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- François Rheault, Directeur du Medical Imaging and Neuroinformatic (MINi) Lab à l'Université de Sherbrooke nous présentera sa conférence : "All you need to know about tractometry or the art of brain spaghetti analysis"
- Joël Lefebvre, Directeur du Digital Imaging, Neurophotonics and Microscopy Laboratory (LINUM) à l'Université du Québec à Montréal (UQAM), nous fera une présentation intitulée : "Introduction to neurophotonics and Optical Coherence Tomography serial histology for myelin imaging"
Vous pourrez également assister à ces deux conférences via ce lien zoom: https://u-bordeaux-fr.zoom.us/j/88389457645?pwd=QldrSU12NU9nZlVMNkUvVGw4MS81UT09
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Publication - Brain structure ages - A new biomarker for multi-disease
classificationTesting the Disconnectome Symptom Discoverer model on out-of-sample post-stroke language outcomes. by Nguyen HD, Clément M, Mansencal B. and Coupé P. , Hum Brain Mapp
Age is an important variable to describe the expected brain's anatomy status across the normal aging trajectory. The deviation from that normative aging trajectory may provide some insights into neurological diseases. In neuroimaging, predicted brain age is widely used to analyze different diseases. However, using only the brain age gap information (i.e., the difference between the chronological age and the estimated age) can be not enough informative for disease classification problems. In this paper, we propose to extend the notion of global brain age by estimating brain structure ages using structural magnetic resonance imaging. To this end, an ensemble of deep learning models is first used to estimate a 3D aging map (i.e., = voxel-wise age estimation). Then, a 3D segmentation mask is used to obtain the final brain structure ages. This biomarker can be used in several situations. First, it enables to accurately estimate the brain age for the purpose of anomaly detection at the population level. In this situation, our approach outperforms several state-of-the-art methods. Second, brain structure ages can be used to compute the deviation from the normal aging process of each brain structure. This feature can be used in a multi-disease classification task for an accurate differential diagnosis at the subject level. Finally, the brain structure age deviations of individuals can be visualized, providing some insights about brain abnormality and helping clinicians in real medical contexts.
Age prediction, Alzheimer's disease, brain structure ages, deep learning, frontotemporal dementia, multi-disease classification, multiple sclerosis, Parkinson's disease, schizophrenia
Publication - Hydrophilic Biocompatible Fluorescent Organic Nanoparticles as Nanocarriers for Biosourced Photosensitizers for Photodynamic Therapy. Nanomaterials (Basel) by Sasaki I, Brégier F, Chemin G, Daniel J, Couvez J, Chkair R, Vaultier M, Sol V, Blanchard-Desce M., MDPI
Previous studies have reported anomalies in the arcuate fasciculus (AF) lateralization in developmental dyslexia (DD). Still, the relationship between AF lateralization and literacy skills in DD remains largely unknown. The purpose of our study is to investigate the relationship between lateralization of three segments of AF (AF anterior segment (AFAS), AF long segment (AFLS), and AF posterior segment (AFPS)) and literacy skills in DD. A total of 26 children with dyslexia and 31 age-matched control children were included in this study. High angular diffusion imaging, combined with spherical deconvolution tractography, was used to reconstruct the AF. Connectivity measures of hindrance-modulated orientational anisotropy (HMOA) were computed for each of the three segments of the AF. The lateralization index (LI) of each AF segment was calculated by (right HMOA - left HMOA)/(right HMOA + left HMOA). Results showed that the LIs of AFAS and AFLS were positively correlated with reading accuracy in children with dyslexia. Specifically, the LI of AFAS was positively correlated with nonword and meaningless text reading accuracy, while the LI of AFLS accounted for word reading accuracy. The results suggest adaptive compensation of arcuate fasciculus lateralization in developmental dyslexia and functional dissociation of the anterior segment and long segment in the compensation.
Publication - The Minimum Admissible Detuning Efficiency of MRI Receive-Only Surface Coils by Marhabaie S, Labbé A, Quesson B, and Poirier-Quinot M., J Magn Reson Imaging
Background: The minimum admissible detuning efficiency (DE) of a receive coil is an essential parameter for coil designers. A receive coil with inefficient detuning leads to inhomogeneous B1 during excitation. Previously proposed criteria for quantifying the DE rely on indirect measurements and are difficult to implement.
Purpose: To present an alternative method to quantify the DE of receive-only surface coils.
Study type: Theoretical study supported by simulations and phantom experiments.
Phantoms: Uniform spherical (100 mm diameter) and cylindrical (66 mm diameter) phantoms.
Field strength/sequence: Dual repetition time B1 mapping sequence at 1.5T, and Bloch-Siegert shift B1 mapping sequence at 3.0T.
Assessment: One non-planar (80 × 43 mm2 ) and two planar (40 and 57 mm diameter) surface coils were built. Theoretical analysis was performed to determine the minimum DE required to avoid B1 distortions. Experimental B1 maps were acquired for the non-planar and planar surface coils at both 1.5T and 3.0T and visually compared with simulated B1 maps to assess the validity of the theoretical analysis.
Statistical tests: None.
Results: Based on the theoretical analysis, the proposed minimum admissible DE, defined as DEthr = 20 Log (Q) + 13 dB, depended only on the quality factor (Q) of the coil and was independent of coil area and field strength. Simulations and phantom experiments showed that when the DE was higher than this minimum threshold level, the B1 field generated by the transmission coil was not modified by the receive coil.
Data conclusion: The proposed criterion for assessing the DE is simple to measure, and does not depend on the area of the coil or on the magnetic field strength, up to 3T. Experimental and simulated B1 maps confirmed that detuning efficiencies above the theoretically derived minimal admissible DE resulted in a non-distorted B1 field.
Evidence level: 2 TECHNICAL EFFICACY: Stage 1.
Keywords: B1 distortion; B1 inh