ESTRO 2022 - Abstract Book

S1260

Abstract book

ESTRO 2022

Figure 1: Histogram of found positioning deviations in OPT. Image insert shows the patient’s reference axes.

Conclusion The found statistics will be used as an baseline accuracy in future work towards clipless treatment.

PO-1485 Contour guided deformable image registration for adaptive radiotherapy

L. Bosma 1 , M. Ries 2 , B. Denis de Senneville 3 , B. Raaymakers 1 , C. Zachiu 1

1 UMC Utrecht, Department of Radiotherapy, Utrecht, The Netherlands; 2 UMC Utrecht, Imaging Division, Utrecht, The Netherlands; 3 CNRS/University of Bordeaux, Institut de Mathematiques de Bordeaux (IMB), Talence, France Purpose or Objective Deformable image registration (DIR) is a core element in the development of adaptive radiotherapy workflows, integrating daily contour propagation and/or dose accumulation within their design. Prior to the daily therapy session however, the contours generated by DIR may undergo manual adjustments by the operator, which in turn locally invalidate the estimated deformation vector field (DVF). With the new contours and accumulated dose no longer in correspondence, the DVF requires a re-calculation in accordance with the corrections of the operator. Here, we present a novel DIR algorithm that incorporates manual contour information to guide automatic registration results.

Materials and Methods We propose estimating the adjusted deformations as the minimizer of the following cost function:

where the first term aims to align similar contrast patterns in the reference and moving images (as proposed in [1]). The second term is the sum of squared differences between the reference and the daily “operator-validated” contours. The final term constrains the estimated deformations to be spatially smooth, making the problem mathematically well-posed. We have validated the algorithm on 20 clinical “planning MR” to “daily MR” registrations for prostate cancer patients, with clinical contours available for both image sets, as well as on a dataset generated using biomechanically-simulated deformations. The algorithm is compared against the EVolution algorithm [1], which employs the same cost function as above but without the second contour-guidance term. The algorithm is evaluated in terms of the Dice similarity coefficient, and the endpoint error and dose error for the biomechanical simulation. Results As expected, our contour-guided algorithm increases the mean Dice similarity coefficient for the 20 prostate registrations from 0.81 for EVolution without contour-guidance to 0.99, see Figure 1a. More importantly, compared to EVolution without contour-guidance, the mean endpoint error on the prostate decreases by a factor of 1.4 from 0.65 mm to 0.46 mm for the simulated prostate case (see Figure 1b) and the mean absolute dose error on the prostate decreases by a factor of 1.4 from 0.13 Gy to 0.09 Gy, see Figure 1c. Also, no new errors are created by using our proposed method.