Sylvestheller4557

with significant CAD.© RSNA, 2020See also commentary by François in this issue.

To present the findings of 21 coronavirus disease 2019 (COVID-19) cases from two Chinese centers with CT and chest radiographic findings, as well as follow-up imaging in five cases.

This was a retrospective study in Shenzhen and Hong Kong. Patients with COVID-19 infection were included. A systematic review of the published literature on radiologic features of COVID-19 infection was conducted.

The predominant imaging pattern was of ground-glass opacification with occasional consolidation in the peripheries. Pleural effusions and lymphadenopathy were absent in all cases. Patients demonstrated evolution of the ground-glass opacities into consolidation and subsequent resolution of the airspace changes. Ground-glass and consolidative opacities visible on CT are sometimes undetectable on chest radiography, suggesting that CT is a more sensitive imaging modality for investigation. The systematic review identified four other studies confirming the findings of bilateral and peripheral ground glass with or without consolidation as the predominant finding at CT chest examinations.

Pulmonary manifestation of COVID-19 infection is predominantly characterized by ground-glass opacification with occasional consolidation on CT. Radiographic findings in patients presenting in Shenzhen and Hong Kong are in keeping with four previous publications from other sites.© RSNA, 2020See editorial by Kay and Abbara in this issue.

Pulmonary manifestation of COVID-19 infection is predominantly characterized by ground-glass opacification with occasional consolidation on CT. Radiographic findings in patients presenting in Shenzhen and Hong Kong are in keeping with four previous publications from other sites.© RSNA, 2020See editorial by Kay and Abbara in this issue.Coronavirus disease 2019 (COVID-19) (previously known as novel coronavirus [2019-nCoV]), first reported in China, has now been declared a global health emergency by the World Health Organization. As confirmed cases are being reported in several countries from all over the world, it becomes important for all radiologists to be aware of the imaging spectrum of the disease and contribute to effective surveillance and response measures. © RSNA, 2020 See editorial by Kay and Abbara in this issue.The mitral valve is a complex structure with a three-dimensional saddle shape annulus. Mitral regurgitation occurs from leaflet coaptation failure that is either primary (a problem with the leaflets) or secondary (chamber dilatation in the setting of cardiomyopathy). There has been an increase in focus on transcatheter mitral valve interventions, for both mitral repair and replacement. These technologies have rapidly developed to provide treatment for a substantial number of patients with severe symptomatic mitral regurgitation who are at too high of a risk to undergo open heart surgery. CT assessment of the mitral valve has developed with equal rapidity, with regard to preprocedural planning for transcatheter therapies. This review will provide an overview of mitral valve anatomy, an update on the current transcatheter repair and replacement therapies, as well as a focused overview of the role of multislice CT in mitral assessment prior to intervention. © RSNA, 2020.

To employ four-dimensional (4D) flow MRI to investigate associations between hemodynamic parameters with systolic anterior motion (SAM), mitral regurgitation (MR), stroke volume, and cardiac mass in patients with hypertrophic cardiomyopathy (HCM).

A total of 13 patients with HCM (51 years ± 16 [standard deviation]; 10 men) and 11 age-matched healthy control subjects (54 years ± 15; eight men) underwent cardiac 4D flow MRI data analysis including calculation of peak systolic and diastolic control-averaged left ventricular (LV) velocity maps to quantify volumes of elevated velocity (EVV) in the left ventricle. Standard-of-care cine imaging was performed in short-axis, LV outflow tract (LVOT), and two-, three-, and four-chamber views on which the presence of SAM, presence of MR, total stroke volume, and cardiac mass were assessed.

Systolic EVV in patients with HCM was 7 mL ± 5, which was significantly associated with elevated aortic peak velocity (

= 0.87;

< .001), decreased LVOT diameter (

= 0.68;

= .01), and increased cardiac mass (

= 0.62;

= .02). In addition, EVV differed significantly between patients with and those without SAM (10 mL ± 4.7 vs 3 mL ± 2.3;

= .03) and those with and those without MR (9.9 mL ± 4.8 vs 4.0 mL ± 3.2;

< .05). In the atrial systolic phase, peak diastolic velocity in the LV correlated with septal thickness (

= 0.66;

= .01).

Quantification and visualization of EVV in the LV is feasible and may provide further insight into the clinical manifestations of altered hemodynamics in HCM.© RSNA, 2020.

Quantification and visualization of EVV in the LV is feasible and may provide further insight into the clinical manifestations of altered hemodynamics in HCM.© RSNA, 2020.Dysregulation of gene expression plays an important role in cancer development. Identifying transcriptional regulators, including transcription factors and chromatin regulators, that drive the oncogenic gene expression program is a critical task in cancer research. Genomic profiles of active transcriptional regulators from primary cancer samples are limited in the public domain. Here we present BART Cancer (bartcancer.org), an interactive web resource database to display the putative transcriptional regulators that are responsible for differentially regulated genes in 15 different cancer types in The Cancer Genome Atlas (TCGA). BART Cancer integrates over 10000 gene expression profiling RNA-seq datasets from TCGA with over 7000 ChIP-seq datasets from the Cistrome Data Browser database and the Gene Expression Omnibus (GEO). BART Cancer uses Binding Analysis for Regulation of Transcription (BART) for predicting the transcriptional regulators from the differentially expressed genes in cancer samples compared to normal samples. BART Cancer also displays the activities of over 900 transcriptional regulators across cancer types, by integrating computational prediction results from BART and the Cistrome Cancer database. Focusing on transcriptional regulator activities in human cancers, BART Cancer can provide unique insights into epigenetics and transcriptional regulation in cancer, and is a useful data resource for genomics and cancer research communities.The RNA methyltransferase TRDMT1 has recently emerged as a key regulator of homologous recombination (HR) in the transcribed regions of the genome, but how it is regulated and its relevance in cancer remain unknown. Here, we identified that TRDMT1 is poly-ubiquitinated at K251 by the E3 ligase TRIM28, removing TRDMT1 from DNA damage sites and allowing completion of HR. Interestingly, K251 is adjacent to G155 in the 3D structure, and the G155V mutation leads to hyper ubiquitination of TRDMT1, reduced TRDMT1 levels and impaired HR. Accordingly, a TRDMT1 G155V mutation in an ovarian cancer super responder to platinum treatment. Cells expressing TRDMT1-G155V are sensitive to cisplatin in vitro and in vivo. In contrast, high expression of TRDMT1 in patients with ovarian cancer correlates with platinum resistance. A potent TRDMT1 inhibitor resensitizes TRDMT1-high tumor cells to cisplatin. These results suggest that TRDMT1 is a promising therapeutic target to sensitize ovarian tumors to platinum therapy.

Molecular profiling of gliomas is vital to ensure diagnostic accuracy, inform prognosis, and identify clinical trial options for primary and recurrent tumors. This study aimed to determine the accuracy of reporting the whole arm 1p19q codeletion status from the FoundationOne platform.

Testing was performed on glioma samples as part of clinical care and analyzed up to 395 cancer-associated genes (including

). The whole arm 1p19q codeletion status was predicted from the same assay using a custom research-use only algorithm, which was validated using 463 glioma samples with available fluorescence in-situ hybridization (FISH) data. For 519 patients with available outcomes data, progression-free and overall survival were assessed based on whole arm 1p19q codeletion status derived from sequencing data.

Concordance between 1p19q status based on FISH and our algorithm was 96.7% (449/463) with a positive predictive value (PPV) of 100% and a positive percent agreement (PPA) of 91.0%. All discordant samples were positive for codeletion by FISH and harbored genomic alterations inconsistent with oligodendrogliomas. Median overall survival was 168 months for the

mutant, codeleted group, and 122 months for

mutant-only (hazard ratio (HR) 0.42;

< .05).

1p19q codeletion status derived from FoundationOne testing is highly concordant with FISH results. Genomic profiling may be a reliable substitute for traditional FISH testing while also providing

status.

1p19q codeletion status derived from FoundationOne testing is highly concordant with FISH results. read more Genomic profiling may be a reliable substitute for traditional FISH testing while also providing IDH1/2 status.Chromosome conformation capture (3C) technologies measure the interaction frequency between pairs of chromatin regions within the nucleus in a cell or a population of cells. Some of these 3C technologies retrieve interactions involving non-contiguous sets of loci, resulting in sparse interaction matrices. One of such 3C technologies is Promoter Capture Hi-C (pcHi-C) that is tailored to probe only interactions involving gene promoters. As such, pcHi-C provides sparse interaction matrices that are suitable to characterize short- and long-range enhancer-promoter interactions. Here, we introduce a new method to reconstruct the chromatin structural (3D) organization from sparse 3C-based datasets such as pcHi-C. Our method allows for data normalization, detection of significant interactions and reconstruction of the full 3D organization of the genomic region despite of the data sparseness. Specifically, it builds, with as low as the 2-3% of the data from the matrix, reliable 3D models of similar accuracy of those based on dense interaction matrices. Furthermore, the method is sensitive enough to detect cell-type-specific 3D organizational features such as the formation of different networks of active gene communities.Pathological images are easily accessible data with the potential of prognostic biomarkers. Moreover, integration of heterogeneous data types from multi-modality, such as pathological image and gene expression data, is invaluable to help predicting cancer patient survival. However, the analytical challenges are significant. Here, we take the hepatocellular carcinoma (HCC) pathological image features extracted by CellProfiler, and apply them as the input for Cox-nnet, a neural network-based prognosis prediction model. We compare this model with the conventional Cox proportional hazards (Cox-PH) model, CoxBoost, Random Survival Forests and DeepSurv, using C-index and log-rank P-values. The results show that Cox-nnet is significantly more accurate than Cox-PH and Random Survival Forests models and comparable with CoxBoost and DeepSurv models, on pathological image features. Further, to integrate pathological image and gene expression data of the same patients, we innovatively construct a two-stage Cox-nnet model, and compare it with another complex neural-network model called PAGE-Net.