Dual-energy computed tomography to assess intra- and inter-patient tissue variability for proton treatment planning of patients with brain tumor
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 u...
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| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2 July 2019
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| In: |
International journal of radiation oncology, biology, physics
Year: 2019, Jahrgang: 105, Heft: 3, Pages: 504-513 |
| ISSN: | 1879-355X |
| DOI: | 10.1016/j.ijrobp.2019.06.2529 |
| Online-Zugang: | Verlag, Volltext: https://doi.org/10.1016/j.ijrobp.2019.06.2529 Verlag: http://www.sciencedirect.com/science/article/pii/S0360301619334170 
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| Verfasserangaben: | Patrick Wohlfahrt, PhD, Christian Möhler, PhD, Esther G.C. Troost, MD, PhD, Steffen Greilich, PhD, and Christian Richter, PhD |
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| 245 | 1 | 0 | |a Dual-energy computed tomography to assess intra- and inter-patient tissue variability for proton treatment planning of patients with brain tumor |c Patrick Wohlfahrt, PhD, Christian Möhler, PhD, Esther G.C. Troost, MD, PhD, Steffen Greilich, PhD, and Christian Richter, PhD |
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| 520 | |a 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. | ||
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