Iwan Paolucci, Jessica Albuquerque Marques Silva, Yuan-Mao Lin, Alexander Shieh, Anna Maria Ierardi, Gianpaolo Caraffiello, Carlo Gazzera, Kyle A Jones, Paolo Fonio, Reto Bale, Kristy K Brock, Marco Calandri, Bruno C Odisio
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{"title":"经皮肝恶性肿瘤热消融定量消融确认方法:技术见解、临床证据和未来展望。","authors":"Iwan Paolucci, Jessica Albuquerque Marques Silva, Yuan-Mao Lin, Alexander Shieh, Anna Maria Ierardi, Gianpaolo Caraffiello, Carlo Gazzera, Kyle A Jones, Paolo Fonio, Reto Bale, Kristy K Brock, Marco Calandri, Bruno C Odisio","doi":"10.1148/rycan.240293","DOIUrl":null,"url":null,"abstract":"<p><p>Percutaneous image-guided thermal ablation is an established local curative-intent treatment technique for the treatment of primary and secondary malignant liver tumors. Whereas margin assessment after surgical resection can be accomplished with microscopic examination of the resected specimen, margin assessment after percutaneous thermal ablation relies on cross-sectional imaging. The critical measure of technical success is the minimal ablative margin (MAM), defined as the minimum distance between the tumor and the edge of the ablation zone. Traditionally, the MAM has been assessed qualitatively using anatomic landmarks, which has suboptimal accuracy and reproducibility and is prone to operator bias. Consequently, specialized software-based methods have been developed to standardize and automate MAM quantification. In this review, the authors discuss the technical components of such methods, including image acquisition, segmentation, registration, and MAM computation, define the sources of measurement error, describe available software solutions in terms of image processing techniques and modes of integration, and outline the current clinical evidence, which strongly supports the use of such dedicated software. Finally, the authors discuss current logistical and financial barriers to widespread use of ablation confirmation methods as well as potential solutions. <b>Keywords:</b> Ablation Techniques, CT, Image Postprocessing, Liver <i>Supplemental material is available for this article.</i> © RSNA, 2025.</p>","PeriodicalId":20786,"journal":{"name":"Radiology. Imaging cancer","volume":"7 3","pages":"e240293"},"PeriodicalIF":5.6000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantitative Ablation Confirmation Methods in Percutaneous Thermal Ablation of Malignant Liver Tumors: Technical Insights, Clinical Evidence, and Future Outlook.\",\"authors\":\"Iwan Paolucci, Jessica Albuquerque Marques Silva, Yuan-Mao Lin, Alexander Shieh, Anna Maria Ierardi, Gianpaolo Caraffiello, Carlo Gazzera, Kyle A Jones, Paolo Fonio, Reto Bale, Kristy K Brock, Marco Calandri, Bruno C Odisio\",\"doi\":\"10.1148/rycan.240293\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Percutaneous image-guided thermal ablation is an established local curative-intent treatment technique for the treatment of primary and secondary malignant liver tumors. Whereas margin assessment after surgical resection can be accomplished with microscopic examination of the resected specimen, margin assessment after percutaneous thermal ablation relies on cross-sectional imaging. The critical measure of technical success is the minimal ablative margin (MAM), defined as the minimum distance between the tumor and the edge of the ablation zone. Traditionally, the MAM has been assessed qualitatively using anatomic landmarks, which has suboptimal accuracy and reproducibility and is prone to operator bias. Consequently, specialized software-based methods have been developed to standardize and automate MAM quantification. In this review, the authors discuss the technical components of such methods, including image acquisition, segmentation, registration, and MAM computation, define the sources of measurement error, describe available software solutions in terms of image processing techniques and modes of integration, and outline the current clinical evidence, which strongly supports the use of such dedicated software. Finally, the authors discuss current logistical and financial barriers to widespread use of ablation confirmation methods as well as potential solutions. <b>Keywords:</b> Ablation Techniques, CT, Image Postprocessing, Liver <i>Supplemental material is available for this article.</i> © RSNA, 2025.</p>\",\"PeriodicalId\":20786,\"journal\":{\"name\":\"Radiology. Imaging cancer\",\"volume\":\"7 3\",\"pages\":\"e240293\"},\"PeriodicalIF\":5.6000,\"publicationDate\":\"2025-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Radiology. Imaging cancer\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1148/rycan.240293\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiology. Imaging cancer","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1148/rycan.240293","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
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