{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Huang Y"],"funding":["National Science Fund for Distinguished Young Scholars","Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application","National Natural Science Foundation of China","Regional Innovation and Development Joint Fund of National Natural Science Foundation of China"],"pagination":["32"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11803022"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["16(1)"],"pubmed_abstract":["<h4>Objectives</h4>This study investigates the association between baseline CT body composition parameters and clinical outcomes in patients with resectable non-small cell lung cancer (NSCLC).<h4>Methods</h4>Patients who underwent surgical resection for NSCLC between January 2006 and December 2017 were retrospectively enrolled in this multicenter study. Body composition metrics, including the area of skeletal muscle, intermuscular adipose tissue, subcutaneous adipose tissue, visceral adipose tissue, muscle radiodensity, and derivative parameters from five basic metrics mentioned before, were calculated based on preoperative non-contrast-enhanced chest CT images at L1 level. The Cox proportional hazards regression analysis was used to evaluate the association between body composition metric"],"journal":["Insights into imaging"],"pubmed_title":["Multiparameter body composition analysis on chest CT predicts clinical outcomes in resectable non-small cell lung cancer."],"pmcid":["PMC11803022"],"funding_grant_id":["U22A20345","82302131","2022B1212010011","82260338","81925023"],"pubmed_authors":["Jiang Y","Cun H","Liu Z","Huang Y","Du C","Zhu Y","Zhang Z","Luo L","Chen X","Mou Z","Yu Z","He B"],"additional_accession":[]},"is_claimable":false,"name":"Multiparameter body composition analysis on chest CT predicts clinical outcomes in resectable non-small cell lung cancer.","description":"<h4>Objectives</h4>This study investigates the association between baseline CT body composition parameters and clinical outcomes in patients with resectable non-small cell lung cancer (NSCLC).<h4>Methods</h4>Patients who underwent surgical resection for NSCLC between January 2006 and December 2017 were retrospectively enrolled in this multicenter study. Body composition metrics, including the area of skeletal muscle, intermuscular adipose tissue, subcutaneous adipose tissue, visceral adipose tissue, muscle radiodensity, and derivative parameters from five basic metrics mentioned before, were calculated based on preoperative non-contrast-enhanced chest CT images at L1 level. The Cox proportional hazards regression analysis was used to evaluate the association between body composition metric","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Feb","modification":"2025-04-26T01:36:35.562Z","creation":"2025-04-06T10:13:49.737Z"},"accession":"S-EPMC11803022","cross_references":{"pubmed":["39912982"],"doi":["10.1186/s13244-025-01910-0"]}}