Characteristics of brain glucose metabolism in Parkinson’s disease patients with freezing of gait: a study based on 18F-FDG PET imaging and deep learning
Specific glucose metabolism patterns in PD-FOG mainly covered the frontoparietal network (FPN). The integration of <sup>18</sup>F-FDG PET imaging with deep learning methods effectively differentiated patients with FOG. The 3D CNN exhibited a high diagnosis accuracy level, providing reliable imaging and artificial intelligence support for PD with FOG.
Authors
- Qi Zhu (ORCID: https://orcid.org/0000-0001-8393-9360)
- Caiting Gan (ORCID: https://orcid.org/0000-0003-1024-4722)
- Kezhong Zhang (ORCID: https://orcid.org/0000-0002-4437-1095)
- Jiaxin Shi (ORCID: https://orcid.org/0000-0001-6842-4211)
- Linghui Liu
- Xixi Wang (ORCID: https://orcid.org/0000-0003-1213-1430)
- Yao Geng
- Shengrong Li (ORCID: https://orcid.org/0000-0001-9061-3481)
- Zhuang Zhu
- Yongsheng Yuan (ORCID: https://orcid.org/0009-0005-0820-7887)
- Hualin Wang
Institutions
- Nanjing Medical University (CN)
- Nanjing University of Aeronautics and Astronautics (CN)
Publication Details
- Journal
- BMC Neurology
- Published
- 2025-10-31
- DOI
- https://doi.org/10.1186/s12883-025-04468-y
- Primary Topic
- Parkinson's Disease Mechanisms and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China