Machine Learning Algorithms Utilizing Quantitative CT Features May Predict Eventual Onset of Bronchiolitis Obliterans Syndrome After Lung Transplantation

Article ID	Journal	Published Year	Pages	File Type
8820836	Academic Radiology	2018	12 Pages	PDF

Abstract

ML utilizing qCT could discern distinct mechanisms driving FEV1 decline in BOS and non-BOS LTx patients and predict eventual onset of BOS. This approach may become useful to optimize management of LTx patients.

Keywords

FEV1 FRC BOS TLC QCT LTX FRI Quantitative CT chronic lung allograft dysfunction Forced Expiratory Volume in the first second Bronchiolitis obliterans syndrome Functional residual capacity Total lung capacity Computer-assisted image processing CLAD Lung transplantation

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Health Sciences Medicine and Dentistry Radiology and Imaging

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Machine Learning Algorithms Utilizing Quantitative CT Features May Predict Eventual Onset of Bronchiolitis Obliterans Syndrome After Lung Transplantation

Authors

Eduardo J. Mortani MD, Maarten MSc, Wim PhD, Cedric PhD, William MD, PhD, Jan PhD, James MD,