Longitudinal assessment of MRI-based radiomics feature changes in caudate and putamen over progression of parkinson’s disease

Abstract Background Parkinson’s disease (PD) is the second most common neurological disorder, characterized by both motor and non-motor symptoms. Recent studies have shown that the nigrostriatal pathway undergoes changes as Parkinson's progresses. Radiomics, a quantitative image analysis technique, has recently gained attention in clinical issue. This longitudinal study aimed to evaluate radiomics features extracted from the bilateral caudate and putamen during Parkinson’s progression. Methods Twenty PD and eighteen healthy control (HC) subjects with two-time-point MRI scans selected from Parkinson’s disease Progression Markers Initiative (PPMI) database, thirty-two features were extracted between the Parkinson's and healthy groups over two-year follow-up. Results Among these thirty-two features, eighteen significant radiomics features ( P < 0.05) between PD and HC groups showed meaningful alteration over two-year follow-up. The left caudate exhibited 12 significant features, surpassing the left/right putamen and right caudate, and its significance levels were also considerably higher [p-value = 0.001- 0.008]. Conclusion Several radiomics features in the caudate and putamen change significantly during Parkinson's progression, specifically in the left caudate. Our features that based on a quantification of the pattern of gray level or gray-level runs of voxels, reflecting gray scale heterogeneity/uniformity, offer diagnostic information beyond naked eyes detection and may reflect pathophysiology. Radiomics textural changes in left caudate may reflect pathophysiology, serving as a noninvasive biomarker for disease management.

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Publication Details

Journal
The Egyptian Journal of Radiology and Nuclear Medicine
Published
2025-08-11
DOI
https://doi.org/10.1186/s43055-025-01552-8
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
1.36
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article

Longitudinal assessment of MRI-based radiomics feature changes in caudate and putamen over progression of parkinson’s disease

Davood Khezerloo, Melika Rahimiyan, Amir Reza Jahanshahi, Mona Fazel Ghaziani et al.
1 citations
The Egyptian Journal of Radiology and Nuclear Medicine
Radiomics and Machine Learning in Medical Imaging
1.36
article

Longitudinal assessment of MRI-based radiomics feature changes in caudate and putamen over progression of parkinson’s disease

Davood Khezerloo, Melika Rahimiyan, Amir Reza Jahanshahi, Mona Fazel Ghaziani, Nesa Seify
article en
1 citations

Abstract

Abstract Background Parkinson’s disease (PD) is the second most common neurological disorder, characterized by both motor and non-motor symptoms. Recent studies have shown that the nigrostriatal pathway undergoes changes as Parkinson's progresses. Radiomics, a quantitative image analysis technique, has recently gained attention in clinical issue. This longitudinal study aimed to evaluate radiomics features extracted from the bilateral caudate and putamen during Parkinson’s progression. Methods Twenty PD and eighteen healthy control (HC) subjects with two-time-point MRI scans selected from Parkinson’s disease Progression Markers Initiative (PPMI) database, thirty-two features were extracted between the Parkinson's and healthy groups over two-year follow-up. Results Among these thirty-two features, eighteen significant radiomics features ( P < 0.05) between PD and HC groups showed meaningful alteration over two-year follow-up. The left caudate exhibited 12 significant features, surpassing the left/right putamen and right caudate, and its significance levels were also considerably higher [p-value = 0.001- 0.008]. Conclusion Several radiomics features in the caudate and putamen change significantly during Parkinson's progression, specifically in the left caudate. Our features that based on a quantification of the pattern of gray level or gray-level runs of voxels, reflecting gray scale heterogeneity/uniformity, offer diagnostic information beyond naked eyes detection and may reflect pathophysiology. Radiomics textural changes in left caudate may reflect pathophysiology, serving as a noninvasive biomarker for disease management.

The Egyptian Journal of Radiology and Nuclear MedicineVol. 56(1)
Tabriz University of Medical Sciences (IR)
Good health and well-being
Openalex Percentile: Top 17%
Radiomics and Machine Learning in Medical Imaging
1.36
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