Multiphysics modeling toward enhanced guidance in hepatic microwave ablation: a preliminary framework

doi:10.1117/1.jmi.6.2.025007

Cited by 4 publications

(12 citation statements)

References 61 publications

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“…Where 𝑓%, 𝑚 𝑙𝑖𝑣𝑒𝑟 , 𝑚 𝑓𝑎𝑡 are the fat fraction percentage from imaging data and the respective value for the material property (m) value for liver and fat, respectively. −𝜏 𝑘 is the factor used to generate an exponential curve fit to values obtained from a previous study [15]. 2.…”

Section: Constitutive Equations For Materials Propertiesmentioning

confidence: 99%

“…Shows the disease state index and the corresponding percent fat derived from the fat quantification imaging data for each patient. Material properties at a particular disease state were determined using the material characteristic curves established in previous work but with a modified scale based on the human data range [13], [15]. The specific values were only applied to the homogenous-tissue models.…”

Section: Constitutive Equations For Materials Propertiesmentioning

confidence: 99%

See 1 more Smart Citation

Digital twin forecasting of microwave ablation via fat quantification image-to-grid computational methods

Servin

Collins

Heiselman

et al. 2023

Medical Imaging 2023: Image-Guided Procedures, Robotic Interventions, and Modeling

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Computational tools, such as "digital twin" modeling, are beginning to enable patient-specific surgical planning of ablative therapies to treat hepatocellular carcinoma. Digital twins models use patient functional data and biomarker imaging to build anatomically accurate models to forecast therapeutic outcomes through simulation, i.e., providing accurate information for guiding clinical decision-making. In microwave ablation (MWA), tissue-specific factors (e.g., tissue perfusion, material properties, disease state, etc.) can affect ablative therapies, but current thermal dosing guidelines do not account for these differences. This study establishes an imaging-data-driven framework to construct digital twin biophysical models to predict ablation extents in livers with varying fat content in MWA. Patient anatomic scans were segmented to develop customized three-dimensional computational biophysical models, and fat-quantification images were acquired to reconstruct spatially accurate biophysical material properties. Simulated patient-specific microwave ablations of homogenous digital-twin models (control) and enhanced digital twin models were performed at four levels of fatty liver disease. When looking at the short diameter (SD), long diameter (LD), ablation volume, and spherical index of the ablation margins -the heterogenous digital-twin models did not produce significantly different ablation margins compared to the control models. Both models produced results that report ablation margins for patients with high-fat livers are larger than low-fat livers (LD of 6.17cm vs. 6.30cm and SD of 2.10 vs. 1.99, respectively). Overall, the results suggest that modeling heterogeneous clinical fatty liver disease using fat-quantitative imaging data has the potential to improve patient specificity for this treatment modality.

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Section: Constitutive Equations For Materials Propertiesmentioning

confidence: 99%

Section: Constitutive Equations For Materials Propertiesmentioning

confidence: 99%

Digital twin forecasting of microwave ablation via fat quantification image-to-grid computational methods

Servin

Collins

Heiselman

et al. 2023

Medical Imaging 2023: Image-Guided Procedures, Robotic Interventions, and Modeling

View full text Add to dashboard Cite

show abstract

“…A 3D finite-element model was created in COMSOL Multiphysics 5.6 (COMSOL Inc., Burlington, MA, United States) to simulate electromagnetic wave propagation and heat transfer in a patient-specific liver model with a 915 MHz coaxial antenna with a ring slot (Collins et al, 2019). The propagation and absorption of electromagnetic waves radiating from the antenna in the model, assuming no existing charge, is described by Maxwell's electromagnetic wave equation in three dimensions,…”

Section: Computational Modelmentioning

confidence: 99%

“…To acquire the temporal course of the necrotic zone development, this process was performed every 15 s over the entire 15-min ablation period. The Arrhenius value threshold was based on similar ablation volume analyses reported in the literature at similar thermal doses and experimental configurations (Deshazer et al, 2016;Collins et al, 2019). The ablation volume (cm 3 ) vs. the delivered thermal dose was plotted with varying degrees of fat fraction percentages displayed as an overlay.…”

Section: Temperature and Ablation Analysismentioning

confidence: 99%

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Fat Quantification Imaging and Biophysical Modeling for Patient-Specific Forecasting of Microwave Ablation Therapy

et al. 2022

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Computational tools are beginning to enable patient-specific surgical planning to localize and prescribe thermal dosing for liver cancer ablation therapy. Tissue-specific factors (e.g., tissue perfusion, material properties, disease state, etc.) have been found to affect ablative therapies, but current thermal dosing guidance practices do not account for these differences. Computational modeling of ablation procedures can integrate these sources of patient specificity to guide therapy planning and delivery. This paper establishes an imaging-data-driven framework for patient-specific biophysical modeling to predict ablation extents in livers with varying fat content in the context of microwave ablation (MWA) therapy. Patient anatomic scans were segmented to develop customized three-dimensional computational biophysical models and mDIXON fat-quantification images were acquired and analyzed to establish fat content and determine biophysical properties. Simulated patient-specific microwave ablations of tumor and healthy tissue were performed at four levels of fatty liver disease. Ablation models with greater fat content demonstrated significantly larger treatment volumes compared to livers with less severe disease states. More specifically, the results indicated an eightfold larger difference in necrotic volumes with fatty livers vs. the effects from the presence of more conductive tumor tissue. Additionally, the evolution of necrotic volume formation as a function of the thermal dose was influenced by the presence of a tumor. Fat quantification imaging showed multi-valued spatially heterogeneous distributions of fat deposition, even within their respective disease classifications (e.g., low, mild, moderate, high-fat). Altogether, the results suggest that clinical fatty liver disease levels can affect MWA, and that fat-quantitative imaging data may improve patient specificity for this treatment modality.

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Simulation of Image-Guided Microwave Ablation Therapy Using a Digital Twin Computational Model

Servin,

Collins,

Heiselman

et al. 2024

IEEE Open J. Eng. Med. Biol.

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Emerging computational tools such as healthcare digital twin modeling are enabling the creation of patient-specific surgical planning, including microwave ablation to treat primary and secondary liver cancers. Healthcare digital twins (DTs) are anatomically one-to-one biophysical models constructed from structural, functional, and biomarker-based imaging data to simulate patient-specific therapies and guide clinical decision-making. In microwave ablation (MWA), tissue-specific factors including tissue perfusion, hepatic steatosis, and fibrosis affect therapeutic extent, but current thermal dosing guidelines do not account for these parameters. This study establishes an MR imaging framework to construct three-dimensional biophysical digital twins to predict ablation delivery in livers with 5 levels of fat content in the presence of a tumor. Four microwave antenna placement strategies were considered, and simulated microwave ablations were then performed using 915 MHz and 2450 MHz antennae in Tumor Naïve DTs (control), and Tumor Informed DTs at five grades of steatosis. Across the range of fatty liver steatosis grades, fat content was found to significantly increase ablation volumes by approximately 29–l42% in the Tumor Naïve and 55–60% in the Tumor Informed DTs in 915 MHz and 2450 MHz antenna simulations. The presence of tumor did not significantly affect ablation volumes within the same steatosis grade in 915 MHz simulations, but did significantly increase ablation volumes within mild-, moderate-, and high-fat steatosis grades in 2450 MHz simulations. An analysis of signed distance to agreement for placement strategies suggests that accounting for patient-specific tumor tissue properties significantly impacts ablation forecasting for the preoperative evaluation of ablation zone coverage.

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Multiphysics modeling toward enhanced guidance in hepatic microwave ablation: a preliminary framework

Cited by 4 publications

References 61 publications

Digital twin forecasting of microwave ablation via fat quantification image-to-grid computational methods

Digital twin forecasting of microwave ablation via fat quantification image-to-grid computational methods

Fat Quantification Imaging and Biophysical Modeling for Patient-Specific Forecasting of Microwave Ablation Therapy

Simulation of Image-Guided Microwave Ablation Therapy Using a Digital Twin Computational Model

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