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Diagnostic performance of artificial intelligence-assisted PET imaging for Parkinson's disease: a systematic review and meta-analysis.
Wang, Jing; Xue, Le; Jiang, Jiehui; Liu, Fengtao; Wu, Ping; Lu, Jiaying; Zhang, Huiwei; Bao, Weiqi; Xu, Qian; Ju, Zizhao; Chen, Li; Jiao, Fangyang; Lin, Huamei; Ge, Jingjie; Zuo, Chuantao; Tian, Mei.
Afiliación
  • Wang J; Huashan Hospital & Human Phenome Institute, Fudan University, Shanghai, China.
  • Xue L; Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China.
  • Jiang J; Department of Nuclear Medicine, the Second Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Liu F; Institute of Biomedical Engineering, School of Life Science, Shanghai University, Shanghai, China.
  • Wu P; Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China.
  • Lu J; National Clinical Research Center for Aging and Medicine, & National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
  • Zhang H; Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China.
  • Bao W; Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China.
  • Xu Q; Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China.
  • Ju Z; Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China.
  • Chen L; Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China.
  • Jiao F; Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China.
  • Lin H; Department of Ultrasound Medicine, Huashan Hospital, Fudan University, Shanghai, China.
  • Ge J; Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China.
  • Zuo C; Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China.
  • Tian M; Department of Nuclear Medicine/PET Center, Huashan Hospital, Fudan University, Shanghai, China. lovejingjie@126.com.
NPJ Digit Med ; 7(1): 17, 2024 Jan 22.
Article en En | MEDLINE | ID: mdl-38253738
ABSTRACT
Artificial intelligence (AI)-assisted PET imaging is emerging as a promising tool for the diagnosis of Parkinson's disease (PD). We aim to systematically review the diagnostic accuracy of AI-assisted PET in detecting PD. The Ovid MEDLINE, Ovid Embase, Web of Science, and IEEE Xplore databases were systematically searched for related studies that developed an AI algorithm in PET imaging for diagnostic performance from PD and were published by August 17, 2023. Binary diagnostic accuracy data were extracted for meta-analysis to derive outcomes of interest area under the curve (AUC). 23 eligible studies provided sufficient data to construct contingency tables that allowed the calculation of diagnostic accuracy. Specifically, 11 studies were identified that distinguished PD from normal control, with a pooled AUC of 0.96 (95% CI 0.94-0.97) for presynaptic dopamine (DA) and 0.90 (95% CI 0.87-0.93) for glucose metabolism (18F-FDG). 13 studies were identified that distinguished PD from the atypical parkinsonism (AP), with a pooled AUC of 0.93 (95% CI 0.91 - 0.95) for presynaptic DA, 0.79 (95% CI 0.75-0.82) for postsynaptic DA, and 0.97 (95% CI 0.96-0.99) for 18F-FDG. Acceptable diagnostic performance of PD with AI algorithms-assisted PET imaging was highlighted across the subgroups. More rigorous reporting standards that take into account the unique challenges of AI research could improve future studies.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies / Systematic_reviews Idioma: En Revista: NPJ Digit Med Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies / Systematic_reviews Idioma: En Revista: NPJ Digit Med Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido