Universität zu Köln

Rak, Marko, Koenig, Tim, Toennies, Klaus D., Walke, Mathias, Ricke, Jens and Wybranski, Christian (2017). Joint deformable liver registration and bias field correction for MR-guided HDR brachytherapy. Int. J. Comput. Assist. Radiol. Surg., 12 (12). S. 2169 - 2181. HEIDELBERG: SPRINGER HEIDELBERG. ISSN 1861-6429

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Abstract

In interstitial high-dose rate brachytherapy, liver cancer is treated by internal radiation, requiring percutaneous placement of applicators within or close to the tumor. To maximize utility, the optimal applicator configuration is pre-planned on magnetic resonance images. The pre-planned configuration is then implemented via a magnetic resonance-guided intervention. Mapping the pre-planning information onto interventional data would reduce the radiologist's cognitive load during the intervention and could possibly minimize discrepancies between optimally pre-planned and actually placed applicators. We propose a fast and robust two-step registration framework suitable for interventional settings: first, we utilize a multi-resolution rigid registration to correct for differences in patient positioning (rotation and translation). Second, we employ a novel iterative approach alternating between bias field correction and Markov random field deformable registration in a multi-resolution framework to compensate for non-rigid movements of the liver, the tumors and the organs at risk. In contrast to existing pre-correction methods, our multi-resolution scheme can recover bias field artifacts of different extents at marginal computational costs. We compared our approach to deformable registration via B-splines, demons and the SyN method on 22 registration tasks from eleven patients. Results showed that our approach is more accurate than the contenders for liver as well as for tumor tissues. We yield average liver volume overlaps of 94.0 +/- 2.7% and average surface-to-surface distances of 2.02 +/- 0.87 mm and 3.55 +/- 2.19 mm for liver and tumor tissue, respectively. The reported distances are close to (or even below) the slice spacing (2.5 - 3.0 mm) of our data. Our approach is also the fastest, taking 35.8 +/- 12.8 s per task. The presented approach is sufficiently accurate to map information available from brachytherapy pre-planning onto interventional data. It is also reasonably fast, providing a starting point for computer-aidance during intervention.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Rak, Marko UNSPECIFIED UNSPECIFIED UNSPECIFIED Koenig, Tim UNSPECIFIED UNSPECIFIED UNSPECIFIED Toennies, Klaus D. UNSPECIFIED UNSPECIFIED UNSPECIFIED Walke, Mathias UNSPECIFIED UNSPECIFIED UNSPECIFIED Ricke, Jens UNSPECIFIED UNSPECIFIED UNSPECIFIED Wybranski, Christian UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-209609
DOI:	10.1007/s11548-017-1633-2
Journal or Publication Title:	Int. J. Comput. Assist. Radiol. Surg.
Volume:	12
Number:	12
Page Range:	S. 2169 - 2181
Date:	2017
Publisher:	SPRINGER HEIDELBERG
Place of Publication:	HEIDELBERG
ISSN:	1861-6429
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language DIFFEOMORPHIC IMAGE REGISTRATION; INTERSTITIAL BRACHYTHERAPY; TUMOR Multiple languages Engineering, Biomedical; Radiology, Nuclear Medicine & Medical Imaging; Surgery Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/20960