Integration of operator-validated contours in deformable image registration for dose accumulation in radiotherapy

Lando S Bosma; Mario Ries; Baudouin Denis de Senneville; Bas W Raaymakers; Cornel Zachiu

doi:10.1016/j.phro.2023.100483

Integration of operator-validated contours in deformable image registration for dose accumulation in radiotherapy

Phys Imaging Radiat Oncol. 2023 Aug 20:27:100483. doi: 10.1016/j.phro.2023.100483. eCollection 2023 Jul.

Authors

Lando S Bosma¹, Mario Ries², Baudouin Denis de Senneville^{1

3}, Bas W Raaymakers¹, Cornel Zachiu¹

Affiliations

¹ Department of Radiotherapy, UMC Utrecht, Heidelberglaan 100, 3508 GA Utrecht, The Netherlands.
² Imaging Division, UMC Utrecht, Heidelberglaan 100, 3508 GA Utrecht, The Netherlands.
³ Institut de Mathématiques de Bordeaux (IMB), UMR 5251 CNRS/University of Bordeaux, F-33400 Talence, France.

Abstract

Background and purpose: Deformable image registration (DIR) is a core element of adaptive radiotherapy workflows, integrating daily contour propagation and/or dose accumulation in their design. Propagated contours are usually manually validated and may be edited, thereby locally invalidating the registration result. This means the registration cannot be used for dose accumulation. In this study we proposed and evaluated a novel multi-modal DIR algorithm that incorporated contour information to guide the registration. This integrates operator-validated contours with the estimated deformation vector field and warped dose.

Materials and methods: The proposed algorithm consisted of both a normalized gradient field-based data-fidelity term on the images and an optical flow data-fidelity term on the contours. The Helmholtz-Hodge decomposition was incorporated to ensure anatomically plausible deformations. The algorithm was validated for same- and cross-contrast Magnetic Resonance (MR) image registrations, Computed Tomography (CT) registrations, and CT-to-MR registrations for different anatomies, all based on challenging clinical situations. The contour-correspondence, anatomical fidelity, registration error, and dose warping error were evaluated.

Results: The proposed contour-guided algorithm considerably and significantly increased contour overlap, decreasing the mean distance to agreement by a factor of 1.3 to 13.7, compared to the best algorithm without contour-guidance. Importantly, the registration error and dose warping error decreased significantly, by a factor of 1.2 to 2.0.

Conclusions: Our contour-guided algorithm ensured that the deformation vector field and warped quantitative information were consistent with the operator-validated contours. This provides a feasible semi-automatic strategy for spatially correct warping of quantitative information even in difficult and artefacted cases.

Keywords: Adaptive radiotherapy; Constrained motion estimation; Contour guidance; Deformable dose warping; Deformable image registration; Preconditioning.