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])
ISSN1619-7070
EISSN1619-7089
卷号52期号:4页码:1566-1575
发表状态已发表
DOI10.1007/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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