• Roee S Lazebnik, Brent D Weinberg, Michael S Breen, Jonathan S Lewin, and David L Wilson.
• Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
• Acad Radiol. 2005 Dec 1; 12 (12): 1491-501.

Rationale And ObjectivesInterventional magnetic resonance imaging (iMRI) allows real-time guidance and optimization of radiofrequency ablation of pathologic tissue. For many tissues, resulting lesions have a characteristic two-boundary appearance featuring an inner region and an outer hyper-intense margin in both T2 and contrast-enhanced (CE) T1-weighted MR images. We created a geometric model-based semiautomatic method to aid in real-time lesion segmentation, cross-sectional/three-dimensional visualization, and intra/posttreatment evaluation.Materials And MethodsOur method relies on a 12-parameter, 3-dimensional, globally deformable model with quadric surfaces that describe both lesion boundaries. We present an energy minimization approach to quickly and semiautomatically fit the model to a gray-scale MR image volume. We applied the method to in vivo lesions (n = 10) in a rabbit thigh model, using T2 and CE T1-weighted MR images, and compared the results with manually segmented boundaries.ResultsFor all lesions, the median error was < or =1.21 mm for the inner region and < or =1.00 mm for the outer hyper-intense region, values that favorably compare to a voxel width of 0.7 mm and distances between the borders manually segmented by the two operators.ConclusionOur method provides a precise, semiautomatic approximation of lesion shape for ellipsoidal lesions. Further, the method has clinical applications in lesion visualization, volume estimation, and treatment evaluation.

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