Update on new technologies in digital mammography

Evaluation of the FUSION-X-US-II prototype to combine automated breast ultrasound and tomosynthesis

OBJECTIVE

The FUSION-X-US-II prototype was developed to combine 3D automated breast ultrasound (ABUS) and digital breast tomosynthesis in a single device. We evaluated the performance of ABUS and tomosynthesis in a single examination in a clinical setting.

METHODS

In this prospective feasibility study, digital breast tomosynthesis and ABUS were performed using the FUSION-X-US-II prototype without any change of the breast position in patients referred for clarification of breast lesions with an indication for tomosynthesis. The tomosynthesis and ABUS images of the prototype were interpreted independently from the clinical standard by a breast diagnostics specialist. Any detected lesion was classified using BI-RADS® scores, and results of the standard clinical routine workup (gold standard) were compared to the result of the separate evaluation of the prototype images. Image quality was rated subjectively and coverage of the breast was measured.

RESULTS

One hundred one patients received both ABUS and tomosynthesis using the prototype. The duration of the additional ABUS acquisition was 40 to 60 s. Breast coverage by ABUS was approximately 80.0%. ABUS image quality was rated as diagnostically useful in 86 of 101 cases (85.1%). Thirty-three of 34 malignant breast lesions (97.1%) were identified using the prototype.

CONCLUSION

The FUSION-X-US-II prototype allows a fast ABUS scan in combination with digital breast tomosynthesis in a single device integrated in the clinical workflow. Malignant breast lesions can be localized accurately with direct correlation of ABUS and tomosynthesis images. The FUSION system shows the potential to improve breast cancer screening in the future after further technical improvements.

KEY POINTS

• The FUSION-X-US-II prototype allows the combination of automated breast ultrasound and digital breast tomosynthesis in a single device without decompression of the breast. • Image quality and coverage of ABUS are sufficient to accurately detect malignant breast lesions. • If tomosynthesis and ABUS should become part of breast cancer screening, the combination of both techniques in one device could offer practical and logistic advantages. To evaluate a potential benefit of a combination of ABUS and tomosynthesis in screening-like settings, further studies are needed.

Health literacy and cancer screening behaviors among community-dwelling female adults in Taiwan

This study was designed to explore the association among health literacy and cancer screening behaviors in Taiwanese females. A total of 353 community-dwelling females were recruited in this cross-sectional study from February to October 2015. Demographic, socioeconomic and personal behavior variables including physical activity, community activity, smoking, alcohol consumption, and betel nut chewing were recorded. Health literacy was evaluated using the Mandarin version of the European Health Literacy Survey Questionnaire. Data on screening behaviors for cervical, breast and colorectal cancers were confirmed by the Taiwanese National eHealth Database. Most respondents with inadequate or problematic general health literacy had no or irregular screening behaviors for cervical, breast and colorectal cancers. In multivariable regression analysis, women with inadequate health literacy were at a greater risk (Odds ratio = 5.71; 95% CI: 1.40-23.26) of having no previous Pap smear screening or >3 years screening interval regardless of education level. However, this association was not detected for breast or colorectal cancer. Women with inadequate health literacy were more likely to have irregular cervical cancer screening, however no associations among health literacy and breast or colorectal cancer were detected. The impact of health literacy on cancer screening behavior warrants further attention and research.

Deep Learning: A Breakthrough in Medical Imaging

Deep learning has attracted great attention in the medical imaging community as a promising solution for automated, fast and accurate medical image analysis, which is mandatory for quality healthcare. Convolutional neural networks and its variants have become the most preferred and widely used deep learning models in medical image analysis. In this paper, concise overviews of the modern deep learning models applied in medical image analysis are provided and the key tasks performed by deep learning models, i.e. classification, segmentation, retrieval, detection, and registration are reviewed in detail. Some recent researches have shown that deep learning models can outperform medical experts in certain tasks. With the significant breakthroughs made by deep learning methods, it is expected that patients will soon be able to safely and conveniently interact with AI-based medical systems and such intelligent systems will actually improve patient healthcare. There are various complexities and challenges involved in deep learning-based medical image analysis, such as limited datasets. But researchers are actively working in this area to mitigate these challenges and further improve health care with AI.

The cost-effectiveness of digital breast tomosynthesis in a population breast cancer screening program

OBJECTIVES

To evaluate at which sensitivity digital breast tomosynthesis (DBT) would become cost-effective compared to digital mammography (DM) in a population breast cancer screening program, given a constant estimate of specificity.

METHODS

In a microsimulation model, the cost-effectiveness of biennial screening for women aged 50-75 was simulated for three scenarios: DBT for women with dense breasts and DM for women with fatty breasts (scenario 1), DBT for the whole population (scenario 2) or maintaining DM screening (reference). For DM, sensitivity was varied depending on breast density from 65 to 87%, and for DBT from 65 to 100%. The specificity was set at 96.5% for both DM and DBT. Direct medical costs were considered, including screening, biopsy and treatment costs. Scenarios were considered to be cost-effective if the incremental cost-effectiveness ratio (ICER) was below €20,000 per life year gain (LYG).

RESULTS

For both scenarios, the ICER was more favourable at increasing DBT sensitivity. Compared with DM screening, 0.8-10.2% more LYGs were found when DBT sensitivity was at least 75% for scenario 1, and 4.7-18.7% when DBT sensitivity was at least 80% for scenario 2. At €96 per DBT, scenario 1 was cost-effective at a DBT sensitivity of at least 90%, and at least 95% for scenario 2. At €80 per DBT, these values decreased to 80% and 90%, respectively.

CONCLUSION

DBT is more likely to be a cost-effective alternative to mammography in women with dense breasts. Whether DBT could be cost-effective in a general population highly depends on DBT costs.

KEY POINTS

• DBT could be a cost-effective screening modality for women with dense breasts when its sensitivity is at least 90% at a maximum cost per screen of €96. • DBT has the potential to be cost-effective for screening all women when sensitivity is at least 90% at a maximum cost per screen of €80. • Whether DBT could be used as an alternative to mammography for screening all women is highly dependent on the cost of DBT per screen.

Breast Density of Mammography is Correlated with Reproductive Risk Factors Regardless of Menopausal Status: A Cross-Sectional Study of the Korean National Screening Program

OBJECTIVE

To clarify the limitations of mammography screening for women with dense breasts, we examined breast density and its effects on screening results.

PATIENTS AND METHODS

We performed a cross-sectional, observational study on women who underwent mammography. Data from the National Cancer Screening Program(NCSP) from 2009 to 2013 were used. The study population consisted of participants with high breast density. We used a logistic regression analysis to evaluate the relationships between breast density and reproductive factors and screening results according to menopause status.

RESULTS

High breast density was reported for 57.5% of all participants (3,417,319 participants). Screening results indicated breast density of <25%, 25-50%, 51-75%, and ≥76% for 16.4%, 26.3%, 37.8%, and 19.5%, respectively, of participants. According to the screening results, high breast density was correlated with high deferment and recall rates. Reproductive factors, especially parity, breastfeeding, and use of oral contraceptives, had consistent effects on screening results of premenopausal and postmenopausal women. Regardless of menopausal status, age, early onset of menarche (15 years or younger), fewer live births (≤1 birth), and previous benign breast disease were correlated with increased breast density. In postmenopausal women, early-onset menopause and longer-term hormone replacement therapy (≥2 years) also independently increased breast density.

CONCLUSION

Breast density influenced screening results, which could increase the rate of recall. Breast density was also influenced by reproductive factors, with patterns similar to those of breast cancer risk, regardless of menopausal status. We need to identify high-risk women with high density who would probably benefit from supplemental breast cancer screening.

An overview of mammographic density and its association with breast cancer

In 2017, breast cancer became the most commonly diagnosed cancer among women in the US. After lung cancer, breast cancer is the leading cause of cancer-related mortality in women. The breast consists of several components, including milk storage glands, milk ducts made of epithelial cells, adipose tissue, and stromal tissue. Mammographic density (MD) is based on the proportion of stromal, epithelial, and adipose tissue. Women with high MD have more stromal and epithelial cells and less fatty adipose tissue, and are more likely to develop breast cancer in their lifetime compared to women with low MD. Because of this correlation, high MD is an independent risk factor for breast cancer. Further, mammographic screening is less effective in detecting suspicious lesions in dense breast tissue, which can lead to late-stage diagnosis. Molecular differences between dense and non-dense breast tissues explain the underlying biological reasons for why women with dense breasts are at a higher risk for developing breast cancer. The goal of this review is to highlight the current molecular understanding of MD, its association with breast cancer risk, the demographics pertaining to MD, and the environmental factors that modulate MD. Finally, we will review the current legislation regarding the disclosure of MD on a traditional screening mammogram and the supplemental screening options available to women with dense breast tissue.

Digital Mammography in Young Women: Is a Single View Sufficient?

INTRODUCTION

Single view mammography may be a less time consuming, more comfortable and radiation reduced alternative for young women, but there are no studies examining this approach after the implementation of digital mammography into clinical practice.

MATERIALS AND METHODS

Retrospective analysis of all mammographies performed in women younger than 40 years during a 24 month period. The sample consisted of 109 women with 212 examined breasts. All patients initially received standard two- view mammography. In the study setting the MLO- views were read by a single viewer and compared to a composite reference standard.

RESULTS

In this sample 7 malignant findings were present and the review of the MLO-view detected 6 of them (85%). In patients with dense breasts 4 out of 5 malignant findings were found on the single-view (sensitivity 80%) and all 2 malignant findings were detected in patients with low breast density (sensitivity 100%). There were 7 false positive findings (3.3%). i.e. in total 8 out of 212 examined breasts were therefore misinterpreted (3.8%).

CONCLUSION

Single view digital mammography detects the vast majority of malignant findings, especially in low density breast tissue and the rate of false-positive findings is within acceptable limits. Therefore this approach may be used in different scenarios (for example in increasing patient throughout in resource poor settings, reducing radiation burden in the young or in combination with ultrasound to use the strengths of both methods). More research on this topic is needed to establish its potential role in breast imaging.

The effect of anatomical noise on perception of low contrast in intra-oral radiographs: an in vitro study

OBJECTIVES

Radiographic images suffer from varying amounts of noise. The most studied and discussed of these is random noise. However, recent research has shown that the projected anatomy contributes substantially to noise, especially when detecting low-contrast objects in the images. Our aim, therefore, was to evaluate the extent to which overprojected anatomical noise affects the detection of low-contrast objects in intra-oral images.

METHODS

Our study used four common sensor models. With each sensor, we took four series of images, three series with and one series without an anatomical phantom present. In each series, we exposed a low-contrast phantom at 18 different exposure times using a standardized method. 4 observers evaluated all 288 images.

RESULTS

The low-contrast characteristics differed substantially when imaging low contrast on a homogeneous background compared with imaging low contrast when an anatomical phantom was present. For three of the sensors, optimal exposure times for low-contrast imaging were found, while the fourth sensor displayed a completely different behaviour.

CONCLUSIONS

Calibrating the low-contrast properties of an imaging system using low-contrast objects on a homogeneous background is not recommended. On an anatomical background, low-contrast properties are completely different, and these will mimic the clinical situation much more closely, directing the operator how to best use the system. There is a clear demand for further research on this subject.