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Processing of Structural and Diffusion MRI for Real-Time Tractography-Based Ntms

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Processing of Structural and Diffusion MRI for Real-Time Tractography-Based Ntms Processing of structural and diffusion MRI for real-time tractography-based nTMS Dogu Baran Aydogan, Victor Hugo Souza, Risto Ilmoniemi Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland Introduc�on Results and conclusion Real-time information about the structural connections in the brain would be highly valuable when performing navigated transcranial magnetic stimulation (nTMS). This information can be obtained using diffusion MRI (dMRI) based tractography that can extract major structural connections in the brain, in-vivo and non-invasively. However, this has been challenging to achieve in real-time, mainly because obtaining reliable tractograms is in general a difficult task. To address this problem, we leveraged our in-house-developed fiber tracking tool, Trekker [1], that implements the state-of-the-art parallel transport tracking (PTT) algorithm [2]. Trekker is not only capable of producing highly organized streamlines owing to PTT, but it also can apply anatomical constraints in a real-time setting. Method Our approach is based on a modular framework which seamlessly integrates offline (preparatory) analysis output, with online (real-time) tractography and visualization. OFFLINE ONLINE dMRI Diffusion MRI processing Tractography 3 Resolution: 1.5x1.5x1.5 mm Denoise (MPPCA [3]) Update seed points Real-time tractography-based nTMS holds great potential to improve TMS targeting, thereby b-values: 900, 1600, 2500 s/mm2 based on coil location Gibbs artefact correction (unring [4]) Directions: 18, 32, 50 helping to develop new treatments where connectivity plays a decisive role. b0s: 11 interleaved Distortion correction (eddy [5]) Trekker [1] Phase : AP and PA Three-compartment model (Tran and Shi [6]) Anatomical constraints InVesalius [9] encoding Our work shows that this can be achieved by: (i) splitting the preprocessing part to be done Simulated uncertainty Neuronavigation offline and (ii) using a real-time tracker, enabling real-time adjustments for reliability. & Visualization Structure MRI visualization References Brain mask to T1w space Register dMRI Register Generate mesh [1] Trekker: https://dmritrekker.github.io/ [5] Fsl eddy tool: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/eddy from brain surface [2] Aydogan D.B., Shi Y., “A novel fiber tracking algorithm using parallel transport frames”, Proceedings [6] Tran, G. and Shi, Y. (2015). Fiber Orientation and Compartment Parameter Estimation From Multi- T1w MRI Structural MRI processing Peel down surfaces of the 27th Annual Meeting of the International Society of Magnetic Resonance in Medicine (ISMRM) Shell Diffusion Imaging. IEEE Transactions on Medical Imaging, 34(11):2320–2332. 3 at 1mm intervals MPRAGE 1x1x1 mm Brain extraction (ANTs [7]) Display interpolated T1w 2019 [7] Tustison, Nicholas J., et al. "Large-scale evaluation of ANTs and FreeSurfer cortical thickness Automatic Segmentation (Freesurfer [8]) intensities on peeled surfaces [3] Veraart, J., Novikov, D. S., Christiaens, D., Ades-aron, B., Sijbers, J., and Fieremans, E. (2016). measurements." Neuroimage 99 (2014): 166-179. for anatomical navigation Denoising of diffusion MRI using random matrix theory. NeuroImage, 142:394–406. [8] Fischl, Bruce (2012). Freesurfer, NeuroImage, 62(2):774-781 [4] Kellner E, Dhital B, Kiselev VG, Reisert M. Gibbs-ringing artifact removal based on local subvoxel- [9] Souza, Victor Hugo, et al. "Development and characterization of the InVesalius Navigator software for shifts. Magnetic Resonance in Medicine. 2016 Nov 1;76(5):1574–81. navigated transcranial magnetic stimulation." Journal of neuroscience methods 309 (2018): 109-120. Core so�ware Acknowledgements Department of Neuroscience This project has received funding from the European Research Council (ERC) under the European Union’s Fiber tracking with Trekker Neuronavigation with InVesalius and Biomedical Engineering Horizon 2020 research and innovation programme Aalto University School of Science (grant agreement No 810377). https://dmritrekker.github.io/ https://invesalius.github.io/ baran.aydogan@aalto.fi - Jane and Aatos Erkko Founda�on nbe.aalto.fi - The Academy of Finland.
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