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. 2022 Mar 3;9:773524. doi: 10.3389/fcvm.2022.773524

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Copyright © 2022 Wen, An, Lin, Yang, Jia and Zheng.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Manhattan plots demonstrated the strength of association [–log10 (P-value)] of univariate logistic regression] comparing PCAT radiomics features derived from lesion-based (A) and vessel-based (B) PCAT segmentation against the hemodynamic significance of coronary stenosis. Solid points above the horizontal cutoff line denote features qualified for univariate logistic regression and LASSO-logistic regression, and their corresponding feature names are displayed. LASSO, least absolute shrinkage and selection operator; PCAT, pericoronary adipose tissue.