Gland surgery · 2025
Development and validation of a new formula to predict standard pancreas volume in Chinese adults using body surface area.
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Zhang Yaping, Chen Feng, Cao Jiasheng, Asbun Domenech, Chan Kai Siang, Ramia Jose M, Xiao Dongju, Fang Jun, Shen Jiliang
Аннотация
BACKGROUND: Changes in pancreas volume have been reported in many disorders. In clinical practice, pre-disease total pancreas volume (TPV) is often unavailable for patients with pancreatic pathologies (e.g., tumors, cysts, or pancreatitis), as prior imaging may not exist or may reflect abnormal volumes. While three-dimensional (3D) computed tomography (CT) reconstruction provides accurate TPV measurements, its utility is limited in these scenarios, necessitating a predictive formula. However, no widely clinically accepted standard pancreas volume (SPV) formula currently exists. This study aims to develop an SPV prediction formula based on 3D CT reconstruction and the characteristics of Chinese adults.
METHODS: The TPV of 377 Chinese adults were obtained via CT 3D reconstruction estimation, 287 of whom were used to construct the formula and 90 of whom were used to validate the formula. The associations of age, gender, weight, height, body mass index (BMI), and body surface area (BSA) with TPV were assessed using Pearson correlation analysis. Stepwise multiple linear regression analysis was used to identify the independent correlation factors that could predict TPV.
RESULTS: Age, gender, weight, height, BMI, and BSA significantly correlated with TPV. In addition, stepwise multiple linear regression showed that BSA was the only independent correlation factor for TPV. Therefore, BSA was used as the factor in the following formula for calculating SPV: SPV (cm3) = 52.40 × BSA (m2) - 21.33 (R2=0.384).
CONCLUSIONS: We created a BSA-based formula to predict SPV in Chinese adults. It can be used to evaluate pancreas volume changes in patients with diabetes or other pancreatic diseases.
METHODS: The TPV of 377 Chinese adults were obtained via CT 3D reconstruction estimation, 287 of whom were used to construct the formula and 90 of whom were used to validate the formula. The associations of age, gender, weight, height, body mass index (BMI), and body surface area (BSA) with TPV were assessed using Pearson correlation analysis. Stepwise multiple linear regression analysis was used to identify the independent correlation factors that could predict TPV.
RESULTS: Age, gender, weight, height, BMI, and BSA significantly correlated with TPV. In addition, stepwise multiple linear regression showed that BSA was the only independent correlation factor for TPV. Therefore, BSA was used as the factor in the following formula for calculating SPV: SPV (cm3) = 52.40 × BSA (m2) - 21.33 (R2=0.384).
CONCLUSIONS: We created a BSA-based formula to predict SPV in Chinese adults. It can be used to evaluate pancreas volume changes in patients with diabetes or other pancreatic diseases.