Journal article Open Access

Validation of an optimized SPM procedure for FDG-PET in dementia diagnosis in a clinical setting

Perani, Daniela; Della Rosa, Pasquale Anthony; Cerami, Chiara; Gallivanone, Francesca; Fallanca, Federico; Vanoli, Emilia Giovanna; Panzacchi, Andrea; Nobili, Flavio; Pappata, Sabina; Marcone, Alessandra; Garibotto, Valentina; Castiglioni, Isabella; Magnani, Giuseppe; Cappa, Stefano F; Gianolli, Luigi; EADC-PET Consortium

Diagnostic accuracy in FDG-PET imaging highly depends on the operating procedures. In this clinical study on dementia, we compared the diagnostic accuracy at a single-subject level of a) Clinical Scenarios, b) Standard FDG Images and c) Statistical Parametrical (SPM)Maps generated via a newoptimized SPMprocedure. We evaluated the added value of FDG-PET, either Standard FDG Images or SPM Maps, to Clinical Scenarios. In 88 patients with neurodegenerative diseases (Alzheimer's Disease—AD, Frontotemporal Lobar Degeneration—FTLD, Dementia with Lewy bodies—DLB and Mild Cognitive Impairment—MCI), 9 neuroimaging experts made a forced diagnostic decision on the basis of the evaluation of the three types of information. There was also the possibility of a decision of normality on the FDG-PET images. The clinical diagnosis confirmed at a long-term follow-up was used as the gold standard. SPMMaps showed higher sensitivity and specificity (96% and 84%), and better diagnostic positive (6.8) and negative (0.05) likelihood ratios compared to Clinical Scenarios and Standard FDG Images. SPM Maps increased diagnostic accuracy for differential diagnosis (AD vs. FTD; beta 1.414, p = 0.019). The AUC of the ROC curve was 0.67 for SPM Maps, 0.57 for Clinical Scenarios and 0.50 for Standard FDG Images. In the MCI group, SPMMaps showed the highest predictive prognostic value (mean LOC=2.46), by identifying either normal brain metabolism (exclusionary role) or hypometabolic patterns typical of different neurodegenerative conditions.

Files (1.7 MB)
Name Size
Perani_NeuroImage_2014-P11.pdf
md5:1b9f7af628810fc190d8ba132b26daa6
1.7 MB Download
38
25
views
downloads
Views 38
Downloads 25
Data volume 43.6 MB
Unique views 38
Unique downloads 25

Share

Cite as