ArticleInternational journal of radiation oncology, biology, physics2018
Velocity-based Adaptive Registration and Fusion for Fractionated Stereotactic Radiosurgery Using the Small Animal Radiation Research Platform.
Article in International journal of radiation oncology, biology, physics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Multi-stage image registration based on list-mode proton radiographies for small animal proton irradiation: A simulation study.Zeitschrift fur medizinische Physik · 2024Article
- Radiotherapy in Preclinical Models of Brain Metastases: A Review and Recommendations for Future Studies.International journal of biological sciences · 2024Review
- Advantages and robustness of partial VMAT with prone position for neoadjuvant rectal cancer evaluated by CBCT-based offline adaptive radiotherapy.Radiation oncology (London, England) · 2023Article
- Integrating Small Animal Irradiators withFunctional Imaging for Advanced Preclinical Radiotherapy Research.Cancers · 2019Review
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Authors and funding
15 authors at 1 institution in 1 country.
Funding
Abstract
purposeTo implement Velocity-based image fusion and adaptive deformable registration to enable treatment planning for preclinical murine models of fractionated stereotactic radiosurgery (fSRS) using the small animal radiation research platform (SARRP). METHODS AND MATERIALS: C57BL6 mice underwent 3 unique cone beam computed tomography (CBCT) scans: 2 in the prone position and a third supine. A single T1-weighted post-contrast magnetic resonance imaging (MRI) series of a murine metastatic brain tumor model was selected for MRI-to-CBCT registration and gross tumor volume (GTV) identification. Two arms were compared: Arm 1, where we performed 3 individual MRI-to-CBCT fusions using rigid registration, contouring GTVs on each, and Arm 2, where the authors performed MRI-to-CBCT fusion and contoured GTV on the first CBCT followed by Velocity-based adaptive registration. The first CBCT and associated GTV were exported from MuriPlan (Xstrahl Life Sciences) into Velocity (Varian Medical Systems, Inc, Palo Alto, CA). In Arm 1, the second and third CBCTs were exported similarly along with associated GTVs (Arm 1), while in Arm 2, the first (prone) CBCT was fused separately to the second (prone) and third (supine) CBCTs, performing deformable registrations on initial CBCTs and applying resulting matrices to the contoured GTV. Resulting GTVs were compared between Arms 1 and 2.
resultsComparing GTV overlays using repeated MRI fusion and GTV delineation (Arm 1) versus those of Velocity-based CBCT and GTV adaptive fusion (Arm 2), mean deviations ± standard deviation in the axial, sagittal, and coronal planes were 0.46 ± 0.16, 0.46 ± 0.22, and 0.37 ± 0.22 mm for prone-to-prone and 0.52 ± 0.27, 0.52 ± 0.36, and 0.68 ± 0.31 mm for prone-to-supine adaptive fusions, respectively.
conclusionsVelocity-based adaptive fusion of CBCTs and contoured volumes allows for efficient fSRS planning using a single MRI-to-CBCT fusion. This technique is immediately implementable on current SARRP systems, facilitating advanced preclinical treatment paradigms using existing clinical treatment planning software.
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