Literature DB >> 25767187

Usefulness of quantitative susceptibility mapping for the diagnosis of Parkinson disease.

Y Murakami1, S Kakeda2, K Watanabe1, I Ueda1, A Ogasawara1, J Moriya1, S Ide1, K Futatsuya1, T Sato1, K Okada3, T Uozumi3, S Tsuji3, T Liu4, Y Wang4, Y Korogi1.   

Abstract

BACKGROUND AND
PURPOSE: Quantitative susceptibility mapping allows overcoming several nonlocal restrictions of susceptibility-weighted and phase imaging and enables quantification of magnetic susceptibility. We compared the diagnostic accuracy of quantitative susceptibility mapping and R2* (1/T2*) mapping to discriminate between patients with Parkinson disease and controls.
MATERIALS AND METHODS: For 21 patients with Parkinson disease and 21 age- and sex-matched controls, 2 radiologists measured the quantitative susceptibility mapping values and R2* values in 6 brain structures (the thalamus, putamen, caudate nucleus, pallidum, substantia nigra, and red nucleus).
RESULTS: The quantitative susceptibility mapping values and R2* values of the substantia nigra were significantly higher in patients with Parkinson disease (P < .01); measurements in other brain regions did not differ significantly between patients and controls. For the discrimination of patients with Parkinson disease from controls, receiver operating characteristic analysis suggested that the optimal cutoff values for the substantia nigra, based on the Youden Index, were >0.210 for quantitative susceptibility mapping and >28.8 for R2*. The sensitivity, specificity, and accuracy of quantitative susceptibility mapping were 90% (19 of 21), 86% (18 of 21), and 88% (37 of 42), respectively; for R2* mapping, they were 81% (17 of 21), 52% (11 of 21), and 67% (28 of 42). Pair-wise comparisons showed that the areas under the receiver operating characteristic curves were significantly larger for quantitative susceptibility mapping than for R2* mapping (0.91 versus 0.69, P < .05).
CONCLUSIONS: Quantitative susceptibility mapping showed higher diagnostic performance than R2* mapping for the discrimination between patients with Parkinson disease and controls.
© 2015 by American Journal of Neuroradiology.

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Year:  2015        PMID: 25767187      PMCID: PMC8013031          DOI: 10.3174/ajnr.A4260

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  45 in total

1.  Cerebral microbleeds: burden assessment by using quantitative susceptibility mapping.

Authors:  Tian Liu; Krishna Surapaneni; Min Lou; Liuquan Cheng; Pascal Spincemaille; Yi Wang
Journal:  Radiology       Date:  2011-11-04       Impact factor: 11.105

2.  Brain iron deposition and sequence characteristics in Parkinsonism: comparison of SWI, T₂* maps, T₂-weighted-, and FLAIR-SPACE.

Authors:  Maija Rossi; Hanna Ruottinen; Irina Elovaara; Pertti Ryymin; Seppo Soimakallio; Hannu Eskola; Prasun Dastidar
Journal:  Invest Radiol       Date:  2010-12       Impact factor: 6.016

3.  Magnetic resonance imaging markers of Parkinson's disease nigrostriatal signature.

Authors:  Patrice Péran; Andrea Cherubini; Francesca Assogna; Fabrizio Piras; Carlo Quattrocchi; Antonella Peppe; Pierre Celsis; Olivier Rascol; Jean-François Démonet; Alessandro Stefani; Mariangela Pierantozzi; Francesco Ernesto Pontieri; Carlo Caltagirone; Gianfranco Spalletta; Umberto Sabatini
Journal:  Brain       Date:  2010-08-23       Impact factor: 13.501

4.  Toward in vivo histology: a comparison of quantitative susceptibility mapping (QSM) with magnitude-, phase-, and R2*-imaging at ultra-high magnetic field strength.

Authors:  Andreas Deistung; Andreas Schäfer; Ferdinand Schweser; Uta Biedermann; Robert Turner; Jürgen R Reichenbach
Journal:  Neuroimage       Date:  2012-10-02       Impact factor: 6.556

5.  Quantitative susceptibility mapping in multiple sclerosis.

Authors:  Christian Langkammer; Tian Liu; Michael Khalil; Christian Enzinger; Margit Jehna; Siegrid Fuchs; Franz Fazekas; Yi Wang; Stefan Ropele
Journal:  Radiology       Date:  2013-01-11       Impact factor: 11.105

6.  Quantitative mapping of T1 and T2* discloses nigral and brainstem pathology in early Parkinson's disease.

Authors:  Simon Baudrexel; Lucas Nürnberger; Udo Rüb; Carola Seifried; Johannes C Klein; Thomas Deller; Helmuth Steinmetz; Ralf Deichmann; Rüdiger Hilker
Journal:  Neuroimage       Date:  2010-03-06       Impact factor: 6.556

7.  Assessment of relative brain iron concentrations using T2-weighted and T2*-weighted MRI at 3 Tesla.

Authors:  R J Ordidge; J M Gorell; J C Deniau; R A Knight; J A Helpern
Journal:  Magn Reson Med       Date:  1994-09       Impact factor: 4.668

8.  Cerebral involvement in systemic lupus erythematosus (SLE): comparison of positron emission tomography (PET) with other imaging methods.

Authors:  G J Meyer; O Schober; G Stoppe; K Wildhagen; J W Seidel; H Hundeshagen
Journal:  Psychiatry Res       Date:  1989-09       Impact factor: 3.222

9.  Hematoma volume measurement in gradient echo MRI using quantitative susceptibility mapping.

Authors:  Shuo Wang; Min Lou; Tian Liu; Deqi Cui; Xiaomei Chen; Yi Wang
Journal:  Stroke       Date:  2013-05-23       Impact factor: 7.914

10.  Midbrain iron content in early Parkinson disease: a potential biomarker of disease status.

Authors:  W R Wayne Martin; Marguerite Wieler; Myrlene Gee
Journal:  Neurology       Date:  2008-01-02       Impact factor: 9.910

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  48 in total

1.  Potential usefulness of signal intensity of cerebral gyri on quantitative susceptibility mapping for discriminating corticobasal degeneration from progressive supranuclear palsy and Parkinson's disease.

Authors:  Mari Miyata; Shingo Kakeda; Yasuko Toyoshima; Satoru Ide; Kazumasa Okada; Hiroaki Adachi; Yi Wang; Yukunori Korogi
Journal:  Neuroradiology       Date:  2019-07-02       Impact factor: 2.804

2.  Fidelity imposed network edit (FINE) for solving ill-posed image reconstruction.

Authors:  Jinwei Zhang; Zhe Liu; Shun Zhang; Hang Zhang; Pascal Spincemaille; Thanh D Nguyen; Mert R Sabuncu; Yi Wang
Journal:  Neuroimage       Date:  2020-01-22       Impact factor: 6.556

3.  Automated adaptive preconditioner for quantitative susceptibility mapping.

Authors:  Zhe Liu; Yan Wen; Pascal Spincemaille; Shun Zhang; Yihao Yao; Thanh D Nguyen; Yi Wang
Journal:  Magn Reson Med       Date:  2019-08-11       Impact factor: 4.668

Review 4.  Introduction to Quantitative Susceptibility Mapping and Susceptibility Weighted Imaging.

Authors:  Pascal P R Ruetten; Jonathan H Gillard; Martin J Graves
Journal:  Br J Radiol       Date:  2019-07-26       Impact factor: 3.039

5.  Simultaneous metabolic and functional imaging of the brain using SPICE.

Authors:  Rong Guo; Yibo Zhao; Yudu Li; Yao Li; Zhi-Pei Liang
Journal:  Magn Reson Med       Date:  2019-07-11       Impact factor: 4.668

6.  Ventral posterior substantia nigra iron increases over 3 years in Parkinson's disease.

Authors:  Niels Bergsland; Robert Zivadinov; Ferdinand Schweser; Jesper Hagemeier; David Lichter; Thomas Guttuso
Journal:  Mov Disord       Date:  2019-06-10       Impact factor: 10.338

Review 7.  Region-Specific Iron Measured by MRI as a Biomarker for Parkinson's Disease.

Authors:  Xiaojun Guan; Xiaojun Xu; Minming Zhang
Journal:  Neurosci Bull       Date:  2017-05-17       Impact factor: 5.203

8.  Clinical Integration of Automated Processing for Brain Quantitative Susceptibility Mapping: Multi-Site Reproducibility and Single-Site Robustness.

Authors:  Pascal Spincemaille; Zhe Liu; Shun Zhang; Ilhami Kovanlikaya; Matteo Ippoliti; Marcus Makowski; Richard Watts; Ludovic de Rochefort; Vijay Venkatraman; Patricia Desmond; Mathieu D Santin; Stéphane Lehéricy; Brian H Kopell; Patrice Péran; Yi Wang
Journal:  J Neuroimaging       Date:  2019-08-04       Impact factor: 2.486

Review 9.  Susceptibility tensor imaging (STI) of the brain.

Authors:  Wei Li; Chunlei Liu; Timothy Q Duong; Peter C M van Zijl; Xu Li
Journal:  NMR Biomed       Date:  2016-04-27       Impact factor: 4.044

Review 10.  Neuroimaging of Parkinson's disease: Expanding views.

Authors:  Carol P Weingarten; Mark H Sundman; Patrick Hickey; Nan-kuei Chen
Journal:  Neurosci Biobehav Rev       Date:  2015-09-26       Impact factor: 8.989

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