Yuan-Mao Lin1, Iwan Paolucci1, Brian M Anderson2, Caleb S O'Connor2, Bastien Rigaud2, Maria Briones-Dimayuga1, Kyle A Jones2, Kristy K Brock2, Bryan M Fellman3, Bruno C Odisio4. 1. Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA. 2. Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, TX, 77030, Houston, USA. 3. Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA. 4. Department of Interventional Radiology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA. bcodisio@mdanderson.org.
Abstract
PURPOSE: This study aims to evaluate the intra-procedural use of a novel ablation confirmation (AC) method, consisting of biomechanical deformable image registration incorporating AI-based auto-segmentation, and its impact on tumor coverage by quantitative three-dimensional minimal ablative margin (MAM) CT-generated assessment. MATERIALS AND METHODS: This single-center, randomized, phase II, intent-to-treat trial is enrolling 100 subjects with primary and secondary liver tumors (≤ 3 tumors, 1-5 cm in diameter) undergoing microwave or radiofrequency ablation with a goal of achieving ≥ 5 mm MAM. For the experimental arm, the proposed novel AC method is utilized for ablation applicator(s) placement verification and MAM assessment. For the control arm, the same variables are assessed by visual inspection and anatomical landmarks-based quantitative measurements aided by co-registration of pre- and post-ablation contrast-enhanced CT images. The primary objective is to evaluate the impact of the proposed AC method on the MAM. Secondary objectives are 2-year LTP-free survival, complication rates, quality of life, liver function, other oncological outcomes, and impact of AC method on procedure workflow. DISCUSSION: The COVER-ALL trial will provide information on the role of a biomechanical deformable image registration-based ablation confirmation method incorporating AI-based auto-segmentation for improving MAM, which might translate in improvements of liver ablation efficacy. CONCLUSION: The COVER-ALL trial aims to provide information on the role of a novel intra-procedural AC method for improving MAM, which might translate in improvements of liver ablation efficacy. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04083378.
PURPOSE: This study aims to evaluate the intra-procedural use of a novel ablation confirmation (AC) method, consisting of biomechanical deformable image registration incorporating AI-based auto-segmentation, and its impact on tumor coverage by quantitative three-dimensional minimal ablative margin (MAM) CT-generated assessment. MATERIALS AND METHODS: This single-center, randomized, phase II, intent-to-treat trial is enrolling 100 subjects with primary and secondary liver tumors (≤ 3 tumors, 1-5 cm in diameter) undergoing microwave or radiofrequency ablation with a goal of achieving ≥ 5 mm MAM. For the experimental arm, the proposed novel AC method is utilized for ablation applicator(s) placement verification and MAM assessment. For the control arm, the same variables are assessed by visual inspection and anatomical landmarks-based quantitative measurements aided by co-registration of pre- and post-ablation contrast-enhanced CT images. The primary objective is to evaluate the impact of the proposed AC method on the MAM. Secondary objectives are 2-year LTP-free survival, complication rates, quality of life, liver function, other oncological outcomes, and impact of AC method on procedure workflow. DISCUSSION: The COVER-ALL trial will provide information on the role of a biomechanical deformable image registration-based ablation confirmation method incorporating AI-based auto-segmentation for improving MAM, which might translate in improvements of liver ablation efficacy. CONCLUSION: The COVER-ALL trial aims to provide information on the role of a novel intra-procedural AC method for improving MAM, which might translate in improvements of liver ablation efficacy. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04083378.
Authors: Eddie K Abdalla; Jean-Nicolas Vauthey; Lee M Ellis; Vickie Ellis; Raphael Pollock; Kristine R Broglio; Kenneth Hess; Steven A Curley Journal: Ann Surg Date: 2004-06 Impact factor: 12.969