Radiomics Features of the Hippocampus Based on 3D-TIWI Improve the Diagnosis of Cerebral Small Vessel Disease with Cognitive Impairment

Motivation: Tracking hippocampal radiomic changes over time may provide a biomarker to monitor disease progression and treatment response in cerebral small vessel disease (CSVD). Extending proven hippocampal radiomic methods from AD research to the study of CSVD represents a promising approach worthy of further investigation. Goal(s): To develop a radiomics model based on 3D-T1WI images to improve the diagnosis of CSVD with cognitive impairment. Approach: LASSO regression was used for feature selection and model constructionResults: The model attained an accuracy of 0.781, AUC of 0.818, sensitivity of 0.538, and specificity of 0.947 in distinguishing group 2 from NCs in the test sets. Impact: Overall, our findings support the potential for hippocampal textural features to serve as neuroimaging biomarkers of CSVD, providing a useful tool to aid clinical decision-making in precision medicine.

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Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/2490
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Radiomics Features of the Hippocampus Based on 3D-TIWI Improve the Diagnosis of Cerebral Small Vessel Disease with Cognitive Impairment

X. P. Qin, Ronghua Mu, Peng Yang, Kan Deng et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Radiomics and Machine Learning in Medical Imaging
article

Radiomics Features of the Hippocampus Based on 3D-TIWI Improve the Diagnosis of Cerebral Small Vessel Disease with Cognitive Impairment

X. P. Qin, Ronghua Mu, Peng Yang, Kan Deng, J. Kuang, Wei Zheng, Xiongzhao Zhu, Y. L. Xiao, Bingqin Huang, Yuling Feng
article en

Abstract

Motivation: Tracking hippocampal radiomic changes over time may provide a biomarker to monitor disease progression and treatment response in cerebral small vessel disease (CSVD). Extending proven hippocampal radiomic methods from AD research to the study of CSVD represents a promising approach worthy of further investigation. Goal(s): To develop a radiomics model based on 3D-T1WI images to improve the diagnosis of CSVD with cognitive impairment. Approach: LASSO regression was used for feature selection and model constructionResults: The model attained an accuracy of 0.781, AUC of 0.818, sensitivity of 0.538, and specificity of 0.947 in distinguishing group 2 from NCs in the test sets. Impact: Overall, our findings support the potential for hippocampal textural features to serve as neuroimaging biomarkers of CSVD, providing a useful tool to aid clinical decision-making in precision medicine.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
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Openalex Percentile: Top 64%
Radiomics and Machine Learning in Medical Imaging
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Radiomics Features of the Hippocampus Based on 3D-TIWI Improve the Diagnosis of Cerebral Small Vessel Disease with Cognitive Impairment — X. P. Qin, Ronghua Mu, et al. · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2024) | TGRS Research Map | TGRS