NEURORADIOLOGY / REVIEW PAPER
Quantitative brain volumetry in neurological disorders:
from disease mechanisms to software solutions
1
2nd Department of Clinical Radiology, Medical University of Warsaw, Warsaw, Poland
2
Central Clinical Hospital, University Clinical Centre, Medical University of Warsaw, Warsaw, Poland
3
Institute of Physiology and Pathology of Hearing, World Hearing Centre, Warsaw, Poland
Submission date: 2025-04-02
Final revision date: 2025-04-07
Acceptance date: 2025-04-07
Publication date: 2025-06-11
Corresponding author
Dominika Bachurska
Central Clinical Hospital, University Clinical Centre, Medical University of Warsaw, Warsaw, Poland
Central Clinical Hospital, University Clinical Centre, Medical University of Warsaw, Warsaw, Poland
Pol J Radiol, 2025; 90: 299-306
KEYWORDS
TOPICS
ABSTRACT
Quantitative magnetic resonance imaging (MRI) volumetry has become a pivotal component in modern neurology, bridging the gap between detailed neuroimaging and clinical decision-making. By employing advanced imaging techniques like 3D T1-weighted, T2-weighted, and fluid-attenuated inversion recovery (FLAIR) sequences, MRI volumetry enables clinicians to objectively quantify brain volume changes associated with neurological conditions such as Alzheimer’s disease, multiple sclerosis, epilepsy, and myotonic dystrophy. Automated segmentation tools, including FreeSurfer, NeuroQuant, volBrain, and AccuBrain, facilitate precise and reproducible analysis of structural brain changes, contributing significantly to early diagnosis, patient monitoring, and therapeutic planning. In Alzheimer’s disease, volumetric MRI enables the detection of early hippocampal and temporal lobe atrophy, providing a crucial biomarker for diagnosis and monitoring disease progression. Similarly, in multiple sclerosis, volumetric analyses quantify grey and white matter degeneration, reflecting motor and cognitive impairment severity. Moreover, quantitative MRI techniques precisely delineate structural abnormalities like hippocampal sclerosis and focal cortical dysplasia in epilepsy, crucial for accurate surgical intervention. Ongoing advances in artificial intelligence and machine learning are set to further enhance these volumetric approaches, addressing current limitations such as inter-observer variability and expanding their clinical applicability. This review outlines the existing landscape and future trajectory of quantitative MRI volumetry, underscoring its expanding role in clinical neurology and personalised medicine.
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