Biology subjects

Knoll, J. H. M.

Publications and source records attributed to Knoll, J. H. M..

4 recordsLinked to original sources

bioRxiv2021

Radiation Exposure Determination in a Secure, Cloud-based Online Environment

Rapid sample processing and interpretation of estimated exposures will be critical for triaging exposed individuals after a major radiation incident. The dicentric chromosome (DC) assay assesses absorbed radiation using metaphase cells from blood. The Automated Dicentric Chromosome Identifier and Dose Estimator System (ADCI) identifies DCs and determines radiation doses. This study aimed to broaden accessibility and speed of this system, while protecting data and software integrity. ADCI Online is a secure web-streaming platform accessible worldwide from local servers. Cloud-based systems containing data and software are separated until they are linked for radiation exposure estimation. Dose estimates are identical to ADCI on dedicated computer hardware. Image processing and selection, calibration curve generation, and dose estimation of 9 test samples completed in <2 days. ADCI Online has the capacity to alleviate analytic bottlenecks in intermediate-to-large radiation incidents. Multiple cloned software instances configured on different cloud environments accelerated dose estimation to within clinically relevant time frames.

bioinformatics↗

bioRxiv2020

Estimating partial body ionizing radiation exposure by automated cytogenetic biodosimetry

PurposeInhomogeneous exposures to ionizing radiation can be detected and quantified with the Dicentric Chromosome Assay (DCA) of metaphase cells. Complete automation of interpretation of the DCA for whole body irradiation has significantly improved throughput without compromising accuracy, however low levels of residual false positive dicentric chromosomes (DCs) have confounded its application for partial body exposure determination. Materials and MethodsWe describe a method of estimating and correcting for false positive DCs in digitally processed images of metaphase cells. Nearly all DCs detected in unirradiated calibration samples are introduced by digital image processing. DC frequencies of irradiated calibration samples and those exposed to unknown radiation levels are corrected subtracting this false positive fraction from each. In partial body exposures, the fraction of cells exposed, and radiation dose can be quantified after applying this modification of the contaminated Poisson method. ResultsDose estimates of three partially irradiated samples diverged 0.2 to 2.5 Gy from physical doses and irradiated cell fractions deviated by 2.3-15.8% from the known levels. Synthetic partial body samples comprised of unirradiated and 3 Gy samples from 4 laboratories were correctly discriminated as inhomogeneous by multiple criteria. Root mean squared errors of these dose estimates ranged from 0.52 to 1.14 Gy2 and from 8.1 to 33.3%2 for the fraction of cells irradiated. ConclusionsAutomated DCA can differentiate whole-from partial-body radiation exposures and provides timely quantification of estimated whole-body equivalent dose. Biographical NoteBen Shirley M.Sc. is Chief Software Architect, CytoGnomix Inc. Canada; Joan Knoll Ph.D. Dipl.ABMGG, FCCMG is Professor in Pathology and Laboratory Medicine, Schulich School of Medicine and Dentistry, University of Western Ontario, Canada and cofounder, CytoGnomix Inc.; Jayne Moquet Ph.D. is Principal Radiation Protection Scientist in the Cytogenetics Group, Public Health England; Elizabeth Ainsbury Ph.D. is Head, Cytogenetics Group and the Chromosome Dosimetry Service, Public Health England; Pham Ngoc Duy M.Sc. is deputy director of Biotechnology Center, Dalat Nuclear Research Institute, Vietnam; Farrah Norton M.Sc.is Research Scientist and Lead of the Biodosimetry emergency response and research capability at Canadian Nuclear Laboratories; Ruth Wilkins, Ph.D. is Research Scientist and Chief of the Ionizing Radiation Health Sciences Division at Health Canada, Ontario, Canada; and Peter K. Rogan Ph.D. is Professor of Biochemistry and Oncology, Schulich School of Medicine and Dentistry, University of Western Ontario, Canada, and President, CytoGnomix Inc.

genetics↗

bioRxiv2019

Automated Cytogenetic Biodosimetry at Population-Scale

IntroductionThe dicentric chromosome (DC) assay accurately quantifies exposure to radiation, however manual and semi-automated assignment of DCs has limited its use for a potential large-scale radiation incident. The Automated Dicentric Chromosome Identifier and Dose Estimator Chromosome (ADCI) software automates unattended DC detection and determines radiation exposures, fulfilling IAEA criteria for triage biodosimetry. We present high performance ADCI (ADCI-HT), with the requisite throughput to stratify exposures of populations in large scale radiation events.\n\nMethodsADCI-HT streamlines dose estimation by optimal scheduling of DC detection, given that the numbers of samples and metaphase cell images in each sample vary. A supercomputer analyzes these data in parallel, with each processor handling a single image at a time. Processor resources are managed hierarchically to maximize a constant stream of sample and image analysis. Metaphase data from populations of individuals with clinically relevant radiation exposures after simulated large nuclear incidents were analyzed. Sample counts were derived from US Census data. Analysis times and exposures were quantified for 15 different scenarios.\n\nResultsProcessing of metaphase images from 1,744 samples (500 images each) used 16,384 CPUs and was completed in 1hr 11min 23sec, with radiation dose of all samples determined in 32 sec with 1,024 CPUs. Processing of 40,000 samples with varying numbers of metaphase cells, 10 different exposures from 5 different biodosimetry labs met IAEA accuracy criteria (dose estimate differences were < 0.5 Gy; median = 0.07) and was completed in ~25 hours. Population-scale metaphase image datasets within radiation contours of nuclear incidents were defined by exposure levels (either >1 Gy or >2 Gy). The time needed to analyze samples of all individuals receiving exposures from a high yield airborne nuclear device ranged from 0.6-7.4 days, depending on the population density.\n\nConclusionADCI-HT delivers timely and accurate dose estimates in a simulated population-scale radiation incident.

bioinformatics↗

bioRxiv2017

Accurate Cytogenetic Biodosimetry Through Automation Of Dicentric Chromosome Curation And Metaphase Cell Selection

Software to automate digital pathology relies on image quality and the rates of false positive and negative objects in these images. Cytogenetic biodosimetry detects dicentric chromosomes (DCs) that arise from exposure to ionizing radiation, and determines radiation dose received from the frequency of DCs. We present image segmentation methods to rank high quality cytogenetic images and eliminate suboptimal metaphase cell data based on novel quality measures. Improvements in DC recognition increase the accuracy of dose estimates, by reducing false positive (FP) DC detection. A set of chromosome morphology segmentation methods selectively filtered out false DCs, arising primarily from extended prometaphase chromosomes, sister chromatid separation and chromosome fragmentation. This reduced FPs by 55% and was highly specific to the abnormal structures ([≥]97.7%). Additional procedures were then developed to fully automate image review, resulting in 6 image-level filters that, when combined, selectively remove images with consistently unparsable or incorrectly segmented chromosome morphologies. Overall, these filters can eliminate half of the FPs detected by manual image review. Optimal image selection and FP DCs are minimized by combining multiple feature based segmentation filters and a novel image sorting procedure based on the known distribution of chromosome lengths. Applying the same segmentation filtering procedures to both calibration and test sample image data reduced the average dose estimation error from 0.4Gy to <0.2Gy, obviating the need to first manually review these images. This reliable and scalable solution enables batch processing multiple samples of unknown dose, and meets current requirements for triage radiation biodosimetry of high quality metaphase cell preparations.

genetics↗