Multimodal precision neuroimaging of the individual human brain at ultra-high field
Presented During:
Monday, June 24, 2024: 5:45 PM - 7:00 PM
COEX
Room:
ASEM Ballroom 202
Poster No:
2217
Submission Type:
Abstract Submission
Authors:
Donna Gift Cabalo1, Ilana Leppert2, Yezhou Wang1, Risa Thevakumaran3, Shahin Tavakol4, Jessica Royer5, Jordan DeKraker6, Valeria Kebets7, Oualid Benkarim6, Bin Wan8, Youngeun Hwang7, Nicole Eichert9, Casey Paquola10, Sofie Valk8, Jonathan Smallwood11, Christine Tardif2, David Rudko2, Raúl Rodriguez-Cruces6, Boris Bernhardt6
Institutions:
1McGill University, Montreal, Quebec, 2McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Quebec, 3McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Montreal, Quebec, 4McGill University, Montreal Neurological Institute and Hospital, Montreal, Quebec, 5Montreal Neurological Institute and Hospital, Montreal, QC, 6Montreal Neurological Institute and Hospital, Montreal, Quebec, 7McGill University, Montreal Neurological Institute, Montreal, Quebec, 8Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 9University of Oxford, Oxford, Oxfordshire, 10INM-7, Jülich, Jülich, 11Department of Psychology, Queen’s University, Ontario, Canada
First Author:
Co-Author(s):
Ilana Leppert
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital
Montreal, Quebec
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital
Montreal, Quebec
Risa Thevakumaran
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal
Montreal, Quebec
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal
Montreal, Quebec
Christine Tardif
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital
Montreal, Quebec
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital
Montreal, Quebec
David Rudko
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital
Montreal, Quebec
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital
Montreal, Quebec
Introduction:
Neuroimaging has advanced our understanding of the human brain by allowing non-invasive examination of brain structure and function. Nevertheless, human MRI research has predominantly centred around group-averaged data, which limits the specificity and clinical utility that MRI can offer[1]. Precision neuroimaging facilitates individualized mapping of brain structure and function through the use of repeated and prolonged scans[1]. A dense sampling of fMRI allows for detailed and reliable characterization of individual brain states and heteromodal networks[2]. Structural MRI's specificity can be augmented by using multiple quantitative MRI sequences, providing microstructural parameters characterizing inter-regional heterogeneity and inter-individual differences. Harnessing ultra-high field (UHF) neuroimaging at magnetic field strengths of 7 Tesla, can further enhance spatial and temporal resolution and is often imperative for precise mapping of highly susceptible and deep structures[3, 4]. Several initiatives have generated open-source UHF datasets; however, these focused either on functional[4] or structural sequences[3]. Here, we describe a multimodal precision neuroimaging dataset that capitalized on multiple sessions 7T MRI.
Methods:
Our imaging protocol was implemented at the Montreal Neurological Institute and data were acquired on a 7T Terra Siemens scanner with the 8/32-channel transmit/receive Nova head coil. Ten healthy subjects (5M/5F, age=26.8±4.61, left/right handed=2/8) underwent three imaging sessions, each consisting of five distinct structural and five functional imaging protocols (Fig. 1A,C). Our UHF MRI data were processed with micapipe_v0.2.2[5], a surface-based processing software developed in my host lab, which introduced a standardized processing workflow for multiparametric UHF MRI acquisition. Structural scans included: (i) T1w and (ii) T1 relaxometry (T1) for examining intracortical microstructural organization, (iii) DWI for examining structural connectomes and fibre architectures, (iv) myelin-sensitive magnetization transfer, and, (v) iron-sensitive T2*-weighted multi-echo gradient echo. Each multi-echo fMRI scan lasted for 6 minutes and included, (i) rs-fMRI, (ii,iii,iv) multi-state task-based fMRI[6] with episodic encoding/retrieval and semantic tasks (Fig. 2B left). We also collected fMRI data as subjects watched (v) movies to study brain activity during naturalistic conditions[7]. Finally, we used the multidimensional experience sampling questionnaire (MDES), to study patterns of ongoing thought[7 ] (Fig. 2B right).
·Figure1_OHBM2024
Results:
Alongside anonymized raw data, we will release fully processed[5] data for each modality, which provides surface-based neuroimaging features such as cortical thickness, quantitative MRI maps, and inter-regional structural and functional connectomes (Fig.1A,B). With this unprecedented dataset, we have generated upsampled data (i.e., from 0.5mm to 0.25mm isovoxels) from MRI acquisitions and averaged denoised data across sessions[8,9]. We have tested this method, particularly focusing on T1w images which substantially enhanced image contrast, and, with T1 maps which provided more granular intensity profiles than single-session data (Fig. 2A bottom left). The multi-session data also allows to assess test-retest reliability[10] of various MRI features. Exemplary analysis of DMN connectivity derived from rs-functional connectomes demonstrated high intra-subject reliability and inter-subject DMN uniformity, with strong identifiability[10] (d=1.95), indicating reliable and distinct DMN patterns from our UHF rs-fMRI data while preserving individual differences (Fig. 2A bottom right).
·Figure2_OHBM2024
Conclusions:
Our open-access precision UHF dataset promises to become a key resource for researchers aiming to advance our understanding of structure-function relationships in individual human brains and is instrumental in the development of novel image processing and analysis methodology.
Learning and Memory:
Long-Term Memory (Episodic and Semantic)
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Anatomy and Brain Mapping
Cortical Cyto- and Myeloarchitecture
Neuroinformatics and Data Sharing:
Databasing and Data Sharing 1
Novel Imaging Acquisition Methods:
Multi-Modal Imaging 2
Keywords:
FUNCTIONAL MRI
HIGH FIELD MR
Open Data
STRUCTURAL MRI
Other - Ultra-high field 7T
1|2Indicates the priority used for review
Provide references using author date format
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