Studies have shown large variations in stopping-power ratio (SPR) prediction from computed tomography (CT) across European proton centres. To standardise this process, a step-by-step guide on specifying a Hounsfield look-up table (HLUT) is presented here.
The HLUT specification process is divided into six steps: Phantom setup, CT acquisition, CT number extraction, SPR determination, HLUT specification, and HLUT validation. Appropriate CT phantoms have a head- and body-sized part, with tissue-equivalent inserts in regard to X-ray and proton interactions. CT numbers are extracted from a region-of-interest covering the inner 70% of each insert in-plane and several axial CT slices in scan direction. For optimal HLUT specification, the SPR of phantom inserts is measured in a proton beam and the SPR of tabulated human tissues is computed stoichiometrically at 100 MeV. Including both phantom inserts and tabulated human tissues increases HLUT stability. Piecewise linear regressions are performed between CT numbers and SPRs for four tissue groups (lung, adipose, soft tissue, and bone) and then connected with straight lines. Finally, a thorough but simple validation is performed.
The best practices and individual challenges are explained comprehensively for each step. A well-defined strategy for specifying the connection points between the individual line segments of the HLUT is presented. The guide was tested exemplarily on three CT scanners from different vendors, proving its feasibility.
The presented step-by-step guide for CT-based HLUT specification with recommendations and examples can contribute to reduce inter-centre variations in SPR prediction.

OBJECTIVE: Proton treatment planning relies on an accurate determination of stopping-power ratio (SPR) from x-ray computed tomography (CT). A refinement of the heuristic CT-based SPR prediction using a state-of-the-art Hounsfield look-up table (HLUT) is proposed, which incorporates patient SPR information obtained from dual-energy CT (DECT) in a retrospective patient-cohort analysis.
METHODS: SPR datasets of 25 brain-tumor patients, 25 prostate-cancer patients, and three nonsmall cell lung-cancer (NSCLC) patients were calculated from clinical DECT scans with the comprehensively validated DirectSPR approach. Based on the median frequency distribution of voxelwise correlations between CT number and SPR within the irradiated volume, a piecewise linear function was specified (DirectSPR-based adapted HLUT). Differences in dose distribution and proton range were assessed for the nonadapted and adapted HLUT in comparison to the DirectSPR method, which has been shown to be an accurate and reliable SPR estimation method.
RESULTS: The application of the DirectSPR-based adapted HLUT instead of the nonadapted HLUT reduced the systematic proton range differences from 1.2% (1.1 mm) to -0.1% (0.0 mm) for brain-tumor patients, 1.7% (4.1 mm) to 0.2% (0.5 mm) for prostate-cancer patients, and 2.0% (2.9 mm) to -0.1% (0.0 mm) for NSCLC patients. Due to the large intra- and inter-patient tissue variability, range differences to DirectSPR larger than 1% remained for the adapted HLUT.
CONCLUSIONS: The incorporation of patient-specific correlations between CT number and SPR, derived from a retrospective application of DirectSPR to a broad patient cohort, improves the SPR accuracy of the current state-of-the-art HLUT approach. The DirectSPR-based adapted HLUT has been clinically implemented at the University Proton Therapy Dresden (Dresden, Germany) in 2017. This already facilitates the benefits of an improved DECT-based tissue differentiation within clinical routine without changing the general approach for range prediction (HLUT), and represents a further step toward full integration of the DECT-based DirectSPR method for treatment planning in proton therapy.