Related Experiment Video
Updated: Jul 2, 2026
Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
Published on: January 7, 2019
Structural MRI Volumetry Index for Differentiation of Progressive Supranuclear Palsy From Parkinson's Disease and
Mingnan Jia1, Hui You1, Zhaoxi Liu2
1Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Background:
Although Parkinson's disease (PD) and Parkinsonism-Plus syndromes (PPS) exhibit distinct brain atrophy, current clinical differentiation heavily relies on manual, plane-specific 2D metrics, which are labor-intensive and observer-dependent. To fill this gap, this study developed an automated, software-independent metric-the parkinsonism volumetric index (PDSVI)-calculated as [(pons volume × third ventricle volume)/(midbrain volume × thalamus volume) × 10].
Purpose:
To evaluate the performance of PDSVI in precisely differentiating progressive supranuclear palsy (PSP) from PD, multiple system atrophy cerebellar (MSA-C) and parkinsonian (MSA-P) types.
Study Type:
Retrospective.
Population:
246 PD, 108 PSP, 63 MSA-C, 63 MSA-P (N = 480, 253 males and 227 females; mean age: 63.3 ± 9.2 years) and 252 healthy controls (HC) (134 males and 118 females; mean age: 64.9 ± 8.2 years).
Field Strength/Sequence:
3 T, 3D inversion-prepared fast spoiled gradient echo sequence T1-weighted Imaging.
Assessment:
Manual magnetic resonance parkinsonism index (MRPI) was measured by two raters. Automated brain volumetry was performed using a pre-trained cascaded VB-Net. Patients were randomly assigned to training (n = 320) and internal validation (n = 160) cohorts via 2:1 stratified randomization. Diagnostic performance of manual MRPI, pons/midbrain volume ratio, and PDSVI were assessed.
Statistical Tests:
Diagnostic performance was assessed via receiver operating characteristic (ROC) curve analysis and DeLong's test; p < 0.05 was considered statistically significant.
Results:
In internal validation cohort, ROC analysis showed that PDSVI distinguished PSP from non-PSP (AUC = 0.897), PD (0.873), MSA-P (0.950), MSA-C (0.939), and HC (0.909), comparable to manual MRPI (AUCs: 0.909, 0.886, 0.923, 0.984 and 0.862, p values: 0.760, 0.786, 0.492, 0.092, 0.287, respectively).
Data Conclusion:
This study proposes a fully automated, 3D-T1-derived parameter that, while exhibiting lower sensitivity compared to the manual MRPI, provides comparable overall diagnostic performance among PSP, PD, MSA, and healthy controls.
Evidence Level:
3.
Technical Efficacy:
Stage 2.
More Related Videos
09:06Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease
Published on: June 9, 2018
12:50Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
Published on: April 14, 2014
