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Multimodal structural MRI in the diagnosis of motor neuron diseases
Pilar M Ferraro1, Federica Agosta1, Nilo Riva2
1Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
Abstract:
This prospective study developed an MRI-based method for identification of individual motor neuron disease (MND) patients and test its accuracy at the individual patient level in an independent sample compared with mimic disorders. 123 patients with amyotrophic lateral sclerosis (ALS), 44 patients with predominantly upper motor neuron disease (PUMN), 20 patients with ALS-mimic disorders, and 78 healthy controls were studied. The diagnostic accuracy of precentral cortical thickness and diffusion tensor (DT) MRI metrics of corticospinal and motor callosal tracts were assessed in a training cohort and externally proved in a validation cohort using a random forest analysis. In the training set, precentral cortical thickness showed 0.86 and 0.89 accuracy in differentiating ALS and PUMN patients from controls, while DT MRI distinguished the two groups from controls with 0.78 and 0.92 accuracy. In ALS vs controls, the combination of cortical thickness and DT MRI metrics (combined model) improved the classification pattern (0.91 accuracy). In the validation cohort, the best accuracy was reached by DT MRI (0.87 and 0.95 accuracy in ALS and PUMN vs mimic disorders). The combined model distinguished ALS and PUMN patients from mimic syndromes with 0.87 and 0.94 accuracy. A multimodal MRI approach that incorporates motor cortical and white matter alterations yields statistically significant improvement in accuracy over using each modality separately in the individual MND patient classification. DT MRI represents the most powerful tool to distinguish MND from mimic disorders.
Insights
This study shows that advanced MRI techniques can accurately identify motor neuron disease (MND) patients, including amyotrophic lateral sclerosis (ALS) and predominantly upper motor neuron disease (PUMN), distinguishing them from mimic disorders. Diffusion tensor (DT) MRI proved most effective for diagnosis.
Area of Science:
- Neuroimaging
- Neurology
- Radiology
Background:
- Accurate diagnosis of motor neuron disease (MND), including amyotrophic lateral sclerosis (ALS) and predominantly upper motor neuron disease (PUMN), is crucial for patient management.
- Distinguishing MND from mimic disorders can be challenging, necessitating improved diagnostic tools.
- Magnetic Resonance Imaging (MRI) offers potential for non-invasive assessment of neurodegeneration.
Purpose of the Study:
- To develop and validate an MRI-based method for individual motor neuron disease (MND) patient identification.
- To assess the diagnostic accuracy of precentral cortical thickness and diffusion tensor (DT) MRI metrics in differentiating MND subtypes from controls and mimic disorders.
- To evaluate the combined utility of multimodal MRI approaches for enhanced diagnostic performance.
Main Methods:
- A prospective study involving 123 amyotrophic lateral sclerosis (ALS) patients, 44 predominantly upper motor neuron disease (PUMN) patients, 20 mimic disorder patients, and 78 healthy controls.
- Assessment of precentral cortical thickness and diffusion tensor (DT) MRI metrics of corticospinal and motor callosal tracts using random forest analysis.
- Validation of the developed MRI method in an independent cohort.
Main Results:
- In the training set, precentral cortical thickness and DT MRI showed high accuracy in differentiating ALS and PUMN from controls.
- The combined model of cortical thickness and DT MRI improved classification accuracy for ALS and PUMN versus controls.
- In the validation cohort, DT MRI achieved the highest accuracy (0.87 for ALS, 0.95 for PUMN vs. mimic disorders), with the combined model showing 0.87 and 0.94 accuracy.
Conclusions:
- A multimodal MRI approach integrating motor cortical and white matter assessments significantly improves diagnostic accuracy for individual MND patients.
- Diffusion tensor (DT) MRI is a powerful tool for differentiating motor neuron disease (MND) from mimic disorders.
- The developed MRI-based method shows high potential for accurate, individual-level diagnosis of motor neuron disease (MND).
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