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Cross-modality PET image synthesis for Parkinson's Disease diagnosis: a leap from [18F]FDG to [11C]CFT | |
2025 | |
发表期刊 | EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING (IF:8.6[JCR-2023],8.2[5-Year]) |
ISSN | 1619-7070 |
EISSN | 1619-7089 |
卷号 | 52期号:4页码:1566-1575 |
发表状态 | 已发表 |
DOI | 10.1007/s00259-025-07096-3 |
摘要 | Purpose Dopamine transporter [C-11]CFT PET is highly effective for diagnosing Parkinson's Disease (PD), whereas it is not widely available in most hospitals. To develop a deep learning framework to synthesize [C-11]CFT PET images from real [F-18]FDG PET images and leverage their cross-modal correlation to distinguish PD from normal control (NC). Methods We developed a deep learning framework to synthesize [C-11]CFT PET images from real [F-18]FDG PET images, and leveraged their cross-modal correlation to distinguish PD from NC. A total of 604 participants (274 with PD and 330 with NC) who underwent [C-11]CFT and [F-18]FDG PET scans were included. The quality of the synthetic [C-11]CFT PET images was evaluated through quantitative comparison with the ground-truth images and radiologist visual assessment. The evaluations of PD diagnosis performance were conducted using biomarker-based quantitative analyses (using striatal binding ratios from synthetic [C-11]CFT PET images) and the proposed PD classifier (incorporating both real [F-18]FDG and synthetic [C-11]CFT PET images). Results Visualization result shows that the synthetic [C-11]CFT PET images resemble the real ones with no significant differences visible in the error maps. Quantitative evaluation demonstrated that synthetic [C-11]CFT PET images exhibited a high peak signal-to-noise ratio (PSNR: 25.0-28.0) and structural similarity (SSIM: 0.87-0.96) across different unilateral striatal subregions. The radiologists achieved a diagnostic accuracy of 91.9% (+/- 2.02%) based on synthetic [C-11]CFT PET images, while biomarker-based quantitative analysis of the posterior putamen yielded an AUC of 0.912 (95% CI, 0.889-0.936), and the proposed PD Classifier achieved an AUC of 0.937 (95% CI, 0.916-0.957). Conclusion By bridging the gap between [F-18]FDG and [C-11]CFT, our deep learning framework can significantly enhance PD diagnosis without the need for [C-11]CFT tracers, thereby expanding the reach of advanced diagnostic tools to clinical settings where [C-11]CFT PET imaging is inaccessible. |
关键词 | Parkinson's disease Diagnosis [F-18]FDG PET [C-11]CFT PET Cross-modality image synthesis |
URL | 查看原文 |
收录类别 | SCI ; EI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[ |
WOS研究方向 | Radiology, Nuclear Medicine & Medical Imaging |
WOS类目 | Radiology, Nuclear Medicine & Medical Imaging |
WOS记录号 | WOS:001399938000001 |
出版者 | SPRINGER |
EI入藏号 | 20250717852999 |
EI主题词 | Neurodegenerative diseases |
EI分类号 | 102.1.2 Health Science ; 1106.3.1 Image Processing |
原始文献类型 | Article in Press |
文献类型 | 期刊论文 |
条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/483891 |
专题 | 生物医学工程学院 信息科学与技术学院_博士生 生物医学工程学院_PI研究组_王乾组 生物医学工程学院_硕士生 生物医学工程学院_PI研究组_孙开聪组 |
通讯作者 | Wang, Qian; Zuo, Chuantao |
作者单位 | 1.Fudan Univ, PET Ctr, Dept Nucl Med, Huashan Hosp, Shanghai 200235, Peoples R China 2.Shanghai Jiao Tong Univ, Sch Biomed Engn, Shanghai, Peoples R China 3.ShanghaiTech Univ, Sch Biomed Engn, Shanghai, Peoples R China 4.ShanghaiTech Univ, State Key Lab Adv Med Mat & Devices, Shanghai, Peoples R China 5.Shanghai Clin Res & Trial Ctr, Shanghai, Peoples R China 6.Fudan Univ, Huashan Hosp, Dept Neurol, Shanghai, Peoples R China 7.Fudan Univ, Human Phenome Inst, Shanghai, Peoples R China 8.Fudan Univ, Huashan Hosp, Natl Ctr Neurol Disorders, Natl Clin Res Ctr Aging & Med, Shanghai, Peoples R China |
通讯作者单位 | 生物医学工程学院; 上海科技大学 |
推荐引用方式 GB/T 7714 | Shen, Zhenrong,Wang, Jing,Huang, Haolin,et al. Cross-modality PET image synthesis for Parkinson's Disease diagnosis: a leap from [18F]FDG to [11C]CFT[J]. EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING,2025,52(4):1566-1575. |
APA | Shen, Zhenrong.,Wang, Jing.,Huang, Haolin.,Lu, Jiaying.,Ge, Jingjie.,...&Zuo, Chuantao.(2025).Cross-modality PET image synthesis for Parkinson's Disease diagnosis: a leap from [18F]FDG to [11C]CFT.EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING,52(4),1566-1575. |
MLA | Shen, Zhenrong,et al."Cross-modality PET image synthesis for Parkinson's Disease diagnosis: a leap from [18F]FDG to [11C]CFT".EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING 52.4(2025):1566-1575. |
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