Predicting mild cognitive impairment in patients with Parkinson’s disease by integrating striatal MRI radiomics with clinical features

Topic: Risk, prevention and care in population studies

Age and years of education (YOE) were identified as independent clinical risk factors for PD-MCI. The clinical-radiomics combined model outperformed the radiomics-only model in both the training and test sets, with the model incorporating the right PU (PUR) radiomics features achieving the highest AUC: 0.852 (95% CI: 0.787-0.918) in the training set and 0.790 (95% CI: 0.657-0.923) in the test set. The corresponding F1 scores were 0.704 and 0.667, respectively. Additionally, specific radiomics features showed weak but significant correlations with MoCA scores (P < 0.05). Integration of striatal radiomics features derived from structural MRI images with routine clinical factors demonstrates promising predictive performance for PD-MCI. The proposed clinical-radiomics combined model leverages clinically accessible resources, and its predictive value for PD-MCI establishes a preliminary foundation for subsequent related explorations. However, the model's generalizability remains unconfirmed, further validation on independent datasets is required before any consideration of its clinical application.

@article{chen2025-41239229,
  author  = {Chen, Haisong and Debora, Asta and Wang, Hongyan and Xu, Jian and Zhao, Xuemiao and Wang, Jingru and Yang, Yunjun and Yu, Mengying},
  title   = {{Predicting mild cognitive impairment in patients with Parkinson’s disease by integrating striatal MRI radiomics with clinical features}},
  journal = {BMC Medical Imaging},
  year    = {2025},
  doi     = {10.1186/s12880-025-02014-3},
  pmid    = {41239229},
  url     = {https://doi.org/10.1186/s12880-025-02014-3}
}

Key findings

• Age and years of education (YOE) were identified as independent clinical risk factors for PD-MCI.
• The clinical-radiomics combined model outperformed the radiomics-only model in both the training and test sets, with the model incorporating the right PU (PUR) radiomics features achieving the highest AUC: 0.852 (95% CI: 0.787-0.918) in the training set and 0.790 (95% CI: 0.657-0.923) in the test set.
• The corresponding F1 scores were 0.704 and 0.667, respectively.
• Additionally, specific radiomics features showed weak but significant correlations with MoCA scores (P < 0.05).
• Integration of striatal radiomics features derived from structural MRI images with routine clinical factors demonstrates promising predictive performance for PD-MCI.

Why it matters

This study combined striatal MRI radiomics features with clinical factors to predict mild cognitive impairment in Parkinson's disease, with the best model reaching an AUC of 0.852 in training and 0.790 in testing. The authors state the model's generalizability is unconfirmed and further validation is required before any consideration of clinical application.

Study details

• Participants1,316
• Effect sizeAUC: 0.852 (95% CI: 0.787-0.918)
• Evidence strengthLow

Read the original

• DOI: 10.1186/s12880-025-02014-3
• PubMed: 41239229
• Original source →
• Free full text: BMC Medical Imaging →

Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).

Studies this one cites

Referenced by this study and also in the alzhub library, so you can read them here.

• Education and Cognitive Functioning Across the Life Span Psychological science in the public interest : a journal of the American Psychological Society · 2020-08-01 · usefulness score 72/100 · How common it is
• The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment Journal of the American Geriatrics Society · 2005-04-01 · usefulness score 60/100 · Getting a diagnosis
• Parkinson disease-associated cognitive impairment Nature reviews. Disease primers · 2021-07-01 · usefulness score 59/100 · How common it is
• Biomarkers for dementia and mild cognitive impairment in Parkinson's disease Movement disorders : official journal of the Movement Disorder Society · 2016-05-19 · usefulness score 53/100 · Mild cognitive impairment

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