Combined 18F-FDG PET-CT markers in dementia with Lewy bodies
© 2023 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals LLC on behalf of Alzheimer's Association..
INTRODUCTION: 18F-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.
METHODS: FDG-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.
RESULTS: At 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%).
DISCUSSION: FDG-PET is a valuable tool in DLB diagnosis, having visual and semi-quantitative analyses with the highest diagnostic accuracy at ML analyses.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2023 |
|---|---|
| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:15 |
|---|---|
| Enthalten in: |
Alzheimer's & dementia (Amsterdam, Netherlands) - 15(2023), 4 vom: 20. Okt., Seite e12515 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Mattoli, Maria Vittoria [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
18F‐FDG |
|---|
| Anmerkungen: |
Date Revised 25.12.2023 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
|---|
| doi: |
10.1002/dad2.12515 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM366358545 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM366358545 | ||
| 003 | DE-627 | ||
| 005 | 20231227141238.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231227s2023 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1002/dad2.12515 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1238.xml |
| 035 | |a (DE-627)NLM366358545 | ||
| 035 | |a (NLM)38145190 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Mattoli, Maria Vittoria |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Combined 18F-FDG PET-CT markers in dementia with Lewy bodies |
| 264 | 1 | |c 2023 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Revised 25.12.2023 | ||
| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a © 2023 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals LLC on behalf of Alzheimer's Association. | ||
| 520 | |a INTRODUCTION: 18F-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 | ||
| 520 | |a METHODS: FDG-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 | ||
| 520 | |a RESULTS: At 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%) | ||
| 520 | |a DISCUSSION: FDG-PET is a valuable tool in DLB diagnosis, having visual and semi-quantitative analyses with the highest diagnostic accuracy at ML analyses | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a 18F‐FDG | |
| 650 | 4 | |a Lewy body dementia | |
| 650 | 4 | |a PET‐CT | |
| 650 | 4 | |a artificial intelligence | |
| 650 | 4 | |a biomarkers | |
| 650 | 4 | |a dementia | |
| 650 | 4 | |a machine learning | |
| 650 | 4 | |a radiomics | |
| 700 | 1 | |a Cocciolillo, Fabrizio |e verfasserin |4 aut | |
| 700 | 1 | |a Chiacchiaretta, Piero |e verfasserin |4 aut | |
| 700 | 1 | |a Dotta, Francesco |e verfasserin |4 aut | |
| 700 | 1 | |a Trevisi, Gianluca |e verfasserin |4 aut | |
| 700 | 1 | |a Carrarini, Claudia |e verfasserin |4 aut | |
| 700 | 1 | |a Thomas, Astrid |e verfasserin |4 aut | |
| 700 | 1 | |a Sensi, Stefano |e verfasserin |4 aut | |
| 700 | 1 | |a Pizzi, Andrea Delli |e verfasserin |4 aut | |
| 700 | 1 | |a Nicola, Angelo Domenico Di |e verfasserin |4 aut | |
| 700 | 1 | |a Crosta, Adolfo Di |e verfasserin |4 aut | |
| 700 | 1 | |a Mammarella, Nicola |e verfasserin |4 aut | |
| 700 | 1 | |a Padovani, Alessandro |e verfasserin |4 aut | |
| 700 | 1 | |a Pilotto, Andrea |e verfasserin |4 aut | |
| 700 | 1 | |a Moda, Fabio |e verfasserin |4 aut | |
| 700 | 1 | |a Tiraboschi, Pietro |e verfasserin |4 aut | |
| 700 | 1 | |a Martino, Gianluigi |e verfasserin |4 aut | |
| 700 | 1 | |a Bonanni, Laura |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Alzheimer's & dementia (Amsterdam, Netherlands) |d 2015 |g 15(2023), 4 vom: 20. Okt., Seite e12515 |w (DE-627)NLM248022180 |x 2352-8729 |7 nnns |
| 773 | 1 | 8 | |g volume:15 |g year:2023 |g number:4 |g day:20 |g month:10 |g pages:e12515 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1002/dad2.12515 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 15 |j 2023 |e 4 |b 20 |c 10 |h e12515 | ||