Diffusion MRI for Anatomical Nuclei Imaging (DiMANI): Visualizing Thalamic Subnuclei
Poster No:
2364
Submission Type:
Abstract Submission
Authors:
Remi Patriat1, Tara Palnitkar1, Jayashree Chandrasekaran1, Karianne Sretavan Wong2, Henry Braun1, Essa Yacoub3, Robert McGovern III1, Joshua Aman1, Scott Cooper1, Jerrold Vitek1, Noam Harel1
Institutions:
1University of Minnesota, Minneapolis, MN, 2University of Minnesota, SAINT LOUIS PARK, MN, 3Center for Magnetic Resonance Research, Minneapolis, MN
First Author:
Co-Author(s):
Introduction:
Conventional MRI has limited ability to visualize thalamic subnuclei, hindering precise targeting for interventions like deep brain stimulation (DBS) and MR-guided focused ultrasound (MRgFUS), resulting in variable patient outcomes (Agrawal et al., 2021; Flora et al., 2010) and repeat surgeries (Rolston et al., 2016). Several imaging methods have been developed for direct visualization, including susceptibility weighted imaging (Abosch et al., 2010; Najdenovska et al., 2019), quantitative magnetic susceptibility mapping (Deistung et al., 2013), and white-matter nulled T1 imaging, such as FGATIR (Sudhyadhom et al., 2009), 3D-EDGE (Middlebrooks et al., 2021), and WMn-MPRAGE (Su et al., 2019); however, these techniques have limitations for routine clinical use. Here, we present DiMANI, a novel method for directly visualizing thalamic subnuclei using diffusion MRI (dMRI).
Methods:
One healthy control and six essential tremor (ET) patients underwent scanning on a 7T Siemens MRI scanner, supplemented by 3T and 7T data from a single Human Connectome Project (HCP) control subject. Standard preprocessing, including FSL's eddy and topup, was applied. DiMANI contrast was computed by averaging diffusion-weighted volumes (e.g., 50 b =1500s/mm² volumes). The resulting contrast was compared with THOMAS (Su et al., 2019) and Morel atlases (Morel et al., 1997). We evaluated the reproducibility of DiMANI by computing dice coefficients on manual segmentations performed on a unique dataset comprising eight scans of a single participant collected over a 3-year period. Inter-rater reliability was quantitatively evaluated for manual segmentations of thalamic subnuclei (3 raters and 5 patients). Then, DiMANI imaging data was qualitatively correlated with intra-operative electrophysiology obtained during ET-DBS surgery (for subnucleus identification), post-operative computed tomography (for DBS lead location), and clinical evaluations (final DBS stimulation settings).
Results:
DiMANI provides enhanced contrast and enables direct visualization of thalamic subnuclei, including their borders (see Figure1 for manual segmentations). The DiMANI contrast corresponds to the overall anatomical organization as described by the THOMAS and Morel atlases. Dice coefficients (DCs) for manual segmentations of one volunteer's eight datasets, based on 12 nuclei from the THOMAS atlas nomenclature, averaged between 0.62 and 0.85, except for the habenula (DC = 0.50). Three raters independently segmented the subnuclei for 5 ET patients, yielding comparable DCs (0.46 to 0.81). DiMANI contrast enables the generation of 3D patient-specific models for thalamic subnuclei location depiction as shown in Figure 2 for 6 ET patients. All nine active DBS contacts were at or near the ventral lateral posterior (VLPv) – ventral lateral anterior (VLa) border, which is consistent with expected lead locations. Micro-electrode recording tracks correlated with manual segmentations: 11 of 12 micro-electrode recording tracks, showed that regions of activity interpreted as neuronal firing of cells belonging to the ventral posterior lateral (VPL) overlapped fully with the manual segmentations of the VPL. The twelfth track was found just anterior to VPL within VLPv.
·Figure 1: Manual segmentation of thalamic subnuclei using the DiMANI image following conventions from the THOMAS atlas in axial (A,B,C), sagittal (D and E), coronal (F), and in 3D (G).
·Figure 2: 3D models of patient-specific thalamic segmentations combined with DBS lead and VPL cell locations for six patients totaling nine leads.
Conclusions:
DiMANI is a dMRI-based image contrast that facilitates direct visualization of numerous thalamic subnuclei. DiMANI holds significant potential for immediate clinical applications, aiding in segmentations, targeting, and optimizing thalamic therapies like DBS and MRgFUS. While the proof-of-concept displays common dMRI limitations, DiMANI shows promise for both research and clinical purposes. Ongoing work will leverage advanced acquisition and post-processing methods to enhance translational capabilities.
Brain Stimulation:
Deep Brain Stimulation 2
Modeling and Analysis Methods:
Methods Development
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Subcortical Structures
Novel Imaging Acquisition Methods:
Diffusion MRI 1
Keywords:
Movement Disorder
MRI
Sub-Cortical
Thalamus
1|2Indicates the priority used for review
Provide references using author date format
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