Scientific publications

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

Jul 1, 2018 | Magazine: European Journal of Nuclear Medicine and Molecular Imaging

Nobili F (1), Festari C (2,3), Altomare D (2,3), Agosta F (4), Orini S (5), Van Laere K (6,7), Arbizu J (8), Bouwman F (9), Drzezga A (10), Nestor P 11,12, Walker Z (13), Boccardi M (14,15); EANM-EAN Task Force for the Prescription of FDG-PET for Dementing Neurodegenerative Disorders.


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.


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.


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.


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.

CITATION  Eur J Nucl Med Mol Imaging. 2018 Jul;45(9):1557-1566. doi: 10.1007/s00259-018-4030-3. Epub 2018 May 2.