Caudolenticular gray bridges of the brain: A magnetic resonance imaging study

The caudolenticular (or transcapsular) gray bridges (CLGBs) connect the caudate nucleus (CN) and putamen across the internal capsule. The CLGBs function as the main efferent terminus from premotor and supplementary motor area cortex to the basal ganglia (BG). We conjectured if inherent variations in...

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Bibliographic Details
Published in:Clinical anatomy (New York, N.Y.) N.Y.), 2023-05, Vol.36 (4), p.669-674
Main Authors: Dang, Brian, Necker, Fabian N., Dhawan, Siddhant Suri, Murty, Tara, Massoud, Tarik F.
Format: Article
Language:English
Subjects:
Age
Atrophy
Basal ganglia
Basal Ganglia - diagnostic imaging
Basal Ganglia - pathology
Brain
Brain - diagnostic imaging
Bridges
Caudate nucleus
Cortex (motor)
Dependent variables
Female
Ganglia
Humans
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Mathematical analysis
Middle Aged
Morphometry
Movement disorders
Neural networks
Neurodegenerative diseases
Neuroimaging
Parkinson disease
Parkinson Disease - pathology
Parkinson's disease
Putamen
Retrospective Studies
Sex
Supplementary motor area
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Summary:The caudolenticular (or transcapsular) gray bridges (CLGBs) connect the caudate nucleus (CN) and putamen across the internal capsule. The CLGBs function as the main efferent terminus from premotor and supplementary motor area cortex to the basal ganglia (BG). We conjectured if inherent variations in numbers and sizes of CLGBs could contribute to abnormal cortical–subcortical connectivity in Parkinson's disease (PD), a neurodegenerative disorder featuring a hindrance of BG processing. However, there are no literature accounts of normative anatomy and morphometry of CLGBs. We therefore retrospectively analyzed axial and coronal 3T fast spoiled gradient‐echo magnetic resonance images (MRIs) of 34 healthy individuals for bilateral CLGBs symmetry, their numbers, dimensions of thickest and longest bridge, and axial surface areas of CN head and putamen. We calculated Evans' index (EI) to account for any brain atrophy. We statistically tested associations between sex or age and measured dependent variables, and linear correlations between all measured variables (significance at p 
ISSN:0897-3806
1098-2353
DOI:10.1002/ca.24026