Surface-constrained nonrigid registration for dose monitoring in prostate cancer radiotherapy - Abstract

When no means are available for directly measuring 3D dose distribution, online imaging could be employed for dose monitoring in image guided radiotherapy (IGRT).

This paper addresses the issue of cumulative dose estimation from CBCT images in prostate cancer radiotherapy cases. It focuses on the dose received by the surfaces of the main organs at risk, namely the bladder and rectum. We have proposed both a surfaceconstrained dose accumulation approach and its extensive evaluation. Our approach relied on the nonrigid registration (NRR) of daily acquired CBCT images on the planning CT image. This proposed NRR method was based on a Demons-like algorithm, implemented in combination with mutual information metric. It allowed for different levels of geometrical constraints to be considered, ensuring a better point to point correspondence, especially when large deformations occurred, or in high dose gradient areas. The three following implementations of the NRR approach with different levels of constraints were considered: (i) full iconic NRR; (ii) iconic NRR constrained with landmarks defined interactively at the surface of organs (LCNRR); (iii) NRR constrained with full delineation of organs (DBNRR). To assess dose accumulation accuracy, we designed a numerical phantom based on finite-element modeling and image simulation. This model provided known deformations of organs and a reference accumulated dose. The methods were assessed on both the numerical phantom and real patient data in order to quantify uncertainties in terms of dose accumulation. The LCNRR method appeared to constitute a good compromise between dose monitoring capability and compatibility with clinical practice constraints (low interactivity level).

Written by:
Cazoulat G, Simon A, Dumenil A, Gnep K, de Crevoisier R, Acosta-Tamayo O, Haigron P.   Are you the author?

Reference: IEEE Trans Med Imaging. 2014 Apr 1. Epub ahead of print.
doi: 10.1109/TMI.2014.2314574


PubMed Abstract
PMID: 24710827

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