作者
Kobra Etminani, Amira Soliman, Anette Davidsson, Jose R Chang, Begoña Martínez-Sanchis, Stefan Byttner, Valle Camacho, Matteo Bauckneht, Roxana Stegeran, Marcus Ressner, Marc Agudelo-Cifuentes, Andrea Chincarini, Matthias Brendel, Axel Rominger, Rose Bruffaerts, Rik Vandenberghe, Milica G Kramberger, Maja Trost, Nicolas Nicastro, Giovanni B Frisoni, Afina W Lemstra, Bart NM van Berckel, Andrea Pilotto, Alessandro Padovani, Silvia Morbelli, Dag Aarsland, Flavio Nobili, Valentina Garibotto, Miguel Ochoa-Figueroa
发表日期
2022/1/1
期刊
European journal of nuclear medicine and molecular imaging
页码范围
1-22
出版商
Springer Berlin Heidelberg
简介
Purpose
The purpose of this study is to develop and validate a 3D deep learning model that predicts the final clinical diagnosis of Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), mild cognitive impairment due to Alzheimer’s disease (MCI-AD), and cognitively normal (CN) using fluorine 18 fluorodeoxyglucose PET (18F-FDG PET) and compare model’s performance to that of multiple expert nuclear medicine physicians’ readers.
Materials and methods
Retrospective 18F-FDG PET scans for AD, MCI-AD, and CN were collected from Alzheimer’s disease neuroimaging initiative (556 patients from 2005 to 2020), and CN and DLB cases were from European DLB Consortium (201 patients from 2005 to 2018). The introduced 3D convolutional neural network was trained using 90% of the data and externally tested using 10% as well as comparison to human …
学术搜索中的文章
K Etminani, A Soliman, A Davidsson, JR Chang… - European journal of nuclear medicine and molecular …, 2022