ORIGINAL RESEARCH article
Front. Psychiatry
Sec. Schizophrenia
Quantitative computed tomography for assessing body composition in schizophrenia: a potential predictor of insulin resistance
Provisionally accepted
Xinping Kuai
Fangsong ZhangMengyang HanJianye ZhangChanjun DingLili YuanQicheng YuanLei ChenZiyue XuXuexue WangJinhong Wang*- Department of Radiology, Shanghai Mental Health Center, Shanghai, China
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Objective: To investigate the relationship between the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) index and organ body composition, and to evaluate the potential of quantitative computed tomography (QCT) parameters as biomarkers for predicting insulin resistance (IR) in schizophrenia. Materials and Methods: A total of 924 patients with schizophrenia were enrolled and categorized into non-IR (HOMA-IR ≤ 2.5) and IR (HOMA-IR > 2.5) groups. Quantitative computed tomography (QCT) systematically measured parameters such as bone mineral density (BMD), hepatic fat fraction, and areas of subcutaneous adipose tissues (SAT) and visceral adipose tissues (VAT). Univariate and multivariate logistic regression analyses were performed to identify independent predictors of IR. The predictive performance of individual parameters and combined models-including a QCT parameters-only model and a model integrating QCT parameters with clinical covariates (gender, age, BMI)-was evaluated using receiver operating characteristic (ROC) curve analysis. Results: Patients in the IR group (n=332) demonstrated significantly elevated levels of all QCT parameters compared to the non-IR group (n=592): BMD (125.27 vs. 114.01 mg/cm³), liver fat (10.14% vs. 6.61%), SAT (138.55 vs. 82.20 cm²), and VAT (222.83 vs. 131.92 cm²) (all P < 0.001). While all four parameters were significant in univariate analysis, multivariate analysis adjusted for age, sex, and BMI identified VAT (Adjusted OR: 1.013, 95% CI: 1.009–1.016, P < 0.001) and liver fat content (Adjusted OR: 1.092, 95% CI: 1.051–1.135, P < 0.001) as the only independent predictors. The area under the curve (AUC) for individual parameters was 0.790 for VAT, 0.769 for SAT, 0.664 for liver fat, and 0.574 for BMD. The combined QCT parameters-only model achieved an AUC of 0.834, which was significantly improved to 0.852 (P = 0.001 by DeLong's test) after incorporating clinical covariates. Conclusion: Visceral adipose tissue and liver fat content, as measured by QCT, are robust and independent predictors of insulin resistance in patients with schizophrenia. A model combining QCT parameters with basic clinical covariates offers the best predictive performance for identifying IR risk in this population, highlighting the critical role of ectopic fat deposition in metabolic dysregulation.
Keywords: Schizophrenia, Quantitative computed tomography, Insulin Resistance, visceral adipose tissue, subcutaneous adipose tissue
Received: 31 Jul 2025; Accepted: 12 Nov 2025.
Copyright: © 2025 Kuai, Zhang, Han, Zhang, Ding, Yuan, Yuan, Chen, Xu, Wang and Wang. 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) or licensor 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.
* Correspondence: Jinhong Wang, jinhongw2004@smhc.org.cn
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