Abstract Book

S1160

ESTRO 37

Research, Milano, Italy 2 European Institute of Oncology, Unit of Medical Physics, Milano, Italy 3 European Institute of Oncology, Nuclear Medicine, Milano, Italy 4 University of Milano, Radiology and Radiotherapy Techniques, Milano, Italy 5 Centro Nazionale di Adroterapia Oncologica CNAO, Medical Physics Unit, Milano, Italy 6 Centro Nazionale di Adroterapia Oncologica CNAO, Radiation Oncology, Milano, Italy 7 Tecnologie Avanzate T.A. s.r.l., Research & Development, Udine, Italy Purpose or Objective To investigate the potential impact of 68Ga-DOTATOC PET/CT in addition to MRI and CT for retrospectively assessing the GTV delineation of meningiomas of the skull base in patients treated with particle therapy. Material and Methods Sixteen patients (median age 51.4 y) with skull base meningiomas underwent 68Ga-DOTATOC PET/CT for diagnosis followed by constract-enhanced (CE) MRI and CT for treatment planning with particle therapy. GTV for treatment was defined on the CE-MRI fused to the simulation CT (CT sim ) integrating information from the PET/CT. Three methods to delineate the PET volume were evaluated: manual (PET man ), semiautomatic (42% threshold of SUV max , PET SUV42% ) and an automatic adaptive thresholding method incorporating PET reconstruction parameters (PET auto ) (iTA, TA, Udine). PET man volumes were delineated by the same nuclear medicine physician, while PET SUV42% and PET auto volumes were determined by medical physicists. The PET/CT, CE-RMI and CT sim were co-registered with a deformable image registration algorithm using the MIM Software (v. 6.1) and tumor volumes and positions were determined. The overlapping region of MRI and PET man resulted in GTV common . Results The analyzed lesions had a median SUV max of 12.1 ± 6.8 (range: 3.2-32.6). Overall, the GTV-MRI was larger than GTV-PET man in 7 patients (43.8%), smaller in 6 (37.5%) and almost the same in 3 (18.8%). The median value of the different volumes were: GTV-MRI = 14.3 ± 37.2 cc, GTV- PET man = 14.4 ± 47.0 cc, GTV common = 12.2 ± 33.6 cc, GTV- PET SUV42% = 8.3 ± 18.3 cc, GTV-PET auto = 11.3 ± 26.2 cc. As expected, volumes determined by the fixed threshold technique were always smaller than GTV-PET man (D = - 51.0 ± 32.7%) and GTV-PET auto (D = - 21.5 ± 12.7%) since they do not take into account variations in tumor heterogeneity. The largest differences were observed for lesion showing a high SD of SUV. The median difference between GTV-PET man and GTV-PET auto was 39.6 ± 29.5 cc. Conclusion 68Ga-DOTATOC-PET/CT seems to improve the target volume delineation in skull base meningiomas, often leading to a reduction of GTV compared with results from MRI. The automatic adaptive thresholding delineation method may provide robust and reliable tool to help physician in segmenting PET images, reducing inter- and intra-observer variability. EP-2111 Improving the spatial accuracy of PET-guided dose painting through constrained PET image deblurring D. Di Perri 1,2 , S. Guérit 3 , N. Christian 4 , A. Robert 5 , J. Lee 1 , X. Geets 1,2 1 Université catholique de Louvain, IREC/MIRO, Brussels, Belgium 2 Cliniques universitaires Saint-Luc, Radiation oncology, Brussels, Belgium 3 Université catholique de Louvain, ICTM/ELEN, Louvain- la-Neuve, Belgium 4 Hôpital de Jolimont-Lobbes, Radiation oncology, La Louvière, Belgium

might be of prognostic value in patients with head and neck squamous cell carcinoma (HNSCC) and allows for treatment modification. However, tumor visibility on MRI decreases during treatment hampering tumor delineation and increasing observer variation. To avoid this, functional diffusion maps can be used to objectively analyze ADC changes in time on a per-voxel basis. This requires images with good geometric accuracy to enable image registration of the time series. Split-echo acquisition of FSE signals (SPLICE) sequences have superior geometric performance to echo planar imaging (EPI) sequences and can therefore provide these distortion free DW-MRI images. Aim: To follow treatment response on DWI of head and neck tumors using functional diffusion maps. Material and Methods Twelve patients treated with radiotherapy, with or without concurrent chemotherapy, underwent MRI prior to and during week 2, 3, 4 and 5 of the radiotherapy treatment. The MRI protocol contained SPLICE DW-MRI sequences with b-values of 0, 200 and 800 s/mm 2 . All imaging was obtained with the patient positioned in the radiotherapy mask. The tumor was solely de lineated on the pretreatment diffusion weighted MR images and ADC map resulting in a tumor mask. ADC maps were all registered rigidly to the MRI pretreatment . Functional diffusion maps were created for all patients using a threshold of 0.3 10 -3 mm 2 /s for ADC changes (figure 1). Results During (chemo)radiotherapy more tumor voxels showed increase (mean 33%) in ADC than a decrease (9%) (figure2). ADC increase was already apparent in the second week of treatment except in one patient. ADC decrease mostly points to volume decrease, which was most apparent from week 4 during treatment on. Conclusion During (chemo)radiotherapy, tumor response using DW- MRI mostly showed increase of apparent diffusion coefficient in around one third of voxels as soon as the second week into treatment. This can be interpreted as reduction of cell density by necrosis, replacement of tumor by normal tissue and edema in and around remaining tumor tissue. Decrease in ADC is most evident from week 4 into treatment on. This suggests a reduction of tumor voxels replaced by air containing voxels. Functional diffusion maps provide an objective measure to follow response on DW-MRI during treatment provided a good geometric accuracy as is offered by the SPLICE technique.

Figure 1 Functional diffusion map of a patient. Showing the ADC maps acquired prior to and during treatment (upper row). The tumor mask is shown in the lower left corner. Further the increase (red) and decrease (blue) on a per-voxel basis is shown in the lower row. EP-2110 Target volume definition with MRI and 68Ga- DOTATOC-PET/CT for patients with meningiomas C. Garibaldi 1 , M. Ferrari 2 , M. Colandrea 3 , A. Cascio 4 , M. Ciocca 5 , A. Iannalfi 6 , E. D'Ippolito 6 , S. Pesente 7 , C. Grana 3 , M. Cremonesi 1 1 European Institute of Oncology, Unit of Radiation