Abstract
Age and gender are the important factors for brain metabolic declines in both normal aging and neurodegeneration, and the confounding effects may influence early and differential diagnosis of neurodegenerative diseases based on the [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG PET). We aimed to explore the potential of the adjustment of age- and gender-related confounding factors on [18F]FDG PET images in differentiation of Parkinson’s disease (PD), multiple system atrophy (MSA) and progressive supra-nuclear palsy (PSP). Eight hundred and seventy-seven clinically definitely diagnosed Parkinsonian patients from a benchmark Huashan Parkinsonian PET imaging database were included. An age- and gender-adjusted Z (AGAZ) score was established based on the gender-specific longitudinal metabolic changes on healthy subjects. AGAZ scores and standardized uptake value ratio (SUVR) values were quantified at regional-level and support vector machine-based error-correcting output codes method was applied for classification. Additional references of the classifications based on metabolic pattern scores were included. The feature-based AGAZ score showed the best performance in classification (accuracy for PD, MSA, PSP: 93.1%, 96.3%, 94.8%). In both genders, the AGAZ score consistently achieved the best efficiency, and the improvements compared to the conventional SUVR value for PD, MSA, and PSP mainly laid in specificity (Male: 5.7%; Female: 11.1%), sensitivity (Male: 7.2%; Female: 7.3%), and sensitivity (Male: 7.3%; Female: 17.2%). Female patients benefited more from the adjustment on [18F]FDG PET in MSA and PSP groups (absolute net reclassification index, p < 0.001). Collectively, the adjustment of age- and gender-related confounding factors may improve the differential diagnosis of Parkinsonism. Particularly, the diagnosis of female Parkinsonian population has the best improvement from this correction.
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Acknowledgements
The authors thank the patients and family members who participated in the research.
Funding
This work was supported by National Natural Science Foundation of China (81671239, 81361120393, 82171252, 81701250, 81401135, 81971641, 91949118, 81771372, 82021002), the Ministry of Science and Technology of China (2016YFC1306504), Shanghai Municipal Science and Technology Major Project (2017SHZDZX01, 2018SHZDZX03) and ZJ Lab, Shanghai Aging and Maternal and Child Health Research Special Project (2020YJZX0111), Clinical Research Plan of Shanghai Hospital Development Center (SHDC2020CR1038B), Science and Technology Innovation 2030 Major Projects (2022ZD0211600), Youth Medical Talents—Medical Imaging Practitioner Program by Shanghai Municipal Health Commission and Shanghai Medical and Health Development Foundation (SHWRS(2020)_087), the Swiss National Science Foundation (188350), and Jacques & Gloria Gossweiler Foundation and Siemens Healthineers.
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CZ, FL, and KS conceived and designed the clinical study; MW and KS conceived and developed the algorithms. MW conducted the computational experiments. JL, PW, and HZ collected the imaging data and inspected images together with IY, SZ, JJ, SF, MS, AR, and SCH. JW, FL, JL, and PW collected clinical data and defined the standards of subject inclusion and evaluations. MW, JL, and KS contributed to the analysis of the data. JL, MW, KS, CZ, and FL wrote the manuscript with the advice, input and proof of other co-authors.
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Axel Rominger and Kuangyu Shi received research support from Novartis and Siemens Healthineers. Other authors report no commercial interests or potential conflicts of interest.
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This study obtained ethics permission from the Institutional Review Board of Huashan Hospital. All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional and/or national research committee, and the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
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Lu, J., Wang, M., Wu, P. et al. Adjustment for the Age- and Gender-Related Metabolic Changes Improves the Differential Diagnosis of Parkinsonism. Phenomics 3, 50–63 (2023). https://doi.org/10.1007/s43657-022-00079-6
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DOI: https://doi.org/10.1007/s43657-022-00079-6