ESTRO 36 Abstract Book

S496 ESTRO 36 _______________________________________________________________________________________________

Physics, Odense, Denmark 16 Hospital of Næstved, Oncology, Næstved, Denmark

Figure 1.

Purpose or Objective To internally and externally validate an atlas based automated segmentation (ABAS) tool for loco-regional radiation therapy of early breast cancer based on the ESTRO consensus guideline for target volume delineation. Material and Methods Structures of 60 patients manually delineated according to the ESTRO consensus guideline were included in four categorized multi-atlas libraries (based on laterality and surgery) using MIM Maestro ™ software. These libraries were used for automated segmentation of primary and nodal target volumes and organs at risk. Internal Validation of ABAS was done by comparing ABAS before and after correction against a gold standard manual segmentation (MS) in 50 patients from the local institution using Dice Similarity Coefficient (DSC), Average Hausdorff Distance (AHD), difference in volume (∆V) and time. External validation was done by comparing ABAS without correction against MS in 40 patients from other institutions using DSC and AHD. In the internal validation phase MS and correction of ABAS was performed by only one observer, while in the external validation phase MS was performed by multiple observers from 10 different institutions. Results ABAS reduced the time of MS before and after correction by 93% and 32%, respectively. In the internal validation phase, ABAS showed high agreement with MS for lung, heart, breast and humeral head, moderate agreement for chest wall and axillary nodal levels and poor agreement for inter-pectoral, internal mammary nodal regions and left anterior descending coronary artery (Figure 1). Correcting ABAS significantly improved all the parameters defined as increased DSC and decreased AHD and ∆V. Applying ABAS in an external group of patients with different arm positions, immobilization techniques and respiratory gating status showed comparable results (Table 1). Table 1.

Conclusion ABAS is a clinically useful tool for segmenting structures in breast cancer loco-regional radiation therapy in a multi- institutional setting. The introduction of ABAS in daily clinical practice will significantly reduce the workload especially in departments where the radiation therapy technologists (RTTs) are responsible for target volume delineation and treatment planning. Manual correction of some structures is important before clinical use. Moreover, applying ABAS may be a reasonable alternative for consistent segmentation and easy quality assurance testing in multi-institutional trials. Careful selection and stratification of atlas subjects seems to be the most influencing factor in the outcome of the ABAS. Further investigation to find out the best stratification factors is encouraged. Based on these results, ABAS is now made available for Danish patients. PO-0899 Tumor volume delineation us ing non-EPI diffusion weighted MRI and FDG-PET in he ad-and-neck patients. B. Peltenburg 1 , T. Schakel 1 , J.W. Dankbaar 2 , M. Aristophanous 3 , C.H.J. Terhaard 1 , J.M. Hoogduin 2 , M.E.P. Philippens 1 1 UMC Utrecht, Radiation Oncology, Utrecht, The Netherlands 2 UMC Utrecht, Radiology, Utrecht, The Netherlands 3 MD Anderson Cancer Center, Radiation Physics, Houston, USA Purpose or Objective Diffusion weighted (DW) MRI shows high contrast between tumor and the surrounding tissue, which makes it a candidate to facilitate target volume delineation in head- and-neck (HN) radiotherapy treatment planning. In this study we assess the performance of geometrically undistorted DW MRI for target delineation in terms of interobserver agreement and spatial concordance with automatic delineation on 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET). Material and Methods Fifteen head-and-neck cancer patients underwent both standard echo-planar imaging based (EPI) and undistorted fast spin-echo based (SPLICE) DW MRI in addition to FDG- PET for RT treatment planning. Target delineation on DW MRI was performed by 3 observers, while for PET a semi- automatic segmentation was performed using a Gaussian mixture model. Volumes, overlap metrics, defined as dice similarity coefficient and generalized conformity index, and hausdorff distances were calculated from the delineations. Results The median volumes delineated by the 3 observers on DW MRI were 10.8, 10.5 and 9.0 mL respectively. The median conformity index over all patients was 0.73 (range 0.38 – 0.80). On PET, a significantly smaller median volume of 8.0 mL was found. Compared with PET, the delineations