Application value of MRI radiomics in differential diagnosis of osteoporotic and malignant neoplastic vertebral compression fractures

Background: To explore the radiomics features of osteoporotic and malignant neoplastic vertebral compression fractures (VCFs), and to analyze the application value of radiomics in differential diagnosis of osteoporotic and malignant neoplastic VCFs.Materials and Methods: Fifty-one patients with VCFs caused by malignant tumors and forty-nine patients with osteoporosis-induced VCFs treated in the Xiaoshan Hospital Affiliated to Hangzhou Normal University from January 2020 to June 2023 were retrospectively collected into a training set (70 cases) and a verification set (30 cases) according to a stratified random sampling design and a 7:3 ratio.The radiomics parameters of T2WI images of the diseased vertebral bodies were extracted, and the parameters with statistical differences were screened out by dimensionality reduction, so as to build a prediction model.Receiver operating characteristic (ROC) curves were drawn to evaluate the differential diagnosis performance of radiomics for the etiology of vertebral fractures.Results: Eight radiomics features were obtained after dimensionality reduction using the LASSO algorithm.The constructed model was effective in differentiating osteoporotic and malignant neoplastic VCFs, with an area under the ROC curve (AUC) of 0.95; while the AUC for the validation set was 0.84. Conclusions:The radiomics features of T2WI images of vertebral fractures have high efficiency in the differential diagnosis of fracture etiology.

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Publication Details

Journal
International Journal of Radiation Research
Published
2024-10-01
DOI
https://doi.org/10.61186/ijrr.22.4.927
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Application value of MRI radiomics in differential diagnosis of osteoporotic and malignant neoplastic vertebral compression fractures

H. Zhang, Min Zhan, Yi Qian, Ying Li et al.
International Journal of Radiation Research
Radiomics and Machine Learning in Medical Imaging
article

Application value of MRI radiomics in differential diagnosis of osteoporotic and malignant neoplastic vertebral compression fractures

H. Zhang, Min Zhan, Yi Qian, Ying Li, Han Zh, Zhi Gao, Ch. Xu
article en

Abstract

Background: To explore the radiomics features of osteoporotic and malignant neoplastic vertebral compression fractures (VCFs), and to analyze the application value of radiomics in differential diagnosis of osteoporotic and malignant neoplastic VCFs.Materials and Methods: Fifty-one patients with VCFs caused by malignant tumors and forty-nine patients with osteoporosis-induced VCFs treated in the Xiaoshan Hospital Affiliated to Hangzhou Normal University from January 2020 to June 2023 were retrospectively collected into a training set (70 cases) and a verification set (30 cases) according to a stratified random sampling design and a 7:3 ratio.The radiomics parameters of T2WI images of the diseased vertebral bodies were extracted, and the parameters with statistical differences were screened out by dimensionality reduction, so as to build a prediction model.Receiver operating characteristic (ROC) curves were drawn to evaluate the differential diagnosis performance of radiomics for the etiology of vertebral fractures.Results: Eight radiomics features were obtained after dimensionality reduction using the LASSO algorithm.The constructed model was effective in differentiating osteoporotic and malignant neoplastic VCFs, with an area under the ROC curve (AUC) of 0.95; while the AUC for the validation set was 0.84. Conclusions:The radiomics features of T2WI images of vertebral fractures have high efficiency in the differential diagnosis of fracture etiology.

International Journal of Radiation ResearchVol. 22(4)
Shanghai University of Traditional Chinese Medicine (CN), 117th Hospital of People's Liberation Army (CN), Affiliated Hospital of Hangzhou Normal University (CN), Zhejiang Hospital (CN), Traditional Chinese Medicine Hospital of Kunshan (CN), Hangzhou Hospital of Traditional Chinese Medicine (CN), Hangzhou Xixi hospital (CN), The First People's Hospital of Xiaoshan District, Hangzhou (CN)
Openalex Percentile: Top 58%
Radiomics and Machine Learning in Medical Imaging
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