ESTRO 38 Abstract book

S1091 ESTRO 38

these results suggest the definition of anisotropic clinical ITV-to-PTV margins depending on target position: tighter margins for LL and AP directions and for lung tumors positioned in the upper lobe of the lung. EP-1996 Assessment of bulk-density CT accuracy for MR-guided proton therapy of prostate cancer J. Handrack 1,2 , M. Bangert 1,2 , C. Möhler 1,2 , M. Ellerbrock 2,3 , S. Greilich 1,2 1 German Cancer Research Center DKFZ, Department of Medical Physics in Radiation Oncology, Heidelberg, Germany ; 2 National Center for Radiation Research in Oncology, Heidelberg Institute for Radiation Oncology, Heidelberg, Germany ; 3 Heidelberg University Hospital, Heidelberg Ion-Beam Therapy Center HIT- Department of Radiation Oncology, Heidelberg, Germany Purpose or Objective Magnetic resonance (MR) imaging offers superior soft tissue contrast in comparison to computed tomography (CT) images and can be used to monitor anatomical changes in the patient during the treatment. Therefore, interest in MR guidance for proton therapy, which is highly susceptible to changes, is growing. However, the conversion of the MR image to so-called “synthetic CT (sCT)” images is necessary, since they lack stopping-power information. So far, mostly machine learning techniques have been applied to address this problem, but the required complexity of the sCT is still unknown. In this work, the influence of bulk density (BD) substitutes for different tissues was investigated for the male pelvis to identify the minimum number of BD classes necessary for accurate range prediction with a sCT. Material and Methods The planning CT images from three prostate cancer patients irradiated with protons were retrospectively analysed by segmenting the CT into different tissue classes, which were replaced with mean BD values. Two types of BD-CTs were investigated: BD-CT1 contains four tissue classes, namely air, fat, non-fatty soft tissue and bone. For BD-CT2, the bone segment was further split into soft and hard bone. The clinical dose plans, consisting of two opposing beams, were re-calculated on the BD-CTs. The resulting dose distributions were compared to the original ones by means of gamma analysis (2mm/2%), dose volume metrics (DVMs), and proton range differences. Results For BD-CT1, a mean absolute range difference (± mean s.d.) of (2.2±2.7) mm was found. When splitting bone into soft and hard bone (BD-CT2), the mean absolute range difference was reduced to (1.4±1.8) mm. Figure 1 shows this reduction exemplarily for the range shift maps of BD- CT1 and BD-CT2 for one patient. The mean gamma pass rates for the CTV and V >2%presDose (the volume where the dose was larger than 2% of the prescribed dose) were 99.6% and 98.8% for BD-CT1, and 99.9% and 99.6% for BD- CT2, respectively. For target volumes, D 2 , D 50 and D 98 were compared, which deviated less than 1.5% from the original plan for both BD-CT1 and BD-CT2, except for PTV-D 98 of one patient case, which deviated up to 2.9%. For the organs at risk, D 50 and D 15 were compared, which deviated up to 2.6%, however no RTOG dose constraints were exceeded.

Results The inter-fraction target motion variability showed a distribution that ranges from zero to almost 1 cm in the worst case. SI direction was found to have the biggest discrepancy, followed by AP direction and LL. As expected, the variability was particularly significant for patients with a lesion in the lower lobe of the lung. For SI direction median values are respectively 0.9, 1.8 and 2.8 mm for upper, middle and lower lobe (fig.2).Target in the upper and medium lobe showed a stable motion along LL direction:for most of the patients the variability was less than 2 mm.

Conclusion Targets in the lower lobe of the lung showed higher motion variability. SI direction, was found to have the biggest target motion discrepancy, followed respectively by AP and LL directions. Since the inter-fraction variability of the respiratory induced tumor motion contributes to the definition of the motion component of the PTV margin,