein localization and intermolecular binding affinities. Alterations of compartmentalized PPIs emanating from certain deregulated kinases are implicated in the manifestation of diseases such as cancer. Here we describe the application of a genetically encoded Protein-fragment Complementation Assay (PCA) based on the Renilla Luciferase (Rluc) enzyme to compare binary PPIs of the spatially and temporally controlled protein kinase A (PKA) network in diverse eukaryotic model systems. The simplicity and sensitivity of this cell-based reporter allows for real-time recordings of mutually exclusive PPIs of PKA upon activation of selected endogenous G protein-coupled receptors (GPCRs) in cancer cells, xenografts of mice, budding yeast, and zebrafish embryos. This extends the application spectrum of Rluc PCA for the quantification of PPI-based receptor-effector relationships in physiological and pathological model systems. PMID:26099953

Detection of l-Cysteine in wheat flour by Raman microspectroscopy combined chemometrics of HCA and PCA.

PubMed

Cebi, Nur; Dogan, Canan Ekinci; Develioglu, Ayşen; Yayla, Mediha Esra Altuntop; Sagdic, Osman

2017-08-01

l-Cysteine is deliberately added to various flour types since l-Cysteine has enabled favorable baking conditions such as low viscosity, increased elasticity and rise during baking. In Turkey, usage of l-Cysteine as a food additive isn't allowed in wheat flour according to the Turkish Food Codex Regulation on food additives. There is an urgent need for effective methods to detect l-Cysteine in wheat flour. In this study, for the first time, a new, rapid, effective, non-destructive and cost-effective method was developed for detection of l-Cysteine in wheat flour using Raman microscopy. Detection of l-Cysteine in wheat flour was accomplished successfully using Raman microscopy combined chemometrics of PCA (Principal Component Analysis) and HCA (Hierarchical Cluster Analysis). In this work, 500-2000cm -1 spectral range (fingerprint region) was determined to perform PCA and HCA analysis. l-Cysteine and l-Cystine were determined with detection limit of 0.125% (w/w) in different wheat flour samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automated matching of supine and prone colonic polyps based on PCA and SVMs

NASA Astrophysics Data System (ADS)

Wang, Shijun; Van Uitert, Robert L.; Summers, Ronald M.

2008-03-01

Computed tomographic colonography (CTC) is a feasible and minimally invasive method for the detection of colorectal polyps and cancer screening. In current practice, a patient will be scanned twice during the CTC examination - once supine and once prone. In order to assist the radiologists in evaluating colon polyp candidates in both scans, we expect the computer aided detection (CAD) system can provide not only the locations of suspicious polyps, but also the possible matched pairs of polyps in two scans. In this paper, we propose a new automated matching method based on the extracted features of polyps by using principal component analysis (PCA) and Support Vector Machines (SVMs). Our dataset comes from the 104 CT scans of 52 patients with supine and prone positions collected from three medical centers. From it we constructed two groups of matched polyp candidates according to the size of true polyps: group A contains 12 true polyp pairs (> 9 mm) and 454 false pairs; group B contains 24 true polyp pairs (6-9 mm) and 514 false pairs. By using PCA, we reduced the dimensions of original data (with 157 attributes) to 30 dimensions. We did leave-one-patient-out test on the two groups of data. ROC analysis shows that it is easier to match bigger polyps than that of smaller polyps. On group A data, when false alarm probability is 0.18, the sensitivity of SVM achieves 0.83 which shows that automated matching of polyp candidates is practicable for clinical applications.

Prostate-specific membrane antigen for prostate cancer theranostics: from imaging to targeted therapy.

PubMed

Arsenault, Frédéric; Beauregard, Jean-Mathieu; Pouliot, Frédéric

2018-06-22

In recent years, major advances in molecular imaging of prostate cancers (PCa) were made with the development and clinical validation of highly accurate PET tracers to stage and restage the disease. Prostate-specific membrane antigen (PSMA) is a transmembrane protein highly expressed in PCa, and its expression has led to the development of PSMA-binding radiopharmaceuticals for molecular imaging or radioligand therapy (RLT). We herein review the recent literature published on diagnostic and therapeutic (i.e. theranostic) PSMA tracers. Development in small PSMA-targeted molecules labeled with gallium-68 and fluorine-18 show promising results for primary staging and detection of disease at biochemical recurrence using PET/computed tomography (PET/CT). Studies show a higher sensitivity and specificity, along with an improved detection rate over conventional imaging (CT scan and bone scan) or choline PET tracers, especially for restaging after prostate-specific antigen failure following loco-regional therapy. In addition, some PSMA tracers can be labeled with beta-minus and alpha particle emitters, yielding encouraging response rates and low toxicity, and potentially offering a new line of targeted therapy for metastatic castration-resistant PCa. PSMA-targeted tracers have shown unprecedented accuracy to stage and restage PCa using PET/CT. Given their specific biodistribution toward PCa tissue, PSMA RLT now offers new therapeutic possibilities to target metastatic PCa. Prospective multicenter randomized studies investigating the clinical impact management impacts of PSMA-targeted molecules are urgently needed.

A comprehensive evaluation of CHEK2 germline mutations in men with prostate cancer.

PubMed

Wu, Yishuo; Yu, Hongjie; Zheng, S Lilly; Na, Rong; Mamawala, Mufaddal; Landis, Tricia; Wiley, Kathleen; Petkewicz, Jacqueline; Shah, Sameep; Shi, Zhuqing; Novakovic, Kristian; McGuire, Michael; Brendler, Charles B; Ding, Qiang; Helfand, Brian T; Carter, H Ballentine; Cooney, Kathleen A; Isaacs, William B; Xu, Jianfeng

2018-06-01

Germline mutations in CHEK2 have been associated with prostate cancer (PCa) risk. Our objective is to examine whether germline pathogenic CHEK2 mutations can differentiate risk of lethal from indolent PCa. A case-case study of 703 lethal PCa patients and 1455 patients with low-risk localized PCa of European, African, and Chinese origin was performed. Germline DNA samples from these patients were sequenced for CHEK2. Mutation carrier rates and their association with lethal PCa were analyzed using the Fisher exact test and Kaplan-Meier survival analysis. In the entire study population, 40 (1.85%) patients were identified as carrying one of 15 different germline CHEK2 pathogenic or likely pathogenic mutations. CHEK2 mutations were detected in 16 (2.28%) of 703 lethal PCa patients compared with 24 (1.65%) of 1455 low-risk PCa patients (P = 0.31). No association was found between CHEK2 mutation status and early-diagnosis or PCa-specific survival time. However, the most common mutation in CHEK2, c.1100delC (p.T367 fs), had a significantly higher carrier rate (1.28%) in lethal PCa patients than low-risk PCa patients of European American origin (0.16%), P = 0.0038. The estimated Odds Ratio of this mutation for lethal PCa was 7.86. The carrier rate in lethal PCa was also significantly higher than that (0.46%) in 32 461 non-Finnish European subjects from the Exome Aggregation Consortium (ExAC) (P = 0.01). While overall CHEK2 mutations were not significantly more common in men with lethal compared to low-risk PCa, the specific CHEK2 mutation, c.1100delC, appears to contribute to an increased risk of lethal PCa in European American men. © 2018 Wiley Periodicals, Inc.

PCA3-based nomogram for predicting prostate cancer and high grade cancer on initial transrectal guided biopsy.

PubMed

Elshafei, Ahmed; Chevli, K Kent; Moussa, Ayman S; Kara, Onder; Chueh, Shih-Chieh; Walter, Peter; Hatem, Asmaa; Gao, Tianming; Jones, J Stephen; Duff, Michael

2015-12-01

To develop a validated prostate cancer antigen 3 (PCA3) based nomogram that predicts likelihood of overall prostate cancer (PCa) and intermediate/high grade prostate cancer (HGPCa) in men pursuing initial transrectal prostate biopsy (TRUS-PBx). Data were collected on 3,675 men with serum prostate specific antigen level (PSA) ≤ 20 ng/ml who underwent initial prostate biopsy with at least 10 cores sampling at time of the biopsy. Two logistic regression models were constructed to predict overall PCa and HGPCa incorporating age, race, family history (FH) of PCa, PSA at diagnosis, PCA3, total prostate volume (TPV), and digital rectal exam (DRE). One thousand six hundred twenty (44%) patients had biopsy confirmed PCa with 701 men (19.1%) showing HGPCa. Statistically significant predictors of overall PCa were age (P < 0.0001, OR. 1.51), PSA at diagnosis (P < 0.0001, OR.1.95), PCA3 (P < 0.0001, OR.3.06), TPV (P < 0.0001, OR.0.47), FH (P = 0.003, OR.1.32), and abnormal DRE (P = 0.001, OR. 1.32). While for HGPCa, predictors were age (P < 0.0001, OR.1.77), PSA (P < 0.0001, OR.2.73), PCA3 (P < 0.0001, OR.2.26), TPV (P < 0.0001, OR.0.4), and DRE (P < 0.0001, OR.1.53). Two nomograms were reconstructed for predicted overall PCa probability at time of initial biopsy with a concordance index of 0.742 (Fig. 1), and HGPCa with a concordance index of 0.768 (Fig. 2). Our internally validated initial biopsy PCA3 based nomogram is reconstructed based on a large dataset. The c-index indicates high predictive accuracy, especially for high grade PCa and improves the ability to predict biopsy outcomes. © 2015 Wiley Periodicals, Inc.

Anomaly Detection in Gamma-Ray Vehicle Spectra with Principal Components Analysis and Mahalanobis Distances

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

Tardiff, Mark F.; Runkle, Robert C.; Anderson, K. K.

2006-01-23

The goal of primary radiation monitoring in support of routine screening and emergency response is to detect characteristics in vehicle radiation signatures that indicate the presence of potential threats. Two conceptual approaches to analyzing gamma-ray spectra for threat detection are isotope identification and anomaly detection. While isotope identification is the time-honored method, an emerging technique is anomaly detection that uses benign vehicle gamma ray signatures to define an expectation of the radiation signature for vehicles that do not pose a threat. Newly acquired spectra are then compared to this expectation using statistical criteria that reflect acceptable false alarm rates andmore » probabilities of detection. The gamma-ray spectra analyzed here were collected at a U.S. land Port of Entry (POE) using a NaI-based radiation portal monitor (RPM). The raw data were analyzed to develop a benign vehicle expectation by decimating the original pulse-height channels to 35 energy bins, extracting composite variables via principal components analysis (PCA), and estimating statistically weighted distances from the mean vehicle spectrum with the mahalanobis distance (MD) metric. This paper reviews the methods used to establish the anomaly identification criteria and presents a systematic analysis of the response of the combined PCA and MD algorithm to modeled mono-energetic gamma-ray sources.« less

Extra virgin (EV) and ordinary (ON) olive oils: distinction and detection of adulteration (EV with ON) as determined by direct infusion electrospray ionization mass spectrometry and chemometric approaches.

PubMed

Alves, Júnia de O; Neto, Waldomiro B; Mitsutake, Hery; Alves, Paulo S P; Augusti, Rodinei

2010-07-15

Extra virgin (EV), the finest and most expensive among all the olive oil grades, is often adulterated by the cheapest and lowest quality ordinary (ON) olive oil. A new methodology is described herein that provides a simple, rapid, and accurate way not only to detect such type of adulteration, but also to distinguish between these olive oil grades (EV and ON). This approach is based on the application of direct infusion electrospray ionization mass spectrometry in the positive ion mode, ESI(+)-MS, followed by the treatment of the MS data via exploratory statistical approaches, PCA (principal component analysis) and HCA (hierarchical clustering analysis). Ten distinct brands of each EV and ON olive oil, acquired at local stores, were analyzed by ESI(+)-MS and the results from HCA and PCA clearly indicated the formation of two distinct groups related to these two categories. For the adulteration study, one brand of each olive oil grade (EV and ON) was selected. The counterfeit samples (a total of 20) were then prepared by adding assorted proportions, from 1 to 20% w/w, with increments of 1% w/w, of the ON to the EV olive oil. The PCA and HCA methodologies, applied to the ESI(+)-MS data from the counterfeit (20) and authentic (10) EV samples, were able to readily detect adulteration, even at levels as low as 1% w/w. Copyright 2010 John Wiley & Sons, Ltd.

[Focusing on MRI-suspected lesions in targeted transrectal prostate biopsy guided by MRI-TRUS fusion imaging for the diagnosis of prostate cancer].

PubMed

Qu, Hua-Wei; Liu, Hui; Cui, Zi-Lian; Jin, Xun-Bo; Zhao, Yong; Wang, Mu-Wen; Song, Wei; Zhang, Xin-Juan

2016-09-01

To improve the accuracy of prostate cancer (PCa) detection by focusing biopsy on the suspected lesion manifested by MRI with the total number of biopsy cores relatively unchanged. A prospective randomized analysis was performed on 262 cases of suspected PCa detected by multi-parametric MRI (mp-MRI), each with a single suspected lesion with 10 μg/L≤ PSA <20 μg/L. All the patients underwent targeted transrectal prostate biopsy guided by fusion imaging of MRI with transrectal ultrasonography (TRUS), using the 6X+6 strategy (6 cores in the suspected region and another 6 in the systematic prostate) for 134 cases and the traditional 12+2X method (12 cores in the systematic prostate and 2 in the suspected region) for the other 128. Comparisons were made between the two methods in the PCa detection rate in the cases of suspected lesion, total PCa detection rate, incidence of post-biopsy complications, and Gleason scores. Analyses were performed on the prostate imaging reporting and data system (PI-RADS) score, location, transverse section, and diameter of the suspected lesion. Both the total PCa detection rate and that in the cases of suspected lesion were significantly higher in the 6X+6 (44.8% and 37.3%) than in the 12+2X group (37.5% and 27.3%) (P<0.05). MRI showed that the suspected lesions were mostly (45%) located in the middle part of the prostate, the mean area of the transverse section was (0.48±0.11) cm2, and the mean diameter of the tumor was (8.51±2.21) mm. The results of biopsy showed that low-grade tumors (Gleason 3+3=6) accounted for 68% in the 6X+6 group and 71% in the 12+2X group. No statistically significant differences were found between the two groups in the incidence rate of post-biopsy complications. Compared with the traditional 12+2X method, for the suspected lesion manifested by mp-MRI, focusing biopsy on the suspected region with the 6X+6 strategy can achieve a higher PCa detection rate without increasing the incidence of complications.

Prostate stem cell antigen (PSCA) mRNA expression in peripheral blood in patients with benign prostatic hyperplasia and/or prostate cancer.

PubMed

Fawzy, Mohamed S; Mohamed, Randa H; Elfayoumi, Abdel-Rahman R

2015-03-01

The aim of this study was to determine whether detection of prostate stem cell antigen (PSCA) expression in BPH might be associated with the subsequent presence of Prostate cancer (PCa) and also to determine whether detection of PSCA expression has potential for prognosis in PCa. This study was comprised of 112 PCa patients, 111 BPH patients and 120 control subjects. We employed reverse-transcriptase polymerase chain reaction (RT-PCR) to detect PSCA mRNA-bearing cells in peripheral blood. PSCA mRNA was detected in the peripheral blood of 71.4% PCa patients and in 13.5% of patients with BPH by RT-PCR. PSCA was positive in 80% of high-grade diseases compared with 20% of low-grade diseases (P = 0.01). Whereas only 38.8% of prostate-confined diseases were PSCA positive, 61.2% of extraprostatic diseases were PSCA positive (P < 0.001). Patients with a lymphovascular invasion of tumor emboli tended to be PSCA positive (P = 0.02). BPH patients with RT-PCR PSCA positive were significantly more likely to develop prostate cancer (OR = 16, 95% CI = 8.1-31.6, P < 0.001). In conclusion, RT-PCR PSCA positivity is significantly associated with the Gleason score, LV tumor emboli and whether or not the tumor was organ confined. In this study, RT-PCR PSCA detection may be a promising tumor marker of diagnostic and metastasis detection for patients with prostate cancer. Also, it may be an important test for predicting BPH patients who are at high risk of subsequent cancer development.

Principal component analysis of indocyanine green fluorescence dynamics for diagnosis of vascular diseases

NASA Astrophysics Data System (ADS)

Seo, Jihye; An, Yuri; Lee, Jungsul; Choi, Chulhee

2015-03-01

Indocyanine green (ICG), a near-infrared fluorophore, has been used in visualization of vascular structure and non-invasive diagnosis of vascular disease. Although many imaging techniques have been developed, there are still limitations in diagnosis of vascular diseases. We have recently developed a minimally invasive diagnostics system based on ICG fluorescence imaging for sensitive detection of vascular insufficiency. In this study, we used principal component analysis (PCA) to examine ICG spatiotemporal profile and to obtain pathophysiological information from ICG dynamics. Here we demonstrated that principal components of ICG dynamics in both feet showed significant differences between normal control and diabetic patients with vascula complications. We extracted the PCA time courses of the first three components and found distinct pattern in diabetic patient. We propose that PCA of ICG dynamics reveal better classification performance compared to fluorescence intensity analysis. We anticipate that specific feature of spatiotemporal ICG dynamics can be useful in diagnosis of various vascular diseases.

A meta-analysis of use of Prostate Imaging Reporting and Data System Version 2 (PI-RADS V2) with multiparametric MR imaging for the detection of prostate cancer.

PubMed

Zhang, Li; Tang, Min; Chen, Sipan; Lei, Xiaoyan; Zhang, Xiaoling; Huan, Yi

2017-12-01

This meta-analysis was undertaken to review the diagnostic accuracy of PI-RADS V2 for prostate cancer (PCa) detection with multiparametric MR (mp-MR). A comprehensive literature search of electronic databases was performed by two observers independently. Inclusion criteria were original research using the PI-RADS V2 system in reporting prostate MRI. The methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Data necessary to complete 2 × 2 contingency tables were obtained from the included studies. Thirteen studies (2,049 patients) were analysed. This is an initial meta-analysis of PI-RADs V2 and the overall diagnostic accuracy in diagnosing PCa was as follows: pooled sensitivity, 0.85 (0.78-0.91); pooled specificity, 0.71 (0.60-0.80); pooled positive likelihood ratio (LR+), 2.92 (2.09-4.09); pooled negative likelihood ratio (LR-), 0.21 (0.14-0.31); pooled diagnostic odds ratio (DOR), 14.08 (7.93-25.01), respectively. Positive predictive values ranged from 0.54 to 0.97 and negative predictive values ranged from 0.26 to 0.92. Currently available evidence indicates that PI-RADS V2 appears to have good diagnostic accuracy in patients with PCa lesions with high sensitivity and moderate specificity. However, no recommendation regarding the best threshold can be provided because of heterogeneity. • PI-RADS V2 shows good diagnostic accuracy for PCa detection. • Initially pooled specificity of PI-RADS v2 remains moderate. • PCa detection is increased by experienced radiologists. • There is currently a high heterogeneity in prostate diagnostics with MRI.

Alterations in expressed prostate secretion-urine PSA N-glycosylation discriminate prostate cancer from benign prostate hyperplasia

PubMed Central

Sun, Chenxia; Wen, Fuping; Wang, Haifeng; Guo, Huaizu; Gao, Xu; Xu, Chuanliang; Xu, Chuanliang; Yang, Chenghua; Sun, Yinghao

2017-01-01

The prostate specific antigen (PSA) test is widely used for early diagnosis of prostate cancer (PCa). However, its limited sensitivity has led to over-diagnosis and over-treatment of PCa. Glycosylation alteration is a common phenomenon in cancer development. Different PSA glycan subforms have been proposed as diagnostic markers to better differentiate PCa from benign prostate hyperplasia (BPH). In this study, we purified PSA from expressed prostate secretions (EPS)-urine samples from 32 BPH and 30 PCa patients and provided detailed PSA glycan profiles in Chinese population. We found that most of the PSA glycans from EPS-urine were complex type biantennary glycans. We observed two major patterns in PSA glycan profiles. Overall there was no distinct separation of PSA glycan profiles between BPH and PCa patients. However, we detected a significant increase of glycan FA2 and FM5A2G2S1 in PCa when compared with BPH patients. Furthermore, we observed that the composition of FA2 glycan increased significantly in advanced PCa with Gleason score ≥8, which potentially could be translated to clinic as a marker for aggressive PCa. PMID:29100363

Alterations in expressed prostate secretion-urine PSA N-glycosylation discriminate prostate cancer from benign prostate hyperplasia.

PubMed

Jia, Gaozhen; Dong, Zhenyang; Sun, Chenxia; Wen, Fuping; Wang, Haifeng; Guo, Huaizu; Gao, Xu; Xu, Chuanliang; Xu, Chuanliang; Yang, Chenghua; Sun, Yinghao

2017-09-29

The prostate specific antigen (PSA) test is widely used for early diagnosis of prostate cancer (PCa). However, its limited sensitivity has led to over-diagnosis and over-treatment of PCa. Glycosylation alteration is a common phenomenon in cancer development. Different PSA glycan subforms have been proposed as diagnostic markers to better differentiate PCa from benign prostate hyperplasia (BPH). In this study, we purified PSA from expressed prostate secretions (EPS)-urine samples from 32 BPH and 30 PCa patients and provided detailed PSA glycan profiles in Chinese population. We found that most of the PSA glycans from EPS-urine were complex type biantennary glycans. We observed two major patterns in PSA glycan profiles. Overall there was no distinct separation of PSA glycan profiles between BPH and PCa patients. However, we detected a significant increase of glycan FA2 and FM5A2G2S1 in PCa when compared with BPH patients. Furthermore, we observed that the composition of FA2 glycan increased significantly in advanced PCa with Gleason score ≥8, which potentially could be translated to clinic as a marker for aggressive PCa.

Probabilistic PCA of censored data: accounting for uncertainties in the visualization of high-throughput single-cell qPCR data.

PubMed

Buettner, Florian; Moignard, Victoria; Göttgens, Berthold; Theis, Fabian J

2014-07-01

High-throughput single-cell quantitative real-time polymerase chain reaction (qPCR) is a promising technique allowing for new insights in complex cellular processes. However, the PCR reaction can be detected only up to a certain detection limit, whereas failed reactions could be due to low or absent expression, and the true expression level is unknown. Because this censoring can occur for high proportions of the data, it is one of the main challenges when dealing with single-cell qPCR data. Principal component analysis (PCA) is an important tool for visualizing the structure of high-dimensional data as well as for identifying subpopulations of cells. However, to date it is not clear how to perform a PCA of censored data. We present a probabilistic approach that accounts for the censoring and evaluate it for two typical datasets containing single-cell qPCR data. We use the Gaussian process latent variable model framework to account for censoring by introducing an appropriate noise model and allowing a different kernel for each dimension. We evaluate this new approach for two typical qPCR datasets (of mouse embryonic stem cells and blood stem/progenitor cells, respectively) by performing linear and non-linear probabilistic PCA. Taking the censoring into account results in a 2D representation of the data, which better reflects its known structure: in both datasets, our new approach results in a better separation of known cell types and is able to reveal subpopulations in one dataset that could not be resolved using standard PCA. The implementation was based on the existing Gaussian process latent variable model toolbox (https://github.com/SheffieldML/GPmat); extensions for noise models and kernels accounting for censoring are available at http://icb.helmholtz-muenchen.de/censgplvm. © The Author 2014. Published by Oxford University Press. All rights reserved.

Probabilistic PCA of censored data: accounting for uncertainties in the visualization of high-throughput single-cell qPCR data

PubMed Central

Buettner, Florian; Moignard, Victoria; Göttgens, Berthold; Theis, Fabian J.

2014-01-01

Motivation: High-throughput single-cell quantitative real-time polymerase chain reaction (qPCR) is a promising technique allowing for new insights in complex cellular processes. However, the PCR reaction can be detected only up to a certain detection limit, whereas failed reactions could be due to low or absent expression, and the true expression level is unknown. Because this censoring can occur for high proportions of the data, it is one of the main challenges when dealing with single-cell qPCR data. Principal component analysis (PCA) is an important tool for visualizing the structure of high-dimensional data as well as for identifying subpopulations of cells. However, to date it is not clear how to perform a PCA of censored data. We present a probabilistic approach that accounts for the censoring and evaluate it for two typical datasets containing single-cell qPCR data. Results: We use the Gaussian process latent variable model framework to account for censoring by introducing an appropriate noise model and allowing a different kernel for each dimension. We evaluate this new approach for two typical qPCR datasets (of mouse embryonic stem cells and blood stem/progenitor cells, respectively) by performing linear and non-linear probabilistic PCA. Taking the censoring into account results in a 2D representation of the data, which better reflects its known structure: in both datasets, our new approach results in a better separation of known cell types and is able to reveal subpopulations in one dataset that could not be resolved using standard PCA. Availability and implementation: The implementation was based on the existing Gaussian process latent variable model toolbox (https://github.com/SheffieldML/GPmat); extensions for noise models and kernels accounting for censoring are available at http://icb.helmholtz-muenchen.de/censgplvm. Contact: fbuettner.phys@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24618470

Principal component analysis-based anatomical motion models for use in adaptive radiation therapy of head and neck cancer patients

NASA Astrophysics Data System (ADS)

Chetvertkov, Mikhail A.

Purpose: To develop standard and regularized principal component analysis (PCA) models of anatomical changes from daily cone beam CTs (CBCTs) of head and neck (H&N) patients, assess their potential use in adaptive radiation therapy (ART), and to extract quantitative information for treatment response assessment. Methods: Planning CT (pCT) images of H&N patients were artificially deformed to create "digital phantom" images, which modeled systematic anatomical changes during Radiation Therapy (RT). Artificial deformations closely mirrored patients' actual deformations, and were interpolated to generate 35 synthetic CBCTs, representing evolving anatomy over 35 fractions. Deformation vector fields (DVFs) were acquired between pCT and synthetic CBCTs (i.e., digital phantoms), and between pCT and clinical CBCTs. Patient-specific standard PCA (SPCA) and regularized PCA (RPCA) models were built from these synthetic and clinical DVF sets. Eigenvectors, or eigenDVFs (EDVFs), having the largest eigenvalues were hypothesized to capture the major anatomical deformations during treatment. Modeled anatomies were used to assess the dose deviations with respect to the planned dose distribution. Results: PCA models achieve variable results, depending on the size and location of anatomical change. Random changes prevent or degrade SPCA's ability to detect underlying systematic change. RPCA is able to detect smaller systematic changes against the background of random fraction-to-fraction changes, and is therefore more successful than SPCA at capturing systematic changes early in treatment. SPCA models were less successful at modeling systematic changes in clinical patient images, which contain a wider range of random motion than synthetic CBCTs, while the regularized approach was able to extract major modes of motion. For dose assessment it has been shown that the modeled dose distribution was different from the planned dose for the parotid glands due to their shrinkage and shift into the higher dose volumes during the radiotherapy course. Modeled DVHs still underestimated the effect of parotid shrinkage due to the large compression factor (CF) used to acquire DVFs. Conclusion: Leading EDVFs from both PCA approaches have the potential to capture systematic anatomical changes during H&N radiotherapy when systematic changes are large enough with respect to random fraction-to-fraction changes. In all cases the RPCA approach appears to be more reliable than SPCA at capturing systematic changes, enabling dosimetric consequences to be projected to the future treatment fractions based on trends established early in a treatment course, or, potentially, based on population models. This work showed that PCA has a potential in identifying the major mode of anatomical changes during the radiotherapy course and subsequent use of this information in future dose predictions is feasible. Use of smaller CF values for DVFs is preferred, otherwise anatomical motion will be underestimated.

Discoveries and application of prostate-specific antigen, and some proposals to optimize prostate cancer screening.

PubMed

Tokudome, Shinkan; Ando, Ryosuke; Koda, Yoshiro

2016-01-01

The discoveries and application of prostate-specific antigen (PSA) have been much appreciated because PSA-based screening has saved millions of lives of prostate cancer (PCa) patients. Historically speaking, Flocks et al first identified antigenic properties in prostate tissue in 1960. Then, Barnes et al detected immunologic characteristics in prostatic fluid in 1963. Hara et al characterized γ-semino-protein in semen in 1966, and it has been proven to be identical to PSA. Subsequently, Ablin et al independently reported the presence of precipitation antigens in the prostate in 1970. Wang et al purified the PSA in 1979, and Kuriyama et al first applied an enzyme-linked immunosorbent assay for PSA in 1980. However, the positive predictive value with a cutoff figure of 4.0 ng/mL appeared substantially low (∼30%). There are overdiagnoses and overtreatments for latent/low-risk PCa. Controversies exist in the PCa mortality-reducing effects of PSA screening between the European Randomized Study of Screening for Prostate Cancer (ERSPC) and the US Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. For optimizing PCa screening, PSA-related items may require the following: 1) adjustment of the cutoff values according to age, as well as setting limits to age and screening intervals; 2) improving test performance using doubling time, density, and ratio of free: total PSA; and 3) fostering active surveillance for low-risk PCa with monitoring by PSA value. Other items needing consideration may include the following: 1) examinations of cell proliferation and cell cycle markers in biopsy specimens; 2) independent quantification of Gleason grading; 3) developing ethnicity-specific staging nomograms based on tumor stage, PSA value, and Gleason score; 4) delineation of the natural history; 5) revisiting the significance of the androgen/testosterone hypothesis; and 6) devoting special attention to individuals with a certain genetic predisposition. Finally, considering the uncertainty that exists in medicine, risk communication on PSA-based screening is indeed due.

Consensus classification of posterior cortical atrophy

PubMed Central

Crutch, Sebastian J.; Schott, Jonathan M.; Rabinovici, Gil D.; Murray, Melissa; Snowden, Julie S.; van der Flier, Wiesje M.; Dickerson, Bradford C.; Vandenberghe, Rik; Ahmed, Samrah; Bak, Thomas H.; Boeve, Bradley F.; Butler, Christopher; Cappa, Stefano F.; Ceccaldi, Mathieu; de Souza, Leonardo Cruz; Dubois, Bruno; Felician, Olivier; Galasko, Douglas; Graff-Radford, Jonathan; Graff-Radford, Neill R.; Hof, Patrick R.; Krolak-Salmon, Pierre; Lehmann, Manja; Magnin, Eloi; Mendez, Mario F.; Nestor, Peter J.; Onyike, Chiadi U.; Pelak, Victoria S.; Pijnenburg, Yolande; Primativo, Silvia; Rossor, Martin N.; Ryan, Natalie S.; Scheltens, Philip; Shakespeare, Timothy J.; González, Aida Suárez; Tang-Wai, David F.; Yong, Keir X. X.; Carrillo, Maria; Fox, Nick C.

2017-01-01

Introduction A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings. Methods Consensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA. Results A three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum. Discussion There was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work. PMID:28259709

Consensus classification of posterior cortical atrophy.

PubMed

Crutch, Sebastian J; Schott, Jonathan M; Rabinovici, Gil D; Murray, Melissa; Snowden, Julie S; van der Flier, Wiesje M; Dickerson, Bradford C; Vandenberghe, Rik; Ahmed, Samrah; Bak, Thomas H; Boeve, Bradley F; Butler, Christopher; Cappa, Stefano F; Ceccaldi, Mathieu; de Souza, Leonardo Cruz; Dubois, Bruno; Felician, Olivier; Galasko, Douglas; Graff-Radford, Jonathan; Graff-Radford, Neill R; Hof, Patrick R; Krolak-Salmon, Pierre; Lehmann, Manja; Magnin, Eloi; Mendez, Mario F; Nestor, Peter J; Onyike, Chiadi U; Pelak, Victoria S; Pijnenburg, Yolande; Primativo, Silvia; Rossor, Martin N; Ryan, Natalie S; Scheltens, Philip; Shakespeare, Timothy J; Suárez González, Aida; Tang-Wai, David F; Yong, Keir X X; Carrillo, Maria; Fox, Nick C

2017-08-01

A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings. Consensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA. A three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum. There was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Multiparametric dynamic contrast-enhanced ultrasound imaging of prostate cancer.

PubMed

Wildeboer, Rogier R; Postema, Arnoud W; Demi, Libertario; Kuenen, Maarten P J; Wijkstra, Hessel; Mischi, Massimo

2017-08-01

The aim of this study is to improve the accuracy of dynamic contrast-enhanced ultrasound (DCE-US) for prostate cancer (PCa) localization by means of a multiparametric approach. Thirteen different parameters related to either perfusion or dispersion were extracted pixel-by-pixel from 45 DCE-US recordings in 19 patients referred for radical prostatectomy. Multiparametric maps were retrospectively produced using a Gaussian mixture model algorithm. These were subsequently evaluated on their pixel-wise performance in classifying 43 benign and 42 malignant histopathologically confirmed regions of interest, using a prostate-based leave-one-out procedure. The combination of the spatiotemporal correlation (r), mean transit time (μ), curve skewness (κ), and peak time (PT) yielded an accuracy of 81% ± 11%, which was higher than the best performing single parameters: r (73%), μ (72%), and wash-in time (72%). The negative predictive value increased to 83% ± 16% from 70%, 69% and 67%, respectively. Pixel inclusion based on the confidence level boosted these measures to 90% with half of the pixels excluded, but without disregarding any prostate or region. Our results suggest multiparametric DCE-US analysis might be a useful diagnostic tool for PCa, possibly supporting future targeting of biopsies or therapy. Application in other types of cancer can also be foreseen. • DCE-US can be used to extract both perfusion and dispersion-related parameters. • Multiparametric DCE-US performs better in detecting PCa than single-parametric DCE-US. • Multiparametric DCE-US might become a useful tool for PCa localization.

Chemiresistive Electronic Nose toward Detection of Biomarkers in Exhaled Breath.

PubMed

Moon, Hi Gyu; Jung, Youngmo; Han, Soo Deok; Shim, Young-Seok; Shin, Beomju; Lee, Taikjin; Kim, Jin-Sang; Lee, Seok; Jun, Seong Chan; Park, Hyung-Ho; Kim, Chulki; Kang, Chong-Yun

2016-08-17

Detection of gas-phase chemicals finds a wide variety of applications, including food and beverages, fragrances, environmental monitoring, chemical and biochemical processing, medical diagnostics, and transportation. One approach for these tasks is to use arrays of highly sensitive and selective sensors as an electronic nose. Here, we present a high performance chemiresistive electronic nose (CEN) based on an array of metal oxide thin films, metal-catalyzed thin films, and nanostructured thin films. The gas sensing properties of the CEN show enhanced sensitive detection of H2S, NH3, and NO in an 80% relative humidity (RH) atmosphere similar to the composition of exhaled breath. The detection limits of the sensor elements we fabricated are in the following ranges: 534 ppt to 2.87 ppb for H2S, 4.45 to 42.29 ppb for NH3, and 206 ppt to 2.06 ppb for NO. The enhanced sensitivity is attributed to the spillover effect by Au nanoparticles and the high porosity of villi-like nanostructures, providing a large surface-to-volume ratio. The remarkable selectivity based on the collection of sensor responses manifests itself in the principal component analysis (PCA). The excellent sensing performance indicates that the CEN can detect the biomarkers of H2S, NH3, and NO in exhaled breath and even distinguish them clearly in the PCA. Our results show high potential of the CEN as an inexpensive and noninvasive diagnostic tool for halitosis, kidney disorder, and asthma.

Biomarkers for Early Detection of Clinically Relvant Prostate Cancer: A Multi-Institutional Validation Trial - Genomic Health, Inc. — EDRN Public Portal

Cancer.gov

Validate a panel of tissue-based biomarkers to determine the presence of or progression to clinically relevant prostate cancer at the time of diagnosis. Utilize a novel, biopsy based multi-gene quantitative RT-PCR assay developed by Genomic Health, Oncotype DX Prostate Cancer Assay, which discriminates aggressive from indolent cancer on multivariate modeling of PCa patients.

Multiparametric Magnetic Resonance Imaging (MRI) and MRI-Transrectal Ultrasound Fusion Biopsy for Index Tumor Detection: Correlation with Radical Prostatectomy Specimen.

PubMed

Radtke, Jan P; Schwab, Constantin; Wolf, Maya B; Freitag, Martin T; Alt, Celine D; Kesch, Claudia; Popeneciu, Ionel V; Huettenbrink, Clemens; Gasch, Claudia; Klein, Tilman; Bonekamp, David; Duensing, Stefan; Roth, Wilfried; Schueler, Svenja; Stock, Christian; Schlemmer, Heinz-Peter; Roethke, Matthias; Hohenfellner, Markus; Hadaschik, Boris A

2016-11-01

Multiparametric magnetic resonance imaging (mpMRI) and MRI fusion targeted biopsy (FTB) detect significant prostate cancer (sPCa) more accurately than conventional biopsies alone. To evaluate the detection accuracy of mpMRI and FTB on radical prostatectomy (RP) specimen. From a cohort of 755 men who underwent transperineal MRI and transrectal ultrasound fusion biopsy under general anesthesia between 2012 and 2014, we retrospectively analyzed 120 consecutive patients who had subsequent RP. All received saturation biopsy (SB) in addition to FTB of lesions with Prostate Imaging Reporting and Data System (PI-RADS) score ≥2. The index lesion was defined as the lesion with extraprostatic extension, the highest Gleason score (GS), or the largest tumor volume (TV) if GS were the same, in order of priority. GS 3+3 and TV ≥1.3ml or GS ≥3+4 and TV ≥0.55ml were considered sPCa. We assessed the detection accuracy by mpMRI and different biopsy approaches and analyzed lesion agreement between mpMRI and RP specimen. Overall, 120 index and 71 nonindex lesions were detected. Overall, 107 (89%) index and 51 (72%) nonindex lesions harbored sPCa. MpMRI detected 110 of 120 (92%) index lesions, FTB (two cores per lesion) alone diagnosed 96 of 120 (80%) index lesions, and SB alone diagnosed 110 of 120 (92%) index lesions. Combined SB and FTB detected 115 of 120 (96%) index foci. FTB performed significantly less accurately compared with mpMRI (p=0.02) and the combination for index lesion detection (p=0.002). Combined FTB and SB detected 97% of all sPCa lesions and was superior to mpMRI (85%), FTB (79%), and SB (88%) alone (p<0.001 each). Spearman's rank correlation coefficient for index lesion agreement between mpMRI and RP was 0.87 (p<0.001). Limitations included the retrospective design, multiple operators, and nonblinding of radiologists. MpMRI identified 92% of index lesions compared with RP histopathology. The combination of FTB and SB was superior to both approaches alone, reliably detecting 97% of sPCa lesions. Multiparametric magnetic resonance imaging detects the index lesion accurately in 9 of 10 patients; however, the combined biopsy approach, while missing less significant cancer, comes at the cost of detecting more insignificant cancer. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Swift does not detect a source near H 1743-322

NASA Astrophysics Data System (ADS)

Motta, S.; Belloni, T.; Campana, S.; Munoz-Darias, T.

2011-04-01

A low-frequency oscillation with a period of approximately 91 s was visible in the RXTE/PCA light curve of the black-hole candidate H1743-322 (ATel #3277), in outburst since April 6, 2011 (ATel #32763) and currently in hard state. The oscillation was detected only in the first RXTE observation (performed 16:05:01 (UTC) on April 12, 2011). The hypothesis that the oscillations are due to a second active source in the PCA field of view was put forward.

Priority of VHS Development Based in Potential Area using Principal Component Analysis

NASA Astrophysics Data System (ADS)

Meirawan, D.; Ana, A.; Saripudin, S.

2018-02-01

The current condition of VHS is still inadequate in quality, quantity and relevance. The purpose of this research is to analyse the development of VHS based on the development of regional potential by using principal component analysis (PCA) in Bandung, Indonesia. This study used descriptive qualitative data analysis using the principle of secondary data reduction component. The method used is Principal Component Analysis (PCA) analysis with Minitab Statistics Software tool. The results of this study indicate the value of the lowest requirement is a priority of the construction of development VHS with a program of majors in accordance with the development of regional potential. Based on the PCA score found that the main priority in the development of VHS in Bandung is in Saguling, which has the lowest PCA value of 416.92 in area 1, Cihampelas with the lowest PCA value in region 2 and Padalarang with the lowest PCA value.

Spatial Mapping of Pyocyanin in Pseudomonas aeruginosa Bacterial Communities by Surface Enhanced Raman Scattering

PubMed Central

Polisetti, Sneha; Baig, Nameera F.; Morales-Soto, Nydia; Shrout, Joshua D.; Bohn, Paul W.

2017-01-01

Surface Enhanced Raman Spectroscopy (SERS) imaging was used in conjunction with Principal Component Analysis (PCA) for the in situ spatiotemporal mapping of the virulence factor pyocyanin, in communities of the pathogenic bacterium Pseudomonas aeruginosa. The combination of SERS imaging and PCA analysis provides a robust method for characterization of heterogeneous biological systems while circumventing issues associated with interference from sample autofluorescence and low reproducibility of SERS signals. The production of pyocyanin is found to depend both on the growth carbon source and on the specific strain of P. aeruginosa studied. A cystic fibrosis lung isolate strain of P. aeruginosa synthesizes and secretes pyocyanin when grown with glucose and glutamate, while the laboratory strain exhibits detectable production of pyocyanin only when grown with glutamate as the source of carbon. Pyocyanin production in the laboratory strain grown with glucose was below the limit of detection of SERS. In addition, the combination of SERS imaging and PCA can elucidate subtle differences in the molecular composition of biofilms. PCA loading plots from the clinical isolate exhibit features corresponding to vibrational bands of carbohydrates, which represent the mucoid biofilm matrix specific to that isolate, features that are not seen in the PCA loading plots of the laboratory strain. PMID:27354400

Recruitment Methods and Show Rates to a Prostate Cancer Early Detection Program for High-Risk Men: A Comprehensive Analysis

PubMed Central

Giri, Veda N.; Coups, Elliot J.; Ruth, Karen; Goplerud, Julia; Raysor, Susan; Kim, Taylor Y.; Bagden, Loretta; Mastalski, Kathleen; Zakrzewski, Debra; Leimkuhler, Suzanne; Watkins-Bruner, Deborah

2009-01-01

Purpose Men with a family history (FH) of prostate cancer (PCA) and African American (AA) men are at higher risk for PCA. Recruitment and retention of these high-risk men into early detection programs has been challenging. We report a comprehensive analysis on recruitment methods, show rates, and participant factors from the Prostate Cancer Risk Assessment Program (PRAP), which is a prospective, longitudinal PCA screening study. Materials and Methods Men 35–69 years are eligible if they have a FH of PCA, are AA, or have a BRCA1/2 mutation. Recruitment methods were analyzed with respect to participant demographics and show to the first PRAP appointment using standard statistical methods Results Out of 707 men recruited, 64.9% showed to the initial PRAP appointment. More individuals were recruited via radio than from referral or other methods (χ2 = 298.13, p < .0001). Men recruited via radio were more likely to be AA (p<0.001), less educated (p=0.003), not married or partnered (p=0.007), and have no FH of PCA (p<0.001). Men recruited via referrals had higher incomes (p=0.007). Men recruited via referral were more likely to attend their initial PRAP visit than those recruited by radio or other methods (χ2 = 27.08, p < .0001). Conclusions This comprehensive analysis finds that radio leads to higher recruitment of AA men with lower socioeconomic status. However, these are the high-risk men that have lower show rates for PCA screening. Targeted motivational measures need to be studied to improve show rates for PCA risk assessment for these high-risk men. PMID:19758657

Use of Standing Gold Nanorods for Detection of Malachite Green and Crystal Violet in Fish by SERS.

PubMed

Chen, Xiaowei; Nguyen, Trang H D; Gu, Liqun; Lin, Mengshi

2017-07-01

With growing consumption of aquaculture products, there is increasing demand on rapid and sensitive techniques that can detect prohibited substances in the seafood products. This study aimed to develop a novel surface-enhanced Raman spectroscopy (SERS) method coupled with simplified extraction protocol and novel gold nanorod (AuNR) substrates to detect banned aquaculture substances (malachite green [MG] and crystal violet [CV]) and their mixture (1:1) in aqueous solution and fish samples. Multivariate statistical tools such as principal component analysis (PCA) and partial least squares regression (PLSR) were used in data analysis. PCA results demonstrate that SERS can distinguish MG, CV and their mixture (1:1) in aqueous solution and in fish samples. The detection limit of SERS coupled with standing AuNR substrates is 1 ppb for both MG and CV in fish samples. A good linear relationship between the actual concentration and predicted concentration of analytes based on PLSR models with R 2 values from 0.87 to 0.99 were obtained, indicating satisfactory quantification results of this method. These results demonstrate that the SERS method coupled with AuNR substrates can be used for rapid and accurate detection of MG and CV in fish samples. © 2017 Institute of Food Technologists®.

The Clinical Impact of Additional Late PET/CT Imaging with 68Ga-PSMA-11 (HBED-CC) in the Diagnosis of Prostate Cancer.

PubMed

Afshar-Oromieh, Ali; Sattler, Lars Peter; Mier, Walter; Hadaschik, Boris A; Debus, Jürgen; Holland-Letz, Tim; Kopka, Klaus; Haberkorn, Uwe

2017-05-01

Although PET/CT with 68 Ga-PSMA-11 in the diagnosis of prostate cancer (PCa) is routinely performed at 1 h after injection, later scans may be beneficial because most lesions present with higher uptake and contrast. This evaluation aimed to investigate the clinical impact of additional late 68 Ga-PSMA-11 PET/CT. Methods: Between 2011 and 2016, 112 patients with PCa who underwent early (at 1 h after injection) and late (at 3 h after injection) 68 Ga-PSMA-11 PET/CT scans were retrospectively evaluated. The late scans were conducted to clarify unclear findings in early scans or to increase the probability of tumor detection in the case of negative early scans. All patients were asked to drink 1 L of water between early and late scans. In addition, 20 patients received 20 mg of furosemide before late scans. Tumor detection and radioactivity concentration within the urinary bladder were analyzed in both scans. The SUV max and contrast of 149 tumor lesions were measured in 69 patients with pathologic findings. Results: Overall, 134 lesions characteristic for PCa in 57 patients clearly presented at 1 h after injection and 147 lesions in 68 patients at 3 h after injection. Forty-three patients showed no pathologic findings. Eight patients (7.1%) showed 1 unclear finding in early scans, which could be clarified as characteristic for PCa at 3 h after injection. Four patients (3.6%) presented with 1 lesion characteristic for PCa at 3 h after injection only. Twelve patients (10.7%) presented with 12 possible PCa lesions at 1 h after injection, which, however, could not be confirmed as PCa in late scans. Two patients presented with 1 lesion characteristic for PCa at 1 h after injection, which became invisible at 3 h after injection because of low contrast. At 3 h after injection, 62.4% of the lesions demonstrated a higher SUV max and 65.1% a higher contrast than at 1 h after injection. Patients with furosemide presented with lower SUV and radioactivity concentration within the urinary bladder. Conclusion: 68 Ga-PSMA-11 PET/CT at 3 h after injection showed most lesions characteristic for PCa with a higher uptake and contrast. In addition, the radioactivity signal within the urinary bladder was lower at 3 h after injection, especially when furosemide was applied. Consequently, scans at 3 h after injection detected more tumor lesions than at 1 h after injection. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Targeted and non-targeted detection of lemon juice adulteration by LC-MS and chemometrics.

PubMed

Wang, Zhengfang; Jablonski, Joseph E

2016-01-01

Economically motivated adulteration (EMA) of lemon juice was detected by LC-MS and principal component analysis (PCA). Twenty-two batches of freshly squeezed lemon juice were adulterated by adding an aqueous solution containing 5% citric acid and 6% sucrose to pure lemon juice to obtain 30%, 60% and 100% lemon juice samples. Their total titratable acidities, °Brix and pH values were measured, and then all the lemon juice samples were subject to LC-MS analysis. Concentrations of hesperidin and eriocitrin, major phenolic components of lemon juice, were quantified. The PCA score plots for LC-MS datasets were used to preview the classification of pure and adulterated lemon juice samples. Results showed a large inherent variability in the chemical properties among 22 batches of 100% lemon juice samples. Measurement or quantitation of one or several chemical properties (targeted detection) was not effective in detecting lemon juice adulteration. However, by using the LC-MS datasets, including both chromatographic and mass spectrometric information, 100% lemon juice samples were successfully differentiated from adulterated samples containing 30% lemon juice in the PCA score plot. LC-MS coupled with chemometric analysis can be a complement to existing methods for detecting juice adulteration.

Facilitating text reading in posterior cortical atrophy.

PubMed

Yong, Keir X X; Rajdev, Kishan; Shakespeare, Timothy J; Leff, Alexander P; Crutch, Sebastian J

2015-07-28

We report (1) the quantitative investigation of text reading in posterior cortical atrophy (PCA), and (2) the effects of 2 novel software-based reading aids that result in dramatic improvements in the reading ability of patients with PCA. Reading performance, eye movements, and fixations were assessed in patients with PCA and typical Alzheimer disease and in healthy controls (experiment 1). Two reading aids (single- and double-word) were evaluated based on the notion that reducing the spatial and oculomotor demands of text reading might support reading in PCA (experiment 2). Mean reading accuracy in patients with PCA was significantly worse (57%) compared with both patients with typical Alzheimer disease (98%) and healthy controls (99%); spatial aspects of passages were the primary determinants of text reading ability in PCA. Both aids led to considerable gains in reading accuracy (PCA mean reading accuracy: single-word reading aid = 96%; individual patient improvement range: 6%-270%) and self-rated measures of reading. Data suggest a greater efficiency of fixations and eye movements under the single-word reading aid in patients with PCA. These findings demonstrate how neurologic characterization of a neurodegenerative syndrome (PCA) and detailed cognitive analysis of an important everyday skill (reading) can combine to yield aids capable of supporting important everyday functional abilities. This study provides Class III evidence that for patients with PCA, 2 software-based reading aids (single-word and double-word) improve reading accuracy. © 2015 American Academy of Neurology.

Facilitating text reading in posterior cortical atrophy

PubMed Central

Rajdev, Kishan; Shakespeare, Timothy J.; Leff, Alexander P.; Crutch, Sebastian J.

2015-01-01

Objective: We report (1) the quantitative investigation of text reading in posterior cortical atrophy (PCA), and (2) the effects of 2 novel software-based reading aids that result in dramatic improvements in the reading ability of patients with PCA. Methods: Reading performance, eye movements, and fixations were assessed in patients with PCA and typical Alzheimer disease and in healthy controls (experiment 1). Two reading aids (single- and double-word) were evaluated based on the notion that reducing the spatial and oculomotor demands of text reading might support reading in PCA (experiment 2). Results: Mean reading accuracy in patients with PCA was significantly worse (57%) compared with both patients with typical Alzheimer disease (98%) and healthy controls (99%); spatial aspects of passages were the primary determinants of text reading ability in PCA. Both aids led to considerable gains in reading accuracy (PCA mean reading accuracy: single-word reading aid = 96%; individual patient improvement range: 6%–270%) and self-rated measures of reading. Data suggest a greater efficiency of fixations and eye movements under the single-word reading aid in patients with PCA. Conclusions: These findings demonstrate how neurologic characterization of a neurodegenerative syndrome (PCA) and detailed cognitive analysis of an important everyday skill (reading) can combine to yield aids capable of supporting important everyday functional abilities. Classification of evidence: This study provides Class III evidence that for patients with PCA, 2 software-based reading aids (single-word and double-word) improve reading accuracy. PMID:26138948

68Ga-HBED-CC-PSMA PET/CT Versus Histopathology in Primary Localized Prostate Cancer: A Voxel-Wise Comparison

PubMed Central

Zamboglou, Constantinos; Schiller, Florian; Fechter, Tobias; Wieser, Gesche; Jilg, Cordula Annette; Chirindel, Alin; Salman, Nasr; Drendel, Vanessa; Werner, Martin; Mix, Michael; Meyer, Philipp Tobias; Grosu, Anca Ligia

2016-01-01

Purpose: We performed a voxel-wise comparison of 68Ga-HBED-CC-PSMA PET/CT with prostate histopathology to evaluate the performance of 68Ga-HBED-CC-PSMA for the detection and delineation of primary prostate cancer (PCa). Methodology: Nine patients with histopathological proven primary PCa underwent 68Ga-HBED-CC-PSMA PET/CT followed by radical prostatectomy. Resected prostates were scanned by ex-vivo CT in a special localizer and histopathologically prepared. Histopathological information was matched to ex-vivo CT. PCa volume (PCa-histo) and non-PCa tissue in the prostate (NPCa-histo) were processed to obtain a PCa-model, which was adjusted to PET-resolution (histo-PET). Each histo-PET was coregistered to in-vivo PSMA-PET/CT data. Results: Analysis of spatial overlap between histo-PET and PSMA PET revealed highly significant correlations (p < 10-5) in nine patients and moderate to high coefficients of determination (R²) from 42 to 82 % with an average of 60 ± 14 % in eight patients (in one patient R2 = 7 %). Mean SUVmean in PCa-histo and NPCa-histo was 5.6 ± 6.1 and 3.3 ± 2.5 (p = 0.012). Voxel-wise receiver-operating characteristic (ROC) analyses comparing the prediction by PSMA-PET with the non-smoothed tumor distribution from histopathology yielded an average area under the curve of 0.83 ± 0.12. Absolute and relative SUV (normalized to SUVmax) thresholds for achieving at least 90 % sensitivity were 3.19 ± 3.35 and 0.28 ± 0.09, respectively. Conclusions: Voxel-wise analyses revealed good correlations of 68Ga-HBED-CC-PSMA PET/CT and histopathology in eight out of nine patients. Thus, PSMA-PET allows a reliable detection and delineation of PCa as basis for PET-guided focal therapies. PMID:27446496

Integration of lipidomics and transcriptomics unravels aberrant lipid metabolism and defines cholesteryl oleate as potential biomarker of prostate cancer

NASA Astrophysics Data System (ADS)

Li, Jia; Ren, Shancheng; Piao, Hai-Long; Wang, Fubo; Yin, Peiyuan; Xu, Chuanliang; Lu, Xin; Ye, Guozhu; Shao, Yaping; Yan, Min; Zhao, Xinjie; Sun, Yinghao; Xu, Guowang

2016-02-01

In-depth delineation of lipid metabolism in prostate cancer (PCa) is significant to open new insights into prostate tumorigenesis and progression, and provide potential biomarkers with greater accuracy for improved diagnosis. Here, we performed lipidomics and transcriptomics in paired prostate cancer tumor (PCT) and adjacent nontumor (ANT) tissues, followed by external validation of biomarker candidates. We identified major dysregulated pathways involving lipogenesis, lipid uptake and phospholipids remodeling, correlated with widespread lipid accumulation and lipid compositional reprogramming in PCa. Specifically, cholesteryl esters (CEs) were most prominently accumulated in PCa, and significantly associated with cancer progression and metastasis. We showed that overexpressed scavenger receptor class B type I (SR-BI) may contribute to CEs accumulation. In discovery set, CEs robustly differentiated PCa from nontumor (area under curve (AUC) of receiver operating characteristics (ROC), 0.90-0.94). In validation set, CEs potently distinguished PCa and non-malignance (AUC, 0.84-0.91), and discriminated PCa and benign prostatic hyperplasia (BPH) (AUC, 0.90-0.96), superior to serum prostate-specific antigen (PSA) (AUC = 0.83). Cholesteryl oleate showed highest AUCs in distinguishing PCa from non-malignance or BPH (AUC = 0.91 and 0.96). Collectively, our results unravel the major lipid metabolic aberrations in PCa and imply the potential role of CEs, particularly, cholesteryl oleate, as molecular biomarker for PCa detection.

Preliminary Study on Appearance-Based Detection of Anatomical Point Landmarks in Body Trunk CT Images

NASA Astrophysics Data System (ADS)

Nemoto, Mitsutaka; Nomura, Yukihiro; Hanaoka, Shohei; Masutani, Yoshitaka; Yoshikawa, Takeharu; Hayashi, Naoto; Yoshioka, Naoki; Ohtomo, Kuni

Anatomical point landmarks as most primitive anatomical knowledge are useful for medical image understanding. In this study, we propose a detection method for anatomical point landmark based on appearance models, which include gray-level statistical variations at point landmarks and their surrounding area. The models are built based on results of Principal Component Analysis (PCA) of sample data sets. In addition, we employed generative learning method by transforming ROI of sample data. In this study, we evaluated our method with 24 data sets of body trunk CT images and obtained 95.8 ± 7.3 % of the average sensitivity in 28 landmarks.

Development of a Voided Urine Assay for Detecting Prostate Cancer Noninvasively: A Pilot Study

PubMed Central

Trabulsi, Edouard J.; Tripathi, Sushil K.; Gomella, Leonard; Solomides, Charalambos; Wickstrom, Eric; Thakur, Mathew L.

2017-01-01

Objective To validate a hypothesis that prostate cancer (PCa) can be detected noninvasively by a simple and reliable assay by targeting genomic VPAC receptors expressed on malignant PCa cells shed in voided urine. Materials and Methods VPAC receptors were targeted with a specific biomolecule, TP4303, developed in our laboratory. With an IRB “exempt” approval of use of de-identified discarded samples, an aliquot of urine collected as a standard of care, from patients presenting to the urology clinic, (N=207, M= 176, F= 31, 21 years or older) was cytospun. The cells were fixed and treated with TP4303 and 4, 6 Dimidino-2-phenylindole, Dihydrochloride (DAPI). The cells were then observed under a microscope and cells with TP4303 orange fluorescence around the blue (DAPI) nucleus were considered malignant and those only with blue nucleus were regarded as normal. VPAC presence was validated using receptor blocking assay and cell malignancy was confirmed by PCa gene profile examination. Results The urine specimens were labeled only with gender and presenting diagnosis, with no personal health identifiers or other clinical data. The assay detected VPAC positive cells in 98.6% of the patients having a PCa diagnosis, (N=141), and none (0%) of the males with benign prostatic hyperplasia (BPH) (N=10). Of the 56 “normal” patients, 62.5% (N=35, M=10, F=25) were negative for VPAC cells; 19.6% (N=11, M=11, F=0) had VPAC positive cells; and 17.8% (N=10, M=4, F=6) were uninterpretable due to excessive crystals in the urine. Although data are limited, the sensitivity of the assay was 99.3% with confidence interval of 96.1%–100% and the specificity was 100% with confidence interval of 69.2%–100%. Receptor blocking assay and FACS analyses demonstrated the presence of VPAC receptors and gene profiling examinations confirmed that the cells expressing VPAC receptors were malignant PCa cells. Conclusion These preliminary data are highly encouraging and warrant further evaluation of the assay to serve as a simple and reliable tool to detect PCa noninvasively. PMID:28075510

Elastic Versus Rigid Image Registration in Magnetic Resonance Imaging-transrectal Ultrasound Fusion Prostate Biopsy: A Systematic Review and Meta-analysis.

PubMed

Venderink, Wulphert; de Rooij, Maarten; Sedelaar, J P Michiel; Huisman, Henkjan J; Fütterer, Jurgen J

2016-07-29

The main difference between the available magnetic resonance imaging-transrectal ultrasound (MRI-TRUS) fusion platforms for prostate biopsy is the method of image registration being either rigid or elastic. As elastic registration compensates for possible deformation caused by the introduction of an ultrasound probe for example, it is expected that it would perform better than rigid registration. The aim of this meta-analysis is to compare rigid with elastic registration by calculating the detection odds ratio (OR) for both subgroups. The detection OR is defined as the ratio of the odds of detecting clinically significant prostate cancer (csPCa) by MRI-TRUS fusion biopsy compared with systematic TRUS biopsy. Secondary objectives were the OR for any PCa and the OR after pooling both registration techniques. The electronic databases PubMed, Embase, and Cochrane were systematically searched for relevant studies according to the Preferred Reporting Items for Systematic Review and Meta-analysis Statement. Studies comparing MRI-TRUS fusion and systematic TRUS-guided biopsies in the same patient were included. The quality assessment of included studies was performed using the Quality Assessment of Diagnostic Accuracy Studies version 2. Eleven papers describing elastic and 10 describing rigid registration were included. Meta-analysis showed an OR of csPCa for elastic and rigid registration of 1.45 (95% confidence interval [CI]: 1.21-1.73, p<0.0001) and 1.40 (95% CI: 1.13-1.75, p=0.002), respectively. No significant difference was seen between the subgroups (p=0.83). Pooling subgroups resulted in an OR of 1.43 (95% CI: 1.25-1.63, p<0.00001). No significant difference was identified between rigid and elastic registration for MRI-TRUS fusion-guided biopsy in the detection of csPCa; however, both techniques detected more csPCa than TRUS-guided biopsy alone. We did not identify any significant differences in prostate cancer detection between two distinct magnetic resonance imaging-transrectal ultrasound fusion systems which vary in their method of compensating for prostate deformation. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Anomaly Detection of Electromyographic Signals.

PubMed

Ijaz, Ahsan; Choi, Jongeun

2018-04-01

In this paper, we provide a robust framework to detect anomalous electromyographic (EMG) signals and identify contamination types. As a first step for feature selection, optimally selected Lawton wavelets transform is applied. Robust principal component analysis (rPCA) is then performed on these wavelet coefficients to obtain features in a lower dimension. The rPCA based features are used for constructing a self-organizing map (SOM). Finally, hierarchical clustering is applied on the SOM that separates anomalous signals residing in the smaller clusters and breaks them into logical units for contamination identification. The proposed methodology is tested using synthetic and real world EMG signals. The synthetic EMG signals are generated using a heteroscedastic process mimicking desired experimental setups. A sub-part of these synthetic signals is introduced with anomalies. These results are followed with real EMG signals introduced with synthetic anomalies. Finally, a heterogeneous real world data set is used with known quality issues under an unsupervised setting. The framework provides recall of 90% (± 3.3) and precision of 99%(±0.4).

Enhanced expression of SRPK2 contributes to aggressive progression and metastasis in prostate cancer.

PubMed

Zhuo, Yang Jia; Liu, Ze Zhen; Wan, Song; Cai, Zhi Duan; Xie, Jian Jiang; Cai, Zhou da; Song, Sheng da; Wan, Yue Ping; Hua, Wei; Zhong, Wei de; Wu, Chin Lee

2018-06-01

Serine/Arginine-Rich Protein-Specific Kinase-2 (SRSF protein kinase-2, SRPK2) is up-regulated in multiple human tumors. However, the expression, function and clinical significance of SRPK2 in prostate cancer (PCa) has not yet been understood. We therefore aimed to determine the association of SRPK2 with tumor progression and metastasis in PCa patients in our present study. The expression of SRPK2 was detected by some public datasets and validated using a clinical tissue microarray (TMA) by immunohistochemistry. The association of SRPK2 expression with various clinicopathological characteristics of PCa patients was subsequently statistically analyzed based on the The Cancer Genome Atlas (TCGA) dataset and clinical TMA. The effects of SRPK2 on cancer cell proliferation, migration, invasion, cell cycle progression, apoptosis and tumor growth were then respectively investigated using in vitro and in vivo experiments. First, public datasets showed that SRPK2 expression was greater in PCa tissues when compared with non-cancerous tissues. Statistical analysis demonstrated that high expression of SRPK2 was significantly correlated with a higher Gleason Score, advanced pathological stage and the presence of tumor metastasis in the TCGA Dataset (all P < 0.01). Similar correlations between SRPK2 and a higher Gleason Score or advanced pathological stage were also identified in the TMA (P < 0.05). Kaplan-Meier curve analyses showed that the biochemical recurrence (BCR)-free time of PCa patients with SRPK2 high expression was shorter than for those with SRPK2 low expression (P < 0.05). Second, cell function experiments in PCa cell lines revealed that enhanced SRPK2 expression could promote cell proliferation, migration, invasion and cell cycle progression but suppress tumor cell apoptosis in vitro. Xenograft experiments showed that SRPK2 promoted tumor growth in vivo. In conclusion, our data demonstrated that SRPK2 may play an important role in the progression and metastasis of PCa, which suggests that it might be a potential therapeutic target for PCa clinical therapy. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Non-invasive urinary metabolomic profiling discriminates prostate cancer from benign prostatic hyperplasia.

PubMed

Pérez-Rambla, Clara; Puchades-Carrasco, Leonor; García-Flores, María; Rubio-Briones, José; López-Guerrero, José Antonio; Pineda-Lucena, Antonio

2017-01-01

Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results. In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH. Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using 1 H nuclear magnetic resonance ( 1 H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches. The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH. PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.

VizieR Online Data Catalog: List of 1254 X-ray bursts (in't Zand+, 2017)

NASA Astrophysics Data System (ADS)

in't Zand, J. J. M.; Visser, M. E. B.; Galloway, D. K.; Chenevez, J.; Keek, L.; Kuulkers, E.; Sanchez-Fernandez, C.; Worpel, H.

2017-09-01

The list of thermonuclear X-ray bursts that RXTE detected was obtained from the Multi-INstrument Burst ARchive (MINBAR; Galloway et al. 2010, in COSPAR Meeting, Vol. 38, 38th COSPAR Scientific Assembly, 6). In addition to RXTE/PCA data, MINBAR contains the bursts detected with BeppoSAX/WFC (Jager et al., 1997A&AS..125..557J) and the still operational INTEGRAL/JEM-X (Lund et al., 2003A&A...411L.231L). The PCA list in MINBAR consists of 2288 bursts from 60 sources (i.e., this is slightly more than half the currently known burster population). Some sources only exhibited one burst in the PCA (e.g., KS 1741-293), while others had close to 400 (e.g., 4U 1636-536). (2 data files).

Potential impact of 68Ga-PSMA-11 PET/CT on prostate cancer definitive radiation therapy planning.

PubMed

Calais, Jérémie; Kishan, Amar U; Cao, Minsong; Fendler, Wolfgang P; Eiber, Matthias; Herrmann, Ken; Ceci, Francesco; Reiter, Robert E; Rettig, Matthew B; Hegde, John V; Shaverdian, Narek; King, Christopher R; Steinberg, Michael L; Czernin, Johannes; Nickols, Nicholas G

2018-04-13

Background: Standard-of-care imaging for initial staging of prostate cancer (PCa) underestimates disease burden. Prostate specific membrane antigen (PSMA) positron emission tomography/ computed tomography (PET/CT) detects PCa metastasis with superior accuracy with potential impact definitive radiation therapy (RT) planning for non-metastatic PCa. Objectives: i) To determine how often definitive PCa RT planning based on standard target volumes cover 68 Ga-PSMA-11 PET/CT defined disease, and ii) To assess the potential impact of 68 Ga-PSMA-11 PET/CT on definitive PCa RT planning. Patients and Methods: This is a post-hoc analysis of an intention to treat population of 73 patients with localized PCa without prior local therapy who underwent 68 Ga-PSMA PET/CT for initial staging as part of an Investigational New Drug trial. 11/73 were intermediate-risk (15%), 33/73 were high-risk (45%), 22/73 were very high risk (30%), and 7/73 were N1 (9.5%). Clinical target volumes (CTVs) that included the prostate, seminal vesicles, and pelvic lymph nodes (LNs) using Radiation Therapy Oncology Group (RTOG) consensus guidelines were contoured on the CT portion of the PET/CT by a radiation oncologist blinded to the PET findings. 68 Ga-PSMA-11 PET/CT images were analyzed by a nuclear medicine physician. PSMA-positive lesions not covered by planning volumes based on the CTVs were considered to have a major potential impact on treatment planning. Results: All patients had PSMA-positive primary prostate lesion(s). 25/73 (34%) and 7/73 (9.5%) had PSMA-positive pelvic nodal and distant metastases, respectively. The sites of nodal metastases in decreasing order of frequency were external iliac (20.5%), common iliac (13.5%), internal iliac (12.5%) obturator (12.5%), perirectal (4%), abdominal (4%), upper-diaphragm (4%), and presacral (1.5%). The median size of the nodal lesions was 6 mm (range 4-24 mm). RT planning based on the CTVs covered 69/73 (94.5%) of primary disease and 20/25 (80%) of pelvic nodal disease, on a per-patient analysis. Conclusion: 68 Ga-PSMA-11 PET/CT had a major impact on intended definitive PCa RT planning in 12/73 of patients (16.5%) when RT fields covered the prostate, seminal vesicles and the pelvic LNs, and in 25/66 of patients (37%) when RT fields covered only the prostate and seminal vesicles (without pelvic LNs). Copyright © 2018 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

SU-D-207A-07: The Effects of Inter-Cycle Respiratory Motion Variation On Dose Accumulation in Single Fraction MR-Guided SBRT Treatment of Renal Cell Carcinoma

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

Stemkens, B; Glitzner, M; Kontaxis, C

Purpose: To assess the dose deposition in simulated single-fraction MR-Linac treatments of renal cell carcinoma, when inter-cycle respiratory motion variation is taken into account using online MRI. Methods: Three motion characterization methods, with increasing complexity, were compared to evaluate the effect of inter-cycle motion variation and drifts on the accumulated dose for an SBRT kidney MR-Linac treatment: 1) STATIC, in which static anatomy was assumed, 2) AVG-RESP, in which 4D-MRI phase-volumes were time-weighted, based on the respiratory phase and 3) PCA, in which 3D volumes were generated using a PCA-model, enabling the detection of inter-cycle variations and drifts. An experimentalmore » ITV-based kidney treatment was simulated in a 1.5T magnetic field on three volunteer datasets. For each volunteer a retrospectively sorted 4D-MRI (ten respiratory phases) and fast 2D cine-MR images (temporal resolution = 476ms) were acquired to simulate MR-imaging during radiation. For each method, the high spatio-temporal resolution 3D volumes were non-rigidly registered to obtain deformation vector fields (DVFs). Using the DVFs, pseudo-CTs (generated from the 4D-MRI) were deformed and the dose was accumulated for the entire treatment. The accuracies of all methods were independently determined using an additional, orthogonal 2D-MRI slice. Results: Motion was most accurately estimated using the PCA method, which correctly estimated drifts and inter-cycle variations (RMSE=3.2, 2.2, 1.1mm on average for STATIC, AVG-RESP and PCA, compared to the 2DMRI slice). Dose-volume parameters on the ITV showed moderate changes (D99=35.2, 32.5, 33.8Gy for STATIC, AVG-RESP and PCA). AVG-RESP showed distinct hot/cold spots outside the ITV margin, which were more distributed for the PCA scenario, since inter-cycle variations were not modeled by the AVG-RESP method. Conclusion: Dose differences were observed when inter-cycle variations were taken into account. The increased inter-cycle randomness in motion as captured by the PCA model mitigates the local (erroneous) hotspots estimated by the AVG-RESP method.« less

Detectability Factors for Earth-based Imaging of the LCROSS Ejecta Plume

NASA Astrophysics Data System (ADS)

Strycker, Paul D.; Schotte, Jonathan M.; Temme, Ruth L.; Chanover, Nancy J.

2017-10-01

NASA’s Lunar Crater Observation and Sensing Satellite (LCROSS) mission delivered a kinetic impactor into Cabeus Crater on 9 October 2009 [1, 2]. Observing campaigns from Earth-based telescopes at multiple facilities attempted to obtain temporally-resolved imaging of the ejecta plume [3], but no Earth-based imaging detections were reported until 2013 after processing images with Principal Component Analysis (PCA) filtering [4]. Subsequently, PCA filtering has revealed plume detections in two additional cameras and also confirmed a non-detection from one telescope [5, 6]. This combination of detection and non-detection data is useful in determining the criteria for detectability in future observations of transient events. The goal of this work is to identify factors contributing to detectability and to establish thresholds applicable to the LCROSS event. We take the data containing detections and then degrade a specific factor in them until the plume is no longer detectable. These derived thresholds for factors (e.g., scattered light, temporal resolution, spatial resolution, field of view, and signal-to-noise of the illuminated foreground of Cabeus) can be compared to the properties of the actual non-detection data to identify problems specific to its observing conditions or observational setup. The percent differences between the thresholds and both the detection data and non-detection data may also reveal the relative importance of these detectability factors. This work was supported by NASA’s Lunar Data Analysis Program through grant number NNX15AP92G. Observations reported here were obtained at the MMT Observatory, a joint facility of the Smithsonian Institution and the University of Arizona.References: [1] Colaprete, A. et al. (2010) Science, 330, 463-468. [2] Schultz, P. H. et al. (2010) Science, 330, 468-472. [3] Heldmann, J. L. et al. (2012) Space Sci. Rev., 167:93-140, doi:10.1007/s11214-011-9759-y. [4] Strycker, P. D. et al. (2013) Nat. Commun., 4:2620, doi:10.1038/ncomms3620. [5] Temme, R. L. et al. (2016) LPS XLVII, Abstract #1166. [6] Schotte, J. M. et al. (2017) LPS XLVIII, Abstract #1503.

68Ga-PSMA-11 PET/CT for prostate cancer staging and risk stratification in Chinese patients.

PubMed

Zang, Shiming; Shao, Guoqiang; Cui, Can; Li, Tian-Nv; Huang, Yue; Yao, Xiaochen; Fan, Qiu; Chen, Zejun; Du, Jin; Jia, Ruipeng; Sun, Hongbin; Hua, Zichun; Tang, Jun; Wang, Feng

2017-02-14

We evaluated the clinical utility of 68Ga-PSMA-11 PET/CT for staging and risk stratification of treatment-naïve prostate cancer (PCa) and metastatic castrate-resistant prostate cancer (mCRPC). Twenty-two consecutive patients with treatment-naïve PCa and 18 with mCRPC were enrolled. 68Ga-PSMA-11 PET/CT and magnetic resonance imaging (MRI) were performed for the evaluation of primary prostatic lesions, and bone scans were used for evaluation bone metastasis. Among the 40 patients, 37 (92.5% [22 treatment-naïve PCa, 15 mCRPC]) showed PSMA-avid lesions on 68Ga-PSMA-11 images. Only 3 patients with stable mCRPC after chemotherapy were negative for PSMA. The sensitivity, specificity and accuracy of 68Ga-PSMA-11 imaging were 97.3%, 100.0% and 97.5%, respectively. The maximum standardized uptake (SUVmax) of prostatic lesions was 17.09 ± 11.08 and 13.33 ± 12.31 in treatment-naïve PCa and mCRPC, respectively. 68Ga-PSMA-11 revealed 105 metastatic lymph nodes in 15 patients; the SUVmax was 16.85 ± 9.70 and 7.54 ± 5.20 in treatment-naïve PCa and mCRPC, respectively. 68Ga-PSMA-11 PET/CT also newly detected visceral metastasis in 9 patients (22.5%) and bone metastasis in 29 patients (72.5%). 68Ga-PSMA-11 PET/CT exhibits potential for staging and risk stratification in naïve PCa, as well as improved sensitivity for detection of lymph node and remote metastasis.

Follow-up of negative MRI-targeted prostate biopsies: when are we missing cancer?

PubMed

Gold, Samuel A; Hale, Graham R; Bloom, Jonathan B; Smith, Clayton P; Rayn, Kareem N; Valera, Vladimir; Wood, Bradford J; Choyke, Peter L; Turkbey, Baris; Pinto, Peter A

2018-05-21

Multiparametric magnetic resonance imaging (mpMRI) has improved clinicians' ability to detect clinically significant prostate cancer (csPCa). Combining or fusing these images with the real-time imaging of transrectal ultrasound (TRUS) allows urologists to better sample lesions with a targeted biopsy (Tbx) leading to the detection of greater rates of csPCa and decreased rates of low-risk PCa. In this review, we evaluate the technical aspects of the mpMRI-guided Tbx procedure to identify possible sources of error and provide clinical context to a negative Tbx. A literature search was conducted of possible reasons for false-negative TBx. This includes discussion on false-positive mpMRI findings, termed "PCa mimics," that may incorrectly suggest high likelihood of csPCa as well as errors during Tbx resulting in inexact image fusion or biopsy needle placement. Despite the strong negative predictive value associated with Tbx, concerns of missed disease often remain, especially with MR-visible lesions. This raises questions about what to do next after a negative Tbx result. Potential sources of error can arise from each step in the targeted biopsy process ranging from "PCa mimics" or technical errors during mpMRI acquisition to failure to properly register MRI and TRUS images on a fusion biopsy platform to technical or anatomic limits on needle placement accuracy. A better understanding of these potential pitfalls in the mpMRI-guided Tbx procedure will aid interpretation of a negative Tbx, identify areas for improving technical proficiency, and improve both physician understanding of negative Tbx and patient-management options.

68Ga-PSMA-11 PET/CT for prostate cancer staging and risk stratification in Chinese patients

PubMed Central

Cui, Can; Li, Tian-Nv; Huang, Yue; Yao, Xiaochen; Fan, Qiu; Chen, Zejun; Du, Jin; Jia, Ruipeng; Sun, Hongbin; Hua, Zichun; Tang, Jun; Wang, Feng

2017-01-01

We evaluated the clinical utility of 68Ga-PSMA-11 PET/CT for staging and risk stratification of treatment-naïve prostate cancer (PCa) and metastatic castrate-resistant prostate cancer (mCRPC). Twenty-two consecutive patients with treatment-naïve PCa and 18 with mCRPC were enrolled. 68Ga-PSMA-11 PET/CT and magnetic resonance imaging (MRI) were performed for the evaluation of primary prostatic lesions, and bone scans were used for evaluation bone metastasis. Among the 40 patients, 37 (92.5% [22 treatment-naïve PCa, 15 mCRPC]) showed PSMA-avid lesions on 68Ga-PSMA-11 images. Only 3 patients with stable mCRPC after chemotherapy were negative for PSMA. The sensitivity, specificity and accuracy of 68Ga-PSMA-11 imaging were 97.3%, 100.0% and 97.5%, respectively. The maximum standardized uptake (SUVmax) of prostatic lesions was 17.09 ± 11.08 and 13.33 ± 12.31 in treatment-naïve PCa and mCRPC, respectively. 68Ga-PSMA-11 revealed 105 metastatic lymph nodes in 15 patients; the SUVmax was 16.85 ± 9.70 and 7.54 ± 5.20 in treatment-naïve PCa and mCRPC, respectively. 68Ga-PSMA-11 PET/CT also newly detected visceral metastasis in 9 patients (22.5%) and bone metastasis in 29 patients (72.5%). 68Ga-PSMA-11 PET/CT exhibits potential for staging and risk stratification in naïve PCa, as well as improved sensitivity for detection of lymph node and remote metastasis. PMID:28103574

Whole milk intake is associated with prostate cancer-specific mortality among U.S. male physicians.

PubMed

Song, Yan; Chavarro, Jorge E; Cao, Yin; Qiu, Weiliang; Mucci, Lorelei; Sesso, Howard D; Stampfer, Meir J; Giovannucci, Edward; Pollak, Michael; Liu, Simin; Ma, Jing

2013-02-01

Previous studies have associated higher milk intake with greater prostate cancer (PCa) incidence, but little data are available concerning milk types and the relation between milk intake and risk of fatal PCa. We investigated the association between intake of dairy products and the incidence and survival of PCa during a 28-y follow-up. We conducted a cohort study in the Physicians' Health Study (n = 21,660) and a survival analysis among the incident PCa cases (n = 2806). Information on dairy product consumption was collected at baseline. PCa cases and deaths (n = 305) were confirmed during follow-up. The intake of total dairy products was associated with increased PCa incidence [HR = 1.12 (95% CI: 0.93, 1.35); >2.5 servings/d vs. ≤0.5 servings/d]. Skim/low-fat milk intake was positively associated with risk of low-grade, early stage, and screen-detected cancers, whereas whole milk intake was associated only with fatal PCa [HR = 1.49 (95% CI: 0.97, 2.28); ≥237 mL/d (1 serving/d) vs. rarely consumed]. In the survival analysis, whole milk intake remained associated with risk of progression to fatal disease after diagnosis [HR = 2.17 (95% CI: 1.34, 3.51)]. In this prospective cohort, higher intake of skim/low-fat milk was associated with a greater risk of nonaggressive PCa. Most importantly, only whole milk was consistently associated with higher incidence of fatal PCa in the entire cohort and higher PCa-specific mortality among cases. These findings add further evidence to suggest the potential role of dairy products in the development and prognosis of PCa.

Immunoseroproteomic Profiling in African American Men with Prostate Cancer: Evidence for an Autoantibody Response to Glycolysis and Plasminogen-Associated Proteins*

PubMed Central

Sanchez, Tino W.; Zhang, Guangyu; Li, Jitian; Dai, Liping; Mirshahidi, Saied; Wall, Nathan R.; Yates, Clayton; Wilson, Colwick; Montgomery, Susanne; Zhang, Jian-Ying; Casiano, Carlos A.

2016-01-01

African American (AA) men suffer from a disproportionately high incidence and mortality of prostate cancer (PCa) compared with other racial/ethnic groups. Despite these disparities, African American men are underrepresented in clinical trials and in studies on PCa biology and biomarker discovery. We used immunoseroproteomics to profile antitumor autoantibody responses in AA and European American (EA) men with PCa, and explored differences in these responses. This minimally invasive approach detects autoantibodies to tumor-associated antigens that could serve as clinical biomarkers and immunotherapeutic agents. Sera from AA and EA men with PCa were probed by immunoblotting against PC3 cell proteins, with AA sera showing stronger immunoreactivity. Mass spectrometry analysis of immunoreactive protein spots revealed that several AA sera contained autoantibodies to a number of proteins associated with both the glycolysis and plasminogen pathways, particularly to alpha-enolase (ENO1). The proteomic data is deposited in ProteomeXchange with identifier PXD003968. Analysis of sera from 340 racially diverse men by enzyme-linked immunosorbent assays (ELISA) showed higher frequency of anti-ENO1 autoantibodies in PCa sera compared with control sera. We observed differences between AA-PCa and EA-PCa patients in their immunoreactivity against ENO1. Although EA-PCa sera reacted with higher frequency against purified ENO1 in ELISA and recognized by immunoblotting the endogenous cellular ENO1 across a panel of prostate cell lines, AA-PCa sera reacted weakly against this protein by ELISA but recognized it by immunoblotting preferentially in metastatic cell lines. These race-related differences in immunoreactivity to ENO1 could not be accounted by differential autoantibody recognition of phosphoepitopes within this antigen. Proteomic analysis revealed differences in the posttranslational modification profiles of ENO1 variants differentially recognized by AA-PCa and EA-PCa sera. These intriguing results suggest the possibility of race-related differences in the antitumor autoantibody response in PCa, and have implications for defining novel biological determinants of PCa health disparities. PMID:27742740

Detection of Iberian ham aroma by a semiconductor multisensorial system.

PubMed

Otero, Laura; Horrillo, M A Carmen; García, María; Sayago, Isabel; Aleixandre, Manuel; Fernández, M A Jesús; Arés, Luis; Gutiérrez, Javier

2003-11-01

A semiconductor multisensorial system, based on tin oxide, to control the quality of dry-cured Iberian hams is described. Two types of ham (submitted to different drying temperatures) were selected. Good responses were obtained from the 12 elements forming the multisensor for different operating temperatures. Discrimination between the two types of ham was successfully realised through principal component analysis (PCA).

Fast clustering algorithm for large ECG data sets based on CS theory in combination with PCA and K-NN methods.

PubMed

Balouchestani, Mohammadreza; Krishnan, Sridhar

2014-01-01

Long-term recording of Electrocardiogram (ECG) signals plays an important role in health care systems for diagnostic and treatment purposes of heart diseases. Clustering and classification of collecting data are essential parts for detecting concealed information of P-QRS-T waves in the long-term ECG recording. Currently used algorithms do have their share of drawbacks: 1) clustering and classification cannot be done in real time; 2) they suffer from huge energy consumption and load of sampling. These drawbacks motivated us in developing novel optimized clustering algorithm which could easily scan large ECG datasets for establishing low power long-term ECG recording. In this paper, we present an advanced K-means clustering algorithm based on Compressed Sensing (CS) theory as a random sampling procedure. Then, two dimensionality reduction methods: Principal Component Analysis (PCA) and Linear Correlation Coefficient (LCC) followed by sorting the data using the K-Nearest Neighbours (K-NN) and Probabilistic Neural Network (PNN) classifiers are applied to the proposed algorithm. We show our algorithm based on PCA features in combination with K-NN classifier shows better performance than other methods. The proposed algorithm outperforms existing algorithms by increasing 11% classification accuracy. In addition, the proposed algorithm illustrates classification accuracy for K-NN and PNN classifiers, and a Receiver Operating Characteristics (ROC) area of 99.98%, 99.83%, and 99.75% respectively.

Comparison of 68Ga-PSMA-11 PET-CT with mpMRI for preoperative lymph node staging in patients with intermediate to high-risk prostate cancer.

PubMed

Zhang, Qing; Zang, Shiming; Zhang, Chengwei; Fu, Yao; Lv, Xiaoyu; Zhang, Qinglei; Deng, Yongming; Zhang, Chuan; Luo, Rui; Zhao, Xiaozhi; Wang, Wei; Wang, Feng; Guo, Hongqian

2017-11-07

To evaluate the diagnostic value of 68 Ga-PSMA-11 PET-CT with multiparametric magnetic resonance imaging (mpMRI) for lymph node (LN) staging in patients with intermediate- to high-risk prostate cancer (PCa) undergoing radical prostatectomy (RP) with pelvic lymph node dissection (PLND). We retrospectively identified 42 consecutive patients with intermediate- to high-risk PCa according to D'Amico and without concomitant cancer. Preoperative 68 Ga-PSMA-11 PET-CT, pelvic mpMRI and subsequent robot assisted laparoscopic RP with PLND were performed in all patients. Among 42 patients assessed, the preoperative PSA value, Gleason score, pT stage and intraprostatic PCa volume of patients with LN metastases were all significantly higher than those without metastases (P = 0.029, 0.028, 0.004, respectively). The average maximum standardized uptake value (SUV) of 68 Ga-PSMA-11 PET-CT positive PCa of patients with or without LN metastases were 13.10 (range 6.12-51.75) and 7.22 (range 5.4-11.2), respectively (P < 0.001). 68 Ga-PSMA-11 PET-CT and pelvic mpMRI had the ability of succeed on preoperative definite accurate diagnosis and accurate localization of primary PCa in all 42 patients. Fifteen patients (35.71%) had a pN1 stage. 51 positive LN were found. Both 68 Ga-PSMA-11 PET-CT and pelvic mpMRI displayed brillient patient-based and region-based sensitivity, specificity, negative predictive value and positive predictive value. There was no statistical difference for the detection of LNMs according to the diameter of the LNMs between 68 Ga-PSMA-11 PET-CT and mpMRI in this study. Both 68 Ga-PSMA-11 PET-CT and mpMRI performed great value for LN staging in patients with intermediate- to high-risk PCa undergoing RP with PLND. However, despite excellent performance of 68 Ga-PSMA-11 PET-CT, it cannot replace mpMRI that remains excellent for lymph node staging.

Hyperspectral Image Denoising Using a Nonlocal Spectral Spatial Principal Component Analysis

NASA Astrophysics Data System (ADS)

Li, D.; Xu, L.; Peng, J.; Ma, J.

2018-04-01

Hyperspectral images (HSIs) denoising is a critical research area in image processing duo to its importance in improving the quality of HSIs, which has a negative impact on object detection and classification and so on. In this paper, we develop a noise reduction method based on principal component analysis (PCA) for hyperspectral imagery, which is dependent on the assumption that the noise can be removed by selecting the leading principal components. The main contribution of paper is to introduce the spectral spatial structure and nonlocal similarity of the HSIs into the PCA denoising model. PCA with spectral spatial structure can exploit spectral correlation and spatial correlation of HSI by using 3D blocks instead of 2D patches. Nonlocal similarity means the similarity between the referenced pixel and other pixels in nonlocal area, where Mahalanobis distance algorithm is used to estimate the spatial spectral similarity by calculating the distance in 3D blocks. The proposed method is tested on both simulated and real hyperspectral images, the results demonstrate that the proposed method is superior to several other popular methods in HSI denoising.

A case-control study of lower urinary-tract infections, associated antibiotics and the risk of developing prostate cancer using PCBaSe 3.0.

PubMed

Russell, Beth; Garmo, Hans; Beckmann, Kerri; Stattin, Pär; Adolfsson, Jan; Van Hemelrijck, Mieke

2018-01-01

To investigate the association between lower urinary-tract infections, their associated antibiotics and the subsequent risk of developing PCa. Using data from the Swedish PCBaSe 3.0, we performed a matched case-control study (8762 cases and 43806 controls). Conditional logistic regression analysis was used to assess the association between lower urinary-tract infections, related antibiotics and PCa, whilst adjusting for civil status, education, Charlson Comorbidity Index and time between lower urinary-tract infection and PCa diagnosis. It was found that lower urinary-tract infections did not affect PCa risk, however, having a lower urinary-tract infection or a first antibiotic prescription 6-12 months before PCa were both associated with an increased risk of PCa (OR: 1.50, 95% CI: 1.23-1.82 and 1.96, 1.71-2.25, respectively), as compared to men without lower urinary-tract infections. Compared to men with no prescriptions for antibiotics, men who were prescribed ≥10 antibiotics, were 15% less likely to develop PCa (OR: 0.85, 95% CI: 0.78-0.91). PCa was not found to be associated with diagnosis of a urinary-tract infection or frequency, but was positively associated with short time since diagnoses of lower urinary-tract infection or receiving prescriptions for antibiotics. These observations can likely be explained by detection bias, which highlights the importance of data on the diagnostic work-up when studying potential risk factors for PCa.

Principal component and spatial correlation analysis of spectroscopic-imaging data in scanning probe microscopy.

PubMed

Jesse, Stephen; Kalinin, Sergei V

2009-02-25

An approach for the analysis of multi-dimensional, spectroscopic-imaging data based on principal component analysis (PCA) is explored. PCA selects and ranks relevant response components based on variance within the data. It is shown that for examples with small relative variations between spectra, the first few PCA components closely coincide with results obtained using model fitting, and this is achieved at rates approximately four orders of magnitude faster. For cases with strong response variations, PCA allows an effective approach to rapidly process, de-noise, and compress data. The prospects for PCA combined with correlation function analysis of component maps as a universal tool for data analysis and representation in microscopy are discussed.

Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning.

PubMed

Wang, Xinggang; Yang, Wei; Weinreb, Jeffrey; Han, Juan; Li, Qiubai; Kong, Xiangchuang; Yan, Yongluan; Ke, Zan; Luo, Bo; Liu, Tao; Wang, Liang

2017-11-13

Prostate cancer (PCa) is a major cause of death since ancient time documented in Egyptian Ptolemaic mummy imaging. PCa detection is critical to personalized medicine and varies considerably under an MRI scan. 172 patients with 2,602 morphologic images (axial 2D T2-weighted imaging) of the prostate were obtained. A deep learning with deep convolutional neural network (DCNN) and a non-deep learning with SIFT image feature and bag-of-word (BoW), a representative method for image recognition and analysis, were used to distinguish pathologically confirmed PCa patients from prostate benign conditions (BCs) patients with prostatitis or prostate benign hyperplasia (BPH). In fully automated detection of PCa patients, deep learning had a statistically higher area under the receiver operating characteristics curve (AUC) than non-deep learning (P = 0.0007 < 0.001). The AUCs were 0.84 (95% CI 0.78-0.89) for deep learning method and 0.70 (95% CI 0.63-0.77) for non-deep learning method, respectively. Our results suggest that deep learning with DCNN is superior to non-deep learning with SIFT image feature and BoW model for fully automated PCa patients differentiation from prostate BCs patients. Our deep learning method is extensible to image modalities such as MR imaging, CT and PET of other organs.

Optimized principal component analysis on coronagraphic images of the fomalhaut system

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

Meshkat, Tiffany; Kenworthy, Matthew A.; Quanz, Sascha P.

We present the results of a study to optimize the principal component analysis (PCA) algorithm for planet detection, a new algorithm complementing angular differential imaging and locally optimized combination of images (LOCI) for increasing the contrast achievable next to a bright star. The stellar point spread function (PSF) is constructed by removing linear combinations of principal components, allowing the flux from an extrasolar planet to shine through. The number of principal components used determines how well the stellar PSF is globally modeled. Using more principal components may decrease the number of speckles in the final image, but also increases themore » background noise. We apply PCA to Fomalhaut Very Large Telescope NaCo images acquired at 4.05 μm with an apodized phase plate. We do not detect any companions, with a model dependent upper mass limit of 13-18 M {sub Jup} from 4-10 AU. PCA achieves greater sensitivity than the LOCI algorithm for the Fomalhaut coronagraphic data by up to 1 mag. We make several adaptations to the PCA code and determine which of these prove the most effective at maximizing the signal-to-noise from a planet very close to its parent star. We demonstrate that optimizing the number of principal components used in PCA proves most effective for pulling out a planet signal.« less

Prospective evaluation of 18F-FACBC PET/CT and PET/MRI versus multiparametric MRI in intermediate- to high-risk prostate cancer patients (FLUCIPRO trial).

PubMed

Jambor, Ivan; Kuisma, Anna; Kähkönen, Esa; Kemppainen, Jukka; Merisaari, Harri; Eskola, Olli; Teuho, Jarmo; Perez, Ileana Montoya; Pesola, Marko; Aronen, Hannu J; Boström, Peter J; Taimen, Pekka; Minn, Heikki

2018-03-01

The purpose of this study was to evaluate 18 F-FACBC PET/CT, PET/MRI, and multiparametric MRI (mpMRI) in detection of primary prostate cancer (PCa). Twenty-six men with histologically confirmed PCa underwent PET/CT immediately after injection of 369 ± 10 MBq 18 F-FACBC (fluciclovine) followed by PET/MRI started 55 ± 7 min from injection. Maximum standardized uptake values (SUV max ) were measured for both hybrid PET acquisitions. A separate mpMRI was acquired within a week of the PET scans. Logan plots were used to calculate volume of distribution (V T ). The presence of PCa was estimated in 12 regions with radical prostatectomy findings as ground truth. For each imaging modality, area under the curve (AUC) for detection of PCa was determined to predict diagnostic performance. The clinical trial registration number is NCT02002455. In the visual analysis, 164/312 (53%) regions contained PCa, and 41 tumor foci were identified. PET/CT demonstrated the highest sensitivity at 87% while its specificity was low at 56%. The AUC of both PET/MRI and mpMRI significantly (p < 0.01) outperformed that of PET/CT while no differences were detected between PET/MRI and mpMRI. SUV max and V T of Gleason score (GS) >3 + 4 tumors were significantly (p < 0.05) higher than those for GS 3 + 3 and benign hyperplasia. A total of 442 lymph nodes were evaluable for staging, and PET/CT and PET/MRI demonstrated true-positive findings in only 1/7 patients with metastatic lymph nodes. Quantitative 18 F-FACBC imaging significantly correlated with GS but failed to outperform MRI in lesion detection. 18 F-FACBC may assist in targeted biopsies in the setting of hybrid imaging with MRI.

Comparison of water extraction methods in Tibet based on GF-1 data

NASA Astrophysics Data System (ADS)

Jia, Lingjun; Shang, Kun; Liu, Jing; Sun, Zhongqing

2018-03-01

In this study, we compared four different water extraction methods with GF-1 data according to different water types in Tibet, including Support Vector Machine (SVM), Principal Component Analysis (PCA), Decision Tree Classifier based on False Normalized Difference Water Index (FNDWI-DTC), and PCA-SVM. The results show that all of the four methods can extract large area water body, but only SVM and PCA-SVM can obtain satisfying extraction results for small size water body. The methods were evaluated by both overall accuracy (OAA) and Kappa coefficient (KC). The OAA of PCA-SVM, SVM, FNDWI-DTC, PCA are 96.68%, 94.23%, 93.99%, 93.01%, and the KCs are 0.9308, 0.8995, 0.8962, 0.8842, respectively, in consistent with visual inspection. In summary, SVM is better for narrow rivers extraction and PCA-SVM is suitable for water extraction of various types. As for dark blue lakes, the methods using PCA can extract more quickly and accurately.

Tomato seeds maturity detection system based on chlorophyll fluorescence

NASA Astrophysics Data System (ADS)

Li, Cuiling; Wang, Xiu; Meng, Zhijun

2016-10-01

Chlorophyll fluorescence intensity can be used as seed maturity and quality evaluation indicator. Chlorophyll fluorescence intensity of seed coats is tested to judge the level of chlorophyll content in seeds, and further to judge the maturity and quality of seeds. This research developed a detection system of tomato seeds maturity based on chlorophyll fluorescence spectrum technology, the system included an excitation light source unit, a fluorescent signal acquisition unit and a data processing unit. The excitation light source unit consisted of two high power LEDs, two radiators and two constant current power supplies, and it was designed to excite chlorophyll fluorescence of tomato seeds. The fluorescent signal acquisition unit was made up of a fluorescence spectrometer, an optical fiber, an optical fiber scaffolds and a narrowband filter. The data processing unit mainly included a computer. Tomato fruits of green ripe stage, discoloration stage, firm ripe stage and full ripe stage were harvested, and their seeds were collected directly. In this research, the developed tomato seeds maturity testing system was used to collect fluorescence spectrums of tomato seeds of different maturities. Principal component analysis (PCA) method was utilized to reduce the dimension of spectral data and extract principal components, and PCA was combined with linear discriminant analysis (LDA) to establish discriminant model of tomato seeds maturity, the discriminant accuracy was greater than 90%. Research results show that using chlorophyll fluorescence spectrum technology is feasible for seeds maturity detection, and the developed tomato seeds maturity testing system has high detection accuracy.

Nanocrystalline Nb-Al-Ge mixtures fabricated using wet mechanical milling

NASA Astrophysics Data System (ADS)

Pusceddu, E.; Charlton, S.; Hampshire, D. P.

2008-02-01

An investigation into Nb-Al-Ge mixtures is presented with special attention to the superconducting compounds Nb3(Al1-xGex) with x = 0, 0.3 and 1, which are reported to provide the highest upper critical field values for Nb-based compounds. Wet mechanical milling using copper milling media and distilled water as a process control agent (PCA) was used with the intention of improving the yield, properties and the performance of these materials. Very high yields of nanocrystalline material were achieved but significant copper contamination occurred - confirmed using inductively-coupled-plasma atomic-emission-spectroscopy. Simultaneous thermogravimetric measurements and differential scanning calorimetry were performed on powders milled for up to 20 h with different PCA content, to quantify the work done on the powders. A typical grain size of a few nm was obtained for the Nb-Al-Ge mixtures after several hours milling. Powder ground for 20 h with 5% PCA was processed using a hot isostatic press (HIP) operating at 2000 atm and temperatures up to 750 °C. The room temperature resistivity decreased as the temperature of the HIPing increased. Unfortunately, despite the nanocrystalline microstructure of the powders and the high HIP temperatures, if superconducting material was formed it was below the detection level of resistivity, Ac. susceptibility and SQUID measurements. We conclude that during milling there was widespread contamination of the powders by the PCA so that milling with distilled water as a PCA is not to be recommended for fabricating nanocrystalline Nb3(Al1-xGex) A15 superconducting compounds.

Contrast-Enhanced Ultrasound Angiogenesis Imaging by Mutual Information Analysis for Prostate Cancer Localization.

PubMed

Schalk, Stefan G; Demi, Libertario; Bouhouch, Nabil; Kuenen, Maarten P J; Postema, Arnoud W; de la Rosette, Jean J M C H; Wijkstra, Hessel; Tjalkens, Tjalling J; Mischi, Massimo

2017-03-01

The role of angiogenesis in cancer growth has stimulated research aimed at noninvasive cancer detection by blood perfusion imaging. Recently, contrast ultrasound dispersion imaging was proposed as an alternative method for angiogenesis imaging. After the intravenous injection of an ultrasound-contrast-agent bolus, dispersion can be indirectly estimated from the local similarity between neighboring time-intensity curves (TICs) measured by ultrasound imaging. Up until now, only linear similarity measures have been investigated. Motivated by the promising results of this approach in prostate cancer (PCa), we developed a novel dispersion estimation method based on mutual information, thus including nonlinear similarity, to further improve its ability to localize PCa. First, a simulation study was performed to establish the theoretical link between dispersion and mutual information. Next, the method's ability to localize PCa was validated in vivo in 23 patients (58 datasets) referred for radical prostatectomy by comparison with histology. A monotonic relationship between dispersion and mutual information was demonstrated. The in vivo study resulted in a receiver operating characteristic (ROC) curve area equal to 0.77, which was superior (p = 0.21-0.24) to that obtained by linear similarity measures (0.74-0.75) and (p <; 0.05) to that by conventional perfusion parameters (≤0.70). Mutual information between neighboring time-intensity curves can be used to indirectly estimate contrast dispersion and can lead to more accurate PCa localization. An improved PCa localization method can possibly lead to better grading and staging of tumors, and support focal-treatment guidance. Moreover, future employment of the method in other types of angiogenic cancer can be considered.

PCA leverage: outlier detection for high-dimensional functional magnetic resonance imaging data.

PubMed

Mejia, Amanda F; Nebel, Mary Beth; Eloyan, Ani; Caffo, Brian; Lindquist, Martin A

2017-07-01

Outlier detection for high-dimensional (HD) data is a popular topic in modern statistical research. However, one source of HD data that has received relatively little attention is functional magnetic resonance images (fMRI), which consists of hundreds of thousands of measurements sampled at hundreds of time points. At a time when the availability of fMRI data is rapidly growing-primarily through large, publicly available grassroots datasets-automated quality control and outlier detection methods are greatly needed. We propose principal components analysis (PCA) leverage and demonstrate how it can be used to identify outlying time points in an fMRI run. Furthermore, PCA leverage is a measure of the influence of each observation on the estimation of principal components, which are often of interest in fMRI data. We also propose an alternative measure, PCA robust distance, which is less sensitive to outliers and has controllable statistical properties. The proposed methods are validated through simulation studies and are shown to be highly accurate. We also conduct a reliability study using resting-state fMRI data from the Autism Brain Imaging Data Exchange and find that removal of outliers using the proposed methods results in more reliable estimation of subject-level resting-state networks using independent components analysis. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

MRI in early prostate cancer detection: how to manage indeterminate or equivocal PI-RADS 3 lesions?

PubMed

Schoots, Ivo G

2018-02-01

This review focuses on indeterminate lesions on prostate magnetic resonance imaging (MRI), assigned as PI-RADS category 3. The prevalence of PI-RADS 3 index lesion in the diagnostic work-up is significant, varying between one in three (32%) to one in five (22%) men, depending on patient cohort of first biopsies, previously negative biopsies, and active surveillance biopsies. A management strategy must be developed for this group of men with an indeterminate suspicion of having clinically significant prostate cancer (csPCa). Currently available data show that the actual prevalence of csPCa after targeted biopsy in PI-RADS 3 lesions vary between patients groups from one in five (21%) to one in six (16%), depending on previous biopsy status. Although this prevalence is lower in comparison to PI-RADS 4 and PI-RADS 5 lesions, still a considerable proportion of men harbor significant disease. Men with such a PI-RADS 3 lesion should therefore be adequately managed. In general, the clinical approach of using a threshold of PI-RADS ≥4 instead of PI-RADS ≥3 to select MRI for targeted biopsies is not supported by data from our explorative literature search using current definitions of csPCa. A possible adaptation to the threshold of PI-RADS ≥4 in combination with other clinical markers could be considered within an active surveillance protocol, where the balance between the individual risk of missing csPCa and the constant process of repeating prostate biopsies is crucial. In the future, improvements in MR imaging and interpretation, combined with molecular biomarkers and multivariate risk models will all be employed in prostate cancer detection and monitoring. These combinations will aid decision-making in challenging circumstances, such as unclear and diagnostic equivocal results for csPCa at early detection.

Principal component analysis for the early detection of mastitis and lameness in dairy cows.

PubMed

Miekley, Bettina; Traulsen, Imke; Krieter, Joachim

2013-08-01

This investigation analysed the applicability of principal component analysis (PCA), a latent variable method, for the early detection of mastitis and lameness. Data used were recorded on the Karkendamm dairy research farm between August 2008 and December 2010. For mastitis and lameness detection, data of 338 and 315 cows in their first 200 d in milk were analysed, respectively. Mastitis as well as lameness were specified according to veterinary treatments. Diseases were defined as disease blocks. The different definitions used (two for mastitis, three for lameness) varied solely in the sequence length of the blocks. Only the days before the treatment were included in the blocks. Milk electrical conductivity, milk yield and feeding patterns (feed intake, number of feeding visits and time at the trough) were used for recognition of mastitis. Pedometer activity and feeding patterns were utilised for lameness detection. To develop and verify the PCA model, the mastitis and the lameness datasets were divided into training and test datasets. PCA extracted uncorrelated principle components (PC) by linear transformations of the raw data so that the first few PCs captured most of the variations in the original dataset. For process monitoring and disease detection, these resulting PCs were applied to the Hotelling's T 2 chart and to the residual control chart. The results show that block sensitivity of mastitis detection ranged from 77·4 to 83·3%, whilst specificity was around 76·7%. The error rates were around 98·9%. For lameness detection, the block sensitivity ranged from 73·8 to 87·8% while the obtained specificities were between 54·8 and 61·9%. The error rates varied from 87·8 to 89·2%. In conclusion, PCA seems to be not yet transferable into practical usage. Results could probably be improved if different traits and more informative sensor data are included in the analysis.

Developing and Evaluating Creativity Gamification Rehabilitation System: The Application of PCA-ANFIS Based Emotions Model

ERIC Educational Resources Information Center

Su, Chung-Ho; Cheng, Ching-Hsue

2016-01-01

This study aims to explore the factors in a patient's rehabilitation achievement after a total knee replacement (TKR) patient exercises, using a PCA-ANFIS emotion model-based game rehabilitation system, which combines virtual reality (VR) and motion capture technology. The researchers combine a principal component analysis (PCA) and an adaptive…

Osteopontin is a tumor autoantigen in prostate cancer patients

PubMed Central

TILLI, TATIANA M.; SILVA, ELOÍSIO A.; MATOS, LÍVIA C.; FAGET, DOUGLAS V.; DIAS, BIANCA F.P.; VASCONCELOS, JULIANA S.P.; YOKOSAKI, YASUYUKI; GIMBA, ETEL R.P.

2011-01-01

Anti-tumor antibodies act as biomarkers for the early diagnosis of prostate cancer (PCa). Osteopontin (OPN) is overexpressed in PCa cells and contributes to the progression of the disease. This study aimed to evaluate whether OPN evokes a humoral immune response in PCa patients and whether the reactivity levels of anti-OPN antibodies may be used to better differentiate PCa from benign and healthy donor plasma samples. Plasma samples from biopsy-proven PCa patients (29), benign prostate hyperplasia (BPH) (18) and control healthy donors (HD) (30) were tested by immunoblots using the recombinant human OPN. The frequency of anti-OPN antibodies was significantly higher in PCa (66%) plasma samples as compared to BPH (33%) and HD controls (10%). Anti-OPN antibodies were detected in a high proportion of plasma samples from patients with a Gleason score of less than 6 (57%), prostate-specific antigen levels lower than 10 ng/ml (67%) and pT2 organ-confined disease (70%), suggesting that anti-OPN antibodies may be used as an early serum marker for PCa. To the best of our knowledge, this is the first description of OPN as a tumor autoantigen and one of the most reactive individual autoantigens described thus far. These data support the inclusion of OPN in a multiplex of tumor antigens in order to perform antibody profiling in PCa as well as in other malignancies overexpressing OPN. PMID:22870138

A Biomimetic Sensor for the Classification of Honeys of Different Floral Origin and the Detection of Adulteration

PubMed Central

Zakaria, Ammar; Shakaff, Ali Yeon Md; Masnan, Maz Jamilah; Ahmad, Mohd Noor; Adom, Abdul Hamid; Jaafar, Mahmad Nor; Ghani, Supri A.; Abdullah, Abu Hassan; Aziz, Abdul Hallis Abdul; Kamarudin, Latifah Munirah; Subari, Norazian; Fikri, Nazifah Ahmad

2011-01-01

The major compounds in honey are carbohydrates such as monosaccharides and disaccharides. The same compounds are found in cane-sugar concentrates. Unfortunately when sugar concentrate is added to honey, laboratory assessments are found to be ineffective in detecting this adulteration. Unlike tracing heavy metals in honey, sugar adulterated honey is much trickier and harder to detect, and traditionally it has been very challenging to come up with a suitable method to prove the presence of adulterants in honey products. This paper proposes a combination of array sensing and multi-modality sensor fusion that can effectively discriminate the samples not only based on the compounds present in the sample but also mimic the way humans perceive flavours and aromas. Conversely, analytical instruments are based on chemical separations which may alter the properties of the volatiles or flavours of a particular honey. The present work is focused on classifying 18 samples of different honeys, sugar syrups and adulterated samples using data fusion of electronic nose (e-nose) and electronic tongue (e-tongue) measurements. Each group of samples was evaluated separately by the e-nose and e-tongue. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were able to separately discriminate monofloral honey from sugar syrup, and polyfloral honey from sugar and adulterated samples using the e-nose and e-tongue. The e-nose was observed to give better separation compared to e-tongue assessment, particularly when LDA was applied. However, when all samples were combined in one classification analysis, neither PCA nor LDA were able to discriminate between honeys of different floral origins, sugar syrup and adulterated samples. By applying a sensor fusion technique, the classification for the 18 different samples was improved. Significant improvement was observed using PCA, while LDA not only improved the discrimination but also gave better classification. An improvement in performance was also observed using a Probabilistic Neural Network classifier when the e-nose and e-tongue data were fused. PMID:22164046

A biomimetic sensor for the classification of honeys of different floral origin and the detection of adulteration.

PubMed

Zakaria, Ammar; Shakaff, Ali Yeon Md; Masnan, Maz Jamilah; Ahmad, Mohd Noor; Adom, Abdul Hamid; Jaafar, Mahmad Nor; Ghani, Supri A; Abdullah, Abu Hassan; Aziz, Abdul Hallis Abdul; Kamarudin, Latifah Munirah; Subari, Norazian; Fikri, Nazifah Ahmad

2011-01-01

The major compounds in honey are carbohydrates such as monosaccharides and disaccharides. The same compounds are found in cane-sugar concentrates. Unfortunately when sugar concentrate is added to honey, laboratory assessments are found to be ineffective in detecting this adulteration. Unlike tracing heavy metals in honey, sugar adulterated honey is much trickier and harder to detect, and traditionally it has been very challenging to come up with a suitable method to prove the presence of adulterants in honey products. This paper proposes a combination of array sensing and multi-modality sensor fusion that can effectively discriminate the samples not only based on the compounds present in the sample but also mimic the way humans perceive flavours and aromas. Conversely, analytical instruments are based on chemical separations which may alter the properties of the volatiles or flavours of a particular honey. The present work is focused on classifying 18 samples of different honeys, sugar syrups and adulterated samples using data fusion of electronic nose (e-nose) and electronic tongue (e-tongue) measurements. Each group of samples was evaluated separately by the e-nose and e-tongue. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were able to separately discriminate monofloral honey from sugar syrup, and polyfloral honey from sugar and adulterated samples using the e-nose and e-tongue. The e-nose was observed to give better separation compared to e-tongue assessment, particularly when LDA was applied. However, when all samples were combined in one classification analysis, neither PCA nor LDA were able to discriminate between honeys of different floral origins, sugar syrup and adulterated samples. By applying a sensor fusion technique, the classification for the 18 different samples was improved. Significant improvement was observed using PCA, while LDA not only improved the discrimination but also gave better classification. An improvement in performance was also observed using a Probabilistic Neural Network classifier when the e-nose and e-tongue data were fused.

Feasibility Study on the Use of On-line Multivariate Statistical Process Control for Safeguards Applications in Natural Uranium Conversion Plants

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

Ladd-Lively, Jennifer L

2014-01-01

The objective of this work was to determine the feasibility of using on-line multivariate statistical process control (MSPC) for safeguards applications in natural uranium conversion plants. Multivariate statistical process control is commonly used throughout industry for the detection of faults. For safeguards applications in uranium conversion plants, faults could include the diversion of intermediate products such as uranium dioxide, uranium tetrafluoride, and uranium hexafluoride. This study was limited to a 100 metric ton of uranium (MTU) per year natural uranium conversion plant (NUCP) using the wet solvent extraction method for the purification of uranium ore concentrate. A key component inmore » the multivariate statistical methodology is the Principal Component Analysis (PCA) approach for the analysis of data, development of the base case model, and evaluation of future operations. The PCA approach was implemented through the use of singular value decomposition of the data matrix where the data matrix represents normal operation of the plant. Component mole balances were used to model each of the process units in the NUCP. However, this approach could be applied to any data set. The monitoring framework developed in this research could be used to determine whether or not a diversion of material has occurred at an NUCP as part of an International Atomic Energy Agency (IAEA) safeguards system. This approach can be used to identify the key monitoring locations, as well as locations where monitoring is unimportant. Detection limits at the key monitoring locations can also be established using this technique. Several faulty scenarios were developed to test the monitoring framework after the base case or normal operating conditions of the PCA model were established. In all of the scenarios, the monitoring framework was able to detect the fault. Overall this study was successful at meeting the stated objective.« less

Selective Detection of Target Volatile Organic Compounds in Contaminated Humid Air Using a Sensor Array with Principal Component Analysis

PubMed Central

Itoh, Toshio; Akamatsu, Takafumi; Tsuruta, Akihiro; Shin, Woosuck

2017-01-01

We investigated selective detection of the target volatile organic compounds (VOCs) nonanal, n-decane, and acetoin for lung cancer-related VOCs, and acetone and methyl i-butyl ketone for diabetes-related VOCs, in humid air with simulated VOC contamination (total concentration: 300 μg/m3). We used six “grain boundary-response type” sensors, including four commercially available sensors (TGS 2600, 2610, 2610, and 2620) and two Pt, Pd, and Au-loaded SnO2 sensors (Pt, Pd, Au/SnO2), and two “bulk-response type” sensors, including Zr-doped CeO2 (CeZr10), i.e., eight sensors in total. We then analyzed their sensor signals using principal component analysis (PCA). Although the six “grain boundary-response type” sensors were found to be insufficient for selective detection of the target gases in humid air, the addition of two “bulk-response type” sensors improved the selectivity, even with simulated VOC contamination. To further improve the discrimination, we selected appropriate sensors from the eight sensors based on the PCA results. The selectivity to each target gas was maintained and was not affected by contamination. PMID:28753948

PCA3 Reference Set Application: T2-Erg-Martin Sanda-Emory (2014) — EDRN Public Portal

Cancer.gov

We hypothesize that combining T2:erg (T2:erg) fusion and PCA3 detection in urine collected after digital rectal exam can improve the specificity of identifying clinically significant prostate cancer presence over the standard PSA and DRE. To address this hypothesis we propose to validate the performance of the urinary T2:erg in a multiplex model predicting the diagnosis of clinically significant prostate cancer on subsequent prostate biopsy using post-DRE pre biopsy urine specimens from a cohort of 900 men on the EDRN’s PCA3 trial.

Molecular Imaging and Precision Medicine in Prostate Cancer.

PubMed

Ceci, Francesco; Fiorentino, Michelangelo; Castellucci, Paolo; Fanti, Stefano

2017-01-01

The aim of the present review is to discuss about the role of new probes for molecular imaging in the evaluation of prostate cancer (PCa). This review focuses particularly on the role of new promising radiotracers for the molecular imaging with PET/computed tomography in the detection of PCa recurrence. The role of these new imaging techniques to guide lesion-target therapies and the potential application of these molecular probes as theranostics agents is discussed. Finally, the molecular mechanisms underlying resistance to castration in PCa and the maintenance of active androgen receptor are discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

68Ga-PSMA PET/CT in patients with recurrent prostate cancer after radical treatment: prospective results in 314 patients.

PubMed

Caroli, Paola; Sandler, Israel; Matteucci, Federica; De Giorgi, Ugo; Uccelli, Licia; Celli, Monica; Foca, Flavia; Barone, Domenico; Romeo, Antonino; Sarnelli, Anna; Paganelli, Giovanni

2018-06-19

We studied the usefulness of 68 Ga-prostate-specific membrane antigen (PSMA) PET/CT for detecting relapse in a prospective series of patients with biochemical recurrence (BCR) of prostate cancer (PCa) after radical treatment. Patients with BCR of PCa after radical surgery and/or radiotherapy with or without androgen-deprivation therapy were included in the study. 68 Ga-PSMA PET/CT scans performed from the top of the head to the mid-thigh 60 min after intravenous injection of 150 ± 50 MBq of 68 Ga-PSMA were interpreted by two nuclear medicine physicians. The results were correlated with prostate-specific antigen (PSA) levels at the time of the scan (PSApet), PSA doubling time, Gleason score, tumour stage, postsurgery tumour residue, time from primary therapy to BCR, and patient age. When available, 68 Ga-PSMA PET/CT scans were compared with negative 18 F-choline PET/CT scans routinely performed up to 1 month previously. From November 2015 to October 2017, 314 PCa patients with BCR were evaluated. Their median age was 70 years (range 44-92 years) and their median PSApet was 0.83 ng/ml (range 0.003-80.0 ng/ml). 68 Ga-PSMA PET/CT was positive (one or more suspected PCa lesions detected) in 197 patients (62.7%). Lesions limited to the pelvis, i.e. the prostate/prostate bed and/or pelvic lymph nodes (LNs), were detected in 117 patients (59.4%). At least one distant lesion (LNs, bone, other organs, separately or combined with local lesions) was detected in 80 patients (40.6%). PSApet was higher in PET-positive than in PET-negative patients (P < 0.0001). Of 88 patients negative on choline PET/CT scans, 59 (67%) were positive on 68 Ga-PSMA PET/CT. We confirmed the value of 68 Ga-PSMA PET/CT in restaging PCa patients with BCR, highlighting its superior performance and safety compared with choline PET/CT. Higher PSApet was associated with a higher relapse detection rate.

Prostate cancer in senior adults: over- or undertreated?

PubMed

Berger, Ingrid; Böhmer, Franz; Ponholzer, Anton; Madersbacher, Stephan

2009-01-01

Despite the widespread use of prostate specific antigen for early prostate cancer (PCa) detection in younger men, PCa is still as disease of the elderly as 2/3 of incident cases are detected in men older than 65 years and 25% are older than 75 years at diagnosis. Opportunistic screening for PCa is not recommended for men with a life expectancy of less than 10 years. The therapeutic strategy for senior adults is driven by tumour stage/aggressiveness, co-morbidity and chronological age. Elderly patients with low/intermediate risk tumours - particularly those with a life expectancy of less than 10 years - are best managed by watchful waiting. Senior adults with intermediate/high risk tumours and a life expectancy of >10 years may benefit from curative local therapy such as radical prostatectomy or combined external beam irradiation/androgen ablation therapy. For elderly patients with metastatic disease, androgen deprivation remains the mainstay of therapy, intermittent androgen ablation is a promising approach.

Real-time monitoring of a coffee roasting process with near infrared spectroscopy using multivariate statistical analysis: A feasibility study.

PubMed

Catelani, Tiago A; Santos, João Rodrigo; Páscoa, Ricardo N M J; Pezza, Leonardo; Pezza, Helena R; Lopes, João A

2018-03-01

This work proposes the use of near infrared (NIR) spectroscopy in diffuse reflectance mode and multivariate statistical process control (MSPC) based on principal component analysis (PCA) for real-time monitoring of the coffee roasting process. The main objective was the development of a MSPC methodology able to early detect disturbances to the roasting process resourcing to real-time acquisition of NIR spectra. A total of fifteen roasting batches were defined according to an experimental design to develop the MSPC models. This methodology was tested on a set of five batches where disturbances of different nature were imposed to simulate real faulty situations. Some of these batches were used to optimize the model while the remaining was used to test the methodology. A modelling strategy based on a time sliding window provided the best results in terms of distinguishing batches with and without disturbances, resourcing to typical MSPC charts: Hotelling's T 2 and squared predicted error statistics. A PCA model encompassing a time window of four minutes with three principal components was able to efficiently detect all disturbances assayed. NIR spectroscopy combined with the MSPC approach proved to be an adequate auxiliary tool for coffee roasters to detect faults in a conventional roasting process in real-time. Copyright © 2017 Elsevier B.V. All rights reserved.

PSMA Ligands for Radionuclide Imaging and Therapy of Prostate Cancer: Clinical Status

PubMed Central

Lütje, Susanne; Heskamp, Sandra; Cornelissen, Alexander S.; Poeppel, Thorsten D.; van den Broek, Sebastiaan A. M. W.; Rosenbaum-Krumme, Sandra; Bockisch, Andreas; Gotthardt, Martin; Rijpkema, Mark; Boerman, Otto C.

2015-01-01

Prostate cancer (PCa) is the most common malignancy in men worldwide, leading to substantial morbidity and mortality. At present, imaging of PCa has become increasingly important for staging, restaging, and treatment selection. Until recently, choline-based positron emission tomography/computed tomography (PET/CT) represented the state-of-the-art radionuclide imaging technique for these purposes. However, its application is limited to patients with high PSA levels and Gleason scores. Prostate-specific membrane antigen (PSMA) is a promising new target for specific imaging of PCa, because it is upregulated in the majority of PCa. Moreover, PSMA can serve as a target for therapeutic applications. Currently, several small-molecule PSMA ligands with excellent in vivo tumor targeting characteristics are being investigated for their potential in theranostic applications in PCa. Here, a review of the recent developments in PSMA-based diagnostic imaging and therapy in patients with PCa with radiolabeled PSMA ligands is provided. PMID:26681984

Benchmarking of data fusion algorithms in support of earth observation based Antarctic wildlife monitoring

NASA Astrophysics Data System (ADS)

Witharana, Chandi; LaRue, Michelle A.; Lynch, Heather J.

2016-03-01

Remote sensing is a rapidly developing tool for mapping the abundance and distribution of Antarctic wildlife. While both panchromatic and multispectral imagery have been used in this context, image fusion techniques have received little attention. We tasked seven widely-used fusion algorithms: Ehlers fusion, hyperspherical color space fusion, high-pass fusion, principal component analysis (PCA) fusion, University of New Brunswick fusion, and wavelet-PCA fusion to resolution enhance a series of single-date QuickBird-2 and Worldview-2 image scenes comprising penguin guano, seals, and vegetation. Fused images were assessed for spectral and spatial fidelity using a variety of quantitative quality indicators and visual inspection methods. Our visual evaluation elected the high-pass fusion algorithm and the University of New Brunswick fusion algorithm as best for manual wildlife detection while the quantitative assessment suggested the Gram-Schmidt fusion algorithm and the University of New Brunswick fusion algorithm as best for automated classification. The hyperspherical color space fusion algorithm exhibited mediocre results in terms of spectral and spatial fidelities. The PCA fusion algorithm showed spatial superiority at the expense of spectral inconsistencies. The Ehlers fusion algorithm and the wavelet-PCA algorithm showed the weakest performances. As remote sensing becomes a more routine method of surveying Antarctic wildlife, these benchmarks will provide guidance for image fusion and pave the way for more standardized products for specific types of wildlife surveys.

A stable systemic risk ranking in China's banking sector: Based on principal component analysis

NASA Astrophysics Data System (ADS)

Fang, Libing; Xiao, Binqing; Yu, Honghai; You, Qixing

2018-02-01

In this paper, we compare five popular systemic risk rankings, and apply principal component analysis (PCA) model to provide a stable systemic risk ranking for the Chinese banking sector. Our empirical results indicate that five methods suggest vastly different systemic risk rankings for the same bank, while the combined systemic risk measure based on PCA provides a reliable ranking. Furthermore, according to factor loadings of the first component, PCA combined ranking is mainly based on fundamentals instead of market price data. We clearly find that price-based rankings are not as practical a method as fundamentals-based ones. This PCA combined ranking directly shows systemic risk contributions of each bank for banking supervision purpose and reminds banks to prevent and cope with the financial crisis in advance.

Binding Isotherms and Time Courses Readily from Magnetic Resonance.

PubMed

Xu, Jia; Van Doren, Steven R

2016-08-16

Evidence is presented that binding isotherms, simple or biphasic, can be extracted directly from noninterpreted, complex 2D NMR spectra using principal component analysis (PCA) to reveal the largest trend(s) across the series. This approach renders peak picking unnecessary for tracking population changes. In 1:1 binding, the first principal component captures the binding isotherm from NMR-detected titrations in fast, slow, and even intermediate and mixed exchange regimes, as illustrated for phospholigand associations with proteins. Although the sigmoidal shifts and line broadening of intermediate exchange distorts binding isotherms constructed conventionally, applying PCA directly to these spectra along with Pareto scaling overcomes the distortion. Applying PCA to time-domain NMR data also yields binding isotherms from titrations in fast or slow exchange. The algorithm readily extracts from magnetic resonance imaging movie time courses such as breathing and heart rate in chest imaging. Similarly, two-step binding processes detected by NMR are easily captured by principal components 1 and 2. PCA obviates the customary focus on specific peaks or regions of images. Applying it directly to a series of complex data will easily delineate binding isotherms, equilibrium shifts, and time courses of reactions or fluctuations.

Visible micro-Raman spectroscopy of single human mammary epithelial cells exposed to x-ray radiation.

PubMed

Delfino, Ines; Perna, Giuseppe; Lasalvia, Maria; Capozzi, Vito; Manti, Lorenzo; Camerlingo, Carlo; Lepore, Maria

2015-03-01

A micro-Raman spectroscopy investigation has been performed in vitro on single human mammary epithelial cells after irradiation by graded x-ray doses. The analysis by principal component analysis (PCA) and interval-PCA (i-PCA) methods has allowed us to point out the small differences in the Raman spectra induced by irradiation. This experimental approach has enabled us to delineate radiation-induced changes in protein, nucleic acid, lipid, and carbohydrate content. In particular, the dose dependence of PCA and i-PCA components has been analyzed. Our results have confirmed that micro-Raman spectroscopy coupled to properly chosen data analysis methods is a very sensitive technique to detect early molecular changes at the single-cell level following exposure to ionizing radiation. This would help in developing innovative approaches to monitor radiation cancer radiotherapy outcome so as to reduce the overall radiation dose and minimize damage to the surrounding healthy cells, both aspects being of great importance in the field of radiation therapy.

A new statistic for identifying batch effects in high-throughput genomic data that uses guided principal component analysis.

PubMed

Reese, Sarah E; Archer, Kellie J; Therneau, Terry M; Atkinson, Elizabeth J; Vachon, Celine M; de Andrade, Mariza; Kocher, Jean-Pierre A; Eckel-Passow, Jeanette E

2013-11-15

Batch effects are due to probe-specific systematic variation between groups of samples (batches) resulting from experimental features that are not of biological interest. Principal component analysis (PCA) is commonly used as a visual tool to determine whether batch effects exist after applying a global normalization method. However, PCA yields linear combinations of the variables that contribute maximum variance and thus will not necessarily detect batch effects if they are not the largest source of variability in the data. We present an extension of PCA to quantify the existence of batch effects, called guided PCA (gPCA). We describe a test statistic that uses gPCA to test whether a batch effect exists. We apply our proposed test statistic derived using gPCA to simulated data and to two copy number variation case studies: the first study consisted of 614 samples from a breast cancer family study using Illumina Human 660 bead-chip arrays, whereas the second case study consisted of 703 samples from a family blood pressure study that used Affymetrix SNP Array 6.0. We demonstrate that our statistic has good statistical properties and is able to identify significant batch effects in two copy number variation case studies. We developed a new statistic that uses gPCA to identify whether batch effects exist in high-throughput genomic data. Although our examples pertain to copy number data, gPCA is general and can be used on other data types as well. The gPCA R package (Available via CRAN) provides functionality and data to perform the methods in this article. reesese@vcu.edu

Strain Transient Detection Techniques: A Comparison of Source Parameter Inversions of Signals Isolated through Principal Component Analysis (PCA), Non-Linear PCA, and Rotated PCA

NASA Astrophysics Data System (ADS)

Lipovsky, B.; Funning, G. J.

2009-12-01

We compare several techniques for the analysis of geodetic time series with the ultimate aim to characterize the physical processes which are represented therein. We compare three methods for the analysis of these data: Principal Component Analysis (PCA), Non-Linear PCA (NLPCA), and Rotated PCA (RPCA). We evaluate each method by its ability to isolate signals which may be any combination of low amplitude (near noise level), temporally transient, unaccompanied by seismic emissions, and small scale with respect to the spatial domain. PCA is a powerful tool for extracting structure from large datasets which is traditionally realized through either the solution of an eigenvalue problem or through iterative methods. PCA is an transformation of the coordinate system of our data such that the new "principal" data axes retain maximal variance and minimal reconstruction error (Pearson, 1901; Hotelling, 1933). RPCA is achieved by an orthogonal transformation of the principal axes determined in PCA. In the analysis of meteorological data sets, RPCA has been seen to overcome domain shape dependencies, correct for sampling errors, and to determine principal axes which more closely represent physical processes (e.g., Richman, 1986). NLPCA generalizes PCA such that principal axes are replaced by principal curves (e.g., Hsieh 2004). We achieve NLPCA through an auto-associative feed-forward neural network (Scholz, 2005). We show the geophysical relevance of these techniques by application of each to a synthetic data set. Results are compared by inverting principal axes to determine deformation source parameters. Temporal variability in source parameters, estimated by each method, are also compared.

Rapid and quantitative detection of the microbial spoilage in chicken meat by diffuse reflectance spectroscopy (600-1100 nm).

PubMed

Lin, M; Al-Holy, M; Mousavi-Hesary, M; Al-Qadiri, H; Cavinato, A G; Rasco, B A

2004-01-01

To evaluate the feasibility of visible and short-wavelength near-infrared (SW-NIR) diffuse reflectance spectroscopy (600-1100 nm) to quantify the microbial loads in chicken meat and to develop a rapid methodology for monitoring the onset of spoilage. Twenty-four prepackaged fresh chicken breast muscle samples were prepared and stored at 21 degrees C for 24 h. Visible and SW-NIR was used to detect and quantify the microbial loads in chicken breast muscle at time intervals of 0, 2, 4, 6, 8, 10, 12 and 24 h. Spectra were collected in the diffuse reflectance mode (600-1100 nm). Total aerobic plate count (APC) of each sample was determined by the spread plate method at 32 degrees C for 48 h. Principal component analysis (PCA) and partial least squares (PLS) based prediction models were developed. PCA analysis showed clear segregation of samples held 8 h or longer compared with 0-h control. An optimum PLS model required eight latent variables for chicken muscle (R = 0.91, SEP = 0.48 log CFU g(-1)). Visible and SW-NIR combined with PCA is capable of perceiving the change of the microbial loads in chicken muscle once the APC increases slightly above 1 log cycle. Accurate quantification of the bacterial loads in chicken muscle can be calculated from the PLS-based prediction method. Visible and SW-NIR spectroscopy is a technique with a considerable potential for monitoring food safety and food spoilage. Visible and SW-NIR can acquire a metabolic snapshot and quantify the microbial loads of food samples rapidly, accurately, and noninvasively. This method would allow for more expeditious applications of quality control in food industries.

A PCA-based hyperspectral approach to detect infections by mycophilic fungi on dried porcini mushrooms (boletus edulis and allied species).

PubMed

Bagnasco, Lucia; Zotti, Mirca; Sitta, Nicola; Oliveri, Paolo

2015-11-01

Mycophilic fungi of anamorphic genus Sepedonium (telomorphs in Hypomyces, Hypocreales, Ascomycota) infect and parasitize sporomata of boletes. The obligated hosts such as Boletus edulis and allied species (known as "porcini mushrooms") are among the most valued and prized edible wild mushrooms in the world. Sepedonium infections have a great morphological variability: at the initial state, contaminated mushrooms present a white coating covering tubes and pores; at the final state, Sepedonium forms a deep and thick hyphal layer that eventually leads to the total necrosis of the host. Up to date, Sepedonium infections in porcini mushrooms have been evaluated only through macroscopic and microscopic visual analysis. In this study, in order to implement the infection evaluation as a routine methodology for industrial purposes, the potential application of Hyperspectral Imaging (HSI) and Principal Component Analysis (PCA) for detection of Sepedonium presence on sliced and dried B. edulis and allied species was investigated. Hyperspectral images were obtained using a pushbroom line-scanning HSI instrument, operating in the wavelength range between 400 and 1000 nm with 5 nm resolution. PCA was applied on normal and contaminated samples. To reduce the spectral variability caused by factors unrelated to Sepedonium infection, such as scattering effects and differences in sample height, different spectral pre-treatments were applied. A supervised rule was then developed to assign spectra recorded on new test samples to each of the two classes, based on the PC scores. This allowed to visualize directly - within false-color images of test samples - which points of the samples were contaminated. The results achieved may lead to the development of a non-destructive monitoring system for a rapid on-line screening of contaminated mushrooms. Copyright © 2015 Elsevier B.V. All rights reserved.

Investigation of inversion polymorphisms in the human genome using principal components analysis.

PubMed

Ma, Jianzhong; Amos, Christopher I

2012-01-01

Despite the significant advances made over the last few years in mapping inversions with the advent of paired-end sequencing approaches, our understanding of the prevalence and spectrum of inversions in the human genome has lagged behind other types of structural variants, mainly due to the lack of a cost-efficient method applicable to large-scale samples. We propose a novel method based on principal components analysis (PCA) to characterize inversion polymorphisms using high-density SNP genotype data. Our method applies to non-recurrent inversions for which recombination between the inverted and non-inverted segments in inversion heterozygotes is suppressed due to the loss of unbalanced gametes. Inside such an inversion region, an effect similar to population substructure is thus created: two distinct "populations" of inversion homozygotes of different orientations and their 1:1 admixture, namely the inversion heterozygotes. This kind of substructure can be readily detected by performing PCA locally in the inversion regions. Using simulations, we demonstrated that the proposed method can be used to detect and genotype inversion polymorphisms using unphased genotype data. We applied our method to the phase III HapMap data and inferred the inversion genotypes of known inversion polymorphisms at 8p23.1 and 17q21.31. These inversion genotypes were validated by comparing with literature results and by checking Mendelian consistency using the family data whenever available. Based on the PCA-approach, we also performed a preliminary genome-wide scan for inversions using the HapMap data, which resulted in 2040 candidate inversions, 169 of which overlapped with previously reported inversions. Our method can be readily applied to the abundant SNP data, and is expected to play an important role in developing human genome maps of inversions and exploring associations between inversions and susceptibility of diseases.

Stacking and determination of phenazine-1-carboxylic acid with low pKa in soil via moving reaction boundary formed by alkaline and double acidic buffers in capillary electrophoresis.

PubMed

Sun, Chong; Yang, Xiao-Di; Fan, Liu-Yin; Zhang, Wei; Xu, Yu-Quan; Cao, Cheng-Xi

2011-04-01

As shown herein, a normal moving reaction boundary (MRB) formed by an alkaline buffer and a single acidic buffer had poor stacking to the new important plant growth promoter of phenazine-1-carboxylic acid (PCA) in soil due to the leak induced by its low pK(a). To stack the PCA with low pK(a) efficiently, a novel stacking system of MRB was developed, which was formed by an alkaline buffer and double acidic buffers (viz., acidic sample and blank buffers). With the novel system, the PCA leaking into the blank buffer from the sample buffer could be well stacked by the prolonged MRB formed between the alkaline buffer and blank buffer. The relevant mechanism of stacking was discussed briefly. The stacking system, coupled with sample pretreatment, could achieve a 214-fold increase of PCA sensitivity under the optimal conditions (15 mM (pH 11.5) Gly-NaOH as the alkaline buffer, 15 mM (pH 3.0) Gly-HCl-acetonitrile (20%, v/v) as the acidic sample buffer, 15 mM (pH 3.0) Gly-HCl as the blank buffer, 3 min 13 mbar injection of double acidic buffers, benzoic acid as the internal standard, 75 μm i.d. × 53 cm (44 cm effective length) capillary, 25 kV and 248 nm). The limit of detection of PCA in soil was decreased to 17 ng/g, the intra-day and inter-day precision values (expressed as relative standard deviations) were 3.17-4.24% and 4.17-4.87%, respectively, and the recoveries of PCA at three concentration levels changed from 52.20% to 102.61%. The developed method could be used for the detection of PCA in soil at trace level.

Computer aided detection in prostate cancer diagnostics: A promising alternative to biopsy? A retrospective study from 104 lesions with histological ground truth.

PubMed

Thon, Anika; Teichgräber, Ulf; Tennstedt-Schenk, Cornelia; Hadjidemetriou, Stathis; Winzler, Sven; Malich, Ansgar; Papageorgiou, Ismini

2017-01-01

Prostate cancer (PCa) diagnosis by means of multiparametric magnetic resonance imaging (mpMRI) is a current challenge for the development of computer-aided detection (CAD) tools. An innovative CAD-software (Watson Elementary™) was proposed to achieve high sensitivity and specificity, as well as to allege a correlate to Gleason grade. To assess the performance of Watson Elementary™ in automated PCa diagnosis in our hospital´s database of MRI-guided prostate biopsies. The evaluation was retrospective for 104 lesions (47 PCa, 57 benign) from 79, 64.61±6.64 year old patients using 3T T2-weighted imaging, Apparent Diffusion Coefficient (ADC) maps and dynamic contrast enhancement series. Watson Elementary™ utilizes signal intensity, diffusion properties and kinetic profile to compute a proportional Gleason grade predictor, termed Malignancy Attention Index (MAI). The analysis focused on (i) the CAD sensitivity and specificity to classify suspect lesions and (ii) the MAI correlation with the histopathological ground truth. The software revealed a sensitivity of 46.80% for PCa classification. The specificity for PCa was found to be 75.43% with a positive predictive value of 61.11%, a negative predictive value of 63.23% and a false discovery rate of 38.89%. CAD classified PCa and benign lesions with equal probability (P 0.06, χ2 test). Accordingly, receiver operating characteristic analysis suggests a poor predictive value for MAI with an area under curve of 0.65 (P 0.02), which is not superior to the performance of board certified observers. Moreover, MAI revealed no significant correlation with Gleason grade (P 0.60, Pearson´s correlation). The tested CAD software for mpMRI analysis was a weak PCa biomarker in this dataset. Targeted prostate biopsy and histology remains the gold standard for prostate cancer diagnosis.

Computer aided detection in prostate cancer diagnostics: A promising alternative to biopsy? A retrospective study from 104 lesions with histological ground truth

PubMed Central

Thon, Anika; Teichgräber, Ulf; Tennstedt-Schenk, Cornelia; Hadjidemetriou, Stathis; Winzler, Sven; Malich, Ansgar

2017-01-01

Background Prostate cancer (PCa) diagnosis by means of multiparametric magnetic resonance imaging (mpMRI) is a current challenge for the development of computer-aided detection (CAD) tools. An innovative CAD-software (Watson Elementary™) was proposed to achieve high sensitivity and specificity, as well as to allege a correlate to Gleason grade. Aim/Objective To assess the performance of Watson Elementary™ in automated PCa diagnosis in our hospital´s database of MRI-guided prostate biopsies. Methods The evaluation was retrospective for 104 lesions (47 PCa, 57 benign) from 79, 64.61±6.64 year old patients using 3T T2-weighted imaging, Apparent Diffusion Coefficient (ADC) maps and dynamic contrast enhancement series. Watson Elementary™ utilizes signal intensity, diffusion properties and kinetic profile to compute a proportional Gleason grade predictor, termed Malignancy Attention Index (MAI). The analysis focused on (i) the CAD sensitivity and specificity to classify suspect lesions and (ii) the MAI correlation with the histopathological ground truth. Results The software revealed a sensitivity of 46.80% for PCa classification. The specificity for PCa was found to be 75.43% with a positive predictive value of 61.11%, a negative predictive value of 63.23% and a false discovery rate of 38.89%. CAD classified PCa and benign lesions with equal probability (P 0.06, χ2 test). Accordingly, receiver operating characteristic analysis suggests a poor predictive value for MAI with an area under curve of 0.65 (P 0.02), which is not superior to the performance of board certified observers. Moreover, MAI revealed no significant correlation with Gleason grade (P 0.60, Pearson´s correlation). Conclusion The tested CAD software for mpMRI analysis was a weak PCa biomarker in this dataset. Targeted prostate biopsy and histology remains the gold standard for prostate cancer diagnosis. PMID:29023572

Decision tree and PCA-based fault diagnosis of rotating machinery

NASA Astrophysics Data System (ADS)

Sun, Weixiang; Chen, Jin; Li, Jiaqing

2007-04-01

After analysing the flaws of conventional fault diagnosis methods, data mining technology is introduced to fault diagnosis field, and a new method based on C4.5 decision tree and principal component analysis (PCA) is proposed. In this method, PCA is used to reduce features after data collection, preprocessing and feature extraction. Then, C4.5 is trained by using the samples to generate a decision tree model with diagnosis knowledge. At last the tree model is used to make diagnosis analysis. To validate the method proposed, six kinds of running states (normal or without any defect, unbalance, rotor radial rub, oil whirl, shaft crack and a simultaneous state of unbalance and radial rub), are simulated on Bently Rotor Kit RK4 to test C4.5 and PCA-based method and back-propagation neural network (BPNN). The result shows that C4.5 and PCA-based diagnosis method has higher accuracy and needs less training time than BPNN.

Radical Prostatectomy Findings in White Hispanic/Latino Men With NCCN Very Low-risk Prostate Cancer Detected by Template Biopsy.

PubMed

Kryvenko, Oleksandr N; Lyapichev, Kirill; Chinea, Felix M; Prakash, Nachiketh Soodana; Pollack, Alan; Gonzalgo, Mark L; Punnen, Sanoj; Jorda, Merce

2016-08-01

Radical prostatectomy (RP) outcomes have been studied in White and Black non-Hispanic men qualifying for Epstein active surveillance criteria (EASC). Herein, we first analyzed such outcomes in White Hispanic men. We studied 70 men with nonpalpable Gleason score 3+3=6 (Grade Group [GG] 1) prostate cancer (PCa) with ≤2 positive cores on biopsy who underwent RP. In 18 men, prostate-specific antigen (PSA) density (PSAD) was >0.15 ng/mL/g. Three of these had insignificant and 15 had significant PCa. The remaining 52 men qualified for EASC. One patient had no PCa identified at RP. Nineteen (37%) had significant PCa defined by volume (n=7), grade (n=7), and volume and grade (n=5). Nine cases were 3+4=7 (GG 2) (5/9 [56%] with pattern 4 <5%), 2 were 3+5=8 (GG 4), and 1 was 4+5=9 (GG 5). Patients with significant PCa more commonly had anterior dominant disease (11/19, 58%) versus patients with insignificant cancer (7/33, 21%) (P=0.01). In 12 cases with higher grade at RP, the dominant tumor nodule was anterior in 6 (50%) and posterior in 6 (median volumes: 1.1 vs. 0.17 cm, respectively; P=0.01). PSA correlated poorly with tumor volume (r=0.28, P=0.049). Gland weight significantly correlated with PSA (r=0.54, P<0.001). While PSAD and PSA mass density correlated with tumor volume, only PSA mass density distinguished cases with significant disease (median, 0.008 vs. 0.012 μg/g; P=0.03). In summary, a PSAD threshold of 0.15 works well in predicting significant tumor volume in Hispanic men. EASC appear to perform better in White Hispanic men than previously reported outcomes for Black non-Hispanic and worse than in White non-Hispanic men. Significant disease is often Gleason score 3+3=6 (GG 1) PCa >0.5 cm. Significant PCa is either a larger-volume anterior disease that may be detected by multiparametric magnetic resonance imaging-targeted biopsy or anterior sampling of the prostate or higher-grade smaller-volume posterior disease that in most cases should not pose immediate harm and may be detected by repeat template biopsies.

Improved method for fluorescence cytometric immunohematology testing.

PubMed

Roback, John D; Barclay, Sheilagh; Hillyer, Christopher D

2004-02-01

A method for accurate immunohematology testing by fluorescence cytometry (FC) was previously described. Nevertheless, the use of vacuum filtration to wash RBCs and a standard-flow cytometer for data acquisition hindered efforts to incorporate this method into an automated platform. A modified procedure was developed that used low-speed centrifugation of 96-well filter plates for RBC staining. Small-footprint benchtop capillary cytometers (PCA and PCA-96, Guava Technologies, Inc.) were used for data acquisition. Authentic clinical samples from hospitalized patients were tested for ABO group and the presence of D antigen (n = 749) as well as for the presence of RBC alloantibodies (n = 428). Challenging samples with mixed-field reactions and weak antibodies were included. Results were compared to those obtained by column agglutination technology (CAT), and discrepancies were resolved by standard tube methods. Detailed investigations of FC sensitivity and reproducibility were also performed. The modified FC method with the PCA determined the correct ABO group and D type for 98.7 percent of 520 samples, compared to 98.8 percent for CAT (p > 0.05). No-type-determined (NTD) rates were 1.2 percent for both methods. In testing for unexpected alloantibodies, FC determined the correct result for 98.6 percent of 215 samples, compared to 96.3 percent for CAT (p > 0.05). When samples were automatically acquired in the 96-well plate format with the PCA-96, 98.7 percent of 229 samples had correct ABO group and D type determined by FC, compared to 97.4 percent for CAT (p > 0.05). NTD rates were 0.9 and 2.6 percent, respectively. Antibody screens were accurate for 99.1 percent of 213 samples with the PCA-96, compared to 99.5 percent for CAT (p > 0.05). Further investigations demonstrated that FC with the PCA-96 was better than CAT at detecting weak anti-A (p < 0.0001) and alloantibodies. An improved method for FC immunohematology testing has been described. This assay was comparable in accuracy to standard CAT techniques, but had better sensitivity for detecting weak antibodies and was superior in detecting mixed-field reactions (p < 0.005). The FC method demonstrated excellent reproducibility. The compatibility of this assay with the PCA-96 capillary cytometer with plate-handling capabilities should simplify development of a completely automated platform.

Qualitative analysis of precipitate formation on the surface and in the tubules of dentin irrigated with sodium hypochlorite and a final rinse of chlorhexidine or QMiX.

PubMed

Kolosowski, Kamil P; Sodhi, Rana N S; Kishen, Anil; Basrani, Bettina R

2014-12-01

Interaction of sodium hypochlorite (NaOCl) mixed with chlorhexidine (CHX) produces a brown precipitate containing para-chloroaniline (PCA). When QMiX is mixed with NaOCl, no precipitate forms, but color change occurs. The aim of this study was to qualitatively assess the formation of precipitate and PCA on the surface and in the tubules of dentin irrigated with NaOCl, followed either by EDTA, NaOCl, and CHX or by saline and QMiX by using time-of-flight secondary ion mass spectrometry (TOF-SIMS). Dentin blocks were obtained from human maxillary molars, embedded in resin, and cross-sectioned to expose dentin. Specimens in group 1 were immersed in 2.5% NaOCl, followed by 17% EDTA, 2.5% NaOCl, and 2% CHX. Specimens in group 2 were immersed in 2.5% NaOCl, followed by saline and QMiX. The dentin surfaces were subjected to TOF-SIMS spectra analysis. Longitudinal sections of dentin blocks were then exposed and subjected to TOF-SIMS analysis. All samples and analysis were performed in triplicate for confirmation. TOF-SIMS analysis of group 1 revealed an irregular precipitate, containing PCA and CHX breakdown products, on the dentin surfaces, occluding and extending into the tubules. In TOF-SIMS analysis of group 2, no precipitates, including PCA, were detected on the dentin surface or in the tubules. Within the limitations of this study, precipitate containing PCA was formed in the tubules of dentin irrigated with NaOCl followed by CHX. No precipitates or PCA were detected in the tubules of dentin irrigated with NaOCl followed by saline and QMiX. Copyright © 2014 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

A case-control study of lower urinary-tract infections, associated antibiotics and the risk of developing prostate cancer using PCBaSe 3.0

PubMed Central

Garmo, Hans; Beckmann, Kerri; Stattin, Pär; Adolfsson, Jan; Van Hemelrijck, Mieke

2018-01-01

Objectives To investigate the association between lower urinary-tract infections, their associated antibiotics and the subsequent risk of developing PCa. Subjects/Patients (or materials) and methods Using data from the Swedish PCBaSe 3.0, we performed a matched case-control study (8762 cases and 43806 controls). Conditional logistic regression analysis was used to assess the association between lower urinary-tract infections, related antibiotics and PCa, whilst adjusting for civil status, education, Charlson Comorbidity Index and time between lower urinary-tract infection and PCa diagnosis. Results It was found that lower urinary-tract infections did not affect PCa risk, however, having a lower urinary-tract infection or a first antibiotic prescription 6–12 months before PCa were both associated with an increased risk of PCa (OR: 1.50, 95% CI: 1.23–1.82 and 1.96, 1.71–2.25, respectively), as compared to men without lower urinary-tract infections. Compared to men with no prescriptions for antibiotics, men who were prescribed ≥10 antibiotics, were 15% less likely to develop PCa (OR: 0.85, 95% CI: 0.78–0.91). Conclusion PCa was not found to be associated with diagnosis of a urinary-tract infection or frequency, but was positively associated with short time since diagnoses of lower urinary-tract infection or receiving prescriptions for antibiotics. These observations can likely be explained by detection bias, which highlights the importance of data on the diagnostic work-up when studying potential risk factors for PCa. PMID:29649268

Incidental prostate cancer in patients with muscle-invasive bladder cancer who underwent radical cystoprostatectomy.

PubMed

Tanaka, Toshikazu; Koie, Takuya; Ohyama, Chikara; Hashimoto, Yasuhiro; Imai, Atsushi; Tobisawa, Yuki; Hatakeyama, Shingo; Yamamoto, Hayato; Yoneyama, Tohru; Horiguchi, Hirotaka; Kodama, Hirotake; Yoneyama, Takahiro

2017-11-01

The aim of this study was to analyze the features of incidentally detected prostate cancer (PCa) in radical cystoprostatectomy (RCP) specimens to determine their pathological characteristics and clinical significance. In this retrospective study, we reviewed the clinical and pathological records of 431 consecutive patients with muscle-invasive bladder cancer who underwent RCP at Hirosaki University. Of these, we focused on 237 male patients with prostate-specific antigen (PSA) measurements and digital rectal examinations (DRE) that were recorded prior to the RCP. Significant PCa was defined as a tumor with a Gleason 4 or 5 pattern, pathological T3 or higher stage, lymph node involvement or three or more multifocal lesions within the prostate specimen. We compared clinically significant and insignificant PCa. In this study, a total of 43 patients (18.1%) were diagnosed with incidental PCa via RCP specimens. Age, preoperative PSA levels and pathological T stage in patients with clinically significant PCa were considerably higher than in those with insignificant cancer. Apical involvement was found in 16 patients, including 11 of those with clinically significant PCa. By the end of the follow-up period, none of the enrolled patients had a biochemical recurrence after surgery or died from PCa. According to our findings, preoperative risk factors were not reliable enough to accurately predict clinically significant PCa. Although there was no biochemical relapse or clinical recurrence of PCa in this study, the potential oncologic risk of prostate-sparing RCP must be considered. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Two-dimensional statistical linear discriminant analysis for real-time robust vehicle-type recognition

NASA Astrophysics Data System (ADS)

Zafar, I.; Edirisinghe, E. A.; Acar, S.; Bez, H. E.

2007-02-01

Automatic vehicle Make and Model Recognition (MMR) systems provide useful performance enhancements to vehicle recognitions systems that are solely based on Automatic License Plate Recognition (ALPR) systems. Several car MMR systems have been proposed in literature. However these approaches are based on feature detection algorithms that can perform sub-optimally under adverse lighting and/or occlusion conditions. In this paper we propose a real time, appearance based, car MMR approach using Two Dimensional Linear Discriminant Analysis that is capable of addressing this limitation. We provide experimental results to analyse the proposed algorithm's robustness under varying illumination and occlusions conditions. We have shown that the best performance with the proposed 2D-LDA based car MMR approach is obtained when the eigenvectors of lower significance are ignored. For the given database of 200 car images of 25 different make-model classifications, a best accuracy of 91% was obtained with the 2D-LDA approach. We use a direct Principle Component Analysis (PCA) based approach as a benchmark to compare and contrast the performance of the proposed 2D-LDA approach to car MMR. We conclude that in general the 2D-LDA based algorithm supersedes the performance of the PCA based approach.

Toward a strategy of patient-centered access to primary care.

PubMed

Berry, Leonard L; Beckham, Dan; Dettman, Amy; Mead, Robert

2014-10-01

Patient-centered access (PCA) to primary care services is rapidly becoming an imperative for efficiently delivering high-quality health care to patients. To enhance their PCA-related efforts, some medical practices and health systems have begun to use various tactics, including team-based care, satellite clinics, same-day and group appointments, greater use of physician assistants and nurse practitioners, and remote access to health services. However, few organizations are addressing the PCA imperative comprehensively by integrating these various tactics to develop an overall PCA management strategy. Successful integration means taking into account the changing competitive and reimbursement landscape in primary care, conducting an evidence-based assessment of the barriers and benefits of PCA implementation, and attending to the particular needs of the institution engaged in this important effort. This article provides a blueprint for creating a multifaceted but coordinated PCA strategy-one aimed squarely at making patient access a centerpiece of how health care is delivered. The case of a Wisconsin-based health system is used as an illustrative example of how other institutions might begin to conceive their fledgling PCA strategies without proposing it as a one-size-fits-all model. Copyright © 2014 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.

Detection of prostate cancer with multiparametric MRI (mpMRI): effect of dedicated reader education on accuracy and confidence of index and anterior cancer diagnosis

PubMed Central

Garcia-Reyes, Kirema; Passoni, Niccolò M.; Palmeri, Mark L.; Kauffman, Christopher R.; Choudhury, Kingshuk Roy; Polascik, Thomas J.; Gupta, Rajan T.

2015-01-01

Purpose To evaluate the impact of dedicated reader education on accuracy/confidence of peripheral zone index cancer and anterior prostate cancer (PCa) diagnosis with mpMRI; secondary aim was to assess the ability of readers to differentiate low-grade cancer (Gleason 6 or below) from high-grade cancer (Gleason 7+). Materials and methods Five blinded radiology fellows evaluated 31 total prostate mpMRIs in this IRB-approved, HIPAA-compliant, retrospective study for index lesion detection, confidence in lesion diagnosis (1–5 scale), and Gleason grade (Gleason 6 or lower vs. Gleason 7+). Following a dedicated education program, readers reinterpreted cases after a memory extinction period, blinded to initial reads. Reference standard was established combining whole mount histopathology with mpMRI findings by a board-certified radiologist with 5 years of prostate mpMRI experience. Results Index cancer detection: pre-education accuracy 74.2%; post-education accuracy 87.7% (p = 0.003). Confidence in index lesion diagnosis: pre-education 4.22 ± 1.04; post-education 3.75 ± 1.41 (p = 0.0004). Anterior PCa detection: pre-education accuracy 54.3%; post-education accuracy 94.3% (p = 0.001). Confidence in anterior PCa diagnosis: pre-education 3.22 ± 1.54; post-education 4.29 ± 0.83 (p = 0.0003). Gleason score accuracy: pre-education 54.8%; post-education 73.5% (p = 0.0005). Conclusions A dedicated reader education program on PCa detection with mpMRI was associated with a statistically significant increase in diagnostic accuracy of index cancer and anterior cancer detection as well as Gleason grade identification as compared to pre-education values. This was also associated with a significant increase in reader diagnostic confidence. This suggests that substantial interobserver variability in mpMRI interpretation can potentially be reduced with a focus on education and that this can occur over a fellowship training year. PMID:25034558

Age-dependent modulation of serum IgE and mast cell sensitization by Nippostrongylus brasiliensis infestation in rats.

PubMed

Turner, K J; Fisher, E H; Mayrhofer, G

1981-08-01

The capacity of N. brasiliensis (Nb) infestation to modify synthesis of ovalbumin (OV) specific IgE antibody was monitored in weanling, juvenile and adult female WAG rats by both passive cutaneous anaphylaxis (PCA) activity and by a rat radio-allergosorbent test (RAST). Infestation with Nb larvae 10 days after immunization with OV produced marginal potentiation of anti-OV Ig antibody production by both RAST and PCA in weanlings, marginal suppression by both parameters in juveniles and was without effect in adults. However, immunization with OV after infestation with Nb partially suppressed anti-OV IgE antibody production in weanlings (RAST) and totally abolished the PCA activity. Although this regime did not impair anti-OV IgE antibody synthesis (RAST) in juveniles, the sera were PCA-negative. In contrast, normal responses were found in adult rats. Negative PCA titres in sera containing high levels of specific antibody occurred when serum total IgE levels were elevated, and are explained on the basis of competition for binding sites on mast cells. The ratio of OV-specific IgE to 'total' IgE is a critical factor in detecting PCA activity.

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

Bednarz, Natalia; Eltze, Elke; Semjonow, Axel

A recent study concluded that serum prostate specific antigen (PSA)-based screening is beneficial for reducing the lethality of PCa, but was also associated with a high risk of 'overdiagnosis'. Nevertheless, also PCa patients who suffered from organ confined tumors and had negative bone scans succumb to distant metastases after complete tumor resection. It is reasonable to assume that those tumors spread to other organs long before the overt manifestation of metastases. Our current results confirm that prostate tumors are highly heterogeneous. Even a small subpopulation of cells bearing BRCA1 losses can initiate PCa cell regional and distant dissemination indicating thosemore » patients which might be at high risk of metastasis. A preliminary study performed on a small cohort of multifocal prostate cancer (PCa) detected BRCA1 allelic imbalances (AI) among circulating tumor cells (CTCs). The present analysis was aimed to elucidate the biological and clinical role of BRCA1 losses on metastatic spread and tumor progression in prostate cancer patients. Experimental Design: To map molecular progression in PCa outgrowth we used FISH analysis of tissue microarrays (TMA), lymph node sections and CTC from peripheral blood. We found that 14% of 133 tested patients carried monoallelic BRCA1 loss in at least one tumor focus. Extended molecular analysis of chr17q revealed that this aberration was often a part of larger cytogenetic rearrangement involving chr17q21 accompanied by AI of the tumor suppressor gene PTEN and lack of the BRCA1 promoter methylation. The BRCA1 losses correlated with advanced T stage (p < 0.05), invasion to pelvic lymph nodes (LN, p < 0.05) as well as BR (p < 0.01). Their prevalence was twice as high within 62 LN metastases (LNMs) as in primary tumors (27%, p < 0.01). The analysis of 11 matched primary PCa-LNM pairs confirmed the suspected transmission of genetic abnormalities between those two sites. In 4 of 7 patients with metastatic disease, BRCA1 losses appeared in a minute fraction of cytokeratin- and vimentin-positive CTCs. Small subpopulations of PCa cells bearing BRCA1 losses might be one confounding factor initiating tumor dissemination and might provide an early indicator of shortened disease-free survival.« less

Development and external multicenter validation of Chinese Prostate Cancer Consortium prostate cancer risk calculator for initial prostate biopsy.

PubMed

Chen, Rui; Xie, Liping; Xue, Wei; Ye, Zhangqun; Ma, Lulin; Gao, Xu; Ren, Shancheng; Wang, Fubo; Zhao, Lin; Xu, Chuanliang; Sun, Yinghao

2016-09-01

Substantial differences exist in the relationship of prostate cancer (PCa) detection rate and prostate-specific antigen (PSA) level between Western and Asian populations. Classic Western risk calculators, European Randomized Study for Screening of Prostate Cancer Risk Calculator, and Prostate Cancer Prevention Trial Risk Calculator, were shown to be not applicable in Asian populations. We aimed to develop and validate a risk calculator for predicting the probability of PCa and high-grade PCa (defined as Gleason Score sum 7 or higher) at initial prostate biopsy in Chinese men. Urology outpatients who underwent initial prostate biopsy according to the inclusion criteria were included. The multivariate logistic regression-based Chinese Prostate Cancer Consortium Risk Calculator (CPCC-RC) was constructed with cases from 2 hospitals in Shanghai. Discriminative ability, calibration and decision curve analysis were externally validated in 3 CPCC member hospitals. Of the 1,835 patients involved, PCa was identified in 338/924 (36.6%) and 294/911 (32.3%) men in the development and validation cohort, respectively. Multivariate logistic regression analyses showed that 5 predictors (age, logPSA, logPV, free PSA ratio, and digital rectal examination) were associated with PCa (Model 1) or high-grade PCa (Model 2), respectively. The area under the curve of Model 1 and Model 2 was 0.801 (95% CI: 0.771-0.831) and 0.826 (95% CI: 0.796-0.857), respectively. Both models illustrated good calibration and substantial improvement in decision curve analyses than any single predictors at all threshold probabilities. Higher predicting accuracy, better calibration, and greater clinical benefit were achieved by CPCC-RC, compared with European Randomized Study for Screening of Prostate Cancer Risk Calculator and Prostate Cancer Prevention Trial Risk Calculator in predicting PCa. CPCC-RC performed well in discrimination and calibration and decision curve analysis in external validation compared with Western risk calculators. CPCC-RC may aid in decision-making of prostate biopsy in Chinese or in other Asian populations with similar genetic and environmental backgrounds. Copyright © 2016 Elsevier Inc. All rights reserved.

Heterogeneity of DNA methylation in multifocal prostate cancer.

PubMed

Serenaite, Inga; Daniunaite, Kristina; Jankevicius, Feliksas; Laurinavicius, Arvydas; Petroska, Donatas; Lazutka, Juozas R; Jarmalaite, Sonata

2015-01-01

Most prostate cancer (PCa) cases are multifocal, and separate foci display histological and molecular heterogeneity. DNA hypermethylation is a frequent alteration in PCa, but interfocal heterogeneity of these changes has not been extensively investigated. Ten pairs of foci from multifocal PCa and 15 benign prostatic hyperplasia (BPH) samples were obtained from prostatectomy specimens, resulting altogether in 35 samples. Methylation-specific PCR (MSP) was used to evaluate methylation status of nine tumor suppressor genes (TSGs), and a set of selected TSGs was quantitatively analyzed for methylation intensity by pyrosequencing. Promoter sequences of the RASSF1 and ESR1 genes were methylated in all paired PCa foci, and frequent (≥75 %) DNA methylation was detected in RARB, GSTP1, and ABCB1 genes. MSP revealed different methylation status of at least one gene in separate foci in 8 out of 10 multifocal tumors. The mean methylation level of ESR1, GSTP1, RASSF1, and RARB differed between the paired foci of all PCa cases. The intensity of DNA methylation in these TSGs was significantly higher in PCa cases than in BPH (p < 0.001). Hierarchical cluster analysis revealed a divergent methylation profile of paired PCa foci, while the foci from separate cases with biochemical recurrence showed similar methylation profile and the highest mean levels of DNA methylation. Our findings suggest that PCa tissue is heterogeneous, as between paired foci differences in DNA methylation status were found. Common epigenetic profile of recurrent tumors can be inferred from our data.

Damage detection methodology under variable load conditions based on strain field pattern recognition using FBGs, nonlinear principal component analysis, and clustering techniques

NASA Astrophysics Data System (ADS)

Sierra-Pérez, Julián; Torres-Arredondo, M.-A.; Alvarez-Montoya, Joham

2018-01-01

Structural health monitoring consists of using sensors integrated within structures together with algorithms to perform load monitoring, damage detection, damage location, damage size and severity, and prognosis. One possibility is to use strain sensors to infer structural integrity by comparing patterns in the strain field between the pristine and damaged conditions. In previous works, the authors have demonstrated that it is possible to detect small defects based on strain field pattern recognition by using robust machine learning techniques. They have focused on methodologies based on principal component analysis (PCA) and on the development of several unfolding and standardization techniques, which allow dealing with multiple load conditions. However, before a real implementation of this approach in engineering structures, changes in the strain field due to conditions different from damage occurrence need to be isolated. Since load conditions may vary in most engineering structures and promote significant changes in the strain field, it is necessary to implement novel techniques for uncoupling such changes from those produced by damage occurrence. A damage detection methodology based on optimal baseline selection (OBS) by means of clustering techniques is presented. The methodology includes the use of hierarchical nonlinear PCA as a nonlinear modeling technique in conjunction with Q and nonlinear-T 2 damage indices. The methodology is experimentally validated using strain measurements obtained by 32 fiber Bragg grating sensors bonded to an aluminum beam under dynamic bending loads and simultaneously submitted to variations in its pitch angle. The results demonstrated the capability of the methodology for clustering data according to 13 different load conditions (pitch angles), performing the OBS and detecting six different damages induced in a cumulative way. The proposed methodology showed a true positive rate of 100% and a false positive rate of 1.28% for a 99% of confidence.

USE OF THE PROSTATE HEALTH INDEX FOR DETECTION OF PROSTATE CANCER: RESULTS FROM A LARGE ACADEMIC PRACTICE

PubMed Central

Tosoian, Jeffrey J.; Druskin, Sasha C.; Andreas, Darian; Mullane, Patrick; Chappidi, Meera; Joo, Sarah; Ghabili, Kamyar; Agostino, Joseph; Macura, Katarzyna J.; Carter, H. Ballentine; Schaeffer, Edward M.; Partin, Alan W.; Sokoll, Lori J.; Ross, Ashley E.

2016-01-01

BACKGROUND The Prostate Health Index (phi) outperforms PSA and other PSA derivatives for the diagnosis of prostate cancer (PCa). The impact of phi testing in the real-world clinical setting has not been previously assessed. METHODS In a single, large, academic center, phi was tested in 345 patients presenting for diagnostic evaluation for PCa. Findings on prostate biopsy (including Grade Group [GG], defined as GG1: Gleason score [GS] 6, GG2: GS 3+4=7, GG3: GS 4+3=7, GG4: GS 8, and GG5: GS 9-10), magnetic resonance imaging (MRI), and radical prostatectomy (RP) were prospectively recorded. Biopsy rates and outcomes were compared to a contemporary cohort that did not undergo phi testing (n=1318). RESULTS Overall, 39% of men with phi testing underwent prostate biopsy. No men with phi<19.6 were diagnosed with PCa, and only 3 men with phi<27 had cancer of GG≥2. Phi was superior to PSA for the prediction of any PCa (AUC 0.72 vs. 0.47) and GG≥2 PCa (AUC 0.77 vs. 0.53) on prostate biopsy. Among men undergoing MRI and phi, no men with phi<27 and PI-RADS≤3 had GG≥2 cancer. For those men proceeding to RP, increasing phi was associated with higher pathologic GG (p=0.002) and stage (p=0.001). Compared to patients who did not undergo phi testing, the use of phi was associated with a 9% reduction in the rate of prostate biopsy (39% vs. 48%; p<0.001). Importantly, the reduction in biopsy among the phi population was secondary to decreased incidence of negative (8%) and GG1 (1%) biopsies, while the proportion of biopsies detecting GG≥2 cancers remained unchanged. CONCLUSIONS In this large, real-time clinical experience, phi outperformed PSA alone, was associated with high-grade PCa, and provided complementary information to MRI. Incorporation of phi into clinical practice reduced the rate of unnecessary biopsies without changing the frequency of detection of higher grade cancers. PMID:28117387

SU-F-R-41: Regularized PCA Can Model Treatment-Related Changes in Head and Neck Patients Using Daily CBCTs

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

Chetvertkov, M; Henry Ford Health System, Detroit, MI; Siddiqui, F

2016-06-15

Purpose: To use daily cone beam CTs (CBCTs) to develop regularized principal component analysis (PCA) models of anatomical changes in head and neck (H&N) patients, to guide replanning decisions in adaptive radiation therapy (ART). Methods: Known deformations were applied to planning CT (pCT) images of 10 H&N patients to model several different systematic anatomical changes. A Pinnacle plugin was used to interpolate systematic changes over 35 fractions, generating a set of 35 synthetic CTs for each patient. Deformation vector fields (DVFs) were acquired between the pCT and synthetic CTs and random fraction-to-fraction changes were superimposed on the DVFs. Standard non-regularizedmore » and regularized patient-specific PCA models were built using the DVFs. The ability of PCA to extract the known deformations was quantified. PCA models were also generated from clinical CBCTs, for which the deformations and DVFs were not known. It was hypothesized that resulting eigenvectors/eigenfunctions with largest eigenvalues represent the major anatomical deformations during the course of treatment. Results: As demonstrated with quantitative results in the supporting document regularized PCA is more successful than standard PCA at capturing systematic changes early in the treatment. Regularized PCA is able to detect smaller systematic changes against the background of random fraction-to-fraction changes. To be successful at guiding ART, regularized PCA should be coupled with models of when anatomical changes occur: early, late or throughout the treatment course. Conclusion: The leading eigenvector/eigenfunction from the both PCA approaches can tentatively be identified as a major systematic change during radiotherapy course when systematic changes are large enough with respect to random fraction-to-fraction changes. In all cases the regularized PCA approach appears to be more reliable at capturing systematic changes, enabling dosimetric consequences to be projected once trends are established early in the treatment course. This work is supported in part by a grant from Varian Medical Systems, Palo Alto, CA.« less

CAPE suppresses migration and invasion of prostate cancer cells via activation of non-canonical Wnt signaling.

PubMed

Tseng, Jen-Chih; Lin, Ching-Yu; Su, Liang-Chen; Fu, Hsiao-Hui; Yang, Shiaw-Der; Chuu, Chih-Pin

2016-06-21

Prostate cancer (PCa) was the fifth most common cancer overall in the world. More than 80% of patients died from PCa developed bone metastases. Caffeic acid phenethyl ester (CAPE) is a main bioactive component of honeybee hive propolis. Transwell and wound healing assays demonstrated that CAPE treatment suppressed the migration and invasion of PC-3 and DU-145 PCa cells. Gelatin zymography and Western blotting indicated that CAPE treatment reduced the abundance and activity of MMP-9 and MMP-2. Analysis using Micro-Western Array (MWA), a high-throughput antibody-based proteomics platform with 264 antibodies detecting signaling proteins involved in important pathways indicated that CAPE treatment induced receptor tyrosine kinase-like orphan receptor 2 (ROR2) in non-canonical Wnt signaling pathway but suppressed abundance of β-catenin, NF-κB activity, PI3K-Akt signaling, and epithelial-mesenchymal transition (EMT). Overexpression or knockdown of ROR2 suppressed or enhanced cell migration of PC-3 cells, respectively. TCF-LEF promoter binding assay revealed that CAPE treatment reduced canonical Wnt signaling. Intraperitoneal injection of CAPE reduced the metastasis of PC-3 xenografts in tail vein injection nude mice model. Immunohistochemical staining demonstrated that CAPE treatment increased abundance of ROR2 and Wnt5a but decreased protein expression of Ki67, Frizzle 4, NF-κB p65, MMP-9, Snail, β-catenin, and phosphorylation of IκBα. Clinical evidences suggested that genes affected by CAPE treatment (CTNNB1, RELA, FZD5, DVL3, MAPK9, SNAl1, ROR2, SMAD4, NFKBIA, DUSP6, and PLCB3) correlate with the aggressiveness of PCa. Our study suggested that CAPE may be a potential therapeutic agent for patients with advanced PCa.

Machine learning-based analysis of MR radiomics can help to improve the diagnostic performance of PI-RADS v2 in clinically relevant prostate cancer.

PubMed

Wang, Jing; Wu, Chen-Jiang; Bao, Mei-Ling; Zhang, Jing; Wang, Xiao-Ning; Zhang, Yu-Dong

2017-10-01

To investigate whether machine learning-based analysis of MR radiomics can help improve the performance PI-RADS v2 in clinically relevant prostate cancer (PCa). This IRB-approved study included 54 patients with PCa undergoing multi-parametric (mp) MRI before prostatectomy. Imaging analysis was performed on 54 tumours, 47 normal peripheral (PZ) and 48 normal transitional (TZ) zone based on histological-radiological correlation. Mp-MRI was scored via PI-RADS, and quantified by measuring radiomic features. Predictive model was developed using a novel support vector machine trained with: (i) radiomics, (ii) PI-RADS scores, (iii) radiomics and PI-RADS scores. Paired comparison was made via ROC analysis. For PCa versus normal TZ, the model trained with radiomics had a significantly higher area under the ROC curve (Az) (0.955 [95% CI 0.923-0.976]) than PI-RADS (Az: 0.878 [0.834-0.914], p < 0.001). The Az between them was insignificant for PCa versus PZ (0.972 [0.945-0.988] vs. 0.940 [0.905-0.965], p = 0.097). When radiomics was added, performance of PI-RADS was significantly improved for PCa versus PZ (Az: 0.983 [0.960-0.995]) and PCa versus TZ (Az: 0.968 [0.940-0.985]). Machine learning analysis of MR radiomics can help improve the performance of PI-RADS in clinically relevant PCa. • Machine-based analysis of MR radiomics outperformed in TZ cancer against PI-RADS. • Adding MR radiomics significantly improved the performance of PI-RADS. • DKI-derived Dapp and Kapp were two strong markers for the diagnosis of PCa.

Prostate-cancer diagnosis by non-invasive prostatic Zinc mapping using X-Ray Fluorescence (XRF)

NASA Astrophysics Data System (ADS)

Cortesi, Marco

At present, the major screening tools (PSA, DRE, TRUS) for prostate cancer lack sensitivity and specificity, and none can distinguish between low-grade indolent cancer and high-grade lethal one. The situation calls for the promotion of alternative approaches, with better detection sensitivity and specificity, to provide more efficient selection of patients to biopsy and with possible guidance of the biopsy needles. The prime objective of the present work was the development of a novel non-invasive method and tool for promoting detection, localization, diagnosis and follow-up of PCa. The method is based on in-vivo imaging of Zn distribution in the peripheral zone of the prostate, by a trans-rectal X-ray fluorescence (XRF) probe. Local Zn levels, measured in 1--4 mm3 fresh tissue biopsy segments from an extensive clinical study involving several hundred patients, showed an unambiguous correlation with the histological classification of the tissue (Non-Cancer or PCa), and a systematic positive correlation of its depletion level with the cancer-aggressiveness grade (Gleason classification). A detailed analysis of computer-simulated Zn-concentration images (with input parameters from clinical data) disclosed the potential of the method to provide sensitive and specific detection and localization of the lesion, its grade and extension. Furthermore, it also yielded invaluable data on some requirements, such as the image resolution and counting-statistics, requested from a trans-rectal XRF probe for in-vivo recording of prostatic-Zn maps in patients. By means of systematic table-top experiments on prostate-phantoms comprising tumor-like inclusions, followed by dedicated Monte Carlo simulations, the XRF-probe and its components have been designed and optimized. Multi-parameter analysis of the experimental data confirmed the simulation estimations of the XRF detection system in terms of: delivered dose, counting statistics, scanning resolution, target-volume size and the accuracy of locating at various depths of small-volume tumor-like inclusions in tissue-phantoms. The clinical study, the Monte Carlo simulations and the analysis of Zn-map images provided essential information and promising vision on the potential performance of the Zn-based PCa detection concept. Simulations focusing on medical-probe design and its performance at permissible radiation doses yielded positive results - confirmed by a series of systematic laboratory experiments with a table-top XRF system.

Phase I/II trial of dendritic cell-based active cellular immunotherapy with DCVAC/PCa in patients with rising PSA after primary prostatectomy or salvage radiotherapy for the treatment of prostate cancer.

PubMed

Fucikova, Jitka; Podrazil, Michal; Jarolim, Ladislav; Bilkova, Pavla; Hensler, Michal; Becht, Etienne; Gasova, Zdenka; Klouckova, Jana; Kayserova, Jana; Horvath, Rudolf; Fialova, Anna; Vavrova, Katerina; Sochorova, Klara; Rozkova, Daniela; Spisek, Radek; Bartunkova, Jirina

2018-01-01

Immunotherapy of cancer has the potential to be effective mostly in patients with a low tumour burden. Rising PSA (prostate-specific antigen) levels in patients with prostate cancer represents such a situation. We performed the present clinical study with dendritic cell (DC)-based immunotherapy in this patient population. The single-arm phase I/II trial registered as EudraCT 2009-017259-91 involved 27 patients with rising PSA levels. The study medication consisted of autologous DCs pulsed with the killed LNCaP cell line (DCVAC/PCa). Twelve patients with a favourable PSA response continued with the second cycle of immunotherapy. The primary and secondary objectives of the study were to assess the safety and determine the PSA doubling time (PSADT), respectively. No significant side effects were recorded. The median PSADT in all treated patients increased from 5.67 months prior to immunotherapy to 18.85 months after 12 doses (p < 0.0018). Twelve patients who continued immunotherapy with the second cycle had a median PSADT of 58 months that remained stable after the second cycle. In the peripheral blood, specific PSA-reacting T lymphocytes were increased significantly already after the fourth dose, and a stable frequency was detected throughout the remainder of DCVAC/PCa treatment. Long-term immunotherapy of prostate cancer patients experiencing early signs of PSA recurrence using DCVAC/PCa was safe, induced an immune response and led to the significant prolongation of PSADT. Long-term follow-up may show whether the changes in PSADT might improve the clinical outcome in patients with biochemical recurrence of the prostate cancer.

On-line early fault detection and diagnosis of municipal solid waste incinerators

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

Zhao Jinsong; Huang Jianchao; Sun Wei

A fault detection and diagnosis framework is proposed in this paper for early fault detection and diagnosis (FDD) of municipal solid waste incinerators (MSWIs) in order to improve the safety and continuity of production. In this framework, principal component analysis (PCA), one of the multivariate statistical technologies, is used for detecting abnormal events, while rule-based reasoning performs the fault diagnosis and consequence prediction, and also generates recommendations for fault mitigation once an abnormal event is detected. A software package, SWIFT, is developed based on the proposed framework, and has been applied in an actual industrial MSWI. The application shows thatmore » automated real-time abnormal situation management (ASM) of the MSWI can be achieved by using SWIFT, resulting in an industrially acceptable low rate of wrong diagnosis, which has resulted in improved process continuity and environmental performance of the MSWI.« less

[Research on optimal modeling strategy for licorice extraction process based on near-infrared spectroscopy technology].

PubMed

Wang, Hai-Xia; Suo, Tong-Chuan; Yu, He-Shui; Li, Zheng

2016-10-01

The manufacture of traditional Chinese medicine (TCM) products is always accompanied by processing complex raw materials and real-time monitoring of the manufacturing process. In this study, we investigated different modeling strategies for the extraction process of licorice. Near-infrared spectra associate with the extraction time was used to detemine the states of the extraction processes. Three modeling approaches, i.e., principal component analysis (PCA), partial least squares regression (PLSR) and parallel factor analysis-PLSR (PARAFAC-PLSR), were adopted for the prediction of the real-time status of the process. The overall results indicated that PCA, PLSR and PARAFAC-PLSR can effectively detect the errors in the extraction procedure and predict the process trajectories, which has important significance for the monitoring and controlling of the extraction processes. Copyright© by the Chinese Pharmaceutical Association.

Door Security using Face Detection and Raspberry Pi

NASA Astrophysics Data System (ADS)

Bhutra, Venkatesh; Kumar, Harshav; Jangid, Santosh; Solanki, L.

2018-03-01

With the world moving towards advanced technologies, security forms a crucial part in daily life. Among the many techniques used for this purpose, Face Recognition stands as effective means of authentication and security. This paper deals with the user of principal component and security. PCA is a statistical approach used to simplify a data set. The minimum Euclidean distance found from the PCA technique is used to recognize the face. Raspberry Pi a low cost ARM based computer on a small circuit board, controls the servo motor and other sensors. The servo-motor is in turn attached to the doors of home and opens up when the face is recognized. The proposed work has been done using a self-made training database of students from B.K. Birla Institute of Engineering and Technology, Pilani, Rajasthan, India.

Diagnostic performance of expression of PCA3, Hepsin and miR biomarkers inejaculate in combination with serum PSA for the detection of prostate cancer.

PubMed

Roberts, Matthew J; Chow, Clement W K; Schirra, Horst Joachim; Richards, Renee; Buck, Marion; Selth, Luke A; Doi, Suhail A R; Samaratunga, Hema; Perry-Keene, Joanna; Payton, Diane; Yaxley, John; Lavin, Martin F; Gardiner, Robert A

2015-04-01

Here, we report on the evaluation of the diagnostic performance of ejaculate-derived PCA3, Hepsin, and miRNAs to complement serum PSA to detect prostate cancer. cDNA was prepared from 152 candidate specimens following RNA isolation and amplification for PSA, PCA3 and Hepsin qPCR, with 66 having adequate RNA for all three assays. Small RNA sequencing and examination of PCa-associated miRNAs miR-200b, miR-200c, miR-375 and miR-125b was performed on 20 specimens. We compared findings from prostate biopsies using D'Amico and PRIAS classifications and in relation to whole gland histopathology following radical prostatectomy. Multivariate logistic regression modeling and clinical risk (incorporating standard clinicopathological variables) were performed for all ejaculate-based markers. While Hepsin alone was not of predictive value, the Hepsin:PCA3 ratio together with serum PSA, expressed as a univariate composite score based on multivariate logistic regression, was shown to be a better predictor than PSA alone of prostate cancer status (AUC 0.724 vs. 0.676) and risk, using D'Amico (AUC 0.701 vs. 0.680) and PRIAS (AUC 0.679 vs. 0.659) risk stratification criteria as classified using prostate biopsies. It was also possible to analyse a subgroup of patients for miRNA expression with miR-200c (AUC 0.788) and miR-375 (AUC 0.758) showing best single marker performance, while a combination of serum PSA, miR-200c, and miR-125b further improved prediction for prostate cancer status when compared to PSA alone determined by biopsy (AUC 0.869 vs. 0.672; P < 0.05), and risk (D'Amico/PRIAS) as well as by radical prostatectomy histology (AUC 0.809 vs. 0.690). For prostate cancer status by biopsy, at a sensitivity of 90%, the specificity of the test increased from 11% for PSA alone to 67% for a combination of PSA, miR-200c, and miR-125b. These results show that use of a combination of different types of genetic markers in ejaculate together with serum PSA are at least as sensitive as those reported in DRE urine. Furthermore, a combination of serum PSA and selected miRNAs improved prediction of prostate cancer status. This approach may be helpful in triaging patients for MRI and biopsy, when confirmed by larger studies. © 2015 Wiley Periodicals, Inc.

Diagnostic performance of 68Ga-PSMA-11 (HBED-CC) PET/CT in patients with recurrent prostate cancer: evaluation in 1007 patients.

PubMed

Afshar-Oromieh, Ali; Holland-Letz, Tim; Giesel, Frederik L; Kratochwil, Clemens; Mier, Walter; Haufe, Sabine; Debus, Nils; Eder, Matthias; Eisenhut, Michael; Schäfer, Martin; Neels, Oliver; Hohenfellner, Markus; Kopka, Klaus; Kauczor, Hans-Ulrich; Debus, Jürgen; Haberkorn, Uwe

2017-08-01

Since the clinical introduction of 68 Ga-PSMA-11 PET/CT, this imaging method has rapidly spread and is now regarded as a significant step forward in the diagnosis of recurrent prostate cancer (PCa). The aim of this study was to analyse the influence of several variables with possible influence on PSMA ligand uptake in a large cohort. We performed a retrospective analysis of 1007 consecutive patients who were scanned with 68 Ga-PSMA-11 PET/CT (1 h after injection) from January 2014 to January 2017 to detect recurrent disease. Patients with untreated primary PCa or patients referred for PSMA radioligand therapy were excluded. The possible effects of different variables including PSA level and PSA doubling time (PSA DT ), PSA velocity (PSA Vel ), Gleason score (GSC, including separate analysis of GSC 7a and 7b), ongoing androgen deprivation therapy (ADT), patient age and amount of injected activity were evaluated. In 79.5% of patients at least one lesion with characteristics suggestive of recurrent PCa was detected. A pathological (positive) PET/CT scan was associated with PSA level and ADT. GSC, amount of injected activity, patient age, PSA DT and PSA Vel were not associated with a positive PET/CT scan in multivariate analysis. 68 Ga-PSMA-11 PET/CT detects tumour lesions in a high percentage of patients with recurrent PCa. Tumour detection is clearly associated with PSA level and ADT. Only a tendency for an association without statistical significance was found between higher GSC and a higher probability of a pathological PET/CT scan. No associations were found between a pathological 68 Ga-PSMA-11 PET/CT scan and patient age, amount of injected activity, PSA DT or PSA Vel.

Discrimination of geographical origin and detection of adulteration of kudzu root by fluorescence spectroscopy coupled with multi-way pattern recognition

NASA Astrophysics Data System (ADS)

Hu, Leqian; Ma, Shuai; Yin, Chunling

2018-03-01

In this work, fluorescence spectroscopy combined with multi-way pattern recognition techniques were developed for determining the geographical origin of kudzu root and detection and quantification of adulterants in kudzu root. Excitation-emission (EEM) spectra were obtained for 150 pure kudzu root samples of different geographical origins and 150 fake kudzu roots with different adulteration proportions by recording emission from 330 to 570 nm with excitation in the range of 320-480 nm, respectively. Multi-way principal components analysis (M-PCA) and multilinear partial least squares discriminant analysis (N-PLS-DA) methods were used to decompose the excitation-emission matrices datasets. 150 pure kudzu root samples could be differentiated exactly from each other according to their geographical origins by M-PCA and N-PLS-DA models. For the adulteration kudzu root samples, N-PLS-DA got better and more reliable classification result comparing with the M-PCA model. The results obtained in this study indicated that EEM spectroscopy coupling with multi-way pattern recognition could be used as an easy, rapid and novel tool to distinguish the geographical origin of kudzu root and detect adulterated kudzu root. Besides, this method was also suitable for determining the geographic origin and detection the adulteration of the other foodstuffs which can produce fluorescence.

Detection And Identification Of Inflammatory Bowel Disease Electronic Nose

NASA Astrophysics Data System (ADS)

Covington, J. A.; Ouaret, N.; Gardner, J. W.; Nwokolo, C.; Bardhan, K. D.; Arasaradnam, R. P.

2011-11-01

Inflammatory bowel disease (IBD) is an inflammation of the lining of the human bowel and a major health issue in Europe. IBD carries with it significant morbidity from toxic treatment, surgery and a risk of developing bowel cancer. Thus there is a need for early identification of the disease using non-invasive tests. Present diagnostic techniques are based around invasive tests (i.e. endoscopy) and laboratory culture; the latter is limited as only 50% of the gut bacteria can be identified. Here we explore the use of an e-nose as a tool to detect and identify two IBDs (i.e. Crohn's disease (CD) & Ulcerative Colitis (UC)) based on headspace analysis from urine samples. We believe that the gut bacterial flora is altered by disease (due to fermentation) that in-turn modulates the gas composition within urine samples. 24 samples (9 CD, 6 UC, 9 controls) were analysed with an in-house e-nose and an Owlstone IMS instrument. Data analysis was performed using linear discriminant analysis (LDA and principal components analysis (PCA). Using the e-nose, LDA separates both disease groups and control, whilst PCA shows a small overlap of classes. The IMS data are more complex but shows some disease/control separation. We are presently collecting further samples for a larger study using more advanced data processing methods.

South Atlantic Anomaly Entry and Exit as Measured by the X-Ray Timing Explorer

NASA Technical Reports Server (NTRS)

Smith, Evan; Stark, Michael; Giles, Barry; Antunes, Sandy; Gawne, Bill

1996-01-01

The Rossi X-ray Timing Explorer (RXTE) carries instruments that must switch off high voltages (HV) when passing through the South Atlantic Anomaly (SAA). The High Energy X-ray Timing Experiment (HEXTE) contains a particle monitor that detects the increased particle flux associated with the SAA and autonomously reduces its voltage. The Proportional Counter Array (PCA) relies on uplinked predictions of SAA entry/exit times based on ephemeris data provided by the Flight Dynamics Facility. A third instrument, the All-Sky Monitor (ASM) also uses a predicted SAA model to reduce voltage when passing through the SAA. Data collected from the HEXTE particle monitor, as well as other instrument readings near the times of SAA entry/exit offer the potential for refining models of the boundaries of the SAA. The SAA has an increased particle flux which causes high rates of detection in the RXTE instruments designed to observe x-rays. The high counting rates could degrade the PCA if HV is not reduced during SAA passages. On the other hand, PCA downtime can be minimized and the science return can be optimized by having the best possible model of the SAA boundary. Thus, the PCA team planned an extensive effort during in-orbit checkout to utilize both the HEXTE particle monitor data and instrument counting rates to refine the model of the SAA boundary. The times of SAA entry and exit are compared with the definitive epemeris to determine the precise location (latitude and longitude) of the SAA boundary. Over time, the SAA and its perimeter were mapped. The RXTE Science Operations Center is continuously working to feed back the results of this effort into the science scheduling process, improving the SAA model as it affects the RXTE instruments, thus obtaining more accurate estimates of the SAA entry/exit times.

Near-Infrared Neodymium Tag for Quantifying Targeted Biomarker and Counting Its Host Circulating Tumor Cells.

PubMed

Liu, Chunlan; Lu, Shu; Yang, Limin; Chen, Peijie; Bai, Peiming; Wang, Qiuquan

2017-09-05

Quantitative information on a targeted analyte in a complex biological system is the most basic premise for understanding its involved mechanisms, and thus precise diagnosis of a disease if it is a so-called biomarker. Here, we designed and synthesized a neodymium (Nd)-cored tag [1,4,7,10-tetraazacyclododecane-1,4,7-trisacetic acid (DOTA)-Nd complex together with a light-harvesting antenna aminofluorescein (AMF, λ ex/em = 494/520 nm), AMF-DOTA-Nd] with duplex signals, second near-infrared (NIR) window luminescence (λ em = 1065 nm, 2.5 μs), and stable isotopic mass ( 142 Nd). AMF-DOTA-Nd covalently linked with a urea-based peptidomimetic targeting group, 2-[3-(1,3-dicarboxypropyl)-ureido]pentanedioic acid (DUPA)-8-Aoc-Phe-Phe-Cys (DUPAaFFC) (DUPAaFFC-AMF-DOTA-Nd), allowing us to detect and quantify prostate-specific membrane antigen (PSMA) and its splice variants (total PSMA, tPSMA), which was set as an example of targeted biomarkers in this study, using NIR and inductively coupled plasma mass spectrometry (ICPMS) with the limit of detection (LOD) (3σ) of 0.3 ng/mL. When it was applied to the analysis of 80 blood samples from prostate cancer (PCa) and benign prostatic hyperplasia (BPH) patients as well as healthy volunteers, we found that 320 and 600 ng/mL tPSMA could be recommended as the threshold values to differentiate BPH from PCa and for the diagnosis of PCa. Moreover, PSMA-positive circulating tumor cells (CTCs) were counted using ICPMS being from 134 to 773 CTCs in the PCa blood samples of the Gleason score from 6 to 9 when the cell membrane-spanning mPSMA was tagged. Such a methodology developed could be expected to be applicable to other clinic-meaningful biomolecules and their host CTCs in liquid biopsy, when other specific targeting groups are modified to the NIR Nd tag.

Near-infrared confocal micro-Raman spectroscopy combined with PCA-LDA multivariate analysis for detection of esophageal cancer

NASA Astrophysics Data System (ADS)

Chen, Long; Wang, Yue; Liu, Nenrong; Lin, Duo; Weng, Cuncheng; Zhang, Jixue; Zhu, Lihuan; Chen, Weisheng; Chen, Rong; Feng, Shangyuan

2013-06-01

The diagnostic capability of using tissue intrinsic micro-Raman signals to obtain biochemical information from human esophageal tissue is presented in this paper. Near-infrared micro-Raman spectroscopy combined with multivariate analysis was applied for discrimination of esophageal cancer tissue from normal tissue samples. Micro-Raman spectroscopy measurements were performed on 54 esophageal cancer tissues and 55 normal tissues in the 400-1750 cm-1 range. The mean Raman spectra showed significant differences between the two groups. Tentative assignments of the Raman bands in the measured tissue spectra suggested some changes in protein structure, a decrease in the relative amount of lactose, and increases in the percentages of tryptophan, collagen and phenylalanine content in esophageal cancer tissue as compared to those of a normal subject. The diagnostic algorithms based on principal component analysis (PCA) and linear discriminate analysis (LDA) achieved a diagnostic sensitivity of 87.0% and specificity of 70.9% for separating cancer from normal esophageal tissue samples. The result demonstrated that near-infrared micro-Raman spectroscopy combined with PCA-LDA analysis could be an effective and sensitive tool for identification of esophageal cancer.

Water quality analysis of the Rapur area, Andhra Pradesh, South India using multivariate techniques

NASA Astrophysics Data System (ADS)

Nagaraju, A.; Sreedhar, Y.; Thejaswi, A.; Sayadi, Mohammad Hossein

2017-10-01

The groundwater samples from Rapur area were collected from different sites to evaluate the major ion chemistry. The large number of data can lead to difficulties in the integration, interpretation, and representation of the results. Two multivariate statistical methods, hierarchical cluster analysis (HCA) and factor analysis (FA), were applied to evaluate their usefulness to classify and identify geochemical processes controlling groundwater geochemistry. Four statistically significant clusters were obtained from 30 sampling stations. This has resulted two important clusters viz., cluster 1 (pH, Si, CO3, Mg, SO4, Ca, K, HCO3, alkalinity, Na, Na + K, Cl, and hardness) and cluster 2 (EC and TDS) which are released to the study area from different sources. The application of different multivariate statistical techniques, such as principal component analysis (PCA), assists in the interpretation of complex data matrices for a better understanding of water quality of a study area. From PCA, it is clear that the first factor (factor 1), accounted for 36.2% of the total variance, was high positive loading in EC, Mg, Cl, TDS, and hardness. Based on the PCA scores, four significant cluster groups of sampling locations were detected on the basis of similarity of their water quality.

Electric Power Engineering Cost Predicting Model Based on the PCA-GA-BP

NASA Astrophysics Data System (ADS)

Wen, Lei; Yu, Jiake; Zhao, Xin

2017-10-01

In this paper a hybrid prediction algorithm: PCA-GA-BP model is proposed. PCA algorithm is established to reduce the correlation between indicators of original data and decrease difficulty of BP neural network in complex dimensional calculation. The BP neural network is established to estimate the cost of power transmission project. The results show that PCA-GA-BP algorithm can improve result of prediction of electric power engineering cost.

Novel algorithm for simultaneous component detection and pseudo-molecular ion characterization in liquid chromatography-mass spectrometry.

PubMed

Zhang, Yufeng; Wang, Xiaoan; Wo, Siukwan; Ho, Hingman; Han, Quanbin; Fan, Xiaohui; Zuo, Zhong

2015-01-01

Resolving components and determining their pseudo-molecular ions (PMIs) are crucial steps in identifying complex herbal mixtures by liquid chromatography-mass spectrometry. To tackle such labor-intensive steps, we present here a novel algorithm for simultaneous detection of components and their PMIs. Our method consists of three steps: (1) obtaining a simplified dataset containing only mono-isotopic masses by removal of background noise and isotopic cluster ions based on the isotopic distribution model derived from all the reported natural compounds in dictionary of natural products; (2) stepwise resolving and removing all features of the highest abundant component from current simplified dataset and calculating PMI of each component according to an adduct-ion model, in which all non-fragment ions in a mass spectrum are considered as PMI plus one or several neutral species; (3) visual classification of detected components by principal component analysis (PCA) to exclude possible non-natural compounds (such as pharmaceutical excipients). This algorithm has been successfully applied to a standard mixture and three herbal extract/preparations. It indicated that our algorithm could detect components' features as a whole and report their PMI with an accuracy of more than 98%. Furthermore, components originated from excipients/contaminants could be easily separated from those natural components in the bi-plots of PCA. Copyright © 2014 Elsevier B.V. All rights reserved.

The role of serum neuron-specific enolase in patients with prostate cancer: a systematic review of the recent literature.

PubMed

Muoio, Barbara; Pascale, Mariarosa; Roggero, Enrico

2018-01-01

In this systematic review, we evaluated the value of serum concentrations of neuron-specific enolase (NSE) in patients with prostate cancer (PCa) in order to clarify the possible role of NSE in the diagnosis, management, treatment and monitoring of PCa. A comprehensive search of the recent literature was conducted to find relevant data on the role of NSE in PCa. Two hundred and eighty-two records were revealed, and 19 articles including 1,772 patients with PCa (either confirmed or suspected) were selected. After reviewing the articles, the major result was that elevated serum NSE appears to correlate with prognosis in advanced PCa, particularly in patients with progressive and metastatic castration-resistant PCa. Based on the existing literature, the role of serum NSE in PCa patients should be further evaluated.

Revealing the ultrafast outflow in IRAS 13224-3809 through spectral variability

NASA Astrophysics Data System (ADS)

Parker, M. L.; Alston, W. N.; Buisson, D. J. K.; Fabian, A. C.; Jiang, J.; Kara, E.; Lohfink, A.; Pinto, C.; Reynolds, C. S.

2017-08-01

We present an analysis of the long-term X-ray variability of the extreme narrow-line Seyfert 1 galaxy IRAS 13224-3809 using principal component analysis (PCA) and fractional excess variability (Fvar) spectra to identify model-independent spectral components. We identify a series of variability peaks in both the first PCA component and Fvar spectrum which correspond to the strongest predicted absorption lines from the ultrafast outflow (UFO) discovered by Parker et al. (2017). We also find higher order PCA components, which correspond to variability of the soft excess and reflection features. The subtle differences between RMS and PCA results argue that the observed flux-dependence of the absorption is due to increased ionization of the gas, rather than changes in column density or covering fraction. This result demonstrates that we can detect outflows from variability alone and that variability studies of UFOs are an extremely promising avenue for future research.

Magnetic Resonance Spectroscopy (MRS) of Prostatic Fluids for Early Detection of Prostate Cancer

DTIC Science & Technology

2006-10-01

nuclear magnetic resonance spectroscopy (1H-NMRS). The metabolites quantified included citrate, spermine, myo- inositol , lactate, alanine...adjusting for age. The LR models indicated that the absolute concentrations of citrate, myo- inositol , and spermine were highly predictive of PCa and...inversely related to the risk of PCa. The areas under the receiver operating characteristic curves (AUROC) for citrate, myo- inositol and spermine were

Magnetic Resonance Spectroscopy (MRS) of Prostatic Fluids for Early Detection of Prostate Cancer

DTIC Science & Technology

2007-04-01

quantitative proton nuclear magnetic resonance spectroscopy (1H-NMRS). The metabolites quantified included citrate, spermine, myo- inositol , lactate, alanine...concentrations while adjusting for age. The LR models indicated that the absolute concentrations of citrate, myo- inositol , and spermine were highly predictive...of PCa and inversely related to the risk of PCa. The areas under the receiver operating characteristic curves (AUROC) for citrate, myo- inositol and

Examination of polymorphic glutathione S-transferase (GST) genes, tobacco smoking and prostate cancer risk among Men of African Descent: A case-control study

PubMed Central

2009-01-01

Background Polymorphisms in glutathione S-transferase (GST) genes may influence response to oxidative stress and modify prostate cancer (PCA) susceptibility. These enzymes generally detoxify endogenous and exogenous agents, but also participate in the activation and inactivation of oxidative metabolites that may contribute to PCA development. Genetic variations within selected GST genes may influence PCA risk following exposure to carcinogen compounds found in cigarette smoke and decreased the ability to detoxify them. Thus, we evaluated the effects of polymorphic GSTs (M1, T1, and P1) alone and combined with cigarette smoking on PCA susceptibility. Methods In order to evaluate the effects of GST polymorphisms in relation to PCA risk, we used TaqMan allelic discrimination assays along with a multi-faceted statistical strategy involving conventional and advanced statistical methodologies (e.g., Multifactor Dimensionality Reduction and Interaction Graphs). Genetic profiles collected from 873 men of African-descent (208 cases and 665 controls) were utilized to systematically evaluate the single and joint modifying effects of GSTM1 and GSTT1 gene deletions, GSTP1 105 Val and cigarette smoking on PCA risk. Results We observed a moderately significant association between risk among men possessing at least one variant GSTP1 105 Val allele (OR = 1.56; 95%CI = 0.95-2.58; p = 0.049), which was confirmed by MDR permutation testing (p = 0.001). We did not observe any significant single gene effects among GSTM1 (OR = 1.08; 95%CI = 0.65-1.82; p = 0.718) and GSTT1 (OR = 1.15; 95%CI = 0.66-2.02; p = 0.622) on PCA risk among all subjects. Although the GSTM1-GSTP1 pairwise combination was selected as the best two factor LR and MDR models (p = 0.01), assessment of the hierarchical entropy graph suggested that the observed synergistic effect was primarily driven by the GSTP1 Val marker. Notably, the GSTM1-GSTP1 axis did not provide additional information gain when compared to either loci alone based on a hierarchical entropy algorithm and graph. Smoking status did not significantly modify the relationship between the GST SNPs and PCA. Conclusion A moderately significant association was observed between PCA risk and men possessing at least one variant GSTP1 105 Val allele (p = 0.049) among men of African descent. We also observed a 2.1-fold increase in PCA risk associated with men possessing the GSTP1 (Val/Val) and GSTM1 (*1/*1 + *1/*0) alleles. MDR analysis validated these findings; detecting GSTP1 105 Val (p = 0.001) as the best single factor for predicting PCA risk. Our findings emphasize the importance of utilizing a combination of traditional and advanced statistical tools to identify and validate single gene and multi-locus interactions in relation to cancer susceptibility. PMID:19917083

Imaging of prostate cancer with PET/CT using 18F-Fluorocholine

PubMed Central

Vali, Reza; Loidl, Wolfgang; Pirich, Christian; Langesteger, Werner; Beheshti, Mohsen

2015-01-01

While 18F-Fluorodeoxyglucose (18F-FDG) Positron-Emission Tomography (PET) has limited value in prostate cancer (PCa), it may be useful for specific subgroups of PCa patients with hormone-resistant poorly differentiated cell types. 18F-Fluorocholine (18F-FCH) PET/CT has been increasingly used in primary and recurrent PCa and has been shown to add valuable information. Although there is a correlation between the foci of activity and the areas of malignancy in the prostate gland, the clinical value of 18F-FCH is still controversial for detection of the malignant focus in the prostate. For the T-staging of PCa at diagnosis the value of 18F-FCH is limited. This is probably due to limited resolution of PET system and positive findings in benign prostate diseases. Conversely, 18F-FCH PET/CT is a promising imaging modality for the delineation of local and distant nodal recurrence and bone metastases and is poised to have an impact on therapy management. In this review, recent studies of 18F-FCH PET/CT in PCa are summarized. PMID:25973332

Prostate cancer and polymorphism D85Y in gene for dihydrotestosterone degrading enzyme UGT2B15: Frequency of DD homozygotes increases with Gleason Score.

PubMed

Hajdinjak, Tine; Zagradisnik, Boris

2004-06-01

Although, a functional rationale for influence of polymorphism D85Y in gene UGT2B15 on prostate cancer (PCa) exists (different V(max) of enzyme), conflicting results have been reported. DNA from 178 controls and 206 PCa patients with known Gleason score were genotyped using a newly developed RFLP assay, which allowed the detection of both alleles in an individual after single PCR amplification. 16% DD, 52% DY; PCa patients: 23% DD, 49% DY. Subgroups of PCa: well differentiated: 11% DD, 37% DY; moderately differentiated: 22% DD, 50% DY; poorly differentiated: 34% DD, 50% DY. Correlation was confirmed between Gleason score and number of D alleles (P = 0.018) and persisted after age adjustment. When comparing controls to patients with a Gleason score of 7 or more, difference for the frequency of homozygosity DD was significant between the groups (P = 0.032, OR = 2.04). Polymorphism D85Y in gene UGT2B15 correlates with differentiation of PCa. Copyright 2004 Wiley-Liss, Inc.

Novel Multiplex MethyLight Protocol for Detection of DNA Methylation in Patient Tissues and Bodily Fluids

PubMed Central

Olkhov-Mitsel, Ekaterina; Zdravic, Darko; Kron, Ken; van der Kwast, Theodorus; Fleshner, Neil; Bapat, Bharati

2014-01-01

Aberrant DNA methylation is a hallmark of cancer and is an important potential biomarker. Particularly, combined analysis of a panel of hypermethylated genes shows the most promising clinical performance. Herein, we developed, optimized and standardized a multiplex MethyLight assay to simultaneously detect hypermethylation of APC, HOXD3 and TGFB2 in DNA extracted from prostate cancer (PCa) cell lines, archival tissue specimens, and urine samples. We established that the assay is capable of discriminating between fully methylated and unmethylated alleles with 100% specificity and demonstrated the assay as highly accurate and reproducible as the singleplex approach. For proof of principle, we analyzed the methylation status of these genes in tissue and urine samples of PCa patients as well as PCa-free controls. These data show that the multiplex MethyLight assay offers a significant advantage when working with limited quantities of DNA and has potential applications in research and clinical settings. PMID:24651255

3D non-rigid surface-based MR-TRUS registration for image-guided prostate biopsy

NASA Astrophysics Data System (ADS)

Sun, Yue; Qiu, Wu; Romagnoli, Cesare; Fenster, Aaron

2014-03-01

Two dimensional (2D) transrectal ultrasound (TRUS) guided prostate biopsy is the standard approach for definitive diagnosis of prostate cancer (PCa). However, due to the lack of image contrast of prostate tumors needed to clearly visualize early-stage PCa, prostate biopsy often results in false negatives, requiring repeat biopsies. Magnetic Resonance Imaging (MRI) has been considered to be a promising imaging modality for noninvasive identification of PCa, since it can provide a high sensitivity and specificity for the detection of early stage PCa. Our main objective is to develop and validate a registration method of 3D MR-TRUS images, allowing generation of volumetric 3D maps of targets identified in 3D MR images to be biopsied using 3D TRUS images. Our registration method first makes use of an initial rigid registration of 3D MR images to 3D TRUS images using 6 manually placed approximately corresponding landmarks in each image. Following the manual initialization, two prostate surfaces are segmented from 3D MR and TRUS images and then non-rigidly registered using a thin-plate spline (TPS) algorithm. The registration accuracy was evaluated using 4 patient images by measuring target registration error (TRE) of manually identified corresponding intrinsic fiducials (calcifications and/or cysts) in the prostates. Experimental results show that the proposed method yielded an overall mean TRE of 2.05 mm, which is favorably comparable to a clinical requirement for an error of less than 2.5 mm.

Analysis of the principal component algorithm in phase-shifting interferometry.

PubMed

Vargas, J; Quiroga, J Antonio; Belenguer, T

2011-06-15

We recently presented a new asynchronous demodulation method for phase-sampling interferometry. The method is based in the principal component analysis (PCA) technique. In the former work, the PCA method was derived heuristically. In this work, we present an in-depth analysis of the PCA demodulation method.

RXTE Detection of the Spin Period of Swift J1822.3-1606

NASA Astrophysics Data System (ADS)

Gogus, Ersin; Kouveliotou, Chryssa; Strohmayer, Tod

2011-07-01

RXTE/PCA observed the new source, Swift J1822.3-1606 (Cummings et al. GCN Circ. 12159) on 2011 July 16, for 6.7 ks. We performed a timing analysis on the barycentered data and detected a coherent pulsation at 0.1185149(2) Hz corresponding to 8.4377585 s. Pulsations are clearly visible in the PCA light curve. The peak-to-peak pulsed amplitude in the 2-10 keV band is 0.41. This pulsed fraction is highly unlikely from an SGR source, and very reminiscent of the outburst onset of Swift J1626.6-5156 (Palmer et al.

Physical activity in relation to risk of prostate cancer: a systematic review and meta-analysis.

PubMed

Benke, I N; Leitzmann, M F; Behrens, G; Schmid, D

2018-05-01

Prostate cancer (PCa) is one of the most common cancers among men, yet little is known about its modifiable risk and protective factors. This study aims to quantitatively summarize observational studies relating physical activity (PA) to PCa incidence and mortality. Published articles pertaining to PA and PCa incidence and mortality were retrieved in July 2017 using the Medline and EMBASE databases. The literature review yielded 48 cohort studies and 24 case-control studies with a total of 151 748 PCa cases. The mean age of the study participants at baseline was 61 years. In random-effects models, comparing the highest versus the lowest level of overall PA showed a summary relative risk (RR) estimate for total PCa incidence close to the null [RR = 0.99, 95% confidence interval (CI) = 0.94-1.04]. The corresponding RRs for advanced and non-advanced PCa were 0.92 (95% CI = 0.80-1.06) and 0.95 (95% CI = 0.85-1.07), respectively. We noted a statistically significant inverse association between long-term occupational activity and total PCa (RR = 0.83, 95% CI = 0.71-0.98, n studies = 13), although that finding became statistically non-significant when individual studies were removed from the analysis. When evaluated by cancer subtype, an inverse association with long-term occupational activity was noted for non-advanced/non-aggressive PCa (RR = 0.51, 95% CI = 0.37-0.71, n studies = 2) and regular recreational activity was inversely related to advanced/aggressive PCa (RR = 0.75, 95% CI = 0.60-0.95, n studies = 2), although these observations are based on a low number of studies. Moreover, PA after diagnosis was related to reduced risk of PCa mortality among survivors of PCa (summary RR based on four studies = 0.69, 95% CI = 0.55-0.85). Whether PA protects against PCa remains elusive. Further investigation taking into account the complex clinical and pathologic nature of PCa is needed to clarify the PA and PCa incidence relation. Moreover, future studies are needed to confirm whether PA after diagnosis reduces risk of PCa mortality.

Combined serum and EPS-urine proteomic analysis using iTRAQ technology for discovery of potential prostate cancer biomarkers.

PubMed

Zhang, Mo; Chen, Lizhu; Yuan, Zhengwei; Yang, Zeyu; Li, Yue; Shan, Liping; Yin, Bo; Fei, Xiang; Miao, Jianing; Song, Yongsheng

2016-11-01

Prostate cancer (PCa) is one of the most common malignant tumors and a major cause of cancer-related death for men worldwide. The aim of our study was to identify potential non-invasive serum and expressed prostatic secretion (EPS)-urine biomarkers for accurate diagnosis of PCa. Here, we performed a combined isobaric tags for relative and absolute quantification (iTRAQ) proteomic analysis to compare protein profiles using pooled serum and EPS-urine samples from 4 groups of patients: benign prostate hyperplasia (BPH), high grade prostatic intraepithelial neoplasia (HGPIN), localized PCa and metastatic PCa. The differentially expressed proteins were rigorously selected and further validated in a large and independent cohort using classical ELISA and Western blot assays. Finally, we established a multiplex biomarker panel consisting of 3 proteins (serum PF4V1, PSA, and urinary CRISP3) with an excellent diagnostic capacity to differentiate PCa from BPH [area under the receiver operating characteristic curve (AUC) of 0.941], which showed an evidently greater discriminatory ability than PSA alone (AUC, 0.757) (P<0.001). Importantly, even when PSA level was in the gray zone (4-10 ng/mL), a combination of PF4V1 and CRISP3 could achieve a relatively high diagnostic efficacy (AUC, 0.895). Furthermore, their combination also had the potential to distinguish PCa from HGPIN (AUC, 0.934). Our results demonstrated that the combined application of serum and EPS-urine biomarkers can improve the diagnosis of PCa and provide a new prospect for non-invasive PCa detection.

Recognizing different tissues in human fetal femur cartilage by label-free Raman microspectroscopy

NASA Astrophysics Data System (ADS)

Kunstar, Aliz; Leijten, Jeroen; van Leuveren, Stefan; Hilderink, Janneke; Otto, Cees; van Blitterswijk, Clemens A.; Karperien, Marcel; van Apeldoorn, Aart A.

2012-11-01

Traditionally, the composition of bone and cartilage is determined by standard histological methods. We used Raman microscopy, which provides a molecular "fingerprint" of the investigated sample, to detect differences between the zones in human fetal femur cartilage without the need for additional staining or labeling. Raman area scans were made from the (pre)articular cartilage, resting, proliferative, and hypertrophic zones of growth plate and endochondral bone within human fetal femora. Multivariate data analysis was performed on Raman spectral datasets to construct cluster images with corresponding cluster averages. Cluster analysis resulted in detection of individual chondrocyte spectra that could be separated from cartilage extracellular matrix (ECM) spectra and was verified by comparing cluster images with intensity-based Raman images for the deoxyribonucleic acid/ribonucleic acid (DNA/RNA) band. Specific dendrograms were created using Ward's clustering method, and principal component analysis (PCA) was performed with the separated and averaged Raman spectra of cells and ECM of all measured zones. Overall (dis)similarities between measured zones were effectively visualized on the dendrograms and main spectral differences were revealed by PCA allowing for label-free detection of individual cartilaginous zones and for label-free evaluation of proper cartilaginous matrix formation for future tissue engineering and clinical purposes.

Relationships between serum PSA levels, Gleason scores and results of 68Ga-PSMAPET/CT in patients with recurrent prostate cancer.

PubMed

Sanli, Yasemin; Kuyumcu, Serkan; Sanli, Oner; Buyukkaya, Fikret; İribaş, Ayça; Alcin, Goksel; Darendeliler, Emin; Ozluk, Yasemin; Yildiz, Sevda Ozel; Turkmen, Cüneyt

2017-11-01

To investigate the relationship between serum PSA level, Gleason score of PCa and the outcomes of Ga 68 -PSMA PET/CT in patients with recurrent PCa. A total of 109 consecutive patients (median age 71 years; range 48-89 years) who had PSA recurrence after RP and/or hormonotherapy and/or radiotherapy were included in this study. Local recurrences, lymph node metastasis (pelvic, abdominal and/or supradiaphragmatic), bone metastases (oligometastatic/multimetastatic) and other metastatic sites (lung, liver, brain, etc) were documented. In 91(83.4%) patients at least one lesion characteristic for PCa was detected by 68 Ga-PSMA PET/CT. The median serum total PSA (tPSA) was 6.5 (0.2-640) ng/ml.There was a significant difference between 68 Ga-PSMA PET/CT positive and negative patients in terms of serum total PSA value. No statistical significance was found between positive and negative 68 Ga-PSMA PET/CT findings in terms of Gleason score. Local recurrence was detected in 56 patients. whereas lymph node metastases were demonstrated in 46 patients. Pelvic nodal disease was the most frequent presentation followed by abdominal and supradiaphragmaticnodal involvement. Bone metastases [oligometastasis, (n = 20); multimetastasis, (n = 35)⦌ were also detected in 55 patients. In the ROC analysis for the study cohort, the optimal cut-off value of total serum PSA was determined as 0.67 ng/ml for distinguishing between positive and negative 68 Ga-PSMA PET/CT images, with an area under curve of 0.952 (95% CI 0.911-0.993). 68 Ga-PSMA PET/CT was found to be an effective tool for the detection of recurrent PCa. Even though no relationship was detected between the GS and 68 Ga-PSMA PET/CT findings, serum total PSA values may be used for estimating the likelihood of positive 68 Ga-PSMA PET/CT results.

Why and Where do We Miss Significant Prostate Cancer with Multi-parametric Magnetic Resonance Imaging followed by Magnetic Resonance-guided and Transrectal Ultrasound-guided Biopsy in Biopsy-naïve Men?

PubMed

Schouten, Martijn G; van der Leest, Marloes; Pokorny, Morgan; Hoogenboom, Martijn; Barentsz, Jelle O; Thompson, Les C; Fütterer, Jurgen J

2017-06-01

Knowledge of significant prostate (sPCa) locations being missed with magnetic resonance (MR)- and transrectal ultrasound (TRUS)-guided biopsy (Bx) may help to improve these techniques. To identify the location of sPCa lesions being missed with MR- and TRUS-Bx. In a referral center, 223 consecutive Bx-naive men with elevated prostate specific antigen level and/or abnormal digital rectal examination were included. Histopathologically-proven cancer locations, Gleason score, and tumor length were determined. All patients underwent multi-parametric MRI and 12-core systematic TRUS-Bx. MR-Bx was performed in all patients with suspicion of PCa on multi-parametric MRI (n=142). Cancer locations were compared between MR- and TRUS-Bx. Proportions were expressed as percentages, and the corresponding 95% confidence intervals were calculated. In total, 191 lesions were found in 108 patients with sPCa. From these lesion 74% (141/191) were defined as sPCa on either MR- or TRUS-Bx. MR-Bx detected 74% (105/141) of these lesions and 61% (86/141) with TRUS-Bx. TRUS-Bx detected more lesions compared with MR-Bx (140 vs 109). However, these lesions were often low risk (39%). Significant lesions missed with MR-Bx most often had involvement of dorsolateral (58%) and apical (37%) segments and missed segments with TRUS-Bx were located anteriorly (79%), anterior midprostate (50%), and anterior apex (23%). Both techniques have difficulties in detecting apical lesions. MR-Bx most often missed cancer with involvement of the dorsolateral part (58%) and TRUS-Bx with involvement of the anterior part (79%). Both biopsy techniques miss cancer in specific locations within the prostate. Identification of these lesions may help to improve these techniques. Copyright © 2016 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Consensus statement on definition, diagnosis, and management of high-risk prostate cancer patients on behalf of the Spanish Groups of Uro-Oncology Societies URONCOR, GUO, and SOGUG.

PubMed

Henríquez, I; Rodríguez-Antolín, A; Cassinello, J; Gonzalez San Segundo, C; Unda, M; Gallardo, E; López-Torrecilla, J; Juarez, A; Arranz, J

2018-03-01

Prostate cancer (PCa) is the most prevalent malignancy in men and the second cause of mortality in industrialized countries. Based on Spanish Register of PCa, the incidence of high-risk PCa is 29%, approximately. In spite of the evidence-based beneficial effect of radiotherapy and androgen deprivation therapy in high-risk PCa, these patients (pts) are still a therapeutic challenge for all specialists involved, in part due to the absence of comparative studies to establish which of the present disposable treatments offer better results. Nowadays, high-risk PCa definition is not well consensual through the published oncology guides. Clinical stage, tumour grade, and number of risk factors are relevant to be considered on PCa prognosis. However, these factors are susceptible to change depending on when surgical or radiation therapy is considered to be the treatment of choice. Other factors, such as reference pathologist, different diagnosis biopsy schedules, surgical or radiotherapy techniques, adjuvant treatments, biochemical failures, and follow-up, make it difficult to compare the results between different therapeutic options. This article reviews important issues concerning high-risk PCa. URONCOR, GUO, and SOGUG on behalf of the Spanish Groups of Uro-Oncology Societies have reached a consensus addressing a practical recommendation on definition, diagnosis, and management of high-risk PCa.

Risk of Localized and Advanced Prostate Cancer Among Immigrants Versus Native-Born Swedish Men: A nation-wide, population-based study

PubMed Central

Loeb, Stacy; Drevin, Linda; Robinson, David; Holmberg, Erik; Carlsson, Sigrid; Lambe, Mats; Stattin, Pär

2016-01-01

Purpose Prostate cancer (PCa) incidence and prognosis vary geographically. We examined possible differences in PCa risk by clinical risk category between native-born and immigrant populations in Sweden. Our hypothesis was that lower PSA-testing uptake among foreign-born men would result in lower rates of localized disease, and similar or higher risk of metastatic disease. Methods Using the Prostate Cancer database Sweden (PCBaSe), we identified 117,328 men with PCa diagnosed from 1991–2008, of which 8,332 were foreign-born. For each case, 5 cancer-free matched controls were randomly selected from the population register. Conditional logistic regression was used to compare low-risk, intermediate-risk, high-risk, regionally metastatic, and distant metastatic PCa based upon region of origin. Results Across all risk categories, immigrants had significantly lower PCa risk than native-born Swedish men, except North Americans and Northern Europeans. The lowest PCa risk was observed in men from the Middle East, Southern Europe and Asia. Multivariable adjustment for socioeconomic factors and comorbidities did not materially change risk estimates. Older age at immigration and more recent arrival in Sweden were associated with lower PCa risk. Non-native men were less likely to be diagnosed with PCa through PSA-testing during a health check-up. Conclusions The risk for all stages of PCa was lower among first-generation immigrants to Sweden compared to native-born men. Older age at immigration and more recent immigration were associated with particularly low risks. Patterns of PSA testing appeared to only partly explain the differences in PCa risk, since immigrant men also had a lower risk of metastatic disease. PMID:23266834

Relative importance of habitat filtering and limiting similarity on species assemblages of alpine and subalpine plant communities.

PubMed

Takahashi, Koichi; Tanaka, Saeka

2016-11-01

This study examined how habitat filtering and limiting similarity affect species assemblages of alpine and subalpine plant communities along a slope gradient on Mt. Norikura in central Japan. Plant traits (plant height, individual leaf area, specific leaf area (SLA), leaf linearity, leaf nitrogen and chlorophyll concentrations) and abiotic environmental factors (elevation, slope inclination, ground surface texture, soil water, soil pH, soil nutrient concentrations of NH 4 -N and NO 3 -N) were examined. The metrics of variance, range, kurtosis and the standard deviation of neighbor distance divided by the range of traits present (SDNDr) were calculated for each plant trait to measure trait distribution patterns. Limiting similarity was detected only for chlorophyll concentration. By contrast, habitat filtering was detected for individual leaf area, SLA, leaf linearity, chlorophyll concentration. Abiotic environmental factors were summarized by the principal component analysis (PCA). The first PCA axis positively correlated with elevation and soil pH, and negatively correlated with sand cover, soil water, NH 4 -N and NO 3 -N concentrations. High values of the first PCA axis represent the wind-exposed upper slope with lower soil moisture and nutrient availabilities. Plant traits changed along the first PCA axis. Leaf area, SLA and chlorophyll concentration decreased, and leaf linearity increased with the first PCA axis. This study showed that the species assemblage of alpine and subalpine plants was determined mainly by habitat filtering, indicating that abiotic environmental factors are more important for species assemblage than interspecific competition. Therefore, only species adapting to abiotic environments can distribute to these environments.

Prostate cancer molecular detection in plasma samples by glutathione S-transferase P1 (GSTP1) methylation analysis.

PubMed

Dumache, Raluca; Puiu, Maria; Motoc, Marilena; Vernic, Corina; Dumitrascu, Victor

2014-01-01

Prostate cancer (PCa) represents the most commonly diagnosed type of malignancy among men in Western European countries and the second cause of cancer-related deaths among men worldwide. Methylation of the CpG island has an important role in prostate carcinogenesis and progression. The purpose of the study was to analyse the diagnostic value of aberrant promoter hypermethylation of the gene for glutathione S-transferase P1 (GSTP1) in plasma DNA to discriminate between prostate cancer (PCa) and benign prostatic hyperplasia (BPH) patients by minimally invasive methods. Aberrant promoter hypermethylation was investigated in DNA isolated from plasma samples of 31 patients with diagnostic of PCa and 44 cancer-free males (control subjects). Extracted genomic DNA was bisulfite treated and analyzed using methylation-specific polymerase chain reaction (MS-PCR) technique. Hypermethylation of the GSTP1 gene was detected in plasma samples from 27 of 31 (92.86%) patients with PCa. Genomic DNA from plasma samples from the 44 controls without genitourinary cancer revealed promoter hypermethylation of GSTP1 gene in 3 (10.6%) of the 44 patients. Receiver operating curve (ROC) included clinico-pathological parameters such as: serum PSA levels, pathological stage, Gleason score, hypermethylation status of GSTP1 gene, and it gave a predictive accuracy of 93% with a sensitivity and specificity of 95% and 87%, respectively. In this study, we have evaluated the ability of GSTP1 gene to discriminate between PCa and BPH patients in genomic DNA from plasma samples by non-invasive methods.

A novel urinary long non-coding RNA transcript improves diagnostic accuracy in patients undergoing prostate biopsy.

PubMed

Zhang, Wei; Ren, Shan-Cheng; Shi, Xiao-Lei; Liu, Ya-Wei; Zhu, Ya-Sheng; Jing, Tai-Le; Wang, Fu-Bo; Chen, Rui; Xu, Chuan-Liang; Wang, Hui-Qing; Wang, Hai-Feng; Wang, Yan; Liu, Bing; Li, Yao-Ming; Fang, Zi-Yu; Guo, Fei; Lu, Xin; Shen, Dan; Gao, Xu; Hou, Jian-Guo; Sun, Ying-Hao

2015-05-01

Long non-coding RNA (LncRNA) PCA3 has been a well-established urine biomarker for the detection of prostate cancer (PCa). Our previous study showed a novel LncRNA FR0348383 is up-regulated in over 70% of PCa compared with matched benign tissues. The aim of this study was to evaluate the diagnostic value of urinary FR0348383 for men undergoing prostate biopsy due to elevated PSA (PSA > 4.0 ng/ml) and/or abnormal digital rectal examination (DRE). Post-DRE first-catch urine specimens prior to prostate biopsies were prospectively collected. After the whole transcriptome amplification, quantitative real time polymerase chain reaction was applied to quantify urine FR0348383 and PSA levels. The FR0348383 score was calculated as the ratio of PSA and FR0348383 mRNA (PSA mRNA/FR0348383 mRNA × 1000). The diagnostic value of FR0348383 score was evaluated by logistic regression and decision curve analysis. 213 cases with urine samples containing sufficient mRNA were included, 94 cases had serum PSA level 4.0-10.0 ng/ml. PCa was identified in 72 cases. An increasing FR0348383 score was correlated with an increasing probability of a positive biopsy (P < 0.001). Multivariable logistic analysis indicated FR0348383 score (P < 0.001), PSA (P = 0.004), age (P = 0.007), prostate volume (P < 0.001) were independent predictors of PCa. ROC analysis demonstrated FR0348383 score outperformed PSA, %free PSA, and PSA Density in the prediction of PCa in the subgroup of patients with grey area PSA (AUC: 0.815 vs. 0.562 vs. 0.599 vs. 0.645). When using a probability threshold of 30% in the grey zone cohort, The FR0348383 score would save 52.0% of avoidable biopsies without missing any high grade cancers. FR0348383 transcript in post-DRE urine may be a novel biomarker for detection of PCa with great diagnostic value, especially in the grey zone cohort. The application of FR0348383 score in clinical practice might avoid unnecessary prostate biopsies and increase the specificity of PCa diagnosis. © 2015 Wiley Periodicals, Inc.

Image restoration for three-dimensional fluorescence microscopy using an orthonormal basis for efficient representation of depth-variant point-spread functions

PubMed Central

Patwary, Nurmohammed; Preza, Chrysanthe

2015-01-01

A depth-variant (DV) image restoration algorithm for wide field fluorescence microscopy, using an orthonormal basis decomposition of DV point-spread functions (PSFs), is investigated in this study. The efficient PSF representation is based on a previously developed principal component analysis (PCA), which is computationally intensive. We present an approach developed to reduce the number of DV PSFs required for the PCA computation, thereby making the PCA-based approach computationally tractable for thick samples. Restoration results from both synthetic and experimental images show consistency and that the proposed algorithm addresses efficiently depth-induced aberration using a small number of principal components. Comparison of the PCA-based algorithm with a previously-developed strata-based DV restoration algorithm demonstrates that the proposed method improves performance by 50% in terms of accuracy and simultaneously reduces the processing time by 64% using comparable computational resources. PMID:26504634

[Determination of phenazine-1-carboxylic acid in anti-fungal agent M18 by high performance liquid chromatography].

PubMed

Zhu, D H; Zhu, X D; Xu, Y Q

2001-11-01

A reversed-phase HPLC method for the determination of phenazine-1-carboxylic acid (PCA) in antifungal agent M18 is established. The mobile phase was a mixture of MeOH-5 mmol/L phosphate buffer (pH 5.0) (60:40, volume ratio). The flow rate was 1.0 mL/min, and the detection wavelength was 248 nm. The linear range and detectable limit were 50 mg/L-500 mg/L and 30 mg/L respectively. The recovery was 97.53% and RSD was 1.5%. The method of PCA extraction and detection has proven to be much faster, simpler, more sensitive, accurate and reproducible than those reported already. The assay results can be used as a very important criterion for large-scale production.

Prostate health index significantly reduced unnecessary prostate biopsies in patients with PSA 2-10 ng/mL and PSA >10 ng/mL: Results from a Multicenter Study in China.

PubMed

Na, Rong; Ye, Dingwei; Qi, Jun; Liu, Fang; Helfand, Brian T; Brendler, Charles B; Conran, Carly A; Packiam, Vignesh; Gong, Jian; Wu, Yishuo; Zheng, Siqun L; Mo, Zengnan; Ding, Qiang; Sun, Yinghao; Xu, Jianfeng

2017-08-01

The performance of prostate health index (phi) in predicting prostate biopsy outcomes has been well established for patients with prostate-specific antigen (PSA) values between 2 and 10 ng/mL. However, the performance of phi remains unknown in patients with PSA >10 ng/mL, the vast majority in Chinese biopsy patients. We aimed to assess the ability of phi to predict prostate cancer (PCa) and high-grade disease (Gleason Score ≥7) on biopsy in a Chinese population. This is a prospective, observational, multi-center study of consecutive patients who underwent a transrectal ultrasound guided prostate biopsy at four hospitals in Shanghai, China from August 2013 to December 2014. In the cohort of 1538 patients, the detection rate of PCa was 40.2%. phi had a significantly better predictive performance for PCa than total PSA (tPSA). The areas under the receiver operating characteristic curve (AUC) were 0.90 and 0.79 for phi and tPSA, respectively, P < 0.0001. A considerable proportion of patients in the cohort had PSAs >10 ng/mL (N = 838, 54.5%). The detection rates of PCa were 35.9% and 57.7% in patients with tPSA 10.1-20 and 20.1-50 ng/mL, respectively. The AUCs of phi (0.79 and 0.89, for these two groups, respectively) were also significantly higher than tPSA (0.57 and 0.63, respectively), both P < 0.0001. If a phi ≤35 was used as the cutoff, 599/1538 (39%) biopsies could have been avoided at a cost of missing small numbers of PCa patients: 49 (7.93%) PCa patients, including 18 (3.69%) high-grade tumors. Results from this study suggest that phi can be used to predict PCa and high-grade disease in Chinese men with high PSA levels (>10 ng/mL). © 2017 Wiley Periodicals, Inc.

Racial Differences in the Diagnosis and Treatment of Prostate Cancer.

PubMed

Pietro, Giuliano Di; Chornokur, Ganna; Kumar, Nagi B; Davis, Chemar; Park, Jong Y

2016-11-01

Disparities between African American and Caucasian men in prostate cancer (PCa) diagnosis and treatment in the United States have been well established, with significant racial disparities documented at all stages of PCa management, from differences in the type of treatment offered to progression-free survival or death. These disparities appear to be complex in nature, involving biological determinants as well as socioeconomic and cultural aspects. We present a review of the literature on racial disparities in the diagnosis of PCa, treatment, survival, and genetic susceptibility. Significant differences were found among African Americans and whites in the incidence and mortality rates; namely, African Americans are diagnosed with PCa at younger ages than whites and usually with more advanced stages of the disease, and also undergo prostate-specific antigen testing less frequently. However, the determinants of the high rate of incidence and aggressiveness of PCa in African Americans remain unresolved. This pattern can be attributed to socioeconomic status, detection occurring at advanced stages of the disease, biological aggressiveness, family history, and differences in genetic susceptibility. Another risk factor for PCa is obesity. We found many discrepancies regarding treatment, including a tendency for more African American patients to be in watchful waiting than whites. Many factors are responsible for the higher incidence and mortality rates in African Americans. Better screening, improved access to health insurance and clinics, and more homogeneous forms of treatment will contribute to the reduction of disparities between African Americans and white men in PCa incidence and mortality.

Evaluation of Coptidis Rhizoma-Euodiae Fructus couple and Zuojin products based on HPLC fingerprint chromatogram and simultaneous determination of main bioactive constituents.

PubMed

Gao, Xin; Yang, Xiu-Wei; Marriott, Philip J

2013-11-01

Coptidis Rhizoma-Euodiae Fructus couple (CEC) is a classic traditional Chinese medicine preparation consisting of Coptidis Rhizoma and Euodiae Fructus at the ratio of 6:1, and used to treat gastro-intestinal disorders. Alkaloids are the main bioactive component. This research provides comprehensive analysis information for the quality control of CEC. To develop a high-performance liquid chromatography-diode array detection fingerprint for chemical composition characteristics of CEC and its products. The samples were separated with a Gemini C18 column by using gradient elution with water-formic acid (100:0.03) and acetonitrile as mobile phase. Flow rate was 1.0 mL/min and detection wavelength was 250 nm. Similarity analysis and principal component analysis (PCA) were employed to evaluate quality consistencies of analytes. Mean chromatograms and correlation coefficients of analytes were calculated by the software "Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine". Fingerprint chromatogram comparison determined 20 representative general fingerprint peaks, and the fingerprint chromatogram resemblances are all better than 0.988. Consistent results were obtained to show that CEC and its related samples could be successfully divided into three groups. Contribution plots generated by PCA were performed to interpret differences among the sample groups while peaks which significantly contributed to classification were identified. Seven bioactive constituents in the samples were verified by quantitative analysis. The chromatographic fingerprint with similarity evaluation and PCA assay combined with quantification of seven compounds could be utilized as a quality control method for the herbal couple.

Pepper seed variety identification based on visible/near-infrared spectral technology

NASA Astrophysics Data System (ADS)

Li, Cuiling; Wang, Xiu; Meng, Zhijun; Fan, Pengfei; Cai, Jichen

2016-11-01

Pepper is a kind of important fruit vegetable, with the expansion of pepper hybrid planting area, detection of pepper seed purity is especially important. This research used visible/near infrared (VIS/NIR) spectral technology to detect the variety of single pepper seed, and chose hybrid pepper seeds "Zhuo Jiao NO.3", "Zhuo Jiao NO.4" and "Zhuo Jiao NO.5" as research sample. VIS/NIR spectral data of 80 "Zhuo Jiao NO.3", 80 "Zhuo Jiao NO.4" and 80 "Zhuo Jiao NO.5" pepper seeds were collected, and the original spectral data was pretreated with standard normal variable (SNV) transform, first derivative (FD), and Savitzky-Golay (SG) convolution smoothing methods. Principal component analysis (PCA) method was adopted to reduce the dimension of the spectral data and extract principal components, according to the distribution of the first principal component (PC1) along with the second principal component(PC2) in the twodimensional plane, similarly, the distribution of PC1 coupled with the third principal component(PC3), and the distribution of PC2 combined with PC3, distribution areas of three varieties of pepper seeds were divided in each twodimensional plane, and the discriminant accuracy of PCA was tested through observing the distribution area of samples' principal components in validation set. This study combined PCA and linear discriminant analysis (LDA) to identify single pepper seed varieties, results showed that with the FD preprocessing method, the discriminant accuracy of pepper seed varieties was 98% for validation set, it concludes that using VIS/NIR spectral technology is feasible for identification of single pepper seed varieties.

SU-E-I-58: Objective Models of Breast Shape Undergoing Mammography and Tomosynthesis Using Principal Component Analysis.

PubMed

Feng, Ssj; Sechopoulos, I

2012-06-01

To develop an objective model of the shape of the compressed breast undergoing mammographic or tomosynthesis acquisition. Automated thresholding and edge detection was performed on 984 anonymized digital mammograms (492 craniocaudal (CC) view mammograms and 492 medial lateral oblique (MLO) view mammograms), to extract the edge of each breast. Principal Component Analysis (PCA) was performed on these edge vectors to identify a limited set of parameters and eigenvectors that. These parameters and eigenvectors comprise a model that can be used to describe the breast shapes present in acquired mammograms and to generate realistic models of breasts undergoing acquisition. Sample breast shapes were then generated from this model and evaluated. The mammograms in the database were previously acquired for a separate study and authorized for use in further research. The PCA successfully identified two principal components and their corresponding eigenvectors, forming the basis for the breast shape model. The simulated breast shapes generated from the model are reasonable approximations of clinically acquired mammograms. Using PCA, we have obtained models of the compressed breast undergoing mammographic or tomosynthesis acquisition based on objective analysis of a large image database. Up to now, the breast in the CC view has been approximated as a semi-circular tube, while there has been no objectively-obtained model for the MLO view breast shape. Such models can be used for various breast imaging research applications, such as x-ray scatter estimation and correction, dosimetry estimates, and computer-aided detection and diagnosis. © 2012 American Association of Physicists in Medicine.

Contact- and distance-based principal component analysis of protein dynamics.

PubMed

Ernst, Matthias; Sittel, Florian; Stock, Gerhard

2015-12-28

To interpret molecular dynamics simulations of complex systems, systematic dimensionality reduction methods such as principal component analysis (PCA) represent a well-established and popular approach. Apart from Cartesian coordinates, internal coordinates, e.g., backbone dihedral angles or various kinds of distances, may be used as input data in a PCA. Adopting two well-known model problems, folding of villin headpiece and the functional dynamics of BPTI, a systematic study of PCA using distance-based measures is presented which employs distances between Cα-atoms as well as distances between inter-residue contacts including side chains. While this approach seems prohibitive for larger systems due to the quadratic scaling of the number of distances with the size of the molecule, it is shown that it is sufficient (and sometimes even better) to include only relatively few selected distances in the analysis. The quality of the PCA is assessed by considering the resolution of the resulting free energy landscape (to identify metastable conformational states and barriers) and the decay behavior of the corresponding autocorrelation functions (to test the time scale separation of the PCA). By comparing results obtained with distance-based, dihedral angle, and Cartesian coordinates, the study shows that the choice of input variables may drastically influence the outcome of a PCA.

Contact- and distance-based principal component analysis of protein dynamics

NASA Astrophysics Data System (ADS)

Ernst, Matthias; Sittel, Florian; Stock, Gerhard

2015-12-01

To interpret molecular dynamics simulations of complex systems, systematic dimensionality reduction methods such as principal component analysis (PCA) represent a well-established and popular approach. Apart from Cartesian coordinates, internal coordinates, e.g., backbone dihedral angles or various kinds of distances, may be used as input data in a PCA. Adopting two well-known model problems, folding of villin headpiece and the functional dynamics of BPTI, a systematic study of PCA using distance-based measures is presented which employs distances between Cα-atoms as well as distances between inter-residue contacts including side chains. While this approach seems prohibitive for larger systems due to the quadratic scaling of the number of distances with the size of the molecule, it is shown that it is sufficient (and sometimes even better) to include only relatively few selected distances in the analysis. The quality of the PCA is assessed by considering the resolution of the resulting free energy landscape (to identify metastable conformational states and barriers) and the decay behavior of the corresponding autocorrelation functions (to test the time scale separation of the PCA). By comparing results obtained with distance-based, dihedral angle, and Cartesian coordinates, the study shows that the choice of input variables may drastically influence the outcome of a PCA.

Relevance of prostate cancer in patients with synchronous invasive bladder urothelial carcinoma: a monocentric retrospective analysis.

PubMed

Dell'Atti, Lucio

2015-03-31

We retrospectively reviewed data of patients with incidental prostate cancer (PCa) who underwent radical cystoprostatectomy (RCP) for invasive bladder cancer and we analyzed their features with regard to incidence, pathologic characteristics, clinical significance, and implications for management. Clinical data and pathological features of 64 patients who underwent standard RCP for bladder cancer were included in this study. Besides the urothelial carcinoma of the urinary bladder, the location and tumor volume of the PCa, prostate apex involvement, Gleason score, pathological staging and surgical margins were evaluated. Clinically significant PCa was defined as a tumor with a Gleason 4 or 5 pattern, stage ≥ pT3, lymph node involvement, positive surgical margin or multifocality of three or more lesions. Postoperative follow-up was scheduled every 3 months in the first year, every 6 months in the second and third year, annually thereafter. 11 out of 64 patients (17.2%) who underwent RCP had incidentally diagnosed PCa. 3 cases (27.3%) were diagnosed as significant PCa, while 8 cases (72.7%) were clinically insignificant. The positive surgical margin of PCa was detected in 1 patient with significant disease. The prostate apex involvement was present in 1 patient of the significant PCa group. Median follow-up period was 47.8 ± 29.2 (range 4-79). During the follow-up, biochemical recurrence occurred in 1 patient (9%). Concerning the cancer specific survival there was no statistical significance (P = 0.326) between the clinically significant and clinical insignificant cancer group. In line with published studies, incidental PCa does not impact on the prognosis of bladder cancer of patients undergoing RCP.

Detecting most influencing courses on students grades using block PCA

NASA Astrophysics Data System (ADS)

Othman, Osama H.; Gebril, Rami Salah

2014-12-01

One of the modern solutions adopted in dealing with the problem of large number of variables in statistical analyses is the Block Principal Component Analysis (Block PCA). This modified technique can be used to reduce the vertical dimension (variables) of the data matrix Xn×p by selecting a smaller number of variables, (say m) containing most of the statistical information. These selected variables can then be employed in further investigations and analyses. Block PCA is an adapted multistage technique of the original PCA. It involves the application of Cluster Analysis (CA) and variable selection throughout sub principal components scores (PC's). The application of Block PCA in this paper is a modified version of the original work of Liu et al (2002). The main objective was to apply PCA on each group of variables, (established using cluster analysis), instead of involving the whole large pack of variables which was proved to be unreliable. In this work, the Block PCA is used to reduce the size of a huge data matrix ((n = 41) × (p = 251)) consisting of Grade Point Average (GPA) of the students in 251 courses (variables) in the faculty of science in Benghazi University. In other words, we are constructing a smaller analytical data matrix of the GPA's of the students with less variables containing most variation (statistical information) in the original database. By applying the Block PCA, (12) courses were found to `absorb' most of the variation or influence from the original data matrix, and hence worth to be keep for future statistical exploring and analytical studies. In addition, the course Independent Study (Math.) was found to be the most influencing course on students GPA among the 12 selected courses.

Reduced TH expression and α-synuclein accumulation contribute towards nigrostriatal dysfunction in experimental hepatic encephalopathy.

PubMed

Suárez, Isabel; Bodega, Guillermo; Rubio, Miguel; Fernández, Benjamín

2017-01-01

The present work examines α-synuclein expression in the nigrostriatal system of a rat chronic hepatic encephalopathy model induced by portacaval anastomosis (PCA). There is evidence that dopaminergic dysfunction in disease conditions is strongly associated with such expression. Possible relationships among dopaminergic neurons, astroglial cells and α-synuclein expression were sought. Brain tissue samples from rats at 1 and 6 months post-PCA, and controls, were analysed immunohistochemically using antibodies against tyrosine hydroxylase (TH), α-synuclein, glial fibrillary acidic protein (GFAP) and ubiquitin (Ub). In the control rats, TH immunoreactivity was detected in the neuronal cell bodies and processes in the substantia nigra pars compacta (SNc). A dense TH-positive network of neurons was also seen in the striatum. In the PCA-exposed rats, however, a reduction in TH-positive neurons was seen at both 1 and 6 months in the SNc, as well as a reduction in TH-positive fibres in the striatum. This was coincident with the appearance of α-synuclein-immunoreactive neurons in the SNc; some of the TH-positive neurons also showed α-synuclein immunoreactivity. In addition, α-synuclein accumulation was seen in the SNc and striatum at both 1 and 6 months post-PCA, whereas α-synuclein was only mildly expressed in the nigrostriatal pathway of the controls. Astrogliosis was also seen following PCA, as revealed by increased GFAP expression from 1 month to 6 months post-PCA in both the SN and striatum. The astroglial activation level in the SN paralleled the reduced neuronal expression of TH throughout PCA exposure. α-synuclein accumulation following PCA may induce dopaminergic dysfunction via the downregulation of TH, as well as astroglial activation.

E-selectin ligand-1 controls circulating prostate cancer cell rolling/adhesion and metastasis

PubMed Central

Yasmin-Karim, Sayeda; King, Michael R.; Messing, Edward M.; Lee, Yi-Fen

2014-01-01

Circulating prostate cancer (PCa) cells preferentially roll and adhere on bone marrow vascular endothelial cells, where abundant E-selectin and stromal cell-derived factor 1 (SDF-1) are expressed, subsequently initiating a cascade of activation events that eventually lead to the development of metastases. To elucidate the roles of circulating PCa cells' rolling and adhesion behaviors in cancer metastases, we applied a dynamic cylindrical flow-based microchannel device that is coated with E-selectin and SDF-1, mimicking capillary endothelium. Using this device we captured a small fraction of rolling PCa cells. These rolling cells display higher static adhesion ability, more aggressive cancer phenotypes and stem-like properties. Importantly, mice received rolling PCa cells, but not floating PCa cells, developed cancer metastases. Genes coding for E-selectin ligands and genes associated with cancer stem cells and metastasis were elevated in rolling PCa cells. Knock down of E-selectin ligand 1(ESL-1), significantly impaired PCa cells' rolling capacity and reduced cancer aggressiveness. Moreover, ESL-1 activates RAS and MAP kinase signal cascade, consequently inducing the downstream targets. In summary, circulating PCa cells' rolling capacity contributes to PCa metastasis, and that is in part controlled by ESL-1. PMID:25301730

Sensor Failure Detection of FASSIP System using Principal Component Analysis

NASA Astrophysics Data System (ADS)

Sudarno; Juarsa, Mulya; Santosa, Kussigit; Deswandri; Sunaryo, Geni Rina

2018-02-01

In the nuclear reactor accident of Fukushima Daiichi in Japan, the damages of core and pressure vessel were caused by the failure of its active cooling system (diesel generator was inundated by tsunami). Thus researches on passive cooling system for Nuclear Power Plant are performed to improve the safety aspects of nuclear reactors. The FASSIP system (Passive System Simulation Facility) is an installation used to study the characteristics of passive cooling systems at nuclear power plants. The accuracy of sensor measurement of FASSIP system is essential, because as the basis for determining the characteristics of a passive cooling system. In this research, a sensor failure detection method for FASSIP system is developed, so the indication of sensor failures can be detected early. The method used is Principal Component Analysis (PCA) to reduce the dimension of the sensor, with the Squarred Prediction Error (SPE) and statistic Hotteling criteria for detecting sensor failure indication. The results shows that PCA method is capable to detect the occurrence of a failure at any sensor.

The influence of stigma on the quality of life for prostate cancer survivors.

PubMed

Wood, Andrew W; Barden, Sejal; Terk, Mitchell; Cesaretti, Jamie

2017-01-01

The purpose of the present study was to investigate the influence of stigma on prostate cancer (PCa) survivors' quality of life. Stigma for lung cancer survivors has been the focus of considerable research (Else-Quest & Jackson, 2014); however, gaps remain in understanding the experience of PCa stigma. A cross-sectional correlational study was designed to assess the incidence of PCa stigma and its influence on the quality of life of survivors. Eighty-five PCa survivors were administered survey packets consisting of a stigma measure, a PCa-specific quality of life measure, and a demographic survey during treatment of their disease. A linear regression analysis was conducted with the data received from PCa survivors. Results indicated that PCa stigma has a significant, negative influence on the quality of life for survivors (R 2 = 0.33, F(4, 80) = 11.53, p < 0.001). There were no statistically significant differences in PCa stigma based on demographic variables (e.g., race and age). Implications for physical and mental health practitioners and researchers are discussed.

Motor features in posterior cortical atrophy and their imaging correlates☆

PubMed Central

Ryan, Natalie S.; Shakespeare, Timothy J.; Lehmann, Manja; Keihaninejad, Shiva; Nicholas, Jennifer M.; Leung, Kelvin K.; Fox, Nick C.; Crutch, Sebastian J.

2014-01-01

Posterior cortical atrophy (PCA) is a neurodegenerative syndrome characterized by impaired higher visual processing skills; however, motor features more commonly associated with corticobasal syndrome may also occur. We investigated the frequency and clinical characteristics of motor features in 44 PCA patients and, with 30 controls, conducted voxel-based morphometry, cortical thickness, and subcortical volumetric analyses of their magnetic resonance imaging. Prominent limb rigidity was used to define a PCA-motor subgroup. A total of 30% (13) had PCA-motor; all demonstrating asymmetrical left upper limb rigidity. Limb apraxia was more frequent and asymmetrical in PCA-motor, as was myoclonus. Tremor and alien limb phenomena only occurred in this subgroup. The subgroups did not differ in neuropsychological test performance or apolipoprotein E4 allele frequency. Greater asymmetry of atrophy occurred in PCA-motor, particularly involving right frontoparietal and peri-rolandic cortices, putamen, and thalamus. The 9 patients (including 4 PCA-motor) with pathology or cerebrospinal fluid all showed evidence of Alzheimer's disease. Our data suggest that PCA patients with motor features have greater atrophy of contralateral sensorimotor areas but are still likely to have underlying Alzheimer's disease. PMID:25086839

MindEdit: A P300-based text editor for mobile devices.

PubMed

Elsawy, Amr S; Eldawlatly, Seif; Taher, Mohamed; Aly, Gamal M

2017-01-01

Practical application of Brain-Computer Interfaces (BCIs) requires that the whole BCI system be portable. The mobility of BCI systems involves two aspects: making the electroencephalography (EEG) recording devices portable, and developing software applications with low computational complexity to be able to run on low computational-power devices such as tablets and smartphones. This paper addresses the development of MindEdit; a P300-based text editor for Android-based devices. Given the limited resources of mobile devices and their limited computational power, a novel ensemble classifier is utilized that uses Principal Component Analysis (PCA) features to identify P300 evoked potentials from EEG recordings. PCA computations in the proposed method are channel-based as opposed to concatenating all channels as in traditional feature extraction methods; thus, this method has less computational complexity compared to traditional P300 detection methods. The performance of the method is demonstrated on data recorded from MindEdit on an Android tablet using the Emotiv wireless neuroheadset. Results demonstrate the capability of the introduced PCA ensemble classifier to classify P300 data with maximum average accuracy of 78.37±16.09% for cross-validation data and 77.5±19.69% for online test data using only 10 trials per symbol and a 33-character training dataset. Our analysis indicates that the introduced method outperforms traditional feature extraction methods. For a faster operation of MindEdit, a variable number of trials scheme is introduced that resulted in an online average accuracy of 64.17±19.6% and a maximum bitrate of 6.25bit/min. These results demonstrate the efficacy of using the developed BCI application with mobile devices. Copyright © 2016 Elsevier Ltd. All rights reserved.

A PLSPM-Based Test Statistic for Detecting Gene-Gene Co-Association in Genome-Wide Association Study with Case-Control Design

PubMed Central

Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong

2013-01-01

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods. PMID:23620809

A PLSPM-based test statistic for detecting gene-gene co-association in genome-wide association study with case-control design.

PubMed

Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong

2013-01-01

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods.

Detection of candidate biomarkers of prostate cancer progression in serum: a depletion-free 3D LC/MS quantitative proteomics pilot study.

PubMed

Larkin, S E T; Johnston, H E; Jackson, T R; Jamieson, D G; Roumeliotis, T I; Mockridge, C I; Michael, A; Manousopoulou, A; Papachristou, E K; Brown, M D; Clarke, N W; Pandha, H; Aukim-Hastie, C L; Cragg, M S; Garbis, S D; Townsend, P A

2016-10-25

Prostate cancer (PCa) is the most common male cancer in the United Kingdom and we aimed to identify clinically relevant biomarkers corresponding to stage progression of the disease. We used enhanced proteomic profiling of PCa progression using iTRAQ 3D LC mass spectrometry on high-quality serum samples to identify biomarkers of PCa. We identified >1000 proteins. Following specific inclusion/exclusion criteria we targeted seven proteins of which two were validated by ELISA and six potentially interacted forming an 'interactome' with only a single protein linking each marker. This network also includes accepted cancer markers, such as TNF, STAT3, NF-κB and IL6. Our linked and interrelated biomarker network highlights the potential utility of six of our seven markers as a panel for diagnosing PCa and, critically, in determining the stage of the disease. Our validation analysis of the MS-identified proteins found that SAA alongside KLK3 may improve categorisation of PCa than by KLK3 alone, and that TSR1, although not significant in this model, might also be a clinically relevant biomarker.

Prostate cancer: computer-aided diagnosis on multiparametric MRI

NASA Astrophysics Data System (ADS)

Marin, Laura; Racoceanu, Daniel; Renard Penna, Raphaele; Ezziane, Malek

2017-11-01

Prostate cancer (PCa) is one of the most common cancers in men, being also the second most deadly cancer after lung cancer. There is increasing interest in active surveillance and minimally invasive focal therapies in PCa to avoid morbidities associated with whole gland therapy. Tumor volume represents an essential prognostic factor of PCa and the definition of index lesion volume is critical for appropriate decision making, especially for image guide focal treatment or in case of active surveillance. Multi-parametric Magnetic Resonance Imaging (mp-MRI) is the modality of choice for the detection and the localization of PCa foci. However, little has been published on mp-MRI accuracy in determining PCa volume, especially at 3T. There is insufficient evidence and no consensus to determine which of the methods for measuring volume is optimal. The objective of this study concerns the elaboration of an algorithm for automatic interpretation of mp-MRI. We determine the accuracy of the proposed method by comparing the prostate tumor volume issued from the automated volumetric mp-MRI measurements of the tumoral region, with manual and semi-automated volumetric measurements done by and respectively with radiologists. Information issued from whole mount histopathology is used to validate the whole approach.

Regulators of gene expression as biomarkers for prostate cancer

PubMed Central

Willard, Stacey S; Koochekpour, Shahriar

2012-01-01

Recent technological advancements in gene expression analysis have led to the discovery of a promising new group of prostate cancer (PCa) biomarkers that have the potential to influence diagnosis and the prediction of disease severity. The accumulation of deleterious changes in gene expression is a fundamental mechanism of prostate carcinogenesis. Aberrant gene expression can arise from changes in epigenetic regulation or mutation in the genome affecting either key regulatory elements or gene sequences themselves. At the epigenetic level, a myriad of abnormal histone modifications and changes in DNA methylation are found in PCa patients. In addition, many mutations in the genome have been associated with higher PCa risk. Finally, over- or underexpression of key genes involved in cell cycle regulation, apoptosis, cell adhesion and regulation of transcription has been observed. An interesting group of biomarkers are emerging from these studies which may prove more predictive than the standard prostate specific antigen (PSA) serum test. In this review, we discuss recent results in the field of gene expression analysis in PCa including the most promising biomarkers in the areas of epigenetics, genomics and the transcriptome, some of which are currently under investigation as clinical tests for early detection and better prognostic prediction of PCa. PMID:23226612

Basic visual function and cortical thickness patterns in posterior cortical atrophy.

PubMed

Lehmann, Manja; Barnes, Josephine; Ridgway, Gerard R; Wattam-Bell, John; Warrington, Elizabeth K; Fox, Nick C; Crutch, Sebastian J

2011-09-01

Posterior cortical atrophy (PCA) is characterized by a progressive decline in higher-visual object and space processing, but the extent to which these deficits are underpinned by basic visual impairments is unknown. This study aimed to assess basic and higher-order visual deficits in 21 PCA patients. Basic visual skills including form detection and discrimination, color discrimination, motion coherence, and point localization were measured, and associations and dissociations between specific basic visual functions and measures of higher-order object and space perception were identified. All participants showed impairment in at least one aspect of basic visual processing. However, a number of dissociations between basic visual skills indicated a heterogeneous pattern of visual impairment among the PCA patients. Furthermore, basic visual impairments were associated with particular higher-order object and space perception deficits, but not with nonvisual parietal tasks, suggesting the specific involvement of visual networks in PCA. Cortical thickness analysis revealed trends toward lower cortical thickness in occipitotemporal (ventral) and occipitoparietal (dorsal) regions in patients with visuoperceptual and visuospatial deficits, respectively. However, there was also a lot of overlap in their patterns of cortical thinning. These findings suggest that different presentations of PCA represent points in a continuum of phenotypical variation.

Principal Components Analysis of Triaxial Vibration Data From Helicopter Transmissions

NASA Technical Reports Server (NTRS)

Tumer, Irem Y.; Huff, Edward M.

2001-01-01

Research on the nature of the vibration data collected from helicopter transmissions during flight experiments has led to several crucial observations believed to be responsible for the high rates of false alarms and missed detections in aircraft vibration monitoring systems. This work focuses on one such finding, namely, the need to consider additional sources of information about system vibrations. In this light, helicopter transmission vibration data, collected using triaxial accelerometers, were explored in three different directions, analyzed for content, and then combined using Principal Components Analysis (PCA) to analyze changes in directionality. In this paper, the PCA transformation is applied to 176 test conditions/data sets collected from an OH58C helicopter to derive the overall experiment-wide covariance matrix and its principal eigenvectors. The experiment-wide eigenvectors. are then projected onto the individual test conditions to evaluate changes and similarities in their directionality based on the various experimental factors. The paper will present the foundations of the proposed approach, addressing the question of whether experiment-wide eigenvectors accurately model the vibration modes in individual test conditions. The results will further determine the value of using directionality and triaxial accelerometers for vibration monitoring and anomaly detection.

Occupation, industry, and the risk of prostate cancer: a case-control study in Montréal, Canada.

PubMed

Sauvé, Jean-François; Lavoué, Jérôme; Parent, Marie-Élise

2016-10-21

Age, family history and ancestry are the only recognized risk factors for prostate cancer (PCa) but a role for environmental factors is suspected. Due to the lack of knowledge on the etiological factors for PCa, studies that are both hypothesis-generating and confirmatory are still needed. This study explores relationships between employment, by occupation and industry, and PCa risk. Cases were 1937 men aged ≤75 years with incident PCa diagnosed across Montreal French hospitals in 2005-2009. Controls were 1994 men recruited concurrently from electoral lists of French-speaking Montreal residents, frequency-matched to cases by age. In-person interviews elicited occupational histories. Unconditional logistic regression estimated odds ratios (OR) and 95 % confidence intervals (CI) for the association between employment across 696 occupations and 613 industries and PCa risk, adjusting for potential confounders. Multinomial logistic models assessed risks by PCa grade. Semi-Bayes (SB) adjustment accounted for the large number of associations evaluated. Consistently positive associations-and generally robust to SB adjustment-were found for occupations in forestry and logging (OR 1.9, 95 % CI: 1.2-3.0), social sciences (OR 1.6, 95 % CI: 1.1-2.2) and for police officers and detectives (OR: 1.8, 95 % CI 1.1-2.9). Occupations where elevated risk of high grade PCa was found included gasoline station attendants (OR 4.3, 95 % CI 1.8-10.4) and textile processing occupations (OR 1.8, 95 % CI 1.1-3.2). Aside from logging, industries with elevated PCa risk included provincial government and financial institutions. Occupations with reduced risk included farmers (OR 0.6, 95 % CI 0.4-1.0) and aircraft maintenance workers (OR 0.1, 95 % CI 0.0-0.7). Excess PCa risks were observed across several occupations, including predominantly white collar workers. Further analyses will focus on specific occupational exposures.

Genetic variation of genes involved in dihydrotestosterone metabolism and the risk of prostate cancer.

PubMed

Setlur, Sunita R; Chen, Chen X; Hossain, Ruhella R; Ha, Jung Sook; Van Doren, Vanessa E; Stenzel, Birgit; Steiner, Eberhard; Oldridge, Derek; Kitabayashi, Naoki; Banerjee, Samprit; Chen, Jin Yun; Schäfer, Georg; Horninger, Wolfgang; Lee, Charles; Rubin, Mark A; Klocker, Helmut; Demichelis, Francesca

2010-01-01

Dihydrotestosterone (DHT) is an important factor in prostate cancer (PCA) genesis and disease progression. Given PCA's strong genetic component, we evaluated the possibility that variation in genes involved in DHT metabolism influence PCA risk. We investigated copy number variants (CNV) and single nucleotide polymorphisms (SNP). We explored associations between CNV of uridine diphospho-glucuronosyltransferase (UGT) genes from the 2B subclass, given their prostate specificity and/or involvement in steroid metabolism and PCA risk. We also investigated associations between SNPs in genes (HSD3B1, SRD5A1/2, and AKR1C2) involved in the conversion of testosterone to DHT, and in DHT metabolism and PCA risk. The population consisted of 426 men (205 controls and 221 cases) who underwent prostate-specific antigen screening as part of a PCA early detection program in Tyrol, Austria. No association between CNV in UGT2B17 and UGT2B28 and PCA risk was identified. Men carrying the AA genotype at SNP rs6428830 (HSD3B1) had an odds ratio (OR) of 2.0 [95% confidence intervals (95% CI), 1.1-4.1] compared with men with GG, and men with AG or GG versus AA in rs1691053 (SRD5A1) had an OR of 1.8 (95% CI, 1.04-3.13). Individuals carrying both risk alleles had an OR of 3.1 (95% CI, 1.4-6.7) when compared with men carrying neither (P = 0.005). Controls with the AA genotype on rs7594951 (SRD5A2) tended toward higher serum DHT levels (P = 0.03). This is the first study to implicate the 5alpha-reductase isoform 1 (SRD5A1) and PCA risk, supporting the rationale of blocking enzymatic activity of both isoforms of 5alpha-reductase for PCA chemoprevention.

On a PCA-based lung motion model

NASA Astrophysics Data System (ADS)

Li, Ruijiang; Lewis, John H.; Jia, Xun; Zhao, Tianyu; Liu, Weifeng; Wuenschel, Sara; Lamb, James; Yang, Deshan; Low, Daniel A.; Jiang, Steve B.

2011-09-01

Respiration-induced organ motion is one of the major uncertainties in lung cancer radiotherapy and is crucial to be able to accurately model the lung motion. Most work so far has focused on the study of the motion of a single point (usually the tumor center of mass), and much less work has been done to model the motion of the entire lung. Inspired by the work of Zhang et al (2007 Med. Phys. 34 4772-81), we believe that the spatiotemporal relationship of the entire lung motion can be accurately modeled based on principle component analysis (PCA) and then a sparse subset of the entire lung, such as an implanted marker, can be used to drive the motion of the entire lung (including the tumor). The goal of this work is twofold. First, we aim to understand the underlying reason why PCA is effective for modeling lung motion and find the optimal number of PCA coefficients for accurate lung motion modeling. We attempt to address the above important problems both in a theoretical framework and in the context of real clinical data. Second, we propose a new method to derive the entire lung motion using a single internal marker based on the PCA model. The main results of this work are as follows. We derived an important property which reveals the implicit regularization imposed by the PCA model. We then studied the model using two mathematical respiratory phantoms and 11 clinical 4DCT scans for eight lung cancer patients. For the mathematical phantoms with cosine and an even power (2n) of cosine motion, we proved that 2 and 2n PCA coefficients and eigenvectors will completely represent the lung motion, respectively. Moreover, for the cosine phantom, we derived the equivalence conditions for the PCA motion model and the physiological 5D lung motion model (Low et al 2005 Int. J. Radiat. Oncol. Biol. Phys. 63 921-9). For the clinical 4DCT data, we demonstrated the modeling power and generalization performance of the PCA model. The average 3D modeling error using PCA was within 1 mm (0.7 ± 0.1 mm). When a single artificial internal marker was used to derive the lung motion, the average 3D error was found to be within 2 mm (1.8 ± 0.3 mm) through comprehensive statistical analysis. The optimal number of PCA coefficients needs to be determined on a patient-by-patient basis and two PCA coefficients seem to be sufficient for accurate modeling of the lung motion for most patients. In conclusion, we have presented thorough theoretical analysis and clinical validation of the PCA lung motion model. The feasibility of deriving the entire lung motion using a single marker has also been demonstrated on clinical data using a simulation approach.

The Prostate Health Index in predicting initial prostate biopsy outcomes in Asian men with prostate-specific antigen levels of 4-10 ng/mL.

PubMed

Ng, C F; Chiu, Peter K F; Lam, N Y; Lam, H C; Lee, Kim W M; Hou, Simon S M

2014-04-01

To investigate the role of the Prostate Health Index (phi) in prostate cancer (PCa) detection in patients with a prostate-specific antigen (PSA) level of 4-10 ng/mL receiving their first prostatic biopsy in an Asian population. This was a retrospective study of archived serum samples from patients enlisted in our tissue bank. Patients over 50 years old, with PSA level of 4-10 ng/mL, a negative digital rectal examination, and received their first prostatic biopsy between April 2008 and April 2013, were recruited. The serum sample collected before biopsy was retrieved for the measurement of various PSA derivatives and the phi value was calculated for each patient. The performance of these parameters in predicting the prostatic biopsy results was assessed. Two hundred and thirty consecutive patients, with 21 (9.13 %) diagnosed with PCa, were recruited for this study. Statistically significant differences between PCa patients and non-PCa patients were found for total PSA, PSA density, [-2]proPSA (p2PSA), free-to-total PSA ratio (%fPSA), p2PSA-to-free PSA ratio (%p2PSA), and phi. The areas under the curve of the receiver operating characteristic curve for total PSA, PSA density, %fPSA, %p2PSA, and phi were 0.547, 0.634, 0.654, 0.768, and 0.781, respectively. The phi was the best predictor of the prostatic biopsies results. At a sensitivity of 90 %, the use of the phi could have avoided unnecessary biopsies in 104 (45.2 %) patients. Use of the phi could improve the accuracy of PCa detection in patients with an elevated PSA level and thus avoid unnecessary prostatic biopsies.

The impact of prostate cancer diagnosis and treatment decision-making on health-related quality of life before treatment onset.

PubMed

Cuypers, Maarten; Lamers, Romy E D; Cornel, Erik B; van de Poll-Franse, Lonneke V; de Vries, Marieke; Kil, Paul J M

2018-04-01

The objective of this study is to test if patients' health-related quality of life (HRQoL) declines after prostate biopsy to detect Pca, and after subsequent treatment decision-making in case Pca is confirmed, and to test whether personality state and traits are associated with these potential changes in HRQoL. Patients who were scheduled for prostate biopsy to detect Pca (N = 377) filled out a baseline questionnaire about HRQoL (EORTC QLQ-C30 and PR25), "big five" personality traits (BFI-10), optimism (LOT-r), and self-efficacy (Decision Self-efficacy Scale) (t0). Patients with confirmed Pca (N = 126) filled out a follow-up questionnaire on HRQoL within 2 weeks after treatment was chosen but had not yet started (t1). HRQoL declined between t0 and t1, reflected in impaired role and cognitive functioning, and elevated fatigue, constipation, and prostate-specific symptoms. Sexual activity and functioning improved. Baseline HRQoL scores were unrelated to the selection of a particular treatment, but for patients who chose a curative treatment, post-decision HRQoL showed a greater decline compared to patients who chose active surveillance. Optimism was associated with HRQoL at baseline; decisional self-efficacy was positively associated with HRQoL at follow-up. No associations between HRQoL and the "big five" personality traits were found. Patients who have undergone prostate biopsy and treatment decision-making for Pca experience a decline in HRQoL. Choosing treatment with a curative intent was associated with greater decline in HRQoL. Interventions aimed at optimism and decision self-efficacy could be helpful to reduce HRQoL impairment around the time of prostate biopsy and treatment decision-making.

Co-Expression of Putative Cancer Stem Cell Markers CD44 and CD133 in Prostate Carcinomas.

PubMed

Kalantari, Elham; Asgari, Mojgan; Nikpanah, Seyedehmoozhan; Salarieh, Naghme; Asadi Lari, Mohammad Hossein; Madjd, Zahra

2017-10-01

Cancer stem cells (CSCs) are the main players of prostate tumorigenesis thus; characterization of CSCs can pave the way for understanding the early detection, drug resistance, metastasis and relapse. The current study was conducted to evaluate the expression level and clinical significance of the potential CSC markers CD44 and CD133 in a series of prostate tissues. One hundred and forty eight prostate tissues composed of prostate cancer (PCa), high-grade prostatic intraepithelial neoplasia (HGPIN), and benign prostate hyperplasia (BPH) were immunostained for the putative CSC markers CD44 and CD133. Subsequently, the correlation between the expression of these markers and the clinicopathological variables was examined. A higher level of CD44 expression was observed in 42% of PCa, 57% of HGPIN, and 42% BPH tissues. In the case of CD133 expression PCa, HGPIN, and BPH samples demonstrated high immunoreactivity in 46%, 43%, and 42% of cells, respectively. Statistical analysis showed an inverse significant correlation between CD44 expression with Gleason score of PCa (P = 0.02), while no significant correlation was observed between CD133 expression and clinicopathological parameters. A significant reciprocal correlation was observed between the expression of two putative CSC markers CD44 and CD133 in PCa specimens while not indicating clinical significance. Further clinical investigation is required to consider these markers as targets of new therapeutic strategies for PCa.

Liposome bupivacaine for improvement in economic outcomes and opioid burden in GI surgery: IMPROVE Study pooled analysis.

PubMed

Cohen, Stephen M; Vogel, Jon D; Marcet, Jorge E; Candiotti, Keith A

2014-01-01

Postsurgical pain management remains a significant challenge. Liposome bupivacaine, as part of a multimodal analgesic regimen, has been shown to significantly reduce postsurgical opioid consumption, hospital length of stay (LOS), and hospitalization costs in gastrointestinal (GI) surgery, compared with intravenous (IV) opioid-based patient-controlled analgesia (PCA). Pooled results from open-label studies comparing a liposome bupivacaine-based multimodal analgesic regimen with IV opioid PCA were analyzed. Patients (n=191) who underwent planned surgery and received study drug (IV opioid PCA, n=105; multimodal analgesia, n=86) were included. Liposome bupivacaine-based multimodal analgesia compared with IV opioid PCA significantly reduced mean (standard deviation [SD]) postsurgical opioid consumption (38 [55] mg versus [vs] 96 [85] mg; P<0.0001), postsurgical LOS (median 2.9 vs 4.3 days; P<0.0001), and mean hospitalization costs (US$8,271 vs US$10,726; P=0.0109). The multimodal analgesia group reported significantly fewer patients with opioid-related adverse events (AEs) than the IV opioid PCA group (P=0.0027); there were no significant between-group differences in patient satisfaction scores at 30 days. A liposome bupivacaine-based multimodal analgesic regimen was associated with significantly less opioid consumption, opioid-related AEs, and better health economic outcomes compared with an IV opioid PCA-based regimen in patients undergoing GI surgery. This pooled analysis is based on data from Phase IV clinical trials registered on the US National Institutes of Health www.ClinicalTrials.gov database under study identifiers NCT01460485, NCT01507220, NCT01507233, NCT01509638, NCT01509807, NCT01509820, NCT01461122, NCT01461135, NCT01534988, and NCT01507246.

Hard X-ray Emission along the Z Track in GX 17 + 2

NASA Astrophysics Data System (ADS)

Ding, G. Q.; Huang, C. P.

2015-09-01

Using the data from the Proportional Counter Array (PCA) and the High-Energy X-ray Timing Experiment (HEXTE) on board Rossi X-Ray Timing Explorer for Z source GX 17 + 2, we investigate the evolution of its PCA spectra and HEXTE spectra along a `Z' track on its hardness-intensity diagram. A hard X-ray tail is detected in the HEXTE spectra. The detected hard X-ray tails are discontinuously scattered throughout the Z track. The found hard X-ray tail hardens from the horizontal branch, through the normal branch, to the flaring branch in principle and it contributes ˜(20-50)% of the total flux in 20-200 keV. Our joint fitting results of the PCA + HEXTE spectra in 3-200 keV show that the portion of Comptonization in the Bulk-Motion Comptonization (BMC) model accounts for the hard X-ray tail, which indicates that the BMC process could be responsible for the detected hard tail. The temperature of the seed photons for BMC is ˜2.7 keV, implying that these seed photons might be emitted from the surface of the neutron star (NS) or the boundary layer between the NS and the disk and, therefore, this process could take place around the NS or in the boundary layer.

[Research on outlier detection methods for determination of oil yield in oil shales using near-infrared spectroscopy].

PubMed

Zhang, Huai-zhu; Lin, Jun; Zhang, Huai-Zhu

2014-06-01

In the present paper, the outlier detection methods for determination of oil yield in oil shale using near-infrared (NIR) diffuse reflection spectroscopy was studied. During the quantitative analysis with near-infrared spectroscopy, environmental change and operator error will both produce outliers. The presence of outliers will affect the overall distribution trend of samples and lead to the decrease in predictive capability. Thus, the detection of outliers are important for the construction of high-quality calibration models. The methods including principal component analysis-Mahalanobis distance (PCA-MD) and resampling by half-means (RHM) were applied to the discrimination and elimination of outliers in this work. The thresholds and confidences for MD and RHM were optimized using the performance of partial least squares (PLS) models constructed after the elimination of outliers, respectively. Compared with the model constructed with the data of full spectrum, the values of RMSEP of the models constructed with the application of PCA-MD with a threshold of a value equal to the sum of average and standard deviation of MD, RHM with the confidence level of 85%, and the combination of PCA-MD and RHM, were reduced by 48.3%, 27.5% and 44.8%, respectively. The predictive ability of the calibration model has been improved effectively.

An In Vitro Spectroscopic Analysis to Determine Whether para-Chloroaniline is Produced from Mixing Sodium Hypochlorite and Chlorhexidine

PubMed Central

Thomas, John E.; Sem, Daniel S.

2009-01-01

Introduction The purpose of this in vitro study was to determine whether para-chloroaniline (PCA) is formed through the reaction of mixing sodium hypochlorite (NaOCl) and chlorhexidine (CHX). Methods Initially commercially available samples of chlorhexidine acetate (CHXa) and PCA were analyzed with 1H NMR spectroscopy. Two solutions, NaOCl and CHXa, were warmed to 37°C and when mixed they produced a brown precipitate. This precipitate was separated in half and pure PCA was added to one of the samples for comparison before they were each analyzed with 1H NMR spectroscopy. Results The peaks in the 1H NMR spectra of CHXa and PCA were assigned to specific protons of the molecules, and the location of the aromatic peaks in the PCA spectrum defined the PCA doublet region. While the spectrum of the precipitate alone resulted in a complex combination of peaks, upon magnification there were no peaks in the PCA doublet region which were intense enough to be quantified. In the spectrum of the precipitate, to which PCA was added, two peaks do appear in the PCA doublet region. Comparing this spectrum to that of precipitate alone, the peaks in the PCA doublet region are not visible prior to the addition of PCA. Conclusions Based on this in vitro study, the reaction mixture of NaOCl and CHXa does not produce PCA at any measurable quantity and further investigation is needed to determine the chemical composition of the brown precipitate. PMID:20113799

Investigation of Inversion Polymorphisms in the Human Genome Using Principal Components Analysis

PubMed Central

Ma, Jianzhong; Amos, Christopher I.

2012-01-01

Despite the significant advances made over the last few years in mapping inversions with the advent of paired-end sequencing approaches, our understanding of the prevalence and spectrum of inversions in the human genome has lagged behind other types of structural variants, mainly due to the lack of a cost-efficient method applicable to large-scale samples. We propose a novel method based on principal components analysis (PCA) to characterize inversion polymorphisms using high-density SNP genotype data. Our method applies to non-recurrent inversions for which recombination between the inverted and non-inverted segments in inversion heterozygotes is suppressed due to the loss of unbalanced gametes. Inside such an inversion region, an effect similar to population substructure is thus created: two distinct “populations” of inversion homozygotes of different orientations and their 1∶1 admixture, namely the inversion heterozygotes. This kind of substructure can be readily detected by performing PCA locally in the inversion regions. Using simulations, we demonstrated that the proposed method can be used to detect and genotype inversion polymorphisms using unphased genotype data. We applied our method to the phase III HapMap data and inferred the inversion genotypes of known inversion polymorphisms at 8p23.1 and 17q21.31. These inversion genotypes were validated by comparing with literature results and by checking Mendelian consistency using the family data whenever available. Based on the PCA-approach, we also performed a preliminary genome-wide scan for inversions using the HapMap data, which resulted in 2040 candidate inversions, 169 of which overlapped with previously reported inversions. Our method can be readily applied to the abundant SNP data, and is expected to play an important role in developing human genome maps of inversions and exploring associations between inversions and susceptibility of diseases. PMID:22808122

Feature extraction for ultrasonic sensor based defect detection in ceramic components

NASA Astrophysics Data System (ADS)

Kesharaju, Manasa; Nagarajah, Romesh

2014-02-01

High density silicon carbide materials are commonly used as the ceramic element of hard armour inserts used in traditional body armour systems to reduce their weight, while providing improved hardness, strength and elastic response to stress. Currently, armour ceramic tiles are inspected visually offline using an X-ray technique that is time consuming and very expensive. In addition, from X-rays multiple defects are also misinterpreted as single defects. Therefore, to address these problems the ultrasonic non-destructive approach is being investigated. Ultrasound based inspection would be far more cost effective and reliable as the methodology is applicable for on-line quality control including implementation of accept/reject criteria. This paper describes a recently developed methodology to detect, locate and classify various manufacturing defects in ceramic tiles using sub band coding of ultrasonic test signals. The wavelet transform is applied to the ultrasonic signal and wavelet coefficients in the different frequency bands are extracted and used as input features to an artificial neural network (ANN) for purposes of signal classification. Two different classifiers, using artificial neural networks (supervised) and clustering (un-supervised) are supplied with features selected using Principal Component Analysis(PCA) and their classification performance compared. This investigation establishes experimentally that Principal Component Analysis(PCA) can be effectively used as a feature selection method that provides superior results for classifying various defects in the context of ultrasonic inspection in comparison with the X-ray technique.

Target oriented dimensionality reduction of hyperspectral data by Kernel Fukunaga-Koontz Transform

NASA Astrophysics Data System (ADS)

Binol, Hamidullah; Ochilov, Shuhrat; Alam, Mohammad S.; Bal, Abdullah

2017-02-01

Principal component analysis (PCA) is a popular technique in remote sensing for dimensionality reduction. While PCA is suitable for data compression, it is not necessarily an optimal technique for feature extraction, particularly when the features are exploited in supervised learning applications (Cheriyadat and Bruce, 2003) [1]. Preserving features belonging to the target is very crucial to the performance of target detection/recognition techniques. Fukunaga-Koontz Transform (FKT) based supervised band reduction technique can be used to provide this requirement. FKT achieves feature selection by transforming into a new space in where feature classes have complimentary eigenvectors. Analysis of these eigenvectors under two classes, target and background clutter, can be utilized for target oriented band reduction since each basis functions best represent target class while carrying least information of the background class. By selecting few eigenvectors which are the most relevant to the target class, dimension of hyperspectral data can be reduced and thus, it presents significant advantages for near real time target detection applications. The nonlinear properties of the data can be extracted by kernel approach which provides better target features. Thus, we propose constructing kernel FKT (KFKT) to present target oriented band reduction. The performance of the proposed KFKT based target oriented dimensionality reduction algorithm has been tested employing two real-world hyperspectral data and results have been reported consequently.

Ship Detection Based on Multiple Features in Random Forest Model for Hyperspectral Images

NASA Astrophysics Data System (ADS)

Li, N.; Ding, L.; Zhao, H.; Shi, J.; Wang, D.; Gong, X.

2018-04-01

A novel method for detecting ships which aim to make full use of both the spatial and spectral information from hyperspectral images is proposed. Firstly, the band which is high signal-noise ratio in the range of near infrared or short-wave infrared spectrum, is used to segment land and sea on Otsu threshold segmentation method. Secondly, multiple features that include spectral and texture features are extracted from hyperspectral images. Principal components analysis (PCA) is used to extract spectral features, the Grey Level Co-occurrence Matrix (GLCM) is used to extract texture features. Finally, Random Forest (RF) model is introduced to detect ships based on the extracted features. To illustrate the effectiveness of the method, we carry out experiments over the EO-1 data by comparing single feature and different multiple features. Compared with the traditional single feature method and Support Vector Machine (SVM) model, the proposed method can stably achieve the target detection of ships under complex background and can effectively improve the detection accuracy of ships.

Multi-segmental movements as a function of experience in karate.

PubMed

Zago, Matteo; Codari, Marina; Iaia, F Marcello; Sforza, Chiarella

2017-08-01

Karate is a martial art that partly depends on subjective scoring of complex movements. Principal component analysis (PCA)-based methods can identify the fundamental synergies (principal movements) of motor system, providing a quantitative global analysis of technique. In this study, we aimed at describing the fundamental multi-joint synergies of a karate performance, under the hypothesis that the latter are skilldependent; estimate karateka's experience level, expressed as years of practice. A motion capture system recorded traditional karate techniques of 10 professional and amateur karateka. At any time point, the 3D-coordinates of body markers produced posture vectors that were normalised, concatenated from all karateka and submitted to a first PCA. Five principal movements described both gross movement synergies and individual differences. A second PCA followed by linear regression estimated the years of practice using principal movements (eigenpostures and weighting curves) and centre of mass kinematics (error: 3.71 years; R2 = 0.91, P ≪ 0.001). Principal movements and eigenpostures varied among different karateka and as functions of experience. This approach provides a framework to develop visual tools for the analysis of motor synergies in karate, allowing to detect the multi-joint motor patterns that should be restored after an injury, or to be specifically trained to increase performance.

¹H and ¹³C NMR-based sugar profiling with chemometric analysis and antioxidant activity of herbhoneys and honeys.

PubMed

Jamróz, Marta K; Paradowska, Katarzyna; Zawada, Katarzyna; Makarova, Katerina; Kaźmierski, Sławomir; Wawer, Iwona

2014-01-30

Herbhoneys, relatively new bee products, are expected to have interesting medicinal properties. However, there is still a lack of data concerning their composition and antioxidant properties. ¹H and ¹³C NMR spectroscopy coupled with chemometric analysis (PCA and PLS-DA) and antioxidant assays (DPPH-ESR and ORAC-FL) were used to study 25 samples of Polish herbhoneys and honeys. Antioxidant activity varied among the samples. The best properties were exhibited by cocoa and instant coffee herbhoneys. The contents of total polyphenols and total carotenoids in the studied samples were found to be 70-1340 mg GAE kg⁻¹ and 0-28.05 mg kg⁻¹ respectively. No significant differences between herbhoney and honey samples were found in their sugar profiles. The PCA of ¹³C NMR spectra of the samples in DMSO-d6 resulted in sample clustering due to sucrose content. Herbhoneys have similar antioxidant properties to traditional honeys, being therefore of equal nutritional value. There was a noticeable influence of the extract concentration on the observed antioxidant effect. For samples with high antioxidant activity, polyphenols were responsible for the observed effect. Sample clustering due to sucrose content in the NMR-PCA study allowed effortless detection of adulteration. © 2013 Society of Chemical Industry.

Comparative evaluation of urinary PCA3 and TMPRSS2: ERG scores and serum PHI in predicting prostate cancer aggressiveness.

PubMed

Tallon, Lucile; Luangphakdy, Devillier; Ruffion, Alain; Colombel, Marc; Devonec, Marian; Champetier, Denis; Paparel, Philippe; Decaussin-Petrucci, Myriam; Perrin, Paul; Vlaeminck-Guillem, Virginie

2014-07-30

It has been suggested that urinary PCA3 and TMPRSS2:ERG fusion tests and serum PHI correlate to cancer aggressiveness-related pathological criteria at prostatectomy. To evaluate and compare their ability in predicting prostate cancer aggressiveness, PHI and urinary PCA3 and TMPRSS2:ERG (T2) scores were assessed in 154 patients who underwent radical prostatectomy for biopsy-proven prostate cancer. Univariate and multivariate analyses using logistic regression and decision curve analyses were performed. All three markers were predictors of a tumor volume≥0.5 mL. Only PHI predicted Gleason score≥7. T2 score and PHI were both independent predictors of extracapsular extension(≥pT3), while multifocality was only predicted by PCA3 score. Moreover, when compared to a base model (age, digital rectal examination, serum PSA, and Gleason sum at biopsy), the addition of both PCA3 score and PHI to the base model induced a significant increase (+12%) when predicting tumor volume>0.5 mL. PHI and urinary PCA3 and T2 scores can be considered as complementary predictors of cancer aggressiveness at prostatectomy.

An analytical approach based on ESI-MS, LC-MS and PCA for the quali-quantitative analysis of cycloartane derivatives in Astragalus spp.

PubMed

Napolitano, Assunta; Akay, Seref; Mari, Angela; Bedir, Erdal; Pizza, Cosimo; Piacente, Sonia

2013-11-01

Astragalus species are widely used as health foods and dietary supplements, as well as drugs in traditional medicine. To rapidly evaluate metabolite similarities and differences among the EtOH extracts of the roots of eight commercial Astragalus spp., an approach based on direct analyses by ESI-MS followed by PCA of ESI-MS data, was carried out. Successively, quali-quantitative analyses of cycloartane derivatives in the eight Astragalus spp. by LC-ESI-MS(n) and PCA of LC-ESI-MS data were performed. This approach allowed to promptly highlighting metabolite similarities and differences among the various Astragalus spp. PCA results from LC-ESI-MS data of Astragalus samples were in reasonable agreement with both PCA results of ESI-MS data and quantitative results. This study affords an analytical method for the quali-quantitative determination of cycloartane derivatives in herbal preparations used as health and food supplements. Copyright © 2013 Elsevier B.V. All rights reserved.

Source Apportionment and Risk Assessment of Emerging Contaminants: An Approach of Pharmaco-Signature in Water Systems

PubMed Central

Jiang, Jheng Jie; Lee, Chon Lin; Fang, Meng Der; Boyd, Kenneth G.; Gibb, Stuart W.

2015-01-01

This paper presents a methodology based on multivariate data analysis for characterizing potential source contributions of emerging contaminants (ECs) detected in 26 river water samples across multi-scape regions during dry and wet seasons. Based on this methodology, we unveil an approach toward potential source contributions of ECs, a concept we refer to as the “Pharmaco-signature.” Exploratory analysis of data points has been carried out by unsupervised pattern recognition (hierarchical cluster analysis, HCA) and receptor model (principal component analysis-multiple linear regression, PCA-MLR) in an attempt to demonstrate significant source contributions of ECs in different land-use zone. Robust cluster solutions grouped the database according to different EC profiles. PCA-MLR identified that 58.9% of the mean summed ECs were contributed by domestic impact, 9.7% by antibiotics application, and 31.4% by drug abuse. Diclofenac, ibuprofen, codeine, ampicillin, tetracycline, and erythromycin-H2O have significant pollution risk quotients (RQ>1), indicating potentially high risk to aquatic organisms in Taiwan. PMID:25874375

Molecular Imaging and Therapy of Prostate Cancer

DTIC Science & Technology

2015-10-01

arsenic-based, IGF1R-targeted radiopharmaceuticals can allow for PET imaging, IRT, and monitoring the therapeutic response of PCa. Specific Aims: Aim 1: To...models with PET imaging. Aim 3: To monitor the efficacy of 76As-based IRT of PCa with multimodality imaging.

ARLTS1 and Prostate Cancer Risk - Analysis of Expression and Regulation

PubMed Central

Siltanen, Sanna; Fischer, Daniel; Rantapero, Tommi; Laitinen, Virpi; Mpindi, John Patrick; Kallioniemi, Olli; Wahlfors, Tiina; Schleutker, Johanna

2013-01-01

Prostate cancer (PCa) is a heterogeneous trait for which several susceptibility loci have been implicated by genome-wide linkage and association studies. The genomic region 13q14 is frequently deleted in tumour tissues of both sporadic and familial PCa patients and is consequently recognised as a possible locus of tumour suppressor gene(s). Deletions of this region have been found in many other cancers. Recently, we showed that homozygous carriers for the T442C variant of the ARLTS1 gene (ADP-ribosylation factor-like tumour suppressor protein 1 or ARL11, located at 13q14) are associated with an increased risk for both unselected and familial PCa. Furthermore, the variant T442C was observed in greater frequency among malignant tissue samples, PCa cell lines and xenografts, supporting its role in PCa tumourigenesis. In this study, 84 PCa cases and 15 controls were analysed for ARLTS1 expression status in blood-derived RNA. A statistically significant (p = 0.0037) decrease of ARLTS1 expression in PCa cases was detected. Regulation of ARLTS1 expression was analysed with eQTL (expression quantitative trait loci) methods. Altogether fourteen significant cis-eQTLs affecting the ARLTS1 expression level were found. In addition, epistatic interactions of ARLTS1 genomic variants with genes involved in immune system processes were predicted with the MDR program. In conclusion, this study further supports the role of ARLTS1 as a tumour suppressor gene and reveals that the expression is regulated through variants localised in regulatory regions. PMID:23940804

Mortality among men with locally advanced prostate cancer managed with noncurative intent: a nationwide study in PCBaSe Sweden.

PubMed

Akre, Olof; Garmo, Hans; Adolfsson, Jan; Lambe, Mats; Bratt, Ola; Stattin, Pär

2011-09-01

There are limited prognostic data for locally advanced prostate cancer PCa to guide in the choice of treatment. To assess mortality in different prognostic categories among men with locally advanced PCa managed with noncurative intent. We conducted a register-based nationwide cohort study within the Prostate Cancer DataBase Sweden. The entire cohort of locally advanced PCa included 14 908 men. After the exclusion of 2724 (18%) men treated with curative intent, 12 184 men with locally advanced PCa either with local clinical stage T3 or T4 or with T2 with serum levels of prostate-specific antigen (PSA) between 50 and 99 ng/ml and without signs of metastases remained for analysis. We followed up the patient cohort in the Cause of Death Register for ≤ 11 yr and assessed cumulative incidence of PCa -specific death stratified by age and clinical characteristics. The PCa -specific mortality at 8 yr of follow-up was 28% (95% confidence interval [CI], 25-32%) for Gleason score (GS) 2-6, 41% (95% CI, 38-44%) for GS 7, 52% (95% CI, 47-57%) for GS 8, and 64% (95% CI, 59-69%) for GS 9-10. Even for men aged >85 yr at diagnosis with GS 8-10, PCa was a major cause of death: 42% (95% CI, 37-47%). Men with locally advanced disease and a PSA<4 ng/ml at diagnosis were at particularly increased risk of dying from PCa. One important limitation is the lack of bone scans in 42% of the patient cohort, but results remained after exclusion of patients with unknown metastasis status. The PCa-specific mortality within 8 yr of diagnosis is high in locally advanced PCa, suggesting undertreatment, particularly among men in older age groups. Our results underscore the need for more studies of treatment with curative intent for locally advanced tumors. Copyright © 2011 European Association of Urology. Published by Elsevier B.V. All rights reserved.

The simultaneous detection of free and total prostate antigen in serum samples with high sensitivity and specificity by using the dual-channel surface plasmon resonance.

PubMed

Jiang, Zhongxiu; Qin, Yun; Peng, Zhen; Chen, Shenghua; Chen, Shu; Deng, Chunyan; Xiang, Juan

2014-12-15

Free/total prostate antigen (f/t-PSA) ratio in serum as a promising parameter has been used to improve the differentiation of benign and malignant prostate disease. In order to obtain the accurate and reliable f/t-PSA ratio, the simultaneous detection of f-PSA and t-PSA with high sensitivity and specificity is required. In this work, the dual-channel surface plasmon resonance (SPR) has been employed to meet the requirement. In one channel, t-PSA was directly measured with a linear range from 1.0 to 20.0 ng/mL. In another channel, due to the low concentration of f-PSA in serum, the asynchronous competitive inhibition immunoassay with f-PSA@Au nanoparticles (AuNPs) was developed. As expected, the detection sensitivity of f-PSA was greatly enhanced, and a linear correlation with wider linear range from 0.010 to 0.40 ng/mL was also achieved. On the other hand, a simple method was explored for significantly reducing the non-specific adsorption of co-existing proteins. On basis of this, the f/t-PSA ratios in serum samples from prostate cancer (PCa) or benign prostatic hyperplasia (BPH) patients were measured. And it was found that there was significant difference between the distributions of f/t-PSA ratio in BPH patients (16.44±1.77%) and those in PCa patients (24.53±4.97%). This present work provides an effective method for distinguishing PCa from BPH, which lays a potential foundation for the early diagnosis of PCa. Copyright © 2014. Published by Elsevier B.V.

Differentiation of neuropsychological features between posterior cortical atrophy and early onset Alzheimer's disease.

PubMed

Li, Jieying; Wu, Liyong; Tang, Yi; Zhou, Aihong; Wang, Fen; Xing, Yi; Jia, Jianping

2018-05-10

Posterior cortical atrophy (PCA) is a group of clinical syndromes characterized by visuospatial and visuoperceptual impairment, with memory relatively preserved. Although PCA is pathologically almost identical to Alzheimer's disease (AD), they have different cognitive features. Those differences have only rarely been reported in any Chinese population. The purpose of the study is to establish neuropsychological tests that distinguish the clinical features of PCA from early onset AD (EOAD). Twenty-one PCA patients, 20 EOAD patients, and 20 healthy controls participated in this study. Patients had disease duration of ≤4 years. All participants completed a series of neuropsychological tests to evaluate their visuospatial, visuoperceptual, visuo-constructive, language, executive function, memory, calculation, writing, and reading abilities. The cognitive features of PCA and EOAD were compared. All the neuropsychological test scores showed that both the PCA and EOAD patients were significantly more impaired than people in the control group. However, PCA patients were significantly more impaired than EOAD patients in visuospatial, visuoperceptual, and visuo-constructive function, as well as in handwriting, and reading Chinese characters. The profile of neuropsychological test results highlights cognitive features that differ between PCA and EOAD. One surprising result is that the two syndromes could be distinguished by patients' ability to read and write Chinese characters. Tests based on these characteristics could therefore form a brief PCA neuropsychological examination that would improve the diagnosis of PCA.

Trans-rectal ultrasound visibility of prostate lesions identified by magnetic resonance imaging increases accuracy of image-fusion targeted biopsies.

PubMed

Ukimura, Osamu; Marien, Arnaud; Palmer, Suzanne; Villers, Arnauld; Aron, Manju; de Castro Abreu, Andre Luis; Leslie, Scott; Shoji, Sunao; Matsugasumi, Toru; Gross, Mitchell; Dasgupta, Prokar; Gill, Inderbir S

2015-11-01

To compare the diagnostic yield of targeted prostate biopsy using image-fusion of multi-parametric magnetic resonance (mp-MR) with real-time trans-rectal ultrasound (TRUS) for clinically significant lesions that are suspicious only on mp-MR versus lesions that are suspicious on both mp-MR and TRUS. Pre-biopsy MRI and TRUS were each scaled on a 3-point score: highly suspicious, likely, and unlikely for clinically significant cancer (sPCa). Using an MR-TRUS elastic image-fusion system (Koelis), a 127 consecutive patients with a suspicious clinically significant index lesion on pre-biopsy mp-MR underwent systematic biopsies and MR/US-fusion targeted biopsies (01/2010-09/2013). Biopsy histological outcomes were retrospectively compared with MR suspicion level and TRUS-visibility of the MR-suspicious lesion. sPCa was defined as biopsy Gleason score ≥7 and/or maximum cancer core length ≥5 mm. Targeted biopsies outperformed systematic biopsies in overall cancer detection rate (61 vs. 41 %; p = 0.007), sPCa detection rate (43 vs. 23 %; p = 0.0013), cancer core length (7.5 vs. 3.9 mm; p = 0.0002), and cancer rate per core (56 vs. 12 %; p < 0.0001), respectively. Highly suspicious lesions on mp-MR correlated with higher positive biopsy rate (p < 0.0001), higher Gleason score (p = 0.018), and greater cancer core length (p < 0.0001). Highly suspicious lesions on TRUS in corresponding to MR-suspicious lesion had a higher biopsy yield (p < 0.0001) and higher sPCa detection rate (p < 0.0001). Since majority of MR-suspicious lesions were also suspicious on TRUS, TRUS-visibility allowed selection of the specific MR-visible lesion which should be targeted from among the multiple TRUS suspicious lesions in each prostate. MR-TRUS fusion-image-guided biopsies outperformed systematic biopsies. TRUS-visibility of a MR-suspicious lesion facilitates image-guided biopsies, resulting in higher detection of significant cancer.

64Cu-PSMA-617 PET/CT Imaging of Prostate Adenocarcinoma: First In-Human Studies.

PubMed

Grubmüller, Bernhard; Baum, Richard P; Capasso, Enza; Singh, Aviral; Ahmadi, Yasaman; Knoll, Peter; Floth, Andreas; Righi, Sergio; Zandieh, Shahin; Meleddu, Carlo; Shariat, Shahrokh F; Klingler, Hans Christoph; Mirzaei, Siroos

2016-10-07

The prostate-specific membrane antigen (PSMA) is a cell surface protein, which is overexpressed in nearly all cases of prostate cancer (PCa). PET imaging with 68 Ga-PSMA-HBED-CC has recently found widespread application in the diagnosis of recurrent PCa. In this study, the diagnostic potential of 64 Cu-labeled PSMA ligand (PSMA-617) PET in patients with PCa has been investigated. The study was conducted simultaneously at two nuclear medicine centers, Austria (Vienna, Center 1) and Germany (Bad Berka, Center 2). The patients (n = 29) included in this study were referred for PET (Center 1, 21 patients) or PET/CT (Center 2, 8 patients) imaging with either a high suspicion of recurrent disease or for possible surgical or PSMA radioligand therapy planning. PET images of the whole body were performed at 1 hour p.i. and additional images of the pelvis at 2 hours p.i. In 23 of 29 patients, at least one focus of pathological tracer uptake suspicious for primary disease in the prostate lobe or recurrent disease was detected. Among healthy organs, the salivary glands, kidneys, and liver showed the highest radiotracer uptake. Lesions suspicious for PCa were detected with excellent contrast as early as 1 hour p.i. with high detection rates even at low prostate-specific antigen (PSA) levels. The preliminary results of this study demonstrate the high potential of 64 Cu-PSMA ligand PET/CT imaging in patients with recurrent disease and in the primary staging of selected patients with progressive local disease. The acquired PET images showed an excellent resolution of the detected lesions with very high lesion-to- background contrast. Furthermore, the long half-life of 64 Cu allows distribution of the tracer to clinical PET centers that lack radiochemistry facilities for the preparation of 68 Ga-PSMA ligand (satellite concept).

Detectable end of radiation prostate specific antigen assists in identifying men with unfavorable intermediate-risk prostate cancer at high risk of distant recurrence and cancer-specific mortality.

PubMed

Hayman, Jonathan; Phillips, Ryan; Chen, Di; Perin, Jamie; Narang, Amol K; Trieu, Janson; Radwan, Noura; Greco, Stephen; Deville, Curtiland; McNutt, Todd; Song, Daniel Y; DeWeese, Theodore L; Tran, Phuoc T

2018-06-01

Undetectable End of Radiation PSA (EOR-PSA) has been shown to predict improved survival in prostate cancer (PCa). While validating the unfavorable intermediate-risk (UIR) and favorable intermediate-risk (FIR) stratifications among Johns Hopkins PCa patients treated with radiotherapy, we examined whether EOR-PSA could further risk stratify UIR men for survival. A total of 302 IR patients were identified in the Johns Hopkins PCa database (178 UIR, 124 FIR). Kaplan-Meier curves and multivariable analysis was performed via Cox regression for biochemical recurrence free survival (bRFS), distant metastasis free survival (DMFS), and overall survival (OS), while a competing risks model was used for PCa specific survival (PCSS). Among the 235 patients with known EOR-PSA values, we then stratified by EOR-PSA and performed the aforementioned analysis. The median follow-up time was 11.5 years (138 months). UIR was predictive of worse DMFS and PCSS (P = 0.008 and P = 0.023) on multivariable analysis (MVA). Increased radiation dose was significant for improved DMFS (P = 0.016) on MVA. EOR-PSA was excluded from the models because it did not trend towards significance as a continuous or binary variable due to interaction with UIR, and we were unable to converge a multivariable model with a variable to control for this interaction. However, when stratifying by detectable versus undetectable EOR-PSA, UIR had worse DMFS and PCSS among detectable EOR-PSA patients, but not undetectable patients. UIR was significant on MVA among detectable EOR-PSA patients for DMFS (P = 0.021) and PCSS (P = 0.033), while RT dose also predicted PCSS (P = 0.013). EOR-PSA can assist in predicting DMFS and PCSS among UIR patients, suggesting a clinically meaningful time point for considering intensification of treatment in clinical trials of intermediate-risk men. © 2018 Wiley Periodicals, Inc.

Application of higher order SVD to vibration-based system identification and damage detection

NASA Astrophysics Data System (ADS)

Chao, Shu-Hsien; Loh, Chin-Hsiung; Weng, Jian-Huang

2012-04-01

Singular value decomposition (SVD) is a powerful linear algebra tool. It is widely used in many different signal processing methods, such principal component analysis (PCA), singular spectrum analysis (SSA), frequency domain decomposition (FDD), subspace identification and stochastic subspace identification method ( SI and SSI ). In each case, the data is arranged appropriately in matrix form and SVD is used to extract the feature of the data set. In this study three different algorithms on signal processing and system identification are proposed: SSA, SSI-COV and SSI-DATA. Based on the extracted subspace and null-space from SVD of data matrix, damage detection algorithms can be developed. The proposed algorithm is used to process the shaking table test data of the 6-story steel frame. Features contained in the vibration data are extracted by the proposed method. Damage detection can then be investigated from the test data of the frame structure through subspace-based and nullspace-based damage indices.

Comparative preclinical evaluation of 68Ga-NODAGA and 68Ga-HBED-CC conjugated procainamide in melanoma imaging.

PubMed

Trencsényi, György; Dénes, Noémi; Nagy, Gábor; Kis, Adrienn; Vida, András; Farkas, Flóra; Szabó, Judit P; Kovács, Tünde; Berényi, Ervin; Garai, Ildikó; Bai, Péter; Hunyadi, János; Kertész, István

2017-05-30

Malignant melanoma is the most aggressive form of skin cancer. The early detection of primary melanoma tumors and metastases using non-invasive PET imaging determines the outcome of this disease. Previous studies have shown that benzamide derivatives (e.g. procainamide) conjugated with PET radionuclides specifically bind to melanin pigment of melanoma tumors. 68 Ga chelating agents can have high influence on physiological properties of 68 Ga labeled bioactive molecules, as was experienced during the application of HBED-CC on PSMA ligand. The aim of this study was to assess this concept in the case of the melanin specific procaindamide (PCA) and to compare the melanin specificity of 68 Ga-labeled PCA using HBED-CC and NODAGA chelators under in vitro and in vivo conditions. Procainamide (PCA) was conjugated with HBED-CC and NODAGA chelators and was labeled with Ga-68. The melanin specificity of 68 Ga-HBED-CC-PCA and 68 Ga-NODAGA-PCA was investigated in vitro and in vivo using amelanotic (MELUR and A375) and melanin containing (B16-F10) melanoma cell lines. Tumor-bearing mice were prepared by subcutaneous injection of B16-F10, MELUR and A375 melanoma cells into C57BL/6 and SCID mice. 21±2days after tumor cell inoculation and 90min after intravenous injection of the 68 Ga-labelledlabeled radiopharmacons whole body PET/MRI scans were performed. 68 Ga-NODAGA-PCA and 68 Ga-HBED-CC-PCA were produced with excellent radiochemical purity (98%). In vitro experiments demonstrated that after 30 and 90min incubation time 68 Ga-NODAGA-PCA uptake of B16-F10 cells was significantly (p≤0.01) higher than the 68 Ga-HBED-CC-conjugated PCA accumulation in the same cell line. Furthermore, significant difference (p≤0.01 and 0.05) was found between the uptake of melanin negative and positive cell lines using 68 Ga-NODAGA-PCA and 68 Ga-HBED-CC-PCA. In vivo PET/MRI studies using tumor models revealed significantly (p≤0.01) higher 68 Ga-NODAGA-PCA uptake (SUVmean: 0.46±0.05, SUVmax: 1.96±0.25,T/M ratio: 40.7±4.23) in B16-F10 tumors in contrast to 68 Ga-HBED-CC-PCA where the SUVmean, SUVmax and T/M ratio were 0.13±0.01, 0.56±0.11 and 11.43±1.24, respectively. Melanin specific PCA conjugated with NODAGA chelator showed higher specific binding properties than conjugated with HBED-CC. The chemical properties of the bifunctional chelators used for 68 Ga-labeling of PCA determine the biological behaviour of the probes. Due to the high specificity and sensitivity 68 Ga-labeled PCA molecules are promising radiotracers in melanoma imaging. Copyright © 2017 Elsevier B.V. All rights reserved.

Larger men have larger prostates: Detection bias in epidemiologic studies of obesity and prostate cancer risk

PubMed Central

Rundle, Andrew; Wang, Yun; Sadasivan, Sudha; Chitale, Dhananjay A.; Gupta, Nilesh S.; Tang, Deliang; Rybicki, Benjamin A.

2017-01-01

BACKGROUND Obesity is associated with risk of aggressive prostate cancer (PCa), but not with over-all PCa risk. However, obese men have larger prostates which may lower biopsy accuracy and cause a systematic bias towards the null in epidemiologic studies of over-all risk. METHODS Within a cohort of 6,692 men followed-up after a biopsy or transurethral resection of the prostate (TURP) with benign findings, a nested case-control study was conducted of 495 prostate cancer cases and controls matched on age, race, follow-up duration, biopsy versus TURP and procedure date. Data on body mass index and prostate volume at the time of the initial procedure were abstracted from medical records. RESULTS Prior to consideration of differences in prostate volume, overweight (OR = 1.41; 95% CI 1.01, 1.97) and obese status (OR = 1.59; 95% CI 1.09, 2.33) at the time of the original benign biopsy or TURP were associated with PCa incidence during follow-up. Prostate volume did not significantly moderate the association between body-size and PCa, however it did act as an inverse confounder; adjustment for prostate volume increased the effect size for overweight by 22% (adjusted OR = 1.52; 95% CI 1.08, 2.14) and for obese status by 23% (adjusted OR = 1.77; 95% CI 1.20, 2.62). Larger prostate volume at the time of the original benign biopsy or TURP was inversely associated with PCa incidence during follow-up (OR = 0.92 per 10 cc difference in volume; 95% CI 0.88, 0.97). In analyses that stratified case-control pairs by tumor aggressiveness of the case, prostate volume acted as an inverse confounder in analyses of non-aggressive PCa but not in analyses of aggressive PCa. CONCLUSIONS In studies of obesity and PCa, differences in prostate volume cause a bias towards the null, particularly in analyses of non-aggressive PCa. A pervasive underestimation of the association between obesity and overall PCa risk may exist in the literature. PMID:28349547

Larger men have larger prostates: Detection bias in epidemiologic studies of obesity and prostate cancer risk.

PubMed

Rundle, Andrew; Wang, Yun; Sadasivan, Sudha; Chitale, Dhananjay A; Gupta, Nilesh S; Tang, Deliang; Rybicki, Benjamin A

2017-06-01

Obesity is associated with risk of aggressive prostate cancer (PCa), but not with over-all PCa risk. However, obese men have larger prostates which may lower biopsy accuracy and cause a systematic bias toward the null in epidemiologic studies of over-all risk. Within a cohort of 6692 men followed-up after a biopsy or transurethral resection of the prostate (TURP) with benign findings, a nested case-control study was conducted of 495 prostate cancer cases and controls matched on age, race, follow-up duration, biopsy versus TURP, and procedure date. Data on body mass index and prostate volume at the time of the initial procedure were abstracted from medical records. Prior to consideration of differences in prostate volume, overweight (OR = 1.41; 95%CI 1.01, 1.97), and obese status (OR = 1.59; 95%CI 1.09, 2.33) at the time of the original benign biopsy or TURP were associated with PCa incidence during follow-up. Prostate volume did not significantly moderate the association between body-size and PCa, however it did act as an inverse confounder; adjustment for prostate volume increased the effect size for overweight by 22% (adjusted OR = 1.52; 95%CI 1.08, 2.14) and for obese status by 23% (adjusted OR = 1.77; 95%CI 1.20, 2.62). Larger prostate volume at the time of the original benign biopsy or TURP was inversely associated with PCa incidence during follow-up (OR = 0.92 per 10 cc difference in volume; 95%CI 0.88, 0.97). In analyses that stratified case-control pairs by tumor aggressiveness of the case, prostate volume acted as an inverse confounder in analyses of non-aggressive PCa but not in analyses of aggressive PCa. In studies of obesity and PCa, differences in prostate volume cause a bias toward the null, particularly in analyses of non-aggressive PCa. A pervasive underestimation of the association between obesity and overall PCa risk may exist in the literature. © 2017 Wiley Periodicals, Inc.

Genetic variations in genes involved in testosterone metabolism are associated with prostate cancer progression: A Spanish multicenter study.

PubMed

Henríquez-Hernández, Luis Alberto; Valenciano, Almudena; Foro-Arnalot, Palmira; Álvarez-Cubero, María Jesús; Cozar, José Manuel; Suárez-Novo, José Francisco; Castells-Esteve, Manel; Fernández-Gonzalo, Pablo; De-Paula-Carranza, Belén; Ferrer, Montse; Guedea, Ferrán; Sancho-Pardo, Gemma; Craven-Bartle, Jordi; Ortiz-Gordillo, María José; Cabrera-Roldán, Patricia; Rodríguez-Melcón, Juan Ignacio; Herrera-Ramos, Estefanía; Rodríguez-Gallego, Carlos; Lara, Pedro C

2015-07-01

Prostate cancer (PCa) is an androgen-dependent disease. Nonetheless, the role of single nucleotide polymorphisms (SNPs) in genes encoding androgen metabolism remains an unexplored area. To investigate the role of germline variations in cytochrome P450 17A1 (CYP17A1) and steroid-5α-reductase, α-polypeptides 1 and 2 (SRD5A1 and SRD5A2) genes in PCa. In total, 494 consecutive Spanish patients diagnosed with nonmetastatic localized PCa were included in this multicenter study and were genotyped for 32 SNPs in SRD5A1, SRD5A2, and CYP17A1 genes using a Biotrove OpenArray NT Cycler. Clinical data were available. Genotypic and allelic frequencies, as well as haplotype analyses, were determined using the web-based environment SNPator. All additional statistical analyses comparing clinical data and SNPs were performed using PASW Statistics 15. The call rate obtained (determined as the percentage of successful determinations) was 97.3% of detection. A total of 2 SNPs in SRD5A1-rs3822430 and rs1691053-were associated with prostate-specific antigen level at diagnosis. Moreover, G carriers for both SNPs were at higher risk of presenting initial prostate-specific antigen levels>20ng/ml (Exp(B) = 2.812, 95% CI: 1.397-5.657, P = 0.004) than those who are AA-AA carriers. Haplotype analyses showed that patients with PCa nonhomozygous for the haplotype GCTTGTAGTA were at an elevated risk of presenting bigger clinical tumor size (Exp(B) = 3.823, 95% CI: 1.280-11.416, P = 0.016), and higher Gleason score (Exp(B) = 2.808, 95% CI: 1.134-6.953, P = 0.026). SNPs in SRD5A1 seem to affect the clinical characteristics of Spanish patients with PCa. Copyright © 2015 Elsevier Inc. All rights reserved.

Prostate atypia: does repeat biopsy detect clinically significant prostate cancer?

PubMed

Dorin, Ryan P; Wiener, Scott; Harris, Cory D; Wagner, Joseph R

2015-05-01

While the treatment pathway in response to benign or malignant prostate biopsies is well established, there is uncertainty regarding the risk of subsequently diagnosing prostate cancer when an initial diagnosis of prostate atypia is made. As such, we investigated the likelihood of a repeat biopsy diagnosing prostate cancer (PCa) in patients in which an initial biopsy diagnosed prostate atypia. We reviewed our prospectively maintained prostate biopsy database to identify patients who underwent a repeat prostate biopsy within one year of atypia (atypical small acinar proliferation; ASAP) diagnosis between November 1987 and March 2011. Patients with a history of PCa were excluded. Chart review identified patients who underwent radical prostatectomy (RP), radiotherapy (RT), or active surveillance (AS). For some analyses, patients were divided into two subgroups based on their date of service. Ten thousand seven hundred and twenty patients underwent 13,595 biopsies during November 1987-March 2011. Five hundred and sixty seven patients (5.3%) had ASAP on initial biopsy, and 287 (50.1%) of these patients underwent a repeat biopsy within one year. Of these, 122 (42.5%) were negative, 44 (15.3%) had atypia, 19 (6.6%) had prostatic intraepithelial neoplasia, and 102 (35.6%) contained PCa. Using modified Epstein's criteria, 27/53 (51%) patients with PCa on repeat biopsy were determined to have clinically significant tumors. 37 (36.3%) proceeded to RP, 25 (24.5%) underwent RT, and 40 (39.2%) received no immediate treatment. In patients who underwent surgery, Gleason grade on final pathology was upgraded in 11 (35.5%), and downgraded 1 (3.2%) patient. ASAP on initial biopsy was associated with a significant risk of PCa on repeat biopsy in patients who subsequently underwent definitive local therapy. Patients with ASAP should be counseled on the probability of harboring both clinically significant and insignificant prostate cancer. © 2015 Wiley Periodicals, Inc.

Using multi-scale entropy and principal component analysis to monitor gears degradation via the motor current signature analysis

NASA Astrophysics Data System (ADS)

Aouabdi, Salim; Taibi, Mahmoud; Bouras, Slimane; Boutasseta, Nadir

2017-06-01

This paper describes an approach for identifying localized gear tooth defects, such as pitting, using phase currents measured from an induction machine driving the gearbox. A new tool of anomaly detection based on multi-scale entropy (MSE) algorithm SampEn which allows correlations in signals to be identified over multiple time scales. The motor current signature analysis (MCSA) in conjunction with principal component analysis (PCA) and the comparison of observed values with those predicted from a model built using nominally healthy data. The Simulation results show that the proposed method is able to detect gear tooth pitting in current signals.

Superpixel-based spectral classification for the detection of head and neck cancer with hyperspectral imaging

NASA Astrophysics Data System (ADS)

Chung, Hyunkoo; Lu, Guolan; Tian, Zhiqiang; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

2016-03-01

Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications. HSI acquires two dimensional images at various wavelengths. The combination of both spectral and spatial information provides quantitative information for cancer detection and diagnosis. This paper proposes using superpixels, principal component analysis (PCA), and support vector machine (SVM) to distinguish regions of tumor from healthy tissue. The classification method uses 2 principal components decomposed from hyperspectral images and obtains an average sensitivity of 93% and an average specificity of 85% for 11 mice. The hyperspectral imaging technology and classification method can have various applications in cancer research and management.

Posterior cortical atrophy: an investigation of scan paths generated during face matching tasks

PubMed Central

Meek, Benjamin P.; Locheed, Keri; Lawrence-Dewar, Jane M.; Shelton, Paul; Marotta, Jonathan J.

2013-01-01

When viewing a face, healthy individuals focus more on the area containing the eyes and upper nose in order to retrieve important featural and configural information. In contrast, individuals with face blindness (prosopagnosia) tend to direct fixations toward individual facial features—particularly the mouth. Presented here is an examination of face perception deficits in individuals with Posterior Cortical Atrophy (PCA). PCA is a rare progressive neurodegenerative disorder that is characterized by atrophy in occipito-parietal and occipito-temporal cortices. PCA primarily affects higher visual processing, while memory, reasoning, and insight remain relatively intact. A common symptom of PCA is a decreased effective field of vision caused by the inability to “see the whole picture.” Individuals with PCA and healthy control participants completed a same/different discrimination task in which images of faces were presented as cue-target pairs. Eye-tracking equipment and a novel computer-based perceptual task—the Viewing Window paradigm—were used to investigate scan patterns when faces were presented in open view or through a restricted-view, respectively. In contrast to previous prosopagnosia research, individuals with PCA each produced unique scan paths that focused on non-diagnostically useful locations. This focus on non-diagnostically useful locations was also present when using a restricted viewing aperture, suggesting that individuals with PCA have difficulty processing the face at either the featural or configural level. In fact, it appears that the decreased effective field of view in PCA patients is so severe that it results in an extreme dependence on local processing, such that a feature-based approach is not even possible. PMID:23825453

Global Epigenetic Changes May Underlie Ethnic Differences and Susceptibility to Prostate Cancer

DTIC Science & Technology

2013-09-01

malignancy and can often be found in non-cancerous tissues; in the prostate, hypermethylation of the GSTP1 CpG has been detected in PIA lesions [8]. DNA...methylcytosine (5-meC; [9, 10]). Since the recognition that the GSTP1 CpG island was frequently hypermethylated in PCa, more than 40 genes have been reported to...has also been identified for several genes. One study demonstrated that GSTP1 hypermethylation was significantly higher in PCa samples from AA men

Global Epigenetic Changes May Underlie Ethnic Differences and susceptibility to Prostate Cancer

DTIC Science & Technology

2012-09-01

tissues; in the prostate, hypermethylation of the GSTP1 CpG has been detected in PIA lesions [8]. DNA methylation occurs at CpG sites in the human...that the GSTP1 CpG island was frequently hypermethylated in PCa, more than 40 genes have been reported to be targets of DNA hypermethylation-associated...One study demonstrated that GSTP1 hypermethylation was significantly higher in PCa samples from AA men in comparison with EA and Asians [12]. Another

Intelligent detection and identification in fiber-optical perimeter intrusion monitoring system based on the FBG sensor network

NASA Astrophysics Data System (ADS)

Wu, Huijuan; Qian, Ya; Zhang, Wei; Li, Hanyu; Xie, Xin

2015-12-01

A real-time intelligent fiber-optic perimeter intrusion detection system (PIDS) based on the fiber Bragg grating (FBG) sensor network is presented in this paper. To distinguish the effects of different intrusion events, a novel real-time behavior impact classification method is proposed based on the essential statistical characteristics of signal's profile in the time domain. The features are extracted by the principal component analysis (PCA), which are then used to identify the event with a K-nearest neighbor classifier. Simulation and field tests are both carried out to validate its effectiveness. The average identification rate (IR) for five sample signals in the simulation test is as high as 96.67%, and the recognition rate for eight typical signals in the field test can also be achieved up to 96.52%, which includes both the fence-mounted and the ground-buried sensing signals. Besides, critically high detection rate (DR) and low false alarm rate (FAR) can be simultaneously obtained based on the autocorrelation characteristics analysis and a hierarchical detection and identification flow.

Isolation of candidate genes for apomictic development in buffelgrass (Pennisetum ciliare).

PubMed

Singh, Manjit; Burson, Byron L; Finlayson, Scott A

2007-08-01

Asexual reproduction through seeds, or apomixis, is a process that holds much promise for agricultural advances. However, the molecular mechanisms underlying apomixis are currently poorly understood. To identify genes related to female gametophyte development in apomictic ovaries of buffelgrass (Pennisetum ciliare (L.) Link), Suppression Subtractive Hybridization of ovary cDNA with leaf cDNA was performed. Through macroarray screening of subtracted cDNAs two genes were identified, Pca21 and Pca24, that showed differential expression between apomictic and sexual ovaries. Sequence analysis showed that both Pca21 and Pca24 are novel genes not previously characterized in plants. Pca21 shows homology to two wheat genes that are also expressed during reproductive development. Pca24 has similarity to coiled-coil-helix-coiled-coil-helix (CHCH) domain containing proteins from maize and sugarcane. Northern blot analysis revealed that both of these genes are expressed throughout female gametophyte development in apomictic ovaries. In situ hybridizations localized the transcript of these two genes to the developing embryo sacs in the apomictic ovaries. Based on the expression patterns it was concluded that Pca21 and Pca24 likely play a role during apomictic development in buffelgrass.

Motor features in posterior cortical atrophy and their imaging correlates.

PubMed

Ryan, Natalie S; Shakespeare, Timothy J; Lehmann, Manja; Keihaninejad, Shiva; Nicholas, Jennifer M; Leung, Kelvin K; Fox, Nick C; Crutch, Sebastian J

2014-12-01

Posterior cortical atrophy (PCA) is a neurodegenerative syndrome characterized by impaired higher visual processing skills; however, motor features more commonly associated with corticobasal syndrome may also occur. We investigated the frequency and clinical characteristics of motor features in 44 PCA patients and, with 30 controls, conducted voxel-based morphometry, cortical thickness, and subcortical volumetric analyses of their magnetic resonance imaging. Prominent limb rigidity was used to define a PCA-motor subgroup. A total of 30% (13) had PCA-motor; all demonstrating asymmetrical left upper limb rigidity. Limb apraxia was more frequent and asymmetrical in PCA-motor, as was myoclonus. Tremor and alien limb phenomena only occurred in this subgroup. The subgroups did not differ in neuropsychological test performance or apolipoprotein E4 allele frequency. Greater asymmetry of atrophy occurred in PCA-motor, particularly involving right frontoparietal and peri-rolandic cortices, putamen, and thalamus. The 9 patients (including 4 PCA-motor) with pathology or cerebrospinal fluid all showed evidence of Alzheimer's disease. Our data suggest that PCA patients with motor features have greater atrophy of contralateral sensorimotor areas but are still likely to have underlying Alzheimer's disease. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Clinical efficacy of transrectal ultrasound-guided prostate biopsy in men younger than 50 years old with an elevated prostate-specific antigen concentration (>4.0 ng/mL).

PubMed

Lu, Chin-Heng; Lin, Tzu-Ping; Shen, She Huei; Huang, Yi-Hsiu; Chung, Hsiao-Jen; Kuo, Junne-Yih; Huang, William J S; Wu, Howard H H; Chang, Yen-Hwa; Lin, Alex T L; Chen, Kuang-Kuo

2017-07-01

Prostate cancer (PCa) is not commonly found in men younger than 50 years of age. However, serum prostate-specific antigen (PSA) concentration has been examined more frequently at a younger age in Asia partially due to an increased awareness of prostate cancer. The purpose of our study was to investigate the efficacy and complication of PSA-triggered transrectal ultrasonography-guided prostate (TRUSP) biopsies. We retrospectively reviewed TRUSP biopsies in young men with elevated PSA concentration in Taipei Veterans General Hospital. We reviewed the cases of patients younger than 50 years of age with elevated PSA concentration (>4.0 ng/mL), who received 12 cores TRUSP biopsies at TPEVGH from January 2008-December 2013. The age, family history, digital rectal examination (DRE) results, PSA concentration, free/total PSA ratio, total prostate volume, PSA density, lower urinary tract symptoms and complications after the procedure were reviewed. The pathologic findings of TRUSP biopsy and clinical follow-up were reviewed and analyzed according to the Epstein criteria. A total of 77 patients were included and were divided into 2 groups: 1) the younger group consisted of 20 patients <40 years of age; and 2) the elder group had 57 patients who were 40-50 years of age. The overall detection rate of PCa was 11.69% (9/77), and all of the PCa cases were diagnosed in the elder group (group detection rate: 15.8%). There was a significant difference in the severity of lower urinary tract symptoms (LUTS) between these 2 groups. All PCa patients were clinically significant according to the Epstein criteria. Two patients experienced fever (2.60%) after TRUSP biopsy. From our patient cohort, it appears that no benefit was apparent for patients younger than 40 years old who received TRUSP biopsy, even with elevated PSA. However, PCa detected in men between 40 and 50 years of age were all clinically significant. Overall, our results supported current major practice guidelines which recommend an initial PSA checkup at 40 years of age. Copyright © 2017. Published by Elsevier Taiwan LLC.

Metabolic syndrome is not associated with greater evidences of proliferative inflammatory atrophy and inflammation in patients with suspected prostate cancer.

PubMed

Russo, Giorgio I; Cimino, Sebastiano; Giranio, Giorgia; Regis, Federica; Favilla, Vincenzo; Privitera, Salvatore; Motta, Fabio; Caltabiano, Rosario; Stenzl, Arnulf; Todenhöfer, Tilman; Morgia, Giuseppe

2018-05-01

To evaluate the association between metabolic syndrome (MetS) and proliferative inflammatory atrophy (PIA) in patients with suspected prostate cancer (PCa). From June 2015 to July 2016, we conducted the FIERY (Flogosis Increased Events of pRostatic biopsY) study at the Urology section, Department of Surgery of the University of Catania (Local registration number: #131/2015). A total of 205 patients with elevated prostate-specific antigen (≥ 4 ng/ml) or clinical suspicion of PCa who underwent primary transperineal prostate biopsy were included in this cross-sectional study. The assessment of PIA, HGPIN, and PCa were performed by 2 experienced pathologists and samples were investigated for the presence of an inflammatory infiltrate, according to the Irani score. Primary and secondary Gleason grade of tumor in positive biopsies were evaluated according to the 2016 ISUP Modified Gleason System. In the entire cohort, median age was 68.0 (interquartile range: 62.0-74.5), median prostate-specific antigen was 6.5 (interquartile range: 5.51-9.57). The prevalence of MetS was 34.1%, the detection rate of PCa was 32.7%, the rate of PIA was 28.3%, the rate of HGPIN was 32.2%, whereas the rate of severe intraprostatic inflammation (Irani-score ≥4) was 28.8%. When comparing clinical and histological variables in patients without and with PIA, metabolic aberrations where not significantly different in both groups. We did not find statistical association in detection rate of PCa (29.3% vs. 34.0%; P = 0.07) and HGPIN (27.6% vs. 34.0%; P = 0.37) in patients with and without PIA, respectively. When considering metabolic aberrations, MetS was not associated with Irani-score ≥4 (28.6% vs. 28.4%; P = 0.96) and none of each component was statistically predictive of severe inflammation. At the multivariable logistic regression analysis, PIA, HGPIN, and MetS were not associated with greater risk of PCa. In this study, we did not show an association between MetS and PIA and PCa. Although the small sample size and the cross-sectional nature of the study, we do not suppose that MetS could be associated with greater evidence of PIA. Further studies should be conducted to evaluate the exact nature of this pathological lesion. Copyright © 2018 Elsevier Inc. All rights reserved.

Estrogen induces androgen-repressed SOX4 expression to promote progression of prostate cancer cells.

PubMed

Yang, Muyi; Wang, Jing; Wang, Lin; Shen, Chengwu; Su, Bo; Qi, Mei; Hu, Jing; Gao, Wei; Tan, Weiwei; Han, Bo

2015-09-01

The sex determing region Y-box 4 (SOX4) gene is a critical developmental transcriptional factor that is overexpressed in prostate cancer (PCa). While we and others have investigated the role of SOX4 overexpression in PCa, the molecular mechanism underlying its aberrant expression remains unclear. Immunohistochemistry were utilized to detect SOX4 expression and the correlation between estrogen receptor β (ERβ), androgen receptor (AR) and SOX4 in a cohort of 94 clinical specimens. Real-time quantitative PCR and Western blotting were used to study the transcript and protein expression levels. Immunofluorescence staining and co-immunoprecipitation were performed to assess the interaction and subcellular location of ERβ and AR. Chromatin immunoprecipitation (ChIP) assays and Luciferase reporter assays were performed to explore the binding and transcriptional activities of ERβ and AR to the SOX4 promoter. Cellular function was evaluated by MTS, invasion and wound healing assays. SOX4 expression is up-regulated in Castration-Resistant Prostate Cancer (CRPC) tumors compared to hormone-dependent PCa (HDPC) cases. Increased expression was also observed in PCa cells after long-term androgen-deprivation treatment (ADT). In vitro data indicated that SOX4 is an AR transcriptional target and down-regulated by dihydrotestosterone (DHT) via AR. 17β-estradiol (E2) up-regulates SOX4 expression in the absence of androgen through the formation of a protein complex between ERβ and AR. Knockdown of AR or ERβ blocks the E2-induced SOX4 expression. ChIP assays confirmed that both ERβ and AR bind to the SOX4 promoter in response to E2. Functionally, silencing SOX4 significantly attenuates the proliferative effect, as well as the capacity of migration and invasion of E2 on PCa cells. Clinically, overexpression of SOX4 is significantly associated with ERβ expression in PCa. In addition, this association is still retained in CRPC patients with poor prognosis. These findings suggest that SOX4 is a novel DHT-repressed AR-target gene. E2 could promote proliferation of PCa cells through the up-regulation of SOX4 under androgen-depleted environment. Our data provides a possible molecular basis for the overexpression of SOX4 in CRPC and may facilitate the detection and prevention of the emergence of CRPC. © 2015 Wiley Periodicals, Inc.

Is Eotaxin-1 a serum and urinary biomarker for prostate cancer detection and recurrence?

PubMed

Heidegger, Isabel; Höfer, Julia; Luger, Markus; Pichler, Renate; Klocker, Helmut; Horninger, Wolfgang; Steiner, Eberhard; Jochberger, Stefan; Culig, Zoran

2015-12-01

Eotaxin-1 (CCL11) is a protein expressed in various tissues influencing immunoregulatory processes by acting as selective eosinophil chemo-attractant. In prostate cancer (PCa), the expression and functional role of CCL11 have not been intensively investigated so far. Therefore, the aim of the present study was to investigate the diagnostic or prognostic potential of Eotaxin-1 in PCa patients. We analyzed serum from 140 patients who have undergone prostate biopsy due to elevated prostate-specific antigen (PSA) levels as well as serum of 20 individuals with PSA levels < 1ng/ml (healthy control group). Moreover, 40 urine samples were analyzed. A custom-made Q-Plex array ELISA (Quansys Biosciences) for the detection of Eotaxin-1 was performed and Q-View Software used for quantification. In addition, clinical courses of patients documented in our Prostate Biobank database were analyzed. ROC and survival analyses were used to determine the diagnostic and prognostic power of Eotaxin-1 levels. Serum Eotaxin-1 levels were significantly decreased in PCa (P = 0.006) as well as in benign prostate hyperplasia (P = 0.0006) compared to the control group. ROC analysis revealed that Eotaxin-1 is a significant marker to distinguish PCa from disease-free prostate. Moreover, we found that Eotaxin-1 expression is significantly decreased in Gleason score (GS) 6 (P = 0.0135) and GS 8 (P = 0.0057) patients compared to samples of healthy men, respectively. However, PCa aggressiveness was not predictable by Eotaxin-1 levels. In line with serum analyses, urine Eotaxin-1 was significantly decreased in patients with PCa compared to cancer-free individuals (P = 0.0185) but was not different between cancers of different GS. Patientś follow-up analyses showed no significant correlation between serum Eotaxin-1 levels and time to biochemical recurrence. Survival analyses also revealed no significant changes in progression-free survival among low (≤ 112.2 pg/ml) and high (> 112.2 pg/ml) Eotaxin-1 serum levels. Although this study has not established a prognostic role of Eotaxin-1 in PCa patients, this chemokine may serve as a diagnostic marker to distinguish between disease-free prostate and cancer. © 2015 Wiley Periodicals, Inc.

Regulation of tissue factor in NT2 germ cell tumor cells by cisplatin chemotherapy.

PubMed

Jacobsen, Christine; Oechsle, Karin; Hauschild, Jessica; Steinemann, Gustav; Spath, Brigitte; Bokemeyer, Carsten; Ruf, Wolfram; Honecker, Friedemann; Langer, Florian

2015-09-01

Patients with germ cell tumors (GCTs) receiving cisplatin-based chemotherapy are at increased risk of thrombosis, but the underlying cellular and molecular mechanisms remain obscure. To study baseline tissue factor (TF) expression by GCT cell lines and its modulation by cisplatin treatment. TF expression was assessed by single-stage clotting and thrombin generation assay, flow cytometry, ELISA, and Western blot analysis. Cell cycle analysis and detection of phosphatidylserine (PS) membrane exposure were carried out by flow cytometry. TF mRNA was analyzed by quantitative RT-PCR. Significant expression of TF-specific procoagulant activity (PCA) was detected on three non-seminoma (NT2, 2102Ep, NCCIT) and one seminoma cell line (TCam-2). Treatment with 0.4μM cisplatin (corresponding to the IC50) for 48hrs increased TF PCA on NT2 cells 3-fold, an effect that was largely independent of PS exposure and that could not be explained by translocation of active TF from intracellular storage pools. Cisplatin-induced TF PCA expression in NT2 cells did not occur before 12hrs, but was steady thereafter and accompanied by a 2-fold increase in total and surface-located TF antigen. Importantly, increased TF gene transcription or production and release of an intermediate factor were not involved in this process. Cell cycle analysis suggested that cisplatin-induced G2/M arrest resulted in an accumulation of procoagulant TF on the membrane surface of NT2 cells. In addition to induction of apoptosis/necrosis with PS-mediated activation of preformed TF, cisplatin may alter the procoagulant phenotype of GCT cells through an increase in total cellular TF antigen. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Association Between Calcium Channel Blocker Use and Prostate Cancer Outcome

PubMed Central

Poch, Michael A.; Mehedint, Diana; Green, Dawn J.; Payne-Ondracek, Rochelle; Fontham, Elizabeth T.H.; Bensen, Jeannette T.; Attwood, Kristopher; Wilding, Gregory E.; Guru, Khurshid A.; Underwood, Willie; Mohler, James L.; Heemers, Hannelore V.

2018-01-01

BACKGROUND Epidemiological studies indicate that calcium channel blocker (CCB) use is inversely related to prostate cancer (PCa) incidence. The association between CCB use and PCa aggressiveness at the time of radical prostatectomy (RP) and outcome after RP was examined. METHODS Medication use, PCa aggressiveness and post-RP outcome were retrieved from a prospectively populated database that contains clinical and outcome for RP patients at Roswell Park Cancer Institute (RPCI) from 1993 to 2010. The database was queried for anti-hypertensive medication use at diagnosis for patients with ≥1 year follow-up. Recurrence was defined using NCCN guidelines. Chi-Square tests assessed the relationship between CCB use and PCa aggressiveness. Cox regression models compared the distribution of progression-free survival (PFS) and overall survival (OS) with adjustment for covariates. Results for association between CCB usage and PCa aggressiveness were validated using data from the population-based North Carolina-Louisiana Prostate Cancer Project (PCaP). RESULTS 48%, 37%, and 15% of RPCI’s RP patients (n = 875) had low, intermediate, and high aggressive PCa, respectively. 104 (11%) had a history of CCB use. Patients taking CCBs were more likely to be older, have a higher BMI and use additional anti-hypertensive medications. Diagnostic PSA levels, PCa aggressiveness, and margin status were similar for CCB users and non-users. PFS and OS did not differ between the two groups. Tumor aggressiveness was associated with PFS. CCB use in the PCaP study population was not associated with PCa aggressiveness. CONCLUSIONS CCB use is not associated with PCa aggressiveness at diagnosis, PFS or OS. PMID:23280547

Geochemical modeling of orogenic gold deposit using PCANN hybrid method in the Alut, Kurdistan province, Iran

NASA Astrophysics Data System (ADS)

Mohammadzadeh, Mohammadjafar; Nasseri, Aynur

2018-03-01

In this paper stream sediments based geochemical exploration program with the aim of delineating potentially promising areas by a comprehensive stepwise optimization approach from univariate statistics, PCA, ANN, and fusion method PCANN were under taken for an orogenic gold deposit located in the Alut, Kurdistan province, NW of Iran. At first the data were preprocessed and then PCA were applied to determine the maximum variability directions of elements in the area. Subsequently the artificial neural network (ANN) was used for quick estimation of elemental concentration, as well as discriminating anomalous populations and intelligent determination of internal structure among the data. However, both the methods revealed constraints for modeling. To overcome the deficiency and shortcoming of each individual method a new methodology is presented by integration of both "PCA & ANN" referred as PCANN method. For integrating purpose, the detected PCs pertinent to ore mineralization selected and intruded to neural network structure, as a result different MLPs with various algorithms and structures were produced. The resulting PCANN maps suggest that the gold mineralization and its pathfinder elements (Au, Mo, W, Bi, Sb, Cu, Pb, Ag & As) are associated with metamorphic host rocks intruded by granite bodies in the Alut area. In addition, more concealed and distinct Au anomalies with higher intensity were detected, confirming the privileges of the method in evaluating susceptibility of the area in delineating new hidden potential zones. The proposed method demonstrates simpler network architecture, easy computational implementation, faster training speed, as well as no need to consider any primary assumption about the behavior of data and their probability distribution type, with more satisfactory predicting performance for generating gold potential map of the area. Comparing the results of three methods (PCA, ANN and PCANN), representing the higher efficiency and more reliability of PCANN with lesser training time, simple structure, and correlate components while avoiding the duplicate entry of data to network. This study also suggests that in many similar cases integrated methods have capability to fix bugs more effectively and successfully in exploration programs.

Motorcyclists safety system to avoid rear end collisions based on acoustic signatures

NASA Astrophysics Data System (ADS)

Muzammel, M.; Yusoff, M. Zuki; Malik, A. Saeed; Mohamad Saad, M. Naufal; Meriaudeau, F.

2017-03-01

In many Asian countries, motorcyclists have a higher fatality rate as compared to other vehicles. Among many other factors, rear end collisions are also contributing for these fatalities. Collision detection systems can be useful to minimize these accidents. However, the designing of efficient and cost effective collision detection system for motorcyclist is still a major challenge. In this paper, an acoustic information based, cost effective and efficient collision detection system is proposed for motorcycle applications. The proposed technique uses the Short time Fourier Transform (STFT) to extract the features from the audio signal and Principal component analysis (PCA) has been used to reduce the feature vector length. The reduction of feature length, further increases the performance of this technique. The proposed technique has been tested on self recorded dataset and gives accuracy of 97.87%. We believe that this method can help to reduce a significant number of motorcycle accidents.

On a PCA-based lung motion model

PubMed Central

Li, Ruijiang; Lewis, John H; Jia, Xun; Zhao, Tianyu; Liu, Weifeng; Wuenschel, Sara; Lamb, James; Yang, Deshan; Low, Daniel A; Jiang, Steve B

2014-01-01

Respiration-induced organ motion is one of the major uncertainties in lung cancer radiotherapy and is crucial to be able to accurately model the lung motion. Most work so far has focused on the study of the motion of a single point (usually the tumor center of mass), and much less work has been done to model the motion of the entire lung. Inspired by the work of Zhang et al (2007 Med. Phys. 34 4772–81), we believe that the spatiotemporal relationship of the entire lung motion can be accurately modeled based on principle component analysis (PCA) and then a sparse subset of the entire lung, such as an implanted marker, can be used to drive the motion of the entire lung (including the tumor). The goal of this work is twofold. First, we aim to understand the underlying reason why PCA is effective for modeling lung motion and find the optimal number of PCA coefficients for accurate lung motion modeling. We attempt to address the above important problems both in a theoretical framework and in the context of real clinical data. Second, we propose a new method to derive the entire lung motion using a single internal marker based on the PCA model. The main results of this work are as follows. We derived an important property which reveals the implicit regularization imposed by the PCA model. We then studied the model using two mathematical respiratory phantoms and 11 clinical 4DCT scans for eight lung cancer patients. For the mathematical phantoms with cosine and an even power (2n) of cosine motion, we proved that 2 and 2n PCA coefficients and eigenvectors will completely represent the lung motion, respectively. Moreover, for the cosine phantom, we derived the equivalence conditions for the PCA motion model and the physiological 5D lung motion model (Low et al 2005 Int. J. Radiat. Oncol. Biol. Phys. 63 921–9). For the clinical 4DCT data, we demonstrated the modeling power and generalization performance of the PCA model. The average 3D modeling error using PCA was within 1 mm (0.7 ± 0.1 mm). When a single artificial internal marker was used to derive the lung motion, the average 3D error was found to be within 2 mm (1.8 ± 0.3 mm) through comprehensive statistical analysis. The optimal number of PCA coefficients needs to be determined on a patient-by-patient basis and two PCA coefficients seem to be sufficient for accurate modeling of the lung motion for most patients. In conclusion, we have presented thorough theoretical analysis and clinical validation of the PCA lung motion model. The feasibility of deriving the entire lung motion using a single marker has also been demonstrated on clinical data using a simulation approach. PMID:21865624

Reconstruction Error and Principal Component Based Anomaly Detection in Hyperspectral Imagery

DTIC Science & Technology

2014-03-27

2003), and (Jackson D. A., 1993). In 1933, Hotelling ( Hotelling , 1933), who coined the term ‘principal components,’ surmised that there was a...goodness of fit and multivariate quality control with the statistic Qi = (Xi(1×p) − X̂i(1×p) )(Xi(1×p) − X̂i(1×p) ) T (20) where, under the...sparsely targeted scenes through SNR or other methods. 5) Customize sorting and histogram construction methods in Multiple PCA to avoid redundancy

The monoamine oxidase A gene promoter repeat and prostate cancer risk.

PubMed

White, Thomas A; Kwon, Erika M; Fu, Rong; Lucas, Jared M; Ostrander, Elaine A; Stanford, Janet L; Nelson, Peter S

2012-11-01

Amine catabolism by monoamine oxidase A (MAOA) contributes to oxidative stress, which plays a role in prostate cancer (PCa) development and progression. An upstream variable-number tandem repeat (uVNTR) in the MAOA promoter influences gene expression and activity, and may thereby affect PCa susceptibility. Caucasian (n = 2,572) men from two population-based case-control studies of PCa were genotyped for the MAOA-VNTR. Logistic regression was used to assess PCa risk in relation to genotype. Common alleles of the MAOA-VNTR were not associated with the relative risk of PCa, nor did the relationship differ by clinical features of the disease. The rare 5-copy variant (frequency: 0.5% in cases; 1.8% in controls), however, was associated with a reduced PCa risk (odds ratio, OR = 0.30, 95% CI 0.13-0.71). A rare polymorphism of the MAOA promoter previously shown to confer low expression was associated with a reduced risk of developing PCa. This novel finding awaits confirmation in other study populations. Copyright © 2012 Wiley Periodicals, Inc.

Decreased expression of serine protease inhibitor family G1 (SERPING1) in prostate cancer can help distinguish high-risk prostate cancer and predicts malignant progression.

PubMed

Peng, Shengmeng; Du, Tao; Wu, Wanhua; Chen, Xianju; Lai, Yiming; Zhu, Dingjun; Wang, Qiong; Ma, Xiaoming; Lin, Chunhao; Li, Zean; Guo, Zhenghui; Huang, Hai

2018-06-11

The aim of this study was to investigate the associations of serine proteinase inhibitor family G1 (SERPING1) down-regulation with poor prognosis in patients with prostate cancer (PCa). Furthermore, we aim to find more novel and effective PCa molecular markers to provide an early screening of PCa, distinguish patients with aggressive PCa, predict the prognosis, or reduce the economic burden of PCa. SERPING1 protein expression in both human PCa and normal prostate tissues was detected by immunohistochemical staining, which intensity was analyzed in association with clinical pathological parameters such Gleason score, pathological grade, clinical stage, tumor stage, lymph node metastasis, and distant metastasis. Moreover, we used The Cancer Genome Atlas (TCGA) Database, Taylor Database, and Oncomine dataset to validate our immunohistochemical results and investigated the value of SERPING1 in PCa at mRNA level. Kaplan-Meier analysis and Cox regression analysis were performed to evaluate the relationship between SERPING1 and prognosis of patients with PCa. The outcome showed that SERPING1 was expressed mainly in cytoplasm of grand cells of prostate tissue and was significantly expressed less in PCa (P<0.001). Furthermore, in the tissue microarray of our samples, decreasing expression of SERPING1 was correlated with the higher Gleason score (P = 0.004), the higher pathological grade (P = 0.01) and the advanced tumor stage (P = 0.005) at protein level. In TCGA dataset and Taylor Dataset, low-expressed SERPING1 was correlated with the younger patient (P = 0.02 in TCGA, P = 0.044 in Taylor) and the higher Gleason score (P = 0.019 in TCGA, P<0.001 in Taylor) at mRNA level. Kaplan-Meier analysis revealed that the lower mRNA of SERPING1 predicted lower overall survivals (P = 0.027 in TCGA), lower disease-free survival (P = 0.029) and lower biochemical recurrence-free survival (P = 0.011 in Taylor). Data from Oncomine database shown that SERPING1 low expression implying higher malignancy of prostate lesions. Using multivariate analysis, we also found that SERPING1 expression was independent prognostic marker of poor disease-free survival and biochemical recurrence-free survival. SERPING1 may play an important role in PCa and can be serve as a novel marker in diagnosis and prognostic prediction in PCa. In addition, levels of SERPING1 can help identify low-risk prostate to provide reference for patients with PCa to accept active surveillance and reduce overtreatment. Copyright © 2018 Elsevier Inc. All rights reserved.

Patient-specific pharmacokinetic parameter estimation on dynamic contrast-enhanced MRI of prostate: Preliminary evaluation of a novel AIF-free estimation method.

PubMed

Ginsburg, Shoshana B; Taimen, Pekka; Merisaari, Harri; Vainio, Paula; Boström, Peter J; Aronen, Hannu J; Jambor, Ivan; Madabhushi, Anant

2016-12-01

To develop and evaluate a prostate-based method (PBM) for estimating pharmacokinetic parameters on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) by leveraging inherent differences in pharmacokinetic characteristics between the peripheral zone (PZ) and transition zone (TZ). This retrospective study, approved by the Institutional Review Board, included 40 patients who underwent a multiparametric 3T MRI examination and subsequent radical prostatectomy. A two-step PBM for estimating pharmacokinetic parameters exploited the inherent differences in pharmacokinetic characteristics associated with the TZ and PZ. First, the reference region model was implemented to estimate ratios of K trans between normal TZ and PZ. Subsequently, the reference region model was leveraged again to estimate values for K trans and v e for every prostate voxel. The parameters of PBM were compared with those estimated using an arterial input function (AIF) derived from the femoral arteries. The ability of the parameters to differentiate prostate cancer (PCa) from benign tissue was evaluated on a voxel and lesion level. Additionally, the effect of temporal downsampling of the DCE MRI data was assessed. Significant differences (P < 0.05) in PBM K trans between PCa lesions and benign tissue were found in 26/27 patients with TZ lesions and in 33/38 patients with PZ lesions; significant differences in AIF-based K trans occurred in 26/27 and 30/38 patients, respectively. The 75 th and 100 th percentiles of K trans and v e estimated using PBM positively correlated with lesion size (P < 0.05). Pharmacokinetic parameters estimated via PBM outperformed AIF-based parameters in PCa detection. J. Magn. Reson. Imaging 2016;44:1405-1414. © 2016 International Society for Magnetic Resonance in Medicine.

Patient-Specific Pharmacokinetic Parameter Estimation on Dynamic Contrast-Enhanced MRI of Prostate: Preliminary Evaluation of a Novel AIF-Free Estimation Method

PubMed Central

Ginsburg, Shoshana B.; Taimen, Pekka; Merisaari, Harri; Vainio, Paula; Boström, Peter J.; Aronen, Hannu J.; Jambor, Ivan; Madabhushi, Anant

2017-01-01

Purpose To develop and evaluate a prostate-based method (PBM) for estimating pharmacokinetic parameters on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) by leveraging inherent differences in pharmacokinetic characteristics between the peripheral zone (PZ) and transition zone (TZ). Materials and Methods This retrospective study, approved by the Institutional Review Board, included 40 patients who underwent a multiparametric 3T MRI examination and subsequent radical prostatectomy. A two-step PBM for estimating pharmacokinetic parameters exploited the inherent differences in pharmacokinetic characteristics associated with the TZ and PZ. First, the reference region model was implemented to estimate ratios of Ktrans between normal TZ and PZ. Subsequently, the reference region model was leveraged again to estimate values for Ktrans and ve for every prostate voxel. The parameters of PBM were compared with those estimated using an arterial input function (AIF) derived from the femoral arteries. The ability of the parameters to differentiate prostate cancer (PCa) from benign tissue was evaluated on a voxel and lesion level. Additionally, the effect of temporal downsampling of the DCE MRI data was assessed. Results Significant differences (P < 0.05) in PBM Ktrans between PCa lesions and benign tissue were found in 26/27 patients with TZ lesions and in 33/38 patients with PZ lesions; significant differences in AIF-based Ktrans occurred in 26/27 and 30/38 patients, respectively. The 75th and 100th percentiles of Ktrans and ve estimated using PBM positively correlated with lesion size (P < 0.05). Conclusion Pharmacokinetic parameters estimated via PBM outperformed AIF-based parameters in PCa detection. PMID:27285161

Investigation of gastric cancers in nude mice using X-ray in-line phase contrast imaging.

PubMed

Tao, Qiang; Luo, Shuqian

2014-07-24

This paper is to report the new imaging of gastric cancers without the use of imaging agents. Both gastric normal regions and gastric cancer regions can be distinguished by using the principal component analysis (PCA) based on the gray level co-occurrence matrix (GLCM). Human gastric cancer BGC823 cells were implanted into the stomachs of nude mice. Then, 3, 5, 7, 9 or 11 days after cancer cells implantation, the nude mice were sacrificed and their stomachs were removed. X-ray in-line phase contrast imaging (XILPCI), an X-ray phase contrast imaging method, has greater soft tissue contrast than traditional absorption radiography and generates higher-resolution images. The gastric specimens were imaged by an XILPCIs' charge coupled device (CCD) of 9 μm image resolution. The PCA of the projective images' region of interests (ROIs) based on GLCM were extracted to discriminate gastric normal regions and gastric cancer regions. Different stages of gastric cancers were classified by using support vector machines (SVMs). The X-ray in-line phase contrast images of nude mice gastric specimens clearly show the gastric architectures and the details of the early gastric cancers. The phase contrast computed tomography (CT) images of nude mice gastric cancer specimens are better than the traditional absorption CT images without the use of imaging agents. The results of the PCA of the texture parameters based on GLCM of normal regions is (F1+F2) >8.5, but those of cancer regions is (F1+F2) <8.5. The classification accuracy is 83.3% that classifying gastric specimens into different stages using SVMs. This is a very preliminary feasibility study. With further researches, XILPCI could become a noninvasive method for future the early detection of gastric cancers or medical researches.

An unusual haplotype structure on human chromosome 8p23 derived from the inversion polymorphism.

PubMed

Deng, Libin; Zhang, Yuezheng; Kang, Jian; Liu, Tao; Zhao, Hongbin; Gao, Yang; Li, Chaohua; Pan, Hao; Tang, Xiaoli; Wang, Dunmei; Niu, Tianhua; Yang, Huanming; Zeng, Changqing

2008-10-01

Chromosomal inversion is an important type of genomic variations involved in both evolution and disease pathogenesis. Here, we describe the refined genetic structure of a 3.8-Mb inversion polymorphism at chromosome 8p23. Using HapMap data of 1,073 SNPs generated from 209 unrelated samples from CEPH-Utah residents with ancestry from northern and western Europe (CEU); Yoruba in Ibadan, Nigeria (YRI); and Asian (ASN) samples, which were comprised of Han Chinese from Beijing, China (CHB) and Japanese from Tokyo, Japan (JPT)-we successfully deduced the inversion orientations of all their 418 haplotypes. In particular, distinct haplotype subgroups were identified based on principal component analysis (PCA). Such genetic substructures were consistent with clustering patterns based on neighbor-joining tree reconstruction, which revealed a total of four haplotype clades across all samples. Metaphase fluorescence in situ hybridization (FISH) in a subset of 10 HapMap samples verified their inversion orientations predicted by PCA or phylogenetic tree reconstruction. Positioning of the outgroup haplotype within one of YRI clades suggested that Human NCBI Build 36-inverted order is most likely the ancestral orientation. Furthermore, the population differentiation test and the relative extended haplotype homozygosity (REHH) analysis in this region discovered multiple selection signals, also in a population-specific manner. A positive selection signal was detected at XKR6 in the ASN population. These results revealed the correlation of inversion polymorphisms to population-specific genetic structures, and various selection patterns as possible mechanisms for the maintenance of a large chromosomal rearrangement at 8p23 region during evolution. In addition, our study also showed that haplotype-based clustering methods, such as PCA, can be applied in scanning for cryptic inversion polymorphisms at a genome-wide scale.

Scene perception in posterior cortical atrophy: categorization, description and fixation patterns.

PubMed

Shakespeare, Timothy J; Yong, Keir X X; Frost, Chris; Kim, Lois G; Warrington, Elizabeth K; Crutch, Sebastian J

2013-01-01

Partial or complete Balint's syndrome is a core feature of the clinico-radiological syndrome of posterior cortical atrophy (PCA), in which individuals experience a progressive deterioration of cortical vision. Although multi-object arrays are frequently used to detect simultanagnosia in the clinical assessment and diagnosis of PCA, to date there have been no group studies of scene perception in patients with the syndrome. The current study involved three linked experiments conducted in PCA patients and healthy controls. Experiment 1 evaluated the accuracy and latency of complex scene perception relative to individual faces and objects (color and grayscale) using a categorization paradigm. PCA patients were both less accurate (faces < scenes < objects) and slower (scenes < objects < faces) than controls on all categories, with performance strongly associated with their level of basic visual processing impairment; patients also showed a small advantage for color over grayscale stimuli. Experiment 2 involved free description of real world scenes. PCA patients generated fewer features and more misperceptions than controls, though perceptual errors were always consistent with the patient's global understanding of the scene (whether correct or not). Experiment 3 used eye tracking measures to compare patient and control eye movements over initial and subsequent fixations of scenes. Patients' fixation patterns were significantly different to those of young and age-matched controls, with comparable group differences for both initial and subsequent fixations. Overall, these findings describe the variability in everyday scene perception exhibited by individuals with PCA, and indicate the importance of exposure duration in the perception of complex scenes.

A Neighborhood-Based Intervention to Reduce Prostate Cancer Disparities

DTIC Science & Technology

2017-10-01

for men from the neighborhoods. We also began recruitment and sessions to test the PCa educational intervention. Results: Focus group participants had...making about PCa screening Sub-aim 4: To observe the rates of PCa screening in the intervention and control groups 2. Keywords Prostate Cancer...mobilization of community health workers from high risk neighborhoods. Recruitment and conduct of “ control ” group educational sessions. Establishment of

IMPROVED SEARCH OF PRINCIPAL COMPONENT ANALYSIS DATABASES FOR SPECTRO-POLARIMETRIC INVERSION

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

Casini, R.; Lites, B. W.; Ramos, A. Asensio

2013-08-20

We describe a simple technique for the acceleration of spectro-polarimetric inversions based on principal component analysis (PCA) of Stokes profiles. This technique involves the indexing of the database models based on the sign of the projections (PCA coefficients) of the first few relevant orders of principal components of the four Stokes parameters. In this way, each model in the database can be attributed a distinctive binary number of 2{sup 4n} bits, where n is the number of PCA orders used for the indexing. Each of these binary numbers (indices) identifies a group of ''compatible'' models for the inversion of amore » given set of observed Stokes profiles sharing the same index. The complete set of the binary numbers so constructed evidently determines a partition of the database. The search of the database for the PCA inversion of spectro-polarimetric data can profit greatly from this indexing. In practical cases it becomes possible to approach the ideal acceleration factor of 2{sup 4n} as compared to the systematic search of a non-indexed database for a traditional PCA inversion. This indexing method relies on the existence of a physical meaning in the sign of the PCA coefficients of a model. For this reason, the presence of model ambiguities and of spectro-polarimetric noise in the observations limits in practice the number n of relevant PCA orders that can be used for the indexing.« less

Biological Evaluation and Molecular Docking of Protocatechuic Acid from Hibiscus sabdariffa L. as a Potent Urease Inhibitor by an ESI-MS Based Method.

PubMed

Hassan, Sherif T S; Švajdlenka, Emil

2017-10-11

Studies on enzyme inhibition remain a crucial area in drug discovery since these studies have led to the discoveries of new lead compounds useful in the treatment of several diseases. In this study, protocatechuic acid (PCA), an active compound from Hibiscus sabdariffa L. has been evaluated for its inhibitory properties against jack bean urease (JBU) as well as its possible toxic effect on human gastric epithelial cells (GES-1). Anti-urease activity was evaluated by an Electrospray Ionization-Mass Spectrometry (ESI-MS) based method, while cytotoxicity was assayed by the MTT method. PCA exerted notable anti-JBU activity compared with that of acetohydroxamic acid (AHA), with IC 50 values of 1.7 and 3.2 µM, respectively. PCA did not show any significant cytotoxic effect on (GES-1) cells at concentrations ranging from 1.12 to 3.12 µM. Molecular docking study revealed high spontaneous binding ability of PCA to the active site of urease. Additionally, the anti-urease activity was found to be related to the presence of hydroxyl moieties of PCA. This study presents PCA as a natural urease inhibitor, which could be used safely in the treatment of diseases caused by urease-producing bacteria.

Investigation of domain walls in PPLN by confocal raman microscopy and PCA analysis

NASA Astrophysics Data System (ADS)

Shur, Vladimir Ya.; Zelenovskiy, Pavel; Bourson, Patrice

2017-07-01

Confocal Raman microscopy (CRM) is a powerful tool for investigation of ferroelectric domains. Mechanical stresses and electric fields existed in the vicinity of neutral and charged domain walls modify frequency, intensity and width of spectral lines [1], thus allowing to visualize micro- and nanodomain structures both at the surface and in the bulk of the crystal [2,3]. Stresses and fields are naturally coupled in ferroelectrics due to inverse piezoelectric effect and hardly can be separated in Raman spectra. PCA is a powerful statistical method for analysis of large data matrix providing a set of orthogonal variables, called principal components (PCs). PCA is widely used for classification of experimental data, for example, in crystallization experiments, for detection of small amounts of components in solid mixtures etc. [4,5]. In Raman spectroscopy PCA was applied for analysis of phase transitions and provided critical pressure with good accuracy [6]. In the present work we for the first time applied Principal Component Analysis (PCA) method for analysis of Raman spectra measured in periodically poled lithium niobate (PPLN). We found that principal components demonstrate different sensitivity to mechanical stresses and electric fields in the vicinity of the domain walls. This allowed us to separately visualize spatial distribution of fields and electric fields at the surface and in the bulk of PPLN.

Tumor-suppressive microRNA-497 targets IKKβ to regulate NF-κB signaling pathway in human prostate cancer cells.

PubMed

Kong, Xiang-Jie; Duan, Liu-Jian; Qian, Xiao-Qiang; Xu, Ding; Liu, Hai-Long; Zhu, Ying-Jian; Qi, Jun

2015-01-01

Prostate cancer (PCa) is one of the most prevalent malignant tumors, PCa-related death is mainly due to the high probability of metastasis. MicroRNAs (miRNAs) play an important role in cancer initiation, progression and metastasis by regulating their target genes. real-time PCR was used to detected the expression of microRNA-497. The molecular biological function was investigated by using cell proliferation assays, cell cycle assay, and migration and invasion assay. We used several Algorithms and confirmed that IKKβ is directly regulated by miR-497. Here, we found miR-497 is downregulated in human prostate cancer (PCa) and inhibites the proliferation activity, migration and invasion of PC3-AR cells. Subsequently, IKKβ is confi rmed as a target of miR-497. Furthermore, knockdown of IKKβ expression resulted in decreased proliferation activity, migration and invasion. Finally, similar results was found after treatment with a novel IKK-β inhibitor (IMD-0354) in PC3-AR cells. CDK8, MMP-9, and PSA were involved in all these process. Taken together, our results show evidence that miR-497 may function as a tumor suppressor genes by regulating IKK-β in PCa, and may provide a strategy for blocking PCa metastasis.

Can non-urological doctors play a role in early prostate cancer detection?

PubMed

Yazici, Cenk M; Dogan, Cagri

2014-05-06

To evaluate the awareness of non-urological doctors for their role in evaluating prostate cancer (Pca) in scientific manner which may be a possible probability for late diagnosis of Pca. A total of 936 non-urological specialists working in 1 university and 4 education and research hospital who were able to evaluate male patients over 50 years of age were included to the survey. A face to face questionnaire had been administered to all participants. A total of 92 (9.8%) participants were evaluating prostate-specific antigen (PSA) level to all their elderly male patients while 404 (43.2%) participants had never made this evaluation. Among the participants who were evaluating PSA, none was performing an informed decision making consult and even they did not have any idea about the meaning of this strategy. About the criteria for urological consultation, 56 (6%) reported that they consult all their elderly male patients, whereas 880 (94%) answered that they perform consultation if their patients has sought help for any urological symptom. Urologists must remind the non-urological specialists that their approaches to Pca evaluation may change mortality rates of this disease and give them proper information about the scientific evaluation of Pca. This may help us to decrease the mortality rates of Pca.

The use of the finasteride-adjusted Prostate Cancer Prevention Trial Prostate Cancer Risk Calculator in a Mexican referral population: a validation study.

PubMed

Liang, Yuanyuan; Ketchum, Norma S; Louden, Christopher; Jimenez-Rios, Miguel A; Thompson, Ian M; Camarena-Reynoso, Hector R

2012-01-01

To perform the first validation study of the finasteride-adjusted Prostate Cancer Prevention Trial Prostate Cancer Risk Calculator (finPCPTRC) in a contemporary referral population in Mexico. 837 patients referred to the Instituto Nacional de Cancerología, Mexico City, Mexico, between 2005 and 2009 were used to validate the finPCPTRC by examining various measures of discrimination and calibration. Net benefit curve analysis was used to gain insight into the use of the finPCPTRC for clinical decisions. Prostate cancer (PCa) incidence (72.8%) was high in this Mexican referral cohort and 45.7% of men who were diagnosed with PCa had high-grade lesions (HGPCa, Gleason score >6). 1.3% of the patients were taking finasteride. The finPCPTRC was a superior diagnostic tool compared to prostate-specific antigen alone when discriminating patients with PCa from those without PCa (AUC = 0.784 vs. AUC = 0.687, p < 0.001) and when discriminating patients with HGPCa from those without HGPCa (AUC = 0.768 vs. AUC = 0.739, p < 0.001). The finPCPTRC underestimated the risk of PCa but overestimated the risk of HGPCa (both p < 0.001). Compared with other strategies to opt for biopsy, the net benefit would be larger with utilization of the finPCPTRC for patients accepting higher risks of HGPCa. Rates of biopsy-detectable PCa and HGPCa were high and 1.3% of this referral cohort in Mexico was taking finasteride. The risks of PCa or HGPCa calculated by the finPCPTRC were not well calibrated for this referral Mexican population and new clinical diagnostic tools are needed. Copyright © 2012 S. Karger AG, Basel.

Upregulation of miR-146a by YY1 depletion correlates with delayed progression of prostate cancer

PubMed Central

Huang, Yeqing; Tao, Tao; Liu, Chunhui; Guan, Han; Zhang, Guangyuan; Ling, Zhixin; Zhang, Lei; Lu, Kai; Chen, Shuqiu; Xu, Bin; Chen, Ming

2017-01-01

Previously published studies explained that the excessive expression of miR-146a influences the prostate cancer (PCa) cells in terms of apoptosis, progression, and viability. Although miR-146a acts as a tumor suppressor, current knowledge on the molecular mechanisms that controls its expression in PCa is limited. In this study, gene set enrichment analysis (GSEA) showed negatively enriched expression of miR-146a target gene sets and positively enriched expression of gene sets suppressed by the enhancer of zeste homolog 2 (EZH2) after YY1 depletion in PCa cells. The current results demonstrated that the miR-146a levels in PCa tissues with high Gleason scores (>7) are significantly lower than those in PCa tissues with low Gleason scores (≤7), which were initially observed in the clinical specimens. An inverse relationship between YY1 and miR-146a expression was also observed. Experiments indicated the decrease in cell viability, proliferation, and promoting apoptosis after YY1 depletion, while through inhibiting miR-146a could alleviate the negative effect brought by YY1 depletion. We detected the reversed adjustment of YY1 to accommodate miR-146a transcriptions. On the basis of YY1 depletion, we determined that the expression of miR-146a increased after EZH2 knockdown. We validated the combination of YY1 and its interaction with EZH2 at the miR-146a promoter binding site, thereby prohibiting the transcriptional activity of miR-146a in PCa cells. Our results suggested that YY1 depletion repressed PCa cell viability and proliferation and induced apoptosis at least in a miR-146a-assisted manner. PMID:28101571

Lack of association between NAT2 polymorphism and prostate cancer risk: a meta-analysis and trial sequential analysis

PubMed Central

Tang, Jingyuan; Xu, Lingyan; Xu, Haoxiang; Li, Ran; Han, Peng; Yang, Haiwei

2017-01-01

Previous studies have investigated the association between NAT2 polymorphism and the risk of prostate cancer (PCa). However, the findings from these studies remained inconsistent. Hence, we performed a meta-analysis to provide a more reliable conclusion about such associations. In the present meta-analysis, 13 independent case-control studies were included with a total of 14,469 PCa patients and 10,689 controls. All relevant studies published were searched in the databates PubMed, EMBASE, and Web of Science, till March 1st, 2017. We used the pooled odds ratios (ORs) with 95% confidence intervals (CIs) to evaluate the strength of the association between NAT2*4 allele and susceptibility to PCa. Subgroup analysis was carried out by ethnicity, source of controls and genotyping method. What's more, we also performed trial sequential analysis (TSA) to reduce the risk of type I error and evaluate whether the evidence of the results was firm. Firstly, our results indicated that NAT2*4 allele was not associated with PCa susceptibility (OR = 1.00, 95% CI= 0.95–1.05; P = 0.100). However, after excluding two studies for its heterogeneity and publication bias, no significant relationship was also detected between NAT2*4 allele and the increased risk of PCa, in fixed-effect model (OR = 0.99, 95% CI= 0.94–1.04; P = 0.451). Meanwhile, no significant increased risk of PCa was found in the subgroup analyses by ethnicity, source of controls and genotyping method. Moreover, TSA demonstrated that such association was confirmed in the present study. Therefore, this meta-analysis suggested that no significant association between NAT2 polymorphism and the risk of PCa was found. PMID:28915684

Novel antiproliferative flavonoids induce cell cycle arrest in human prostate cancer cell lines.

PubMed

Haddad, A Q; Venkateswaran, V; Viswanathan, L; Teahan, S J; Fleshner, N E; Klotz, L H

2006-01-01

Epidemiologic studies have demonstrated an inverse association between flavonoid intake and prostate cancer (PCa) risk. The East Asian diet is very high in flavonoids and, correspondingly, men in China and Japan have the lowest incidence of PCa worldwide. There are thousands of different naturally occurring and synthetic flavonoids. However, only a few have been studied in PCa. Our aim was to identify novel flavonoids with antiproliferative effect in PCa cell lines, as well as determine their effects on cell cycle. We have screened a representative subgroup of 26 flavonoids for antiproliferative effect on the human PCa (LNCaP and PC3), breast cancer (MCF-7), and normal prostate stromal cell lines (PrSC). Using a fluorescence-based cell proliferation assay (Cyquant), we have identified five flavonoids, including the novel compounds 2,2'-dihydroxychalcone and fisetin, with antiproliferative and cell cycle arresting properties in human PCa in vitro. Most of the flavonoids tested exerted antiproliferative effect at lower doses in the PCa cell lines compared to the non-PCa cells. Flow cytometry was used as a means to determine the effects on cell cycle. PC3 cells were arrested in G2/M phase by flavonoids. LNCaP cells demonstrated different cell cycle profiles. Further studies are warranted to determine the molecular mechanism of action of 2,2'-DHC and fisetin in PCa, and to establish their effectiveness in vivo.

Small molecule screening reveals a transcription-independent pro-survival function of androgen receptor in castration-resistant prostate cancer

PubMed Central

Narizhneva, Natalia V.; Tararova, Natalia D.; Ryabokon, Petro; Shyshynova, Inna; Prokvolit, Anatoly; Komarov, Pavel G.; Purmal, Andrei A.; Gudkov, Andrei V.; Gurova, Katerina V.

2010-01-01

In prostate cancer (PCa) patients, initial responsiveness to androgen deprivation therapy is frequently followed by relapse due to development of treatment-resistant androgen-independent PCa. This is typically associated with acquisition of mutations in AR that allow activity as a transcription factor in the absence of ligand, indicating that androgen-independent PCa remains dependent on AR function. Our strategy to effectively target AR in androgen-independent PCa involved using a cell-based readout to isolate small molecules that inhibit AR transactivation function through mechanisms other than modulation of ligand binding. A number of the identified inhibitors were toxic to AR-expressing PCa cells regardless of their androgen dependence. Among these, some only suppressed PCa cell growth (ARTIS), while others induced cell death (ARTIK). ARTIK, but not ARTIS, compounds caused disappearance of AR protein from treated cells. siRNA against AR behaved like ARTIK compounds, while a dominant negative AR mutant that prevents AR-mediated transactivation but does not eliminate the protein showed only a growth suppressive effect. These observations reveal a transcription-independent function of AR that is essential for PCa cell viability and, therefore, is an ideal target for anti-PCa treatment. Indeed, several of the identified AR inhibitors demonstrated in vivo efficacy in mouse models of PCa and are candidates for pharmacologic optimization. PMID:19946220

Statin use and risk of prostate cancer: a Danish population-based case-control study, 1997-2010.

PubMed

Jespersen, Christina G; Nørgaard, Mette; Friis, Søren; Skriver, Charlotte; Borre, Michael

2014-02-01

Conflicting evidence has suggested that statins possess chemopreventive properties against prostate cancer (PCa). Therefore, we examined the association between statin use and risk of PCa in a Denmark-based case-control study. We identified 42,480 patients diagnosed with incident PCa during 1997-2010 from a national cancer registry. Five age-matched population controls (n=212,400) were selected for each case using risk-set sampling. Statin use from 1996 to the index date was obtained from the National Prescription Registry. Odds ratios (ORs) adjusted for age, comorbidity, non-steroidal anti-inflammatory drug use, and educational level for PCa associated with statin use, were computed using conditional logistic regression. Analyses were stratified by duration of statin use (0-1, 2-4, 5-9, or ≥10 years), stage of PCa (localized or advanced), and type of statin used (lipophilic or hydrophilic). In total, 7915 patients (19%) and 39,384 controls (19%) redeemed statin prescriptions prior to the index date. Overall, statin users had a 6% lower risk of PCa compared with non-users [adjusted OR (ORa), 0.94; 95% confidence interval (CI), 0.91-0.97]. Risk estimates did not differ substantially by duration or type of statin used. Slightly larger statin use-associated risk reductions were observed for advanced PCa (ORa, 0.90; 95% CI, 0.85-0.96) and with statin use ≥10 years (ORa, 0.78; 95% CI, 0.65-0.95). Statin use was associated with a risk reduction overall (6%) and, specifically with advanced PCa (10%). Differences in diagnostic measures and residual confounding by socioeconomic parameters may have influenced our results. Copyright © 2013 Elsevier Ltd. All rights reserved.

A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

PubMed

Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J

2015-01-01

In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.

A Stock Market Forecasting Model Combining Two-Directional Two-Dimensional Principal Component Analysis and Radial Basis Function Neural Network

PubMed Central

Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J.

2015-01-01

In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron. PMID:25849483

Combinations of elevated tissue miRNA-17-92 cluster expression and serum prostate-specific antigen as potential diagnostic biomarkers for prostate cancer.

PubMed

Feng, Sujuan; Qian, Xiaosong; Li, Han; Zhang, Xiaodong

2017-12-01

The aim of the present study was to investigate the effectiveness of the miR-17-92 cluster as a disease progression marker in prostate cancer (PCa). Reverse transcription-quantitative polymerase chain reaction analysis was used to detect the microRNA (miR)-17-92 cluster expression levels in tissues from patients with PCa or benign prostatic hyperplasia (BPH), in addition to in PCa and BPH cell lines. Spearman correlation was used for comparison and estimation of correlations between miRNA expression levels and clinicopathological characteristics such as the Gleason score and prostate-specific antigen (PSA). Receiver operating curve (ROC) analysis was performed for evaluation of specificity and sensitivity of miR-17-92 cluster expression levels for discriminating patients with PCa from patients with BPH. Kaplan-Meier analysis was plotted to investigate the predictive potential of miR-17-92 cluster for PCa biochemical recurrence. Expression of the majority of miRNAs in the miR-17-92 cluster was identified to be significantly increased in PCa tissues and cell lines. Bivariate correlation analysis indicated that the high expression of unregulated miRNAs was positively correlated with Gleason grade, but had no significant association with PSA. ROC curves demonstrated that high expression of miR-17-92 cluster predicted a higher diagnostic accuracy compared with PSA. Improved discriminating quotients were observed when combinations of unregulated miRNAs with PSA were used. Survival analysis confirmed a high combined miRNA score of miR-17-92 cluster was associated with shorter biochemical recurrence interval. miR-17-92 cluster could be a potential diagnostic and prognostic biomarker for PCa, and the combination of the miR-17-92 cluster and serum PSA may enhance the accuracy for diagnosis of PCa.

Damage detection of engine bladed-disks using multivariate statistical analysis

NASA Astrophysics Data System (ADS)

Fang, X.; Tang, J.

2006-03-01

The timely detection of damage in aero-engine bladed-disks is an extremely important and challenging research topic. Bladed-disks have high modal density and, particularly, their vibration responses are subject to significant uncertainties due to manufacturing tolerance (blade-to-blade difference or mistuning), operating condition change and sensor noise. In this study, we present a new methodology for the on-line damage detection of engine bladed-disks using their vibratory responses during spin-up or spin-down operations which can be measured by blade-tip-timing sensing technique. We apply a principle component analysis (PCA)-based approach for data compression, feature extraction, and denoising. The non-model based damage detection is achieved by analyzing the change between response features of the healthy structure and of the damaged one. We facilitate such comparison by incorporating the Hotelling's statistic T2 analysis, which yields damage declaration with a given confidence level. The effectiveness of the method is demonstrated by case studies.

Expression of SLCO transport genes in castration resistant prostate cancer and impact of genetic variation in SCLO1B3 and SLCO2B1 on prostate cancer outcomes

PubMed Central

Wright, Jonathan L; Kwon, Erika M; Ostrander, Elaine A; Montgomery, R Bruce; Lin, Daniel W; Vessella, Robert; Stanford, Janet L; Mostaghel, Elahe A

2011-01-01

Background Metastases from men with castration resistant prostate cancer (CRPC) harbor increased tumoral androgens vs. untreated prostate cancers (PCa). This may reflect steroid uptake by OATP/SLCO transporters. We evaluated SLCO gene expression in CRPC metastases and determined whether PCa outcomes are associated with single nucleotide polymorphisms (SNPs) in SLCO2B1 and SLCO1B3, transporters previously demonstrated to mediate androgen uptake. Methods Transcripts encoding 11 SLCO genes were analyzed in untreated PCa, and in metastatic CRPC tumors obtained by rapid autopsy. SNPs in SLCO2B1 and SLCO1B3 were genotyped in a population-based cohort of 1,309 Caucasian PCa patients. Median survival follow-up was 7.0 years (0.77–16.4). The risk of PCa recurrence/progression and PCa-specific mortality (PCSM) was estimated with Cox proportional hazards analysis. Results Six SLCO genes were highly expressed in CRPC metastases vs. untreated PCa, including SLCO1B3 (3.6 fold, p=0.0517) and SLCO2B1 (5.5 fold, p=0.0034). Carriers of the variant alleles SLCO2B1 SNP rs12422149 (HR 1.99, 95% CI 1.11 – 3.55) or SLCO1B3 SNP rs4149117 (HR 1.76, 95% CI 1.00 – 3.08) had an increased risk of PCSM. Conclusions CRPC metastases demonstrate increased expression of SLCO genes vs. primary PCa. Genetic variants of SLCO1B3 and SLCO2B1 are associated with PCSM. Expression and genetic variation of SLCO genes which alter androgen uptake may be important in PCa outcomes. Impact OATP/SLCO genes may be potential biomarkers for assessing risk of prostate cancer-specific mortality. Expression and genetic variation in these genes may allow stratification of patients to more aggressive hormonal therapy or earlier incorporation of non-hormonal based treatment strategies. PMID:21266523

AMACR polymorphisms, dietary intake of red meat and dairy and prostate cancer risk.

PubMed

Wright, Jonathan L; Neuhouser, Marian L; Lin, Daniel W; Kwon, Erika M; Feng, Ziding; Ostrander, Elaine A; Stanford, Janet L

2011-04-01

Alpha-methylacyl CoA racemase (AMACR) is an enzyme involved in fatty acids metabolism. One of AMACRs primary substrates, phytanic acid, is principally obtained from dietary red meat/dairy, which are associated with prostate cancer (PCa) risk. AMACR is also a tumor tissue biomarker over-expressed in PCa. In this study, we explored the potential relationship between AMACR polymorphisms, red meat/dairy intake, and PCa risk. Caucasian participants from two population-based PCa case-control studies were included. AMACR single nucleotide polymorphisms (SNPs) were selected to capture variation across the gene and regulatory regions. Red meat and dairy intake was determined from food frequency questionnaires. The odds ratio (OR) of PCa (overall and by disease aggressiveness) was estimated by logistic and polytomous regression. Potential interactions between genotypes and dietary exposures were evaluated. Data from 1,309 cases and 1,267 controls were analyzed. Carriers of the variant T allele (rs2287939) had an OR of 0.81 (95% CI 0.68-0.97) for less aggressive PCa, but no alteration in risk for more aggressive PCa. Red meat consumption was positively associated with PCa risk, and the association was stronger for more aggressive disease (lowest vs. highest tertile OR=1.55, 95% CI 1.10-2.20). No effect modification of AMACR polymorphisms by either dietary red meat or dairy intake on PCa risk was observed. PCa risk varied by level of red meat intake and by one AMACR SNP, but there was no evidence for gene-environment interaction. These findings suggest that the effects of AMACR polymorphisms and red meat and dairy on PCa risk are independent. Copyright © 2010 Wiley-Liss, Inc.

Rolling Bearing Fault Diagnosis Based on an Improved HTT Transform

PubMed Central

Tang, Guiji; Tian, Tian; Zhou, Chong

2018-01-01

When rolling bearing failure occurs, vibration signals generally contain different signal components, such as impulsive fault feature signals, background noise and harmonic interference signals. One of the most challenging aspects of rolling bearing fault diagnosis is how to inhibit noise and harmonic interference signals, while enhancing impulsive fault feature signals. This paper presents a novel bearing fault diagnosis method, namely an improved Hilbert time–time (IHTT) transform, by combining a Hilbert time–time (HTT) transform with principal component analysis (PCA). Firstly, the HTT transform was performed on vibration signals to derive a HTT transform matrix. Then, PCA was employed to de-noise the HTT transform matrix in order to improve the robustness of the HTT transform. Finally, the diagonal time series of the de-noised HTT transform matrix was extracted as the enhanced impulsive fault feature signal and the contained fault characteristic information was identified through further analyses of amplitude and envelope spectrums. Both simulated and experimental analyses validated the superiority of the presented method for detecting bearing failures. PMID:29662013

Quercetin inhibits prostate cancer by attenuating cell survival and inhibiting anti-apoptotic pathways.

PubMed

Ward, Ashley B; Mir, Hina; Kapur, Neeraj; Gales, Dominique N; Carriere, Patrick P; Singh, Shailesh

2018-06-14

Despite recent advances in diagnosis and treatment, prostate cancer (PCa) remains the leading cause of cancer-related deaths in men. Current treatments offered in the clinics are often toxic and have severe side effects. Hence, to treat and manage PCa, new agents with fewer side effects or having potential to reduce side effects of conventional therapy are needed. In this study, we show anti-cancer effects of quercetin, an abundant bioflavonoid commonly used to treat prostatitis, and defined quercetin-induced cellular and molecular changes leading to PCa cell death. Cell viability was assessed using MTT. Cell death mode, mitochondrial outer membrane potential, and oxidative stress levels were determined by flow cytometry using Annexin V-7 AAD dual staining kit, JC-1 dye, and ROS detection kit, respectively. Antibody microarray and western blot were used to delineate the molecular changes induced by quercetin. PCa cells treated with various concentrations of quercetin showed time- and dose-dependent decrease in cell viability compared to controls, without affecting normal prostate epithelial cells. Quercetin led to apoptotic and necrotic cell death in PCa cells by affecting the mitochondrial integrity and disturbing the ROS homeostasis depending upon the genetic makeup and oxidative status of the cells. LNCaP and PC-3 cells that have an oxidative cellular environment showed ROS quenching after quercetin treatment while DU-145 showed rise in ROS levels despite having a highly reductive environment. Opposing effects of quercetin were also observed on the pro-survival pathways of PCa cells. PCa cells with mutated p53 (DU-145) and increased ROS showed significant reduction in the activation of pro-survival Akt pathway while Raf/MEK were activated in response to quercetin. PC-3 cells lacking p53 and PTEN with reduced ROS levels showed significant activation of Akt and NF-κB pathway. Although some of these changes are commonly associated with oncogenic response, the cumulative effect of these alterations is PCa cell death. Our results demonstrated quercetin exerts its anti-cancer effects by modulating ROS, Akt, and NF-κB pathways. Quercetin could be used as a chemopreventive option as well as in combination with chemotherapeutic drugs to improve clinical outcomes of PCa patients.

Application of EOF/PCA-based methods in the post-processing of GRACE derived water variations

NASA Astrophysics Data System (ADS)

Forootan, Ehsan; Kusche, Jürgen

2010-05-01

Two problems that users of monthly GRACE gravity field solutions face are 1) the presence of correlated noise in the Stokes coefficients that increases with harmonic degree and causes ‘striping', and 2) the fact that different physical signals are overlaid and difficult to separate from each other in the data. These problems are termed the signal-noise separation problem and the signal-signal separation problem. Methods that are based on principal component analysis and empirical orthogonal functions (PCA/EOF) have been frequently proposed to deal with these problems for GRACE. However, different strategies have been applied to different (spatial: global/regional, spectral: global/order-wise, geoid/equivalent water height) representations of the GRACE level 2 data products, leading to differing results and a general feeling that PCA/EOF-based methods are to be applied ‘with care'. In addition, it is known that conventional EOF/PCA methods force separated modes to be orthogonal, and that, on the other hand, to either EOFs or PCs an arbitrary orthogonal rotation can be applied. The aim of this paper is to provide a common theoretical framework and to study the application of PCA/EOF-based methods as a signal separation tool due to post-process GRACE data products. In order to investigate and illustrate the applicability of PCA/EOF-based methods, we have employed them on GRACE level 2 monthly solutions based on the Center for Space Research, University of Texas (CSR/UT) RL04 products and on the ITG-GRACE03 solutions from the University of Bonn, and on various representations of them. Our results show that EOF modes do reveal the dominating annual, semiannual and also long-periodic signals in the global water storage variations, but they also show how choosing different strategies changes the outcome and may lead to unexpected results.

Single-Input and Multiple-Output Surface Acoustic Wave Sensing for Damage Quantification in Piezoelectric Sensors.

PubMed

Pamwani, Lavish; Habib, Anowarul; Melandsø, Frank; Ahluwalia, Balpreet Singh; Shelke, Amit

2018-06-22

The main aim of the paper is damage detection at the microscale in the anisotropic piezoelectric sensors using surface acoustic waves (SAWs). A novel technique based on the single input and multiple output of Rayleigh waves is proposed to detect the microscale cracks/flaws in the sensor. A convex-shaped interdigital transducer is fabricated for excitation of divergent SAWs in the sensor. An angularly shaped interdigital transducer (IDT) is fabricated at 0 degrees and ±20 degrees for sensing the convex shape evolution of SAWs. A precalibrated damage was introduced in the piezoelectric sensor material using a micro-indenter in the direction perpendicular to the pointing direction of the SAW. Damage detection algorithms based on empirical mode decomposition (EMD) and principal component analysis (PCA) are implemented to quantify the evolution of damage in piezoelectric sensor material. The evolution of the damage was quantified using a proposed condition indicator (CI) based on normalized Euclidean norm of the change in principal angles, corresponding to pristine and damaged states. The CI indicator provides a robust and accurate metric for detection and quantification of damage.

2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications.

PubMed

Du, Qi-Shi; Wang, Shu-Qing; Xie, Neng-Zhong; Wang, Qing-Yan; Huang, Ri-Bo; Chou, Kuo-Chen

2017-09-19

A two-level principal component predictor (2L-PCA) was proposed based on the principal component analysis (PCA) approach. It can be used to quantitatively analyze various compounds and peptides about their functions or potentials to become useful drugs. One level is for dealing with the physicochemical properties of drug molecules, while the other level is for dealing with their structural fragments. The predictor has the self-learning and feedback features to automatically improve its accuracy. It is anticipated that 2L-PCA will become a very useful tool for timely providing various useful clues during the process of drug development.

Identification and classification of upper limb motions using PCA.

PubMed

Veer, Karan; Vig, Renu

2018-03-28

This paper describes the utility of principal component analysis (PCA) in classifying upper limb signals. PCA is a powerful tool for analyzing data of high dimension. Here, two different input strategies were explored. The first method uses upper arm dual-position-based myoelectric signal acquisition and the other solely uses PCA for classifying surface electromyogram (SEMG) signals. SEMG data from the biceps and the triceps brachii muscles and four independent muscle activities of the upper arm were measured in seven subjects (total dataset=56). The datasets used for the analysis are rotated by class-specific principal component matrices to decorrelate the measured data prior to feature extraction.

Near infrared and Raman spectroscopy as Process Analytical Technology tools for the manufacturing of silicone-based drug reservoirs.

PubMed

Mantanus, J; Rozet, E; Van Butsele, K; De Bleye, C; Ceccato, A; Evrard, B; Hubert, Ph; Ziémons, E

2011-08-05

Using near infrared (NIR) and Raman spectroscopy as PAT tools, 3 critical quality attributes of a silicone-based drug reservoir were studied. First, the Active Pharmaceutical Ingredient (API) homogeneity in the reservoir was evaluated using Raman spectroscopy (mapping): the API distribution within the industrial drug reservoirs was found to be homogeneous while API aggregates were detected in laboratory scale samples manufactured with a non optimal mixing process. Second, the crosslinking process of the reservoirs was monitored at different temperatures with NIR spectroscopy. Conformity tests and Principal Component Analysis (PCA) were performed on the collected data to find out the relation between the temperature and the time necessary to reach the crosslinking endpoints. An agreement was found between the conformity test results and the PCA results. Compared to the conformity test method, PCA had the advantage to discriminate the heating effect from the crosslinking effect occurring together during the monitored process. Therefore the 2 approaches were found to be complementary. Third, based on the HPLC reference method, a NIR model able to quantify the API in the drug reservoir was developed and thoroughly validated. Partial Least Squares (PLS) regression on the calibration set was performed to build prediction models of which the ability to quantify accurately was tested with the external validation set. The 1.2% Root Mean Squared Error of Prediction (RMSEP) of the NIR model indicated the global accuracy of the model. The accuracy profile based on tolerance intervals was used to generate a complete validation report. The 95% tolerance interval calculated on the validation results indicated that each future result will have a relative error below ±5% with a probability of at least 95%. In conclusion, 3 critical quality attributes of silicone-based drug reservoirs were quickly and efficiently evaluated by NIR and Raman spectroscopy. Copyright © 2011 Elsevier B.V. All rights reserved.

Evaluation of different approaches for identifying optimal sites to predict mean hillslope soil moisture content

NASA Astrophysics Data System (ADS)

Liao, Kaihua; Zhou, Zhiwen; Lai, Xiaoming; Zhu, Qing; Feng, Huihui

2017-04-01

The identification of representative soil moisture sampling sites is important for the validation of remotely sensed mean soil moisture in a certain area and ground-based soil moisture measurements in catchment or hillslope hydrological studies. Numerous approaches have been developed to identify optimal sites for predicting mean soil moisture. Each method has certain advantages and disadvantages, but they have rarely been evaluated and compared. In our study, surface (0-20 cm) soil moisture data from January 2013 to March 2016 (a total of 43 sampling days) were collected at 77 sampling sites on a mixed land-use (tea and bamboo) hillslope in the hilly area of Taihu Lake Basin, China. A total of 10 methods (temporal stability (TS) analyses based on 2 indices, K-means clustering based on 6 kinds of inputs and 2 random sampling strategies) were evaluated for determining optimal sampling sites for mean soil moisture estimation. They were TS analyses based on the smallest index of temporal stability (ITS, a combination of the mean relative difference and standard deviation of relative difference (SDRD)) and based on the smallest SDRD, K-means clustering based on soil properties and terrain indices (EFs), repeated soil moisture measurements (Theta), EFs plus one-time soil moisture data (EFsTheta), and the principal components derived from EFs (EFs-PCA), Theta (Theta-PCA), and EFsTheta (EFsTheta-PCA), and global and stratified random sampling strategies. Results showed that the TS based on the smallest ITS was better (RMSE = 0.023 m3 m-3) than that based on the smallest SDRD (RMSE = 0.034 m3 m-3). The K-means clustering based on EFsTheta (-PCA) was better (RMSE <0.020 m3 m-3) than these based on EFs (-PCA) and Theta (-PCA). The sampling design stratified by the land use was more efficient than the global random method. Forty and 60 sampling sites are needed for stratified sampling and global sampling respectively to make their performances comparable to the best K-means method (EFsTheta-PCA). Overall, TS required only one site, but its accuracy was limited. The best K-means method required <8 sites and yielded high accuracy, but extra soil and terrain information is necessary when using this method. The stratified sampling strategy can only be used if no pre-knowledge about soil moisture variation is available. This information will help in selecting the optimal methods for estimation the area mean soil moisture.

Differential principal component analysis of ChIP-seq.

PubMed

Ji, Hongkai; Li, Xia; Wang, Qian-fei; Ning, Yang

2013-04-23

We propose differential principal component analysis (dPCA) for analyzing multiple ChIP-sequencing datasets to identify differential protein-DNA interactions between two biological conditions. dPCA integrates unsupervised pattern discovery, dimension reduction, and statistical inference into a single framework. It uses a small number of principal components to summarize concisely the major multiprotein synergistic differential patterns between the two conditions. For each pattern, it detects and prioritizes differential genomic loci by comparing the between-condition differences with the within-condition variation among replicate samples. dPCA provides a unique tool for efficiently analyzing large amounts of ChIP-sequencing data to study dynamic changes of gene regulation across different biological conditions. We demonstrate this approach through analyses of differential chromatin patterns at transcription factor binding sites and promoters as well as allele-specific protein-DNA interactions.

Investigation of probabilistic principal component analysis compared to proper orthogonal decomposition methods for basis extraction and missing data estimation

NASA Astrophysics Data System (ADS)

Lee, Kyunghoon

To evaluate the maximum likelihood estimates (MLEs) of probabilistic principal component analysis (PPCA) parameters such as a factor-loading, PPCA can invoke an expectation-maximization (EM) algorithm, yielding an EM algorithm for PPCA (EM-PCA). In order to examine the benefits of the EM-PCA for aerospace engineering applications, this thesis attempts to qualitatively and quantitatively scrutinize the EM-PCA alongside both POD and gappy POD using high-dimensional simulation data. In pursuing qualitative investigations, the theoretical relationship between POD and PPCA is transparent such that the factor-loading MLE of PPCA, evaluated by the EM-PCA, pertains to an orthogonal basis obtained by POD. By contrast, the analytical connection between gappy POD and the EM-PCA is nebulous because they distinctively approximate missing data due to their antithetical formulation perspectives: gappy POD solves a least-squares problem whereas the EM-PCA relies on the expectation of the observation probability model. To juxtapose both gappy POD and the EM-PCA, this research proposes a unifying least-squares perspective that embraces the two disparate algorithms within a generalized least-squares framework. As a result, the unifying perspective reveals that both methods address similar least-squares problems; however, their formulations contain dissimilar bases and norms. Furthermore, this research delves into the ramifications of the different bases and norms that will eventually characterize the traits of both methods. To this end, two hybrid algorithms of gappy POD and the EM-PCA are devised and compared to the original algorithms for a qualitative illustration of the different basis and norm effects. After all, a norm reflecting a curve-fitting method is found to more significantly affect estimation error reduction than a basis for two example test data sets: one is absent of data only at a single snapshot and the other misses data across all the snapshots. From a numerical performance aspect, the EM-PCA is computationally less efficient than POD for intact data since it suffers from slow convergence inherited from the EM algorithm. For incomplete data, this thesis quantitatively found that the number of data missing snapshots predetermines whether the EM-PCA or gappy POD outperforms the other because of the computational cost of a coefficient evaluation, resulting from a norm selection. For instance, gappy POD demands laborious computational effort in proportion to the number of data-missing snapshots as a consequence of the gappy norm. In contrast, the computational cost of the EM-PCA is invariant to the number of data-missing snapshots thanks to the L2 norm. In general, the higher the number of data-missing snapshots, the wider the gap between the computational cost of gappy POD and the EM-PCA. Based on the numerical experiments reported in this thesis, the following criterion is recommended regarding the selection between gappy POD and the EM-PCA for computational efficiency: gappy POD for an incomplete data set containing a few data-missing snapshots and the EM-PCA for an incomplete data set involving multiple data-missing snapshots. Last, the EM-PCA is applied to two aerospace applications in comparison to gappy POD as a proof of concept: one with an emphasis on basis extraction and the other with a focus on missing data reconstruction for a given incomplete data set with scattered missing data. The first application exploits the EM-PCA to efficiently construct reduced-order models of engine deck responses obtained by the numerical propulsion system simulation (NPSS), some of whose results are absent due to failed analyses caused by numerical instability. Model-prediction tests validate that engine performance metrics estimated by the reduced-order NPSS model exhibit considerably good agreement with those directly obtained by NPSS. Similarly, the second application illustrates that the EM-PCA is significantly more cost effective than gappy POD at repairing spurious PIV measurements obtained from acoustically-excited, bluff-body jet flow experiments. The EM-PCA reduces computational cost on factors 8 ˜ 19 compared to gappy POD while generating the same restoration results as those evaluated by gappy POD. All in all, through comprehensive theoretical and numerical investigation, this research establishes that the EM-PCA is an efficient alternative to gappy POD for an incomplete data set containing missing data over an entire data set. (Abstract shortened by UMI.)

Photoacoustic spectroscopy based investigatory approach to discriminate breast cancer from normal: a pilot study

NASA Astrophysics Data System (ADS)

Priya, Mallika; Rao, Bola Sadashiva Satish; Chandra, Subhash; Ray, Satadru; Mathew, Stanley; Datta, Anirbit; Nayak, Subramanya G.; Mahato, Krishna Kishore

2016-02-01

In spite of many efforts for early detection of breast cancer, there is still lack of technology for immediate implementation. In the present study, the potential photoacoustic spectroscopy was evaluated in discriminating breast cancer from normal, involving blood serum samples seeking early detection. Three photoacoustic spectra in time domain were recorded from each of 20 normal and 20 malignant samples at 281nm pulsed laser excitations and a total of 120 spectra were generated. The time domain spectra were then Fast Fourier Transformed into frequency domain and 116.5625 - 206.875 kHz region was selected for further analysis using a combinational approach of wavelet, PCA and logistic regression. Initially, wavelet analysis was performed on the FFT data and seven features (mean, median, area under the curve, variance, standard deviation, skewness and kurtosis) from each were extracted. PCA was then performed on the feature matrix (7x120) for discriminating malignant samples from the normal by plotting a decision boundary using logistic regression analysis. The unsupervised mode of classification used in the present study yielded specificity and sensitivity values of 100% in each respectively with a ROC - AUC value of 1. The results obtained have clearly demonstrated the capability of photoacoustic spectroscopy in discriminating cancer from the normal, suggesting its possible clinical implications.

Automated Detection and Modeling of Slow Slip: Case Study of the Cascadia Subduction Zone

NASA Astrophysics Data System (ADS)

Crowell, B. W.; Bock, Y.; Liu, Z.

2012-12-01

The discovery of transient slow slip events over the past decade has changed our understanding of tectonic hazards and the earthquake cycle. Proper geodetic characterization of transient deformation is necessary for studies of regional interseismic, coseismic and postseismic tectonics, and miscalculations can affect our understanding of the regional stress field. We utilize two different methods to create a complete record of slow slip from continuous GPS stations in the Cascadia subduction zone between 1996 and 2012: spatiotemporal principal component analysis (PCA) and the relative strength index (RSI). The PCA is performed on 100 day windows of nearby stations to locate signals that exist across many stations in the network by looking at the ratio of the first two eigenvalues. The RSI is a financial momentum oscillator that looks for changes in individual time series with respect to previous epochs to locate rapid changes, indicative of transient deformation. Using both methods, we create a complete history of slow slip across the Cascadia subduction zone, fully characterizing the timing, progression, and magnitude of events. We inject the results from the automated transient detection into a time-dependent slip inversion and apply a Kalman filter based network inversion method to image the spatiotemporal variation of slip transients along the Cascadia margin.

Detection of micro solder balls using active thermography and probabilistic neural network

NASA Astrophysics Data System (ADS)

He, Zhenzhi; Wei, Li; Shao, Minghui; Lu, Xingning

2017-03-01

Micro solder ball/bump has been widely used in electronic packaging. It has been challenging to inspect these structures as the solder balls/bumps are often embedded between the component and substrates, especially in flip-chip packaging. In this paper, a detection method for micro solder ball/bump based on the active thermography and the probabilistic neural network is investigated. A VH680 infrared imager is used to capture the thermal image of the test vehicle, SFA10 packages. The temperature curves are processed using moving average technique to remove the peak noise. And the principal component analysis (PCA) is adopted to reconstruct the thermal images. The missed solder balls can be recognized explicitly in the second principal component image. Probabilistic neural network (PNN) is then established to identify the defective bump intelligently. The hot spots corresponding to the solder balls are segmented from the PCA reconstructed image, and statistic parameters are calculated. To characterize the thermal properties of solder bump quantitatively, three representative features are selected and used as the input vector in PNN clustering. The results show that the actual outputs and the expected outputs are consistent in identification of the missed solder balls, and all the bumps were recognized accurately, which demonstrates the viability of the PNN in effective defect inspection in high-density microelectronic packaging.

Land Use Land Cover Changes in Detection of Water Quality: A Study Based on Remote Sensing and Multivariate Statistics.

PubMed

Hua, Ang Kean

2017-01-01

Malacca River water quality is affected due to rapid urbanization development. The present study applied LULC changes towards water quality detection in Malacca River. The method uses LULC, PCA, CCA, HCA, NHCA, and ANOVA. PCA confirmed DS, EC, salinity, turbidity, TSS, DO, BOD, COD, As, Hg, Zn, Fe, E. coli , and total coliform. CCA confirmed 14 variables into two variates; first variate involves residential and industrial activities; and second variate involves agriculture, sewage treatment plant, and animal husbandry. HCA and NHCA emphasize that cluster 1 occurs in urban area with Hg, Fe, total coliform, and DO pollution; cluster 3 occurs in suburban area with salinity, EC, and DS; and cluster 2 occurs in rural area with salinity and EC. ANOVA between LULC and water quality data indicates that built-up area significantly polluted the water quality through E. coli , total coliform, EC, BOD, COD, TSS, Hg, Zn, and Fe, while agriculture activities cause EC, TSS, salinity, E. coli , total coliform, arsenic, and iron pollution; and open space causes contamination of turbidity, salinity, EC, and TSS. Research finding provided useful information in identifying pollution sources and understanding LULC with river water quality as references to policy maker for proper management of Land Use area.

An expert system based on principal component analysis, artificial immune system and fuzzy k-NN for diagnosis of valvular heart diseases.

PubMed

Sengur, Abdulkadir

2008-03-01

In the last two decades, the use of artificial intelligence methods in medical analysis is increasing. This is mainly because the effectiveness of classification and detection systems have improved a great deal to help the medical experts in diagnosing. In this work, we investigate the use of principal component analysis (PCA), artificial immune system (AIS) and fuzzy k-NN to determine the normal and abnormal heart valves from the Doppler heart sounds. The proposed heart valve disorder detection system is composed of three stages. The first stage is the pre-processing stage. Filtering, normalization and white de-noising are the processes that were used in this stage. The feature extraction is the second stage. During feature extraction stage, wavelet packet decomposition was used. As a next step, wavelet entropy was considered as features. For reducing the complexity of the system, PCA was used for feature reduction. In the classification stage, AIS and fuzzy k-NN were used. To evaluate the performance of the proposed methodology, a comparative study is realized by using a data set containing 215 samples. The validation of the proposed method is measured by using the sensitivity and specificity parameters; 95.9% sensitivity and 96% specificity rate was obtained.

Stability Analysis of Radial Turning Process for Superalloys

NASA Astrophysics Data System (ADS)

Jiménez, Alberto; Boto, Fernando; Irigoien, Itziar; Sierra, Basilio; Suarez, Alfredo

2017-09-01

Stability detection in machining processes is an essential component for the design of efficient machining processes. Automatic methods are able to determine when instability is happening and prevent possible machine failures. In this work a variety of methods are proposed for detecting stability anomalies based on the measured forces in the radial turning process of superalloys. Two different methods are proposed to determine instabilities. Each one is tested on real data obtained in the machining of Waspalloy, Haynes 282 and Inconel 718. Experimental data, in both Conventional and High Pressure Coolant (HPC) environments, are set in four different states depending on materials grain size and Hardness (LGA, LGS, SGA and SGS). Results reveal that PCA method is useful for visualization of the process and detection of anomalies in online processes.

Spectrophotometric Determination of Mycophenolate Mofetil as Its Charge-Transfer Complexes with Two π-Acceptors

PubMed Central

Vinay, K. B.; Revanasiddappa, H. D.; Raghu, M. S.; Abdulrahman, Sameer. A. M.; Rajendraprasad, N.

2012-01-01

Two simple, selective, and rapid spectrophotometric methods are described for the determination of mycophenolate mofetil (MPM) in pure form and in tablets. Both methods are based on charge-transfer complexation reaction of MPM with p-chloranilic acid (p-CA) or 2,3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ) in dioxane-acetonitrile medium resulting in coloured product measurable at 520 nm (p-CA) or 580 nm (DDQ). Beer's law is obeyed over the concentration ranges of 40–400 and 12–120 μg mL−1 MPM for p-CA and DDQ, respectively, with correlation coefficients (r) of 0.9995 and 0.9947. The apparent molar absorptivity values are calculated to be 1.06 × 103 and 3.87 × 103 L mol−1 cm−1, respectively, and the corresponding Sandell's sensitivities are 0.4106 and 0.1119 μg cm−1. The limits of detection (LOD) and quantification (LOQ) are also reported for both methods. The described methods were successfully applied to the determination of MPM in tablets. Statistical comparison of the results with those of the reference method showed excellent agreement. No interference was observed from the common excipients present in tablets. Both methods were validated statistically for accuracy and precision. The accuracy and reliability of the methods were further ascertained by recovery studies via standard addition procedure. PMID:22567572

Diagnostic performance of power doppler and ultrasound contrast agents in early imaging-based diagnosis of organ-confined prostate cancer: Is it possible to spare cores with contrast-guided biopsy?

PubMed

Delgado Oliva, F; Arlandis Guzman, S; Bonillo García, M; Broseta Rico, E; Boronat Tormo, F

2016-10-01

To evaluate the diagnostic performance of gray scale transrectal ultrasound-B-mode US (BMUS), power Doppler (PDUS), and sonographic contrast (CEUS) in early imaging-based diagnosis of localized prostate cancer (PCa) and to compare the diagnostic profitability of randomized biopsy (RB), US-targeted prostate biopsy by means of PDUS and CEUS. A single-center, prospective, transversal, epidemiological study was conducted from January 2010 to January 2014. We consecutively included patients who an imaging study of the prostate with BMUS, PDUS, and CEUS was performed, followed by prostate biopsy due to clinical suspicion of prostate cancer (PSA 4-20ng/mL and/or rectal exam suggestive of malignancy). The diagnostic performance of BMUS, PDUS, and CEUS was determined by calculating the Sensitivity (S), Specificity (Sp), Predictive values (PV), and diagnostic odds ratio (OR) of the diagnosis tests and, for these variables, in the population general and based on their clinical stage according to rectal exam (cT1 and cT2). PCa detection rates determined by means of a randomized 10-core biopsy scheme were compared with detection rates of CEUS-targeted (SonoVue) 2-core biopsies. Of the initial 984 patients, US contrast SonoVue was administered to 179 (18.2%). The PCa detection rate by organ of BMUS/PDUS in the global population was 38% versus 43% in the subpopulation with CEUS. The mean age of the patients was 64.3±7.01years (95% CI, 63.75-64.70); mean total PSA was 8.9±3.61ng/mL (95% CI, 8.67-9.13) and the mean prostate volume was 56.2±29cc (95% CI, 54.2-58.1). The detection rate by organ of targeted biopsy with BMUS, PDUS, and CEUS were as follows: Global population (10.6, 8.2, 24.5%), stage cT1 (5.6, 4.2, 16.4%), and stage cT2 (32.4, 22.3, 43.5%). Comparing the detection rates of the CEUS-targeted biopsy and randomized biopsy, the following results were obtained: Global population (24.5% vs. 41.8%), stage cT1 (16% vs. 35%), and stage cT2 (43.5% vs. 66.6%), with a p value<0.05. Following the "core-by-core" analysis, the detection rates by core of CEUS-targeted biopsy versus randomized biopsy were: Global population (16% vs. 13%), stage cT1 (30.3% vs. 28%), and stage cT2 (48% vs. 37%), with a p value>0.05. The NNT for CEUS-targeted biopsy was 83.3. The low sensitivity, specificity, positive predictive and negative predictive values of gray scale-B-mode, PDUS and CEUS represent scant diagnostic performance of these variables in prostate cancer detection. Prostate cancer detection rates yielded by randomized biopsy were superior than the detection rate of targeted biopsy using B-mode, PDUS and CEUS; as a result, randomized biopsy versus CEUS-targeted biopsies cannot be excluded from biopsy strategy plans for the diagnosis of prostate cancer. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Calcium channel blocker use and risk of prostate cancer by TMPRSS2:ERG gene fusion status

PubMed Central

Geybels, Milan S.; McCloskey, Karen D.; Mills, Ian G.; Stanford, Janet L.

2017-01-01

Background Calcium channel blockers (CCBs) may affect prostate cancer (PCa) growth by various mechanisms including those related to androgens. The fusion of the androgen-regulated gene TMPRSS2 and the oncogene ERG (TMPRSS2:ERG or T2E) is common in PCa, and prostate tumors that harbor the gene fusion are believed to represent a distinct disease subtype. We studied the association of CCB use with the risk of PCa, and molecular subtypes of PCa defined by T2E status. Methods Participants were residents of King County, Washington, recruited for population-based case–control studies (1993–1996 or 2002–2005). Tumor T2E status was determined by fluorescence in situ hybridization using tumor tissue specimens from radical prostatectomy. Detailed information on use of CCBs and other variables was obtained through in-person interviews. Binomial and polytomous logistic regression were used to generate odds ratios (ORs) and 95% confidence intervals (CIs). Results The study includes 1,747 PCa patients and 1,635 age-matched controls. A subset of 563 patients treated with radical prostatectomy had T2E status determined, of which 295 were T2E positive (52%). Use of CCBs (ever vs. never) was not associated with overall PCa risk. However, among European-American men, users had a reduced risk of higher-grade PCa (Gleason scores ≥7: adjusted OR = 0.64; 95% CI: 0.44–0.95). Further, use of CCBs was associated with a reduced risk of T2E positive PCa (adjusted OR = 0.38; 95% CI: 0.19–0.78), but was not associated with T2E negative PCa. Conclusions This study found suggestive evidence that use of CCBs is associated with reduced relative risks for higher Gleason score and T2E positive PCa. Future studies of PCa etiology should consider etiologic heterogeneity as PCa subtypes may develop through different causal pathways. PMID:27753122

Prostate cancer outcomes in France: treatments, adverse effects and two-year mortality

PubMed Central

2014-01-01

Background This very large population-based study investigated outcomes after a diagnosis of prostate cancer (PCa) in terms of mortality rates, treatments and adverse effects. Methods Among the 11 million men aged 40 years and over covered by the general national health insurance scheme, those with newly managed PCa in 2009 were followed for two years based on data from the national health insurance information system (SNIIRAM). Patients were identified using hospitalisation diagnoses and specific refunds related to PCa and PCa treatments. Adverse effects of PCa treatments were identified by using hospital diagnoses, specific procedures and drug refunds. Results The age-standardised two-year all-cause mortality rate among the 43,460 men included in the study was 8.4%, twice that of all men aged 40 years and over. Among the 36,734 two-year survivors, 38% had undergone prostatectomy, 36% had been treated by hormone therapy, 29% by radiotherapy, 3% by brachytherapy and 20% were not treated. The frequency of treatment-related adverse effects varied according to age and type of treatment. Among men between 50 and 69 years of age treated by prostatectomy alone, 61% were treated for erectile dysfunction and 24% were treated for urinary disorders. The frequency of treatment for these disorders decreased during the second year compared to the first year (erectile dysfunction: 41% vs 53%, urinary disorders: 9% vs 20%). The frequencies of these treatments among men treated by external beam radiotherapy alone were 7% and 14%, respectively. Among men between 50 and 69 years with treated PCa, 46% received treatments for erectile dysfunction and 22% for urinary disorders. For controls without PCa but treated surgically for benign prostatic hyperplasia, these frequencies were 1.5% and 6.0%, respectively. Conclusions We report high survival rates two years after a diagnosis of PCa, but a high frequency of PCa treatment-related adverse effects. These frequencies remain underestimated, as they are based on treatments for erectile dysfunction and urinary disorders and do not reflect all functional outcomes. These results should help urologists and general practitioners to inform their patients about outcomes at the time of screening and diagnosis, and especially about potential treatment-related adverse effects. PMID:24927850

Mutational Landscape of Candidate Genes in Familial Prostate Cancer

PubMed Central

Johnson, Anna M.; Zuhlke, Kimberly A.; Plotts, Chris; McDonnell, Shannon K.; Middha, Sumit; Riska, Shaun M.; Thibodeau, Stephen N.; Douglas, Julie A.; Cooney, Kathleen A.

2014-01-01

Background Family history is a major risk factor for prostate cancer (PCa), suggesting a genetic component to the disease. However, traditional linkage and association studies have failed to fully elucidate the underlying genetic basis of familial PCa. Methods Here we use a candidate gene approach to identify potential PCa susceptibility variants in whole exome sequencing data from familial PCa cases. Six hundred ninety-seven candidate genes were identified based on function, location near a known chromosome 17 linkage signal, and/or previous association with prostate or other cancers. Single nucleotide variants (SNVs) in these candidate genes were identified in whole exome sequence data from 33 PCa cases from 11 multiplex PCa families (3 cases/family). Results Overall, 4856 candidate gene SNVs were identified, including 1052 missense and 10 nonsense variants. Twenty missense variants were shared by all 3 family members in each family in which they were observed. Additionally, 15 missense variants were shared by 2 of 3 family members and predicted to be deleterious by 5 different algorithms. Four missense variants, BLM Gln123Arg, PARP2 Arg283Gln, LRCC46 Ala295Thr and KIF2B Pro91Leu, and 1 nonsense variant, CYP3A43 Arg441Ter, showed complete co-segregation with PCa status. Twelve additional variants displayed partial co-segregation with PCa. Conclusions Forty-three nonsense and shared, missense variants were identified in our candidate genes. Further research is needed to determine the contribution of these variants to PCa susceptibility. PMID:25111073

Feasibility of detecting aflatoxin B1 on inoculated maize kernels surface using Vis/NIR hyperspectral imaging.

PubMed

Wang, Wei; Heitschmidt, Gerald W; Windham, William R; Feldner, Peggy; Ni, Xinzhi; Chu, Xuan

2015-01-01

The feasibility of using a visible/near-infrared hyperspectral imaging system with a wavelength range between 400 and 1000 nm to detect and differentiate different levels of aflatoxin B1 (AFB1 ) artificially titrated on maize kernel surface was examined. To reduce the color effects of maize kernels, image analysis was limited to a subset of original spectra (600 to 1000 nm). Residual staining from the AFB1 on the kernels surface was selected as regions of interest for analysis. Principal components analysis (PCA) was applied to reduce the dimensionality of hyperspectral image data, and then a stepwise factorial discriminant analysis (FDA) was performed on latent PCA variables. The results indicated that discriminant factors F2 can be used to separate control samples from all of the other groups of kernels with AFB1 inoculated, whereas the discriminant factors F1 can be used to identify maize kernels with levels of AFB1 as low as 10 ppb. An overall classification accuracy of 98% was achieved. Finally, the peaks of β coefficients of the discrimination factors F1 and F2 were analyzed and several key wavelengths identified for differentiating maize kernels with and without AFB1 , as well as those with differing levels of AFB1 inoculation. Results indicated that Vis/NIR hyperspectral imaging technology combined with the PCA-FDA was a practical method to detect and differentiate different levels of AFB1 artificially inoculated on the maize kernels surface. However, indicated the potential to detect and differentiate naturally occurring toxins in maize kernel. © 2014 Institute of Food Technologists®

Stream-based Hebbian eigenfilter for real-time neuronal spike discrimination

PubMed Central

2012-01-01

Background Principal component analysis (PCA) has been widely employed for automatic neuronal spike sorting. Calculating principal components (PCs) is computationally expensive, and requires complex numerical operations and large memory resources. Substantial hardware resources are therefore needed for hardware implementations of PCA. General Hebbian algorithm (GHA) has been proposed for calculating PCs of neuronal spikes in our previous work, which eliminates the needs of computationally expensive covariance analysis and eigenvalue decomposition in conventional PCA algorithms. However, large memory resources are still inherently required for storing a large volume of aligned spikes for training PCs. The large size memory will consume large hardware resources and contribute significant power dissipation, which make GHA difficult to be implemented in portable or implantable multi-channel recording micro-systems. Method In this paper, we present a new algorithm for PCA-based spike sorting based on GHA, namely stream-based Hebbian eigenfilter, which eliminates the inherent memory requirements of GHA while keeping the accuracy of spike sorting by utilizing the pseudo-stationarity of neuronal spikes. Because of the reduction of large hardware storage requirements, the proposed algorithm can lead to ultra-low hardware resources and power consumption of hardware implementations, which is critical for the future multi-channel micro-systems. Both clinical and synthetic neural recording data sets were employed for evaluating the accuracy of the stream-based Hebbian eigenfilter. The performance of spike sorting using stream-based eigenfilter and the computational complexity of the eigenfilter were rigorously evaluated and compared with conventional PCA algorithms. Field programmable logic arrays (FPGAs) were employed to implement the proposed algorithm, evaluate the hardware implementations and demonstrate the reduction in both power consumption and hardware memories achieved by the streaming computing Results and discussion Results demonstrate that the stream-based eigenfilter can achieve the same accuracy and is 10 times more computationally efficient when compared with conventional PCA algorithms. Hardware evaluations show that 90.3% logic resources, 95.1% power consumption and 86.8% computing latency can be reduced by the stream-based eigenfilter when compared with PCA hardware. By utilizing the streaming method, 92% memory resources and 67% power consumption can be saved when compared with the direct implementation of GHA. Conclusion Stream-based Hebbian eigenfilter presents a novel approach to enable real-time spike sorting with reduced computational complexity and hardware costs. This new design can be further utilized for multi-channel neuro-physiological experiments or chronic implants. PMID:22490725

Impact of a Structured Reporting Template on Adherence to Prostate Imaging Reporting and Data System Version 2 and on the Diagnostic Performance of Prostate MRI for Clinically Significant Prostate Cancer.

PubMed

Shaish, Hiram; Feltus, Whitney; Steinman, Jonathan; Hecht, Elizabeth; Wenske, Sven; Ahmed, Firas

2018-05-01

The aim of this study was to assess the impact of a structured reporting template on adherence to the Prostate Imaging Reporting and Data System (PI-RADS) version 2 lexicon and on the diagnostic performance of prostate MRI to detect clinically significant prostate cancer (CS-PCa). An imaging database was searched for consecutive patients who underwent prostate MRI followed by MRI-ultrasound fusion biopsy from October 2015 through October 2017. The initial MRI reporting template used included only subheadings. In July 2016, the template was changed to a standardized PI-RADS-compliant structured template incorporating dropdown menus. Lesion, patient characteristics, pathology, and adherence to the PI-RADS lexicon were extracted from MRI reports and patient charts. Diagnostic performance of prostate MRI to detect CS-PCa using combined ultrasound-MRI fusion and systematic biopsy as a reference standard was assessed. Three hundred twenty-four lesions in 202 patients (average age, 67 years; average prostate-specific antigen level, 5.9 ng/mL) were analyzed, including 217 MRI peripheral zone (PZ) lesions, 84 MRI non-PZ lesions, and 23 additional PZ lesions found on systematic biopsy but missed on MRI. Thirty-three percent (106 of 324) were CS-PCa. Adherence to the PI-RADS lexicon improved from 32.9% (50 of 152) to 88.4% (152 of 172) (P < .0001) after introduction of the structured template. The sensitivity of prostate MRI for CS-PCa in the PZ increased from 53% to 70% (P = .011). There was no significant change in specificity (60% versus 55%, P = .458). A structured template with dropdown menus incorporating the PI-RADS lexicon and classification rules improves adherence to PI-RADS and may increase the diagnostic performance of prostate MRI for CS-PCa. Copyright © 2018 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Prostate health index (PHI) and prostate-specific antigen (PSA) predictive models for prostate cancer in the Chinese population and the role of digital rectal examination-estimated prostate volume.

PubMed

Chiu, Peter K F; Roobol, Monique J; Teoh, Jeremy Y; Lee, Wai-Man; Yip, Siu-Ying; Hou, See-Ming; Bangma, Chris H; Ng, Chi-Fai

2016-10-01

To investigate PSA- and PHI (prostate health index)-based models for prediction of prostate cancer (PCa) and the feasibility of using DRE-estimated prostate volume (DRE-PV) in the models. This study included 569 Chinese men with PSA 4-10 ng/mL and non-suspicious DRE with transrectal ultrasound (TRUS) 10-core prostate biopsies performed between April 2008 and July 2015. DRE-PV was estimated using 3 pre-defined classes: 25, 40, or 60 ml. The performance of PSA-based and PHI-based predictive models including age, DRE-PV, and TRUS prostate volume (TRUS-PV) was analyzed using logistic regression and area under the receiver operating curves (AUC), in both the whole cohort and the screening age group of 55-75. PCa and high-grade PCa (HGPCa) was diagnosed in 10.9 % (62/569) and 2.8 % (16/569) men, respectively. The performance of DRE-PV-based models was similar to TRUS-PV-based models. In the age group 55-75, the AUCs for PCa of PSA alone, PSA with DRE-PV and age, PHI alone, PHI with DRE-PV and age, and PHI with TRUS-PV and age were 0.54, 0.71, 0.76, 0.78, and 0.78, respectively. The corresponding AUCs for HGPCa were higher (0.60, 0.70, 0.85, 0.83, and 0.83). At 10 and 20 % risk threshold for PCa, 38.4 and 55.4 % biopsies could be avoided in the PHI-based model, respectively. PHI had better performance over PSA-based models and could reduce unnecessary biopsies. A DRE-assessed PV can replace TRUS-assessed PV in multivariate prediction models to facilitate clinical use.

Neural network ensemble based CAD system for focal liver lesions from B-mode ultrasound.

PubMed

Virmani, Jitendra; Kumar, Vinod; Kalra, Naveen; Khandelwal, Niranjan

2014-08-01

A neural network ensemble (NNE) based computer-aided diagnostic (CAD) system to assist radiologists in differential diagnosis between focal liver lesions (FLLs), including (1) typical and atypical cases of Cyst, hemangioma (HEM) and metastatic carcinoma (MET) lesions, (2) small and large hepatocellular carcinoma (HCC) lesions, along with (3) normal (NOR) liver tissue is proposed in the present work. Expert radiologists, visualize the textural characteristics of regions inside and outside the lesions to differentiate between different FLLs, accordingly texture features computed from inside lesion regions of interest (IROIs) and texture ratio features computed from IROIs and surrounding lesion regions of interests (SROIs) are taken as input. Principal component analysis (PCA) is used for reducing the dimensionality of the feature space before classifier design. The first step of classification module consists of a five class PCA-NN based primary classifier which yields probability outputs for five liver image classes. The second step of classification module consists of ten binary PCA-NN based secondary classifiers for NOR/Cyst, NOR/HEM, NOR/HCC, NOR/MET, Cyst/HEM, Cyst/HCC, Cyst/MET, HEM/HCC, HEM/MET and HCC/MET classes. The probability outputs of five class PCA-NN based primary classifier is used to determine the first two most probable classes for a test instance, based on which it is directed to the corresponding binary PCA-NN based secondary classifier for crisp classification between two classes. By including the second step of the classification module, classification accuracy increases from 88.7 % to 95 %. The promising results obtained by the proposed system indicate its usefulness to assist radiologists in differential diagnosis of FLLs.

Scene perception in posterior cortical atrophy: categorization, description and fixation patterns

PubMed Central

Shakespeare, Timothy J.; Yong, Keir X. X.; Frost, Chris; Kim, Lois G.; Warrington, Elizabeth K.; Crutch, Sebastian J.

2013-01-01

Partial or complete Balint's syndrome is a core feature of the clinico-radiological syndrome of posterior cortical atrophy (PCA), in which individuals experience a progressive deterioration of cortical vision. Although multi-object arrays are frequently used to detect simultanagnosia in the clinical assessment and diagnosis of PCA, to date there have been no group studies of scene perception in patients with the syndrome. The current study involved three linked experiments conducted in PCA patients and healthy controls. Experiment 1 evaluated the accuracy and latency of complex scene perception relative to individual faces and objects (color and grayscale) using a categorization paradigm. PCA patients were both less accurate (faces < scenes < objects) and slower (scenes < objects < faces) than controls on all categories, with performance strongly associated with their level of basic visual processing impairment; patients also showed a small advantage for color over grayscale stimuli. Experiment 2 involved free description of real world scenes. PCA patients generated fewer features and more misperceptions than controls, though perceptual errors were always consistent with the patient's global understanding of the scene (whether correct or not). Experiment 3 used eye tracking measures to compare patient and control eye movements over initial and subsequent fixations of scenes. Patients' fixation patterns were significantly different to those of young and age-matched controls, with comparable group differences for both initial and subsequent fixations. Overall, these findings describe the variability in everyday scene perception exhibited by individuals with PCA, and indicate the importance of exposure duration in the perception of complex scenes. PMID:24106469

Site-Specific Photoconjugation of Beta-Lactamase Fragments to Monoclonal Antibodies Enables Sensitive Analyte Detection via Split-Enzyme Complementation.

PubMed

Yu, Feifan; Alesand, Veronica; Nygren, Per-Åke

2018-02-27

Protein fragment complementation assays (PCA) rely on a proximity-driven reconstitution of a split reporter protein activity, typically via interaction between bait and prey units separately fused to the reporter protein halves. The PCA principle can also be formatted for use in immunossays for analyte detection, e.g., via the use of small immunoglobulin binding proteins (IgBp) as fusion partners to split-reporter protein fragments for conversion of pairs of antibodies into split-protein half-probes. However, the non-covalent binding between IgBp and antibodies is not ideal for development of robust assays. Here, the authors describe how split-enzyme reporter halves can be both site-specifically and covalently photoconjugated at antibody Fc-parts for use in homogeneous dual-antibody in vitro immunoassays based on analyte-dependent split-enzyme fragment complementation. The half-probes consist of parts of a beta-lactamase split-protein reporter fused to an immunoglobulin Fc binding domain equipped with a unique cysteine residue at which a photoactivable maleimide benzophenone group (MBP) is attached. Using such antibody conjugates the authors obtain an analyte-driven complementation of the reporter enzyme fragments monitored via conversion of a chromogenic substrate. Results from detection of human interferon-gamma and the extracellular domain of HER2 is shown. The described principles for site-specific conjugation of proteins to antibodies should be broadly applicable. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A dimension reduction strategy for improving the efficiency of computer-aided detection for CT colonography

NASA Astrophysics Data System (ADS)

Song, Bowen; Zhang, Guopeng; Wang, Huafeng; Zhu, Wei; Liang, Zhengrong

2013-02-01

Various types of features, e.g., geometric features, texture features, projection features etc., have been introduced for polyp detection and differentiation tasks via computer aided detection and diagnosis (CAD) for computed tomography colonography (CTC). Although these features together cover more information of the data, some of them are statistically highly-related to others, which made the feature set redundant and burdened the computation task of CAD. In this paper, we proposed a new dimension reduction method which combines hierarchical clustering and principal component analysis (PCA) for false positives (FPs) reduction task. First, we group all the features based on their similarity using hierarchical clustering, and then PCA is employed within each group. Different numbers of principal components are selected from each group to form the final feature set. Support vector machine is used to perform the classification. The results show that when three principal components were chosen from each group we can achieve an area under the curve of receiver operating characteristics of 0.905, which is as high as the original dataset. Meanwhile, the computation time is reduced by 70% and the feature set size is reduce by 77%. It can be concluded that the proposed method captures the most important information of the feature set and the classification accuracy is not affected after the dimension reduction. The result is promising and further investigation, such as automatically threshold setting, are worthwhile and are under progress.

Droplet Digital PCR Based Androgen Receptor Variant 7 (AR-V7) Detection from Prostate Cancer Patient Blood Biopsies.

PubMed

Ma, Yafeng; Luk, Alison; Young, Francis P; Lynch, David; Chua, Wei; Balakrishnar, Bavanthi; de Souza, Paul; Becker, Therese M

2016-08-04

Androgen receptor splice variant V7 (AR-V7) was recently identified as a valuable predictive biomarker in metastatic castrate-resistant prostate cancer. Here, we report a new, sensitive and accurate screen for AR-V7 mRNA expression directly from circulating tumor cells (CTCs): We combined EpCAM-based immunomagnetic CTC isolation using the IsoFlux microfluidic platform with droplet digital polymerase chain reaction (ddPCR) to analyze total AR and AR-V7 expression from prostate cancer patients CTCs. We demonstrate that AR-V7 is reliably detectable in enriched CTC samples with as little as five CTCs, even considering tumor heterogeneity, and confirm detection of AR-V7 in CTC samples from advanced prostate cancer (PCa) patients with AR-V7 detection limited to castrate resistant disease status in our sample set. Sensitive molecular analyses of circulating tumor cells (CTCs) or circulating tumor nucleic acids present exciting strategies to detect biomarkers, such as AR-V7 from non-invasive blood samples, so-called blood biopsies.

PCA-based artifact removal algorithm for stroke detection using UWB radar imaging.

PubMed

Ricci, Elisa; di Domenico, Simone; Cianca, Ernestina; Rossi, Tommaso; Diomedi, Marina

2017-06-01

Stroke patients should be dispatched at the highest level of care available in the shortest time. In this context, a transportable system in specialized ambulances, able to evaluate the presence of an acute brain lesion in a short time interval (i.e., few minutes), could shorten delay of treatment. UWB radar imaging is an emerging diagnostic branch that has great potential for the implementation of a transportable and low-cost device. Transportability, low cost and short response time pose challenges to the signal processing algorithms of the backscattered signals as they should guarantee good performance with a reasonably low number of antennas and low computational complexity, tightly related to the response time of the device. The paper shows that a PCA-based preprocessing algorithm can: (1) achieve good performance already with a computationally simple beamforming algorithm; (2) outperform state-of-the-art preprocessing algorithms; (3) enable a further improvement in the performance (and/or decrease in the number of antennas) by using a multistatic approach with just a modest increase in computational complexity. This is an important result toward the implementation of such a diagnostic device that could play an important role in emergency scenario.

Value of PET/CT and MR Lymphography in Treatment of Prostate Cancer Patients With Lymph Node Metastases

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

Fortuin, Ansje S., E-mail: A.Fortuin@rad.umcn.nl; Deserno, Willem M.L.L.G.; Meijer, Hanneke J.M.

2012-11-01

Purpose: To determine the clinical value of two novel molecular imaging techniques: {sup 11}C-choline positron emission tomography (PET)/computed tomography (CT) and ferumoxtran-10 enhanced magnetic resonance imaging (magnetic resonance lymphography [MRL]) for lymph node (LN) treatment in prostate cancer (PCa) patients. Therefore, we evaluated the ability of PET/CT and MRL to assess the number, size, and location of LN metastases in patients with primary or recurrent PCa. Methods and Materials: A total of 29 patients underwent MRL and PET/CT for LN evaluation. The MRL and PET/CT data were analyzed independently. The number, size, and location of the LN metastases were determined.more » The location was described as within or outside the standard clinical target volume for elective pelvic irradiation as defined by the Radiation Therapy Oncology Group. Subsequently, the results from MRL and PET/CT were compared. Results: Of the 738 LNs visible on MRL, 151 were positive in 23 of 29 patients. Of the 132 LNs visible on PET/CT, 34 were positive in 13 of 29 patients. MRL detected significantly more positive LNs (p < 0.001) in more patients than PET/CT (p = 0.002). The mean diameter of the detected suspicious LNs on MRL was significantly smaller than those detected by PET/CT, 4.9 mm and 8.4 mm, respectively (p < 0.0001). In 14 (61%) of 23 patients, suspicious LNs were found outside the clinical target volume with MRL and in 4 (31%) of 13 patients with PET/CT. Conclusion: In patients with PCa, both molecular imaging techniques, MRL and {sup 11}C-choline PET/CT, can detect LNs suspicious for metastasis, irrespective of the existing size and shape criteria for CT and conventional magnetic resonance imaging. On MRL and PET/CT, 61% and 31% of the suspicious LNs were located outside the conventional clinical target volume. Therefore, these techniques could help to individualize treatment selection and enable image-guided radiotherapy for patients with PCa LN metastases.« less

Cohort Profile: the National Prostate Cancer Register of Sweden and Prostate Cancer data Base Sweden 2.0.

PubMed

Van Hemelrijck, Mieke; Wigertz, Annette; Sandin, Fredrik; Garmo, Hans; Hellström, Karin; Fransson, Per; Widmark, Anders; Lambe, Mats; Adolfsson, Jan; Varenhorst, Eberhard; Johansson, Jan-Erik; Stattin, Pär

2013-08-01

In 1987, the first Regional Prostate Cancer Register was set up in the South-East health-care region of Sweden. Other health-care regions joined and since 1998 virtually all prostate cancer (PCa) cases are registered in the National Prostate Cancer Register (NPCR) of Sweden to provide data for quality assurance, bench marking and clinical research. NPCR includes data on tumour stage, Gleason score, serum level of prostate-specific antigen (PSA) and primary treatment. In 2008, the NPCR was linked to a number of other population-based registers by use of the personal identity number. This database named Prostate Cancer data Base Sweden (PCBaSe) has now been extended with more cases, longer follow-up and a selection of two control series of men free of PCa at the time of sampling, as well as information on brothers of men diagnosed with PCa, resulting in PCBaSe 2.0. This extension allows for studies with case-control, cohort or longitudinal case-only design on aetiological factors, pharmaceutical prescriptions and assessment of long-term outcomes. The NPCR covers >96% of all incident PCa cases registered by the Swedish Cancer Register, which has an underreporting of <3.7%. The NPCR is used to assess trends in incidence, treatment and outcome of men with PCa. Since the national registers linked to PCBaSe are complete, studies from PCBaSe 2.0 are truly population based.

Patient Preferences and Urologist Judgments on Prostate Cancer Therapy in Japan.

PubMed

Nakayama, Masahiko; Kobayashi, Hisanori; Okazaki, Masateru; Imanaka, Keiichiro; Yoshizawa, Kazutake; Mahlich, Jörg

2018-05-01

The purpose of the present study is to investigate the concordance of treatment preferences between patients and physicians in prostate cancer (PCa) in Japan. An internet-based discrete choice experiment was conducted. Patients and physicians were asked to select their preferred treatment from a pair of hypothetical treatments consisting of four attributes: quality of life (QOL), treatment effectiveness, side effects, and accessibility of treatment. The data were analyzed using a conditional logistic regression model to calculate coefficients and the relative importance (RI) of each attribute. A total of 103 PCa patients and 127 physicians responded. The study looked at 37 patients considered as advanced PCa and 66 who were non-advanced PCa. All of the physicians were urologists. Advanced PCa patients ranked the attributes as follows: treatment effectiveness (RI: 32%), accessibility of treatment (RI: 26%), QOL (RI: 23%), and side effects (RI: 19%). For physicians, the RI ranking was the same as for advanced PCa patients; treatment effectiveness (RI: 29%), accessibility of treatment (RI: 27%), QOL (RI: 26%), and side effects (RI: 18%). For non-advanced PCa patients, accessibility of treatment ranked the highest RI (27%) and treatment effectiveness ranked as the lowest RI (14%). Our study suggests that the ranking of the attributes was consistent between advanced PCa patients and physicians. The most influential attribute was treatment effectiveness. Treatment preferences also vary by disease stage.

The fractal characteristic of facial anthropometric data for developing PCA fit test panels for youth born in central China.

PubMed

Yang, Lei; Wei, Ran; Shen, Henggen

2017-01-01

New principal component analysis (PCA) respirator fit test panels had been developed for current American and Chinese civilian workers based on anthropometric surveys. The PCA panels used the first two principal components (PCs) obtained from a set of 10 facial dimensions. Although the PCA panels for American and Chinese subjects adopted the bivairate framework with two PCs, the number of the PCs retained in the PCA analysis was different between Chinese subjects and Americans. For the Chinese youth group, the third PC should be retained in the PCA analysis for developing new fit test panels. In this article, an additional number label (ANL) is used to explain the third PC in PCA analysis when the first two PCs are used to construct the PCA half-facepiece respirator fit test panel for Chinese group. The three-dimensional box-counting method is proposed to estimate the ANLs by calculating fractal dimensions of the facial anthropometric data of the Chinese youth. The linear regression coefficients of scale-free range R 2 are all over 0.960, which demonstrates that the facial anthropometric data of the Chinese youth has fractal characteristic. The youth subjects born in Henan province has an ANL of 2.002, which is lower than the composite facial anthropometric data of Chinese subjects born in many provinces. Hence, Henan youth subjects have the self-similar facial anthropometric characteristic and should use the particular ANL (2.002) as the important tool along with using the PCA panel. The ANL method proposed in this article not only provides a new methodology in quantifying the characteristics of facial anthropometric dimensions for any ethnic/racial group, but also extends the scope of PCA panel studies to higher dimensions.

Plaque Tissue Morphology-Based Stroke Risk Stratification Using Carotid Ultrasound: A Polling-Based PCA Learning Paradigm.

PubMed

Saba, Luca; Jain, Pankaj K; Suri, Harman S; Ikeda, Nobutaka; Araki, Tadashi; Singh, Bikesh K; Nicolaides, Andrew; Shafique, Shoaib; Gupta, Ajay; Laird, John R; Suri, Jasjit S

2017-06-01

Severe atherosclerosis disease in carotid arteries causes stenosis which in turn leads to stroke. Machine learning systems have been previously developed for plaque wall risk assessment using morphology-based characterization. The fundamental assumption in such systems is the extraction of the grayscale features of the plaque region. Even though these systems have the ability to perform risk stratification, they lack the ability to achieve higher performance due their inability to select and retain dominant features. This paper introduces a polling-based principal component analysis (PCA) strategy embedded in the machine learning framework to select and retain dominant features, resulting in superior performance. This leads to more stability and reliability. The automated system uses offline image data along with the ground truth labels to generate the parameters, which are then used to transform the online grayscale features to predict the risk of stroke. A set of sixteen grayscale plaque features is computed. Utilizing the cross-validation protocol (K = 10), and the PCA cutoff of 0.995, the machine learning system is able to achieve an accuracy of 98.55 and 98.83%corresponding to the carotidfar wall and near wall plaques, respectively. The corresponding reliability of the system was 94.56 and 95.63%, respectively. The automated system was validated against the manual risk assessment system and the precision of merit for same cross-validation settings and PCA cutoffs are 98.28 and 93.92%for the far and the near wall, respectively.PCA-embedded morphology-based plaque characterization shows a powerful strategy for risk assessment and can be adapted in clinical settings.

Analysis of urinary PSA glycosylation is not indicative of high-risk prostate cancer.

PubMed

Barrabés, Sílvia; Llop, Esther; Ferrer-Batallé, Montserrat; Ramírez, Manel; Aleixandre, Rosa N; Perry, Antoinette S; de Llorens, Rafael; Peracaula, Rosa

2017-07-01

The levels of core fucosylation and α2,3-linked sialic acid in serum Prostate Specific Antigen (PSA), using the lectins Pholiota squarrosa lectin (PhoSL) and Sambucus nigra agglutinin (SNA), can discriminate between Benign Prostatic Hyperplasia (BPH) and indolent prostate cancer (PCa) from aggressive PCa. In the present work we evaluated whether these glycosylation determinants could also be altered in urinary PSA obtained after digital rectal examination (DRE) and could also be useful for diagnosis determinations. For this purpose, α2,6-sialic acid and α1,6-fucose levels of urinary PSA from 53 patients, 18 biopsy-negative and 35 PCa patients of different aggressiveness degree, were analyzed by sandwich ELLA (Enzyme Linked Lectin Assay) using PhoSL and SNA. Changes in the levels of specific glycosylation determinants, that in serum PSA samples were indicative of PCa aggressiveness, were not found in PSA from DRE urine samples. Although urine is a simpler matrix for analyzing PSA glycosylation compared to serum, an immunopurification step was necessary to specifically detect the glycans on the PSA molecule. Those specific glycosylation determinants on urinary PSA were however not useful to improve PCa diagnosis. This could be probably due to the low proportion of PSA from the tumor in urine samples, which precludes the identification of aberrantly glycosylated PSA. Copyright © 2017 Elsevier B.V. All rights reserved.

Breast Shape Analysis With Curvature Estimates and Principal Component Analysis for Cosmetic and Reconstructive Breast Surgery.

PubMed

Catanuto, Giuseppe; Taher, Wafa; Rocco, Nicola; Catalano, Francesca; Allegra, Dario; Milotta, Filippo Luigi Maria; Stanco, Filippo; Gallo, Giovanni; Nava, Maurizio Bruno

2018-03-20

Breast shape is defined utilizing mainly qualitative assessment (full, flat, ptotic) or estimates, such as volume or distances between reference points, that cannot describe it reliably. We will quantitatively describe breast shape with two parameters derived from a statistical methodology denominated principal component analysis (PCA). We created a heterogeneous dataset of breast shapes acquired with a commercial infrared 3-dimensional scanner on which PCA was performed. We plotted on a Cartesian plane the two highest values of PCA for each breast (principal components 1 and 2). Testing of the methodology on a preoperative and postoperative surgical case and test-retest was performed by two operators. The first two principal components derived from PCA are able to characterize the shape of the breast included in the dataset. The test-retest demonstrated that different operators are able to obtain very similar values of PCA. The system is also able to identify major changes in the preoperative and postoperative stages of a two-stage reconstruction. Even minor changes were correctly detected by the system. This methodology can reliably describe the shape of a breast. An expert operator and a newly trained operator can reach similar results in a test/re-testing validation. Once developed and after further validation, this methodology could be employed as a good tool for outcome evaluation, auditing, and benchmarking.

Ambiguity in a masculine world: Being a BRCA1/2 mutation carrier and a man with prostate cancer.

PubMed

Moynihan, C; Bancroft, E K; Mitra, A; Ardern-Jones, A; Castro, E; Page, E C; Eeles, R A

2017-11-01

Increased risk of prostate cancer (PCa) is observed in men with BRCA1/BRCA2 mutations. Sex and gender are key determinants of health and disease although unequal care exists between the sexes. Stereotypical male attitudes are shown to lead to poor health outcomes. Men with BRCA1/2 mutations and diagnosed with PCa were identified and invited to participate in a qualitative interview study. Data were analysed using a framework approach. "Masculinity theory" was used to report the impact of having both a BRCA1/2 mutation and PCa. Eleven of 15 eligible men were interviewed. The umbrella concept of "Ambiguity in a Masculine World" was evident. Men's responses often matched those of women in a genetic context. Men's BRCA experience was described, as "on the back burner" but "a bonus" enabling familial detection and early diagnosis of PCa. Embodiment of PCa took precedence as men revealed stereotypical "ideal" masculine responses such as stoicism and control while creating new "masculinities" when faced with the vicissitudes of having 2 gendered conditions. Health workers are urged to take a reflexive approach, void of masculine ideals, a belief in which obfuscates men's experience. Research is required regarding men's support needs in the name of equality of care. © 2017 The Authors. Psycho-Oncology published by John Wiley & Sons Ltd.

Differentiation of live and dead salmonella cells using fourier transform infrared (FTIR) spectroscopy and principle component analysis (PCA) technique

USDA-ARS?s Scientific Manuscript database

Various technologies have been developed for pathogen detection using optical, electrochemical, biochemical and physical properties. Conventional microbiological methods need time from days to week to get the result. Though this method is very sensitive and accurate, a rapid detection of pathogens i...

Single cell transcriptomic analysis of prostate cancer cells.

PubMed

Welty, Christopher J; Coleman, Ilsa; Coleman, Roger; Lakely, Bryce; Xia, Jing; Chen, Shu; Gulati, Roman; Larson, Sandy R; Lange, Paul H; Montgomery, Bruce; Nelson, Peter S; Vessella, Robert L; Morrissey, Colm

2013-02-16

The ability to interrogate circulating tumor cells (CTC) and disseminated tumor cells (DTC) is restricted by the small number detected and isolated (typically <10). To determine if a commercially available technology could provide a transcriptomic profile of a single prostate cancer (PCa) cell, we clonally selected and cultured a single passage of cell cycle synchronized C4-2B PCa cells. Ten sets of single, 5-, or 10-cells were isolated using a micromanipulator under direct visualization with an inverted microscope. Additionally, two groups of 10 individual DTC, each isolated from bone marrow of 2 patients with metastatic PCa were obtained. RNA was amplified using the WT-Ovation™ One-Direct Amplification System. The amplified material was hybridized on a 44K Whole Human Gene Expression Microarray. A high stringency threshold, a mean Alexa Fluor® 3 signal intensity above 300, was used for gene detection. Relative expression levels were validated for select genes using real-time PCR (RT-qPCR). Using this approach, 22,410, 20,423, and 17,009 probes were positive on the arrays from 10-cell pools, 5-cell pools, and single-cells, respectively. The sensitivity and specificity of gene detection on the single-cell analyses were 0.739 and 0.972 respectively when compared to 10-cell pools, and 0.814 and 0.979 respectively when compared to 5-cell pools, demonstrating a low false positive rate. Among 10,000 randomly selected pairs of genes, the Pearson correlation coefficient was 0.875 between the single-cell and 5-cell pools and 0.783 between the single-cell and 10-cell pools. As expected, abundant transcripts in the 5- and 10-cell samples were detected by RT-qPCR in the single-cell isolates, while lower abundance messages were not. Using the same stringency, 16,039 probes were positive on the patient single-cell arrays. Cluster analysis showed that all 10 DTC grouped together within each patient. A transcriptomic profile can be reliably obtained from a single cell using commercially available technology. As expected, fewer amplified genes are detected from a single-cell sample than from pooled-cell samples, however this method can be used to reliably obtain a transcriptomic profile from DTC isolated from the bone marrow of patients with PCa.

Detection of Explosives Using Differential Laser-Induced Perturbation Spectroscopy with a Raman-based Probe.

PubMed

Oztekin, Erman K; Burton, Dallas J; Hahn, David W

2016-04-01

Explosives detection is carried out with a novel spectral analysis technique referred to as differential laser-induced perturbation spectroscopy (DLIPS) on thin films of TNT, RDX, HMX, and PETN. The utility of Raman spectroscopy for detection of explosives is enhanced by inducing deep ultraviolet laser perturbation on molecular structures in combination with a differential Raman sensing scheme. Principal components analysis (PCA) is used to quantify the DLIPS method as benchmarked against a traditional Raman scattering probe, and the related photo-induced effects on the molecular structure of the targeted explosives are discussed in detail. Finally, unique detection is observed with TNT samples deposited on commonly available background substrates of nylon and polyester. Overall, the data support DLIPS as a noninvasive method that is promising for screening explosives in real-world environments and backgrounds. © The Author(s) 2016.

Application of reflectance spectroscopies (FTIR-ATR & FT-NIR) coupled with multivariate methods for robust in vivo detection of begomovirus infection in papaya leaves

NASA Astrophysics Data System (ADS)

Haq, Quazi M. I.; Mabood, Fazal; Naureen, Zakira; Al-Harrasi, Ahmed; Gilani, Sayed A.; Hussain, Javid; Jabeen, Farah; Khan, Ajmal; Al-Sabari, Ruqaya S. M.; Al-khanbashi, Fatema H. S.; Al-Fahdi, Amira A. M.; Al-Zaabi, Ahoud K. A.; Al-Shuraiqi, Fatma A. M.; Al-Bahaisi, Iman M.

2018-06-01

Nucleic acid & serology based methods have revolutionized plant disease detection, however, they are not very reliable at asymptomatic stage, especially in case of pathogen with systemic infection, in addition, they need at least 1-2 days for sample harvesting, processing, and analysis. In this study, two reflectance spectroscopies i.e. Near Infrared reflectance spectroscopy (NIR) and Fourier-Transform-Infrared spectroscopy with Attenuated Total Reflection (FT-IR, ATR) coupled with multivariate exploratory methods like Principle Component Analysis (PCA) and Partial least square discriminant analysis (PLS-DA) have been deployed to detect begomovirus infection in papaya leaves. The application of those techniques demonstrates that they are very useful for robust in vivo detection of plant begomovirus infection. These methods are simple, sensitive, reproducible, precise, and do not require any lengthy samples preparation procedures.

A novel method for qualitative analysis of edible oil oxidation using an electronic nose.

PubMed

Xu, Lirong; Yu, Xiuzhu; Liu, Lei; Zhang, Rui

2016-07-01

An electronic nose (E-nose) was used for rapid assessment of the degree of oxidation in edible oils. Peroxide and acid values of edible oil samples were analyzed using data obtained by the American Oil Chemists' Society (AOCS) Official Method for reference. Qualitative discrimination between non-oxidized and oxidized oils was conducted using the E-nose technique developed in combination with cluster analysis (CA), principal component analysis (PCA), and linear discriminant analysis (LDA). The results from CA, PCA and LDA indicated that the E-nose technique could be used for differentiation of non-oxidized and oxidized oils. LDA produced slightly better results than CA and PCA. The proposed approach can be used as an alternative to AOCS Official Method as an innovative tool for rapid detection of edible oil oxidation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Variability search in M 31 using principal component analysis and the Hubble Source Catalogue

NASA Astrophysics Data System (ADS)

Moretti, M. I.; Hatzidimitriou, D.; Karampelas, A.; Sokolovsky, K. V.; Bonanos, A. Z.; Gavras, P.; Yang, M.

2018-06-01

Principal component analysis (PCA) is being extensively used in Astronomy but not yet exhaustively exploited for variability search. The aim of this work is to investigate the effectiveness of using the PCA as a method to search for variable stars in large photometric data sets. We apply PCA to variability indices computed for light curves of 18 152 stars in three fields in M 31 extracted from the Hubble Source Catalogue. The projection of the data into the principal components is used as a stellar variability detection and classification tool, capable of distinguishing between RR Lyrae stars, long-period variables (LPVs) and non-variables. This projection recovered more than 90 per cent of the known variables and revealed 38 previously unknown variable stars (about 30 per cent more), all LPVs except for one object of uncertain variability type. We conclude that this methodology can indeed successfully identify candidate variable stars.

Fusion of multi-parametric MRI and temporal ultrasound for characterization of prostate cancer: in vivo feasibility study

NASA Astrophysics Data System (ADS)

Imani, Farhad; Ghavidel, Sahar; Abolmaesumi, Purang; Khallaghi, Siavash; Gibson, Eli; Khojaste, Amir; Gaed, Mena; Moussa, Madeleine; Gomez, Jose A.; Romagnoli, Cesare; Cool, Derek W.; Bastian-Jordan, Matthew; Kassam, Zahra; Siemens, D. Robert; Leveridge, Michael; Chang, Silvia; Fenster, Aaron; Ward, Aaron D.; Mousavi, Parvin

2016-03-01

Recently, multi-parametric Magnetic Resonance Imaging (mp-MRI) has been used to improve the sensitivity of detecting high-risk prostate cancer (PCa). Prior to biopsy, primary and secondary cancer lesions are identified on mp-MRI. The lesions are then targeted using TRUS guidance. In this paper, for the first time, we present a fused mp-MRI-temporal-ultrasound framework for characterization of PCa, in vivo. Cancer classification results obtained using temporal ultrasound are fused with those achieved using consolidated mp-MRI maps determined by multiple observers. We verify the outcome of our study using histopathology following deformable registration of ultrasound and histology images. Fusion of temporal ultrasound and mp-MRI for characterization of the PCa results in an area under the receiver operating characteristic curve (AUC) of 0.86 for cancerous regions with Gleason scores (GSs)>=3+3, and AUC of 0.89 for those with GSs>=3+4.

Effect of age at onset on cortical thickness and cognition in posterior cortical atrophy

PubMed Central

Suárez-González, Aida; Lehmann, Manja; Shakespeare, Timothy J.; Yong, Keir X.X.; Paterson, Ross W.; Slattery, Catherine F.; Foulkes, Alexander J.M.; Rabinovici, Gil D.; Gil-Néciga, Eulogio; Roldán-Lora, Florinda; Schott, Jonathan M.; Fox, Nick C.; Crutch, Sebastian J.

2016-01-01

Age at onset (AAO) has been shown to influence the phenotype of Alzheimer’s disease (AD), but how it affects atypical presentations of AD remains unknown. Posterior cortical atrophy (PCA) is the most common form of atypical AD. In this study, we aimed to investigate the effect of AAO on cortical thickness and cognitive function in 98 PCA patients. We used Freesurfer (v5.3.0) to compare cortical thickness with AAO both as a continuous variable, and by dichotomizing the groups based on median age (58 years). In both the continuous and dichotomized analyses, we found a pattern suggestive of thinner cortex in precuneus and parietal areas in earlier-onset PCA, and lower cortical thickness in anterior cingulate and prefrontal cortex in later-onset PCA. These cortical thickness differences between PCA subgroups were consistent with earlier-onset PCA patients performing worse on cognitive tests involving parietal functions. Our results provide a suggestion that AAO may not only affect the clinico-anatomical characteristics in AD but may also affect atrophy patterns and cognition within atypical AD phenotypes. PMID:27318138

Impact of Prostate Cancer Treatment on the Sexual Quality of Life for Men-Who-Have-Sex-with-Men.

PubMed

Lee, Tsz Kin; Handy, Ariel Baker; Kwan, Winkle; Oliffe, John Lindsay; Brotto, Lori Anne; Wassersug, Richard Joel; Dowsett, Gary Wayne

2015-12-01

With earlier prostate cancer (PCa) diagnosis and an increased focus on survivorship, post-treatment sexual quality of life (QoL) has become increasingly important. Research and validated instruments for sexual QoL assessment based on heterosexual samples have limited applicability for men-who-have-sex-with-men (MSM). We aimed to create a validated instrument for assessing sexual needs and concerns of MSM post-PCa treatment. Here we explore post-PCa treatment sexual concerns for a sample of MSM, as the first part of this multi-phase project. Individual semi-structured interviews were conducted with 16 MSM face-to-face or via Internet-based video conferencing. Participants were asked open-ended questions about their experiences of sexual QoL following PCa. Interviews were recorded, transcribed verbatim, uploaded to NVivo 8(TM) , and analyzed using qualitative methodology. We have conducted semi-structure qualitative interviews on 16 MSM who were treated for PCa. Focus was on post-treatment sexual concerns. The following themes were inductively derived: (i) erectile, urinary, ejaculation, and orgasmic dysfunctions; (ii) challenges to intimate relationships; and (iii) lack of MSM-specific oncological and psychosocial support for PCa survivorship. Sexual practices pre-treatment ranked in order of frequency were masturbation, oral sex, and anal sex, an ordering that prevailed post-treatment. Sexual QoL decreased with erectile, urinary, and ejaculation dysfunctions. Post-treatment orgasms were compromised. Some single men and men in non-monogamous relationships reported a loss of confidence or difficulty meeting other men post-treatment. Limited access to targeted oncological and psychosocial supports posed difficulties in coping with PCa for MSM. The negative impact on sexual QoL can be severe for MSM and requires targeted attention. Penile-vaginal intercourse and erectile function have been the primary focus of sexual research and rehabilitation for men with PCa, and do not adequately reflect the sexual practices of MSM. Our findings suggest that future research dedicated to MSM with PCa is needed to incorporate their sexual practices and preferences specifically into treatment decisions, and that targeted oncological and psychosocial support services are also warranted. © 2015 International Society for Sexual Medicine.

Competing-risks mortality after radiotherapy vs. observation for localized prostate cancer: a population-based study.

PubMed

Abdollah, Firas; Sun, Maxine; Schmitges, Jan; Thuret, Rodolphe; Tian, Zhe; Shariat, Shahrokh F; Briganti, Alberto; Jeldres, Claudio; Perrotte, Paul; Montorsi, Francesco; Karakiewicz, Pierre I

2012-09-01

Contemporary patients with localized prostate cancer (PCa) are more frequently treated with radiotherapy. However, there are limited data on the effect of this treatment on cancer-specific mortality (CSM). Our objective was to test the relationship between radiotherapy and survival in men with localized PCa and compare it with those treated with observation. A population-based cohort identified 68,797 men with cT1-T2 PCa treated with radiotherapy or observation between the years 1992 and 2005. Propensity-score matching was used to minimize potential bias related to treatment assignment. Competing-risks analyses tested the effect of treatment type (radiotherapy vs. observation) on CSM, after accounting to other-cause mortality. All analyses were carried out within PCa risk, baseline comorbidity status, and age groups. Radiotherapy was associated with more favorable 10-year CSM rates than observation in patients with high-risk PCa (8.8 vs. 14.4%, hazard ratio [HR]: 0.59, 95% confidence interval [CI]: 0.50-0.68). Conversely, the beneficial effect of radiotherapy on CSM was not evident in patients with low-intermediate risk PCa (3.7 vs. 4.1%, HR: 0.91, 95% CI: 0.80-1.04). Radiotherapy was beneficial in elderly patients (5.6 vs. 7.3%, HR: 0.70, 95% CI: 0.59-0.80). Moreover, it was associated with improved CSM rates among patients with no comorbidities (5.7 vs. 6.5%, HR: 0.81, 95% CI: 0.67-0.98), one comorbidity (4.6 vs. 6.0%, HR: 0.87, 95% CI: 0.75-0.99), and more than two comorbidities (4.2 vs. 5.0%, HR: 0.79, 95% CI: 0.65-0.96). Radiotherapy substantially improves CSM in patients with high-risk PCa, with little or no benefit in patients with low-/intermediate-risk PCa relative to observation. These findings must be interpreted within the context of the limitations of observational data. Copyright © 2012 Elsevier Inc. All rights reserved.

PCA based clustering for brain tumor segmentation of T1w MRI images.

PubMed

Kaya, Irem Ersöz; Pehlivanlı, Ayça Çakmak; Sekizkardeş, Emine Gezmez; Ibrikci, Turgay

2017-03-01

Medical images are huge collections of information that are difficult to store and process consuming extensive computing time. Therefore, the reduction techniques are commonly used as a data pre-processing step to make the image data less complex so that a high-dimensional data can be identified by an appropriate low-dimensional representation. PCA is one of the most popular multivariate methods for data reduction. This paper is focused on T1-weighted MRI images clustering for brain tumor segmentation with dimension reduction by different common Principle Component Analysis (PCA) algorithms. Our primary aim is to present a comparison between different variations of PCA algorithms on MRIs for two cluster methods. Five most common PCA algorithms; namely the conventional PCA, Probabilistic Principal Component Analysis (PPCA), Expectation Maximization Based Principal Component Analysis (EM-PCA), Generalize Hebbian Algorithm (GHA), and Adaptive Principal Component Extraction (APEX) were applied to reduce dimensionality in advance of two clustering algorithms, K-Means and Fuzzy C-Means. In the study, the T1-weighted MRI images of the human brain with brain tumor were used for clustering. In addition to the original size of 512 lines and 512 pixels per line, three more different sizes, 256 × 256, 128 × 128 and 64 × 64, were included in the study to examine their effect on the methods. The obtained results were compared in terms of both the reconstruction errors and the Euclidean distance errors among the clustered images containing the same number of principle components. According to the findings, the PPCA obtained the best results among all others. Furthermore, the EM-PCA and the PPCA assisted K-Means algorithm to accomplish the best clustering performance in the majority as well as achieving significant results with both clustering algorithms for all size of T1w MRI images. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Kernel Principal Component Analysis for dimensionality reduction in fMRI-based diagnosis of ADHD.

PubMed

Sidhu, Gagan S; Asgarian, Nasimeh; Greiner, Russell; Brown, Matthew R G

2012-01-01

This study explored various feature extraction methods for use in automated diagnosis of Attention-Deficit Hyperactivity Disorder (ADHD) from functional Magnetic Resonance Image (fMRI) data. Each participant's data consisted of a resting state fMRI scan as well as phenotypic data (age, gender, handedness, IQ, and site of scanning) from the ADHD-200 dataset. We used machine learning techniques to produce support vector machine (SVM) classifiers that attempted to differentiate between (1) all ADHD patients vs. healthy controls and (2) ADHD combined (ADHD-c) type vs. ADHD inattentive (ADHD-i) type vs. controls. In different tests, we used only the phenotypic data, only the imaging data, or else both the phenotypic and imaging data. For feature extraction on fMRI data, we tested the Fast Fourier Transform (FFT), different variants of Principal Component Analysis (PCA), and combinations of FFT and PCA. PCA variants included PCA over time (PCA-t), PCA over space and time (PCA-st), and kernelized PCA (kPCA-st). Baseline chance accuracy was 64.2% produced by guessing healthy control (the majority class) for all participants. Using only phenotypic data produced 72.9% accuracy on two class diagnosis and 66.8% on three class diagnosis. Diagnosis using only imaging data did not perform as well as phenotypic-only approaches. Using both phenotypic and imaging data with combined FFT and kPCA-st feature extraction yielded accuracies of 76.0% on two class diagnosis and 68.6% on three class diagnosis-better than phenotypic-only approaches. Our results demonstrate the potential of using FFT and kPCA-st with resting-state fMRI data as well as phenotypic data for automated diagnosis of ADHD. These results are encouraging given known challenges of learning ADHD diagnostic classifiers using the ADHD-200 dataset (see Brown et al., 2012).

Monitoring of the posterior cricoarytenoid muscle represents another option for neural monitoring during thyroid surgery: Normative vagal and recurrent laryngeal nerve posterior cricoarytenoid muscle electromyographic data.

PubMed

Liddy, Whitney; Barber, Samuel R; Lin, Brian M; Kamani, Dipti; Kyriazidis, Natalia; Lawson, Bradley; Randolph, Gregory W

2018-01-01

Intraoperative neural monitoring (IONM) of laryngeal nerves using electromyography (EMG) is routinely performed using endotracheal tube surface electrodes adjacent to the vocalis muscles. Other laryngeal muscles such as the posterior cricoarytenoid muscle (PCA) are indirectly monitored. The PCA may be directly and reliably monitored through an electrode placed in the postcricoid region. Herein, we describe the method and normative data for IONM using PCA EMG. Retrospective review. Data were reviewed retrospectively for thyroid and parathyroid surgery patients with IONM of laryngeal nerves from January to August 2016. Recordings of vocalis and PCA EMG amplitudes and latencies with stimulation of laryngeal nerves were obtained using endotracheal (ET) tube-based and postcricoid surface electrodes. Data comprised EMG responses in vocalis and PCA recording channels with stimulation of the vagus, recurrent laryngeal nerve (RLN), and external branch of the superior laryngeal nerve from 20 subjects (11 left, 9 right), as well as PCA EMG threshold data with RLN stimulation from 17 subjects. Mean EMG amplitude was 725.69 ± 108.58 microvolts (µV) for the ipsilateral vocalis and 329.44 ± 34.12 µV for the PCA with vagal stimulation, and 1,059.75 ± 140.40 µV for the ipsilateral vocalis and 563.88 ± 116.08 µV for the PCA with RLN stimulation. There were no statistically significant differences in mean latency. For threshold cutoffs of the PCA with RLN stimulation, mean minimum and maximum threshold intensities were 0.37 milliamperes (mA) and 0.84 mA, respectively. This study shows robust and reliable PCA EMG waveforms with direct nerve stimulation. Further studies will evaluate feasibility and application of the PCA electrode as a complementary quantitative tool in IONM. 4. Laryngoscope, 128:283-289, 2018. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

Epigenetics-related genes in prostate cancer: expression profile in prostate cancer tissues, androgen-sensitive and -insensitive cell lines.

PubMed

Shaikhibrahim, Zaki; Lindstrot, Andreas; Ochsenfahrt, Jacqueline; Fuchs, Kerstin; Wernert, Nicolas

2013-01-01

Epigenetic changes have been suggested to drive prostate cancer (PCa) development and progression. Therefore, in this study, we aimed to identify novel epigenetics-related genes in PCa tissues, and to examine their expression in metastatic PCa cell lines. We analyzed the expression of epigenetics-related genes via a clustering analysis based on gene function in moderately and poorly differentiated PCa glands compared to normal glands of the peripheral zone (prostate proper) from PCa patients using Whole Human Genome Oligo Microarrays. Our analysis identified 12 epigenetics-related genes with a more than 2-fold increase or decrease in expression and a p-value <0.01. In modera-tely differentiated tumors compared to normal glands of the peripheral zone, we found the genes, TDRD1, IGF2, DICER1, ADARB1, HILS1, GLMN and TRIM27, to be upregulated, whereas TNRC6A and DGCR8 were found to be downregulated. In poorly differentiated tumors, we found TDRD1, ADARB and RBM3 to be upregulated, whereas DGCR8, PIWIL2 and BC069781 were downregulated. Our analysis of the expression level for each gene in the metastatic androgen-sensitive VCaP and LNCaP, and -insensitive PC3 and DU-145 PCa cell lines revealed differences in expression among the cell lines which may reflect the different biological properties of each cell line, and the potential role of each gene at different metastatic sites. The novel epigenetics-related genes that we identified in primary PCa tissues may provide further insight into the role that epigenetic changes play in PCa. Moreover, some of the genes that we identified may play important roles in primary PCa and metastasis, in primary PCa only, or in metastasis only. Follow-up studies are required to investigate the functional role and the role that the expression of these genes play in the outcome and progression of PCa using tissue microarrays.