Affiliation:
1. Department of Biomedical Engineering, College of Engineering Texas A&M University College Station Texas USA
2. Department of Nutrition, College of Agriculture and Life Sciences Texas A&M University College Station Texas USA
3. Department of Medical Physiology, School of Medicine Texas A&M Health Science Center Bryan Texas USA
4. Department of Cardiovascular Science Houston Methodist Academic Institute Houston Texas USA
Abstract
AbstractSince every biological system requires capillaries to support its oxygenation, design of engineered preclinical models of such systems, for example, vascularized microphysiological systems (vMPS) have gained attention enhancing the physiological relevance of human biology and therapies. But the physiology and function of formed vessels in the vMPS is currently assessed by non‐standardized, user‐dependent, and simple morphological metrics that poorly relate to the fundamental function of oxygenation of organs. Here, a chained neural network is engineered and trained using morphological metrics derived from a diverse set of vMPS representing random combinations of factors that influence the vascular network architecture of a tissue. This machine‐learned algorithm outputs a singular measure, termed as vascular network quality index (VNQI). Cross‐correlation of morphological metrics and VNQI against measured oxygen levels within vMPS revealed that VNQI correlated the most with oxygen measurements. VNQI is sensitive to the determinants of vascular networks and it consistently correlates better to the measured oxygen than morphological metrics alone. Finally, the VNQI is positively associated with the functional outcomes of cell transplantation therapies, shown in the vascularized islet‐chip challenged with hypoxia. Therefore, adoption of this tool will amplify the predictions and enable standardization of organ‐chips, transplant models, and other cell biosystems.
Funder
National Heart, Lung, and Blood Institute
National Science Foundation
American Heart Association
Subject
Pharmaceutical Science,Biomedical Engineering,Biotechnology
Cited by
1 articles.
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