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Improvement of liver ablation treatment for colorectal liver metastases
Author(s): Brian M. Anderson; Ethan Y. Lin; Guillaume Cazoulat; Sanjay Gupta; Bruno C. Odisio; Kristy K. Brock
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Paper Abstract

The purpose of this research is to improve treatment of colorectal liver metastases (CLM) in the clinic. It has been previously shown that an ablation margin of 5 mm or more for CLM greatly increases 5 year local tumor progression free survival, however it is often difficult to ensure proper ablation using intraprocedural imaging. CT images of 30 patients with CLM treated with ablation were retrospectively obtained from the MD Anderson Cancer Center. Contours defining the liver, ablation probes, CLM margins, and ablation margin were created from the pre-treatment contrast enhanced CTs and intra-interventional CT images. Using a biomechanical model-based deformable image registration these contours were deformed onto the contrast enhanced CT images obtained just after treatment. The propagated ablation region was then compared with the GTV, as defined before the procedure, to determine the ablation margin delivered. There was a statistically significant difference (p<0.01) in the achieved ablation margin between patients who did and did not have local recurrence. Results showed that patients without local recurrence received on average 3.19 mm of minimum ablation margin around the gross tumor volume(GTV), while those with local recurrence received an average of 1.14 mm. The model presented can assist in the treatment of CLM by identifying the minimum distance to agreement between the GTV and the ablation region directly after treatment. This metric can help determine if sufficient ablation has been delivered to the treat the disease.

Paper Details

Date Published: 19 March 2018
PDF: 7 pages
Proc. SPIE 10576, Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 105762D (19 March 2018); doi: 10.1117/12.2294554
Show Author Affiliations
Brian M. Anderson, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
The Univ. of Texas Graduate School of Biomedical Sciences at Houston (United States)
Ethan Y. Lin, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
Guillaume Cazoulat, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
Sanjay Gupta, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
Bruno C. Odisio, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)
Kristy K. Brock, The Univ. of Texas M.D. Anderson Cancer Ctr. (United States)


Published in SPIE Proceedings Vol. 10576:
Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Robert J. Webster, Editor(s)

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