npj Parkinson's Disease (Oct 2022)

Neuromelanin and T2*-MRI for the assessment of genetically at-risk, prodromal, and symptomatic Parkinson’s disease

  • Dafna Ben Bashat,
  • Avner Thaler,
  • Hedva Lerman Shacham,
  • Einat Even-Sapir,
  • Matthew Hutchison,
  • Karleyton C. Evans,
  • Avi Orr-Urterger,
  • Jesse M. Cedarbaum,
  • Amgad Droby,
  • Nir Giladi,
  • Anat Mirelman,
  • Moran Artzi

DOI
https://doi.org/10.1038/s41531-022-00405-9
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 8

Abstract

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Abstract 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 T2* 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 T2* 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 T2* 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 T2*-MRI provides insights into the pathophysiology underlying PD, and suggests that iron accumulation precedes neuromelanin depletion during the prodromal phase.