Vienna, Austria

ESTRO 2023

Session Item

Saturday
May 13
10:30 - 11:30
Strauss 1
QA and auditing
Sara Abdollahi, Switzerland;
Victor Hernandez, Spain
Proffered Papers
Physics
11:10 - 11:20
Consensus guide on CT-based prediction of stopping-power ratio using a Hounsfield look-up table
Vicki Taasti, Denmark
OC-0115

Abstract

Consensus guide on CT-based prediction of stopping-power ratio using a Hounsfield look-up table
Authors:

Vicki Taasti1, Nils Peters2, Alessandra Bolsi3, Christina Vallhagen Dahlgren4, Malte Ellerbrock5, Carles Gomà6, Joanna Góra7, Patricia Cambraia Lopes8, Ilaria Rinaldi9, Koen Salvo10, Ivanka Sojat Tarp11, Alessandro Vai12, Thomas Bortfeld13, Antony Lomax14, Christian Richter2, Patrick Wohlfahrt13

1Department of Radiation Oncology (MAASTRO), GROW – School for Oncology, Maastricht University Medical Centre+, Maastricht, The Netherlands; 2OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany; 3Paul Scherrer Institute, Center for Proton Therapy, Villigen, Switzerland; 4The Skandion Clinic, Department of Medical Physics, Uppsala, Sweden; 5Heidelberg Ion-Beam Therapy Center (HIT), Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany; 6Department of Radiation Oncology, Hospital Clínic de Barcelona, Barcelona, Spain; 7EBG MedAustron GmbH, Division of Medical Physics, Wiener Neustadt, Austria; 8Holland Proton Therapy Center, Department of Medical Physics, Delft, The Netherlands; 9Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, Maastricht, The Netherlands; 10Algemeen Ziekenhuis Sint-Maarten, Department of Radiotherapy, Duffel, Belgium; 11Danish Centre for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark; 12Radiotherapy Department, Center for National Oncological Hadrontherapy (CNAO), Pavia, Italy; 13Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, Boston, MA, USA; 14Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland

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Purpose or Objective

Studies within the European Particle Therapy Network (EPTN) have shown a large variation in the estimation of proton stopping-power ratio (SPR) from computed tomography (CT) scans across European proton centres. To standardise the SPR prediction process, we present a step-by-step guide on the Hounsfield look-up table (HLUT) specification process. This consensus guide was created within the ESTRO Physics Workshop 2021 on CT in radiotherapy in a joint effort with the EPTN Work Package 5 (WP5).

Material and Methods

The HLUT specification procedure is divided into six steps (Figure 1): 1) phantom setup, 2) CT scanning, 3) CT number extraction, 4) SPR determination, 5) HLUT specification, 6) HLUT evaluation. For each step, considerations and recommendations are given based on literature and additional experimental evaluations. Appropriate phantom inserts are tissue-equivalent for both X-ray and proton interactions and are scanned in head- and body-d phantoms to mimic different beam hardening conditions. Soft tissue inserts can be scanned together, while bone inserts are scanned individually to avoid imaging artefacts. CT numbers are extracted in material-specific regions-of-interest covering the inner 70% of each phantom insert in-plane and several axial CT slices in scan direction. For an appropriate HLUT specification, the SPR of phantom inserts is experimentally determined in proton range measurements at an energy >200 MeV, and the SPR of tabulated human tissues is computed stoichiometrically at 100 MeV. By including both phantom inserts and tabulated human tissues in the HLUT specification, the influence of the respective dataset-specific uncertainties are mitigated and thus the HLUT accuracy is increased. Piecewise linear regressions are performed between CT numbers and SPRs for four individual tissue segments (lung, adipose, soft tissue and bone) and then connected with straight lines. A thorough but simple validation is finally performed.



Results

The individual challenges and best practices 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 exemplarily performed on three CT scanners from different vendors, proving its feasibility for SPR prediction on both single-energy CT scans and virtual monoenergetic CT images derived from dual-energy CT (Figure 2).



Conclusion

A comprehensive step-by-step guide on CT-based HLUT specification is described, representing a consensus found within the ESTRO Physics Workshop and the EPTN WP5. The presented recommendations and examples can contribute to increase the accuracy in proton range prediction for treatment planning in individual proton centres and, following from this, reduced inter-centre variations in SPR prediction and thus a better comparability of treatment data between different centres for multi-centre clinical studies.