ESTRO 36 Abstract Book

S137 ESTRO 36 _______________________________________________________________________________________________

Purpose or Objective Target volumes based on patient’s individual respiratory motion, so-called motion specific target volumes, can possibly improve target coverage and reduce dose to healthy tissue. We have derived motion specific target volumes for stereotactic body radiation therapy (SBRT) of liver tumors based on deformable image registration (DIR) of 4DCT images and assessed the intrahepatic accuracy for these algorithms. Material and Methods 4DCT data sets of 15 patients in head-first supine position were obtained with a Brilliance Big Bore 16-slice CT scanner (Philips Healthcare, OH, US) and reconstructed using phase binning. Patients were positioned using a BlueBAG Vacuum Cushion (Elekta, Sweden) and immobilized with a SBRT Body Pro-Lok system with abdominal compression plate (CIVCO, IA, US). Consecutive DIR of the 4DCT images was used to track patient’s individual respiratory motion by mapping voxels over 10 respiratory phases. Two DIR algorithms were used: a hybrid algorithm based on intensity and delineated contours (ANACONDA), and a biomechanical algorithm based on the finite element method (MORFEUS). The hybrid algorithm was employed with and without delineation of the liver contour. The motion specific target volume was created by propagating a gross target volume (GTV) contoured on a reference CT over the obtained vector fields. The target volume encompasses the GTV of 10 respiratory phases plus a 3 mm set-up margin in order to account for variations in patient setup. The motion specific target volumes were compared with volumes generated using static margins (6x6x10 mm) according to the clinical protocol. To evaluate the intrahepatic performance, fiducial markers were used as points-of-interest to calculate the residual error after registration. The fiducial registration error (FRE, mean absolute residual error) was chosen as the measure to compare the algorithms. Results The motion specific target volumes resulted in the following average target volumes: hybrid: 33 ± 36.1 cc, hybrid with liver contour guidance: 37.0 ± 27.5 cc and biomechanical: 39.7 ± 29.4 cc. The average volume using static margins of 6x6x10 mm was 56.9 ± 38.8 cc. In 7 out of 15 cases the static margins did not encompass the motion specific situation, leaving target tissue uncovered. The hybrid algorithm with and without additional liver contouring resulted in a FRE of 0.8 ± 0.8 mm and of 0.8 ± 0.5 mm respectively. The biomechanical algorithm showed a FRE of 1.9 ± 1.0 mm. Conclusion The motion specific target volumes show a volume reduction compared to the target volumes generated using static margins. Besides that, the motion specific target volume extends the with static margins derived target volume. Motion specific target volumes using deformable image registration could decrease the dose to healthy tissue and potentially improve target coverage. The hybrid algorithm resulted in a lower FRE compared to the biomechanical algorithm.

consistent reporting of treatment planning for regional nodal radiotherapy, particularly within clinical trials. It is on this foundation that the ESTRO consensus guideline for elective breast cancer radiotherapy has been developed. We set out to evaluate variability of lymph node contouring using the ESTRO consensus guideline across multiple investigators and sites. Material and Methods As part of the UK FAST-Forward trial RTQA programme each co-investigator is required to delineate a LN CTV comprising of levels 1-4 as defined by the ESTRO guideline on an outlining benchmark CT dataset. LN CTV’s were defined by three clinicians (LN_CTV_CLIN_1/2/3) of the Trial Management Group (TMG) with experience of the ESTRO guidelines and a consensus LN CTV defined through discussion and comparison. LN CTV’s of 39 investigators from 32 radiotherapy centres were analysed using in-house software based on the Computational Environment for Radiotherapy Research (CERR). Discordance Index (DI), Geographical Miss Index (GMI), Jaccard Index (JI), and Mean Distance to Conformity (MDC) indices were generated, comparing LN_CTV_CLIN_1/2/3 and investigators LN CTV’s to the consensus LN CTV in addition to standard volume statistics. Results The interobserver variation (SD/Mean) in volume contoured between the investigators was lower compared to published literature(40.8%/55.9% axillary nodes and 60.5% SCF nodes- Li et al,2009). The JI results indicate investigator volumes achieved conformity in relation to the consensus comparable to LN_CTV_CLIN_1 with the SD supporting low interobserver variability across submissions. Larger mean and minimum DI compared to GMI indicate a trend for over contouring across investigator submissions, however associated range and SD supports MDC analysis showing a larger degree of variation was associated with under contouring. MDC analysis on a slice by slice basis identifies defining the caudal extent of level 1 as the region associated with the largest degree of under contouring and the caudal aspect of levels 3/4 with over contouring. It is important to consider the variation in volume and conformity in context of the ESTRO guidelines which acknowledge that the anatomical boundaries are not considered exact to mm, with a range in JI scores between consensus clinicians despite the indices indicating good spatial relationship to the consensus. Conclusion Contouring of the regional lymph nodes using the ESTRO consensus reduces interobserver variability in volume contoured. Comparing the consensus clinicians and investigator results suggest that experience and/or training is associated with less interobserver variability, promoting the role of RTQA when adopting new outlining guidelines as part of a multicentre trial. OC-0266 Motion specific target delineation significantly reduce treated volumes in liver SBRT J. Wielaard 1,2 , C.H. Slump 2 , K. Muller 1 , A.W.H. Minken 1 , H. Westendorp 1 1 Radiotherapiegroep Behandellocatie Deventer, Medical Physics, Deventer, The Netherlands 2 University of Twente, MIRA: Institute for Biomedical Technology and Technical Medicine, Enschede, The Netherlands