Benign Breast Biopsy Research Articles

Microcalcifications in benign breast biopsies: association with lesion type and risk.

To characterize associations of microcalcifications (calcs) with benign breast disease lesion subtypes and assess whether tissue calcs affect risks of ductal carcinoma in situ (DCIS) and invasive breast cancer (IBC). We analyzed detailed histopathologic data for 4,819 BBD biopsies from a single institution cohort (2002-2013) followed for DCIS or IBC for a median of 7.4years for cases (N = 338) and 11.2years for controls. Natural language processing was used to identify biopsies containing calcs based on pathology reports. Univariable and multivariable regression models were applied to assess associations with BBD lesion type and age-adjusted Cox proportional hazard regressions were performed to model risk of IBC or DCIS stratified by the presence or absence of calcs. Calcs were identified in 2063 (42.8%) biopsies. Calcs were associated with older age at BBD diagnosis (56.2 versus 49.0years; P < 0.001). Overall, the risk of developing IBC or DCIS did not differ significantly between patients with calcs (HR 1.13, 95% CI 0.90, 1.41) as compared to patients without calcs. Stratification by BBD severity or subtype, age at BBD biopsy, outcomes of IBC versus DCIS, and mammography technique (screen-film versus full-field digital mammography) did not significantly alter association between calcs and risk. Our analysis of calcs in BBD biopsies did not find a significant association between calcs and risk of breast cancer.

Assessing the Correlation between Allostatic Load and False-Positive Image-Guided Breast Biopsies.

Background: Allostatic load (AL) is the accumulation of physiological dysregulation attributed to repeated activation of the stress response over a lifetime. We assessed the utility of AL as a prognostic measure for high-risk benign breast biopsy pathology results. Method: Eligible patients were women 18 years or older, with a false-positive outpatient breast biopsy between January and December 2022 at a tertiary academic health center. AL was calculated using 12 variables representing four physiological systems: cardiovascular (pulse rate, systolic and diastolic blood pressures, total cholesterol, high-density lipoprotein, and low-density lipoprotein); metabolic (body mass index, albumin, and hemoglobin A1C); renal (creatinine and estimated glomerular filtration rate); and immune (white blood cell count). Multivariable logistic regression was used to assess the association between AL before biopsy and breast biopsy outcomes controlling for patients' sociodemographics. Results: In total, 170 women were included (mean age, 54.1 ± 12.9 years): 89.4% had benign and 10.6% had high-risk pathologies (radial scar/complex sclerosing lesion, atypical ductal or lobular hyperplasia, flat epithelial atypia, intraductal papilloma, or lobular carcinoma in-situ). A total of 56.5% were White, 24.7% Asian, and 17.1% other races. A total of 32.5% identified as Hispanic. The mean breast cancer risk score using the Tyrer-Cuzick model was 11.9 ± 7.0. In multivariable analysis, with every one unit increase in AL, the probability of high-risk pathology increased by 37% (odds ratio, 1.37; 95% confidence interval, 1.03, 1.81; p = 0.03). No significant association was seen between high-risk pathology and age, ethnicity, breast cancer risk, or area deprivation index. Conclusion: Our findings support that increased AL, a biological marker of stress, is associated with high-risk pathology among patients with false-positive breast biopsy results.

Understanding Benign Breast Disease and Subsequent Breast Cancer in Hispanic White Females: A Step Closer to Evidence-Based Management.

Although Hispanic White (HW) females have a lower incidence of breast cancer than non-Hispanic White (NHW) females, breast cancer risk is unclear for HW females after benign breast disease (BBD). We compared BBD characteristics and subsequent breast cancer risk among HW and NHW females in New Mexico using a population-based collection of benign breast biopsies (1996-2007). BBD was categorized as nonproliferative disease (NPD), proliferative disease without atypia (PDWA), or atypical hyperplasia (AH). Breast cancer risk was assessed as absolute risk (AR) using cumulative incidence and RR by comparing the number of breast cancer events in BBDs to non-BBD. This study included 3,684 HW and 6,587 NHW females with BBD. HW females had similar proportions of NPD (58.6% vs. 54.3%), PDWA (21.4% vs. 23.5%), and AH (3.6% vs. 3.3%) as NHW females. Breast cancer risk among all females with BBD was higher than population-based expected rates (RR, 1.87) and was similar for HW and NHW subgroups (RR = 1.99 vs. 1.84). As expected, breast cancer risk increased with increasing BBD severity, both overall [RR, 1.81 (NPD), 1.85 (PDWA), and 3.10 (AH)] and in the HW and NHW subgroups. Adjusted AR of breast cancer at 5 years also increased with the severity of BBD (HW vs. NHW; NPD: 1.4% vs. 2.1%; PDWA: 1.5% vs. 2.7%; AH: 6% vs. 4.8%). We found similar breast cancer RRs and ARs in HW and NHW. Risk counseling should ensure that HW females receive breast cancer clinical management warranted by their similar absolute risks. The present population-based provides evidence for the clinical management of HW females with BBD for the prevention of breast cancer.

Associations of stem cell markers CD44, CD24 and ALDH1A1 with mammographic breast density in women with benign breast biopsies.

We examined associations of CD44, CD24 and ALDH1A1 breast stem cell markers with mammographic breast density (MBD), a well-established breast cancer (BCa) risk factor. We included 218 cancer-free women with biopsy-confirmed benign breast disease within the Nurses' Health Study (NHS) and NHSII. The data on BCa risk factors were obtained from biennial questionnaires. Immunohistochemistry (IHC) was done on tissue microarrays. For each core, the IHC expression was assessed using a semi-automated platform and expressed as percent of positively stained cells for each marker out of the total cell count. MBD was assessed with computer-assisted techniques. Generalised linear regression was used to examine the associations of each marker with square root-transformed percent density (PD), absolute dense and non-dense areas (NDA), adjusted for BCa risk factors. Stromal CD44 and ALDH1A1 expression was positively associated with PD (≥ 10% vs. <10% β = 0.56, 95% confidence interval [CI] [0.06; 1.07] and β = 0.81 [0.27; 1.34], respectively) and inversely associated with NDA (β per 10% increase = -0.17 [-0.34; -0.01] and β for ≥10% vs. <10% = -1.17 [-2.07; -0.28], respectively). Epithelial CD24 expression was inversely associated with PD (β per 10% increase = -0.14 [-0.28; -0.01]. Stromal and epithelial CD24 expression was positively associated with NDA (β per 10% increase = 0.35 [0.2 × 10-2; 0.70] and β per 10% increase = 0.34 [0.11; 0.57], respectively). Expression of stem cell markers is associated with MBD.

Multiplicity of benign breast disease lesions and breast cancer risk in African American women.

The risk of developing subsequent breast cancer is higher in women diagnosed with benign breast disease (BBD) but these studies were primarily performed in non-Hispanic white populations. Still, these estimates have been used to inform breast cancer risk models that are being used clinically across all racial and ethnic groups. Given the high breast cancer mortality rates among African American (AA) women, it is critical to study BBD in this population, to ensure the risk models that include this information perform adequately. This study utilized data from AA women who underwent benign breast biopsies at a hospital served by the University Pathology Group in Detroit, Michigan, from 1998 to 2010. Patients were followed for subsequent breast cancers through the population-based Metropolitan Detroit Cancer Surveillance System (MDCSS). BBD lesion scores were assigned to represent the severity or extent of benign breast lesions, with higher scores indicating a greater number of distinct lesion types. Of 3,461 eligible AA women with BBD in the cohort, 6.88% (n=238) subsequently developed breast cancer. Examined individually, six of the eleven lesions (apocrine metaplasia, ductal hyperplasia, lobular hyperplasia, intraductal papilloma, sclerosing adenosis, columnar alterations and radial scars) were significantly associated with increased risk of breast cancer after adjustment for age and year of biopsy and were further considered in multiple lesion models. For every different type of benign breast lesion, subsequent risk of breast cancer increased by 25% (RR=1.25, 95% CI: 1.10, 1.42) after adjustment for age at biopsy and proliferative versus non-proliferative disease. In summary, this study affirms the increased breast cancer risk in AA women with BBD, particularly in those with multiple lesions. These findings have implications for the management of breast cancer risk in millions of women affected by BBD, a high risk group that could benefit from personalized surveillance and risk reduction strategies.

Associations of Early-Life and Adult Anthropometric Measures with the Expression of Stem Cell Markers CD44, CD24, and ALDH1A1 in Women with Benign Breast Biopsies.

According to the stem cell hypothesis, breast carcinogenesis may be related to the breast stem cell pool size. However, little is known about associations of breast cancer risk factors, such as anthropometric measures, with the expression of stem cell markers in noncancerous breast tissue. The analysis included 414 women with biopsy-confirmed benign breast disease in the Nurses' Health Study and Nurses' Health Study II. Birthweight, weight at age 18, current weight, and current height were reported via self-administered questionnaires. IHC staining of stem cell markers (CD44, CD24, and aldehyde dehydrogenase family 1 member A1) in histopathologically normal epithelial and stromal breast tissue was quantified using an automated computational image analysis system. Linear regression was used to examine the associations of early-life and adult anthropometric measures with log-transformed stem cell marker expression, adjusting for potential confounders. Birthweight [≥10.0 vs. <5.5 lbs: β (95% confidence interval) = 4.29 (1.02, 7.56); P trend = 0.001 in the stroma] and adult height [≥67.0 vs. <63.0 inch: 0.86 (0.14, 1.58); P trend = 0.02 in the epithelium and stroma combined] were positively associated with CD44 expression. Childhood body fatness was inversely associated (P trend = 0.03) whereas adult height was positively associated with CD24 expression in combined stroma and epithelium (P trend = 0.03). Our data suggest that anthropometric measures, such as birthweight, adult height, and childhood body fatness, may be associated with the stem cell expression among women with benign breast disease. Anthropometric measures, such as birthweight, height, and childhood body fatness, may have long-term impacts on stem cell population in the breast.

Abstract 4867: Longitudinal latent class analysis to further understand trajectory of density over time and risk of breast cancer

Abstract Background: It is clinically important to refine strategies to manage women with dense breasts as they represent approximately 50% of all women screened. Change in breast density is related to risk of breast cancer.1 We also must understand this change in density over time in women with dense and non-dense breasts. While population level data have been reported to estimate decrease in density with age, this has largely used digitized film images.2 Expanding use of digital mammography and repeated screening generates a large library of images for each woman, offering the potential to use more of the image data. Methods: We use longitudinal latent class analysis to cluster women and estimate their change in density over time. To evaluate the groups of women with different patterns of change in density we fit latent class models to our previously published data.1 This includes 289 pathology confirmed cases of breast cancer and 658 controls among women followed from November 3, 2008 to October 31, 2020. Results: Among women with dense breasts, there are 107 who developed breast cancer during follow-up and 267 control women who remained free from breast cancer. In the women without dense breasts, 173 cases and 383 controls were evaluated and showed similar age and BMI within the controls as seen in women with dense breasts. Prevalence of family history and history of benign breast biopsy did not differ between the two groups. We observe this latent class and trajectory of density phenomenal separately for dense and non-dense groups in our data. We show that the data define 2 classes, those who have decrease in density over time and those who have increase over time. The odds ratio (OR) for cancer comparing decline vs. incline is 4.9 in women with dense breasts (BI-RADS C, D) and 6.17 on women with non-dense breasts (BI-RADS A, B). Discussion: To refine our understanding of patterns of change in breast density over time in relation to breast cancer risk we fit latent class models. Longitudinal change matters as reflected in the 2-class model. This is independent of starting density and confirms that a one-time measure of density is not enough to define level of risk for subsequent breast cancer. Further work is needed to better define the drivers and inhibitors of decline in breast density over time given this change over time as women age is a universal phenomenon.2 1. Jiang S, Bennett DL, Rosner BA, Colditz GA. Longitudinal Analysis of Change in Mammographic Density in Each Breast and Its Association With Breast Cancer Risk. JAMA Oncol 2023;9(6):808-814. (In English). DOI: 10.1001/jamaoncol.2023.0434. 2. Burton A, Maskarinec G, Perez-Gomez B, et al. Mammographic density and ageing: A collaborative pooled analysis of cross-sectional data from 22 countries worldwide. PLoS Med 2017;14(6):e1002335. DOI: 10.1371/journal.pmed.1002335. Citation Format: Graham A. Colditz, Debbie L. Bennett, Shu Jiang. Longitudinal latent class analysis to further understand trajectory of density over time and risk of breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4867.

Associations of reproductive breast cancer risk factors with expression of stem cell markers in benign breast tissue.

We investigated the associations of reproductive factors known to influence breast cancer risk with the expression of breast stem cell markers CD44, CD24, and ALDH1A1 in benign breast biopsy samples. We included 439 cancer-free women with biopsy-confirmed benign breast disease within the Nurses' Health Study (NHS) and NHSII. The data on reproductive and other breast cancer risk factors were obtained from biennial questionnaires. Immunohistochemistry (IHC) was performed on tissue microarrays. For each core, the IHC expression was assessed using a semi-automated platform and expressed as % of cells that stained positive for a specific marker out of the total cell count. Generalized linear regression was used to examine the associations of reproductive factors with a log-transformed expression of each marker (in epithelium and stroma), adjusted for other breast cancer risk factors. In multivariate analysis, the time between menarche and age at first birth was inversely associated with CD44 in epithelium (β per 5 years = -0.38, 95% CI -0.69; -0.06). Age at first birth and the time between menarche and age at first birth were inversely associated with ALDH1A1 (stroma: β per 5 years = -0.43, 95% CI -0.76; -0.10 and β = -0.47, 95% CI -0.79; -0.15, respectively; epithelium: β = -0.15, 95% CI -0.30; -0.01 and β = -0.17, 95% CI -0.30; -0.03, respectively). Time since last pregnancy was inversely associated with stromal ALDH1A1 (β per 5 years = -0.55, 95% CI -0.98; -0.11). No associations were found for CD24. The observed associations were similar in premenopausal women. In postmenopausal women, lifetime duration of breastfeeding was inversely associated with stromal ALDH1A1 expression (β for ≥24 vs. 0 to <1 months = -2.24, 95% CI 3.96; -0.51, p-trend = 0.01). Early-life reproductive factors may influence CD44 and ALDH1A1 expression in benign breast tissue.

Population Attributable Risk of Advanced-Stage Breast Cancer by Race and Ethnicity

Advanced-stage breast cancer rates vary by race and ethnicity, with Black women having a 2-fold higher rate than White women among regular screeners. Clinical risk factors that explain a large proportion of advanced breast cancers by race and ethnicity are unknown. To evaluate the population attributable risk proportions (PARPs) for advanced-stage breast cancer (prognostic pathologic stage IIA or higher) associated with clinical risk factors among routinely screened premenopausal and postmenopausal women by race and ethnicity. This cohort study used data collected prospectively from Breast Cancer Surveillance Consortium community-based breast imaging facilities from January 2005 to June 2018. Participants were women aged 40 to 74 years undergoing 3 331 740 annual (prior screening within 11-18 months) or biennial (prior screening within 19-30 months) screening mammograms associated with 1815 advanced breast cancers diagnosed within 2 years of screening examinations. Data analysis was performed from September 2022 to August 2023. Heterogeneously or extremely dense breasts, first-degree family history of breast cancer, overweight/obesity (body mass index >25.0), history of benign breast biopsy, and screening interval (biennial vs annual) stratified by menopausal status and race and ethnicity (Asian or Pacific Islander, Black, Hispanic/Latinx, White, other/multiracial). PARPs for advanced breast cancer. Among 904 615 women, median (IQR) age was 57 (50-64) years. Of the 3 331 740 annual or biennial screening mammograms, 10.8% were for Asian or Pacific Islander women; 9.5% were for Black women; 5.3% were for Hispanic/Latinx women; 72.0% were for White women; and 2.0% were for women of other races and ethnicities, including those who were Alaska Native, American Indian, 2 or more reported races, or other. Body mass index PARPs were larger for postmenopausal vs premenopausal women (30% vs 22%) and highest for postmenopausal Black (38.6%; 95% CI, 32.0%-44.8%) and Hispanic/Latinx women (31.8%; 95% CI, 25.3%-38.0%) and premenopausal Black women (30.3%; 95% CI, 17.7%-42.0%), with overall prevalence of having overweight/obesity highest in premenopausal Black (84.4%) and postmenopausal Black (85.1%) and Hispanic/Latinx women (72.4%). Breast density PARPs were larger for premenopausal vs postmenopausal women (37% vs 24%, respectively) and highest among premenopausal Asian or Pacific Islander (46.6%; 95% CI, 37.9%-54.4%) and White women (39.8%; 95% CI, 31.7%-47.3%) whose prevalence of dense breasts was high (62%-79%). For premenopausal and postmenopausal women, PARPs were small for family history of breast cancer (5%-8%), history of breast biopsy (7%-12%), and screening interval (2.1%-2.3%). In this cohort study among routinely screened women, the proportion of advanced breast cancers attributed to biennial vs annual screening was small. To reduce the number of advanced breast cancer diagnoses, primary prevention should focus on interventions that shift patients with overweight and obesity to normal weight.

Extending the Breast Cancer Surveillance Consortium Model of Invasive Breast Cancer.

We extended the Breast Cancer Surveillance Consortium (BCSC) version 2 (v2) model of invasive breast cancer risk to include BMI, extended family history of breast cancer, and age at first live birth (version 3 [v3]) to better inform appropriate breast cancer prevention therapies and risk-based screening. We used Cox proportional hazards regression to estimate the age- and race- and ethnicity-specific relative hazards for family history of breast cancer, breast density, history of benign breast biopsy, BMI, and age at first live birth for invasive breast cancer in the BCSC cohort. We evaluated calibration using the ratio of expected-to-observed (E/O) invasive breast cancers in the cohort and discrimination using the area under the receiver operating characteristic curve (AUROC). We analyzed data from 1,455,493 women age 35-79 years without a history of breast cancer. During a mean follow-up of 7.3 years, 30,266 women were diagnosed with invasive breast cancer. The BCSC v3 model had an E/O of 1.03 (95% CI, 1.01 to 1.04) and an AUROC of 0.646 for 5-year risk. Compared with the v2 model, discrimination of the v3 model improved most in Asian, White, and Black women. Among women with a BMI of 30.0-34.9 kg/m2, the true-positive rate in women with an estimated 5-year risk of 3% or higher increased from 10.0% (v2) to 19.8% (v3) and the improvement was greater among women with a BMI of ≥35 kg/m2 (7.6%-19.8%). The BCSC v3 model updates an already well-calibrated and validated breast cancer risk assessment tool to include additional important risk factors. The inclusion of BMI was associated with the largest improvement in estimated risk for individual women.

Label-free multimodal electro-thermo-mechanical (ETM) phenotyping as a novel biomarker to differentiate between normal, benign, and cancerous breast biopsy tissues.

Technologies for quick and label-free diagnosis of malignancies from breast tissues have the potential to be a significant adjunct to routine diagnostics. The biophysical phenotypes of breast tissues, such as its electrical, thermal, and mechanical properties (ETM), have the potential to serve as novel markers to differentiate between normal, benign, and malignant tissue. We report a system-of-biochips (SoB) integrated into a semi-automated mechatronic system that can characterize breast biopsy tissues using electro-thermo-mechanical sensing. The SoB, fabricated on silicon using microfabrication techniques, can measure the electrical impedance (Z), thermal conductivity (K), mechanical stiffness (k), and viscoelastic stress relaxation (%R) of the samples. The key sensing elements of the biochips include interdigitated electrodes, resistance temperature detectors, microheaters, and a micromachined diaphragm with piezoresistive bridges. Multi-modal ETM measurements performed on formalin-fixed tumour and adjacent normal breast biopsy samples from N = 14 subjects were able to differentiate between invasive ductal carcinoma (malignant), fibroadenoma (benign), and adjacent normal (healthy) tissues with a root mean square error of 0.2419 using a Gaussian process classifier. Carcinoma tissues were observed to have the highest mean impedance (110018.8 ± 20293.8 Ω) and stiffness (0.076 ± 0.009 kNm-1) and the lowest thermal conductivity (0.189 ± 0.019 Wm-1K-1) amongst the three groups, while the fibroadenoma samples had the highest percentage relaxation in normalized load (47.8 ± 5.12%). The work presents a novel strategy to characterize the multi-modal biophysical phenotype of breast biopsy tissues to aid in cancer diagnosis from small-sized tumour samples. The methodology envisions to supplement the existing technology gap in the analysis of breast tissue samples in the pathology laboratories to aid the diagnostic workflow.

259 Avoiding Face-to-Face Appointments Following Benign Breast Biopsies: Improving The Patient Experience Without Compromising Safety

Abstract Aim Minimising face to face (F2F) contact can reduce the costs of outpatient clinics and increase patient satisfaction. Patients undergoing biopsy for suspected benign disease need discussing at an MDT meeting as per national guidelines, however, the majority of these do not need further treatment. We aimed to assess the utility and safety of managing patients without a further F2F appointment following benign MDT discussion. Method A retrospective case-note review was performed on 100 patients discussed at the benign biopsy MDT between June and August 2020. Clinicopathological data was collected on presenting symptoms, histopathology, management, and subsequent requirement for F2F appointment. Results Median age was 43 years (range 25-88). Eighty-one patients (81%) presented with a lump or nipple discharge. The final diagnosis was normal in 22(22%) patients, a diagnosis of fibroadenoma in 35(35%), a B3 lesion in 8 (8%) patients and another benign diagnosis in the remaining 35(35%) patients. Sixteen (16%) patients required surgery or vacuum-assisted-Biopsy, 18(18%) required further clinical or radiology follow up and 66(66%) were reassured and discharged. Forty-three (43%) patients were informed of the MDT plan by letter and 42(42%) by telephone. There were no malignancies identified in any patients. Fourteen (14%) patients required a F2F appointment most commonly because of further clinical review, patient request or interpreter requirements. Conclusions The vast majority of patients undergoing benign biopsy can avoid a further F2F appointment, even if further biopsies or intervention is needed. This can reduce the burden on outpatient clinics whilst improving patient convenience.

Diagnostic accuracy of intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced (DCE) MRI to differentiate benign from malignant breast lesions: A systematic review and meta-analysis

PurposeMagnetic resonance imaging (MRI) can reduce the need for unnecessary invasive diagnostic tests by nearly half. In this meta-analysis, we investigated the diagnostic accuracy of intravoxel incoherent motion modeling (IVIM) and dynamic contrast-enhanced (DCE) MRI in differentiating benign from malignant breast lesions. MethodWe systematically searched PubMed, EMBASE, and Scopus. We included English articles reporting diagnostic accuracy for both sequences in differentiating benign from malignant breast lesions. Articles were assessed by quality assessment of diagnostic accuracy studies-2 (QUADAS-2) questionnaire. We used a bivariate effects model for standardized mean difference (SMD) analysis and diagnostic test accuracy analysis. ResultsTen studies with 537 patients and 707 (435 malignant and 272 benign) lesions were included. The D, f, Ktrans, and Kep mean values significantly differ between benign and malignant lesions. The pooled sensitivity (95 % confidence interval) and specificity were 86.2 % (77.9 %–91.7 %) and 70.3 % (56.5 %–81.1 %) for IVIM, and 93.8 % (85.3 %–97.5 %) and 68.1 % (52.7 %–80.4 %) for DCE, respectively. Combined IVIM and DCE depicted the highest area under the curve of 0.94, with a sensitivity and specificity of 91.8 % (82.8 %–96.3 %) and 87.6 % (73.8 %–94.7 %), respectively. ConclusionsCombined IVIM and DCE had the highest diagnostic accuracy, and multiparametric MRI may help reduce unnecessary benign breast biopsy.

Host, reproductive, and lifestyle factors in relation to quantitative histologic metrics of the normal breast

BackgroundEmerging data indicate that variations in quantitative epithelial and stromal tissue composition and their relative abundance in benign breast biopsies independently impact risk of future invasive breast cancer. To gain further insights into breast cancer etiopathogenesis, we investigated associations between epidemiological factors and quantitative tissue composition metrics of the normal breast.MethodsThe study participants were 4108 healthy women ages 18–75 years who voluntarily donated breast tissue to the US-based Susan G. Komen Tissue Bank (KTB; 2008–2019). Using high-accuracy machine learning algorithms, we quantified the percentage of epithelial, stromal, adipose, and fibroglandular tissue, as well as the proportion of fibroglandular tissue that is epithelium relative to stroma (i.e., epithelium-to-stroma proportion, ESP) on digitized hematoxylin and eosin (H&E)-stained normal breast biopsy specimens. Data on epidemiological factors were obtained from participants using a detailed questionnaire administered at the time of tissue donation. Associations between epidemiological factors and square root transformed tissue metrics were investigated using multivariable linear regression models.ResultsWith increasing age, the amount of stromal, epithelial, and fibroglandular tissue declined and adipose tissue increased, while that of ESP demonstrated a bimodal pattern. Several epidemiological factors were associated with individual tissue composition metrics, impacting ESP as a result. Compared with premenopausal women, postmenopausal women had lower ESP [β (95% Confidence Interval (CI)) = −0.28 (− 0.43, − 0.13); P < 0.001] with ESP peaks at 30–40 years and 60–70 years among pre- and postmenopausal women, respectively. Pregnancy [β (95%CI) vs nulligravid = 0.19 (0.08, 0.30); P < 0.001] and increasing number of live births (P-trend < 0.001) were positively associated with ESP, while breastfeeding was inversely associated with ESP [β (95%CI) vs no breastfeeding = −0.15 (− 0.29, − 0.01); P = 0.036]. A positive family history of breast cancer (FHBC) [β (95%CI) vs no FHBC = 0.14 (0.02–0.26); P = 0.02], being overweight or obese [β (95%CI) vs normal weight = 0.18 (0.06–0.30); P = 0.004 and 0.32 (0.21–0.44); P < 0.001, respectively], and Black race [β (95%CI) vs White = 0.12 (− 0.005, 0.25); P = 0.06] were positively associated with ESP.ConclusionOur findings revealed that cumulative exposure to etiological factors over the lifespan impacts normal breast tissue composition metrics, individually or jointly, to alter their dynamic equilibrium, with potential implications for breast cancer susceptibility and tumor etiologic heterogeneity.

Improving the patient journey by avoiding face-to-face appointments following benign breast biopsies

Improving the patient journey by avoiding face-to-face appointments following benign breast biopsies

Abstract 3587: High resolution microCT to analyze the 3D morphology of microcalcifications in benign breast disease and breast cancer biopsy tissues

Abstract Introduction: We used micro-computed tomography (microCT), a high-resolution imaging option, to detect and characterize microcalcifications (MCs) in three dimensions within pathology blocks of benign and malignant breast tissues. Methods: A set of 44 formalin-fixed, paraffin-embedded breast tissue blocks were assessed from n=22 women at two time points: benign breast biopsy and subsequent DCIS or DCIS with invasive disease breast cancer. Blocks were scanned using the Bruker Skyscan 1276 microCT at a resolution of 10 µm. SkyScan analysis CTAn software was utilized to prepare and analyze morphological parameters and multiple MCs contained within each block were averaged. Paired morphological parameters were compared between the benign and subsequent cancer samples within women using Wilcoxon signed-rank tests. Results: Median age of patients was 53 years (range 37-77 years) at initial benign biopsy and developed breast cancer at median of 5.6 years (range: 2.3-12.8 years) later. The initial benign biopsies were for proliferative disease without atypia in the majority (59%), while 23% had non-proliferative lesions and 18% atypical hyperplasia. The average structural model index was consistent with a near rod-like shape (median 2.99, range: 2.71-3.29). Paired comparisons between benign and cancer blocks showed that the average surface area of MCs was significantly higher in the cancer samples (p=0.0467), as was the average volume of MCs (p=0.0298) (Table 1). Conclusions: Preliminarily, we demonstrate that microCT of routinely prepared pathology blocks of breast tissues may be useful in characterizing the 3-D morphometry of MCs with suggestive differences in benign and cancer tissues. Given that MCs are a sentinel radiologic marker of DCIS but are common in benign breast disease, developing improved approaches for classifying MCs may have value in breast cancer screening and management. Table 1. Comparison of MC parameters in biopsy tissues (IQR = Interquartile Range). Benign sample from women who later developed breast cancer Breast cancer after prior benign sample Paired Differences (Cancer - Benign) Wilcoxon signed-rank p value (N=22) (N=22) (N=22) Number of Objects (Median (IQR)) 43.5 (14, 789) 69.5 (33, 289) -6 (-139, 67) 0.6830 Average Surface Area (mm2)(Median (IQR)) 0.0225 (0.0134, 0.0393) 0.0342 (0.0185, 0.0656) 0.0113 (-0.0027, 0.0322) 0.0467 Average Volume (mm3) (Median (IQR)) 0.0003 (0.0001, 0.0007) 0.0007 (0.0003, 0.0022) 0.0003 (0.000002, 0.0020) 0.0298 Average Surface Area/Volume (mm−1)(Median (IQR)) 214.92 (162.25, 328.39) 199.55 (151.89, 230.52) -20.85 (-86.05, 27.04) 0.1433 Average Structural Thickness (mm)(Median (IQR)) 0.0341(0.0196, 0.0446) 0.0395 (0.0336, 0.0505) 0.0074 (-0.0062, 0.0153) 0.1173 Average Structural Model Index (Median (IQR)) 2.9758 (2.8465, 3.1175) 3.0026 (2.9281, 3.0927) 0.0075 (-0.1073, 0.1381) 0.7656 Citation Format: Sarah E. Schrup, Thomas de Bel, Tanya Hoskin, Teresa Allers, Stacey Winham, Derek Radisky, Laura Pacheco-Spann, Lisa Seymour, Amy Degnim, Mark Sherman. High resolution microCT to analyze the 3D morphology of microcalcifications in benign breast disease and breast cancer biopsy tissues. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3587.

Associations of alcohol consumption with breast tissue composition

BackgroundWe investigated the associations of alcohol with percentage of epithelium, stroma, fibroglandular tissue (epithelium + stroma), and fat in benign breast biopsy samples.MethodsWe included 857 cancer-free women with biopsy-confirmed benign breast disease within the Nurses’ Health Study (NHS) and NHSII cohorts. Percentage of each tissue was measured on whole slide images using a deep-learning algorithm and then log-transformed. Alcohol consumption (recent and cumulative average) was assessed with semi-quantitative food frequency questionnaires. Regression estimates were adjusted for known breast cancer risk factors. All tests were 2-sided.ResultsAlcohol was inversely associated with % of stroma and fibroglandular tissue (recent ≥ 22 g/day vs. none: stroma: β = − 0.08, 95% Confidence Interval [CI] − 0.13; − 0.03; fibroglandular: β = − 0.08, 95% CI − 0.13; − 0.04; cumulative ≥ 22 g/day vs. none: stroma: β = − 0.08, 95% CI − 0.13; − 0.02; fibroglandular: β = − 0.09, 95% CI − 0.14; − 0.04) and positively associated with fat % (recent ≥ 22 g/day vs. none: β = 0.30, 95% CI 0.03; 0.57; cumulative ≥ 22 g/day vs. none: β = 0.32, 95% CI 0.04; 0.61). In stratified analysis, alcohol consumption was not associated with tissue measures in premenopausal women. In postmenopausal women, cumulative alcohol use was inversely associated with % of stroma and fibroglandular tissue and positively associated with fat % (≥ 22 g/day vs. none: stroma: β = − 0.16, 95% CI − 0.28; − 0.07; fibroglandular: β = − 0.18, 95% CI − 0.28; − 0.07; fat: β = 0.61, 95% CI 0.01; 1.22), with similar results for recent alcohol use.ConclusionOur findings suggest that alcohol consumption is associated with smaller % of stroma and fibroglandular tissue and a greater % of fat in postmenopausal women. Future studies are warranted to confirm our findings and to elucidate the underlying biological mechanisms.

Cumulative 6-Year Risk of Screen-Detected Ductal Carcinoma In Situ by Screening Frequency

Detection of ductal carcinoma in situ (DCIS) by mammography screening is a controversial outcome with potential benefits and harms. The association of mammography screening interval and woman's risk factors with the likelihood of DCIS detection after multiple screening rounds is poorly understood. To develop a 6-year risk prediction model for screen-detected DCIS according to mammography screening interval and women's risk factors. This Breast Cancer Surveillance Consortium cohort study assessed women aged 40 to 74 years undergoing mammography screening (digital mammography or digital breast tomosynthesis) from January 1, 2005, to December 31, 2020, at breast imaging facilities within 6 geographically diverse registries of the consortium. Data were analyzed between February and June 2022. Screening interval (annual, biennial, or triennial), age, menopausal status, race and ethnicity, family history of breast cancer, benign breast biopsy history, breast density, body mass index, age at first birth, and false-positive mammography history. Screen-detected DCIS defined as a DCIS diagnosis within 12 months after a positive screening mammography result, with no concurrent invasive disease. A total of 916 931 women (median [IQR] age at baseline, 54 [46-62] years; 12% Asian, 9% Black, 5% Hispanic/Latina, 69% White, 2% other or multiple races, and 4% missing) met the eligibility criteria, with 3757 screen-detected DCIS diagnoses. Screening round-specific risk estimates from multivariable logistic regression were well calibrated (expected-observed ratio, 1.00; 95% CI, 0.97-1.03) with a cross-validated area under the receiver operating characteristic curve of 0.639 (95% CI, 0.630-0.648). Cumulative 6-year risk of screen-detected DCIS estimated from screening round-specific risk estimates, accounting for competing risks of death and invasive cancer, varied widely by all included risk factors. Cumulative 6-year screen-detected DCIS risk increased with age and shorter screening interval. Among women aged 40 to 49 years, the mean 6-year screen-detected DCIS risk was 0.30% (IQR, 0.21%-0.37%) for annual screening, 0.21% (IQR, 0.14%-0.26%) for biennial screening, and 0.17% (IQR, 0.12%-0.22%) for triennial screening. Among women aged 70 to 74 years, the mean cumulative risks were 0.58% (IQR, 0.41%-0.69%) after 6 annual screens, 0.40% (IQR, 0.28%-0.48%) for 3 biennial screens, and 0.33% (IQR, 0.23%-0.39%) after 2 triennial screens. In this cohort study, 6-year screen-detected DCIS risk was higher with annual screening compared with biennial or triennial screening intervals. Estimates from the prediction model, along with risk estimates of other screening benefits and harms, could help inform policy makers' discussions of screening strategies.

Linear Regression Modeling Based Scoring System to Reduce Benign Breast Biopsies Using Multi-parametric US with Color Doppler and SWE

To develop a simple ultrasound (US) based scoring system to reduce benign breast biopsies. Women with BI-RADS 4 or 5 breast lesions underwent shear-wave elastography (SWE) imaging before biopsy. Standard US and color Doppler US (CDUS) parameters were recorded, and the size ratio (SzR=longest/shortest diameter) was calculated. Measured/calculated SWE parameters were minimum (SWVMin) and maximum (SWVMax) shear velocity, velocity heterogeneity (SWVH=SWVMax-SWVMin), velocity ratio (SWVR=SWVMin/SWVMax), and normalized SWVR (SWVRn=(SWVMax-SWVMin)/SWVMin). Linear regression analysis was performed by converting continuous parameters into categorical corresponding equivalents using decision tree analyses. Linear regression models were fitted using stepwise regression analysis and optimal coefficients for the predictors in the models were determined. A scoring model was devised from the results and validated using a different data set from another center consisting of 187 cases with BI-RADS 3, 4, and 5 lesions. A total of 418 lesions (238 benign, 180 malignant) were analyzed. US and CDUS parameters exhibited poor (AUC=0.592-0.696), SWE parameters exhibited poor-good (AUC=0.607-0.816) diagnostic performance in benign/malignant discrimination. Linear regression models of US+CDUS and US+SWE parameters revealed an AUC of 0.819 and 0.882, respectively. The developed scoring system could have avoided biopsy in 37.8% of benign lesions while missing 1.1% of malignant lesions. The scoring system was validated with a 100% NPV rate with a specificity of 74.6%. The linear regression model using US+SWE parameters performed better than any single parameter alone. The developed scoring method could lead to a significant decrease in benign biopsies.

Safely reducing unnecessary benign breast biopsies by applying non-mass and DWI directional variance filters to ADC thresholding

BackgroundThresholding apparent diffusion coefficient (ADC) maps obtained from Diffusion-Weighted-Imaging (DWI) has been proposed for identifying benign lesions that can safely avoid biopsy. The presence of malignancies with high ADC values leads to high thresholds, limiting numbers of avoidable biopsies.PurposeWe evaluate two previously reported methods for identifying avoidable biopsies: using case-set dependent ADC thresholds that assure 100% sensitivity and using negative likelihood ratio (LR-) with a fixed ADC threshold of 1.50 × 10–3 mm2/s. We evaluated improvements in efficacy obtained by excluding non-mass lesions and lesions with anisotropic intra-lesion morphologic characteristics.Study typeProspective.Population55 adult females with dense breasts with 69 BI-RADS 4 or 5 lesions (38 malignant, 31 benign) identified on ultrasound and mammography and imaged with MRI prior to biopsy.Field strength/sequence1.5 T and 3.0 T. DWI.AssessmentAnalysis of DWI, including directional images was done on an ROI basis. ROIs were drawn on DWI images acquired prior to biopsy, referencing all available images including DCE, and mean ADC was measured. Anisotropy was quantified via variation in ADC values in the lesion core across directional DWI images.Statistical testsImprovement in specificity at 100% sensitivity was evaluated with exact McNemar test with 1-sided p-value < 0.05 indicating statistical significance.ResultsUsing ADC thresholding that assures 100% sensitivity, non-mass and directional variance filtering improved the percent of avoidable biopsies to 42% from baseline of 10% achieved with ADC thresholding alone. Using LR-, filtering improved outcome to 0.06 from baseline 0.25 with ADC thresholding alone. ADC thresholding showed a lower percentage of avoidable biopsies in our cohort than reported in prior studies. When ADC thresholding was supplemented with filtering, the percentage of avoidable biopsies exceeded those of prior studies.Data conclusionSupplementing ADC thresholding with filters excluding non-mass lesions and lesions with anisotropic characteristics on DWI can result in an increased number of avoidable biopsies.