Zhang Yaping, Chen Feng, Cao Jiasheng, Asbun Domenech, Chan Kai Siang, Ramia Jose M, Xiao Dongju, Fang Jun, Shen Jiliang
Department of Anesthesiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Department of Breast Surgery, Zhejiang Cancer Hospital, Hangzhou, China.
Gland Surg. 2025 Mar 31;14(3):479-487. doi: 10.21037/gs-2024-550. Epub 2025 Mar 25.
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.
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.
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 (cm) = 52.40 × BSA (m) - 21.33 (R=0.384).
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.
许多疾病中都有胰腺体积变化的报道。在临床实践中，胰腺病变（如肿瘤、囊肿或胰腺炎）患者的疾病前全胰腺体积（TPV）往往无法获取，因为之前可能没有影像学检查，或者之前的影像学检查可能反映的是异常体积。虽然三维（3D）计算机断层扫描（CT）重建可提供准确的TPV测量值，但在这些情况下其应用有限，因此需要一个预测公式。然而，目前尚无广泛临床接受的标准胰腺体积（SPV）公式。本研究旨在基于3D CT重建和中国成年人的特征开发一个SPV预测公式。
通过CT 3D重建估计获得377名中国成年人的TPV，其中287名用于构建公式，90名用于验证公式。采用Pearson相关分析评估年龄、性别、体重、身高、体重指数（BMI）和体表面积（BSA）与TPV的相关性。采用逐步多元线性回归分析确定可预测TPV的独立相关因素。
年龄、性别、体重、身高、BMI和BSA与TPV显著相关。此外，逐步多元线性回归显示，BSA是TPV的唯一独立相关因素。因此，在以下计算SPV的公式中使用BSA作为因素：SPV（cm）=52.40×BSA（m）-21.33（R=0.384）。
我们创建了一个基于BSA的公式来预测中国成年人的SPV。它可用于评估糖尿病或其他胰腺疾病患者的胰腺体积变化。
