The delivery of insufficient thermal dose is a significant contributor to incomplete tissue ablation and leads to arrhythmia recurrence and a large number of patients requiring repeat procedures. In concert with ongoing research efforts aimed at better characterizing the RF energy delivery, here we propose a method that entails modeling and visualization of the lesions in real time. The described image-based ablation model relies on classical heat transfer principles to estimate tissue temperature in response to the ablation parameters, tissue properties, and duration. The ablation lesion quality, geometry, and overall progression is quantified on a voxelby-voxel basis according to each voxel’s cumulative temperature and time exposure. The model was evaluated both numerically under different parameter conditions, as well as experimentally, using ex vivo bovine tissue samples. This study suggests that the proposed technique provides reasonably accurate and sufficiently fast visualizations of the delivered ablation lesions.
In spite of significant efforts to improve image-guided ablation therapy, a large number of patients undergoing ablation therapy to treat cardiac arrhythmic conditions require repeat procedures. The delivery of insufficient thermal dose is a significant contributor to incomplete tissue ablation, in turn leading to the arrhythmia recurrence. Ongoing research efforts aim to better characterize and visualize RF delivery to monitor the induced tissue damage during therapy. Here, we propose a method that entails modeling and visualization of the lesions in real-time. The described image-based ablation model relies on classical heat transfer principles to estimate tissue temperature in response to the ablation parameters, tissue properties, and duration. The ablation lesion quality, geometry, and overall progression are quantified on a voxel-by-voxel basis according to each voxel’s cumulative temperature and time exposure. The model was evaluated both numerically under different parameter conditions, as well as experimentally, using ex vivo bovine tissue samples undergoing ex vivo clinically relevant ablation protocols. The studies demonstrated less than 5°C difference between the model-predicted and experimentally measured end-ablation temperatures. The model predicted lesion patterns were within 0.5 to 1 mm from the observed lesion patterns, suggesting sufficiently accurate modeling of the ablation lesions. Lastly, our proposed method enables therapy delivery feedback with no significant workflow latency. This study suggests that the proposed technique provides reasonably accurate and sufficiently fast visualizations of the delivered ablation lesions.
Magnetic Resonance guided High-intensity Focused Ultrasound (MR-HIFU) can be used to locally heat tissue while non-invasively monitoring tissue temperature via MR-based thermometry. The goal of this study was to
investigate the use of a computational technique based on inverse heat-transfer modeling for the non-invasive measurement of thermal tissue properties from data collected using an MR-HIFU system.
Low temperature sensitive liposomes (LTSL) are drug delivery vehicles with long plasma half-life, which release the
drug upon heating above ~40°C. The combination of LTSL with local heat generated by image-guided focused
ultrasound may thus allow non-invasively targeted drug delivery. We combined a heat-transfer model with a drug
delivery model to determine temperature-dependent release and tumor tissue accumulation of drug in extravascular-extracellular
space, and inside cells. Tissue was heated with a 16 mm focal spot for 7 min at 43°C target temperature. In
addition we examined the effect of an additional subsequent high-temperature pulse to eliminate blood flow after drug
release. Our results show high local plasma concentration during hyperthermia at the target site, during which drug is
taken up by tissue and finally by cells. Following heating, local plasma concentration rapidly drops off and drug not
taken up by cells is removed from tissue by blood flow. Elimination of blood flow following hyperthermia by a high-temperature
pulse avoided this removal and resulted in ~2x higher intracellular concentration.
Tumor ablation using radiofrequency (RF) energy is clinically used for treatment of various cancer types. During RF
ablation, an electrode is inserted into a tumor under imaging-guidance, and the tumor is heated by RF electric current
and cancer cells killed above temperatures of ~50 °C. One of the major factors affecting tissue temperature and ablation
zone dimensions is tissue perfusion. To examine perfusion effects, we created Finite Element Method computer models
of a clinically used RF ablation device, including temperature-dependent electrical and thermal tissue properties.
Microvascular perfusion was modeled according to Pennes' Bioheat Equation, and was varied with temperature to
include perfusion cessation due to coagulation at high temperatures. Microvascular perfusion rate was varied to represent
variations between patients by +/-1 standard deviation based on prior data measured in humans. Macro-vascular
perfusion was modeled by including a large vessel (10 mm diameter) in the model geometry, and assigning a convective
heat transfer coefficient as a boundary condition at the vessel wall. The vessel resulted in local deviation of the ablation
zone around the vessel, and resulted in a region of viable tissue near the vessel wall. Microvascular perfusion affected
overall size and geometry of the ablation zone. Ablation zone volume for average microvascular perfusion was 20.1 cm3,
and was 16.6 and 25.3 cm3 when perfusion rate was increased or reduced by 1 standard deviation. Both micro- and
macrovascular perfusion considerably affect tissue temperature and ablation zone. Patient-specific data on perfusion
would allow for more accurate estimates of ablation zone dimensions and improved treatment planning.