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T1-weighted images-based radiomics for structural lesions evaluation in patients with suspected axial spondyloarthritis

  • Computed Tomography
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Abstract

Purpose

The aim of this study was to investigate the feasibility of radiomics based on T1-weighted images (T1WI) for assessing sacroiliac joint (SIJ) structural lesions in patients with suspected axial spondyloarthritis (axSpA).

Materials and methods

A total of 266 patients with clinical suspicion of axSpA between December 2016 and January 2022 were enrolled. Structural lesions were assessed on low-dose CT (ldCT) and MRI, respectively. Radiomic features, extracted from SIJ T1WI, were included to generate the radiomics model. The performance of the radiomics model was evaluated using receiver operating characteristic (ROC) curve. Furthermore, point-biserial correlation analysis was used to interpret the associations between the radiomic feature and structural lesions.

Results

Using ldCT as the reference standard, the radiomics model showed favorable performance for detecting positive global structural lesions in the training cohort (AUC, 0.82 [95% CI: 0.76, 0.88]) and validation cohort (AUC, 0.82 [95% CI: 0.72, 0.91]. Experienced MRI raters yielded predictive AUCs of 0.73 (95% CI: 0.67, 0.79), and 0.74 (95% CI: 0.66, 0.83) in the training and validation cohort, respectively. The seven radiomic features included in the radiomics model showed significant correlation with different kinds of structural lesions (P all < 0.05). Among them, Wavelet.LHL_firstorder_90Percentile showed the strongest association with fat lesion (r = 0.48, P < 0.05).

Conclusion

The radiomics analysis with T1WI could effectively detect SIJ structural lesions and achieved expert-level performance. Each radiomic feature was correlated with different structural lesions significantly, which might inform radiomic-based applications for axSpA intelligent diagnosis.

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Acknowledgements

We thank Mr Yunjun Yang and Mr Xiang Guo for assistance.

Funding

This work was supported by the Wenzhou Basic Research Project (Grant No. Y2020163) and National Natural Science Foundation of China (Grant No. 82201997).

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Author notes

  1. Lusi Ye and Shouliang Miao contributed equally to this work.

Authors and Affiliations

  1. Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325015, Zhejiang, China

    Mo Zheng, Qinqin Xiao & Shouliang Miao

  2. Department of Radiology, Longgang People’s Hospital, Wenzhou, 325802, Zhejiang, China

    Guanxia Zhu

  3. Department of Rheumatology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325015, Zhejiang, China

    Dan Chen & Lusi Ye

  4. Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China

    Tao Lei, Chenhao Ye & Chenqiang Pan

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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by SM, LY, GZ, DC, QX, TL, CY, CP and MZ. The first draft of the manuscript was written by MZ, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Shouliang Miao or Lusi Ye.

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The authors have no relevant financial or non-financial interests to disclose.

Ethical approval

This study was performed in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of the First Affiliated Hospital of Wenzhou Medical University (YS2020-239). The informed consent was waived due to the retrospective design.

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Zheng, M., Zhu, G., Chen, D. et al. T1-weighted images-based radiomics for structural lesions evaluation in patients with suspected axial spondyloarthritis. Radiol med 128, 1398–1406 (2023). https://doi.org/10.1007/s11547-023-01717-3

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