Noreen S Siddiqi, Yuan-Mao Lin, Jessica Albuquerque Marques Silva, Gregor Laimer, Peter Schullian, Yannick Scharll, Alexandra M Dunker, Caleb S O'Connor, Kyle A Jones, Kristy K Brock, Reto Bale, Bruno C Odisio, Iwan Paolucci
{"title":"肝动脉与门静脉期CT对结肠转移瘤分割的最小消融边缘量化:双中心回顾性分析。","authors":"Noreen S Siddiqi, Yuan-Mao Lin, Jessica Albuquerque Marques Silva, Gregor Laimer, Peter Schullian, Yannick Scharll, Alexandra M Dunker, Caleb S O'Connor, Kyle A Jones, Kristy K Brock, Reto Bale, Bruno C Odisio, Iwan Paolucci","doi":"10.1097/RCT.0000000000001782","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>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).</p><p><strong>Methods: </strong>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).</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":15402,"journal":{"name":"Journal of Computer Assisted Tomography","volume":" ","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12404250/pdf/","citationCount":"0","resultStr":"{\"title\":\"Minimal Ablative Margin Quantification Using Hepatic Arterial Versus Portal Venous Phase CT for Colorectal Metastases Segmentation: A Dual-center, Retrospective Analysis.\",\"authors\":\"Noreen S Siddiqi, Yuan-Mao Lin, Jessica Albuquerque Marques Silva, Gregor Laimer, Peter Schullian, Yannick Scharll, Alexandra M Dunker, Caleb S O'Connor, Kyle A Jones, Kristy K Brock, Reto Bale, Bruno C Odisio, Iwan Paolucci\",\"doi\":\"10.1097/RCT.0000000000001782\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>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).</p><p><strong>Methods: </strong>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).</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":15402,\"journal\":{\"name\":\"Journal of Computer Assisted Tomography\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2025-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12404250/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computer Assisted Tomography\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/RCT.0000000000001782\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer Assisted Tomography","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/RCT.0000000000001782","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Minimal Ablative Margin Quantification Using Hepatic Arterial Versus Portal Venous Phase CT for Colorectal Metastases Segmentation: A Dual-center, Retrospective Analysis.
Objective: 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).
Methods: 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).
Results: 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).
Conclusions: 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.
期刊介绍:
The mission of Journal of Computer Assisted Tomography is to showcase the latest clinical and research developments in CT, MR, and closely related diagnostic techniques. We encourage submission of both original research and review articles that have immediate or promissory clinical applications. Topics of special interest include: 1) functional MR and CT of the brain and body; 2) advanced/innovative MRI techniques (diffusion, perfusion, rapid scanning); and 3) advanced/innovative CT techniques (perfusion, multi-energy, dose-reduction, and processing).