3D US-based Evaluation and Optimization of Tumor Coverage for 2D US-guided Percutaneous Liver Thermal Ablation
Published in IEEE Transactions on Medical Imaging, 2022
Recommended citation: Xing, S., Cambranis-Romero J., Cool, D.W., Mujoomdar, A., Chen ECS, Peters, TM., and Fenster A., (2022). "3D US-based Evaluation and Optimization of Tumor Coverage for 2D US-guided Percutaneous Liver Thermal Ablation"; in IEEE Transactions on Medical Imaging, (41)11, pp.3344-3356 https://ieeexplore.ieee.org/document/9800921
Complete tumor coverage by the thermal ablation zone and with a safety margin (5 or 10 mm) is required to achieve the entire tumor eradication in liver tumor ablation procedures. However, 2D ultrasound (US) imaging has limitations in evaluating the tumor coverage by imaging only one or multiple planes, particularly for cases with multiple inserted applicators or irregular tumor shapes. In this paper, we evaluate the intra-procedural tumor coverage using 3D US imaging and investigate whether it can provide clinically needed information. Using data from 14 cases, we employed surface- and volumebased evaluation metrics to provide information on any uncovered tumor region. For cases with incomplete tumor coverage or uneven ablation margin distribution, we also proposed a novel margin uniformity-based approach to provide quantitative applicator adjustment information for optimization of tumor coverage. Both the surface- and volume-based metrics showed that 5 of 14 cases had incomplete tumor coverage according to the estimated ablation zone. After applying our proposed applicator adjustment approach, the simulated results showed that 92.9% (13 of 14) cases achieved 100% tumor coverage and the remaining case can benefit by increasing the ablation time or power. Our proposed method can evaluate the intraprocedural tumor coverage and intuitively provide applicator adjustment information for the physician. Our 3D US-based method is compatible with the constraints of conventional US-guided ablation procedures and can be easily integrated into the clinical workflow.