Expanded genetic screening panel for the Ashkenazi Jewish population.

PURPOSE: Carrier screening programs that identify the presence of known mutations have been effective for reducing the incidence of autosomal recessive conditions in the Ashkenazi Jewish (AJ) population and other populations. Yet, these programs have not realized their full potential. Furthermore, many known autosomal recessive and dominant conditions are not screened for and the molecular basis of other conditions for which screening might be offered is unknown. METHODS: Through literature review and annotation of full sequenced genomes from healthy individuals, we expanded the list of mutations. Mutations were identified in a sample of 128 fully sequenced AJ genomes that were filtered through clinical databases and curated manually for clinical validity and utility using the American College of Medical Genetics and Genomics scoring (ACMG) system. Other known mutations were identified through literature review. RESULTS: A panel of 163 mutations was identified for 76 autosomal recessive, 24 autosomal dominant, and 3 X-linked disorders. CONCLUSION: Screening for a broader range of disorders not only could further reduce the incidence of autosomal recessive disorders but also could offer the benefits of early or presymptomatic diagnosis.Genet Med 18 5, 522-528.

MISM: A Medical Image Segmentation Metric for Evaluation of Weak Labeled Data.

Performance measures are an important tool for assessing and comparing different medical image segmentation algorithms. Unfortunately, the current measures have their weaknesses when it comes to assessing certain edge cases. These limitations arise when images with a very small region of interest or without a region of interest at all are assessed. As a solution to these limitations, we propose a new medical image segmentation metric: MISm. This metric is a composition of the Dice similarity coefficient and the weighted specificity. MISm was investigated for definition gaps, an appropriate scoring gradient, and different weighting coefficients used to propose a constant value. Furthermore, an evaluation was performed by comparing the popular metrics in the medical image segmentation and MISm using images of magnet resonance tomography from several fictitious prediction scenarios. Our analysis shows that MISm can be applied in a general way and thus also covers the mentioned edge cases, which are not covered by other metrics, in a reasonable way. In order to allow easy access to MISm and therefore widespread application in the community, as well as reproducibility of experimental results, we included MISm in the publicly available evaluation framework MISeval.

Intravenous administration of magnesium and potassium solution lowers energy levels and increases success rates electrically cardioverting atrial fibrillation.

BACKGROUND: External biphasic electrical cardioversion (CV) is a standard treatment option for patients suffering from acute symptoms of atrial fibrillation (AF). Nevertheless, CV is not always successful, and thus strategies to increase the success rate are desirable. OBJECTIVE: The purpose of this study was to evaluate the effect of intravenously administered K/Mg solution on the biphasic CV energy threshold and success rate to restore sinus rhythm (SR) in patients with AF. METHODS: The study consisted of 170 patients with persistent AF. The patients were randomly assigned to undergo biphasic CV either with (n = 84) or without (n = 86) pretreatment with K/Mg solution. An energy step-up protocol of 75, 100, and 150 W (J) was used. RESULTS: Biphasic CV of AF was effective in 81 (96.4%) patients in the pretreatment and 74 (86.0%) patients in the control group (P = 0.005). The effective energy level required to achieve SR was significantly lower in the pretreated group (140.8 ± 26.9 J vs 182.5 ± 52.2 J, P = 0.02). No K/Mg-solution-associated side effects such as hypotension or bradycardia were observed. CONCLUSION: Administration of K/Mg solution positively influences the success rate of CV in patients with persistent AF. Furthermore, significantly less energy is required to successfully restore SR and therefore K/Mg pretreatment may facilitate SR restoration in patients undergoing CV for AF.

MISeval: A Metric Library for Medical Image Segmentation Evaluation.

Correct performance assessment is crucial for evaluating modern artificial intelligence algorithms in medicine like deep-learning based medical image segmentation models. However, there is no universal metric library in Python for standardized and reproducible evaluation. Thus, we propose our open-source publicly available Python package MISeval: a metric library for Medical Image Segmentation Evaluation. The implemented metrics can be intuitively used and easily integrated into any performance assessment pipeline. The package utilizes modern DevOps strategies to ensure functionality and stability. MISeval is available from PyPI (miseval) and GitHub: https://github.com/frankkramer-lab/miseval.

COVID-19 Image Segmentation Based on Deep Learning and Ensemble Learning.

Medical imaging offers great potential for COVID-19 diagnosis and monitoring. Our work introduces an automated pipeline to segment areas of COVID-19 infection in CT scans using deep convolutional neural networks. Furthermore, we evaluate the performance impact of ensemble learning techniques (Bagging and Augmenting). Our models showed highly accurate segmentation results, in which Bagging achieved the highest dice similarity coefficient.

Assessing risk for Mendelian disorders in a Bronx population.

BACKGROUND: To identify variants likely responsible for Mendelian disorders among the three major ethnic groups in the Bronx that might be useful to include in genetic screening panels or whole exome sequencing filters and to estimate their likely prevalence in these populations. METHODS: Variants from a high-density oligonucleotide screen of 192 members from each of the three ethnic-national populations (African Americans, Puerto Ricans, and Dominicans) were evaluated for overlap with next generation sequencing data. Variants were curated manually for clinical validity and utility using the American College of Medical Genetics (ACMG) scoring system. Additional variants were identified through literature review. RESULTS: A panel of 75 variants displaying autosomal dominant, autosomal recessive, autosomal recessive/digenic recessive, X-linked recessive, and X-linked dominant inheritance patterns representing 39 Mendelian disorders were identified among these populations. CONCLUSION: Screening for a broader range of disorders could offer the benefits of early or presymptomatic diagnosis and reproductive choice.

Prediction of diffusion coefficients in porous media using tortuosity factors based on interfacial areas.

Determination of aqueous phase diffusion coefficients of solutes through porous media is essential for understanding and modeling contaminant transport. Prediction of diffusion coefficients in both saturated and unsaturated zones requires knowledge of tortuosity and constrictivity factors. No methods are available for the direct measurement of these factors, which are empirical in their definition. In this paper, a new definition for the tortuosity factor is proposed, as the real to ideal interfacial area ratio. We define the tortuosity factor for saturated porous media (tau5) as the ratio S/S(o) (specific surface of real porous medium to that of an idealized capillary bundle). For unsaturated media, tortuosity factor (tau(a)) is defined as a(aw)/a(aw),o (ratio of the specific air-water interfacial area of real and the corresponding idealized porous medium). This tortuosity factor is suitably measured using sorptive tracers (e.g., nitrogen adsorption method) for saturated media and interfacial tracers for unsaturated media. A model based on this new definition of tortuosity factors, termed the interfacial area ratio (IAR) model, is presented for the prediction of diffusion coefficients as a function of the degree of water saturation. Diffusion coefficients and diffusive resistances measured in a number of saturated and unsaturated granular porous media, for solutes in dilute aqueous solutions, agree well with the predictions of the IAR model. A comparison of permeability of saturated sands estimated based on tau(s) and the same based on the Kozeny-Carman equation confirm the usefulness of the tau(s) parameter as a measure of tortuosity.