Modeling sphere dynamics in blood vessels for SIRT pre-planning: to fathom the potential and limitations
For selective internal radiation therapy (SIRT) the calculation of the 3D distribution of spheres based on individual blood flow properties is still an open and relevant research question. The purpose of this work is to develop and analyze a new treatment planning method for SIRT to calculate the ab...
Gespeichert in:
| Hauptverfasser: | , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
February 2019
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| In: |
Zeitschrift für medizinische Physik
Year: 2019, Jahrgang: 29, Heft: 1, Pages: 5-15 |
| ISSN: | 1876-4436 |
| DOI: | 10.1016/j.zemedi.2018.05.006 |
| Online-Zugang: | Verlag, Volltext: https://doi.org/10.1016/j.zemedi.2018.05.006 Verlag, Volltext: http://www.sciencedirect.com/science/article/pii/S0939388917301605 
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| Verfasserangaben: | Dominik Kretz, Jürgen Hesser, Gerhard Glatting, Steffen Diehl, Frederik Wenz, Wanji He, Lei Zheng |
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| 520 | |a For selective internal radiation therapy (SIRT) the calculation of the 3D distribution of spheres based on individual blood flow properties is still an open and relevant research question. The purpose of this work is to develop and analyze a new treatment planning method for SIRT to calculate the absorbed dose distribution. For this intention, flow dynamics of the SIRT-spheres inside the blood vessels was simulated. The challenge is treatment planning solely using high-resolution imaging data available before treatment. The resolution required to reliably predict the sphere distribution and hence the dose was investigated. For this purpose, arteries of the liver were segmented from a contrast-enhanced angiographic CT. Due to the limited resolution of the given CT, smaller vessels were generated via a vessel model. A combined 1D/3D-flow simulation model was implemented to simulate the final 3D distribution of spheres and dose. Results were evaluated against experimental data from Y90-PET. Analysis showed that the resolution of the vessels within the angiographic CT of about 0.5mm should be improved to a limit of about 150μm to reach a reliable prediction. | ||
| 650 | 4 | |a -PET | |
| 650 | 4 | |a Blood flow simulation | |
| 650 | 4 | |a Constrained constructive optimization | |
| 650 | 4 | |a Smoothed particle hydrodynamics | |
| 650 | 4 | |a Treatment planning | |
| 650 | 4 | |a Vessel segmentation | |
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