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Int J Comput Assist Radiol Surg. 2017 Sep;12(9):1543-1559. doi: 10.1007/s11548-016-1517-x. Epub 2017 Jan 17.

Comprehensive preclinical evaluation of a multi-physics model of liver tumor radiofrequency ablation.

Author information

1
Université Côte d'Azur and Inria Sophia-Antipolis Méditerranée Asclepios team, Inria Sophia Antipolis, France. chloe.audigier@inria.fr.
2
Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, USA. chloe.audigier@inria.fr.
3
Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, USA.
4
Université Côte d'Azur and Inria Sophia-Antipolis Méditerranée Asclepios team, Inria Sophia Antipolis, France.
5
IHU - Institut de Chirugie Guidée Par L'Image, Strasbourg, France.
6
IRCAD - Institut de Recherche Contre Les Cancers de L'Appareil Digestif, Strasbourg, France.

Abstract

PURPOSE:

We aim at developing a framework for the validation of a subject-specific multi-physics model of liver tumor radiofrequency ablation (RFA).

METHODS:

The RFA computation becomes subject specific after several levels of personalization: geometrical and biophysical (hemodynamics, heat transfer and an extended cellular necrosis model). We present a comprehensive experimental setup combining multimodal, pre- and postoperative anatomical and functional images, as well as the interventional monitoring of intra-operative signals: the temperature and delivered power.

RESULTS:

To exploit this dataset, an efficient processing pipeline is introduced, which copes with image noise, variable resolution and anisotropy. The validation study includes twelve ablations from five healthy pig livers: a mean point-to-mesh error between predicted and actual ablation extent of 5.3 ± 3.6 mm is achieved.

CONCLUSION:

This enables an end-to-end preclinical validation framework that considers the available dataset.

KEYWORDS:

Computational modeling; Preclinical evaluation; Radiofrequency ablation

PMID:
28097603
DOI:
10.1007/s11548-016-1517-x
[Indexed for MEDLINE]

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