Dataset Information

MRI radiomics-based evaluation of tuberculous and brucella spondylitis.

ABSTRACT:

Objectives

We analyzed magnetic resonance imaging (MRI) and radiomics labels from tuberculous spondylitis (TBS) and brucella spondylitis (BS) to build machine learning models that differentiate TBS from BS and culture-positive TBS (TBS(+)) from culture-negative TBS (TBS(-).

Methods

This retrospective study included 56 patients with BS, 63 patients with TBS(+) and 71 patients with TBS(-). Radiomics labels were extracted from T2-weighted fat-suppression images. MRI labels were analyzed via logistic regression (LR); radiomics labels were analyzed by t-tests, SelectKBest, and least absolute shrinkage and selection operator (LASSO). Random forest (RF) and support vector machine (SVM) models were established using radiomics or joint (radiomics+MRI) labels. Models were evaluated by receiver operating characteristic curves, areas under the curve (AUCs), decision curve analysis (DCA), and Hosmer-Lemeshow tests.

Results

When joint-label models were used to compare BS vs TBS(+) and BS vs TBS(-) groups, SVM AUCs were 0.904 and 0.944, respectively, whereas RF AUCs were 0.950 and 0.947, respectively; these were higher than the AUCs of the MRI label-based LR model. DCA showed that radiomics-based machine learning models had a greater net benefit; Hosmer-Lemeshow tests demonstrated good prediction consistency for all models.

Conclusions

Radiomics can help distinguish TBS from BS and TBS(+) from TBS(-).

SUBMITTER: Wang W

PROVIDER: S-EPMC10478567 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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Publications

MRI radiomics-based evaluation of tuberculous and brucella spondylitis.

Wang Wenhui W Fan Zhichang Z Zhen Junping J

The Journal of international medical research 20230801 8

<h4>Objectives</h4>We analyzed magnetic resonance imaging (MRI) and radiomics labels from tuberculous spondylitis (TBS) and brucella spondylitis (BS) to build machine learning models that differentiate TBS from BS and culture-positive TBS (TBS(+)) from culture-negative TBS (TBS(-).<h4>Methods</h4>This retrospective study included 56 patients with BS, 63 patients with TBS(+) and 71 patients with TBS(-). Radiomics labels were extracted from T2-weighted fat-suppression images. MRI labels were analy ...[more]

PMID: 37656968

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Dataset Information

MRI radiomics-based evaluation of tuberculous and brucella spondylitis.

Objectives

Methods

Results

Conclusions

Publications

MRI radiomics-based evaluation of tuberculous and brucella spondylitis.

Similar Datasets

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