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The ground-truth, or percent tumor coverage, was determined based on the result of semi-automatic 3D tumor and ablation zone segmentation and elastic registration. The isocenter of the tumor and ablation was isolated on 2D axial CT images. Feature extraction was performed, and classification and linear regression models were built. Images were augmented, and 728 image pairs were used for training and testing. The estimated percent tumor coverage using the models was compared to ground-truth. Validation was performed on eight patient cases from a separate institution, where RFA was performed, and pre- and post-ablation images were collected.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>In testing cohorts, the best model accuracy was with classification and moderate data augmentation (AUC\u2009=\u20090.86, TPR\u2009=\u20090.59, and TNR\u2009=\u20090.89, accuracy\u2009=\u200969%) and regression with random forest (RMSE\u2009=\u200912.6%, MAE\u2009=\u20099.8%). Validation in a separate institution did not achieve accuracy greater than random estimation. Visual review of training cases suggests that poor tumor coverage may be a result of atypical ablation zone shrinkage 1 month post-RFA, which may not be reflected in clinical utilization.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>An AI model that uses 2D images at the center of the tumor and 1 month post-ablation can accurately estimate ablation tumor coverage. In separate validation cohorts, translation could be challenging.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1007\/s11548-025-03423-z","type":"journal-article","created":{"date-parts":[[2025,6,7]],"date-time":"2025-06-07T04:24:34Z","timestamp":1749270274000},"page":"1653-1663","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Estimation of tumor coverage after RF ablation of hepatocellular carcinoma using single 2D image slices"],"prefix":"10.1007","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2273-7962","authenticated-orcid":false,"given":"Nicole","family":"Varble","sequence":"first","affiliation":[]},{"given":"Ming","family":"Li","sequence":"additional","affiliation":[]},{"given":"Laetitia","family":"Saccenti","sequence":"additional","affiliation":[]},{"given":"Tabea","family":"Borde","sequence":"additional","affiliation":[]},{"given":"Antonio","family":"Arrichiello","sequence":"additional","affiliation":[]},{"given":"Anna","family":"Christou","sequence":"additional","affiliation":[]},{"given":"Katerina","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Lindsey","family":"Hazen","sequence":"additional","affiliation":[]},{"given":"Sheng","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Riccardo","family":"Lencioni","sequence":"additional","affiliation":[]},{"given":"Bradford J.","family":"Wood","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,6,7]]},"reference":[{"issue":"1","key":"3423_CR1","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/j.jhep.2018.09.014","volume":"70","author":"SK Asrani","year":"2019","unstructured":"Asrani SK, Devarbhavi H, Eaton J, Kamath PS (2019) Burden of liver diseases in the world. 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BJW is the Principal Investigator in Cooperative Research and Development Agreements between NIH and the following: BTG Biocompatibles\/Boston Scientific, Siemens, NVIDIA, Celsion Corp, Canon Medical, XAct Robotics, and Philips. BJW and NIH are party to Material Transfer or Collaboration Agreements with: Angiodynamics, 3\u00a0T Technologies, Profound Medical, Exact Imaging, Johnson and Johnson, Endocare\/Healthtronics, and Medtronic. Outside the submitted work, BJW is primary inventor on 47 issued patents owned by the NIH (list available upon request), a portion of which have been licensed by NIH to Philips. BJW and NIH report a licensing agreement with Canon Medical on algorithm software with no patent. BJW is joint inventor (assigned to HHS NIH US Government) for patents and pending patents related to drug eluting bead technology, some of which may have joint inventorships with BTG Biocompatibles\/Boston Scientific. BJW is primary inventor on patents owned by NIH in the space of drug eluting embolic beads. No other authors have conflicts of interest to declare.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"This study was a secondary retrospective review of an Institutional Review Board-approved prospective clinical trial, which obtained written and informed consent (NCT02112656).","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}