ReviewTherapeutic advances in chronic disease2021
Feature selection from magnetic resonance imaging data in ALS: a systematic review.
Review in Therapeutic advances in chronic disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 4 of them syntheses that pooled it.
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Who cites it
17 citing papers in PubMed, 4 syntheses or guidelines pooled it, 26 citations in OpenAlex.
- Non-Invasive Brain Stimulation for Amyotrophic Lateral Sclerosis: Current Evidence and Future Perspectives.Medicina (Kaunas, Lithuania) · 2025Pooled it
- Neuroimaging Insights into the Public Health Burden of Neuropsychiatric Disorders: A Systematic Review of Electroencephalography-Based Cognitive Biomarkers.Medicina (Kaunas, Lithuania) · 2025Pooled it
- Cerebrospinal fluid and blood exosomes as biomarkers for amyotrophic lateral sclerosis; a systematic review.Diagnostic pathology · 2024Pooled it
- Structural magnetic resonance imaging findings and histopathological correlations in motor neuron diseases-A systematic review and meta-analysis.Frontiers in neurology · 2022Pooled it
- Magnetic Resonance Neuroimaging in Amyotrophic Lateral Sclerosis: A Comprehensive Umbrella Review of 18 Studies.Brain sciences · 2025Review
- Role and Potential of Artificial Intelligence in Biomarker Discovery and Development of Treatment Strategies for Amyotrophic Lateral Sclerosis.International journal of molecular sciences · 2025Review
- Surface-based Analyses of Diffusional Kurtosis Imaging in Amyotrophic Lateral Sclerosis: Relationship with Onset Subtypes.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Article
- Cortical thickness correlated with peripheral inflammatory cytokines in amyotrophic lateral sclerosis.Frontiers in neuroscience · 2024Article
- Amyotrophic lateral sclerosis with upper motor neuron predominance: diagnostic accuracy of qualitative and quantitative susceptibility metrics in the precentral gyrus.European radiology · 2023Article
- Digital Alternative Communication for Individuals with Amyotrophic Lateral Sclerosis: What We Have.Journal of clinical medicine · 2023Review
- Sequential alterations in diffusion metrics as correlates of disease severity in amyotrophic lateral sclerosis.Journal of neurology · 2023Article
- Diffusion Tensor Imaging in Amyotrophic Lateral Sclerosis: Machine Learning for Biomarker Development.International journal of molecular sciences · 2023Review
- Longitudinal monitoring of amyotrophic lateral sclerosis by diffusion tensor imaging: Power calculations for group studies.Frontiers in neuroscience · 2022Article
- Simultaneous PET/MRI: The future gold standard for characterizing motor neuron disease-A clinico-radiological and neuroscientific perspective.Frontiers in neurology · 2022Review
- Relaxation-weightedTherapeutic advances in chronic disease · 2022Article
- Artificial neural networks for non-linear age correction of diffusion metrics in the brain.Frontiers in aging neuroscience · 2022Article
- Multiparametric Microstructural MRI and Machine Learning Classification Yields High Diagnostic Accuracy in Amyotrophic Lateral Sclerosis: Proof of Concept.Frontiers in neurology · 2021Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWith the advances in neuroimaging in amyotrophic lateral sclerosis (ALS), it has been speculated that multiparametric magnetic resonance imaging (MRI) is capable to contribute to early diagnosis. Machine learning (ML) can be regarded as the missing piece that allows for the useful integration of multiparametric MRI data into a diagnostic classifier. The major challenges in developing ML classifiers for ALS are limited data quantity and a suboptimal sample to feature ratio which can be addressed by sound feature selection.
methodsWe conducted a systematic review to collect MRI biomarkers that could be used as features by searching the online database PubMed for entries in the recent 4 years that contained cross-sectional neuroimaging data of subjects with ALS and an adequate control group. In addition to the qualitative synthesis, a semi-quantitative analysis was conducted for each MRI modality that indicated which brain regions were most commonly reported.
resultsOur search resulted in 151 studies with a total of 221 datasets. In summary, our findings highly resembled generally accepted neuropathological patterns of ALS, with degeneration of the motor cortex and the corticospinal tract, but also in frontal, temporal, and subcortical structures, consistent with the neuropathological four-stage model of the propagation of pTDP-43 in ALS.
conclusionsThese insights are discussed with respect to their potential for MRI feature selection for future ML-based neuroimaging classifiers in ALS. The integration of multiparametric MRI including DTI, volumetric, and texture data using ML may be the best approach to generate a diagnostic neuroimaging tool for ALS.
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