Literature DB >> 29804474

The utility of the combined use of 123I-FP-CIT SPECT and neuromelanin MRI in differentiating Parkinson's disease from other parkinsonian syndromes.

Eiji Matsusue1, Yoshio Fujihara1, Kenichiro Tanaka2, Yuki Aozasa2, Manabu Shimoda2, Hiroyuki Nakayasu2, Kazuhiko Nakamura1, Toshihide Ogawa3.   

Abstract

BACKGROUND: Neuromelanin magnetic resonance imaging (NmMRI) and 123I-FP-CIT dopamine transporter single photon emission computed tomography (DAT-SPECT) provide specific information that distinguishes Parkinson's disease (PD) from non-degenerative parkinsonian syndrome (NDPS).
PURPOSE: To determine whether a multiparametric scoring system (MSS) could improve accuracy compared to each parameter of DAT-SPECT and NmMRI in differentiating PD from NDPS.
MATERIAL AND METHODS: A total of 49 patients, including 14 with NDPS, 30 with PD, and five with atypical parkinsonian disorder (APD) underwent both NmMRI and DAT-SPECT and were evaluated. The average (Ave) and the asymmetry index (AI) were calculated in the substantia nigra compacta area (SNc-area), SNc midbrain-tegmentum contrast ratio (SNc-CR), and specific binding ratio (SBR). Cut-off values were determined, using receiver operating characteristic (ROC) analysis, for the differentiation of PD from NDPS on the statistically significant parameters. All cases were scored as either 1 (PD) or 0 (NDPS) for each parameter according to its threshold. These individual scores were totaled for each case, yielding a combined score for each case to obtain a cut-off value for the MSS.
RESULTS: The Ave-SNc-area, Ave-SNc-CR, and Ave-SBR in PD were significantly lower than those in NDPS. The AI-SNc-area and AI-SBR in PD were significantly higher than those in NDPS. Of the five parameters, the highest accuracy was 93% for the Ave-SNc-area. For the MSS, a cut-off value of 3 was the accuracy of 96%. Besides, no significant difference was observed between PD and APD on all parameters.
CONCLUSION: An MSS has comparable or better accuracy compared to each parameter of DAT-SPECT and NmMRI in distinguishing PD from NDPS.

Entities:  

Keywords:  I-FP-CIT; Magnetic resonance imaging; Parkinson's disease; combined analysis; dopamine transporter imaging; neuromelanin imaging

Mesh:

Substances:

Year:  2018        PMID: 29804474     DOI: 10.1177/0284185118778871

Source DB:  PubMed          Journal:  Acta Radiol        ISSN: 0284-1851            Impact factor:   1.990


  7 in total

1.  Diagnostic performance of neuromelanin-sensitive magnetic resonance imaging for patients with Parkinson's disease and factor analysis for its heterogeneity: a systematic review and meta-analysis.

Authors:  Se Jin Cho; Yun Jung Bae; Jong-Min Kim; Donghyun Kim; Sung Hyun Baik; Leonard Sunwoo; Byung Se Choi; Jae Hyoung Kim
Journal:  Eur Radiol       Date:  2020-09-04       Impact factor: 5.315

Review 2.  Biomarkers for Parkinson's Disease: How Good Are They?

Authors:  Tianbai Li; Weidong Le
Journal:  Neurosci Bull       Date:  2019-10-23       Impact factor: 5.203

3.  Early-stage Parkinson's disease: Abnormal nigrosome 1 and 2 revealed by a voxelwise analysis of neuromelanin-sensitive MRI.

Authors:  Young Hee Sung; Young Noh; Eung Yeop Kim
Journal:  Hum Brain Mapp       Date:  2021-03-10       Impact factor: 5.038

4.  Semi-Automatic Signature-Based Segmentation Method for Quantification of Neuromelanin in Substantia Nigra.

Authors:  Gašper Zupan; Dušan Šuput; Zvezdan Pirtošek; Andrej Vovk
Journal:  Brain Sci       Date:  2019-11-22

Review 5.  Dopamine Transporter Imaging, Current Status of a Potential Biomarker: A Comprehensive Review.

Authors:  Giovanni Palermo; Sara Giannoni; Gabriele Bellini; Gabriele Siciliano; Roberto Ceravolo
Journal:  Int J Mol Sci       Date:  2021-10-18       Impact factor: 5.923

6.  MRI multiparametric scoring system for pial blood supply of intracranial meningiomas.

Authors:  Fumiyo Higaki; Satoshi Inoue; Wakako Oda; Eiji Matsusue; Takao Hiraki
Journal:  Acta Radiol Open       Date:  2022-04-08

7.  Cerebrospinal Fluid Levels of Autophagy-related Proteins Represent Potentially Novel Biomarkers of Early-Stage Parkinson's Disease.

Authors:  Jinyoung Youn; Sang-Bin Lee; Hyo Sang Lee; Hyun Ok Yang; Jinse Park; Ji Sun Kim; Eungseok Oh; Suyeon Park; Wooyoung Jang
Journal:  Sci Rep       Date:  2018-11-15       Impact factor: 4.379

  7 in total

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