Abstract Book

ESTRO 37

S534

Currently, CT scan protocols for treatment planning are not standardized in image acquisition and reconstruction parameters. Hence, the CT-to-SPR conversion (Hounsfield look-up table, HLUT), depending on the former parameters, has to be defined by each center individually. Aiming to access the current status of inter- center differences, this investigation is a first step towards better standardization of CT-based SPR derivation. Material and Methods A questionnaire was sent out to particle therapy centers involved in the EPTN and two centers in the United States. The questionnaire asked for details on CT scanners, acquisition and reconstruction parameters, the calibration and definition of the HLUT, as well as body- region specific HLUT selection. It was also assessed whether the influence of beam hardening (BH) on the HLUT was investigated and if an experimental validation of the HLUT was performed. Furthermore, different future techniques were rated regarding their potential to improve range prediction accuracy. Results Twelve centers completed the survey (10 in Europe, 2 in the US). Scan parameters, in particular reconstruction kernel and beam hardening correction, as well as the HLUT generation varied widely between centers. Eight of the twelve centers applied a stoichiometric calibration method, while three defined the HLUT entirely based on tissue substitutes, and one center used a combination of both. All facilities performed a piecewise linear fit to convert CT numbers into SPRs, but the number of line segments used varied from 2 to 11 (Table 1). Nine centers had investigated the influence of BH, and seven of them had evaluated the size dependence of their conversion. All except one center had validated their HLUT experimentally, but the validation schemes varied widely. A few things were though found to be common for most centers: CT scans were most commonly acquired at 120 kVp, all centers individually customized their CT- to-SPR conversion, and dual energy CT was seen as a promising technique to improve SPR prediction (Figure 1).

Conclusion In general, a large inter-center variability in implementation of CT scans, image reconstruction and especially in CT-to-SPR conversion was found. The benefit of a future standardization is obvious: It would reduce the time-intensive site-specific efforts as well as variations in treatment quality. Due to the interdependency of multiple parameters, no conclusion can be drawn on the derived SPR accuracy and its inter- center variability. As a next step within the EPTN, an inter-center comparison of CT-based SPR prediction accuracy will be performed with a ground-truth phantom. H.Y.C. Wang 1 , E. Donovan 1 , A. Nisbet 2 , S. Alobaidli 3 , I. Phillips 4 , V. Ezhil 4 , P. Webster 5 , M. Ferreira 5 , P. Evans 1 1 University of Surrey, Centre of Vision- Speech and Signal Processing, Guildford, United Kingdom 2 Royal Surrey County Hospital, Medical Physics, Guildford, United Kingdom 3 Kuwait Cancer Control Centre, Radiotherapy Physics, Kuwait, Kuwait 4 Royal Surrey County Hospital, St Lukes Cancer Cantre, Guildford, United Kingdom 5 Alliance Medical Limited, London, United Kingdom Purpose or Objective Grouping of patients based on a threshold value for underlying texture features extracted from standard CT scans is commonly used in prognostic predictive studies including radiomics. Various quantisation levels to reduce noise and artefacts in analyses have been used without a firm recommendation. The aim of this study is to assess the effect of quantisation levels on image entropy (intra- voxel heterogeneity) from Grey Level Co-occurrence Matrix (GLCM) for lung cancer patients based on two methods with different intensity range to arrive at a robust methodology for standardisation and inter-cohort comparison. Material and Methods 37 NSCLC patients with Positon Emission and Computed Tomography (PET/CT) datasets were included. Gross tumour volumes (GTV) were manually outlined by PO-0970 Robustness of Texture as a Biomarker in Radiomics Applications