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

• Verfasst von: Wohlfahrt, Patrick [VerfasserIn]
• Verfasst von: Greilich, Steffen [VerfasserIn]
• Titel: Dual-energy computed tomography to assess intra- and inter-patient tissue variability for proton treatment planning of patients with brain tumor
• Verf.angabe: Patrick Wohlfahrt, PhD, Christian Möhler, PhD, Esther G.C. Troost, MD, PhD, Steffen Greilich, PhD, and Christian Richter, PhD
• E-Jahr: 2019
• Jahr: 2 July 2019
• Umfang: 10 S.
• Fussnoten: Gesehen am 10.10.2019
• Titel Quelle: Enthalten in: International journal of radiation oncology, biology, physics
• Ort Quelle: Amsterdam [u.a.] : Elsevier Science, 1975
• Jahr Quelle: 2019
• Band/Heft Quelle: 105(2019), 3, Seite 504-513
• ISSN Quelle: 1879-355X
• DOI: doi:10.1016/j.ijrobp.2019.06.2529
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1678646946

Abstract

Purpose - Range prediction in particle therapy is associated with an uncertainty originating from calculating the stopping-power ratio (SPR) based on x-ray computed tomography (CT). Here, we assessed the intra- and inter-patient variability of tissue properties in patients with primary brain tumor using dual-energy CT (DECT) and quantified its influence on current SPR prediction. - Methods and Materials - For 102 patients’ DECT scans, SPR distributions were derived from a patient-specific DECT-based approach (DirectSPR). The impact of soft tissue diversity and age-related variations in bone composition on SPR were assessed. 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 the two, the HLUT was also optimized using DECT information. - Results - An intra-patient ± inter-patient soft tissue diversity of 5.6% ± 0.7% in SPR (width of 95% confidence interval) was obtained including imaging- and model-related variations of up to 2.9%. This intra-patient SPR variability is associated with a mean absolute SPR deviation of 1.2% between the patient-specific DirectSPR approach and an optimal HLUT. Between adults and children younger than 6 years, age-related variations in bone composition resulted in a median SPR difference of approximately 5%. - Conclusions - Accurate patient-specific DECT-based stopping-power prediction allows for improved handling of tissue mixtures and can intrinsically incorporate most of the SPR variability arising from tissue mixtures as well as 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.