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Fibre tract segmentation for intraoperative diffusion MRI in neurosurgical patients using tract-specific orientation atlas and tumour deformation modelling
- Source :
- International Journal of Computer Assisted Radiology and Surgery; 20220101, Issue: Preprints p1-9, 9p
- Publication Year :
- 2022
-
Abstract
- Purpose:: Intraoperative diffusion MRI could provide a means of visualising brain fibre tracts near a neurosurgical target after preoperative images have been invalidated by brain shift. We propose an atlas-based intraoperative tract segmentation method, as the standard preoperative method, streamline tractography, is unsuitable for intraoperative implementation. Methods:: A tract-specific voxel-wise fibre orientation atlas is constructed from healthy training data. After registration with a target image, a radial tumour deformation model is applied to the orientation atlas to account for displacement caused by lesions. The final tract map is obtained from the inner product of the atlas and target image fibre orientation data derived from intraoperative diffusion MRI. Results:: The simple tumour model takes only seconds to effectively deform the atlas into alignment with the target image. With minimal processing time and operator effort, maps of surgically relevant tracts can be achieved that are visually and qualitatively comparable with results obtained from streamline tractography. Conclusion:: Preliminary results demonstrate feasibility of intraoperative streamline-free tract segmentation in challenging neurosurgical cases. Demonstrated results in a small number of representative sample subjects are realistic despite the simplicity of the tumour deformation model employed. Following this proof of concept, future studies will focus on achieving robustness in a wide range of tumour types and clinical scenarios, as well as quantitative validation of segmentations.
Details
- Language :
- English
- ISSN :
- 18616410 and 18616429
- Issue :
- Preprints
- Database :
- Supplemental Index
- Journal :
- International Journal of Computer Assisted Radiology and Surgery
- Publication Type :
- Periodical
- Accession number :
- ejs59527601
- Full Text :
- https://doi.org/10.1007/s11548-022-02617-z