ESTRO 37 Abstract book

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ESTRO 37

7 German Cancer Consortium DKTK, partner site Dresden, Dresden, Germany 8 National Center for Tumor Diseases NCT, partner site Dresden, Dresden, Germany Purpose or Objective Recent studies demonstrate the clinical reliability and improved accuracy of dual-energy CT (DECT) in proton therapy. Still, a generic heuristic conversion (HLUT) of CT number to stopping-power ratio (SPR) is used in clinical routine, since a medical device for patient-specific DECT- based SPR prediction is not yet available. Here, we propose an applicable method for HLUT optimization using information from patient-specific DECT-based SPR prediction on a broad patient cohort. Material and Methods Clinical DECT scans of 102 brain-, 25 prostate- and 3 lung- tumor patients were evaluated in total. Each scan was acquired with a single-source DECT scanner (Definition AS) and processed in syngo.via (both Siemens Healthineers) to generate 79keV pseudo-monoenergetic CT (MonoCTs) and SPR datasets (derived from electron density and photon cross section). Voxelwise correlations of CT number and SPR were determined within the irradiated volume (20% isodose) and expressed as frequency distribution including patient information of all 3 cohorts. A piece-wise linear function was defined minimizing the deviation from the median SPR distribution for each CT number (DECT-based adapted HLUT). The intra- and inter-patient variability was also obtained from the frequency distribution. To assess dose differences and range shifts, proton treatment plans were recalculated in XiO (Elekta) on MonoCT using (A) clinical or (B) adapted HLUT, and (C) patient-specific DECT-based SPR datasets. Results Mean range shifts (±1SD) of 1.2(±0.7)% for brain-, 1.7(±0.5)% for prostate- and 2.3(±0.8)% for lung-tumor patients were determined using the clinical HLUT instead of the patient-specific DECT-based SPR prediction. On average the clinical HLUT predicted larger SPR for brain, muscle and trabecular bone leading to this systematic range deviation. This effect is partially compensated in brain-tumor patients, since the clinical HLUT provides a smaller SPR for cortical bone. Using the DECT-based adapted HLUT (Fig. 1), mean range shifts were significantly reduced (p<<0.001, two-sample t-test) below 0.3% (Fig. 2). Hence, the adapted HLUT achieves a reduction of systematic deviations for all 3 tumor sites while standard deviations remained almost unchanged. Still, range shifts larger than 1% arise owing to the large intra-patient soft tissue diversity of approx. 6% (95% CI) and age-dependent inter-patient bone variation of 5%.

Conclusion DECT provides patient-specific information on tissue diversity and its respective proportion, which is applicable to HLUT refinement reducing systematic deviations of a standard clinical CT calibration. In principal, this can also be transferred to particle-therapy centers not using DECT. The HLUT adaptation was clinically implemented in our institution and represents a further step toward full integration of DECT for proton treatment planning. A future clinical implementation of patient-specific DECT-based SPR prediction would also individually consider intra- and inter-patient tissue variability. OC-0086 Validation of proton stopping power ratio estimation based on dual energy CT using organic tissues V.T. Taasti 1 , G.J. Michalak 2 , D.C. Hansen 1 , A.J. Deisher 3 , J.J. Kruse 3 , B. Krauss 4 , L.P. Muren 1 , J.B.B. Petersen 1 , C.H. McCollough 2 1 Aarhus University Hospital, Dept. of Medical Physics, Aarhus, Denmark