Automated, reference-free local error assessment of multimodal deformable image registration for radiotherapy in the head and neck. Issue 3 (December 2017)

• Record Type: Journal Article
• Authors: Nix, Michael G.; Prestwich, Robin J.D.; Speight, Richard
• Is Part Of: Radiotherapy and oncology. Volume 125:Issue 3(2017:Dec.)
• Page Start: 478
• Page End: 484
• Publication Date: 2017-12
• Subjects: Deformable image registration -- Multimodal registration -- Contour propagation -- Accuracy assessment -- Head and neck; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2017.10.004
• Languages: English
• ISSNs: 0167-8140

Abstract

Abstract: Background: Head and neck MR-CT deformable image registration (DIR) for radiotherapy planning is hindered by the lack of both ground-truth and per-patient accuracy assessment methods. This study assesses novel post-registration reference-free error assessment algorithms, based on local rigid re-registration of native and pseudomodality images. Methods: Head and neck MR obtained in and out of the treatment position underwent DIR to planning CT. Block-wise mutual information (b-MI) and pseudomodality mutual information (b-pmMI) algorithms were validated against applied rotations and translations. Inherent registration error detection was compared across 14 patient datasets. Results: Using radiotherapy position MR-CT DIR, quantitative comparison of applied rotations and translations revealed that errors between 1 and 4 mm were accurately determined by both algorithms. Using diagnostic position MR-CT DIR, translations of up to 5 mm were accurately detected within the gross tumour volume by both methods. In 14 patient datasets, b-MI and b-pmMI detected similar errors with improved stability in regions of low contrast or CT artefact and a 10-fold speedup for b-pmMI. Conclusions: b-MI and b-pmMI algorithms have been validated as providing accurate reference-free quantitative assessment of DIR accuracy on a per-patient basis. b-pmMI is faster and more robust in the presence of modality-specific information.