Purpose: Minimally invasive thermal ablative therapies as alternatives to conventional surgical management of solid tumors and other pathologies is increasing owing to the potential benefits of performing these procedures in an outpatient setting with reduced complications and comorbidity. Magnetic resonance temperature imaging ͑MRTI͒ measurement allows existing thermal dose models to use the spatiotemporal temperature history to estimate the thermal damage to tissue. However, the various thermal dose models presented in the literature employ different parameters and thresholds, affecting the reliability of thermal dosimetry. In this study, the authors quantitatively compared three thermal dose models ͑Arrhenius rate process, CEM 43 , and threshold temperature͒ using the dice similarity coefficient ͑DSC͒. Methods: The DSC was used to compare the spatial overlap between the region of thermal damage as predicted by the models for in vivo normal canine brain during thermal therapy to the region of thermal damage as revealed by contrast-enhanced T1-weighted images acquired immediately after therapy ͑Ͻ20 min͒. The outer edge of the hyperintense rim of the ablation region was used as the surrogate marker for the limits of thermal coagulation. The DSC was also used to investigate the impact of varying the thresholds on each models' ability to predict the zone of thermal necrosis. Results: At previously reported thresholds, the authors found that all three models showed good agreement ͑defined as DSCϾ 0.7͒ with post-treatment imaging. All three models examined across the range of commonly applied thresholds consistently showed highly accurate spatial overlap, low variability, and little dependence on temperature uncertainty. DSC values corresponding to cited thresholds were not significantly different from peak DSC values. Conclusions: Thus, the authors conclude that the all three thermal dose models can be used as a reliable surrogate for postcontrast tissue damage verification imaging in rapid ablation procedures and can also be used to enhance the capability of MRTI to control thermal therapy in real time.

Purpose-To evaluate the accuracy of computer simulation in predicting the thermal damage region produced by a radiofrequency (RF) ablation procedure in an in vitro perfused bovine liver model. The thermal dose end point in the liver model is used to quantitatively assess computer prediction for use in prospective treatment planning of RF ablation procedures.Materials and Methods-Geometric details of the tri-cooled-tip electrode were modeled. The resistive heating of a pulsed voltage delivery was simulated in 4D using finite element methods (FEM) implemented on high performance parallel computing architectures. A range of physically realistic blood perfusion parameters, 3.6-53.6kg/s/m 3 were considered in the computer model. An Arrhenius damage model was used to predict the thermal dose. Dice similarity coefficients (DSC) were the metric used to compare computational predictions to T 1 -weighted contrast enhanced images of the damage obtained from a RF procedure performed on an in vitro perfused bovine liver model.Results-For a perfusion parameter greater than 16.3kg/s/m 3 , simulations predict the temporal evolution of the damaged volume is perfusion limited and will reach a maximum value. Over a range of physically meaningful perfusion values, 16.3-33.1kg/s/m 3 , the predicted thermal dose reaches the maximum damage volume within two minutes of the delivery and is in good agreement, DSC > 0.7, with experimental measurements obtained from the perfused liver model. Conclusions-As measured by the computed volumetric DSC, computer prediction accuracy of the thermal dose shows good correlation with ablation lesions measured in vitro perfused bovine liver models over a range of physically realistic perfusion values.

The feasibility of using a stochastic form of Pennes bioheat model within a 3D finite element based Kalman filter (KF) algorithm is critically evaluated for the ability to provide temperature field estimates in the event of magnetic resonance temperature imaging (MRTI) data loss during laser induced thermal therapy (LITT). The ability to recover missing MRTI data was analyzed by systematically removing spatiotemporal information from a clinical MR-guided LITT procedure in human brain and comparing predictions in these regions to the original measurements. Performance was quantitatively evaluated in terms of a dimensionless L2 (RMS) norm of the temperature error weighted by acquisition uncertainty. During periods of no data corruption, observed error histories demonstrate that the Kalman algorithm does not alter the high quality temperature measurement provided by MR thermal imaging. The KF-MRTI implementation considered is seen to predict the bioheat transfer with RMS error < 4 for a short period of time, Δt < 10sec, until the data corruption subsides. In its present form, the KF-MRTI method currently fails to compensate for consecutive for consecutive time periods of data loss Δt > 10sec.

The image quality generated by the MRI system of the integrated MRL was similar to that of a diagnostic MRI scanner. Interference from the MV radiation was minimal, and there was no measurable difference in image quality with the beam on and off. Scatter radiation and leakage radiation of the MRL system were within the expected range of a comparable MV-LINAC.

A novel velocity navigator with Kalman filter postprocessing in real time significantly improves the temperature accuracy over non-triggered acquisitions and suggests being comparable to a breath-held acquisition. The proposed technique might be clinically applied for monitoring of thermal ablations in abdominal organs.