Paper
12 March 2014 Innovative approach for in-vivo ablation validation on multimodal images
O. Shahin, G. Karagkounis, D. Carnegie, A. Schlaefer, E. Boctor
Author Affiliations +
Abstract
Radiofrequency ablation (RFA) is an important therapeutic procedure for small hepatic tumors. To make sure that the target tumor is effectively treated, RFA monitoring is essential. While several imaging modalities can observe the ablation procedure, it is not clear how ablated lesions on the images correspond to actual necroses. This uncertainty contributes to the high local recurrence rates (up to 55%) after radiofrequency ablative therapy. This study investigates a novel approach to correlate images of ablated lesions with actual necroses. We mapped both intraoperative images of the lesion and a slice through the actual necrosis in a common reference frame. An electromagnetic tracking system was used to accurately match lesion slices from different imaging modalities. To minimize the liver deformation effect, the tracking reference frame was defined inside the tissue by anchoring an electromagnetic sensor adjacent to the lesion. A validation test was performed using a phantom and proved that the end-to-end accuracy of the approach was within 2mm. In an in-vivo experiment, intraoperative magnetic resonance imaging (MRI) and ultrasound (US) ablation images were correlated to gross and histopathology. The results indicate that the proposed method can accurately correlate invivo ablations on different modalities. Ultimately, this will improve the interpretation of the ablation monitoring and reduce the recurrence rates associated with RFA.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
O. Shahin, G. Karagkounis, D. Carnegie, A. Schlaefer, and E. Boctor "Innovative approach for in-vivo ablation validation on multimodal images", Proc. SPIE 9036, Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling, 903602 (12 March 2014); https://doi.org/10.1117/12.2041835
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KEYWORDS
Sensors

Tissues

Magnetic resonance imaging

Liver

Radiofrequency ablation

In vivo imaging

Speckle

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