Impact of childbirth history on dense breast in mammographic screening: a cross-sectional study.

BACKGROUND: The evaluation of breast density is important, because dense breast has been shown to be associated with increased risk of breast cancer and a greater risk of a false-negative diagnostic performance due to masking a tumor. Although the relationship between parity and dense breast is under investigation, conclusive evidence is lacking. We aimed to investigate whether parity affects breast density. METHODS: The study design is a cross-sectional study. The subjects are healthy Japanese women who underwent opportunistic mammographic screening at the center for preventive medicine at a single institution from January 2016 to December 2018. Clinical characteristics and lifestyle factors were obtained from questionnaires. Breast density was categorized into 4 groups, namely, almost entirely fatty dense, scattered fibroglandular dense, heterogeneously dense, and extremely dense, according to the Breast Imaging Reporting and Data System. Heterogeneously and extremely dense were considered collectively as dense breast. Multivariate logistic regression analysis was conducted to investigate the relationship between parity and dense breast among premenopausal and postmenopausal women separately. RESULTS: 7612 premenopausal and 9252 postmenopausal women were investigated. Dense breast was shown in 62.6% of nulliparity, 57.3% of single parity, 47.3% of two parity, 37.6% of more than two parity among premenopausal women, and in 41.6% of nulliparity, 31.1% of single parity, 19.3% of two parity, 10.1% of more than two parity among postmenopausal women. For premenopausal women, two parity, single parity and nulliparity showed a higher risk for dense breast with statistically significance (Odds Ratio (OR) adjusted for potential confounding factors: 1.458 (95% Confidence interval (CI); 1.123-1.894), 2.349 (95%CI; 1.801-3.064), 3.222 (95%CI; 2.500-4.151), respectively), compared with more than two parity. For postmenopausal women, two parity, single parity and nulliparity had a higher risk (OR: 1.849 (95%CI; 1.479-2.312), 3.023 (95%CI; 2.385-3.830), 4.954 (95%CI; 3.975-6.174), respectively) with statistically significance, compared with more than two parity. CONCLUSIONS: Parity showed an inverse trend of having dense breast among both premenopausal and postmenopausal women. In particular, nulliparous women need to recognize their higher risk of dense breast. In the future, the declining fertility rate may affect the prevalence of dense breast in the world.

Prognostic impact of multifocal and multicentric breast cancer versus unifocal breast cancer.

PURPOSES: The clinical behavior of multifocal and multicentric breast cancers (MMBCs) is not well characterized. We conducted this study to ascertain whether patients with MMBCs have a worse prognosis than patients with unifocal breast cancers (UBC). METHODS: The subjects of this retrospective study were 734 consecutive patients who underwent definitive surgery for invasive breast carcinoma at our hospital between January 2004 and December 2006. MMBC was defined as ≥ 2 separate invasive unilateral breast tumors and pathological T stage was redefined based on the sum of the maximum diameter of each tumor. We evaluated disease-free survival (DFS) using the Kaplan-Meier method and Cox proportional hazards models. RESULTS: Of the 734 patients, 136 (18.5%) had MMBC. The pathological T stage of 36 of the patients with MMBC was upstaged by adopting the sum of each focus. MMBC did not have any survival impact, but MMBC upstaged by the modified pathological T stage was associated with worse DFS than non-upstaging MMBC (P = 0.004). Multivariate analysis revealed that upstaging MMBC was an independent factor for poor prognosis and worse DFS (HR 2.757, P = 0.043). CONCLUSIONS: MMBC itself may not be predictive of a worse prognosis; however, the sum of the invasive diameters of MMBC might be an important prognostic factor. Further studies are needed to confirm the prognosis associated with MMBC, taking into consideration the biological characteristics of each invasive focus.

BMI change and abdominal circumference are risk factors for breast cancer, even in Asian women.

PURPOSE: We investigated the association between breast cancer incidence and obesity among Asian women. METHODS: We used data from 30,109 women who had undergone medical check-ups and opportunistic breast cancer screening at least twice at the St. Luke's International Hospital Affiliated Clinic, Center for Preventive Medicine, between April 1, 2005 and March 31, 2014. This study evaluated obesity through body mass index (BMI) at age 18-20 years (BMI18-20y), BMI at research entry (entry BMI), change of BMI from age 18-20 to research entry (ΔBMI), abdominal circumference at research entry (AC), and HbA1c [N] at research entry (HbA1c). We used a multivariate Cox proportional hazard model to evaluate hazard ratios (HRs) and 95% confidence intervals (95% CIs). RESULTS: Of the 30,109 women, 325 were initially diagnosed with breast cancer over 131,657 person-years. Postmenopausal women whose BMI increased ≥+5.0 were significantly more likely to develop breast cancer (HR 1.902, 95% CI 1.202-3.009) than were the stable BMI group (ΔBMI: -2.5 to +2.5). Postmenopausal women with AC ≥90 cm were significantly likelier to develop breast cancer than were those with AC <70 cm (HR 2.500, 95% CI 1.091-5.730). Among postmenopausal women whose BMI18-20y was ≥20, those with high (≥6.5) HbA1c were more likely to develop breast cancer than those with low (<5.5) HbA1c (HR 3.325, 95% CI 1.307-8.460). CONCLUSIONS: Breast cancer incidence and obesity are positively associated in postmenopausal Asian women.

A model to predict upstaging to invasive carcinoma in patients preoperatively diagnosed with ductal carcinoma in situ of the breast.

BACKGROUND: The aims of this study were to determine clinicopathological factors associated with postoperative upstaging to invasive carcinoma in patients preoperatively diagnosed with ductal carcinoma in situ (DCIS) and to develop a model to predict the risk of upstaging. METHODS: Pre- and post-operative pathological diagnoses and radiological findings were assessed for 1,187 consecutive patients. RESULTS: Of the patients, 306 (25.8%) were upstaged on the surgical specimen. In multivariate analysis, the following four factors were significantly associated with upstaging: 1) the presence of sclerosing adenosis on the preoperative biopsy specimen (odds ratio [OR] 0.46, P = 0.013); 2) pleomorphic calcifications on the mammogram (OR 1.68, P = 0.009); 3) a mass suspicious for invasive carcinoma on ultrasonography and/or MRI (OR 2.13, P < 0.001); 4) tumor size ≥2 cm on ultrasonography (OR 1.80, P = 0.032). HER2-positive (OR 1.54, P = 0.062) and comedo necrosis (OR 1.42, P = 0.056) demonstrated a trend towards significance. A prediction model incorporating these variables demonstrated that the risk of upstaging was 5.1% with score 0-2 and was 58.1% with score 10. CONCLUSIONS: The prediction model incorporating clinicopathological features may be used to guide the selection of patients with DCIS for sentinel lymph node biopsy.

Psychological impact of breast cancer screening in Japan.

OBJECTIVE: The purpose of this study was to evaluate the psychological impact of breast cancer screening by use of mammography and/or ultrasound, and to reveal factors related to psychological distress. METHODS: Three hundred and twenty women were recalled to our hospital because of suspicious malignant findings from breast cancer screening between March and November 2012. They were asked to complete three questionnaires: the Hospital Anxiety and Depression Scale (HADS) for anxiety and depression, the Brief Coping Orientations to Problems Experienced scale (Brief COPE) for coping styles, and an original questionnaire for personal information. RESULTS: Complete data were available for 312 of 320 women (97.5 %). The median age was 45 years (range 23-73). The HADS revealed borderline or clinically significant anxiety for 70 % of the women. Family history of breast cancer, area of residence, number of times screened, number of recalls, and the period before the first visit were significantly related to psychological distress (p < 0.05). Brief COPE scores showed that self-blame, behavioral disengagement, self-distraction, use of emotional support, venting, denial, and less acceptance were related to increased anxiety. CONCLUSION: Seventy percent of women who were recalled after breast cancer screening experienced psychological distress. Thus, negative psychological impact should be regarded as an adverse effect of breast cancer screening.

A nomogram for predicting locoregional recurrence in primary breast cancer patients who received breast-conserving surgery after neoadjuvant chemotherapy.

BACKGROUND: We sought to develop and validate a predictive model of locoregional recurrence (LRR) in patients who underwent breast-conserving therapy (BCT) after neoadjuvant chemotherapy (NAC). PATIENTS AND METHODS: The clinicopathological characteristics of 520 consecutive primary breast cancer patients with residual tumor who underwent BCT after NAC between 2001 and 2008 were evaluated. Predictive variables of LRR were determined using a multivariate Cox proportional hazards model. The model was validated for discrimination and calibration by bootstrap re-sampling. RESULTS: At a median follow-up period of 51 months, 64 patients (12%) had developed LRR. Clinical stage T3 or T4, lymphovascular invasion, nuclear grade >3, and ≥4 positive lymph nodes metastasis were positively correlated with LRR. The nomogram for predicting LRR developed by using these four-clinicopathologic variables demonstrated high concordance. Patients with score 0-1 derived by the prediction model had significantly low LRR rate compared with patients with score 2 or higher (P < 0.001). CONCLUSIONS: This nomogram may be useful to predict LRR in primary breast cancer patients who underwent BCT after NAC with high reproducibility. This model is useful to conduct a study-identifying patients who may need an additional treatment to standard adjuvant therapy because of a high probability of LRR.

Clinicopathological significance of 'atypical ductal proliferation' in core needle biopsy of the breast.

Atypical ductal proliferation or ADP has been used in histopathological diagnosis of core needle biopsy (CNB) but its details have not been well studied. Therefore, we examined the clinicopathological characteristics of the initial CNB cases diagnosed as 'ADP ' who subsequently turned out to be malignant, and compared the findings to those that did not. Among 101 cases initially diagnosed as ADP in CNB, the second biopsy revealed no carcinoma (38), ductal carcinoma in situ (DCIS) (45) and invasive carcinoma (18). Significant differences were detected between those which turned out to be carcinoma and those that did not, in the status of myoepithelial cells identified by p63 immunohistochemistry (P = 0.026) and ultrasound (US) categories (P < 0.001). We further compared the histopathological characteristics of those initially diagnosed as ADP and subsequently as DCIS or invasive ductal carcinoma (IDC) with those initially diagnosed as such. DCIS or IDC cases initially diagnosed as ADP had significantly lower Ki67 labeling index (P < 0.01, P < 0.01) and histological grade using Van nuys prognostic index (P < 0.01) or Nottingham histological grades (P < 0.01) respectively than those initially as DCIS or IDC. An assessment of myoepithelial components with US findings might contribute to determine the subsequent clinical algorithm of the patients diagnosed as ADP at initial CNB.

Cystic duct with no visible signal on magnetic resonance cholangiography is associated with laparoscopic difficulties: an analysis of 695 cases.

BACKGROUND/AIMS: We investigated the association between the magnetic resonance cholangiography (MRC) results and surgical difficulties and bile duct injuries during laparoscopic cholecystectomy (LC). METHODS: MRC was performed on 695 consecutive patients before LC. We divided the patients into two groups (visible cystic duct group and "no signal" cystic duct on MRC group) and compared them with regard to the length of the operation, conversion rate to open cholecystectomy (OC) and rate of bile duct injury. RESULTS: The "no signal" cystic duct on MRC group had a longer operation and higher rate of conversion to OC compared with the visible cystic duct group. However, there was no statistically significant difference in the occurrence rate of bile duct injury between the two groups. CONCLUSIONS: The "no signal" cystic duct on MRC group was associated with laparoscopic difficulties, but not with an increased rate of biliary injury. When a visible cystic duct is not observed on MRC an early conversion to open surgery may avoid a bile duct injury during LC.

Beyond BI-RADS: Nonmass Abnormalities on Breast Ultrasound.

Abnormalities on breast ultrasound (US) images which do not meet the criteria for masses are referred to as nonmass lesions. These features and outcomes have been investigated in several studies conducted by Asian researchers. However, the term "nonmass" is not included in the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) 5th edition for US. According to the Japan Association of Breast and Thyroid Sonology guidelines, breast lesions are divided into mass and nonmass. US findings of nonmass abnormalities are classified into five subtypes: abnormalities of the ducts, hypoechoic areas in the mammary glands, architectural distortion, multiple small cysts, and echogenic foci without a hypoechoic area. These findings can be benign or malignant; however, focal or segmental distributions and presence of calcifications suggest malignancy. Intraductal, invasive ductal, and lobular carcinomas can present as nonmass abnormalities. For the nonmass concept to be included in the next BI-RADS and be widely accepted in clinical practice, standardized terminologies, an interpretation algorithm, and outcome-based evidence are required for both screening and diagnostic US.

Nonmass Lesions on Breast US: An International Perspective on Clinical Use and Outcomes.

Nonmass lesions (NMLs) on breast US are defined as discrete areas of altered echotexture compared to surrounding breast tissue and lack the 3-dimensionality of a mass. They are not a component of American College of Radiology BI-RADS, but they are a finding type included in the Japan Association of Breast and Thyroid Sonology lexicon. Use of the NML finding is routine in many Asian practices, including the Samsung Medical Center and Seoul National University Hospital, and their features and outcomes have been investigated in multiple studies. Nonmass lesions are most often observed when US is used to evaluate mammographic asymmetries, suspicious calcifications, and nonmass enhancement on MRI and contrast-enhanced mammography. Nonmass lesions can be described by their echogenicity, distribution, presence or absence of associated calcifications, abnormal duct changes, architectural distortion, posterior shadowing, small cysts, and hypervascularity. Malignant lesions, especially ductal carcinoma in situ, can manifest as NMLs on US. There is considerable overlap between the US features of benign and malignant NMLs, and they also must be distinguished from normal variants. The literature indicates that NMLs with linear or segmental distribution, associated calcifications, abnormal duct changes, posterior shadowing, and hypervascularity are suggestive of malignancy, whereas NMLs with only interspersed small cysts are usually benign fibrocystic changes. In this article, we introduce the concepts of NMLs, illustrate US features suggestive of benign and malignant etiologies, and discuss our institutional approach for evaluating NMLs and an algorithm that we use to guide interpretation in clinical practice.

Deep learning model to predict Ki-67 expression of breast cancer using digital breast tomosynthesis.

BACKGROUND: Developing a deep learning (DL) model for digital breast tomosynthesis (DBT) images to predict Ki-67 expression. METHODS: The institutional review board approved this retrospective study and waived the requirement for informed consent from the patients. Initially, 499 patients (mean age: 50.5 years, range: 29-90 years) referred to our hospital for breast cancer were participated, 126 patients with pathologically confirmed breast cancer were selected and their Ki-67 expression measured. The Xception architecture was used in the DL model to predict Ki-67 expression levels. The high Ki-67 vs low Ki-67 expression diagnostic performance of our DL model was assessed by accuracy, sensitivity, specificity, areas under the receiver operating characteristic curve (AUC), and by using sub-datasets divided by the radiological characteristics of breast cancer. RESULTS: The average accuracy, sensitivity, specificity, and AUC were 0.912, 0.629, 0.985, and 0.883, respectively. The AUC of the four subgroups separated by radiological findings for the mass, calcification, distortion, and focal asymmetric density sub-datasets were 0.890, 0.750, 0.870, and 0.660, respectively. CONCLUSIONS: Our results suggest the potential application of our DL model to predict the expression of Ki-67 using DBT, which may be useful for preoperatively determining the treatment strategy for breast cancer.

Inter- and intra-observer variability of qualitative visual breast-composition assessment in mammography among Japanese physicians: a first multi-institutional observer performance study in Japan.

BACKGROUND: Visual assessment of mammographic breast composition remains the most common worldwide, although subjective variability limits its reproducibility. This study aimed to investigate the inter- and intra-observer variability in qualitative visual assessment of mammographic breast composition through a multi-institutional observer performance study for the first time in Japan. METHODS: This study enrolled 10 Japanese physicians from five different institutions. They used the new Japanese breast-composition classification system 4th edition to subjectively evaluate the breast composition in 200 pairs of right and left normal mediolateral oblique mammograms (number determined using precise sample size calculations) twice, with a 1-month interval (median patient age: 59 years [range 40-69 years]). The primary endpoint of this study was the inter-observer variability using kappa (κ) value. RESULTS: Inter-observer variability for the four and two classes of breast-composition assessment revealed moderate agreement (Fleiss' κ: first and second reading = 0.553 and 0.587, respectively) and substantial agreement (Fleiss' κ: first and second reading = 0.689 and 0.70, respectively). Intra-observer variability for the four and two classes of breast-composition assessment demonstrated substantial agreement (Cohen's κ, median = 0.758) and almost perfect agreement (Cohen's κ, median = 0.813). Assessments of consensus between the 10 physicians and the automated software Volpara® revealed slight agreement (Cohen's κ; first and second reading: 0.104 and 0.075, respectively). CONCLUSIONS: Qualitative visual assessment of mammographic breast composition using the new Japanese classification revealed excellent intra-observer reproducibility. However, persistent inter-observer variability, presenting a challenge in establishing it as the gold standard in Japan.

JSUM ultrasound elastography practice guidelines: breast.

Ten years have passed since the first elastography application: Real-time Tissue Elastography™. Now there are several elastography applications in existence. The Quality Control Research Team of The Japan Association of Breast and Thyroid Sonology (JABTS) and the Breast Elasticity Imaging Terminology and Diagnostic Criteria Subcommittee, Terminology and Diagnostic Criteria Committee of the Japan Society of Ultrasonics in Medicine (JSUM) have advocated breast elastography classifications for exact knowledge and good clinical use. We suggest two types of classifications: the technical classification and the classification for interpretation. The technical classification has been created to use vibration energy and to make images, and also shows how to obtain a good elastic image. The classification for interpretation has been prepared on the basis of interpretation of evidence in this decade. Finally, we describe the character and specificity of each vender equipment. We expect the present guidelines to be useful for many physicians and examiners throughout the world.

Clinicopathological and imaging features of ductal carcinoma in situ in BRCA1/2 mutation carriers.

BACKGROUND: BRCA1/2-associated invasive breast cancer has been extensively studied. However, there are few reports of ductal carcinoma in situ (DCIS). OBJECTIVE: This study aimed to investigate the clinicopathological and imaging findings of DCIS in patients with BRCA1/2 mutations. METHODS: This was a single-institution, retrospective study. We identified patients diagnosed with DCIS with BRCA mutations between September 2003 and December 2020. Clinicopathological data and mammography (MG), magnetic resonance imaging (MRI), and ultrasound (US) findings were reviewed. RESULTS: We identified 30 cancers in 28 patients; 7 (25.0%) patients had BRCA1 mutations, and 21 (75.0%) had BRCA2 mutations. The median patient age was 42 years. Screening was the most common reason for the detection of DCIS (50.0%), followed by occult cancer diagnosed by pathological examination after risk-reducing mastectomy (26.7%). The nuclear grade was most often 1 (46.7%), and 93.3% were estrogen and/or progesterone receptor positive. The detection rates of MG, MRI, and US were 64.3%, 72.0%, and 64.0%, respectively. The most common imaging findings were calcification (100%) on MG, non-mass enhancement (88.9%) on MRI, and hypoechoic area (75.0%) on US. CONCLUSION: BRCA-associated DCIS was more strongly associated with BRCA2, and imaging features were similar to those of sporadic DCIS. Our results are helpful in informing surveillance strategies based on genotypes in women with BRCA mutations.

Why is the depth/width ratio of a typical fibroadenoma small in breast ultrasonography?

PURPOSE: Typical myxomatous fibroadenomas have a small depth/width (D/W) ratio on ultrasonography. The small D/W ratio of fibroadenomas is speculated to be caused by the softness of the mass and its orientation along the longitudinal aspect of the ductal elements without adhesion to the surrounding tissue; however, this has not been clearly proven. This study aimed to confirm the reason why fibroadenomas present with a small D/W ratio on ultrasonography. METHODS: We retrospectively analyzed imaging data from 17 patients who were diagnosed with typical fibroadenomas on ultrasonography and who underwent magnetic resonance imaging (MRI) at our hospital. RESULTS: The median D/W ratio obtained from ultrasonography images was 0.48 (0.32-0.67), while that obtained from MRI was 1.38 (0.62-1.68). The D/W ratios calculated from MRI were significantly greater than those calculated from ultrasonography images (p < 0.001). The D/W ratio obtained using ultrasonography was not greater than the D/W ratio obtained using MRI in any of the cases. CONCLUSION: This study revealed that the small D/W ratio of fibroadenomas on ultrasonography may be attributable to the horizontal force acting on the breast against the chest wall in the supine position, the elasticity of the fibroadenoma, and the lack of adhesion between the mass and surrounding tissue.

An association between mammographic breast density and fine particulate matter among postmenopausal women.

Increasing breast density is a risk factor for breast cancer. Geographic variations in breast density may be due to differences in lifestyle and diet, as well as environmental factors such as air pollution exposure. However, these environmental contributors have not been established. In this study, we evaluated an association between air pollution and mammographic breast density. The study population for this study was postmenopausal women who had undergone screening mammography at the Center for Preventive Medicine, St. Luke's International Hospital, from April 2004 to September 2018. Individual mammography results were obtained from electronic charts. The ambient air pollution (PM2.5) density of the locations of interest, namely, the patients' residential areas during the study period, was obtained. The mean PM2.5 exposure levels for 1, 3, 5, and 7 years were determined. A generalized estimating equations model was used to examine the association between air pollution density and dense breast. A total of 44,280 mammography results were included in this study, and 29,135 were classified in the non-dense breast group and 15,145 in the dense breast group. There was a 3% increase in the odds of having dense breasts after 1 year (OR = 1.027, 95% confidence interval (CI) 1.019-1.034) and 3 years of PM2.5 exposure (OR = 1.029, 95% CI 1.022-1.036). This further increased to 4% at 5-year exposure (OR = 1.044, 95% CI 1.037-1.052) and 5% at 7-year exposure (OR = 1.053, 95% CI 1.044-1.063). The risk for dense breasts increased if the factors of smoking, family history of breast and/or ovarian cancer, and history of childbirth were present.

Deep Learning for Differentiation of Breast Masses Detected by Screening Ultrasound Elastography.

Recently, deep learning using convolutional neural networks (CNNs) has yielded consistent results in image-pattern recognition. This study was aimed at investigating the effectiveness of deep learning using CNNs to differentiate benign and malignant breast masses identified by elastography on ultrasound screening. A data set of the elastography images of 245 breast masses (146 benign, 99 malignant) in 239 consecutive patients was retrospectively obtained. The data set was randomly split into training (55%), validation (25%) and test (20%) cohorts. A deep learning model predicting the probability of malignancy was constructed using GoogLeNet architectures (pre-trained by ImageNet) with 50 epochs. The model was then applied to the test data, and the results were compared with those obtained by evaluating the fat-to-lesion ratio (FLR) and by a 5-point visual color assessment (elasticity score). The receiver operating characteristic (ROC) curve was calculated to evaluate the performance of the model. The DeLong test was used to compare the areas under the ROC curve (AUCs). The CNN, FLR and elasticity score had a sensitivity of 0.800, 0.800 and 0.350; specificity of 0.966, 0.586 and 0.931; accuracy of 0.898, 0.673 and 0.694; positive predictive value of 0.941, 0.571 and 0.778; negative predictive value of 0.875, 0.810 and 0.675; and AUC of 0.895, 0.693 and 0.641, respectively. The AUC of the CNN was significantly higher than that of the FLR or elasticity score (p < 0.001). A CNN-based deep learning model for predicting benign or malignant breast masses revealed better diagnostic performance than did FLR or elasticity score-based estimations on ultrasound elastography. The CNN-based model also increased the positive predictive value from 57%-78% to 94%. Therefore, this model may reduce unnecessary biopsy recommendations for masses detected on breast ultrasound screening.

Clinicopathological and ultrasound characteristics of breast cancer in BRCA1 and BRCA2 mutation carriers.

PURPOSE: BRCA1 and BRCA2 tumors exhibit different characteristics. This study aimed to assess and compare the ultrasound findings and pathologic features of BRCA1 and BRCA2 breast cancers. To our knowledge, this is the first study to examine the mass formation, vascularity, and elasticity in breast cancers of BRCA-positive Japanese women. METHODS: We identified patients with breast cancer harboring BRCA1 or BRCA2 mutations. After excluding patients who underwent chemotherapy or surgery before the ultrasound, we evaluated 89 cancers in BRCA1-positive and 83 in BRCA2-positive patients. The ultrasound images were reviewed by three radiologists in consensus. Imaging features, including vascularity and elasticity, were assessed. Pathological data, including tumor subtypes, were reviewed. RESULTS: Significant differences in tumor morphology, peripheral features, posterior echoes, echogenic foci, and vascularity were observed between BRCA1 and BRCA2 tumors. BRCA1 breast cancers tended to be posteriorly accentuating and hypervascular. In contrast, BRCA2 tumors were less likely to form masses. In cases where a tumor formed a mass, it tended to show posterior attenuation, indistinct margins, and echogenic foci. In pathological comparisons, BRCA1 cancers tended to be triple-negative subtypes. In contrast, BRCA2 cancers tended to be luminal or luminal-human epidermal growth factor receptor 2 subtypes. CONCLUSION: In the surveillance of BRCA mutation carriers, radiologists should be aware that the morphological differences between tumors are quite different between BRCA1 and BRCA2 patients.

The location of unilateral axillary lymphadenopathy after COVID-19 vaccination compared with that of metastasis from breast cancer without vaccination.

PURPOSE: Unilateral axillary lymphadenopathy is known to occur after coronavirus disease (COVID-19) vaccination. Post-vaccination lymphadenopathy may mimic the metastatic lymph nodes in breast cancer, and it is challenging to distinguish between them. This study investigated whether the localization of axillary lymphadenopathy on magnetic resonance imaging (MRI) could be used to distinguish reactive lymphadenopathy after COVID-19 vaccines from metastatic nodes. MATERIALS AND METHODS: We retrospectively examined preoperative MRI images of 684 axillae in 342 patients who underwent breast cancer surgery from June to October 2021. Lymphadenopathy was defined as cortical thickening or short axis ≥ 5 mm. The axilla was divided into ventral and dorsal parts on the axial plane using a perpendicular line extending from the most anterior margin of the muscle group, including the deltoid, latissimus dorsi, or teres major muscles, relative to a line along the lateral chest wall. We recorded the presence or absence of axillary lymphadenopathy in each area and the number of visible lymph nodes. RESULTS: Of 80 axillae, 41 and 39 were included in the vaccine and metastasis groups, respectively. The median time from the last vaccination to MRI was 19 days in the vaccine group. The number of visible axillary lymph nodes was significantly higher in the vaccine group (median, 15 nodes) than in the metastasis group (7 nodes) (P < 0.001). Dorsal lymphadenopathy was observed in 16 (39.0%) and two (5.1%) axillae in the vaccine and metastasis groups, respectively (P < 0.001). If the presence of both ventral and dorsal lymphadenopathy is considered indicative of vaccine-induced reaction, this finding has a sensitivity of 34.1%, specificity of 97.4%, and positive and negative predictive values of 93.3％ and 58.5%, respectively. CONCLUSION: The presence of deep axillary lymphadenopathy may be an important factor for distinguishing post-vaccination lymphadenopathy from metastasis. The number of axillary lymph nodes may also help.

Deep learning model for breast cancer diagnosis based on bilateral asymmetrical detection (BilAD) in digital breast tomosynthesis images.

The purpose of this study was to develop a deep learning model to diagnose breast cancer by embedding a diagnostic algorithm that examines the asymmetry of bilateral breast tissue. This retrospective study was approved by the institutional review board. A total of 115 patients who underwent breast surgery and had pathologically confirmed breast cancer were enrolled in this study. Two image pairs [230 pairs of bilateral breast digital breast tomosynthesis (DBT) images with 115 malignant tumors and contralateral tissue (M/N), and 115 bilateral normal areas (N/N)] were generated from each patient enrolled in this study. The proposed deep learning model is called bilateral asymmetrical detection (BilAD), which is a modified convolutional neural network (CNN) model of Xception with two-dimensional tensors for bilateral breast images. BilAD was trained to classify the differences between pairs of M/N and N/N datasets. The results of the BilAD model were compared to those of the unilateral control CNN model (uCNN). The results of BilAD and the uCNN were as follows: accuracy, 0.84 and 0.75; sensitivity, 0.73 and 0.58; and specificity, 0.93 and 0.92, respectively. The mean area under the receiver operating characteristic curve of BilAD was significantly higher than that of the uCNN (p = 0.02): 0.90 and 0.84, respectively. The proposed deep learning model trained by embedding a diagnostic algorithm to examine the asymmetry of bilateral breast tissue improves the diagnostic accuracy for breast cancer.