Preliminary investigation of mammographic density among women in Riyadh: association with breast cancer risk factors and implications for screening practices

Albeshan, Salman M.; Hossain, Syeda Zakia; Mackey, Martin; Peat, Jennifer K.; Tahan, Fatina M. Al; Brennan, Patrick C.

doi:10.1016/j.clinimag.2019.01.002

Cited by 7 publications

(4 citation statements)

References 66 publications

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“…n Automated percent density (PD) estimates from the Laboratory for Individualized Breast Radiodensity Assessment (LIBRA) program from both for-processing (raw) and for-presentation (processed) formats were associated with breast cancer (odds ratio [OR], raw PD and processed PD: 1.2 and 1. (17)(18)(19), correlation with ethnicity (20), and other breast cancer risk factors (21) and have been shown to detect expected changes in density over time (22). In addition, LIBRA can assess density from both raw and processed (ie, for presentation) FFDM image formats.…”

Section: Key Resultsmentioning

confidence: 99%

Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction

Gastounioti¹,

Kasi²,

Scott³

et al. 2020

Radiology

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BREAST IMAGING I ncreased mammographic density has been shown consistently to be an independent risk factor for breast cancer (1-3) and a factor associated with decreased mammographic sensitivity because of masking of tumors within dense breast tissue (4-7). Several approaches have been developed to assess breast density in full-field digital mammography (FFDM) (8-13). The most commonly used method in the clinical setting is the visual grading of breast density by the interpreting radiologist into one of four categories outlined by the American College of Radiology Breast Imaging Reporting and Data System, or BI-RADS (8). Initially the BI-RADS categories were based on approximate area percentage values of the dense tissue in relation to the whole breast area (fourth edition), whereas in the latest revision (fifth edition) there is more emphasis on the masking effect of dense tissue.Semiautomated quantitative approaches such as the Cumulus software (version 4.2.1.0; Sunnybrook Health Sciences Center, Toronto, Canada) (9,14) have been developed to provide finer area-based breast density measures. However, these approaches are subjective and time consuming and can result in substantial intra-and interobserver variability when not performed by experienced individuals (15). Fully automated algorithms have been developed to extract robust and reproducible quantitative measures of breast density ( 16). These include

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Section: Key Resultsmentioning

confidence: 99%

Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction

Gastounioti¹,

Kasi²,

Scott³

et al. 2020

Radiology

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“…Few studies have been conducted that compare these modalities but, to the best of our knowledge, there has been no exhaustive study that has compared all these modalities and used combined methods for the assessment of breast lesions with a histopathological correlation. Also, no such study has been undertaken in an Indian population and, as already discussed, breast density is identified as an independent and the strongest risk factors for breast cancer-this can be different in different ethnic groups and people from different geographical areas [8].…”

Section: Introductionmentioning

confidence: 99%

“…The breast density of a Western population is greater when compared to an Indian population [8], and mammography on dense breasts can yield false negative results, making this study and its combined approach relevant to a Western population as well. The assessment of the breast and its lesions will be of importance in risk assessment and prevention strategies in various groups.…”

Section: Introductionmentioning

confidence: 99%

Characterization of Breast Lesions Using a Novel Combined Approach of Ultrasonography and Elastography Prior to Invasive Procedures: Are New Age Modalities Set to Replace the Diagnostic Giant?

Khanduri

Khan

Shukla

et al. 2019

Cureus

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ObjectiveThe goal of this study was to evaluate the diagnostic yield of B-mode ultrasound and ultrasound elastography used alone and in combination for differentiating breast lesions into benign and malignant. Materials and methodsEighty-five patients were investigated with B-mode ultrasonography and elastography and provided a Breast Imaging Reporting, and Data System (BI-RADS) score based on ultrasonography, strain ratio, and elastography score (ES) based on elastography. Each lesion was then evaluated by a combination method, combining BI-RADS with strain ratio and BI-RADS with elastography score. Each modality was assessed for the successful detection and characterization of the lesion and whether combining ultrasonography B-mode imaging with strain elastography improves diagnosis and is reliable enough to replace invasive procedures such as biopsy that have been the mainstay of diagnosis. ResultsOf 85 lesions, 23 lesions (27%) were found to be malignant, and 62 lesions (72.9%) were benign. When used alone, BI-RADS had 100.0% sensitivity, 13% specificity, 50% and 100% positive and negative predictive values (respectively), and 72.9% accuracy. BI-RADS results were then combined with strain ratio (SR) and ES. BI-RADS with SR had 91.3% sensitivity, 95.2% specificity, 87.5% and 96.7% positive and negative predictive values (respectively), and 94.1% accuracy. Similarly, BI-RADS with ES had 91.3% sensitivity, 93.5% specificity, 84.0% and 96.7% positive and negative predictive values, and 92.9% accuracy. characterize which lesions are better suited for biopsy, leading to a decline in unnecessary invasive procedures.

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“…To the best of our knowledge, this study is the first to examine the relationship between mammographic density and FHBC among Saudi women. To date, much of the mammographic density studies conducted in the Saudi population focus on the relationship between mammographic density and breast cancer risk [37,38]. Thus, this study may provide preliminary data to guide the risk assessment and screening of Saudi premenopausal women.…”

Section: Discussionmentioning

confidence: 94%

Association between Family History of Breast Cancer and Breast Density in Saudi Premenopausal Women Participating in Mammography Screening

Kanbayti,

Alzahrani,

Yeslam

et al. 2024

Clinics and Practice

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Background: Mammographic density and family history of breast cancer (FHBC) are well-established independent factors affecting breast cancer risk; however, the association between these two risk factors in premenopausal-screened women remains unclear. The aim of this study is to investigate the relationship between mammographic density and FHBC among Saudi premenopausal-screened women. Methods: A total of 446 eligible participants were included in the study. Mammographic density was assessed qualitatively using the Breast Imaging Reporting and Data System (BIRADS 4th edition). Logistic regression models were built to investigate the relationship between mammographic density and FHBC. Results: Women with a family history of breast cancer demonstrated an 87% greater chance of having dense tissue than women without a family history of breast cancer (95% CI: 1.14–3.08; p = 0.01). Having a positive family history for breast cancer in mothers was significantly associated with dense tissue (adjusted odds ratio (OR): 5.6; 95% CI: 1.3–24.1; p = 0.02). Conclusion: Dense breast tissue in Saudi premenopausal women undergoing screening may be linked to FHBC. If this conclusion is replicated in larger studies, then breast cancer risk prediction models must carefully consider these breast cancer risk factors.

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Preliminary investigation of mammographic density among women in Riyadh: association with breast cancer risk factors and implications for screening practices

Cited by 7 publications

References 66 publications

Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction

Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction

Characterization of Breast Lesions Using a Novel Combined Approach of Ultrasonography and Elastography Prior to Invasive Procedures: Are New Age Modalities Set to Replace the Diagnostic Giant?

Association between Family History of Breast Cancer and Breast Density in Saudi Premenopausal Women Participating in Mammography Screening

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