Surface-Constrained Nonrigid Registration for Dose Monitoring in Prostate Cancer Radiotherapy

• Published in: IEEE transactions on medical imaging Vol. 33; no. 7; pp. 1464 - 1474
• Main Authors: Cazoulat, Guillaume, Simon, Antoine, Dumenil, Aurelien, Gnep, Khemara, de Crevoisier, Renaud, Acosta, Oscar, Haigron, Pascal
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); Institute of Electrical and Electronics Engineers
• Subjects: Accuracy; Algorithms; Bioengineering; Bladder; Computed tomography; Cone beam computed tomography (CT); Cone-Beam Computed Tomography - methods; dose accumulation; Humans; Life Sciences; Male; nonrigid registration; Numerical models; Phantoms; Phantoms, Imaging; Planning; Prostate - diagnostic imaging; Prostate cancer; Prostatic Neoplasms - diagnostic imaging; Prostatic Neoplasms - radiotherapy; Radiographic Image Enhancement - methods; radiotherapy; Radiotherapy Planning, Computer-Assisted - methods; Rectum - diagnostic imaging; Urinary Bladder - diagnostic imaging; radiotherapy; prostate cancer; dose accumulation; Cone Beam CT; Nonrigid registration
• ISSN: 0278-0062; 1558-254X; 1558-254X
• DOI: 10.1109/TMI.2014.2314574

This paper addresses the issue of cumulative dose estimation from cone beam computed tomography (CBCT) images in prostate cancer radiotherapy. 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 surface-constrained 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: 1) full iconic NRR; 2) iconic NRR constrained with landmarks (LCNRR); 3) NRR constrained with full delineation of organs (DBNRR). To obtain reference data, we designed a numerical phantom based on finite-element modeling and image simulation. 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 for dose monitoring in clinical practice.