ArticleMedical physics2021
Microwave ablation of lung tumors: A probabilistic approach for simulation-based treatment planning.
Article in Medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 24 citations in OpenAlex.
- Evaluation of an augmented reality navigational guidance platform for percutaneous procedures in a cadaver model.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Assessment of thermochromic phantoms for characterizing microwave ablation devices.Medical physics · 2024Article
- Histology-validated electromagnetic characterization of ex-vivo ovine lung tissue for microwave-based medical applications.Scientific reports · 2024Article
- Percutaneous microwave ablation for lung tumors: a retrospective case-control study of conventional CT and C-arm CT guidance.Quantitative imaging in medicine and surgery · 2023Article
- Prediction of Ablation Volume in Percutaneous Lung Microwave Ablation: A Single Centre Retrospective Study.Tomography (Ann Arbor, Mich.) · 2022Article
- Clinical application status and prospect of the combined anti-tumor strategy of ablation and immunotherapy.Frontiers in immunology · 2022Review
- Image-based computer modeling assessment of microwave ablation for treatment of adrenal tumors.International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group · 2022Article
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Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
Abstract
purposeMicrowave ablation (MWA) is a clinically established modality for treatment of lung tumors. A challenge with existing application of MWA, however, is local tumor progression, potentially due to failure to establish an adequate treatment margin. This study presents a robust simulation-based treatment planning methodology to assist operators in comparatively assessing thermal profiles and likelihood of achieving a specified minimum margin as a function of candidate applied energy parameters.
methodsWe employed a biophysical simulation-based probabilistic treatment planning methodology to evaluate the likelihood of achieving a specified minimum margin for candidate treatment parameters (i.e., applied power and ablation duration for a given applicator position within a tumor). A set of simulations with varying tissue properties was evaluated for each considered combination of power and ablation duration, and for four different scenarios of contrast in tissue biophysical properties between tumor and normal lung. A treatment planning graph was then assembled, where distributions of achieved minimum ablation zone margins and collateral damage volumes can be assessed for candidate applied power and treatment duration combinations. For each chosen power and time combination, the operator can also visualize the histogram of ablation zone boundaries overlaid on the tumor and target volumes. We assembled treatment planning graphs for generic 1, 2, and 2.5 cm diameter spherically shaped tumors and also illustrated the impact of tissue heterogeneity on delivered treatment plans and resulting ablation histograms. Finally, we illustrated the treatment planning methodology on two example patient-specific cases of tumors with irregular shapes.
resultsThe assembled treatment planning graphs indicate that 30 W, 6 min ablations achieve a 5-mm minimum margin across all simulated cases for 1-cm diameter spherical tumors, and 70 W, 10 min ablations achieve a 3-mm minimum margin across 90% of simulations for a 2.5-cm diameter spherical tumor. Different scenarios of tissue heterogeneity between tumor and lung tissue revealed 2 min overall difference in ablation duration, in order to reliably achieve a 4-mm minimum margin or larger each time for 2-cm diameter spherical tumor.
conclusionsAn approach for simulation-based treatment planning for microwave ablation of lung tumors is illustrated to account for the impact of specific geometry of the treatment site, tissue property uncertainty, and heterogeneity between the tumor and normal lung.
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