| Title: |
Segmentation of Substantia Nigra, Subthalamic and Red Nuclei with a Multi-Modal Quantitative 7T MRI High Resolution Template |
| Authors: |
Cabane, Alexandre; Le Troter, Arnaud; Testud, Benoit; Grimaldi, Stephan; Guye, Maxime; Ranjeva, Jean‐philippe; de Rochefort, Ludovic |
| Contributors: |
Centre de résonance magnétique biologique et médicale (CRMBM); Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS) |
| Source: |
2023 ISMRM & ISMRT Annual Meeting & Exhibition; https://hal.science/hal-04269489; 2023 ISMRM & ISMRT Annual Meeting & Exhibition, Jun 2023, Toronto, Canada |
| Publisher Information: |
CCSD |
| Publication Year: |
2023 |
| Collection: |
Aix-Marseille Université: HAL |
| Subject Terms: |
Gray Matter; Quantitative Susceptibility Mapping; T1; high-resolution multi-modal template; [SDV]Life Sciences [q-bio]; [PHYS]Physics [physics] |
| Subject Geographic: |
Toronto |
| Time: |
Toronto, Canada |
| Description: |
International audience ; Synopsis: The segmentation of brain substructures is very useful in the characterization of alterations involved in multiple diseases. From 200 7T brain MRI scan including MP2RAGE and MGRE used to generate quantitative T1 maps (qT1), R2* and QSM volumes, a pipeline was developed to create a high-resolution multi-modal template at (400 µm)3 based on these multiple quantitative imaging modalities. Preliminary results show that multi-modality allows for a more precise parcellation of the SN, RN and STH substructures.Introduction: The importance of high spatial resolution in-vivo 7T MRI for deep grey nuclei (DGN) segmentation has been highlighted in recent studies. The parcellation of substructures would enable easier small alteration characterization, such as in Parkinson's disease mainly affecting the Substantia Nigra (SN) [1], [2], a region adjacent to Red (RN) and Subthalamic (STH) nuclei. Multiple atlases for these areas have been proposed, such as the CIT168 atlas [3], that offers a probabilistic subdivision of SN into two parts performed from a T1-w/T2-w multi-modal (MM) template, an atlas of Zona Incerta [4] and adjacent structures that includes the SN, RN and STH, and more recently the 7TAMIbrainDGN high-resolution (500 µm)3 DGN atlas [5]. These methods rely on the creation of templates that improve CNR and SNR via the use of super-resolution [6]. Others authors [7], [8] have shown the relevance of quantitative imaging (QSM [9] in particular) and multi-modal clustering of SN, RN and STH, for automatic segmentation by template-to-subjects co-registrations.In this study, we introduce the 7TAMIbrainqT1_R2*_QSM_400 MM template, an improved version of 7TAMIbrainT1w_30 [5], that is built using a larger number of subjects (30 to 200), with a higher super-resolution target (400 µm)3. Moreover, we also propose an automatic parcellation process of the SN using multi-class clustering on the QSM template, with a segmentation on the subject space optimized by the use of an atlas-based MM ... |
| Document Type: |
conference object |
| Language: |
English |
| Availability: |
https://hal.science/hal-04269489; https://hal.science/hal-04269489v1/document; https://hal.science/hal-04269489v1/file/ISMRM_2023_3551_abstract_HAL.pdf |
| Rights: |
https://about.hal.science/hal-authorisation-v1/ ; info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.225DFA1E |
| Database: |
BASE |