Pierpaolo Alongi1, Davide Stefano Sardina2,3, Rosalia Coppola4, Salvatore Scalisi1, Valentina Puglisi4, Annachiara Arnone5, Giorgio Di Raimondo4, Elisabetta Munerati4, Valerio Alaimo6, Federico Midiri5, Giorgio Russo3, Alessandro Stefano3, Rosalba Giugno7, Tommaso Piccoli8, Massimo Midiri1, Luigi M E Grimaldi4. 1. Department of Radiological Sciences, Nuclear Medicine Service, Fondazione Istituto G. Giglio, Contrada Pietrapollastra-Pisciotto, 90015, Cefalù, Italy. 2. Department of Mathematics and Computer Science, University of Catania, Viale Andrea Doria 6, 95125, Catania, Italy. 3. Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Cefalù, Italy. 4. U.O.C. Neurologia, Fondazione IstitutoG. Giglio, Contrada Pietrapollastra-Pisciotto, 90015, Cefalù, Italy. 5. University of Palermo, Palermo, Italy. 6. Department of Radiological Sciences, Unit of Radiology, Fondazione Istituto G. Giglio, Contrada Pietrapollastra-Pisciotto, 90015, Cefalù, Italy. 7. Department of Computer Science, University of Verona, Strada le Grazie 15, 37134, Verona, Italy. 8. Department of Biomedicine and Clinical Neuroscience, University of Palermo, Palermo, Italy.
Abstract
BACKGROUND AND PURPOSE: While AD can be definitively confirmed by postmortem histopathologic examination, in vivo imaging may improve the clinician's ability to identify AD at the earliest stage. The aim of the study was to test the performance of amyloid PET using new processing imaging algorithm for more precise diagnosis of AD. METHODS: Amyloid PET results using a new processing imaging algorithm (MRI-Less and AAL Atlas) were correlated with clinical, cognitive status, CSF analysis, and other imaging. The regional SUVR using the white matter of cerebellum as reference region and scores from clinical and cognitive tests were used to create ROC curves. Leave-one-out cross-validation was carried out to validate the results. RESULTS: Forty-four consecutive patients with clinical evidence of dementia, were retrospectively evaluated. Amyloid PET scan was positive in 26/44 patients with dementia. After integration with 18F-FDG PET, clinical data and CSF protein levels, 22 of them were classified as AD, the remaining 4 as vascular or frontotemporal dementia. Amyloid and FDG PET, CDR 1, CSF Tau, and p-tau levels showed the best true positive and true negative rates (amyloid PET: AUC = .85, sensitivity .91, specificity .79). A SUVR value of 1.006 in the inferior frontal cortex and of 1.03 in the precuneus region was the best cutoff SUVR value and showed a good correlation with the diagnosis of AD. Thirteen of 44 amyloid PET positive patients have been enrolled in clinical trials using antiamyloid approaches. CONCLUSIONS: Amyloid PET using SPM-normalized SUVR analysis showed high predictive power for the differential diagnosis of AD.
BACKGROUND AND PURPOSE: While AD can be definitively confirmed by postmortem histopathologic examination, in vivo imaging may improve the clinician's ability to identify AD at the earliest stage. The aim of the study was to test the performance of amyloid PET using new processing imaging algorithm for more precise diagnosis of AD. METHODS: Amyloid PET results using a new processing imaging algorithm (MRI-Less and AAL Atlas) were correlated with clinical, cognitive status, CSF analysis, and other imaging. The regional SUVR using the white matter of cerebellum as reference region and scores from clinical and cognitive tests were used to create ROC curves. Leave-one-out cross-validation was carried out to validate the results. RESULTS: Forty-four consecutive patients with clinical evidence of dementia, were retrospectively evaluated. Amyloid PET scan was positive in 26/44 patients with dementia. After integration with 18F-FDG PET, clinical data and CSF protein levels, 22 of them were classified as AD, the remaining 4 as vascular or frontotemporal dementia. Amyloid and FDG PET, CDR 1, CSFTau, and p-tau levels showed the best true positive and true negative rates (amyloid PET: AUC = .85, sensitivity .91, specificity .79). A SUVR value of 1.006 in the inferior frontal cortex and of 1.03 in the precuneus region was the best cutoff SUVR value and showed a good correlation with the diagnosis of AD. Thirteen of 44 amyloid PET positive patients have been enrolled in clinical trials using antiamyloid approaches. CONCLUSIONS: Amyloid PET using SPM-normalized SUVR analysis showed high predictive power for the differential diagnosis of AD.
Authors: Leon Stefanovski; Jil Mona Meier; Roopa Kalsank Pai; Paul Triebkorn; Tristram Lett; Leon Martin; Konstantin Bülau; Martin Hofmann-Apitius; Ana Solodkin; Anthony Randal McIntosh; Petra Ritter Journal: Front Neuroinform Date: 2021-04-01 Impact factor: 4.081