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

PURPOSE: 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. METHODS: 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. RESULTS: The total time to initialize and simulate an MRgLITT procedure using the GUI was [Formula: see text]5 min. Each independent simulation took [Formula: see text]30 s, including the time to visualize the results fused with the planning MRI. For demonstration purposes, a simulated steady-state isotherm contour [Formula: see text] was correlated with MR temperature imaging (N = 5). The mean Hausdorff distance between simulated and actual contours was 2.0 mm [Formula: see text], whereas the mean Dice similarity coefficient was 0.93 [Formula: see text]. CONCLUSIONS: 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.

Generation of 4D access corridors from real-time multislice MRI for guiding transapical aortic valvuloplasties.

Real-time image-guided cardiac procedures (manual or robot-assisted) are emerging due to potential improvement in patient management and reduction in the overall cost. These minimally invasive procedures require both real-time visualization and guidance for maneuvering an interventional tool safely inside the dynamic environment of a heart. In this work, we propose an approach to generate dynamic 4D access corridors from the apex to the aortic annulus for performing real-time MRI guided transapical valvuloplasties. Ultrafast MR images (collected every 49.3 ms) are processed on-the-fly using projections to extract a conservative dynamic trace in form of a three-dimensional access corridor. Our experimental results show that the reconstructed corridors can be refreshed with a delay of less than 0.5ms to reflect the changes inside the left ventricle caused by breathing motion and the heartbeat.

Collaborative tracking for MRI-guided robotic intervention on the beating heart.

Magnetic Resonance Imaging (MRI)-guided robotic interventions for aortic valve repair promise to dramatically reduce time and cost of operations when compared to endoscopically guided (EG) procedures. A challenging issue is real-time and robust tracking of anatomical landmark points. The interventional tool should be constantly adjusted via a closed feedback control loop to avoid harming these points while valve repair is taking place in the beating heart. A Bayesian network of particle filter trackers proves capable to produce real-time, yet robust behavior. The algorithm is extremely flexible and general--more sophisticated behaviors can be produced by simply increasing the cardinality of the tracking network. Experimental results on 16 MRI cine sequences highlight the promise of the method.