William B N Weston, Owen A White, Ruby Callister, Nicos Fotiadis, Joshua Shur, S Nahum Goldberg, Edward W Johnston
{"title":"Modeling the involution of microwave liver ablation zones.","authors":"William B N Weston, Owen A White, Ruby Callister, Nicos Fotiadis, Joshua Shur, S Nahum Goldberg, Edward W Johnston","doi":"10.1080/02656736.2025.2525422","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The post-ablation involution of microwave liver ablation zones (AZs) remains poorly understood. This study develops mathematical models to characterize AZ involution and identifies key predictors influencing its dynamics.</p><p><strong>Materials and methods: </strong>Fifty-four patients (mean age 61 ± 10 years (standard deviation), 33 men) underwent microwave liver ablation (MWA) of 76 liver tumors and follow-up contrast enhanced CT (CECT) imaging in this retrospective single-center cohort study. AZs were segmented on intraprocedural post-ablation portal-venous phase CECT and all available subsequent postprocedural follow-up scans, or until local tumor progression (LTP). Volumetric AZ involution was modeled using non-linear regression methods and correlated with initial tumor and ablation parameters.</p><p><strong>Results: </strong>In total, 366 AZ segmentations were performed over median 304 days CECT-follow-up (range 21-741). Involution was best modeled by mono-exponential decay (SSE = 4.64, RMSE = 0.11). AZs shrank to one-third of baseline volume within a year, with a half-life of 158 days. At 6 weeks, relative volume was 0.81 of baseline (95% prediction interval 0.59-1.04, 95% confidence interval 0.80-0.83). Variables with a significant effect on involution included initial tumor diameter (<i>p</i> = 0.03), initial AZ volume (<i>p</i> < 0.01), and tumor:AZ volume ratio (<i>p</i> = 0.04).</p><p><strong>Conclusions: </strong>Microwave ablation zones rapidly involute and stabilize at approximately one-third of their baseline volume within a year. The involution process is best modeled by mono-exponential decay and influenced by the type of tissue ablated. These findings highlight the potential need for predictive models to adjust for involution for follow-up imaging-based margin assessment to optimize accuracy and ablation outcomes.</p>","PeriodicalId":520653,"journal":{"name":"International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group","volume":"42 1","pages":"2525422"},"PeriodicalIF":3.0000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/02656736.2025.2525422","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/16 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The post-ablation involution of microwave liver ablation zones (AZs) remains poorly understood. This study develops mathematical models to characterize AZ involution and identifies key predictors influencing its dynamics.
Materials and methods: Fifty-four patients (mean age 61 ± 10 years (standard deviation), 33 men) underwent microwave liver ablation (MWA) of 76 liver tumors and follow-up contrast enhanced CT (CECT) imaging in this retrospective single-center cohort study. AZs were segmented on intraprocedural post-ablation portal-venous phase CECT and all available subsequent postprocedural follow-up scans, or until local tumor progression (LTP). Volumetric AZ involution was modeled using non-linear regression methods and correlated with initial tumor and ablation parameters.
Results: In total, 366 AZ segmentations were performed over median 304 days CECT-follow-up (range 21-741). Involution was best modeled by mono-exponential decay (SSE = 4.64, RMSE = 0.11). AZs shrank to one-third of baseline volume within a year, with a half-life of 158 days. At 6 weeks, relative volume was 0.81 of baseline (95% prediction interval 0.59-1.04, 95% confidence interval 0.80-0.83). Variables with a significant effect on involution included initial tumor diameter (p = 0.03), initial AZ volume (p < 0.01), and tumor:AZ volume ratio (p = 0.04).
Conclusions: Microwave ablation zones rapidly involute and stabilize at approximately one-third of their baseline volume within a year. The involution process is best modeled by mono-exponential decay and influenced by the type of tissue ablated. These findings highlight the potential need for predictive models to adjust for involution for follow-up imaging-based margin assessment to optimize accuracy and ablation outcomes.