Siddiqi Noreen S, Lin Yuan-Mao, Marques Silva Jessica Albuquerque, Laimer Gregor, Schullian Peter, Scharll Yannick, Dunker Alexandra M, O'Connor Caleb S, Jones Kyle A, Brock Kristy K, Bale Reto, Odisio Bruno C, Paolucci Iwan
Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX.
Department of Radiology, Interventional Oncology-Microinvasive Therapy, Medical University Innsbruck, Innsbruck, Austria.
J Comput Assist Tomogr. 2025 Jul 24. doi: 10.1097/RCT.0000000000001782.
To compare the predictive value of minimal ablative margin (MAM) quantification using tumor segmentation on intraprocedural contrast-enhanced hepatic arterial (HAP) versus portal venous phase (PVP) CT on local outcomes following percutaneous thermal ablation of colorectal liver metastases (CRLM).
This dual-center retrospective study included patients undergoing thermal ablation of CRLM with intraprocedural preablation and postablation contrast-enhanced CT imaging between 2009 and 2021. Tumors were segmented in both HAP and PVP CT phases using an artificial intelligence-based auto-segmentation model and reviewed by a trained radiologist. The MAM was quantified using a biomechanical deformable image registration process. The area under the receiver operating characteristic curve (AUROC) was used to compare the prognostic value for predicting local tumor progression (LTP).
Among 81 patients (60 y±13, 53 men), 151 CRLMs were included. During 29.4 months of median follow-up, LTP was noted in 24/151 (15.9%). Median tumor volumes on HAP and PVP CT were 1.7 mL and 1.2 mL, respectively, with respective median MAMs of 2.3 and 4.0 mm (both P< 0.001). The AUROC for 1-year LTP prediction was 0.78 (95% CI: 0.70-0.85) on HAP and 0.84 (95% CI: 0.78-0.91) on PVP (P= 0.002).
During CT-guided percutaneous thermal ablation, MAM measured based on tumors segmented on PVP images conferred a higher predictive accuracy of ablation outcomes among CRLM patients than those segmented on HAP images, supporting the use of PVP rather than HAP images for segmentation during ablation of CRLMs.
比较使用肿瘤分割技术对术中对比增强肝动脉期(HAP)与门静脉期(PVP)CT进行最小消融边缘(MAM)定量分析,在经皮热消融结直肠癌肝转移(CRLM)后局部结局方面的预测价值。
这项双中心回顾性研究纳入了2009年至2021年间接受CRLM热消融且术中进行消融前和消融后对比增强CT成像的患者。使用基于人工智能的自动分割模型在HAP和PVP CT期对肿瘤进行分割,并由一名经过培训的放射科医生进行复查。通过生物力学可变形图像配准过程对MAM进行定量分析。采用受试者操作特征曲线下面积(AUROC)来比较预测局部肿瘤进展(LTP)的预后价值。
在81例患者(年龄60岁±13岁,男性53例)中,共纳入151个CRLM。在中位随访29.4个月期间,24/151(15.9%)出现LTP。HAP和PVP CT上肿瘤体积中位数分别为1.7 mL和1.2 mL,相应的MAM中位数分别为2.3 mm和4.0 mm(均P<0.001)。HAP上预测1年LTP的AUROC为0.78(95%CI:0.70 - 0.85),PVP上为0.84(95%CI:0.78 - 0.91)(P = 0.002)。
在CT引导下经皮热消融过程中,基于PVP图像分割的肿瘤测量的MAM在CRLM患者中对消融结局的预测准确性高于基于HAP图像分割的肿瘤,支持在CRLM消融期间使用PVP而非HAP图像进行分割。