1. CT-based stopping-power ratio prediction using a Hounsfield look-up table: A consensus guide
- Author
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Taasti, V., Peters, N., Bolsi, A., Vallhagen Dahlgren, C., Ellerbrock, M., Gomà, C., Góra, J., Cambraia Lopes, P., Rinaldi, I., Salvo, K., Sojat Tarp, I., Vai, A., Bortfeld, T., Lomax, A., (0000-0003-4261-4214) Richter, C., Wohlfahrt, P., Taasti, V., Peters, N., Bolsi, A., Vallhagen Dahlgren, C., Ellerbrock, M., Gomà, C., Góra, J., Cambraia Lopes, P., Rinaldi, I., Salvo, K., Sojat Tarp, I., Vai, A., Bortfeld, T., Lomax, A., (0000-0003-4261-4214) Richter, C., and Wohlfahrt, P.
- Abstract
Motivation Large variations in stopping-power ratio (SPR) prediction from computed tomography (CT) across European proton centres were observed in recent studies. To standardise CT-based SPR prediction using a Hounsfield look-up table (HLUT), a step-by-step consensus guide, created within the ESTRO Physics Workshop 2021 in a joint effort with EPTN-WP5, is presented. Methods The HLUT specification process includes six steps: Phantom setup, CT acquisition, CT number extraction, SPR determination, HLUT specification, and HLUT validation. Appropriate phantom inserts are tissue-equivalent for both X-ray and proton interactions and are scanned in head- and body-sized phantoms to mimic different beam hardening conditions. Soft tissue inserts can be scanned together, while scanning bone inserts individually reduces imaging artefacts. For optimal HLUT specification, the SPR of phantom inserts is measured and the SPR of tabulated human tissues is computed stoichiometrically. The HLUT stability is increased by including both phantom inserts and tabulated human tissues. Piecewise linear regressions of CT numbers and SPRs are performed for four tissue groups (lung, adipose, soft tissue, and bone) and then connected. Finally, a thorough validation is performed. Results 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 on both single-energy CT and virtual monoenergetic images from dual-energy CT. Conclusion The presented step-by-step guide for CT-based HLUT specification with recommendations and examples can increase the clinical range prediction accuracy and reduce its inter-centre variation.
- Published
- 2023