ESTRO 36 Abstract Book

S928 ESTRO 36 2017 _______________________________________________________________________________________________

around the GTV was used. Observers also contoured the GTV in accordance with local clinical protocols using CT- MR images (GTV_c) and scored their confidence in these contours on a scale of 1 to 5, 5 being complete confidence. Differences between CT-MR and MR volumes were assessed using paired T-Test. Inter-observer variability was assessed using an analysis of variance. The threshold for significance was p<0.05. Results Four observers participated in the study, three of whom had at least 3 years’ experience in treating this patient group; two contoured 20 cases, one 19 and one 18. A summary of the results are presented in Table 1. MR only based volumes were statistically significantly smaller for all observers for each GTV_i, GTV_o and GTV_c, whilst the confidence scores in GTV_c were higher for all observers, although for one this was not statistically significant. The magnitude of the offset between the centres of GTV_i and GTV_o was calculated and the difference in these offsets compared between CT-MR and MR only contours. An overall difference was detectable for only one observer, in which the distance between GTV_i and GTV_o were smaller in the MR only images. For the remaining observers, the agreement in the position of the volumes was not affected by the imaging modality. Boundary intervals were smaller on the MR only images for all observers, although this difference was not statistically significant for Observer 3. The impact of multimodality imaging on observer variation for the boundary interval size was tested using 17 cases contoured by all observers, by comparing the ratio of the boundary interval size from CT-MR to MR only between observers. This did not show a statistically significant difference between the observers, with a p-value of 0.507.

Research involving imaging data requires intensive use of costly DICOM operations in order to aggregate the data for research. We installed software SeDI (Semantic DICOM, developed by SOHARD) which creates a database containing all radiotherapy-related DICOM metadata using a Semantic PACS that extracts and stores header tags in a special type of database. The resulting database can be searched with the standardized query language SPARQL using terms from DICOM and a radiation oncology vocabulary. Once all relevant DICOM tags have been extracted by SeDI, DICOM search is significantly accelerated and can often be expressed as a single query. The aim of this work is to show how SeDI helps to quickly resolve typical DICOM queries. Material and Methods In order to quantify the potential speedup for a representative task using SeDI we measured the time spent to retrieve: the UIDs of the RTDose, RTStruct and RTPlan for a set of patients where 1) a relevant organ at risk is delineated and 2) the required DICOM objects exist in the clinical database. Such a question is relevant if, for example, one wants to calculate DVHs for a large number of patients. Our conventional approach to such a problem would be to use a simple tool that browses through all patients on the DICOM server, find the associated RTStruct, check whether the organ at risk is delineated, and check if the associated RTDose exists in a RTPlan that makes use of the RTStruct. Using the logfiles of the tool that performs these steps, we can estimate the efficiency by using a direct indexing of the relevant DICOM objects using SeDI. Results Using the mentioned logfiles, we found that the above question was asked for 7384 patients. Lookups for 2176 patients found the DICOM objects that met all criteria in a total time of 14.24 hours with an average DICOM lookup time of 23.6 seconds. Lookups for 5208 patients failed to find matching DICOM objects at a total cost of 23.48 hours and an average DICOM lookup time of 16.2 seconds. Since failed lookups would not occur using SeDI, the use of SeDI would save at least the 71% of the search time spent on non-matching queries in our study question, amounting to 23.48 hours saved out of 37.72 total hours. By direct indexing of the relevant objects further time decrease is expected, but the magnitude of this remains open for study. Conclusion We expect that SeDI will enable the researchers to rapidly identify the right DICOM objects for calculations, as well as accelerate ongoing research in outcome prediction, toxicity modelling and radiomics. EP-1717 Image Quality Comparison Between Two Radiotherapy Simulators N. Tomic 1 , P. Papaconstadopoulos 1 , J. Seuntjens 1 , F. DeBlois 1 , S. Devic 1 1 McGill University, Oncology, Montreal, Canada Purpose or Objective In this work we compare image quality parameters derived from phantom images taken on two CT simulators most commonly used in radiotherapy departments. To make an unbiased comparison, CT images were obtained with CT scanning protocols leading to the same surface doses, measured using XR-QA2 model GafChromic film reference dosimetry protocol. Material and Methods Two radiotherapy CT simulators GE LS 16 (80 cm bore size) and Philips Brilliance Big Bore (85 cm bore size) were compared in terms of image quality using CATPHAN-504, scanned with Head and Pelvis protocols. Dose was measured at the phantom surface with CT scans taken until doses during CT scans on both scanners were within 5%. Dose profiles were sampled using XR-QA2 model GafChromic TM film strips placed at four sides of the phantom (top, bottom, left, and right) and taped with a

Conclusion Contouring centrally recurrent GTVs using only MR images, instead of the current practice of co-registered CT-MR images, produces smaller volumes. When using MR images alone, clinicians have a higher confidence in their clinical GTV contours as well as having lower delineation uncertainties overall. The differences between CT-MR and MR only boundary intervals did not vary between observers. This reduction in uncertainties supports an MR- based workflow. [1] Bernstein, D., et al., Measurement of GTV delineation uncertainty for centrally recurrent gynaecological cancers. Radiotherapy and Oncology, 2015. 119 (1): p. 5615-5616. EP-1716 Semantic PACS deployment enables research in a radiation oncology research environment M.S. Marshall 1 , H. Beemster 1 , M. Buiter 1 , T. Janssen 1 1 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Clinical Physics, Amsterdam, The Netherlands

Purpose or Objective