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Updated: Jan 16, 2026
Basics of Multivariate Analysis in Neuroimaging Data
Published on: July 24, 2010
Structural Neuroimaging Markers of Dementia: Insights from ROC Curve Analysis
Sam Pepper1, Setorwu Dzesu1, Lauren Yoksh1
1University of Kansas Medical Center.
Background:
Alzheimer's disease and related dementias (ADRD) are growing public health concerns. Early and accurate differentiation between cognitively normal (NL), mild cognitive impairment (MCI), and dementia is essential for timely intervention. Structural MRI biomarkers-such as grey matter volume (GMV), white matter volume (WMV), white matter hyperintensity volume (WMH), AD signature (a meta-region of interest), and hippocampal occupancy score (HOC)-offer promise for objectively staging cognitive decline.
Objective:
This study aimed to evaluate the diagnostic utility of MRI-derived neuroimaging measures using receiver operating characteristic (ROC) curve analysis to identify optimal thresholds for distinguishing between NL, MCI, and dementia.
Methods:
Data were collected from 466 participants at the KU Alzheimer's Disease Research Center between 2010 and 2025. T1-weighted MRI scans were preprocessed using SPM12 and VBM12. Statistical analyses included ANOVA, Tukey's HSD, Welch's t-tests, and ROC analyses. Youden's J statistic was used to determine optimal cut-points, and multivariate models assessed combined biomarker performance.
Results:
Significant differences were found across diagnostic groups for GMV, WMH, AD signature, and HOC. ROC analysis for Demented vs the control group (NL) showed GMV had an AUC of 0.674 [0.6164, 0.7325], WMH an AUC of 0.700 [0.6454, 0.7539], AD signature an AUC of 0.829 [0.780, 0.8761], and HOC the highest individual performance with an AUC of 0.878 [0.8426, 0.9144]. Further ROC analysis confirmed AD signature and HOC as the most effective biomarkers (AUCs = 0.78 and 0.81) for distinguishing MCI/demented from NL. In MCI vs. demented comparisons, AD signature and HOC biomarkers had AUCs of 0.70 and 0.73, respectively.
Conclusions:
MRI-derived biomarkers, particularly AD signature and HOC, show strong potential for differentiating cognitive impairment stages. ROC-based thresholds offer clinically actionable metrics that can improve diagnostic precision.
Insights
Alzheimer's disease and related dementias (ADRD) can be diagnosed earlier using MRI biomarkers. The AD signature and hippocampal occupancy score (HOC) show the most promise for distinguishing cognitive impairment stages.
Area of Science:
- Neuroimaging
- Biomarkers
- Cognitive Neuroscience
Background:
- Alzheimer's disease and related dementias (ADRD) represent a significant public health challenge.
- Early and accurate diagnosis of cognitive decline, from cognitively normal (NL) to mild cognitive impairment (MCI) and dementia, is crucial for timely intervention.
- Structural magnetic resonance imaging (MRI) biomarkers, including grey matter volume (GMV), white matter volume (WMV), white matter hyperintensity volume (WMH), AD signature, and hippocampal occupancy score (HOC), show potential for objectively staging cognitive decline.
Purpose of the Study:
- To evaluate the diagnostic utility of MRI-derived neuroimaging measures.
- To identify optimal thresholds for distinguishing between NL, MCI, and dementia using receiver operating characteristic (ROC) curve analysis.
Main Methods:
- Data from 466 participants at the KU Alzheimer's Disease Research Center (2010-2025).
- T1-weighted MRI scans preprocessed using SPM12 and VBM12.
- Statistical analyses included ANOVA, Tukey's HSD, Welch's t-tests, and ROC analyses with Youden's J statistic for optimal cut-points.
Main Results:
- Significant differences in GMV, WMH, AD signature, and HOC were observed across diagnostic groups.
- ROC analysis revealed high AUCs for individual biomarkers: HOC (0.878) and AD signature (0.829) for Demented vs. NL.
- AD signature and HOC demonstrated strong performance in distinguishing MCI/demented from NL (AUCs = 0.78, 0.81) and MCI from dementia (AUCs = 0.70, 0.73).
Conclusions:
- MRI-derived biomarkers, particularly AD signature and HOC, show significant potential for differentiating stages of cognitive impairment.
- ROC-based thresholds provide clinically actionable metrics to enhance diagnostic precision for ADRD.
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