This repository includes the following:, - Example Case A: complete process of creating a model, running the simulation and examining the results., - Example Case B: segmenting and imposing a patient-specific aortic inflow velocity profile from a provide PC-MRI dataset., - Example Case C: simulation of a patient under rest conditions, and then of the same patient under post-liver-transplant conditions., - GUI Windows Binary Executable (version 2019.11.01), and - Flow Solver Windows Binary Executable (version 1.4.4, 2019.11.01)
CRIMSON: An Open-Source Software Framework for Cardiovascular Integrated Modelling and Simulation C.J. Arthurs, R. Khlebnikov, A. Melville, M. Marčan, A. Gomez, D. Dillon-Murphy, F. Cuomo, M.S. Vieira, J. Schollenberger, S.R. Lynch, C. Tossas-Betancourt, K. Iyer, S. Hopper, E. Livingston, P. Youssefi, A. Noorani, S. Ben Ahmed, F.J.H. Nauta, T.M.J. van Bakel, Y. Ahmed, P.A.J. van Bakel, J. Mynard, P. Di Achille, H. Gharahi, K. D. Lau, V. Filonova, M. Aguirre, N. Nama, N. Xiao, S. Baek, K. Garikipati, O. Sahni, D. Nordsletten, C.A. Figueroa bioRxiv 2020.10.14.339960; doi: https://doi.org/10.1101/2020.10.14.339960
The search data supports a literature review project on Psychological Functioning in Pediatric Patients with Single Ventricle Congenital Heart Disease. The data included are the reproducible search strategies (txt file) and the exported results of all citations from all databases (txt, ris, and.nbib files). Both the original search files and updated search files have been included in the deposit.
The dataset includes all citations considered for inclusion in the systematic review. The citations are accessible in Endnote (Clarivate), as well as through the primary citation export files from each database. The literature search strategies are included for reproducibility and transparency purposes. See the published methods for more information.
Gordon H. Sun, Stephanie W. Chen, Mark P. MacEachern & Jing Wang (2020) Successful decannulation of patients with traumatic spinal cord injury: A scoping review, The Journal of Spinal Cord Medicine, DOI: 10.1080/10790268.2020.1832397
This data repository includes the quantitative features of high frequency, intracranial EEG along with all necessary scripts to reproduce the figures of the accompanying manuscript.
The search data supports a scoping literature review project on Loss to follow-up barriers in care for Cornea Ulcers and Glaucoma. The data included are the reproducible search strategies (txt file) and the exported results of all citations from all databases (txt, ris, and.nbib files). Both the original search files and updated search files have been included in the deposit.
Data comparing the Simplified Endoscopic Mucosal Assessment for Crohn's Disease (SEMA-CD) from video recordings of colonoscopies to SEMA-CD scoring of their corresponding colonoscopy reports from pediatric patients with Crohn's disease.
The search data supports a literature review project on Strategies to Increase Black Enrollment and Retention in Cancer Clinical Trials. This dataset includes the reproducible search strategies (txt file) and the exported results of all citations from all databases (txt, ris, and.nbib files). These searches and exported result files contain all citations originating from the database searches that were considered for inclusion.
This cross-sectional analysis included 584 participants in the Center for Oral Health Research in Appalachia cohort 1 (COHRA1). We sequenced the V4 region of the 16S rRNA of supragingival plaque from 185 caries-active and 565 caries-free teeth using the Illumina MiSeq platform. Sequences were filtered using the R DADA2 package and assigned taxonomy using the Human Oral Microbiome Database ( http://www.homd.org/).
Current methods for patient-specific voxel-level dosimetry in radionuclide therapy suffer from a trade-off between accuracy and computational efficiency. Monte Carlo (MC) radiation transport algorithms are considered the gold standard for voxel-level dosimetry but can be computationally expensive, whereas faster dose voxel kernel (DVK) convolution can be sub-optimal in the presence of tissue heterogeneities. Furthermore, the accuracies of both these methods are limited by the spatial resolution of the reconstructed emission image. To overcome these limitations, this paper considers a single deep convolutional neural network (CNN) with residual learning (named DblurDoseNet) that learns to produce dose-rate maps while compensating for the limited resolution of SPECT images.
We took the novel approach of constructing a convolutional neural network with residual learning to handle the accuracy-efficiency tradeoff while compensating for the limited resolution of SPECT images. We then test our CNN on clinically relevant phantoms and patients undergoing Lu-177 DOTATATE therapy in our clinic. Our network demonstrated superior results than Monte Carlo, the current gold standard for voxel dosimetry, but only takes a fraction of time. Thus, the DblurDoseNet has the potential for real-time patient-specific dosimetry in clinical treatment planning due to its demonstrated improvement in accuracy, resolution, noise and speed over the DVK/MC approaches.
Matlab is needed to access the phantoms and Python (with Numpy package installed) is needed to access the DVKs.
"DblurDoseNet: A Deep Residual Learning Network for Voxel Radionuclide Dosimetry Compensating for SPECT Imaging Resolution" by Zongyu Li, Jeffrey A. Fessler, Justin K. Mikell, Scott J. Wilderman and Yuni K. Dewaraja. Accepted by Medical Physics, 2021. DOI: 10.1002/mp.15397
The dataset includes all citations considered for inclusion in the literature review. Abstracts and keywords have been removed from the citation file. The citation file was exported in an .RIS format and can be imported with any citation manger such as EndNote, Zotero, Mendeley, RefWorks, etc. The literature search strategies are included for reproducibility and transparency purposes.