使用卷积神经网络分析人体成分预测胰腺癌胰十二指肠切除术后胰瘘和生存的研究

Body composition analysis using convolutional neural network in predicting postoperative pancreatic fistula and survival after pancreatoduodenectomy for pancreatic cancer.

机构信息

Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.

Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea; Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.

出版信息

Eur J Radiol. 2023 Dec;169:111182. doi: 10.1016/j.ejrad.2023.111182. Epub 2023 Nov 3.

DOI:10.1016/j.ejrad.2023.111182

PMID:37976764

Abstract

PURPOSE

To evaluate whether body composition measurements acquired using convolutional neural networks (CNNs) from preoperative CT images could predict postoperative pancreatic fistula (POPF) and overall survival (OS) after pancreaticoduodenectomy in patients with pancreatic ductal adenocarcinoma (PDAC).

METHODS

257 patients (160 men; median age [interquartile range], 67 [60-74]) who underwent pancreaticoduodenectomy for PDAC between January 2013 and December 2017 were included in this retrospective study. Body composition measurements were based on a CNN trained to segment CT images into skeletal muscle area, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT). Skeletal muscle area, VAT, and SAT were normalized to height square and labeled as skeletal muscle, VAT, and SAT indices, respectively. The independent risk factors for clinically relevant POPF (grade B or C) were determined using a multivariate logistic regression model, and prognostic factors for OS were assessed using Cox proportional hazards regression analyses.

RESULTS

After pancreatioduodenectomy, 27 patients developed POPF grade B or C (10.5 %, 27/257). The VAT index (odds ratio [OR] = 7.43, p < 0.001) was the only independent prognostic factor for POPF grade B or C. During the median follow-up period of 23 months, 205 (79.8 % [205/257]) patients died. For prediction of OS, skeletal muscle index (hazard ratio [HR] = 0.58, p = 0.018) was a significant factor, along with vascular invasion (HR = 1.85, p < 0.001) and neoadjuvant therapy (HR = 0.58, p = 0.011).

CONCLUSIONS

A high VAT index and a low skeletal muscle index can be utilized in predicting the occurrence of POPF grade B or C and poor OS, respectively.

摘要

目的

评估术前 CT 图像卷积神经网络 (CNN) 获得的身体成分测量值是否可预测胰腺导管腺癌 (PDAC) 患者胰十二指肠切除术后的术后胰瘘 (POPF) 和总生存 (OS)。

方法

本回顾性研究纳入 2013 年 1 月至 2017 年 12 月期间因 PDAC 接受胰十二指肠切除术的 257 例患者（男 160 例；中位年龄 [四分位间距]，67 [60-74] 岁）。基于训练 CT 图像分割骨骼肌面积、内脏脂肪组织 (VAT) 和皮下脂肪组织 (SAT) 的 CNN 进行身体成分测量。将骨骼肌面积、VAT 和 SAT 标准化到身高平方，并分别标记为骨骼肌、VAT 和 SAT 指数。使用多变量逻辑回归模型确定与临床相关 POPF（B 或 C 级）的独立危险因素，并使用 Cox 比例风险回归分析评估 OS 的预后因素。

结果

胰十二指肠切除术后，27 例患者发生 B 或 C 级 POPF（10.5%[27/257]）。VAT 指数（比值比 [OR] = 7.43，p < 0.001）是 B 或 C 级 POPF 的唯一独立预后因素。在中位随访 23 个月期间，205 例（79.8%[205/257]）患者死亡。对于 OS 预测，骨骼肌指数（风险比 [HR] = 0.58，p = 0.018）是一个显著因素，与血管侵犯（HR = 1.85，p < 0.001）和新辅助治疗（HR = 0.58，p = 0.011）相关。