Associations between mammographic density and tumor characteristics in Chinese women with breast cancer

Li, Erni; Guida, Jennifer; Tian, Yuan; Sung, Hyuna; Koka, Hela; Li, Mengjie; Chan, Ariane; Zhang, Han; Tang, Eric; Guo, Changyuan; Deng, Joseph; Hu, Nan; Lü, Ning; Gierach, Gretchen L.; Li, Jing; Yang, Xiaohong R.

doi:10.1007/s10549-019-05325-6

Cited by 23 publications

(22 citation statements)

References 47 publications

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“…A similar study was recently conducted by . According to the findings, the results may partially explain the higher proportion of HER2+ tumors 26 , and these findings were not aligned with our study findings.…”

Section: Discussioncontrasting

confidence: 99%

Mammographic density and its association with molecular subtype of breast cancer.

Jabeen¹,

Rasheed²,

Imran³

et al. 2020

Int. j. endorsing health sci. res.

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Background: Breast cancer is the leading cause of death in women globally. The present study aimed to determine the prevalence of different mammographic density of breast parenchyma along with the association with the molecular subtype of breast cancer. Methodology: The present cross-sectional study was conducted among breast cancer females age 40 and above. The study participants' demographic and clinical data, such as age, sex, menstrual status, gravida, parity, and lactation, were collected using a standard questionnaire. The anthropometric parameters were taken by using the standard techniques. Breast physical examination, mammography, and ultrasound were done. The ultrasound did the breast tumor biopsy -guided techniques and histopathology, and immunohistochemistry was used to identify the molecular subtype of breast cancer. The univariate and multivariate statistic was performed on SPSS version 20.0. Results: Most of the patients<50 years were human epidermal growth factor receptor (HER2), estrogen receptor (ER), progesterone receptor (PR) positive, and are overweight too. Similar findings were noted among lactating and multigravida patients. The Grade I tumor and dense breast patients were 100% with HER2 negative and ER, PR positive. Most heterogeneous dense and fibroglandular containing breast patients were ER, PR positive. There is a significant correlation between BMI, microcalcification, and HER2 positive. Most of the triple Negative and Luminal-B were heterogeneous dense. Conclusion: In conclusion, a significant association between the mammographic density parameters and molecular breast cancer subtype, particularly Luminal-A and luminal B, was seen. The ER, PR, and HER-2 have a positive correlation with the physical radiographical and mammodensity parameters.

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Section: Discussioncontrasting

confidence: 99%

Mammographic density and its association with molecular subtype of breast cancer.

Jabeen¹,

Rasheed²,

Imran³

et al. 2020

Int. j. endorsing health sci. res.

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“…Breast cancer is the most common malignant tumor in women in China ( 1 , 2 ). Breast ultrasound is more suitable for tumor discovery in Asian women considering the higher breast density ( 3 , 4 ) and the younger age at diagnosis ( 5 , 6 ). Patients with Breast Imaging Reporting and Data System (BI-RADS) 4a or higher findings are usually recommended to undergo core needle biopsy or surgery.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Accuracy of Breast Cancer and Molecular Subtype Diagnosis by Ultrasound Image Deep Learning Model

Zhang

Wang

et al. 2021

Front. Oncol.

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Background: Breast ultrasound is the first choice for breast tumor diagnosis in China, but the Breast Imaging Reporting and Data System (BI-RADS) categorization routinely used in the clinic often leads to unnecessary biopsy. Radiologists have no ability to predict molecular subtypes with important pathological information that can guide clinical treatment.Materials and Methods: This retrospective study collected breast ultrasound images from two hospitals and formed training, test and external test sets after strict selection, which included 2,822, 707, and 210 ultrasound images, respectively. An optimized deep learning model (DLM) was constructed with the training set, and the performance was verified in both the test set and the external test set. Diagnostic results were compared with the BI-RADS categorization determined by radiologists. We divided breast cancer into different molecular subtypes according to hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression. The ability to predict molecular subtypes using the DLM was confirmed in the test set.Results: In the test set, with pathological results as the gold standard, the accuracy, sensitivity and specificity were 85.6, 98.7, and 63.1%, respectively, according to the BI-RADS categorization. The same set achieved an accuracy, sensitivity, and specificity of 89.7, 91.3, and 86.9%, respectively, when using the DLM. For the test set, the area under the curve (AUC) was 0.96. For the external test set, the AUC was 0.90. The diagnostic accuracy was 92.86% with the DLM in BI-RADS 4a patients. Approximately 70.76% of the cases were judged as benign tumors. Unnecessary biopsy was theoretically reduced by 67.86%. However, the false negative rate was 10.4%. A good prediction effect was shown for the molecular subtypes of breast cancer with the DLM. The AUC were 0.864, 0.811, and 0.837 for the triple-negative subtype, HER2 (+) subtype and HR (+) subtype predictions, respectively.Conclusion: This study showed that the DLM was highly accurate in recognizing breast tumors from ultrasound images. Thus, the DLM can greatly reduce the incidence of unnecessary biopsy, especially for patients with BI-RADS 4a. In addition, the predictive ability of this model for molecular subtypes was satisfactory,which has specific clinical application value.

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“…Furthermore, they found no significant association of breast density with BMI 17 . Other, smaller studies have yielded inconsistent associations of breast density with breast cancer subtypes 18–26 . Our finding of the interaction of menopause status and BI‐RADS breast density is clinically relevant, as breast density has increasingly been used to identify women who may benefit from supplemental screening, given that mammography is less sensitive among women with dense breasts.…”

Section: Discussionmentioning

confidence: 66%

“…17 Other, smaller studies have yielded inconsistent associations of breast density with breast cancer subtypes. [18][19][20][21][22][23][24][25][26] Our finding of the interaction of menopause status and BI-RADS breast density is clinically relevant, as breast density has increasingly been used to identify women who may benefit from supplemental screening, given that mammography is less sensitive among women with dense breasts. There is controversy about the risk-tobenefit ratio of supplemental screening for all women with dense breasts, given that nearly half of the screening eligible population has heterogeneously or extremely dense breasts.…”

Section: Discussionmentioning

confidence: 93%

Relationship of established risk factors with breast cancer subtypes

et al. 2021

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Associations between mammographic density and tumor characteristics in Chinese women with breast cancer

Cited by 23 publications

References 47 publications

Mammographic density and its association with molecular subtype of breast cancer.

Mammographic density and its association with molecular subtype of breast cancer.

Evaluating the Accuracy of Breast Cancer and Molecular Subtype Diagnosis by Ultrasound Image Deep Learning Model

Relationship of established risk factors with breast cancer subtypes

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