Prevalence of Women with Dense Breasts in Korea: Results from a Nationwide Cross-sectional Study

Development and validation of nomograms using photoacoustic imaging and 2D ultrasound to predict breast nodule benignity and malignancy

BACKGROUND

The application of photoacoustic imaging (PAI), utilizing laser-induced ultrasound, shows potential in assessing blood oxygenation in breast nodules. However, its effectiveness in distinguishing between malignant and benign nodules remains insufficiently explored.

PURPOSE

This study aims to develop nomogram models for predicting the benign or malignant nature of breast nodules using PAI.

METHOD

A prospective cohort study enrolled 369 breast nodules, subjecting them to PAI and ultrasound examination. The training and testing cohorts were randomly divided into two cohorts in a ratio of 3:1. Based on the source of the variables, three models were developed, Model 1: photoacoustic-BIRADS+BMI + blood oxygenation, Model 2: BIRADS+Shape+Intranodal blood (Doppler) + BMI, Model 3: photoacoustic-BIRADS+BIRADS+ Shape+Intranodal blood (Doppler) + BMI + blood oxygenation. Risk factors were identified through logistic regression, resulting in the creation of three predictive models. These models were evaluated using calibration curves, subject receiver operating characteristic (ROC), and decision curve analysis.

RESULTS

The area under the ROC curve for the training cohort was 0.91 (95% confidence interval, 95% CI: 0.88-0.95), 0.92 (95% CI: 0.89-0.95), and 0.97 (95% CI: 0.96-0.99) for Models 1-3, and the ROC curve for the testing cohort was 0.95 (95% CI: 0.91-0.98), 0.89 (95% CI: 0.83-0.96), and 0.97 (95% CI: 0.95-0.99) for Models 1-3.

CONCLUSIONS

The calibration curves demonstrate that the model's predictions agree with the actual values. Decision curve analysis suggests a good clinical application.

Screening mammography performance according to breast density: a comparison between radiologists versus standalone intelligence detection

BACKGROUND

Artificial intelligence (AI) algorithms for the independent assessment of screening mammograms have not been well established in a large screening cohort of Asian women. We compared the performance of screening digital mammography considering breast density, between radiologists and AI standalone detection among Korean women.

METHODS

We retrospectively included 89,855 Korean women who underwent their initial screening digital mammography from 2009 to 2020. Breast cancer within 12 months of the screening mammography was the reference standard, according to the National Cancer Registry. Lunit software was used to determine the probability of malignancy scores, with a cutoff of 10% for breast cancer detection. The AI's performance was compared with that of the final Breast Imaging Reporting and Data System category, as recorded by breast radiologists. Breast density was classified into four categories (A-D) based on the radiologist and AI-based assessments. The performance metrics (cancer detection rate [CDR], sensitivity, specificity, positive predictive value [PPV], recall rate, and area under the receiver operating characteristic curve [AUC]) were compared across breast density categories.

RESULTS

Mean participant age was 43.5 ± 8.7 years; 143 breast cancer cases were identified within 12 months. The CDRs (1.1/1000 examination) and sensitivity values showed no significant differences between radiologist and AI-based results (69.9% [95% confidence interval [CI], 61.7-77.3] vs. 67.1% [95% CI, 58.8-74.8]). However, the AI algorithm showed better specificity (93.0% [95% CI, 92.9-93.2] vs. 77.6% [95% CI, 61.7-77.9]), PPV (1.5% [95% CI, 1.2-1.9] vs. 0.5% [95% CI, 0.4-0.6]), recall rate (7.1% [95% CI, 6.9-7.2] vs. 22.5% [95% CI, 22.2-22.7]), and AUC values (0.8 [95% CI, 0.76-0.84] vs. 0.74 [95% CI, 0.7-0.78]) (all P < 0.05). Radiologist and AI-based results showed the best performance in the non-dense category; the CDR and sensitivity were higher for radiologists in the heterogeneously dense category (P = 0.059). However, the specificity, PPV, and recall rate consistently favored AI-based results across all categories, including the extremely dense category.

CONCLUSIONS

AI-based software showed slightly lower sensitivity, although the difference was not statistically significant. However, it outperformed radiologists in recall rate, specificity, PPV, and AUC, with disparities most prominent in extremely dense breast tissue.

Deep Learning Analysis of Mammography for Breast Cancer Risk Prediction in Asian Women

The purpose of this study was to develop a mammography-based deep learning (DL) model for predicting the risk of breast cancer in Asian women. This retrospective study included 287 examinations in 153 women in the cancer group and 736 examinations in 447 women in the negative group, obtained from the databases of two tertiary hospitals between November 2012 and March 2022. All examinations were labeled as either dense breast or nondense breast, and then randomly assigned to either training, validation, or test sets. DL models, referred to as image-level and examination-level models, were developed. Both models were trained to predict whether or not the breast would develop breast cancer with two datasets: the whole dataset and the dense-only dataset. The performance of DL models was evaluated using the accuracy, precision, sensitivity, specificity, F1 score, and area under the receiver operating characteristic curve (AUC). On a test set, performance metrics for the four scenarios were obtained: image-level model with whole dataset, image-level model with dense-only dataset, examination-level model with whole dataset, and examination-level model with dense-only dataset with AUCs of 0.71, 0.75, 0.66, and 0.67, respectively. Our DL models using mammograms have the potential to predict breast cancer risk in Asian women.

Screening Outcomes of Supplemental Automated Breast US in Asian Women with Dense and Nondense Breasts

Background Automated breast (AB) US effectively depicts mammographically occult breast cancers in Western women. However, few studies have focused on the outcome of supplemental AB US in Asian women who have denser breasts than Western women. Purpose To evaluate the performance of supplemental AB US on mammography-based breast cancer screening in Asian women with dense breasts and those with nondense breasts. Materials and Methods A retrospective database search identified asymptomatic Korean women who underwent digital mammography (DM) and supplemental AB US screening for breast cancer between January 2018 and December 2019. We excluded women without sufficient follow-up, established final diagnosis, or histopathologic results. Performance measures of DM alone and AB US combined with DM (hereafter AB US plus DM) were compared. The primary outcome was cancer detection rate (CDR), and the secondary outcomes were sensitivity and specificity. Subgroup analyses were performed based on mammography density. Results From 2785 screening examinations in 2301 women (mean age, 52 years ± 9 [SD]), 28 cancers were diagnosed (26 screening-detected cancers, two interval cancers). When compared with DM alone, AB US plus DM resulted in a higher CDR of 9.3 per 1000 examinations (95% CI: 7.7, 10.3) versus 6.5 per 1000 examinations (95% CI: 5.2, 7.2; P < .001) and a higher sensitivity of 90.9% (95% CI: 77.3, 100.0) versus 63.6% (95% CI: 40.9, 81.8; P < .001) but a lower specificity of 86.8% (95% CI: 85.2, 88.2) versus 94.6% (95% CI: 93.6, 95.5; P < .001) in women with dense breasts. In women with nondense breasts, AB US plus DM resulted in a higher CDR of 9.5 per 1000 examinations (95% CI: 7.1, 10.6) versus 6.3 per 1000 examinations (95% CI: 3.5, 7.1; P < .001), whereas specificity was lower at 95.2% (95% CI: 93.4, 96.8) versus 97.1% (95% CI: 95.8, 98.4; P < .001). Conclusion In Asian women, the addition of automated breast US to digital mammography showed higher cancer detection rates but lower specificities in both dense and nondense breasts. © RSNA, 2023 Supplemental material is available for this article.

Association of Breast Cancer Family History With Breast Density Over Time in Korean Women

IMPORTANCE

Evidence suggests that women with a family history of breast cancer (FHBC) in first-degree relatives have a higher level of breast density; however, studies of premenopausal women remain limited.

OBJECTIVE

To investigate the association between FHBC and mammographic breast density and breast density changes among premenopausal women.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study used population-based data obtained from the National Health Insurance Service-National Health Information Database of Korea. We included premenopausal women aged 40 to 55 years who underwent mammography for breast cancer screening once between January 1, 2015, and December 31, 2016 (n = 1 174 214), and women who underwent mammography twice (first in 2015-2016 and again between January 1, 2017 and December 31, 2018) (n = 838 855).

EXPOSURES

Family history of breast cancer was assessed using a self-reported questionnaire, which included information on FHBC in the mother and/or sister.

MAIN OUTCOMES AND MEASURES

Breast density, based on the Breast Imaging Reporting and Data System, was categorized as dense (heterogeneously or extremely dense) and nondense (almost entirely fat or scattered fibroglandular areas). Multivariate logistic regression was used to assess the association among FHBC, breast density, and changes in breast density from the first to second screening. Data analysis was performed from June 1 to September 31, 2022.

RESULTS

Of the 1 174 214 premenopausal women, 34 003 (2.4%; mean [SD] age, 46.3 [3.2] years) reported having FHBC among their first-degree relatives, and 1 140 211 (97.1%; mean [SD] age, 46.3 [3.2] years) reported no FHBC. Odds of having dense breasts was 22% higher (adjusted odds ratio [aOR], 1.22; 95% CI, 1.19-1.26) in women with FHBC than in women without FHBC, and the association varied by affected relatives: mother alone (aOR, 1.15; 95% CI, 1.10-1.21), sister alone (aOR, 1.26; 95% CI, 1.22-1.31), and both mother and sister (aOR, 1.64; 95% CI, 1.20-2.25). Among women with fatty breasts at baseline, the odds of developing dense breasts was higher in women with FHBC than in those without FHBC (aOR, 1.19; 95% CI, 1.11-1.26), whereas among women with dense breasts, higher odds of having persistently dense breasts were observed in women with FHBC (aOR, 1.11; 95% CI, 1.05-1.16) than in those without FHBC.

CONCLUSIONS AND RELEVANCE

In this cohort study of premenopausal Korean women, FHBC was positively associated with an increased incidence of having increased or persistently dense breasts over time. These findings suggest the need for a tailored breast cancer risk assessment for women with FHBC.

Mammographic breast density, body mass index and risk of breast cancer in Korean women aged 75 years and older

Mammographic breast density and body mass index (BMI) are strong risk factors of breast cancer, but few studies have investigated these factors in older women. Our study assessed the association between breast density, BMI and the breast cancer risk among women aged ≥75 years. We included women who underwent breast cancer screening between 2009 and 2014 and were followed up until 2020. Breast density was measured using Breast Imaging Reporting and Data System. BMI was classified into three groups: <23, 23 to <25 and ≥25. Cox proportional hazards models were used to estimate the association of breast density and BMI with breast cancer risk. In 483 564 women, 1885 developed breast cancer. The 5-year incidence increased with an increase in breast density and BMI. Increase in breast density was associated with an increased breast cancer risk in all BMI categories: among women with BMI <23, those with heterogeneous/extreme density had a 2.98-fold (95% CI: 2.23-3.80) increased risk of breast cancer compared to those with entirely fatty breasts. An increase in BMI was associated with increased breast cancer risk in women with the same breast density in all density categories. When the combined associations of breast density and BMI on the risk of breast cancer were considered, women with a BMI ≥25 and heterogeneous/extreme breast density had a 5.35-fold (95% CI: 4.26-6.72) increased risk of breast cancer compared to women with a BMI <23 and fatty breasts. Women aged ≥75 years, with dense breasts, regardless of BMI status, might benefit from a tailored screening strategy for early detection of breast cancer.

Association of mammographic density and benign breast calcifications individually or combined with hypertension, diabetes, and hypercholesterolemia in women ≥40 years of age: a retrospective study

Recent evidence has linked certain mammographic characteristics, including breast calcifications (Bcs) and mammographic density (MD), with atherosclerotic cardiovascular disease risk factors in women, but data are limited and inconsistent. We aimed to evaluate the association of MD and/or Bcs with hypertension, diabetes, and hypercholesterolemia in women ≥40 years of age. Through hospital electronic records, we retrospectively identified mammograms of non-pregnant women aged ≥40 years and without breast cancer and retrieved reports and relevant data. MD and Bcs were recorded; risk factor status was diagnosed based on treatment profile and clinical and laboratory data. In total, 1406 women were included. MD was inversely related to hypertension, diabetes, hypercholesterolemia, triglyceride levels, age, and body mass index (BMI) (p value for trend <0.001). Bcs were positively associated with hypertension, diabetes, hypercholesterolemia, age, BMI, and elevated creatinine (p<0.05). Controlling for age and BMI, MD category A (MD-A) was independently associated with hypercholesterolemia; Bcs were independently associated with diabetes. Combining MD-A with Bcs did not increase the odds significantly. Analysis for additive interactions revealed a significant interaction between MD-A and BMI, increasing the odds of hypertension, and a trend for increased odds of diabetes by adding MD-A and/or Bcs to BMI. Decreased MD and presence of Bcs are associated with hypertension, diabetes, and hypercholesterolemia in women ≥40 years of age. MD-A may represent a new obesity index independently associated with hypercholesterolemia and additive to hypertension risk. Bcs are independently associated with diabetes. Combining MD and Bcs did not improve the odds significantly, which may reflect mechanistic differences.

Breast cancer detection across dense and non-dense breasts: Markers of diagnostic confidence and efficacy

Background

The impact of radiologists’ characteristics has become a major focus of recent research. However, the markers of diagnostic efficacy and confidence in dense and non-dense breasts are poorly understood.

Purpose

This study aims to assess the relationship between radiologists’ characteristics and diagnostic performance across dense and non-dense breasts.

Materials and methods

Radiologists specialising in breast imaging (n = 128) who had 0.5–40 (13±10.6) years of experience reading mammograms were recruited. Participants independently interpreted a test set containing 60 digital mammograms (40 normal and 20 abnormal) with similarly distributed breast densities. Diagnostic performance measures were analysed via Jamovi software (version 1.6.22).

Results

In dense breasts, breast-imaging fellowship completion significantly improved specificity (p = 0.004), location sensitivity (p = 0.01) and the area under the curve (AUC) of the receiver operating characteristic (p = 0.03). Only participation in BreastScreen reading significantly improved all performance metrics: specificity (p = 0.04), sensitivity (p = 0.005), location sensitivity (p < 0.001) and AUC (p < 0.001). Reading > 100 mammograms weekly significantly improved sensitivity (p = 0.03), location sensitivity (p = 0.001), and AUC (p = 0.03).In non-dense breasts, breast fellowship completion significantly improved sensitivity (p = 0.02), location sensitivity (p = 0.04) and AUC (p = 0.002). Participation in BreastScreen reading and reading > 100 mammograms weekly significantly improved only sensitivity (p = 0.002 and p = 0.003, respectively) and location sensitivity (p < 0.001 and p < 0.001, respectively).

Conclusion

Participating in screening programs, breast fellowships and reading > 100 mammograms weekly are important indicators of the diagnostic performance of radiologists across dense and non-dense breasts. In dense breasts, optimal performance resulted from participation in a breast screening program.

Artificial Intelligence for Breast Cancer Screening in Mammography (AI-STREAM): A Prospective Multicenter Study Design in Korea Using AI-based CADe/x

Purpose

Artificial intelligence (AI)-based computer-aided detection/diagnosis (CADe/x) has helped improve radiologists’ performance and provides results equivalent or superior to those of radiologists’ alone. This prospective multicenter cohort study aims to generate real-world evidence on the overall benefits and disadvantages of using AI-based CADe/x for breast cancer detection in a population-based breast cancer screening program comprising Korean women aged ≥ 40 years. The purpose of this report is to compare the diagnostic accuracy of radiologists with and without the use of AI-based CADe/x in mammography readings for breast cancer screening of Korean women with average breast cancer risk.

Methods

Approximately 32,714 participants will be enrolled between February 2021 and December 2022 at 5 study sites in Korea. A radiologist specializing in breast imaging will interpret the mammography readings with or without the use of AI-based CADe/x. If recall is required, further diagnostic workup will be conducted to confirm the cancer detected on screening. The findings will be recorded for all participants regardless of their screening status to identify study participants with breast cancer diagnosis within both 1 year and 2 years of screening. The national cancer registry database will be reviewed in 2026 and 2027, and the results of this study are expected to be published in 2027. In addition, the diagnostic accuracy of general radiologists and radiologists specializing in breast imaging from another hospital with or without the use of AI-based CADe/x will be compared considering mammography readings for breast cancer screening.

Discussion

The Artificial Intelligence for Breast Cancer Screening in Mammography (AI-STREAM) study is a prospective multicenter study that aims to compare the diagnostic accuracy of radiologists with and without the use of AI-based CADe/x in mammography readings for breast cancer screening of women with average breast cancer risk. AI-STREAM is currently in the patient enrollment phase.

Trial Registration

ClinicalTrials.gov Identifier: NCT05024591

Association of the Interaction Between Mammographic Breast Density, Body Mass Index, and Menopausal Status With Breast Cancer Risk Among Korean Women

IMPORTANCE

Evidence suggests that breast density and body mass index (BMI) are strong breast cancer risk factors; however, their interactive associations are unknown. Elucidation of these interactive associations may help to increase understanding of the causes of breast cancer and find effective interventions for susceptible subgroups.

OBJECTIVE

To explore the association of the interaction of mammographic breast density and BMI with breast cancer risks among premenopausal and postmenopausal women.

DESIGN, SETTING, AND PARTICIPANTS

This prospective observational cohort study used population-based data of the Korean National Cancer Screening Program embedded in the National Health Insurance Service database to evaluate the breast cancer risk of 3 248 941 premenopausal cancer-free women and 4 373 473 postmenopausal cancer-free women aged 40 years or older who underwent mammographic screening between January 1, 2009, and December 31, 2013, and were followed up until December 31, 2018. Statistical analysis was performed from June 1 to July 15, 2021.

EXPOSURES

Breast Imaging Reporting and Data System (BI-RADS)-defined breast density (with a scale from 1 to 4, where 1 indicates almost entirely fat, 2 indicates scattered fibroglandular densities, 3 indicates heterogeneously dense tissue, and 4 indicates extremely dense tissue) and BMI levels classified according to the World Health Organization Asia-Pacific Region classification.

MAIN OUTCOMES AND MEASURES

Adjusted relative risk (aRR) of breast cancer during the follow-up period and interactions in additive and multiplicative scales. The study end point was the development of breast cancer.

RESULTS

Of 3 248 941 premenopausal women (mean [SD] age, 44.6 [4.3] years) and 4 373 473 postmenopausal women (mean [SD] age, 59.6 [8.4] years) aged 40 years or older, 34 466 cases of breast cancer were identified among the premenopausal women, and 30 816 cases of breast cancer were identified among the postmenopausal women. Increased breast density was associated with an increased risk of breast cancer in both premenopausal and postmenopausal women across the BMI categories. Among premenopausal women, those in BI-RADS category 4 had an approximately 2-fold higher risk of breast cancer irrespective of BMI (all women: aRR, 2.36 [95% CI, 2.24-2.49]; underweight: aRR, 1.80 [95% CI, 1.25-2.59]; normal weight: aRR, 2.10 [95% CI, 1.93-2.28]; overweight: aRR, 2.47 [95% CI, 2.27-2.68]; obese: aRR, 2.87 [95% CI, 2.49-3.32]) than those with underweight status and in BI-RADS category 1. However, an association between BMI and the risk of breast cancer was found only in the postmenopausal women in all breast density categories compared with underweight women with BI-RADS category 1 (BI-RADS category 4, all women: aRR, 2.91 [95% CI, 2.78-3.04]; underweight: aRR, 2.74 [95% CI, 1.89-3.98]; normal weight: aRR, 3.05 [95% CI, 2.82-3.30]; overweight: aRR, 2.85 [95% CI, 2.67-3.04]; obese: aRR, 2.52 [95% CI, 2.22-2.88]). When the combined associations of breast density and BMI with the risk of breast cancer were considered, a high breast density and high BMI had a significant positive interaction on the additive scale for both premenopausal and postmenopausal women, especially the latter (premenopausal women: adjusted relative excess risk due to interaction, 0.53 [95% CI, 0.35-0.71]; postmenopausal women: adjusted relative excess risk due to interaction, 1.68 [95% CI, 1.26-2.10]).

CONCLUSIONS AND RELEVANCE

This study suggests that breast density and BMI interact synergistically to augment breast cancer risk, with a stronger association found among postmenopausal women. Both factors should be incorporated into risk stratification in a population-based screening for public health significance. Women with overweight or obesity and dense breast tissue might benefit from tailored early screening strategies to detect breast cancer.

Multifocality and Multicentrality in Breast Cancer: Comparison of the Efficiency of Mammography, Contrast-Enhanced Spectral Mammography, and Magnetic Resonance Imaging in a Group of Patients with Primarily Operable Breast Cancer

BACKGROUND

The multifocality and multicentrality of breast cancer (MFMCC) are the significant aspects that determine a specialist's choice between applying breast-conserving therapy (BCT) or performing a mastectomy. This study aimed to assess the usefulness of mammography (MG), contrast-enhanced spectral mammography (CESM), and magnetic resonance imaging (MRI) in women diagnosed with breast cancer before qualifying for surgical intervention to visualize other (additional) cancer foci.

METHODS

The study included 60 breast cancer cases out of 630 patients initially who underwent surgery due to breast cancer from January 2015 to April 2019. MG, CESM, and MRI were compared with each other in terms of the presence of MFMCC and assessed for compliance with the postoperative histopathological examination (HP).

RESULTS

Histopathological examination confirmed the presence of MFMCC in 33/60 (55%) patients. The sensitivity of MG in detecting MFMCC was 50%, and its specificity was 95.83%. For CESM, the sensitivity was 85.29%, and the specificity was 96.15%. For MRI, all the above-mentioned parameters were higher as follows: sensitivity-91.18%; specificity-92.31%.

CONCLUSIONS

In patients with MFMCC, both CESM and MRI are highly sensitive in the detection of additional cancer foci. Both CESM and MRI change the extent of surgical intervention in every fourth patient.

Fatty liver disease and changes in dense breasts in pre- and postmenopausal women: the Kangbuk Samsung Health Study

PURPOSE

While increased breast density is a risk factor for breast cancer, the effect of fatty liver disease on breast density is unknown. We investigated whether fatty liver is a risk factor for changes in breast density over ~ 4 years of follow-up in pre- and postmenopausal women.

METHODS

This study included 74,781 middle-aged Korean women with mammographically determined dense breasts at baseline. Changes in dense breasts were identified by more screening mammograms during follow-up. Hepatic steatosis (HS) was measured using ultrasonography. Flexible parametric proportional hazards models were used to determine the adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs), and a Weibull accelerated failure time model (AFT) was used to determine the time ratios (TRs) and 95% CIs.

RESULTS

During a median follow-up of 4.1 years, 4022 women experienced resolution of the dense breasts. The association between HS and dense breast resolution differed by the menopause status (P for interaction < 0.001). After adjusting for body mass index and other covariates, the aHRs (95% CI) for dense breast resolution comparing HS to non-HS were 0.81 (0.70-0.93) in postmenopausal women, while the association was converse in premenopausal women with the corresponding HRs of 1.30 (1.18-1.43). As an alternative approach, the multivariable-adjusted TR (95% CI) for dense breast survival comparing HS to non-HS were 0.81 (0.75-0.87) and 1.19 (1.06-1.33) in premenopausal and postmenopausal women, respectively.

CONCLUSION

The association between HS and changes in dense breasts differed with the menopause status. HS increased persistent dense breast survival in postmenopausal women but decreased it in premenopausal women.

The Relationship Between Breast Density Change During Menopause and the Risk of Breast Cancer in Korean Women

BACKGROUND

The aim of this study was to investigate the relationship between changes in breast density during menopause and breast cancer risk.

METHODS

This study was a retrospective, longitudinal cohort study for women over 30 years of age who had undergone breast mammography serially at baseline and postmenopause during regular health checkups at Samsung Medical Center. None of the participants had been diagnosed with breast cancer at baseline. Mammographic breast density was measured using the American College of Radiology Breast Imaging Reporting and Data System.

RESULTS

During 18,615 person-years of follow-up (median follow-up 4.8 years; interquartile range 2.8-7.5 years), 45 participants were diagnosed with breast cancer. The prevalence of dense breasts was higher in those who were younger, underweight, had low parity or using contraceptives. The cumulative incidence of breast cancer increased 4 years after menopause in participants, and the consistently extremely dense group had a significantly higher cumulative incidence (CI) of breast cancer compared with other groups [CI of extremely dense vs. others (incidence rate per 100,000 person-years): 375 vs. 203, P < 0.01].

CONCLUSION

Korean women whose breast density was extremely dense before menopause and who maintained this density after menopause were at two-fold greater risk of breast cancer.

PREVENTION RELEVANCE

Extremely dense breast density that is maintained persistently from premenopause to postmenopause increases risk of breast cancer two fold in Korean women. Therefore, women having risk factors should receive mammography frequently and if persistently extremely dense breast had been detected, additional modalities of BC screening could be considered.

Detection and recognition of ultrasound breast nodules based on semi-supervised deep learning: a powerful alternative strategy

BACKGROUND

The successful recognition of benign and malignant breast nodules using ultrasound images is based mainly on supervised learning that requires a large number of labeled images. However, because high-quality labeling is expensive and time-consuming, we hypothesized that semi-supervised learning could provide a low-cost and powerful alternative approach. This study aimed to develop an accurate semi-supervised recognition method and compared its performance with supervised methods and sonographers.

METHODS

The faster region-based convolutional neural network was used for nodule detection from ultrasound images. A semi-supervised classifier based on the mean teacher model was proposed to recognize benign and malignant nodule images. The general performance of the proposed method on two datasets (8,966 nodules) was reported.

RESULTS

The detection accuracy was 0.88±0.03 and 0.86±0.02, respectively, on two testing sets (1,350 and 2,220 nodules). When 800 labeled training nodules were available, the proposed semi-supervised model plus 4,396 unlabeled nodules performed better than the supervised learning model (area under the curve (AUC): 0.934±0.026 vs. 0.83±0.050; 0.916±0.022 vs. 0.815±0.049). The performance of the semi-supervised model trained on 800 labeled and 4,396 unlabeled nodules was close to that of the supervised learning model trained on a massive number of labeled nodules (n=5,196) (AUC: 0.934±0.026 vs. 0.952±0.027; 0.916±0.022 vs. 0.918±0.017). Moreover, the semi-supervised model was better than the average accuracy of five human sonographers (AUC: 0.922 vs. 0.889).

CONCLUSIONS

The semi-supervised model can achieve excellent performance for nodule recognition and be useful for medical sciences. The method reduced the number of labeled images required for training, thus significantly alleviating the difficulty in data preparation of medical artificial intelligence.

Value of accurate diagnosis for metastatic supraclavicular lymph nodes in breast cancer: assessment with neck US, CT, and 18F-FDG PET/CT

PURPOSE

Neck ultrasonography (US), computed tomography (CT), and 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) are all known to be useful imaging modalities for detecting supraclavicular lymph node (SCN) metastasis in breast cancer. The authors compared the diagnostic values of neck US, CT, and PET/CT in the detection of SCN metastasis in breast cancer.

METHODS

SCN metastases identified in neck US, CT, or PET/CT during follow-up visits of patients with breast cancer were pathologically confirmed with the use of US-guided fine-needle aspiration cytology. The clinicopathological factors of the patients were analyzed, and the statistical parameters including sensitivity, specificity, positive and negative predictive values, false-positive and false-negative rates, and accuracy of neck US, CT, and PET/CT were compared.

RESULTS

Among 32 cases of suspicious SCNs, 24 were pathologically confirmed as metastasis of breast cancer. The sensitivity of US + CT was 91.7%, which was the same as that of PET/CT, while the sensitivity rates of US alone and CT alone were 87.5% and 83.3%, respectively. Accuracy was 99.8% in PET/CT alone and 98.1% in US + CT. The false-negative rate was 0.1% in US + PET/CT, while it was 0.2% in PET/CT and US + CT, 0.3% in US alone and 0.4% in CT alone.

CONCLUSION

PET/CT can be the first choice for detecting SCN metastases in breast cancer. However, if PET/CT is unavailable for any reason, US + CT could be a good second option to avoid false-negative results.

Clinical Implications of Geometric and Dosimetric Uncertainties of Inter- and Intra-Fractional Movement during Volumetric Modulated Arc Therapy for Breast Cancer Patients

Simple Summary

Radiotherapy is an essential treatment modality for breast cancer. Compared to conventional radiotherapy techniques, modern radiotherapy with fewer fractions and smaller target volumes requires higher accuracy. Image-guidance using cone-beam computed tomography (CBCT) is one of the most common methods used for positional verification before treatment. This study reports geometric and dosimetric outcomes evaluated by analyzing CBCT images acquired before and during treatments. The positional change and internal movement of the patient were less than 1 cm in most cases without significant deviation in the dosimetric parameters of interest. However, there were cases involving extreme variation, which resulted in insufficient radiation delivered to the target areas and increased radiation exposure to adjacent normal organs. The results of the current study suggest that unexpected intra-fractional motion may occur, prompting for marginal adaptation in selected patients who are deemed to suffer from this kind of event.

Abstract

With the introduction of modern sophisticated radiotherapy (RT) techniques, the significance of accuracy has increased considerably. This study evaluated the necessity of pre-treatment and intra-fractional cone-beam computed tomography (CBCT) by analyzing inter- and intra-fractional CBCT images of breast cancer patients receiving RT. From 57 patients, 1206 pre-treatment CBCT and 1067 intra-fractional CBCT images were collected. Geometric movements of patients were measured quantitively in both inter- and intra-fractional CBCT, and changes in dosimetric parameters were evaluated in selected patients with extreme intra-fractional movement. For right-sided breast cancer patients, left-sided breast cancer patients treated using deep-inspiration breath hold (DIBH), and left-sided breast cancer patients treated using continuous positive airway pressure (CPAP), median inter-fractional deviations were 0.53 (range 0.06–2.98) cm, 0.66 (range 0.08–4.41) cm, and 0.69 (range 0.04–3.80) cm, and median intra-fractional deviations were 0.14 (range 0.00–0.62) cm, 0.23 (range 0.02–0.96) cm, and 0.24 (0.00–1.15) cm, respectively. Modified plans reflecting large changes in intra-fractional position in 10 selected cases revealed insufficient target coverage in seven cases and more than 20-fold increase in the volume of heart receiving at least 25 Gy in two cases. Intra-fractional verification, as well as pre-treatment verification, might be considered in patients using DIBH or CPAP.

The mammographic breast density distribution of Finnish women with breast cancer and comparison of breast density reporting using the 4th and 5th editions of the Breast Imaging-Reporting and Data System

PURPOSE

To examine the breast density distribution in patients diagnosed with breast cancer in an eastern Finnish population and to examine the changes in breast density reporting patterns between the 4^th and 5^th editions of the Breast Imaging-Reporting and Data System (BI-RADS).

METHOD

821 women (mean age 62.8 ± 12.2 years, range 28-94 years) with breast cancer were included in this retrospective study and their digital mammographic examinations were assessed semi-automatically and then visually by two radiologists in accordance with the 4^th and 5^th editions of the BI-RADS. Intraclass correlation coefficients (ICCs) were used to evaluate interobserver reproducibility. Chi-square tests were used to examine the associations between the breast density distribution and age or body mass index (BMI).

RESULTS

Interobserver reproducibility of the visual assessment was excellent, with an ICCr = 0.93. The majority of breast cancers occurred in fatty breasts (93.8 %) when density was assessed according to the 4^th edition of the BI-RADS. The distributions remained constant after correction for age and BMI. Using the 5^th edition, there was an overall 50.2 % decrease in almost entirely fatty (p <  0.001), 19.4 % increase in scattered fibroglandular (p <  0.001), 28.7 % increase in heterogeneously dense (p <  0.001), and 2.1 % increase in extremely dense (p <  0.001) categories.

CONCLUSIONS

Most breast cancers in eastern Finland occur in fatty breasts with an area density of < 50 %. Assessing breast density using the 5^th edition of the BI-RADS greatly increased denser assessments.

Digital Mammography as a Screening Tool in Korea

국가암검진사업에서 매년 400만 명 이상의 여성이 유방촬영술을 이용한 유방암 검진을 받고 있다. 2000년 디지털 유방촬영술의 도입 이후, 선행 연구들에 의하면 디지털 유방촬영술은 치밀유방을 가진 여성에서 제한적으로 기존의 필름 방식 또는 computed radiography (이하 CR)보다 높은 진단 정확도를 보고하였다. 최근 국가암검진사업에서 수행된 자료를 분석한 결과에 따르면 디지털 유방촬영술의 진단 정확도가 필름 또는 CR 방식에 비해서 치밀유방을 가진 여성뿐만 아니라 모든 연령대의 여성에서 검진 횟수와 상관없이 보다 정확하였다. 우리나라는 OECD 국가 중에서도 높은 유방촬영기기 보급률에도 불구하고 현재 디지털 유방촬영기기의 보급은 전체 유방촬영기기 중, 35% 정도 수준으로 더디기만 하다. 디지털 유방촬영기기로의 신속한 전환을 위하여 수가제도의 개선, 유방 영상 판독 교육 지원 등 관련법과 제도의 정비가 필요할 것이다. 아울러 국가암검진사업에서 보다 많은 여성이 디지털 유방촬영기기를 이용한 유방암 검진을 받을 수 있도록 장비 보급의 지역 간 격차 해소를 위해 노력해야 할 것이다.

Impact of Awareness of Breast Density on Perceived Risk, Worry, and Intentions for Future Breast Cancer Screening among Korean Women

PURPOSE

This study sought to examine perceived risk and concerns for breast cancer according to awareness of breast density and states thereof among Korea women and to identify the impact of such awareness on screening intentions.

Materials and Methods

This study was based on the 2017 Korean National Cancer Screening Survey of a nationally representative and randomly selected sample of Koreans. Ordinal logistic regression was conducted to examine associations for awareness of and knowledge on breast density in relation to psychological factors. Multivariate logistic regression analyses were conducted to investigate significant factors associated with intentions to undergo breast cancer screening.

RESULTS

Among a total of 1,609 women aged 40-69 years, 62.0% were unaware of their breast density, and only 29.7% had good breast density knowledge. Awareness of one's breast density and knowledge about breast density were positively associated with perceptions of absolute and comparative risk and cancer worry. Women aware of their breast density (adjusted odds ratio [aOR], 1.35 for women aware of having a non-dense breast; aOR, 4.17 for women aware of having a dense breast) and women with a good level of breast density knowledge (aOR, 1.65) were more likely to undergo future breast cancer screening.

CONCLUSION

Breast density awareness and knowledge showed positive associations with psychological factors and breast cancer screening intentions. However, the majority of Korean women were not aware of their breast density status and demonstrated poor knowledge about breast density. These results demonstrate a need for better health communication concerning breast density.

Association of Screening by Thyroid Ultrasonography with Mortality in Thyroid Cancer: A Case-Control Study Using Data from Two National Surveys

Background: The incidence of thyroid cancer is increasing worldwide due to an increased detection of small well-differentiated papillary thyroid carcinomas. This study aimed to evaluate the effect of screening with ultrasonography on deaths from thyroid cancer. Materials and Methods: We conducted a matched case-control study using data from two sources representative of the adult Korean population. Cases were selected from the National Epidemiologic Survey of Thyroid Cancer database, and controls were selected from the Korean National Cancer Screening Survey database. Controls were individually matched to case patients with respect to age, sex, and area with a ratio of 10:1. The primary outcome was death from thyroid cancer. Controls were required to have been alive on the date of thyroid cancer diagnosis in the corresponding case. Results: The analysis included 120 patients who died from thyroid cancer and 1184 controls. Compared with those who had never been screened, the odds ratios for death from thyroid cancer among those who had been screened were 1.44 (95% confidence interval [CI] 0.68-3.05) if cases with missing information on screening were excluded and 1.13 [CI 0.49-2.63] if all cases were included, and missing information was imputed. Stratification by sex, year of diagnosis, and histological type did not show any statistically significant relationships between screening with ultrasonography and death from thyroid cancer, regardless of the statistical model used. Conclusions: Screening for thyroid cancer with ultrasonography does not prevent death from thyroid cancer; therefore, screening asymptomatic adults for thyroid cancer is unwarranted.