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GPU-based 3D iceball modeling for fast cryoablation simulation and planning

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

The elimination of abdominal tumors by percutaneous cryoablation has been shown to be an effective and less invasive alternative to open surgery. Cryoablation destroys malignant cells by freezing them with one or more cryoprobes inserted into the tumor through the skin. Alternating cycles of freezing and thawing produce an enveloping iceball that causes the tumor necrosis. Planning such a procedure is difficult and time-consuming, as it is necessary to plan the number and cryoprobe locations and predict the iceball shape which is also influenced by the presence of heating sources, e.g., major blood vessels and warm saline solution, injected to protect surrounding structures from the cold.

Methods

This paper describes a method for fast GPU-based iceball modeling based on the simulation of thermal propagation in the tissue. Our algorithm solves the heat equation within a cube around the cryoprobes tips and accounts for the presence of heating sources around the iceball.

Results

Experimental results of two studies have been obtained: an ex vivo warm gel setup and simulation on five retrospective patient cases of kidney tumors cryoablation with various levels of complexity of the vascular structure and warm saline solution around the tumor tissue. The experiments have been conducted in various conditions of cube size and algorithm implementations. Results show that it is possible to obtain an accurate result within seconds.

Conclusion

The promising results indicate that our method yields accurate iceball shape predictions in a short time and is suitable for surgical planning.

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Acknowledgements

This work was partially supported by a grant from the Maimonide France-Israel Research in Biomedical Robotics, funded jointly by the French Ministry of Higher Education, Research and Innovation, the French Ministry for the Economy and Finance, and Israel Ministry of Science, Technology and Space, 2016–18, and by Grant 53681 (METASEG) from the Israel Ministry of Science, Technology and Space, 2016–2019.

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Authors and Affiliations

  1. ICube, Université de Strasbourg, Strasbourg, France

    Ehsan Golkar & Caroline Essert

  2. Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

    Ehsan Golkar

  3. Department of Radiology, University Hospital of Strasbourg, Strasbourg, France

    Pramod P. Rao & Afshin Gangi

  4. School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel

    Leo Joskowicz

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  1. Ehsan Golkar
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  2. Pramod P. Rao
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  3. Leo Joskowicz
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  4. Afshin Gangi
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  5. Caroline Essert
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Correspondence to Caroline Essert.

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Golkar, E., Rao, P.P., Joskowicz, L. et al. GPU-based 3D iceball modeling for fast cryoablation simulation and planning. Int J CARS 14, 1577–1588 (2019). https://doi.org/10.1007/s11548-019-02051-8

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  • DOI: https://doi.org/10.1007/s11548-019-02051-8

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