← 返回

人工智能驱动的手术切除胰腺癌免疫表型空间分析

英文原题:Artificial Intelligence-Powered Spatial Analysis of Immune Phenotypes in Resected Pancreatic Cancer.

查看英文原题

Artificial Intelligence-Powered Spatial Analysis of Immune Phenotypes in Resected Pancreatic Cancer.

PubMed 2025/08/01(内容时间) JAMA Surg Q1 · IF 15.6(JCR 2025)

分数与星级只用于站内排序 —— 不代表疗效、安全性或个人适用性。

研究概要

本队列研究结果表明,AI 的使用显著压缩了 TIL 评估这一劳动密集型流程,可能使该流程在临床应用中更具可行性和实用性。重要的是,IP 可能是切除后 PDAC 中最重要的预后生物标志物之一。

研究思路结论见上方概要

尽管TIL(肿瘤浸润淋巴细胞)(TILs)已被认为在多种恶性肿瘤中可作为预后生物标志物,但其临床应用仍面临挑战。本研究评估了人工智能(AI)驱动的TIL密度空间映射在切除胰腺导管腺癌(PDAC)预后评估中的适用性。

评估AI驱动的空间TIL分析在已切除PDAC中的预后意义及其临床适用性。设计、环境,

本队列研究纳入了2017年1月至2020年12月期间在三级转诊中心接受初始R0切除的PDAC患者。对回顾性纳入的接受初始R0切除的PDAC患者的全切片图像进行了分析。使用AI驱动的全切片图像分析仪进行空间TIL定量、肿瘤和间质分割,并将免疫表型分类为免疫炎症型、免疫排斥型或免疫荒漠型。研究数据于2017年1月至2023年8月进行分析。在切除的PDAC中使用AI驱动的肿瘤微环境空间分析。识别了肿瘤微环境相关风险因素及其与总生存期(OS)和无复发生存期(RFS)结局的关联。

在304例患者中,平均(SD)年龄为66.8(9.4)岁,男性患者171例(56.3%),术前临床分期为I期和II期的患者分别占54.3%(165/304)和45.7%(139/304)。肿瘤微环境中的TILs主要集中于间质,瘤内TIL和间质TIL密度的中位数分别为100.64/mm2(IQR,53.25-121.39/mm2)和734.88/mm2(IQR,443.10-911.16/mm2)。总体而言,9.9%的肿瘤(30/304)为免疫炎症型,85.2%(259/304)为免疫排斥型,4.9%(15/304)为免疫荒漠型。免疫炎症型表型与最长的OS(中位数未达到;P < .001)和RFS(中位数未达到;P = .001)相关,其次为免疫排斥型表型和免疫荒漠型表型。高瘤内TIL密度与更长的OS(中位数,52.47个月;95% CI,41.98-62.96;P = .004)和RFS(中位数,21.67个月;95% CI,14.43-28.91;P = .02)相关。将病理分期与免疫表型联合分析可预测,被分层为免疫炎症型表型的II期PDAC患者,其生存优于被分层为非免疫炎症型表型的I期PDAC患者。

展开英文摘要原文

Although tumor-infiltrating lymphocytes (TILs) have been implicated as prognostic biomarkers across various malignancies, the clinical application remains challenging. This study evaluated the applicability of artificial intelligence (AI)-powered spatial mapping of TIL density for prognostic assessment in resected pancreatic ductal adenocarcinoma (PDAC).

To evaluate the prognostic significance of AI-powered spatial TIL analysis in resected PDAC and its clinical applicability. DESIGN, SETTING, AND PARTICIPANTS: This cohort study included patients with PDAC who underwent up-front R0 resection at a tertiary referral center between January 2017 and December 2020. Whole-slide images of retrospectively enrolled patients with PDAC and up-front R0 resection were analyzed. An AI-powered whole-slide image analyzer was used for spatial TIL quantification, segmentation of tumor and stroma, and immune phenotype classification as immune-inflamed phenotype, immune-excluded phenotype, or immune-desert phenotype. Study data were analyzed from January 2017 to August 2023. EXPOSURE: Use of AI-powered spatial analysis of the tumor microenvironment in resected PDACs. MAIN OUTCOMES AND MEASURES: Tumor microenvironment-related risk factors and their associations with overall survival (OS) and recurrence-free survival (RFS) outcomes were identified.

Among 304 patients, the mean (SD) age was 66.8 (9.4) years with 171 male patients (56.3%), and preoperative clinical stages I and II were represented by 54.3% patients (165 of 304) and 45.7% patients (139 of 304), respectively. The TILs in the tumor microenvironment were predominantly concentrated in the stroma, and the median intratumoral TIL and stromal TIL densities were 100.64/mm2 (IQR, 53.25-121.39/mm2) and 734.88/mm2 (IQR, 443.10-911.16/mm2), respectively. Overall, 9.9% of tumors (30 of 304) were immune inflamed, 85.2% (259 of 304) were immune excluded, and 4.9% (15 of 304) were immune desert. The immune-inflamed phenotype was associated with the most prolonged OS (median not reached; P < .001) and RFS (median not reached; P = .001), followed by immune-excluded phenotype and immune-desert phenotype. High intratumoral TIL density was associated with longer OS (median, 52.47 months; 95% CI, 41.98-62.96; P = .004) and RFS (median, 21.67 months; 95% CI, 14.43-28.91; P = .02). A combined analysis of the pathologic stage with immune phenotype predicted better survival of stage II PDAC stratified as immune-inflamed phenotype than stage I PDAC stratified as non-immune-inflamed phenotype.

Results of this cohort study suggest that the use of AI has markedly condensed the labor-intensive process of TIL assessment, potentially rendering the process more feasible and practical in clinical application. Importantly, the IP may be one of the most important prognostic biomarkers in resected PDACs.

论文信息

作者
Kim H、Choi JH、Lim Y、Yoon SJ、Jang KT、Ock CY、Choi YH、Joe C
单位
Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.South Korea
期刊
JAMA surgery2025 Aug 1
原文标识
PubMed 40560550 · DOI 10.1001/jamasurg.2025.1999