Journal of the Korean Society of Radiology (대한영상의학회지)

The Korean Society of Radiology (대한영상의학회)
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Correlation between MR Image-Based Radiomics Features and Risk Scores Associated with Gene Expression Profiles in Breast Cancer

유방암에서 자기공명영상 근거 영상표현형과 유전자 발현 프로파일 근거 위험도의 관계

  • Ga Ram Kim (Department of Radiology, Inha University Hospital, Inha University School of Medicine) ;
  • You Jin Ku (Department of Radiology, International St. Mary's Hospital, Catholic Kwandong University) ;
  • Jun Ho Kim (Department of Radiology, Inha University Hospital, Inha University School of Medicine) ;
  • Eun-Kyung Kim (Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine)
  • 김가람 (인하대학교 의과대학 부속병원 영상의학과) ;
  • 구유진 (가톨릭관동대학교 국제성모병원 영상의학과) ;
  • 김준호 (인하대학교 의과대학 부속병원 영상의학과) ;
  • 김은경 (연세대학교 의과대학 세브란스병원 방사선의과학연구소 영상의학교실)
  • Received : 2019.02.12
  • Accepted : 2019.09.14
  • Published : 2020.05.01
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Abstract

Purpose To investigate the correlation between magnetic resonance (MR) image-based radiomics features and the genomic features of breast cancer by focusing on biomolecular intrinsic subtypes and gene expression profiles based on risk scores. Materials and Methods We used the publicly available datasets from the Cancer Genome Atlas and the Cancer Imaging Archive to extract the radiomics features of 122 breast cancers on MR images. Furthermore, PAM50 intrinsic subtypes were classified and their risk scores were determined from gene expression profiles. The relationship between radiomics features and biomolecular characteristics was analyzed. A penalized generalized regression analysis was performed to build prediction models. Results The PAM50 subtype demonstrated a statistically significant association with the maximum 2D diameter (p = 0.0189), degree of correlation (p = 0.0386), and inverse difference moment normalized (p = 0.0337). Among risk score systems, GGI and GENE70 shared 8 correlated radiomic features (p = 0.0008-0.0492) that were statistically significant. Although the maximum 2D diameter was most significantly correlated to both score systems (p = 0.0139, and p = 0.0008), the overall degree of correlation of the prediction models was weak with the highest correlation coefficient of GENE70 being 0.2171. Conclusion Maximum 2D diameter, degree of correlation, and inverse difference moment normalized demonstrated significant relationships with the PAM50 intrinsic subtypes along with gene expression profile-based risk scores such as GENE70, despite weak correlations.

목적 자기공명영상 근거 영상표현형과 생체분자학적 아형, 유전자 발현 프로파일 근거 위험도 등 유방암 유전체 특징의 관계를 분석하고자 하였다. 대상과 방법 The Cancer Genome Atlas와 and the Cancer Imaging Archive에 공개된 자료를 이용하였다. 122개의 유방암의 자기공명영상에서 영상표현형이 추출되었다. 유전자 발현 프로파일에 따라 PAM50아형을 분류하고 위험도를 지정하였다. 영상표현형과 생체분자학적 특징의 관계를 분석하였다. 예측모델을 알아보기 위해 penalized generalized regression analysis를 이용하였다. 결과 PAM50아형은 maximum 2D diameter (p = 0.0189), degree of correlation (p = 0.0386), 그리고 inverse difference moment normalized (p = 0.0337)와 유의하게 관련이 있었다. 위험도 시스템 중에 GGI와 GENE70이 통계적으로 유의하게 8개의 영상표현형 특징을 서로 공유하였다(p = 0.0008~0.0492). Maximum 2D diameter가 두 위험도 시스템에서 가장 유의하게 관련있는 특징이었으나(p = 0.0139, p = 0.0008) 예측모델의 전반적인 연관 정도는 약했고 가장 높은 연관계수는 GENE70이 0.2171이었다. 결론 영상표현형 중에 maximum 2D diameter, degree of correlation, 그리고 inverse difference moment normalized가 PAM50 아형 그리고 GENE70과 같은 유전자 발현 프로파일 근거 위험도와 그 연관도는 약하였으나 유의한 관련을 보였다.

Keywords

Acknowledgement

This work was supported by an Inha University Hospital Research Grant.

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