Diffusion bubble model: a novel MRI approach for detection and subtyping of neonatal punctate white matter lesions

Erjun Zhang, Benjamin De Leener, Gregory A. Lodygensky

Article de revue (2025)

Accéder à ce document
Disponible
Libre accès au texte intégral dans PolyPublie et chez l'éditeur officiel
Version officielle de l'éditeur
Texte Texte • 3MB •

Résumé

Diffusion magnetic resonance imaging, particularly diffusion tensor imaging (DTI), is an indispensable noninvasive tool for visualizing brain structure and detecting injuries by tracking water molecule motion. However, DTI may overlook subtle microstructural alterations due to its oversimplified model. In this study, we introduced the Diffusion Bubble Model (DBM), a spectrum-based framework that decomposes each voxel’s signal into a continuum of isotropic ‘‘bubbles’’ after the anisotropic tensor adjustment, thereby capturing a spectrum with continuous range of restriction levels. From the resulting isotropic-diffusion spectrum we derive metrics representing the spectrum and free-water of the tissue voxel. We applied DBM to diffusion data from 20 infants with punctate white-matter lesions (PWMLs) in the optic radiation and compared lesion regions with contralateral regions as well as matched controls. DBM segregated the lesions into two phenotypes that DTI could not differentiate: wet-type (Ν = 10) with −68.4% less free water compared to contralateral and no difference versus controls. Notably, wet-type lesions exhibited stronger slow-diffusion shifts on DBM (−37.6% in the ¼ area line, −52.7% in left FWHM) than changes in mean diffusivity (−30.3%) from DTI. These findings suggest that DBM can reveal microstructural heterogeneity invisible to conventional DTI, offering a promising tool for refined characterization and monitoring of neonatal brain injury.

Mots clés

Organismes subventionnaires:
China Scholarship Council, Canada First Research Excellence Fund, CHU Sainte-Justine Research Center, QBIN, TransMedTech Institute
Adresse URL de PolyPublie:
Titre de la revue :
NeuroImage ( vol. 317 )
Maison d'édition:
Elsevier BV
OAI:
oai:publications.polymtl.ca:66297
ORCID
Date du dépôt:
26 juin 2025 16:11
Dernière modification:
14 oct. 2026 14:27
Citer en APA 7:
Zhang, E., De Leener, B., & Lodygensky, G. A. (2025). Diffusion bubble model: a novel MRI approach for detection and subtyping of neonatal punctate white matter lesions. NeuroImage, 317, 121324 (12 pages). https://doi.org/10.1016/j.neuroimage.2025.121324

Statistiques

Total des téléchargements à partir de PolyPublie

Téléchargements par année

Provenance des téléchargements

Dimensions

Actions réservées au personnel

Afficher document
Afficher document