Development and validation of a new formula to predict standard pancreas volume in Chinese adults using body surface area.

IF 1.5 3区 医学 Q3 SURGERY
Gland surgery Pub Date : 2025-03-31 Epub Date: 2025-03-25 DOI:10.21037/gs-2024-550
Yaping Zhang, Feng Chen, Jiasheng Cao, Domenech Asbun, Kai Siang Chan, Jose M Ramia, Dongju Xiao, Jun Fang, Jiliang Shen
{"title":"Development and validation of a new formula to predict standard pancreas volume in Chinese adults using body surface area.","authors":"Yaping Zhang, Feng Chen, Jiasheng Cao, Domenech Asbun, Kai Siang Chan, Jose M Ramia, Dongju Xiao, Jun Fang, Jiliang Shen","doi":"10.21037/gs-2024-550","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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<sup>3</sup>) = 52.40 × BSA (m<sup>2</sup>) - 21.33 (R<sup>2</sup>=0.384).</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":12760,"journal":{"name":"Gland surgery","volume":"14 3","pages":"479-487"},"PeriodicalIF":1.5000,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12004316/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gland surgery","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/gs-2024-550","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/25 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"SURGERY","Score":null,"Total":0}
引用次数: 0

Abstract

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.

利用体表面积预测中国成人标准胰腺体积的新公式的开发与验证。
背景:胰腺体积的变化在许多疾病中都有报道。在临床实践中,对于患有胰腺病变(如肿瘤、囊肿或胰腺炎)的患者,通常无法获得病前胰腺总体积(TPV),因为先前的成像可能不存在或可能反映异常的体积。虽然三维(3D)计算机断层扫描(CT)重建提供了准确的冠脉pv测量,但其在这些情况下的效用有限,因此需要一个预测公式。然而,目前临床上还没有被广泛接受的标准胰腺体积(SPV)公式。本研究旨在建立基于三维CT重建和中国成年人特征的SPV预测公式。方法:通过CT三维重建估计获得377例中国成年人的冠心pv,其中287例用于构建公式,90例用于验证公式。使用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的关系。采用逐步多元线性回归分析确定预测TPV的独立相关因素。结果:年龄、性别、体重、身高、BMI、BSA与TPV有显著相关。逐步多元线性回归结果表明,BSA是TPV的唯一独立相关因子。因此,以BSA为因子,计算SPV的公式如下:SPV (cm3) = 52.40 × BSA (m2) - 21.33 (R2=0.384)。结论:我们建立了一个基于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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Gland surgery
Gland surgery Medicine-Surgery
CiteScore
3.60
自引率
0.00%
发文量
113
期刊介绍: Gland Surgery (Gland Surg; GS, Print ISSN 2227-684X; Online ISSN 2227-8575) being indexed by PubMed/PubMed Central, is an open access, peer-review journal launched at May of 2012, published bio-monthly since February 2015.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信