http://www.cnr.it/ontology/cnr/individuo/prodotto/ID287910

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

Type

Prodotto della ricerca (Classe)
Articolo in rivista (Classe)

Label

Validation of an optimized SPM procedure for FDG-PET in dementia diagnosis in a clinical setting (Articolo in rivista) (literal)

Anno

2014-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

10.1016/j.nicl.2014.10.009 (literal)

Alternative label

Daniela Perani a,b,c,d 1, Pasquale Anthony Della Rosa d 1, Chiara Ceramia e 1, Francesca Gallivanone d, Federico Fallanca c, Emilia Giovanna Vanoli c, Andrea Panzacchi c, Flavio Nobili f, Sabina Pappatà g, Alessandra Marcone f, Valentina Garibotto h, Isabella Castiglioni d, Giuseppe Magnani i, Stefano F. Cappa e,j, Luigi Gianolli c, EADC-PET Consortium 2 (2014)
Validation of an optimized SPM procedure for FDG-PET in dementia diagnosis in a clinical setting
in NeuroImage: Clinical
(literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

Daniela Perani a,b,c,d 1, Pasquale Anthony Della Rosa d 1, Chiara Ceramia e 1, Francesca Gallivanone d, Federico Fallanca c, Emilia Giovanna Vanoli c, Andrea Panzacchi c, Flavio Nobili f, Sabina Pappatà g, Alessandra Marcone f, Valentina Garibotto h, Isabella Castiglioni d, Giuseppe Magnani i, Stefano F. Cappa e,j, Luigi Gianolli c, EADC-PET Consortium 2 (literal)

Pagina inizio

445 (literal)

Pagina fine

454 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

6 (literal)

Rivista

NeuroImage: Clinical (Rivista)

Note

PubMe (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

1. These authors contributed equally to the work. 2 Alexander Drzezga and Robert Perneczky [Munich], Mira Didic and Eric Guedj [Marseilles], Bart N. Van Berckel and Rik Ossenkoppele [Amsterdam], Silvia Morbelli [Genoa], Giovanni Frisoni and Anna Caroli [Brescia]. a. Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy b. Vita-Salute San Raffaele University, Milan, Italy c. Nuclear Medicine Unit, San Raffaele Hospital, Milan, Italy d. Istituto di Bioimmagini e Fisiologia Molecolare, CNR, Segrate, Italy e. Clinical Neurosciences Department, San Raffaele Hospital, Milan, Italy f. Dept of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy g. Institute of Biostructure and Bioimaging, CNR, Naples, Italy h. Department of Medical Imaging, Geneva University, Geneva, Switzerland i. Neurology Department, San Raffaele Hospital, Milan, Italy k. Istituto Universitario degli Studi Superiori, Pavia, Italy (literal)

Titolo

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

Abstract

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 new optimized SPM procedure. 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. SPM Maps 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, SPM Maps 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 (literal)

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