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Radiomics analysis of contrast-enhanced CT for classification of hepatic focal lesions in colorectal cancer patients: its limitations compared to radiologists

  • Imaging Informatics and Artificial Intelligence
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objective

To evaluate diagnostic performance of a radiomics model for classifying hepatic cyst, hemangioma, and metastasis in patients with colorectal cancer (CRC) from portal-phase abdominopelvic CT images.

Methods

This retrospective study included 502 CRC patients who underwent contrast-enhanced CT and contrast-enhanced liver MRI between January 2005 and December 2010. Portal-phase CT images of training (n = 386) and validation (n = 116) cohorts were used to develop a radiomics model for differentiating three classes of liver lesions. Among multiple handcrafted features, the feature selection was performed using ReliefF method, and random forest classifiers were used to train the selected features. Diagnostic performance of the developed model was compared with that of four radiologists. A subgroup analysis was conducted based on lesion size.

Results

The radiomics model demonstrated significantly lower overall and hemangioma- and metastasis-specific polytomous discrimination index (PDI) (overall, 0.8037; hemangioma-specific, 0.6653; metastasis-specific, 0.8027) than the radiologists (overall, 0.9622–0.9680; hemangioma-specific, 0.9452–0.9630; metastasis-specific, 0.9511–0.9869). For subgroup analysis, the PDI of the radiomics model was different according to the lesion size (< 10 mm, 0.6486; ≥ 10 mm, 0.8264) while that of the radiologists was relatively maintained. For classifying metastasis from benign lesions, the radiomics model showed excellent diagnostic performance, with an accuracy of 84.36% and an AUC of 0.9426.

Conclusion

Albeit inferior to the radiologists, the radiomics model achieved substantial diagnostic performance when differentiating hepatic lesions from portal-phase CT images of CRC patients. This model was limited particularly to classifying hemangiomas and subcentimeter lesions.

Key Points

• Albeit inferior to the radiologists, the radiomics model could differentiate cyst, hemangioma, and metastasis with substantial diagnostic performance using portal-phase CT images of colorectal cancer patients.

• The radiomics model demonstrated limitations especially in classifying hemangiomas and subcentimeter liver lesions.

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Abbreviations

CCP:

Correct classification percentage

CRC:

Colorectal cancer

CRLM:

Colorectal liver metastasis

PDI:

Polytomous discrimination index

RF:

Random forest

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Funding

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science and ICT) (2017R1D1A1B03029631).

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Authors and Affiliations

  1. Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea

    Heejin Bae, Sungwon Kim, Kyunghwa Han, Hyungjin Rhee, Dong-kyu Kim, Hyuk Kwon & Joon Seok Lim

  2. School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea

    Hansang Lee

  3. Department of Software Convergence, College of Interdisciplinary Studies for Emerging Industries, Seoul Women’s University, Seoul, Republic of Korea

    Helen Hong

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  1. Heejin Bae
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Correspondence to Joon Seok Lim.

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The scientific guarantor of this publication is Dr. Joon Seok Lim.

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The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

Dr. Kyunghwa Han, one of the authors, kindly provided statistical advice for this manuscript.

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Bae, H., Lee, H., Kim, S. et al. Radiomics analysis of contrast-enhanced CT for classification of hepatic focal lesions in colorectal cancer patients: its limitations compared to radiologists. Eur Radiol 31, 8786–8796 (2021). https://doi.org/10.1007/s00330-021-07877-y

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  • DOI: https://doi.org/10.1007/s00330-021-07877-y

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