DOI: 10.1007/s00259-018-4030-3Pages: 1557-1566

Automated assessment of FDG-PET for differential diagnosis in patients with neurodegenerative disorders

1. University of Genoa and Polyclinic San Martino Hospital, Department of Neuroscience (DINOGMI)

2. IRCCS S. Giovanni di Dio, LANE – Laboratory of Alzheimer’s Neuroimaging & Epidemiology

3. University of Brescia, Department of Molecular and Translational Medicine

4. Vita-Salute San Raffaele University, Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute

5. IRCCS S. Giovanni di Dio, Alzheimer Operative Unit

6. University Hospitals Leuven, Division of Nuclear Medicine

7. KU Leuven, Department of Imaging and Pathology

8. University of Navarra, Department of Nuclear Medicine, Clinica Universidad de Navarra

9. VU University Medical Center, Department of Neurology & Alzheimer Center, Amsterdam Neuroscience

10. University Hospital of Cologne, University of Cologne and German Center for Neurodegenerative Diseases (DZNE), Department of Nuclear Medicine

11. German Center for Neurodegenerative Diseases (DZNE)

12. University of Queensland and Mater Hospital, Queensland Brain Institute

13. University College London, Division of Psychiatry & Essex Partnership University

14. University of Geneva, LANVIE (Laboratoire de Neuroimagerie du Vieillissement), Department of Psychiatry

Correspondence to:
Marina Boccardi
Tel: 0041.(0)22.3055764
Email: marina.boccardi@unige.ch

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Abstract

Purpose

To review literature until November 2015 and reach a consensus on whether automatic semi-quantification of brain FDG-PET is useful in the clinical setting for neurodegenerative disorders.

Methods

A literature search was conducted in Medline, Embase, and Google Scholar. Papers were selected with a lower limit of 30 patients (no limits with autopsy confirmation). Consensus recommendations were developed through a Delphi procedure, based on the expertise of panelists, who were also informed about the availability and quality of evidence, assessed by an independent methodology team.

Results

Critical outcomes were available in nine among the 17 papers initially selected. Only three papers performed a direct comparison between visual and automated assessment and quantified the incremental value provided by the latter. Sensitivity between visual and automatic analysis is similar but automatic assessment generally improves specificity and marginally accuracy. Also, automated assessment increases diagnostic confidence. As expected, performance of visual analysis is reported to depend on the expertise of readers.

Conclusions

Tools for semi-quantitative evaluation are recommended to assist the nuclear medicine physician in reporting brain FDG-PET pattern in neurodegenerative conditions. However, heterogeneity, complexity, and drawbacks of these tools should be known by users to avoid misinterpretation. Head-to-head comparisons and an effort to harmonize procedures are encouraged.

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  • Accepted: Apr 16, 2018
  • Online: May 2, 2018

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