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Design and initial evaluation of a treatment planning software system for MRI-guided laser ablation in the brain



   An open-source software system for planning magnetic resonance (MR)-guided laser-induced thermal therapy (MRgLITT) in brain is presented. The system was designed to provide a streamlined and operator-friendly graphical user interface (GUI) for simulating and visualizing potential outcomes of various treatment scenarios to aid in decisions on treatment approach or feasibility.


   A portable software module was developed on the 3D Slicer platform, an open-source medical imaging and visualization framework. The module introduces an interactive GUI for investigating different laser positions and power settings as well as the influence of patient-specific tissue properties for quickly creating and evaluating custom treatment options. It also provides a common treatment planning interface for use by both open-source and commercial finite element solvers. In this study, an open-source finite element solver for Pennes’ bioheat equation is interfaced to the module to provide rapid 3D estimates of the steady-state temperature distribution and potential tissue damage in the presence of patient-specific tissue boundary conditions identified on segmented MR images.


   The total time to initialize and simulate an MRgLITT procedure using the GUI was \(<\)5 min. Each independent simulation took \(<\)30 s, including the time to visualize the results fused with the planning MRI. For demonstration purposes, a simulated steady-state isotherm contour \((57\,^{\circ }\hbox {C})\) was correlated with MR temperature imaging (N = 5). The mean Hausdorff distance between simulated and actual contours was 2.0 mm \((\sigma \,=\,0.4\,\hbox {mm})\), whereas the mean Dice similarity coefficient was 0.93 \((\sigma =0.026)\).


   We have designed, implemented, and conducted initial feasibility evaluations of a software tool for intuitive and rapid planning of MRgLITT in brain. The retrospective in vivo dataset presented herein illustrates the feasibility and potential of incorporating fast, image-based bioheat predictions into an interactive virtual planning environment for such procedures.

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This research is supported in part by the MD Anderson Cancer Center Support Grant CA016672 and the National Institutes of Health (NIH) award 1R21EB010196-01 and Apache Corporation. All opinions, findings, conclusions, or recommendations expressed in this work are those of the authors and do not necessarily reflect the views of our sponsors. The data were acquired in part from Visualase Inc. (Houston, TX, USA). Conflict of interest   None

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Correspondence to R. J. Stafford.

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Yeniaras, E., Fuentes, D.T., Fahrenholtz, S.J. et al. Design and initial evaluation of a treatment planning software system for MRI-guided laser ablation in the brain. Int J CARS 9, 659–667 (2014).

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