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Original Investigation|Articles in Press

CTE-Based Radiomics Models Can Identify Mucosal Healing in Patients with Crohn's Disease

  • Author Footnotes
    1 These two authors contributed equally to this work.
    Chang Rong
    Footnotes
    1 These two authors contributed equally to this work.
    Affiliations
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, People's Republic of China (C.R., C.Z., L.H., Y.G., C.L., X.W.)
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  • Author Footnotes
    1 These two authors contributed equally to this work.
    Chao Zhu
    Footnotes
    1 These two authors contributed equally to this work.
    Affiliations
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, People's Republic of China (C.R., C.Z., L.H., Y.G., C.L., X.W.)
    Search for articles by this author
  • Li He
    Affiliations
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, People's Republic of China (C.R., C.Z., L.H., Y.G., C.L., X.W.)

    Department of Radiology, The Lu'an People's Hospital, Lu'an, Anhui 237000, People's Republic of China (L.H.)
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  • Jing Hu
    Affiliations
    Department of Gastroenterology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, People's Republic of China (J.H.)
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  • Yankun Gao
    Affiliations
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, People's Republic of China (C.R., C.Z., L.H., Y.G., C.L., X.W.)
    Search for articles by this author
  • Cuiping Li
    Affiliations
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, People's Republic of China (C.R., C.Z., L.H., Y.G., C.L., X.W.)
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  • Baoxin Qian
    Affiliations
    Huiying Medical Technology, Beijing City 100192, People's Republic of China (B.Q.)
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  • Jianying Li
    Affiliations
    CT Research Center, GE Healthcare China, Shanghai 210000, People's Republic of China (J.L.)
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  • Xingwang Wu
    Correspondence
    Address correspondence to: X.W., Department of Radiology, The First Affiliated Hospital of Anhui Medical University, No. 218 Jixi Road, Shushan District, Hefei, Anhui Province 230022, People's Republic of China.
    Affiliations
    Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, People's Republic of China (C.R., C.Z., L.H., Y.G., C.L., X.W.)
    Search for articles by this author
  • Author Footnotes
    1 These two authors contributed equally to this work.

      Rationale and Objectives

      To develop computed tomography enterography (CTE)-based radiomics models to assess mucosal healing (MH) in patients with Crohn's disease (CD).

      Materials and Methods

      CTE images were retrospectively collected from 92 confirmed cases of CD at the post-treatment review. Patients were randomly divided into developing (n = 73) and testing (n = 19) groups. Radiomics features were extracted from the enteric phase images, and the least absolute shrinkage and selection operator (LASSO) logistic regression was applied for feature selection using 5-fold cross-validation on the developing group. The selected features were further identified from the top-ranked features and used to create improved radiomics models. Machine learning models were constructed to compare radiomics models with different radiomics features. The area under the ROC curve (AUC) was calculated to assess the predictive performance for identifying MH in CD.

      Results

      Among the 92 CD patients included in our study, 36 patients achieved MH. The AUC of the radiomics model 1, which was based on the 26 selected radiomics features, was 0.976 for evaluating MH in the testing cohort. The AUCs of radiomics models 2 and 4, based on the top 10 and top 5 positive and negative radiomics features, were 0.974 and 0.952 in the testing cohort, respectively. The AUC of the radiomics model 3, built by removing features with r > 0.5, was 0.956 in the testing cohort. The clinical utility of the clinical radiomics nomogram was confirmed by the decision curve analysis (DCA).

      Conclusion

      The CTE-based radiomics models have demonstrated favorable performance in assessing MH in patients with CD. Radiomics features can be used as a promising imaging biomarker for MH.

      Abbreviations:

      AUC (area under the ROC curve), CD (Crohn's disease), CTE (computed tomography enterography), CRP (C-reactive protein), DCA; (decision curve analysis), HBI (Harvey Bradshaw Index), IFX (infliximab), LASSO (least absolute shrinkage and selection operator), MH (mucosal healing), ROI (regions of interest), ROC (receiver operator characteristic), WBC (white blood cell)

      Key Words

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