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Differentiating renal epithelioid angiomyolipoma from clear cell carcinoma: using a radiomics model combined with CT imaging characteristics

  • Kidneys, Ureters, Bladder, Retroperitoneum
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purpose

This study aims to assess the computed tomography (CT) findings of renal epithelioid angiomyolipoma (EAML) and develop a radiomics-based model for differentiating EAMLs and clear cell renal cell carcinomas (RCCs).

Method

This two-center retrospective study included 28 histologically confirmed EAMLs and 56 size-matched clear cell RCCs with preoperative three-phase kidney CTs. We conducted subjective image analysis to determine the CT parameters that can distinguish EAMLs from clear cell RCCs. Training and test sets were divided by chronological order of CT scans, and radiomics model was built using ten selected features among radiomics and CT features. The diagnostic performance of the radiomics model was compared with that of the three radiologists using the area under the receiver-operating characteristic curve (AUC).

Results

The mean size of the EAMLs was 6.2 ± 5.0 cm. On multivariate analysis, a snowman or ice cream cone tumor shape (OR 16.3; 95% CI 1.7–156.9, P = 0.02) and lower tumor-to-cortex (TOC) enhancement ratio in the corticomedullary phase (OR 33.4; 95% CI 5.7–197, P < 0.001) were significant independent factors for identifying EAMLs. The diagnostic performance of the radiomics model (AUC 0.89) was similar to those of genitourinary radiologists (AUC 0.78 and 0.81, P > 0.05) and superior to that of a third-year resident (AUC 0.63, P = 0.04).

Conclusions

A snowman or ice cream cone shape and lower TOC ratio were more closely associated with EAMLs than with clear cell RCCs. A CT radiomics model was useful for differentiating EAMLs from clear cell RCCs with better diagnostic performance than an inexperienced radiologist.

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Abbreviations

CT:

Computed tomography

EAML:

Epithelioid angiomyolipoma

GLRLM:

Gray-level run length matrices

GLSZM:

Gray-level size zone matrices

HU:

Hounsfield units

ICC:

Intra-class correlation coefficient

RCC:

Renal cell carcinomas

ROC:

Receiver-operating characteristic curve

ROI:

Regions of interest

TOC:

Tumor-to-cortex

WHO:

World Health Organization

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Acknowledgements

We appreciate to SeongYong Pak (Siemens Healthineers, Seoul, Korea) for technical support in this study.

Funding

The authors did not receive support from any organization for the submitted work.

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Author notes

  1. Taek Min Kim, Hyungwoo Ahn have contributed equally as first authors.

Authors and Affiliations

  1. Department of Radiology, Seoul National University Hospital, Seoul, Korea

    Taek Min Kim, Hyo Jeong Lee, Min Gwan Kim, Jeong Yeon Cho & Sang Youn Kim

  2. Department of Radiology, Seoul National University College of Medicine, Seoul, Korea

    Taek Min Kim, Hyungwoo Ahn, Jeong Yeon Cho, Sung Il Hwang & Sang Youn Kim

  3. Department of Radiology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Korea

    Hyungwoo Ahn & Sung Il Hwang

  4. Institute of Radiation Medicine and Kidney Research Institute, Seoul National University Medical Research Center, Seoul, 03080, Korea

    Jeong Yeon Cho

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Contributions

TMK Conceptualization, Methodology, Software, Formal analysis, Data Curation, Writing – Original Draft, Writing – Review & Editing, HA Methodology, Software, Formal analysis, Data Curation, Writing – Original Draft, Writing – Review & Editing, HJL Formal analysis, Data curation, Writing – Review & Editing, MGK Formal analysis, Data curation, Writing – Review & Editing, JYC Supervision, Writing – Review & Editing, SIH Supervision, Writing – Review & Editing, SYK Conceptualization, Methodology, Formal analysis, Data Curation, Writing – Review & Editing.

Corresponding author

Correspondence to Sang Youn Kim.

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The authors have no competing interests to declare that are relevant to the content of this article.

Ethical approval

This retrospective study was approved by the institutional review board in our center, and the requirement for written informed consent was waived.

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Kim, T.M., Ahn, H., Lee, H.J. et al. Differentiating renal epithelioid angiomyolipoma from clear cell carcinoma: using a radiomics model combined with CT imaging characteristics. Abdom Radiol 47, 2867–2880 (2022). https://doi.org/10.1007/s00261-022-03571-9

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