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BackgroundTissue clearing technologies have enabled remarkable advancements for in situ characterization of tissues and exploration of the three-dimensional (3D) relationships between cells, however, these studies have predominantly been performed in non-human tissues and correlative assessment with clinical imaging has yet to be explored. We sought to evaluate the feasibility of tissue clearing technologies for3Dimaging of intact human prostate and the mapping of structurally and molecularly preserved pathology data with multi-parametric volumetric MR imaging (mpMRI).MethodsWhole-mount prostates were processed with either hydrogel-based CLARITY or solvent-based iDISCO. The samples were stained with a nuclear dye or fluorescently labeled with antibodies against androgen receptor, alpha-methylacyl coenzyme-A racemase, or p63, and then imaged with 3D confocal microscopy. The apparent diffusion coefficientand Ktrans maps were computed from preoperative mpMRI.ResultsQuantitative analysis of cleared normal and tumor prostate tissue volumes displayed differences in 3D tissue architecture, marker-specific cell staining, and cell densities that were significantly correlated with mpMRI measurements in this initial, pilot cohort.Conclusions3D imaging of human prostate volumes following tissue clearing is a feasible technique for quantitative radiology-pathology correlation analysis with mpMRI and provides an opportunity to explore functional relationships between cellular structures and cross-sectional clinical imaging.

Parasitic diseases caused by protozoan pathogens lead to hundreds of thousands of deaths per year in addition to substantial suffering and socioeconomic decline for millions of people worldwide. The lack of effective vaccines coupled with the widespread emergence of drug‐resistant parasites necessitates that the research community take an active role in understanding host–parasite infection biology in order to develop improved therapeutics. Recent advances in next‐generation sequencing and the rapid development of publicly accessible genomic databases for many human pathogens have facilitated the application of systems biology to the study of host–parasite interactions. Over the past decade, these technologies have led to the discovery of many important biological processes governing parasitic disease. The integration and interpretation of high‐throughput ‐omic data will undoubtedly generate extraordinary insight into host–parasite interaction networks essential to navigate the intricacies of these complex systems. As systems analysis continues to build the foundation for our understanding of host–parasite biology, this will provide the framework necessary to drive drug discovery research forward and accelerate the development of new antiparasitic therapies. WIREs Syst Biol Med 2015, 7:381–400. doi: 10.1002/wsbm.1311 For further resources related to this article, please visit the WIREs website.

A variety of electronic DNA array devices and techniques have been developed that allow electric field enhanced hybridization to be carried out under special low-conductance conditions. These devices include both planar microelectronic DNA array/chip devices as well as electronic microtiter plate-like devices. Such "active" electronic devices are able to provide controlled electric (electrophoretic) fields that serve as a driving force to move and concentrate nucleic acid molecules (DNA/RNA) to selected microlocation test-sites on the device. In addition to ionic strength, pH, temperature and other agents, the electric field provides another controllable parameter that can affect and enhance DNA hybridization. With regard to the planar microelectronic array devices, special low-conductance buffers were developed in order to maintain rapid transport of DNA molecules and to facilitate hybridization within the constrained low current and voltage ranges for this type of device. With regard to electronic microtiter plate type devices (which do not have the low current/voltage constraints), the use of mixed buffers (low conductance upper chamber/high conductance lower chamber) can be used in a unique fashion to create favorable hybridization conditions in a microzone within the test site location. Both types of devices allow DNA molecules to be rapidly and selectively hybridized at the array test sites under conditions where the DNA in the bulk solution can remain substantially denatured.

Purpose: Objective and reliable quantification of imaging phenotype is an essential part of radiogenomic studies. We compared the reproducibility of two semi-automatic segmentation methods for quantitative image phenotyping in magnetic resonance imaging (MRI) of glioblastoma multiforme (GBM). Methods: MRI examinations with T1 post-gadolinium and FLAIR sequences of 10 GBM patients were downloaded from the Cancer Image Archive site. Two semi-automatic segmentation tools with different algorithms (deformable model and grow cut method) were used to segment contrast enhancement, necrosis and edema regions by two independent observers. A total of 21 imaging features consisting of area and edge groups were extracted automatically from the segmented tumor. The inter-observer variability and coefficient of variation (COV) were calculated to evaluate the reproducibility. Results: Inter-observer correlations and coefficient of variation of imaging features with the deformable model ranged from 0.953 to 0.999 and 2.1% to 9.2%, respectively, and the grow cut method ranged from 0.799 to 0.976 and 3.5% to 26.6%, respectively. Coefficient of variation for especially important features which were previously reported as predictive of patient survival were: 3.4% with deformable model and 7.4% with grow cut method for the proportion of contrast enhanced tumor region; 5.5% with deformable model and 25.7% with growmore » cut method for the proportion of necrosis; and 2.1% with deformable model and 4.4% with grow cut method for edge sharpness of tumor on CE-T1W1. Conclusion: Comparison of two semi-automated tumor segmentation techniques shows reliable image feature extraction for radiogenomic analysis of GBM patients with multiparametric Brain MRI.« less

Purpose: Objective and quantitative radiophenotyping from cancer patients is a core requirement of radiogenomic research. We present our quantitative image phenotyping pipeline which is tuned to extract spatiotemporal tumor traits from DCE breast MRI and initial results of radiogenomic association between spatiotemporal imaging features and RNA expression in breast cancer Methods: DCE MRI with 5 enhancement phases of 61 breast cancer patients were analyzed. A unified energy functional was defined for a joint shape and temporal motion estimation which incorporates intensity variation within a region along with kinetic signature. A level set evolution was carried out under the guidance of the unified energy functional to generate tumor probability maps, which is then thresholded to produce tumor masks. Among them, the observer selected the largest one. A total of 47 features were extracted from the segmented tumor comprising geometric, statistical, and spatiotemporal features. The whole procedure was carried out independently by two observers. Features from 19 cases were used as a training set to discover a prognostic imaging biomarker indicative of poor metastasis-free survival, and the remaining 39 cases were used for validation.In addition, association between the predictive imaging biomarker and genomic profiles were assessed using RNA expression data of these matched patients obtained with next-generation RNA sequencing and RT-PCR. Results: All imaging features from two independent analysis were highly consistent (r > 0.78, p