Flavio Nobili1, Cristina Festari2,3, Daniele Altomare2,3, Federica Agosta4, Stefania Orini5, Koen Van Laere6,7, Javier Arbizu8, Femke Bouwman9, Alexander Drzezga10, Peter Nestor11,12, Zuzana Walker13, Marina Boccardi14,15. 1. Department of Neuroscience (DINOGMI), University of Genoa and Polyclinic San Martino Hospital, Genoa, Italy. flaviomariano.nobili@hsanmartino.it. 2. LANE - Laboratory of Alzheimer's Neuroimaging & Epidemiology, IRCCS S. Giovanni di Dio, Fatebenefratelli, Brescia, Italy. 3. Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy. 4. Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy. 5. Alzheimer Operative Unit, IRCCS S. Giovanni di Dio, Fatebenefratelli, Brescia, Italy. 6. Division of Nuclear Medicine, University Hospitals Leuven, Leuven, Belgium. 7. Department of Imaging and Pathology, KU Leuven, Leuven, Belgium. 8. Department of Nuclear Medicine, Clinica Universidad de Navarra, University of Navarra, Pamplona, Spain. 9. Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands. 10. Department of Nuclear Medicine, University Hospital of Cologne, University of Cologne and German Center for Neurodegenerative Diseases (DZNE), Cologne, Germany. 11. German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany. 12. Queensland Brain Institute, University of Queensland and Mater Hospital, Brisbane, Australia. 13. Division of Psychiatry & Essex Partnership University, University College London, London, UK. 14. LANE - Laboratory of Alzheimer's Neuroimaging & Epidemiology, IRCCS S. Giovanni di Dio, Fatebenefratelli, Brescia, Italy. marina.boccardi@unige.ch. 15. LANVIE (Laboratoire de Neuroimagerie du Vieillissement), Department of Psychiatry, University of Geneva, Chemin du Petit-Bel-Air, 2, 1225, Chene-Bourg, Geneva, Switzerland. marina.boccardi@unige.ch.
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.
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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