ESTRO 36 Abstract Book

S79 ESTRO 36 _______________________________________________________________________________________________

OC-0156 Automated reference-free local error assessment in clinical multimodal deformable image registration M. Nix 1 , R. Speight 1 , R. Prestwich 2 1 St James' Institute of Oncology, Radiotherapy Physics, Leeds, United Kingdom 2 St James' Institute of Oncology, Clinical Oncology, Leeds, United Kingdom Purpose or Objective Multimodal deformable image registration (MM-DIR), for MR-CT fusion in RT planning, is a difficult problem. Algorithms in commercial applications can leave significant residual errors and performance can vary considerably through a 3D image set. Currently, quality assessment relies on clinical judgement or time- consuming landmarking approaches for quantitative comparison. Due to the variability of MM-DIR performance, a pre-clinical commissioning approach cannot be relied upon to quality assure clinical performance. The primary objective was to develop and validate an automated method for localised error assessment of clinical multimodal deformable image registrations, without reference data. This should aid clinical judgement of registration reliability across the volumetric data and hence increase clinical confidence in MM-DIR fusion for RT planning. Material and Methods A computational method for determining the local reliability of a given clinical registration has been developed. Two registration assessment algorithms, using blockwise mutual information (BMI) and pseudo-modal cross correlation (pmCC) respectively, have been implemented and compared. Error information is presented as a quantitative 3D ‘iso-error’ map, showing areas of a registered dataset where errors are greater than a certain magnitude and may not be reliable, e.g. for contouring tumour or organ at risk volumes. The developed software was validated using a ‘gold-standard’ rigidly-registered image set, derived from immobilised MR, registered to immobilised CT, which was deformed with known rotations, translations and more complex deformation fields. Detected and applied errors were compared across the dataset. Mean errors within the GTVs of 14 head and neck MR-CT registrations were analysed using the BMI method and used to identify cases where the registration may be clinically unacceptable. Results Both algorithms consistently detected applied errors larger than 2 mm. Errors detected using the BMI method, following intentional rotation of gold-standard pre- registered clinical MR data, were strongly correlated with applied errors, in magnitude and direction (Pearson’s r > 0.96).

Analysis in the direction orthogonal to the applied deformation showed minimal errors, as expected ( = 0.32 mm, SD = 0.43 mm). Across 14 clinical MR-CT registration datasets, mean magnitude registration errors within the GTV varied from 0.4 to 5.4 mm (population mean = 1.8 mm), indicating that MM-DIR errors can be significant for RT planning.

Conclusion Reference free localised registration quality assessment offers clinicians a tool to judge registration reliability, which could increase confidence in and clinical usage of MM-DIR in radiotherapy. A software tool was developed and validated to achieve this. A strong correlation was found between detected and applied registration errors. Mean GTV error is a potential indicator for clinical acceptability of registrations. OC-0157 Atlas-based segmentation of prostatic urethra in the planning CT of prostate cancer O. Acosta 1 , M. Le Dain 1 , C. Voisin 1 , R. Bastien 1 , C. Lafond 2 , K. Gnep 2 , R. De Crevoisier 2 1 LTSI-INSERM UMR 1099, Université de Rennes 1, Rennes, 2 Centre Eugene Marquis, Radiotherapy, Rennes, France Purpose or Objective to the dose delivered mainly to the bladder) and likely also to the urethra (obstructive symptoms). Identification of urethra for dose assessment from planning CT scans is however challenging as the organ lies inside the prostate and is not visible. Moreover, the dose received by the urethra may not be superposed to the dose received by the whole prostate. In case of prostate IMRT, the goals of this work were therefore: i) to propose an automatic method for urethra segmentation from the planning CT and ii) to quantify the dose received by the urethra. Material and Methods An original weighted multi atlas-based segmentation method was devised standing on a global characterization of the urethra wrt the surrounding organs. For building the atlas a first set of CT scans (512×512 0.63×0.63 mm axial pixels and 3 mm slices) from 80 patients treated for localized prostate cancer with Iodine 125 brachytherapy was used. All the patients had an urinary probe allowing an ease manual urethra segmentation. Prostate, bladder and urethra were delineated by a radiation oncologist. An average patient, in terms of prostate volume, was selected as common reference system where all the patients were rigidly aligned. Each segmented urethra was characterized by its central line, the relative bladder position and prostate characteristics (height, excentricity and volume). An in-house demons based registration using prostate contours and Laplacian maps was performed to