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• Clinical Article •
Assessment of Parkinson's disease severity based on T2-weighted magnetic resonance imaging radiomic modeling
WEI Fuli  LIU Dan  LI Xinya  CAO Wanjun  PENG Yongming  WANG Fang 

Cite this article as: WEI F L, LIU D, LI X Y, et al. Assessment of Parkinson's disease severity based on T2-weighted magnetic resonance imaging radiomic modeling[J]. Chin J Magn Reson Imaging, 2024, 15(11): 12-16, 38. DOI:10.12015/issn.1674-8034.2024.11.003.


[Abstract] Objective To explore the value of assessing the severity of patients with Parkinson's disease (PD) based on the T2WI radiology model.Materials and Methods A total of 201 patients with a clinical diagnosis of PD were retrospectively collected, according to Hoehn-Yahr (H-Y) stage. They were divided into the early group (n=113) and middle-late group (n=88), into a training set of 140 cases and a test set of 61 cases using a 7∶3 ratio at the same time. We established by extracting and screening radiomics features from substantia nigra (SN), red nucleus (RN), caudate nucleus (CN), putamen (PUT), globus pallidus (GP), and used a logistic regression (LR) classifier to build the corresponding models separately. Clinical and imaging data were sequentially incorporated into univariate and multivariate logistic regression analysis to identify independent risk factors about PD severity. Receiver operating characteristic (ROC) curves were used to assess the efficacy of each model, and calibration curves were used to assess calibration accuracy.Results 19 optimal features on T2WI were selected from SN, and the AUC (0.817, 0.733) in the training and test set were higher than those of the RN model (0.758, 0.704), the CN model (0.712, 0.643), the PUT model (0.713, 0.708), and the GP model (0.705, 0.708). The white matter hyperintensities burden and the duration of PD were independent risk factors for diagnosing the severity of PD patients, and the AUC of the combined model with the SN model was 0.865(training set) and 0.836 (test set), but there is no significant difference in diagnostic performance between the two models. The calibration curve indicates good consistency between the diagnostic results of the six models and the actual outcomes.Conclusions SN signatures on T2WI achieved better performance in assessing the severity of PD patients. The assessed efficacy of the combined model established by the combined WMH burden and duration of PD was further improved and provide imaging guidance for timely clinical intervention and treatment.
[Keywords] Parkinson's disease；magnetic resonance imaging；T2-weighted magnetic resonance imaging；radiomics；white matter hyperintensities

WEI Fuli1   LIU Dan1*   LI Xinya1   CAO Wanjun1   PENG Yongming1   WANG Fang2  

1 Department of Radiology, Yongchuan Hospital of Chongqing Medical University, Chongqing402160, China

2 Shanghai United Imaging Intelligence Co., Ltd, Shanghai200232, China

Corresponding author: LIU D, E-mail: 5677676@qq.com

Conflicts of interest   None.

Received  2024-07-01
Accepted  2024-10-15
DOI: 10.12015/issn.1674-8034.2024.11.003
Cite this article as: WEI F L, LIU D, LI X Y, et al. Assessment of Parkinson's disease severity based on T2-weighted magnetic resonance imaging radiomic modeling[J]. Chin J Magn Reson Imaging, 2024, 15(11): 12-16, 38. DOI:10.12015/issn.1674-8034.2024.11.003.

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