Li Jiazheng, Chen Zifan, Wang Yinkui, Chen Heyun, Dong Bin, Li Ziyu, Tang Lei
Department of Radiology, Peking University Cancer Hospital and Institute, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Beijing, China.
Center for Big Data, Peking University, Beijing, China.
Abdom Radiol (NY). 2025 Sep 9. doi: 10.1007/s00261-025-05187-1.
This study aimed to evaluate whether different tumour response assessment methods yield inconsistent results following neoadjuvant chemotherapy (NACT) in patients with gastric cancer and to identify the methods most strongly associated with pathological response and prognosis.
This study included 217 patients with gastric cancer who underwent NACT. Tumour volume, area, and thickness were measured on baseline and post-treatment computed tomography (CT) scans. Reduction rates (%Δ measurement) for each parameter were calculated, and the concordance between different %Δ measurements was assessed. Tumour regression grade (TRG) and overall survival (OS) data were recorded, and the predictive performance of the assessment methods was evaluated.
The concordance between different %Δ measurements ranged from fair to moderate (κ = 0.26-0.50), with 24.88-36.87% of patients showing discordant treatment response assessments across methods. The area under the curve (AUC) values for distinguishing pathological responders from non-responders were 0.70 for %Δ volume, 0.75 for %Δ area, and 0.67 for %Δ thickness. For OS prediction, the c-index values were 0.60 for %Δ volume, 0.59 for %Δ area, and 0.54 for %Δ thickness. Additionally, discrepancies were observed between %Δ measurements and TRG. Both %Δ volume and %Δ area were effective in stratifying OS in patients with TRG 2-3.
Tumour response assessment methods showed discordance across different measurements, with volumetric and planimetric measurements offering superior accuracy than linear measurements in predicting both pathological response and OS. Additionally, %Δ volume and %Δ area were effective in stratifying OS in patients with TRG 2-3.
本研究旨在评估在胃癌患者新辅助化疗(NACT)后,不同的肿瘤反应评估方法是否会产生不一致的结果,并确定与病理反应和预后关联最强的方法。
本研究纳入了217例行NACT的胃癌患者。在基线和治疗后的计算机断层扫描(CT)上测量肿瘤体积、面积和厚度。计算每个参数的缩小率(%Δ测量值),并评估不同%Δ测量值之间的一致性。记录肿瘤退缩分级(TRG)和总生存期(OS)数据,并评估评估方法的预测性能。
不同%Δ测量值之间的一致性从中等到一般(κ = 0.26 - 0.50),24.88% - 36.87%的患者在不同方法间显示出不一致的治疗反应评估。区分病理反应者与无反应者的曲线下面积(AUC)值,%Δ体积为0.70,%Δ面积为0.75,%Δ厚度为0.67。对于OS预测,%Δ体积的c指数值为0.60,%Δ面积为0.59,%Δ厚度为0.54。此外,在%Δ测量值和TRG之间观察到差异。%Δ体积和%Δ面积在对TRG 2 - 3级患者的OS进行分层方面均有效。
肿瘤反应评估方法在不同测量中显示出不一致性,在预测病理反应和OS方面,体积测量和平面测量比线性测量具有更高的准确性。此外,%Δ体积和%Δ面积在对TRG 2 - 3级患者的OS进行分层方面有效。