Fibre tract segmentation for intraoperative diffusion MRI in neurosurgical patients using tract-specific orientation atlas and tumour deformation modelling

Author:

Young FionaORCID,Aquilina Kristian,A. Clark Chris,D. Clayden Jonathan

Abstract

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.

Funder

Engineering and Physical Sciences Research Council

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Radiology, Nuclear Medicine and imaging,General Medicine,Surgery,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering

Reference43 articles.

1. Jeurissen B, Descoteaux M, Mori S, Leemans A (2019) Diffusion MRI fiber tractography of the brain. NMR Biomed 32(4):e3785. https://doi.org/10.1002/nbm.3785

2. Rheault F, Poulin P, Valcourt Caron A, St-Onge E, Descoteaux M (2020) Common misconceptions, hidden biases and modern challenges of dMRI tractography. J Neural Eng 17(1):011011. https://doi.org/10.1088/1741-2552/ab6aad

3. Yang JY-M, Yeh C-H, Poupon C, Calamante F (2021) Diffusion MRI tractography for neurosurgery: the basics, current state, technical reliability and challenges. Phys Med Biol 66(15):15TR011. https://doi.org/10.1088/1361-6560/ac0d90

4. Yeh F-C, Irimia A, Bastos DCdA, Golby AJ (2021) Tractography methods and findings in brain tumors and traumatic brain injury. NeuroImage 245:118651. https://doi.org/10.1016/j.neuroimage.2021.118651

5. Schilling KG, Rheault F, Petit L, Hansen CB, Nath V, Yeh FC, Girard G, Barakovic M, Rafael-Patino J, Yu T, Fischi-Gomez E, Pizzolato M, Ocampo-Pineda M, Schiavi S, Canales-Rodríguez EJ, Daducci A, Granziera C, Innocenti G, Thiran JP, Mancini L, Wastling S, Cocozza S, Petracca M, Pontillo G, Mancini M, Vos SB, Vakharia VN, Duncan JS, Melero H, Manzanedo L, Sanz-Morales E, Peña-Melián Á, Calamante F, Attyé A, Cabeen RP, Korobova L, Toga AW, Vijayakumari AA, Parker D, Verma R, Radwan A, Sunaert S, Emsell L, De Luca A, Leemans A, Bajada CJ, Haroon H, Azadbakht H, Chamberland M, Genc S, Tax CM, Yeh PH, Srikanchana R, Mcknight CD, Yang JYM, Chen J, Kelly CE, Yeh CH, Cochereau J, Maller JJ, Welton T, Almairac F, Seunarine KK, Clark CA, Zhang F, Makris N, Golby A, Rathi Y, O’Donnell LJ, Xia Y, Aydogan DB, Shi Y, Fernandes FG, Raemaekers M, Warrington S, Michielse S, Ramírez-Manzanares A, Concha L, Aranda R, Meraz MR, Lerma-Usabiaga G, Roitman L, Fekonja LS, Calarco N, Joseph M, Nakua H, Voineskos AN, Karan P, Grenier G, Legarreta JH, Adluru N, Nair VA, Prabhakaran V, Alexander AL, Kamagata K, Saito Y, Uchida W, Andica C, Abe M, Bayrak RG, Wheeler-Kingshott CA, D’Angelo E, Palesi F, Savini G, Rolandi N, Guevara P, Houenou J, López-López N, Mangin JF, Poupon C, Román C, Vázquez A, Maffei C, Arantes M, Andrade JP, Silva SM, Calhoun VD, Caverzasi E, Sacco S, Lauricella M, Pestilli F, Bullock D, Zhan Y, Brignoni-Perez E, Lebel C, Reynolds JE, Nestrasil I, Labounek R, Lenglet C, Paulson A, Aulicka S, Heilbronner SR, Heuer K, Chandio BQ, Guaje J, Tang W, Garyfallidis E, Raja R, Anderson AW, Landman BA, Descoteaux M (2021) Tractography dissection variability: what happens when 42 groups dissect 14 white matter bundles on the same dataset? NeuroImage. https://doi.org/10.1016/j.neuroimage.2021.118502

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Fibre orientation atlas guided rapid segmentation of white matter tracts;Human Brain Mapping;2024-01-30

2. Training Data Requirements for Atlas-Based Brain Fibre Tract Identification;2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology;2023-12-07

3. atTRACTive: Semi-automatic White Matter Tract Segmentation Using Active Learning;Lecture Notes in Computer Science;2023

4. Correction to: Fibre tract segmentation for intraoperative diffusion MRI in neurosurgical patients using tract-specific orientation atlas and tumour deformation modelling;International Journal of Computer Assisted Radiology and Surgery;2022-05-26

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