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Dorsal medulla surface texture: Differentiating neuromyelitis optica spectrum disorder from multiple sclerosis
Darin T Okuda1, Thomas Stanley2, Morgan McCreary1
1Department of Neurology, Neuroinnovation Program, Multiple Sclerosis and Neuroimmunology Imaging Program, The University of Texas Southwestern Medical Center at Dallas, Dallas, Texas, USA.
Summary
Diagnosing neuromyelitis optica spectrum disorder (NMOSD) is crucial. Surface texture analysis of the dorsal medulla using MRI can differentiate NMOSD from multiple sclerosis (MS).
Area of Science:
- Neuroimaging
- Neurology
- Medical Diagnostics
Background:
- Accurate diagnosis of neuromyelitis optica spectrum disorder (NMOSD) is critical to prevent neurological disability.
- Distinguishing NMOSD from multiple sclerosis (MS) is challenging but essential for appropriate treatment.
Purpose of the Study:
- To investigate MRI-based surface texture analysis of the dorsal medulla for differentiating NMOSD from MS.
- To evaluate the diagnostic performance of introverted planar triangle counts in the dorsal medulla for NMOSD classification.
Main Methods:
- Retrospective analysis of 3-Tesla 3D brain MRI from NMOSD, MS, other neurological diseases, and healthy controls.
- Comparison of surface texture characteristics, specifically introverted planar triangle counts and their spatial patterns, in the area postrema.
- Calculation of sensitivity, specificity, PPV, and NPV for NMOSD classification using an optimal triangle threshold.
Main Results:
- Significantly higher median introverted triangle counts were found in NMOSD patients compared to MS and other neurological disease groups.
- Distinct spatial dissemination patterns of triangles in the dorsal medulla differentiated NMOSD from MS.
- Out-of-sample analysis achieved 83% sensitivity, 100% specificity, 100% PPV, and 60% NPV for NMOSD identification.
Conclusions:
- Dorsal medulla surface texture analysis via MRI can effectively differentiate NMOSD from MS.
- These findings highlight the potential of advanced MRI texture analysis in diagnosing NMOSD.
