Abstract |
The aim of the present study was to predict amyloid-beta positivity using a conventional T1-weighted image, radiomics, and a diffusion-tensor image obtained by magnetic resonance imaging (MRI). We included 186 patients with mild cognitive impairment (MCI) who underwent Florbetaben positron emission tomography (PET), MRI (three-dimensional T1-weighted and diffusion-tensor images), and neuropsychological tests at the Asan Medical Center. We developed a stepwise machine learning algorithm using demographics, T1 MRI features (volume, cortical thickness and radiomics), and diffusion-tensor image to distinguish amyloid-beta positivity on Florbetaben PET. We compared the performance of each algorithm based on the MRI features used. The study population included 72 patients with MCI in the amyloid-beta-negative group and 114 patients with MCI in the amyloid-beta-positive group. The machine learning algorithm using T1 volume performed better than that using only clinical information (mean area under the curve [AUC]: 0.73 vs. 0.69, p < 0.001). The machine learning algorithm using T1 volume showed better performance than that using cortical thickness (mean AUC: 0.73 vs. 0.68, p < 0.001) or texture (mean AUC: 0.73 vs. 0.71, p = 0.002). The performance of the machine learning algorithm using fractional anisotropy in addition to T1 volume was not better than that using T1 volume alone (mean AUC: 0.73 vs. 0.73, p = 0.60). Among MRI features, T1 volume was the best predictor of amyloid PET positivity. Radiomics or diffusion-tensor images did not provide additional benefits.
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Authors | Sungyang Jo, Hyunna Lee, Hyung-Ji Kim, Chong Hyun Suh, Sang Joon Kim, Yoojin Lee, Jee Hoon Roh, Jae-Hong Lee |
Journal | Scientific reports
(Sci Rep)
Vol. 13
Issue 1
Pg. 9755
(06 16 2023)
ISSN: 2045-2322 [Electronic] England |
PMID | 37328578
(Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
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Copyright | © 2023. The Author(s). |
Chemical References |
- 4-(N-methylamino)-4'-(2-(2-(2-fluoroethoxy)ethoxy)ethoxy)stilbene
- Aniline Compounds
- Stilbenes
- Amyloid beta-Peptides
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Topics |
- Humans
- Tomography, X-Ray Computed
- Brain
(diagnostic imaging, metabolism)
- Aniline Compounds
- Stilbenes
- Magnetic Resonance Imaging
- Amyloid beta-Peptides
(metabolism)
- Retrospective Studies
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