Robust Statistical Fusion of Image Labels

PubMed Central

Landman, Bennett A.; Asman, Andrew J.; Scoggins, Andrew G.; Bogovic, John A.; Xing, Fangxu; Prince, Jerry L.

2011-01-01

Image labeling and parcellation (i.e. assigning structure to a collection of voxels) are critical tasks for the assessment of volumetric and morphometric features in medical imaging data. The process of image labeling is inherently error prone as images are corrupted by noise and artifacts. Even expert interpretations are subject to subjectivity and the precision of the individual raters. Hence, all labels must be considered imperfect with some degree of inherent variability. One may seek multiple independent assessments to both reduce this variability and quantify the degree of uncertainty. Existing techniques have exploited maximum a posteriori statistics to combine data from multiple raters and simultaneously estimate rater reliabilities. Although quite successful, wide-scale application has been hampered by unstable estimation with practical datasets, for example, with label sets with small or thin objects to be labeled or with partial or limited datasets. As well, these approaches have required each rater to generate a complete dataset, which is often impossible given both human foibles and the typical turnover rate of raters in a research or clinical environment. Herein, we propose a robust approach to improve estimation performance with small anatomical structures, allow for missing data, account for repeated label sets, and utilize training/catch trial data. With this approach, numerous raters can label small, overlapping portions of a large dataset, and rater heterogeneity can be robustly controlled while simultaneously estimating a single, reliable label set and characterizing uncertainty. The proposed approach enables many individuals to collaborate in the construction of large datasets for labeling tasks (e.g., human parallel processing) and reduces the otherwise detrimental impact of rater unavailability. PMID:22010145

Siloxane nanoprobes for labeling and dual modality imaging of neural stem cells

PubMed Central

Addington, Caroline P.; Cusick, Alex; Shankar, Rohini Vidya; Agarwal, Shubhangi; Stabenfeldt, Sarah E.; Kodibagkar, Vikram D.

2015-01-01

Cell therapy represents a promising therapeutic for a myriad of medical conditions, including cancer, traumatic brain injury, and cardiovascular disease among others. A thorough understanding of the efficacy and cellular dynamics of these therapies necessitates the ability to non-invasively track cells in vivo. Magnetic resonance imaging (MRI) provides a platform to track cells as a non-invasive modality with superior resolution and soft tissue contrast. We recently reported a new nanoprobe platform for cell labeling and imaging using fluorophore doped siloxane core nanoemulsions as dual modality (1H MRI/Fluorescence), dual-functional (oximetry/detection) nanoprobes. Here, we successfully demonstrate the labeling, dual-modality imaging, and oximetry of neural progenitor/stem cells (NPSCs) in vitro using this platform. Labeling at a concentration of 10 μl/104 cells with a 40%v/v polydimethylsiloxane core nanoemulsion, doped with rhodamine, had minimal effect on viability, no effect on migration, proliferation and differentiation of NPSCs and allowed for unambiguous visualization of labeled NPSCs by 1H MR and fluorescence and local pO2 reporting by labeled NPSCs. This new approach for cell labeling with a positive contrast 1H MR probe has the potential to improve mechanistic knowledge of current therapies, and guide the design of future cell therapies due to its clinical translatability. PMID:26597417

Do we need annotation experts? A case study in celiac disease classification.

PubMed

Kwitt, Roland; Hegenbart, Sebastian; Rasiwasia, Nikhil; Vécsei, Andreas; Uhl, Andreas

2014-01-01

Inference of clinically-relevant findings from the visual appearance of images has become an essential part of processing pipelines for many problems in medical imaging. Typically, a sufficient amount labeled training data is assumed to be available, provided by domain experts. However, acquisition of this data is usually a time-consuming and expensive endeavor. In this work, we ask the question if, for certain problems, expert knowledge is actually required. In fact, we investigate the impact of letting non-expert volunteers annotate a database of endoscopy images which are then used to assess the absence/presence of celiac disease. Contrary to previous approaches, we are not interested in algorithms that can handle the label noise. Instead, we present compelling empirical evidence that label noise can be compensated by a sufficiently large corpus of training data, labeled by the non-experts.

Object-based modeling, identification, and labeling of medical images for content-based retrieval by querying on intervals of attribute values

NASA Astrophysics Data System (ADS)

Thies, Christian; Ostwald, Tamara; Fischer, Benedikt; Lehmann, Thomas M.

2005-04-01

The classification and measuring of objects in medical images is important in radiological diagnostics and education, especially when using large databases as knowledge resources, for instance a picture archiving and communication system (PACS). The main challenge is the modeling of medical knowledge and the diagnostic context to label the sought objects. This task is referred to as closing the semantic gap between low-level pixel information and high level application knowledge. This work describes an approach which allows labeling of a-priori unknown objects in an intuitive way. Our approach consists of four main components. At first an image is completely decomposed into all visually relevant partitions on different scales. This provides a hierarchical organized set of regions. Afterwards, for each of the obtained regions a set of descriptive features is computed. In this data structure objects are represented by regions with characteristic attributes. The actual object identification is the formulation of a query. It consists of attributes on which intervals are defined describing those regions that correspond to the sought objects. Since the objects are a-priori unknown, they are described by a medical expert by means of an intuitive graphical user interface (GUI). This GUI is the fourth component. It enables complex object definitions by browsing the data structure and examinating the attributes to formulate the query. The query is executed and if the sought objects have not been identified its parameterization is refined. By using this heuristic approach, object models for hand radiographs have been developed to extract bones from a single hand in different anatomical contexts. This demonstrates the applicability of the labeling concept. By using a rule for metacarpal bones on a series of 105 images, this type of bone could be retrieved with a precision of 0.53 % and a recall of 0.6%.

Integrating user profile in medical CBIR systems to answer perceptual similarity queries

NASA Astrophysics Data System (ADS)

Bugatti, Pedro H.; Kaster, Daniel S.; Ponciano-Silva, Marcelo; Traina, Agma J. M.; Traina, Caetano, Jr.

2011-03-01

Techniques for Content-Based Image Retrieval (CBIR) have been intensively explored due to the increase in the amount of captured images and the need of fast retrieval of them. The medical field is a specific example that generates a large flow of information, especially digital images employed for diagnosing. One issue that still remains unsolved deals with how to reach the perceptual similarity. That is, to achieve an effective retrieval, one must characterize and quantify the perceptual similarity regarding the specialist in the field. Therefore, the present paper was conceived to fill in this gap creating a consistent support to perform similarity queries over medical images, maintaining the semantics of a given query desired by the user. CBIR systems relying in relevance feedback techniques usually request the users to label relevant images. In this paper, we present a simple but highly effective strategy to survey user profiles, taking advantage of such labeling to implicitly gather the user perceptual similarity. The user profiles maintain the settings desired for each user, allowing tuning the similarity assessment, which encompasses dynamically changing the distance function employed through an interactive process. Experiments using computed tomography lung images show that the proposed approach is effective in capturing the users' perception.

Style-independent document labeling: design and performance evaluation

NASA Astrophysics Data System (ADS)

Mao, Song; Kim, Jong Woo; Thoma, George R.

2003-12-01

The Medical Article Records System or MARS has been developed at the U.S. National Library of Medicine (NLM) for automated data entry of bibliographical information from medical journals into MEDLINE, the premier bibliographic citation database at NLM. Currently, a rule-based algorithm (called ZoneCzar) is used for labeling important bibliographical fields (title, author, affiliation, and abstract) on medical journal article page images. While rules have been created for medical journals with regular layout types, new rules have to be manually created for any input journals with arbitrary or new layout types. Therefore, it is of interest to label any journal articles independent of their layout styles. In this paper, we first describe a system (called ZoneMatch) for automated generation of crucial geometric and non-geometric features of important bibliographical fields based on string-matching and clustering techniques. The rule based algorithm is then modified to use these features to perform style-independent labeling. We then describe a performance evaluation method for quantitatively evaluating our algorithm and characterizing its error distributions. Experimental results show that the labeling performance of the rule-based algorithm is significantly improved when the generated features are used.

Volume estimation of brain abnormalities in MRI data

NASA Astrophysics Data System (ADS)

Suprijadi, Pratama, S. H.; Haryanto, F.

2014-02-01

The abnormality of brain tissue always becomes a crucial issue in medical field. This medical condition can be recognized through segmentation of certain region from medical images obtained from MRI dataset. Image processing is one of computational methods which very helpful to analyze the MRI data. In this study, combination of segmentation and rendering image were used to isolate tumor and stroke. Two methods of thresholding were employed to segment the abnormality occurrence, followed by filtering to reduce non-abnormality area. Each MRI image is labeled and then used for volume estimations of tumor and stroke-attacked area. The algorithms are shown to be successful in isolating tumor and stroke in MRI images, based on thresholding parameter and stated detection accuracy.

Non-rigid ultrasound image registration using generalized relaxation labeling process

NASA Astrophysics Data System (ADS)

Lee, Jong-Ha; Seong, Yeong Kyeong; Park, MoonHo; Woo, Kyoung-Gu; Ku, Jeonghun; Park, Hee-Jun

2013-03-01

This research proposes a novel non-rigid registration method for ultrasound images. The most predominant anatomical features in medical images are tissue boundaries, which appear as edges. In ultrasound images, however, other features can be identified as well due to the specular reflections that appear as bright lines superimposed on the ideal edge location. In this work, an image's local phase information (via the frequency domain) is used to find the ideal edge location. The generalized relaxation labeling process is then formulated to align the feature points extracted from the ideal edge location. In this work, the original relaxation labeling method was generalized by taking n compatibility coefficient values to improve non-rigid registration performance. This contextual information combined with a relaxation labeling process is used to search for a correspondence. Then the transformation is calculated by the thin plate spline (TPS) model. These two processes are iterated until the optimal correspondence and transformation are found. We have tested our proposed method and the state-of-the-art algorithms with synthetic data and bladder ultrasound images of in vivo human subjects. Experiments show that the proposed method improves registration performance significantly, as compared to other state-of-the-art non-rigid registration algorithms.

Label fusion based brain MR image segmentation via a latent selective model

NASA Astrophysics Data System (ADS)

Liu, Gang; Guo, Xiantang; Zhu, Kai; Liao, Hengxu

2018-04-01

Multi-atlas segmentation is an effective approach and increasingly popular for automatically labeling objects of interest in medical images. Recently, segmentation methods based on generative models and patch-based techniques have become the two principal branches of label fusion. However, these generative models and patch-based techniques are only loosely related, and the requirement for higher accuracy, faster segmentation, and robustness is always a great challenge. In this paper, we propose novel algorithm that combines the two branches using global weighted fusion strategy based on a patch latent selective model to perform segmentation of specific anatomical structures for human brain magnetic resonance (MR) images. In establishing this probabilistic model of label fusion between the target patch and patch dictionary, we explored the Kronecker delta function in the label prior, which is more suitable than other models, and designed a latent selective model as a membership prior to determine from which training patch the intensity and label of the target patch are generated at each spatial location. Because the image background is an equally important factor for segmentation, it is analyzed in label fusion procedure and we regard it as an isolated label to keep the same privilege between the background and the regions of interest. During label fusion with the global weighted fusion scheme, we use Bayesian inference and expectation maximization algorithm to estimate the labels of the target scan to produce the segmentation map. Experimental results indicate that the proposed algorithm is more accurate and robust than the other segmentation methods.

Human induced pluripotent stem cells labeled with fluorescent magnetic nanoparticles for targeted imaging and hyperthermia therapy for gastric cancer.

PubMed

Li, Chao; Ruan, Jing; Yang, Meng; Pan, Fei; Gao, Guo; Qu, Su; Shen, You-Lan; Dang, Yong-Jun; Wang, Kan; Jin, Wei-Lin; Cui, Da-Xiang

2015-09-01

Human induced pluripotent stem (iPS) cells exhibit great potential for generating functional human cells for medical therapies. In this paper, we report for use of human iPS cells labeled with fluorescent magnetic nanoparticles (FMNPs) for targeted imaging and synergistic therapy of gastric cancer cells in vivo. Human iPS cells were prepared and cultured for 72 h. The culture medium was collected, and then was co-incubated with MGC803 cells. Cell viability was analyzed by the MTT method. FMNP-labeled human iPS cells were prepared and injected into gastric cancer-bearing nude mice. The mouse model was observed using a small-animal imaging system. The nude mice were irradiated under an external alternating magnetic field and evaluated using an infrared thermal mapping instrument. Tumor sizes were measured weekly. iPS cells and the collected culture medium inhibited the growth of MGC803 cells. FMNP-labeled human iPS cells targeted and imaged gastric cancer cells in vivo, as well as inhibited cancer growth in vivo through the external magnetic field. FMNP-labeled human iPS cells exhibit considerable potential in applications such as targeted dual-mode imaging and synergistic therapy for early gastric cancer.

Shape complexes: the intersection of label orderings and star convexity constraints in continuous max-flow medical image segmentation

PubMed Central

Baxter, John S. H.; Inoue, Jiro; Drangova, Maria; Peters, Terry M.

2016-01-01

Abstract. Optimization-based segmentation approaches deriving from discrete graph-cuts and continuous max-flow have become increasingly nuanced, allowing for topological and geometric constraints on the resulting segmentation while retaining global optimality. However, these two considerations, topological and geometric, have yet to be combined in a unified manner. The concept of “shape complexes,” which combine geodesic star convexity with extendable continuous max-flow solvers, is presented. These shape complexes allow more complicated shapes to be created through the use of multiple labels and super-labels, with geodesic star convexity governed by a topological ordering. These problems can be optimized using extendable continuous max-flow solvers. Previous approaches required computationally expensive coordinate system warping, which are ill-defined and ambiguous in the general case. These shape complexes are demonstrated in a set of synthetic images as well as vessel segmentation in ultrasound, valve segmentation in ultrasound, and atrial wall segmentation from contrast-enhanced CT. Shape complexes represent an extendable tool alongside other continuous max-flow methods that may be suitable for a wide range of medical image segmentation problems. PMID:28018937

18F-positron-emitting/fluorescent labeled erythrocytes allow imaging of internal hemorrhage in a murine intracranial hemorrhage model

PubMed Central

Wang, Ye; An, Fei-Fei; Chan, Mark; Friedman, Beth; Rodriguez, Erik A; Tsien, Roger Y; Aras, Omer

2017-01-01

An agent for visualizing cells by positron emission tomography is described and used to label red blood cells. The labeled red blood cells are injected systemically so that intracranial hemorrhage can be visualized by positron emission tomography (PET). Red blood cells are labeled with 0.3 µg of a positron-emitting, fluorescent multimodal imaging probe, and used to non-invasively image cryolesion induced intracranial hemorrhage in a murine model (BALB/c, 2.36 × 108 cells, 100 µCi, <4 mm hemorrhage). Intracranial hemorrhage is confirmed by histology, fluorescence, bright-field, and PET ex vivo imaging. The low required activity, minimal mass, and high resolution of this technique make this strategy an attractive alternative for imaging intracranial hemorrhage. PET is one solution to a spectrum of issues that complicate single photon emission computed tomography (SPECT). For this reason, this application serves as a PET alternative to [99mTc]-agents, and SPECT technology that is used in 2 million annual medical procedures. PET contrast is also superior to gadolinium and iodide contrast angiography for its lack of clinical contraindications. PMID:28054494

Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?

PubMed

Tajbakhsh, Nima; Shin, Jae Y; Gurudu, Suryakanth R; Hurst, R Todd; Kendall, Christopher B; Gotway, Michael B; Jianming Liang

2016-05-01

Training a deep convolutional neural network (CNN) from scratch is difficult because it requires a large amount of labeled training data and a great deal of expertise to ensure proper convergence. A promising alternative is to fine-tune a CNN that has been pre-trained using, for instance, a large set of labeled natural images. However, the substantial differences between natural and medical images may advise against such knowledge transfer. In this paper, we seek to answer the following central question in the context of medical image analysis: Can the use of pre-trained deep CNNs with sufficient fine-tuning eliminate the need for training a deep CNN from scratch? To address this question, we considered four distinct medical imaging applications in three specialties (radiology, cardiology, and gastroenterology) involving classification, detection, and segmentation from three different imaging modalities, and investigated how the performance of deep CNNs trained from scratch compared with the pre-trained CNNs fine-tuned in a layer-wise manner. Our experiments consistently demonstrated that 1) the use of a pre-trained CNN with adequate fine-tuning outperformed or, in the worst case, performed as well as a CNN trained from scratch; 2) fine-tuned CNNs were more robust to the size of training sets than CNNs trained from scratch; 3) neither shallow tuning nor deep tuning was the optimal choice for a particular application; and 4) our layer-wise fine-tuning scheme could offer a practical way to reach the best performance for the application at hand based on the amount of available data.

In vivo fluorescence imaging of hepatocellular carcinoma xenograft using near-infrared labeled epidermal growth factor receptor (EGFR) peptide

PubMed Central

Li, Z.; Zhou, Q.; Zhou, J.; Duan, X.; Zhu, J.; Wang, T. D.

2016-01-01

Minimally-invasive surgery of hepatocellular carcinoma (HCC) can be limited by poor tumor visualization with white light. We demonstrate systemic administration of a Cy5.5-labeled peptide specific for epidermal growth factor receptor (EGFR) to target HCC in vivo in a mouse xenograft model. We attached a compact imaging module to the proximal end of a medical laparoscope to collect near-infrared fluorescence and reflectance images concurrently at 15 frames/sec. We measured a mean target-to-background ratio of 2.99 ± 0.22 from 13 surgically exposed subcutaneous human HCC tumors in vivo in 5 mice. This integrated imaging methodology is promising to guide laparoscopic resection of HCC. PMID:27699089

Prioritization of brain MRI volumes using medical image perception model and tumor region segmentation.

PubMed

Mehmood, Irfan; Ejaz, Naveed; Sajjad, Muhammad; Baik, Sung Wook

2013-10-01

The objective of the present study is to explore prioritization methods in diagnostic imaging modalities to automatically determine the contents of medical images. In this paper, we propose an efficient prioritization of brain MRI. First, the visual perception of the radiologists is adapted to identify salient regions. Then this saliency information is used as an automatic label for accurate segmentation of brain lesion to determine the scientific value of that image. The qualitative and quantitative results prove that the rankings generated by the proposed method are closer to the rankings created by radiologists. Copyright © 2013 Elsevier Ltd. All rights reserved.

Analysis of the meal-dependent intragastric performance of a gastric-retentive tablet assessed by magnetic resonance imaging.

PubMed

Steingoetter, A; Kunz, P; Weishaupt, D; Mäder, K; Lengsfeld, H; Thumshirn, M; Boesiger, P; Fried, M; Schwizer, W

2003-10-01

Modern medical imaging modalities can trace labelled oral drug dosage forms in the gastrointestinal tract, and thus represent important tools for the evaluation of their in vivo performance. The application of gastric-retentive drug delivery systems to improve bioavailability and to avoid unwanted plasma peak concentrations of orally administered drugs is of special interest in clinical and pharmaceutical research. To determine the influence of meal composition and timing of tablet administration on the intragastric performance of a gastric-retentive floating tablet using magnetic resonance imaging in the sitting position. A tablet formulation was labelled with iron oxide particles as negative magnetic resonance contrast marker to allow the monitoring of the tablet position in the food-filled human stomach. Labelled tablet was administered, together with three different solid meals, to volunteers seated in a 0.5-T open-configuration magnetic resonance system. Volunteers were followed over a 4-h period. Labelled tablet was detectable in all subjects throughout the entire study. The tablet showed persistent good intragastric floating performance independent of meal composition. Unfavourable timing of tablet administration had a minor effect on the intragastric tablet residence time and floating performance. Magnetic resonance imaging can reliably monitor and analyse the in vivo performance of labelled gastric-retentive tablets in the human stomach.

Segmentation of deformable organs from medical images using particle swarm optimization and nonlinear shape priors

NASA Astrophysics Data System (ADS)

Afifi, Ahmed; Nakaguchi, Toshiya; Tsumura, Norimichi

2010-03-01

In many medical applications, the automatic segmentation of deformable organs from medical images is indispensable and its accuracy is of a special interest. However, the automatic segmentation of these organs is a challenging task according to its complex shape. Moreover, the medical images usually have noise, clutter, or occlusion and considering the image information only often leads to meager image segmentation. In this paper, we propose a fully automated technique for the segmentation of deformable organs from medical images. In this technique, the segmentation is performed by fitting a nonlinear shape model with pre-segmented images. The kernel principle component analysis (KPCA) is utilized to capture the complex organs deformation and to construct the nonlinear shape model. The presegmentation is carried out by labeling each pixel according to its high level texture features extracted using the overcomplete wavelet packet decomposition. Furthermore, to guarantee an accurate fitting between the nonlinear model and the pre-segmented images, the particle swarm optimization (PSO) algorithm is employed to adapt the model parameters for the novel images. In this paper, we demonstrate the competence of proposed technique by implementing it to the liver segmentation from computed tomography (CT) scans of different patients.

Lyophilized Kit for the Preparation of the PET Perfusion Agent [(68)Ga]-MAA.

PubMed

Amor-Coarasa, Alejandro; Milera, Andrew; Carvajal, Denny; Gulec, Seza; McGoron, Anthony J

2014-01-01

Rapid developments in the field of medical imaging have opened new avenues for the use of positron emitting labeled microparticles. The radioisotope used in our research was (68)Ga, which is easy to obtain from a generator and has good nuclear properties for PET imaging. Methods. Commercially available macroaggregated albumin (MAA) microparticles were suspended in sterile saline, centrifuged to remove the free albumin and stannous chloride, relyophilized, and stored for later labeling with (68)Ga. Labeling was performed at different temperatures and times. (68)Ga purification settings were also tested and optimized. Labeling yield and purity of relyophilized MAA microparticles were compared with those that were not relyophilized. Results. MAA particles kept their original size distribution after relyophilization. Labeling yield was 98% at 75°C when a (68)Ga purification system was used, compared to 80% with unpurified (68)Ga. Radiochemical purity was over 97% up to 4 hours after the labeling. The relyophilized MAA and labeling method eliminate the need for centrifugation purification of the final product and simplify the labeling process. Animal experiments demonstrated the high in vivo stability of the obtained PET agent with more than 95% of the activity remaining in the lungs after 4 hours.

Multi-Atlas Segmentation using Partially Annotated Data: Methods and Annotation Strategies.

PubMed

Koch, Lisa M; Rajchl, Martin; Bai, Wenjia; Baumgartner, Christian F; Tong, Tong; Passerat-Palmbach, Jonathan; Aljabar, Paul; Rueckert, Daniel

2017-08-22

Multi-atlas segmentation is a widely used tool in medical image analysis, providing robust and accurate results by learning from annotated atlas datasets. However, the availability of fully annotated atlas images for training is limited due to the time required for the labelling task. Segmentation methods requiring only a proportion of each atlas image to be labelled could therefore reduce the workload on expert raters tasked with annotating atlas images. To address this issue, we first re-examine the labelling problem common in many existing approaches and formulate its solution in terms of a Markov Random Field energy minimisation problem on a graph connecting atlases and the target image. This provides a unifying framework for multi-atlas segmentation. We then show how modifications in the graph configuration of the proposed framework enable the use of partially annotated atlas images and investigate different partial annotation strategies. The proposed method was evaluated on two Magnetic Resonance Imaging (MRI) datasets for hippocampal and cardiac segmentation. Experiments were performed aimed at (1) recreating existing segmentation techniques with the proposed framework and (2) demonstrating the potential of employing sparsely annotated atlas data for multi-atlas segmentation.

Silica-coated quantum dots for optical evaluation of perfluorocarbon droplet interactions with cells.

PubMed

Gorelikov, Ivan; Martin, Amanda L; Seo, Minseok; Matsuura, Naomi

2011-12-20

There has been recent interest in developing new, targeted, perfluorocarbon (PFC) droplet-based contrast agents for medical imaging (e.g., magnetic resonance imaging, X-ray/computed tomography, and ultrasound imaging). However, due to the large number of potential PFCs and droplet stabilization strategies available, it is challenging to determine in advance the PFC droplet formulation that will result in the optimal in vivo behavior and imaging performance required for clinical success. We propose that the integration of fluorescent quantum dots (QDs) into new PFC droplet agents can help to rapidly screen new PFC-based candidate agents for biological compatibility early in their development. QD labels can allow the interaction of PFC droplets with single cells to be assessed at high sensitivity and resolution using optical methods in vitro, complementing the deeper depth penetration but lower resolution provided by PFC droplet imaging using in vivo medical imaging systems. In this work, we introduce a simple and robust method to miscibilize silica-coated nanoparticles into hydrophobic and lipophobic PFCs through fluorination of the silica surface via a hydrolysis-condensation reaction with 1H,1H,2H,2H-perfluorodecyltriethoxysilane. Using CdSe/ZnS core/shell QDs, we show that nanoscale, QD-labeled PFC droplets can be easily formed, with similar sizes and surface charges as unlabeled PFC droplets. The QD label can be used to determine the PFC droplet uptake into cells in vitro by fluorescence microscopy and flow cytometry, and can be used to validate the fate of PFC droplets in vivo in small animals via fluorescence microscopy of histological tissue sections. This is demonstrated in macrophage and cancer cells, and in rabbits, respectively. This work reveals the potential of using QD labels for rapid, preclinical, optical assessment of different PFC droplet formulations for their future use in patients. © 2011 American Chemical Society

Toward knowledge-enhanced viewing using encyclopedias and model-based segmentation

NASA Astrophysics Data System (ADS)

Kneser, Reinhard; Lehmann, Helko; Geller, Dieter; Qian, Yue-Chen; Weese, Jürgen

2009-02-01

To make accurate decisions based on imaging data, radiologists must associate the viewed imaging data with the corresponding anatomical structures. Furthermore, given a disease hypothesis possible image findings which verify the hypothesis must be considered and where and how they are expressed in the viewed images. If rare anatomical variants, rare pathologies, unfamiliar protocols, or ambiguous findings are present, external knowledge sources such as medical encyclopedias are consulted. These sources are accessed using keywords typically describing anatomical structures, image findings, pathologies. In this paper we present our vision of how a patient's imaging data can be automatically enhanced with anatomical knowledge as well as knowledge about image findings. On one hand, we propose the automatic annotation of the images with labels from a standard anatomical ontology. These labels are used as keywords for a medical encyclopedia such as STATdx to access anatomical descriptions, information about pathologies and image findings. On the other hand we envision encyclopedias to contain links to region- and finding-specific image processing algorithms. Then a finding is evaluated on an image by applying the respective algorithm in the associated anatomical region. Towards realization of our vision, we present our method and results of automatic annotation of anatomical structures in 3D MRI brain images. Thereby we develop a complex surface mesh model incorporating major structures of the brain and a model-based segmentation method. We demonstrate the validity by analyzing the results of several training and segmentation experiments with clinical data focusing particularly on the visual pathway.

The impact and acceptability of Canadian-style cigarette warning labels among U.S. smokers and nonsmokers.

PubMed

Peters, Ellen; Romer, Daniel; Slovic, Paul; Jamieson, Kathleen Hall; Wharfield, Leisha; Mertz, C K; Carpenter, Stephanie M

2007-04-01

Cigarette smoking is a major source of mortality and medical costs in the United States. More graphic and salient warning labels on cigarette packs as used in Canada may help to reduce smoking initiation and increase quit attempts. However, the labels also may lead to defensive reactions among smokers. In an experimental setting, smokers and nonsmokers were exposed to Canadian or U.S. warning labels. Compared with current U.S. labels, Canadian labels produced more negative affective reactions to smoking cues and to the smoker image among both smokers and nonsmokers without signs of defensive reactions from smokers. A majority of both smokers and nonsmokers endorsed the use of Canadian labels in the United States. Canadian-style warnings should be adopted in the United States as part of the country's overall tobacco control strategy.

Machine learning for medical images analysis.

PubMed

Criminisi, A

2016-10-01

This article discusses the application of machine learning for the analysis of medical images. Specifically: (i) We show how a special type of learning models can be thought of as automatically optimized, hierarchically-structured, rule-based algorithms, and (ii) We discuss how the issue of collecting large labelled datasets applies to both conventional algorithms as well as machine learning techniques. The size of the training database is a function of model complexity rather than a characteristic of machine learning methods. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

Lyophilized Kit for the Preparation of the PET Perfusion Agent [68Ga]-MAA

PubMed Central

Amor-Coarasa, Alejandro; Milera, Andrew; Gulec, Seza; McGoron, Anthony J.

2014-01-01

Rapid developments in the field of medical imaging have opened new avenues for the use of positron emitting labeled microparticles. The radioisotope used in our research was 68Ga, which is easy to obtain from a generator and has good nuclear properties for PET imaging. Methods. Commercially available macroaggregated albumin (MAA) microparticles were suspended in sterile saline, centrifuged to remove the free albumin and stannous chloride, relyophilized, and stored for later labeling with 68Ga. Labeling was performed at different temperatures and times. 68Ga purification settings were also tested and optimized. Labeling yield and purity of relyophilized MAA microparticles were compared with those that were not relyophilized. Results. MAA particles kept their original size distribution after relyophilization. Labeling yield was 98% at 75°C when a 68Ga purification system was used, compared to 80% with unpurified 68Ga. Radiochemical purity was over 97% up to 4 hours after the labeling. The relyophilized MAA and labeling method eliminate the need for centrifugation purification of the final product and simplify the labeling process. Animal experiments demonstrated the high in vivo stability of the obtained PET agent with more than 95% of the activity remaining in the lungs after 4 hours. PMID:24800071

Label-free high-throughput imaging flow cytometry

NASA Astrophysics Data System (ADS)

Mahjoubfar, A.; Chen, C.; Niazi, K. R.; Rabizadeh, S.; Jalali, B.

2014-03-01

Flow cytometry is an optical method for studying cells based on their individual physical and chemical characteristics. It is widely used in clinical diagnosis, medical research, and biotechnology for analysis of blood cells and other cells in suspension. Conventional flow cytometers aim a laser beam at a stream of cells and measure the elastic scattering of light at forward and side angles. They also perform single-point measurements of fluorescent emissions from labeled cells. However, many reagents used in cell labeling reduce cellular viability or change the behavior of the target cells through the activation of undesired cellular processes or inhibition of normal cellular activity. Therefore, labeled cells are not completely representative of their unaltered form nor are they fully reliable for downstream studies. To remove the requirement of cell labeling in flow cytometry, while still meeting the classification sensitivity and specificity goals, measurement of additional biophysical parameters is essential. Here, we introduce an interferometric imaging flow cytometer based on the world's fastest continuous-time camera. Our system simultaneously measures cellular size, scattering, and protein concentration as supplementary biophysical parameters for label-free cell classification. It exploits the wide bandwidth of ultrafast laser pulses to perform blur-free quantitative phase and intensity imaging at flow speeds as high as 10 meters per second and achieves nanometer-scale optical path length resolution for precise measurements of cellular protein concentration.

Labeling transplanted mice islet with polyvinylpyrrolidone coated superparamagnetic iron oxide nanoparticles for in vivo detection by magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Huang, Hai; Xie, Qiuping; Kang, Muxing; Zhang, Bo; Zhang, Hui; Chen, Jin; Zhai, Chuanxin; Yang, Deren; Jiang, Biao; Wu, Yulian

2009-09-01

Superparamagnetic iron oxide nanoparticles (SPIO) are emerging as a novel probe for noninvasive cell tracking with magnetic resonance imaging (MRI) and have potential wide usage in medical research. In this study, we have developed a method using high-temperature hydrolysis of chelate metal alkoxide complexes to synthesize polyvinylpyrrolidone coated iron oxide nanoparticles (PVP-SPIO), as a biocompatible magnetic agent that can efficiently label mice islet β-cells. The size, crystal structure and magnetic properties of the as-synthesized nanoparticles have been characterized. The newly synthesized PVP-SPIO with high stability, crystallinity and saturation magnetization can be efficiently internalized into β-cells, without affecting viability and function. The imaging of 100 PVP-SPIO-labeled mice islets in the syngeneic renal subcapsular model of transplantation under a clinical 3.0 T MR imager showed high spatial resolution in vivo. These results indicated the great potential application of the PVP-SPIO as an MRI contrast agent for monitoring transplanted islet grafts in the clinical management of diabetes in the near future.

Automated torso organ segmentation from 3D CT images using structured perceptron and dual decomposition

NASA Astrophysics Data System (ADS)

Nimura, Yukitaka; Hayashi, Yuichiro; Kitasaka, Takayuki; Mori, Kensaku

2015-03-01

This paper presents a method for torso organ segmentation from abdominal CT images using structured perceptron and dual decomposition. A lot of methods have been proposed to enable automated extraction of organ regions from volumetric medical images. However, it is necessary to adjust empirical parameters of them to obtain precise organ regions. This paper proposes an organ segmentation method using structured output learning. Our method utilizes a graphical model and binary features which represent the relationship between voxel intensities and organ labels. Also we optimize the weights of the graphical model by structured perceptron and estimate the best organ label for a given image by dynamic programming and dual decomposition. The experimental result revealed that the proposed method can extract organ regions automatically using structured output learning. The error of organ label estimation was 4.4%. The DICE coefficients of left lung, right lung, heart, liver, spleen, pancreas, left kidney, right kidney, and gallbladder were 0.91, 0.95, 0.77, 0.81, 0.74, 0.08, 0.83, 0.84, and 0.03, respectively.

Alzheimer's Disease Early Diagnosis Using Manifold-Based Semi-Supervised Learning.

PubMed

Khajehnejad, Moein; Saatlou, Forough Habibollahi; Mohammadzade, Hoda

2017-08-20

Alzheimer's disease (AD) is currently ranked as the sixth leading cause of death in the United States and recent estimates indicate that the disorder may rank third, just behind heart disease and cancer, as a cause of death for older people. Clearly, predicting this disease in the early stages and preventing it from progressing is of great importance. The diagnosis of Alzheimer's disease (AD) requires a variety of medical tests, which leads to huge amounts of multivariate heterogeneous data. It can be difficult and exhausting to manually compare, visualize, and analyze this data due to the heterogeneous nature of medical tests; therefore, an efficient approach for accurate prediction of the condition of the brain through the classification of magnetic resonance imaging (MRI) images is greatly beneficial and yet very challenging. In this paper, a novel approach is proposed for the diagnosis of very early stages of AD through an efficient classification of brain MRI images, which uses label propagation in a manifold-based semi-supervised learning framework. We first apply voxel morphometry analysis to extract some of the most critical AD-related features of brain images from the original MRI volumes and also gray matter (GM) segmentation volumes. The features must capture the most discriminative properties that vary between a healthy and Alzheimer-affected brain. Next, we perform a principal component analysis (PCA)-based dimension reduction on the extracted features for faster yet sufficiently accurate analysis. To make the best use of the captured features, we present a hybrid manifold learning framework which embeds the feature vectors in a subspace. Next, using a small set of labeled training data, we apply a label propagation method in the created manifold space to predict the labels of the remaining images and classify them in the two groups of mild Alzheimer's and normal condition (MCI/NC). The accuracy of the classification using the proposed method is 93.86% for the Open Access Series of Imaging Studies (OASIS) database of MRI brain images, providing, compared to the best existing methods, a 3% lower error rate.

Statistical fusion of continuous labels: identification of cardiac landmarks

NASA Astrophysics Data System (ADS)

Xing, Fangxu; Soleimanifard, Sahar; Prince, Jerry L.; Landman, Bennett A.

2011-03-01

Image labeling is an essential task for evaluating and analyzing morphometric features in medical imaging data. Labels can be obtained by either human interaction or automated segmentation algorithms. However, both approaches for labeling suffer from inevitable error due to noise and artifact in the acquired data. The Simultaneous Truth And Performance Level Estimation (STAPLE) algorithm was developed to combine multiple rater decisions and simultaneously estimate unobserved true labels as well as each rater's level of performance (i.e., reliability). A generalization of STAPLE for the case of continuous-valued labels has also been proposed. In this paper, we first show that with the proposed Gaussian distribution assumption, this continuous STAPLE formulation yields equivalent likelihoods for the bias parameter, meaning that the bias parameter-one of the key performance indices-is actually indeterminate. We resolve this ambiguity by augmenting the STAPLE expectation maximization formulation to include a priori probabilities on the performance level parameters, which enables simultaneous, meaningful estimation of both the rater bias and variance performance measures. We evaluate and demonstrate the efficacy of this approach in simulations and also through a human rater experiment involving the identification the intersection points of the right ventricle to the left ventricle in CINE cardiac data.

Statistical Fusion of Continuous Labels: Identification of Cardiac Landmarks.

PubMed

Xing, Fangxu; Soleimanifard, Sahar; Prince, Jerry L; Landman, Bennett A

2011-01-01

Image labeling is an essential task for evaluating and analyzing morphometric features in medical imaging data. Labels can be obtained by either human interaction or automated segmentation algorithms. However, both approaches for labeling suffer from inevitable error due to noise and artifact in the acquired data. The Simultaneous Truth And Performance Level Estimation (STAPLE) algorithm was developed to combine multiple rater decisions and simultaneously estimate unobserved true labels as well as each rater's level of performance (i.e., reliability). A generalization of STAPLE for the case of continuous-valued labels has also been proposed. In this paper, we first show that with the proposed Gaussian distribution assumption, this continuous STAPLE formulation yields equivalent likelihoods for the bias parameter, meaning that the bias parameter-one of the key performance indices-is actually indeterminate. We resolve this ambiguity by augmenting the STAPLE expectation maximization formulation to include a priori probabilities on the performance level parameters, which enables simultaneous, meaningful estimation of both the rater bias and variance performance measures. We evaluate and demonstrate the efficacy of this approach in simulations and also through a human rater experiment involving the identification the intersection points of the right ventricle to the left ventricle in CINE cardiac data.

Physics-based deformable organisms for medical image analysis

NASA Astrophysics Data System (ADS)

Hamarneh, Ghassan; McIntosh, Chris

2005-04-01

Previously, "Deformable organisms" were introduced as a novel paradigm for medical image analysis that uses artificial life modelling concepts. Deformable organisms were designed to complement the classical bottom-up deformable models methodologies (geometrical and physical layers), with top-down intelligent deformation control mechanisms (behavioral and cognitive layers). However, a true physical layer was absent and in order to complete medical image segmentation tasks, deformable organisms relied on pure geometry-based shape deformations guided by sensory data, prior structural knowledge, and expert-generated schedules of behaviors. In this paper we introduce the use of physics-based shape deformations within the deformable organisms framework yielding additional robustness by allowing intuitive real-time user guidance and interaction when necessary. We present the results of applying our physics-based deformable organisms, with an underlying dynamic spring-mass mesh model, to segmenting and labelling the corpus callosum in 2D midsagittal magnetic resonance images.

Deep and Structured Robust Information Theoretic Learning for Image Analysis.

PubMed

Deng, Yue; Bao, Feng; Deng, Xuesong; Wang, Ruiping; Kong, Youyong; Dai, Qionghai

2016-07-07

This paper presents a robust information theoretic (RIT) model to reduce the uncertainties, i.e. missing and noisy labels, in general discriminative data representation tasks. The fundamental pursuit of our model is to simultaneously learn a transformation function and a discriminative classifier that maximize the mutual information of data and their labels in the latent space. In this general paradigm, we respectively discuss three types of the RIT implementations with linear subspace embedding, deep transformation and structured sparse learning. In practice, the RIT and deep RIT are exploited to solve the image categorization task whose performances will be verified on various benchmark datasets. The structured sparse RIT is further applied to a medical image analysis task for brain MRI segmentation that allows group-level feature selections on the brain tissues.

Learning without labeling: domain adaptation for ultrasound transducer localization.

PubMed

Heimann, Tobias; Mountney, Peter; John, Matthias; Ionasec, Razvan

2013-01-01

The fusion of image data from trans-esophageal echography (TEE) and X-ray fluoroscopy is attracting increasing interest in minimally-invasive treatment of structural heart disease. In order to calculate the needed transform between both imaging systems, we employ a discriminative learning based approach to localize the TEE transducer in X-ray images. Instead of time-consuming manual labeling, we generate the required training data automatically from a single volumetric image of the transducer. In order to adapt this system to real X-ray data, we use unlabeled fluoroscopy images to estimate differences in feature space density and correct covariate shift by instance weighting. An evaluation on more than 1900 images reveals that our approach reduces detection failures by 95% compared to cross validation on the test set and improves the localization error from 1.5 to 0.8 mm. Due to the automatic generation of training data, the proposed system is highly flexible and can be adapted to any medical device with minimal efforts.

Constructing Benchmark Databases and Protocols for Medical Image Analysis: Diabetic Retinopathy

PubMed Central

Kauppi, Tomi; Kämäräinen, Joni-Kristian; Kalesnykiene, Valentina; Sorri, Iiris; Uusitalo, Hannu; Kälviäinen, Heikki

2013-01-01

We address the performance evaluation practices for developing medical image analysis methods, in particular, how to establish and share databases of medical images with verified ground truth and solid evaluation protocols. Such databases support the development of better algorithms, execution of profound method comparisons, and, consequently, technology transfer from research laboratories to clinical practice. For this purpose, we propose a framework consisting of reusable methods and tools for the laborious task of constructing a benchmark database. We provide a software tool for medical image annotation helping to collect class label, spatial span, and expert's confidence on lesions and a method to appropriately combine the manual segmentations from multiple experts. The tool and all necessary functionality for method evaluation are provided as public software packages. As a case study, we utilized the framework and tools to establish the DiaRetDB1 V2.1 database for benchmarking diabetic retinopathy detection algorithms. The database contains a set of retinal images, ground truth based on information from multiple experts, and a baseline algorithm for the detection of retinopathy lesions. PMID:23956787

Exploiting the potential of unlabeled endoscopic video data with self-supervised learning.

PubMed

Ross, Tobias; Zimmerer, David; Vemuri, Anant; Isensee, Fabian; Wiesenfarth, Manuel; Bodenstedt, Sebastian; Both, Fabian; Kessler, Philip; Wagner, Martin; Müller, Beat; Kenngott, Hannes; Speidel, Stefanie; Kopp-Schneider, Annette; Maier-Hein, Klaus; Maier-Hein, Lena

2018-06-01

Surgical data science is a new research field that aims to observe all aspects of the patient treatment process in order to provide the right assistance at the right time. Due to the breakthrough successes of deep learning-based solutions for automatic image annotation, the availability of reference annotations for algorithm training is becoming a major bottleneck in the field. The purpose of this paper was to investigate the concept of self-supervised learning to address this issue. Our approach is guided by the hypothesis that unlabeled video data can be used to learn a representation of the target domain that boosts the performance of state-of-the-art machine learning algorithms when used for pre-training. Core of the method is an auxiliary task based on raw endoscopic video data of the target domain that is used to initialize the convolutional neural network (CNN) for the target task. In this paper, we propose the re-colorization of medical images with a conditional generative adversarial network (cGAN)-based architecture as auxiliary task. A variant of the method involves a second pre-training step based on labeled data for the target task from a related domain. We validate both variants using medical instrument segmentation as target task. The proposed approach can be used to radically reduce the manual annotation effort involved in training CNNs. Compared to the baseline approach of generating annotated data from scratch, our method decreases exploratively the number of labeled images by up to 75% without sacrificing performance. Our method also outperforms alternative methods for CNN pre-training, such as pre-training on publicly available non-medical (COCO) or medical data (MICCAI EndoVis2017 challenge) using the target task (in this instance: segmentation). As it makes efficient use of available (non-)public and (un-)labeled data, the approach has the potential to become a valuable tool for CNN (pre-)training.

A coarse-to-fine approach for medical hyperspectral image classification with sparse representation

NASA Astrophysics Data System (ADS)

Chang, Lan; Zhang, Mengmeng; Li, Wei

2017-10-01

A coarse-to-fine approach with sparse representation is proposed for medical hyperspectral image classification in this work. Segmentation technique with different scales is employed to exploit edges of the input image, where coarse super-pixel patches provide global classification information while fine ones further provide detail information. Different from common RGB image, hyperspectral image has multi bands to adjust the cluster center with more high precision. After segmentation, each super pixel is classified by recently-developed sparse representation-based classification (SRC), which assigns label for testing samples in one local patch by means of sparse linear combination of all the training samples. Furthermore, segmentation with multiple scales is employed because single scale is not suitable for complicate distribution of medical hyperspectral imagery. Finally, classification results for different sizes of super pixel are fused by some fusion strategy, offering at least two benefits: (1) the final result is obviously superior to that of segmentation with single scale, and (2) the fusion process significantly simplifies the choice of scales. Experimental results using real medical hyperspectral images demonstrate that the proposed method outperforms the state-of-the-art SRC.

Label-free Chemical Imaging of Fungal Spore Walls by Raman Microscopy and Multivariate Curve Resolution Analysis

PubMed Central

Noothalapati, Hemanth; Sasaki, Takahiro; Kaino, Tomohiro; Kawamukai, Makoto; Ando, Masahiro; Hamaguchi, Hiro-o; Yamamoto, Tatsuyuki

2016-01-01

Fungal cell walls are medically important since they represent a drug target site for antifungal medication. So far there is no method to directly visualize structurally similar cell wall components such as α-glucan, β-glucan and mannan with high specificity, especially in a label-free manner. In this study, we have developed a Raman spectroscopy based molecular imaging method and combined multivariate curve resolution analysis to enable detection and visualization of multiple polysaccharide components simultaneously at the single cell level. Our results show that vegetative cell and ascus walls are made up of both α- and β-glucans while spore wall is exclusively made of α-glucan. Co-localization studies reveal the absence of mannans in ascus wall but are distributed primarily in spores. Such detailed picture is believed to further enhance our understanding of the dynamic spore wall architecture, eventually leading to advancements in drug discovery and development in the near future. PMID:27278218

Medical imaging by fluorescent x-ray CT: its preliminary clinical evaluation

NASA Astrophysics Data System (ADS)

Takeda, Tohoru; Zeniya, Tsutomu; Wu, Jin; Yu, Quanwen; Lwin, Thet T.; Tsuchiya, Yoshinori; Rao, Donepudi V.; Yuasa, Tetsuya; Yashiro, Toru; Dilmanian, F. Avraham; Itai, Yuji; Akatsuka, Takao

2002-01-01

Fluorescent x-ray CT (FXCT) with synchrotron radiation (SR) is being developed to detect the very low concentration of specific elements. The endogenous iodine of the human thyroid and the non-radioactive iodine labeled BMIPP in myocardium were imaged by FXCT. FXCT system consists of a silicon (111) double crystal monochromator, an x-ray slit, a scanning table for object positioning, a fluorescent x-ray detector, and a transmission x-ray detector. Monochromatic x-ray with 37 keV energy was collimated into a pencil beam (from 1 mm to 0.025 mm). FXCT clearly imaged endogenous iodine of thyroid and iodine labeled BMIPP in myocardium, whereas transmission x-ray CT could not demonstrate iodine. The distribution of iodine was heterogeneous within thyroid cancer, and its concentration was lower than that of normal thyroid. Distribution of BMIPP in normal rat myocardium was almost homogeneous; however, reduced uptake was slightly shown in ischemic region. FXCT is a highly sensitive imaging modality to detect very low concentration of specific element and will be applied to reveal endogenous iodine distribution in thyroid and to use tracer study with various kinds of labeled material.

Multi-atlas segmentation for abdominal organs with Gaussian mixture models

NASA Astrophysics Data System (ADS)

Burke, Ryan P.; Xu, Zhoubing; Lee, Christopher P.; Baucom, Rebeccah B.; Poulose, Benjamin K.; Abramson, Richard G.; Landman, Bennett A.

2015-03-01

Abdominal organ segmentation with clinically acquired computed tomography (CT) is drawing increasing interest in the medical imaging community. Gaussian mixture models (GMM) have been extensively used through medical segmentation, most notably in the brain for cerebrospinal fluid / gray matter / white matter differentiation. Because abdominal CT exhibit strong localized intensity characteristics, GMM have recently been incorporated in multi-stage abdominal segmentation algorithms. In the context of variable abdominal anatomy and rich algorithms, it is difficult to assess the marginal contribution of GMM. Herein, we characterize the efficacy of an a posteriori framework that integrates GMM of organ-wise intensity likelihood with spatial priors from multiple target-specific registered labels. In our study, we first manually labeled 100 CT images. Then, we assigned 40 images to use as training data for constructing target-specific spatial priors and intensity likelihoods. The remaining 60 images were evaluated as test targets for segmenting 12 abdominal organs. The overlap between the true and the automatic segmentations was measured by Dice similarity coefficient (DSC). A median improvement of 145% was achieved by integrating the GMM intensity likelihood against the specific spatial prior. The proposed framework opens the opportunities for abdominal organ segmentation by efficiently using both the spatial and appearance information from the atlases, and creates a benchmark for large-scale automatic abdominal segmentation.

Label-free imaging of brain and brain tumor specimens with combined two-photon excited fluorescence and second harmonic generation microscopy

NASA Astrophysics Data System (ADS)

Jiang, Liwei; Wang, Xingfu; Wu, Zanyi; Du, Huiping; Wang, Shu; Li, Lianhuang; Fang, Na; Lin, Peihua; Chen, Jianxin; Kang, Dezhi; Zhuo, Shuangmu

2017-10-01

Label-free imaging techniques are gaining acceptance within the medical imaging field, including brain imaging, because they have the potential to be applied to intraoperative in situ identifications of pathological conditions. In this paper, we describe the use of two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) microscopy in combination for the label-free detection of brain and brain tumor specimens; gliomas. Two independently detecting channels were chosen to subsequently collect TPEF/SHG signals from the specimen to increase TPEF/SHG image contrasts. Our results indicate that the combined TPEF/SHG microscopic techniques can provide similar rat brain structural information and produce a similar resolution like conventional H&E staining in neuropathology; including meninges, cerebral cortex, white-matter structure corpus callosum, choroid plexus, hippocampus, striatum, and cerebellar cortex. It can simultaneously detect infiltrating human brain tumor cells, the extracellular matrix collagen fiber of connective stroma within brain vessels and collagen depostion in tumor microenvironments. The nuclear-to-cytoplasmic ratio and collagen content can be extracted as quantitative indicators for differentiating brain gliomas from healthy brain tissues. With the development of two-photon fiberscopes and microendoscope probes and their clinical applications, the combined TPEF and SHG microcopy may become an important multimodal, nonlinear optical imaging approach for real-time intraoperative histological diagnostics of residual brain tumors. These occur in various brain regions during ongoing surgeries through the method of simultaneously identifying tumor cells, and the change of tumor microenvironments, without the need for the removal biopsies and without the need for tissue labelling or fluorescent markers.

Learning to rank atlases for multiple-atlas segmentation.

PubMed

Sanroma, Gerard; Wu, Guorong; Gao, Yaozong; Shen, Dinggang

2014-10-01

Recently, multiple-atlas segmentation (MAS) has achieved a great success in the medical imaging area. The key assumption is that multiple atlases have greater chances of correctly labeling a target image than a single atlas. However, the problem of atlas selection still remains unexplored. Traditionally, image similarity is used to select a set of atlases. Unfortunately, this heuristic criterion is not necessarily related to the final segmentation performance. To solve this seemingly simple but critical problem, we propose a learning-based atlas selection method to pick up the best atlases that would lead to a more accurate segmentation. Our main idea is to learn the relationship between the pairwise appearance of observed instances (i.e., a pair of atlas and target images) and their final labeling performance (e.g., using the Dice ratio). In this way, we select the best atlases based on their expected labeling accuracy. Our atlas selection method is general enough to be integrated with any existing MAS method. We show the advantages of our atlas selection method in an extensive experimental evaluation in the ADNI, SATA, IXI, and LONI LPBA40 datasets. As shown in the experiments, our method can boost the performance of three widely used MAS methods, outperforming other learning-based and image-similarity-based atlas selection methods.

["Street" medication in Burkina Faso: local names, social relationships, and alleged therapeutic effects].

PubMed

Pale, Augustin; Ladner, Joël

2006-01-01

This qualitative assessment, based on discussions and discourse collected in interviews with members of the general population, addresses the popular view of pharmaceutical drugs in Burkina Faso. The main results demonstrate a strong preference for drugs sold in the street and their largely "off-label" uses. These drugs not only treat defined diseases but also generate street discussions, popular images and social relationships that lead to their consumption, sometimes excessive. Furthermore, the links between the legal and illegal street markets, related in part to the legal status of different drugs, also leads to questions about good and bad, true and false. These distinctions, considered as labels, influence the population's behavior and attitude concerning street medication.

Large-scale Labeled Datasets to Fuel Earth Science Deep Learning Applications

NASA Astrophysics Data System (ADS)

Maskey, M.; Ramachandran, R.; Miller, J.

2017-12-01

Deep learning has revolutionized computer vision and natural language processing with various algorithms scaled using high-performance computing. However, generic large-scale labeled datasets such as the ImageNet are the fuel that drives the impressive accuracy of deep learning results. Large-scale labeled datasets already exist in domains such as medical science, but creating them in the Earth science domain is a challenge. While there are ways to apply deep learning using limited labeled datasets, there is a need in the Earth sciences for creating large-scale labeled datasets for benchmarking and scaling deep learning applications. At the NASA Marshall Space Flight Center, we are using deep learning for a variety of Earth science applications where we have encountered the need for large-scale labeled datasets. We will discuss our approaches for creating such datasets and why these datasets are just as valuable as deep learning algorithms. We will also describe successful usage of these large-scale labeled datasets with our deep learning based applications.

A survey of medical students on the impact of a new digital imaging library in the dissection room.

PubMed

Turmezei, T D; Tam, M D B S; Loughna, S

2009-09-01

Radiology has a recognised role in undergraduate anatomy education. The recent digitalisation of radiology has created new learning opportunities involving techniques such as image labelling, 3D reconstruction, and multiplanar reformatting. An opportunity was identified at the University of Nottingham to create a digital library of normal radiology images as a learner-driven adjunct in anatomy dissection sessions. We describe the process of creating a de novo digital library by sourcing images for presentation at computer workstations. Students' attitudes towards this new resource were assessed using a questionnaire which used a 5 point Likert scale and also offered free text responses. One hundred and forty-one out of 260 students (54%) completed the questionnaire. The most notable findings were: a positive response to the relevance of imaging to the session topics (median score 4), strong agreement that images should be available on the university website (median score 5), and disagreement that enough workstations were available (median score 2). About 24% of respondents suggested independently that images needed more labeling to help with orientation and identification. This first phase of supplying a comprehensive imaging library can be regarded as a success. Increasing availability and incorporating dynamic labeling are well recognized as important design concepts for electronic learning resources and these will be improved in the second phase of delivery as a direct result of student feedback. Hopefully other centers can benefit from this experience and will consider such a venture to be worthwhile.

Advances in PET myocardial perfusion imaging: F-18 labeled tracers.

PubMed

Rischpler, Christoph; Park, Min-Jae; Fung, George S K; Javadi, Mehrbod; Tsui, Benjamin M W; Higuchi, Takahiro

2012-01-01

Coronary artery disease and its related cardiac disorders represent the most common cause of death in the USA and Western world. Despite advancements in treatment and accompanying improvements in outcome with current diagnostic and therapeutic modalities, it is the correct assignment of these diagnostic techniques and treatment options which are crucial. From a diagnostic standpoint, SPECT myocardial perfusion imaging (MPI) using traditional radiotracers like thallium-201 chloride, Tc-99m sestamibi or Tc-99m tetrofosmin is the most utilized imaging technique. However, PET MPI using N-13 ammonia, rubidium-82 chloride or O-15 water is increasing in availability and usage as a result of the growing number of medical centers with new-generation PET/CT systems taking advantage of the superior imaging properties of PET over SPECT. The routine clinical use of PET MPI is still limited, in part because of the short half-life of conventional PET MPI tracers. The disadvantages of these conventional PET tracers include expensive onsite production and inconvenient on-scanner tracer administration making them unsuitable for physical exercise stress imaging. Recently, two F-18 labeled radiotracers with longer radioactive half-lives than conventional PET imaging agents have been introduced. These are flurpiridaz F 18 (formerly known as F-18 BMS747158-02) and F-18 fluorobenzyltriphenylphosphonium. These longer half-life F-18 labeled perfusion tracers can overcome the production and protocol limitations of currently used radiotracers for PET MPI.

Surface chemistry and morphology in single particle optical imaging

NASA Astrophysics Data System (ADS)

Ekiz-Kanik, Fulya; Sevenler, Derin Deniz; Ünlü, Neşe Lortlar; Chiari, Marcella; Ünlü, M. Selim

2017-05-01

Biological nanoparticles such as viruses and exosomes are important biomarkers for a range of medical conditions, from infectious diseases to cancer. Biological sensors that detect whole viruses and exosomes with high specificity, yet without additional labeling, are promising because they reduce the complexity of sample preparation and may improve measurement quality by retaining information about nanoscale physical structure of the bio-nanoparticle (BNP). Towards this end, a variety of BNP biosensor technologies have been developed, several of which are capable of enumerating the precise number of detected viruses or exosomes and analyzing physical properties of each individual particle. Optical imaging techniques are promising candidates among broad range of label-free nanoparticle detectors. These imaging BNP sensors detect the binding of single nanoparticles on a flat surface functionalized with a specific capture molecule or an array of multiplexed capture probes. The functionalization step confers all molecular specificity for the sensor's target but can introduce an unforeseen problem; a rough and inhomogeneous surface coating can be a source of noise, as these sensors detect small local changes in optical refractive index. In this paper, we review several optical technologies for label-free BNP detectors with a focus on imaging systems. We compare the surface-imaging methods including dark-field, surface plasmon resonance imaging and interference reflectance imaging. We discuss the importance of ensuring consistently uniform and smooth surface coatings of capture molecules for these types of biosensors and finally summarize several methods that have been developed towards addressing this challenge.

Synthesis and biological evaluation of novel radioiodinated imidazopyridine derivatives for amyloid-β imaging in Alzheimer's disease.

PubMed

Chen, Chun-Jen; Bando, Kazunori; Ashino, Hiroki; Taguchi, Kazumi; Shiraishi, Hideaki; Fujimoto, Osuke; Kitamura, Chiemi; Matsushima, Satoshi; Fujinaga, Masayuki; Zhang, Ming-Rong; Kasahara, Hiroyuki; Minamizawa, Takao; Jiang, Cheng; Ono, Maiko; Higuchi, Makoto; Suhara, Tetsuya; Yamada, Kazutaka; Ji, Bin

2014-08-01

Non-invasive detection for amyloid-β peptide (Aβ) deposition has important significance for the early diagnosis and medical intervention for Alzheimer's disease (AD). In this study, we developed a series of imidazopyridine derivatives as potential imaging agents for single-photon emission computed tomography (SPECT). Two of them, compounds DRK092 and DRM106, showed higher affinity for synthetic human Aβ 1-40 fibrils than did the well-known amyloid-imaging agent IMPY. A metabolite analysis revealed brain-permeable radioactive metabolites of (125)I-labeled DRK092 and IMPY; no radioactive metabolites from (125)I-labeled DRM106 ([(125)I]DRM106) were detected. In addition, in vitro autoradiography clearly demonstrated specific binding of [(125)I]DRM106 in the hippocampal region of AD enriched with Aβ plaques. Thus, our results strongly suggested that compound DRM106 can be used as an imaging agent for SPECT to detect Aβ deposition in AD brain. Copyright © 2014 Elsevier Ltd. All rights reserved.

21 CFR 801.15 - Medical devices; prominence of required label statements.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Medical devices; prominence of required label statements. 801.15 Section 801.15 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES LABELING General Labeling Provisions § 801.15 Medical devices; prominence of required label statements. (a...

Intracellular in situ labeling of TiO2 nanoparticles for fluorescence microscopy detection

PubMed Central

Brown, Koshonna; Thurn, Ted; Xin, Lun; Liu, William; Bazak, Remon; Chen, Si; Lai, Barry; Vogt, Stefan; Jacobsen, Chris; Paunesku, Tatjana; Woloschak, Gayle E.

2018-01-01

Titanium dioxide (TiO2) nanoparticles are produced for many different purposes, including development of therapeutic and diagnostic nanoparticles for cancer detection and treatment, drug delivery, induction of DNA double-strand breaks, and imaging of specific cells and subcellular structures. Currently, the use of optical microscopy, an imaging technique most accessible to biology and medical pathology, to detect TiO2 nanoparticles in cells and tissues ex vivo is limited with low detection limits, while more sensitive imaging methods (transmission electron microscopy, X-ray fluorescence microscopy, etc.) have low throughput and technical and operational complications. Herein, we describe two in situ post-treatment labeling approaches to stain TiO2 nanoparticles taken up by the cells. The first approach utilizes fluorescent biotin and fluorescent streptavidin to label the nanoparticles before and after cellular uptake; the second approach is based on the copper-catalyzed azide-alkyne cycloaddition, the so-called Click chemistry, for labeling and detection of azide-conjugated TiO2 nanoparticles with alkyne-conjugated fluorescent dyes such as Alexa Fluor 488. To confirm that optical fluorescence signals of these nanoparticles match the distribution of the Ti element, we used synchrotron X-ray fluorescence microscopy (XFM) at the Advanced Photon Source at Argonne National Laboratory. Titanium-specific XFM showed excellent overlap with the location of optical fluorescence detected by confocal microscopy. Therefore, future experiments with TiO2 nanoparticles may safely rely on confocal microscopy after in situ nanoparticle labeling using approaches described here. PMID:29541425

Intracellular in situ labeling of TiO2 nanoparticles for fluorescence microscopy detection.

PubMed

Brown, Koshonna; Thurn, Ted; Xin, Lun; Liu, William; Bazak, Remon; Chen, Si; Lai, Barry; Vogt, Stefan; Jacobsen, Chris; Paunesku, Tatjana; Woloschak, Gayle E

2018-01-01

Titanium dioxide (TiO 2 ) nanoparticles are produced for many different purposes, including development of therapeutic and diagnostic nanoparticles for cancer detection and treatment, drug delivery, induction of DNA double-strand breaks, and imaging of specific cells and subcellular structures. Currently, the use of optical microscopy, an imaging technique most accessible to biology and medical pathology, to detect TiO 2 nanoparticles in cells and tissues ex vivo is limited with low detection limits, while more sensitive imaging methods (transmission electron microscopy, X-ray fluorescence microscopy, etc.) have low throughput and technical and operational complications. Herein, we describe two in situ post-treatment labeling approaches to stain TiO 2 nanoparticles taken up by the cells. The first approach utilizes fluorescent biotin and fluorescent streptavidin to label the nanoparticles before and after cellular uptake; the second approach is based on the copper-catalyzed azide-alkyne cycloaddition, the so-called Click chemistry, for labeling and detection of azide-conjugated TiO 2 nanoparticles with alkyne-conjugated fluorescent dyes such as Alexa Fluor 488. To confirm that optical fluorescence signals of these nanoparticles match the distribution of the Ti element, we used synchrotron X-ray fluorescence microscopy (XFM) at the Advanced Photon Source at Argonne National Laboratory. Titanium-specific XFM showed excellent overlap with the location of optical fluorescence detected by confocal microscopy. Therefore, future experiments with TiO 2 nanoparticles may safely rely on confocal microscopy after in situ nanoparticle labeling using approaches described here.

Reading about over-the-counter medications.

PubMed

Nabors, Laura A; Lehmkuhl, Heather D; Parkins, Irina S; Drury, Anna M

2004-01-01

Many adolescents and young adults purchase and use over-the-counter (OTC) medications, and some may take these medications without reading about how to use them. Most do read package inserts and labels to learn about the medication, but studies examining what influences label reading for youth are needed. This study assessed factors related to label reading for young people, including demographic variables (gender, health status) and the types of information they were seeking about the medication. Eight hundred and seventy-six high school and college students participated, and most reported reading labels or package inserts to learn about medications. Participants experiencing pain were more likely to read labels, except for those experiencing headaches who reported being less likely to read labels. When reading labels, participants were interested in information about side effects, ingredients, dosage instructions, and symptoms treated by the medication. Future research should examine whether youth take medications as directed and what factors make labels and inserts easier to read and understand.

Update on radionuclide imaging in hepatobiliary disease. [/sup 99m/Tc-labelled acetanilide iminodracetic acid analogues

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

Rosenthall, L.

1981-05-01

The recent introduction of technetium Tc 99m-labeled acetanilide iminodiacetic acid (/sup 99m/Tc-IDA) analogues has facilitated the clincal study of the bile flow pathways. A variety of /sup 99m/Tc-IDA derivaties are under investigation. Basically all are metabolized by the hepatocyte and immediately thereafter excreted unconjugated into the biliary tract. Of the various derivatives tested, e.g., dimethyl (lidofenin), diethyl, paraisopropyl (iprofenin), parabutyl (butilfenin), and diisopropyl (disofenin), the last named is the best universal agent at this time. By serial liver imaging the patency of the cystic duct and the integrity of altered cholangiointestinal anatomy can be assessed, leakage of bile and gastricmore » reflux can be disclosed, and medical and surgical jaundice can be distinguished.« less

Multi-atlas label fusion using hybrid of discriminative and generative classifiers for segmentation of cardiac MR images.

PubMed

Sedai, Suman; Garnavi, Rahil; Roy, Pallab; Xi Liang

2015-08-01

Multi-atlas segmentation first registers each atlas image to the target image and transfers the label of atlas image to the coordinate system of the target image. The transferred labels are then combined, using a label fusion algorithm. In this paper, we propose a novel label fusion method which aggregates discriminative learning and generative modeling for segmentation of cardiac MR images. First, a probabilistic Random Forest classifier is trained as a discriminative model to obtain the prior probability of a label at the given voxel of the target image. Then, a probability distribution of image patches is modeled using Gaussian Mixture Model for each label, providing the likelihood of the voxel belonging to the label. The final label posterior is obtained by combining the classification score and the likelihood score under Bayesian rule. Comparative study performed on MICCAI 2013 SATA Segmentation Challenge demonstrates that our proposed hybrid label fusion algorithm is accurate than other five state-of-the-art label fusion methods. The proposed method obtains dice similarity coefficient of 0.94 and 0.92 in segmenting epicardium and endocardium respectively. Moreover, our label fusion method achieves more accurate segmentation results compared to four other label fusion methods.

Novel approach for image skeleton and distance transformation parallel algorithms

NASA Astrophysics Data System (ADS)

Qing, Kent P.; Means, Robert W.

1994-05-01

Image Understanding is more important in medical imaging than ever, particularly where real-time automatic inspection, screening and classification systems are installed. Skeleton and distance transformations are among the common operations that extract useful information from binary images and aid in Image Understanding. The distance transformation describes the objects in an image by labeling every pixel in each object with the distance to its nearest boundary. The skeleton algorithm starts from the distance transformation and finds the set of pixels that have a locally maximum label. The distance algorithm has to scan the entire image several times depending on the object width. For each pixel, the algorithm must access the neighboring pixels and find the maximum distance from the nearest boundary. It is a computational and memory access intensive procedure. In this paper, we propose a novel parallel approach to the distance transform and skeleton algorithms using the latest VLSI high- speed convolutional chips such as HNC's ViP. The algorithm speed is dependent on the object's width and takes (k + [(k-1)/3]) * 7 milliseconds for a 512 X 512 image with k being the maximum distance of the largest object. All objects in the image will be skeletonized at the same time in parallel.

The Cerefy Neuroradiology Atlas: a Talairach-Tournoux atlas-based tool for analysis of neuroimages available over the internet.

PubMed

Nowinski, Wieslaw L; Belov, Dmitry

2003-09-01

The article introduces an atlas-assisted method and a tool called the Cerefy Neuroradiology Atlas (CNA), available over the Internet for neuroradiology and human brain mapping. The CNA contains an enhanced, extended, and fully segmented and labeled electronic version of the Talairach-Tournoux brain atlas, including parcelated gyri and Brodmann's areas. To our best knowledge, this is the first online, publicly available application with the Talairach-Tournoux atlas. The process of atlas-assisted neuroimage analysis is done in five steps: image data loading, Talairach landmark setting, atlas normalization, image data exploration and analysis, and result saving. Neuroimage analysis is supported by a near-real-time, atlas-to-data warping based on the Talairach transformation. The CNA runs on multiple platforms; is able to process simultaneously multiple anatomical and functional data sets; and provides functions for a rapid atlas-to-data registration, interactive structure labeling and annotating, and mensuration. It is also empowered with several unique features, including interactive atlas warping facilitating fine tuning of atlas-to-data fit, navigation on the triplanar formed by the image data and the atlas, multiple-images-in-one display with interactive atlas-anatomy-function blending, multiple label display, and saving of labeled and annotated image data. The CNA is useful for fast atlas-assisted analysis of neuroimage data sets. It increases accuracy and reduces time in localization analysis of activation regions; facilitates to communicate the information on the interpreted scans from the neuroradiologist to other clinicians and medical students; increases the neuroradiologist's confidence in terms of anatomy and spatial relationships; and serves as a user-friendly, public domain tool for neuroeducation. At present, more than 700 users from five continents have subscribed to the CNA.

Intracellular in situ labeling of TiO 2 nanoparticles for fluorescence microscopy detection

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

Brown, Koshonna; Thurn, Ted; Xin, Lun

Titanium dioxide (TiO 2) nanoparticles are produced for many different purposes, including development of therapeutic and diagnostic nanoparticles for cancer detection and treatment, drug delivery, induction of DNA double-strand breaks, and imaging of specific cells and subcellular structures. Currently, the use of optical microscopy, an imaging technique most accessible to biology and medical pathology, to detect TiO 2 nanoparticles in cells and tissues ex vivo is limited with low detection limits, while more sensitive imaging methods (transmission electron microscopy, X-ray fluorescence microscopy, etc.) have low throughput and technical and operational complications. In this paper, we describe two in situ posttreatmentmore » labeling approaches to stain TiO 2 nanoparticles taken up by the cells. The first approach utilizes fluorescent biotin and fluorescent streptavidin to label the nanoparticles before and after cellular uptake; the second approach is based on the copper-catalyzed azide-alkyne cycloaddition, the so-called Click chemistry, for labeling and detection of azide-conjugated TiO 2 nanoparticles with alkyneconjugated fluorescent dyes such as Alexa Fluor 488. To confirm that optical fluorescence signals of these nanoparticles match the distribution of the Ti element, we used synchrotron X-ray fluorescence microscopy (XFM) at the Advanced Photon Source at Argonne National Laboratory. Titanium-specific XFM showed excellent overlap with the location of optical fluorescence detected by confocal microscopy. Finally and therefore, future experiments with TiO 2 nanoparticles may safely rely on confocal microscopy after in situ nanoparticle labeling using approaches described here.« less

Intracellular in situ labeling of TiO 2 nanoparticles for fluorescence microscopy detection

DOE PAGES

Brown, Koshonna; Thurn, Ted; Xin, Lun; ...

2017-07-19

Titanium dioxide (TiO 2) nanoparticles are produced for many different purposes, including development of therapeutic and diagnostic nanoparticles for cancer detection and treatment, drug delivery, induction of DNA double-strand breaks, and imaging of specific cells and subcellular structures. Currently, the use of optical microscopy, an imaging technique most accessible to biology and medical pathology, to detect TiO 2 nanoparticles in cells and tissues ex vivo is limited with low detection limits, while more sensitive imaging methods (transmission electron microscopy, X-ray fluorescence microscopy, etc.) have low throughput and technical and operational complications. In this paper, we describe two in situ posttreatmentmore » labeling approaches to stain TiO 2 nanoparticles taken up by the cells. The first approach utilizes fluorescent biotin and fluorescent streptavidin to label the nanoparticles before and after cellular uptake; the second approach is based on the copper-catalyzed azide-alkyne cycloaddition, the so-called Click chemistry, for labeling and detection of azide-conjugated TiO 2 nanoparticles with alkyneconjugated fluorescent dyes such as Alexa Fluor 488. To confirm that optical fluorescence signals of these nanoparticles match the distribution of the Ti element, we used synchrotron X-ray fluorescence microscopy (XFM) at the Advanced Photon Source at Argonne National Laboratory. Titanium-specific XFM showed excellent overlap with the location of optical fluorescence detected by confocal microscopy. Finally and therefore, future experiments with TiO 2 nanoparticles may safely rely on confocal microscopy after in situ nanoparticle labeling using approaches described here.« less

Rationale and design of a randomized trial to evaluate an evidence-based prescription drug label on actual medication use.

PubMed

Shrank, William H; Parker, Ruth; Davis, Terry; Pandit, Anjali U; Knox, Joann P; Moraras, Pear; Rademaker, Alfred; Wolf, Michael S

2010-11-01

Medication errors are an important public health concern, and poor understanding of medication labels are a root cause. Research shows that labels are variable, of poor quality, and not patient-centered. No real-world trials have evaluated whether improved medication labels can affect appropriate medication use, adherence or health outcomes. We developed an evidence-based prescription label that addresses both content and format. The enhanced label includes a universal medication schedule (UMS) that standardizes the directions for use incorporating 1) standard time periods for administration (morning, noon, evening, and bedtime), 2) numeric vs. alpha characters, 3) 'carriage returns' to separate daily dose and 4) a graphic aid to visually depict dose and frequency. We will evaluate the effect of providing this label to randomly sampled patients who receive their care from free clinics, mobile vans and federally qualified health centers (FQHCs) in Northern Virginia. We will recruit patients with diabetes or hypertension; these patients will be randomly assigned to receive all of their medications with improved labels or to receive prescriptions with standard labels. The primary outcome will be the patient's ability to correctly demonstrate dosing instructions. Other outcomes include adherence, error rates and health outcomes. To our knowledge, this trial is the first to evaluate the effect of prescription label improvement on understanding, medication use and outcomes in a clinical setting. If successful, these findings could be implemented broadly to promote safe and appropriate medication use and to support evidence-based standards in the development of labels. Copyright © 2010 Elsevier Inc. All rights reserved.

Graphic Warning Labels Elicit Affective and Thoughtful Responses from Smokers: Results of a Randomized Clinical Trial.

PubMed

Evans, Abigail T; Peters, Ellen; Strasser, Andrew A; Emery, Lydia F; Sheerin, Kaitlin M; Romer, Daniel

2015-01-01

Observational research suggests that placing graphic images on cigarette warning labels can reduce smoking rates, but field studies lack experimental control. Our primary objective was to determine the psychological processes set in motion by naturalistic exposure to graphic vs. text-only warnings in a randomized clinical trial involving exposure to modified cigarette packs over a 4-week period. Theories of graphic-warning impact were tested by examining affect toward smoking, credibility of warning information, risk perceptions, quit intentions, warning label memory, and smoking risk knowledge. Adults who smoked between 5 and 40 cigarettes daily (N = 293; mean age = 33.7), did not have a contra-indicated medical condition, and did not intend to quit were recruited from Philadelphia, PA and Columbus, OH. Smokers were randomly assigned to receive their own brand of cigarettes for four weeks in one of three warning conditions: text only, graphic images plus text, or graphic images with elaborated text. Data from 244 participants who completed the trial were analyzed in structural-equation models. The presence of graphic images (compared to text-only) caused more negative affect toward smoking, a process that indirectly influenced risk perceptions and quit intentions (e.g., image->negative affect->risk perception->quit intention). Negative affect from graphic images also enhanced warning credibility including through increased scrutiny of the warnings, a process that also indirectly affected risk perceptions and quit intentions (e.g., image->negative affect->risk scrutiny->warning credibility->risk perception->quit intention). Unexpectedly, elaborated text reduced warning credibility. Finally, graphic warnings increased warning-information recall and indirectly increased smoking-risk knowledge at the end of the trial and one month later. In the first naturalistic clinical trial conducted, graphic warning labels are more effective than text-only warnings in encouraging smokers to consider quitting and in educating them about smoking's risks. Negative affective reactions to smoking, thinking about risks, and perceptions of credibility are mediators of their impact. Clinicaltrials.gov NCT01782053.

Predesigned labels to prevent medication errors in hospitalized patients: a quasi-experimental design study.

PubMed

Morales-González, María Fernanda; Galiano Gálvez, María Alejandra

2017-09-08

Our institution implemented the use of pre-designed labeling of intravenous drugs and fluids, administration routes and infusion pumps of to prevent medication errors. To evaluate the effectiveness of predesigned labeling in reducing medication errors in the preparation and administration stages of prescribed medication in patients hospitalized with invasive lines, and to characterize medication errors. This is a pre/post intervention study. Pre-intervention group: invasively administered dose from July 1st to December 31st, 2014, using traditional labeling (adhesive paper handwritten note). Post-intervention group: dose administered from January 1st to June 30th, 2015, using predesigned labeling (labeling with preset data-adhesive labels, color- grouped by drugs, labels with colors for invasive lines). Outcome: medication errors in hospitalized patients, as measured with notification form and record electronics. Tabulation/analysis Stata-10, with descriptive statistics, hypotheses testing, estimating risk with 95% confidence. In the pre-intervention group, 5,819 doses of drugs were administered invasively in 634 patients. Error rate of 1.4 x 1,000 administrations. The post-intervention group of 1088 doses comprised 8,585 patients with similar routes of administration. The error rate was 0.3 x 1,000 (p = 0.034). Patients receiving medication through an invasive route who did not use predesigned labeling had 4.6 times more risk of medication error than those who had used predesigned labels (95% CI: 1.25 to 25.4). The adult critically ill patient unit had the highest proportion of medication errors. The most frequent error was wrong dose administration. 41.2% produced harm to the patient. The use of predesigned labeling in invasive lines reduces errors in medication in the last two phases: preparation and administration.

Development and utilization of a web-based application as a robust radiology teaching tool (radstax) for medical student anatomy teaching.

PubMed

Colucci, Philip G; Kostandy, Petro; Shrauner, William R; Arleo, Elizabeth; Fuortes, Michele; Griffin, Andrew S; Huang, Yun-Han; Juluru, Krishna; Tsiouris, Apostolos John

2015-02-01

Rationale and Objectives: The primary role of radiology in the preclinical setting is the use of imaging to improve students' understanding of anatomy. Many currently available Web-based anatomy programs include either suboptimal or overwhelming levels of detail for medical students.Our objective was to develop a user-friendly software program that anatomy instructors can completely tailor to match the desired level of detail for their curriculum, meets the unique needs of the first- and the second-year medical students, and is compatible with most Internet browsers and tablets.Materials and Methods: RadStax is a Web-based application developed using free, open-source, ubiquitous software. RadStax was first introduced as an interactive resource for independent study and later incorporated into lectures. First- and second-year medical students were surveyed for quantitative feedback regarding their experience.Results: RadStax was successfully introduced into our medical school curriculum. It allows the creation of learning modules with labeled multiplanar (MPR) image sets, basic anatomic information, and a self-assessment feature. The program received overwhelmingly positive feedback from students. Of 115 students surveyed, 87.0% found it highly effective as a study tool and 85.2% reported high user satisfaction with the program.Conclusions: RadStax is a novel application for instructors wishing to create an atlas of labeled MPR radiologic studies tailored to meet the specific needs their curriculum. Simple and focused, it provides an interactive experience for students similar to the practice of radiologists.This program is a robust anatomy teaching tool that effectively aids in educating the preclinical medical student.

Development and Utilization of a Web-Based Application as a Robust Radiology Teaching Tool (RadStax) for Medical Student Anatomy Teaching

PubMed Central

Colucci, Philip G.; Kostandy, Petro; Shrauner, William R.; Arleo, Elizabeth; Fuortes, Michele; Griffin, Andrew S.; Huang, Yun-Han; Juluru, Krishna; Tsiouris, Apostolos John

2016-01-01

Rationale and Objectives The primary role of radiology in the preclinical setting is the use of imaging to improve students’ understanding of anatomy. Many currently available Web-based anatomy programs include either suboptimal or overwhelming levels of detail for medical students. Our objective was to develop a user-friendly software program that anatomy instructors can completely tailor to match the desired level of detail for their curriculum, meets the unique needs of the first- and the second-year medical students, and is compatible with most Internet browsers and tablets. Materials and Methods RadStax is a Web-based application developed using free, open-source, ubiquitous software. RadStax was first introduced as an interactive resource for independent study and later incorporated into lectures. First- and second-year medical students were surveyed for quantitative feedback regarding their experience. Results RadStax was successfully introduced into our medical school curriculum. It allows the creation of learning modules with labeled multiplanar (MPR) image sets, basic anatomic information, and a self-assessment feature. The program received overwhelmingly positive feedback from students. Of 115 students surveyed, 87.0% found it highly effective as a study tool and 85.2% reported high user satisfaction with the program. Conclusions RadStax is a novel application for instructors wishing to create an atlas of labeled MPR radiologic studies tailored to meet the specific needs their curriculum. Simple and focused, it provides an interactive experience for students similar to the practice of radiologists. This program is a robust anatomy teaching tool that effectively aids in educating the preclinical medical student. PMID:25964956

FITC labeled silica nanoparticles as efficient cell tags: uptake and photostability study in endothelial cells.

PubMed

Veeranarayanan, Srivani; Poulose, Aby Cheruvathoor; Mohamed, Sheikh; Aravind, Athulya; Nagaoka, Yutaka; Yoshida, Yasuhiko; Maekawa, Toru; Kumar, D Sakthi

2012-03-01

The use of fluorescent nanomaterials has gained great importance in the field of medical imaging. Many traditional imaging technologies have been reported utilizing dyes in the past. These methods face drawbacks due to non-specific accumulation and photobleaching of dyes. We studied the uptake and internalization of two different sized (30 nm and 100 nm) FITC labeled silica nanoparticles in Human umbilical vein endothelial cell line. These nanomaterials show high biocompatability and are highly photostable inside live cells for increased period of time in comparison to the dye alone. To our knowledge, we report for the first time the use of 30 nm fluorescent silica nanoparticles as efficient endothelial tags along with the well studied 100 nm particles. We also have emphasized the good photostability of these materials in live cells.

Aptamer-Mediated Up-conversion Core/MOF Shell Nanocomposites for Targeted Drug Delivery and Cell Imaging

PubMed Central

Deng, Kerong; Hou, Zhiyao; Li, Xuejiao; Li, Chunxia; Zhang, Yuanxin; Deng, Xiaoran; Cheng, Ziyong; Lin, Jun

2015-01-01

Multifunctional nanocarriers for targeted bioimaging and drug delivery have attracted much attention in early diagnosis and therapy of cancer. In this work, we develop a novel aptamer-guided nanocarrier based on the mesoporous metal-organic framework (MOF) shell and up-conversion luminescent NaYF4:Yb3+/Er3+ nanoparticles (UCNPs) core for the first time to achieve these goals. These UCNPs, chosen as optical labels in biological assays and medical imaging, could emit strong green emission under 980 nm laser. The MOF structure based on iron (III) carboxylate materials [MIL-100 (Fe)] possesses high porosity and non-toxicity, which is of great value as nanocarriers for drug storage/delivery. As a unique nanoplatform, the hybrid inorganic-organic drug delivery vehicles show great promising for simultaneous targeted labeling and therapy of cancer cells. PMID:25597762

Segmentation of Vasculature from Fluorescently Labeled Endothelial Cells in Multi-Photon Microscopy Images.

PubMed

Bates, Russell; Irving, Benjamin; Markelc, Bostjan; Kaeppler, Jakob; Brown, Graham; Muschel, Ruth J; Brady, Sir Michael; Grau, Vicente; Schnabel, Julia A

2017-08-09

Vasculature is known to be of key biological significance, especially in the study of tumors. As such, considerable effort has been focused on the automated segmentation of vasculature in medical and pre-clinical images. The majority of vascular segmentation methods focus on bloodpool labeling methods, however, particularly in the study of tumors it is of particular interest to be able to visualize both perfused and non-perfused vasculature. Imaging vasculature by highlighting the endothelium provides a way to separate the morphology of vasculature from the potentially confounding factor of perfusion. Here we present a method for the segmentation of tumor vasculature in 3D fluorescence microscopy images using signals from the endothelial and surrounding cells. We show that our method can provide complete and semantically meaningful segmentations of complex vasculature using a supervoxel-Markov Random Field approach. We show that in terms of extracting meaningful segmentations of the vasculature, our method out-performs both a state-ofthe- art method, specific to these data, as well as more classical vasculature segmentation methods.

Label-free optical imaging technologies for rapid translation and use during intraoperative surgical and tumor margin assessment

NASA Astrophysics Data System (ADS)

Boppart, Stephen A.; Brown, J. Quincy; Farah, Camile S.; Kho, Esther; Marcu, Laura; Saunders, Christobel M.; Sterenborg, Henricus J. C. M.

2018-02-01

The biannual International Conference on Biophotonics was recently held on April 30 to May 1, 2017, in Fremantle, Western Australia. This continuing conference series brought together key opinion leaders in biophotonics to present their latest results and, importantly, to participate in discussions on the future of the field and what opportunities exist when we collectively work together for using biophotonics for biological discovery and medical applications. One session in this conference, entitled "Tumor Margin Identification: Critiquing Technologies," challenged invited speakers and attendees to review and critique representative label-free optical imaging technologies and their application for intraoperative assessment and guidance in surgical oncology. We are pleased to share a summary in this outlook paper, with the intent to motivate more research inquiry and investigations, to challenge these and other optical imaging modalities to evaluate and improve performance, to spur translation and adoption, and ultimately, to improve the care and outcomes of patients.

Quantum dot nanoparticle conjugation, characterization, and applications in neuroscience

NASA Astrophysics Data System (ADS)

Pathak, Smita

Quantum dot are semiconducting nanoparticles that have been used for decades in a variety of applications such as solar cells, LEDs and medical imaging. Their use in the last area, however, has been extremely limited despite their potential as revolutionary new biological labeling tools. Quantum dots are much brighter and more stable than conventional fluorophores, making them optimal for high resolution imaging and long term studies. Prior work in this area involves synthesizing and chemically conjugating quantum dots to molecules of interest in-house. However this method is both time consuming and prone to human error. Additionally, non-specific binding and nanoparticle aggregation currently prevent researchers from utilizing this system to its fullest capacity. Another critical issue that has not been addressed is determining the number of ligands bound to nanoparticles, which is crucial for proper interpretation of results. In this work, methods to label fixed cells using two types of chemically modified quantum dots are studied. Reproducible non-specific artifact labeling is consistently demonstrated if antibody-quantum dot conditions are less than optimal. In order to explain this, antibodies bound to quantum dots were characterized and quantified. While other groups have qualitatively characterized antibody functionalized quantum dots using TEM, AFM, UV spectroscopy and gel electrophoresis, and in some cases have reported calculated estimates of the putative number of total antibodies bound to quantum dots, no quantitative experimental results had been reported prior to this work. The chemical functionalization and characterization of quantum dot nanocrystals achieved in this work elucidates binding mechanisms of ligands to nanoparticles and allows researchers to not only translate our tools to studies in their own areas of interest but also derive quantitative results from these studies. This research brings ease of use and increased reliability to nanoparticles in medical imaging.

Automated grading of lumbar disc degeneration via supervised distance metric learning

NASA Astrophysics Data System (ADS)

He, Xiaoxu; Landis, Mark; Leung, Stephanie; Warrington, James; Shmuilovich, Olga; Li, Shuo

2017-03-01

Lumbar disc degeneration (LDD) is a commonly age-associated condition related to low back pain, while its consequences are responsible for over 90% of spine surgical procedures. In clinical practice, grading of LDD by inspecting MRI is a necessary step to make a suitable treatment plan. This step purely relies on physicians manual inspection so that it brings the unbearable tediousness and inefficiency. An automated method for grading of LDD is highly desirable. However, the technical implementation faces a big challenge from class ambiguity, which is typical in medical image classification problems with a large number of classes. This typical challenge is derived from the complexity and diversity of medical images, which lead to a serious class overlapping and brings a great challenge in discriminating different classes. To solve this problem, we proposed an automated grading approach, which is based on supervised distance metric learning to classify the input discs into four class labels (0: normal, 1: slight, 2: marked, 3: severe). By learning distance metrics from labeled instances, an optimal distance metric is modeled and with two attractive advantages: (1) keeps images from the same classes close, and (2) keeps images from different classes far apart. The experiments, performed in 93 subjects, demonstrated the superiority of our method with accuracy 0.9226, sensitivity 0.9655, specificity 0.9083, F-score 0.8615. With our approach, physicians will be free from the tediousness and patients will be provided an effective treatment.

An investigative model evaluating how consumers process pictorial information on nonprescription medication labels.

PubMed

Sansgiry, S S; Cady, P S

1997-01-01

Currently, marketed over-the-counter (OTC) medication labels were simulated and tested in a controlled environment to understand consumer evaluation of OTC label information. Two factors, consumers' age (younger and older adults) and label designs (picture-only, verbal-only, congruent picture-verbal, and noncongruent picture-verbal) were controlled and tested to evaluate consumer information processing. The effects exerted by the independent variables, namely, comprehension of label information (understanding) and product evaluations (satisfaction, certainty, and perceived confusion) were evaluated on the dependent variable purchase intention. Intention measured as purchase recommendation was significantly related to product evaluations and affected by the factor label design. Participants' level of perceived confusion was more important than actual understanding of information on OTC medication labels. A Label Evaluation Process Model was developed which could be used for future testing of OTC medication labels.

Single myelin fiber imaging in living rodents without labeling by deep optical coherence microscopy.

PubMed

Ben Arous, Juliette; Binding, Jonas; Léger, Jean-François; Casado, Mariano; Topilko, Piotr; Gigan, Sylvain; Boccara, A Claude; Bourdieu, Laurent

2011-11-01

Myelin sheath disruption is responsible for multiple neuropathies in the central and peripheral nervous system. Myelin imaging has thus become an important diagnosis tool. However, in vivo imaging has been limited to either low-resolution techniques unable to resolve individual fibers or to low-penetration imaging of single fibers, which cannot provide quantitative information about large volumes of tissue, as required for diagnostic purposes. Here, we perform myelin imaging without labeling and at micron-scale resolution with >300-μm penetration depth on living rodents. This was achieved with a prototype [termed deep optical coherence microscopy (deep-OCM)] of a high-numerical aperture infrared full-field optical coherence microscope, which includes aberration correction for the compensation of refractive index mismatch and high-frame-rate interferometric measurements. We were able to measure the density of individual myelinated fibers in the rat cortex over a large volume of gray matter. In the peripheral nervous system, deep-OCM allows, after minor surgery, in situ imaging of single myelinated fibers over a large fraction of the sciatic nerve. This allows quantitative comparison of normal and Krox20 mutant mice, in which myelination in the peripheral nervous system is impaired. This opens promising perspectives for myelin chronic imaging in demyelinating diseases and for minimally invasive medical diagnosis.

Single myelin fiber imaging in living rodents without labeling by deep optical coherence microscopy

NASA Astrophysics Data System (ADS)

Ben Arous, Juliette; Binding, Jonas; Léger, Jean-François; Casado, Mariano; Topilko, Piotr; Gigan, Sylvain; Claude Boccara, A.; Bourdieu, Laurent

2011-11-01

Myelin sheath disruption is responsible for multiple neuropathies in the central and peripheral nervous system. Myelin imaging has thus become an important diagnosis tool. However, in vivo imaging has been limited to either low-resolution techniques unable to resolve individual fibers or to low-penetration imaging of single fibers, which cannot provide quantitative information about large volumes of tissue, as required for diagnostic purposes. Here, we perform myelin imaging without labeling and at micron-scale resolution with >300-μm penetration depth on living rodents. This was achieved with a prototype [termed deep optical coherence microscopy (deep-OCM)] of a high-numerical aperture infrared full-field optical coherence microscope, which includes aberration correction for the compensation of refractive index mismatch and high-frame-rate interferometric measurements. We were able to measure the density of individual myelinated fibers in the rat cortex over a large volume of gray matter. In the peripheral nervous system, deep-OCM allows, after minor surgery, in situ imaging of single myelinated fibers over a large fraction of the sciatic nerve. This allows quantitative comparison of normal and Krox20 mutant mice, in which myelination in the peripheral nervous system is impaired. This opens promising perspectives for myelin chronic imaging in demyelinating diseases and for minimally invasive medical diagnosis.

Improving accuracy of medication identification in an older population using a medication bottle color symbol label system

PubMed Central

2011-01-01

Background The purpose of this pilot study was to evaluate and refine an adjuvant system of color-specific symbols that are added to medication bottles and to assess whether this system would increase the ability of patients 65 years of age or older in matching their medication to the indication for which it was prescribed. Methods This study was conducted in two phases, consisting of three focus groups of patients from a family medicine clinic (n = 25) and a pre-post medication identification test in a second group of patient participants (n = 100). Results of focus group discussions were used to refine the medication label symbols according to themes and messages identified through qualitative triangulation mechanisms and data analysis techniques. A pre-post medication identification test was conducted in the second phase of the study to assess differences between standard labeling alone and the addition of the refined color-specific symbols. The pre-post test examined the impact of the added labels on participants' ability to accurately match their medication to the indication for which it was prescribed when placed in front of participants and then at a distance of two feet. Results Participants appreciated the addition of a visual aid on existing medication labels because it would not be necessary to learn a completely new system of labeling, and generally found the colors and symbols used in the proposed labeling system easy to understand and relevant. Concerns were raised about space constraints on medication bottles, having too much information on the bottle, and having to remember what the colors meant. Symbols and colors were modified if they were found unclear or inappropriate by focus group participants. Pre-post medication identification test results in a second set of participants demonstrated that the addition of the symbol label significantly improved the ability of participants to match their medication to the appropriate medical indication at a distance of two feet (p < 0.001) and approached significant improvement when placed directly in front of participants (p = 0.07). Conclusions The proposed medication symbol label system provides a promising adjunct to national efforts in addressing the issue of medication misuse in the home through the improvement of medication labeling. Further research is necessary to determine the effectiveness of the labeling system in real-world settings. PMID:22206490

Improving accuracy of medication identification in an older population using a medication bottle color symbol label system.

PubMed

Cardarelli, Roberto; Mann, Christopher; Fulda, Kimberly G; Balyakina, Elizabeth; Espinoza, Anna; Lurie, Sue

2011-12-29

The purpose of this pilot study was to evaluate and refine an adjuvant system of color-specific symbols that are added to medication bottles and to assess whether this system would increase the ability of patients 65 years of age or older in matching their medication to the indication for which it was prescribed. This study was conducted in two phases, consisting of three focus groups of patients from a family medicine clinic (n = 25) and a pre-post medication identification test in a second group of patient participants (n = 100). Results of focus group discussions were used to refine the medication label symbols according to themes and messages identified through qualitative triangulation mechanisms and data analysis techniques. A pre-post medication identification test was conducted in the second phase of the study to assess differences between standard labeling alone and the addition of the refined color-specific symbols. The pre-post test examined the impact of the added labels on participants' ability to accurately match their medication to the indication for which it was prescribed when placed in front of participants and then at a distance of two feet. Participants appreciated the addition of a visual aid on existing medication labels because it would not be necessary to learn a completely new system of labeling, and generally found the colors and symbols used in the proposed labeling system easy to understand and relevant. Concerns were raised about space constraints on medication bottles, having too much information on the bottle, and having to remember what the colors meant. Symbols and colors were modified if they were found unclear or inappropriate by focus group participants. Pre-post medication identification test results in a second set of participants demonstrated that the addition of the symbol label significantly improved the ability of participants to match their medication to the appropriate medical indication at a distance of two feet (p < 0.001) and approached significant improvement when placed directly in front of participants (p = 0.07). The proposed medication symbol label system provides a promising adjunct to national efforts in addressing the issue of medication misuse in the home through the improvement of medication labeling. Further research is necessary to determine the effectiveness of the labeling system in real-world settings.

Chemical Imaging of the Cell Membrane by NanoSIMS

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

Weber, P K; Kraft, M L; Frisz, J F

2010-02-23

The existence of lipid microdomains and their role in cell membrane organization are currently topics of great interest and controversy. The cell membrane is composed of a lipid bilayer with embedded proteins that can flow along the two-dimensional surface defined by the membrane. Microdomains, known as lipid rafts, are believed to play a central role in organizing this fluid system, enabling the cell membrane to carry out essential cellular processes, including protein recruitment and signal transduction. Lipid rafts are also implicated in cell invasion by pathogens, as in the case of the HIV. Therefore, understanding the role of lipid raftsmore » in cell membrane organization not only has broad scientific implications, but also has practical implications for medical therapies. One of the major limitations on lipid organization research has been the inability to directly analyze lipid composition without introducing artifacts and at the relevant length-scales of tens to hundreds of nanometers. Fluorescence microscopy is widely used due to its sensitivity and specificity to the labeled species, but only the labeled components can be observed, fluorophores can alter the behavior of the lipids they label, and the length scales relevant to imaging cell membrane domains are between that probed by fluorescence resonance energy transfer (FRET) imaging (<10 nm) and the diffraction limit of light. Topographical features can be imaged on this length scale by atomic force microscopy (AFM), but the chemical composition of the observed structures cannot be determined. Immuno-labeling can be used to study the distribution of membrane proteins at high resolution, but not lipid composition. We are using imaging mass spectrometry by secondary ion mass spectrometry (SIMS) in concert with other high resolution imaging methods to overcome these limitations. The experimental approach of this project is to combine molecule-specific stable isotope labeling with high-resolution SIMS using a Cameca NanoSIMS 50 to probe membrane organization and test microdomain hypotheses. The NanoSIMS is an imaging secondary ion mass spectrometer with an unprecedented combination of spatial resolution, sensitivity and mass specificity. It has 50 nm lateral resolution and is capable of detecting 1 in 20 nitrogen atoms while excluding near-neighbor isobaric interferences. The tightly focused cesium ion beam is rastered across the sample to produce simultaneous, quantitative digital images of up to five different masses. By labeling each specific components of a membrane with a unique rare stable isotope or element and mapping the location of the labels with the NanoSIMS, the location of the each labeled component can be determined and quantified. This new approach to membrane composition analysis allows molecular interactions of biological membranes to be probed at length-scales relevant to lipid rafts (10s to 100s of nm) that were not previously possible. Results from our most recent experiments analyzing whole cells will be presented.« less

The legibility of prescription medication labelling in Canada

PubMed Central

Ahrens, Kristina; Krishnamoorthy, Abinaya; Gold, Deborah; Rojas-Fernandez, Carlos H.

2014-01-01

Introduction: The legibility of medication labelling is a concern for all Canadians, because poor or illegible labelling may lead to miscommunication of medication information and poor patient outcomes. There are currently few guidelines and no regulations regarding print standards on medication labels. This study analyzed sample prescription labels from Ontario, Canada, and compared them with print legibility guidelines (both generic and specific to medication labels). Methods: Cluster sampling was used to randomly select a total of 45 pharmacies in the tri-cities of Kitchener, Waterloo and Cambridge. Pharmacies were asked to supply a regular label with a hypothetical prescription. The print characteristics of patient-critical information were compared against the recommendations for prescription labels by pharmaceutical and health organizations and for print accessibility by nongovernmental organizations. Results: More than 90% of labels followed the guidelines for font style, contrast, print colour and nonglossy paper. However, only 44% of the medication instructions met the minimum guideline of 12-point print size, and none of the drug or patient names met this standard. Only 5% of the labels were judged to make the best use of space, and 51% used left alignment. None of the instructions were in sentence case, as is recommended. Discussion: We found discrepancies between guidelines and current labels in print size, justification, spacing and methods of emphasis. Conclusion: Improvements in pharmacy labelling are possible without moving to new technologies or changing the size of labels and would be expected to enhance patient outcomes. PMID:24847371

Dissemination of information on the off-label (unapproved) use of medication: a comparative analysis.

PubMed

Jansen, Rita-Marié

2011-03-01

"Off-label" in relation to the use of medication means that a medicine is used in another way or for indications other than those specified in its conditions of registration and reflected in its labelling. The off-label use of medication accounts for an estimated 21 per cent of drug use overall and is an important part of mainstream, legitimate medical practice worldwide. In South Africa, legislation prohibits the dissemination of information regarding the off-label use of medication. There are diverging views on whether pharmaceutical companies should be allowed to distribute scientific publications on off-label uses of approved drugs. Current policy in the United States of America (USA) eases restrictions on the dissemination of information of this nature. The prohibitions existing in South Africa, however, are more comparable with those in European countries. After analysing the different legal positions on the issue, it is submitted that pharmaceutical companies should not be allowed to disseminate information on off-label uses, but that the regulatory authority play an active and leading role in providing the latest, objective medical and scientific information, as well as guidelines on the off-label use of medication. Other related recommendations are also made.

Nonprescription medication use and literacy among New Hampshire eighth graders.

PubMed

Abel, Cheryl; Johnson, Kerri; Waller, Dustin; Abdalla, Maha; Goldsmith, Carroll-Ann W

2012-01-01

To assess whether New Hampshire (NH) eighth graders were self-medicating with over-the-counter (OTC) medications, had literacy skills necessary to safely and accurately interpret OTC medication labels, and showed improvement in OTC medication safe use and literacy skills after student pharmacist-led education. Cross-sectional repeated-measures study. NH, five separate sessions, in 2010 and 2011. 101 NH eighth grade students. Participants answered questions derived from OTC drug facts labels that assessed OTC medication safe use and literacy before and after a student pharmacist-led presentation describing each section of the labels. Participant use of OTC medications, whether participants interpreted OTC drug facts labels correctly, and whether participants were able to identify safe use of OTC medications before and after instruction about OTC drug facts labels. 57% of participants reported taking OTC medications in the previous month, 22% reported taking OTC medications autonomously, and 43% reported checking with a trusted adult before self-administration. After student pharmacist-led education, significant improvements were seen in identifying product indications, calculating adult doses, interpreting adverse effects, knowing when to call a medical provider, understanding proper medication storage, identifying expiration dates, and identifying duplicate medications in products. NH eighth graders were self-medicating with OTC medications. Significant improvements in OTC medication label literacy were seen after student pharmacist-led education. These results provide evidence of the need for, and positive effects of, OTC medication education among U.S. adolescents.

Modification of a medical PET scanner for PEPT studies

NASA Astrophysics Data System (ADS)

Sadrmomtaz, Alireza; Parker, D. J.; Byars, L. G.

2007-04-01

Over the last 20 years, positron emission tomography (PET) has developed as the most powerful functional imaging modality in medicine. Over the same period the University of Birmingham Positron Imaging Centre has applied PET to study engineering processes and developed the alternative technique of positron emission particle tracking (PEPT) in which a single radioactively labelled tracer particle is tracked by detecting simultaneously the pairs of back-to-back photons arising from positron/electron annihilation. Originally PEPT was performed using a pair of multiwire detectors, and more recently using a pair of digital gamma camera heads. In 2002 the Positron Imaging Centre acquired a medical PET scanner, an ECAT 931/08, previously used at Hammersmith Hospital. This scanner has been rebuilt in a flexible geometry for use in PEPT studies. This paper presents initial results from this system. Fast moving tracer particles can be rapidly and accurately located.

Computerized breast cancer analysis system using three stage semi-supervised learning method.

PubMed

Sun, Wenqing; Tseng, Tzu-Liang Bill; Zhang, Jianying; Qian, Wei

2016-10-01

A large number of labeled medical image data is usually a requirement to train a well-performed computer-aided detection (CAD) system. But the process of data labeling is time consuming, and potential ethical and logistical problems may also present complications. As a result, incorporating unlabeled data into CAD system can be a feasible way to combat these obstacles. In this study we developed a three stage semi-supervised learning (SSL) scheme that combines a small amount of labeled data and larger amount of unlabeled data. The scheme was modified on our existing CAD system using the following three stages: data weighing, feature selection, and newly proposed dividing co-training data labeling algorithm. Global density asymmetry features were incorporated to the feature pool to reduce the false positive rate. Area under the curve (AUC) and accuracy were computed using 10 fold cross validation method to evaluate the performance of our CAD system. The image dataset includes mammograms from 400 women who underwent routine screening examinations, and each pair contains either two cranio-caudal (CC) or two mediolateral-oblique (MLO) view mammograms from the right and the left breasts. From these mammograms 512 regions were extracted and used in this study, and among them 90 regions were treated as labeled while the rest were treated as unlabeled. Using our proposed scheme, the highest AUC observed in our research was 0.841, which included the 90 labeled data and all the unlabeled data. It was 7.4% higher than using labeled data only. With the increasing amount of labeled data, AUC difference between using mixed data and using labeled data only reached its peak when the amount of labeled data was around 60. This study demonstrated that our proposed three stage semi-supervised learning can improve the CAD performance by incorporating unlabeled data. Using unlabeled data is promising in computerized cancer research and may have a significant impact for future CAD system applications. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Shape priors for segmentation of the cervix region within uterine cervix images

NASA Astrophysics Data System (ADS)

Lotenberg, Shelly; Gordon, Shiri; Greenspan, Hayit

2008-03-01

The work focuses on a unique medical repository of digital Uterine Cervix images ("Cervigrams") collected by the National Cancer Institute (NCI), National Institute of Health, in longitudinal multi-year studies. NCI together with the National Library of Medicine is developing a unique web-based database of the digitized cervix images to study the evolution of lesions related to cervical cancer. Tools are needed for the automated analysis of the cervigram content to support the cancer research. In recent works, a multi-stage automated system for segmenting and labeling regions of medical and anatomical interest within the cervigrams was developed. The current paper concentrates on incorporating prior-shape information in the cervix region segmentation task. In accordance with the fact that human experts mark the cervix region as circular or elliptical, two shape models (and corresponding methods) are suggested. The shape models are embedded within an active contour framework that relies on image features. Experiments indicate that incorporation of the prior shape information augments previous results.

Semi-supervised manifold learning with affinity regularization for Alzheimer's disease identification using positron emission tomography imaging.

PubMed

Lu, Shen; Xia, Yong; Cai, Tom Weidong; Feng, David Dagan

2015-01-01

Dementia, Alzheimer's disease (AD) in particular is a global problem and big threat to the aging population. An image based computer-aided dementia diagnosis method is needed to providing doctors help during medical image examination. Many machine learning based dementia classification methods using medical imaging have been proposed and most of them achieve accurate results. However, most of these methods make use of supervised learning requiring fully labeled image dataset, which usually is not practical in real clinical environment. Using large amount of unlabeled images can improve the dementia classification performance. In this study we propose a new semi-supervised dementia classification method based on random manifold learning with affinity regularization. Three groups of spatial features are extracted from positron emission tomography (PET) images to construct an unsupervised random forest which is then used to regularize the manifold learning objective function. The proposed method, stat-of-the-art Laplacian support vector machine (LapSVM) and supervised SVM are applied to classify AD and normal controls (NC). The experiment results show that learning with unlabeled images indeed improves the classification performance. And our method outperforms LapSVM on the same dataset.

"Warning: This image has been digitally altered": The effect of disclaimer labels added to fashion magazine shoots on women's body dissatisfaction.

PubMed

Tiggemann, Marika; Brown, Zoe; Zaccardo, Mia; Thomas, Nicole

2017-06-01

The present experiment aimed to investigate the impact of the addition of disclaimer labels to fashion magazine shoots on women's body dissatisfaction. Participants were 320 female undergraduate students who viewed fashion shoots containing a thin and attractive model with no disclaimer label, or a small, large, or very large disclaimer label, or product images. Although thin-ideal fashion shoot images resulted in greater body dissatisfaction than product images, there was no significant effect of disclaimer label. Internalisation of the thin ideal was found to moderate the effect of disclaimer label, such that internalisation predicted increased body dissatisfaction in the no label and small label conditions, but not in the larger label conditions. Overall, the results showed no benefit for any size of disclaimer label in ameliorating the negative effect of viewing thin-ideal media images. It was concluded that more extensive research is required before the effective implementation of disclaimer labels. Copyright © 2017 Elsevier Ltd. All rights reserved.

Enhanced labeling density and whole-cell 3D dSTORM imaging by repetitive labeling of target proteins.

PubMed

Venkataramani, Varun; Kardorff, Markus; Herrmannsdörfer, Frank; Wieneke, Ralph; Klein, Alina; Tampé, Robert; Heilemann, Mike; Kuner, Thomas

2018-04-03

With continuing advances in the resolving power of super-resolution microscopy, the inefficient labeling of proteins with suitable fluorophores becomes a limiting factor. For example, the low labeling density achieved with antibodies or small molecule tags limits attempts to reveal local protein nano-architecture of cellular compartments. On the other hand, high laser intensities cause photobleaching within and nearby an imaged region, thereby further reducing labeling density and impairing multi-plane whole-cell 3D super-resolution imaging. Here, we show that both labeling density and photobleaching can be addressed by repetitive application of trisNTA-fluorophore conjugates reversibly binding to a histidine-tagged protein by a novel approach called single-epitope repetitive imaging (SERI). For single-plane super-resolution microscopy, we demonstrate that, after multiple rounds of labeling and imaging, the signal density is increased. Using the same approach of repetitive imaging, washing and re-labeling, we demonstrate whole-cell 3D super-resolution imaging compensated for photobleaching above or below the imaging plane. This proof-of-principle study demonstrates that repetitive labeling of histidine-tagged proteins provides a versatile solution to break the 'labeling barrier' and to bypass photobleaching in multi-plane, whole-cell 3D experiments.

Toddler drinks, formulas, and milks: Labeling practices and policy implications.

PubMed

Pomeranz, Jennifer L; Romo Palafox, Maria J; Harris, Jennifer L

2018-04-01

Toddler drinks are a growing category of drinks marketed for young children 9-36 months old. Medical experts do not recommend them, and public health experts raise concerns about misleading labeling practices. In the U.S., the toddler drink category includes two types of products: transition formulas, marketed for infants and toddlers 9-24 months; and toddler milks, for children 12-36 months old. The objective of this study was to evaluate toddler drink labeling practices in light of U.S. food labeling policy and international labeling recommendations. In January 2017, we conducted legal research on U.S. food label laws and regulations; collected and evaluated toddler drink packages, including nutrition labels and claims; and compared toddler drink labels with the same brand's infant formula labels. We found that the U.S. has a regulatory structure for food labels and distinct policies for infant formula, but no laws specific to toddler drinks. Toddler drink labels utilized various terms and images to identify products and intended users; made multiple health and nutrition claims; and some stated there was scientific or expert support for the product. Compared to the same manufacturer's infant formula labels, most toddler drink labels utilized similar colors, branding, logos, and graphics. Toddler drink labels may confuse consumers about their nutrition and health benefits and the appropriateness of these products for young children. To support healthy toddler diets and well-informed decision-making by caregivers, the FDA can provide guidance or propose regulations clarifying permissible toddler drink labels and manufacturers should end inappropriate labeling practices. Copyright © 2018 Elsevier Inc. All rights reserved.

Clinical application of 3D arterial spin-labeled brain perfusion imaging for Alzheimer disease: comparison with brain perfusion SPECT.

PubMed

Takahashi, H; Ishii, K; Hosokawa, C; Hyodo, T; Kashiwagi, N; Matsuki, M; Ashikaga, R; Murakami, T

2014-05-01

Alzheimer disease is the most common neurodegenerative disorder with dementia, and a practical and economic biomarker for diagnosis of Alzheimer disease is needed. Three-dimensional arterial spin-labeling, with its high signal-to-noise ratio, enables measurement of cerebral blood flow precisely without any extrinsic tracers. We evaluated the performance of 3D arterial spin-labeling compared with SPECT, and demonstrated the 3D arterial spin-labeled imaging characteristics in the diagnosis of Alzheimer disease. This study included 68 patients with clinically suspected Alzheimer disease who underwent both 3D arterial spin-labeling and SPECT imaging. Two readers independently assessed both images. Kendall W coefficients of concordance (K) were computed, and receiver operating characteristic analyses were performed for each reader. The differences between the images in regional perfusion distribution were evaluated by means of statistical parametric mapping, and the incidence of hypoperfusion of the cerebral watershed area, referred to as "borderzone sign" in the 3D arterial spin-labeled images, was determined. Readers showed K = 0.82/0.73 for SPECT/3D arterial spin-labeled imaging, and the respective areas under the receiver operating characteristic curve were 0.82/0.69 for reader 1 and 0.80/0.69 for reader 2. Statistical parametric mapping showed that the perisylvian and medial parieto-occipital perfusion in the arterial spin-labeled images was significantly higher than that in the SPECT images. Borderzone sign was observed on 3D arterial spin-labeling in 70% of patients misdiagnosed with Alzheimer disease. The diagnostic performance of 3D arterial spin-labeling and SPECT for Alzheimer disease was almost equivalent. Three-dimensional arterial spin-labeled imaging was more influenced by hemodynamic factors than was SPECT imaging. © 2014 by American Journal of Neuroradiology.

Label Design Affects Medication Safety in an Operating Room Crisis: A Controlled Simulation Study.

PubMed

Estock, Jamie L; Murray, Andrew W; Mizah, Margaret T; Mangione, Michael P; Goode, Joseph S; Eibling, David E

2018-06-01

Several factors contribute to medication errors in clinical practice settings, including the design of medication labels. The objective of this study was to quantify the impact of label design on medication safety in a realistic, high-stress clinical situation. Ninety-six anesthesia trainee participants were randomly assigned to either the redesigned or the current label condition. Participants were blinded to the study's focus on medication label design and their assigned label condition. Each participant was the sole anesthesia provider in a simulated operating room scenario involving an unexpected vascular injury. The surgeon asked the participant to administer hetastarch to the simulated patient because of hemodynamic instability. The fluid drawer of the anesthesia cart contained three 500-ml intravenous bags of hetastarch and one 500-ml intravenous bag of lidocaine. We hypothesized that redesigned labels would help participants correctly select hetastarch from the cart. If the participants incorrectly selected lidocaine from the cart, we hypothesized that the redesigned labels would help participants detect the lidocaine before administration. The percentage of participants who correctly selected hetastarch from the cart was significantly higher for the redesigned labels than the current labels (63% versus 40%; odds ratio, 2.61 [95% confidence interval, 1.1-6.1]; P = 0.03). Of the participants who incorrectly selected lidocaine from the cart, the percentage who detected the lidocaine before administration did not differ by label condition. The redesigned labels helped participants correctly select hetastarch from the cart, thus preventing some potentially catastrophic medication errors from reaching the simulated patient.

A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval.

PubMed

Yang, Liu; Jin, Rong; Mummert, Lily; Sukthankar, Rahul; Goode, Adam; Zheng, Bin; Hoi, Steven C H; Satyanarayanan, Mahadev

2010-01-01

Similarity measurement is a critical component in content-based image retrieval systems, and learning a good distance metric can significantly improve retrieval performance. However, despite extensive study, there are several major shortcomings with the existing approaches for distance metric learning that can significantly affect their application to medical image retrieval. In particular, "similarity" can mean very different things in image retrieval: resemblance in visual appearance (e.g., two images that look like one another) or similarity in semantic annotation (e.g., two images of tumors that look quite different yet are both malignant). Current approaches for distance metric learning typically address only one goal without consideration of the other. This is problematic for medical image retrieval where the goal is to assist doctors in decision making. In these applications, given a query image, the goal is to retrieve similar images from a reference library whose semantic annotations could provide the medical professional with greater insight into the possible interpretations of the query image. If the system were to retrieve images that did not look like the query, then users would be less likely to trust the system; on the other hand, retrieving images that appear superficially similar to the query but are semantically unrelated is undesirable because that could lead users toward an incorrect diagnosis. Hence, learning a distance metric that preserves both visual resemblance and semantic similarity is important. We emphasize that, although our study is focused on medical image retrieval, the problem addressed in this work is critical to many image retrieval systems. We present a boosting framework for distance metric learning that aims to preserve both visual and semantic similarities. The boosting framework first learns a binary representation using side information, in the form of labeled pairs, and then computes the distance as a weighted Hamming distance using the learned binary representation. A boosting algorithm is presented to efficiently learn the distance function. We evaluate the proposed algorithm on a mammographic image reference library with an Interactive Search-Assisted Decision Support (ISADS) system and on the medical image data set from ImageCLEF. Our results show that the boosting framework compares favorably to state-of-the-art approaches for distance metric learning in retrieval accuracy, with much lower computational cost. Additional evaluation with the COREL collection shows that our algorithm works well for regular image data sets.

77 FR 38177 - TRICARE; Off-Label Uses of Devices; Partial List of Examples of Unproven Drugs, Devices, Medical...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-27

... medical literature, national organizations, or technology assessment bodies that the off-label use is safe... medical literature, national organizations, or technology assessment bodies that the off-label use is safe.... Due to the rapid and extensive changes in medical technology it is not feasible to maintain this list...

Enhanced fluorescence microscope and its application

NASA Astrophysics Data System (ADS)

Wang, Susheng; Li, Qin; Yu, Xin

1997-12-01

A high gain fluorescence microscope is developed to meet the needs in medical and biological research. By the help of an image intensifier with luminance gain of 4 by 104 the sensitivity of the system can achieve 10-6 1x level and be 104 times higher than ordinary fluorescence microscope. Ultra-weak fluorescence image can be detected by it. The concentration of fluorescent label and emitting light intensity of the system are decreased as much as possible, therefore, the natural environment of the detected call can be kept. The CCD image acquisition set-up controlled by computer obtains the quantitative data of each point according to the gray scale. The relation between luminous intensity and output of CCD is obtained by using a wide range weak photometry. So the system not only shows the image of ultra-weak fluorescence distribution but also gives the intensity of fluorescence of each point. Using this system, we obtained the images of distribution of hypocrellin A (HA) in Hela cell, the images of Hela cell being protected by antioxidant reagent Vit. E, SF and BHT. The images show that the digitized ultra-sensitive fluorescence microscope is a useful tool for medical and biological research.

3D multimodal cardiac data reconstruction using angiography and computerized tomographic angiography registration.

PubMed

Moosavi Tayebi, Rohollah; Wirza, Rahmita; Sulaiman, Puteri S B; Dimon, Mohd Zamrin; Khalid, Fatimah; Al-Surmi, Aqeel; Mazaheri, Samaneh

2015-04-22

Computerized tomographic angiography (3D data representing the coronary arteries) and X-ray angiography (2D X-ray image sequences providing information about coronary arteries and their stenosis) are standard and popular assessment tools utilized for medical diagnosis of coronary artery diseases. At present, the results of both modalities are individually analyzed by specialists and it is difficult for them to mentally connect the details of these two techniques. The aim of this work is to assist medical diagnosis by providing specialists with the relationship between computerized tomographic angiography and X-ray angiography. In this study, coronary arteries from two modalities are registered in order to create a 3D reconstruction of the stenosis position. The proposed method starts with coronary artery segmentation and labeling for both modalities. Then, stenosis and relevant labeled artery in X-ray angiography image are marked by a specialist. Proper control points for the marked artery in both modalities are automatically detected and normalized. Then, a geometrical transformation function is computed using these control points. Finally, this function is utilized to register the marked artery from the X-ray angiography image on the computerized tomographic angiography and get the 3D position of the stenosis lesion. The result is a 3D informative model consisting of stenosis and coronary arteries' information from the X-ray angiography and computerized tomographic angiography modalities. The results of the proposed method for coronary artery segmentation, labeling and 3D reconstruction are evaluated and validated on the dataset containing both modalities. The advantage of this method is to aid specialists to determine a visual relationship between the correspondent coronary arteries from two modalities and also set up a connection between stenosis points from an X-ray angiography along with their 3D positions on the coronary arteries from computerized tomographic angiography. Moreover, another benefit of this work is that the medical acquisition standards remain unchanged, which means that no calibration in the acquisition devices is required. It can be applied on most computerized tomographic angiography and angiography devices.

Novel receptor-targeted contrast agents for optical imaging of tumors

NASA Astrophysics Data System (ADS)

Becker, Andreas; Hessenius, Carsten; Bhargava, Sarah; Ebert, Bernd; Sukowski, Uwe; Rinneberg, Herbert H.; Wiedenmann, Bertram; Semmler, Wolfhard; Licha, Kai

2000-04-01

Many gastroenteropancreatic tumors express receptors for somatostatin (SST) and/or vasoactive intestinal peptide (VIP). These receptors can be used as molecular targets for the delivery of contrast agents for tumor diagnostics. We have synthesized conjugates consisting of a cyanine dye and an SST analogue or VIP for use as contrast agents in optical imaging. Receptor binding and internalization of these compounds were examined with optical methods in transfected RIN38 tumor cells expressing the SST2 receptor or a GFP- labeled VIP (VPAC1) receptor. Furthermore, biodistribution of the conjugates was examined by laser-induced fluorescence imaging in nude mice bearing SST2 or VPAC1 receptor- expressing tumors. After incubation of RIN38 SSTR2 cells in the presence of 100 nM indotricarbocyanine-SST analogue, cell-associated fluorescence increased, whereas no increase was observed when receptor-medicated endocytosis was inhibited. Indodicarbocyanine-VIP accumulated in RIN38 VPAC1 cells and co-localization with the GFP-labeled VPAC1 receptor was observed. After injection of indotricarbocyanine-SST analogue into tumor-bearing nude mice, SST2 receptor-positive tumors could be visualized for a time period from 10 min to at least 48 h. After application of indodicarbocyanine-VIP, a fluorescence signal in VIP1 receptor-expressing tumors was only detected during the first hour. We conclude that cyanine dye-labeled VIP and SST analogue are novel, targeted contrast agents for the optical imaging of tumors expressing the relevant receptor.

Consumer opinion on social policy approaches to promoting positive body image: Airbrushed media images and disclaimer labels.

PubMed

Paraskeva, Nicole; Lewis-Smith, Helena; Diedrichs, Phillippa C

2017-02-01

Disclaimer labels on airbrushed media images have generated political attention and advocacy as a social policy approach to promoting positive body image. Experimental research suggests that labelling is ineffective and consumers' viewpoints have been overlooked. A mixed-method study explored British consumers' ( N = 1555, aged 11-78 years) opinions on body image and social policy approaches. Thematic analysis indicated scepticism about the effectiveness of labelling images. Quantitatively, adults, although not adolescents, reported that labelling was unlikely to improve body image. Appearance diversity in media and reorienting social norms from appearance to function and health were perceived as effective strategies. Social policy and research implications are discussed.

Development and Implementation of a Corriedale Ovine Brain Atlas for Use in Atlas-Based Segmentation.

PubMed

Liyanage, Kishan Andre; Steward, Christopher; Moffat, Bradford Armstrong; Opie, Nicholas Lachlan; Rind, Gil Simon; John, Sam Emmanuel; Ronayne, Stephen; May, Clive Newton; O'Brien, Terence John; Milne, Marjorie Eileen; Oxley, Thomas James

2016-01-01

Segmentation is the process of partitioning an image into subdivisions and can be applied to medical images to isolate anatomical or pathological areas for further analysis. This process can be done manually or automated by the use of image processing computer packages. Atlas-based segmentation automates this process by the use of a pre-labelled template and a registration algorithm. We developed an ovine brain atlas that can be used as a model for neurological conditions such as Parkinson's disease and focal epilepsy. 17 female Corriedale ovine brains were imaged in-vivo in a 1.5T (low-resolution) MRI scanner. 13 of the low-resolution images were combined using a template construction algorithm to form a low-resolution template. The template was labelled to form an atlas and tested by comparing manual with atlas-based segmentations against the remaining four low-resolution images. The comparisons were in the form of similarity metrics used in previous segmentation research. Dice Similarity Coefficients were utilised to determine the degree of overlap between eight independent, manual and atlas-based segmentations, with values ranging from 0 (no overlap) to 1 (complete overlap). For 7 of these 8 segmented areas, we achieved a Dice Similarity Coefficient of 0.5-0.8. The amygdala was difficult to segment due to its variable location and similar intensity to surrounding tissues resulting in Dice Coefficients of 0.0-0.2. We developed a low resolution ovine brain atlas with eight clinically relevant areas labelled. This brain atlas performed comparably to prior human atlases described in the literature and to intra-observer error providing an atlas that can be used to guide further research using ovine brains as a model and is hosted online for public access.

Developing a radiology-based teaching approach for gross anatomy in the digital era.

PubMed

Marker, David R; Bansal, Anshuman K; Juluru, Krishna; Magid, Donna

2010-08-01

The purpose of this study was to assess the implementation of a digital anatomy lecture series based largely on annotated, radiographic images and the utility of the Radiological Society of North America-developed Medical Imaging Resource Center (MIRC) for providing an online educational resource. A series of digital teaching images were collected and organized to correspond to lecture and dissection topics. MIRC was used to provide the images in a Web-based educational format for incorporation into anatomy lectures and as a review resource. A survey assessed the impressions of the medical students regarding this educational format. MIRC teaching files were successfully used in our teaching approach. The lectures were interactive with questions to and from the medical student audience regarding the labeled images used in the presentation. Eighty-five of 120 students completed the survey. The majority of students (87%) indicated that the MIRC teaching files were "somewhat useful" to "very useful" when incorporated into the lecture. The students who used the MIRC files were most likely to access the material from home (82%) on an occasional basis (76%). With regard to areas for improvement, 63% of the students reported that they would have benefited from more teaching files, and only 9% of the students indicated that the online files were not user friendly. The combination of electronic radiology resources available in lecture format and on the Internet can provide multiple opportunities for medical students to learn and revisit first-year anatomy. MIRC provides a user-friendly format for presenting radiology education files for medical students. 2010 AUR. Published by Elsevier Inc. All rights reserved.

(18)F-labeled positron emission tomographic radiopharmaceuticals in oncology: an overview of radiochemistry and mechanisms of tumor localization.

PubMed

Vallabhajosula, Shankar

2007-11-01

Molecular imaging is the visualization, characterization, and measurement of biological processes at the molecular and cellular levels in a living system. At present, positron emission tomography/computed tomography (PET/CT) is one the most rapidly growing areas of medical imaging, with many applications in the clinical management of patients with cancer. Although [(18)F]fluorodeoxyglucose (FDG)-PET/CT imaging provides high specificity and sensitivity in several kinds of cancer and has many applications, it is important to recognize that FDG is not a "specific" radiotracer for imaging malignant disease. Highly "tumor-specific" and "tumor cell signal-specific" PET radiopharmaceuticals are essential to meet the growing demand of radioisotope-based molecular imaging technology. In the last 15 years, many alternative PET tracers have been proposed and evaluated in preclinical and clinical studies to characterize the tumor biology more appropriately. The potential clinical utility of several (18)F-labeled radiotracers (eg, fluoride, FDOPA, FLT, FMISO, FES, and FCH) is being reviewed by several investigators in this issue. An overview of design and development of (18)F-labeled PET radiopharmaceuticals, radiochemistry, and mechanism(s) of tumor cell uptake and localization of radiotracers are presented here. The approval of clinical indications for FDG-PET in the year 2000 by the Food and Drug Administration, based on a review of literature, was a major breakthrough to the rapid incorporation of PET into nuclear medicine practice, particularly in oncology. Approval of a radiopharmaceutical typically involves submission of a "New Drug Application" by a manufacturer or a company clearly documenting 2 major aspects of the drug: (1) manufacturing of PET drug using current good manufacturing practices and (2) the safety and effectiveness of a drug with specific indications. The potential routine clinical utility of (18)F-labeled PET radiopharmaceuticals depends also on regulatory compliance in addition to documentation of potential safety and efficacy by various investigators.

Graphic Warning Labels Elicit Affective and Thoughtful Responses from Smokers: Results of a Randomized Clinical Trial

PubMed Central

Evans, Abigail T.; Peters, Ellen; Strasser, Andrew A.; Emery, Lydia F.; Sheerin, Kaitlin M.; Romer, Daniel

2015-01-01

Objective Observational research suggests that placing graphic images on cigarette warning labels can reduce smoking rates, but field studies lack experimental control. Our primary objective was to determine the psychological processes set in motion by naturalistic exposure to graphic vs. text-only warnings in a randomized clinical trial involving exposure to modified cigarette packs over a 4-week period. Theories of graphic-warning impact were tested by examining affect toward smoking, credibility of warning information, risk perceptions, quit intentions, warning label memory, and smoking risk knowledge. Methods Adults who smoked between 5 and 40 cigarettes daily (N = 293; mean age = 33.7), did not have a contra-indicated medical condition, and did not intend to quit were recruited from Philadelphia, PA and Columbus, OH. Smokers were randomly assigned to receive their own brand of cigarettes for four weeks in one of three warning conditions: text only, graphic images plus text, or graphic images with elaborated text. Results Data from 244 participants who completed the trial were analyzed in structural-equation models. The presence of graphic images (compared to text-only) caused more negative affect toward smoking, a process that indirectly influenced risk perceptions and quit intentions (e.g., image->negative affect->risk perception->quit intention). Negative affect from graphic images also enhanced warning credibility including through increased scrutiny of the warnings, a process that also indirectly affected risk perceptions and quit intentions (e.g., image->negative affect->risk scrutiny->warning credibility->risk perception->quit intention). Unexpectedly, elaborated text reduced warning credibility. Finally, graphic warnings increased warning-information recall and indirectly increased smoking-risk knowledge at the end of the trial and one month later. Conclusions In the first naturalistic clinical trial conducted, graphic warning labels are more effective than text-only warnings in encouraging smokers to consider quitting and in educating them about smoking’s risks. Negative affective reactions to smoking, thinking about risks, and perceptions of credibility are mediators of their impact. Trial Registration Clinicaltrials.gov NCT01782053 PMID:26672982

77 FR 42502 - Agency Information Collection Activities; Announcement of Office of Management and Budget...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-19

...; Survey of ``Health Care Providers' Responses to Medical Device Labeling'' AGENCY: Food and Drug... collection of information entitled Survey of ``Health Care Providers' Responses to Medical Device Labeling... of information entitled Survey of ``Health Care Providers' Responses to Medical Device Labeling'' to...

Deep learning in the small sample size setting: cascaded feed forward neural networks for medical image segmentation

NASA Astrophysics Data System (ADS)

Gaonkar, Bilwaj; Hovda, David; Martin, Neil; Macyszyn, Luke

2016-03-01

Deep Learning, refers to large set of neural network based algorithms, have emerged as promising machine- learning tools in the general imaging and computer vision domains. Convolutional neural networks (CNNs), a specific class of deep learning algorithms, have been extremely effective in object recognition and localization in natural images. A characteristic feature of CNNs, is the use of a locally connected multi layer topology that is inspired by the animal visual cortex (the most powerful vision system in existence). While CNNs, perform admirably in object identification and localization tasks, typically require training on extremely large datasets. Unfortunately, in medical image analysis, large datasets are either unavailable or are extremely expensive to obtain. Further, the primary tasks in medical imaging are organ identification and segmentation from 3D scans, which are different from the standard computer vision tasks of object recognition. Thus, in order to translate the advantages of deep learning to medical image analysis, there is a need to develop deep network topologies and training methodologies, that are geared towards medical imaging related tasks and can work in a setting where dataset sizes are relatively small. In this paper, we present a technique for stacked supervised training of deep feed forward neural networks for segmenting organs from medical scans. Each `neural network layer' in the stack is trained to identify a sub region of the original image, that contains the organ of interest. By layering several such stacks together a very deep neural network is constructed. Such a network can be used to identify extremely small regions of interest in extremely large images, inspite of a lack of clear contrast in the signal or easily identifiable shape characteristics. What is even more intriguing is that the network stack achieves accurate segmentation even when it is trained on a single image with manually labelled ground truth. We validate this approach,using a publicly available head and neck CT dataset. We also show that a deep neural network of similar depth, if trained directly using backpropagation, cannot acheive the tasks achieved using our layer wise training paradigm.

Off-label use of medical products in radiation therapy: Summary of the Report of AAPM Task Group No. 121

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

Thomadsen, Bruce R.; Thompson, Heaton H. II; Jani, Shirish K.

Medical products (devices, drugs, or biologics) contain information in their labeling regarding the manner in which the manufacturer has determined that the products can be used in a safe and effective manner. The Food and Drug Administration (FDA) approves medical products for use for these specific indications which are part of the medical product's labeling. When medical products are used in a manner not specified in the labeling, it is commonly referred to as off-label use. The practice of medicine allows for this off-label use to treat individual patients, but the ethical and legal implications for such unapproved use canmore » be confusing. Although the responsibility and, ultimately, the liability for off-label use often rests with the prescribing physician, medical physicists and others are also responsible for the safe and proper use of the medical products. When these products are used for purposes other than which they were approved, it is important for medical physicists to understand their responsibilities. In the United States, medical products can only be marketed if officially cleared, approved, or licensed by the FDA; they can be used if they are not subject to or specifically exempt from FDA regulations, or if they are being used in research with the appropriate regulatory safeguards. Medical devices are either cleared or approved by FDA's Center for Devices and Radiological Health. Drugs are approved by FDA's Center for Drug Evaluation and Research, and biological products such as vaccines or blood are licensed under a biologics license agreement by FDA's Center for Biologics Evaluation and Research. For the purpose of this report, the process by which the FDA eventually clears, approves, or licenses such products for marketing in the United States will be referred to as approval. This report summarizes the various ways medical products, primarily medical devices, can legally be brought to market in the United States, and includes a discussion of the approval process, along with manufacturers' responsibilities, labeling, marketing and promotion, and off-label use. This is an educational and descriptive report and does not contain prescriptive recommendations. This report addresses the role of the medical physicist in clinical situations involving off-label use. Case studies in radiation therapy are presented. Any mention of commercial products is for identification only; it does not imply recommendations or endorsements of any of the authors or the AAPM. The full report, containing extensive background on off-label use with several appendices, is available on the AAPM website (http://www.aapm.org/pubs/reports/).« less

Novel image processing method study for a label-free optical biosensor

NASA Astrophysics Data System (ADS)

Yang, Chenhao; Wei, Li'an; Yang, Rusong; Feng, Ying

2015-10-01

Optical biosensor is generally divided into labeled type and label-free type, the former mainly contains fluorescence labeled method and radioactive-labeled method, while fluorescence-labeled method is more mature in the application. The mainly image processing methods of fluorescent-labeled biosensor includes smooth filtering, artificial gridding and constant thresholding. Since some fluorescent molecules may influence the biological reaction, label-free methods have been the main developing direction of optical biosensors nowadays. The using of wider field of view and larger angle of incidence light path which could effectively improve the sensitivity of the label-free biosensor also brought more difficulties in image processing, comparing with the fluorescent-labeled biosensor. Otsu's method is widely applied in machine vision, etc, which choose the threshold to minimize the intraclass variance of the thresholded black and white pixels. It's capacity-constrained with the asymmetrical distribution of images as a global threshold segmentation. In order to solve the irregularity of light intensity on the transducer, we improved the algorithm. In this paper, we present a new image processing algorithm based on a reflectance modulation biosensor platform, which mainly comprises the design of sliding normalization algorithm for image rectification and utilizing the improved otsu's method for image segmentation, in order to implement automatic recognition of target areas. Finally we used adaptive gridding method extracting the target parameters for analysis. Those methods could improve the efficiency of image processing, reduce human intervention, enhance the reliability of experiments and laid the foundation for the realization of high throughput of label-free optical biosensors.

Use of Magnetic Nanoparticles to Monitor Alginate-Encapsulated βTC-tet Cells

PubMed Central

Constantinidis, Ioannis; Grant, Samuel C.; Simpson, Nicholas E.; Oca-Cossio, Jose A.; Sweeney, Carol A.; Mao, Hui; Blackband, Stephen J.; Sambanis, Athanassios

2008-01-01

Non-invasive monitoring of tissue-engineered constructs is an important component in optimizing construct design and assessing therapeutic efficacy. In recent years, cellular and molecular imaging initiatives have spurred the use of iron oxide based contrast agents in the field of NMR imaging. Although their use in medical research has been widespread, their application in tissue engineering has been limited. In this study, the utility of Monocrystalline Iron Oxide Nanoparticles (MION) as an NMR contrast agent was evaluated for βTC-tet cells encapsulated within alginate/poly-L-lysine/alginate (APA) microbeads. The constructs were labeled with MION in two different ways: (a) MION-labeled βTC-tet cells were encapsulated in APA beads (i.e., intracellular compartment); and (b) MION particles were suspended in the alginate solution prior to encapsulation so that the alginate matrix was labeled with MION instead of the cells (i.e., extracellular compartment). The data show that although the location of cells can be identified within APA beads, cell growth or rearrangement within these constructs cannot be effectively monitored, regardless of the location of MION compartmentalization. The advantages and disadvantages of these techniques and their potential use in tissue engineering are discussed. PMID:19165877

PET scanning in head and neck oncology: a review.

PubMed

McGuirt, W F; Greven, K; Williams, D; Keyes, J W; Watson, N; Cappellari, J O; Geisinger, K R

1998-05-01

The objective of this study was to review and describe the usage of fluorine-labeled deoxyglucose (FDG) and positron emission tomography (PET) in the diagnosis and management of head and neck cancer. Several prospective series,-including 159 newly diagnosed and previously untreated and 23 previously irradiated head and neck squamous cell carcinoma patients initially seen at the Wake Forest University Medical Center and evaluated by clinical examination, conventional computed tomography/ magnetic resonance imaging (CT/MRI) scans, PET scans, and histopathologic studies,-were reviewed and the findings summarized for comparison of the correct differentiation of primary and metastatic cancers and for postirradiation tumor clearance in a subsegment of those cases. Positron emission tomography scanning using a fluorine-labeled deoxyglucose (FDG) radiotracer proved as reliable as conventional scanning for primary and metastatic tumor identification. Compared with clinical examination, PET was better for identification of nodal metastatic tumors but poorer for small primary tumors. For previously irradiated patients treated at least 4 months before the test, PET scanning was clearly superior to clinical examination and conventional imaging in differentiating tumor recurrence from soft-tissue irradiation effects. Fluorine-labeled deoxyglucose-PET scanning is comparable to conventional imaging of head and neck cancers in detecting primary and metastatic carcinoma. Lack of anatomic detail remains its major drawback. Currently, its greatest role is in the evaluation of the postradiotherapy patient.

Consumer involvement: effects on information processing from over-the-counter medication labels.

PubMed

Sansgiry, S S; Cady, P S; Sansgiry, S

2001-01-01

The objective of this study was to evaluate the effects of consumer involvement on information processing from over-the-counter (OTC) medication labels. A sample of 256 students evaluated simulated OTC product labels for two product categories (headache and cold) in random order. Each participant evaluated labels after reading a scenario to simulate high and low involvement respectively. A questionnaire was used to collect data on variables such as label comprehension, attitude-towards-product label, product evaluation, and purchase intention. The results indicate that when consumers are involved in their purchase of OTC medications they are significantly more likely to understand information from the label and evaluate it accordingly. However, involvement does not affect attitude-towards-product label nor does it enhance purchase intention.

Evaluation of the impact of deep learning architectural components selection and dataset size on a medical imaging task

NASA Astrophysics Data System (ADS)

Dutta, Sandeep; Gros, Eric

2018-03-01

Deep Learning (DL) has been successfully applied in numerous fields fueled by increasing computational power and access to data. However, for medical imaging tasks, limited training set size is a common challenge when applying DL. This paper explores the applicability of DL to the task of classifying a single axial slice from a CT exam into one of six anatomy regions. A total of 29000 images selected from 223 CT exams were manually labeled for ground truth. An additional 54 exams were labeled and used as an independent test set. The network architecture developed for this application is composed of 6 convolutional layers and 2 fully connected layers with RELU non-linear activations between each layer. Max-pooling was used after every second convolutional layer, and a softmax layer was used at the end. Given this base architecture, the effect of inclusion of network architecture components such as Dropout and Batch Normalization on network performance and training is explored. The network performance as a function of training and validation set size is characterized by training each network architecture variation using 5,10,20,40,50 and 100% of the available training data. The performance comparison of the various network architectures was done for anatomy classification as well as two computer vision datasets. The anatomy classifier accuracy varied from 74.1% to 92.3% in this study depending on the training size and network layout used. Dropout layers improved the model accuracy for all training sizes.

Imaging of Prostate Cancer Using 64Cu-Labeled Prostate-Specific Membrane Antigen Ligand.

PubMed

Singh, Aviral; Kulkarni, Harshad R; Baum, Richard P

2017-04-01

Prostate cancer is the most common noncutaneous cancer among men, rendering the diagnosis and staging of significant medical and public interest. One of the most interesting developments in the application of nuclear oncology has been the development of novel diagnostic agents that are able to facilitate targeted therapies using the concept of theranostics. This review summarizes the current and emerging molecular imaging techniques for the investigation of patients with prostate cancer with emphasis on the potential of 64 Cu-PSMA PET/CT in staging, restaging, and the application of theranostics. Copyright © 2016 Elsevier Inc. All rights reserved.

Extraction and labeling high-resolution images from PDF documents

NASA Astrophysics Data System (ADS)

Chachra, Suchet K.; Xue, Zhiyun; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

2013-12-01

Accuracy of content-based image retrieval is affected by image resolution among other factors. Higher resolution images enable extraction of image features that more accurately represent the image content. In order to improve the relevance of search results for our biomedical image search engine, Open-I, we have developed techniques to extract and label high-resolution versions of figures from biomedical articles supplied in the PDF format. Open-I uses the open-access subset of biomedical articles from the PubMed Central repository hosted by the National Library of Medicine. Articles are available in XML and in publisher supplied PDF formats. As these PDF documents contain little or no meta-data to identify the embedded images, the task includes labeling images according to their figure number in the article after they have been successfully extracted. For this purpose we use the labeled small size images provided with the XML web version of the article. This paper describes the image extraction process and two alternative approaches to perform image labeling that measure the similarity between two images based upon the image intensity projection on the coordinate axes and similarity based upon the normalized cross-correlation between the intensities of two images. Using image identification based on image intensity projection, we were able to achieve a precision of 92.84% and a recall of 82.18% in labeling of the extracted images.

Respiratory drugs prescribed off-label among children in the outpatient clinics of a hospital in Malaysia.

PubMed

Mohamad, Nurul Fadilah; Mhd Ali, Adliah; Mohamed Shah, Noraida

2015-02-01

Prescribing medicines in an unlicensed and off-label manner for children is a widespread practice around the world. To determine the extent and predictors of off-label respiratory drug prescriptions for children in the outpatient clinics of a hospital in Malaysia. Outpatient clinics at the Universiti Kebangsaan Malaysia Medical Centre, a tertiary teaching hospital in Malaysia. The pharmacy-based computer system and medical records of the patients were utilized to collect data from 220 pediatric patients who were prescribed at least one respiratory drug from July 2011 to December 2011. Characteristics of the off-label respiratory drug prescriptions were measured. A total of 134 children (60.9 %) received at least one respiratory drug prescribed in an off-label manner. The most common reasons for the off-label prescribing of drugs were off-label use by indication (31.5 %), followed by higher than the recommended dose (24.9 %) and lower than the recommended frequency (17.1 %). Diphenhydramine was the most common respiratory drug prescribed off-label. The number of medications prescribed was the only significant predictor of off-label prescription of respiratory drugs. Pediatric patients receiving 4-6 medications were 7.8 times more likely to receive at least one off-label respiratory drug compared to pediatric patients that received 1-3 medications (OR 7.8, 95 % CI 1.74-37.44). There was substantial prescribing of respiratory drugs for children in an off-label manner at the outpatient clinics at the Universiti Kebangsaan Malaysia Medical Centre. This highlights the need for more research to be carried out on respiratory drugs in the pediatric population.

Convex formulation of multiple instance learning from positive and unlabeled bags.

PubMed

Bao, Han; Sakai, Tomoya; Sato, Issei; Sugiyama, Masashi

2018-05-24

Multiple instance learning (MIL) is a variation of traditional supervised learning problems where data (referred to as bags) are composed of sub-elements (referred to as instances) and only bag labels are available. MIL has a variety of applications such as content-based image retrieval, text categorization, and medical diagnosis. Most of the previous work for MIL assume that training bags are fully labeled. However, it is often difficult to obtain an enough number of labeled bags in practical situations, while many unlabeled bags are available. A learning framework called PU classification (positive and unlabeled classification) can address this problem. In this paper, we propose a convex PU classification method to solve an MIL problem. We experimentally show that the proposed method achieves better performance with significantly lower computation costs than an existing method for PU-MIL. Copyright © 2018 Elsevier Ltd. All rights reserved.

Lipid nanoparticle vectorization of indocyanine green improves fluorescence imaging for tumor diagnosis and lymph node resection.

PubMed

Navarro, Fabrice P; Berger, Michel; Guillermet, Stéphanie; Josserand, Véronique; Guyon, Laurent; Neumann, Emmanuelle; Vinet, Françoise; Texier, Isabelle

2012-10-01

Fluorescence imaging is opening a new era in image-guided surgery and other medical applications. The only FDA approved contrast agent in the near infrared is IndoCyanine Green (ICG), which despites its low toxicity, displays poor chemical and optical properties for long-term and sensitive imaging applications in human. Lipid nanoparticles are investigated for improving ICG optical properties and in vivo fluorescence imaging sensitivity. 30 nm diameter lipid nanoparticles (LNP) are loaded with ICG. Their characterization and use for tumor and lymph node imaging are described. Nano-formulation benefits dye optical properties (6 times improved brightness) and chemical stability (>6 months at 4 degrees C in aqueous buffer). More importantly, LNP vectorization allows never reported sensitive and prolonged (>1 day) labeling of tumors and lymph nodes. Composed of human-use approved ingredients, this novel ICG nanometric formulation is foreseen to expand rapidly the field of clinical fluorescence imaging applications.

High-resolution single photon planar and spect imaging of brain and neck employing a system of two co-registered opposed gamma imaging heads

DOEpatents

Majewski, Stanislaw [Yorktown, VA; Proffitt, James [Newport News, VA

2011-12-06

A compact, mobile, dedicated SPECT brain imager that can be easily moved to the patient to provide in-situ imaging, especially when the patient cannot be moved to the Nuclear Medicine imaging center. As a result of the widespread availability of single photon labeled biomarkers, the SPECT brain imager can be used in many locations, including remote locations away from medical centers. The SPECT imager improves the detection of gamma emission from the patient's head and neck area with a large field of view. Two identical lightweight gamma imaging detector heads are mounted to a rotating gantry and precisely mechanically co-registered to each other at 180 degrees. A unique imaging algorithm combines the co-registered images from the detector heads and provides several SPECT tomographic reconstructions of the imaged object thereby improving the diagnostic quality especially in the case of imaging requiring higher spatial resolution and sensitivity at the same time.

Taking a deep look: modern microscopy technologies to optimize the design and functionality of biocompatible scaffolds for tissue engineering in regenerative medicine

PubMed Central

Vielreicher, M.; Schürmann, S.; Detsch, R.; Schmidt, M. A.; Buttgereit, A.; Boccaccini, A.; Friedrich, O.

2013-01-01

This review focuses on modern nonlinear optical microscopy (NLOM) methods that are increasingly being used in the field of tissue engineering (TE) to image tissue non-invasively and without labelling in depths unreached by conventional microscopy techniques. With NLOM techniques, biomaterial matrices, cultured cells and their produced extracellular matrix may be visualized with high resolution. After introducing classical imaging methodologies such as µCT, MRI, optical coherence tomography, electron microscopy and conventional microscopy two-photon fluorescence (2-PF) and second harmonic generation (SHG) imaging are described in detail (principle, power, limitations) together with their most widely used TE applications. Besides our own cell encapsulation, cell printing and collagen scaffolding systems and their NLOM imaging the most current research articles will be reviewed. These cover imaging of autofluorescence and fluorescence-labelled tissue and biomaterial structures, SHG-based quantitative morphometry of collagen I and other proteins, imaging of vascularization and online monitoring techniques in TE. Finally, some insight is given into state-of-the-art three-photon-based imaging methods (e.g. coherent anti-Stokes Raman scattering, third harmonic generation). This review provides an overview of the powerful and constantly evolving field of multiphoton microscopy, which is a powerful and indispensable tool for the development of artificial tissues in regenerative medicine and which is likely to gain importance also as a means for general diagnostic medical imaging. PMID:23864499

Development and Application of Chemical Probes for Vibrational Imaging by Stimulated Raman Scattering

NASA Astrophysics Data System (ADS)

Hu, Fanghao

During the last decade, Raman microscopy is experiencing rapid development and increasingly applied in biological and medical systems. Especially, stimulated Raman scattering (SRS) microscopy, which significantly improves the sensitivity of Raman scattering through stimulated emission, has allowed direct visualization of many species that are previously challenging with conventional fluorescence imaging. Compared to fluorescence, SRS imaging requires no label or small label on the target molecule, thus with minimal perturbation to the molecule of interest. Moreover, Raman scattering is free from complicated photophysical and photochemical processes such as photobleaching, and has intrinsically narrower linewidth than fluorescence emission. This allows multiplexed Raman imaging with minimal spectral crosstalk and excellent photo-stability. To achieve the full potential of Raman microscopy, vibrational probes have been developed for Raman imaging. Multiple Raman probes with a few atoms in size are applied in Raman imaging with high sensitivity and specificity. An overview of both fluorescence and Raman microscopy and their imaging probes is given in Chapter 1 with a brief discussion on the SRS theory. Built on the current progress of Raman microscopy and vibrational probes, I write on my research in the development of carbon-deuterium, alkyne and nitrile probes for visualizing choline metabolism (Chapter 2), glucose uptake activity (Chapter 3), complex brain metabolism (Chapter 4) and polymeric nanoparticles (Chapter 5) in live cells and tissues, as well as the development of polyyne-based vibrational probes for super-multiplexed imaging, barcoding and analysis (Chapter 6).

White matter tract integrity is associated with antidepressant response to lurasidone in bipolar depression.

PubMed

Lan, Martin J; Rubin-Falcone, Harry; Motiwala, Fatima; Chen, Ying; Stewart, Jonathan W; Hellerstein, David J; Mann, J John; McGrath, Patrick J

2017-09-01

Patients with bipolar disorder spend the most time in the depressed phase, and that phase is associated with the most morbidity and mortality. Treatment of bipolar depression lacks a test to determine who will respond to treatment. White matter disruptions have been found in bipolar disorder. Previous reports suggest that white matter disruptions may be associated with resistance to antidepressant medication, but this has never been investigated in a prospective study using a Food and Drug Administration (FDA)-approved medication. Eighteen subjects with bipolar disorder who were in a major depressive episode and off all medications were recruited. Magnetic resonance imaging was acquired using a 64-direction diffusion tensor imaging sequence on a 3T scanner. Subjects were treated with 8 weeks of open-label lurasidone. The Montgomrey-Asberg Depression Rating Scale (MADRS) was completed weekly. Tract-Based Spatial Statistics were utilized to perform a regression analysis of fractional anisotropy (FA) data with treatment outcome as assessed by percent change in MADRS as a regressor while controlling for age and sex, using a threshold of P (threshold-free cluster enhancement-corrected) <.05. FA was positively correlated with antidepressant treatment response in multiple regions of the mean FA skeleton bilaterally, including tracts in the frontal and parietal lobes. Greater disruptions in the white matter tracts in bipolar disorder were associated with poorer antidepressant response to lurasidone. The disruptions may potentially indicate treatment with a different antidepressant medication class. These results are limited by the open-label study design, sample size and lack of a healthy control group. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

An Automatic Segmentation and Classification Framework Based on PCNN Model for Single Tooth in MicroCT Images.

PubMed

Wang, Liansheng; Li, Shusheng; Chen, Rongzhen; Liu, Sze-Yu; Chen, Jyh-Cheng

2016-01-01

Accurate segmentation and classification of different anatomical structures of teeth from medical images plays an essential role in many clinical applications. Usually, the anatomical structures of teeth are manually labelled by experienced clinical doctors, which is time consuming. However, automatic segmentation and classification is a challenging task because the anatomical structures and surroundings of the tooth in medical images are rather complex. Therefore, in this paper, we propose an effective framework which is designed to segment the tooth with a Selective Binary and Gaussian Filtering Regularized Level Set (GFRLS) method improved by fully utilizing three dimensional (3D) information, and classify the tooth by employing unsupervised learning Pulse Coupled Neural Networks (PCNN) model. In order to evaluate the proposed method, the experiments are conducted on the different datasets of mandibular molars and the experimental results show that our method can achieve better accuracy and robustness compared to other four state of the art clustering methods.

A segmentation and classification scheme for single tooth in MicroCT images based on 3D level set and k-means+.

PubMed

Wang, Liansheng; Li, Shusheng; Chen, Rongzhen; Liu, Sze-Yu; Chen, Jyh-Cheng

2017-04-01

Accurate classification of different anatomical structures of teeth from medical images provides crucial information for the stress analysis in dentistry. Usually, the anatomical structures of teeth are manually labeled by experienced clinical doctors, which is time consuming. However, automatic segmentation and classification is a challenging task because the anatomical structures and surroundings of the tooth in medical images are rather complex. Therefore, in this paper, we propose an effective framework which is designed to segment the tooth with a Selective Binary and Gaussian Filtering Regularized Level Set (GFRLS) method improved by fully utilizing 3 dimensional (3D) information, and classify the tooth by employing unsupervised learning i.e., k-means++ method. In order to evaluate the proposed method, the experiments are conducted on the sufficient and extensive datasets of mandibular molars. The experimental results show that our method can achieve higher accuracy and robustness compared to other three clustering methods. Copyright © 2016 Elsevier Ltd. All rights reserved.

Interactive radiographic image retrieval system.

PubMed

Kundu, Malay Kumar; Chowdhury, Manish; Das, Sudeb

2017-02-01

Content based medical image retrieval (CBMIR) systems enable fast diagnosis through quantitative assessment of the visual information and is an active research topic over the past few decades. Most of the state-of-the-art CBMIR systems suffer from various problems: computationally expensive due to the usage of high dimensional feature vectors and complex classifier/clustering schemes. Inability to properly handle the "semantic gap" and the high intra-class versus inter-class variability problem of the medical image database (like radiographic image database). This yields an exigent demand for developing highly effective and computationally efficient retrieval system. We propose a novel interactive two-stage CBMIR system for diverse collection of medical radiographic images. Initially, Pulse Coupled Neural Network based shape features are used to find out the most probable (similar) image classes using a novel "similarity positional score" mechanism. This is followed by retrieval using Non-subsampled Contourlet Transform based texture features considering only the images of the pre-identified classes. Maximal information compression index is used for unsupervised feature selection to achieve better results. To reduce the semantic gap problem, the proposed system uses a novel fuzzy index based relevance feedback mechanism by incorporating subjectivity of human perception in an analytic manner. Extensive experiments were carried out to evaluate the effectiveness of the proposed CBMIR system on a subset of Image Retrieval in Medical Applications (IRMA)-2009 database consisting of 10,902 labeled radiographic images of 57 different modalities. We obtained overall average precision of around 98% after only 2-3 iterations of relevance feedback mechanism. We assessed the results by comparisons with some of the state-of-the-art CBMIR systems for radiographic images. Unlike most of the existing CBMIR systems, in the proposed two-stage hierarchical framework, main importance is given on constructing efficient and compact feature vector representation, search-space reduction and handling the "semantic gap" problem effectively, without compromising the retrieval performance. Experimental results and comparisons show that the proposed system performs efficiently in the radiographic medical image retrieval field. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Telemedicine: An Application in Search of Users

NASA Technical Reports Server (NTRS)

Khandheria, Bijoy K.

1996-01-01

Telemedicine involves the use of telecommunication technologies as a medium for the provision of medical information and services to consumers at sites that are at a distance from the provider. The concept encompasses everything from the telephone system to high-speed, wide-bandwidth transmission with use of fiberoptics, satellites, or a combination of terrestrial and satellite-communication technologies. The peripheral software could be as simple as a typewriter used to type a letter requesting an opinion or as complex as high-capacity parallel processing computers and imaging devices. Although the definition includes telephone, facsimile, and distance learning, the term "Telemedicine" is currently used as a generic label for remote consultation and diagnosis. Telemedicine is not a medical subspecialty but a facilitator of all medical and surgical specialties.

Matched pairs dosimetry: 124I/131I metaiodobenzylguanidine and 124I/131I and 86Y/90Y antibodies.

PubMed

Lopci, Egesta; Chiti, Arturo; Castellani, Maria Rita; Pepe, Giovanna; Antunovic, Lidija; Fanti, Stefano; Bombardieri, Emilio

2011-05-01

The technological advances in imaging and production of radiopharmaceuticals are driving an innovative way of evaluating the targets for antineoplastic therapies. Besides the use of imaging to better delineate the volume of external beam radiation therapy in oncology, modern imaging techniques are able to identify targets for highly specific medical therapies, using chemotherapeutic drugs and antiangiogenesis molecules. Moreover, radionuclide imaging is able to select targets for radionuclide therapy and to give the way to in vivo dose calculation to target tissues and to critical organs. This contribution reports the main studies published on matched pairs dosimetry with (124)I/(131)I- and (86)Y/(90)Y-labelled radiopharmaceuticals, with an emphasis on metaiodobenzylguanidine (MIBG) and monoclonal antibodies.

Two efficient label-equivalence-based connected-component labeling algorithms for 3-D binary images.

PubMed

He, Lifeng; Chao, Yuyan; Suzuki, Kenji

2011-08-01

Whenever one wants to distinguish, recognize, and/or measure objects (connected components) in binary images, labeling is required. This paper presents two efficient label-equivalence-based connected-component labeling algorithms for 3-D binary images. One is voxel based and the other is run based. For the voxel-based one, we present an efficient method of deciding the order for checking voxels in the mask. For the run-based one, instead of assigning each foreground voxel, we assign each run a provisional label. Moreover, we use run data to label foreground voxels without scanning any background voxel in the second scan. Experimental results have demonstrated that our voxel-based algorithm is efficient for 3-D binary images with complicated connected components, that our run-based one is efficient for those with simple connected components, and that both are much more efficient than conventional 3-D labeling algorithms.

A novel method to label preformed liposomes with 64Cu for positron emission tomography (PET) imaging.

PubMed

Seo, Jai Woong; Zhang, Hua; Kukis, David L; Meares, Claude F; Ferrara, Katherine W

2008-12-01

Radiolabeling of liposomes with 64Cu (t(1/2)=12.7 h) is attractive for molecular imaging and monitoring drug delivery. A simple chelation procedure, performed at a low temperature and under mild conditions, is required to radiolabel preloaded liposomes without lipid hydrolysis or the release of the encapsulated contents. Here, we report a 64Cu postlabeling method for liposomes. A 64Cu-specific chelator, 6-[p-(bromoacetamido)benzyl]-1,4,8,11-tetraazacyclotetradecane-N,N',N'',N'''-tetraacetic acid (BAT), was conjugated with an artificial lipid to form a BAT-PEG-lipid. After incorporation of 0.5% (mol/mol) BAT-PEG-lipid during liposome formulation, liposomes were successfully labeled with 64Cu in 0.1 M NH4OAc pH 5 buffer at 35 degrees C for 30-40 min with an incorporation yield as high as 95%. After 48 h of incubation of 64Cu-liposomes in 50/50 serum/PBS solution, more than 88% of the 64Cu label was still associated with liposomes. After injection of liposomal 64Cu in a mouse model, 44+/-6.9, 21+/-2.7, 15+/-2.5, and 7.4+/-1.1 (n=4) % of the injected dose per cubic centimeter remained within the blood pool at 30 min, 18, 28, and 48 h, respectively. The biodistribution at 48 h after injection verified that 7.0+/-0.47 (n=4) and 1.4+/-0.58 (n=3) % of the injected dose per gram of liposomal 64Cu and free 64Cu remained in the blood pool, respectively. Our results suggest that this fast and easy 64Cu labeling of liposomes could be exploited in tracking liposomes in vivo for medical imaging and targeted delivery.

Scalable High Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning

PubMed Central

Wu, Guorong; Kim, Minjeong; Wang, Qian; Munsell, Brent C.

2015-01-01

Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data,, the development of deformable image registration method that scales well to new image modalities or new image applications with little to no human intervention would have a significant impact on the medical image analysis community. To address these concerns, a learning-based image registration framework is proposed that uses deep learning to discover compact and highly discriminative features upon observed imaging data. Specifically, the proposed feature selection method uses a convolutional stacked auto-encoder to identify intrinsic deep feature representations in image patches. Since deep learning is an unsupervised learning method, no ground truth label knowledge is required. This makes the proposed feature selection method more flexible to new imaging modalities since feature representations can be directly learned from the observed imaging data in a very short amount of time. Using the LONI and ADNI imaging datasets, image registration performance was compared to two existing state-of-the-art deformable image registration methods that use handcrafted features. To demonstrate the scalability of the proposed image registration framework image registration experiments were conducted on 7.0-tesla brain MR images. In all experiments, the results showed the new image registration framework consistently demonstrated more accurate registration results when compared to state-of-the-art. PMID:26552069

Scalable High-Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning.

PubMed

Wu, Guorong; Kim, Minjeong; Wang, Qian; Munsell, Brent C; Shen, Dinggang

2016-07-01

Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data, the development of deformable image registration method that scales well to new image modalities or new image applications with little to no human intervention would have a significant impact on the medical image analysis community. To address these concerns, a learning-based image registration framework is proposed that uses deep learning to discover compact and highly discriminative features upon observed imaging data. Specifically, the proposed feature selection method uses a convolutional stacked autoencoder to identify intrinsic deep feature representations in image patches. Since deep learning is an unsupervised learning method, no ground truth label knowledge is required. This makes the proposed feature selection method more flexible to new imaging modalities since feature representations can be directly learned from the observed imaging data in a very short amount of time. Using the LONI and ADNI imaging datasets, image registration performance was compared to two existing state-of-the-art deformable image registration methods that use handcrafted features. To demonstrate the scalability of the proposed image registration framework, image registration experiments were conducted on 7.0-T brain MR images. In all experiments, the results showed that the new image registration framework consistently demonstrated more accurate registration results when compared to state of the art.

Off-label use of intravascular iodinated organic and MR contrast media.

PubMed

Tamburrini, O; Aprile, I; Falcone, C; Console, D; Rotundo, A; Rotondo, A

2011-02-01

This paper analyses off-label prescribing of the iodinated organic and magnetic resonance (MR) contrast media used in diagnostic imaging and evaluates the liability profiles and medicolegal issues associated with such use. The term off-label generally indicates the use of known drugs for which new scientific evidence suggests use in a manner and in clinical scenarios not explicitly addressed by the drug data sheet and is outside the indications for which the medication was approved. In addition, the term also indicates the use of drugs with a different route of administration and dosage from those indicated in the information leaflet. Intravascular contrast media used in diagnostic imaging are drugs in the complete sense of the term, even though they have unique characteristics which in many ways distinguish them from other pharmacological agents. The off-label use of contrast media in diagnostic imaging is a little-investigated field and most commonly, but not exclusively, applies to gadolinium-based contrast media used in MR angiography as well as cardiac and paediatric applications. In particular, the off-label use of contrast media mostly concerns deviations from the recommended dose. As contrast media are to all effects pharmaceutical agents, their off-label use can be considered admissible within the limitations laid down by the Italian law in force (Article 3 of Law 94/98) and its interpretation, i.e. the following criteria must be present: the lack of a valid diagnostic alternative; written informed consent by the patient; the presence of scientific publications validated at the international level; assumption of responsibility by the radiologist. The use of contrast media in modern image-guided medicine is essential. In cases in which the information contained in the information leaflet is modified and updated in any way whatsoever (indications, dosage, at others), specifically if restrictions are introduced in accordance with the law in force, the pharmaceutical industry must provide formal and timely notification to radiologists. On their part as prescribers and users of contrast media, radiologists must remain up to date regarding any changes in indications, dosage and route of administration. Lastly, we propose that the radiology report includes not only the type but also the dose of contrast medium used.

Presenting Numeric Information with Percentages and Descriptive Risk Labels: A Randomized Trial.

PubMed

Sinayev, Aleksandr; Peters, Ellen; Tusler, Martin; Fraenkel, Liana

2015-11-01

Previous research demonstrated that providing (v. not providing) numeric information about the adverse effects (AEs) of medications increased comprehension and willingness to use medication but left open the question about which numeric format is best. The objective was to determine which of 4 tested formats (percentage, frequency, percentage + risk label, frequency + risk label) maximizes comprehension and willingness to use medication across age and numeracy levels. In a cross-sectional internet survey (N = 368; American Life Panel, 15 May 2008 to 18 June 2008), respondents were presented with a hypothetical prescription medication for high cholesterol. AE likelihoods were described using 1 of 4 tested formats. Main outcome measures were risk comprehension (ability to identify AE likelihood from a table) and willingness to use the medication (7-point scale; not likely = 0, very likely = 6). The percentage + risk label format resulted in the highest comprehension and willingness to use the medication compared with the other 3 formats (mean comprehension in percentage + risk label format = 95% v. mean across the other 3 formats = 81%; mean willingness = 3.3 v. 2.95, respectively). Comprehension differences between percentage and frequency formats were smaller among the less numerate. Willingness to use medication depended less on age and numeracy when labels were used. Generalizability is limited by the use of a sample that was older, more educated, and better off financially than national averages. Providing numeric AE-likelihood information in a percentage format with risk labels is likely to increase risk comprehension and willingness to use a medication compared with other numeric formats. © The Author(s) 2015.

Near-infrared emitting fluorescent nanocrystals-labeled natural killer cells as a platform technology for the optical imaging of immunotherapeutic cells-based cancer therapy

NASA Astrophysics Data System (ADS)

Taik Lim, Yong; Cho, Mi Young; Noh, Young-Woock; Chung, Jin Woong; Chung, Bong Hyun

2009-11-01

This study describes the development of near-infrared optical imaging technology for the monitoring of immunotherapeutic cell-based cancer therapy using natural killer (NK) cells labeled with fluorescent nanocrystals. Although NK cell-based immunotherapeutic strategies have drawn interest as potent preclinical or clinical methods of cancer therapy, there are few reports documenting the molecular imaging of NK cell-based cancer therapy, primarily due to the difficulty of labeling of NK cells with imaging probes. Human natural killer cells (NK92MI) were labeled with anti-human CD56 antibody-coated quantum dots (QD705) for fluorescence imaging. FACS analysis showed that the NK92MI cells labeled with anti-human CD56 antibody-coated QD705 have no effect on the cell viability. The effect of anti-human CD56 antibody-coated QD705 labeling on the NK92MI cell function was investigated by measuring interferon gamma (IFN- γ) production and cytolytic activity. Finally, the NK92MI cells labeled with anti-human CD56 antibody-coated QD705 showed a therapeutic effect similar to that of unlabeled NK92MI cells. Images of intratumorally injected NK92MI cells labeled with anti-human CD56 antibody-coated could be acquired using near-infrared optical imaging both in vivo and in vitro. This result demonstrates that the immunotherapeutic cells labeled with fluorescent nanocrystals can be a versatile platform for the effective tracking of injected therapeutic cells using optical imaging technology, which is very important in cell-based cancer therapies.

Advancements of labelled radio-pharmaceutics imaging with the PIM-MPGD

NASA Astrophysics Data System (ADS)

Donnard, J.; Arlicot, N.; Berny, R.; Carduner, H.; Leray, P.; Morteau, E.; Servagent, N.; Thers, D.

2009-11-01

The Beta autoradiography is widely used in pharmacology or in biological fields to study the response of an organism to a certain kind of molecule. The image of the distribution is processed by studying the concentration of the radioactivity into different organs. We report on the development of an integrated apparatus based on a PIM device (Parallel Ionization Multiplier) able to process the image of 10 microscope slides at the same time over an area of 18*18 cm2. Thanks to a vacuum pump and a regulation gas circuit, 5 minutes is sufficient to begin an acquisition. All the electronics and the gas distribution are included in the structure leading to a transportable device. Special software has been developed to process data in real time with image visualization. Biological samples can be labelled with β emitters of low energy like 3H/14C or Auger electrons of 125I/99mTc. The measured spatial resolution is 30 μm in 3H and the trigger and the charge rate are constant over more than 6 days of acquisition showing good stability of the device. Moreover, collaboration with doctors and biologists of INSERM (National Institute for Medical Research in France) has started in order to demonstrate that MPGD's can be easily proposed outside a physics laboratory.

Coherent Raman Scattering Microscopy for Evaluation of Head and Neck Carcinoma.

PubMed

Hoesli, Rebecca C; Orringer, Daniel A; McHugh, Jonathan B; Spector, Matthew E

2017-09-01

Objective We aim to describe a novel, label-free, real-time imaging technique, coherent Raman scattering (CRS) microscopy, for histopathological evaluation of head and neck cancer. We evaluated the ability of CRS microscopy to delineate between tumor and nonneoplastic tissue in tissue samples from patients with head and neck cancer. Study Design Prospective case series. Setting Tertiary care medical center. Subjects and Methods Patients eligible were surgical candidates with biopsy-proven, previously untreated head and neck carcinoma and were consented preoperatively for participation in this study. Tissue was collected from 50 patients, and after confirmation of tumor and normal specimens by hematoxylin and eosin (H&E), there were 42 tumor samples and 42 normal adjacent controls. Results There were 42 confirmed carcinoma specimens on H&E, and CRS microscopy identified 37 as carcinoma. Of the 42 normal specimens, CRS microscopy identified 40 as normal. This resulted in a sensitivity of 88.1% and specificity of 95.2% in distinguishing between neoplastic and nonneoplastic images. Conclusion CRS microscopy is a unique label-free imaging technique that can provide rapid, high-resolution images and can accurately determine the presence of head and neck carcinoma. This holds potential for implementation into standard practice, allowing frozen margin evaluation even at institutions without a histopathology laboratory.

Weakly supervised image semantic segmentation based on clustering superpixels

NASA Astrophysics Data System (ADS)

Yan, Xiong; Liu, Xiaohua

2018-04-01

In this paper, we propose an image semantic segmentation model which is trained from image-level labeled images. The proposed model starts with superpixel segmenting, and features of the superpixels are extracted by trained CNN. We introduce a superpixel-based graph followed by applying the graph partition method to group correlated superpixels into clusters. For the acquisition of inter-label correlations between the image-level labels in dataset, we not only utilize label co-occurrence statistics but also exploit visual contextual cues simultaneously. At last, we formulate the task of mapping appropriate image-level labels to the detected clusters as a problem of convex minimization. Experimental results on MSRC-21 dataset and LableMe dataset show that the proposed method has a better performance than most of the weakly supervised methods and is even comparable to fully supervised methods.

In vivo histology: optical biopsies with chemical contrast using clinical multiphoton/coherent anti-Stokes Raman scattering tomography

NASA Astrophysics Data System (ADS)

Weinigel, M.; Breunig, H. G.; Kellner-Höfer, M.; Bückle, R.; Darvin, M. E.; Klemp, M.; Lademann, J.; König, K.

2014-05-01

The majority of existing coherent anti-Stokes Raman scattering (CARS) imaging systems are still huge and complicated laboratory systems and neither compact nor user-friendly nor mobile medically certified CARS systems. We have developed a new flexible multiphoton/CARS tomograph for imaging in a clinical environment. The system offers exceptional 360° flexibility with a very stable setup and enables label free ‘in vivo histology’ with chemical contrast within seconds. It can be completely operated by briefly trained non-laser experts. The imaging capability and flexibility of the novel in vivo tomograph are shown on optical biopsies with subcellular resolution and chemical contrast of patients suffering from psoriasis and squamous cell carcinoma.

One-to-one quantum dot-labeled single long DNA probes.

PubMed

He, Shibin; Huang, Bi-Hai; Tan, Junjun; Luo, Qing-Ying; Lin, Yi; Li, Jun; Hu, Yong; Zhang, Lu; Yan, Shihan; Zhang, Qi; Pang, Dai-Wen; Li, Lijia

2011-08-01

Quantum dots (QDs) have been received most attention due to their unique properties. Constructing QDs conjugated with certain number of biomolecules is considered as one of the most important research goals in nanobiotechnology. In this study, we report polymerase chain reaction (PCR) amplification of primer oligonucleotides bound to QDs, termed as QD-based PCR. Characterization of QD-based PCR products by gel electrophoresis and atomic force microscopy showed that QD-labeled long DNA strands were synthesized and only a single long DNA strand was conjugated with a QD. The QD-based PCR products still kept fluorescence properties. Moreover, the one-to-one QD-labeled long DNA conjugates as probes could detect a single-copy gene on maize chromosomes by fluorescence in situ hybridization. Labeling a single QD to a single long DNA will make detection of small single-copy DNA fragments, quantitative detection and single molecule imaging come true by nanotechnology, and it will promote medical diagnosis and basic biological research as well as nano-material fabrication. Copyright © 2011 Elsevier Ltd. All rights reserved.

HCP: A Flexible CNN Framework for Multi-label Image Classification.

PubMed

Wei, Yunchao; Xia, Wei; Lin, Min; Huang, Junshi; Ni, Bingbing; Dong, Jian; Zhao, Yao; Yan, Shuicheng

2015-10-26

Convolutional Neural Network (CNN) has demonstrated promising performance in single-label image classification tasks. However, how CNN best copes with multi-label images still remains an open problem, mainly due to the complex underlying object layouts and insufficient multi-label training images. In this work, we propose a flexible deep CNN infrastructure, called Hypotheses-CNN-Pooling (HCP), where an arbitrary number of object segment hypotheses are taken as the inputs, then a shared CNN is connected with each hypothesis, and finally the CNN output results from different hypotheses are aggregated with max pooling to produce the ultimate multi-label predictions. Some unique characteristics of this flexible deep CNN infrastructure include: 1) no ground-truth bounding box information is required for training; 2) the whole HCP infrastructure is robust to possibly noisy and/or redundant hypotheses; 3) the shared CNN is flexible and can be well pre-trained with a large-scale single-label image dataset, e.g., ImageNet; and 4) it may naturally output multi-label prediction results. Experimental results on Pascal VOC 2007 and VOC 2012 multi-label image datasets well demonstrate the superiority of the proposed HCP infrastructure over other state-of-the-arts. In particular, the mAP reaches 90.5% by HCP only and 93.2% after the fusion with our complementary result in [44] based on hand-crafted features on the VOC 2012 dataset.

Contour-Driven Atlas-Based Segmentation

PubMed Central

Wachinger, Christian; Fritscher, Karl; Sharp, Greg; Golland, Polina

2016-01-01

We propose new methods for automatic segmentation of images based on an atlas of manually labeled scans and contours in the image. First, we introduce a Bayesian framework for creating initial label maps from manually annotated training images. Within this framework, we model various registration- and patch-based segmentation techniques by changing the deformation field prior. Second, we perform contour-driven regression on the created label maps to refine the segmentation. Image contours and image parcellations give rise to non-stationary kernel functions that model the relationship between image locations. Setting the kernel to the covariance function in a Gaussian process establishes a distribution over label maps supported by image structures. Maximum a posteriori estimation of the distribution over label maps conditioned on the outcome of the atlas-based segmentation yields the refined segmentation. We evaluate the segmentation in two clinical applications: the segmentation of parotid glands in head and neck CT scans and the segmentation of the left atrium in cardiac MR angiography images. PMID:26068202

Methods and applications of positron-based medical imaging

NASA Astrophysics Data System (ADS)

Herzog, H.

2007-02-01

Positron emission tomography (PET) is a diagnostic imaging method to examine metabolic functions and their disorders. Dedicated ring systems of scintillation detectors measure the 511 keV γ-radiation produced in the course of the positron emission from radiolabelled metabolically active molecules. A great number of radiopharmaceuticals labelled with 11C, 13N, 15O, or 18F positron emitters have been applied both for research and clinical purposes in neurology, cardiology and oncology. The recent success of PET with rapidly increasing installations is mainly based on the use of [ 18F]fluorodeoxyglucose (FDG) in oncology where it is most useful to localize primary tumours and their metastases.

Rapid Synthesis of 68Ga-labeled macroaggregated human serum albumin (MAA) for routine application in perfusion imaging using PET/CT.

PubMed

Mueller, D; Kulkarni, Harshad; Baum, Richard P; Odparlik, Andreas

2017-04-01

99m Tc-labeled MAA is commonly used for single photon emission computed tomography SPECT. In contrast, positron emission tomography/CT (PET/CT) delivers images with significantly higher resolution. The generator produced radionuclide 68 Ga is widely used for PET/CT imaging agents and 68 Ga-labeled MAA represents an attractive alternative to 99m Tc-labeled MAA. We report a simple and rapid NaCl based labeling procedure for the labeling of MAA with 68 Ga using a commercially available MAA labeling kit for 99m Tc. The procedure delivers 68 Ga-labeled MAA with a high specific activity and a high labeling efficiency (>99%). The synthesis does not require a final step of separation or the use of organic solvents. Copyright © 2017 Elsevier Ltd. All rights reserved.

21 CFR 801.6 - Medical devices; misleading statements.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Medical devices; misleading statements. 801.6 Section 801.6 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES LABELING General Labeling Provisions § 801.6 Medical devices; misleading...

21 CFR 801.6 - Medical devices; misleading statements.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Medical devices; misleading statements. 801.6 Section 801.6 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES LABELING General Labeling Provisions § 801.6 Medical devices; misleading...

Deep neural ensemble for retinal vessel segmentation in fundus images towards achieving label-free angiography.

PubMed

Lahiri, A; Roy, Abhijit Guha; Sheet, Debdoot; Biswas, Prabir Kumar

2016-08-01

Automated segmentation of retinal blood vessels in label-free fundus images entails a pivotal role in computed aided diagnosis of ophthalmic pathologies, viz., diabetic retinopathy, hypertensive disorders and cardiovascular diseases. The challenge remains active in medical image analysis research due to varied distribution of blood vessels, which manifest variations in their dimensions of physical appearance against a noisy background. In this paper we formulate the segmentation challenge as a classification task. Specifically, we employ unsupervised hierarchical feature learning using ensemble of two level of sparsely trained denoised stacked autoencoder. First level training with bootstrap samples ensures decoupling and second level ensemble formed by different network architectures ensures architectural revision. We show that ensemble training of auto-encoders fosters diversity in learning dictionary of visual kernels for vessel segmentation. SoftMax classifier is used for fine tuning each member autoencoder and multiple strategies are explored for 2-level fusion of ensemble members. On DRIVE dataset, we achieve maximum average accuracy of 95.33% with an impressively low standard deviation of 0.003 and Kappa agreement coefficient of 0.708. Comparison with other major algorithms substantiates the high efficacy of our model.

Specific in vivo labeling with GFP retroviruses, lentiviruses, and adenoviruses for imaging

NASA Astrophysics Data System (ADS)

Hoffman, Robert M.; Kishimoto, Hiroyuki; Fujiwara, Toshiyoshi

2008-02-01

Fluorescent proteins have revolutionized the field of imaging. Our laboratory pioneered in vivo imaging with fluorescent proteins. Fluorescent proteins have enabled imaging at the subcellular level in mice. We review here the use of different vectors carrying fluorescent proteins to selectively label normal and tumor tissue in vivo. We show that a GFP retrovirus and telomerase-driven GFP adenovirus can selectively label tumors in mice. We also show that a GFP lentivirus can selectively label the liver in mice. The practical application of these results are discussed.

Image annotation based on positive-negative instances learning

NASA Astrophysics Data System (ADS)

Zhang, Kai; Hu, Jiwei; Liu, Quan; Lou, Ping

2017-07-01

Automatic image annotation is now a tough task in computer vision, the main sense of this tech is to deal with managing the massive image on the Internet and assisting intelligent retrieval. This paper designs a new image annotation model based on visual bag of words, using the low level features like color and texture information as well as mid-level feature as SIFT, and mixture the pic2pic, label2pic and label2label correlation to measure the correlation degree of labels and images. We aim to prune the specific features for each single label and formalize the annotation task as a learning process base on Positive-Negative Instances Learning. Experiments are performed using the Corel5K Dataset, and provide a quite promising result when comparing with other existing methods.

Molecular imaging in stem cell-based therapies of cardiac diseases.

PubMed

Li, Xiang; Hacker, Marcus

2017-10-01

In the past 15years, despite that regenerative medicine has shown great potential for cardiovascular diseases, the outcome and safety of stem cell transplantation has shown controversial results in the published literature. Medical imaging might be useful for monitoring and quantifying transplanted cells within the heart and to serially characterize the effects of stem cell therapy of the myocardium. From the multiple available noninvasive imaging techniques, magnetic resonance imaging and nuclear imaging by positron (PET) or single photon emission computer tomography (SPECT) are the most used clinical approaches to follow the fate of transplanted stem cells in vivo. In this article, we provide a review on the role of different noninvasive imaging modalities and discuss their advantages and disadvantages. We focus on the different in-vivo labeling and reporter gene imaging strategies for stem cell tracking as well as the concept and reliability to use imaging parameters as noninvasive surrogate endpoints for the evaluation of the post-therapeutic outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

Tumor propagation model using generalized hidden Markov model

NASA Astrophysics Data System (ADS)

Park, Sun Young; Sargent, Dustin

2017-02-01

Tumor tracking and progression analysis using medical images is a crucial task for physicians to provide accurate and efficient treatment plans, and monitor treatment response. Tumor progression is tracked by manual measurement of tumor growth performed by radiologists. Several methods have been proposed to automate these measurements with segmentation, but many current algorithms are confounded by attached organs and vessels. To address this problem, we present a new generalized tumor propagation model considering time-series prior images and local anatomical features using a Hierarchical Hidden Markov model (HMM) for tumor tracking. First, we apply the multi-atlas segmentation technique to identify organs/sub-organs using pre-labeled atlases. Second, we apply a semi-automatic direct 3D segmentation method to label the initial boundary between the lesion and neighboring structures. Third, we detect vessels in the ROI surrounding the lesion. Finally, we apply the propagation model with the labeled organs and vessels to accurately segment and measure the target lesion. The algorithm has been designed in a general way to be applicable to various body parts and modalities. In this paper, we evaluate the proposed algorithm on lung and lung nodule segmentation and tracking. We report the algorithm's performance by comparing the longest diameter and nodule volumes using the FDA lung Phantom data and a clinical dataset.

Designing a strategy to promote safe, innovative off-label use of medications.

PubMed

Ansani, Nicole; Sirio, Carl; Smitherman, Thomas; Fedutes-Henderson, Bethany; Skledar, Susan; Weber, Robert J; Zgheib, Nathalie; Branch, Robert

2006-01-01

Innovative off-label medication use (defined as prescribing with reasonable rationale for use, but insufficient evidence to allay safety, efficacy, and cost-effectiveness concerns, yet is not clinical research) is common practice and provides challenges to ensuring high-quality health care and patient safety. This article describes a strategy to promote policy and standardization of innovative off-label medication use, ensure oversight of patient safety, and prospectively assess efficacy. A multidisciplinary group developed a policy and process to regulate innovative off-label medication use that standardizes formulary review, maximizes peer expertise input, and minimizes institution liability by evaluating the effectiveness of use, promoting evidence-based practices, and ensuring ethical obligations to patients and society. This strategy has been implemented through institutional staff structure. The review process balances benefits/risks for biologically plausible therapy that lacks rigorous data support. The authors' strategy illustrates collaboration that enables a priori consideration for innovative off-label medication use while providing safety surveillance and outcomes monitoring.

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

Hoff, M; Rane-Levandovsky, S; Andre, J

Purpose: Traditional arterial spin labeling (ASL) acquisitions with echo planar imaging (EPI) readouts suffer from image distortion due to susceptibility effects, compromising ASL’s ability to accurately quantify cerebral blood flow (CBF) and assess disease-specific patterns associated with CBF abnormalities. Phase labeling for additional coordinate encoding (PLACE) can remove image distortion; our goal is to apply PLACE to improve the quantitative accuracy of ASL CBF in humans. Methods: Four subjects were imaged on a 3T Philips Ingenia scanner using a 16-channel receive coil with a 21/21/10cm (frequency/phase/slice direction) field-of-view. An ASL sequence with a pseudo-continuous ASL (pCASL) labeling scheme was employedmore » to acquire thirty dynamics of single-shot EPI data, with control and label datasets for all dynamics, and PLACE gradients applied on odd dynamics. Parameters included a post-labeling delay = 2s, label duration = 1.8s, flip angle = 90°, TR/TE = 5000/23.5ms, and 2.9/2.9/5.0mm (frequency/phase/slice direction) voxel size. “M0” EPI-reference images and T1-weighted spin-echo images with 0.8/1.0/3.3mm (frequency/phase/slice directions) voxel size were also acquired. Complex conjugate image products of pCASL odd and even dynamics were formed, a linear phase ramp applied, and data expanded and smoothed. Data phase was extracted to map control, label, and M0 magnitude image pixels to their undistorted locations, and images were rebinned to original size. All images were corrected for motion artifacts in FSL 5.0. pCASL images were registered to M0 images, and control and label images were subtracted to compute quantitative CBF maps. Results: pCASL image and CBF map distortions were removed by PLACE in all subjects. Corrected images conformed well to the anatomical T1-weighted reference image, and deviations in corrected CBF maps were evident. Conclusion: Eliminating pCASL distortion with PLACE can improve CBF quantification accuracy using minimal pulse sequence modifications and no additional scan time, improving ASL’s clinical applicability.« less

Real-time ultrasound transducer localization in fluoroscopy images by transfer learning from synthetic training data.

PubMed

Heimann, Tobias; Mountney, Peter; John, Matthias; Ionasec, Razvan

2014-12-01

The fusion of image data from trans-esophageal echography (TEE) and X-ray fluoroscopy is attracting increasing interest in minimally-invasive treatment of structural heart disease. In order to calculate the needed transformation between both imaging systems, we employ a discriminative learning (DL) based approach to localize the TEE transducer in X-ray images. The successful application of DL methods is strongly dependent on the available training data, which entails three challenges: (1) the transducer can move with six degrees of freedom meaning it requires a large number of images to represent its appearance, (2) manual labeling is time consuming, and (3) manual labeling has inherent errors. This paper proposes to generate the required training data automatically from a single volumetric image of the transducer. In order to adapt this system to real X-ray data, we use unlabeled fluoroscopy images to estimate differences in feature space density and correct covariate shift by instance weighting. Two approaches for instance weighting, probabilistic classification and Kullback-Leibler importance estimation (KLIEP), are evaluated for different stages of the proposed DL pipeline. An analysis on more than 1900 images reveals that our approach reduces detection failures from 7.3% in cross validation on the test set to zero and improves the localization error from 1.5 to 0.8mm. Due to the automatic generation of training data, the proposed system is highly flexible and can be adapted to any medical device with minimal efforts. Copyright © 2014 Elsevier B.V. All rights reserved.

Diagnostic Accuracy of Lumbosacral Spine Magnetic Resonance Image Reading by Chiropractors, Chiropractic Radiologists, and Medical Radiologists.

PubMed

de Zoete, Annemarie; Ostelo, Raymond; Knol, Dirk L; Algra, Paul R; Wilmink, Jan T; van Tulder, Maurits W

2015-06-01

A cross-sectional diagnostic accuracy study was conducted in 2 sessions. It is important to know whether it is possible to accurately detect "specific findings" on lumbosacral magnetic resonance (MR) images and whether the results of different observers are comparable. Health care providers frequently use magnetic resonance imaging in the diagnostic process of patients with low back pain. The use of MR scans is increasing. This leads to an increase in costs and to an increase in risk of inaccurately labeling patients with an anatomical diagnosis that might not be the actual cause of symptoms. A set of 300 blinded MR images was read by medical radiologists, chiropractors, and chiropractic radiologists in 2 sessions. Each assessor read 100 scans in round 1 and 50 scans in round 2. The reference test was an expert panel.For all analyses, the magnetic resonance imaging findings were dichotomized into "specific findings" or "no specific findings." For the agreement, percentage agreement and κ values were calculated and for validity, sensitivity, and specificity. Sensitivity analysis was done for classifications A and B (prevalence of 31% and 57%, respectively). The intraobserver κ values for chiropractors, chiropractic radiologists, and medical radiologists were 0.46, 0.49, and 0.69 for A and 0.55, 0.75, and 0.64 for B, respectively.The interobserver κ values were lowest for chiropractors (0.28 for A, 0.37 for B) and highest for chiropractic radiologists (0.50 for A, 0.49 for B).The sensitivities of the medical radiologists, chiropractors, and chiropractic radiologists were 0.62, 0.71, and 0.75 for A and 0.70, 0.74, 0.84 for B, respectively.The specificities of medical radiologists, chiropractic radiologists, and chiropractors were 0.82, 0.77, and 0.70 for A and 0.74, 0.52, and 0.61 for B, respectively. Agreement and validity of MR image readings of chiropractors and chiropractic and medical radiologists is modest at best. This study supports recommendations in clinical guidelines against routine use of magnetic resonance imaging in patients with low back pain. 3.

Sample Preparation for Mass Spectrometry Imaging of Plant Tissues: A Review

PubMed Central

Dong, Yonghui; Li, Bin; Malitsky, Sergey; Rogachev, Ilana; Aharoni, Asaph; Kaftan, Filip; Svatoš, Aleš; Franceschi, Pietro

2016-01-01

Mass spectrometry imaging (MSI) is a mass spectrometry based molecular ion imaging technique. It provides the means for ascertaining the spatial distribution of a large variety of analytes directly on tissue sample surfaces without any labeling or staining agents. These advantages make it an attractive molecular histology tool in medical, pharmaceutical, and biological research. Likewise, MSI has started gaining popularity in plant sciences; yet, information regarding sample preparation methods for plant tissues is still limited. Sample preparation is a crucial step that is directly associated with the quality and authenticity of the imaging results, it therefore demands in-depth studies based on the characteristics of plant samples. In this review, a sample preparation pipeline is discussed in detail and illustrated through selected practical examples. In particular, special concerns regarding sample preparation for plant imaging are critically evaluated. Finally, the applications of MSI techniques in plants are reviewed according to different classes of plant metabolites. PMID:26904042

Presenting numeric information with percentages and descriptive risk labels: A randomized trial

PubMed Central

Sinayev, Aleksandr; Peters, Ellen; Tusler, Martin; Fraenkel, Liana

2015-01-01

Background Previous research demonstrated that providing (vs. not providing) numeric information about medications’ adverse effects (AEs) increased comprehension and willingness to use medication, but left open the question about which numeric format is best. Objective To determine which of four tested formats (percentage, frequency, percentage+risk label, frequency+risk label) maximizes comprehension and willingness to use medication across age and numeracy levels. Design In a cross-sectional internet survey (N=368; American Life Panel, 5/15/08–6/18/08), respondents were presented with a hypothetical prescription medication for high cholesterol. AE likelihoods were described using one of four tested formats. Main outcome measures were risk comprehension (ability to identify AE likelihood from a table) and willingness to use the medication (7-point scale; not likely=0, very likely=6). Results The percentage+risk label format resulted in the highest comprehension and willingness to use the medication compared to the other three formats (mean comprehension in percentage + risk label format=95% vs mean across the other three formats = 81%; mean willingness= 3.3 vs 2.95, respectively). Comprehension differences between percentage and frequency formats were smaller among the less numerate. Willingness to use medication depended less on age and numeracy when labels were used. Limitations Generalizability is limited by use of a sample that was older, more educated, and better off financially than national averages. Conclusions Providing numeric AE-likelihood information in a percentage format with risk labels is likely to increase risk comprehension and willingness to use a medication compared to other numeric formats. PMID:25952743

Deep learning of the sectional appearances of 3D CT images for anatomical structure segmentation based on an FCN voting method.

PubMed

Zhou, Xiangrong; Takayama, Ryosuke; Wang, Song; Hara, Takeshi; Fujita, Hiroshi

2017-10-01

We propose a single network trained by pixel-to-label deep learning to address the general issue of automatic multiple organ segmentation in three-dimensional (3D) computed tomography (CT) images. Our method can be described as a voxel-wise multiple-class classification scheme for automatically assigning labels to each pixel/voxel in a 2D/3D CT image. We simplify the segmentation algorithms of anatomical structures (including multiple organs) in a CT image (generally in 3D) to a majority voting scheme over the semantic segmentation of multiple 2D slices drawn from different viewpoints with redundancy. The proposed method inherits the spirit of fully convolutional networks (FCNs) that consist of "convolution" and "deconvolution" layers for 2D semantic image segmentation, and expands the core structure with 3D-2D-3D transformations to adapt to 3D CT image segmentation. All parameters in the proposed network are trained pixel-to-label from a small number of CT cases with human annotations as the ground truth. The proposed network naturally fulfills the requirements of multiple organ segmentations in CT cases of different sizes that cover arbitrary scan regions without any adjustment. The proposed network was trained and validated using the simultaneous segmentation of 19 anatomical structures in the human torso, including 17 major organs and two special regions (lumen and content inside of stomach). Some of these structures have never been reported in previous research on CT segmentation. A database consisting of 240 (95% for training and 5% for testing) 3D CT scans, together with their manually annotated ground-truth segmentations, was used in our experiments. The results show that the 19 structures of interest were segmented with acceptable accuracy (88.1% and 87.9% voxels in the training and testing datasets, respectively, were labeled correctly) against the ground truth. We propose a single network based on pixel-to-label deep learning to address the challenging issue of anatomical structure segmentation in 3D CT cases. The novelty of this work is the policy of deep learning of the different 2D sectional appearances of 3D anatomical structures for CT cases and the majority voting of the 3D segmentation results from multiple crossed 2D sections to achieve availability and reliability with better efficiency, generality, and flexibility than conventional segmentation methods, which must be guided by human expertise. © 2017 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

21 CFR 862.2050 - General purpose laboratory equipment labeled or promoted for a specific medical use.

Code of Federal Regulations, 2012 CFR

2012-04-01

..., DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL... human body and that is labeled or promoted for a specific medical use. (b) Classification. Class I...

21 CFR 862.2050 - General purpose laboratory equipment labeled or promoted for a specific medical use.

Code of Federal Regulations, 2014 CFR

2014-04-01

..., DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL... human body and that is labeled or promoted for a specific medical use. (b) Classification. Class I...

21 CFR 862.2050 - General purpose laboratory equipment labeled or promoted for a specific medical use.

Code of Federal Regulations, 2013 CFR

2013-04-01

..., DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL... human body and that is labeled or promoted for a specific medical use. (b) Classification. Class I...

21 CFR 862.2050 - General purpose laboratory equipment labeled or promoted for a specific medical use.

Code of Federal Regulations, 2010 CFR

2010-04-01

... human body and that is labeled or promoted for a specific medical use. (b) Classification. Class I..., DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL...

21 CFR 862.2050 - General purpose laboratory equipment labeled or promoted for a specific medical use.

Code of Federal Regulations, 2011 CFR

2011-04-01

... human body and that is labeled or promoted for a specific medical use. (b) Classification. Class I..., DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES CLINICAL CHEMISTRY AND CLINICAL...

First performance evaluation of software for automatic segmentation, labeling and reformation of anatomical aligned axial images of the thoracolumbar spine at CT.

PubMed

Scholtz, Jan-Erik; Wichmann, Julian L; Kaup, Moritz; Fischer, Sebastian; Kerl, J Matthias; Lehnert, Thomas; Vogl, Thomas J; Bauer, Ralf W

2015-03-01

To evaluate software for automatic segmentation, labeling and reformation of anatomical aligned axial images of the thoracolumbar spine on CT in terms of accuracy, potential for time savings and workflow improvement. 77 patients (28 women, 49 men, mean age 65.3±14.4 years) with known or suspected spinal disorders (degenerative spine disease n=32; disc herniation n=36; traumatic vertebral fractures n=9) underwent 64-slice MDCT with thin-slab reconstruction. Time for automatic labeling of the thoracolumbar spine and reconstruction of double-angulated axial images of the pathological vertebrae was compared with manually performed reconstruction of anatomical aligned axial images. Reformatted images of both reconstruction methods were assessed by two observers regarding accuracy of symmetric depiction of anatomical structures. In 33 cases double-angulated axial images were created in 1 vertebra, in 28 cases in 2 vertebrae and in 16 cases in 3 vertebrae. Correct automatic labeling was achieved in 72 of 77 patients (93.5%). Errors could be manually corrected in 4 cases. Automatic labeling required 1min in average. In cases where anatomical aligned axial images of 1 vertebra were created, reconstructions made by hand were significantly faster (p<0.05). Automatic reconstruction was time-saving in cases of 2 and more vertebrae (p<0.05). Both reconstruction methods revealed good image quality with excellent inter-observer agreement. The evaluated software for automatic labeling and anatomically aligned, double-angulated axial image reconstruction of the thoracolumbar spine on CT is time-saving when reconstructions of 2 and more vertebrae are performed. Checking results of automatic labeling is necessary to prevent errors in labeling. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A low-cost method for visible fluorescence imaging.

PubMed

Tarver, Crissy L; Pusey, Marc

2017-12-01

A wide variety of crystallization solutions are screened to establish conditions that promote the growth of a diffraction-quality crystal. Screening these conditions requires the assessment of many crystallization plates for the presence of crystals. Automated systems for screening and imaging are very expensive. A simple approach to imaging trace fluorescently labeled protein crystals in crystallization plates has been devised, and can be implemented at a cost as low as $50. The proteins β-lactoglobulin B, trypsin and purified concanavalin A (ConA) were trace fluorescently labeled using three different fluorescent probes: Cascade Yellow (CY), Carboxyrhodamine 6G (CR) and Pacific Blue (PB). A crystallization screening plate was set up using β-lactoglobulin B labeled with CR, trypsin labeled with CY, ConA labeled with each probe, and a mixture consisting of 50% PB-labeled ConA and 50% CR-labeled ConA. The wells of these plates were imaged using a commercially available macro-imaging lens attachment for smart devices that have a camera. Several types of macro lens attachments were tested with smartphones and tablets. Images with the highest quality were obtained with an iPhone 6S and an AUKEY Ora 10× macro lens. Depending upon the fluorescent probe employed and its Stokes shift, a light-emitting diode or a laser diode was used for excitation. An emission filter was used for the imaging of protein crystals labeled with CR and crystals with two-color fluorescence. This approach can also be used with microscopy systems commonly used to observe crystallization plates.

Fruit-related terms and images on food packages and advertisements affect children's perceptions of foods' fruit content.

PubMed

Heller, Rebecca; Martin-Biggers, Jennifer; Berhaupt-Glickstein, Amanda; Quick, Virginia; Byrd-Bredbenner, Carol

2015-10-01

To determine whether food label information and advertisements for foods containing no fruit cause children to have a false impression of the foods' fruit content. In the food label condition, a trained researcher showed each child sixteen different food label photographs depicting front-of-food label packages that varied with regard to fruit content (i.e. real fruit v. sham fruit) and label elements. In the food advertisement condition, children viewed sixteen, 30 s television food advertisements with similar fruit content and label elements as in the food label condition. After viewing each food label and advertisement, children responded to the question 'Did they use fruit to make this?' with responses of yes, no or don't know. Schools, day-care centres, after-school programmes and other community groups. Children aged 4-7 years. In the food label condition, χ 2 analysis of within fruit content variation differences indicated children (n 58; mean age 4·2 years) were significantly more accurate in identifying real fruit foods as the label's informational load increased and were least accurate when neither a fruit name nor an image was on the label. Children (n 49; mean age 5·4 years) in the food advertisement condition were more likely to identify real fruit foods when advertisements had fruit images compared with when no image was included, while fruit images in advertisements for sham fruit foods significantly reduced accuracy of responses. Findings suggest that labels and advertisements for sham fruit foods mislead children with regard to the food's real fruit content.

NEED FOR HARMONIZATION OF LABELING OF MEDICAL DEVICES: A REVIEW

PubMed Central

Songara, Raiendra K.; Sharma, Ganesh N.; Gupta, Vipul K.; Gupta, Promila

2010-01-01

Medical device labeling is any information associated with a device targeted to the patient or lay caregiver. It is intended to help assure that the device is used safely and effectively. Medical device labeling is supplied in many formats, for example, as patient brochures, patient leaflets, user manuals, and videotapes. The European commission has discussed a series of agreements with third countries, Australia, New Zealand, USA, Canada, Japan and Eastern European countries wishing to join the EU, concerning the mutual acceptance of inspection bodies, proof of conformity in connection with medical devices. Device labeling is exceedingly difficult for manufacturers for many reasons like regulations from government bodies to ensure compliance, increased competent authority surveillance, increased audits and language requirements. PMID:22247840

A review of performance of near-infrared fluorescence imaging devices used in clinical studies

PubMed Central

Zhu, B

2015-01-01

Near-infrared fluorescence (NIRF) molecular imaging holds great promise as a new “point-of-care” medical imaging modality that can potentially provide the sensitivity of nuclear medicine techniques, but without the radioactivity that can otherwise place limitations of usage. Recently, NIRF imaging devices of a variety of designs have emerged in the market and in investigational clinical studies using indocyanine green (ICG) as a non-targeting NIRF contrast agent to demark the blood and lymphatic vasculatures both non-invasively and intraoperatively. Approved in the USA since 1956 for intravenous administration, ICG has been more recently used off label in intradermal or subcutaneous administrations for fluorescence imaging of the lymphatic vasculature and lymph nodes. Herein, we summarize the devices of a variety of designs, summarize their performance in lymphatic imaging in a tabular format and comment on necessary efforts to develop standards for device performance to compare and use these emerging devices in future, NIRF molecular imaging studies. PMID:25410320

A digital interactive human brain atlas based on Chinese visible human datasets for anatomy teaching.

PubMed

Li, Qiyu; Ran, Xu; Zhang, Shaoxiang; Tan, Liwen; Qiu, Mingguo

2014-01-01

As we know, the human brain is one of the most complicated organs in the human body, which is the key and difficult point in neuroanatomy and sectional anatomy teaching. With the rapid development and extensive application of imaging technology in clinical diagnosis, doctors are facing higher and higher requirement on their anatomy knowledge. Thus, to cultivate medical students to meet the needs of medical development today and to improve their ability to read and understand radiographic images have become urgent challenges for the medical teachers. In this context, we developed a digital interactive human brain atlas based on the Chinese visible human datasets for anatomy teaching (available for free download from http://www.chinesevisiblehuman.com/down/DHBA.rar). The atlas simultaneously provides views in all 3 primary planes of section. The main structures of the human brain have been anatomically labeled in all 3 views. It is potentially useful for anatomy browsing, user self-testing, and automatic student assessment. In a word, it is interactive, 3D, user friendly, and free of charge, which can provide a new, intuitive means for anatomy teaching.

101 Labeled Brain Images and a Consistent Human Cortical Labeling Protocol

PubMed Central

Klein, Arno; Tourville, Jason

2012-01-01

We introduce the Mindboggle-101 dataset, the largest and most complete set of free, publicly accessible, manually labeled human brain images. To manually label the macroscopic anatomy in magnetic resonance images of 101 healthy participants, we created a new cortical labeling protocol that relies on robust anatomical landmarks and minimal manual edits after initialization with automated labels. The “Desikan–Killiany–Tourville” (DKT) protocol is intended to improve the ease, consistency, and accuracy of labeling human cortical areas. Given how difficult it is to label brains, the Mindboggle-101 dataset is intended to serve as brain atlases for use in labeling other brains, as a normative dataset to establish morphometric variation in a healthy population for comparison against clinical populations, and contribute to the development, training, testing, and evaluation of automated registration and labeling algorithms. To this end, we also introduce benchmarks for the evaluation of such algorithms by comparing our manual labels with labels automatically generated by probabilistic and multi-atlas registration-based approaches. All data and related software and updated information are available on the http://mindboggle.info/data website. PMID:23227001

Automatic multi-label annotation of abdominal CT images using CBIR

NASA Astrophysics Data System (ADS)

Xue, Zhiyun; Antani, Sameer; Long, L. Rodney; Thoma, George R.

2017-03-01

We present a technique to annotate multiple organs shown in 2-D abdominal/pelvic CT images using CBIR. This annotation task is motivated by our research interests in visual question-answering (VQA). We aim to apply results from this effort in Open-iSM, a multimodal biomedical search engine developed by the National Library of Medicine (NLM). Understanding visual content of biomedical images is a necessary step for VQA. Though sufficient annotational information about an image may be available in related textual metadata, not all may be useful as descriptive tags, particularly for anatomy on the image. In this paper, we develop and evaluate a multi-label image annotation method using CBIR. We evaluate our method on two 2-D CT image datasets we generated from 3-D volumetric data obtained from a multi-organ segmentation challenge hosted in MICCAI 2015. Shape and spatial layout information is used to encode visual characteristics of the anatomy. We adapt a weighted voting scheme to assign multiple labels to the query image by combining the labels of the images identified as similar by the method. Key parameters that may affect the annotation performance, such as the number of images used in the label voting and the threshold for excluding labels that have low weights, are studied. The method proposes a coarse-to-fine retrieval strategy which integrates the classification with the nearest-neighbor search. Results from our evaluation (using the MICCAI CT image datasets as well as figures from Open-i) are presented.

Labeling of macrophages using bacterial magnetosomes and their characterization by magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Hartung, Annegret; Lisy, Marcus R.; Herrmann, Karl-Heinz; Hilger, Ingrid; Schüler, Dirk; Lang, Claus; Bellemann, Matthias E.; Kaiser, Werner A.; Reichenbach, Jürgen R.

2007-04-01

This work investigated macrophages labeled with magnetosomes for the possible detection of inflammations by MR molecular imaging. Pure magnetosomes and macrophages containing magnetosomes were analyzed using a clinical 1.5 T MR-scanner. Relaxivities of magnetosomes and relaxation rates of cells containing magnetosomes were determined. Peritonitis was induced in two mice. T1, T2 and T2* weighted images were acquired following injection of the probes. Pure magnetosomes and labeled cells showed slight effects on T1, but strong effects on T2 and T2* images. Labeled macrophages were located with magnetic resonance imaging (MRI) in the colon area, thus demonstrating the feasibility of the proposed approach.

The effect of illustrations on patient comprehension of medication instruction labels.

PubMed

Hwang, Stephen W; Tram, Carolyn Q N; Knarr, Nadia

2005-06-16

Labels with special instructions regarding how a prescription medication should be taken or its possible side effects are often applied to pill bottles. The goal of this study was to determine whether the addition of illustrations to these labels affects patient comprehension. Study participants (N = 130) were enrolled by approaching patients at three family practice clinics in Toronto, Canada. Participants were asked to interpret two sets of medication instruction labels, the first with text only and the second with the same text accompanied by illustrations. Two investigators coded participants' responses as incorrect, partially correct, or completely correct. Health literacy levels of participants were measured using a validated instrument, the REALM test. All participants gave a completely correct interpretation for three out of five instruction labels, regardless of whether illustrations were present or not. For the two most complex labels, only 34-55% of interpretations of the text-only version were completely correct. The addition of illustrations was associated with improved performance in 5-7% of subjects and worsened performance in 7-9% of subjects. The commonly-used illustrations on the medication labels used in this study were of little or no use in improving patients' comprehension of the accompanying written instructions.

Radiolabeling Silica-Based Nanoparticles via Coordination Chemistry: Basic Principles, Strategies, and Applications.

PubMed

Ni, Dalong; Jiang, Dawei; Ehlerding, Emily B; Huang, Peng; Cai, Weibo

2018-03-20

As one of the most biocompatible and well-tolerated inorganic nanomaterials, silica-based nanoparticles (SiNPs) have received extensive attention over the last several decades. Recently, positron emission tomography (PET) imaging of radiolabeled SiNPs has provided a highly sensitive, noninvasive, and quantitative readout of the organ/tissue distribution, pharmacokinetics, and tumor targeting efficiency in vivo, which can greatly expedite the clinical translation of these promising NPs. Encouraged by the successful PET imaging of patients with metastatic melanoma using 124 I-labeled ultrasmall SiNPs (known as Cornell dots or C dots) and their approval as an Investigational New Drug (IND) by the United States Food and Drug Administration, different radioisotopes ( 64 Cu, 89 Zr, 18 F, 68 Ga, 124 I, etc.) have been reported to radiolabel a wide variety of SiNPs-based nanostructures, including dense silica (dSiO 2 ), mesoporous silica (MSN), biodegradable mesoporous silica (bMSN), and hollow mesoporous silica nanoparticles (HMSN). With in-depth knowledge of coordination chemistry, abundant silanol groups (-Si-O-) on the silica surface or inside mesoporous channels not only can be directly used for chelator-free radiolabeling but also can be readily modified with the right chelators for chelator-based labeling. However, integrating these labeling strategies for constructing stably radiolabeled SiNPs with high efficiency has proven difficult because of the complexity of the involved key parameters, such as the choice of radioisotopes and chelators, nanostructures, and radiolabeling strategy. In this Account, we present an overview of recent progress in the development of radiolabeled SiNPs for cancer theranostics in the hope of speeding up their biomedical applications and potential translation into the clinic. We first introduce the basic principles and mechanisms for radiolabeling SiNPs via coordination chemistry, including general rules of selecting proper radioisotopes, engineering silica nanoplatforms (e.g., dSiO 2 , MSN, HMSN) accordingly, and chelation strategies for enhanced labeling efficiency and stability, on which our group has focused over the past decade. Generally, the medical applications guide the choice of specific SiNPs for radiolabeling by considering the inherent functionality of SiNPs. The radioisotopes can then be determined according to the amenability of the particular SiNPs for chelator-based or chelator-free radiolabeling to obtain high labeling stability in vivo, which is a prerequisite for PET to truly reflect the behavior of SiNPs since PET imaging detects the isotopes rather than nanoparticles. Next, we highlight several recent representative biomedical applications of radiolabeled SiNPs including molecular imaging to detect specific lesions, PET-guided drug delivery, SiNP-based theranostic cancer agents, and clinical studies. Finally, the challenges and prospects of radiolabeled SiNPs are briefly discussed toward clinical cancer research. We hope that this Account will clarify the recent progress on the radiolabeling of SiNPs for specific medical applications and generate broad interest in integrating nanotechnology and PET imaging. With several ongoing clinical trials, radiolabeled SiNPs offer great potential for future patient stratification and cancer management in clinical settings.

Multi-Atlas Based Segmentation of Brainstem Nuclei from MR Images by Deep Hyper-Graph Learning.

PubMed

Dong, Pei; Guo, Yangrong; Gao, Yue; Liang, Peipeng; Shi, Yonghong; Wang, Qian; Shen, Dinggang; Wu, Guorong

2016-10-01

Accurate segmentation of brainstem nuclei (red nucleus and substantia nigra) is very important in various neuroimaging applications such as deep brain stimulation and the investigation of imaging biomarkers for Parkinson's disease (PD). Due to iron deposition during aging, image contrast in the brainstem is very low in Magnetic Resonance (MR) images. Hence, the ambiguity of patch-wise similarity makes the recently successful multi-atlas patch-based label fusion methods have difficulty to perform as competitive as segmenting cortical and sub-cortical regions from MR images. To address this challenge, we propose a novel multi-atlas brainstem nuclei segmentation method using deep hyper-graph learning. Specifically, we achieve this goal in three-fold. First , we employ hyper-graph to combine the advantage of maintaining spatial coherence from graph-based segmentation approaches and the benefit of harnessing population priors from multi-atlas based framework. Second , besides using low-level image appearance, we also extract high-level context features to measure the complex patch-wise relationship. Since the context features are calculated on a tentatively estimated label probability map, we eventually turn our hyper-graph learning based label propagation into a deep and self-refining model. Third , since anatomical labels on some voxels (usually located in uniform regions) can be identified much more reliably than other voxels (usually located at the boundary between two regions), we allow these reliable voxels to propagate their labels to the nearby difficult-to-label voxels. Such hierarchical strategy makes our proposed label fusion method deep and dynamic. We evaluate our proposed label fusion method in segmenting substantia nigra (SN) and red nucleus (RN) from 3.0 T MR images, where our proposed method achieves significant improvement over the state-of-the-art label fusion methods.

A Locality-Constrained and Label Embedding Dictionary Learning Algorithm for Image Classification.

PubMed

Zhengming Li; Zhihui Lai; Yong Xu; Jian Yang; Zhang, David

2017-02-01

Locality and label information of training samples play an important role in image classification. However, previous dictionary learning algorithms do not take the locality and label information of atoms into account together in the learning process, and thus their performance is limited. In this paper, a discriminative dictionary learning algorithm, called the locality-constrained and label embedding dictionary learning (LCLE-DL) algorithm, was proposed for image classification. First, the locality information was preserved using the graph Laplacian matrix of the learned dictionary instead of the conventional one derived from the training samples. Then, the label embedding term was constructed using the label information of atoms instead of the classification error term, which contained discriminating information of the learned dictionary. The optimal coding coefficients derived by the locality-based and label-based reconstruction were effective for image classification. Experimental results demonstrated that the LCLE-DL algorithm can achieve better performance than some state-of-the-art algorithms.

Cryo-Imaging and Software Platform for Analysis of Molecular MR Imaging of Micrometastases

PubMed Central

Qutaish, Mohammed Q.; Zhou, Zhuxian; Prabhu, David; Liu, Yiqiao; Busso, Mallory R.; Izadnegahdar, Donna; Gargesha, Madhusudhana; Lu, Hong; Lu, Zheng-Rong

2018-01-01

We created and evaluated a preclinical, multimodality imaging, and software platform to assess molecular imaging of small metastases. This included experimental methods (e.g., GFP-labeled tumor and high resolution multispectral cryo-imaging), nonrigid image registration, and interactive visualization of imaging agent targeting. We describe technological details earlier applied to GFP-labeled metastatic tumor targeting by molecular MR (CREKA-Gd) and red fluorescent (CREKA-Cy5) imaging agents. Optimized nonrigid cryo-MRI registration enabled nonambiguous association of MR signals to GFP tumors. Interactive visualization of out-of-RAM volumetric image data allowed one to zoom to a GFP-labeled micrometastasis, determine its anatomical location from color cryo-images, and establish the presence/absence of targeted CREKA-Gd and CREKA-Cy5. In a mouse with >160 GFP-labeled tumors, we determined that in the MR images every tumor in the lung >0.3 mm2 had visible signal and that some metastases as small as 0.1 mm2 were also visible. More tumors were visible in CREKA-Cy5 than in CREKA-Gd MRI. Tape transfer method and nonrigid registration allowed accurate (<11 μm error) registration of whole mouse histology to corresponding cryo-images. Histology showed inflammation and necrotic regions not labeled by imaging agents. This mouse-to-cells multiscale and multimodality platform should uniquely enable more informative and accurate studies of metastatic cancer imaging and therapy. PMID:29805438

Analyzing tree-shape anatomical structures using topological descriptors of branching and ensemble of classifiers.

PubMed

Skoura, Angeliki; Bakic, Predrag R; Megalooikonomou, Vasilis

2013-01-01

The analysis of anatomical tree-shape structures visualized in medical images provides insight into the relationship between tree topology and pathology of the corresponding organs. In this paper, we propose three methods to extract descriptive features of the branching topology; the asymmetry index, the encoding of branching patterns using a node labeling scheme and an extension of the Sholl analysis. Based on these descriptors, we present classification schemes for tree topologies with respect to the underlying pathology. Moreover, we present a classifier ensemble approach which combines the predictions of the individual classifiers to optimize the classification accuracy. We applied the proposed methodology to a dataset of x-ray galactograms, medical images which visualize the breast ductal tree, in order to recognize images with radiological findings regarding breast cancer. The experimental results demonstrate the effectiveness of the proposed framework compared to state-of-the-art techniques suggesting that the proposed descriptors provide more valuable information regarding the topological patterns of ductal trees and indicating the potential of facilitating early breast cancer diagnosis.

Analyzing tree-shape anatomical structures using topological descriptors of branching and ensemble of classifiers

PubMed Central

Skoura, Angeliki; Bakic, Predrag R.; Megalooikonomou, Vasilis

2014-01-01

The analysis of anatomical tree-shape structures visualized in medical images provides insight into the relationship between tree topology and pathology of the corresponding organs. In this paper, we propose three methods to extract descriptive features of the branching topology; the asymmetry index, the encoding of branching patterns using a node labeling scheme and an extension of the Sholl analysis. Based on these descriptors, we present classification schemes for tree topologies with respect to the underlying pathology. Moreover, we present a classifier ensemble approach which combines the predictions of the individual classifiers to optimize the classification accuracy. We applied the proposed methodology to a dataset of x-ray galactograms, medical images which visualize the breast ductal tree, in order to recognize images with radiological findings regarding breast cancer. The experimental results demonstrate the effectiveness of the proposed framework compared to state-of-the-art techniques suggesting that the proposed descriptors provide more valuable information regarding the topological patterns of ductal trees and indicating the potential of facilitating early breast cancer diagnosis. PMID:25414850

SIMulation of Medication Error induced by Clinical Trial drug labeling: the SIMME-CT study.

PubMed

Dollinger, Cecile; Schwiertz, Vérane; Sarfati, Laura; Gourc-Berthod, Chloé; Guédat, Marie-Gabrielle; Alloux, Céline; Vantard, Nicolas; Gauthier, Noémie; He, Sophie; Kiouris, Elena; Caffin, Anne-Gaelle; Bernard, Delphine; Ranchon, Florence; Rioufol, Catherine

2016-06-01

To assess the impact of investigational drug labels on the risk of medication error in drug dispensing. A simulation-based learning program focusing on investigational drug dispensing was conducted. The study was undertaken in an Investigational Drugs Dispensing Unit of a University Hospital of Lyon, France. Sixty-three pharmacy workers (pharmacists, residents, technicians or students) were enrolled. Ten risk factors were selected concerning label information or the risk of confusion with another clinical trial. Each risk factor was scored independently out of 5: the higher the score, the greater the risk of error. From 400 labels analyzed, two groups were selected for the dispensing simulation: 27 labels with high risk (score ≥3) and 27 with low risk (score ≤2). Each question in the learning program was displayed as a simulated clinical trial prescription. Medication error was defined as at least one erroneous answer (i.e. error in drug dispensing). For each question, response times were collected. High-risk investigational drug labels correlated with medication error and slower response time. Error rates were significantly 5.5-fold higher for high-risk series. Error frequency was not significantly affected by occupational category or experience in clinical trials. SIMME-CT is the first simulation-based learning tool to focus on investigational drug labels as a risk factor for medication error. SIMME-CT was also used as a training tool for staff involved in clinical research, to develop medication error risk awareness and to validate competence in continuing medical education. © The Author 2016. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia

DTIC Science & Technology

2015-10-01

eyes and image choroidal vessels/capillaries using CARS intravital microscopy Subtask 3: Measure oxy-hemoglobin levels in PBI test and control eyes...AWARD NUMBER: W81XWH-14-1-0537 TITLE: Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia...4. TITLE AND SUBTITLE Mobile, Multimodal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia 5a. CONTRACT NUMBER W81XWH

Nonlocal atlas-guided multi-channel forest learning for human brain labeling

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

Ma, Guangkai; Gao, Yaozong; Wu, Guorong

Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features canmore » be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI-LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the dice similarity coefficient to measure the overlap degree. Their method achieves average overlaps of 82.56% on 54 regions of interest (ROIs) and 79.78% on 80 ROIs, respectively, which significantly outperform the baseline method (random forests), with the average overlaps of 72.48% on 54 ROIs and 72.09% on 80 ROIs, respectively. Conclusions: The proposed methods have achieved the highest labeling accuracy, compared to several state-of-the-art methods in the literature.« less

Nonlocal atlas-guided multi-channel forest learning for human brain labeling

PubMed Central

Ma, Guangkai; Gao, Yaozong; Wu, Guorong; Wu, Ligang; Shen, Dinggang

2016-01-01

Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features can be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI_LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the dice similarity coefficient to measure the overlap degree. Their method achieves average overlaps of 82.56% on 54 regions of interest (ROIs) and 79.78% on 80 ROIs, respectively, which significantly outperform the baseline method (random forests), with the average overlaps of 72.48% on 54 ROIs and 72.09% on 80 ROIs, respectively. Conclusions: The proposed methods have achieved the highest labeling accuracy, compared to several state-of-the-art methods in the literature. PMID:26843260

Student beats the teacher: deep neural networks for lateral ventricles segmentation in brain MR

NASA Astrophysics Data System (ADS)

Ghafoorian, Mohsen; Teuwen, Jonas; Manniesing, Rashindra; Leeuw, Frank-Erik d.; van Ginneken, Bram; Karssemeijer, Nico; Platel, Bram

2018-03-01

Ventricular volume and its progression are known to be linked to several brain diseases such as dementia and schizophrenia. Therefore accurate measurement of ventricle volume is vital for longitudinal studies on these disorders, making automated ventricle segmentation algorithms desirable. In the past few years, deep neural networks have shown to outperform the classical models in many imaging domains. However, the success of deep networks is dependent on manually labeled data sets, which are expensive to acquire especially for higher dimensional data in the medical domain. In this work, we show that deep neural networks can be trained on muchcheaper-to-acquire pseudo-labels (e.g., generated by other automated less accurate methods) and still produce more accurate segmentations compared to the quality of the labels. To show this, we use noisy segmentation labels generated by a conventional region growing algorithm to train a deep network for lateral ventricle segmentation. Then on a large manually annotated test set, we show that the network significantly outperforms the conventional region growing algorithm which was used to produce the training labels for the network. Our experiments report a Dice Similarity Coefficient (DSC) of 0.874 for the trained network compared to 0.754 for the conventional region growing algorithm (p < 0.001).

Comparison of Confocal and Super-Resolution Reflectance Imaging of Metal Oxide Nanoparticles

PubMed Central

Guggenheim, Emily J.; Khan, Abdullah; Pike, Jeremy; Chang, Lynne; Lynch, Iseult; Rappoport, Joshua Z.

2016-01-01

The potential for human exposure to manufactured nanoparticles (NPs) has increased in recent years, in part through the incorporation of engineered particles into a wide range of commercial goods and medical applications. NP are ideal candidates for use as therapeutic and diagnostic tools within biomedicine, however concern exists regarding their efficacy and safety. Thus, developing techniques for the investigation of NP uptake into cells is critically important. Current intracellular NP investigations rely on the use of either Transmission Electron Microscopy (TEM), which provides ultrahigh resolution, but involves cumbersome sample preparation rendering the technique incompatible with live cell imaging, or fluorescent labelling, which suffers from photobleaching, poor bioconjugation and, often, alteration of NP surface properties. Reflected light imaging provides an alternative non-destructive label free technique well suited, but not limited to, the visualisation of NP uptake within model systems, such as cells. Confocal reflectance microscopy provides optical sectioning and live imaging capabilities, with little sample preparation. However confocal microscopy is diffraction limited, thus the X-Y resolution is restricted to ~250 nm, substantially larger than the <100 nm size of NPs. Techniques such as super-resolution light microscopy overcome this fundamental limitation, providing increased X-Y resolution. The use of Reflectance SIM (R-SIM) for NP imaging has previously only been demonstrated on custom built microscopes, restricting the widespread use and limiting NP investigations. This paper demonstrates the use of a commercial SIM microscope for the acquisition of super-resolution reflectance data with X-Y resolution of 115 nm, a greater than two-fold increase compared to that attainable with RCM. This increase in resolution is advantageous for visualising small closely spaced structures, such as NP clusters, previously unresolvable by RCM. This is advantageous when investigating the subcellular trafficking of NP within fluorescently labelled cellular compartments. NP signal can be observed using RCM, R-SIM and TEM and a direct comparison is presented. Each of these techniques has its own benefits and limitations; RCM and R-SIM provide novel complementary information while the combination of modalities provides a unique opportunity to gain additional information regarding NP uptake. The use of multiple imaging methods therefore greatly enhances the range of NPs that can be studied under label-free conditions. PMID:27695038

The symmetry rule: a seven-year study of symptoms and explanatory labels among Gulf War veterans.

PubMed

Brewer, Noel T; Hallman, William K; Kipen, Howard M

2008-12-01

Noticing medical symptoms can cause one to search for explanatory labels such as "ate bad food" or even "exposed to anthrax," and perhaps these labels may cause new symptom reports. The present study examined whether there is empirical support for this symptom-label "symmetry rule." We interviewed veterans (N= 362) from the Gulf War Registry in 1995 and 2002 about their medical symptoms and about their exposure to war-related hazards and stressors. Health symptom reports were strongly correlated between the two time periods and showed relatively stable mean levels, whereas recall of war-related exposures was notably unstable. Veterans starting with fewer medical symptoms recalled fewer war-related exposures seven years later. Initial recollection of chemical and biological warfare exposure (but not other exposures) longitudinally predicted novel medical symptoms. The findings generally support the symmetry rule hypotheses, although the evidence for the label to symptom link was less strong. The findings account for some variability in symptoms and exposure recall over time, but they do not, on their own, account for the Gulf War veterans' elevated number of unexplained medical symptoms.

Munchausen's Syndrome by Google©

PubMed Central

Griffiths, EJ; Kampa, R; Pearce, C; Sakellariou, A; Solan, MC

2009-01-01

A case is discussed of the use of medical images from the internet to support claims of injury. There were several inconsistencies in both history and examination even prior to the presentation of the specimen radiograph from the internet. Clinicians are advised to be vigilant, to question histories that do not match with examination findings, to ensure that all radiographs are adequately labelled with patient-specific information and to look for radiographic inconsistencies such as the presence or absence of accessory ossicles. PMID:19317939

Off-label prescribing of medications for pain: maintaining optimal care at an intersection of law, public policy, and ethics.

PubMed

Ruble, James

2012-06-01

For more than 60 years, regulations limited marketing of medications for off-label uses to very low levels. Some key policy changes in the late 1990s ushered in an era of deregulation of off-label marketing. Policy changes included revised United States federal law as well as modifications of Food and Drug Administration (FDA) regulations. Subsequent investigations documented an explosion in scope off-label prescribing. Attempts to limit off-label advertising by manufacturers were vigorously challenged in the courts. Other modalities are needed to maintain a clinical care environment that places the patients' best interests first. In many circumstances, an off-label medication may be in the patient's best interests; however, where there is a lower level of clinical justification, the informed consent of the patient and shared decision making of the patient is essential to optimize outcome.

Site-Specific Bioorthogonal Labeling for Fluorescence Imaging of Intracellular Proteins in Living Cells.

PubMed

Peng, Tao; Hang, Howard C

2016-11-02

Over the past years, fluorescent proteins (e.g., green fluorescent proteins) have been widely utilized to visualize recombinant protein expression and localization in live cells. Although powerful, fluorescent protein tags are limited by their relatively large sizes and potential perturbation to protein function. Alternatively, site-specific labeling of proteins with small-molecule organic fluorophores using bioorthogonal chemistry may provide a more precise and less perturbing method. This approach involves site-specific incorporation of unnatural amino acids (UAAs) into proteins via genetic code expansion, followed by bioorthogonal chemical labeling with small organic fluorophores in living cells. While this approach has been used to label extracellular proteins for live cell imaging studies, site-specific bioorthogonal labeling and fluorescence imaging of intracellular proteins in live cells is still challenging. Herein, we systematically evaluate site-specific incorporation of diastereomerically pure bioorthogonal UAAs bearing stained alkynes or alkenes into intracellular proteins for inverse-electron-demand Diels-Alder cycloaddition reactions with tetrazine-functionalized fluorophores for live cell labeling and imaging in mammalian cells. Our studies show that site-specific incorporation of axial diastereomer of trans-cyclooct-2-ene-lysine robustly affords highly efficient and specific bioorthogonal labeling with monosubstituted tetrazine fluorophores in live mammalian cells, which enabled us to image the intracellular localization and real-time dynamic trafficking of IFITM3, a small membrane-associated protein with only 137 amino acids, for the first time. Our optimized UAA incorporation and bioorthogonal labeling conditions also enabled efficient site-specific fluorescence labeling of other intracellular proteins for live cell imaging studies in mammalian cells.

Java Image I/O for VICAR, PDS, and ISIS

NASA Technical Reports Server (NTRS)

Deen, Robert G.; Levoe, Steven R.

2011-01-01

This library, written in Java, supports input and output of images and metadata (labels) in the VICAR, PDS image, and ISIS-2 and ISIS-3 file formats. Three levels of access exist. The first level comprises the low-level, direct access to the file. This allows an application to read and write specific image tiles, lines, or pixels and to manipulate the label data directly. This layer is analogous to the C-language "VICAR Run-Time Library" (RTL), which is the image I/O library for the (C/C++/Fortran) VICAR image processing system from JPL MIPL (Multimission Image Processing Lab). This low-level library can also be used to read and write labeled, uncompressed images stored in formats similar to VICAR, such as ISIS-2 and -3, and a subset of PDS (image format). The second level of access involves two codecs based on Java Advanced Imaging (JAI) to provide access to VICAR and PDS images in a file-format-independent manner. JAI is supplied by Sun Microsystems as an extension to desktop Java, and has a number of codecs for formats such as GIF, TIFF, JPEG, etc. Although Sun has deprecated the codec mechanism (replaced by IIO), it is still used in many places. The VICAR and PDS codecs allow any program written using the JAI codec spec to use VICAR or PDS images automatically, with no specific knowledge of the VICAR or PDS formats. Support for metadata (labels) is included, but is format-dependent. The PDS codec, when processing PDS images with an embedded VIAR label ("dual-labeled images," such as used for MER), presents the VICAR label in a new way that is compatible with the VICAR codec. The third level of access involves VICAR, PDS, and ISIS Image I/O plugins. The Java core includes an "Image I/O" (IIO) package that is similar in concept to the JAI codec, but is newer and more capable. Applications written to the IIO specification can use any image format for which a plug-in exists, with no specific knowledge of the format itself.

Micrometer-sized iron oxide particle labeling of mesenchymal stem cells for magnetic resonance imaging-based monitoring of cartilage tissue engineering.

PubMed

Saldanha, Karl J; Doan, Ryan P; Ainslie, Kristy M; Desai, Tejal A; Majumdar, Sharmila

2011-01-01

To examine mesenchymal stem cell (MSC) labeling with micrometer-sized iron oxide particles (MPIOs) for magnetic resonance imaging (MRI)-based tracking and its application to monitoring articular cartilage regeneration. Rabbit MSCs were labeled using commercial MPIOs. In vitro MRI was performed with gradient echo (GRE) and spin echo (SE) sequences at 3T and quantitatively characterized using line profile and region of interest analysis. Ex vivo MRI of hydrogel-encapsulated labeled MSCs implanted within a bovine knee was performed with spoiled GRE (SPGR) and T(1ρ) sequences. Fluorescence microscopy, labeling efficiency, and chondrogenesis of MPIO-labeled cells were also examined. MPIO labeling results in efficient contrast uptake and signal loss that can be visualized and quantitatively characterized via MRI. SPGR imaging of implanted cells results in ex vivo detection within native tissue, and T(1ρ) imaging is unaffected by the presence of labeled cells immediately following implantation. MPIO labeling does not affect quantitative glycosaminoglycan production during chondrogenesis, but iron aggregation hinders extracellular matrix visualization. This aggregation may result from excess unincorporated particles following labeling and is an issue that necessitates further investigation. This study demonstrates the promise of MPIO labeling for monitoring cartilage regeneration and highlights its potential in the development of cell-based tissue engineering strategies. Published by Elsevier Inc.

Automatic labeling of MR brain images through extensible learning and atlas forests.

PubMed

Xu, Lijun; Liu, Hong; Song, Enmin; Yan, Meng; Jin, Renchao; Hung, Chih-Cheng

2017-12-01

Multiatlas-based method is extensively used in MR brain images segmentation because of its simplicity and robustness. This method provides excellent accuracy although it is time consuming and limited in terms of obtaining information about new atlases. In this study, an automatic labeling of MR brain images through extensible learning and atlas forest is presented to address these limitations. We propose an extensible learning model which allows the multiatlas-based framework capable of managing the datasets with numerous atlases or dynamic atlas datasets and simultaneously ensure the accuracy of automatic labeling. Two new strategies are used to reduce the time and space complexity and improve the efficiency of the automatic labeling of brain MR images. First, atlases are encoded to atlas forests through random forest technology to reduce the time consumed for cross-registration between atlases and target image, and a scatter spatial vector is designed to eliminate errors caused by inaccurate registration. Second, an atlas selection method based on the extensible learning model is used to select atlases for target image without traversing the entire dataset and then obtain the accurate labeling. The labeling results of the proposed method were evaluated in three public datasets, namely, IBSR, LONI LPBA40, and ADNI. With the proposed method, the dice coefficient metric values on the three datasets were 84.17 ± 4.61%, 83.25 ± 4.29%, and 81.88 ± 4.53% which were 5% higher than those of the conventional method, respectively. The efficiency of the extensible learning model was evaluated by state-of-the-art methods for labeling of MR brain images. Experimental results showed that the proposed method could achieve accurate labeling for MR brain images without traversing the entire datasets. In the proposed multiatlas-based method, extensible learning and atlas forests were applied to control the automatic labeling of brain anatomies on large atlas datasets or dynamic atlas datasets and obtain accurate results. © 2017 American Association of Physicists in Medicine.

Crowdsourcing scoring of immunohistochemistry images: Evaluating Performance of the Crowd and an Automated Computational Method

NASA Astrophysics Data System (ADS)

Irshad, Humayun; Oh, Eun-Yeong; Schmolze, Daniel; Quintana, Liza M.; Collins, Laura; Tamimi, Rulla M.; Beck, Andrew H.

2017-02-01

The assessment of protein expression in immunohistochemistry (IHC) images provides important diagnostic, prognostic and predictive information for guiding cancer diagnosis and therapy. Manual scoring of IHC images represents a logistical challenge, as the process is labor intensive and time consuming. Since the last decade, computational methods have been developed to enable the application of quantitative methods for the analysis and interpretation of protein expression in IHC images. These methods have not yet replaced manual scoring for the assessment of IHC in the majority of diagnostic laboratories and in many large-scale research studies. An alternative approach is crowdsourcing the quantification of IHC images to an undefined crowd. The aim of this study is to quantify IHC images for labeling of ER status with two different crowdsourcing approaches, image-labeling and nuclei-labeling, and compare their performance with automated methods. Crowdsourcing- derived scores obtained greater concordance with the pathologist interpretations for both image-labeling and nuclei-labeling tasks (83% and 87%), as compared to the pathologist concordance achieved by the automated method (81%) on 5,338 TMA images from 1,853 breast cancer patients. This analysis shows that crowdsourcing the scoring of protein expression in IHC images is a promising new approach for large scale cancer molecular pathology studies.

Adaptive and automatic red blood cell counting method based on microscopic hyperspectral imaging technology

NASA Astrophysics Data System (ADS)

Liu, Xi; Zhou, Mei; Qiu, Song; Sun, Li; Liu, Hongying; Li, Qingli; Wang, Yiting

2017-12-01

Red blood cell counting, as a routine examination, plays an important role in medical diagnoses. Although automated hematology analyzers are widely used, manual microscopic examination by a hematologist or pathologist is still unavoidable, which is time-consuming and error-prone. This paper proposes a full-automatic red blood cell counting method which is based on microscopic hyperspectral imaging of blood smears and combines spatial and spectral information to achieve high precision. The acquired hyperspectral image data of the blood smear in the visible and near-infrared spectral range are firstly preprocessed, and then a quadratic blind linear unmixing algorithm is used to get endmember abundance images. Based on mathematical morphological operation and an adaptive Otsu’s method, a binaryzation process is performed on the abundance images. Finally, the connected component labeling algorithm with magnification-based parameter setting is applied to automatically select the binary images of red blood cell cytoplasm. Experimental results show that the proposed method can perform well and has potential for clinical applications.

Generalization error analysis: deep convolutional neural network in mammography

NASA Astrophysics Data System (ADS)

Richter, Caleb D.; Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir; Cha, Kenny

2018-02-01

We conducted a study to gain understanding of the generalizability of deep convolutional neural networks (DCNNs) given their inherent capability to memorize data. We examined empirically a specific DCNN trained for classification of masses on mammograms. Using a data set of 2,454 lesions from 2,242 mammographic views, a DCNN was trained to classify masses into malignant and benign classes using transfer learning from ImageNet LSVRC-2010. We performed experiments with varying amounts of label corruption and types of pixel randomization to analyze the generalization error for the DCNN. Performance was evaluated using the area under the receiver operating characteristic curve (AUC) with an N-fold cross validation. Comparisons were made between the convergence times, the inference AUCs for both the training set and the test set of the original image patches without corruption, and the root-mean-squared difference (RMSD) in the layer weights of the DCNN trained with different amounts and methods of corruption. Our experiments observed trends which revealed that the DCNN overfitted by memorizing corrupted data. More importantly, this study improved our understanding of DCNN weight updates when learning new patterns or new labels. Although we used a specific classification task with the ImageNet as example, similar methods may be useful for analysis of the DCNN learning processes, especially those that employ transfer learning for medical image analysis where sample size is limited and overfitting risk is high.

78 FR 24211 - Draft Guidance for Industry on Safety Considerations for Container Labels and Carton Labeling...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-24

... container labels and carton labeling design, is the second in a series of three planned guidance documents...] Draft Guidance for Industry on Safety Considerations for Container Labels and Carton Labeling Design To... entitled ``Safety Considerations for Container Labels and Carton Labeling Design to Minimize Medication...

Ensemble LUT classification for degraded document enhancement

NASA Astrophysics Data System (ADS)

Obafemi-Ajayi, Tayo; Agam, Gady; Frieder, Ophir

2008-01-01

The fast evolution of scanning and computing technologies have led to the creation of large collections of scanned paper documents. Examples of such collections include historical collections, legal depositories, medical archives, and business archives. Moreover, in many situations such as legal litigation and security investigations scanned collections are being used to facilitate systematic exploration of the data. It is almost always the case that scanned documents suffer from some form of degradation. Large degradations make documents hard to read and substantially deteriorate the performance of automated document processing systems. Enhancement of degraded document images is normally performed assuming global degradation models. When the degradation is large, global degradation models do not perform well. In contrast, we propose to estimate local degradation models and use them in enhancing degraded document images. Using a semi-automated enhancement system we have labeled a subset of the Frieder diaries collection.1 This labeled subset was then used to train an ensemble classifier. The component classifiers are based on lookup tables (LUT) in conjunction with the approximated nearest neighbor algorithm. The resulting algorithm is highly effcient. Experimental evaluation results are provided using the Frieder diaries collection.1

Dopaminergic Therapy Modulates Cortical Perfusion in Parkinson Disease With and Without Dementia According to Arterial Spin Labeled Perfusion Magnetic Resonance Imaging

PubMed Central

Lin, Wei-Che; Chen, Pei-Chin; Huang, Yung-Cheng; Tsai, Nai-Wen; Chen, Hsiu-Ling; Wang, Hung-Chen; Lin, Tsu-Kung; Chou, Kun-Hsien; Chen, Meng-Hsiang; Chen, Yi-Wen; Lu, Cheng-Hsien

2016-01-01

Abstract Arterial spin labeling (ASL) magnetic resonance imaging analyses allow for the quantification of altered cerebral blood flow, and provide a novel means of examining the impact of dopaminergic treatments. The authors examined the cerebral perfusion differences among 17 Parkinson disease (PD) patients, 17 PD with dementia (PDD) patients, and 17 healthy controls and used ASL-MRI to assess the effects of dopaminergic therapies on perfusion in the patients. The authors demonstrated progressive widespread cortical hypoperfusion in PD and PDD and robust effects for the dopaminergic therapies. Specifically, dopaminergic medications further decreased frontal lobe and cerebellum perfusion in the PD and PDD groups, respectively. These patterns of hypoperfusion could be related to cognitive dysfunctions and disease severity. Furthermore, desensitization to dopaminergic therapies in terms of cortical perfusion was found as the disease progressed, supporting the concept that long-term therapies are associated with the therapeutic window narrowing. The highly sensitive pharmaceutical response of ASL allows clinicians and researchers to easily and effectively quantify the absolute perfusion status, which might prove helpful for therapeutic planning. PMID:26844450

Dopaminergic Therapy Modulates Cortical Perfusion in Parkinson Disease With and Without Dementia According to Arterial Spin Labeled Perfusion Magnetic Resonance Imaging.

PubMed

Lin, Wei-Che; Chen, Pei-Chin; Huang, Yung-Cheng; Tsai, Nai-Wen; Chen, Hsiu-Ling; Wang, Hung-Chen; Lin, Tsu-Kung; Chou, Kun-Hsien; Chen, Meng-Hsiang; Chen, Yi-Wen; Lu, Cheng-Hsien

2016-02-01

Arterial spin labeling (ASL) magnetic resonance imaging analyses allow for the quantification of altered cerebral blood flow, and provide a novel means of examining the impact of dopaminergic treatments. The authors examined the cerebral perfusion differences among 17 Parkinson disease (PD) patients, 17 PD with dementia (PDD) patients, and 17 healthy controls and used ASL-MRI to assess the effects of dopaminergic therapies on perfusion in the patients. The authors demonstrated progressive widespread cortical hypoperfusion in PD and PDD and robust effects for the dopaminergic therapies. Specifically, dopaminergic medications further decreased frontal lobe and cerebellum perfusion in the PD and PDD groups, respectively. These patterns of hypoperfusion could be related to cognitive dysfunctions and disease severity. Furthermore, desensitization to dopaminergic therapies in terms of cortical perfusion was found as the disease progressed, supporting the concept that long-term therapies are associated with the therapeutic window narrowing. The highly sensitive pharmaceutical response of ASL allows clinicians and researchers to easily and effectively quantify the absolute perfusion status, which might prove helpful for therapeutic planning.

Lesional perfusion abnormalities in Leigh disease demonstrated by arterial spin labeling correlate with disease activity.

PubMed

Whitehead, Matthew T; Lee, Bonmyong; Gropman, Andrea

2016-08-01

Leigh disease is a metabolic disorder of the mitochondrial respiratory chain culminating in symmetrical necrotizing lesions in the deep gray nuclei or brainstem. Apart from classic gliotic/necrotic lesions, small-vessel proliferation is also characteristic on histopathology. We have observed lesional hyperperfusion on arterial spin-labeling (ASL) sequence in children with Leigh disease. In this cross-sectional analysis, we evaluated lesional ASL perfusion characteristics in children with Leigh syndrome. We searched the imaging database from an academic children's hospital for "arterial spin labeling, perfusion, necrosis, lactate, and Leigh" to build a cohort of children for retrospective analysis. We reviewed each child's medical record to confirm a diagnosis of Leigh disease, excluding exams with artifact, technical limitations, and without ASL images. We evaluated the degree and extent of cerebral blood flow and relationship to brain lesions. Images were compared to normal exams from an aged-matche cohort. The database search yielded 45 exams; 30 were excluded. We evaluated 15 exams from 8 children with Leigh disease and 15 age-matched normal exams. In general, Leigh brain perfusion ranged from hyperintense (n=10) to hypointense (n=5). Necrotic lesions appeared hypointense/hypoperfused. Active lesions with associated restricted diffusion demonstrated hyperperfusion. ASL perfusion patterns differed significantly from those on age-matched normal studies (P=<.0001). Disease activity positively correlated with cerebral deep gray nuclei hyperperfusion (P=0.0037) and lesion grade (P=0.0256). Children with Leigh disease have abnormal perfusion of brain lesions. Hyperperfusion can be found in active brain lesions, possibly associated with small-vessel proliferation characteristic of the disease.

Head-to-Head Visual Comparison between Brain Perfusion SPECT and Arterial Spin-Labeling MRI with Different Postlabeling Delays in Alzheimer Disease.

PubMed

Kaneta, T; Katsuse, O; Hirano, T; Ogawa, M; Yoshida, K; Odawara, T; Hirayasu, Y; Inoue, T

2017-08-01

Arterial spin-labeling MR imaging has been recently developed as a noninvasive technique with magnetically labeled arterial blood water as an endogenous contrast medium for the evaluation of CBF. Our aim was to compare arterial spin-labeling MR imaging and SPECT in the visual assessment of CBF in patients with Alzheimer disease. In 33 patients with Alzheimer disease or mild cognitive impairment due to Alzheimer disease, CBF images were obtained by using both arterial spin-labeling-MR imaging with a postlabeling delay of 1.5 seconds and 2.5 seconds (PLD 1.5 and PLD 2.5 , respectively) and brain perfusion SPECT. Twenty-two brain regions were visually assessed, and the diagnostic confidence of Alzheimer disease was recorded. Among all arterial spin-labeling images, 84.9% of PLD 1.5 and 9% of PLD 2.5 images showed the typical pattern of advanced Alzheimer disease (ie, decreased CBF in the bilateral parietal, temporal, and frontal lobes). PLD 1.5 , PLD 2.5 , and SPECT imaging resulted in obviously different visual assessments. PLD 1.5 showed a broad decrease in CBF, which could have been due to an early perfusion. In contrast, PLD 2.5 did not appear to be influenced by an early perfusion but showed fewer pathologic findings than SPECT. The distinctions observed by us should be carefully considered in the visual assessments of Alzheimer disease. Further studies are required to define the patterns of change in arterial spin-labeling-MR imaging associated with Alzheimer disease. © 2017 by American Journal of Neuroradiology.

Does Choline PET/CT Change the Management of Prostate Cancer Patients With Biochemical Failure?

PubMed

Goldstein, Jeffrey; Even-Sapir, Einat; Ben-Haim, Simona; Saad, Akram; Spieler, Benjamin; Davidson, Tima; Berger, Raanan; Weiss, Ilana; Appel, Sarit; Lawrence, Yaacov R; Symon, Zvi

2017-06-01

The FDA approved C-11 choline PET/computed tomography (CT) for imaging patients with recurrent prostate cancer in 2012. Subsequently, the 2014 NCCN guidelines have introduced labeled choline PET/CT in the imaging algorithm of patients with suspected recurrent disease. However, there is only scarce data on the impact of labeled choline PET/CT findings on disease management. We hypothesized that labeled-choline PET/CT studies showing local or regional recurrence or distant metastases will have a direct role in selection of appropriate patient management and improve radiation planning in patients with disease that can be controlled using this mode of therapy. This retrospective study was approved by the Tel Aviv Sourasky and Sheba Medical Center's Helsinki ethical review committees. Patient characteristics including age, PSA, stage, prior treatments, and pre-PET choline treatment recommendations based on NCCN guidelines were recorded. Patients with biochemical failure and without evidence of recurrence on physical examination or standard imaging were offered the option of additional imaging with labeled choline PET/CT. Treatment recommendations post-PET/CT were compared with pre-PET/CT ones. Pathologic confirmation was obtained before prostate retreatment. A nonparametric χ test was used to compare the initial and final treatment recommendations following choline PET/CT. Between June 2010 and January 2014, 34 labeled-choline PET/CT studies were performed on 33 patients with biochemical failure following radical prostatectomy (RP) (n=6), radiation therapy (RT) (n=6), brachytherapy (n=2), RP+salvage prostate fossa RT (n=14), and RP+salvage prostate fossa/lymph node RT (n=6). Median PSA level before imaging was 2 ng/mL (range, 0.16 to 79). Labeled choline PET/CT showed prostate, prostate fossa, or pelvic lymph node increased uptake in 17 studies, remote metastatic disease in 9 studies, and failed to identify the cause for biochemical failure in 7 scans.PET/CT altered treatment approach in 18 of 33 (55%) patients (P=0.05). Sixteen of 27 patients (59%) treated previously with radiation were retreated with RT and delayed or eliminated androgen deprivation therapy: 1 received salvage brachytherapy, 10 received salvage pelvic lymph node or prostate fossa irradiation, 2 brachytherapy failures received salvage prostate and lymph nodes IMRT, and 3 with solitary bone metastasis were treated with radiosurgery. Eleven of 16 patients retreated responded to salvage therapy with a significant PSA response (<0.2 ng/mL), 2 patients had partial biochemical responses, and 3 patients failed. The median duration of response was 500±447 days. Two of 6 patients with no prior RT were referred for salvage prostatic fossa RT: 1 received dose escalation for disease identified in the prostate fossa and another had inclusion of "hot" pelvic lymph nodes in the treatment volume. These early results suggest that labeled choline PET/CT imaging performed according to current NCCN guidelines may change management and improve care in prostate cancer patients with biochemical failure by identifying patients for referral for salvage radiation therapy, improving radiation planning, and delaying or avoiding use of androgen deprivation therapy.

Chelator-Free Labeling of Layered Double Hydroxide Nanoparticles for in Vivo PET Imaging

NASA Astrophysics Data System (ADS)

Shi, Sixiang; Fliss, Brianne C.; Gu, Zi; Zhu, Yian; Hong, Hao; Valdovinos, Hector F.; Hernandez, Reinier; Goel, Shreya; Luo, Haiming; Chen, Feng; Barnhart, Todd E.; Nickles, Robert J.; Xu, Zhi Ping; Cai, Weibo

2015-11-01

Layered double hydroxide (LDH) nanomaterial has emerged as a novel delivery agent for biomedical applications due to its unique structure and properties. However, in vivo positron emission tomography (PET) imaging with LDH nanoparticles has not been achieved. The aim of this study is to explore chelator-free labeling of LDH nanoparticles with radioisotopes for in vivo PET imaging. Bivalent cation 64Cu2+ and trivalent cation 44Sc3+ were found to readily label LDH nanoparticles with excellent labeling efficiency and stability, whereas tetravalent cation 89Zr4+ could not label LDH since it does not fit into the LDH crystal structure. PET imaging shows that prominent tumor uptake was achieved in 4T1 breast cancer with 64Cu-LDH-BSA via passive targeting alone (7.7 ± 0.1%ID/g at 16 h post-injection; n = 3). These results support that LDH is a versatile platform that can be labeled with various bivalent and trivalent radiometals without comprising the native properties, highly desirable for PET image-guided drug delivery.

Development of an Anthropomorphic Breast Phantom for Combined PET, B-Mode Ultrasound and Elastographic Imaging

NASA Astrophysics Data System (ADS)

Dang, Jun; Frisch, Benjamin; Lasaygues, Philippe; Zhang, Dachun; Tavernier, Stefaan; Felix, Nicolas; Lecoq, Paul; Auffray, Etiennette; Varela, Joao; Mensah, Serge; Wan, Mingxi

2011-06-01

Combining the advantages of different imaging modalities leads to improved clinical results. For example, ultrasound provides good real-time structural information without any radiation and PET provides sensitive functional information. For the ongoing ClearPEM-Sonic project combining ultrasound and PET for breast imaging, we developed a dual-modality PET/Ultrasound (US) phantom. The phantom reproduces the acoustic and elastic properties of human breast tissue and allows labeling the different tissues in the phantom with different concentrations of FDG. The phantom was imaged with a whole-body PET/CT and with the Supersonic Imagine Aixplorer system. This system allows both B-mode US and shear wave elastographic imaging. US elastography is a new imaging method for displaying the tissue elasticity distribution. It was shown to be useful in breast imaging. We also tested the phantom with static elastography. A 6D magnetic positioning system allows fusing the images obtained with the two modalities. ClearPEM-Sonic is a project of the Crystal Clear Collaboration and the European Centre for Research on Medical Imaging (CERIMED).

SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation.

PubMed

Xue, Yuan; Xu, Tao; Zhang, Han; Long, L Rodney; Huang, Xiaolei

2018-05-03

Inspired by classic Generative Adversarial Networks (GANs), we propose a novel end-to-end adversarial neural network, called SegAN, for the task of medical image segmentation. Since image segmentation requires dense, pixel-level labeling, the single scalar real/fake output of a classic GAN's discriminator may be ineffective in producing stable and sufficient gradient feedback to the networks. Instead, we use a fully convolutional neural network as the segmentor to generate segmentation label maps, and propose a novel adversarial critic network with a multi-scale L 1 loss function to force the critic and segmentor to learn both global and local features that capture long- and short-range spatial relationships between pixels. In our SegAN framework, the segmentor and critic networks are trained in an alternating fashion in a min-max game: The critic is trained by maximizing a multi-scale loss function, while the segmentor is trained with only gradients passed along by the critic, with the aim to minimize the multi-scale loss function. We show that such a SegAN framework is more effective and stable for the segmentation task, and it leads to better performance than the state-of-the-art U-net segmentation method. We tested our SegAN method using datasets from the MICCAI BRATS brain tumor segmentation challenge. Extensive experimental results demonstrate the effectiveness of the proposed SegAN with multi-scale loss: on BRATS 2013 SegAN gives performance comparable to the state-of-the-art for whole tumor and tumor core segmentation while achieves better precision and sensitivity for Gd-enhance tumor core segmentation; on BRATS 2015 SegAN achieves better performance than the state-of-the-art in both dice score and precision.

Comparison of indium-labeled-leukocyte imaging with sequential technetium-gallium scanning in the diagnosis of low-grade musculoskeletal sepsis. A prospective study

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

Merkel, K.D.; Brown, M.L.; Dewanjee, M.K.

We prospectively compared sequential technetium-gallium imaging with indium-labeled-leukocyte imaging in fifty patients with suspected low-grade musculoskeletal sepsis. Adequate images and follow-up examinations were obtained for forty-two patients. The presence or absence of low-grade sepsis was confirmed by histological and bacteriological examinations of tissue specimens taken at surgery in thirty of the forty-two patients. In these thirty patients, the sensitivity of sequential Tc-Ga imaging was 48 per cent, the specificity was 86 per cent, and the accuracy was 57 per cent, whereas the sensitivity of the indium-labeled-leukocyte technique was 83 per cent, the specificity was 86 per cent, and the accuracymore » was 83 per cent. When the additional twelve patients for whom surgery was deemed unnecessary were considered, the sensitivity of sequential Tc-Ga imaging was 50 per cent, the specificity was 78 per cent, and the accuracy was 62 per cent, as compared with a sensitivity of 83 per cent, a specificity of 94 per cent, and an accuracy of 88 per cent with the indium-labeled-leukocyte method. In patients with a prosthesis the indium-labeled-leukocyte image was 94 per cent accurate, compared with 75 per cent accuracy for sequential Tc-Ga imaging. Statistical analysis of these data demonstrated that the indium-labeled-leukocyte technique was superior to sequential Tc-Ga imaging in detecting areas of low-grade musculoskeletal sepsis.« less

A dual-labeled knottin peptide for PET and near-infrared fluorescence imaging of integrin expression in living subjects

PubMed Central

Kimura, Richard H.; Miao, Zheng; Cheng, Zhen; Gambhir, Sanjiv S.; Cochran, Jennifer R.

2010-01-01

Previously, we used directed evolution to engineer mutants of the Ecballium elaterium trypsin inhibitor (EETI-II) knottin that bind to αvβ3 and αvβ5 integrin receptors with low nanomolar affinity, and showed that Cy5.5- or 64Cu-DOTA-labeled knottin peptides could be used to image integrin expression in mouse tumor models using near-infrared fluorescence (NIRF) imaging or positron emission tomography (PET). Here, we report the development of a dual-labeled knottin peptide conjugated to both NIRF and PET imaging agents for multimodality imaging in living subjects. We created an orthogonally-protected peptide-based linker for stoichiometric coupling of 64Cu-DOTA and Cy5.5 onto the knottin N-terminus, and confirmed that conjugation did not affect binding to αvβ3 and αvβ5 integrins. NIRF and PET imaging studies in tumor xenograft models showed that Cy5.5 conjugation significantly increased kidney uptake and retention compared to the knottin peptide labeled with 64Cu-DOTA alone. In the tumor, the dual-labeled 64Cu-DOTA/Cy5.5 knottin probe showed decreased wash-out leading to significantly better retention (p < 0.05) compared to the 64Cu-DOTA-labeled knottin probe. Tumor uptake was significantly reduced (p < 0.05) when the dual-labeled probe was co-injected with an excess of unlabeled competitor and when tested in a tumor model with lower levels of integrin expression. Finally, plots of tumor-to-background tissue ratios for Cy5.5 versus 64Cu uptake were well correlated over several time points post injection, demonstrating pharmacokinetic cross validation of imaging labels. This dual-modality NIRF/PET imaging agent is promising for further development in clinical applications where high sensitivity and high-resolution are desired, such as detection of tumors located deep within the body and image-guided surgical resection. PMID:20131753

76 FR 24494 - Draft Guidance for Industry and FDA Staff: Processing/Reprocessing Medical Devices in Health Care...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-02

...] Draft Guidance for Industry and FDA Staff: Processing/ Reprocessing Medical Devices in Health Care... Devices in Health Care Settings: Validation Methods and Labeling.'' The recommendations in this guidance... Staff: Processing/Reprocessing Medical Devices in Health Care Settings: Validation Methods and Labeling...

Simultaneous acquisition of perfusion image and dynamic MR angiography using time‐encoded pseudo‐continuous ASL

PubMed Central

Helle, Michael; Koken, Peter; Van Cauteren, Marc; van Osch, Matthias J. P.

2017-01-01

Purpose Both dynamic magnetic resonance angiography (4D‐MRA) and perfusion imaging can be acquired by using arterial spin labeling (ASL). While 4D‐MRA highlights large vessel pathology, such as stenosis or collateral blood flow patterns, perfusion imaging provides information on the microvascular status. Therefore, a complete picture of the cerebral hemodynamic condition could be obtained by combining the two techniques. Here, we propose a novel technique for simultaneous acquisition of 4D‐MRA and perfusion imaging using time‐encoded pseudo‐continuous arterial spin labeling. Methods The time‐encoded pseudo‐continuous arterial spin labeling module consisted of a first subbolus that was optimized for perfusion imaging by using a labeling duration of 1800 ms, whereas the other six subboli of 130 ms were used for encoding the passage of the labeled spins through the arterial system for 4D‐MRA acquisition. After the entire labeling module, a multishot 3D turbo‐field echo‐planar‐imaging readout was executed for the 4D‐MRA acquisition, immediately followed by a single‐shot, multislice echo‐planar‐imaging readout for perfusion imaging. The optimal excitation flip angle for the 3D turbo‐field echo‐planar‐imaging readout was investigated by evaluating the image quality of the 4D‐MRA and perfusion images as well as the accuracy of the estimated cerebral blood flow values. Results When using 36 excitation radiofrequency pulses with flip angles of 5 or 7.5°, the saturation effects of the 3D turbo‐field echo‐planar‐imaging readout on the perfusion images were relatively moderate and after correction, there were no statistically significant differences between the obtained cerebral blood flow values and those from traditional time‐encoded pseudo‐continuous arterial spin labeling. Conclusions This study demonstrated that simultaneous acquisition of 4D‐MRA and perfusion images can be achieved by using time‐encoded pseudo‐continuous arterial spin labeling. Magn Reson Med 79:2676–2684, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. PMID:28913838

Comprehension by older people of medication information with or without supplementary pharmaceutical pictograms.

PubMed

Ng, Annie W Y; Chan, Alan H S; Ho, Vincy W S

2017-01-01

This study examined the benefits of pharmaceutical pictograms for improving comprehension of medication information for older people. Fifty Hong Kong Chinese older people completed a medical information comprehension task for five drugs. Participants in the control group were presented with text labels while those in the experimental group were given the text labels plus supplementary pharmaceutical pictograms, and then all reported their understanding of the medication information conveyed. Lower educated older people had poorer understanding of medication information. The addition of pharmaceutical pictograms significantly improved the comprehension of medication information for older people. The majority of older people tested with pictograms favored adding pictograms to text and thought the pictograms were useful for conveying medical information rather than using written text alone. The findings suggested that pharmaceutical and health care professionals should include pharmaceutical pictograms on labels to better convey instructions on medication to older people. Copyright © 2016 Elsevier Ltd. All rights reserved.

The effect of illustrations on patient comprehension of medication instruction labels

PubMed Central

Hwang, Stephen W; Tram, Carolyn QN; Knarr, Nadia

2005-01-01

Background Labels with special instructions regarding how a prescription medication should be taken or its possible side effects are often applied to pill bottles. The goal of this study was to determine whether the addition of illustrations to these labels affects patient comprehension. Methods Study participants (N = 130) were enrolled by approaching patients at three family practice clinics in Toronto, Canada. Participants were asked to interpret two sets of medication instruction labels, the first with text only and the second with the same text accompanied by illustrations. Two investigators coded participants' responses as incorrect, partially correct, or completely correct. Health literacy levels of participants were measured using a validated instrument, the REALM test. Results All participants gave a completely correct interpretation for three out of five instruction labels, regardless of whether illustrations were present or not. For the two most complex labels, only 34–55% of interpretations of the text-only version were completely correct. The addition of illustrations was associated with improved performance in 5–7% of subjects and worsened performance in 7–9% of subjects. Conclusion The commonly-used illustrations on the medication labels used in this study were of little or no use in improving patients' comprehension of the accompanying written instructions. PMID:15960849

Communicating doses of pediatric liquid medicines to parents/caregivers: a comparison of written dosing directions on prescriptions with labels applied by dispensed pharmacy.

PubMed

Shah, Rita; Blustein, Leona; Kuffner, Ed; Davis, Lisa

2014-03-01

To identify and compare volumetric measures used by healthcare providers in communicating dosing instructions for pediatric liquid prescriptions to parents/caregivers. Dosing instructions were retrospectively reviewed for the 10 most frequently prescribed liquid medications dispensed from 4 community pharmacies for patients aged ≤ 12 years during a 3-month period. Volumetric measures on original prescriptions (ie, milliliters, teaspoons) were compared with those utilized by the pharmacist on the pharmacy label dispensed to the parent/caregiver. Of 649 prescriptions and corresponding pharmacy labels evaluated, 68% of prescriptions and 62% of pharmacy labels communicated dosing in milliliters, 24% of prescriptions and 29% of pharmacy labels communicated dosing in teaspoonfuls, 7% of prescriptions and 0% of pharmacy labels communicated dosing in other measures (ie, milligrams, cubic centimeters, "dose"), and 25% of dispensed pharmacy labels did not reflect units as written in the prescription. Volumetric measures utilized by healthcare professionals in dosing instructions for prescription pediatric oral liquid medications are not consistent. Healthcare professionals and parents/caregivers should be educated on safe dosing practices for liquid pediatric medications. Generalizability to the larger pediatric population may vary depending on pharmacy chain, location, and medications evaluated. Copyright © 2014 Mosby, Inc. All rights reserved.

Multi-label classification of chronically ill patients with bag of words and supervised dimensionality reduction algorithms.

PubMed

Bromuri, Stefano; Zufferey, Damien; Hennebert, Jean; Schumacher, Michael

2014-10-01

This research is motivated by the issue of classifying illnesses of chronically ill patients for decision support in clinical settings. Our main objective is to propose multi-label classification of multivariate time series contained in medical records of chronically ill patients, by means of quantization methods, such as bag of words (BoW), and multi-label classification algorithms. Our second objective is to compare supervised dimensionality reduction techniques to state-of-the-art multi-label classification algorithms. The hypothesis is that kernel methods and locality preserving projections make such algorithms good candidates to study multi-label medical time series. We combine BoW and supervised dimensionality reduction algorithms to perform multi-label classification on health records of chronically ill patients. The considered algorithms are compared with state-of-the-art multi-label classifiers in two real world datasets. Portavita dataset contains 525 diabetes type 2 (DT2) patients, with co-morbidities of DT2 such as hypertension, dyslipidemia, and microvascular or macrovascular issues. MIMIC II dataset contains 2635 patients affected by thyroid disease, diabetes mellitus, lipoid metabolism disease, fluid electrolyte disease, hypertensive disease, thrombosis, hypotension, chronic obstructive pulmonary disease (COPD), liver disease and kidney disease. The algorithms are evaluated using multi-label evaluation metrics such as hamming loss, one error, coverage, ranking loss, and average precision. Non-linear dimensionality reduction approaches behave well on medical time series quantized using the BoW algorithm, with results comparable to state-of-the-art multi-label classification algorithms. Chaining the projected features has a positive impact on the performance of the algorithm with respect to pure binary relevance approaches. The evaluation highlights the feasibility of representing medical health records using the BoW for multi-label classification tasks. The study also highlights that dimensionality reduction algorithms based on kernel methods, locality preserving projections or both are good candidates to deal with multi-label classification tasks in medical time series with many missing values and high label density. Copyright © 2014 Elsevier Inc. All rights reserved.

Efficient Multi-Atlas Registration using an Intermediate Template Image

PubMed Central

Dewey, Blake E.; Carass, Aaron; Blitz, Ari M.; Prince, Jerry L.

2017-01-01

Multi-atlas label fusion is an accurate but time-consuming method of labeling the human brain. Using an intermediate image as a registration target can allow researchers to reduce time constraints by storing the deformations required of the atlas images. In this paper, we investigate the effect of registration through an intermediate template image on multi-atlas label fusion and propose a novel registration technique to counteract the negative effects of through-template registration. We show that overall computation time can be decreased dramatically with minimal impact on final label accuracy and time can be exchanged for improved results in a predictable manner. We see almost complete recovery of Dice similarity over a simple through-template registration using the corrected method and still maintain a 3–4 times speed increase. Further, we evaluate the effectiveness of this method on brains of patients with normal-pressure hydrocephalus, where abnormal brain shape presents labeling difficulties, specifically the ventricular labels. Our correction method creates substantially better ventricular labeling than traditional methods and maintains the speed increase seen in healthy subjects. PMID:28943702

Efficient multi-atlas registration using an intermediate template image

NASA Astrophysics Data System (ADS)

Dewey, Blake E.; Carass, Aaron; Blitz, Ari M.; Prince, Jerry L.

2017-03-01

Multi-atlas label fusion is an accurate but time-consuming method of labeling the human brain. Using an intermediate image as a registration target can allow researchers to reduce time constraints by storing the deformations required of the atlas images. In this paper, we investigate the effect of registration through an intermediate template image on multi-atlas label fusion and propose a novel registration technique to counteract the negative effects of through-template registration. We show that overall computation time can be decreased dramatically with minimal impact on final label accuracy and time can be exchanged for improved results in a predictable manner. We see almost complete recovery of Dice similarity over a simple through-template registration using the corrected method and still maintain a 3-4 times speed increase. Further, we evaluate the effectiveness of this method on brains of patients with normal-pressure hydrocephalus, where abnormal brain shape presents labeling difficulties, specifically the ventricular labels. Our correction method creates substantially better ventricular labeling than traditional methods and maintains the speed increase seen in healthy subjects.

Three-dimensional spatiotemporal features for fast content-based retrieval of focal liver lesions.

PubMed

Roy, Sharmili; Chi, Yanling; Liu, Jimin; Venkatesh, Sudhakar K; Brown, Michael S

2014-11-01

Content-based image retrieval systems for 3-D medical datasets still largely rely on 2-D image-based features extracted from a few representative slices of the image stack. Most 2 -D features that are currently used in the literature not only model a 3-D tumor incompletely but are also highly expensive in terms of computation time, especially for high-resolution datasets. Radiologist-specified semantic labels are sometimes used along with image-based 2-D features to improve the retrieval performance. Since radiological labels show large interuser variability, are often unstructured, and require user interaction, their use as lesion characterizing features is highly subjective, tedious, and slow. In this paper, we propose a 3-D image-based spatiotemporal feature extraction framework for fast content-based retrieval of focal liver lesions. All the features are computer generated and are extracted from four-phase abdominal CT images. Retrieval performance and query processing times for the proposed framework is evaluated on a database of 44 hepatic lesions comprising of five pathological types. Bull's eye percentage score above 85% is achieved for three out of the five lesion pathologies and for 98% of query lesions, at least one same type of lesion is ranked among the top two retrieved results. Experiments show that the proposed system's query processing is more than 20 times faster than other already published systems that use 2-D features. With fast computation time and high retrieval accuracy, the proposed system has the potential to be used as an assistant to radiologists for routine hepatic tumor diagnosis.

Google glass based immunochromatographic diagnostic test analysis

NASA Astrophysics Data System (ADS)

Feng, Steve; Caire, Romain; Cortazar, Bingen; Turan, Mehmet; Wong, Andrew; Ozcan, Aydogan

2015-03-01

Integration of optical imagers and sensors into recently emerging wearable computational devices allows for simpler and more intuitive methods of integrating biomedical imaging and medical diagnostics tasks into existing infrastructures. Here we demonstrate the ability of one such device, the Google Glass, to perform qualitative and quantitative analysis of immunochromatographic rapid diagnostic tests (RDTs) using a voice-commandable hands-free software-only interface, as an alternative to larger and more bulky desktop or handheld units. Using the built-in camera of Glass to image one or more RDTs (labeled with Quick Response (QR) codes), our Glass software application uploads the captured image and related information (e.g., user name, GPS, etc.) to our servers for remote analysis and storage. After digital analysis of the RDT images, the results are transmitted back to the originating Glass device, and made available through a website in geospatial and tabular representations. We tested this system on qualitative human immunodeficiency virus (HIV) and quantitative prostate-specific antigen (PSA) RDTs. For qualitative HIV tests, we demonstrate successful detection and labeling (i.e., yes/no decisions) for up to 6-fold dilution of HIV samples. For quantitative measurements, we activated and imaged PSA concentrations ranging from 0 to 200 ng/mL and generated calibration curves relating the RDT line intensity values to PSA concentration. By providing automated digitization of both qualitative and quantitative test results, this wearable colorimetric diagnostic test reader platform on Google Glass can reduce operator errors caused by poor training, provide real-time spatiotemporal mapping of test results, and assist with remote monitoring of various biomedical conditions.

On-the-spot lung cancer differential diagnosis by label-free, molecular vibrational imaging and knowledge-based classification

NASA Astrophysics Data System (ADS)

Gao, Liang; Li, Fuhai; Thrall, Michael J.; Yang, Yaliang; Xing, Jiong; Hammoudi, Ahmad A.; Zhao, Hong; Massoud, Yehia; Cagle, Philip T.; Fan, Yubo; Wong, Kelvin K.; Wang, Zhiyong; Wong, Stephen T. C.

2011-09-01

We report the development and application of a knowledge-based coherent anti-Stokes Raman scattering (CARS) microscopy system for label-free imaging, pattern recognition, and classification of cells and tissue structures for differentiating lung cancer from non-neoplastic lung tissues and identifying lung cancer subtypes. A total of 1014 CARS images were acquired from 92 fresh frozen lung tissue samples. The established pathological workup and diagnostic cellular were used as prior knowledge for establishment of a knowledge-based CARS system using a machine learning approach. This system functions to separate normal, non-neoplastic, and subtypes of lung cancer tissues based on extracted quantitative features describing fibrils and cell morphology. The knowledge-based CARS system showed the ability to distinguish lung cancer from normal and non-neoplastic lung tissue with 91% sensitivity and 92% specificity. Small cell carcinomas were distinguished from nonsmall cell carcinomas with 100% sensitivity and specificity. As an adjunct to submitting tissue samples to routine pathology, our novel system recognizes the patterns of fibril and cell morphology, enabling medical practitioners to perform differential diagnosis of lung lesions in mere minutes. The demonstration of the strategy is also a necessary step toward in vivo point-of-care diagnosis of precancerous and cancerous lung lesions with a fiber-based CARS microendoscope.

Measured body composition and geometrical data of four ``virtual family'' members for thermoregulatory modeling

NASA Astrophysics Data System (ADS)

Xu, Xiaojiang; Rioux, Timothy P.; MacLeod, Tynan; Patel, Tejash; Rome, Maxwell N.; Potter, Adam W.

2017-03-01

The purpose of this paper is to develop a database of tissue composition, distribution, volume, surface area, and skin thickness from anatomically correct human models, the virtual family. These models were based on high-resolution magnetic resonance imaging (MRI) of human volunteers, including two adults (male and female) and two children (boy and girl). In the segmented image dataset, each voxel is associated with a label which refers to a tissue type that occupies up that specific cubic millimeter of the body. The tissue volume was calculated from the number of the voxels with the same label. Volumes of 24 organs in body and volumes of 7 tissues in 10 specific body regions were calculated. Surface area was calculated from the collection of voxels that are touching the exterior air. Skin thicknesses were estimated from its volume and surface area. The differences between the calculated and original masses were about 3 % or less for tissues or organs that are important to thermoregulatory modeling, e.g., muscle, skin, and fat. This accurate database of body tissue distributions and geometry is essential for the development of human thermoregulatory models. Data derived from medical imaging provide new effective tools to enhance thermal physiology research and gain deeper insight into the mechanisms of how the human body maintains heat balance.

Readability of prescription labels and medication recall in a population of tertiary referral glaucoma patients.

PubMed

O'Hare, Fleur; Jeganathan, V Swetha E; Rokahr, Catherine G; Rogers, Sophie L; Crowston, Jonathan G

2009-12-01

To evaluate readability of eye drop labels and accurate recall of prescription instructions in a glaucoma population. A hospital-based, cross-sectional study. A trained, interviewer examined patient ability to read standard and larger font medication labels. A questionnaire was administered to ascertain accurate recall of prescribed eye drops. Clinical information was obtained through independent chart review. Glaucoma severity was classified according to a glaucoma staging system. The setting for the study was the glaucoma outpatient clinic, Royal Victorian Eye and Ear Hospital (Melbourne, Australia), a major tertiary referral centre. A total of 200 glaucoma patients (96.2% response), aged 45-90 years, on eye drops took part in the study. Non-English-speaking patients were excluded. The main outcome measure was the ability to read prescribed medication labels and accurately recall treatment regime was compared with glaucoma severity and the number of eye drops. Of the glaucoma patients, 12% were unable to read standard pharmacy labels. Only 5.5% were unable to read the larger font labels. Of the patients, 32% were not able to accurately recall the type of drops or prescribed frequency of instillation. An inability to read standard labels was associated with a threefold reduction in the likelihood of accurate medication recall (95% confidence intervals, 1.40-7.66, P < 0.05). Patients with three or more types of eye drops were five times less likely to recall their medications (95% confidence interval, 0.07-0.57, P < 0.05). Inability to read or recall prescribed eye drops was associated with glaucoma severity and the number of prescribed eye drops. These factors may impact significantly on patients' adherence to glaucoma medications.

Room-temperature storage of medications labeled for refrigeration.

PubMed

Cohen, Victor; Jellinek, Samantha P; Teperikidis, Leftherios; Berkovits, Elliot; Goldman, William M

2007-08-15

Data regarding the recommended maximum duration that refrigerated medications available in hospital pharmacies may be stored safely at room temperature were collected and compiled in a tabular format. During May and June of 2006, the prescribing information for medications labeled for refrigeration as obtained from the supplier were reviewed for data addressing room-temperature storage. Telephone surveys of the products' manufacturers were conducted when this information was not available in the prescribing information. Medications were included in the review if they were labeled to be stored at 2-8 degrees C and purchased by the pharmacy department for uses indicated on the hospital formulary. Frozen antibiotics thawed in the refrigerator and extemporaneously compounded medications were excluded. Information was compiled and arranged in tabular format. The U.S. Pharmacopeia's definition of room temperature (20-25 degrees C [68-77 degrees F]) was used for this review. Of the 189 medications listed in AHFS Drug Information 2006 for storage in a refrigerator, 89 were present in the pharmacy department's refrigerator. Since six manufacturers were unable to provide information for 10 medications, only 79 medications were included in the review. This table may help to avoid unnecessary drug loss and expenditures due to improper storage temperatures. Information regarding the room-temperature storage of 79 medications labeled for refrigerated storage was compiled.

Off-Label Drug Use

MedlinePlus

... their drugs for off-label uses. Off-label marketing is very different from off-label use. Why ... at a higher risk for medication errors, side effects, and unwanted drug reactions. It’s important that the ...

Embedding and Chemical Reactivation of Green Fluorescent Protein in the Whole Mouse Brain for Optical Micro-Imaging

PubMed Central

Gang, Yadong; Zhou, Hongfu; Jia, Yao; Liu, Ling; Liu, Xiuli; Rao, Gong; Li, Longhui; Wang, Xiaojun; Lv, Xiaohua; Xiong, Hanqing; Yang, Zhongqin; Luo, Qingming; Gong, Hui; Zeng, Shaoqun

2017-01-01

Resin embedding has been widely applied to fixing biological tissues for sectioning and imaging, but has long been regarded as incompatible with green fluorescent protein (GFP) labeled sample because it reduces fluorescence. Recently, it has been reported that resin-embedded GFP-labeled brain tissue can be imaged with high resolution. In this protocol, we describe an optimized protocol for resin embedding and chemical reactivation of fluorescent protein labeled mouse brain, we have used mice as experiment model, but the protocol should be applied to other species. This method involves whole brain embedding and chemical reactivation of the fluorescent signal in resin-embedded tissue. The whole brain embedding process takes a total of 7 days. The duration of chemical reactivation is ~2 min for penetrating 4 μm below the surface in the resin-embedded brain. This protocol provides an efficient way to prepare fluorescent protein labeled sample for high-resolution optical imaging. This kind of sample was demonstrated to be imaged by various optical micro-imaging methods. Fine structures labeled with GFP across a whole brain can be detected. PMID:28352214

Label-free chemical imaging of live Euglena gracilis by high-speed SRS spectral microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wakisaka, Yoshifumi; Suzuki, Yuta; Tokunaga, Kyoya; Hirose, Misa; Domon, Ryota; Akaho, Rina; Kuroshima, Mai; Tsumura, Norimichi; Shimobaba, Tomoyoshi; Iwata, Osamu; Suzuki, Kengo; Nakashima, Ayaka; Goda, Keisuke; Ozeki, Yasuyuki

2016-03-01

Microbes, especially microalgae, have recently been of great interest for developing novel biofuels, drugs, and biomaterials. Imaging-based screening of live cells can provide high selectivity and is attractive for efficient bio-production from microalgae. Although conventional cellular screening techniques use cell labeling, labeling of microbes is still under development and can interfere with their cellular functions. Furthermore, since live microbes move and change their shapes rapidly, a high-speed imaging technique is required to suppress motion artifacts. Stimulated Raman scattering (SRS) microscopy allows for label-free and high-speed spectral imaging, which helps us visualize chemical components inside biological cells and tissues. Here we demonstrate high-speed SRS imaging, with temporal resolution of 0.14 seconds, of intracellular distributions of lipid, polysaccharide, and chlorophyll concentrations in rapidly moving Euglena gracilis, a unicellular phytoflagellate. Furthermore, we show that our method allows us to analyze the amount of chemical components inside each living cell. Our results indicate that SRS imaging may be applied to label-free screening of living microbes based on chemical information.

Controlling off-label medication use.

PubMed

Gillick, Muriel R

2009-03-03

Off-label prescribing may lead to innovative new uses of old medications, is essential in such fields as pediatrics, and avoids the lengthy and expensive process of modifying U.S. Food and Drug Administration (FDA) drug labeling. Using medications for unapproved indications, however, raises concerns about patient safety when the drugs have a high potential for toxicity and generates economic concerns when their cost is high. A possible means of controlling the use of off-label drugs is to focus on medications used off-label that are both expensive and potentially risky. These are principally biotechnology drugs, such as recombinant enzymes, cytokines, and monoclonal antibodies. This article suggests a 2-step process for controlling use of such drugs, analogous to that used for devices. Once a drug is FDA approved, it would undergo scrutiny using the Centers for Medicare & Medicaid Services (CMS) National Coverage Determination method if its cost exceeds a specified benchmark-for example, $12 000, which is the average cost of a pacemaker. The CMS would pay only for off-label uses for which there is adequate evidence in its National Coverage Determination process. Other insurance companies would probably adopt the recommendations of CMS.

Traceless affinity labeling of endogenous proteins for functional analysis in living cells.

PubMed

Hayashi, Takahiro; Hamachi, Itaru

2012-09-18

Protein labeling and imaging techniques have provided tremendous opportunities to study the structure, function, dynamics, and localization of individual proteins in the complex environment of living cells. Molecular biology-based approaches, such as GFP-fusion tags and monoclonal antibodies, have served as important tools for the visualization of individual proteins in cells. Although these techniques continue to be valuable for live cell imaging, they have a number of limitations that have only been addressed by recent progress in chemistry-based approaches. These chemical approaches benefit greatly from the smaller probe sizes that should result in fewer perturbations to proteins and to biological systems as a whole. Despite the research in this area, so far none of these labeling techniques permit labeling and imaging of selected endogenous proteins in living cells. Researchers have widely used affinity labeling, in which the protein of interest is labeled by a reactive group attached to a ligand, to identify and characterize proteins. Since the first report of affinity labeling in the early 1960s, efforts to fine-tune the chemical structures of both the reactive group and ligand have led to protein labeling with excellent target selectivity in the whole proteome of living cells. Although the chemical probes used for affinity labeling generally inactivate target proteins, this strategy holds promise as a valuable tool for the labeling and imaging of endogenous proteins in living cells and by extension in living animals. In this Account, we summarize traceless affinity labeling, a technique explored mainly in our laboratory. In our overview of the different labeling techniques, we emphasize the challenge of designing chemical probes that allow for dissociation of the affinity module (often a ligand) after the labeling reaction so that the labeled protein retains its native function. This feature distinguishes the traceless labeling approach from the traditional affinity labeling method and allows for real-time monitoring of protein activity. With the high target specificity and biocompatibility of this technique, we have achieved individual labeling and imaging of endogenously expressed proteins in samples of high biological complexity. We also highlight applications in which our current approach enabled the monitoring of important biological events, such as ligand binding, in living cells. These novel chemical labeling techniques are expected to provide a molecular toolbox for studying a wide variety of proteins and beyond in living cells.

An Interactive User Interface for Drug Labeling to Improve Readability and Decision-Making

PubMed Central

Abedtash, Hamed; Duke, Jon D.

2015-01-01

FDA-approved prescribing information (also known as product labeling or labels) contain critical safety information for health care professionals. Drug labels have often been criticized, however, for being overly complex, difficult to read, and rife with overwarning, leading to high cognitive load. In this project, we aimed to improve the usability of drug labels by increasing the ‘signal-to-noise ratio’ and providing meaningful information to care providers based on patient-specific comorbidities and concomitant medications. In the current paper, we describe the design process and resulting web application, known as myDrugLabel. Using the Structured Product Label documents as a base, we describe the process of label personalization, readability improvements, and integration of diverse evidence sources, including the medical literature from PubMed, pharmacovigilance reports from FDA adverse event reporting system (FAERS), and social media signals directly into the label. PMID:26958158

An Interactive User Interface for Drug Labeling to Improve Readability and Decision-Making.

PubMed

Abedtash, Hamed; Duke, Jon D

FDA-approved prescribing information (also known as product labeling or labels) contain critical safety information for health care professionals. Drug labels have often been criticized, however, for being overly complex, difficult to read, and rife with overwarning, leading to high cognitive load. In this project, we aimed to improve the usability of drug labels by increasing the 'signal-to-noise ratio' and providing meaningful information to care providers based on patient-specific comorbidities and concomitant medications. In the current paper, we describe the design process and resulting web application, known as myDrugLabel. Using the Structured Product Label documents as a base, we describe the process of label personalization, readability improvements, and integration of diverse evidence sources, including the medical literature from PubMed, pharmacovigilance reports from FDA adverse event reporting system (FAERS), and social media signals directly into the label.

The Symmetry Rule: A Seven-Year Study of Symptoms and Explanatory Labels Among GulfWar Veterans

PubMed Central

Brewer, Noel T.; Hallman, William K.; Kipen, Howard M.

2014-01-01

Noticing medical symptoms can cause one to search for explanatory labels such as “ate bad food” or even “exposed to anthrax,” and perhaps these labels may cause new symptom reports. The present study examined whether there is empirical support for this symptom-label “symmetry rule.” We interviewed veterans (N = 362) from the Gulf War Registry in 1995 and 2002 about their medical symptoms and about their exposure to war-related hazards and stressors. Health symptom reports were strongly correlated between the two time periods and showed relatively stable mean levels, whereas recall of war-related exposures was notably unstable. Veterans starting with fewer medical symptoms recalled fewer war-related exposures seven years later. Initial recollection of chemical and biological warfare exposure (but not other exposures) longitudinally predicted novel medical symptoms. The findings generally support the symmetry rule hypotheses, although the evidence for the label to symptom link was less strong. The findings account for some variability in symptoms and exposure recall over time, but they do not, on their own, account for the Gulf War veterans’ elevated number of unexplained medical symptoms. PMID:18795995

Automated identification of cone photoreceptors in adaptive optics retinal images.

PubMed

Li, Kaccie Y; Roorda, Austin

2007-05-01

In making noninvasive measurements of the human cone mosaic, the task of labeling each individual cone is unavoidable. Manual labeling is a time-consuming process, setting the motivation for the development of an automated method. An automated algorithm for labeling cones in adaptive optics (AO) retinal images is implemented and tested on real data. The optical fiber properties of cones aided the design of the algorithm. Out of 2153 manually labeled cones from six different images, the automated method correctly identified 94.1% of them. The agreement between the automated and the manual labeling methods varied from 92.7% to 96.2% across the six images. Results between the two methods disagreed for 1.2% to 9.1% of the cones. Voronoi analysis of large montages of AO retinal images confirmed the general hexagonal-packing structure of retinal cones as well as the general cone density variability across portions of the retina. The consistency of our measurements demonstrates the reliability and practicality of having an automated solution to this problem.

SVM Pixel Classification on Colour Image Segmentation

NASA Astrophysics Data System (ADS)

Barui, Subhrajit; Latha, S.; Samiappan, Dhanalakshmi; Muthu, P.

2018-04-01

The aim of image segmentation is to simplify the representation of an image with the help of cluster pixels into something meaningful to analyze. Segmentation is typically used to locate boundaries and curves in an image, precisely to label every pixel in an image to give each pixel an independent identity. SVM pixel classification on colour image segmentation is the topic highlighted in this paper. It holds useful application in the field of concept based image retrieval, machine vision, medical imaging and object detection. The process is accomplished step by step. At first we need to recognize the type of colour and the texture used as an input to the SVM classifier. These inputs are extracted via local spatial similarity measure model and Steerable filter also known as Gabon Filter. It is then trained by using FCM (Fuzzy C-Means). Both the pixel level information of the image and the ability of the SVM Classifier undergoes some sophisticated algorithm to form the final image. The method has a well developed segmented image and efficiency with respect to increased quality and faster processing of the segmented image compared with the other segmentation methods proposed earlier. One of the latest application result is the Light L16 camera.

Off-Label Prescribing for Children with Migraines in U.S. Ambulatory Care Settings.

PubMed

Lai, L Leanne; Koh, Leroy; Ho, Jane Ai-Chen; Ting, Alexander; Obi, Augustine

2017-03-01

Migraines, Which Affect About 10% Of School-Age Children In The United States, Can Significantly Impair Quality Of Life. Despite Potential Disability, Many Children Do Not Receive Treatment Or Prophylaxis, Since Medications Specifically Approved For Children Are Significantly Less Than For Adults. There Is Also Controversy Surrounding The Apparent Widespread Practice Of Prescribing Off-Label Medications For Children With Migraines. However, Little Research Has Been Done To Identify Physician-Prescribing Patterns Of Migraine Medication For Children. To Investigate The Prevalence And Pattern Of Off-Label Prescribing For Children With Migraines. A Secondary Data Analysis Was Conducted Using The Pooled National Ambulatory Medical Care Survey (Namcs) 2011 And 2012. Patients Aged 17 Years Or Younger With A Migraine Diagnosis Were Included. A Series Of Weighted Descriptive Analyses Were Used To Estimate The Prevalence Of Migraine Drugs Prescribed During Pediatric Office Visits. A Weighted Logistic Regression Was Constructed To Compare The Prescribing Patterns Between Off-Label And Fda-Approved Medications. Analyses Used Sas 9.4 Methodology And Incorporated Sample Weights To Adjust For The Complex Sampling Design Employed By Namcs. Of The 12.9 Million Outpatient Visits With A Migraine Diagnosis That Took Place Between 2010 And 2012, 1.2 Million Were Pediatric Visits. Females Accounted For Nearly Twice The Number Of Migraine Visits Than Males (66% Vs. 34%). Children Aged 12-17 Years Accounted For The Highest Frequency Of Visits (84%), Compared With Those Aged Under 12 Years (16%). 66.7% Of These Pediatric Patients Received At Least 1 Migraine Drug. Of These, Off-Label Medications Were Prescribed 1.5 Times More Than Fda-Approved Medications For Children (60.34% Vs. 39.65%). The Results Of Logistic Regression Showed A Significant Likelihood Of Prescribing Off-Label Medications Based On Physician Specialty, Patient Race, And Reason For Visit. Neurologists (Or = 0.028, P < 0.05) And Pediatricians (Or = 0.095, P < 0.05) Were Less Likely To Prescribe Off-Label Drugs Than General And Family Practitioners. Visits For Preventive Care (Or = 5.8, P < 0.05) And Flare-Ups From Chronic Migraines (Or = 5.0, P < 0.05) Were More Likely To Result In Off-Label Drug Prescriptions Than Visits For New Migraine Incidence. This Study Provides Significant Real-World Evidence Of The Widespread Practice Of Prescribing Off-Label Drugs To Children With Migraines. Although Medical Literature Shows That Off-Label Prescribing May Not Be Harmful, There Is A Dearth Of Research And Practice Guidelines To Help Practitioners Uphold Safety Standards And Ensure The Prescription Of Age-Appropriate Medications To Children. No outside funding supported this study. The authors report no potential conflicts of interest relevant to this research. Lai and Ting contributed to study concept and design and collected the data, along with the other authors. Data interpretation was performed by Lai, Koh, Obi, Ho, and Ting. The manuscript was written and revised by Lai, Koh, and Ho, with assistance from Ting and Obi.

Technical Note: Deep learning based MRAC using rapid ultra-short echo time imaging.

PubMed

Jang, Hyungseok; Liu, Fang; Zhao, Gengyan; Bradshaw, Tyler; McMillan, Alan B

2018-05-15

In this study, we explore the feasibility of a novel framework for MR-based attenuation correction for PET/MR imaging based on deep learning via convolutional neural networks, which enables fully automated and robust estimation of a pseudo CT image based on ultrashort echo time (UTE), fat, and water images obtained by a rapid MR acquisition. MR images for MRAC are acquired using dual echo ramped hybrid encoding (dRHE), where both UTE and out-of-phase echo images are obtained within a short single acquisition (35 sec). Tissue labeling of air, soft tissue, and bone in the UTE image is accomplished via a deep learning network that was pre-trained with T1-weighted MR images. UTE images are used as input to the network, which was trained using labels derived from co-registered CT images. The tissue labels estimated by deep learning are refined by a conditional random field based correction. The soft tissue labels are further separated into fat and water components using the two-point Dixon method. The estimated bone, air, fat, and water images are then assigned appropriate Hounsfield units, resulting in a pseudo CT image for PET attenuation correction. To evaluate the proposed MRAC method, PET/MR imaging of the head was performed on 8 human subjects, where Dice similarity coefficients of the estimated tissue labels and relative PET errors were evaluated through comparison to a registered CT image. Dice coefficients for air (within the head), soft tissue, and bone labels were 0.76±0.03, 0.96±0.006, and 0.88±0.01. In PET quantification, the proposed MRAC method produced relative PET errors less than 1% within most brain regions. The proposed MRAC method utilizing deep learning with transfer learning and an efficient dRHE acquisition enables reliable PET quantification with accurate and rapid pseudo CT generation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Research into the origins and characteristics of unicorns: mental illness as the unicorn.

PubMed

Simon, L

2000-01-01

Basic research, particularly into the psychological and neurological underpinnings of schizophrenia and other "mental illnesses," is flawed because of its adherence to the ideology that unwanted, hard-to-understand behavior constitutes true medical illness. It is argued here that psychiatric diagnostic terms represent moral judgments rather than medical entities. By reducing experimental subjects to a moral label, and assuming that neurological differences associated with unwanted behavior are brain diseases, researchers fail to take into account the conscious experience, organization of self and self-image, patterns of motivation, history and social contexts of their patients. The failure to consider the psychology of their subjects renders the results of these studies ambiguous and irrelevant for any uses except bolstering the biomedical model of psychiatry.

Impact of brand or generic labeling on medication effectiveness and side effects.

PubMed

Faasse, Kate; Martin, Leslie R; Grey, Andrew; Gamble, Greg; Petrie, Keith J

2016-02-01

Branding medication with a known pharmaceutical company name or product name bestows on the drug an added assurance of authenticity and effectiveness compared to a generic preparation. This study examined the impact of brand name and generic labeling on medication effectiveness and side effects. 87 undergraduate students with frequent headaches took part in the study. Using a within-subjects counterbalanced design, each participant took tablets labeled either as brand name "Nurofen" or "Generic Ibuprofen" to treat each of 4 headaches. In reality, half of the tablets were placebos, and half were active ibuprofen (400 mg). Participants recorded their headache pain on a verbal descriptor and visual analogue scale prior to taking the tablets, and again 1 hour afterward. Medication side effects were also reported. Pain reduction following the use of brand name labeled tablets was similar in active ibuprofen or a placebo. However, if the tablets had a generic label, placebo tablets were significantly less effective compared to active ibuprofen. Fewer side effects were attributed to placebo tablets with brand name labeling compared to the same placebo tablets with a generic label. Branding of a tablet appears to have conferred a treatment benefit in the absence of an active ingredient, while generic labeled tablets were substantially less effective if they contained no active ingredient. Branding is also associated with reduced attribution of side effects to placebo tablets. Future interventions to improve perceptions of generics may have utility in improving treatment outcomes from generic drugs. (c) 2016 APA, all rights reserved).

Multiclassifier fusion in human brain MR segmentation: modelling convergence.

PubMed

Heckemann, Rolf A; Hajnal, Joseph V; Aljabar, Paul; Rueckert, Daniel; Hammers, Alexander

2006-01-01

Segmentations of MR images of the human brain can be generated by propagating an existing atlas label volume to the target image. By fusing multiple propagated label volumes, the segmentation can be improved. We developed a model that predicts the improvement of labelling accuracy and precision based on the number of segmentations used as input. Using a cross-validation study on brain image data as well as numerical simulations, we verified the model. Fit parameters of this model are potential indicators of the quality of a given label propagation method or the consistency of the input segmentations used.

No difference in sensitivity for occult infection between tropolone- and oxine-labeled indium-111 leukocytes

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

Datz, F.L.; Bedont, R.A.; Baker, W.J.

1985-05-01

There is considerable disagreement as to whether oxine or tropolone is the best labeling agent for indium leukocytes. The authors have previously looked at the sensitivity of oxine-labeled /sup 111/In leukocyte scans for occult infections and now present a similar group of patients imaged with tropolone-labeled /sup 111/In leukocytes. Thirty-four patients (38 studies) with possible occult infection were prospectively studied. Patients were imaged 1-4 hr after injection and again at 24 hr postinjection. The differences in sensitivity between oxine and tropolone when imaged early and at 24 hr were not statistically significant. They conclude that there is not significant differencemore » in the ability to detect infection between oxine- and tropolone-labeled leukocytes, both early at 1-4 hr, and on delayed imaging 24 hr after injection.« less

Evaluating Varied Label Designs for Use with Medical Devices: Optimized Labels Outperform Existing Labels in the Correct Selection of Devices and Time to Select.

PubMed

Bix, Laura; Seo, Do Chan; Ladoni, Moslem; Brunk, Eric; Becker, Mark W

2016-01-01

Effective standardization of medical device labels requires objective study of varied designs. Insufficient empirical evidence exists regarding how practitioners utilize and view labeling. Measure the effect of graphic elements (boxing information, grouping information, symbol use and color-coding) to optimize a label for comparison with those typical of commercial medical devices. Participants viewed 54 trials on a computer screen. Trials were comprised of two labels that were identical with regard to graphics, but differed in one aspect of information (e.g., one had latex, the other did not). Participants were instructed to select the label along a given criteria (e.g., latex containing) as quickly as possible. Dependent variables were binary (correct selection) and continuous (time to correct selection). Eighty-nine healthcare professionals were recruited at Association of Surgical Technologists (AST) conferences, and using a targeted e-mail of AST members. Symbol presence, color coding and grouping critical pieces of information all significantly improved selection rates and sped time to correct selection (α = 0.05). Conversely, when critical information was graphically boxed, probability of correct selection and time to selection were impaired (α = 0.05). Subsequently, responses from trials containing optimal treatments (color coded, critical information grouped with symbols) were compared to two labels created based on a review of those commercially available. Optimal labels yielded a significant positive benefit regarding the probability of correct choice ((P<0.0001) LSM; UCL, LCL: 97.3%; 98.4%, 95.5%)), as compared to the two labels we created based on commercial designs (92.0%; 94.7%, 87.9% and 89.8%; 93.0%, 85.3%) and time to selection. Our study provides data regarding design factors, namely: color coding, symbol use and grouping of critical information that can be used to significantly enhance the performance of medical device labels.

Image labeling. The need for a better look.

PubMed

Hunter, T

1994-10-01

The important message in this editorial is for radiologists to critically examine how well images are labeled in their own department. If it is not satisfactory, then institute corrective measures. These can range from sophisticated computer programs for printing flashcards to merely sending the chief technologist all those films one comes across with unreadable labels. The quality of the image labeling should also be a consideration when purchasing CT, MRI, ultrasound, computed radiography and digital angiography equipment. The fact that you consider this important should be communicated to equipment manufacturers in the hope that they will pay more attention to it and offer more flexibility for each department to design its own labels. In any event, I feel consistently bad film labeling results in sloppy radiology with possible patient harm and unpleasant legal consequences for the radiologist.

What You Need to Know When Taking Anticoagulantion Medication

MedlinePlus

... or week. However, once the medication leaves the original bottle, it loses its identification and instruction label. ... the number prescription on the label matches the original prescription.  Plan to get a new prescription when ...

Label inspection of approximate cylinder based on adverse cylinder panorama

NASA Astrophysics Data System (ADS)

Lin, Jianping; Liao, Qingmin; He, Bei; Shi, Chenbo

2013-12-01

This paper presents a machine vision system for automated label inspection, with the goal to reduce labor cost and ensure consistent product quality. Firstly, the images captured from each single-camera are distorted, since the inspection object is approximate cylindrical. Therefore, this paper proposes an algorithm based on adverse cylinder projection, where label images are rectified by distortion compensation. Secondly, to overcome the limited field of viewing for each single-camera, our method novelly combines images of all single-cameras and build a panorama for label inspection. Thirdly, considering the shake of production lines and error of electronic signal, we design the real-time image registration to calculate offsets between the template and inspected images. Experimental results demonstrate that our system is accurate, real-time and can be applied for numerous real- time inspections of approximate cylinders.

Superparamagnetic iron oxide nanoparticle-labeled cells as an effective vehicle for tracking the GFP gene marker using magnetic resonance imaging

PubMed Central

Zhang, Z; Mascheri, N; Dharmakumar, R; Fan, Z; Paunesku, T; Woloschak, G; Li, D

2010-01-01

Background Detection of a gene using magnetic resonance imaging (MRI) is hindered by the magnetic resonance (MR) targeting gene technique. Therefore it may be advantageous to image gene-expressing cells labeled with superparamagnetic iron oxide (SPIO) nanoparticles by MRI. Methods The GFP-R3230Ac (GFP) cell line was incubated for 24 h using SPIO nanoparticles at a concentration of 20 μg Fe/mL. Cell samples were prepared for iron content analysis and cell function evaluation. The labeled cells were imaged using fluorescent microscopy and MRI. Results SPIO was used to label GFP cells effectively, with no effects on cell function and GFP expression. Iron-loaded GFP cells were successfully imaged with both fluorescent microscopy and T2*-weighted MRI. Prussian blue staining showed intracellular iron accumulation in the cells. All cells were labeled (100% labeling efficiency). The average iron content per cell was 4.75±0.11 pg Fe/cell (P<0.05 versus control). Discussion This study demonstrates that the GFP expression of cells is not altered by the SPIO labeling process. SPIO-labeled GFP cells can be visualized by MRI; therefore, GFP, a gene marker, was tracked indirectly with the SPIO-loaded cells using MRI. The technique holds promise for monitoring the temporal and spatial migration of cells with a gene marker and enhancing the understanding of cell- and gene-based therapeutic strategies. PMID:18956269

Structured prediction models for RNN based sequence labeling in clinical text.

PubMed

Jagannatha, Abhyuday N; Yu, Hong

2016-11-01

Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application of sequence labeling involves extraction of medical entities such as medication, indication, and side-effects from Electronic Health Record narratives. Sequence labeling in this domain, presents its own set of challenges and objectives. In this work we experimented with various CRF based structured learning models with Recurrent Neural Networks. We extend the previously studied LSTM-CRF models with explicit modeling of pairwise potentials. We also propose an approximate version of skip-chain CRF inference with RNN potentials. We use these methodologies for structured prediction in order to improve the exact phrase detection of various medical entities.

Structured prediction models for RNN based sequence labeling in clinical text

PubMed Central

Jagannatha, Abhyuday N; Yu, Hong

2016-01-01

Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application of sequence labeling involves extraction of medical entities such as medication, indication, and side-effects from Electronic Health Record narratives. Sequence labeling in this domain, presents its own set of challenges and objectives. In this work we experimented with various CRF based structured learning models with Recurrent Neural Networks. We extend the previously studied LSTM-CRF models with explicit modeling of pairwise potentials. We also propose an approximate version of skip-chain CRF inference with RNN potentials. We use these methodologies1 for structured prediction in order to improve the exact phrase detection of various medical entities. PMID:28004040

Cross contrast multi-channel image registration using image synthesis for MR brain images.

PubMed

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

2017-02-01

Multi-modal deformable registration is important for many medical image analysis tasks such as atlas alignment, image fusion, and distortion correction. Whereas a conventional method would register images with different modalities using modality independent features or information theoretic metrics such as mutual information, this paper presents a new framework that addresses the problem using a two-channel registration algorithm capable of using mono-modal similarity measures such as sum of squared differences or cross-correlation. To make it possible to use these same-modality measures, image synthesis is used to create proxy images for the opposite modality as well as intensity-normalized images from each of the two available images. The new deformable registration framework was evaluated by performing intra-subject deformation recovery, intra-subject boundary alignment, and inter-subject label transfer experiments using multi-contrast magnetic resonance brain imaging data. Three different multi-channel registration algorithms were evaluated, revealing that the framework is robust to the multi-channel deformable registration algorithm that is used. With a single exception, all results demonstrated improvements when compared against single channel registrations using the same algorithm with mutual information. Copyright © 2016 Elsevier B.V. All rights reserved.

Single Cell Fluorescence Imaging Using Metal Plasmon-Coupled Probe

PubMed Central

Zhang, Jian; Fu, Yi; Lakowicz, Joseph R.

2009-01-01

This work constitutes the first fluorescent imaging of cells using metal plasmon-coupled probes (PCPs) at single cell resolution. N-(2-Mercapto-propionyl)glycine-coated silver nanoparticles were synthesized by reduction of silver nitrate using sodium borohyride and then succinimidylated via ligand exchange. Alexa Fluor 647-labeled concanavalin A (con A) was chemically bound to the silver particles to make the fluorescent metal plasmon-coupled probes. The fluorescence images were collected using a scanning confocal microscopy. The fluorescence intensity was observed to enhance 7-fold when binding the labeled con A on a single silver particle. PCPs were conjugated on HEK 293 A cells. Imaging results demonstrate that cells labeled by PCPs were 20-fold brighter than those by free labeled con A. PMID:17375898

Temporal and Spatial Variances in Arterial Spin-Labeling Are Inversely Related to Large-Artery Blood Velocity.

PubMed

Robertson, A D; Matta, G; Basile, V S; Black, S E; Macgowan, C K; Detre, J A; MacIntosh, B J

2017-08-01

The relationship between extracranial large-artery characteristics and arterial spin-labeling MR imaging may influence the quality of arterial spin-labeling-CBF images for older adults with and without vascular pathology. We hypothesized that extracranial arterial blood velocity can explain between-person differences in arterial spin-labeling data systematically across clinical populations. We performed consecutive pseudocontinuous arterial spin-labeling and phase-contrast MR imaging on 82 individuals (20-88 years of age, 50% women), including healthy young adults, healthy older adults, and older adults with cerebral small vessel disease or chronic stroke infarcts. We examined associations between extracranial phase-contrast hemodynamics and intracranial arterial spin-labeling characteristics, which were defined by labeling efficiency, temporal signal-to-noise ratio, and spatial coefficient of variation. Large-artery blood velocity was inversely associated with labeling efficiency ( P = .007), temporal SNR ( P < .001), and spatial coefficient of variation ( P = .05) of arterial spin-labeling, after accounting for age, sex, and group. Correction for labeling efficiency on an individual basis led to additional group differences in GM-CBF compared to correction using a constant labeling efficiency. Between-subject arterial spin-labeling variance was partially explained by extracranial velocity but not cross-sectional area. Choosing arterial spin-labeling timing parameters with on-line knowledge of blood velocity may improve CBF quantification. © 2017 by American Journal of Neuroradiology.

[Alzheimer disease and society: an analysis of its social representation].

PubMed

Ngatcha-Ribert, Laëtitia

2004-03-01

The purpose of this article is to analyze the social representations of Alzheimer's disease as well as the rhetorical logic, through a study of the literature, newspapers and about thirty interviews. The entry of the disease in the medical field, thanks to the drugs, and in the scientific research allowed a re-civilization of the patients and a generalization of Alzheimer disease which the media seized, therefore the emergence of positive representations. This evolution remains however fragile insofar as the negative and sinister images persist and are seized in the collective imagination. The Alzheimer disease in particular became a label to report the senile collapse. In face of the still sordidly realistic social image, patients themselves can change the perception of the public opinion.

Positron Emission Tomography: Principles, Technology, and Recent Developments

NASA Astrophysics Data System (ADS)

Ziegler, Sibylle I.

2005-04-01

Positron emission tomography (PET) is a nuclear medical imaging technique for quantitative measurement of physiologic parameters in vivo (an overview of principles and applications can be found in [P.E. Valk, et al., eds. Positron Emission Tomography. Basic Science and Clinical Practice. 2003, Springer: Heidelberg]), based on the detection of small amounts of posi-tron-emitter-labelled biologic molecules. Various radiotracers are available for neuro-logical, cardiological, and oncological applications in the clinic and in research proto-cols. This overview describes the basic principles, technology, and recent develop-ments in PET, followed by a section on the development of a tomograph with ava-lanche photodiodes dedicated for small animal imaging as an example of efforts in the domain of high resolution tomographs.

Object-Location-Aware Hashing for Multi-Label Image Retrieval via Automatic Mask Learning.

PubMed

Huang, Chang-Qin; Yang, Shang-Ming; Pan, Yan; Lai, Han-Jiang

2018-09-01

Learning-based hashing is a leading approach of approximate nearest neighbor search for large-scale image retrieval. In this paper, we develop a deep supervised hashing method for multi-label image retrieval, in which we propose to learn a binary "mask" map that can identify the approximate locations of objects in an image, so that we use this binary "mask" map to obtain length-limited hash codes which mainly focus on an image's objects but ignore the background. The proposed deep architecture consists of four parts: 1) a convolutional sub-network to generate effective image features; 2) a binary "mask" sub-network to identify image objects' approximate locations; 3) a weighted average pooling operation based on the binary "mask" to obtain feature representations and hash codes that pay most attention to foreground objects but ignore the background; and 4) the combination of a triplet ranking loss designed to preserve relative similarities among images and a cross entropy loss defined on image labels. We conduct comprehensive evaluations on four multi-label image data sets. The results indicate that the proposed hashing method achieves superior performance gains over the state-of-the-art supervised or unsupervised hashing baselines.

Magnetic Resonance Imaging of Iron Oxide-Labeled Human Embryonic Stem Cell-Derived Cardiac Progenitors.

PubMed

Skelton, Rhys J P; Khoja, Suhail; Almeida, Shone; Rapacchi, Stanislas; Han, Fei; Engel, James; Zhao, Peng; Hu, Peng; Stanley, Edouard G; Elefanty, Andrew G; Kwon, Murray; Elliott, David A; Ardehali, Reza

2016-01-01

Given the limited regenerative capacity of the heart, cellular therapy with stem cell-derived cardiac cells could be a potential treatment for patients with heart disease. However, reliable imaging techniques to longitudinally assess engraftment of the transplanted cells are scant. To address this issue, we used ferumoxytol as a labeling agent of human embryonic stem cell-derived cardiac progenitor cells (hESC-CPCs) to facilitate tracking by magnetic resonance imaging (MRI) in a large animal model. Differentiating hESCs were exposed to ferumoxytol at different time points and varying concentrations. We determined that treatment with ferumoxytol at 300 μg/ml on day 0 of cardiac differentiation offered adequate cell viability and signal intensity for MRI detection without compromising further differentiation into definitive cardiac lineages. Labeled hESC-CPCs were transplanted by open surgical methods into the left ventricular free wall of uninjured pig hearts and imaged both ex vivo and in vivo. Comprehensive T2*-weighted images were obtained immediately after transplantation and 40 days later before termination. The localization and dispersion of labeled cells could be effectively imaged and tracked at days 0 and 40 by MRI. Thus, under the described conditions, ferumoxytol can be used as a long-term, differentiation-neutral cell-labeling agent to track transplanted hESC-CPCs in vivo using MRI. The development of a safe and reproducible in vivo imaging technique to track the fate of transplanted human embryonic stem cell-derived cardiac progenitor cells (hESC-CPCs) is a necessary step to clinical translation. An iron oxide nanoparticle (ferumoxytol)-based approach was used for cell labeling and subsequent in vivo magnetic resonance imaging monitoring of hESC-CPCs transplanted into uninjured pig hearts. The present results demonstrate the use of ferumoxytol labeling and imaging techniques in tracking the location and dispersion of cell grafts, highlighting its utility in future cardiac stem cell therapy trials. ©AlphaMed Press.

Label-Free Raman Imaging to Monitor Breast Tumor Signatures

NASA Astrophysics Data System (ADS)

Ciubuc, John

Methods built on Raman spectroscopy have shown major potential in describing and discriminating between malignant and benign specimens. Accurate, real-time medical diagnosis benefits in substantial improvements through this vibrational optical method. Not only is acquisition of data possible in milliseconds and analysis in minutes, Raman allows concurrent detection and monitoring of all biological components. Besides validating a significant Raman signature distinction between non-tumorigenic (MCF-10A) and tumorigenic (MCF-7) breast epithelial cells, this study reveals a label-free method to assess overexpression of epidermal growth factor receptors (EGFR) in tumor cells. EGFR overexpression sires Raman features associated with phosphorylated threonine and serine, and modifications of DNA/RNA characteristics. Investigations by gel electrophoresis reveal EGF induction of phosphorylated Akt, agreeing with the Raman results. The analysis presented is a vital step toward Raman-based evaluation of EGF receptors in breast cancer cells. With the goal of clinically applying Raman-guided methods for diagnosis of breast tumors, the current results lay the basis for proving label-free optical alternatives in making prognosis of the disease.

Mediation effects of medication information processing and adherence on association between health literacy and quality of life.

PubMed

Song, Sunmi; Lee, Seung-Mi; Jang, Sunmee; Lee, Yoon Jin; Kim, Na-Hyun; Sohn, Hye-Ryoung; Suh, Dong-Churl

2017-09-16

To examine whether medication related information processing defined as reading of over-the-counter drug labels, understanding prescription instructions, and information seeking-and medication adherence account for the association between health literacy and quality of life, and whether these associations may be moderated by age and gender. A sample of 305 adults in South Korea was recruited through a proportional quota sampling to take part in a cross-sectional survey on health literacy, medication-related information processing, medication adherence, and quality of life. Descriptive statistics and structural equation modeling (SEM) were performed. Two mediation pathways linking health literacy with quality of life were found. First, health literacy was positively associated with reading drug labels, which was subsequently linked to medication adherence and quality of life. Second, health literacy was positively associated with accurate understanding of prescription instructions, which was associated with quality of life. Age moderation was found, as the mediation by reading drug labels was significant only among young adults whereas the mediation by understanding of medication instruction was only among older adults. Reading drug labels and understanding prescription instructions explained the pathways by which health literacy affects medication adherence and quality of life. The results suggest that training skills for processing medication information can be effective to enhance the health of those with limited health literacy.

Labelling fashion magazine advertisements: Effectiveness of different label formats on social comparison and body dissatisfaction.

PubMed

Tiggemann, Marika; Brown, Zoe

2018-06-01

The experiment investigated the impact on women's body dissatisfaction of different forms of label added to fashion magazine advertisements. Participants were 340 female undergraduate students who viewed 15 fashion advertisements containing a thin and attractive model. They were randomly allocated to one of five label conditions: no label, generic disclaimer label (indicating image had been digitally altered), consequence label (indicating that viewing images might make women feel bad about themselves), informational label (indicating the model in the advertisement was underweight), or a graphic label (picture of a paint brush). Although exposure to the fashion advertisements resulted in increased body dissatisfaction, there was no significant effect of label type on body dissatisfaction; no form of label demonstrated any ameliorating effect. In addition, the consequence and informational labels resulted in increased perceived realism and state appearance comparison. Yet more extensive research is required before the effective implementation of any form of label. Copyright © 2018 Elsevier Ltd. All rights reserved.

Labeling tetracysteine-tagged proteins with biarsenical dyes for live cell imaging.

PubMed

Gaietta, Guido M; Deerinck, Thomas J; Ellisman, Mark H

2011-01-01

Correlation of real-time or time-lapse light microscopy (LM) with electron microscopy (EM) of cells can be performed with biarsenical dyes. These dyes fluorescently label tetracysteine-tagged proteins so that they can be imaged with LM and, upon fluorescent photoconversion of 3,3'-diaminobenzidine tetrahydrochloride (DAB), with EM as well. In the following protocol, cells expressing tetracysteine-tagged proteins are labeled for 1 h with biarsenical dyes. The volumes indicated are for a single 30-mm culture dish containing 2 mL of labeling medium. Scale the suggested volumes up or down depending upon the size of the culture dish used in the labeling. The same procedure can be adapted for longer labeling times by lowering the amount of dye used to 50-100 nM; however, the amount of the competing dithiol EDT is maintained at 10-20 μM. Longer labeling times often produce higher signal-to-noise ratios and cause less trauma to the treated cells prior to imaging.

The role of image registration in brain mapping

PubMed Central

Toga, A.W.; Thompson, P.M.

2008-01-01

Image registration is a key step in a great variety of biomedical imaging applications. It provides the ability to geometrically align one dataset with another, and is a prerequisite for all imaging applications that compare datasets across subjects, imaging modalities, or across time. Registration algorithms also enable the pooling and comparison of experimental findings across laboratories, the construction of population-based brain atlases, and the creation of systems to detect group patterns in structural and functional imaging data. We review the major types of registration approaches used in brain imaging today. We focus on their conceptual basis, the underlying mathematics, and their strengths and weaknesses in different contexts. We describe the major goals of registration, including data fusion, quantification of change, automated image segmentation and labeling, shape measurement, and pathology detection. We indicate that registration algorithms have great potential when used in conjunction with a digital brain atlas, which acts as a reference system in which brain images can be compared for statistical analysis. The resulting armory of registration approaches is fundamental to medical image analysis, and in a brain mapping context provides a means to elucidate clinical, demographic, or functional trends in the anatomy or physiology of the brain. PMID:19890483

Live Imaging of Cellular Internalization of Single Colloidal Particle by Combined Label-Free and Fluorescence Total Internal Reflection Microscopy.

PubMed

Byrne, Gerard D; Vllasaliu, Driton; Falcone, Franco H; Somekh, Michael G; Stolnik, Snjezana

2015-11-02

In this work we utilize the combination of label-free total internal reflection microscopy and total internal reflectance fluorescence (TIRM/TIRF) microscopy to achieve a simultaneous, live imaging of single, label-free colloidal particle endocytosis by individual cells. The TIRM arm of the microscope enables label free imaging of the colloid and cell membrane features, while the TIRF arm images the dynamics of fluorescent-labeled clathrin (protein involved in endocytosis via clathrin pathway), expressed in transfected 3T3 fibroblasts cells. Using a model polymeric colloid and cells with a fluorescently tagged clathrin endocytosis pathway, we demonstrate that wide field TIRM/TIRF coimaging enables live visualization of the process of colloidal particle interaction with the labeled cell structure, which is valuable for discerning the membrane events and route of colloid internalization by the cell. We further show that 500 nm in diameter model polystyrene colloid associates with clathrin, prior to and during its cellular internalization. This association is not apparent with larger, 1 μm in diameter colloids, indicating an upper particle size limit for clathrin-mediated endocytosis.

High-level production of C-11-carboxyl-labeled amino acids. [For use in tumor and pancreatic imaging

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

Washburn, L. C.; Sun, T. T.; Byrd, B. L.

Carbon-11-labeled amino acids have significant potential as agents for positron tomographic functional imaging. We have developed a rapid, high-temperature, high-pressure modification of the Buecherer--Strecker amino acid synthesis and found it to be quite general for the production of C-11-carboxyl-labeled neutral amino acids. Production of C-11-carboxyl-labeled DL-tryptophan requires certain modifications in the procedure. Twelve different amino acids have been produced to date by this technique. Synthesis and chromatographic purification require approximately 40 min, and C-11-carboxyl-labeled amino acids have been produced in yields of up to 425 mCi. Two C-11-carboxyl-labeled amino acids are being investigated clinically for tumor scanning and two othersmore » for pancreatic imaging. Over 120 batches of the various agents have been produced for clinical use over a three-year period.« less

Imaging of cellular spread on a three-dimensional scaffold by means of a novel cell-labeling technique for high-resolution computed tomography.

PubMed

Thimm, Benjamin W; Hofmann, Sandra; Schneider, Philipp; Carretta, Roberto; Müller, Ralph

2012-03-01

Computed tomography (CT) represents a truly three-dimensional (3D) imaging technique that can provide high-resolution images on the cellular level. Thus, one approach to detect single cells is X-ray absorption-based CT, where cells are labeled with a dense, opaque material providing the required contrast for CT imaging. Within the present work, a novel cell-labeling method has been developed showing the feasibility of labeling fixed cells with iron oxide (FeO) particles for subsequent CT imaging and quantitative morphometry. A biotin-streptavidin detection system was exploited to bind FeO particles to its target endothelial cells. The binding of the particles was predominantly close to the cell centers on 2D surfaces as shown by light microscopy, scanning electron microscopy, and CT. When cells were cultured on porous, 3D polyurethane surfaces, significantly more FeO particles were detected compared with surfaces without cells and FeO particle labeling using CT. Here, we report on the implementation and evaluation of a novel cell detection method based on high-resolution CT. This system has potential in cell tracking for 3D in vitro imaging in the future.

Direct fluorescent-dye labeling of α-tubulin in mammalian cells for live cell and superresolution imaging

PubMed Central

Schvartz, Tomer; Aloush, Noa; Goliand, Inna; Segal, Inbar; Nachmias, Dikla; Arbely, Eyal; Elia, Natalie

2017-01-01

Genetic code expansion and bioorthogonal labeling provide for the first time a way for direct, site-specific labeling of proteins with fluorescent-dyes in live cells. Although the small size and superb photophysical parameters of fluorescent-dyes offer unique advantages for high-resolution microscopy, this approach has yet to be embraced as a tool in live cell imaging. Here we evaluated the feasibility of this approach by applying it for α-tubulin labeling. After a series of calibrations, we site-specifically labeled α-tubulin with silicon rhodamine (SiR) in live mammalian cells in an efficient and robust manner. SiR-labeled tubulin successfully incorporated into endogenous microtubules at high density, enabling video recording of microtubule dynamics in interphase and mitotic cells. Applying this labeling approach to structured illumination microscopy resulted in an increase in resolution, highlighting the advantages in using a smaller, brighter tag. Therefore, using our optimized assay, genetic code expansion provides an attractive tool for labeling proteins with a minimal, bright tag in quantitative high-resolution imaging. PMID:28835375

Label-free DNA imaging in vivo with stimulated Raman scattering microscopy

PubMed Central

Lu, Fa-Ke; Basu, Srinjan; Igras, Vivien; Hoang, Mai P.; Ji, Minbiao; Fu, Dan; Holtom, Gary R.; Neel, Victor A.; Freudiger, Christian W.; Fisher, David E.; Xie, X. Sunney

2015-01-01

Label-free DNA imaging is highly desirable in biology and medicine to perform live imaging without affecting cell function and to obtain instant histological tissue examination during surgical procedures. Here we show a label-free DNA imaging method with stimulated Raman scattering (SRS) microscopy for visualization of the cell nuclei in live animals and intact fresh human tissues with subcellular resolution. Relying on the distinct Raman spectral features of the carbon-hydrogen bonds in DNA, the distribution of DNA is retrieved from the strong background of proteins and lipids by linear decomposition of SRS images at three optimally selected Raman shifts. Based on changes on DNA condensation in the nucleus, we were able to capture chromosome dynamics during cell division both in vitro and in vivo. We tracked mouse skin cell proliferation, induced by drug treatment, through in vivo counting of the mitotic rate. Furthermore, we demonstrated a label-free histology method for human skin cancer diagnosis that provides comparable results to other conventional tissue staining methods such as H&E. Our approach exhibits higher sensitivity than SRS imaging of DNA in the fingerprint spectral region. Compared with spontaneous Raman imaging of DNA, our approach is three orders of magnitude faster, allowing both chromatin dynamic studies and label-free optical histology in real time. PMID:26324899

Learning-Based Object Identification and Segmentation Using Dual-Energy CT Images for Security.

PubMed

Martin, Limor; Tuysuzoglu, Ahmet; Karl, W Clem; Ishwar, Prakash

2015-11-01

In recent years, baggage screening at airports has included the use of dual-energy X-ray computed tomography (DECT), an advanced technology for nondestructive evaluation. The main challenge remains to reliably find and identify threat objects in the bag from DECT data. This task is particularly hard due to the wide variety of objects, the high clutter, and the presence of metal, which causes streaks and shading in the scanner images. Image noise and artifacts are generally much more severe than in medical CT and can lead to splitting of objects and inaccurate object labeling. The conventional approach performs object segmentation and material identification in two decoupled processes. Dual-energy information is typically not used for the segmentation, and object localization is not explicitly used to stabilize the material parameter estimates. We propose a novel learning-based framework for joint segmentation and identification of objects directly from volumetric DECT images, which is robust to streaks, noise and variability due to clutter. We focus on segmenting and identifying a small set of objects of interest with characteristics that are learned from training images, and consider everything else as background. We include data weighting to mitigate metal artifacts and incorporate an object boundary field to reduce object splitting. The overall formulation is posed as a multilabel discrete optimization problem and solved using an efficient graph-cut algorithm. We test the method on real data and show its potential for producing accurate labels of the objects of interest without splits in the presence of metal and clutter.

Telepharmacy and bar-code technology in an i.v. chemotherapy admixture area.

PubMed

O'Neal, Brian C; Worden, John C; Couldry, Rick J

2009-07-01

A program using telepharmacy and bar-code technology to increase the presence of the pharmacist at a critical risk point during chemotherapy preparation is described. Telepharmacy hardware and software were acquired, and an inspection camera was placed in a biological safety cabinet to allow the pharmacy technician to take digital photographs at various stages of the chemotherapy preparation process. Once the pharmacist checks the medication vials' agreement with the work label, the technician takes the product into the biological safety cabinet, where the appropriate patient is selected from the pending work list, a queue of patient orders sent from the pharmacy information system. The technician then scans the bar code on the vial. Assuming the bar code matches, the technician photographs the work label, vials, diluents and fluids to be used, and the syringe (before injecting the contents into the bag) along with the vial. The pharmacist views all images as a part of the final product-checking process. This process allows the pharmacist to verify that the correct quantity of medication was transferred from the primary source to a secondary container without being physically present at the time of transfer. Telepharmacy and bar coding provide a means to improve the accuracy of chemotherapy preparation by decreasing the likelihood of using the incorrect product or quantity of drug. The system facilitates the reading of small product labels and removes the need for a pharmacist to handle contaminated syringes and vials when checking the final product.

Gamma camera dual imaging with a somatostatin receptor and thymidine kinase after gene transfer with a bicistronic adenovirus in mice.

PubMed

Zinn, Kurt R; Chaudhuri, Tandra R; Krasnykh, Victor N; Buchsbaum, Donald J; Belousova, Natalya; Grizzle, William E; Curiel, David T; Rogers, Buck E

2002-05-01

To compare two systems for assessing gene transfer to cancer cells and xenograft tumors with noninvasive gamma camera imaging. A replication-incompetent adenovirus encoding the human type 2 somatostatin receptor (hSSTr2) and the herpes simplex virus thymidine kinase (TK) enzyme (Ad-hSSTr2-TK) was constructed. A-427 human lung cancer cells were infected in vitro and mixed with uninfected cells at different ratios. A-427 tumors in nude mice (n = 23) were injected with 1 x 10(6) to 5 x 10(8) plaque-forming units (pfu) of Ad-hSSTr2-TK. The expressed hSSTr2 and TK proteins were imaged owing to internally bound, or trapped, technetium 99m ((99m)Tc)-labeled hSSTr2-binding peptide (P2045) and radioiodinated 2'-deoxy-2'-fluoro-beta-D-arabinofuranosyl-5-iodouracil (FIAU), respectively. Iodine 125 ((125)I)-labeled FIAU was used in vitro and iodine 131 ((131)I)-labeled FIAU, in vivo. The (99m)Tc-labeled P2045 and (125)I- or (131)I-labeled FIAU were imaged simultaneously with different window settings with an Anger gamma camera. Treatment effects were tested with analysis of variance. Infected cells in culture trapped (125)I-labeled FIAU and (99m)Tc-labeled P2045; uptake correlated with the percentage of Ad-hSSTr2-TK-positive cells. For 100% of infected cells, 24% +/- 0.4 (mean +/- SD) of the added (99m)Tc-labeled P2045 was trapped, which is significantly lower (P <.05) than the 40% +/- 2 of (125)I-labeled FIAU that was trapped. For the highest Ad-hSSTr2-TK tumor dose (5 x 10(8) pfu), the uptake of (99m)Tc-labeled P2045 was 11.1% +/- 2.9 of injected dose per gram of tumor (thereafter, dose per gram), significantly higher (P <.05) than the uptake of (131)I-labeled FIAU at 1.6% +/- 0.4 dose per gram. (99m)Tc-labeled P2045 imaging consistently depicted hSSTr2 gene transfer in tumors at all adenovirus doses. Tumor uptake of (99m)Tc-labeled P2045 positively correlated with Ad-hSSTr2-TK dose; (131)I-labeled FIAU tumor uptake did not correlate with vector dose. The hSSTr2 and TK proteins were simultaneously imaged following dual gene transfer with an adenovirus vector. Copyright RSNA, 2002

Research on segmentation based on multi-atlas in brain MR image

NASA Astrophysics Data System (ADS)

Qian, Yuejing

2018-03-01

Accurate segmentation of specific tissues in brain MR image can be effectively achieved with the multi-atlas-based segmentation method, and the accuracy mainly depends on the image registration accuracy and fusion scheme. This paper proposes an automatic segmentation method based on the multi-atlas for brain MR image. Firstly, to improve the registration accuracy in the area to be segmented, we employ a target-oriented image registration method for the refinement. Then In the label fusion, we proposed a new algorithm to detect the abnormal sparse patch and simultaneously abandon the corresponding abnormal sparse coefficients, this method is made based on the remaining sparse coefficients combined with the multipoint label estimator strategy. The performance of the proposed method was compared with those of the nonlocal patch-based label fusion method (Nonlocal-PBM), the sparse patch-based label fusion method (Sparse-PBM) and majority voting method (MV). Based on our experimental results, the proposed method is efficient in the brain MR images segmentation compared with MV, Nonlocal-PBM, and Sparse-PBM methods.

Learning a Dictionary of Shape Epitomes with Applications to Image Labeling

PubMed Central

Chen, Liang-Chieh; Papandreou, George; Yuille, Alan L.

2015-01-01

The first main contribution of this paper is a novel method for representing images based on a dictionary of shape epitomes. These shape epitomes represent the local edge structure of the image and include hidden variables to encode shift and rotations. They are learnt in an unsupervised manner from groundtruth edges. This dictionary is compact but is also able to capture the typical shapes of edges in natural images. In this paper, we illustrate the shape epitomes by applying them to the image labeling task. In other work, described in the supplementary material, we apply them to edge detection and image modeling. We apply shape epitomes to image labeling by using Conditional Random Field (CRF) Models. They are alternatives to the superpixel or pixel representations used in most CRFs. In our approach, the shape of an image patch is encoded by a shape epitome from the dictionary. Unlike the superpixel representation, our method avoids making early decisions which cannot be reversed. Our resulting hierarchical CRFs efficiently capture both local and global class co-occurrence properties. We demonstrate its quantitative and qualitative properties of our approach with image labeling experiments on two standard datasets: MSRC-21 and Stanford Background. PMID:26321886

Image segmentation via foreground and background semantic descriptors

NASA Astrophysics Data System (ADS)

Yuan, Ding; Qiang, Jingjing; Yin, Jihao

2017-09-01

In the field of image processing, it has been a challenging task to obtain a complete foreground that is not uniform in color or texture. Unlike other methods, which segment the image by only using low-level features, we present a segmentation framework, in which high-level visual features, such as semantic information, are used. First, the initial semantic labels were obtained by using the nonparametric method. Then, a subset of the training images, with a similar foreground to the input image, was selected. Consequently, the semantic labels could be further refined according to the subset. Finally, the input image was segmented by integrating the object affinity and refined semantic labels. State-of-the-art performance was achieved in experiments with the challenging MSRC 21 dataset.

Prolonged Dye Release from Mesoporous Silica-Based Imaging Probes Facilitates Long-Term Optical Tracking of Cell Populations In Vivo.

PubMed

Rosenholm, Jessica M; Gulin-Sarfraz, Tina; Mamaeva, Veronika; Niemi, Rasmus; Özliseli, Ezgi; Desai, Diti; Antfolk, Daniel; von Haartman, Eva; Lindberg, Desiré; Prabhakar, Neeraj; Näreoja, Tuomas; Sahlgren, Cecilia

2016-03-23

Nanomedicine is gaining ground worldwide in therapy and diagnostics. Novel nanoscopic imaging probes serve as imaging tools for studying dynamic biological processes in vitro and in vivo. To allow detectability in the physiological environment, the nanostructure-based probes need to be either inherently detectable by biomedical imaging techniques, or serve as carriers for existing imaging agents. In this study, the potential of mesoporous silica nanoparticles carrying commercially available fluorochromes as self-regenerating cell labels for long-term cellular tracking is investigated. The particle surface is organically modified for enhanced cellular uptake, the fluorescence intensity of labeled cells is followed over time both in vitro and in vivo. The particles are not exocytosed and particles which escaped cells due to cell injury or death are degraded and no labeling of nontargeted cell populations are observed. The labeling efficiency is significantly improved as compared to that of quantum dots of similar emission wavelength. Labeled human breast cancer cells are xenotransplanted in nude mice, and the fluorescent cells can be detected in vivo for a period of 1 month. Moreover, ex vivo analysis reveals fluorescently labeled metastatic colonies in lymph node and rib, highlighting the capability of the developed probes for tracking of metastasis. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Disclaimer labels on fashion magazine advertisements: effects on social comparison and body dissatisfaction.

PubMed

Tiggemann, Marika; Slater, Amy; Bury, Belinda; Hawkins, Kimberley; Firth, Bonny

2013-01-01

Recent proposals across a number of Western countries have suggested that idealised media images should carry some sort of disclaimer informing readers when these images have been digitally enhanced. The present studies aimed to experimentally investigate the impact on women's body dissatisfaction of the addition of such warning labels to fashion magazine advertisements. Participants were 120 and 114 female undergraduate students in Experiment 1 and Experiment 2 respectively. In both experiments, participants viewed fashion magazine advertisements with either no warning label, a generic warning label, or a specific more detailed warning label. In neither experiment was there a significant effect of type of label. However, state appearance comparison was found to predict change in body dissatisfaction irrespective of condition. Unexpectedly, trait appearance comparison moderated the effect of label on body dissatisfaction, such that for women high on trait appearance comparison, exposure to specific warning labels actually resulted in increased body dissatisfaction. In sum, the present results showed no benefit of warning labels in ameliorating the known negative effect of viewing thin-ideal media images, and even suggested that one form of warning (specific) might be harmful for some individuals. Accordingly, it was concluded that more extensive research is required to guide the most effective use of disclaimer labels. Copyright © 2012 Elsevier Ltd. All rights reserved.

21 CFR 250.12 - Stramonium preparations labeled with directions for use in self-medication regarded as misbranded.

Code of Federal Regulations, 2011 CFR

2011-04-01

... of Food and Drugs has concluded that such articles have a potentiality for harmful effect through... ingredients, will be regarded as misbranded if they are labeled with directions for use in self-medication. (2...

21 CFR 250.12 - Stramonium preparations labeled with directions for use in self-medication regarded as misbranded.

Code of Federal Regulations, 2013 CFR

2013-04-01

... of Food and Drugs has concluded that such articles have a potentiality for harmful effect through... ingredients, will be regarded as misbranded if they are labeled with directions for use in self-medication. (2...

21 CFR 250.12 - Stramonium preparations labeled with directions for use in self-medication regarded as misbranded.

Code of Federal Regulations, 2014 CFR

2014-04-01

... of Food and Drugs has concluded that such articles have a potentiality for harmful effect through... ingredients, will be regarded as misbranded if they are labeled with directions for use in self-medication. (2...

21 CFR 250.12 - Stramonium preparations labeled with directions for use in self-medication regarded as misbranded.

Code of Federal Regulations, 2012 CFR

2012-04-01

... of Food and Drugs has concluded that such articles have a potentiality for harmful effect through... ingredients, will be regarded as misbranded if they are labeled with directions for use in self-medication. (2...

Magnetic resonance brain tissue segmentation based on sparse representations

NASA Astrophysics Data System (ADS)

Rueda, Andrea

2015-12-01

Segmentation or delineation of specific organs and structures in medical images is an important task in the clinical diagnosis and treatment, since it allows to characterize pathologies through imaging measures (biomarkers). In brain imaging, segmentation of main tissues or specific structures is challenging, due to the anatomic variability and complexity, and the presence of image artifacts (noise, intensity inhomogeneities, partial volume effect). In this paper, an automatic segmentation strategy is proposed, based on sparse representations and coupled dictionaries. Image intensity patterns are singly related to tissue labels at the level of small patches, gathering this information in coupled intensity/segmentation dictionaries. This dictionaries are used within a sparse representation framework to find the projection of a new intensity image onto the intensity dictionary, and the same projection can be used with the segmentation dictionary to estimate the corresponding segmentation. Preliminary results obtained with two publicly available datasets suggest that the proposal is capable of estimating adequate segmentations for gray matter (GM) and white matter (WM) tissues, with an average overlapping of 0:79 for GM and 0:71 for WM (with respect to original segmentations).

Medical Gas Containers and Closures; Current Good Manufacturing Practice Requirements. Final rule.

PubMed

2016-11-18

The Food and Drug Administration (FDA or the Agency) is amending its current good manufacturing practice (CGMP) and labeling regulations regarding medical gases. FDA is requiring that portable cryogenic medical gas containers not manufactured with permanent gas use outlet connections have gas-specific use outlet connections that cannot be readily removed or replaced except by the manufacturer. FDA is also requiring that portable cryogenic medical gas containers and high-pressure medical gas cylinders meet certain labeling, naming, and color requirements. These requirements are intended to increase the likelihood that the contents of medical gas containers are accurately identified and reduce the likelihood of the wrong gas being connected to a gas supply system or container. FDA is also revising an existing regulation that conditionally exempts certain medical gases from certain otherwise-applicable labeling requirements in order to add oxygen and nitrogen to the list of gases subject to the exemption, and to remove cyclopropane and ethylene from the list.

Synthesis of 2'-deoxy-2'-[.sup.18F]fluoro-5-methyl-1-B-D-arabinofuranosyluracil (.sup.18F-FMAU)

DOEpatents

Li, Zibo; Cai, Hancheng; Conti, Peter S

2014-12-16

The present invention relates to methods of synthesizing .sup.18F-FMAU. In particular, .sup.18F-FMAU is synthesized using one-pot reaction conditions in the presence of Friedel-Crafts catalysts. The one-pot reaction conditions are incorporated into a fully automated cGMP-compliant radiosynthesis module, which results in a reduction in synthesis time and simplifies reaction conditions. The one-pot reaction conditions are also suitable for the production of 5-substituted thymidine or cytidine analogs. The products from the one-pot reaction (e.g. the labeled thymidine or cytidine analogs) can be used as probes for imaging tumor proliferative activity. More specifically, these [.sup.18F]-labeled thymidine or cytidine analogs can be used as a PET tracer for certain medical conditions, including, but not limited to, cancer disease, autoimmunity inflammation, and bone marrow transplant.

volBrain: An Online MRI Brain Volumetry System

PubMed Central

Manjón, José V.; Coupé, Pierrick

2016-01-01

The amount of medical image data produced in clinical and research settings is rapidly growing resulting in vast amount of data to analyze. Automatic and reliable quantitative analysis tools, including segmentation, allow to analyze brain development and to understand specific patterns of many neurological diseases. This field has recently experienced many advances with successful techniques based on non-linear warping and label fusion. In this work we present a novel and fully automatic pipeline for volumetric brain analysis based on multi-atlas label fusion technology that is able to provide accurate volumetric information at different levels of detail in a short time. This method is available through the volBrain online web interface (http://volbrain.upv.es), which is publically and freely accessible to the scientific community. Our new framework has been compared with current state-of-the-art methods showing very competitive results. PMID:27512372

volBrain: An Online MRI Brain Volumetry System.

PubMed

Manjón, José V; Coupé, Pierrick

2016-01-01

The amount of medical image data produced in clinical and research settings is rapidly growing resulting in vast amount of data to analyze. Automatic and reliable quantitative analysis tools, including segmentation, allow to analyze brain development and to understand specific patterns of many neurological diseases. This field has recently experienced many advances with successful techniques based on non-linear warping and label fusion. In this work we present a novel and fully automatic pipeline for volumetric brain analysis based on multi-atlas label fusion technology that is able to provide accurate volumetric information at different levels of detail in a short time. This method is available through the volBrain online web interface (http://volbrain.upv.es), which is publically and freely accessible to the scientific community. Our new framework has been compared with current state-of-the-art methods showing very competitive results.

Robust tissue classification for reproducible wound assessment in telemedicine environments

NASA Astrophysics Data System (ADS)

Wannous, Hazem; Treuillet, Sylvie; Lucas, Yves

2010-04-01

In telemedicine environments, a standardized and reproducible assessment of wounds, using a simple free-handled digital camera, is an essential requirement. However, to ensure robust tissue classification, particular attention must be paid to the complete design of the color processing chain. We introduce the key steps including color correction, merging of expert labeling, and segmentation-driven classification based on support vector machines. The tool thus developed ensures stability under lighting condition, viewpoint, and camera changes, to achieve accurate and robust classification of skin tissues. Clinical tests demonstrate that such an advanced tool, which forms part of a complete 3-D and color wound assessment system, significantly improves the monitoring of the healing process. It achieves an overlap score of 79.3 against 69.1% for a single expert, after mapping on the medical reference developed from the image labeling by a college of experts.

Quantum dots in imaging, drug delivery and sensor applications

PubMed Central

Matea, Cristian T; Mocan, Teodora; Tabaran, Flaviu; Pop, Teodora; Mosteanu, Ofelia; Puia, Cosmin; Iancu, Cornel; Mocan, Lucian

2017-01-01

Quantum dots (QDs), also known as nanoscale semiconductor crystals, are nanoparticles with unique optical and electronic properties such as bright and intensive fluorescence. Since most conventional organic label dyes do not offer the near-infrared (>650 nm) emission possibility, QDs, with their tunable optical properties, have gained a lot of interest. They possess characteristics such as good chemical and photo-stability, high quantum yield and size-tunable light emission. Different types of QDs can be excited with the same light wavelength, and their narrow emission bands can be detected simultaneously for multiple assays. There is an increasing interest in the development of nano-theranostics platforms for simultaneous sensing, imaging and therapy. QDs have great potential for such applications, with notable results already published in the fields of sensors, drug delivery and biomedical imaging. This review summarizes the latest developments available in literature regarding the use of QDs for medical applications. PMID:28814860

Quantum dots in imaging, drug delivery and sensor applications.

PubMed

Matea, Cristian T; Mocan, Teodora; Tabaran, Flaviu; Pop, Teodora; Mosteanu, Ofelia; Puia, Cosmin; Iancu, Cornel; Mocan, Lucian

2017-01-01

Quantum dots (QDs), also known as nanoscale semiconductor crystals, are nanoparticles with unique optical and electronic properties such as bright and intensive fluorescence. Since most conventional organic label dyes do not offer the near-infrared (>650 nm) emission possibility, QDs, with their tunable optical properties, have gained a lot of interest. They possess characteristics such as good chemical and photo-stability, high quantum yield and size-tunable light emission. Different types of QDs can be excited with the same light wavelength, and their narrow emission bands can be detected simultaneously for multiple assays. There is an increasing interest in the development of nano-theranostics platforms for simultaneous sensing, imaging and therapy. QDs have great potential for such applications, with notable results already published in the fields of sensors, drug delivery and biomedical imaging. This review summarizes the latest developments available in literature regarding the use of QDs for medical applications.

Fine-grained leukocyte classification with deep residual learning for microscopic images.

PubMed

Qin, Feiwei; Gao, Nannan; Peng, Yong; Wu, Zizhao; Shen, Shuying; Grudtsin, Artur

2018-08-01

Leukocyte classification and cytometry have wide applications in medical domain, previous researches usually exploit machine learning techniques to classify leukocytes automatically. However, constrained by the past development of machine learning techniques, for example, extracting distinctive features from raw microscopic images are difficult, the widely used SVM classifier only has relative few parameters to tune, these methods cannot efficiently handle fine-grained classification cases when the white blood cells have up to 40 categories. Based on deep learning theory, a systematic study is conducted on finer leukocyte classification in this paper. A deep residual neural network based leukocyte classifier is constructed at first, which can imitate the domain expert's cell recognition process, and extract salient features robustly and automatically. Then the deep neural network classifier's topology is adjusted according to the prior knowledge of white blood cell test. After that the microscopic image dataset with almost one hundred thousand labeled leukocytes belonging to 40 categories is built, and combined training strategies are adopted to make the designed classifier has good generalization ability. The proposed deep residual neural network based classifier was tested on microscopic image dataset with 40 leukocyte categories. It achieves top-1 accuracy of 77.80%, top-5 accuracy of 98.75% during the training procedure. The average accuracy on the test set is nearly 76.84%. This paper presents a fine-grained leukocyte classification method for microscopic images, based on deep residual learning theory and medical domain knowledge. Experimental results validate the feasibility and effectiveness of our approach. Extended experiments support that the fine-grained leukocyte classifier could be used in real medical applications, assist doctors in diagnosing diseases, reduce human power significantly. Copyright © 2018 Elsevier B.V. All rights reserved.

Radionuclide and Fluorescence Imaging of Clear Cell Renal Cell Carcinoma Using Dual Labeled Anti-Carbonic Anhydrase IX Antibody G250.

PubMed

Muselaers, Constantijn H J; Rijpkema, Mark; Bos, Desirée L; Langenhuijsen, Johan F; Oyen, Wim J G; Mulders, Peter F A; Oosterwijk, Egbert; Boerman, Otto C

2015-08-01

Tumor targeted optical imaging using antibodies labeled with near infrared fluorophores is a sensitive imaging modality that might be used during surgery to assure complete removal of malignant tissue. We evaluated the feasibility of dual modality imaging and image guided surgery with the dual labeled anti-carbonic anhydrase IX antibody preparation (111)In-DTPA-G250-IRDye800CW in mice with intraperitoneal clear cell renal cell carcinoma. BALB/c nu/nu mice with intraperitoneal SK-RC-52 lesions received 10 μg DTPA-G250-IRDye800CW labeled with 15 MBq (111)In or 10 μg of the dual labeled irrelevant control antibody NUH-82 (20 mice each). To evaluate when tumors could be detected, 4 mice per group were imaged weekly during 5 weeks with single photon emission computerized tomography/computerized tomography and the fluorescence imaging followed by ex vivo biodistribution studies. As early as 1 week after tumor cell inoculation single photon emission computerized tomography and fluorescence images showed clear delineation of intraperitoneal clear cell renal cell carcinoma with good concordance between single photon emission computerized tomography/computerized tomography and fluorescence images. The high and specific accumulation of the dual labeled antibody conjugate in tumors was confirmed in the biodistribution studies. Maximum tumor uptake was observed 1 week after inoculation (mean ± SD 58.5% ± 18.7% vs 5.6% ± 2.3% injected dose per gm for DTPA-G250-IRDye800CW vs NUH-82, respectively). High tumor uptake was also observed at other time points. This study demonstrates the feasibility of dual modality imaging with dual labeled antibody (111)In-DTPA-G250-IRDye800CW in a clear cell renal cell carcinoma model. Results indicate that preoperative and intraoperative detection of carbonic anhydrase IX expressing tumors, positive resection margins and metastasis might be feasible with this approach. Copyright © 2015 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Patch forest: a hybrid framework of random forest and patch-based segmentation

NASA Astrophysics Data System (ADS)

Xie, Zhongliu; Gillies, Duncan

2016-03-01

The development of an accurate, robust and fast segmentation algorithm has long been a research focus in medical computer vision. State-of-the-art practices often involve non-rigidly registering a target image with a set of training atlases for label propagation over the target space to perform segmentation, a.k.a. multi-atlas label propagation (MALP). In recent years, the patch-based segmentation (PBS) framework has gained wide attention due to its advantage of relaxing the strict voxel-to-voxel correspondence to a series of pair-wise patch comparisons for contextual pattern matching. Despite a high accuracy reported in many scenarios, computational efficiency has consistently been a major obstacle for both approaches. Inspired by recent work on random forest, in this paper we propose a patch forest approach, which by equipping the conventional PBS with a fast patch search engine, is able to boost segmentation speed significantly while retaining an equal level of accuracy. In addition, a fast forest training mechanism is also proposed, with the use of a dynamic grid framework to efficiently approximate data compactness computation and a 3D integral image technique for fast box feature retrieval.

Application of neuroanatomical ontologies for neuroimaging data annotation.

PubMed

Turner, Jessica A; Mejino, Jose L V; Brinkley, James F; Detwiler, Landon T; Lee, Hyo Jong; Martone, Maryann E; Rubin, Daniel L

2010-01-01

The annotation of functional neuroimaging results for data sharing and re-use is particularly challenging, due to the diversity of terminologies of neuroanatomical structures and cortical parcellation schemes. To address this challenge, we extended the Foundational Model of Anatomy Ontology (FMA) to include cytoarchitectural, Brodmann area labels, and a morphological cortical labeling scheme (e.g., the part of Brodmann area 6 in the left precentral gyrus). This representation was also used to augment the neuroanatomical axis of RadLex, the ontology for clinical imaging. The resulting neuroanatomical ontology contains explicit relationships indicating which brain regions are "part of" which other regions, across cytoarchitectural and morphological labeling schemas. We annotated a large functional neuroimaging dataset with terms from the ontology and applied a reasoning engine to analyze this dataset in conjunction with the ontology, and achieved successful inferences from the most specific level (e.g., how many subjects showed activation in a subpart of the middle frontal gyrus) to more general (how many activations were found in areas connected via a known white matter tract?). In summary, we have produced a neuroanatomical ontology that harmonizes several different terminologies of neuroanatomical structures and cortical parcellation schemes. This neuroanatomical ontology is publicly available as a view of FMA at the Bioportal website. The ontological encoding of anatomic knowledge can be exploited by computer reasoning engines to make inferences about neuroanatomical relationships described in imaging datasets using different terminologies. This approach could ultimately enable knowledge discovery from large, distributed fMRI studies or medical record mining.

Morphometric information to reduce the semantic gap in the characterization of microscopic images of thyroid nodules.

PubMed

Macedo, Alessandra A; Pessotti, Hugo C; Almansa, Luciana F; Felipe, Joaquim C; Kimura, Edna T

2016-07-01

The analyses of several systems for medical-imaging processing typically support the extraction of image attributes, but do not comprise some information that characterizes images. For example, morphometry can be applied to find new information about the visual content of an image. The extension of information may result in knowledge. Subsequently, results of mappings can be applied to recognize exam patterns, thus improving the accuracy of image retrieval and allowing a better interpretation of exam results. Although successfully applied in breast lesion images, the morphometric approach is still poorly explored in thyroid lesions due to the high subjectivity thyroid examinations. This paper presents a theoretical-practical study, considering Computer Aided Diagnosis (CAD) and Morphometry, to reduce the semantic discontinuity between medical image features and human interpretation of image content. The proposed method aggregates the content of microscopic images characterized by morphometric information and other image attributes extracted by traditional object extraction algorithms. This method carries out segmentation, feature extraction, image labeling and classification. Morphometric analysis was included as an object extraction method in order to verify the improvement of its accuracy for automatic classification of microscopic images. To validate this proposal and verify the utility of morphometric information to characterize thyroid images, a CAD system was created to classify real thyroid image-exams into Papillary Cancer, Goiter and Non-Cancer. Results showed that morphometric information can improve the accuracy and precision of image retrieval and the interpretation of results in computer-aided diagnosis. For example, in the scenario where all the extractors are combined with the morphometric information, the CAD system had its best performance (70% of precision in Papillary cases). Results signalized a positive use of morphometric information from images to reduce semantic discontinuity between human interpretation and image characterization. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Nuclear and Fluorescent Labeled PD-1-Liposome-DOX-64Cu/IRDye800CW Allows Improved Breast Tumor Targeted Imaging and Therapy.

PubMed

Du, Yang; Liang, Xiaolong; Li, Yuan; Sun, Ting; Jin, Zhengyu; Xue, Huadan; Tian, Jie

2017-11-06

The overexpression of programmed cell death-1 (PD-1) in tumors as breast cancer makes it a possible target for cancer imaging and therapy. Advances in molecular imaging, including radionuclide imaging and near-infrared fluorescence (NIRF) imaging, enable the detection of tumors with high sensitivity. In this study, we aim to develop a novel PD-1 antibody targeted positron emission tomography (PET) and NIRF labeled liposome loaded with doxorubicin (DOX) and evaluate its application for in vivo cancer imaging and therapy. IRDye800CW and 64 Cu were conjugated to liposomes with PD-1 antibody labeling, and DOX was inside the liposomes to form theranostic nanoparticles. The 4T1 tumors were successfully visualized with PD-1-Liposome-DOX- 64 Cu/IRDye800CW using NIRF/PET imaging. The bioluminescent imaging (BLI) results showed that tumor growth was significantly inhibited in the PD-1-Liposome-DOX-treated group than the IgG control. Our results highlight the potential of using dual-labeled theranostic PD-1 mAb-targeted Liposome-DOX- 64 Cu/IRDye800CW for the management of breast tumor.

Isotropic differential phase contrast microscopy for quantitative phase bio-imaging.

PubMed

Chen, Hsi-Hsun; Lin, Yu-Zi; Luo, Yuan

2018-05-16

Quantitative phase imaging (QPI) has been investigated to retrieve optical phase information of an object and applied to biological microscopy and related medical studies. In recent examples, differential phase contrast (DPC) microscopy can recover phase image of thin sample under multi-axis intensity measurements in wide-field scheme. Unlike conventional DPC, based on theoretical approach under partially coherent condition, we propose a new method to achieve isotropic differential phase contrast (iDPC) with high accuracy and stability for phase recovery in simple and high-speed fashion. The iDPC is simply implemented with a partially coherent microscopy and a programmable thin-film transistor (TFT) shield to digitally modulate structured illumination patterns for QPI. In this article, simulation results show consistency of our theoretical approach for iDPC under partial coherence. In addition, we further demonstrate experiments of quantitative phase images of a standard micro-lens array, as well as label-free live human cell samples. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

3D Imaging of Nanoparticle Distribution in Biological Tissue by Laser-Induced Breakdown Spectroscopy

NASA Astrophysics Data System (ADS)

Gimenez, Y.; Busser, B.; Trichard, F.; Kulesza, A.; Laurent, J. M.; Zaun, V.; Lux, F.; Benoit, J. M.; Panczer, G.; Dugourd, P.; Tillement, O.; Pelascini, F.; Sancey, L.; Motto-Ros, V.

2016-07-01

Nanomaterials represent a rapidly expanding area of research with huge potential for future medical applications. Nanotechnology indeed promises to revolutionize diagnostics, drug delivery, gene therapy, and many other areas of research. For any biological investigation involving nanomaterials, it is crucial to study the behavior of such nano-objects within tissues to evaluate both their efficacy and their toxicity. Here, we provide the first account of 3D label-free nanoparticle imaging at the entire-organ scale. The technology used is known as laser-induced breakdown spectroscopy (LIBS) and possesses several advantages such as speed of operation, ease of use and full compatibility with optical microscopy. We then used two different but complementary approaches to achieve 3D elemental imaging with LIBS: a volume reconstruction of a sliced organ and in-depth analysis. This proof-of-concept study demonstrates the quantitative imaging of both endogenous and exogenous elements within entire organs and paves the way for innumerable applications.

3D Imaging of Nanoparticle Distribution in Biological Tissue by Laser-Induced Breakdown Spectroscopy.

PubMed

Gimenez, Y; Busser, B; Trichard, F; Kulesza, A; Laurent, J M; Zaun, V; Lux, F; Benoit, J M; Panczer, G; Dugourd, P; Tillement, O; Pelascini, F; Sancey, L; Motto-Ros, V

2016-07-20

Nanomaterials represent a rapidly expanding area of research with huge potential for future medical applications. Nanotechnology indeed promises to revolutionize diagnostics, drug delivery, gene therapy, and many other areas of research. For any biological investigation involving nanomaterials, it is crucial to study the behavior of such nano-objects within tissues to evaluate both their efficacy and their toxicity. Here, we provide the first account of 3D label-free nanoparticle imaging at the entire-organ scale. The technology used is known as laser-induced breakdown spectroscopy (LIBS) and possesses several advantages such as speed of operation, ease of use and full compatibility with optical microscopy. We then used two different but complementary approaches to achieve 3D elemental imaging with LIBS: a volume reconstruction of a sliced organ and in-depth analysis. This proof-of-concept study demonstrates the quantitative imaging of both endogenous and exogenous elements within entire organs and paves the way for innumerable applications.

3D Imaging of Nanoparticle Distribution in Biological Tissue by Laser-Induced Breakdown Spectroscopy

PubMed Central

Gimenez, Y.; Busser, B.; Trichard, F.; Kulesza, A.; Laurent, J. M.; Zaun, V.; Lux, F.; Benoit, J. M.; Panczer, G.; Dugourd, P.; Tillement, O.; Pelascini, F.; Sancey, L.; Motto-Ros, V.

2016-01-01

Nanomaterials represent a rapidly expanding area of research with huge potential for future medical applications. Nanotechnology indeed promises to revolutionize diagnostics, drug delivery, gene therapy, and many other areas of research. For any biological investigation involving nanomaterials, it is crucial to study the behavior of such nano-objects within tissues to evaluate both their efficacy and their toxicity. Here, we provide the first account of 3D label-free nanoparticle imaging at the entire-organ scale. The technology used is known as laser-induced breakdown spectroscopy (LIBS) and possesses several advantages such as speed of operation, ease of use and full compatibility with optical microscopy. We then used two different but complementary approaches to achieve 3D elemental imaging with LIBS: a volume reconstruction of a sliced organ and in-depth analysis. This proof-of-concept study demonstrates the quantitative imaging of both endogenous and exogenous elements within entire organs and paves the way for innumerable applications. PMID:27435424

Decreased sensitivity of early imaging with In-111 oxine-labeled leukocytes in detection of occult infection: concise communication

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

Datz, F.L.; Jacobs, J.; Baker, W.

1984-03-01

Imaging with leukocytes labeled with indium-111 oxine is a sensitive technique for detecting sites of occult infection. Traditionally, imaging is performed 24 hr after injection. The authors undertook a prospective study of 35 patients (40 studies) with possible occult infection to see whether a 24-hr delay in imaging is really necessary. Patients were imaged at 1-4 hr and again at 24 hr after injection. The early images had a sensitivity of only 33%, compared with 95% for the 24-hr images. Of the seven studies that were positive on both early and delayed images, 71% had more intense uptake at 24more » hr. There were no false-positive early images. It was concluded that imaging 1-4 hr after injection with In-111 oxine-labeled leukocytes has a low sensitivity for detecting occult infection. However, a positive early image is specific for a site of infection.« less

Targeted Nuclear Imaging Probes for Cardiac Amyloidosis.

PubMed

Bravo, Paco E; Dorbala, Sharmila

2017-07-01

The aim of the present manuscript is to review the latest advancements of radionuclide molecular imaging in the diagnosis and prognosis of individuals with cardiac amyloidosis. 99m Technetium labeled bone tracer scintigraphy had been known to image cardiac amyloidosis, since the 1980s; over the past decade, bone scintigraphy has been revived specifically to diagnose transthyretin cardiac amyloidosis. 18 F labeled and 11 C labeled amyloid binding radiotracers developed for imaging Alzheimer's disease, have been repurposed since 2013, to image light chain and transthyretin cardiac amyloidosis. 99m Technetium bone scintigraphy for transthyretin cardiac amyloidosis, and amyloid binding targeted PET imaging for light chain and transthyretin cardiac amyloidosis, are emerging as highly accurate methods. Targeted radionuclide imaging may soon replace endomyocardial biopsy in the evaluation of patients with suspected cardiac amyloidosis. Further research is warranted on the role of targeted imaging to quantify cardiac amyloidosis and to guide therapy.

Label-free DNA imaging in vivo with stimulated Raman scattering microscopy

DOE PAGES

Lu, Fa-Ke; Basu, Srinjan; Igras, Vivien; ...

2015-08-31

Label-free DNA imaging is highly desirable in biology and medicine to perform live imaging without affecting cell function and to obtain instant histological tissue examination during surgical procedures. Here we show a label-free DNA imaging method with stimulated Raman scattering (SRS) microscopy for visualization of the cell nuclei in live animals and intact fresh human tissues with subcellular resolution. Relying on the distinct Raman spectral features of the carbon-hydrogen bonds in DNA, the distribution of DNA is retrieved from the strong background of proteins and lipids by linear decomposition of SRS images at three optimally selected Raman shifts. Based onmore » changes on DNA condensation in the nucleus, we were able to capture chromosome dynamics during cell division both in vitro and in vivo. We tracked mouse skin cell proliferation, induced by drug treatment, through in vivo counting of the mitotic rate. Moreover, we demonstrated a label-free histology method for human skin cancer diagnosis that provides comparable results to other conventional tissue staining methods such as H&E. In conclusion, our approach exhibits higher sensitivity than SRS imaging of DNA in the fingerprint spectral region. Compared with spontaneous Raman imaging of DNA, our approach is three orders of magnitude faster, allowing both chromatin dynamic studies and label-free optical histology in real time.« less

Cryo-imaging of fluorescently labeled single cells in a mouse

NASA Astrophysics Data System (ADS)

Steyer, Grant J.; Roy, Debashish; Salvado, Olivier; Stone, Meredith E.; Wilson, David L.

2009-02-01

We developed a cryo-imaging system to provide single-cell detection of fluorescently labeled cells in mouse, with particular applicability to stem cells and metastatic cancer. The Case cryoimaging system consists of a fluorescence microscope, robotic imaging positioner, customized cryostat, PC-based control system, and visualization/analysis software. The system alternates between sectioning (10-40 μm) and imaging, collecting color brightfield and fluorescent blockface image volumes >60GB. In mouse experiments, we imaged quantum-dot labeled stem cells, GFP-labeled cancer and stem cells, and cell-size fluorescent microspheres. To remove subsurface fluorescence, we used a simplified model of light-tissue interaction whereby the next image was scaled, blurred, and subtracted from the current image. We estimated scaling and blurring parameters by minimizing entropy of subtracted images. Tissue specific attenuation parameters were found [uT : heart (267 +/- 47.6 μm), liver (218 +/- 27.1 μm), brain (161 +/- 27.4 μm)] to be within the range of estimates in the literature. "Next image" processing removed subsurface fluorescence equally well across multiple tissues (brain, kidney, liver, adipose tissue, etc.), and analysis of 200 microsphere images in the brain gave 97+/-2% reduction of subsurface fluorescence. Fluorescent signals were determined to arise from single cells based upon geometric and integrated intensity measurements. Next image processing greatly improved axial resolution, enabled high quality 3D volume renderings, and improved enumeration of single cells with connected component analysis by up to 24%. Analysis of image volumes identified metastatic cancer sites, found homing of stem cells to injury sites, and showed microsphere distribution correlated with blood flow patterns. We developed and evaluated cryo-imaging to provide single-cell detection of fluorescently labeled cells in mouse. Our cryo-imaging system provides extreme (>60GB), micron-scale, fluorescence, and bright field image data. Here we describe our image preprocessing, analysis, and visualization techniques. Processing improves axial resolution, reduces subsurface fluorescence by 97%, and enables single cell detection and counting. High quality 3D volume renderings enable us to evaluate cell distribution patterns. Applications include the myriad of biomedical experiments using fluorescent reporter gene and exogenous fluorophore labeling of cells in applications such as stem cell regenerative medicine, cancer, tissue engineering, etc.

Desiderata for product labeling of medical expert systems.

PubMed

Geissbühler, A; Miller, R A

1997-12-01

The proliferation and increasing complexity of medical expert systems raise ethical and legal concerns about the ability of practitioners to protect their patients from defective or misused software. Appropriate product labeling of expert systems can help clinical users to understand software indications and limitations. Mechanisms of action and knowledge representation schema should be explained in layperson's terminology. User qualifications and resources available for acquiring the skills necessary to understand and critique the system output should be listed. The processes used for building and maintaining the system's knowledge base are key determinants of the product's quality, and should be carefully documented. To meet these desiderata, a printed label is insufficient. The authors suggest a new, more active, model of product labeling for medical expert systems that involves embedding 'knowledge of the knowledge base', creating user-specific data, and sharing global information using the Internet.

Magneto-optical labeling of fetal neural stem cells for in vivo MRI tracking.

PubMed

Flexman, J A; Minoshima, S; Kim, Y; Cross, D J

2006-01-01

Neural stem cell therapy for neurological pathologies, such as Alzheimer's and Parkinson's disease, may delay the onset of symptoms, replace damaged neurons and/or support the survival of endogenous cells. Magnetic resonance imaging (MRI) can be used to track magnetically labeled cells in vivo to observe migration. Prior to transplantation, labeled cells must be characterized to show that they retain their intrinsic properties, such as cell proliferation into neurospheres in a supplemented environment. In vivo images must also be correlated to sensitive, histological markers. In this study, we show that fetus-derived neural stem cells can be co-labeled with superparamagnetic iron oxide and PKH26, a fluorescent dye. Labeled cells retain the ability to proliferate into neurospheres in culture, but labeling prevents neurospheres from merging in a non-adherent culture environment. After labeled NSCs were transplantation into the rat brain, their location and subsequent migration along the corpus callosum was detected using MRI. This study demonstrates an imaging paradigm with which to develop an in vivo assay for quantitatively evaluating fetal neural stem cell migration.

Stem Cell Monitoring with a Direct or Indirect Labeling Method.

PubMed

Kim, Min Hwan; Lee, Yong Jin; Kang, Joo Hyun

2016-12-01

The molecular imaging techniques allow monitoring of the transplanted cells in the same individuals over time, from early localization to the survival, migration, and differentiation. Generally, there are two methods of stem cell labeling: direct and indirect labeling methods. The direct labeling method introduces a labeling agent into the cell, which is stably incorporated or attached to the cells prior to transplantation. Direct labeling of cells with radionuclides is a simple method with relatively fewer adverse events related to genetic responses. However, it can only allow short-term distribution of transplanted cells because of the decreasing imaging signal with radiodecay, according to the physical half-lives, or the signal becomes more diffuse with cell division and dispersion. The indirect labeling method is based on the expression of a reporter gene transduced into the cell before transplantation, which is then visualized upon the injection of an appropriate probe or substrate. In this review, various imaging strategies to monitor the survival and behavior change of transplanted stem cells are covered. Taking these new approaches together, the direct and indirect labeling methods may provide new insights on the roles of in vivo stem cell monitoring, from bench to bedside.

47 CFR 95.1217 - Labeling requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... SERVICES Medical Device Radiocommunication Service (MedRadio) § 95.1217 Labeling requirements. (a) MedRadio... operating in the 400.150-406.000 MHz band in the Meteorological Aids, Meteorological Satellite, and Earth... shall be identified with a serial number. The FCC ID number associated with a medical implant...

Quantification of free cysteines in membrane and soluble proteins using a fluorescent dye and thermal unfolding.

PubMed

Branigan, Emma; Pliotas, Christos; Hagelueken, Gregor; Naismith, James H

2013-11-01

Cysteine is an extremely useful site for selective attachment of labels to proteins for many applications, including the study of protein structure in solution by electron paramagnetic resonance (EPR), fluorescence spectroscopy and medical imaging. The demand for quantitative data for these applications means that it is important to determine the extent of the cysteine labeling. The efficiency of labeling is sensitive to the 3D context of cysteine within the protein. Where the label or modification is not directly measurable by optical or magnetic spectroscopy, for example, in cysteine modification to dehydroalanine, assessing labeling efficiency is difficult. We describe a simple assay for determining the efficiency of modification of cysteine residues, which is based on an approach previously used to determine membrane protein stability. The assay involves a reaction between the thermally unfolded protein and a thiol-specific coumarin fluorophore that is only fluorescent upon conjugation with thiols. Monitoring fluorescence during thermal denaturation of the protein in the presence of the dye identifies the temperature at which the maximum fluorescence occurs; this temperature differs among proteins. Comparison of the fluorescence intensity at the identified temperature between modified, unmodified (positive control) and cysteine-less protein (negative control) allows for the quantification of free cysteine. We have quantified both site-directed spin labeling and dehydroalanine formation. The method relies on a commonly available fluorescence 96-well plate reader, which rapidly screens numerous samples within 1.5 h and uses <100 μg of material. The approach is robust for both soluble and detergent-solubilized membrane proteins.

Label-free imaging to study phenotypic behavioural traits of cells in complex co-cultures

NASA Astrophysics Data System (ADS)

Suman, Rakesh; Smith, Gabrielle; Hazel, Kathryn E. A.; Kasprowicz, Richard; Coles, Mark; O'Toole, Peter; Chawla, Sangeeta

2016-02-01

Time-lapse imaging is a fundamental tool for studying cellular behaviours, however studies of primary cells in complex co-culture environments often requires fluorescent labelling and significant light exposure that can perturb their natural function over time. Here, we describe ptychographic phase imaging that permits prolonged label-free time-lapse imaging of microglia in the presence of neurons and astrocytes, which better resembles in vivo microenvironments. We demonstrate the use of ptychography as an assay to study the phenotypic behaviour of microglial cells in primary neuronal co-cultures through the addition of cyclosporine A, a potent immune-modulator.

A comparative study of dietary curcumin, nanocurcumin, and other classical amyloid-binding dyes for labeling and imaging of amyloid plaques in brain tissue of 5×-familial Alzheimer's disease mice.

PubMed

Maiti, Panchanan; Hall, Tia C; Paladugu, Leela; Kolli, Nivya; Learman, Cameron; Rossignol, Julien; Dunbar, Gary L

2016-11-01

Deposition of amyloid beta protein (Aβ) is a key component in the pathogenesis of Alzheimer's disease (AD). As an anti-amyloid natural polyphenol, curcumin (Cur) has been used as a therapy for AD. Its fluorescent activity, preferential binding to Aβ, as well as structural similarities with other traditional amyloid-binding dyes, make it a promising candidate for labeling and imaging of Aβ plaques in vivo. The present study was designed to test whether dietary Cur and nanocurcumin (NC) provide more sensitivity for labeling and imaging of Aβ plaques in brain tissues from the 5×-familial AD (5×FAD) mice than the classical Aβ-binding dyes, such as Congo red and Thioflavin-S. These comparisons were made in postmortem brain tissues from the 5×FAD mice. We observed that Cur and NC labeled Aβ plaques to the same degree as Aβ-specific antibody and to a greater extent than those of the classical amyloid-binding dyes. Cur and NC also labeled Aβ plaques in 5×FAD brain tissues when injected intraperitoneally. Nanomolar concentrations of Cur or NC are sufficient for labeling and imaging of Aβ plaques in 5×FAD brain tissue. Cur and NC also labeled different types of Aβ plaques, including core, neuritic, diffuse, and burned-out, to a greater degree than other amyloid-binding dyes. Therefore, Cur and or NC can be used as an alternative to Aβ-specific antibody for labeling and imaging of Aβ plaques ex vivo and in vivo. It can provide an easy and inexpensive means of detecting Aβ-plaque load in postmortem brain tissue of animal models of AD after anti-amyloid therapy.

Fusing Continuous-Valued Medical Labels Using a Bayesian Model.

PubMed

Zhu, Tingting; Dunkley, Nic; Behar, Joachim; Clifton, David A; Clifford, Gari D

2015-12-01

With the rapid increase in volume of time series medical data available through wearable devices, there is a need to employ automated algorithms to label data. Examples of labels include interventions, changes in activity (e.g. sleep) and changes in physiology (e.g. arrhythmias). However, automated algorithms tend to be unreliable resulting in lower quality care. Expert annotations are scarce, expensive, and prone to significant inter- and intra-observer variance. To address these problems, a Bayesian Continuous-valued Label Aggregator (BCLA) is proposed to provide a reliable estimation of label aggregation while accurately infer the precision and bias of each algorithm. The BCLA was applied to QT interval (pro-arrhythmic indicator) estimation from the electrocardiogram using labels from the 2006 PhysioNet/Computing in Cardiology Challenge database. It was compared to the mean, median, and a previously proposed Expectation Maximization (EM) label aggregation approaches. While accurately predicting each labelling algorithm's bias and precision, the root-mean-square error of the BCLA was 11.78 ± 0.63 ms, significantly outperforming the best Challenge entry (15.37 ± 2.13 ms) as well as the EM, mean, and median voting strategies (14.76 ± 0.52, 17.61 ± 0.55, and 14.43 ± 0.57 ms respectively with p < 0.0001). The BCLA could therefore provide accurate estimation for medical continuous-valued label tasks in an unsupervised manner even when the ground truth is not available.

Studying the Stoichiometry of Epidermal Growth Factor Receptor in Intact Cells using Correlative Microscopy.

PubMed

Peckys, Diana B; de Jonge, Niels

2015-09-11

This protocol describes the labeling of epidermal growth factor receptor (EGFR) on COS7 fibroblast cells, and subsequent correlative fluorescence microscopy and environmental scanning electron microscopy (ESEM) of whole cells in hydrated state. Fluorescent quantum dots (QDs) were coupled to EGFR via a two-step labeling protocol, providing an efficient and specific protein labeling, while avoiding label-induced clustering of the receptor. Fluorescence microscopy provided overview images of the cellular locations of the EGFR. The scanning transmission electron microscopy (STEM) detector was used to detect the QD labels with nanoscale resolution. The resulting correlative images provide data of the cellular EGFR distribution, and the stoichiometry at the single molecular level in the natural context of the hydrated intact cell. ESEM-STEM images revealed the receptor to be present as monomer, as homodimer, and in small clusters. Labeling with two different QDs, i.e., one emitting at 655 nm and at 800 revealed similar characteristic results.

Detection of intramyocardially injected DiR-labeled mesenchymal stem cells by optical and optoacoustic tomography.

PubMed

Berninger, Markus T; Mohajerani, Pouyan; Wildgruber, Moritz; Beziere, Nicolas; Kimm, Melanie A; Ma, Xiaopeng; Haller, Bernhard; Fleming, Megan J; Vogt, Stephan; Anton, Martina; Imhoff, Andreas B; Ntziachristos, Vasilis; Meier, Reinhard; Henning, Tobias D

2017-06-01

The distribution of intramyocardially injected rabbit MSCs, labeled with the near-infrared dye 1,1'-dioctadecyl-3,3,3',3'-tetramethylindotricarbo-cyanine-iodide (DiR) using hybrid Fluorescence Molecular Tomography-X-ray Computed Tomography (FMT-XCT) and Multispectral Optoacoustic Tomography (MSOT) imaging technologies, was investigated. Viability and induction of apoptosis of DiR labeled MSCs were assessed by XTT- and Caspase-3/-7-testing in vitro . 2 × 10 6 , 2 × 10 5 and 2 × 10 4 MSCs labeled with 5 and 10 μg DiR/ml were injected into fresh frozen rabbit hearts. FMT-XCT, MSOT and fluorescence cryosection imaging were performed. Concentrations up to 10 μg DiR/ml did not cause apoptosis in vitro (p > 0.05). FMT and MSOT imaging of labeled MSCs led to a strong signal. The imaging modalities highlighted a difference in cell distribution and concentration correlated to the number of injected cells. Ex-vivo cryosectioning confirmed the molecular fluorescence signal. FMT and MSOT are sensitive imaging techniques offering high-anatomic resolution in terms of detection and distribution of intramyocardially injected stem cells in a rabbit model.

Medicalizing versus psychologizing mental illness: what are the implications for help seeking and stigma? A general population study.

PubMed

Pattyn, E; Verhaeghe, M; Sercu, C; Bracke, P

2013-10-01

This study contrasts the medicalized conceptualization of mental illness with psychologizing mental illness and examines what the consequences are of adhering to one model versus the other for help seeking and stigma. The survey "Stigma in a Global Context-Belgian Mental Health Study" (2009) conducted face-to-face interviews among a representative sample of the general Belgian population using the vignette technique to depict schizophrenia (N = 381). Causal attributions, labeling processes, and the disease view are addressed. Help seeking refers to open-ended help-seeking suggestions (general practitioner, psychiatrist, psychologist, family, friends, and self-care options). Stigma refers to social exclusion after treatment. The data are analyzed by means of logistic and linear regression models in SPSS Statistics 19. People who adhere to the biopsychosocial (versus psychosocial) model are more likely to recommend general medical care and people who apply the disease view are more likely to recommend specialized medical care. Regarding informal help, those who prefer the biopsychosocial model are less likely to recommend consulting friends than those who adhere to the psychosocial model. Respondents who apply a medical compared to a non-medical label are less inclined to recommend self-care. As concerns treatment stigma, respondents who apply a medical instead of a non-medical label are more likely to socially exclude someone who has been in psychiatric treatment. Medicalizing mental illness involves a package deal: biopsychosocial causal attributions and applying the disease view facilitate medical treatment recommendations, while labeling seems to trigger stigmatizing attitudes.

3D marker-controlled watershed for kidney segmentation in clinical CT exams.

PubMed

Wieclawek, Wojciech

2018-02-27

Image segmentation is an essential and non trivial task in computer vision and medical image analysis. Computed tomography (CT) is one of the most accessible medical examination techniques to visualize the interior of a patient's body. Among different computer-aided diagnostic systems, the applications dedicated to kidney segmentation represent a relatively small group. In addition, literature solutions are verified on relatively small databases. The goal of this research is to develop a novel algorithm for fully automated kidney segmentation. This approach is designed for large database analysis including both physiological and pathological cases. This study presents a 3D marker-controlled watershed transform developed and employed for fully automated CT kidney segmentation. The original and the most complex step in the current proposition is an automatic generation of 3D marker images. The final kidney segmentation step is an analysis of the labelled image obtained from marker-controlled watershed transform. It consists of morphological operations and shape analysis. The implementation is conducted in a MATLAB environment, Version 2017a, using i.a. Image Processing Toolbox. 170 clinical CT abdominal studies have been subjected to the analysis. The dataset includes normal as well as various pathological cases (agenesis, renal cysts, tumors, renal cell carcinoma, kidney cirrhosis, partial or radical nephrectomy, hematoma and nephrolithiasis). Manual and semi-automated delineations have been used as a gold standard. Wieclawek Among 67 delineated medical cases, 62 cases are 'Very good', whereas only 5 are 'Good' according to Cohen's Kappa interpretation. The segmentation results show that mean values of Sensitivity, Specificity, Dice, Jaccard, Cohen's Kappa and Accuracy are 90.29, 99.96, 91.68, 85.04, 91.62 and 99.89% respectively. All 170 medical cases (with and without outlines) have been classified by three independent medical experts as 'Very good' in 143-148 cases, as 'Good' in 15-21 cases and as 'Moderate' in 6-8 cases. An automatic kidney segmentation approach for CT studies to compete with commonly known solutions was developed. The algorithm gives promising results, that were confirmed during validation procedure done on a relatively large database, including 170 CTs with both physiological and pathological cases.

21 CFR 820.120 - Device labeling.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Device labeling. 820.120 Section 820.120 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES QUALITY SYSTEM REGULATION Labeling and Packaging Control § 820.120 Device labeling. Each manufacturer...

Biological and Catalytic Conversion of Sugars and Lignin | Bioenergy | NREL

Science.gov Websites

strings and ribbons twisted on themselves: lilac is labeled "LPMO", red is labeled "Family 5", blue is labeled "Family 6", green is labeled "Family 7", purple is labeled "Family 12", and yellow is labeled "Family 45". Two side-by-side images. The

Imaging of experimental amyloidosis with /sup 131/I-labeled serum amyloid P component

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

Caspi, D.; Zalzman, S.; Baratz, M.

1987-11-01

/sup 131/I-labeled human serum amyloid P component, which was injected into mice with experimentally induced systemic AA amyloidosis and into controls, became specifically localized and was retained in amyloidotic organs. In comparison, it was rapidly and completely eliminated from unaffected tissues and from control animals. Distinctive images of this amyloid-specific deposition of labeled serum amyloid P component were derived from whole body scanning, in vivo, of amyloidotic mice. These findings suggest that such imaging may have applications for the diagnosis and quantitation of amyloid deposits in humans.

Interactive Map | USDA Plant Hardiness Zone Map

Science.gov Websites

Choose Basemap: Terrain Road Map Satellite Image Turn on Basemap Roads and Labels Zone Color Transparency menu to switch between Terrain, Road Map, and Satellite Image. Turn on Basemap Roads and Labels Click option is available only for Terrain and Satellite Image basemap choices. Zone Color Transparency The

Automatic segmentation of the choroid in enhanced depth imaging optical coherence tomography images.

PubMed

Tian, Jing; Marziliano, Pina; Baskaran, Mani; Tun, Tin Aung; Aung, Tin

2013-03-01

Enhanced Depth Imaging (EDI) optical coherence tomography (OCT) provides high-definition cross-sectional images of the choroid in vivo, and hence is used in many clinical studies. However, the quantification of the choroid depends on the manual labelings of two boundaries, Bruch's membrane and the choroidal-scleral interface. This labeling process is tedious and subjective of inter-observer differences, hence, automatic segmentation of the choroid layer is highly desirable. In this paper, we present a fast and accurate algorithm that could segment the choroid automatically. Bruch's membrane is detected by searching the pixel with the biggest gradient value above the retinal pigment epithelium (RPE) and the choroidal-scleral interface is delineated by finding the shortest path of the graph formed by valley pixels using Dijkstra's algorithm. The experiments comparing automatic segmentation results with the manual labelings are conducted on 45 EDI-OCT images and the average of Dice's Coefficient is 90.5%, which shows good consistency of the algorithm with the manual labelings. The processing time for each image is about 1.25 seconds.

Liquid scanning transmission electron microscopy: imaging protein complexes in their native environment in whole eukaryotic cells.

PubMed

Peckys, Diana B; de Jonge, Niels

2014-04-01

Scanning transmission electron microscopy (STEM) of specimens in liquid, so-called Liquid STEM, is capable of imaging the individual subunits of macromolecular complexes in whole eukaryotic cells in liquid. This paper discusses this new microscopy modality within the context of state-of-the-art microscopy of cells. The principle of operation and equations for the resolution are described. The obtained images are different from those acquired with standard transmission electron microscopy showing the cellular ultrastructure. Instead, contrast is obtained on specific labels. Images can be recorded in two ways, either via STEM at 200 keV electron beam energy using a microfluidic chamber enclosing the cells, or via environmental scanning electron microscopy at 30 keV of cells in a wet environment. The first series of experiments involved the epidermal growth factor receptor labeled with gold nanoparticles. The labels were imaged in whole fixed cells with nanometer resolution. Since the cells can be kept alive in the microfluidic chamber, it is also feasible to detect the labels in unfixed, live cells. The rapid sample preparation and imaging allows studies of multiple whole cells.

Total-hip arthroplasty: Periprosthetic indium-111-labeled leukocyte activity and complementary technetium-99m-sulfur colloid imaging in suspected infection

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

Palestro, C.J.; Kim, C.K.; Swyer, A.J.

1990-12-01

Indium-111-labeled leukocyte images of 92 cemented total-hip arthroplasties were correlated with final diagnoses. Prostheses were divided into four zones: head (including acetabulum), trochanter, shaft, and tip. The presence (or absence) and intensity of activity in each zone was noted, and compared to the corresponding contralateral zone. Though present in all 23 infected arthroplasties, periprosthetic activity was also present in 77% of uninfected arthroplasties, and was greater than the contralateral zone 51% of the time. When analyzed by zone, head zone activity was the best criterion for infection (87% sensitivity, 94% specificity, 92% accuracy). Fifty of the arthroplasties were studied withmore » combined labeled leukocyte/sulfur colloid imaging. Using incongruence of images as the criterion for infection, the sensitivity, specificity, and accuracy of the study were 100%, 97%, and 98%, respectively. While variable periprosthetic activity makes labeled leukocyte imaging alone unreliable for diagnosing hip arthroplasty infection, the addition of sulfur colloid imaging results in a highly accurate diagnostic procedure.« less

Numerical study on simultaneous emission and transmission tomography in the MRI framework

NASA Astrophysics Data System (ADS)

Gjesteby, Lars; Cong, Wenxiang; Wang, Ge

2017-09-01

Multi-modality imaging methods are instrumental for advanced diagnosis and therapy. Specifically, a hybrid system that combines computed tomography (CT), nuclear imaging, and magnetic resonance imaging (MRI) will be a Holy Grail of medical imaging, delivering complementary structural/morphological, functional, and molecular information for precision medicine. A novel imaging method was recently demonstrated that takes advantage of radiotracer polarization to combine MRI principles with nuclear imaging. This approach allows the concentration of a polarized Υ-ray emitting radioisotope to be imaged with MRI resolution potentially outperforming the standard nuclear imaging mode at a sensitivity significantly higher than that of MRI. In our work, we propose to acquire MRI-modulated nuclear data for simultaneous image reconstruction of both emission and transmission parameters, suggesting the potential for simultaneous CT-SPECT-MRI. The synchronized diverse datasets allow excellent spatiotemporal registration and unique insight into physiological and pathological features. Here we describe the methodology involving the system design with emphasis on the formulation for tomographic images, even when significant radiotracer signals are limited to a region of interest (ROI). Initial numerical results demonstrate the feasibility of our approach for reconstructing concentration and attenuation images through a head phantom with various radio-labeled ROIs. Additional considerations regarding the radioisotope characteristics are also discussed.

Advanced cardiac chemical exchange saturation transfer (cardioCEST) MRI for in vivo cell tracking and metabolic imaging

PubMed Central

Pumphrey, Ashley; Yang, Zhengshi; Ye, Shaojing; Powell, David K.; Thalman, Scott; Watt, David S.; Abdel-Latif, Ahmed; Unrine, Jason; Thompson, Katherine; Fornwalt, Brandon; Ferrauto, Giuseppe; Vandsburger, Moriel

2016-01-01

An improved pre-clinical cardiac chemical exchange saturation transfer (CEST) pulse sequence (cardioCEST) was used to selectively visualize paramagnetic CEST (paraCEST)-labeled cells following intramyocardial implantation. In addition, cardioCEST was used to examine the effect of diet-induced obesity upon myocardial creatine CEST contrast. CEST pulse sequences were designed from standard turbo-spin-echo and gradient-echo sequences, and a cardiorespiratory-gated steady-state cine gradient-echo sequence. In vitro validation studies performed in phantoms composed of 20mM Eu-HPDO3A, 20mM Yb-HPDO3A, or saline demonstrated similar CEST contrast by spin-echo and gradient-echo pulse sequences. Skeletal myoblast cells (C2C12) were labeled with either Eu-HPDO3A or saline using a hypotonic swelling procedure and implanted into the myocardium of C57B6/J mice. Inductively coupled plasma mass spectrometry confirmed cellular levels of Eu of 2.1 × 10−3 ng/cell in Eu-HPDO3A-labeled cells and 2.3 × 10−5 ng/cell in saline-labeled cells. In vivo cardioCEST imaging of labeled cells at ±15ppm was performed 24 h after implantation and revealed significantly elevated asymmetric magnetization transfer ratio values in regions of Eu-HPDO3A-labeled cells when compared with surrounding myocardium or saline-labeled cells. We further utilized the cardioCEST pulse sequence to examine changes in myocardial creatine in response to diet-induced obesity by acquiring pairs of cardioCEST images at ±1.8 ppm. While ventricular geometry and function were unchanged between mice fed either a high-fat diet or a corresponding control low-fat diet for 14 weeks, myocardial creatine CEST contrast was significantly reduced in mice fed the high-fat diet. The selective visualization of paraCEST-labeled cells using cardioCEST imaging can enable investigation of cell fate processes in cardioregenerative medicine, or multiplex imaging of cell survival with imaging of cardiac structure and function and additional imaging of myocardial creatine. PMID:26684053

Correlative fluorescence and electron microscopy of quantum dot labeled proteins on whole cells in liquid.

PubMed

Peckys, Diana B; Dukes, Madeline J; de Jonge, Niels

2014-01-01

Correlative fluorescence microscopy and scanning transmission electron microscopy (STEM) of cells fully immersed in liquid is a new methodology with many application areas. Proteins, in live cells immobilized on microchips, are labeled with fluorescent quantum dot (QD) nanoparticles. In this protocol, the epidermal growth factor receptor (EGFR) is labeled. The cells are fixed after a selected labeling time, for example, 5 min as needed to form EGFR dimers. The microchip with cells is then imaged with fluorescence microscopy. Thereafter, the microchip with the labeled cells and one with a spacer are assembled in a special microfluidic device and imaged with STEM.

In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images.

PubMed

Christiansen, Eric M; Yang, Samuel J; Ando, D Michael; Javaherian, Ashkan; Skibinski, Gaia; Lipnick, Scott; Mount, Elliot; O'Neil, Alison; Shah, Kevan; Lee, Alicia K; Goyal, Piyush; Fedus, William; Poplin, Ryan; Esteva, Andre; Berndl, Marc; Rubin, Lee L; Nelson, Philip; Finkbeiner, Steven

2018-04-19

Microscopy is a central method in life sciences. Many popular methods, such as antibody labeling, are used to add physical fluorescent labels to specific cellular constituents. However, these approaches have significant drawbacks, including inconsistency; limitations in the number of simultaneous labels because of spectral overlap; and necessary perturbations of the experiment, such as fixing the cells, to generate the measurement. Here, we show that a computational machine-learning approach, which we call "in silico labeling" (ISL), reliably predicts some fluorescent labels from transmitted-light images of unlabeled fixed or live biological samples. ISL predicts a range of labels, such as those for nuclei, cell type (e.g., neural), and cell state (e.g., cell death). Because prediction happens in silico, the method is consistent, is not limited by spectral overlap, and does not disturb the experiment. ISL generates biological measurements that would otherwise be problematic or impossible to acquire. Copyright © 2018 Elsevier Inc. All rights reserved.

Appearance of acute gouty arthritis on indium-111-labeled leukocyte scintigraphy

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

Palestro, C.J.; Vega, A.; Kim, C.K.

1990-05-01

Indium-111-labeled leukocyte scintigraphy was performed on a 66-yr-old male with polyarticular acute gouty arthritis. Images revealed intense labeled leukocyte accumulation in a pattern indistinguishable from septic arthritis, in both knees and ankles, and the metatarsophalangeal joint of both great toes, all of which were involved in the acute gouty attack. Joint aspirate as well as blood cultures were reported as no growth; the patient was treated with intravenous colchicine and ACTH for 10 days with dramatic improvement noted. Labeled leukocyte imaging, repeated 12 days after the initial study, revealed near total resolution of joint abnormalities, concordant with the patient's clinicalmore » improvement. This case demonstrates that while acute gouty arthritis is a potential pitfall in labeled leukocyte imaging, in the presence of known gout, it may provide a simple, objective, noninvasive method of evaluating patient response to therapy.« less

The Role of Positron Emission Tomography With (68)Gallium (Ga)-Labeled Prostate-specific Membrane Antigen (PSMA) in the Management of Patients With Organ-confined and Locally Advanced Prostate Cancer Prior to Radical Treatment and After Radical Prostatectomy.

PubMed

Rai, Bhavan Prasad; Baum, Richard Paul; Patel, Amit; Hughes, Robert; Alonzi, Roberto; Lane, Tim; Adshead, Jim; Vasdev, Nikhil

2016-09-01

The role of positron emission tomography (PET) with (68)Gallium (Ga)-labeled prostate-specific membrane antigen (PSMA) imaging for prostate cancer is gaining prominence. Current imaging strategies, despite having progressed significantly, have limitations, in particular their ability to diagnose metastatic lymph node involvement. Preliminary results of PET with (68)Ga-labeled PSMA have shown encouraging results, particularly in the recurrent prostate cancer setting. Furthermore, the ability of PET with (68)Ga-labeled PSMA of playing a dual diagnostic and therapeutic setting (theranostics) is currently being investigated as well. PET with (68)Ga-labeled PSMA certainly has a role to play in bridging some of the voids in contemporary prostate cancer imaging tools. Copyright © 2016 Elsevier Inc. All rights reserved.

Carbon-11 and Fluorine-18 Labeled Amino Acid Tracers for Positron Emission Tomography Imaging of Tumors

NASA Astrophysics Data System (ADS)

Sun, Aixia; Liu, Xiang; Tang, Ganghua

2017-12-01

Tumor cells have an increased nutritional demand for amino acids(AAs) to satisfy their rapid proliferation. Positron-emitting nuclide labeled AAs are interesting probes and are of great importance for imaging tumors using positron emission tomography (PET). Carbon-11 and fluorine-18 labeled AAs include the [1-11C] amino acids, labeling alpha-C- amino acids, the branched-chain of amino acids and N-substituted carbon-11 labeled amino acids. These tracers target protein synthesis or amino acid(AA) transport, and their uptake mechanism mainly involves AA transport. AA PET tracers have been widely used in clinical settings to image brain tumors, neuroendocrine tumors, prostate cancer, breast cancer, non–small cell lung cancer (NSCLC) and hepatocellular carcinoma. This review focuses on the fundamental concepts and the uptake mechanism of AAs, AA PET tracers and their clinical applications.

New horizons in cardiac innervation imaging: introduction of novel 18F-labeled PET tracers.

PubMed

Kobayashi, Ryohei; Chen, Xinyu; Werner, Rudolf A; Lapa, Constantin; Javadi, Mehrbod S; Higuchi, Takahiro

2017-12-01

Cardiac sympathetic nervous activity can be uniquely visualized by non-invasive radionuclide imaging techniques due to the fast growing and widespread application of nuclear cardiology in the last few years. The norepinephrine analogue 123 I-meta-iodobenzylguanidine ( 123 I-MIBG) is a single photon emission computed tomography (SPECT) tracer for the clinical implementation of sympathetic nervous imaging for both diagnosis and prognosis of heart failure. Meanwhile, positron emission tomography (PET) imaging has become increasingly attractive because of its higher spatial and temporal resolution compared to SPECT, which allows regional functional and dynamic kinetic analysis. Nevertheless, wider use of cardiac sympathetic nervous PET imaging is still limited mainly due to the demand of costly on-site cyclotrons, which are required for the production of conventional 11 C-labeled (radiological half-life, 20 min) PET tracers. Most recently, more promising 18 F-labeled (half-life, 110 min) PET radiopharmaceuticals targeting sympathetic nervous system have been introduced. These tracers optimize PET imaging and, by using delivery networks, cost less to produce. In this article, the latest advances of sympathetic nervous imaging using 18 F-labeled radiotracers along with their possible applications are reviewed.

Multi-atlas based segmentation using probabilistic label fusion with adaptive weighting of image similarity measures.

PubMed

Sjöberg, C; Ahnesjö, A

2013-06-01

Label fusion multi-atlas approaches for image segmentation can give better segmentation results than single atlas methods. We present a multi-atlas label fusion strategy based on probabilistic weighting of distance maps. Relationships between image similarities and segmentation similarities are estimated in a learning phase and used to derive fusion weights that are proportional to the probability for each atlas to improve the segmentation result. The method was tested using a leave-one-out strategy on a database of 21 pre-segmented prostate patients for different image registrations combined with different image similarity scorings. The probabilistic weighting yields results that are equal or better compared to both fusion with equal weights and results using the STAPLE algorithm. Results from the experiments demonstrate that label fusion by weighted distance maps is feasible, and that probabilistic weighted fusion improves segmentation quality more the stronger the individual atlas segmentation quality depends on the corresponding registered image similarity. The regions used for evaluation of the image similarity measures were found to be more important than the choice of similarity measure. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Chemical reactivation of fluorescein isothiocyanate immunofluorescence-labeled resin-embedded samples

NASA Astrophysics Data System (ADS)

Li, Longhui; Rao, Gong; Lv, Xiaohua; Chen, Ruixi; Cheng, Xiaofeng; Wang, Xiaojun; Zeng, Shaoqun; Liu, Xiuli

2018-02-01

Resin embedding is widely used and facilitates microscopic imaging of biological tissues. In contrast, quenching of fluorescence during embedding process hinders the application of resin embedding for imaging of fluorescence-labeled samples. For samples expressing fluorescent proteins, it has been demonstrated that the weakened fluorescence could be recovered by reactivating the fluorophore with alkaline buffer. We extended this idea to immunofluorescence-labeling technology. We showed that the fluorescence of pH-sensitive fluorescein isothiocyanate (FITC) was quenched after resin embedding but reactivated after treating by alkaline buffer. We observed 138.5% fluorescence preservation ratio of reactivated state, sixfold compared with the quenched state in embedding resin, which indicated its application for fluorescence imaging of high signal-to-background ratio. Furthermore, we analyzed the chemical reactivation mechanism of FITC fluorophore. This work would show a way for high-resolution imaging of immunofluorescence-labeled samples embedded in resin.

General Staining and Segmentation Procedures for High Content Imaging and Analysis.

PubMed

Chambers, Kevin M; Mandavilli, Bhaskar S; Dolman, Nick J; Janes, Michael S

2018-01-01

Automated quantitative fluorescence microscopy, also known as high content imaging (HCI), is a rapidly growing analytical approach in cell biology. Because automated image analysis relies heavily on robust demarcation of cells and subcellular regions, reliable methods for labeling cells is a critical component of the HCI workflow. Labeling of cells for image segmentation is typically performed with fluorescent probes that bind DNA for nuclear-based cell demarcation or with those which react with proteins for image analysis based on whole cell staining. These reagents, along with instrument and software settings, play an important role in the successful segmentation of cells in a population for automated and quantitative image analysis. In this chapter, we describe standard procedures for labeling and image segmentation in both live and fixed cell samples. The chapter will also provide troubleshooting guidelines for some of the common problems associated with these aspects of HCI.

Affimer proteins for F-actin: novel affinity reagents that label F-actin in live and fixed cells.

PubMed

Lopata, Anna; Hughes, Ruth; Tiede, Christian; Heissler, Sarah M; Sellers, James R; Knight, Peter J; Tomlinson, Darren; Peckham, Michelle

2018-04-26

Imaging the actin cytoskeleton in cells uses a wide range of approaches. Typically, a fluorescent derivative of the small cyclic peptide phalloidin is used to image F-actin in fixed cells. Lifeact and F-tractin are popular for imaging the cytoskeleton in live cells. Here we characterised novel affinity reagents called Affimers that specifically bind to F-actin in vitro to determine if they are suitable alternatives as eGFP-fusion proteins, to label actin in live cells, or for labeling F-actin in fixed cells. In vitro experiments showed that 3 out of the 4 Affimers (Affimers 6, 14 and 24) tested bind tightly to purified F-actin, and appear to have overlapping binding sites. As eGFP-fusion proteins, the same 3 Affimers label F-actin in live cells. FRAP experiments suggest that eGFP-Affimer 6 behaves most similarly to F-tractin and Lifeact. However, it does not colocalise with mCherry-actin in dynamic ruffles, and may preferentially bind stable actin filaments. All 4 Affimers label F-actin in methanol fixed cells, while only Affimer 14 labels F-actin after paraformaldehyde fixation. eGFP-Affimer 6 has potential for use in selectively imaging the stable actin cytoskeleton in live cells, while all 4 Affimers are strong alternatives to phalloidin for labelling F-actin in fixed cells.

Nonlinear Interferometric Vibrational Imaging (NIVI) with Novel Optical Sources

NASA Astrophysics Data System (ADS)

Boppart, Stephen A.; King, Matthew D.; Liu, Yuan; Tu, Haohua; Gruebele, Martin

Optical imaging is essential in medicine and in fundamental studies of biological systems. Although many existing imaging modalities can supply valuable information, not all are capable of label-free imaging with high-contrast and molecular specificity. The application of molecular or nanoparticle contrast agents may adversely influence the biological system under investigation. These substances also present ongoing concerns over toxicity or particle clearance, which must be properly addressed before their approval for in vivo human imaging. Hence there is an increasing appreciation for label-free imaging techniques. It is of primary importance to develop imaging techniques that can indiscriminately identify and quantify biochemical compositions to high degrees of sensitivity and specificity through only the intrinsic optical response of endogenous molecular species. The development and use of nonlinear interferometric vibrational imaging, which is based on the interferometric detection of optical signals from coherent anti-Stokes Raman scattering (CARS), along with novel optical sources, offers the potential for label-free molecular imaging.

Direct imaging of glycans in Arabidopsis roots via click labeling of metabolically incorporated azido-monosaccharides.

PubMed

Hoogenboom, Jorin; Berghuis, Nathalja; Cramer, Dario; Geurts, Rene; Zuilhof, Han; Wennekes, Tom

2016-10-10

Carbohydrates, also called glycans, play a crucial but not fully understood role in plant health and development. The non-template driven formation of glycans makes it impossible to image them in vivo with genetically encoded fluorescent tags and related molecular biology approaches. A solution to this problem is the use of tailor-made glycan analogs that are metabolically incorporated by the plant into its glycans. These metabolically incorporated probes can be visualized, but techniques documented so far use toxic copper-catalyzed labeling. To further expand our knowledge of plant glycobiology by direct imaging of its glycans via this method, there is need for novel click-compatible glycan analogs for plants that can be bioorthogonally labelled via copper-free techniques. Arabidopsis seedlings were incubated with azido-containing monosaccharide analogs of N-acetylglucosamine, N-acetylgalactosamine, L-fucose, and L-arabinofuranose. These azido-monosaccharides were metabolically incorporated in plant cell wall glycans of Arabidopsis seedlings. Control experiments indicated active metabolic incorporation of the azido-monosaccharide analogs into glycans rather than through non-specific absorption of the glycan analogs onto the plant cell wall. Successful copper-free labeling reactions were performed, namely an inverse-electron demand Diels-Alder cycloaddition reaction using an incorporated N-acetylglucosamine analog, and a strain-promoted azide-alkyne click reaction. All evaluated azido-monosaccharide analogs were observed to be non-toxic at the used concentrations under normal growth conditions. Our results for the metabolic incorporation and fluorescent labeling of these azido-monosaccharide analogs expand the possibilities for studying plant glycans by direct imaging. Overall we successfully evaluated five azido-monosaccharide analogs for their ability to be metabolically incorporated in Arabidopsis roots and their imaging after fluorescent labeling. This expands the molecular toolbox for direct glycan imaging in plants, from three to eight glycan analogs, which enables more extensive future studies of spatiotemporal glycan dynamics in a wide variety of plant tissues and species. We also show, for the first time in metabolic labeling and imaging of plant glycans, the potential of two copper-free click chemistry methods that are bio-orthogonal and lead to more uniform labeling. These improved labeling methods can be generalized and extended to already existing and future click chemistry-enabled monosaccharide analogs in Arabidopsis.

Automated segmentation and geometrical modeling of the tricuspid aortic valve in 3D echocardiographic images.

PubMed

Pouch, Alison M; Wang, Hongzhi; Takabe, Manabu; Jackson, Benjamin M; Sehgal, Chandra M; Gorman, Joseph H; Gorman, Robert C; Yushkevich, Paul A

2013-01-01

The aortic valve has been described with variable anatomical definitions, and the consistency of 2D manual measurement of valve dimensions in medical image data has been questionable. Given the importance of image-based morphological assessment in the diagnosis and surgical treatment of aortic valve disease, there is considerable need to develop a standardized framework for 3D valve segmentation and shape representation. Towards this goal, this work integrates template-based medial modeling and multi-atlas label fusion techniques to automatically delineate and quantitatively describe aortic leaflet geometry in 3D echocardiographic (3DE) images, a challenging task that has been explored only to a limited extent. The method makes use of expert knowledge of aortic leaflet image appearance, generates segmentations with consistent topology, and establishes a shape-based coordinate system on the aortic leaflets that enables standardized automated measurements. In this study, the algorithm is evaluated on 11 3DE images of normal human aortic leaflets acquired at mid systole. The clinical relevance of the method is its ability to capture leaflet geometry in 3DE image data with minimal user interaction while producing consistent measurements of 3D aortic leaflet geometry.

Microwave Sensors for Breast Cancer Detection

PubMed Central

2018-01-01

Breast cancer is the leading cause of death among females, early diagnostic methods with suitable treatments improve the 5-year survival rates significantly. Microwave breast imaging has been reported as the most potential to become the alternative or additional tool to the current gold standard X-ray mammography for detecting breast cancer. The microwave breast image quality is affected by the microwave sensor, sensor array, the number of sensors in the array and the size of the sensor. In fact, microwave sensor array and sensor play an important role in the microwave breast imaging system. Numerous microwave biosensors have been developed for biomedical applications, with particular focus on breast tumor detection. Compared to the conventional medical imaging and biosensor techniques, these microwave sensors not only enable better cancer detection and improve the image resolution, but also provide attractive features such as label-free detection. This paper aims to provide an overview of recent important achievements in microwave sensors for biomedical imaging applications, with particular focus on breast cancer detection. The electric properties of biological tissues at microwave spectrum, microwave imaging approaches, microwave biosensors, current challenges and future works are also discussed in the manuscript. PMID:29473867

Spectroscopic imaging of biomaterials and biological systems with FTIR microscopy or with quantum cascade lasers.

PubMed

Kimber, James A; Kazarian, Sergei G

2017-10-01

Spectroscopic imaging of biomaterials and biological systems has received increased interest within the last decade because of its potential to aid in the detection of disease using biomaterials/biopsy samples and to probe the states of live cells in a label-free manner. The factors behind this increased attention include the availability of improved infrared microscopes and systems that do not require the use of a synchrotron as a light source, as well as the decreasing costs of these systems. This article highlights the current technical challenges and future directions of mid-infrared spectroscopic imaging within this field. Specifically, these are improvements in spatial resolution and spectral quality through the use of novel added lenses and computational algorithms, as well as quantum cascade laser imaging systems, which offer advantages over traditional Fourier transform infrared systems with respect to the speed of acquisition and field of view. Overcoming these challenges will push forward spectroscopic imaging as a viable tool for disease diagnostics and medical research. Graphical abstract Absorbance images of a biopsy obtained using an FTIR imaging microscope with and without an added lens, and also using a QCL microscope with high-NA objective.

Microwave Sensors for Breast Cancer Detection.

PubMed

Wang, Lulu

2018-02-23

Breast cancer is the leading cause of death among females, early diagnostic methods with suitable treatments improve the 5-year survival rates significantly. Microwave breast imaging has been reported as the most potential to become the alternative or additional tool to the current gold standard X-ray mammography for detecting breast cancer. The microwave breast image quality is affected by the microwave sensor, sensor array, the number of sensors in the array and the size of the sensor. In fact, microwave sensor array and sensor play an important role in the microwave breast imaging system. Numerous microwave biosensors have been developed for biomedical applications, with particular focus on breast tumor detection. Compared to the conventional medical imaging and biosensor techniques, these microwave sensors not only enable better cancer detection and improve the image resolution, but also provide attractive features such as label-free detection. This paper aims to provide an overview of recent important achievements in microwave sensors for biomedical imaging applications, with particular focus on breast cancer detection. The electric properties of biological tissues at microwave spectrum, microwave imaging approaches, microwave biosensors, current challenges and future works are also discussed in the manuscript.

Label-free imaging of developing vasculature in zebrafish with phase variance optical coherence microscopy

NASA Astrophysics Data System (ADS)

Chen, Yu; Fingler, Jeff; Trinh, Le A.; Fraser, Scott E.

2016-03-01

A phase variance optical coherence microscope (pvOCM) has been created to visualize blood flow in the vasculature of zebrafish embryos, without using exogenous labels. The pvOCM imaging system has axial and lateral resolutions of 2 μm in tissue, and imaging depth of more than 100 μm. Imaging of 2-5 days post-fertilization zebrafish embryos identified the detailed structures of somites, spinal cord, gut and notochord based on intensity contrast. Visualization of the blood flow in the aorta, veins and intersegmental vessels was achieved with phase variance contrast. The pvOCM vasculature images were confirmed with corresponding fluorescence microscopy of a zebrafish transgene that labels the vasculature with green fluorescent protein. The pvOCM images also revealed functional information of the blood flow activities that is crucial for the study of vascular development.

Whole-organ atlas imaged by label-free high-resolution photoacoustic microscopy assisted by a microtome

NASA Astrophysics Data System (ADS)

Wong, Terence T. W.; Zhang, Ruiying; Hsu, Hsun-Chia; Maslov, Konstantin I.; Shi, Junhui; Chen, Ruimin; Shung, K. Kirk; Zhou, Qifa; Wang, Lihong V.

2018-02-01

In biomedical imaging, all optical techniques face a fundamental trade-off between spatial resolution and tissue penetration. Therefore, obtaining an organelle-level resolution image of a whole organ has remained a challenging and yet appealing scientific pursuit. Over the past decade, optical microscopy assisted by mechanical sectioning or chemical clearing of tissue has been demonstrated as a powerful technique to overcome this dilemma, one of particular use in imaging the neural network. However, this type of techniques needs lengthy special preparation of the tissue specimen, which hinders broad application in life sciences. Here, we propose a new label-free three-dimensional imaging technique, named microtomy-assisted photoacoustic microscopy (mPAM), for potentially imaging all biomolecules with 100% endogenous natural staining in whole organs with high fidelity. We demonstrate the first label-free mPAM, using UV light for label-free histology-like imaging, in whole organs (e.g., mouse brains), most of them formalin-fixed and paraffin- or agarose-embedded for minimal morphological deformation. Furthermore, mPAM with dual wavelength illuminations is also employed to image a mouse brain slice, demonstrating the potential for imaging of multiple biomolecules without staining. With visible light illumination, mPAM also shows its deep tissue imaging capability, which enables less slicing and hence reduces sectioning artifacts. mPAM could potentially provide a new insight for understanding complex biological organs.

Alzheimer disease detection from structural MR images using FCM based weighted probabilistic neural network.

PubMed

Duraisamy, Baskar; Shanmugam, Jayanthi Venkatraman; Annamalai, Jayanthi

2018-02-19

An early intervention of Alzheimer's disease (AD) is highly essential due to the fact that this neuro degenerative disease generates major life-threatening issues, especially memory loss among patients in society. Moreover, categorizing NC (Normal Control), MCI (Mild Cognitive Impairment) and AD early in course allows the patients to experience benefits from new treatments. Therefore, it is important to construct a reliable classification technique to discriminate the patients with or without AD from the bio medical imaging modality. Hence, we developed a novel FCM based Weighted Probabilistic Neural Network (FWPNN) classification algorithm and analyzed the brain images related to structural MRI modality for better discrimination of class labels. Initially our proposed framework begins with brain image normalization stage. In this stage, ROI regions related to Hippo-Campus (HC) and Posterior Cingulate Cortex (PCC) from the brain images are extracted using Automated Anatomical Labeling (AAL) method. Subsequently, nineteen highly relevant AD related features are selected through Multiple-criterion feature selection method. At last, our novel FWPNN classification algorithm is imposed to remove suspicious samples from the training data with an end goal to enhance the classification performance. This newly developed classification algorithm combines both the goodness of supervised and unsupervised learning techniques. The experimental validation is carried out with the ADNI subset and then to the Bordex-3 city dataset. Our proposed classification approach achieves an accuracy of about 98.63%, 95.4%, 96.4% in terms of classification with AD vs NC, MCI vs NC and AD vs MCI. The experimental results suggest that the removal of noisy samples from the training data can enhance the decision generation process of the expert systems.

Exploring lipids with nonlinear optical microscopy in multiple biological systems

NASA Astrophysics Data System (ADS)

Alfonso-Garcia, Alba

Lipids are crucial biomolecules for the well being of humans. Altered lipid metabolism may give rise to a variety of diseases that affect organs from the cardiovascular to the central nervous system. A deeper understanding of lipid metabolic processes would spur medical research towards developing precise diagnostic tools, treatment methods, and preventive strategies for reducing the impact of lipid diseases. Lipid visualization remains a complex task because of the perturbative effect exerted by traditional biochemical assays and most fluorescence markers. Coherent Raman scattering (CRS) microscopy enables interrogation of biological samples with minimum disturbance, and is particularly well suited for label-free visualization of lipids, providing chemical specificity without compromising on spatial resolution. Hyperspectral imaging yields large datasets that benefit from tailored multivariate analysis. In this thesis, CRS microscopy was combined with Raman spectroscopy and other label-free nonlinear optical techniques to analyze lipid metabolism in multiple biological systems. We used nonlinear Raman techniques to characterize Meibum secretions in the progression of dry eye disease, where the lipid and protein contributions change in ratio and phase segregation. We employed similar tools to examine lipid droplets in mice livers aboard a spaceflight mission, which lose their retinol content contributing to the onset of nonalcoholic fatty-liver disease. We also focused on atherosclerosis, a disease that revolves around lipid-rich plaques in arterial walls. We examined the lipid content of macrophages, whose variable phenotype gives rise to contrasting healing and inflammatory activities. We also proposed new label-free markers, based on lifetime imaging, for macrophage phenotype, and to detect products of lipid oxidation. Cholesterol was also detected in hepatitis C virus infected cells, and in specific strains of age-related macular degeneration diseased cells by spontaneous Raman spectroscopy. We used synthesized highly-deuterated cholesterol to track its compartmentalization in adrenal cells, revealing heterogeneous lipid droplet content. These examples illustrate the potential of label-free nonlinear optical microscopy for unveiling complex physiological processes by direct visualization of lipids. Detailed image analysis and combined microscopy modalities will continue to reveal and quantify fundamental biology that will support the advance of biomedicine.

Comparison of pre-processing techniques for fluorescence microscopy images of cells labeled for actin.

PubMed

Muralidhar, Gautam S; Channappayya, Sumohana S; Slater, John H; Blinka, Ellen M; Bovik, Alan C; Frey, Wolfgang; Markey, Mia K

2008-11-06

Automated analysis of fluorescence microscopy images of endothelial cells labeled for actin is important for quantifying changes in the actin cytoskeleton. The current manual approach is laborious and inefficient. The goal of our work is to develop automated image analysis methods, thereby increasing cell analysis throughput. In this study, we present preliminary results on comparing different algorithms for cell segmentation and image denoising.

Label-free imaging of cellular malformation using high resolution photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Chen, Zhongjiang; Li, Bingbing; Yang, Sihua

2014-09-01

A label-free high resolution photoacoustic microscopy (PAM) system for imaging cellular malformation is presented. The carbon fibers were used to testify the lateral resolution of the PAM. Currently, the lateral resolution is better than 2.7 μm. The human normal red blood cells (RBCs) were used to prove the imaging capability of the system, and a single red blood cell was mapped with high contrast. Moreover, the iron deficiency anemia RBCs were clearly distinguished from the cell morphology by using the PAM. The experimental results demonstrate that the photoacoustic microscopy system can accomplish label-free photoacoustic imaging and that it has clinical potential for use in the detection of erythrocytes and blood vessels malformation.

Systems-level analysis of microbial community organization through combinatorial labeling and spectral imaging.

PubMed

Valm, Alex M; Mark Welch, Jessica L; Rieken, Christopher W; Hasegawa, Yuko; Sogin, Mitchell L; Oldenbourg, Rudolf; Dewhirst, Floyd E; Borisy, Gary G

2011-03-08

Microbes in nature frequently function as members of complex multitaxon communities, but the structural organization of these communities at the micrometer level is poorly understood because of limitations in labeling and imaging technology. We report here a combinatorial labeling strategy coupled with spectral image acquisition and analysis that greatly expands the number of fluorescent signatures distinguishable in a single image. As an imaging proof of principle, we first demonstrated visualization of Escherichia coli labeled by fluorescence in situ hybridization (FISH) with 28 different binary combinations of eight fluorophores. As a biological proof of principle, we then applied this Combinatorial Labeling and Spectral Imaging FISH (CLASI-FISH) strategy using genus- and family-specific probes to visualize simultaneously and differentiate 15 different phylotypes in an artificial mixture of laboratory-grown microbes. We then illustrated the utility of our method for the structural analysis of a natural microbial community, namely, human dental plaque, a microbial biofilm. We demonstrate that 15 taxa in the plaque community can be imaged simultaneously and analyzed and that this community was dominated by early colonizers, including species of Streptococcus, Prevotella, Actinomyces, and Veillonella. Proximity analysis was used to determine the frequency of inter- and intrataxon cell-to-cell associations which revealed statistically significant intertaxon pairings. Cells of the genera Prevotella and Actinomyces showed the most interspecies associations, suggesting a central role for these genera in establishing and maintaining biofilm complexity. The results provide an initial systems-level structural analysis of biofilm organization.

'Off-label' prescribing, the Physician's Desk Reference and the court.

PubMed

Spector, Richard A; Marquez, Eva

2011-01-01

"Off-label" prescribing is the use of a drug in a fashion other than one approved by the Food and Drug Administration (FDA). Some courts assume that the PDR is comprehensive enough to apply its guidelines to establish the standard of care. This assumption undermines the physician's judgment in deciding how, when and for what ailment a drug should be used. It substitutes the judgment of the PDR and FDA for the physician in assessing illness and applied pharmacology. We report the results of a survey presented to leaders in the United States medical community and review medical literature and legal cases addressing off-label prescribing. Unlike some US courts, the medical community does not consider the PDR as representative of all applications of drug use, nor does it consider the PDR as the standard of medical care.

78 FR 951 - Accessible Medical Device Labeling in a Standard Content and Format Public Workshop; Request for...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-07

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2012-N-1205] Accessible Medical Device Labeling in a Standard Content and Format Public Workshop; Request for Comments AGENCY: Food and Drug Administration, HHS. ACTION: Notice of public workshop; request for comments...

78 FR 6825 - Accessible Medical Device Labeling in a Standard Content and Format Public Workshop; Request for...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-31

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2012-N-1205] Accessible Medical Device Labeling in a Standard Content and Format Public Workshop; Request for Comments; Correction AGENCY: Food and Drug Administration, HHS. ACTION: Notice of public workshop; request for comments...

What do Australian consumers, pharmacists and prescribers think about documenting indications on prescriptions and dispensed medicines labels?: A qualitative study.

PubMed

Garada, Mona; McLachlan, Andrew J; Schiff, Gordon D; Lehnbom, Elin C

2017-11-15

Documenting the indication on prescriptions and dispensed medicines labels is not standard practice in Australia. However, previous studies that have focused on the content and design of dispensed medicines labels, have suggested including the indication as a safety measure. The aim of this study was to investigate the perspectives of Australian consumers, pharmacists and prescribers on documenting the indication on prescriptions and dispensed medicines labels. Semi-structured interviews were conducted and mock-up of dispensed medicines labels were designed for participants. Consumers (n = 19) and pharmacists (n = 7) were recruited by convenience sample at community pharmacies in Sydney (Australia) and prescribers (n = 8), including two medical students, were recruited through snowballing. Thirty-four participants were interviewed. Most participants agreed that documenting the indication would be beneficial especially for patients who are forgetful or take multiple medications. Participants also believed it would improve consumers' medication understanding and adherence. Prescribers and pharmacists believed it could help reduce prescribing and dispensing errors by matching the drug/dosage to the correct indication. Prescribers refrained from documenting the indication to protect patients' privacy; however, most patients did not consider documenting the indication as a breach of privacy. Prescribers raised concerns about the extra time to include indications on prescriptions and best language to document indications, using plain language as opposed to medical terminology. All interviewed stakeholders identified numerous benefits of documenting the indication on prescriptions and dispensed medicines labels. Whether these potential benefits can be realized remains unknown and addressing prescribers' concern regarding the time involved in documenting the indication on prescriptions remains a challenge for vendors of electronic medication management systems.

Multimodality imaging using SPECT/CT and MRI and ligand functionalized 99mTc-labeled magnetic microbubbles

PubMed Central

2013-01-01

Background In the present study, we used multimodal imaging to investigate biodistribution in rats after intravenous administration of a new 99mTc-labeled delivery system consisting of polymer-shelled microbubbles (MBs) functionalized with diethylenetriaminepentaacetic acid (DTPA), thiolated poly(methacrylic acid) (PMAA), chitosan, 1,4,7-triacyclononane-1,4,7-triacetic acid (NOTA), NOTA-super paramagnetic iron oxide nanoparticles (SPION), or DTPA-SPION. Methods Examinations utilizing planar dynamic scintigraphy and hybrid imaging were performed using a commercially available single-photon emission computed tomography (SPECT)/computed tomography (CT) system. For SPION containing MBs, the biodistribution pattern of 99mTc-labeled NOTA-SPION and DTPA-SPION MBs was investigated and co-registered using fusion SPECT/CT and magnetic resonance imaging (MRI). Moreover, to evaluate the biodistribution, organs were removed and radioactivity was measured and calculated as percentage of injected dose. Results SPECT/CT and MRI showed that the distribution of 99mTc-labeled ligand-functionalized MBs varied with the type of ligand as well as with the presence of SPION. The highest uptake was observed in the lungs 1 h post injection of 99mTc-labeled DTPA and chitosan MBs, while a similar distribution to the lungs and the liver was seen after the administration of PMAA MBs. The highest counts of 99mTc-labeled NOTA-SPION and DTPA-SPION MBs were observed in the lungs, liver, and kidneys 1 h post injection. The highest counts were observed in the liver, spleen, and kidneys as confirmed by MRI 24 h post injection. Furthermore, the results obtained from organ measurements were in good agreement with those obtained from SPECT/CT. Conclusions In conclusion, microbubbles functionalized by different ligands can be labeled with radiotracers and utilized for SPECT/CT imaging, while the incorporation of SPION in MB shells enables imaging using MR. Our investigation revealed that biodistribution may be modified using different ligands. Furthermore, using a single contrast agent with fusion SPECT/CT/MR multimodal imaging enables visualization of functional and anatomical information in one image, thus improving the diagnostic benefit for patients. PMID:23442550

Monitoring Cerebrovascular Reactivity through the Use of Arterial Spin Labeling in Patients with Moyamoya Disease.

PubMed

Yun, Tae Jin; Paeng, Jin Chul; Sohn, Chul-Ho; Kim, Jeong Eun; Kang, Hyun-Seung; Yoon, Byung-Woo; Choi, Seung Hong; Kim, Ji-hoon; Lee, Ho-Young; Han, Moon Hee; Zaharchuk, Greg

2016-01-01

To assess arterial spin labeling in the identification of impaired cerebrovascular reactivity in patients with moyamoya disease. The institutional review board approved this prospective study, and written informed consent was obtained from all patients. A prospective study was conducted in 78 subjects with moyamoya disease (of whom 31 underwent unilateral direct arterial anastomosis). The concordance between the cerebrovascular reactivity index values from arterial spin labeling and single photon emission computed tomography (SPECT) was assessed by using Bland-Altman analysis, and the area under the receiver operating characteristic curve was used to evaluate the diagnostic accuracy of arterial spin labeling to depict impaired cerebrovascular reactivity (in which the cerebrovascular reactivity index value is less than 0% on SPECT images). The cerebrovascular reactivity index from arterial spin labeling had a lower value than that from SPECT (mean difference, -4.2%). The area under the receiver operating characteristic curve for arterial spin labeling in the detection of impaired cerebrovascular reactivity was at least 0.85. On the anastomotic side, a significant increase was found between the cerebrovascular reactivity index values on arterial spin labeling images obtained preoperatively and those obtained 6 months after surgery, as well as on SPECT images (mean ± standard deviation values of cerebrovascular reactivity index increased by 5.9% ± 10.9 and 3.0% ± 6.3 for arterial spin labeling and SPECT, respectively). Arterial spin labeling has excellent performance in the identification of impaired cerebrovascular reactivity in patients with moyamoya disease, and it has the potential to serve as a noninvasive imaging tool to monitor cerebrovascular reactivity in patients with moyamoya disease. © RSNA, 2015

A web-based computer aided system for liver surgery planning: initial implementation on RayPlus

NASA Astrophysics Data System (ADS)

Luo, Ming; Yuan, Rong; Sun, Zhi; Li, Tianhong; Xie, Qingguo

2016-03-01

At present, computer aided systems for liver surgery design and risk evaluation are widely used in clinical all over the world. However, most systems are local applications that run on high-performance workstations, and the images have to processed offline. Compared with local applications, a web-based system is accessible anywhere and for a range of regardless of relative processing power or operating system. RayPlus (http://rayplus.life.hust.edu.cn), a B/S platform for medical image processing, was developed to give a jump start on web-based medical image processing. In this paper, we implement a computer aided system for liver surgery planning on the architecture of RayPlus. The system consists of a series of processing to CT images including filtering, segmentation, visualization and analyzing. Each processing is packaged into an executable program and runs on the server side. CT images in DICOM format are processed step by to interactive modeling on browser with zero-installation and server-side computing. The system supports users to semi-automatically segment the liver, intrahepatic vessel and tumor from the pre-processed images. Then, surface and volume models are built to analyze the vessel structure and the relative position between adjacent organs. The results show that the initial implementation meets satisfactorily its first-order objectives and provide an accurate 3D delineation of the liver anatomy. Vessel labeling and resection simulation are planned to add in the future. The system is available on Internet at the link mentioned above and an open username for testing is offered.

Multifunctional PSCA antibody fragments for PET and optical prostate cancer imaging

DTIC Science & Technology

2017-10-01

INVESTIGATOR: Anna M. Wu CONTRACTING ORGANIZATION: University of California, Los Angeles Los Angeles, CA 90095-1406 REPORT DATE : October 2017 TYPE OF...cys- minibodies and cys-diabodies) can be labeled with radioisotopes for non-invasive PET imaging for use at multiple points in the prostate cancer...optimize and test multifunctional, F-18, and alternatively labeled fragments Major Task 3. New technologies: alternative site-specific labeling methods

Parental misinterpretations of over-the-counter pediatric cough and cold medication labels.

PubMed

Lokker, Nicole; Sanders, Lee; Perrin, Eliana M; Kumar, Disha; Finkle, Joanne; Franco, Vivian; Choi, Leena; Johnston, Philip E; Rothman, Russell L

2009-06-01

Concerns about the safety and efficacy of over-the-counter cold medications have led to a recent US Food and Drug Administration public health advisory against their use in children <2 years of age. Our goal was to examine caregiver understanding of the age indication of over-the-counter cold medication labels and identify factors, associated with caregiver understanding. Caregivers of infant children (< or =1 year old) were recruited from clinics at 3 institutions. Questions were administered regarding the use of 4 previously common "infant" over-the-counter cold and cough medicines labeled to consult a physician if used in children <2 years of age. Literacy and numeracy skills were assessed with validated instruments. A total of 182 caregivers were recruited; 87% were the infants' mothers. Mean education level was 12.5 years, and 99% had adequate literacy skills, but only 17% had >9th-grade numeracy skills. When examining the front of the product label, 86% of the time parents thought these products were appropriate for use in children <2 years of age. More than 50% of the time, parents stated they would give these over-the-counter products to a 13-month-old child with cold symptoms. Common factors that influenced parental decisions included label saying "infant," graphics (eg, infants, teddy bears, droppers), and dosing directions. Caregivers were influenced by the dosing directions only 47% of the time. Caregivers with lower numeracy skills were more likely to provide inappropriate reasons for giving an over-the-counter medication. Misunderstanding of over-the-counter cold products is common and could result in harm if medications are given inappropriately. Label language and graphics seem to influence inappropriate interpretation of over-the-counter product age indications. Poorer parental numeracy skills may increase the misinterpretation of these products. Opportunities exist for the Food and Drug Administration and manufacturers to revise existing labels to improve parental comprehension and enhance child safety.

Nanoparticles and clinically applicable cell tracking

PubMed Central

Guenoun, Jamal; van Tiel, Sandra T; Krestin, Gabriel P

2015-01-01

In vivo cell tracking has emerged as a much sought after tool for design and monitoring of cell-based treatment strategies. Various techniques are available for pre-clinical animal studies, from which much has been learned and still can be learned. However, there is also a need for clinically translatable techniques. Central to in vivo cell imaging is labelling of cells with agents that can give rise to signals in vivo, that can be detected and measured non-invasively. The current imaging technology of choice for clinical translation is MRI in combination with labelling of cells with magnetic agents. The main challenge encountered during the cell labelling procedure is to efficiently incorporate the label into the cell, such that the labelled cells can be imaged at high sensitivity for prolonged periods of time, without the labelling process affecting the functionality of the cells. In this respect, nanoparticles offer attractive features since their structure and chemical properties can be modified to facilitate cellular incorporation and because they can carry a high payload of the relevant label into cells. While these technologies have already been applied in clinical trials and have increased the understanding of cell-based therapy mechanism, many challenges are still faced. PMID:26248872

Optimized labeling of membrane proteins for applications to super-resolution imaging in confined cellular environments using monomeric streptavidin.

PubMed

Chamma, Ingrid; Rossier, Olivier; Giannone, Grégory; Thoumine, Olivier; Sainlos, Matthieu

2017-04-01

Recent progress in super-resolution imaging (SRI) has created a strong need to improve protein labeling with probes of small size that minimize the target-to-label distance, increase labeling density, and efficiently penetrate thick biological tissues. This protocol describes a method for labeling genetically modified proteins incorporating a small biotin acceptor peptide with a 3-nm fluorescent probe, monomeric streptavidin. We show how to express, purify, and conjugate the probe to organic dyes with different fluorescent properties, and how to label selectively biotinylated membrane proteins for SRI techniques (point accumulation in nanoscale topography (PAINT), stimulated emission depletion (STED), stochastic optical reconstruction microscopy (STORM)). This method is complementary to the previously described anti-GFP-nanobody/SNAP-tag strategies, with the main advantage being that it requires only a short 15-amino-acid tag, and can thus be used with proteins resistant to fusion with large tags and for multicolor imaging. The protocol requires standard molecular biology/biochemistry equipment, making it easily accessible for laboratories with only basic skills in cell biology and biochemistry. The production/purification/conjugation steps take ∼5 d, and labeling takes a few minutes to an hour.

Segmentation of radiologic images with self-organizing maps: the segmentation problem transformed into a classification task

NASA Astrophysics Data System (ADS)

Pelikan, Erich; Vogelsang, Frank; Tolxdorff, Thomas

1996-04-01

The texture-based segmentation of x-ray images of focal bone lesions using topological maps is introduced. Texture characteristics are described by image-point correlation of feature images to feature vectors. For the segmentation, the topological map is labeled using an improved labeling strategy. Results of the technique are demonstrated on original and synthetic x-ray images and quantified with the aid of quality measures. In addition, a classifier-specific contribution analysis is applied for assessing the feature space.

Prospects and challenges of quantitative phase imaging in tumor cell biology

NASA Astrophysics Data System (ADS)

Kemper, Björn; Götte, Martin; Greve, Burkhard; Ketelhut, Steffi

2016-03-01

Quantitative phase imaging (QPI) techniques provide high resolution label-free quantitative live cell imaging. Here, prospects and challenges of QPI in tumor cell biology are presented, using the example of digital holographic microscopy (DHM). It is shown that the evaluation of quantitative DHM phase images allows the retrieval of different parameter sets for quantification of cellular motion changes in migration and motility assays that are caused by genetic modifications. Furthermore, we demonstrate simultaneously label-free imaging of cell growth and morphology properties.

Change Detection in Uav Video Mosaics Combining a Feature Based Approach and Extended Image Differencing

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2016-06-01

Change detection is an important task when using unmanned aerial vehicles (UAV) for video surveillance. We address changes of short time scale using observations in time distances of a few hours. Each observation (previous and current) is a short video sequence acquired by UAV in near-Nadir view. Relevant changes are, e.g., recently parked or moved vehicles. Examples for non-relevant changes are parallaxes caused by 3D structures of the scene, shadow and illumination changes, and compression or transmission artifacts. In this paper we present (1) a new feature based approach to change detection, (2) a combination with extended image differencing (Saur et al., 2014), and (3) the application to video sequences using temporal filtering. In the feature based approach, information about local image features, e.g., corners, is extracted in both images. The label "new object" is generated at image points, where features occur in the current image and no or weaker features are present in the previous image. The label "vanished object" corresponds to missing or weaker features in the current image and present features in the previous image. This leads to two "directed" change masks and differs from image differencing where only one "undirected" change mask is extracted which combines both label types to the single label "changed object". The combination of both algorithms is performed by merging the change masks of both approaches. A color mask showing the different contributions is used for visual inspection by a human image interpreter.

A New F-18 Labeled PET Agent For Imaging Alzheimer's Plaques

NASA Astrophysics Data System (ADS)

Kulkarni, Padmakar V.; Vasdev, Neil; Hao, Guiyang; Arora, Veera; Long, Michael; Slavine, Nikolai; Chiguru, Srinivas; Qu, Bao Xi; Sun, Xiankai; Bennett, Michael; Antich, Peter P.; Bonte, Frederick J.

2011-06-01

Amyloid plaques and neurofibrillary tangles are hallmarks of Alzheimer's disease (AD). Advances in development of imaging agents have focused on targeting amyloid plaques. Notable success has been the development of C-11 labeled PIB (Pittsburgh Compound) and a number of studies have demonstrated the utility of this agent. However, the short half life of C-11 (t1/2: 20 min), is a limitation, thus has prompted the development of F-18 labeled agents. Most of these agents are derivatives of amyloid binding dyes; Congo red and Thioflavin. Some of these agents are in clinical trials with encouraging results. We have been exploring new class of agents based on 8-hydroxy quinoline, a weak metal chelator, targeting elevated levels of metals in plaques. Iodine-123 labeled clioquinol showed affinity for amyloid plaques however, it had limited brain uptake and was not successful in imaging in intact animals and humans. We have been successful in synthesizing F-18 labeled 8-hydroxy quinoline. Small animal PET/CT imaging studies with this agent showed high (7-10% ID/g), rapid brain uptake and fast washout of the agent from normal mice brains and delayed washout from transgenic Alzheimer's mice. These promising results encouraged us in further evaluation of this class of compounds for imaging AD plaques.

Clinical, legal and ethical implications of the intra-ocular (off-label) use of bevacizumab (avastin)--a South African perspective.

PubMed

Jansen, Rita-Marié; Gouws, Chris

2009-06-01

Choroidal neovascularisation is a potentially visually devastating element of various forms of eye pathology. Recent research has focused on neurovascular age-related macular degeneration (AMD) as a cause. AMD can be classified as being exudative (wet) or atrophic (dry). Wet AMD is characterised by a pathological process in which new blood vessels develop in the choroids, causing leakage of fluid and haemorrhage under the retina and leading to localised serous detachment and loss of central vision. Vascular endothelial growth factor (VEGF) stimulates growth of neovascular membranes. Treatments have until recently yielded disappointing results. Ophthalmologists are using intra-ocular injections of bevacizumab (Avastin), an anti-VEGF, to treat AMD. Avastin appears to be safe and effective in the short term, but its intra-ocular administration is entirely off-label. Avastin is registered for treating metastatic colorectal and breast cancer. The off-label use of medication is an important part of mainstream, legitimate medical practice worldwide. Lawyers representing plaintiffs injured by drugs increasingly encounter off-label use claims. From a legal/ethical point of view the off-label use of medication represents a delicate balance between the statutory regulation of medication and a physician's prerogative to prescribe medication that in his or her medical opinion will be beneficial to the patient. The main reason for the controversy created by the off-label use of Avastin is that there are anti-VEGF drugs on the market that have formal approval for the treatment of AMD (and other eye conditions). Lucentis, for example, is extremely expensive, with treatment cost approximately 50 times that of Avastin. Many patients suffering from AMD and macular oedema cannot afford the registered product. The off-label use of Avastin has passed the innovative or experimental stages, as ophthalmologists have used it regularly and openly for a long time, with good success. Such use therefore cannot be considered careless, imprudent or unprofessional. We submit that an ophthalmologist who omits to inform a patient of the availability of Avastin for this form of treatment may be found to be negligent. Protocols developed by the South African Vitreoretinal Society and endorsed by the Ophthalmological Society of South Africa for administering Avastin and other intra-ocular medication intravitreally should be strictly adhered to.

Opto-fluidics based microscopy and flow cytometry on a cell phone for blood analysis.

PubMed

Zhu, Hongying; Ozcan, Aydogan

2015-01-01

Blood analysis is one of the most important clinical tests for medical diagnosis. Flow cytometry and optical microscopy are widely used techniques to perform blood analysis and therefore cost-effective translation of these technologies to resource limited settings is critical for various global health as well as telemedicine applications. In this chapter, we review our recent progress on the integration of imaging flow cytometry and fluorescent microscopy on a cell phone using compact, light-weight and cost-effective opto-fluidic attachments integrated onto the camera module of a smartphone. In our cell-phone based opto-fluidic imaging cytometry design, fluorescently labeled cells are delivered into the imaging area using a disposable micro-fluidic chip that is positioned above the existing camera unit of the cell phone. Battery powered light-emitting diodes (LEDs) are butt-coupled to the sides of this micro-fluidic chip without any lenses, which effectively acts as a multimode slab waveguide, where the excitation light is guided to excite the fluorescent targets within the micro-fluidic chip. Since the excitation light propagates perpendicular to the detection path, an inexpensive plastic absorption filter is able to reject most of the scattered light and create a decent dark-field background for fluorescent imaging. With this excitation geometry, the cell-phone camera can record fluorescent movies of the particles/cells as they are flowing through the microchannel. The digital frames of these fluorescent movies are then rapidly processed to quantify the count and the density of the labeled particles/cells within the solution under test. With a similar opto-fluidic design, we have recently demonstrated imaging and automated counting of stationary blood cells (e.g., labeled white blood cells or unlabeled red blood cells) loaded within a disposable cell counting chamber. We tested the performance of this cell-phone based imaging cytometry and blood analysis platform by measuring the density of red and white blood cells as well as hemoglobin concentration in human blood samples, which showed a good match to our measurement results obtained using a commercially available hematology analyzer. Such a cell-phone enabled opto-fluidics microscopy, flow cytometry, and blood analysis platform could be especially useful for various telemedicine applications in remote and resource-limited settings.

Labeling and Magnetic Resonance Imaging of Exosomes Isolated from Adipose Stem Cells.

PubMed

Busato, Alice; Bonafede, Roberta; Bontempi, Pietro; Scambi, Ilaria; Schiaffino, Lorenzo; Benati, Donatella; Malatesta, Manuela; Sbarbati, Andrea; Marzola, Pasquina; Mariotti, Raffaella

2017-06-19

Adipose stem cells (ASC) represent a promising therapeutic approach for neurodegenerative diseases. Most biological effects of ASC are probably mediated by extracellular vesicles, such as exosomes, which influence the surrounding cells. Current development of exosome therapies requires efficient and noninvasive methods to localize, monitor, and track the exosomes. Among imaging methods used for this purpose, magnetic resonance imaging (MRI) has advantages: high spatial resolution, rapid in vivo acquisition, and radiation-free operation. To be detectable with MRI, exosomes must be labeled with MR contrast agents, such as ultra-small superparamagnetic iron oxide nanoparticles (USPIO). Here, we set up an innovative approach for exosome labeling that preserves their morphology and physiological characteristics. We show that by labeling ASC with USPIO before extraction of nanovesicles, the isolated exosomes retain nanoparticles and can be visualized by MRI. The current work aims at validating this novel USPIO-based exosome labeling method by monitoring the efficiency of the labeling with MRI both in ASC and in exosomes. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Parallel-multiplexed excitation light-sheet microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Xu, Dongli; Zhou, Weibin; Peng, Leilei

2017-02-01

Laser scanning light-sheet imaging allows fast 3D image of live samples with minimal bleach and photo-toxicity. Existing light-sheet techniques have very limited capability in multi-label imaging. Hyper-spectral imaging is needed to unmix commonly used fluorescent proteins with large spectral overlaps. However, the challenge is how to perform hyper-spectral imaging without sacrificing the image speed, so that dynamic and complex events can be captured live. We report wavelength-encoded structured illumination light sheet imaging (λ-SIM light-sheet), a novel light-sheet technique that is capable of parallel multiplexing in multiple excitation-emission spectral channels. λ-SIM light-sheet captures images of all possible excitation-emission channels in true parallel. It does not require compromising the imaging speed and is capable of distinguish labels by both excitation and emission spectral properties, which facilitates unmixing fluorescent labels with overlapping spectral peaks and will allow more labels being used together. We build a hyper-spectral light-sheet microscope that combined λ-SIM with an extended field of view through Bessel beam illumination. The system has a 250-micron-wide field of view and confocal level resolution. The microscope, equipped with multiple laser lines and an unlimited number of spectral channels, can potentially image up to 6 commonly used fluorescent proteins from blue to red. Results from in vivo imaging of live zebrafish embryos expressing various genetic markers and sensors will be shown. Hyper-spectral images from λ-SIM light-sheet will allow multiplexed and dynamic functional imaging in live tissue and animals.

Discriminative confidence estimation for probabilistic multi-atlas label fusion.

PubMed

Benkarim, Oualid M; Piella, Gemma; González Ballester, Miguel Angel; Sanroma, Gerard

2017-12-01

Quantitative neuroimaging analyses often rely on the accurate segmentation of anatomical brain structures. In contrast to manual segmentation, automatic methods offer reproducible outputs and provide scalability to study large databases. Among existing approaches, multi-atlas segmentation has recently shown to yield state-of-the-art performance in automatic segmentation of brain images. It consists in propagating the labelmaps from a set of atlases to the anatomy of a target image using image registration, and then fusing these multiple warped labelmaps into a consensus segmentation on the target image. Accurately estimating the contribution of each atlas labelmap to the final segmentation is a critical step for the success of multi-atlas segmentation. Common approaches to label fusion either rely on local patch similarity, probabilistic statistical frameworks or a combination of both. In this work, we propose a probabilistic label fusion framework based on atlas label confidences computed at each voxel of the structure of interest. Maximum likelihood atlas confidences are estimated using a supervised approach, explicitly modeling the relationship between local image appearances and segmentation errors produced by each of the atlases. We evaluate different spatial pooling strategies for modeling local segmentation errors. We also present a novel type of label-dependent appearance features based on atlas labelmaps that are used during confidence estimation to increase the accuracy of our label fusion. Our approach is evaluated on the segmentation of seven subcortical brain structures from the MICCAI 2013 SATA Challenge dataset and the hippocampi from the ADNI dataset. Overall, our results indicate that the proposed label fusion framework achieves superior performance to state-of-the-art approaches in the majority of the evaluated brain structures and shows more robustness to registration errors. Copyright © 2017 Elsevier B.V. All rights reserved.

Alzheimer's disease and the law: positive and negative consequences of structural stigma and labeling in the legal system.

PubMed

Werner, Perla; Doron, Israel Issi

2017-11-01

To explore the meaning and consequences of labeling on structural stigma in the context of Alzheimer's disease (AD) in the legal system. This qualitative study was made up of three focus groups including social workers and lawyers (n = 26). Participants were asked to report their experience in circumstances in which persons with AD and their family members engage with the legal system. Thematic analysis using the constant comparative method was used. The discussions in the focus groups raised two overall themes. (1) The significance of the medical diagnostic labeling of AD in the legal system and (2) the consequences of labeling of AD within the legal system. This last theme included four sub-themes: (a) negative consequences of labeling; (b) reasons associated with negative consequences of labeling; (c) positive consequences of labeling; and (d) reasons associated with positive consequences of labeling. Findings of the study provide a first foundation for future research on the meaning and consequences of labeling in legal cases involving persons with AD. They suggest that increasing judges' knowledge about AD and reforming the existing 'status-based' legal capacity legislation might benefit by limiting the legal weight given today to the medical diagnosis.

Labeling of Medication and Placebo Alters the Outcome of Episodic Migraine Attacks

PubMed Central

Kam-Hansen, Slavenka; Jakubowski, Moshe; Kelley, John M.; Kirsch, Irving; Hoaglin, David C.; Kaptchuk, Ted J.; Burstein, Rami

2014-01-01

Information provided to patients is thought to influence placebo and drug effects. We investigated the potential relationship between treatment labeling and its outcome in a prospective, within-subjects, repeated measures study of episodic migraine. A cohort of 66 participants documented 7 separate migraine attack: one untreated attack, followed by six attacks that were randomly assigned for either rizatriptan (10 mg Maxalt) or placebo treatments, each of which labeled once as ‘Maxalt’, once as ‘Placebo’, and once as ‘Maxalt or Placebo’ (459 documented attacks). Data were analyzed using generalized linear mixed model statistics. While Maxalt was generally superior to placebo, the placebo effect, and to a lesser extent Maxalt efficacy, increased monotonically with treatment labeling as follows: ‘Placebo’ label < ‘Maxalt or placebo’ label ≤ ‘Maxalt’ label. Efficacy of Maxalt mislabeled as placebo was not significantly different from the efficacy of placebo mislabeled as Maxalt. The placebo effect was significant under each labeling condition relative to no treatment, amounting in magnitude to >50% of Maxalt effect under the corresponding labeling condition. Thus, incremental “positive” information yielded incremental efficacy of placebo and medication during migraine attacks. PMID:24401940

Immersive virtual reality as a teaching tool for neuroanatomy.

PubMed

Stepan, Katelyn; Zeiger, Joshua; Hanchuk, Stephanie; Del Signore, Anthony; Shrivastava, Raj; Govindaraj, Satish; Iloreta, Alfred

2017-10-01

Three-dimensional (3D) computer modeling and interactive virtual reality (VR) simulation are validated teaching techniques used throughout medical disciplines. Little objective data exists supporting its use in teaching clinical anatomy. Learner motivation is thought to limit the rate of utilization of such novel technologies. The purpose of this study is to evaluate the effectiveness, satisfaction, and motivation associated with immersive VR simulation in teaching medical students neuroanatomy. Images of normal cerebral anatomy were reconstructed from human Digital Imaging and Communications in Medicine (DICOM) computed tomography (CT) imaging and magnetic resonance imaging (MRI) into 3D VR formats compatible with the Oculus Rift VR System, a head-mounted display with tracking capabilities allowing for an immersive VR experience. The ventricular system and cerebral vasculature were highlighted and labeled to create a focused interactive model. We conducted a randomized controlled study with 66 medical students (33 in both the control and experimental groups). Pertinent neuroanatomical structures were studied using either online textbooks or the VR interactive model, respectively. We then evaluated the students' anatomy knowledge, educational experience, and motivation (using the Instructional Materials Motivation Survey [IMMS], a previously validated assessment). There was no significant difference in anatomy knowledge between the 2 groups on preintervention, postintervention, or retention quizzes. The VR group found the learning experience to be significantly more engaging, enjoyable, and useful (all p < 0.01) and scored significantly higher on the motivation assessment (p < 0.01). Immersive VR educational tools awarded a more positive learner experience and enhanced student motivation. However, the technology was equally as effective as the traditional text books in teaching neuroanatomy. © 2017 ARS-AAOA, LLC.

77 FR 15298 - Rule Concerning Disclosures Regarding Energy Consumption and Water Use of Certain Home Appliances...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-15

... manufacturers make images of their labels available on a Web site for linking and downloading by both paper... rather than using the images provided by the manufacturers, as long as the labels conform to all the... the covered product and its price,'' rather than alongside every image of a covered product on the...

Photosynthetic Energy Transduction Publications | Bioenergy | NREL

Science.gov Websites

, Microbial Biotechnol. Image of two green spheres: one labeled Growth and the other labeled Catalysis. From Rhodobacter capsulatus, Int. J. Hydrogen Energy Image of two charts showing H2 sensitivity of the R NC74A, Planta Image of a diagrammatic view of current algal phylogeny illustrating common (e.g., Algae

Firefly Luciferin-Inspired Biocompatible Chemistry for Protein Labeling and In Vivo Imaging.

PubMed

Wang, Yuqi; An, Ruibing; Luo, Zhiliang; Ye, Deju

2018-04-17

Biocompatible reactions have emerged as versatile tools to build various molecular imaging probes that hold great promise for the detection of biological processes in vitro and/or in vivo. In this Minireview, we describe the recent advances in the development of a firefly luciferin-inspired biocompatible reaction between cyanobenzothiazole (CBT) and cysteine (Cys), and highlight its versatility to label proteins and build multimodality molecular imaging probes. The review starts from the general introduction of biocompatible reactions, which is followed by briefly describing the development of the firefly luciferin-inspired biocompatible chemistry. We then discuss its applications for the specific protein labeling and for the development of multimodality imaging probes (fluorescence, bioluminescence, MRI, PET, photoacoustic, etc.) that enable high sensitivity and spatial resolution imaging of redox environment, furin and caspase-3/7 activity in living cells and mice. Finally, we offer the conclusions and our perspective on the various and potential applications of this reaction. We hope that this review will contribute to the research of biocompatible reactions for their versatile applications in protein labeling and molecular imaging. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Superresolution intrinsic fluorescence imaging of chromatin utilizing native, unmodified nucleic acids for contrast

PubMed Central

Dong, Biqin; Almassalha, Luay M.; Stypula-Cyrus, Yolanda; Urban, Ben E.; Chandler, John E.; Nguyen, The-Quyen; Sun, Cheng; Zhang, Hao F.; Backman, Vadim

2016-01-01

Visualizing the nanoscale intracellular structures formed by nucleic acids, such as chromatin, in nonperturbed, structurally and dynamically complex cellular systems, will help expand our understanding of biological processes and open the next frontier for biological discovery. Traditional superresolution techniques to visualize subdiffractional macromolecular structures formed by nucleic acids require exogenous labels that may perturb cell function and change the very molecular processes they intend to study, especially at the extremely high label densities required for superresolution. However, despite tremendous interest and demonstrated need, label-free optical superresolution imaging of nucleotide topology under native nonperturbing conditions has never been possible. Here we investigate a photoswitching process of native nucleotides and present the demonstration of subdiffraction-resolution imaging of cellular structures using intrinsic contrast from unmodified DNA based on the principle of single-molecule photon localization microscopy (PLM). Using DNA-PLM, we achieved nanoscopic imaging of interphase nuclei and mitotic chromosomes, allowing a quantitative analysis of the DNA occupancy level and a subdiffractional analysis of the chromosomal organization. This study may pave a new way for label-free superresolution nanoscopic imaging of macromolecular structures with nucleotide topologies and could contribute to the development of new DNA-based contrast agents for superresolution imaging. PMID:27535934

Supervised local error estimation for nonlinear image registration using convolutional neural networks

NASA Astrophysics Data System (ADS)

Eppenhof, Koen A. J.; Pluim, Josien P. W.

2017-02-01

Error estimation in medical image registration is valuable when validating, comparing, or combining registration methods. To validate a nonlinear image registration method, ideally the registration error should be known for the entire image domain. We propose a supervised method for the estimation of a registration error map for nonlinear image registration. The method is based on a convolutional neural network that estimates the norm of the residual deformation from patches around each pixel in two registered images. This norm is interpreted as the registration error, and is defined for every pixel in the image domain. The network is trained using a set of artificially deformed images. Each training example is a pair of images: the original image, and a random deformation of that image. No manually labeled ground truth error is required. At test time, only the two registered images are required as input. We train and validate the network on registrations in a set of 2D digital subtraction angiography sequences, such that errors up to eight pixels can be estimated. We show that for this range of errors the convolutional network is able to learn the registration error in pairs of 2D registered images at subpixel precision. Finally, we present a proof of principle for the extension to 3D registration problems in chest CTs, showing that the method has the potential to estimate errors in 3D registration problems.

Self-assembled gold coating enhances X-ray imaging of alginate microcapsules

NASA Astrophysics Data System (ADS)

Qie, Fengxiang; Astolfo, Alberto; Wickramaratna, Malsha; Behe, Martin; Evans, Margaret D. M.; Hughes, Timothy C.; Hao, Xiaojuan; Tan, Tianwei

2015-01-01

Therapeutic biomolecules produced from cells encapsulated within alginate microcapsules (MCs) offer a potential treatment for a number of diseases. However the fate of such MCs once implanted into the body is difficult to establish. Labelling the MCs with medical imaging contrast agents may aid their detection and give researchers the ability to track them over time thus aiding the development of such cellular therapies. Here we report the preparation of MCs with a self-assembled gold nanoparticle (AuNPs) coating which results in distinctive contrast and enables them to be readily identified using a conventional small animal X-ray micro-CT scanner. Cationic Reversible Addition-Fragmentation chain Transfer (RAFT) homopolymer modified AuNPs (PAuNPs) were coated onto the surface of negatively charged alginate MCs resulting in hybrids which possessed low cytotoxicity and high mechanical stability in vitro. As a result of their high localized Au concentration, the hybrid MCs exhibited a distinctive bright circular ring even with a low X-ray dose and rapid scanning in post-mortem imaging experiments facilitating their positive identification and potentially enabling them to be used for in vivo tracking experiments over multiple time-points.Therapeutic biomolecules produced from cells encapsulated within alginate microcapsules (MCs) offer a potential treatment for a number of diseases. However the fate of such MCs once implanted into the body is difficult to establish. Labelling the MCs with medical imaging contrast agents may aid their detection and give researchers the ability to track them over time thus aiding the development of such cellular therapies. Here we report the preparation of MCs with a self-assembled gold nanoparticle (AuNPs) coating which results in distinctive contrast and enables them to be readily identified using a conventional small animal X-ray micro-CT scanner. Cationic Reversible Addition-Fragmentation chain Transfer (RAFT) homopolymer modified AuNPs (PAuNPs) were coated onto the surface of negatively charged alginate MCs resulting in hybrids which possessed low cytotoxicity and high mechanical stability in vitro. As a result of their high localized Au concentration, the hybrid MCs exhibited a distinctive bright circular ring even with a low X-ray dose and rapid scanning in post-mortem imaging experiments facilitating their positive identification and potentially enabling them to be used for in vivo tracking experiments over multiple time-points. Electronic supplementary information (ESI) available: Including NMR spectra and TGA chromatogram of polymers, SEM imaging, EDS analysis, UV-Visible spectra of MCs and CT images of unlabeled MCs. See DOI: 10.1039/c4nr06692h

21 CFR 201.310 - Phenindione; labeling of drug preparations intended for use by man.

Code of Federal Regulations, 2014 CFR

2014-04-01

... in the medical literature and data accumulated by the Food and Drug Administration indicate that... label and labeling on or within the package from which the drug is to be dispensed, and any other...

Small-molecule-based protein-labeling technology in live cell studies: probe-design concepts and applications.

PubMed

Mizukami, Shin; Hori, Yuichiro; Kikuchi, Kazuya

2014-01-21

The use of genetic engineering techniques allows researchers to combine functional proteins with fluorescent proteins (FPs) to produce fusion proteins that can be visualized in living cells, tissues, and animals. However, several limitations of FPs, such as slow maturation kinetics or issues with photostability under laser illumination, have led researchers to examine new technologies beyond FP-based imaging. Recently, new protein-labeling technologies using protein/peptide tags and tag-specific probes have attracted increasing attention. Although several protein-labeling systems are com mercially available, researchers continue to work on addressing some of the limitations of this technology. To reduce the level of background fluorescence from unlabeled probes, researchers have pursued fluorogenic labeling, in which the labeling probes do not fluoresce until the target proteins are labeled. In this Account, we review two different fluorogenic protein-labeling systems that we have recently developed. First we give a brief history of protein labeling technologies and describe the challenges involved in protein labeling. In the second section, we discuss a fluorogenic labeling system based on a noncatalytic mutant of β-lactamase, which forms specific covalent bonds with β-lactam antibiotics such as ampicillin or cephalosporin. Based on fluorescence (or Förster) resonance energy transfer and other physicochemical principles, we have developed several types of fluorogenic labeling probes. To extend the utility of this labeling system, we took advantage of a hydrophobic β-lactam prodrug structure to achieve intracellular protein labeling. We also describe a small protein tag, photoactive yellow protein (PYP)-tag, and its probes. By utilizing a quenching mechanism based on close intramolecular contact, we incorporated a turn-on switch into the probes for fluorogenic protein labeling. One of these probes allowed us to rapidly image a protein while avoiding washout. In the future, we expect that protein-labeling systems with finely designed probes will lead to novel methodologies that allow researchers to image biomolecules and to perturb protein functions.

Off-Label Prescribing, Polypharmacy, and Black-Box Warnings: A Primer for School Psychologists

ERIC Educational Resources Information Center

Shahidullah, Jeffrey D.

2012-01-01

Psychotropic medications are increasingly used to treat children and adolescents with mental health conditions. Between the years 1994 and 2001, there was a 191.7% increase in number of office visits resulting in a psychotropic medication prescription among children and adolescents. Many drugs are prescribed to children "off-label", whereby they…

Automated processing of label-free Raman microscope images of macrophage cells with standardized regression for high-throughput analysis.

PubMed

Milewski, Robert J; Kumagai, Yutaro; Fujita, Katsumasa; Standley, Daron M; Smith, Nicholas I

2010-11-19

Macrophages represent the front lines of our immune system; they recognize and engulf pathogens or foreign particles thus initiating the immune response. Imaging macrophages presents unique challenges, as most optical techniques require labeling or staining of the cellular compartments in order to resolve organelles, and such stains or labels have the potential to perturb the cell, particularly in cases where incomplete information exists regarding the precise cellular reaction under observation. Label-free imaging techniques such as Raman microscopy are thus valuable tools for studying the transformations that occur in immune cells upon activation, both on the molecular and organelle levels. Due to extremely low signal levels, however, Raman microscopy requires sophisticated image processing techniques for noise reduction and signal extraction. To date, efficient, automated algorithms for resolving sub-cellular features in noisy, multi-dimensional image sets have not been explored extensively. We show that hybrid z-score normalization and standard regression (Z-LSR) can highlight the spectral differences within the cell and provide image contrast dependent on spectral content. In contrast to typical Raman imaging processing methods using multivariate analysis, such as single value decomposition (SVD), our implementation of the Z-LSR method can operate nearly in real-time. In spite of its computational simplicity, Z-LSR can automatically remove background and bias in the signal, improve the resolution of spatially distributed spectral differences and enable sub-cellular features to be resolved in Raman microscopy images of mouse macrophage cells. Significantly, the Z-LSR processed images automatically exhibited subcellular architectures whereas SVD, in general, requires human assistance in selecting the components of interest. The computational efficiency of Z-LSR enables automated resolution of sub-cellular features in large Raman microscopy data sets without compromise in image quality or information loss in associated spectra. These results motivate further use of label free microscopy techniques in real-time imaging of live immune cells.

Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGD Peptide Probe

PubMed Central

Zhu, Lei; Guo, Ning; Li, Quanzheng; Ma, Ying; Jacboson, Orit; Lee, Seulki; Choi, Hak Soo; Mansfield, James R.; Niu, Gang; Chen, Xiaoyuan

2012-01-01

Purpose: The aim of this study is to determine if dynamic optical imaging could provide comparable kinetic parameters to that of dynamic PET imaging by a near-infrared dye/64Cu dual-labeled cyclic RGD peptide. Methods: The integrin αvβ3 binding RGD peptide was conjugated with a macrocyclic chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) for copper labeling and PET imaging and a near-infrared dye ZW-1 for optical imaging. The in vitro biological activity of RGD-C(DOTA)-ZW-1 was characterized by cell staining and receptor binding assay. Sixty-min dynamic PET and optical imaging were acquired on a MDA-MB-435 tumor model. Singular value decomposition (SVD) method was applied to compute the dynamic optical signal from the two-dimensional optical projection images. Compartment models were used to quantitatively analyze and compare the dynamic optical and PET data. Results: The dual-labeled probe 64Cu-RGD-C(DOTA)-ZW-1 showed integrin specific binding in vitro and in vivo. The binding potential (Bp) derived from dynamic optical imaging (1.762 ± 0.020) is comparable to that from dynamic PET (1.752 ± 0.026). Conclusion: The signal un-mixing process using SVD improved the accuracy of kinetic modeling of 2D dynamic optical data. Our results demonstrate that 2D dynamic optical imaging with SVD analysis could achieve comparable quantitative results as dynamic PET imaging in preclinical xenograft models. PMID:22916074

Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGD Peptide Probe.

PubMed

Zhu, Lei; Guo, Ning; Li, Quanzheng; Ma, Ying; Jacboson, Orit; Lee, Seulki; Choi, Hak Soo; Mansfield, James R; Niu, Gang; Chen, Xiaoyuan

2012-01-01

The aim of this study is to determine if dynamic optical imaging could provide comparable kinetic parameters to that of dynamic PET imaging by a near-infrared dye/(64)Cu dual-labeled cyclic RGD peptide. The integrin α(v)β(3) binding RGD peptide was conjugated with a macrocyclic chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) for copper labeling and PET imaging and a near-infrared dye ZW-1 for optical imaging. The in vitro biological activity of RGD-C(DOTA)-ZW-1 was characterized by cell staining and receptor binding assay. Sixty-min dynamic PET and optical imaging were acquired on a MDA-MB-435 tumor model. Singular value decomposition (SVD) method was applied to compute the dynamic optical signal from the two-dimensional optical projection images. Compartment models were used to quantitatively analyze and compare the dynamic optical and PET data. The dual-labeled probe (64)Cu-RGD-C(DOTA)-ZW-1 showed integrin specific binding in vitro and in vivo. The binding potential (Bp) derived from dynamic optical imaging (1.762 ± 0.020) is comparable to that from dynamic PET (1.752 ± 0.026). The signal un-mixing process using SVD improved the accuracy of kinetic modeling of 2D dynamic optical data. Our results demonstrate that 2D dynamic optical imaging with SVD analysis could achieve comparable quantitative results as dynamic PET imaging in preclinical xenograft models.

Ten Common Questions (and Their Answers) About Off-label Drug Use

PubMed Central

Wittich, Christopher M.; Burkle, Christopher M.; Lanier, William L.

2012-01-01

The term off-label drug use (OLDU) is used extensively in the medical literature, continuing medical education exercises, and the media. Yet, we propose that many health care professionals have an underappreciation of its definition, prevalence, and implications. This article introduces and answers 10 questions regarding OLDU in an effort to clarify the practice's meaning, breadth of application, acceptance, and liabilities. Off-label drug use involves prescribing medications for indications, or using a dosage or dosage form, that have not been approved by the US Food and Drug Administration. Since the Food and Drug Administration does not regulate the practice of medicine, OLDU has become common. It occurs in every specialty of medicine, but it may be more common in areas of medicine in which the patient population is less likely to be included in clinical trials (eg, pediatric, pregnant, or psychiatric patients). Pharmaceutical companies are not allowed to promote their medications for an off-label use, which has lead to several large settlements for illegal marketing. To limit liability, physicians should prescribe medications only for indications that they believe are in the best interest of the patient. In addition, health care professionals should educate themselves about OLDU to weigh the risks and benefits and provide the best possible care for their patients. PMID:22877654

SPIO-labeled Yttrium Microspheres for MR Imaging Quantification of Transcatheter Intrahepatic Delivery in a Rodent Model

PubMed Central

Li, Weiguo; Zhang, Zhuoli; Gordon, Andrew C.; Chen, Jeane; Nicolai, Jodi; Lewandowski, Robert J.; Omary, Reed A.

2016-01-01

Purpose To investigate the qualitative and quantitative impacts of labeling yttrium microspheres with increasing amounts of superparamagnetic iron oxide (SPIO) material for magnetic resonance (MR) imaging in phantom and rodent models. Materials and Methods Animal model studies were approved by the institutional Animal Care and Use Committee. The r2* relaxivity for each of four microsphere SPIO compositions was determined from 32 phantoms constructed with agarose gel and in eight concentrations from each of the four compositions. Intrahepatic transcatheter infusion procedures were performed in rats by using each of the four compositions before MR imaging to visualize distributions within the liver. For quantitative studies, doses of 5, 10, 15, or 20 mg 2% SPIO-labeled yttrium microspheres were infused into 24 rats (six rats per group). MR imaging R2* measurements were used to quantify the dose delivered to each liver. Pearson correlation, analysis of variance, and intraclass correlation analyses were performed to compare MR imaging measurements in phantoms and animal models. Results Increased r2* relaxivity was observed with incremental increases of SPIO microsphere content. R2* measurements of the 2% SPIO–labeled yttrium microsphere concentration were well correlated with known phantom concentrations (R2 = 1.00, P < .001) over a broader linear range than observed for the other three compositions. Microspheres were heterogeneously distributed within each liver; increasing microsphere SPIO content produced marked signal voids. R2*-based measurements of 2% SPIO–labeled yttrium microsphere delivery were well correlated with infused dose (intraclass correlation coefficient, 0.98; P < .001). Conclusion MR imaging R2* measurements of yttrium microspheres labeled with 2% SPIO can quantitatively depict in vivo intrahepatic biodistribution in a rat model. © RSNA, 2015 Online supplemental material is available for this article. PMID:26313619

Neuronal Tracing with Magnetic Labels: NMR Imaging Methods, Preliminary Results, and New Optimized Coils.

NASA Astrophysics Data System (ADS)

Ghosh, Pratik

1992-01-01

The investigations focussed on in vivo NMR imaging studies of magnetic particles with and within neural cells. NMR imaging methods, both Fourier transform and projection reconstruction, were implemented and new protocols were developed to perform "Neuronal Tracing with Magnetic Labels" on small animal brains. Having performed the preliminary experiments with neuronal tracing, new optimized coils and experimental set-up were devised. A novel gradient coil technology along with new rf-coils were implemented, and optimized for future use with small animals in them. A new magnetic labelling procedure was developed that allowed labelling of billions of cells with ultra -small magnetite particles in a short time. The relationships among the viability of such cells, the amount of label and the contrast in the images were studied as quantitatively as possible. Intracerebral grafting of magnetite labelled fetal rat brain cells made it possible for the first time to attempt monitoring in vivo the survival, differentiation, and possible migration of both host and grafted cells in the host rat brain. This constituted the early steps toward future experiments that may lead to the monitoring of human brain grafts of fetal brain cells. Preliminary experiments with direct injection of horse radish peroxidase-conjugated magnetite particles into neurons, followed by NMR imaging, revealed a possible non-invasive alternative, allowing serial study of the dynamic transport pattern of tracers in single living animals. New gradient coils were built by using parallel solid-conductor ribbon cables that could be wrapped easily and quickly. Rapid rise times provided by these coils allowed implementation of fast imaging methods. Optimized rf-coil circuit development made it possible to understand better the sample-coil properties and the associated trade -offs in cases of small but conducting samples.

In vivo label-free photoacoustic microscopy of the anterior segment of the mouse eye

NASA Astrophysics Data System (ADS)

Rao, Bin; Hu, Song; Li, Li; Maslov, Konstantin; Wang, Lihong V.

2010-02-01

Both iris fluorescein angiography (IFA) and indocyanine green angiography (ICGA) provide ophthalmologists imaging tools in studying the microvasculature structure and hemodynamics of the anterior segment of the eye in normal and diseased status. However, a non-invasive, endogenous imaging modality is preferable for the monitoring of hemodynamics of the iris microvasculature. We investigated the in vivo, label-free ocular anterior segment imaging with photo-acoustic microscopy (PAM) in mouse eyes. We demonstrated the unique advantage of endogenous contrast that is not available in both IFA and ICGA. The laser radiation was maintained within the ANSI laser safety limit. The in vivo, label-free nature of our imaging technology has the potential for ophthalmic applications.

The Protein Corona around Nanoparticles Facilitates Stem Cell Labeling for Clinical MR Imaging.

PubMed

Nejadnik, Hossein; Taghavi-Garmestani, Seyed-Meghdad; Madsen, Steven J; Li, Kai; Zanganeh, Saeid; Yang, Phillip; Mahmoudi, Morteza; Daldrup-Link, Heike E

2018-03-01

Purpose To evaluate if the formation of a protein corona around ferumoxytol nanoparticles can facilitate stem cell labeling for in vivo tracking with magnetic resonance (MR) imaging. Materials and Methods Ferumoxytol was incubated in media containing human serum (group 1), fetal bovine serum (group 2), StemPro medium (group 3), protamine (group 4), and protamine plus heparin (group 5). Formation of a protein corona was characterized by means of dynamic light scattering, ζ potential, and liquid chromatography-mass spectrometry. Iron uptake was evaluated with 3,3'-diaminobenzidine-Prussian blue staining, lysosomal staining, and inductively coupled plasma spectrometry. To evaluate the effect of a protein corona on stem cell labeling, human mesenchymal stem cells (hMSCs) were labeled with the above formulations, implanted into pig knee specimens, and investigated with T2-weighted fast spin-echo and multiecho spin-echo sequences on a 3.0-T MR imaging unit. Data in different groups were compared by using a Kruskal-Wallis test. Results Compared with bare nanoparticles, all experimental groups showed significantly increased negative ζ values (from -37 to less than -10; P = .008). Nanoparticles in groups 1-3 showed an increased size because of the formation of a protein corona. hMSCs labeled with group 1-5 media showed significantly shortened T2 relaxation times compared with unlabeled control cells (P = .0012). hMSCs labeled with group 3 and 5 media had the highest iron uptake after cells labeled with group 1 medium. After implantation into pig knees, hMSCs labeled with group 1 medium showed significantly shorter T2 relaxation times than hMSCs labeled with group 2-5 media (P = .0022). Conclusion The protein corona around ferumoxytol nanoparticles can facilitate stem cell labeling for clinical cell tracking with MR imaging. © RSNA, 2017 Online supplemental material is available for this article.

Potential Impact of ADHD with Stimulant Medication Label on Teacher Expectations

ERIC Educational Resources Information Center

Batzle, Christina S.; Weyandt, Lisa L.; Janusis, Grace M.; DeVietti, Terry L.

2010-01-01

Objective: The present study investigated how teachers rated children's Behavior, IQ, and Personality contingent on the presence or absence of an Attention Deficit Hyperactivity Disorder (ADHD) label. Method: Teachers from K-12 read a hypothetical description of either a male or female child with no label, an ADHD label, or an ADHD with stimulant…

Multimodal quantitative phase and fluorescence imaging of cell apoptosis

NASA Astrophysics Data System (ADS)

Fu, Xinye; Zuo, Chao; Yan, Hao

2017-06-01

Fluorescence microscopy, utilizing fluorescence labeling, has the capability to observe intercellular changes which transmitted and reflected light microscopy techniques cannot resolve. However, the parts without fluorescence labeling are not imaged. Hence, the processes simultaneously happen in these parts cannot be revealed. Meanwhile, fluorescence imaging is 2D imaging where information in the depth is missing. Therefore the information in labeling parts is also not complete. On the other hand, quantitative phase imaging is capable to image cells in 3D in real time through phase calculation. However, its resolution is limited by the optical diffraction and cannot observe intercellular changes below 200 nanometers. In this work, fluorescence imaging and quantitative phase imaging are combined to build a multimodal imaging system. Such system has the capability to simultaneously observe the detailed intercellular phenomenon and 3D cell morphology. In this study the proposed multimodal imaging system is used to observe the cell behavior in the cell apoptosis. The aim is to highlight the limitations of fluorescence microscopy and to point out the advantages of multimodal quantitative phase and fluorescence imaging. The proposed multimodal quantitative phase imaging could be further applied in cell related biomedical research, such as tumor.

Immunotargeting of Integrin α6β4 for Single-Photon Emission Computed Tomography and Near-Infrared Fluorescence Imaging in a Pancreatic Cancer Model

PubMed Central

Tsuji, Atsushi B.; Sudo, Hitomi; Sugyo, Aya; Furukawa, Takako; Ukai, Yoshinori; Kurosawa, Yoshikazu; Saga, Tsuneo

2016-01-01

To explore suitable imaging probes for early and specific detection of pancreatic cancer, we demonstrated that α6β4 integrin is a good target and employed single-photon emission computed tomography (SPECT) or near-infrared (NIR) imaging for immunotargeting. Expression levels of α6β4 were examined by Western blotting and flow cytometry in certain human pancreatic cancer cell lines. The human cell line BxPC-3 was used for α6β4-positive and a mouse cell line, A4, was used for negative counterpart. We labeled antibody against α6β4 with Indium-111 (111In) or indocyanine green (ICG). After injection of 111In-labeled probe to tumor-bearing mice, biodistribution, SPECT, autoradiography (ARG), and immunohistochemical (IHC) studies were conducted. After administration of ICG-labeled probe, in vivo and ex vivo NIR imaging and fluorescence microscopy of tumors were performed. BxPC-3 tumor showed a higher radioligand binding in SPECT and higher fluorescence intensity as well as a delay in the probe washout in NIR imaging when compared to A4 tumor. The biodistribution profile of 111In-labeled probe, ARG, and IHC confirmed the α6β4 specific binding of the probe. Here, we propose that α6β4 is a desirable target for the diagnosis of pancreatic cancer and that it could be detected by radionuclide imaging and NIR imaging using a radiolabeled or ICG-labeled α6β4 antibody. PMID:27030400

Time-resolved delayed luminescence image microscopy using an europium ion chelate complex.

PubMed Central

Marriott, G.; Heidecker, M.; Diamandis, E. P.; Yan-Marriott, Y.

1994-01-01

Improvements and extended applications of time-resolved delayed luminescence imaging microscopy (TR-DLIM) in cell biology are described. The emission properties of europium ion complexed to a fluorescent chelating group capable of labeling proteins are exploited to provide high contrast images of biotin labeled ligands through detection of the delayed emission. The streptavidin-based macromolecular complex (SBMC) employs streptavidin cross-linked to thyroglobulin multiply labeled with the europium-fluorescent chelate. The fluorescent chelate is efficiently excited with 340-nm light, after which it sensitizes europium ion emission at 612 nm hundreds of microseconds later. The SBMC complex has a high quantum yield orders of magnitude higher than that of eosin, a commonly used delayed luminescent probe, and can be readily seen by the naked eye, even in specimens double-labeled with prompt fluorescent probes. Unlike triplet-state phosphorescent probes, sensitized europium ion emission is insensitive to photobleaching and quenching by molecular oxygen; these properties have been exploited to obtain delayed luminescence images of living cells in aerated medium thus complementing imaging studies using prompt fluorescent probes. Since TR-DLIM has the unique property of rejecting enormous signals that originate from scattered light, autofluorescence, and prompt fluorescence it has been possible to resolve double emission images of living amoeba cells containing an intensely stained lucifer yellow in pinocytosed vesicles and membrane surface-bound SBMC-labeled biotinylated concanavalin A. Images of fixed cells represented in terms of the time decay of the sensitized emission show the lifetime of the europium ion emission is sensitive to the environment in which it is found. Through the coupling of SBMC to streptavidin,a plethora of biotin-based tracer molecules are available for immunocytochemical studies. Images FIGURE 1 FIGURE 2 FIGURE 3 FIGURE 4 FIGURE 5 FIGURE 6 FIGURE 7 PMID:7811952

Block-Based Connected-Component Labeling Algorithm Using Binary Decision Trees

PubMed Central

Chang, Wan-Yu; Chiu, Chung-Cheng; Yang, Jia-Horng

2015-01-01

In this paper, we propose a fast labeling algorithm based on block-based concepts. Because the number of memory access points directly affects the time consumption of the labeling algorithms, the aim of the proposed algorithm is to minimize neighborhood operations. Our algorithm utilizes a block-based view and correlates a raster scan to select the necessary pixels generated by a block-based scan mask. We analyze the advantages of a sequential raster scan for the block-based scan mask, and integrate the block-connected relationships using two different procedures with binary decision trees to reduce unnecessary memory access. This greatly simplifies the pixel locations of the block-based scan mask. Furthermore, our algorithm significantly reduces the number of leaf nodes and depth levels required in the binary decision tree. We analyze the labeling performance of the proposed algorithm alongside that of other labeling algorithms using high-resolution images and foreground images. The experimental results from synthetic and real image datasets demonstrate that the proposed algorithm is faster than other methods. PMID:26393597

Rational design of a monomeric and photostable far-red fluorescent protein for fluorescence imaging in vivo.

PubMed

Yu, Dan; Dong, Zhiqiang; Gustafson, William Clay; Ruiz-González, Rubén; Signor, Luca; Marzocca, Fanny; Borel, Franck; Klassen, Matthew P; Makhijani, Kalpana; Royant, Antoine; Jan, Yuh-Nung; Weiss, William A; Guo, Su; Shu, Xiaokun

2016-02-01

Fluorescent proteins (FPs) are powerful tools for cell and molecular biology. Here based on structural analysis, a blue-shifted mutant of a recently engineered monomeric infrared fluorescent protein (mIFP) has been rationally designed. This variant, named iBlueberry, bears a single mutation that shifts both excitation and emission spectra by approximately 40 nm. Furthermore, iBlueberry is four times more photostable than mIFP, rendering it more advantageous for imaging protein dynamics. By tagging iBlueberry to centrin, it has been demonstrated that the fusion protein labels the centrosome in the developing zebrafish embryo. Together with GFP-labeled nucleus and tdTomato-labeled plasma membrane, time-lapse imaging to visualize the dynamics of centrosomes in radial glia neural progenitors in the intact zebrafish brain has been demonstrated. It is further shown that iBlueberry can be used together with mIFP in two-color protein labeling in living cells and in two-color tumor labeling in mice. © 2015 The Protein Society.

Tc-99m Labeled carrier for imaging

DOEpatents

Henze, Eberhard

1984-01-01

Novel radionuclide imaging agents, having particular application for lymphangiography are provided by non-covalently binding Tc-99m to a pharmaceutically acceptable cross-linked polysaccharide. Upon injection of the Tc-99m labeled polysaccharide into the blood stream, optimum contrast can be obtained within one hour.

The Effective Use of Labels in Strategic Communication

DTIC Science & Technology

2015-06-12

Images and symbols can achieve huge impact in communicating narratives, themes, and messages” (Farwell 2012, 79). These images and the associated......Effective Use of Labels in Strategic Communication 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) MAJ

89Zr-Oxine Complex for In Vivo PET Imaging of Labelled Cells and Associated Methods | NCI Technology Transfer Center | TTC

Cancer.gov

The National Cancer Institute seek parties interested in in-licensing and/or collaborative research to develop and commercialize cell labeling, cell tracking, cell trafficking, cell-based therapy, and PET imaging for cancer.

Dynamic nano-imaging of label-free living cells using electron beam excitation-assisted optical microscope

PubMed Central

Fukuta, Masahiro; Kanamori, Satoshi; Furukawa, Taichi; Nawa, Yasunori; Inami, Wataru; Lin, Sheng; Kawata, Yoshimasa; Terakawa, Susumu

2015-01-01

Optical microscopes are effective tools for cellular function analysis because biological cells can be observed non-destructively and non-invasively in the living state in either water or atmosphere condition. Label-free optical imaging technique such as phase-contrast microscopy has been analysed many cellular functions, and it is essential technology for bioscience field. However, the diffraction limit of light makes it is difficult to image nano-structures in a label-free living cell, for example the endoplasmic reticulum, the Golgi body and the localization of proteins. Here we demonstrate the dynamic imaging of a label-free cell with high spatial resolution by using an electron beam excitation-assisted optical (EXA) microscope. We observed the dynamic movement of the nucleus and nano-scale granules in living cells with better than 100 nm spatial resolution and a signal-to-noise ratio (SNR) around 10. Our results contribute to the development of cellular function analysis and open up new bioscience applications. PMID:26525841

Dynamic nano-imaging of label-free living cells using electron beam excitation-assisted optical microscope.

PubMed

Fukuta, Masahiro; Kanamori, Satoshi; Furukawa, Taichi; Nawa, Yasunori; Inami, Wataru; Lin, Sheng; Kawata, Yoshimasa; Terakawa, Susumu

2015-11-03

Optical microscopes are effective tools for cellular function analysis because biological cells can be observed non-destructively and non-invasively in the living state in either water or atmosphere condition. Label-free optical imaging technique such as phase-contrast microscopy has been analysed many cellular functions, and it is essential technology for bioscience field. However, the diffraction limit of light makes it is difficult to image nano-structures in a label-free living cell, for example the endoplasmic reticulum, the Golgi body and the localization of proteins. Here we demonstrate the dynamic imaging of a label-free cell with high spatial resolution by using an electron beam excitation-assisted optical (EXA) microscope. We observed the dynamic movement of the nucleus and nano-scale granules in living cells with better than 100 nm spatial resolution and a signal-to-noise ratio (SNR) around 10. Our results contribute to the development of cellular function analysis and open up new bioscience applications.

Clinical imaging in regenerative medicine

PubMed Central

Naumova, Anna V; Modo, Michel; Moore, Anna; Murry, Charles E; Frank, Joseph A

2014-01-01

In regenerative medicine, clinical imaging is indispensable for characterizing damaged tissue and for measuring the safety and efficacy of therapy. However, the ability to track the fate and function of transplanted cells with current technologies is limited. Exogenous contrast labels such as nanoparticles give a strong signal in the short term but are unreliable long term. Genetically encoded labels are good both short- and long-term in animals, but in the human setting they raise regulatory issues related to the safety of genomic integration and potential immunogenicity of reporter proteins. Imaging studies in brain, heart and islets share a common set of challenges, including developing novel labeling approaches to improve detection thresholds and early delineation of toxicity and function. Key areas for future research include addressing safety concerns associated with genetic labels and developing methods to follow cell survival, differentiation and integration with host tissue. Imaging may bridge the gap between cell therapies and health outcomes by elucidating mechanisms of action through longitudinal monitoring. PMID:25093889

Dynamic nano-imaging of label-free living cells using electron beam excitation-assisted optical microscope

NASA Astrophysics Data System (ADS)

Fukuta, Masahiro; Kanamori, Satoshi; Furukawa, Taichi; Nawa, Yasunori; Inami, Wataru; Lin, Sheng; Kawata, Yoshimasa; Terakawa, Susumu

2015-11-01

Optical microscopes are effective tools for cellular function analysis because biological cells can be observed non-destructively and non-invasively in the living state in either water or atmosphere condition. Label-free optical imaging technique such as phase-contrast microscopy has been analysed many cellular functions, and it is essential technology for bioscience field. However, the diffraction limit of light makes it is difficult to image nano-structures in a label-free living cell, for example the endoplasmic reticulum, the Golgi body and the localization of proteins. Here we demonstrate the dynamic imaging of a label-free cell with high spatial resolution by using an electron beam excitation-assisted optical (EXA) microscope. We observed the dynamic movement of the nucleus and nano-scale granules in living cells with better than 100 nm spatial resolution and a signal-to-noise ratio (SNR) around 10. Our results contribute to the development of cellular function analysis and open up new bioscience applications.

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

PubMed

Nanthagopal, A Padma; Rajamony, R Sukanesh

2012-07-01

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

Direct fluorescent-dye labeling of α-tubulin in mammalian cells for live cell and superresolution imaging.

PubMed

Schvartz, Tomer; Aloush, Noa; Goliand, Inna; Segal, Inbar; Nachmias, Dikla; Arbely, Eyal; Elia, Natalie

2017-10-15

Genetic code expansion and bioorthogonal labeling provide for the first time a way for direct, site-specific labeling of proteins with fluorescent-dyes in live cells. Although the small size and superb photophysical parameters of fluorescent-dyes offer unique advantages for high-resolution microscopy, this approach has yet to be embraced as a tool in live cell imaging. Here we evaluated the feasibility of this approach by applying it for α-tubulin labeling. After a series of calibrations, we site-specifically labeled α-tubulin with silicon rhodamine (SiR) in live mammalian cells in an efficient and robust manner. SiR-labeled tubulin successfully incorporated into endogenous microtubules at high density, enabling video recording of microtubule dynamics in interphase and mitotic cells. Applying this labeling approach to structured illumination microscopy resulted in an increase in resolution, highlighting the advantages in using a smaller, brighter tag. Therefore, using our optimized assay, genetic code expansion provides an attractive tool for labeling proteins with a minimal, bright tag in quantitative high-resolution imaging. © 2017 Schvartz et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Experience with the use of the Codonics Safe Label System(™) to improve labelling compliance of anaesthesia drugs.

PubMed

Ang, S B L; Hing, W C; Tung, S Y; Park, T

2014-07-01

The Codonics Safe Labeling System(™) (http://www.codonics.com/Products/SLS/flash/) is a piece of equipment that is able to barcode scan medications, read aloud the medication and the concentration and print a label of the appropriate concentration in the appropriate colour code. We decided to test this system in our facility to identify risks, benefits and usability. Our project comprised a baseline survey (25 anaesthesia cases during which 212 syringes were prepared from 223 drugs), an observational study (47 cases with 330 syringes prepared) and a user acceptability survey. The baseline compliance with all labelling requirements was 58%. In the observational study the compliance using the Codonics system was 98.6% versus 63.8% with conventional labelling. In the user acceptability survey the majority agreed the Codonics machine was easy to use, more legible and adhered with better security than the conventional preprinted label. However, most were neutral when asked about the likelihood of flexibility and customisation and were dissatisfied with the increased workload. Our findings suggest that the Codonics labelling machine is user-friendly and it improved syringe labelling compliance in our study. However, staff need to be willing to follow proper labelling workflow rather than batch label during preparation. Future syringe labelling equipment developers need to concentrate on user interface issues to reduce human factor and workflow problems. Support logistics are also an important consideration prior to implementation of any new labelling system.

Fully convolutional networks with double-label for esophageal cancer image segmentation by self-transfer learning

NASA Astrophysics Data System (ADS)

Xue, Di-Xiu; Zhang, Rong; Zhao, Yuan-Yuan; Xu, Jian-Ming; Wang, Ya-Lei

2017-07-01

Cancer recognition is the prerequisite to determine appropriate treatment. This paper focuses on the semantic segmentation task of microvascular morphological types on narrowband images to aid clinical examination of esophageal cancer. The most challenge for semantic segmentation is incomplete-labeling. Our key insight is to build fully convolutional networks (FCNs) with double-label to make pixel-wise predictions. The roi-label indicating ROIs (region of interest) is introduced as extra constraint to guild feature learning. Trained end-to-end, the FCN model with two target jointly optimizes both segmentation of sem-label (semantic label) and segmentation of roi-label within the framework of self-transfer learning based on multi-task learning theory. The learning representation ability of shared convolutional networks for sem-label is improved with support of roi-label via achieving a better understanding of information outside the ROIs. Our best FCN model gives satisfactory segmentation result with mean IU up to 77.8% (pixel accuracy > 90%). The results show that the proposed approach is able to assist clinical diagnosis to a certain extent.

The use of radiocobalt as a label improves imaging of EGFR using DOTA-conjugated Affibody molecule.

PubMed

Garousi, Javad; Andersson, Ken G; Dam, Johan H; Olsen, Birgitte B; Mitran, Bogdan; Orlova, Anna; Buijs, Jos; Ståhl, Stefan; Löfblom, John; Thisgaard, Helge; Tolmachev, Vladimir

2017-07-20

Several anti-cancer therapies target the epidermal growth factor receptor (EGFR). Radionuclide imaging of EGFR expression in tumours may aid in selection of optimal cancer therapy. The 111 In-labelled DOTA-conjugated Z EGFR:2377 Affibody molecule was successfully used for imaging of EGFR-expressing xenografts in mice. An optimal combination of radionuclide, chelator and targeting protein may further improve the contrast of radionuclide imaging. The aim of this study was to evaluate the targeting properties of radiocobalt-labelled DOTA-Z EGFR:2377 . DOTA-Z EGFR:2377 was labelled with 57 Co (T 1/2  = 271.8 d), 55 Co (T 1/2  = 17.5 h), and, for comparison, with the positron-emitting radionuclide 68 Ga (T 1/2  = 67.6 min) with preserved specificity of binding to EGFR-expressing A431 cells. The long-lived cobalt radioisotope 57 Co was used in animal studies. Both 57 Co-DOTA-Z EGFR:2377 and 68 Ga-DOTA-Z EGFR:2377 demonstrated EGFR-specific accumulation in A431 xenografts and EGFR-expressing tissues in mice. Tumour-to-organ ratios for the radiocobalt-labelled DOTA-Z EGFR:2377 were significantly higher than for the gallium-labelled counterpart already at 3 h after injection. Importantly, 57 Co-DOTA-Z EGFR:2377 demonstrated a tumour-to-liver ratio of 3, which is 7-fold higher than the tumour-to-liver ratio for 68 Ga-DOTA-Z EGFR:2377 . The results of this study suggest that the positron-emitting cobalt isotope 55 Co would be an optimal label for DOTA-Z EGFR:2377 and further development should concentrate on this radionuclide as a label.

18F-Labeling of Sensitive Biomolecules for Positron Emission Tomography

PubMed Central

Krishnan, Hema S.; Ma, Longle; Vasdev, Neil; Liang, Steven H.

2017-01-01

Positron emission tomography (PET) imaging study of fluorine-18 labeled biomolecules is an emerging and rapidly growing area for preclinical and clinical research. The present review focuses on recent advances in radiochemical methods for incorporating fluorine-18 into biomolecules via ‘direct’ or ‘indirect’ bioconjugation. Recently developed prosthetic groups and pre-targeting strategies, as well as representative examples in 18F-labeling of biomolecules in PET imaging research studies are highlighted. PMID:28704575

PET-radioimmunodetection of integrins: imaging acute colitis using a ⁶⁴Cu-labeled anti-β₇ integrin antibody.

PubMed

Dearling, Jason L J; Packard, Alan B

2012-01-01

Integrins are involved in a wide range of cell interactions. Imaging their distribution using high-resolution noninvasive techniques that are directly translatable to the clinic can provide new insights into disease processes and presents the opportunity to directly monitor new therapies. In this chapter, we describe a protocol to image, the in vivo distribution of the integrin β(7), expressed by lymphocytes recruited to and retained by the inflamed gut, using a radiolabeled whole antibody. The antibody is purified, conjugated with a bifunctional chelator for labeling with a radiometal, labeled with the positron-emitting radionuclide (64)Cu, and injected into mice for microPET studies. Mice with DSS-induced colitis were found to have higher uptake of the (64)Cu-labeled antibody in the gut than control groups.

Cellular internalization of LiNbO3 nanocrystals for second harmonic imaging and the effects on stem cell differentiation

NASA Astrophysics Data System (ADS)

Li, Jianhua; Qiu, Jichuan; Guo, Weibo; Wang, Shu; Ma, Baojin; Mou, Xiaoning; Tanes, Michael; Jiang, Huaidong; Liu, Hong

2016-03-01

Second harmonic generation (SHG) nanocrystals have recently been reported to label cancer cells and other functional cell lines due to their unique double-frequency property. In this paper, we report for the first time the use of lithium niobate (LiNbO3, LN) nanocrystals as SHG labels for imaging stem cells. Rat mesenchymal stem cells (rMSCs) were labeled with LN nanocrystals in order to study the cellular internalization of the nanocrystals and the influence on stem cell differentiation. The results showed that LN nanocrystals were endocytosed by the rMSCs and the distribution of the internalized nanoparticles demonstrated a high consistency with the orientation of the actin filaments. Besides, LN-labeled rMSCs showed a concentration-dependent viability. Most importantly, rMSCs labeled with 50 μg per mL of LN nanocrystals retained their ability to differentiate into both osteogenic and adipogenic lineages. The results prove that LN nanocrystals can be used as a cytocompatible, near-infrared (NIR) light driven cell label for long-term imaging, without hindering stem cell differentiation. This work will promote the use of LN nanocrystals to broader applications like deep-tissue tracking, remote drug delivery and stem cell therapy.Second harmonic generation (SHG) nanocrystals have recently been reported to label cancer cells and other functional cell lines due to their unique double-frequency property. In this paper, we report for the first time the use of lithium niobate (LiNbO3, LN) nanocrystals as SHG labels for imaging stem cells. Rat mesenchymal stem cells (rMSCs) were labeled with LN nanocrystals in order to study the cellular internalization of the nanocrystals and the influence on stem cell differentiation. The results showed that LN nanocrystals were endocytosed by the rMSCs and the distribution of the internalized nanoparticles demonstrated a high consistency with the orientation of the actin filaments. Besides, LN-labeled rMSCs showed a concentration-dependent viability. Most importantly, rMSCs labeled with 50 μg per mL of LN nanocrystals retained their ability to differentiate into both osteogenic and adipogenic lineages. The results prove that LN nanocrystals can be used as a cytocompatible, near-infrared (NIR) light driven cell label for long-term imaging, without hindering stem cell differentiation. This work will promote the use of LN nanocrystals to broader applications like deep-tissue tracking, remote drug delivery and stem cell therapy. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr00785f

Licensing and labelling of drugs in a paediatric oncology ward

PubMed Central

van den Berg, Henk; Tak, Nanda

2011-01-01

AIM Paediatric drug prescriptions are known for their high percentages of off-label and unlicensed use. In paediatric oncology data available are scarce. The aim of this paper is an analysis of the licensing and labelling status of all prescribed medication over a 2 week period in a Dutch paediatric oncology centre. METHODS An analysis of the delivery of medication by the hospital pharmacy to patients admitted to the paediatric oncology centre was carried out. RESULTS In total 268 precriptions were filed for 39 patients. In 87% of children unlicensed medication was used. Fifty-nine per cent of the children received at least two unlicensed drugs. In total 72% of the drugs were used licensed and on-label was found in 57% of the prescriptions. There was a trend that in younger children percentages were lower. International and local guidelines necessitated in many cases unlicensed use, e.g. intrathecal prednisolone, low dose medication such as heparin, ethanol and vancomycin for locking intravenous devices and higher intravenous vancomycin dosages. There were no major differences with respect to type of malignancy. CONCLUSION Our figures are substantially higher than the figures reported from adult oncology. Comparison with other paediatric reports are cumbersome, due to different percentages of diseases in the reports and other rules to dispense medication in the outpatient setting. Our data are in line with reports mentioning the higher percentages of unlicensed and off-label use. Our data further underpin the need for more research on suitable formulations, dosages, safety and efficacy in these children. PMID:21453298

Licensing and labelling of drugs in a paediatric oncology ward.

PubMed

van den Berg, Henk; Tak, Nanda

2011-09-01

Paediatric drug prescriptions are known for their high percentages of off-label and unlicensed use. In paediatric oncology data available are scarce. The aim of this paper is an analysis of the licensing and labelling status of all prescribed medication over a 2 week period in a Dutch paediatric oncology centre. An analysis of the delivery of medication by the hospital pharmacy to patients admitted to the paediatric oncology centre was carried out. In total 268 precriptions were filed for 39 patients. In 87% of children unlicensed medication was used. Fifty-nine per cent of the children received at least two unlicensed drugs. In total 72% of the drugs were used licensed and on-label was found in 57% of the prescriptions. There was a trend that in younger children percentages were lower. International and local guidelines necessitated in many cases unlicensed use, e.g. intrathecal prednisolone, low dose medication such as heparin, ethanol and vancomycin for locking intravenous devices and higher intravenous vancomycin dosages. There were no major differences with respect to type of malignancy. Our figures are substantially higher than the figures reported from adult oncology. Comparison with other paediatric reports are cumbersome, due to different percentages of diseases in the reports and other rules to dispense medication in the outpatient setting. Our data are in line with reports mentioning the higher percentages of unlicensed and off-label use. Our data further underpin the need for more research on suitable formulations, dosages, safety and efficacy in these children. © 2011 The Authors. British Journal of Clinical Pharmacology © 2011 The British Pharmacological Society.

Factors Affecting the Perceived Effectiveness of Pictorial Health Warnings on Cigarette Packages in Gulf Countries: A Cross-sectional Study.

PubMed

Mansour, Ameerah Y; Bakhsh, Zuhair

2017-01-01

To explore the perceived effectiveness of pictorial health warning (PHW) labels required by the Gulf Cooperation Council, to compare them with the Food and Drug Administration-approved PHW labels, and to determine factors affecting their perceived effectiveness. A cross-sectional study using a convenience sample of adult smokers and nonsmokers was conducted. The data were collected through a self-administered online questionnaire. The perceived effectiveness scores of PHW labels were calculated and compared among different subgroups using the Kruskal-Wallis test and the Dunn multiple comparison test at a .05 significance level. Of the 90 people invited to participate in the survey, 77 (86%) completed it, with 39 (50%) nonsmokers, 22 (29%) smokers, and 16 (21%) former smokers. Overall, labels having graphic images of illness or pathology are perceived to be most effective. Smokers generally perceived labels significantly less effective compared with former smokers and nonsmokers. Also, 55 respondents (71%) suggested that the presence of a telephone quit-line would be effective. Smoking status and image type had the most effect on the perceived effectiveness of the PHW labels on cigarette packs. Pictorial health warning labels with graphic images of pathology and a telephone quit-line are perceived to be most effective.

Nearest neighbor 3D segmentation with context features

NASA Astrophysics Data System (ADS)

Hristova, Evelin; Schulz, Heinrich; Brosch, Tom; Heinrich, Mattias P.; Nickisch, Hannes

2018-03-01

Automated and fast multi-label segmentation of medical images is challenging and clinically important. This paper builds upon a supervised machine learning framework that uses training data sets with dense organ annotations and vantage point trees to classify voxels in unseen images based on similarity of binary feature vectors extracted from the data. Without explicit model knowledge, the algorithm is applicable to different modalities and organs, and achieves high accuracy. The method is successfully tested on 70 abdominal CT and 42 pelvic MR images. With respect to ground truth, an average Dice overlap score of 0.76 for the CT segmentation of liver, spleen and kidneys is achieved. The mean score for the MR delineation of bladder, bones, prostate and rectum is 0.65. Additionally, we benchmark several variations of the main components of the method and reduce the computation time by up to 47% without significant loss of accuracy. The segmentation results are - for a nearest neighbor method - surprisingly accurate, robust as well as data and time efficient.

Resource Planning Model | Energy Analysis | NREL

Science.gov Websites

balancing authority. An image of a overlapping circles labelled Resource, Technical, Economic, and Market competing electricity technologies. An image of a overlapping circles labelled Resource, Technical, Economic ; Federal Resource Planning. Volume 1: Sectoral, Technical, and Economic Trends, NREL Technical Report (2016

Adverse Event extraction from Structured Product Labels using the Event-based Text-mining of Health Electronic Records (ETHER)system.

PubMed

Pandey, Abhishek; Kreimeyer, Kory; Foster, Matthew; Botsis, Taxiarchis; Dang, Oanh; Ly, Thomas; Wang, Wei; Forshee, Richard

2018-01-01

Structured Product Labels follow an XML-based document markup standard approved by the Health Level Seven organization and adopted by the US Food and Drug Administration as a mechanism for exchanging medical products information. Their current organization makes their secondary use rather challenging. We used the Side Effect Resource database and DailyMed to generate a comparison dataset of 1159 Structured Product Labels. We processed the Adverse Reaction section of these Structured Product Labels with the Event-based Text-mining of Health Electronic Records system and evaluated its ability to extract and encode Adverse Event terms to Medical Dictionary for Regulatory Activities Preferred Terms. A small sample of 100 labels was then selected for further analysis. Of the 100 labels, Event-based Text-mining of Health Electronic Records achieved a precision and recall of 81 percent and 92 percent, respectively. This study demonstrated Event-based Text-mining of Health Electronic Record's ability to extract and encode Adverse Event terms from Structured Product Labels which may potentially support multiple pharmacoepidemiological tasks.

21 CFR 801.30 - General exceptions from the requirement for the label of a device to bear a unique device...

Code of Federal Regulations, 2014 CFR

2014-04-01

... structure or any function of the body of man. (8) A device intended for export from the United States. (9) A... ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES LABELING Labeling...

76 FR 39041 - Infectious Diseases

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-05

... controls, and personal protective equipment); medical surveillance; worker training; signage and labeling.... Whether and to what extent an OSHA standard should contain signage, labeling, and worker training...

Semiconductor Quantum Dots for Bioimaging and Biodiagnostic Applications

NASA Astrophysics Data System (ADS)

Kairdolf, Brad A.; Smith, Andrew M.; Stokes, Todd H.; Wang, May D.; Young, Andrew N.; Nie, Shuming

2013-06-01

Semiconductor quantum dots (QDs) are light-emitting particles on the nanometer scale that have emerged as a new class of fluorescent labels for chemical analysis, molecular imaging, and biomedical diagnostics. Compared with traditional fluorescent probes, QDs have unique optical and electronic properties such as size-tunable light emission, narrow and symmetric emission spectra, and broad absorption spectra that enable the simultaneous excitation of multiple fluorescence colors. QDs are also considerably brighter and more resistant to photobleaching than are organic dyes and fluorescent proteins. These properties are well suited for dynamic imaging at the single-molecule level and for multiplexed biomedical diagnostics at ultrahigh sensitivity. Here, we discuss the fundamental properties of QDs; the development of next-generation QDs; and their applications in bioanalytical chemistry, dynamic cellular imaging, and medical diagnostics. For in vivo and clinical imaging, the potential toxicity of QDs remains a major concern. However, the toxic nature of cadmium-containing QDs is no longer a factor for in vitro diagnostics, so the use of multicolor QDs for molecular diagnostics and pathology is probably the most important and clinically relevant application for semiconductor QDs in the immediate future.

Semiconductor quantum dots for bioimaging and biodiagnostic applications.

PubMed

Kairdolf, Brad A; Smith, Andrew M; Stokes, Todd H; Wang, May D; Young, Andrew N; Nie, Shuming

2013-01-01

Semiconductor quantum dots (QDs) are light-emitting particles on the nanometer scale that have emerged as a new class of fluorescent labels for chemical analysis, molecular imaging, and biomedical diagnostics. Compared with traditional fluorescent probes, QDs have unique optical and electronic properties such as size-tunable light emission, narrow and symmetric emission spectra, and broad absorption spectra that enable the simultaneous excitation of multiple fluorescence colors. QDs are also considerably brighter and more resistant to photobleaching than are organic dyes and fluorescent proteins. These properties are well suited for dynamic imaging at the single-molecule level and for multiplexed biomedical diagnostics at ultrahigh sensitivity. Here, we discuss the fundamental properties of QDs; the development of next-generation QDs; and their applications in bioanalytical chemistry, dynamic cellular imaging, and medical diagnostics. For in vivo and clinical imaging, the potential toxicity of QDs remains a major concern. However, the toxic nature of cadmium-containing QDs is no longer a factor for in vitro diagnostics, so the use of multicolor QDs for molecular diagnostics and pathology is probably the most important and clinically relevant application for semiconductor QDs in the immediate future.

Semiconductor Quantum Dots for Bioimaging and Biodiagnostic Applications

PubMed Central

Kairdolf, Brad A.; Smith, Andrew M.; Stokes, Todd H.; Wang, May D.; Young, Andrew N.; Nie, Shuming

2013-01-01

Semiconductor quantum dots (QDs) are light-emitting particles on the nanometer scale that have emerged as a new class of fluorescent labels for chemical analysis, molecular imaging, and biomedical diagnostics. Compared with traditional fluorescent probes, QDs have unique optical and electronic properties such as size-tunable light emission, narrow and symmetric emission spectra, and broad absorption spectra that enable the simultaneous excitation of multiple fluorescence colors. QDs are also considerably brighter and more resistant to photobleaching than are organic dyes and fluorescent proteins. These properties are well suited for dynamic imaging at the single-molecule level and for multiplexed biomedical diagnostics at ultrahigh sensitivity. Here, we discuss the fundamental properties of QDs; the development of next-generation QDs; and their applications in bioanalytical chemistry, dynamic cellular imaging, and medical diagnostics. For in vivo and clinical imaging, the potential toxicity of QDs remains a major concern. However, the toxic nature of cadmium-containing QDs is no longer a factor for in vitro diagnostics, so the use of multicolor QDs for molecular diagnostics and pathology is probably the most important and clinically relevant application for semiconductor QDs in the immediate future. PMID:23527547

Third-harmonic generation susceptibility spectroscopy in free fatty acids

NASA Astrophysics Data System (ADS)

Chen, Yu-Cheng; Hsu, Hsun-Chia; Lee, Chien-Ming; Sun, Chi-Kuang

2015-09-01

Lipid-correlated disease such as atherosclerosis has been an important medical research topic for decades. Many new microscopic imaging techniques such as coherent anti-Stokes Raman scattering and third-harmonic generation (THG) microscopy were verified to have the capability to target lipids in vivo. In the case of THG microscopy, biological cell membranes and lipid bodies in cells and tissues have been shown as good sources of contrast with a laser excitation wavelength around 1200 nm. We report the THG excitation spectroscopy study of two pure free fatty acids including oleic acid and linoleic acid from 1090 to 1330 nm. Different pure fatty acids presented slightly-different THG χ(3) spectra. The measured peak values of THG third-order susceptibility χ(3) in both fatty acids were surprisingly found not to match completely with the resonant absorption wavelengths around 1190 to 1210 nm, suggesting possible wavelengths selection for enhanced THG imaging of lipids while avoiding laser light absorption. Along with the recent advancement in THG imaging, this new window between 1240 to 1290 nm may offer tremendous new opportunities for sensitive label-free lipid imaging in biological tissues.

FDA preemption of drug and device labeling: who should decide what goes on a drug label?

PubMed

Valoir, Tamsen; Ghosh, Shubha

2011-01-01

The Supreme Court decided an issue that is critical to consumer health and safety last year. In April 2009, the Supreme Court held that extensive FDA regulation of drugs did not preempt a state law claim that an additional warning on the label was necessary to make the drug reasonably safe for use. Thus, states--and even courts and juries--are now free to cast their vote on what a drug label should say. This is in direct contrast to medical devices, where the federal statute regulating medical devices expressly provides that state regulations are preempted. This Article discusses basic preemption principles and drugs, and explores the policy ramifications of pro- and anti-preemption policy in the healthcare industry.

Differentiating intratumoral melanocytes from Langerhans cells in nonmelanocytic pigmented skin tumors in vivo by label-free third-harmonic generation microscopy

NASA Astrophysics Data System (ADS)

Weng, Wei-Hung; Liao, Yi-Hua; Tsai, Ming-Rung; Wei, Ming-Liang; Huang, Hsin-Yi; Sun, Chi-Kuang

2016-07-01

Morphology and distribution of melanocytes are critical imaging information for the diagnosis of melanocytic lesions. However, how to image intratumoral melanocytes noninvasively in pigmented skin tumors is seldom investigated. Third-harmonic generation (THG) is shown to be enhanced by melanin, whereas high accuracy has been demonstrated using THG microscopy for in vivo differential diagnosis of nonmelanocytic pigmented skin tumors. It is thus desirable to investigate if label-free THG microscopy was capable to in vivo identify intratumoral melanocytes. In this study, histopathological correlations of label-free THG images with the immunohistochemical images stained with human melanoma black (HMB)-45 and cluster of differentiation 1a (CD1a) were made. The correlation results indicated that the intratumoral THG-bright dendritic-cell-like signals were endogenously derived from melanocytes rather than Langerhans cells (LCs). The consistency between THG-bright dendritic-cell-like signals and HMB-45 melanocyte staining showed a kappa coefficient of 0.807, 84.6% sensitivity, and 95% specificity. In contrast, a kappa coefficient of -0.37, 21.7% sensitivity, and 30% specificity were noted between the THG-bright dendritic-cell-like signals and CD1a staining for LCs. Our study indicates the capability of noninvasive label-free THG microscopy to differentiate intratumoral melanocytes from LCs, which is not feasible in previous in vivo label-free clinical-imaging modalities.

Imaging Lung Clearance of Radiolabeled Tumor Cells to Study Mice with Normal, Activated or Depleted Natural Killer (NK) Cells

NASA Astrophysics Data System (ADS)

Kulkarni, P. V.; Bennett, M.; Constantinescu, A.; Arora, V.; Viguet, M.; Antich, P.; Parkey, R. W.; Mathews, D.; Mason, R. P.; Oz, O. K.

2003-08-01

Lung clearance of 51CR and 125I iododeoxyuridine (IUDR) labeled cancer cells assess NK cell activity. It is desirable to develop noninvasive imaging technique to assess NK activity in mice. We labeled target YAC-1 tumor cells with 125I, 111In, 99mTc, or 67Ga and injected I.V. into three groups of BALB/c mice. Animals were treated with medium (group I), 300mg/kg cyclophosmamide (CY) to kill NK cell (group II), or anti-LY49C/1) (ab')2 mAb to augment NK function (group III). Lungs were removed 15 min or 2 h later for tissue counting. Control and treated mice were imaged every 5 min with a scintillating camera for 1 h after 15 min of infusion of the 111In labeled cells. Lung clearance increased after 15 min (lodging: 60-80%) and (2 h retention: 3-7%). Similar results were obtained with all the isotopes studied. Images distinguished the control and treated mice for lung activity. Cells labeled with 111In, 99mTc or 67Ga are cleared similar to those labeled with 51Cr or 125I. NK cell destruction of tumor cells may be assessed by noninvasive imaging method either by SPECT (99mTc, 111In, 67Ga) or by PET (68Ga).

21 CFR 250.12 - Stramonium preparations labeled with directions for use in self-medication regarded as misbranded.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 4 2010-04-01 2010-04-01 false Stramonium preparations labeled with directions for use in self-medication regarded as misbranded. 250.12 Section 250.12 Food and Drugs FOOD AND DRUG... come to the attention of the Food and Drug Administration showing that such products have been subject...

Off-label use of misoprostol in gynaecology

PubMed Central

Turner, JV; Agatonovic-Kustrn, S; Ward, HRG

2015-01-01

Clinical use of drugs is approved for specified clinical indication, route of administration, dose and population group. Off-label prescribing of a registered medicine occurs outside of these parameters and may be justified by pharmacology and physiology, as well as sufficient evidence from published clinical trials and reviews. Misoprostol and mifepristone in combination have recently been registered in Australia for medical termination of pregnancy in women of child-bearing age. There is good clinical evidence for efficacy and safety of misoprostol in uterine evacuation in both miscarriage and termination of pregnancy. The pharmacological effects of misoprostol on the uterus and clinical outcomes in both early miscarriage and abortion are comparable. Medical management of miscarriage with misoprostol in Australia is performed off-label. A woman presenting with first trimester miscarriage must be clearly informed that use of misoprostol in her case is for a non-approved indication. This raises the issue of inequity in her management compared with that of first trimester medical abortion, including being treated off-label and the potential cost of non-subsidised medication. The clinician must also be careful to use an evidence-based protocol that would withstand medicolegal challenge in the case of an adverse outcome. PMID:27729972

Interactive lung segmentation in abnormal human and animal chest CT scans

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

Kockelkorn, Thessa T. J. P., E-mail: thessa@isi.uu.nl; Viergever, Max A.; Schaefer-Prokop, Cornelia M.

2014-08-15

Purpose: Many medical image analysis systems require segmentation of the structures of interest as a first step. For scans with gross pathology, automatic segmentation methods may fail. The authors’ aim is to develop a versatile, fast, and reliable interactive system to segment anatomical structures. In this study, this system was used for segmenting lungs in challenging thoracic computed tomography (CT) scans. Methods: In volumetric thoracic CT scans, the chest is segmented and divided into 3D volumes of interest (VOIs), containing voxels with similar densities. These VOIs are automatically labeled as either lung tissue or nonlung tissue. The automatic labeling resultsmore » can be corrected using an interactive or a supervised interactive approach. When using the supervised interactive system, the user is shown the classification results per slice, whereupon he/she can adjust incorrect labels. The system is retrained continuously, taking the corrections and approvals of the user into account. In this way, the system learns to make a better distinction between lung tissue and nonlung tissue. When using the interactive framework without supervised learning, the user corrects all incorrectly labeled VOIs manually. Both interactive segmentation tools were tested on 32 volumetric CT scans of pigs, mice and humans, containing pulmonary abnormalities. Results: On average, supervised interactive lung segmentation took under 9 min of user interaction. Algorithm computing time was 2 min on average, but can easily be reduced. On average, 2.0% of all VOIs in a scan had to be relabeled. Lung segmentation using the interactive segmentation method took on average 13 min and involved relabeling 3.0% of all VOIs on average. The resulting segmentations correspond well to manual delineations of eight axial slices per scan, with an average Dice similarity coefficient of 0.933. Conclusions: The authors have developed two fast and reliable methods for interactive lung segmentation in challenging chest CT images. Both systems do not require prior knowledge of the scans under consideration and work on a variety of scans.« less

99M-technetium labeled macroaggregated human serum albumin pharmaceutical

DOEpatents

Winchell, Harry S.; Barak, Morton; Van Fleet, III, Parmer

1977-05-17

A reagent comprising macroaggregated human serum albumin having dispersed therein particles of stannous tin and a method for instantly making a labeled pharmaceutical therefrom, are disclosed. The labeled pharmaceutical is utilized in organ imaging.

Programmable oligonucleotide probes design and applications for in situ and in vivo RNA imaging in cells

NASA Astrophysics Data System (ADS)

Cheglakov, Zoya

Unequal spreading of mRNA is a frequent experience observed in varied cell lines. The study of cellular processes dynamics and precise localization of mRNAs offers a vital toolbox to target specific proteins in precise cytoplasmic areas and provides a convenient instrument to uncover their mechanisms and functions. Latest methodological innovations have allowed imaging of a single mRNA molecule in situ and in vivo. Today, Fluorescent In Situ Hybridization (FISH) methods allow the studying of mRNA expression and offer a vital toolbox for accurate biological models. Studies enable analysis of the dynamics of an individual mRNA, have uncovered the multiplex RNA transport systems. With all current approaches, a single mRNA tracking in the mammalian cells is still challenging. This thesis describes mRNA detection methods based on programmable fluorophore-labeled DNA structures complimentary to native targets providing an accurate mRNA imaging in mammalian cells. First method represents beta-actin (ACTB) transcripts in situ detection in human cells, the technique strategy is based on programmable DNA probes, amplified by rolling circle amplification (RCA). The method reports precise localization of molecule of interest with an accuracy of a single-cell. Visualization and localization of specific endogenous mRNA molecules in real-time in vivo has the promising to innovate cellular biology studies, medical analysis and to provide a vital toolbox in drugs invention area. Second method described in this thesis represents miR-21 miRNA detection within a single live-cell resolution. The method using fluorophore-labeled short synthetic DNAs probes forming a stem-loop shape and generating Fluorescent Resonance Energy Transfer (FRET) as a result of target-probes hybridization. Catalytic nucleic acid (DNAzymes) probes are cooperative tool for precise detection of different mRNA targets. With assistance of a complementary fluorophore-quencher labeled substrate, the DNAzymes provide a beneficial strategy for simultaneous tracking readily accomplished by multicolor imaging with diverse fluorescent tags. The third method in this thesis will demonstrate the advantage of DNAzymes probes amplification, and offers potential strategy to monitor miRNAs in mammalian live cells.

Method and apparatus for imaging a sample on a device

DOEpatents

Trulson, Mark; Stern, David; Fiekowsky, Peter; Rava, Richard; Walton, Ian; Fodor, Stephen P. A.

1996-01-01

The present invention provides methods and systems for detecting a labeled marker on a sample located on a support. The imaging system comprises a body for immobilizing the support, an excitation radiation source and excitation optics to generate and direct the excitation radiation at the sample. In response, labeled material on the sample emits radiation which has a wavelength that is different from the excitation wavelength, which radiation is collected by collection optics and imaged onto a detector which generates an image of the sample.

Synthesis and biological studies of positron-emitting radiopharmaceuticals

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

Dischino, D.D.

The development and clinical evaluation of two-positron emitting radiopharmaceuticals designed to image myelin in humans is reported. Carbon-11-labeled benzyl methyl ether was synthesized by the reaction of carbon-11-labeled methanol and benzyl chloride in dimethyl sulfoxide containing powdered potassium hydroxide in a radiochemical yield of 43% and a synthesis and purification time of 40 minutes. Carbon-11-labeled diphenylmethanol was synthesized by the reaction of carbon-11-labeled carbon dioxide and phenyllithium followed by the reduction of the carbon-11-labeled intermediate to diphenylmethanol via lithium aluminum hydride in a radiochemical yield of 71% and a synthesis and purification time of 38 minutes. Carbon-11-labeled benzyl methyl ethermore » and diphenylmethanol were each evaluated as myelin imaging agents in three patients with multiple sclerosis via positron-emission tomography. In two out of three patients studied with carbon-11-labeled benzyl methyl ether, the distribution of activity in the brain was not consistent with local lipid content. A new synthesis of carbon-11-labeled-DL-phenylalanine labeled in the benzylic position and the synthesis of fluorine-18-labeled 1-(2-nitro-1-imidazolyl)-3-fluoro-2-propanol, a potential in vivo marker of hypoxic tissue, are reported.« less

Nuclear medicine and imaging research: quantitative studies in radiopharmaceutical science. Comprehensive progress report, January 1, 1980-December 31, 1982

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

Beck, R.N.; Cooper, M.C.

1982-06-01

This 3-y report cites progress in the following areas of radiopharmaceutical research: cyclotron operations; /sup 51/Mn for myocardial localization; /sup 82/Rb for heart imaging; /sup 15/O-labelled H/sub 2/O and molecular oxygen; studies on /sup 11/C-2-deoxyglucose localization; /sup 13/NH/sub 3/ measurements of myocardial perfusion; /sup 130/Cs myocardial imaging; heart motion studies; labelled amino acids for pancreatic imaging; /sup 11/C-hexamethonium for cartilage imaging; /sup 11/C-cholic acid pharmacology; blood element labelling with /sup 115m/In; /sup 75/Br studies; extrapolation of animal data to humans; in vivo quantification of radioactivity; fetal and neonatal radiation effects from radiopharmaceuticals administered to pregnant and lactating mice; and verificationmore » of MIRD absorbed dose calculations for some organ-incorporated radionuclides. (ERB)« less

Multimodal nonlinear imaging of arabidopsis thaliana root cell

NASA Astrophysics Data System (ADS)

Jang, Bumjoon; Lee, Sung-Ho; Woo, Sooah; Park, Jong-Hyun; Lee, Myeong Min; Park, Seung-Han

2017-07-01

Nonlinear optical microscopy has enabled the possibility to explore inside the living organisms. It utilizes ultrashort laser pulse with long wavelength (greater than 800nm). Ultrashort pulse produces high peak power to induce nonlinear optical phenomenon such as two-photon excitation fluorescence (TPEF) and harmonic generations in the medium while maintaining relatively low average energy pre area. In plant developmental biology, confocal microscopy is widely used in plant cell imaging after the development of biological fluorescence labels in mid-1990s. However, fluorescence labeling itself affects the sample and the sample deviates from intact condition especially when labelling the entire cell. In this work, we report the dynamic images of Arabidopsis thaliana root cells. This demonstrates the multimodal nonlinear optical microscopy is an effective tool for long-term plant cell imaging.

Simultaneous stimulated Raman scattering and higher harmonic generation imaging for liver disease diagnosis without labeling

NASA Astrophysics Data System (ADS)

Lin, Jian; Wang, Zi; Zheng, Wei; Huang, Zhiwei

2014-02-01

Nonlinear optical microscopy (e.g., higher harmonic (second-/third- harmonic) generation (HHG), simulated Raman scattering (SRS)) has high diagnostic sensitivity and chemical specificity, making it a promising tool for label-free tissue and cell imaging. In this work, we report a development of a simultaneous SRS and HHG imaging technique for characterization of liver disease in a bile-duct-ligation rat-modal. HHG visualizes collagens formation and reveals the cell morphologic changes associated with liver fibrosis; whereas SRS identifies the distributions of hepatic fat cells formed in steatosis liver tissue. This work shows that the co-registration of SRS and HHG images can be an effective means for label-free diagnosis and characterization of liver steatosis/fibrosis at the cellular and molecular levels.

[Visualization and Functional Regulation of Live Cell Proteins Based on Labeling Probe Design].

PubMed

Mizukami, Shin; Kikuchi, Kazuya

2016-01-01

  There are several approaches to understanding the physiological roles of biomolecules: (1) by observing the localization or activities of biomolecules (based on microscopic imaging experiments with fluorescent proteins or fluorescent probes) and (2) by investigating the cellular response via activation or suppression of functions of the target molecule (by using inhibitors, antagonists, siRNAs, etc.). In this context, protein-labeling technology serves as a powerful tool that can be used in various experiments, such as for fluorescence imaging of target proteins. Recently, we developed a protein-labeling technology that uses a mutant β-lactamase (a bacterial hydrolase) as the tag protein. In this protein-labeling technology, also referred to as the BL-tag technology, various β-lactam compounds were used as specific ligands that were covalently labeled to the tag. One major advantage of this labeling technology is that various functions can be carried out by suitably designing both the functional moieties such as the fluorophore and the β-lactam ligand structure. In this review, we briefly introduce the BL-tag technology and describe our future outlook for this technology, such as in fluorescence imaging of biomolecules and functional regulation of cellular proteins in living cells.

Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features

PubMed Central

Bakas, Spyridon; Akbari, Hamed; Sotiras, Aristeidis; Bilello, Michel; Rozycki, Martin; Kirby, Justin S.; Freymann, John B.; Farahani, Keyvan; Davatzikos, Christos

2017-01-01

Gliomas belong to a group of central nervous system tumors, and consist of various sub-regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for both clinical and computational studies, including radiomic and radiogenomic analyses. Towards this end, we release segmentation labels and radiomic features for all pre-operative multimodal magnetic resonance imaging (MRI) (n=243) of the multi-institutional glioma collections of The Cancer Genome Atlas (TCGA), publicly available in The Cancer Imaging Archive (TCIA). Pre-operative scans were identified in both glioblastoma (TCGA-GBM, n=135) and low-grade-glioma (TCGA-LGG, n=108) collections via radiological assessment. The glioma sub-region labels were produced by an automated state-of-the-art method and manually revised by an expert board-certified neuroradiologist. An extensive panel of radiomic features was extracted based on the manually-revised labels. This set of labels and features should enable i) direct utilization of the TCGA/TCIA glioma collections towards repeatable, reproducible and comparative quantitative studies leading to new predictive, prognostic, and diagnostic assessments, as well as ii) performance evaluation of computer-aided segmentation methods, and comparison to our state-of-the-art method. PMID:28872634

Image Quality Assessment of JPEG Compressed Mars Science Laboratory Mastcam Images using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Kerner, H. R.; Bell, J. F., III; Ben Amor, H.

2017-12-01

The Mastcam color imaging system on the Mars Science Laboratory Curiosity rover acquires images within Gale crater for a variety of geologic and atmospheric studies. Images are often JPEG compressed before being downlinked to Earth. While critical for transmitting images on a low-bandwidth connection, this compression can result in image artifacts most noticeable as anomalous brightness or color changes within or near JPEG compression block boundaries. In images with significant high-frequency detail (e.g., in regions showing fine layering or lamination in sedimentary rocks), the image might need to be re-transmitted losslessly to enable accurate scientific interpretation of the data. The process of identifying which images have been adversely affected by compression artifacts is performed manually by the Mastcam science team, costing significant expert human time. To streamline the tedious process of identifying which images might need to be re-transmitted, we present an input-efficient neural network solution for predicting the perceived quality of a compressed Mastcam image. Most neural network solutions require large amounts of hand-labeled training data for the model to learn the target mapping between input (e.g. distorted images) and output (e.g. quality assessment). We propose an automatic labeling method using joint entropy between a compressed and uncompressed image to avoid the need for domain experts to label thousands of training examples by hand. We use automatically labeled data to train a convolutional neural network to estimate the probability that a Mastcam user would find the quality of a given compressed image acceptable for science analysis. We tested our model on a variety of Mastcam images and found that the proposed method correlates well with image quality perception by science team members. When assisted by our proposed method, we estimate that a Mastcam investigator could reduce the time spent reviewing images by a minimum of 70%.

Multiplex and label-free screening of foodborne pathogens using surface plasmon resonance imaging

USDA-ARS?s Scientific Manuscript database

In order to protect outbreaks caused by foodborne pathogens, more rapid and efficient methods are needed for pathogen screening from food samples. Surface plasmon resonance imaging (SPRi) is an emerging optical technique, which allows for label-free screening of multiple targets simultaneously with ...

Multiplex surface plasmon resonance imaging platform for label-free detection of foodborne pathogens

USDA-ARS?s Scientific Manuscript database

Salmonellae are among the leading causes of foodborne outbreaks in the United States, and more rapid and efficient detection methods are needed. Surface plasmon resonance imaging (SPRi) is an emerging optical technique, which allows for rapid and label-free screening of multiple targets simultaneous...

Surface plasmon resonance imaging for label-free detection of foodborne pathogens and toxins

USDA-ARS?s Scientific Manuscript database

More rapid and efficient detection methods for foodborne pathogenic bacteria and toxins are needed to address the long assay time and limitations in multiplex capacity. Surface plasmon resonance imaging (SPRi) is an emerging optical technique, which allows for rapid and label-free screening of multi...

Chinese regulation of off-label use of drugs.

PubMed

Ma, Feng; Lou, Nan

2013-01-01

China has significant gaps and weaknesses in its regulatory oversight of the off-label use of drugs. As in the United States, the off-label prescribing of drugs is not prohibited in China if there is a sound scientific basis. Physicians are allowed to prescribe off-label drugs based on their medical judgment if they follow certain requirements. There is some constraint on the right to prescribe by the imposition of malpractice liability if patients are harmed from improper off-label prescribing. However, damages awarded to successful plaintiffs are usually insignificant compared to malpractice damage awards in the U.S. Advertisement of off-label use is prohibited in China. All drug advertisements in China are subject to pre-approval, and must be based on information included in the approved package insert. However, the term "advertisement" is poorly defined. As a result, non-advertisement promotion of drugs for on-label or off-label use exist in a unregulated gray area. To better address the problem of inappropriate off-label promotion and use, China should (i) regulate both drug advertisements and non-advertisement promotion under a standard requiring off-label use to have a sound scientific basis, (ii) introduce harsher regulatory penalties, and (iii) increase compensation available for victims of medical malpractice. Such reform would not only discourage improper off-label use by introducing penalties (or increasing existing penalties) for improper promotion, but would also provide reasonable compensation for victims harmed by off-label use.

Manganese-impregnated mesoporous silica nanoparticles for signal enhancement in MRI cell labelling studies

NASA Astrophysics Data System (ADS)

Guillet-Nicolas, Rémy; Laprise-Pelletier, Myriam; Nair, Mahesh M.; Chevallier, Pascale; Lagueux, Jean; Gossuin, Yves; Laurent, Sophie; Kleitz, Freddy; Fortin, Marc-André

2013-11-01

Mesoporous silica nanoparticles (MSNs) are used in drug delivery and cell tracking applications. As Mn2+ is already implemented as a ``positive'' cell contrast agent in preclinical imaging procedures (in the form of MnCl2 for neurological studies), the introduction of Mn in the porous network of MSNs would allow labelling cells and tracking them using MRI. These particles are in general internalized in endosomes, an acidic environment with high saline concentration. In addition, the available MSN porosity could also serve as a carrier to deliver medical/therapeutic substances through the labelled cells. In the present study, manganese oxide was introduced in the porous network of MCM-48 silica nanoparticles (Mn-M48SNs). The particles exhibit a narrow size distribution (~140 nm diam.) and high porosity (~60% vol.), which was validated after insertion of Mn. The resulting Mn-M48SNs were characterized by TEM, N2 physisorption, and XRD. Evidence was found with H2-TPR, and XPS characterization, that Mn(ii) is the main oxidation state of the paramagnetic species after suspension in water, most probably in the form of Mn-OOH. The colloidal stability as a function of time was confirmed by DLS in water, acetate buffer and cell culture medium. In NMR data, no significant evidence of Mn2+ leaching was found in Mn-M48SNs in acidic water (pH 6), up to 96 hours after suspension. High longitudinal relaxivity values of r1 = 8.4 mM-1 s-1 were measured at 60 MHz and 37 °C, with the lowest relaxometric ratios (r2/r1 = 2) reported to date for a Mn-MSN system. Leukaemia cells (P388) were labelled with Mn-M48SNs and nanoparticle cell internalization was confirmed by TEM. Finally, MRI contrast enhancement provided by cell labelling with escalated incubation concentrations of Mn-M48SNs was quantified at 1 T. This study confirmed the possibility of efficiently confining Mn into M48SNs using incipient wetness, while maintaining an open porosity and relatively high pore volume. Because these Mn-labelled M48SNs express strong ``positive'' contrast media properties at low concentrations, they are potentially applicable for cell tracking and drug delivery methodologies.Mesoporous silica nanoparticles (MSNs) are used in drug delivery and cell tracking applications. As Mn2+ is already implemented as a ``positive'' cell contrast agent in preclinical imaging procedures (in the form of MnCl2 for neurological studies), the introduction of Mn in the porous network of MSNs would allow labelling cells and tracking them using MRI. These particles are in general internalized in endosomes, an acidic environment with high saline concentration. In addition, the available MSN porosity could also serve as a carrier to deliver medical/therapeutic substances through the labelled cells. In the present study, manganese oxide was introduced in the porous network of MCM-48 silica nanoparticles (Mn-M48SNs). The particles exhibit a narrow size distribution (~140 nm diam.) and high porosity (~60% vol.), which was validated after insertion of Mn. The resulting Mn-M48SNs were characterized by TEM, N2 physisorption, and XRD. Evidence was found with H2-TPR, and XPS characterization, that Mn(ii) is the main oxidation state of the paramagnetic species after suspension in water, most probably in the form of Mn-OOH. The colloidal stability as a function of time was confirmed by DLS in water, acetate buffer and cell culture medium. In NMR data, no significant evidence of Mn2+ leaching was found in Mn-M48SNs in acidic water (pH 6), up to 96 hours after suspension. High longitudinal relaxivity values of r1 = 8.4 mM-1 s-1 were measured at 60 MHz and 37 °C, with the lowest relaxometric ratios (r2/r1 = 2) reported to date for a Mn-MSN system. Leukaemia cells (P388) were labelled with Mn-M48SNs and nanoparticle cell internalization was confirmed by TEM. Finally, MRI contrast enhancement provided by cell labelling with escalated incubation concentrations of Mn-M48SNs was quantified at 1 T. This study confirmed the possibility of efficiently confining Mn into M48SNs using incipient wetness, while maintaining an open porosity and relatively high pore volume. Because these Mn-labelled M48SNs express strong ``positive'' contrast media properties at low concentrations, they are potentially applicable for cell tracking and drug delivery methodologies. Electronic supplementary information (ESI) available: TEM images, particle size distributions, XRD, TPR, magnetometric profiles, T1 and T2 measurements at 60 MHz over time, NMRD profiles of materials, P388 cell proliferation assay after 4 h and T1-w. MR images of P388 cells incubated with a solution of M48SNs. See DOI: 10.1039/c3nr02969g

Multimodality Molecular Imaging of [18F]-Fluorinated Carboplatin Derivative Encapsulated in [111In]-Labeled Liposomes

NASA Astrophysics Data System (ADS)

Lamichhane, Narottam

Platinum based chemotherapy is amongst the mainstream DNA-damaging agents used in clinical cancer therapy today. Agents such as cisplatin, carboplatin are clinically prescribed for the treatment of solid tumors either as single agents, in combination, or as part of multi-modality treatment strategy. Despite the potent anti-tumor activity of these drugs, overall effectiveness is still hampered by inadequate delivery and retention of drug in tumor and unwanted normal tissue toxicity, induced by non-selective accumulation of drug in normal cells and tissues. Utilizing molecular imaging and nanoparticle technologies, this thesis aims to contribute to better understanding of how to improve the profile of platinum based therapy. By developing a novel fluorinated derivative of carboplatin, incorporating a Flourine-18 (18F) moiety as an inherent part of the molecule, quantitative measures of drug concentration in tumors and normal tissues can be directly determined in vivo and within the intact individual environment. A potential impact of this knowledge will be helpful in predicting the overall response of individual patients to the treatment. Specifically, the aim of this project, therefore, is the development of a fluorinated carboplatin drug derivative with an inherent positron emission tomography (PET) imaging capability, so that the accumulation of the drug in the tumor and normal organs can be studied during the course of therapy . A secondary objective of this research is to develop a proof of concept for simultaneous imaging of a PET radiolabeled drug with a SPECT radiolabeled liposomal formulation, enabling thereby bi-modal imaging of drug and delivery vehicle in vivo. The approach is challenging because it involves development in PET radiochemistry, PET and SPECT imaging, drug liposomal encapsulation, and a dual-modal imaging of radiolabeled drug and radiolabeled vehicle. The principal development is the synthesis of fluorinated carboplatin 19F-FCP using 2-(5-fluoro-pentyl)-2-methyl malonic acid as the labeling agent to coordinate with the cisplatin aqua complex. It was then used to treat various cell lines and compared with cisplatin and carboplatin at different concentrations ranging from 0.001 microM to 100 microM for 72 hrs and 96 hrs. IC50 values calculated from cell viability indicated that 19F-FCP is a more potent drug than Carboplatin. Manual radiosynthesis and characterization of [18F]-FCP was performed using [18F]-2-(5-fluoro-pentyl)-2-methyl malonic acid with coordination with cisplatin aqua complex. Automated radiosynthesis of [18F]-FCP was optimized using the manual synthetic procedures and using them as macros for the radiosynthesizer. [18F]-FCP was evaluated in vivo with detailed biodistribution studies and PET imaging in normal and KB 3-1 and KB 8-5 tumor xenograft bearing nude mice. The biodistribution studies and PET imaging of [18F]-FCP showed major uptake in kidneys which attributes to the renal clearance of radiotracer. In vivo plasma and urine stability demonstrated intact [18F]-FCP. [ 111In]-Labeled Liposomes was synthesized and physiochemical properties were assessed with DLS. [111In]-Labeled Liposome was evaluated in vivo with detailed pharmacokinetic studies and SPECT imaging. The biodistribution and ROI analysis from SPECT imaging showed the spleen and liver uptake of [111In]-Labeled Liposome and subsequent clearance of activity with time. [18F]-FCP encapsulated [111In]-Labeled Liposome was developed and physiochemical properties were characterized with DLS. [18F]-FCP encapsulated [111In]-Labeled Liposome was used for in vivo dual tracer PET and SPECT imaging from the same nanoconstruct in KB 3-1 (sensitive) and COLO 205 (resistant) tumor xenograft bearing nude mice. PET imaging of [18F]-FCP in KB 3-1 (sensitive) and COLO 205 (resistant) tumor xenograft bearing nude mice was performed. Naked [18F]-FCP and [18F]-FCP encapsulated [ 111In]-Labeled Liposome showed different pharmacokinetic profiles. PET imaging of [18F]-FCP showed major uptake in kidneys and bladder. However, [18F]-FCP encapsulated [111In]-Labeled Liposome showed major uptake in RES in both PET and SPECT images. ROI analysis of SPECT image enabled by 111In corresponded with PET image enabled by 18F demonstrating the feasibility of dual tracer imaging from the single nanoconstruct. Future work involves the intensive in vitro characterization of [18F]-FCP encapsulated [ 111In]-Labeled Liposome and detailed in vivo evaluation of [ 18F]-FCP encapsulated [111In]-Labeled Liposome in various tumor models.

Fungal Infections: The Stubborn Cases

PubMed Central

Adam, John E.

1982-01-01

Despite development of numerous antifungal preparations, mycotic infections persist, because of inaccurate diagnosis leading to inappropriate therapy, drug failure, non-compliance or resistance of the organism to antifungal medication. Direct KOH examination is the simplest method of proving the existence of a fungus. Fungal infections tend to be overdiagnosed; disorders which do not improve with three to four weeks of treatment should be reassessed before being labelled ‘stubborn’. Griseofulvin is effective treatment for all dermatophytes, but has certain side effects. Newer topical antifungals are also effective, but no single drug cures all fungal infections. ImagesFig. 1Fig. 2Fig. 3Fig. 4Fig. 5Fig. 6Fig. 7Fig. 8 PMID:20469387

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

Lu, Fa-Ke; Basu, Srinjan; Igras, Vivien

Label-free DNA imaging is highly desirable in biology and medicine to perform live imaging without affecting cell function and to obtain instant histological tissue examination during surgical procedures. Here we show a label-free DNA imaging method with stimulated Raman scattering (SRS) microscopy for visualization of the cell nuclei in live animals and intact fresh human tissues with subcellular resolution. Relying on the distinct Raman spectral features of the carbon-hydrogen bonds in DNA, the distribution of DNA is retrieved from the strong background of proteins and lipids by linear decomposition of SRS images at three optimally selected Raman shifts. Based onmore » changes on DNA condensation in the nucleus, we were able to capture chromosome dynamics during cell division both in vitro and in vivo. We tracked mouse skin cell proliferation, induced by drug treatment, through in vivo counting of the mitotic rate. Moreover, we demonstrated a label-free histology method for human skin cancer diagnosis that provides comparable results to other conventional tissue staining methods such as H&E. In conclusion, our approach exhibits higher sensitivity than SRS imaging of DNA in the fingerprint spectral region. Compared with spontaneous Raman imaging of DNA, our approach is three orders of magnitude faster, allowing both chromatin dynamic studies and label-free optical histology in real time.« less

18 F-Labeling of Sensitive Biomolecules for Positron Emission Tomography.

PubMed

Krishnan, Hema S; Ma, Longle; Vasdev, Neil; Liang, Steven H

2017-11-07

Positron emission tomography (PET) imaging study of fluorine-18 labeled biomolecules is an emerging and rapidly growing area for preclinical and clinical research. The present review focuses on recent advances in radiochemical methods for incorporating fluorine-18 into biomolecules via "direct" or "indirect" bioconjugation. Recently developed prosthetic groups and pre-targeting strategies, as well as representative examples in 18 F-labeling of biomolecules in PET imaging research studies are highlighted. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Luminescent probes for optical in vivo imaging

NASA Astrophysics Data System (ADS)

Texier, Isabelle; Josserand, Veronique; Garanger, Elisabeth; Razkin, Jesus; Jin, Zhaohui; Dumy, Pascal; Favrot, Marie; Boturyn, Didier; Coll, Jean-Luc

2005-04-01

Going along with instrumental development for small animal fluorescence in vivo imaging, we are developing molecular fluorescent probes, especially for tumor targeting. Several criteria have to be taken into account for the optimization of the luminescent label. It should be adapted to the in vivo imaging optical conditions : red-shifted absorption and emission, limited overlap between absorption and emission for a good signal filtering, optimized luminescence quantum yield, limited photo-bleaching. Moreover, the whole probe should fulfill the biological requirements for in vivo labeling : adapted blood-time circulation, biological conditions compatibility, low toxicity. We here demonstrate the ability of the imaging fluorescence set-up developed in LETI to image the bio-distribution of molecular probes on short times after injection. Targeting with Cy5 labeled holo-transferrin of subcutaneous TS/Apc (angiogenic murine breast carcinoma model) or IGROV1 (human ovarian cancer) tumors was achieved. Differences in the kinetics of the protein uptake by the tumors were evidenced. IGROV1 internal metastatic nodes implanted in the peritoneal cavity could be detected in nude mice. However, targeted metastatic nodes in lung cancer could only be imaged after dissection of the mouse. These results validate our fluorescence imaging set-up and the use of Cy5 as a luminescent label. New fluorescent probes based on this dye and a molecular delivery template (the RAFT molecule) can thus be envisioned.

Pattern Recognition Of Blood Vessel Networks In Ocular Fundus Images

NASA Astrophysics Data System (ADS)

Akita, K.; Kuga, H.

1982-11-01

We propose a computer method of recognizing blood vessel networks in color ocular fundus images which are used in the mass diagnosis of adult diseases such as hypertension and diabetes. A line detection algorithm is applied to extract the blood vessels, and the skeleton patterns of them are made to analyze and describe their structures. The recognition of line segments of arteries and/or veins in the vessel networks consists of three stages. First, a few segments which satisfy a certain constraint are picked up and discriminated as arteries or veins. This is the initial labeling. Then the remaining unknown ones are labeled by utilizing the physical level knowledge. We propose two schemes for this stage : a deterministic labeling and a probabilistic relaxation labeling. Finally the label of each line segment is checked so as to minimize the total number of labeling contradictions. Some experimental results are also presented.

Deep learning for segmentation of brain tumors: can we train with images from different institutions?

NASA Astrophysics Data System (ADS)

Paredes, David; Saha, Ashirbani; Mazurowski, Maciej A.

2017-03-01

Deep learning and convolutional neural networks (CNNs) in particular are increasingly popular tools for segmentation and classification of medical images. CNNs were shown to be successful for segmentation of brain tumors into multiple regions or labels. However, in the environment which fosters data-sharing and collection of multi-institutional datasets, a question arises: does training with data from another institution with potentially different imaging equipment, contrast protocol, and patient population impact the segmentation performance of the CNN? Our study presents preliminary data towards answering this question. Specifically, we used MRI data of glioblastoma (GBM) patients for two institutions present in The Cancer Imaging Archive. We performed a process of training and testing CNN multiple times such that half of the time the CNN was tested on data from the same institution that was used for training and half of the time it was tested on another institution, keeping the training and testing set size constant. We observed a decrease in performance as measured by Dice coefficient when the CNN was trained with data from a different institution as compared to training with data from the same institution. The changes in performance for the entire tumor and for four different labels within the tumor were: 0.72 to 0.65 (p=0.06), 0.61 to 0.58 (p=0.49), 0.54 to 0.51 (p=0.82), 0.31 to 0.24 (p<0.03), and 0.43 to 0.31(p<0.003) respectively. In summary, we found that while data across institutions can be used for development of CNNs, this might be associated with a decrease in performance.

Machine Learning Interface for Medical Image Analysis.

PubMed

Zhang, Yi C; Kagen, Alexander C

2017-10-01

TensorFlow is a second-generation open-source machine learning software library with a built-in framework for implementing neural networks in wide variety of perceptual tasks. Although TensorFlow usage is well established with computer vision datasets, the TensorFlow interface with DICOM formats for medical imaging remains to be established. Our goal is to extend the TensorFlow API to accept raw DICOM images as input; 1513 DaTscan DICOM images were obtained from the Parkinson's Progression Markers Initiative (PPMI) database. DICOM pixel intensities were extracted and shaped into tensors, or n-dimensional arrays, to populate the training, validation, and test input datasets for machine learning. A simple neural network was constructed in TensorFlow to classify images into normal or Parkinson's disease groups. Training was executed over 1000 iterations for each cross-validation set. The gradient descent optimization and Adagrad optimization algorithms were used to minimize cross-entropy between the predicted and ground-truth labels. Cross-validation was performed ten times to produce a mean accuracy of 0.938 ± 0.047 (95 % CI 0.908-0.967). The mean sensitivity was 0.974 ± 0.043 (95 % CI 0.947-1.00) and mean specificity was 0.822 ± 0.207 (95 % CI 0.694-0.950). We extended the TensorFlow API to enable DICOM compatibility in the context of DaTscan image analysis. We implemented a neural network classifier that produces diagnostic accuracies on par with excellent results from previous machine learning models. These results indicate the potential role of TensorFlow as a useful adjunct diagnostic tool in the clinical setting.

Traffic Video Image Segmentation Model Based on Bayesian and Spatio-Temporal Markov Random Field

NASA Astrophysics Data System (ADS)

Zhou, Jun; Bao, Xu; Li, Dawei; Yin, Yongwen

2017-10-01

Traffic video image is a kind of dynamic image and its background and foreground is changed at any time, which results in the occlusion. In this case, using the general method is more difficult to get accurate image segmentation. A segmentation algorithm based on Bayesian and Spatio-Temporal Markov Random Field is put forward, which respectively build the energy function model of observation field and label field to motion sequence image with Markov property, then according to Bayesian' rule, use the interaction of label field and observation field, that is the relationship of label field’s prior probability and observation field’s likelihood probability, get the maximum posterior probability of label field’s estimation parameter, use the ICM model to extract the motion object, consequently the process of segmentation is finished. Finally, the segmentation methods of ST - MRF and the Bayesian combined with ST - MRF were analyzed. Experimental results: the segmentation time in Bayesian combined with ST-MRF algorithm is shorter than in ST-MRF, and the computing workload is small, especially in the heavy traffic dynamic scenes the method also can achieve better segmentation effect.

External scintigraphy in monitoring the behavior of pharmaceutical formulations in vivo I: technique for acquiring high-resolution images of tablets

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

Theodorakis, M.C.; Simpson, D.R.; Leung, D.M.

1983-02-01

A new method for monitoring tablet disintegration in vivo was developed. In this method, the tablets were labeled with a short-lived radionuclide, technetium 99m, and monitored by a gamma camera. Several innovations were introduced with this method. First, computer reconstruction algorithms were used to enhance the scintigraphic images of the disintegrating tablet in vivo. Second, the use of a four-pinhole collimator to acquire multiple views of the tablet resulted in high count rates and reduced acquisition times of the scintigraphic images. Third, the magnification of the scintigraphic images achieved by pinhole collimation led to significant improvement in resolution. Fourth, themore » radioinuclide was incorporated into the granulation so that the whole mass of the tablet was uniformly labeled with high levels of activity. This technique allowed the continuous monitoring of the disintegration process of tablets in vivo in experimental animals. Multiple pinhole collimation and the labeling process permitted the acquisition of quality scintigraphic images of the labeled tablet every 30 sec. The resolution of the method was tested in vitro and in vivo.« less

Imaging Complex Protein Metabolism in Live Organisms by Stimulated Raman Scattering Microscopy with Isotope Labeling

PubMed Central

2016-01-01

Protein metabolism, consisting of both synthesis and degradation, is highly complex, playing an indispensable regulatory role throughout physiological and pathological processes. Over recent decades, extensive efforts, using approaches such as autoradiography, mass spectrometry, and fluorescence microscopy, have been devoted to the study of protein metabolism. However, noninvasive and global visualization of protein metabolism has proven to be highly challenging, especially in live systems. Recently, stimulated Raman scattering (SRS) microscopy coupled with metabolic labeling of deuterated amino acids (D-AAs) was demonstrated for use in imaging newly synthesized proteins in cultured cell lines. Herein, we significantly generalize this notion to develop a comprehensive labeling and imaging platform for live visualization of complex protein metabolism, including synthesis, degradation, and pulse–chase analysis of two temporally defined populations. First, the deuterium labeling efficiency was optimized, allowing time-lapse imaging of protein synthesis dynamics within individual live cells with high spatial–temporal resolution. Second, by tracking the methyl group (CH3) distribution attributed to pre-existing proteins, this platform also enables us to map protein degradation inside live cells. Third, using two subsets of structurally and spectroscopically distinct D-AAs, we achieved two-color pulse–chase imaging, as demonstrated by observing aggregate formation of mutant hungtingtin proteins. Finally, going beyond simple cell lines, we demonstrated the imaging ability of protein synthesis in brain tissues, zebrafish, and mice in vivo. Hence, the presented labeling and imaging platform would be a valuable tool to study complex protein metabolism with high sensitivity, resolution, and biocompatibility for a broad spectrum of systems ranging from cells to model animals and possibly to humans. PMID:25560305

Labeling of DOTA-conjugated HPMA-based polymers with trivalent metallic radionuclides for molecular imaging.

PubMed

Eppard, Elisabeth; de la Fuente, Ana; Mohr, Nicole; Allmeroth, Mareli; Zentel, Rudolf; Miederer, Matthias; Pektor, Stefanie; Rösch, Frank

2018-02-27

In this work, the in vitro and in vivo stabilities and the pharmacology of HPMA-made homopolymers were studied by means of radiometal-labeled derivatives. Aiming to identify the fewer amount and the optimal DOTA-linker structure that provides quantitative labeling yields, diverse DOTA-linker systems were conjugated in different amounts to HPMA homopolymers to coordinate trivalent radiometals Me(III)* = gallium-68, scandium-44, and lutetium-177. Short linkers and as low as 1.6% DOTA were enough to obtain labeling yields > 90%. Alkoxy linkers generally exhibited lower labeling yields than alkane analogues despite of similar chain length and DOTA incorporation rate. High stability of the radiolabel in all examined solutions was observed for all conjugates. Labeling with scandium-44 allowed for in vivo PET imaging and ex vivo measurements of organ distribution for up to 24 h. This study confirms the principle applicability of DOTA-HPMA conjugates for labeling with different trivalent metallic radionuclides allowing for diagnosis and therapy.

Measurement of brain perfusion in newborns: Pulsed arterial spin labeling (PASL) versus pseudo-continuous arterial spin labeling (pCASL)

PubMed Central

Boudes, Elodie; Gilbert, Guillaume; Leppert, Ilana Ruth; Tan, Xianming; Pike, G. Bruce; Saint-Martin, Christine; Wintermark, Pia

2014-01-01

Background Arterial spin labeling (ASL) perfusion-weighted imaging (PWI) by magnetic resonance imaging (MRI) has been shown to be useful for identifying asphyxiated newborns at risk of developing brain injury, whether or not therapeutic hypothermia was administered. However, this technique has been only rarely used in newborns until now, because of the challenges to obtain sufficient signal-to-noise ratio (SNR) and spatial resolution in newborns. Objective To compare two methods of ASL-PWI (i.e., single inversion-time pulsed arterial spin labeling [single TI PASL], and pseudo-continuous arterial spin labeling [pCASL]) to assess brain perfusion in asphyxiated newborns treated with therapeutic hypothermia and in healthy newborns. Design/methods We conducted a prospective cohort study of term asphyxiated newborns meeting the criteria for therapeutic hypothermia; four additional healthy term newborns were also included as controls. Each of the enrolled newborns was scanned at least once during the first month of life. Each MRI scan included conventional anatomical imaging, as well as PASL and pCASL PWI-MRI. Control and labeled images were registered separately to reduce the effect of motion artifacts. For each scan, the axial slice at the level of the basal ganglia was used for comparisons. Each scan was scored for its image quality. Quantification of whole-slice cerebral blood flow (CBF) was done afterwards using previously described formulas. Results A total number of 61 concomitant PASL and pCASL scans were obtained in nineteen asphyxiated newborns treated with therapeutic hypothermia and four healthy newborns. After discarding the scans with very poor image quality, 75% (46/61) remained for comparison between the two ASL methods. pCASL images presented a significantly superior image quality score compared to PASL images (p < 0.0001). Strong correlation was found between the CBF measured by PASL and pCASL (r = 0.61, p < 0.0001). Conclusion This study demonstrates that both ASL methods are feasible to assess brain perfusion in healthy and sick newborns. However, pCASL might be a better choice over PASL in newborns, as pCASL perfusion maps had a superior image quality that allowed a more detailed identification of the different brain structures. PMID:25379424

Biocompatible inorganic nanoparticles for [18F]-fluoride binding with applications in PET imaging

PubMed Central

Jauregui-Osoro, Maite; Williamson, Peter A.; Glaria, Arnaud; Sunassee, Kavitha; Charoenphun, Putthiporn; Green, Mark A.; Mullen, Gregory E. D.; Blower, Philip J.

2014-01-01

A wide selection of insoluble nanoparticulate metal salts was screened for avid binding of [18F]-fluoride. Hydroxyapatite and aluminium hydroxide nanoparticles showed particularly avid and stable binding of [18F]-fluoride in various biological media. The in vivo behaviour of the [18F]-labelled hydroxyapatite and aluminium hydroxide particles was determined by PET-CT imaging in mice. [18F]-labelled hydroxyapatite was stable in circulation and when trapped in various tissues (lung embolisation, subcutaneous and intramuscular), but accumulation in liver via reticuloendothelial clearance was followed by gradual degradation and release of [18F]-fluoride (over a period of 4 h) which accumulated in bone. [18F]-labelled aluminium hydroxide was also cleared to liver and spleen but degraded slightly even without liver uptake (subcutanenous and intramuscular). Both materials have properties that are an attractive basis for the design of molecular targeted PET imaging agents labelled with 18F. PMID:21394352

Chemical reactivation of quenched fluorescent protein molecules enables resin-embedded fluorescence microimaging

PubMed Central

Xiong, Hanqing; Zhou, Zhenqiao; Zhu, Mingqiang; Lv, Xiaohua; Li, Anan; Li, Shiwei; Li, Longhui; Yang, Tao; Wang, Siming; Yang, Zhongqin; Xu, Tonghui; Luo, Qingming; Gong, Hui; Zeng, Shaoqun

2014-01-01

Resin embedding is a well-established technique to prepare biological specimens for microscopic imaging. However, it is not compatible with modern green-fluorescent protein (GFP) fluorescent-labelling technique because it significantly quenches the fluorescence of GFP and its variants. Previous empirical optimization efforts are good for thin tissue but not successful on macroscopic tissue blocks as the quenching mechanism remains uncertain. Here we show most of the quenched GFP molecules are structurally preserved and not denatured after routine embedding in resin, and can be chemically reactivated to a fluorescent state by alkaline buffer during imaging. We observe up to 98% preservation in yellow-fluorescent protein case, and improve the fluorescence intensity 11.8-fold compared with unprocessed samples. We demonstrate fluorescence microimaging of resin-embedded EGFP/EYFP-labelled tissue block without noticeable loss of labelled structures. This work provides a turning point for the imaging of fluorescent protein-labelled specimens after resin embedding. PMID:24886825

Imaging of immunolabeled membrane receptors in uncoated SEM specimens.

PubMed

Heinzmann, U; Reninger, A; Autrata, R; Höfler, H

1994-01-01

Epidermal growth factor receptors (EGFR) were labeled with 10 nm immunogold and examined on uncoated specimens of A431 human epidermoid carcinoma cells. A field emission gun and a high-sensitivity YAG ring detector were used to demonstrate the affinity labeling simultaneously in the secondary-electron (SE) and backscattered-electron (BSE) modes with a low accelerating voltage (Vo). At Vo = 2 kV, the SE and BSE signals were too weak to identify all markers, while at Vo = 3-7 kV labeling was observed unambiguously in both the SE and BSE modes with smaller and higher working distances. Increasing the Vo to above 7 kV sometimes provokes instability of the specimens. A Vo of > or = 10 kV produces charging artifacts in the SE image, but permits a BSE image of the gold markers providing additional topographic information. In conclusion, immunogold labeling can be used with good results for uncoated specimens.

Enhancement of the MODIS Snow and Ice Product Suite Utilizing Image Segmentation

NASA Technical Reports Server (NTRS)

Tilton, James C.; Hall, Dorothy K.; Riggs, George A.

2006-01-01

A problem has been noticed with the current NODIS Snow and Ice Product in that fringes of certain snow fields are labeled as "cloud" whereas close inspection of the data indicates that the correct labeling is a non-cloud category such as snow or land. This occurs because the current MODIS Snow and Ice Product generation algorithm relies solely on the MODIS Cloud Mask Product for the labeling of image pixels as cloud. It is proposed here that information obtained from image segmentation can be used to determine when it is appropriate to override the cloud indication from the cloud mask product. Initial tests show that this approach can significantly reduce the cloud "fringing" in modified snow cover labeling. More comprehensive testing is required to determine whether or not this approach consistently improves the accuracy of the snow and ice product.

Advancing School and Community Engagement Now for Disease Prevention (ASCEND).

PubMed

Treu, Judith A; Doughty, Kimberly; Reynolds, Jesse S; Njike, Valentine Y; Katz, David L

2017-03-01

To compare two intensity levels (standard vs. enhanced) of a nutrition and physical activity intervention vs. a control (usual programs) on nutrition knowledge, body mass index, fitness, academic performance, behavior, and medication use among elementary school students. Quasi-experimental with three arms. Elementary schools, students' homes, and a supermarket. A total of 1487 third-grade students. The standard intervention (SI) provided daily physical activity in classrooms and a program on making healthful foods, using food labels. The enhanced intervention (EI) provided these plus additional components for students and their families. Body mass index (zBMI), food label literacy, physical fitness, academic performance, behavior, and medication use for asthma or attention-deficit hyperactivity disorder (ADHD). Multivariable generalized linear model and logistic regression to assess change in outcome measures. Both the SI and EI groups gained less weight than the control (p < .001), but zBMI did not differ between groups (p = 1.00). There were no apparent effects on physical fitness or academic performance. Both intervention groups improved significantly but similarly in food label literacy (p = .36). Asthma medication use was reduced significantly in the SI group, and nonsignificantly (p = .10) in the EI group. Use of ADHD medication remained unchanged (p = .34). The standard intervention may improve food label literacy and reduce asthma medication use in elementary school children, but an enhanced version provides no further benefit.

Initial evaluation of the use of USPIO cell labeling and noninvasive MR monitoring of human tissue-engineered vascular grafts in vivo.

PubMed

Nelson, G N; Roh, J D; Mirensky, T L; Wang, Y; Yi, T; Tellides, G; Pober, J S; Shkarin, P; Shapiro, E M; Saltzman, W M; Papademetris, X; Fahmy, T M; Breuer, C K

2008-11-01

This pilot study examines noninvasive MR monitoring of tissue-engineered vascular grafts (TEVGs) in vivo using cells labeled with iron oxide nanoparticles. Human aortic smooth muscle cells (hASMCs) were labeled with ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles. The labeled hASMCs, along with human aortic endothelial cells, were incorporated into eight TEVGs and were then surgically implanted as aortic interposition grafts in a C.B-17 SCID/bg mouse host. USPIO-labeled hASMCs persisted in the grafts throughout a 3 wk observation period and allowed noninvasive MR imaging of the human TEVGs for real-time, serial monitoring of hASMC retention. This study demonstrates the feasibility of applying noninvasive imaging techniques for evaluation of in vivo TEVG performance.

Data fitting and image fine-tuning approach to solve the inverse problem in fluorescence molecular imaging

NASA Astrophysics Data System (ADS)

Gorpas, Dimitris; Politopoulos, Kostas; Yova, Dido; Andersson-Engels, Stefan

2008-02-01

One of the most challenging problems in medical imaging is to "see" a tumour embedded into tissue, which is a turbid medium, by using fluorescent probes for tumour labeling. This problem, despite the efforts made during the last years, has not been fully encountered yet, due to the non-linear nature of the inverse problem and the convergence failures of many optimization techniques. This paper describes a robust solution of the inverse problem, based on data fitting and image fine-tuning techniques. As a forward solver the coupled radiative transfer equation and diffusion approximation model is proposed and compromised via a finite element method, enhanced with adaptive multi-grids for faster and more accurate convergence. A database is constructed by application of the forward model on virtual tumours with known geometry, and thus fluorophore distribution, embedded into simulated tissues. The fitting procedure produces the best matching between the real and virtual data, and thus provides the initial estimation of the fluorophore distribution. Using this information, the coupled radiative transfer equation and diffusion approximation model has the required initial values for a computational reasonable and successful convergence during the image fine-tuning application.

AutoBD: Automated Bi-Level Description for Scalable Fine-Grained Visual Categorization.

PubMed

Yao, Hantao; Zhang, Shiliang; Yan, Chenggang; Zhang, Yongdong; Li, Jintao; Tian, Qi

Compared with traditional image classification, fine-grained visual categorization is a more challenging task, because it targets to classify objects belonging to the same species, e.g. , classify hundreds of birds or cars. In the past several years, researchers have made many achievements on this topic. However, most of them are heavily dependent on the artificial annotations, e.g., bounding boxes, part annotations, and so on . The requirement of artificial annotations largely hinders the scalability and application. Motivated to release such dependence, this paper proposes a robust and discriminative visual description named Automated Bi-level Description (AutoBD). "Bi-level" denotes two complementary part-level and object-level visual descriptions, respectively. AutoBD is "automated," because it only requires the image-level labels of training images and does not need any annotations for testing images. Compared with the part annotations labeled by the human, the image-level labels can be easily acquired, which thus makes AutoBD suitable for large-scale visual categorization. Specifically, the part-level description is extracted by identifying the local region saliently representing the visual distinctiveness. The object-level description is extracted from object bounding boxes generated with a co-localization algorithm. Although only using the image-level labels, AutoBD outperforms the recent studies on two public benchmark, i.e. , classification accuracy achieves 81.6% on CUB-200-2011 and 88.9% on Car-196, respectively. On the large-scale Birdsnap data set, AutoBD achieves the accuracy of 68%, which is currently the best performance to the best of our knowledge.Compared with traditional image classification, fine-grained visual categorization is a more challenging task, because it targets to classify objects belonging to the same species, e.g. , classify hundreds of birds or cars. In the past several years, researchers have made many achievements on this topic. However, most of them are heavily dependent on the artificial annotations, e.g., bounding boxes, part annotations, and so on . The requirement of artificial annotations largely hinders the scalability and application. Motivated to release such dependence, this paper proposes a robust and discriminative visual description named Automated Bi-level Description (AutoBD). "Bi-level" denotes two complementary part-level and object-level visual descriptions, respectively. AutoBD is "automated," because it only requires the image-level labels of training images and does not need any annotations for testing images. Compared with the part annotations labeled by the human, the image-level labels can be easily acquired, which thus makes AutoBD suitable for large-scale visual categorization. Specifically, the part-level description is extracted by identifying the local region saliently representing the visual distinctiveness. The object-level description is extracted from object bounding boxes generated with a co-localization algorithm. Although only using the image-level labels, AutoBD outperforms the recent studies on two public benchmark, i.e. , classification accuracy achieves 81.6% on CUB-200-2011 and 88.9% on Car-196, respectively. On the large-scale Birdsnap data set, AutoBD achieves the accuracy of 68%, which is currently the best performance to the best of our knowledge.

21 CFR 801.420 - Hearing aid devices; professional and patient labeling.

Code of Federal Regulations, 2010 CFR

2010-04-01

... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES LABELING Special Requirements for Specific Devices § 801.420 Hearing aid devices; professional and patient labeling. (a) Definitions for the purposes of this section... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Hearing aid devices; professional and patient...

21 CFR 801.420 - Hearing aid devices; professional and patient labeling.

Code of Federal Regulations, 2011 CFR

2011-04-01

... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES LABELING Special Requirements for Specific Devices § 801.420 Hearing aid devices; professional and patient labeling. (a) Definitions for the purposes of this section... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Hearing aid devices; professional and patient...

Effect of preparation procedures on intensity of radioautographic labeling is studied

NASA Technical Reports Server (NTRS)

Baserga, R.; Kisieleski, W. E.

1967-01-01

Effects of tissue preparation and extractive procedures on the intensity of radioautographic labeling are presented in terms of mean grain count per cell in cells labeled with tritiated precursors of proteins or nucleic acids. This information would be of interest to medical researchers and cytologists.

21 CFR 801.50 - Labeling requirements for stand-alone software.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Labeling requirements for stand-alone software....50 Labeling requirements for stand-alone software. (a) Stand-alone software that is not distributed... in packaged form, stand-alone software regulated as a medical device must provide its unique device...

Performance evaluation of multi-material electronic cleansing for ultra-low-dose dual-energy CT colonography

NASA Astrophysics Data System (ADS)

Tachibana, Rie; Kohlhase, Naja; Näppi, Janne J.; Hironaka, Toru; Ota, Junko; Ishida, Takayuki; Regge, Daniele; Yoshida, Hiroyuki

2016-03-01

Accurate electronic cleansing (EC) for CT colonography (CTC) enables the visualization of the entire colonic surface without residual materials. In this study, we evaluated the accuracy of a novel multi-material electronic cleansing (MUMA-EC) scheme for non-cathartic ultra-low-dose dual-energy CTC (DE-CTC). The MUMA-EC performs a wateriodine material decomposition of the DE-CTC images and calculates virtual monochromatic images at multiple energies, after which a random forest classifier is used to label the images into the regions of lumen air, soft tissue, fecal tagging, and two types of partial-volume boundaries based on image-based features. After the labeling, materials other than soft tissue are subtracted from the CTC images. For pilot evaluation, 384 volumes of interest (VOIs), which represented sources of subtraction artifacts observed in current EC schemes, were sampled from 32 ultra-low-dose DE-CTC scans. The voxels in the VOIs were labeled manually to serve as a reference standard. The metric for EC accuracy was the mean overlap ratio between the labels of the reference standard and the labels generated by the MUMA-EC, a dualenergy EC (DE-EC), and a single-energy EC (SE-EC) scheme. Statistically significant differences were observed between the performance of the MUMA/DE-EC and the SE-EC methods (p<0.001). Visual assessment confirmed that the MUMA-EC generated less subtraction artifacts than did DE-EC and SE-EC. Our MUMA-EC scheme yielded superior performance over conventional SE-EC scheme in identifying and minimizing subtraction artifacts on noncathartic ultra-low-dose DE-CTC images.

Robust hepatic vessel segmentation using multi deep convolution network

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

3D GRASE PROPELLER: improved image acquisition technique for arterial spin labeling perfusion imaging.

PubMed

Tan, Huan; Hoge, W Scott; Hamilton, Craig A; Günther, Matthias; Kraft, Robert A

2011-07-01

Arterial spin labeling is a noninvasive technique that can quantitatively measure cerebral blood flow. While traditionally arterial spin labeling employs 2D echo planar imaging or spiral acquisition trajectories, single-shot 3D gradient echo and spin echo (GRASE) is gaining popularity in arterial spin labeling due to inherent signal-to-noise ratio advantage and spatial coverage. However, a major limitation of 3D GRASE is through-plane blurring caused by T(2) decay. A novel technique combining 3D GRASE and a periodically rotated overlapping parallel lines with enhanced reconstruction trajectory (PROPELLER) is presented to minimize through-plane blurring without sacrificing perfusion sensitivity or increasing total scan time. Full brain perfusion images were acquired at a 3 × 3 × 5 mm(3) nominal voxel size with pulsed arterial spin labeling preparation sequence. Data from five healthy subjects was acquired on a GE 1.5T scanner in less than 4 minutes per subject. While showing good agreement in cerebral blood flow quantification with 3D gradient echo and spin echo, 3D GRASE PROPELLER demonstrated reduced through-plane blurring, improved anatomical details, high repeatability and robustness against motion, making it suitable for routine clinical use. Copyright © 2011 Wiley-Liss, Inc.

Synthesis of a Fluorescently Labeled 68Ga-DOTA-TOC Analog for Somatostatin Receptor Targeting.

PubMed

Ghosh, Sukhen C; Hernandez Vargas, Servando; Rodriguez, Melissa; Kossatz, Susanne; Voss, Julie; Carmon, Kendra S; Reiner, Thomas; Schonbrunn, Agnes; Azhdarinia, Ali

2017-07-13

Fluorescently labeled imaging agents can identify surgical margins in real-time to help achieve complete resections and minimize the likelihood of local recurrence. However, photon attenuation limits fluorescence-based imaging to superficial lesions or lesions that are a few millimeters beneath the tissue surface. Contrast agents that are dual-labeled with a radionuclide and fluorescent dye can overcome this limitation and combine quantitative, whole-body nuclear imaging with intraoperative fluorescence imaging. Using a multimodality chelation (MMC) scaffold, IRDye 800CW was conjugated to the clinically used somatostatin analog, 68 Ga-DOTA-TOC, to produce the dual-labeled analog, 68 Ga-MMC(IRDye 800CW)-TOC, with high yield and specific activity. In vitro pharmacological assays demonstrated retention of receptor-targeting properties for the dual-labeled compound with robust internalization that was somatostatin receptor (SSTR) 2-mediated. Biodistribution studies in mice identified the kidneys as the primary excretion route for 68 Ga-MMC(IRDye 800CW)-TOC, along with clearance via the reticuloendothelial system. Higher uptake was observed in most tissues compared to 68 Ga-DOTA-TOC but decreased as a function of time. The combination of excellent specificity for SSTR2-expressing cells and suitable biodistribution indicate potential application of 68 Ga-MMC(IRDye 800CW)-TOC for intraoperative detection of SSTR2-expressing tumors.

Quantitative nanoscale imaging of orientational order in biological filaments by polarized superresolution microscopy

PubMed Central

Valades Cruz, Cesar Augusto; Shaban, Haitham Ahmed; Kress, Alla; Bertaux, Nicolas; Monneret, Serge; Mavrakis, Manos; Savatier, Julien; Brasselet, Sophie

2016-01-01

Essential cellular functions as diverse as genome maintenance and tissue morphogenesis rely on the dynamic organization of filamentous assemblies. For example, the precise structural organization of DNA filaments has profound consequences on all DNA-mediated processes including gene expression, whereas control over the precise spatial arrangement of cytoskeletal protein filaments is key for mechanical force generation driving animal tissue morphogenesis. Polarized fluorescence is currently used to extract structural organization of fluorescently labeled biological filaments by determining the orientation of fluorescent labels, however with a strong drawback: polarized fluorescence imaging is indeed spatially limited by optical diffraction, and is thus unable to discriminate between the intrinsic orientational mobility of the fluorophore labels and the real structural disorder of the labeled biomolecules. Here, we demonstrate that quantitative single-molecule polarized detection in biological filament assemblies allows not only to correct for the rotational flexibility of the label but also to image orientational order of filaments at the nanoscale using superresolution capabilities. The method is based on polarized direct stochastic optical reconstruction microscopy, using dedicated optical scheme and image analysis to determine both molecular localization and orientation with high precision. We apply this method to double-stranded DNA in vitro and microtubules and actin stress fibers in whole cells. PMID:26831082

Wide-field imaging and flow cytometric analysis of cancer cells in blood by fluorescent nanodiamond labeling and time gating

NASA Astrophysics Data System (ADS)

Hui, Yuen Yung; Su, Long-Jyun; Chen, Oliver Yenjyh; Chen, Yit-Tsong; Liu, Tzu-Ming; Chang, Huan-Cheng

2014-07-01

Nanodiamonds containing high density ensembles of negatively charged nitrogen-vacancy (NV-) centers are promising fluorescent biomarkers due to their excellent photostability and biocompatibility. The NV- centers in the particles have a fluorescence lifetime of up to 20 ns, which distinctly differs from those (<10 ns) of cell and tissue autofluorescence, making it possible to achieve background-free detection in vivo by time gating. Here, we demonstrate the feasibility of using fluorescent nanodiamonds (FNDs) as optical labels for wide-field time-gated fluorescence imaging and flow cytometric analysis of cancer cells with a nanosecond intensified charge-coupled device (ICCD) as the detector. The combined technique has allowed us to acquire fluorescence images of FND-labeled HeLa cells in whole blood covered with a chicken breast of ~0.1-mm thickness at the single cell level, and to detect individual FND-labeled HeLa cells in blood flowing through a microfluidic device at a frame rate of 23 Hz, as well as to locate and trace FND-labeled lung cancer cells in the blood vessels of a mouse ear. It opens a new window for real-time imaging and tracking of transplanted cells (such as stem cells) in vivo.

Automatic and hierarchical segmentation of the human skeleton in CT images.

PubMed

Fu, Yabo; Liu, Shi; Li, Harold; Yang, Deshan

2017-04-07

Accurate segmentation of each bone of the human skeleton is useful in many medical disciplines. The results of bone segmentation could facilitate bone disease diagnosis and post-treatment assessment, and support planning and image guidance for many treatment modalities including surgery and radiation therapy. As a medium level medical image processing task, accurate bone segmentation can facilitate automatic internal organ segmentation by providing stable structural reference for inter- or intra-patient registration and internal organ localization. Even though bones in CT images can be visually observed with minimal difficulty due to the high image contrast between the bony structures and surrounding soft tissues, automatic and precise segmentation of individual bones is still challenging due to the many limitations of the CT images. The common limitations include low signal-to-noise ratio, insufficient spatial resolution, and indistinguishable image intensity between spongy bones and soft tissues. In this study, a novel and automatic method is proposed to segment all the major individual bones of the human skeleton above the upper legs in CT images based on an articulated skeleton atlas. The reported method is capable of automatically segmenting 62 major bones, including 24 vertebrae and 24 ribs, by traversing a hierarchical anatomical tree and by using both rigid and deformable image registration. The degrees of freedom of femora and humeri are modeled to support patients in different body and limb postures. The segmentation results are evaluated using the Dice coefficient and point-to-surface error (PSE) against manual segmentation results as the ground-truth. The results suggest that the reported method can automatically segment and label the human skeleton into detailed individual bones with high accuracy. The overall average Dice coefficient is 0.90. The average PSEs are 0.41 mm for the mandible, 0.62 mm for cervical vertebrae, 0.92 mm for thoracic vertebrae, and 1.45 mm for pelvis bones.

Automatic and hierarchical segmentation of the human skeleton in CT images

NASA Astrophysics Data System (ADS)

Fu, Yabo; Liu, Shi; Li, H. Harold; Yang, Deshan

2017-04-01

Accurate segmentation of each bone of the human skeleton is useful in many medical disciplines. The results of bone segmentation could facilitate bone disease diagnosis and post-treatment assessment, and support planning and image guidance for many treatment modalities including surgery and radiation therapy. As a medium level medical image processing task, accurate bone segmentation can facilitate automatic internal organ segmentation by providing stable structural reference for inter- or intra-patient registration and internal organ localization. Even though bones in CT images can be visually observed with minimal difficulty due to the high image contrast between the bony structures and surrounding soft tissues, automatic and precise segmentation of individual bones is still challenging due to the many limitations of the CT images. The common limitations include low signal-to-noise ratio, insufficient spatial resolution, and indistinguishable image intensity between spongy bones and soft tissues. In this study, a novel and automatic method is proposed to segment all the major individual bones of the human skeleton above the upper legs in CT images based on an articulated skeleton atlas. The reported method is capable of automatically segmenting 62 major bones, including 24 vertebrae and 24 ribs, by traversing a hierarchical anatomical tree and by using both rigid and deformable image registration. The degrees of freedom of femora and humeri are modeled to support patients in different body and limb postures. The segmentation results are evaluated using the Dice coefficient and point-to-surface error (PSE) against manual segmentation results as the ground-truth. The results suggest that the reported method can automatically segment and label the human skeleton into detailed individual bones with high accuracy. The overall average Dice coefficient is 0.90. The average PSEs are 0.41 mm for the mandible, 0.62 mm for cervical vertebrae, 0.92 mm for thoracic vertebrae, and 1.45 mm for pelvis bones.

In vivo stem cell tracking with imageable nanoparticles that bind bioorthogonal chemical receptors on the stem cell surface.

PubMed

Lee, Sangmin; Yoon, Hwa In; Na, Jin Hee; Jeon, Sangmin; Lim, Seungho; Koo, Heebeom; Han, Sang-Soo; Kang, Sun-Woong; Park, Soon-Jung; Moon, Sung-Hwan; Park, Jae Hyung; Cho, Yong Woo; Kim, Byung-Soo; Kim, Sang Kyoon; Lee, Taekwan; Kim, Dongkyu; Lee, Seulki; Pomper, Martin G; Kwon, Ick Chan; Kim, Kwangmeyung

2017-09-01

It is urgently necessary to develop reliable non-invasive stem cell imaging technology for tracking the in vivo fate of transplanted stem cells in living subjects. Herein, we developed a simple and well controlled stem cell imaging method through a combination of metabolic glycoengineering and bioorthogonal copper-free click chemistry. Firstly, the exogenous chemical receptors containing azide (-N 3 ) groups were generated on the surfaces of stem cells through metabolic glycoengineering using metabolic precursor, tetra-acetylated N-azidoacetyl-d-mannosamine(Ac 4 ManNAz). Next, bicyclo[6.1.0]nonyne-modified glycol chitosan nanoparticles (BCN-CNPs) were prepared as imageable nanoparticles to deliver different imaging agents. Cy5.5, iron oxide nanoparticles and gold nanoparticles were conjugated or encapsulated to BCN-CNPs for optical, MR and CT imaging, respectively. These imageable nanoparticles bound chemical receptors on the Ac 4 ManNAz-treated stem cell surface specifically via bioorthogonal copper-free click chemistry. Then they were rapidly taken up by the cell membrane turn-over mechanism resulting in higher endocytic capacity compared non-specific uptake of nanoparticles. During in vivo animal test, BCN-CNP-Cy5.5-labeled stem cells could be continuously tracked by non-invasive optical imaging over 15 days. Furthermore, BCN-CNP-IRON- and BCN-CNP-GOLD-labeled stem cells could be efficiently visualized using in vivo MR and CT imaging demonstrating utility of our stem cell labeling method using chemical receptors. These results conclude that our method based on metabolic glycoengineering and bioorthogonal copper-free click chemistry can stably label stem cells with diverse imageable nanoparticles representing great potential as new stem cell imaging technology. Copyright © 2017 Elsevier Ltd. All rights reserved.

In-111 WBC imaging in musculoskeletal sepsis

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

Thompson, L.; Ouzounian, T.J.; Webber, M.M.

This study evaluated the accuracy and utility of the In-111 labeled WBC imaging in a series of patients who were suspected of having musculoskeletal sepsis. The labeling of the WBCs was patterned after a method previously described, in which the WBCs are labeled with In-111 oxine in plasma. The WBCs from 100 ml of blood are separated and incubated with In-111 oxine complex, and then 500 ..mu..Ci. of the labeled cells were reinjected into the patient. Images of the areas in question were obtained at 24 hrs. In some instances, 48 hour images were also obtained. Images were interpreted usingmore » consistent criteria. Forty imaging procedures were done on 39 patients. These included 39 total joint protheses, and 17 other images to evaluate possible osteomyelitis, septic arthritis or deep abscesses. Of these studies, 15 were positive, and 42 negative. The findings were then correlated with operative culture and pathology in 21, aspiration cultures and gram stains in 14, and with clinical findings in the remaining 21. This correlation showed 41 true negatives, 12 true positives, 1 false negative, and 2 false positives. The sensitivity was 92.9% and the specificity was 95.2%l. The false negative occurred in a patient on chronic suppressive antibiotic therapy for an infected total hip replacement. The false positive images occurred in a patient with active rheumatoid arthritis and in a patient imaged one month post operative placement of the prosthesis. These images were very useful in several septic patients who had many possible sites of infection. The authors conclude that In-III imaging is an accurate and useful non-invasive method of evaluating musculoskeletal sepsis.« less

F-18 Labeled Diabody-Luciferase Fusion Proteins for Optical-ImmunoPET

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

Wu, Anna M.

2013-01-18

The goal of the proposed work is to develop novel dual-labeled molecular imaging probes for multimodality imaging. Based on small, engineered antibodies called diabodies, these probes will be radioactively tagged with Fluorine-18 for PET imaging, and fused to luciferases for optical (bioluminescence) detection. Performance will be evaluated and validated using a prototype integrated optical-PET imaging system, OPET. Multimodality probes for optical-PET imaging will be based on diabodies that are dually labeled with 18F for PET detection and fused to luciferases for optical imaging. 1) Two sets of fusion proteins will be built, targeting the cell surface markers CEA or HER2.more » Coelenterazine-based luciferases and variant forms will be evaluated in combination with native substrate and analogs, in order to obtain two distinct probes recognizing different targets with different spectral signatures. 2) Diabody-luciferase fusion proteins will be labeled with 18F using amine reactive [18F]-SFB produced using a novel microwave-assisted, one-pot method. 3) Sitespecific, chemoselective radiolabeling methods will be devised, to reduce the chance that radiolabeling will inactivate either the target-binding properties or the bioluminescence properties of the diabody-luciferase fusion proteins. 4) Combined optical and PET imaging of these dual modality probes will be evaluated and validated in vitro and in vivo using a prototype integrated optical-PET imaging system, OPET. Each imaging modality has its strengths and weaknesses. Development and use of dual modality probes allows optical imaging to benefit from the localization and quantitation offered by the PET mode, and enhances the PET imaging by enabling simultaneous detection of more than one probe.« less

Supervised pixel classification using a feature space derived from an artificial visual system

NASA Technical Reports Server (NTRS)

Baxter, Lisa C.; Coggins, James M.

1991-01-01

Image segmentation involves labelling pixels according to their membership in image regions. This requires the understanding of what a region is. Using supervised pixel classification, the paper investigates how groups of pixels labelled manually according to perceived image semantics map onto the feature space created by an Artificial Visual System. Multiscale structure of regions are investigated and it is shown that pixels form clusters based on their geometric roles in the image intensity function, not by image semantics. A tentative abstract definition of a 'region' is proposed based on this behavior.

How the elderly and young adults differ in the decision making process of nonprescription medication purchases.

PubMed

Sansgiry, S S; Cady, P S

1996-01-01

The study compared elderly and young adults in their behavior and involvement in the decision making process of over-the-counter (OTC) medication purchases. Elderly subjects were more involved in the decision making process to purchase OTC medications compared to young adults. The elderly not only purchase and spend more money on medications but also read OTC labels completely. They requested help from the pharmacist more frequently than young adults. Needs of the elderly in making an OTC medication purchase were different compared to young adults. The two age groups differed on importance rating for several attributes regarding OTC medications, such as; ease of opening the package, child resistant package, side effects of medicine, manufacturer of medicine, print size on package labels, and greater choice of medicine.

Toward improved pregnancy labelling.

PubMed

Koren, Gideon; Sakaguchi, Sachi; Klieger, Chagit; Kazmin, Alex; Osadchy, Alla; Yazdani-Brojeni, Parvaneh; Matok, Ilan

2010-01-01

Information about the use of a medication in pregnancy is part of overall drug labelling as prepared by the pharmaceutical company and approved by the regulators. It is aimed at assisting clinicians in prescribing, however, very few drugs are labelled for specific indications in pregnancy, since there is rarely information about the use of a drug in this condition. Recently the FDA has drafted new guidelines for the labeling of drugs in pregnancy and breastfeeding, to replace the A,B,C,D,X system that was used for more than 30 years. Here we document the use of the new system through 3 different medications; each representing a different clinical situation in pregnancy--acute infection, chronic pain, and drug use during labor. Advantages and challenges in the new system are being highlighted.

Label-free optical imaging of lymphatic vessels within tissue beds in vivo

PubMed Central

Yousefi, Siavash; Zhi, Zhongwei; Wang, Ruikang K.

2015-01-01

Lymphatic vessels are a part of circulatory system in vertebrates that maintain tissue fluid homeostasis and drain excess fluid and large cells that cannot easily find their way back into venous system. Due to the lack of non-invasive monitoring tools, lymphatic vessels are known as forgotten circulation. However, lymphatic system plays an important role in diseases such as cancer and inflammatory conditions. In this paper, we start to briefly review the current existing methods for imaging lymphatic vessels, mostly involving dye/targeting cell injection. We then show the capability of optical coherence tomography (OCT) for label-free non-invasive in vivo imaging of lymph vessels and nodes. One of the advantages of using OCT over other imaging modalities is its ability to assess label-free blood flow perfusion that can be simultaneously observed along with lymphatic vessels for imaging the microcirculatory system within tissue beds. Imaging the microcirculatory system including blood and lymphatic vessels can be utilized for imaging and better understanding pathologic mechanisms and treatment technique development in some critical diseases such as inflammation, malignant cancer angiogenesis and metastasis. PMID:25642129

Label-free in vivo flow cytometry in zebrafish using two-photon autofluorescence imaging.

PubMed

Zeng, Yan; Xu, Jin; Li, Dong; Li, Li; Wen, Zilong; Qu, Jianan Y

2012-07-01

We demonstrate a label-free in vivo flow cytometry in zebrafish blood vessels based on two-photon excited autofluorescence imaging. The major discovery in this work is the strong autofluorescence emission from the plasma in zebrafish blood. The plasma autofluorescence provides excellent contrast for visualizing blood vessels and counting blood cells. In addition, the cellular nicotinamide adenine dinucleotide autofluorescence enables in vivo imaging and counting of white blood cells (neutrophils).

Semantic labeling of digital photos by classification

NASA Astrophysics Data System (ADS)

Ciocca, Gianluigi; Cusano, Claudio; Schettini, Raimondo; Brambilla, Carla

2003-01-01

The paper addresses the problem of annotating photographs with broad semantic labels. To cope with the great variety of photos available on the WEB we have designed a hierarchical classification strategy which first classifies images as pornographic or not-pornographic. Not-pornographic images are then classified as indoor, outdoor, or close-up. On a database of over 9000 images, mostly downloaded from the web, our method achieves an average accuracy of close to 90%.

Effect of Dye and Conjugation Chemistry on the Biodistribution Profile of Near-Infrared-Labeled Nanobodies as Tracers for Image-Guided Surgery.

PubMed

Debie, Pieterjan; Van Quathem, Jannah; Hansen, Inge; Bala, Gezim; Massa, Sam; Devoogdt, Nick; Xavier, Catarina; Hernot, Sophie

2017-04-03

Advances in optical imaging technologies have stimulated the development of near-infrared (NIR) fluorescently labeled targeted probes for use in image-guided surgery. As nanobodies have already proven to be excellent candidates for molecular imaging, we aimed in this project to design NIR-conjugated nanobodies targeting the tumor biomarker HER2 for future applications in this field and to evaluate the effect of dye and dye conjugation chemistry on their pharmacokinetics during development. IRDye800CW or IRdye680RD were conjugated either randomly (via lysines) or site-specifically (via C-terminal cysteine) to the anti-HER2 nanobody 2Rs15d. After verification of purity and functionality, the biodistribution and tumor targeting of the NIR-nanobodies were assessed in HER2-positive and -negative xenografted mice. Site-specifically IRDye800CW- and IRdye680RD-labeled 2Rs15d as well as randomly labeled 2Rs15d-IRDye680RD showed rapid tumor accumulation and low nonspecific uptake, resulting in high tumor-to-muscle ratios at early time points (respectively 6.6 ± 1.0, 3.4 ± 1.6, and 3.5 ± 0.9 for HER2-postive tumors at 3 h p.i., while <1.0 for HER2-negative tumors at 3 h p.i., p < 0.05). Contrarily, using the randomly labeled 2Rs15d-IRDye800CW, HER2-positive and -negative tumors could only be distinguished after 24 h due to high nonspecific signals. Moreover, both randomly labeled 2Rs15d nanobodies were not only cleared via the kidneys but also partially via the hepatobiliary route. In conclusion, near-infrared fluorescent labeling of nanobodies allows rapid, specific, and high contrast in vivo tumor imaging. Nevertheless, the fluorescent dye as well as the chosen conjugation strategy can affect the nanobodies' properties and consequently have a major impact on their pharmacokinetics.

New Dioxaborolane Chemistry Enables [18F]-Positron-Emitting, Fluorescent [18F]-Multimodality Biomolecule Generation from the Solid Phase

PubMed Central

Crisp, Jessica L.; Vera, David R.; Tsien, Roger Y.; Ting, Richard

2016-01-01

New protecting group chemistry is used to greatly simplify imaging probe production. Temperature and organic solvent-sensitive biomolecules are covalently attached to a biotin-bearing dioxaborolane, which facilitates antibody immobilization on a streptavidin-agarose solid-phase support. Treatment with aqueous fluoride triggers fluoride-labeled antibody release from the solid phase, separated from unlabeled antibody, and creates [18F]-trifluoroborate-antibody for positron emission tomography and near-infrared fluorescent (PET/NIRF) multimodality imaging. This dioxaborolane-fluoride reaction is bioorthogonal, does not inhibit antigen binding, and increases [18F]-specific activity relative to solution-based radiosyntheses. Two applications are investigated: an anti-epithelial cell adhesion molecule (EpCAM) monoclonal antibody (mAb) that labels prostate tumors and Cetuximab, an anti-epidermal growth factor receptor (EGFR) mAb (FDA approved) that labels lung adenocarcinoma tumors. Colocalized, tumor-specific NIRF and PET imaging confirm utility of the new technology. The described chemistry should allow labeling of many commercial systems, diabodies, nanoparticles, and small molecules for dual modality imaging of many diseases. PMID:27064381

New Dioxaborolane Chemistry Enables [(18)F]-Positron-Emitting, Fluorescent [(18)F]-Multimodality Biomolecule Generation from the Solid Phase.

PubMed

Rodriguez, Erik A; Wang, Ye; Crisp, Jessica L; Vera, David R; Tsien, Roger Y; Ting, Richard

2016-05-18

New protecting group chemistry is used to greatly simplify imaging probe production. Temperature and organic solvent-sensitive biomolecules are covalently attached to a biotin-bearing dioxaborolane, which facilitates antibody immobilization on a streptavidin-agarose solid-phase support. Treatment with aqueous fluoride triggers fluoride-labeled antibody release from the solid phase, separated from unlabeled antibody, and creates [(18)F]-trifluoroborate-antibody for positron emission tomography and near-infrared fluorescent (PET/NIRF) multimodality imaging. This dioxaborolane-fluoride reaction is bioorthogonal, does not inhibit antigen binding, and increases [(18)F]-specific activity relative to solution-based radiosyntheses. Two applications are investigated: an anti-epithelial cell adhesion molecule (EpCAM) monoclonal antibody (mAb) that labels prostate tumors and Cetuximab, an anti-epidermal growth factor receptor (EGFR) mAb (FDA approved) that labels lung adenocarcinoma tumors. Colocalized, tumor-specific NIRF and PET imaging confirm utility of the new technology. The described chemistry should allow labeling of many commercial systems, diabodies, nanoparticles, and small molecules for dual modality imaging of many diseases.

Adult stem cell lineage tracing and deep tissue imaging

PubMed Central

Fink, Juergen; Andersson-Rolf, Amanda; Koo, Bon-Kyoung

2015-01-01

Lineage tracing is a widely used method for understanding cellular dynamics in multicellular organisms during processes such as development, adult tissue maintenance, injury repair and tumorigenesis. Advances in tracing or tracking methods, from light microscopy-based live cell tracking to fluorescent label-tracing with two-photon microscopy, together with emerging tissue clearing strategies and intravital imaging approaches have enabled scientists to decipher adult stem and progenitor cell properties in various tissues and in a wide variety of biological processes. Although technical advances have enabled time-controlled genetic labeling and simultaneous live imaging, a number of obstacles still need to be overcome. In this review, we aim to provide an in-depth description of the traditional use of lineage tracing as well as current strategies and upcoming new methods of labeling and imaging. [BMB Reports 2015; 48(12): 655-667] PMID:26634741

High MRI performance fluorescent mesoporous silica-coated magnetic nanoparticles for tracking neural progenitor cells in an ischemic mouse model

NASA Astrophysics Data System (ADS)

Zhang, Lu; Wang, Yao; Tang, Yaohui; Jiao, Zheng; Xie, Chengying; Zhang, Haijiao; Gu, Ping; Wei, Xunbin; Yang, Guo-Yuan; Gu, Hongchen; Zhang, Chunfu

2013-05-01

Multifunctional probes with high MRI sensitivity and high efficiency for cell labeling are desirable for MR cell imaging. Herein, we have fabricated fluorescent mesoporous silica-coated superparamagnetic iron oxide nanoparticles (fmSiO4@SPIONs) for neural progenitor cell (C17.2) MR imaging. FmSiO4@SPIONs were discrete and uniform in size, and had a clear core-shell structure. The magnetic core size was about 10 nm and the fluorescent mesoporous silica coating layer was around 20 nm. Compared with fluorescent dense silica-coated SPIONs (fdSiO4@SPIONs) with a similar size, fmSiO4@SPIONs demonstrated higher MR sensitivity and cell labeling efficiency. When implanted into the right hemisphere of stroke mice, contralateral to the ischemic territory, a small amount of labeled cells were able to be tracked migrating to the lesion sites using a clinical MRI scanner (3 T). More impressively, even when administered intravenously, the labeled cells could also be monitored homing to the ischemic area. MRI observations were corroborated by histological studies of the brain tissues. Our study demonstrated that fmSiO4@SPIONs are highly effective for cell imaging and hold great promise for MRI cell tracking in future.Multifunctional probes with high MRI sensitivity and high efficiency for cell labeling are desirable for MR cell imaging. Herein, we have fabricated fluorescent mesoporous silica-coated superparamagnetic iron oxide nanoparticles (fmSiO4@SPIONs) for neural progenitor cell (C17.2) MR imaging. FmSiO4@SPIONs were discrete and uniform in size, and had a clear core-shell structure. The magnetic core size was about 10 nm and the fluorescent mesoporous silica coating layer was around 20 nm. Compared with fluorescent dense silica-coated SPIONs (fdSiO4@SPIONs) with a similar size, fmSiO4@SPIONs demonstrated higher MR sensitivity and cell labeling efficiency. When implanted into the right hemisphere of stroke mice, contralateral to the ischemic territory, a small amount of labeled cells were able to be tracked migrating to the lesion sites using a clinical MRI scanner (3 T). More impressively, even when administered intravenously, the labeled cells could also be monitored homing to the ischemic area. MRI observations were corroborated by histological studies of the brain tissues. Our study demonstrated that fmSiO4@SPIONs are highly effective for cell imaging and hold great promise for MRI cell tracking in future. Electronic supplementary information (ESI) available: Details of cell internalization of fmSiO4@SPIONs compared with SHU555A, immunofluorescence image of the immature phenotype of labeled C17.2. See DOI: 10.1039/c3nr00119a

Cryopreservation of embryonic stem cell-derived multicellular neural aggregates labeled with micron-sized particles of iron oxide for magnetic resonance imaging.

PubMed

Yan, Yuanwei; Sart, Sébastien; Calixto Bejarano, Fabian; Muroski, Megan E; Strouse, Geoffrey F; Grant, Samuel C; Li, Yan

2015-01-01

Magnetic resonance imaging (MRI) provides an effective approach to track labeled pluripotent stem cell (PSC)-derived neural progenitor cells (NPCs) for neurological disorder treatments after cell labeling with a contrast agent, such as an iron oxide derivative. Cryopreservation of pre-labeled neural cells, especially in three-dimensional (3D) structure, can provide a uniform cell population and preserve the stem cell niche for the subsequent applications. In this study, the effects of cryopreservation on PSC-derived multicellular NPC aggregates labeled with micron-sized particles of iron oxide (MPIO) were investigated. These NPC aggregates were labeled prior to cryopreservation because labeling thawed cells can be limited by inefficient intracellular uptake, variations in labeling efficiency, and increased culture time before use, minimizing their translation to clinical settings. The results indicated that intracellular MPIO incorporation was retained after cryopreservation (70-80% labeling efficiency), and MPIO labeling had little adverse effects on cell recovery, proliferation, cytotoxicity and neural lineage commitment post-cryopreservation. MRI analysis showed comparable detectability for the MPIO-labeled cells before and after cryopreservation indicated by T2 and T2* relaxation rates. Cryopreserving MPIO-labeled 3D multicellular NPC aggregates can be applied in in vivo cell tracking studies and lead to more rapid translation from preservation to clinical implementation. © 2015 American Institute of Chemical Engineers.

Nanobiodevices for Biomolecule Analysis and Imaging

NASA Astrophysics Data System (ADS)

Yasui, Takao; Kaji, Noritada; Baba, Yoshinobu

2013-06-01

Nanobiodevices have been developed to analyze biomolecules and cells for biomedical applications. In this review, we discuss several nanobiodevices used for disease-diagnostic devices, molecular imaging devices, regenerative medicine, and drug-delivery systems and describe the numerous advantages of nanobiodevices, especially in biological, medical, and clinical applications. This review also outlines the fabrication technologies for nanostructures and nanomaterials, including top-down nanofabrication and bottom-up molecular self-assembly approaches. We describe nanopillar arrays and nanowall arrays for the ultrafast separation of DNA or protein molecules and nanoball materials for the fast separation of a wide range of DNA molecules, and we present examples of applications of functionalized carbon nanotubes to obtain information about subcellular localization on the basis of mobility differences between free fluorophores and fluorophore-labeled carbon nanotubes. Finally, we discuss applications of newly synthesized quantum dots to the screening of small interfering RNA, highly sensitive detection of disease-related proteins, and development of cancer therapeutics and diagnostics.

Label-Free Raman Imaging to Monitor Breast Tumor Signatures.

PubMed

Manciu, Felicia S; Ciubuc, John D; Parra, Karla; Manciu, Marian; Bennet, Kevin E; Valenzuela, Paloma; Sundin, Emma M; Durrer, William G; Reza, Luis; Francia, Giulio

2017-08-01

Although not yet ready for clinical application, methods based on Raman spectroscopy have shown significant potential in identifying, characterizing, and discriminating between noncancerous and cancerous specimens. Real-time and accurate medical diagnosis achievable through this vibrational optical method largely benefits from improvements in current technological and software capabilities. Not only is the acquisition of spectral information now possible in milliseconds and analysis of hundreds of thousands of data points achieved in minutes, but Raman spectroscopy also allows simultaneous detection and monitoring of several biological components. Besides demonstrating a significant Raman signature distinction between nontumorigenic (MCF-10A) and tumorigenic (MCF-7) breast epithelial cells, our study demonstrates that Raman can be used as a label-free method to evaluate epidermal growth factor activity in tumor cells. Comparative Raman profiles and images of specimens in the presence or absence of epidermal growth factor show important differences in regions attributed to lipid, protein, and nucleic acid vibrations. The occurrence, which is dependent on the presence of epidermal growth factor, of new Raman features associated with the appearance of phosphothreonine and phosphoserine residues reflects a signal transduction from the membrane to the nucleus, with concomitant modification of DNA/RNA structural characteristics. Parallel Western blotting analysis reveals an epidermal growth factor induction of phosphorylated Akt protein, corroborating the Raman results. The analysis presented in this work is an important step toward Raman-based evaluation of biological activity of epidermal growth factor receptors on the surfaces of breast cancer cells. With the ultimate future goal of clinically implementing Raman-guided techniques for the diagnosis of breast tumors (e.g., with regard to specific receptor activity), the current results just lay the foundation for further label-free optical tools to diagnose the disease.

Direct labeling of serum proteins by fluorescent dye for antibody microarray.

PubMed

Klimushina, M V; Gumanova, N G; Metelskaya, V A

2017-05-06

Analysis of serum proteome by antibody microarray is used to identify novel biomarkers and to study signaling pathways including protein phosphorylation and protein-protein interactions. Labeling of serum proteins is important for optimal performance of the antibody microarray. Proper choice of fluorescent label and optimal concentration of protein loaded on the microarray ensure good quality of imaging that can be reliably scanned and processed by the software. We have optimized direct serum protein labeling using fluorescent dye Arrayit Green 540 (Arrayit Corporation, USA) for antibody microarray. Optimized procedure produces high quality images that can be readily scanned and used for statistical analysis of protein composition of the serum. Copyright © 2017 Elsevier Inc. All rights reserved.

Fluorine-containing nanoemulsions for MRI cell tracking

PubMed Central

Janjic, Jelena M.; Ahrens, Eric T.

2009-01-01

In this article we review the chemistry and nanoemulsion formulation of perfluorocarbons used for in vivo 19F MRI cell tracking. In this application, cells of interest are labeled in culture using a perfluorocarbon nanoemulsion. Labeled cells are introduced into a subject and tracked using 19F MRI or NMR spectroscopy. In the same imaging session, a high-resolution, conventional (1H) image can be used to place the 19F-labeled cells into anatomical context. Perfluorocarbon-based 19F cell tracking is a useful technology because of the high specificity for labeled cells, ability to quantify cell accumulations, and biocompatibility. This technology can be widely applied to studies of inflammation, cellular regenerative medicine, and immunotherapy. PMID:19920872

Cell labeling with magnetic nanoparticles: Opportunity for magnetic cell imaging and cell manipulation

PubMed Central

2013-01-01

This tutorial describes a method of controlled cell labeling with citrate-coated ultra small superparamagnetic iron oxide nanoparticles. This method may provide basically all kinds of cells with sufficient magnetization to allow cell detection by high-resolution magnetic resonance imaging (MRI) and to enable potential magnetic manipulation. In order to efficiently exploit labeled cells, quantify the magnetic load and deliver or follow-up magnetic cells, we herein describe the main requirements that should be applied during the labeling procedure. Moreover we present some recommendations for cell detection and quantification by MRI and detail magnetic guiding on some real-case studies in vitro and in vivo. PMID:24564857

Ptychography: use of quantitative phase information for high-contrast label free time-lapse imaging of living cells

NASA Astrophysics Data System (ADS)

Suman, Rakesh; O'Toole, Peter

2014-03-01

Here we report a novel label free, high contrast and quantitative method for imaging live cells. The technique reconstructs an image from overlapping diffraction patterns using a ptychographical algorithm. The algorithm utilises both amplitude and phase data from the sample to report on quantitative changes related to the refractive index (RI) and thickness of the specimen. We report the ability of this technique to generate high contrast images, to visualise neurite elongation in neuronal cells, and to provide measure of cell proliferation.

Photoacoustic microscopy of single cells employing an intensity-modulated diode laser

NASA Astrophysics Data System (ADS)

Langer, Gregor; Buchegger, Bianca; Jacak, Jaroslaw; Dasa, Manoj Kumar; Klar, Thomas A.; Berer, Thomas

2018-02-01

In this work, we employ frequency-domain photoacoustic microscopy to obtain photoacoustic images of labeled and unlabeled cells. The photoacoustic microscope is based on an intensity-modulated diode laser in combination with a focused piezo-composite transducer and allows imaging of labeled cells without severe photo-bleaching. We demonstrate that frequency-domain photoacoustic microscopy realized with a diode laser is capable of recording photoacoustic images of single cells with sub-µm resolution. As examples, we present images of undyed human red blood cells, stained human epithelial cells, and stained yeast cells.

Nanoscale Photoacoustic Tomography (nPAT) for label-free super-resolution 3D imaging of red blood cells

NASA Astrophysics Data System (ADS)

Samant, Pratik; Hernandez, Armando; Conklin, Shelby; Xiang, Liangzhong

2017-08-01

We present our results in developing nanoscale photoacoustic tomography (nPAT) for label-free super-resolution imaging in 3D. We have made progress in the development of nPAT, and have acquired our first signal. We have also performed simulations that demonstrate that nPAT is a viable imaging modality for the visualization of malaria infected red blood cells (RBCs). Our results demonstrate that nPAT is both feasible and powerful for the high resolution labelfree imaging of RBCs.

PET and SPECT imaging of a radiolabeled minigastrin analogue conjugated with DOTA, NOTA, and NODAGA and labeled with (64)Cu, (68)Ga, and (111)In.

PubMed

Roosenburg, S; Laverman, P; Joosten, L; Cooper, M S; Kolenc-Peitl, P K; Foster, J M; Hudson, C; Leyton, J; Burnet, J; Oyen, W J G; Blower, P J; Mather, S J; Boerman, O C; Sosabowski, J K

2014-11-03

Cholecystokinin-2 (CCK-2) receptors, overexpressed in cancer types such as small cell lung cancers (SCLC) and medullary thyroid carcinomas (MTC), may serve as targets for peptide receptor radionuclide imaging. A variety of CCK and gastrin analogues has been developed, but a major drawback is metabolic instability or high kidney uptake. The minigastrin analogue PP-F11 has previously been shown to be a promising peptide for imaging of CCK-2 receptor positive tumors and was therefore further evaluated. The peptide was conjugated with one of the macrocyclic chelators DOTA, NOTA, or NODAGA. The peptide conjugates were then radiolabeled with either (68)Ga, (64)Cu, or (111)In. All (radio)labeled compounds were evaluated in vitro (IC50) and in vivo (biodistribution and PET/CT and SPECT/CT imaging). IC50 values were in the low nanomolar range for all compounds (0.79-1.51 nM). In the biodistribution studies, (68)Ga- and (111)In-labeled peptides showed higher tumor-to-background ratios than the (64)Cu-labeled compounds. All tested radiolabeled compounds clearly visualized the CCK2 receptor positive tumor in PET or SPECT imaging. The chelator did not seem to affect in vivo behavior of the peptide for (111)In- and (68)Ga-labeled peptides. In contrast, the biodistribution of the (64)Cu-labeled peptides showed high uptake in the liver and in other organs, most likely caused by high blood levels, probably due to dissociation of (64)Cu from the chelator and subsequent transchelation to proteins. Based on the present study, (68)Ga-DOTA-PP-F11 might be a promising radiopharmaceutical for PET/CT imaging of CCK2 receptor expressing tumors such as MTC and SCLC. Clinical studies are warranted to investigate the potential of this tracer.