Literature DB >> 36271084

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

Dafna Ben Bashat1,2,3, Avner Thaler4,5,6, Hedva Lerman Shacham7, Einat Even-Sapir4,7, Matthew Hutchison8, Karleyton C Evans8, Avi Orr-Urterger4,5,9, Jesse M Cedarbaum10,11, Amgad Droby4,5,6, Nir Giladi4,5,6, Anat Mirelman4,5,6, Moran Artzi12,4,5.   

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.
© 2022. The Author(s).

Entities:  

Year:  2022        PMID: 36271084     DOI: 10.1038/s41531-022-00405-9

Source DB:  PubMed          Journal:  NPJ Parkinsons Dis        ISSN: 2373-8057


  33 in total

Review 1.  Imaging approaches to Parkinson disease.

Authors:  David J Brooks
Journal:  J Nucl Med       Date:  2010-04       Impact factor: 10.057

2.  Brain dopamine and the syndromes of Parkinson and Huntington. Clinical, morphological and neurochemical correlations.

Authors:  H Bernheimer; W Birkmayer; O Hornykiewicz; K Jellinger; F Seitelberger
Journal:  J Neurol Sci       Date:  1973-12       Impact factor: 3.181

3.  Parkinson risk in idiopathic REM sleep behavior disorder: preparing for neuroprotective trials.

Authors:  Ronald B Postuma; Jean-Francois Gagnon; Josie-Anne Bertrand; Daphné Génier Marchand; Jacques Y Montplaisir
Journal:  Neurology       Date:  2015-02-13       Impact factor: 9.910

Review 4.  Magnetic resonance imaging for the diagnosis of Parkinson's disease.

Authors:  Beatrice Heim; Florian Krismer; Roberto De Marzi; Klaus Seppi
Journal:  J Neural Transm (Vienna)       Date:  2017-04-04       Impact factor: 3.575

5.  Time course of nigrostriatal degeneration in parkinson's disease. A detailed study of influential factors in human brain amine analysis.

Authors:  P Riederer; S Wuketich
Journal:  J Neural Transm       Date:  1976       Impact factor: 3.575

Review 6.  Advances in markers of prodromal Parkinson disease.

Authors:  Ronald B Postuma; Daniela Berg
Journal:  Nat Rev Neurol       Date:  2016-10-27       Impact factor: 42.937

7.  DaT-SPECT assessment depicts dopamine depletion among asymptomatic G2019S LRRK2 mutation carriers.

Authors:  Moran Artzi; Einat Even-Sapir; Hedva Lerman Shacham; Avner Thaler; Avi Orr Urterger; Susan Bressman; Karen Marder; Talma Hendler; Nir Giladi; Dafna Ben Bashat; Anat Mirelman
Journal:  PLoS One       Date:  2017-04-13       Impact factor: 3.240

Review 8.  Impact of gene mutation in the development of Parkinson's disease.

Authors:  Suganya Selvaraj; Shanmughavel Piramanayagam
Journal:  Genes Dis       Date:  2019-02-27

9.  Neuromelanin or DaT-SPECT: which is the better marker for discriminating advanced Parkinson's disease?

Authors:  A Okuzumi; T Hatano; K Kamagata; M Hori; A Mori; Y Oji; D Taniguchi; K Daida; Y Shimo; N Yanagisawa; S Nojiri; S Aoki; N Hattori
Journal:  Eur J Neurol       Date:  2019-06-24       Impact factor: 6.089

10.  Iron Imaging as a Diagnostic Tool for Parkinson's Disease: A Systematic Review and Meta-Analysis.

Authors:  Nadya Pyatigorskaya; Clara B Sanz-Morère; Rahul Gaurav; Emma Biondetti; Romain Valabregue; Mathieu Santin; Lydia Yahia-Cherif; Stéphane Lehéricy
Journal:  Front Neurol       Date:  2020-05-28       Impact factor: 4.003

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