CT-Assessed Body Composition as Predictor of Post-Operative Complications in Lung Cancer Patients
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Clinic of Radiology EOC, Via Tesserete 46, 6900 Lugano, Switzerland
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Faculty of Biomedical Sciences, Università della Svizzera Italiana (USI), Via G.Buffi 13, 6900 Lugano, Switzerland
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Department of Thoracic Surgery, Fondazione IRCCS San Gerardo dei Tintori, 20900 Monza, Italy
4
Department of Oncology and Hemato-Oncology, University of Milan, Via Festa del Perdono 7, 20122 Milan, Italy
*
Author to whom correspondence should be addressed.
Cancers 2026, 18(3), 431; https://doi.org/10.3390/cancers18030431
Submission received: 15 January 2026
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Revised: 27 January 2026
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Accepted: 28 January 2026
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Published: 29 January 2026
(This article belongs to the Special Issue The Emerging Role of Multiplexed Imaging for Cancer Diagnosis and Therapy (2nd Edition))
Simple Summary
Patients with lung cancer can have very different amounts of muscle and body fat, and these differences may affect how well they recover from surgery. Traditional measures like body weight or body mass index do not fully capture these risks. The authors aim to show how routine computed tomography scans taken before surgery can be used to measure muscle and fat more accurately and identify patients who are more likely to develop complications. In particular, low muscle mass, especially when combined with high body fat, increases the risk of breathing problems, longer hospital stays, and poorer long-term outcomes. These findings may help researchers and clinicians to better estimate the surgical risks, to improve patient selection, and to encourage future studies on nutrition, exercise, and personalized care to improve recovery after lung cancer surgery.
Abstract
Body composition, specifically the quantification of skeletal muscle and adipose tissue using preoperative computed tomography (CT) imaging, is a clinically significant predictor of postoperative complications after lung cancer surgery. The main features of CT-derived body composition analysis are: skeletal muscle index, muscle density, adipose tissue quantification and automated or semi-automated segmentation. Low skeletal muscle mass (sarcopenia) independently increases the risk of perioperative complications, including respiratory complications, and is associated with longer hospital length of stay and worse long-term survival. Sarcopenic obesity—characterized by low muscle mass in the context of high adiposity—further elevates complication risk and prolongs recovery. CT-derived measures such as muscle cross-sectional area, muscle density, and adipose tissue distribution (visceral, subcutaneous, and intramuscular) provide more precise risk stratification than BMI alone. Skeletal muscle area and density are inversely correlated with postoperative complications and recurrence risk; patients with lower muscle mass and density experience more adverse outcomes. In men, age and reduced skeletal muscle area are particularly strong predictors of complications after pneumonectomy. Obesity, when not accompanied by sarcopenia or myosteatosis, may confer a survival advantage—the so-called “obesity paradox”—but this protective effect is lost in patients with low muscle mass or poor muscle quality. Systemic inflammation and nutritional status further modulate the impact of body composition on surgical risk. This review highlights the critical role of CT-derived body composition analysis in predicting postoperative outcomes following lung cancer surgery.
