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European Radiology

, Volume 27, Issue 6, pp 2665–2675 | Cite as

Magnetic Resonance Parkinsonism Index: diagnostic accuracy of a fully automated algorithm in comparison with the manual measurement in a large Italian multicentre study in patients with progressive supranuclear palsy

  • Salvatore Nigro
  • Gennarina Arabia
  • Angelo Antonini
  • Luca Weis
  • Andrea Marcante
  • Alessandro Tessitore
  • Mario Cirillo
  • Gioacchino Tedeschi
  • Stefano Zanigni
  • Giovanna Calandra-Buonaura
  • Caterina Tonon
  • Gianni Pezzoli
  • Roberto Cilia
  • Mario Zappia
  • Alessandra Nicoletti
  • Calogero Edoardo Cicero
  • Michele Tinazzi
  • Pierluigi Tocco
  • Nicolò Cardobi
  • Aldo Quattrone
Neuro

Abstract

Objectives

To investigate the reliability of a new in-house automatic algorithm for calculating the Magnetic Resonance Parkinsonism Index (MRPI), in a large multicentre study population of patients affected by progressive supranuclear palsy (PSP) or Parkinson’s disease (PD), and healthy controls (HC), and to compare the diagnostic accuracy of the automatic and manual MRPI values.

Methods

The study included 88 PSP patients, 234 PD patients and 117 controls. MRI was performed using both 3T and 1.5T scanners. Automatic and manual MRPI values were evaluated, and accuracy of both methods in distinguishing PSP from PD and controls was calculated.

Results

No statistical differences were found between automated and manual MRPI values in all groups. The automatic MRPI values differentiated PSP from PD with an accuracy of 95 % (manual MRPI accuracy 96 %) and 97 % (manual MRPI accuracy 100 %) for 1.5T and 3T scanners, respectively.

Conclusion

Our study showed that the new in-house automated method for MRPI calculation was highly accurate in distinguishing PSP from PD. Our automatic approach allows a widespread use of MRPI in clinical practice and in longitudinal research studies.

Key Points

• A new automatic method for calculating the MRPI is presented.

• Automatic MRPI values are in good agreement with manual values.

• Automatic MRPI can distinguish patients with PSP from patients with PD.

• The automatic method overcomes MRPI application limitations in routine practice.

• The automatic method may allow a more widespread use of MRPI.

Keywords

Magnetic Resonance Parkinsonism Index Progressive supranuclear palsy Parkinson’s disease Automatic segmentation Neurodegenerative disease 

Abbreviations

M

Midbrain

MCP

Middle cerebellar peduncle

MRPI

Magnetic Resonance Parkinsonism Index

P

Pons

PD

Parkinson’s disease

PSP

Progressive supranuclear palsy

ROC

Receiver operating characteristic

SCP

Superior cerebellar peduncle

Notes

Acknowledgements

The scientific guarantor of this publication is Professor Aldo Quattrone. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. The authors state that this work has not received any funding. No complex statistical methods were necessary for this paper. Institutional Review Board approval was obtained. Written informed consent was obtained from all subjects (patients) in this study. Methodology: cross sectional study, multicentre study.

Supplementary material

330_2016_4622_MOESM1_ESM.docx (6.3 mb)
ESM 1 (DOCX 6481 kb)
330_2016_4622_MOESM2_ESM.docx (16 kb)
ESM 2 (DOCX 16 kb)

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Copyright information

© European Society of Radiology 2016

Authors and Affiliations

  • Salvatore Nigro
    • 1
  • Gennarina Arabia
    • 2
  • Angelo Antonini
    • 3
  • Luca Weis
    • 3
  • Andrea Marcante
    • 3
  • Alessandro Tessitore
    • 4
    • 5
  • Mario Cirillo
    • 4
    • 5
  • Gioacchino Tedeschi
    • 4
    • 5
  • Stefano Zanigni
    • 6
    • 7
  • Giovanna Calandra-Buonaura
    • 7
    • 8
  • Caterina Tonon
    • 6
    • 7
  • Gianni Pezzoli
    • 9
  • Roberto Cilia
    • 9
  • Mario Zappia
    • 10
  • Alessandra Nicoletti
    • 10
  • Calogero Edoardo Cicero
    • 10
  • Michele Tinazzi
    • 11
  • Pierluigi Tocco
    • 11
  • Nicolò Cardobi
    • 12
  • Aldo Quattrone
    • 1
    • 2
  1. 1.Institute of Bioimaging and Molecular PhysiologyNational Research CouncilCatanzaroItaly
  2. 2.Institute of Neurology, Department of Medical and Surgical SciencesUniversity ‘Magna Graecia’CatanzaroItaly
  3. 3.Parkinson’s Disease and Movement Disorders Unit‘Fondazione Ospedale San Camillo’ - I.R.C.C.SVenice-LidoItaly
  4. 4.Department of Medical, Surgical, Neurological, Metabolic and Aging SciencesSecond University of NaplesNaplesItaly
  5. 5.MRI Research Center SUN-FISMSecond University of NaplesNaplesItaly
  6. 6.Functional MR UnitPoliclinico S. Orsola – MalpighiBolognaItaly
  7. 7.Department of Biomedical and Neuromotor SciencesUniversity of BolognaBolognaItaly
  8. 8.IRCCS Istituto delle Scienze Neurologiche di BolognaBolognaItaly
  9. 9.Parkinson InstituteASST G.Pini - CTO, ex ICPMilanoItaly
  10. 10.Department ‘G.F. Ingrassia’, Section of NeurosciencesUniversity of CataniaCataniaItaly
  11. 11.Department of Neurological and Movement SciencesUniversity Hospital of VeronaVeronaItaly
  12. 12.Institute of RadiologyUniversity Hospital of VeronaVeronaItaly

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