Combined 18F-FDG PET-CT markers in dementia with Lewy bodies

被引:0
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作者
Mattoli, Maria Vittoria [1 ,2 ]
Cocciolillo, Fabrizio [3 ]
Chiacchiaretta, Piero [4 ,5 ]
Dotta, Francesco [4 ]
Trevisi, Gianluca [1 ]
Carrarini, Claudia [6 ,7 ]
Thomas, Astrid [1 ]
Sensi, Stefano [1 ]
Pizzi, Andrea Delli [4 ]
Nicola, Angelo Domenico Di [2 ]
Crosta, Adolfo Di [8 ,9 ]
Mammarella, Nicola [8 ]
Padovani, Alessandro [10 ]
Pilotto, Andrea [10 ,11 ]
Moda, Fabio [12 ]
Tiraboschi, Pietro [12 ]
Martino, Gianluigi [13 ]
Bonanni, Laura [9 ,14 ]
机构
[1] Univ G Annunzio Chieti Pescara, Dept Neurosci Imaging & Clin Sci, Chieti, Italy
[2] Presidio Ospedaliero St Spirito, Nucl Med Unit, Pescara, Italy
[3] Fdn Policlin Univ Agostino Gemelli IRCCS, Dipartimento Diagnost Immagini Radioterapia Oncolo, UOC Med Nucleare, Rome, Italy
[4] Univ G Annunzio Chieti Pescara, Dept Innovat Technol Med & Dent, Chieti, Italy
[5] Univ G Annunzio Chieti Pescara, Ctr Adv Studies & Technol CAST, Adv Comp Core, Chieti, Italy
[6] Univ Cattolica Sacro Cuore, Dept Neurosci, Rome, Italy
[7] IRCCS San Raffaele, Rome, Italy
[8] Univ G Annunzio Chieti Pescara, Dept Psychol Sci Humanities & Terr, Chieti, Italy
[9] Univ G Annunzio Chieti Pescara, Dept Med & Aging Sci, Chieti, Italy
[10] Univ Brescia, Dept Clin & Expt Sci, Neurol Unit, Brescia, Italy
[11] FERB ONLUS S Isidoro Hosp, Parkinsons Dis Rehabil Ctr, Trescore Balneario, Bergamo, Italy
[12] Fdn IRCCS Ist Neurol Carlo Besta, Div Neurol 5 & Neuropathol, I-20133 Milan, Italy
[13] SS Annunziata Hosp, Dept Radiol Sci, Nucl Med Unite, Via Vestini 31, Chieti, Italy
[14] Univ G Annunzio Chieti Pescara, Dept Med & Aging Sci, Via Vestini 31, I-66100 Chieti, Italy
关键词
18F-FDG; artificial intelligence; biomarkers; dementia; Lewy body dementia; machine learning; PET-CT; radiomics; ALZHEIMERS-DISEASE; GLUCOSE-METABOLISM; F-18-FDG PET; FDG-PET; DIAGNOSIS; MANAGEMENT; SPECT;
D O I
10.1002/dad2.12515
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
INTRODUCTION18F-Fluoro-deoxyglucose-positron emission tomography (FDG-PET) is a supportive biomarker in dementia with Lewy bodies (DLB) diagnosis and its advanced analysis methods, including radiomics and machine learning (ML), were developed recently. The aim of this study was to evaluate the FDG-PET diagnostic performance in predicting a DLB versus Alzheimer's disease (AD) diagnosis.METHODSFDG-PET scans were visually and semi-quantitatively analyzed in 61 patients. Radiomics and ML analyses were performed, building five ML models: (1) clinical features; (2) visual and semi-quantitative PET features; (3) radiomic features; (4) all PET features; and (5) overall features.RESULTSAt follow-up, 34 patients had DLB and 27 had AD. At visual analysis, DLB PET signs were significantly more frequent in DLB, having the highest diagnostic accuracy (86.9%). At semi-quantitative analysis, the right precuneus, superior parietal, lateral occipital, and primary visual cortices showed significantly reduced uptake in DLB. The ML model 2 had the highest diagnostic accuracy (84.3%).DISCUSSIONFDG-PET is a valuable tool in DLB diagnosis, having visual and semi-quantitative analyses with the highest diagnostic accuracy at ML analyses.
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页数:12
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