Dual-energy computed tomography to assess intra- and inter-patient tissue variability for proton treatment planning of brain-tumor patients


Dual-energy computed tomography to assess intra- and inter-patient tissue variability for proton treatment planning of brain-tumor patients

Wohlfahrt, P.; Möhler, C.; Troost, E.; Greilich, S.; Richter, C.

Background and Purpose:

Range prediction in particle therapy is associated with an uncertainty originating from the calculation of stopping-power ratio (SPR) based on x-ray computed tomography (CT). Here, we assessed the intra- and inter-patient variability of tissue properties in primary brain-tumor patients using dual-energy CT (DECT) and quantified its influence on current SPR prediction.

Material and Methods:

Based on 102 patient DECT scans, SPR distributions were derived from a patient-specific DECT-based approach. Tissue-specific and global deviations between this method and the state-of-the-art CT-number-to-SPR conversion applying a Hounsfield look-up table (HLUT) were quantified. To isolate systematic deviations between both, the HLUT was optimized using DECT. Subsequently, the influence of soft tissue diversity and age-related variations in bone composition on SPR were assessed.

Results:

An intra-patient ± inter-patient soft tissue diversity of (4.4±0.7)% in SPR was obtained after conservative consideration of noise-induced variation. Between adults and children younger than 6 years, age-related variations in bone composition resulted in a median SPR difference of approximately 5%.

Conclusions:

Patient-specific DECT-based stopping-power prediction can intrinsically incorporate most of the SPR variability arising from tissue mixtures, inter-patient and intra-tissue variations. Since the state-of-the-art HLUT - even after cohort-specific optimization - cannot fully consider the broad tissue variability, patient-specific DECT-based stopping-power prediction is advisable in particle therapy.

Keywords: dual-energy CT; tissue variability; proton therapy

Downloads

Permalink: https://www.hzdr.de/publications/Publ-27917
Publ.-Id: 27917