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Article

Quantitative Chest Computed Tomography and Machine Learning for Subphenotyping Small Airways Disease in Long COVID.

Journal of thoracic imaging - 1 Mar 2026

Chate Rodrigo Caruso, Carvalho Carlos Roberto Ribeiro, Sawamura Marcio Valente Yamada, Salge João Marcos, Fonseca Eduardo Kaiser Ururahy Nunes, Amaral Paula Terra Martins Almeida, de Almeida Lamas Celina, de Luna Luis Augusto Visani, Kay Fernando Uliana, Junior Antonildes Nascimento Assunção, Nomura Cesar Higa

Abstract excerpt

PURPOSE: To investigate imaging phenotypes in posthospitalized COVID-19 patients by integrating quantitative CT (QCT) and machine learning (ML), with a focus on small airway disease (SAD) and its correlation with plethysmography. MATERIALS AND METHODS: In this single-center cross-sectional retrospective study, a subanalysis of a larger prospective cohort, 257 adult survivors from the initial COVID-19 peak (mean...

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PMID: 41099164
DOI: 10.1097/RTI.0000000000000861

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 8 Sept 2026.

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