TY - JOUR
T1 - A comparison of two statistical mapping tools for automated brain fdg-pet analysis in predicting conversion to alzheimer’s disease in subjects with mild cognitive impairment
AU - Garibotto, Valentina
AU - Trombella, Sara
AU - Antelmi, Luigi
AU - Bosco, Paolo
AU - Redolfi, Alberto
AU - Tabouret-Viaud, Claire
AU - Rager, Olivier
AU - Gold, Gabriel
AU - Giannakopoulos, Panteleimon
AU - Morbelli, Silvia
AU - Nobili, Flavio
AU - Perneczky, Robert
AU - Didic, Mira
AU - Guedj, Eric
AU - Drzezga, Alexander
AU - Ossenkoppele, Rik
AU - van Berckel, Bart
AU - Ratib, Osman
AU - Frisoni, Giovanni B.
PY - 2020
Y1 - 2020
N2 - Objective: Automated voxel-based analysis methods are used to detect cortical hypometabo-lism typical of Alzheimer’s Disease (AD) on FDG-PET brain scans. We compared the accuracy of two clinically validated tools for their ability to identify those MCI subjects progressing to AD at follow-up, to evaluate the impact of the analysis method on FDG-PET diagnostic performance. Methods: SPMGrid and BRASS (Hermes Medical Solutions, Stockholm, Sweden) were tested on 131 MCI and elderly healthy controls from the EADC PET dataset. The concordance between the tools was tested by correlating the quantitative parameters (z-and t-values), calculated by the two software tools, and by measuring the topographical overlap of the abnormal regions (Dice score). Three independent expert readers blindly assigned a diagnosis based on the two map sets. We used conversion to AD dementia as the gold standard. Results: The t-map and z-map calculated with SPMGrid and BRASS, respectively, showed a good correlation (R >.50) for the majority of individual cases (128/131) and for the majority of selected regions of interest (ROIs) (98/116 [22]). The overlap of the hypometabolic patterns from the two tools was, however, poor (Dice score.36). The diagnostic performance was comparable, with BRASS showing significantly higher sensitivity (.82 versus.59) and SPMGrid showing higher specificity (.87 versus.52). Conclusion: Despite similar diagnostic performance in predicting conversion to AD in MCI subjects, the two tools showed significant differences, and the maps provided by the tools showed limited over-lap. These results underline the urgency for standardization across FDG-PET analysis methods for their use in clinical practice.
AB - Objective: Automated voxel-based analysis methods are used to detect cortical hypometabo-lism typical of Alzheimer’s Disease (AD) on FDG-PET brain scans. We compared the accuracy of two clinically validated tools for their ability to identify those MCI subjects progressing to AD at follow-up, to evaluate the impact of the analysis method on FDG-PET diagnostic performance. Methods: SPMGrid and BRASS (Hermes Medical Solutions, Stockholm, Sweden) were tested on 131 MCI and elderly healthy controls from the EADC PET dataset. The concordance between the tools was tested by correlating the quantitative parameters (z-and t-values), calculated by the two software tools, and by measuring the topographical overlap of the abnormal regions (Dice score). Three independent expert readers blindly assigned a diagnosis based on the two map sets. We used conversion to AD dementia as the gold standard. Results: The t-map and z-map calculated with SPMGrid and BRASS, respectively, showed a good correlation (R >.50) for the majority of individual cases (128/131) and for the majority of selected regions of interest (ROIs) (98/116 [22]). The overlap of the hypometabolic patterns from the two tools was, however, poor (Dice score.36). The diagnostic performance was comparable, with BRASS showing significantly higher sensitivity (.82 versus.59) and SPMGrid showing higher specificity (.87 versus.52). Conclusion: Despite similar diagnostic performance in predicting conversion to AD in MCI subjects, the two tools showed significant differences, and the maps provided by the tools showed limited over-lap. These results underline the urgency for standardization across FDG-PET analysis methods for their use in clinical practice.
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85102009902&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/33583380
U2 - https://doi.org/10.2174/1567205018666210212162443
DO - https://doi.org/10.2174/1567205018666210212162443
M3 - Article
C2 - 33583380
SN - 1567-2050
VL - 17
SP - 1186
EP - 1194
JO - Current Alzheimer research
JF - Current Alzheimer research
IS - 13
ER -