Department of Radiology, The Jiangsu Key Laboratory of Molecular and Functional Imaging, Zhongda Hospital, School of Medicine.
School of Instrument Science and Engineering, Southeast University, Nanjing.
Int J Surg. 2024 Feb 1;110(2):740-749. doi: 10.1097/JS9.0000000000000908.
Undetectable occult liver metastases block the long-term survival of pancreatic ductal adenocarcinoma (PDAC). This study aimed to develop a radiomics-based model to predict occult liver metastases and assess its prognostic capacity for survival.
Patients who underwent surgical resection and were pathologically proven with PDAC were recruited retrospectively from five tertiary hospitals between January 2015 and December 2020. Radiomics features were extracted from tumors, and the radiomics-based model was developed in the training cohort using LASSO-logistic regression. The model's performance was assessed in the internal and external validation cohorts using the area under the receiver operating curve (AUC). Subsequently, the association of the model's risk stratification with progression-free survival (PFS) and overall survival (OS) was then statistically examined using Cox regression analysis and the log-rank test.
A total of 438 patients [mean (SD) age, 62.0 (10.0) years; 255 (58.2%) male] were divided into the training cohort ( n =235), internal validation cohort ( n =100), and external validation cohort ( n =103). The radiomics-based model yielded an AUC of 0.73 (95% CI: 0.66-0.80), 0.72 (95% CI: 0.62-0.80), and 0.71 (95% CI: 0.61-0.80) in the training, internal validation, and external validation cohorts, respectively, which were higher than the preoperative clinical model. The model's risk stratification was an independent predictor of PFS (all P <0.05) and OS (all P <0.05). Furthermore, patients in the high-risk group stratified by the model consistently had a significantly shorter PFS and OS at each TNM stage (all P <0.05).
The proposed radiomics-based model provided a promising tool to predict occult liver metastases and had a great significance in prognosis.
无法检测到的隐匿性肝转移阻断了胰腺导管腺癌（PDAC）的长期生存。本研究旨在开发一种基于放射组学的模型来预测隐匿性肝转移，并评估其对生存的预后能力。
回顾性招募了 2015 年 1 月至 2020 年 12 月期间在五家三级医院接受手术切除并经病理证实为 PDAC 的患者。从肿瘤中提取放射组学特征，并使用 LASSO-逻辑回归在训练队列中建立基于放射组学的模型。使用接收者操作特征曲线（AUC）下的面积在内部和外部验证队列中评估模型的性能。随后，使用 Cox 回归分析和对数秩检验统计检验模型的风险分层与无进展生存期（PFS）和总生存期（OS）的相关性。
共纳入 438 例患者[平均（标准差）年龄，62.0（10.0）岁；255（58.2%）例男性]，分为训练队列（n=235）、内部验证队列（n=100）和外部验证队列（n=103）。基于放射组学的模型在训练、内部验证和外部验证队列中的 AUC 分别为 0.73（95%CI：0.66-0.80）、0.72（95%CI：0.62-0.80）和 0.71（95%CI：0.61-0.80），均高于术前临床模型。模型的风险分层是 PFS（均 P<0.05）和 OS（均 P<0.05）的独立预测因素。此外，在每个 TNM 分期中，根据模型分层的高危组患者的 PFS 和 OS 均显著缩短（均 P<0.05）。
提出的基于放射组学的模型为预测隐匿性肝转移提供了一种有前途的工具，对预后具有重要意义。
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