Literature DB >> 35111622

Association between quantitative and qualitative image features of contrast-enhanced mammography and molecular subtypes of breast cancer.

Simin Wang1,2, Zhenxun Wang3, Ruimin Li1,2, Chao You1,2, Ning Mao4, Tingting Jiang1,2, Zhongyi Wang4, Haizhu Xie4, Yajia Gu1,2.   

Abstract

BACKGROUND: The molecular subtype of breast cancer is one of the most important factors affecting patient prognosis. The study aimed to analyze the association between quantitative and qualitative features of contrast-enhanced mammography (CEM) images and breast cancer molecular subtypes.
METHODS: This retrospective double-center study included women who underwent CEM between November 2017 and April 2020. Each patient had at least 1 malignant lesion confirmed by pathology. The CEM images were evaluated by 2 radiologists to obtain quantitative and qualitative image features. The molecular subtypes were studied as dichotomous outcomes, including luminal versus non-luminal, human epidermal growth factor receptor (HER2)-enriched versus non-HER2-enriched, and triple-negative breast cancer (TNBC) versus non-TNBC subtypes. The association between the image features and molecular subtypes was analyzed by multivariate logistic regression, with odds ratios (ORs) and 95% confidence intervals (CIs) provided.
RESULTS: A total of 151 patients with 160 malignant lesions were included in the study. For quantitative features, a higher standard deviation of lesion density was associated with non-luminal (OR =0.88, 95% CI: 0.81 to 0.96, P=0.004) and HER2-enriched breast cancers (OR =1.16, 95% CI: 1.04 to 1.28, P=0.006). The relative degree of enhancement (RDE) and contrast-to-noise ratio (CNR) were not associated with molecular subtypes. However, a higher CNR/lesion size (OR =1.06, 95% CI: 1.01 to 1.12, P=0.012) was associated with luminal subtype cancers, and a higher RDE/lesion size (OR =0.94, 95% CI: 0.88 to 1.00, P=0.035) or a higher CNR/lesion size (OR =0.94, 95% CI: 0.88-1.00, P=0.038) was associated with non-TNBCs. For qualitative features, the presence of calcification was associated with HER2-enriched breast cancers (OR =2.91, 95% CI: 1.10 to 7.67, P=0.031). The presence of architectural distortion was associated with luminal cancer (OR =14.50, 95% CI: 1.91 to 110.14, P=0.010) and non-TNBC (OR =0.05, 95% CI: 0.00 to 0.43, P=0.022). Non-mass enhancement (OR =2.78, 95% CI: 1.08 to 7.14, P=0.033) was associated with HER2-enriched breast cancers. An association remained after adjustments for age, breast thickness, and breast density (all adjusted P<0.050).
CONCLUSIONS: The quantitative and qualitative imaging features of CEM could contribute to distinguishing breast cancer molecular subtypes. 2022 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Entities:  

Keywords:  Contrast-enhanced mammography (CEM); breast cancer; molecular subtype; quantitative

Year:  2022        PMID: 35111622      PMCID: PMC8739155          DOI: 10.21037/qims-21-589

Source DB:  PubMed          Journal:  Quant Imaging Med Surg        ISSN: 2223-4306


  42 in total

1.  Tomosynthesis and contrast-enhanced digital mammography: recent advances in digital mammography.

Authors:  Felix Diekmann; Ulrich Bick
Journal:  Eur Radiol       Date:  2007-07-28       Impact factor: 5.315

2.  MRI phenotype of breast cancer: Kinetic assessment for molecular subtypes.

Authors:  Eric Blaschke; Hiroyuki Abe
Journal:  J Magn Reson Imaging       Date:  2015-03-09       Impact factor: 4.813

Review 3.  Angiomammography: A review of current evidences.

Authors:  C Dromain; N Vietti-Violi; J Y Meuwly
Journal:  Diagn Interv Imaging       Date:  2019-04-05       Impact factor: 4.026

4.  Can we apply the MRI BI-RADS lexicon morphology descriptors on contrast-enhanced spectral mammography?

Authors:  Rasha M Kamal; Maha H Helal; Sahar M Mansour; Marwa A Haggag; Omniya M Nada; Iman G Farahat; Nelly H Alieldin
Journal:  Br J Radiol       Date:  2016-06-21       Impact factor: 3.039

5.  Computational approach to radiogenomics of breast cancer: Luminal A and luminal B molecular subtypes are associated with imaging features on routine breast MRI extracted using computer vision algorithms.

Authors:  Lars J Grimm; Jing Zhang; Maciej A Mazurowski
Journal:  J Magn Reson Imaging       Date:  2015-03-17       Impact factor: 4.813

6.  Correlation between MR imaging - prognosis factors and molecular classification of breast cancers.

Authors:  C Alili; E Pages; F Curros Doyon; H Perrochia; I Millet; P Taourel
Journal:  Diagn Interv Imaging       Date:  2014-02-10       Impact factor: 4.026

7.  Enhancement parameters on dynamic contrast enhanced breast MRI: do they correlate with prognostic factors and subtypes of breast cancers?

Authors:  Ji Youn Kim; Sung Hun Kim; Yun Ju Kim; Bong Joo Kang; Yeong Yi An; A Won Lee; Byung Joo Song; Yong Soo Park; Han Bi Lee
Journal:  Magn Reson Imaging       Date:  2014-08-29       Impact factor: 2.546

Review 8.  Calcification in breast lesions: pathologists' perspective.

Authors:  G M Tse; P-H Tan; A L M Pang; A P Y Tang; H S Cheung
Journal:  J Clin Pathol       Date:  2007-08-17       Impact factor: 3.411

9.  Evaluation of low-energy contrast-enhanced spectral mammography images by comparing them to full-field digital mammography using EUREF image quality criteria.

Authors:  U C Lalji; C R L P N Jeukens; I Houben; P J Nelemans; R E van Engen; E van Wylick; R G H Beets-Tan; J E Wildberger; L E Paulis; M B I Lobbes
Journal:  Eur Radiol       Date:  2015-03-27       Impact factor: 5.315

10.  Quantitative Analysis of Enhancement Intensity and Patterns on Contrast-enhanced Spectral Mammography.

Authors:  Ying Liu; Shuang Zhao; Juan Huang; Xueqin Zhang; Yun Qin; Huanhuan Zhong; Jianqun Yu
Journal:  Sci Rep       Date:  2020-06-17       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.