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Neuromelanin and T(2)*-MRI for the assessment of genetically at-risk, prodromal, and symptomatic Parkinson’s disease
MRI was suggested as a promising method for the diagnosis and assessment of Parkinson’s Disease (PD). We aimed to assess the sensitivity of neuromelanin-MRI and T(2)* with radiomics analysis for detecting PD, identifying individuals at risk, and evaluating genotype-related differences. Patients with...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9586960/ https://www.ncbi.nlm.nih.gov/pubmed/36271084 http://dx.doi.org/10.1038/s41531-022-00405-9 |
Sumario: | MRI was suggested as a promising method for the diagnosis and assessment of Parkinson’s Disease (PD). We aimed to assess the sensitivity of neuromelanin-MRI and T(2)* with radiomics analysis for detecting PD, identifying individuals at risk, and evaluating genotype-related differences. Patients with PD and non-manifesting (NM) participants [NM-carriers (NMC) and NM-non-carriers (NMNC)], underwent MRI and DAT-SPECT. Imaging-based metrics included 48 neuromelanin and T(2)* radiomics features and DAT-SPECT specific-binding-ratios (SBR), were extracted from several brain regions. Imaging values were assessed for their correlations with age, differences between groups, and correlations with the MDS-likelihood-ratio (LR) score. Several machine learning classifiers were evaluated for group classification. A total of 127 participants were included: 46 patients with PD (62.3 ± 10.0 years) [15:LRRK2-PD, 16:GBA-PD, and 15:idiopathic-PD (iPD)], 47 NMC (51.5 ± 8.3 years) [24:LRRK2-NMC and 23:GBA-NMC], and 34 NMNC (53.5 ± 10.6 years). No significant correlations were detected between imaging parameters and age. Thirteen MRI-based parameters and radiomics features demonstrated significant differences between PD and NMNC groups. Support-Vector-Machine (SVM) classifier achieved the highest performance (AUC = 0.77). Significant correlations were detected between LR scores and two radiomic features. The classifier successfully identified two out of three NMC who converted to PD. Genotype-related differences were detected based on radiomic features. SBR values showed high sensitivity in all analyses. In conclusion, neuromelanin and T(2)* MRI demonstrated differences between groups and can be used for the assessment of individuals at-risk in cases when DAT-SPECT can’t be performed. Combining neuromelanin and T(2)*-MRI provides insights into the pathophysiology underlying PD, and suggests that iron accumulation precedes neuromelanin depletion during the prodromal phase. |
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