A methodology for thermal dose model parameter development using perioperative MRI.

Post-treatment imaging is the principal method for evaluating thermal lesions following image-guided thermal ablation procedures. While real-time temperature feedback using magnetic resonance temperature imaging (MRTI) is a complementary tool that can be used to optimise lesion size throughout the procedure, a thermal dose model is needed to convert temperature-time histories to estimates of thermal damage. However, existing models rely on empirical parameters derived from laboratory experiments that are not direct indicators of post-treatment radiologic appearance. In this work, we investigate a technique that uses perioperative MR data to find novel thermal dose model parameters that are tailored to the appearance of the thermal lesion on post-treatment contrast-enhanced imaging. Perioperative MR data were analysed for five patients receiving magnetic resonance-guided laser-induced thermal therapy (MRgLITT) for brain metastases. The characteristic enhancing ring was manually segmented on post-treatment T1-weighted imaging and registered into the MRTI geometry. Post-treatment appearance was modelled using a coupled Arrhenius-logistic model and non-linear optimisation techniques were used to find the maximum-likelihood kinetic parameters and dose thresholds that characterise the inner and outer boundary of the enhancing ring. The parameter values and thresholds were consistent with previous investigations, while the average difference between the predicted and segmented boundaries was on the order of one pixel (1 mm). The areas predicted using the optimised model parameters were also within 1 mm of those predicted by clinically utilised dose models. This technique makes clinically acquired data available for investigating new thermal dose model parameters driven by clinically relevant endpoints.