Breast-Cancer Tumor Size, Overdiagnosis, and Mammography Screening Effectiveness

Gene Expression Assays to Tailor Adjuvant Endocrine Therapy for HR+/HER2- Breast Cancer

Adjuvant endocrine therapy (ET) represents the standard of care for almost all hormone receptor (HR)+/HER2- breast cancers, and different agents and durations are currently available. In this context, the tailoring and optimization of adjuvant endocrine treatment by reducing unnecessary toxic treatment while taking into account the biological heterogeneity of HR+/HER2- breast cancer represents a clinical priority. There is therefore a significant need for the integration of biological biomarkers in the choice of adjuvant ET beyond currently used clinicopathological characteristics. Several gene expression assays have been developed to identify patients with HR+/HER2- breast cancer who will not derive benefit from the addition of adjuvant chemotherapy. By enhancing risk stratification and predicting therapeutic response, genomic assays have also shown to be a promising tool for optimizing endocrine treatment decisions. In this study, we review evidence supporting the use of most common commercially available gene expression assays [Oncotype DX, MammaPrint, Breast Cancer Index (BCI), Prosigna, and EndoPredict] in tailoring adjuvant ET. Available data on the use of genomic tests to inform extended adjuvant treatment choice based on the risk of late relapse and on the estimated benefit of a prolonged ET are discussed. Moreover, preliminary evidence regarding the use of genomic assays to inform de-escalation of endocrine treatment, such as shorter durations or omission, for low-risk patients is reviewed. Overall, gene expression assays are emerging as potential tools to further personalize adjuvant treatment for patients with HR+/HER2- breast cancers.

Diagnostic value of contrast-enhanced ultrasound and shear-wave elastography for small breast nodules

Background

The study aims to evaluate the diagnostic efficacy of contrast-enhanced ultrasound (CEUS) and shear-wave elastography (SWE) in detecting small malignant breast nodules in an effort to inform further refinements of the Breast Imaging Reporting and Data System (BI-RADS) classification system.

Methods

This study retrospectively analyzed patients with breast nodules who underwent conventional ultrasound, CEUS, and SWE at Gongli Hospital from November 2015 to December 2019. The inclusion criteria were nodules ≤ 2 cm in diameter with pathological outcomes determined by biopsy, no prior treatments, and solid or predominantly solid nodules. The exclusion criteria included pregnancy or lactation and low-quality images. Imaging features were detailed and classified per BI-RADS. Diagnostic accuracy was assessed using receiver operating characteristic curves.

Results

The study included 302 patients with 305 breast nodules, 113 of which were malignant. The diagnostic accuracy was significantly improved by combining the BI-RADS classification with CEUS and SWE. The combined approach yielded a sensitivity of 88.5%, specificity of 87.0%, positive predictive value of 80.0%, negative predictive value of 92.8%, and accuracy of 87.5% with an area under the curve of 0.877. Notably, 55.8% of BI-RADS 4A nodules were downgraded to BI-RADS 3 and confirmed as benign after pathological examination, suggesting the potential to avoid unnecessary biopsies.

Conclusion

The integrated use of the BI-RADS classification, CEUS, and SWE enhances the accuracy of differentiating benign and malignant small breast nodule, potentially reducing the need for unnecessary biopsies.

Diagnostic Accuracy of Contrast-Enhanced Thoracic Photon-Counting Computed Tomography for Opportunistic Locoregional Staging of Breast Cancer Compared With Digital Mammography: A Prospective Trial

OBJECTIVE

Accurate locoregional staging is crucial for effective breast cancer treatment. Photon-counting computed tomography (PC-CT) is an emerging technology with high spatial resolution and the ability to depict uptake of contrast agents in tissues, making it a promising tool for breast cancer imaging. The aim of this study was to establish the feasibility of locoregional staging of breast cancer through contrast-enhanced thoracic PC-CT, assess its diagnostic performance, and compare it with that of digital mammography (DM).

MATERIALS AND METHODS

Patients with newly diagnosed breast cancer, DM, and indication of thoracic CT staging were prospectively enrolled in this clinical cohort study over a period of 6 months. Participants underwent contrast-enhanced thoracic PC-CT and breast magnetic resonance imaging in prone position. After blinding to patient data, 2 radiologists independently rated PC-CT and DM regarding the following 6 characteristics: (1) diameter of the largest mass lesion, (2) infiltration of cutis/pectoral muscle/thoracic wall, (3) number of mass lesions, (4) presence/absence of adjacent ductal carcinoma in situ (DCIS), (5) tumor conspicuity, and (6) diagnostic confidence. Reference standard was generated from consensus reading of magnetic resonance imaging combined with all histopathological/clinical data by an independent adjudication committee applying TNM eighth edition.

RESULTS

Among 32 enrolled female subjects (mean ± SD age, 59 ± 13.0 years), diagnostic accuracy for T-classification was higher for PC-CT compared with DM (0.94 vs 0.50, P < 0.01). Moreover, the correlation of the number of detected tumor masses with the reference standard was stronger for PC-CT than for DM (0.72 vs 0.50, P < 0.01). We observed that PC-CT significantly ( P < 0.04) outperformed DM regarding not only sensitivity (0.83 and 0.25, respectively) but also specificity (0.99 and 0.80, respectively) for adjacent DCIS. The κ values for interreader reliability were higher for PC-CT compared with DM (mean 0.88 vs 0.54, respectively; P = 0.01).

CONCLUSIONS

Photon-counting computed tomography outperformed DM in T-classification and provided higher diagnostic accuracy for the detection of adjacent DCIS. Therefore, opportunistic locoregional staging of breast cancer in contrast-enhanced thoracic PC-CT is feasible and could overcome limitations of DM with the potential to improve patient management.

Non-contrast Breast MR Imaging

Considering the high cost of dynamic contrast-enhanced MR imaging and various contraindications and health concerns related to administration of intravenous gadolinium-based contrast agents, there is emerging interest in non-contrast-enhanced breast MR imaging. Diffusion-weighted MR imaging (DWI) is a fast, unenhanced technique that has wide clinical applications in breast cancer detection, characterization, prognosis, and predicting treatment response. It also has the potential to serve as a non-contrast MR imaging screening method. Standardized protocols and interpretation strategies can help to enhance the clinical utility of breast DWI. A variety of other promising non-contrast MR imaging techniques are in development, but currently, DWI is closest to clinical integration, while others are still mostly used in the research setting.

Screening for Breast Cancer: Evidence Report and Systematic Review for the US Preventive Services Task Force

Importance

Breast cancer is a leading cause of cancer mortality for US women. Trials have established that screening mammography can reduce mortality risk, but optimal screening ages, intervals, and modalities for population screening guidelines remain unclear.

Objective

To review studies comparing different breast cancer screening strategies for the US Preventive Services Task Force.

Data Sources

MEDLINE, Cochrane Library through August 22, 2022; literature surveillance through March 2024.

Study Selection

English-language publications; randomized clinical trials and nonrandomized studies comparing screening strategies; expanded criteria for screening harms.

Data Extraction and Synthesis

Two reviewers independently assessed study eligibility and quality; data extracted from fair- and good-quality studies.

Main Outcomes and Measures

Mortality, morbidity, progression to advanced cancer, interval cancers, screening harms.

Results

Seven randomized clinical trials and 13 nonrandomized studies were included; 2 nonrandomized studies reported mortality outcomes. A nonrandomized trial emulation study estimated no mortality difference for screening beyond age 74 years (adjusted hazard ratio, 1.00 [95% CI, 0.83 to 1.19]). Advanced cancer detection did not differ following annual or biennial screening intervals in a nonrandomized study. Three trials compared digital breast tomosynthesis (DBT) mammography screening with digital mammography alone. With DBT, more invasive cancers were detected at the first screening round than with digital mammography, but there were no statistically significant differences in interval cancers (pooled relative risk, 0.87 [95% CI, 0.64-1.17]; 3 studies [n = 130 196]; I2 = 0%). Risk of advanced cancer (stage II or higher) at the subsequent screening round was not statistically significant for DBT vs digital mammography in the individual trials. Limited evidence from trials and nonrandomized studies suggested lower recall rates with DBT. An RCT randomizing individuals with dense breasts to invitations for supplemental screening with magnetic resonance imaging reported reduced interval cancer risk (relative risk, 0.47 [95% CI, 0.29-0.77]) and additional false-positive recalls and biopsy results with the intervention; no longer-term advanced breast cancer incidence or morbidity and mortality outcomes were available. One RCT and 1 nonrandomized study of supplemental ultrasound screening reported additional false-positives and no differences in interval cancers.

Conclusions and Relevance

Evidence comparing the effectiveness of different breast cancer screening strategies is inconclusive because key studies have not yet been completed and few studies have reported the stage shift or mortality outcomes necessary to assess relative benefits.

Effect of T Stages on the Choice of Axillary Evaluation Modality in Breast Cancer Patients With 1-2 Sentinel Lymph Node Metastases

INTRODUCTION

The survival benefit of axillary lymph node dissection (ALND), sentinel lymph node biopsy (SLNB) combined with radiation, and ALND combined with radiation remains unclear in breast cancer (BC) patients with 1-2 metastatic sentinel lymph nodes (SLNs). This study aims to rigorously evaluate the prognostic impact of these axillary evaluation modalities on BC patients with varying T-stages and to construct a survival prediction nomogram.

METHODS

Following screening for inclusion and exclusion criteria, data pertaining to BC patients were extracted from the SEER database. Overall survival (OS) and breast cancer-specific survival (BCSS) were assessed using Kaplan-Meier curves and Cox proportional hazards model among patients with different stages who underwent various axillary evaluation modalities. A nomogram was constructed to predict the probability of OS and BCSS.

RESULTS

A total of 20,283 patients were included, comprising 9626 who underwent breast-conserving surgery (BCS) and 10,657 who underwent mastectomy. In the T4 stage stratified analysis, both BCS and mastectomy groups exhibited superior OS and BCSS with ALND compared to SLNB combined with radiation. Further, ALND combined with radiation improved OS. However, for T1-3 stages, patients treated with ALND experienced similar or worse survival compared to those treated with SLNB combined with radiation. The calibration curve and C-index (0.746-0.794) of the nomogram demonstrated the efficacy of the survival prediction model.

CONCLUSION

In T1-3 BC patients with 1-2 metastatic SLNs, SLNB combined with radiation is a safe alternative to ALND. Conversely, for T4 patients, ALND combined with radiation may offer a preferable choice.

The Impact of Neoadjuvant Chemotherapy on Patients With T1N0M0 Triple-Negative and HER-2 Positive Breast Cancer: A Retrospective Analysis Based on the SEER Database

BACKGROUND

The utilization of neoadjuvant chemotherapy (NAC) originated in the treatment of locally advanced breast cancer (BC). Our study is designed to elucidate the effects of NAC on patients with T1N0M0 triple-negative and HER-2 positive BC.

METHODS

This study involved the selection of 10,614 patients diagnosed with T1N0M0 triple-negative and HER-2 positive breast cancer (BC) from the surveillance, epidemiology, and end results (SEER) database. To ascertain the impact of neoadjuvant chemotherapy (NAC) on T1a, T1b, and T1c N0M0 BC, we conducted multivariate Cox regression analyses. Similarly, we performed multivariate Cox regression analyses to compare the effects of neoadjuvant chemotherapy against adjuvant chemotherapy on T1N0M0 BC. The Kaplan-Meier method was employed to delineate survival curves for different molecular subtypes and clinical stages.

RESULTS

The data results from the SEER database reveal a significant enhancement of overall survival (OS) in T1c BC patients as a result of NAC. For T1b BC patients, NAC does not present any significant effect. Contrarily, NAC seems to adversely impact the OS of T1a triple-negative BC patients. However, the prognosis comparison between neoadjuvant and adjuvant chemotherapy for T1N0M0 breast cancer did not show any significant difference, with the exception of T1a triple-negative BC.

CONCLUSIONS

Patients with T1cN0M0 triple-negative and HER-2 positive BC may derive OS benefits from NAC. Additionally, NAC could be detrimental to T1a triple-negative BC.

Surgical marker navigation system in breast conserving surgery and excision of non-palpable lesions: first Spanish single-center experience

BACKGROUND

Due to the establishment of screening mammography for breast cancer detection, the number of non-palpable lesions has increased. Thus, an optimal localization system is mandatory for the excision of non-palpable breast tumors.

OBJECTIVE

The aim of the study is to report the feasibility Surgical Marker Navigation (SMN) system Sirius Pintuition® for the excision of non-palpable breast tumors and non-palpable axillary lymph nodes.

METHODS

A retrospective observational study of patients undergoing breast-conserving surgery and lymph node excision guided by SMN between December 2022 and May 2023 was performed.

RESULTS

A total of 84 patients underwent excision of non-palpable breast tumors (77; 91.7%) or non-palpable axillary lymph-nodes (7; 8.3%) using SMN. In total, 94 markers were placed, in 74 patients (88.1%) only one marker was placed, whereas in 10 patients (11.9%) two markers were placed to correctly localize the lesion in the operating room. Most markers were placed using ultrasonographic guidance (69; 82.1%). Seventy-seven patients underwent breast-conserving surgery (91.7%) and 7 (8.3%) lymph node excision. In 10 cases (11.9%), the marker was accidentally displaced during surgery due to the use of magnetized instruments, although the specimen could be removed. In sum, all the markers were removed from the patients, although the marker retrieval rate, as we defined it (percentage of patients in whom the initial excised specimen contained the marker divided by the total number of patients), was 88.1%.

CONCLUSION

The use of Sirius Pintuition® SMN for non-palpable breast tumors and non-palpable lymph nodes is feasible, with a retrieval rate of 88.1%.

Learning interpretable causal networks from very large datasets, application to 400,000 medical records of breast cancer patients

Discovering causal effects is at the core of scientific investigation but remains challenging when only observational data are available. In practice, causal networks are difficult to learn and interpret, and limited to relatively small datasets. We report a more reliable and scalable causal discovery method (iMIIC), based on a general mutual information supremum principle, which greatly improves the precision of inferred causal relations while distinguishing genuine causes from putative and latent causal effects. We showcase iMIIC on synthetic and real-world healthcare data from 396,179 breast cancer patients from the US Surveillance, Epidemiology, and End Results program. More than 90% of predicted causal effects appear correct, while the remaining unexpected direct and indirect causal effects can be interpreted in terms of diagnostic procedures, therapeutic timing, patient preference or socio-economic disparity. iMIIC's unique capabilities open up new avenues to discover reliable and interpretable causal networks across a range of research fields.

A Review of Artificial Intelligence in Breast Imaging

With the increasing dominance of artificial intelligence (AI) techniques, the important prospects for their application have extended to various medical fields, including domains such as in vitro diagnosis, intelligent rehabilitation, medical imaging, and prognosis. Breast cancer is a common malignancy that critically affects women's physical and mental health. Early breast cancer screening-through mammography, ultrasound, or magnetic resonance imaging (MRI)-can substantially improve the prognosis for breast cancer patients. AI applications have shown excellent performance in various image recognition tasks, and their use in breast cancer screening has been explored in numerous studies. This paper introduces relevant AI techniques and their applications in the field of medical imaging of the breast (mammography and ultrasound), specifically in terms of identifying, segmenting, and classifying lesions; assessing breast cancer risk; and improving image quality. Focusing on medical imaging for breast cancer, this paper also reviews related challenges and prospects for AI.

Minimally invasive treatment of early, good prognosis breast cancer-is this feasible?

Breast cancer screening programmes frequently detect early, good prognosis breast cancers with significant treatment burden for patients, and associated health-cost implications. Emerging evidence suggests a role for minimally invasive techniques in the management of these patients enabling many women to avoid surgical intervention. Minimally invasive techniques include vacuum-assisted excision, cryoablation, and radiofrequency ablation. We review published evidence in relation to the risks and benefits of each technique and discuss ongoing trials. Data to date are promising, and we predict a trend towards minimally invasive treatment for early, good-prognosis breast cancer as technical skills, suitability criteria, and follow-up protocols are established.

Nonlinear progression across the occult transition establishes cancer lethality

Cancer screening is based upon a linear model of growth and invasion. Yet, early dissemination during the lengthy pre-diagnostic phase suggests that nonlinearity in growth can also occur. Therefore, we quantitatively traced the invisible and visible phases of tumorigenesis in the mammary gland for more than two-thousand tumors. Dynamic mathematical models of the invisible phase revealed an occult checkpoint resulting in nonlinear progression of transformed field cells. We found that expansile fields have increased dwell time at the occult checkpoint resulting in a large reservoir of image detectable precursors prior to invasion. In contrast, slowly proliferating lesions disseminate early and then transition rapidly through an occult checkpoint in a process we term nascent lethality. Our data illustrate how nonlinear growth across an occult checkpoint can account for a paradoxical increase in early-stage cancer detection without a dramatic reduction in metastatic burden.

Highlights

Growth during the invisible phase of tumorigenesis is a nonlinear processField size and field growth rate are uncoupled from metastatic potentialOccult transition rates vary by genotypeNascent lethal lesions are currently undetectable.

High-risk and silent clonal hematopoietic genotypes in patients with nonhematologic cancer

ABSTRACT

Clonal hematopoiesis (CH) identified by somatic gene variants with variant allele fraction (VAF) ≥ 2% is associated with an increased risk of hematologic malignancy. However, CH defined by a broader set of genotypes and lower VAFs is ubiquitous in older individuals. To improve our understanding of the relationship between CH genotype and risk of hematologic malignancy, we analyzed data from 42 714 patients who underwent blood sequencing as a normal comparator for nonhematologic tumor testing using a large cancer-related gene panel. We cataloged hematologic malignancies in this cohort using natural language processing and manual curation of medical records. We found that some CH genotypes including JAK2, RUNX1, and XPO1 variants were associated with high hematologic malignancy risk. Chronic disease was predicted better than acute disease suggesting the influence of length bias. To better understand the implications of hematopoietic clonality independent of mutational function, we evaluated a set of silent synonymous and noncoding mutations. We found that silent CH, particularly when multiple variants were present or VAF was high, was associated with increased risk of hematologic malignancy. We tracked expansion of CH mutations in 26 hematologic malignancies sequenced with the same platform. JAK2 and TP53 VAF consistently expanded at disease onset, whereas DNMT3A and silent CH VAFs mostly decreased. These data inform the clinical and biological interpretation of CH in the context of nonhematologic cancer.

Effect of monthly reminders by telephone message on women's beliefs and practice behaviours regarding breast self-examination: A randomized controlled study

AIMS

This study was conducted to examine the effect of monthly telephone message reminders after training on women's beliefs and practice behaviours regarding breast self-examination.

METHODS

This randomized controlled study was conducted with 83 women aged 20-69 years living in Turkey between September 2021 and July 2022. Women were randomly assigned (1:1) to the intervention (n = 41) or control group (n = 42), both groups received online breast self-examination training, and the intervention group received monthly reminders on their mobile phones for 3 months. Participants completed the Champion's Health Belief Model Scale and breast self-examination practice evaluation form at baseline and 3 months after intervention.

RESULTS

After the intervention, the mean scores of the benefits and self-efficacy subscales of Champion's Health Belief Model Scales were significantly higher in the intervention group compared to the control group, and the mean score of barriers was lower. The rate of performing breast self-exam regularly and at the appropriate time was higher in the intervention group. The rate of forgetting to perform breast self-examination was higher in control group.

CONCLUSION

A monthly reminder message may be recommended to increase women's belief in breast self-examination and increase regular practice.

The effects of contemporary treatment of DCIS on the risk of developing an ipsilateral invasive Breast cancer (iIBC) in the Dutch population

PURPOSE

To assess the effects of contemporary treatment of ductal carcinoma in situ (DCIS) on the risk of developing an ipsilateral invasive breast cancer (iIBC) in the Dutch female population.

METHODS

Clinical data was obtained from the Netherlands Cancer Registry (NCR), a nationwide registry of all primary malignancies in the Netherlands integrated with the data from PALGA, the Dutch nationwide network and registry of histo- and cytopathology in the Netherlands, on all women in the Netherlands treated for primary DCIS from 2005 to 2015, resulting in a population-based cohort of 14.419 women. Cumulative iIBC incidence was assessed and associations of DCIS treatment type with subsequent iIBC risk were evaluated by multivariable Cox regression analyses.

RESULTS

Ten years after DCIS diagnosis, the cumulative incidence of iIBC was 3.1% (95% CI: 2.6-3.5%) in patients treated by breast conserving surgery (BCS) plus radiotherapy (RT), 7.1% (95% CI: 5.5-9.1) in patients treated by BCS alone, and 1.6% (95% CI: 1.3-2.1) in patients treated by mastectomy. BCS was associated with a significantly higher risk for iIBC compared to BCS + RT during the first 5 years after treatment (HR 2.80, 95% CI: 1.91-4.10%). After 5 years of follow-up, the iIBC risk declined in the BCS alone group but remained higher than the iIBC risk in the BCS + RT group (HR 1.73, 95% CI: 1.15-2.61).

CONCLUSIONS

Although absolute risks of iIBC were low in patients treated for DCIS with either BCS or BCS + RT, risks remained higher in the BCS alone group compared to patients treated with BCS + RT for at least 10 years after DCIS diagnosis.

Beyond a decade: a comparative study of 15-year survival rates in screen-detected vs. symptomatic breast cancer patients in Hungary

BACKGROUND

Breast cancer is the leading cancer in women globally. Despite decreasing mortality rates, largely due to early detection and modern treatment, the effectiveness of screening on long-term survival outcomes remains unclear.

AIMS

This study evaluates the 15-year survival outcomes of a national breast cancer screening program initiated in Hungary in 2002.

METHODS

Using a prospectively maintained patient database, the study included individuals from the first 6 years of the program who underwent surgery for histologically confirmed breast cancer and had available follow-up information. Patients were categorized based on the method of breast cancer detection into two groups: those diagnosed during or 2 years after the population-based screening exam (Group A), and those who self-detected or sought medical attention for symptoms (Group B).

RESULTS

Of the 309 patients who underwent breast cancer surgery, 208 were screen-detected (Group A) and 101 were symptomatic (Group B). The 15-year overall survival was 75.0% for Group A and 76.2% for Group B (p = 0.927). The 15-year disease-specific survival was 85.6% and 81.2% (p = 0.249), respectively. A statistically not significant positive trend in disease-free survival was observed in Group A (81.7% vs. 75.2%; p = 0.144).

CONCLUSIONS

The study underscores the importance of extended follow-up periods in evaluating the outcomes of breast cancer screening programs. While the screening program may not significantly enhance overall survival rates, it has demonstrated a reduction in the mastectomy rate and could potentially extend periods of disease-free survival. These findings contribute to the ongoing discourse about the long-term benefits of breast cancer screening programs.

The prognostic potential of mammographic growth rate of invasive breast cancer in the Nijmegen breast cancer screening cohort

OBJECTIVES

Insight into the aggressiveness of potential breast cancers found in screening may optimize recall decisions. Specific growth rate (SGR), measured on mammograms, may provide valuable prognostic information. This study addresses the association of SGR with prognostic factors and overall survival in patients with invasive carcinoma of no special type (NST) from a screened population.

METHODS

In this historic cohort study, 293 women with NST were identified from all participants in the Nijmegen screening program (2003-2007). Information on clinicopathological factors was retrieved from patient files and follow-up on vital status through municipalities. On consecutive mammograms, tumor volumes were estimated. After comparing five growth functions, SGR was calculated using the best-fitting function. Regression and multivariable survival analyses described associations between SGR and prognostic factors as well as overall survival.

RESULTS

Each one standard deviation increase in SGR was associated with an increase in the Nottingham prognostic index by 0.34 [95% confidence interval (CI): 0.21-0.46]. Each one standard deviation increase in SGR increased the odds of a tumor with an unfavorable subtype (based on histologic grade and hormone receptors; odds ratio 2.14 [95% CI: 1.45-3.15]) and increased the odds of diagnosis as an interval cancer (versus screen-detected; odds ratio 1.57 [95% CI: 1.20-2.06]). After a median of 12.4 years of follow-up, 78 deaths occurred. SGR was not associated with overall survival (hazard ratio 1.12 [95% CI: 0.87-1.43]).

CONCLUSIONS

SGR may indicate prognostically relevant differences in tumor aggressiveness if serial mammograms are available. A potential association with cause-specific survival could not be determined and is of interest for future research.

Harms and benefits of mammographic screening for breast cancer in Brazil

INTRODUCTION

In the absence of evidence on the effect of mammographic screening on overall mortality, comparing the number of deaths avoided with the number of deaths caused by screening would be ideal, but the only existing models of this type adopt a very narrow definition of harms. The objective of the present study was to estimate the number of deaths prevented and induced by various mammography screening protocols in Brazil.

METHODS

A simulation study of cohorts of Brazilian women screened, considering various age groups and screening interval protocols, was performed based on life tables. The number of deaths avoided and caused by screening was estimated, as was the absolute risk reduction, the number needed to invite for screening-NNS, the net benefit of screening, and the ratio of "lives saved" to "lives lost". Nine possible combinations of balances between benefits and harms were performed for each protocol, in addition to other sensitivity analyses.

RESULTS AND CONCLUSIONS

The most efficient protocol was biennial screening from 60 to 69 years of age, with almost three times more deaths avoided than biennial screening from 50 to 59 years of age, with a similar number of deaths avoided by biennial screening from 50 to 69 years of age and with the greatest net benefit. Compared with the best scenario of annual screening from 40 to 49 years of age, the NNS of the protocol with biennial screening from 60 to 69 years of age was three-fold lower. Even in its best scenario, the addition of annual screening from 40 to 49 years of age to biennial screening from 50 to 69 years of age results in a decreased net benefit. However, even in the 50-69 year age group, the estimated reduction in breast cancer mortality for Brazil was half that estimated for the United Kingdom.

The effectiveness of educational intervention based on the Health Action Model (HAM) in improving breast cancer screening behaviors

INTRODUCTION

Breast cancer disease is known as the most common cancer among women. Lack of knowledge and awareness is a leading cause of breast cancer, and since nearly all women are increasingly susceptible to this disease, training screening behaviors for early detection is proven essential in order to reduce breast cancer mortality. Therefore, the present study was designed to determine the effect of educational intervention based on the Health Action Model in improving breast cancer screening behaviors in women aged 30 to 69 in Kashan, Iran.

METHODS

This quasi-experimental study was conducted on 162 women aged 30-69 years old among the clients of Comprehensive health service centers in Kashan, Iran and they were assigned to intervention and control groups. The research instrument included a questionnaire assessed within three phases: baseline, 3-months, and 6-months, containing Health Action Model (HAM) structures and also three screening behaviors. The intervention consisted of a model-based education package and was carried out over 2 months. To evaluate the effect of the intervention, the mean of model structures and proportion screening behaviors in the third and sixth months were compared with the baseline phase. All analyses were carried out using SPSS, version 22.

RESULTS

The intervention and control groups were homogeneous regarding the structures of the HAM and the proportion of screening behaviors in the baseline phase (p > 0.05). In the 3-month (p < 0.05) and 6-month (p < 0.05) phases, the mean scores of the HAM constructs in the intervention group were found higher compared with the control group. Moreover, the proportion of clinical breast examinations in the intervention group was statistically higher than in the control group in the 3-month (p < 0.001) and 6-month (p < 0.001) phases. In addition, the proportion of mammography performed in the 3-month (p = 0.002) and 6-month (p < 0.001) phases were reported to be higher in the intervention group compared with the control group.

CONCLUSION

Overall, these results provide important insight into the effectiveness of the interventions based on the Health Action Model in promoting breast cancer screening behaviors and the determinants of such behaviors.

Benefit of adjuvant chemotherapy in lymph node-negative, T1b and T1c triple-negative breast cancer

INTRODUCTION

Current guidelines recommendations regarding chemotherapy in small (T1b and T1c), node-negative triple-negative breast cancer (TNBC) differ due to lack of high-quality data. Our study aimed to assess the benefit of adjuvant chemotherapy in patients with T1bN0M0 and T1cN0M0 TNBC.

METHODS

We obtained data from the Surveillance, Epidemiology, and End Results database for patients with node-negative, T1b/T1c TNBC diagnosed between 2010 and 2020. Logistic regresion models assessed variables associated with chemotherapy administration. We evaluated the effect of chemotherapy on overall survival (OS) and breast cancer specific survival (BCSS) with Kaplan-Meier methods and Cox proportional hazards methods.

RESULTS

We included 11,510 patients: 3,388 with T1b and 8,122 with T1c TNBC. During a median follow-up of 66 months, 305 patients with T1b and 995 with T1c died. After adjusting for clinicopathological, demographic and treatment factors, adjuvant chemotherapy improved OS in T1b TNBC (HR, 0.52; 95% CI, 0.41-0.68 p < 0.001) but did not improve BCSS (HR, 0.70; 95% CI, 0.45-1.07; p = 0.10); the association between chemotherapy and BCSS was not statistically significant in any subgroup. In T1c TNBC, adjuvant chemotherapy improved OS (HR, 0.54; 95% CI, 0.47-0.62; p < 0.001) and BCSS (HR, 0.79; 95% CI, 0.63-0.99; p = 0.043); the benefit of chemotherapy in OS varied by age (Pinteraction=0.024); moreover, the benefit in BCSS was similar in all subgroups.

CONCLUSIONS

Our study results support the use of adjuvant chemotherapy in patients with node-negative, T1c TNBC. Patients with node-negative, T1b TNBC had excellent long-term outcomes; furthermore, chemotherapy was not associated with improved BCSS in these patients.

Multi-MicroRNA Analysis Can Improve the Diagnostic Performance of Mammography in Determining Breast Cancer Risk

The objective of this study was to determine whether multi-microRNA analysis using a combination of four microRNA biomarkers (miR-1246, 202, 21, and 219B) could improve the diagnostic performance of mammography in determining breast cancer risk by age group (under 50 vs. over 50) and distinguish breast cancer from benign breast diseases and other cancers (thyroid, colon, stomach, lung, liver, and cervix cancers). To verify breast cancer classification performance of the four miRNA biomarkers and whether the model providing breast cancer risk score could distinguish between benign breast disease and other cancers, the model was verified using nonlinear support vector machine (SVM) and generalized linear model (GLM) and age and four miRNA qRT-PCR analysis values (dCt) were input to these models. Breast cancer risk scores for each Breast Imaging-Reporting and Data System (BI-RADS) category in multi-microRNA analysis were analyzed to examine the correlation between breast cancer risk scores and mammography categories. We generated two models using two classification algorithms, SVM and GLM, with a combination of four miRNA biomarkers showing high performance and sensitivities of 84.5% and 82.1%, a specificity of 85%, and areas under the curve (AUCs) of 0.967 and 0.965, respectively, which showed consistent performance across all stages of breast cancer and patient ages. The results of this study showed that this multi-microRNA analysis using the four miRNA biomarkers was effective in classifying breast cancer in patients under the age of 50, which is challenging to accurately diagnose. In addition, breast cancer and benign breast diseases can be classified, showing the possibility of helping with diagnosis by mammography. Verification of the performance of the four miRNA biomarkers confirmed that multi-microRNA analysis could be used as a new breast cancer screening aid to improve the accuracy of mammography. However, many factors must be considered for clinical use. Further validation with an appropriate screening population in large clinical trials is required. This trial is registered with (KNUCH 2022-04-036).

Economic evaluation of breast MRI in screening - a systematic review and basic approach to cost-effectiveness analyses

Background

Economic evaluations have become an accepted methodology for decision makers to allocate resources in healthcare systems. Particularly in screening, where short-term costs are associated with long-term benefits, and adverse effects of screening intermingle, cost-effectiveness analyses provide a means to estimate the economic value of screening.

Purpose

To introduce the methodology of economic evaluations and to review the existing evidence on cost-effectiveness of MR-based breast cancer screening.

Materials and methods

The various concepts and techniques of economic evaluations critical to the interpretation of cost-effectiveness analyses are briefly introduced. In a systematic review of the literature, economic evaluations from the years 2000-2022 are reviewed.

Results

Despite a considerable heterogeneity in the reported input variables, outcome categories and methodological approaches, cost-effectiveness analyses report favorably on the economic value of breast MRI screening for different risk groups, including both short- and long-term costs and outcomes.

Conclusion

Economic evaluations indicate a strongly favorable economic value of breast MRI screening for women at high risk and for women with dense breast tissue.

Prognostic impact of adjuvant endocrine therapy for estrogen receptor-positive and HER2-negative T1a/bN0M0 breast cancer

PURPOSE

Mammography screening has increased the detection of subcentimeter breast cancers. The prognosis for estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative T1a/bN0M0 breast cancers is excellent; however, the necessity of adjuvant endocrine therapy (ET) is uncertain.

METHODS

We evaluated the effectiveness of adjuvant ET in patients with ER-positive and HER2-negative T1a/bN0M0 breast cancer who underwent surgery from 2008 to 2012. Standard ET was administrated after surgery. The primary endpoint was the cumulative incidence of distant metastasis. All statistical tests were 2-sided.

RESULTS

Adjuvant ET was administered to 3991 (83%) of the 4758 eligible patients (1202 T1a [25.3%] and 3556 T1b [74.7%], diseases). The median follow-up period was 9.2 years. The 9-year cumulative incidence of distant metastasis was 1.5% with ET and 2.6% without ET (adjusted subdistribution hazard ratio [sHR], 0.54; 95% CI, 0.32-0.93). In multivariate analysis, the independent risk factors for distant metastasis were no history of ET, mastectomy, high-grade, and lymphatic invasion. The 9-year overall survival was 97.0% and 94.4% with and without ET, respectively (adjusted HR, 0.57; 95% CI, 0.39-0.83). In addition, adjuvant ET reduced the incidence of ipsilateral and contralateral breast cancer (9-year rates; 1.1% vs. 6.9%; sHR, 0.17, and 1.9% vs. 5.2%; sHR, 0.33).

CONCLUSIONS

The prognosis was favorable in patients with ER-positive and HER2-negative T1a/bN0M0 breast cancer. Furthermore, adjuvant ET reduced the incidence of distant metastasis with minimal absolute risk difference. These findings support considering the omission of adjuvant ET, especially for patients with low-grade and no lymphatic invasion disease.

Breast Cancer Detection with an Ensemble of Deep Learning Networks Using a Consensus-Adaptive Weighting Method

Breast cancer's high mortality rate is often linked to late diagnosis, with mammograms as key but sometimes limited tools in early detection. To enhance diagnostic accuracy and speed, this study introduces a novel computer-aided detection (CAD) ensemble system. This system incorporates advanced deep learning networks-EfficientNet, Xception, MobileNetV2, InceptionV3, and Resnet50-integrated via our innovative consensus-adaptive weighting (CAW) method. This method permits the dynamic adjustment of multiple deep networks, bolstering the system's detection capabilities. Our approach also addresses a major challenge in pixel-level data annotation of faster R-CNNs, highlighted in a prominent previous study. Evaluations on various datasets, including the cropped DDSM (Digital Database for Screening Mammography), DDSM, and INbreast, demonstrated the system's superior performance. In particular, our CAD system showed marked improvement on the cropped DDSM dataset, enhancing detection rates by approximately 1.59% and achieving an accuracy of 95.48%. This innovative system represents a significant advancement in early breast cancer detection, offering the potential for more precise and timely diagnosis, ultimately fostering improved patient outcomes.

Copper isotope ratios in serum do not track cancerous tumor evolution, but organ failure

Relative to healthy controls, lighter copper isotopic compositions have been observed in the serum of breast cancer and end-stage liver disease patients, raising the possibility that Cu isotope ratios could be used as a tracer for disease progression. Here, we assess the potential of natural Cu isotopic variations (expressed as δ65Cu) as diagnostic tools for cancer progression and/or liver failure by performing a first-order analysis of Cu isotopic cycling in the human body. Using a box model, we simulate the kinetics of Cu mass transfer throughout significant reservoirs in the body, allowing isotopic fractionation to occur during Cu uptake/release from these reservoirs. With this model, we determine under which conditions the serum δ65Cu values would reflect perturbation related to cancer growth and/or liver failure at a level resolvable with modern mass spectrometry. We find that tumor growth alone is unable to explain the light isotopic signature observed in serum. Instead, we find that metabolic changes to the liver function resulting in a ∼1‰ isotope fractionation during Cu uptake from the blood into the liver can readily explain the long-term serum isotopic shift of ∼0.2‰ observed in cancer patients. A similar fractionation (∼1.3‰) during Cu uptake into the liver also readily explains the -1.2‰ shift observed in the serum of cirrhosis patients with ascites, suggesting a potentially common driver of isotopic fractionation in both cases. Using this model, we then test hypotheses put forward by previous studies and begin to probe the mechanisms behind the measured isotopic compositions.

Data-driven overdiagnosis definitions: A scoping review

INTRODUCTION

Adequate methods to promptly translate digital health innovations for improved patient care are essential. Advances in Artificial Intelligence (AI) and Machine Learning (ML) have been sources of digital innovation and hold the promise to revolutionize the way we treat, manage and diagnose patients. Understanding the benefits but also the potential adverse effects of digital health innovations, particularly when these are made available or applied on healthier segments of the population is essential. One of such adverse effects is overdiagnosis.

OBJECTIVE

to comprehensively analyze quantification strategies and data-driven definitions for overdiagnosis reported in the literature.

METHODS

we conducted a scoping systematic review of manuscripts describing quantitative methods to estimate the proportion of overdiagnosed patients.

RESULTS

we identified 46 studies that met our inclusion criteria. They covered a variety of clinical conditions, primarily breast and prostate cancer. Methods to quantify overdiagnosis included both prospective and retrospective methods including randomized clinical trials, and simulations.

CONCLUSION

a variety of methods to quantify overdiagnosis have been published, producing widely diverging results. A standard method to quantify overdiagnosis is needed to allow its mitigation during the rapidly increasing development of new digital diagnostic tools.

Breast cancer in young Indian women: factors, challenges in screening, and upcoming diagnostics

Breast cancer management for young Indian women are full of challenges. The National Cancer Registry Programme (NCRP) has predicted that nearly 2,30,000 cases of breast cancer will be reported annually by 2025; with a steady increase in cases of young women (< 45 years of age) with breast cancer. In this review, the available literature is evaluated to understand the various risk factors contributing to the rise in cases of breast cancer in young women in India. Further, the challenges that are faced by the technicians in early diagnosis (e.g., physiology of young breasts, limited trained professionals, and awareness among patients, and cost of the treatment) of breast cancer. This review also focuses on the upcoming diagnostics like serum biomarkers and nanosensors for the early identification of the disease. For better prognosis and to reduce the chances of disease reoccurrence and metastasis, it is important that the disease has to be identified at an early stage.

Recent advancements in artificial intelligence for breast cancer: Image augmentation, segmentation, diagnosis, and prognosis approaches

Breast cancer is a significant global health burden, with increasing morbidity and mortality worldwide. Early screening and accurate diagnosis are crucial for improving prognosis. Radiographic imaging modalities such as digital mammography (DM), digital breast tomosynthesis (DBT), magnetic resonance imaging (MRI), ultrasound (US), and nuclear medicine techniques, are commonly used for breast cancer assessment. And histopathology (HP) serves as the gold standard for confirming malignancy. Artificial intelligence (AI) technologies show great potential for quantitative representation of medical images to effectively assist in segmentation, diagnosis, and prognosis of breast cancer. In this review, we overview the recent advancements of AI technologies for breast cancer, including 1) improving image quality by data augmentation, 2) fast detection and segmentation of breast lesions and diagnosis of malignancy, 3) biological characterization of the cancer such as staging and subtyping by AI-based classification technologies, 4) prediction of clinical outcomes such as metastasis, treatment response, and survival by integrating multi-omics data. Then, we then summarize large-scale databases available to help train robust, generalizable, and reproducible deep learning models. Furthermore, we conclude the challenges faced by AI in real-world applications, including data curating, model interpretability, and practice regulations. Besides, we expect that clinical implementation of AI will provide important guidance for the patient-tailored management.

Compact reverse time migration: A real-time approach for full waveform ultrasound imaging for breast

We present compact reverse time migration (CRTM), a real-time ultrasound imaging method that can exploit the full waveform information of ultrasonic wave records for imaging breast tissue. Conventional reverse time migration (RTM) computes the gradient of the reflective ultrasound data with respect to the perturbation of the velocity model of the soft tissues and the gradient can indicate the interface between different types of body tissue. In contrast to conventional reflection ultrasound (B-mode), which is based on the high-frequency approximation to the wave equation, the RTM algorithm is based on the complete wave equation, and can thus exploit the full waveform (wide-spectrum) information of the data and provide an image with higher resolution. Unfortunately, the computational burden of RTM is noticeably higher than the ray-based B-mode. This precludes real-time applications, one of the most important features of ultrasound imaging. The proposed CRTM algorithm can significantly reduce the computational costs of RTM, such that it can be applied for real-time imaging. We demonstrate the performance of CRTM through a synthetic experiment of ultrasound breast imaging. CRTM can be potentially adapted to related signal-processing fields, such as seismic imaging, acoustic camera systems, and radar imaging.

Engineered bacteria guide T cells to tumors

T cells and bacteria are engineered to work together to find and destroy tumor cells.

Breast Cancer Screening and Diagnosis: Recent Advances in Imaging and Current Limitations

Breast cancer detection has a significant impact on population health. Although there are many breast imaging modalities, mammography is the predominant tool for breast cancer screening. The introduction of digital breast tomosynthesis to mammography has contributed to increased cancer detection rates and decreased recall rates. In average-risk women, starting annual screening mammography at age 40 years has demonstrated the highest mortality reduction. In intermediate- and high-risk women as well as in those with dense breasts, additional modalities, including MRI, ultrasound, and molecular breast imaging, can also be considered for adjunct screening to improve the detection of mammographically occult malignancy.

Computational mechanobiology model evaluating healing of postoperative cavities following breast-conserving surgery

Breast cancer is the most commonly diagnosed cancer type worldwide. Given high survivorship, increased focus has been placed on long-term treatment outcomes and patient quality of life. While breast-conserving surgery (BCS) is the preferred treatment strategy for early-stage breast cancer, anticipated healing and breast deformation (cosmetic) outcomes weigh heavily on surgeon and patient selection between BCS and more aggressive mastectomy procedures. Unfortunately, surgical outcomes following BCS are difficult to predict, owing to the complexity of the tissue repair process and significant patient-to-patient variability. To overcome this challenge, we developed a predictive computational mechanobiological model that simulates breast healing and deformation following BCS. The coupled biochemical-biomechanical model incorporates multi-scale cell and tissue mechanics, including collagen deposition and remodeling, collagen-dependent cell migration and contractility, and tissue plastic deformation. Available human clinical data evaluating cavity contraction and histopathological data from an experimental porcine lumpectomy study were used for model calibration. The computational model was successfully fit to data by optimizing biochemical and mechanobiological parameters through Gaussian process surrogates. The calibrated model was then applied to define key mechanobiological parameters and relationships influencing healing and breast deformation outcomes. Variability in patient characteristics including cavity-to-breast volume percentage and breast composition were further evaluated to determine effects on cavity contraction and breast cosmetic outcomes, with simulation outcomes aligning well with previously reported human studies. The proposed model has the potential to assist surgeons and their patients in developing and discussing individualized treatment plans that lead to more satisfying post-surgical outcomes and improved quality of life.

Vacuum-assisted excision of small breast cancers under ultrasound guidance

PURPOSE

The purpose of this study was to evaluate if it is possible to completely remove small breast cancer tumours with vacuum-assisted excision (VAE) under ultrasound guidance.

METHODS

Women ≥ 50 years old with a biopsy proven invasive cancer ≤ 10 mm were selected between October 2021 and November 2021 based on referrals and enrolled in this prospective study. The patients underwent VAE within six weeks following biopsy to remove the tumour. After the tumour was excised and the biopsy cavities margins were shaved, a radioactive seed was inserted into the biopsy cavity. The VAE excision cavity and surrounding tissue were surgically excised. Preliminary VAE results were evaluated after ten patients. For the study to proceed at least 80 % of the breast cancer tumours had to be completely removed by VAE.

RESULTS

The tumours median size in mammography was 8.5 mm (6-9 mm) and in ultrasound 6.5 mm (4-9 mm). The shape of the lesion was round in three (30 %), oval in two (20 %) and irregular in five (50 %) patients. None of the tumours were completely removed in the first VAE specimen, meaning that there was invasive cancer or ductal carcinoma in situ (DCIS) in the "shaved margins" and/or the surgical specimen. In five (50 %) cases, the surgical specimen was free of invasive cancer and DCIS.

CONCLUSIONS

None of the small invasive breast cancers were completely excised with VAE under ultrasound guidance, therefore it is not a reliable method to remove small breast cancers.

Spherical nucleic acids-based nanoplatforms for tumor precision medicine and immunotherapy

Precise diagnosis and treatment of tumors currently still face considerable challenges due to the development of highly degreed heterogeneity in the dynamic evolution of tumors. With the rapid development of genomics, personalized diagnosis and treatment using specific genes may be a robust strategy to break through the bottleneck of traditional tumor treatment. Nevertheless, efficient in vivo gene delivery has been frequently hampered by the inherent defects of vectors and various biological barriers. Encouragingly, spherical nucleic acids (SNAs) with good modularity and programmability are excellent candidates capable of addressing traditional gene transfer-associated issues, which enables SNAs a precision nanoplatform with great potential for diverse biomedical applications. In this regard, there have been detailed reviews of SNA in drug delivery, gene regulation, and dermatology treatment. Still, to the best of our knowledge, there is no published systematic review summarizing the use of SNAs in oncology precision medicine and immunotherapy, which are considered new guidelines for oncology treatment. To this end, we summarized the notable advances in SNAs-based precision therapy and immunotherapy for tumors following a classification standard of different types of precise spatiotemporal control on active species by SNAs. Specifically, we focus on the structural diversity and programmability of SNAs. Finally, the challenges and possible solutions were discussed in the concluding remarks. This review will promote the rational design and development of SNAs for tumor-precise medicine and immunotherapy.

Assessment of Use and Impact of Chemotherapy in Lymph Node-Negative, T1a Triple-Negative Breast Cancer

BACKGROUND

Current treatment guidelines suggest considering adjuvant chemotherapy in high-risk patients with T1a, node-negative triple-negative breast cancer (TNBC); however, limited quality data support this statement. Our population-based study assessed the efficacy of adjuvant chemotherapy and factors associated with its administration in node-negative, T1a TNBC.

MATERIALS AND METHODS

We obtained data from the Surveillance, Epidemiology, and End Results database for patients with T1aN0 TNBC diagnosed between 2010 and 2019. We utilized the Kaplan-Meier method and Cox regression model to analyze the overall survival (OS) and breast cancer-specific survival (BCSS) in chemotherapy benefit. We performed stratified models to identify differences in OS and BCSS between those who received chemotherapy and those who did not across subgroups. Competing risk analysis was conducted to assess differences in risk of breast cancer death in patients with chemotherapy administration versus no chemotherapy. Additionally, propensity score matching was executed to assess survival analysis in a matched cohort.

RESULTS

We included 1739 patients with T1a TNBC. Patients who received chemotherapy were younger, had higher histological grade and ductal histology subtype, were more likely to be married and undergo mastectomy. Our study did not show improvement in OS (HR, 0.63; 95% CI, 0.35-1.13; P = .122) or BCSS (HR, 0.95; 95% CI, 0.37-2.43; P = .908) after chemotherapy use. We did not identify any subgroup of patients that may benefit from chemotherapy. Without chemotherapy, 8-year risk of breast cancer death is 2.75% for these patients.

CONCLUSION

Adjuvant chemotherapy is not associated with benefit on OS or BCSS in node-negative, T1a TNBC.

Expanding mammography screening for women aged 40-80 years: evidence from a modeling approach using real-world data

If a mammography screening program (MS) is to be expanded, the benefit must be demonstrated for each additional age cohort. For the age interval between 40 and 80 years, the association between tumor-related and tumor-independent mortality of 21 2-year cohorts is modeled using up-to-date, valid data to determine MS outcome. Disease trajectories with and without biennial MS are extrapolated for each age cohort using the available data and knowledge on MS. The competing mortality is randomly generated for each age cohort with and without MS for a follow-up period of 20 years. Analyses of the modeled cohorts describe incremental change for each year, quantifying the changing benefits of MS. With increasing age, the proportion of tumor-independent mortality before and with metastatic disease increases and the benefit decreases. The simulations with 21 studies on the age interval 40-80 years provide four parameters to determine the benefits and costs of MS: The number of prevented deaths, required mammography screening exams (MSE) and their costs, life-years gained, and the required MSEs. If one additional MSE is offered for age groups 48/70 years, this will result in 311/320 prevented breast cancer (BC) deaths with 1742/1494 required MSEs or 8784/4168 life-years gained with 64/140 required MSEs. A rational cutoff cannot be quantified. The mortality effect of MS between 40 and 80 years is quantified in 21 steps using two metrics, number of MSEs per tumor-related mortality prevented and per life-year gained. This provides a decision support for stepwise expansions. Given this real-world evidence no rational age cutoffs for MS becomes evident. A society has to decide which MS costs, including side effects of MS for women who remain BC-free, it is willing and able to accept in order to reduce breast cancer mortality.

Potential role of vacuum-assisted procedures in resecting breast cancers and highlighting selection criteria to support future trials

Purpose

The purpose of this study was to evaluate the role of vacuum-assisted biopsy (VAB) in resecting breast cancers.

Methods

Retrospective database analysis of 116 cancers [both invasive breast cancers (IC) and ductal carcinoma in situ (DCIS)] diagnosed by VAB submitted to standard surgical treatment with complete histological data from VAB and surgery. Excision following VAB was defined as complete resection (CR) if there was no residual tumor in the surgical specimen, minimal residual disease (MRD) if residual tumor ≤ 3 mm, gross residual disease (GRD) if residual tumor > 3 mm, and upgrade from DCIS on VAB to IC. CR and MRD were combined as potentially resected percutaneously (PRP). GRD and those with upgrade to IC were determined not eligible for percutaneous resection (NPR). Factors predictive of PRP were evaluated.

Results

Mean age was 55.6 years (20-91; SD: 12,27). CR was seen in 29 of 116 cases (25%), MRD in 18 of 116 cases (15.5%), GRD in 64 of 116 cases (55.2%), and five of 116 cases (4.3%) were upgraded from DCIS to IC, and those groups combined represented 47 cases of PRP (40.5%) and 69 (59,5%) of NPR. For 77 tumors ≤ 10 mm, 45 (58.5%) were PRP. Multivariate analysis reveals significance for enlarged VAB (EVAB) (p = 0.008, OR: 4.4, 95% CI), low/intermediate nuclear grade (p < 0.001, OR: 12.5, 95% CI) and final tumor size (T) ≤ 10 mm (p = 0.001, OR: 50.1, 95% CI) for PRP.

Conclusions

This study showed that lesions completely excised with VAB that were cancer could have been treated with VAB rather than surgery but tumor selection in terms of subtype and size is important.

Estimating Breast Cancer Overdiagnosis After Screening Mammography Among Older Women in the United States

BACKGROUND

Overdiagnosis is increasingly recognized as a harm of breast cancer screening, particularly for older women.

OBJECTIVE

To estimate overdiagnosis associated with breast cancer screening among older women by age.

DESIGN

Retrospective cohort study comparing the cumulative incidence of breast cancer among older women who continued screening in the next interval with those who did not. Analyses used competing risk models, stratified by age.

SETTING

Fee-for-service Medicare claims, linked to the SEER (Surveillance, Epidemiology, and End Results) program.

PATIENTS

Women 70 years and older who had been recently screened.

MEASUREMENTS

Breast cancer diagnoses and breast cancer death for up to 15 years of follow-up.

RESULTS

This study included 54 635 women. Among women aged 70 to 74 years, the adjusted cumulative incidence of breast cancer was 6.1 cases (95% CI, 5.7 to 6.4) per 100 screened women versus 4.2 cases (CI, 3.5 to 5.0) per 100 unscreened women. An estimated 31% of breast cancer among screened women were potentially overdiagnosed. For women aged 75 to 84 years, cumulative incidence was 4.9 (CI, 4.6 to 5.2) per 100 screened women versus 2.6 (CI, 2.2 to 3.0) per 100 unscreened women, with 47% of cases potentially overdiagnosed. For women aged 85 and older, the cumulative incidence was 2.8 (CI, 2.3 to 3.4) among screened women versus 1.3 (CI, 0.9 to 1.9) among those not, with up to 54% overdiagnosis. We did not see statistically significant reductions in breast cancer-specific death associated with screening.

LIMITATIONS

This study was designed to estimate overdiagnosis, limiting our ability to draw conclusions on all benefits and harms of screening. Unmeasured differences in risk for breast cancer and differential competing mortality between screened and unscreened women may confound results. Results were sensitive to model specifications and definition of a screening mammogram.

CONCLUSION

Continued breast cancer screening was associated with greater incidence of breast cancer, suggesting overdiagnosis may be common among older women who are diagnosed with breast cancer after screening. Whether harms of overdiagnosis are balanced by benefits and for whom remains an important question.

PRIMARY FUNDING SOURCE

National Cancer Institute.

Deep learning model with collage images for the segmentation of dedicated breast positron emission tomography images

BACKGROUND

Dedicated breast positron emission tomography (dbPET) has high contrast and resolution optimized for detecting small breast cancers, leading to its noisy characteristics. This study evaluated the application of deep learning to the automatic segmentation of abnormal uptakes on dbPET to facilitate the assessment of lesions. To address data scarcity in model training, we used collage images composed of cropped abnormal uptakes and normal breasts for data augmentation.

METHODS

This retrospective study included 1598 examinations between April 2015 and August 2020. A U-Net-based model with an uptake shape classification head was trained using either the original or augmented dataset comprising collage images. The Dice score, which measures the pixel-wise agreement between a prediction and its ground truth, of the models was compared using the Wilcoxon signed-rank test. Moreover, the classification accuracies were evaluated.

RESULTS

After applying the exclusion criteria, 662 breasts were included; among these, 217 breasts had abnormal uptakes (mean age: 58 ± 14 years). Abnormal uptakes on the cranio-caudal and mediolateral maximum intensity projection images of 217 breasts were annotated and labeled as focus, mass, or non-mass. The inclusion of collage images into the original dataset yielded a Dice score of 0.884 and classification accuracy of 91.5%. Improvement in the Dice score was observed across all subgroups, and the score of images without breast cancer improved significantly from 0.750 to 0.834 (effect size: 0.76, P = 0.02).

CONCLUSIONS

Deep learning can be applied for the automatic segmentation of dbPET, and collage images can improve model performance.

A multiplex blood-based assay targeting DNA methylation in PBMCs enables early detection of breast cancer

The immune system can monitor tumor development, and DNA methylation is involved in the body's immune response to tumors. In this work, we investigate whether DNA methylation alterations in peripheral blood mononuclear cells (PBMCs) could be used as markers for early detection of breast cancer (BC) from the perspective of tumor immune alterations. We identify four BC-specific methylation markers by combining Infinium 850 K BeadChips, pyrosequencing and targeted bisulfite sequencing. Based on the four methylation markers in PBMCs of BC, we develop an efficient and convenient multiplex methylation-specific quantitative PCR assay for the detection of BC and validate its diagnostic performance in a multicenter cohort. This assay was able to distinguish early-stage BC patients from normal controls, with an AUC of 0.940, sensitivity of 93.2%, and specificity of 90.4%. More importantly, this assay outperformed existing clinical diagnostic methods, especially in the detection of early-stage and minimal tumors.

Diagnostic Scrutiny and Patterns of Elevated Cancer Risk: Uncovering Overdiagnosis Through Standardized Incidence Ratios

Certain medical diagnoses and environmental or occupational exposures may be associated with elevated risk of cancer diagnosis, either through causal mechanisms or via increased detection of a subclinical reservoir through increased diagnostic scrutiny (overdiagnosis). The present study aimed to investigate the distribution of elevated cancer risks associated with different diagnoses and exposures. A systematic literature search was conducted to identify studies published in the last 30 years that examined the standardized incidence ratio (SIR) associated with exposures and risk factors. Meta-SIRs for each cancer type were calculated. The distribution of elevated cancer risks was then compared between cancer types previously reported to be susceptible to overdiagnosis and those that have not been associated with overdiagnosis. The review of 108 studies identified four patterns: SIR generally elevated for 1) only overdiagnosis-susceptible cancer types, 2) both overdiagnosed and non-overdiagnosed cancer types, 3) select cancers in accordance with risk factor or exposure, and 4) SIRs that did not exhibit a distinct increase in any cancer type. The distribution of elevated cancer risks may serve as a signature of whether the underlying risk factor or exposure is a carcinogenic process or a mechanism of increased diagnostic scrutiny uncovering clinically occult diseases. The identification of increased cancer risk should be viewed with caution, and analyzing the pattern of elevated cancer risk distribution can potentially reveal conditions that appear to be cancer risk factors but are in fact the result of exposure to medical surveillance or other healthcare activities that lead to the detection of indolent tumors.

Radiofrequency localization of nonpalpable breast cancer in a multicentre prospective cohort study: feasibility, clinical acceptability, and safety

PURPOSE

In breast conserving surgery, accurate lesion localization is essential for obtaining adequate surgical margins. Preoperative wire localization (WL) and radioactive seed localization (RSL) are widely accepted methods to guide surgical excision of nonpalpable breast lesions but are limited by logistical challenges, migration issues, and legislative complexities. Radiofrequency identification (RFID) technology may offer a viable alternative. The purpose of this study was to evaluate the feasibility, clinical acceptability, and safety of RFID surgical guidance for localization of nonpalpable breast cancer.

METHODS

In a prospective multicentre cohort study, the first 100 RFID localization procedures were included. The primary outcome was the percentage of clear resection margins and re-excision rate. Secondary outcomes included procedure details, user experience, learningcurve, and adverse events.

RESULTS

Between April 2019 and May 2021, 100 women underwent RFID guided breast conserving surgery. Clear resection margins were obtained in 89 out of 96 included patients (92.7%), re-excision was indicated in three patients (3.1%). Radiologists reported difficulties with the placement of the RFID tag, partially related to the relatively large needle-applicator (12-gauge). This led to the premature termination of the study in the hospital using RSL as regular care. The radiologist experience was improved after a manufacturer modification of the needle-applicator. Surgical localization involved a low learning curve. Adverse events (n = 33) included dislocation of the marker during insertion (8%) and hematomas (9%). The majority of adverse events (85%) occurred using the first-generation needle-applicator.

CONCLUSION

RFID technology is a potential alternative for non-radioactive and non-wire localization of nonpalpable breast lesions.

Automated Estimation of Mammary Gland Content Ratio Using Regression Deep Convolutional Neural Network and the Effectiveness in Clinical Practice as Explainable Artificial Intelligence

Recently, breast types were categorized into four types based on the Breast Imaging Reporting and Data System (BI-RADS) atlas, and evaluating them is vital in clinical practice. A Japanese guideline, called breast composition, was developed for the breast types based on BI-RADS. The guideline is characterized using a continuous value called the mammary gland content ratio calculated to determine the breast composition, therefore allowing a more objective and visual evaluation. Although a discriminative deep convolutional neural network (DCNN) has been developed conventionally to classify the breast composition, it could encounter two-step errors or more. Hence, we propose an alternative regression DCNN based on mammary gland content ratio. We used 1476 images, evaluated by an expert physician. Our regression DCNN contained four convolution layers and three fully connected layers. Consequently, we obtained a high correlation of 0.93 (p < 0.01). Furthermore, to scrutinize the effectiveness of the regression DCNN, we categorized breast composition using the estimated ratio obtained by the regression DCNN. The agreement rates are high at 84.8%, suggesting that the breast composition can be calculated using regression DCNN with high accuracy. Moreover, the occurrence of two-step errors or more is unlikely, and the proposed method can intuitively understand the estimated results.

Differences in breast cancer survival and stage by age in off-target screening groups: a population-based retrospective study

BACKGROUND

Age is an important prognostic factor in breast cancer. The target age to screen is under debate.

OBJECTIVE

This study aimed to assess the influence of age on the diagnosis and survival among women with breast cancer.

STUDY DESIGN

This was a retrospective cohort study of the Population-Based Cancer Registry of Campinas, Brazil, and included all women diagnosed from 2010 to 2014. The outcomes assessed were overall survival and stage. For statistical analyses, the Kaplan-Meier method, log-rank tests, and chi-square tests were used.

RESULTS

The sample comprised 1741 women aged 40 to 79 years. Diagnoses at stages 0 to II were the more frequent. In the 40 to 49 years and 50 to 59 years age groups, the frequency of stage 0 (in situ) was 20.5% and 14.9% (P=.022), respectively, and the frequency of stage I was 20.2% and 25.8% (P=.042), respectively. The mean overall survival was 8.9 years (8.6-9.2) in the 40 to 49 years age group and 7.7 years (7.3-8.1) in the 70 to 79 years age group. The 5-year overall survival was higher in the 40 to 49 years age group than in the 50 to 59 years age group for stage 0 (in situ) (100.0% vs 95.0%; P=.036) and stage III (77.4% vs 66.2%; P=.046) diagnoses. The 5-year overall survival was higher in 60 to 69 years age group than in the 70 to 79 years age group for stages I (94.6% vs 86.5%; P=.002) and III (83.5% vs 64.9%; P=.010). In all age groups, significant differences in survival were not observed for stage 0 (in situ) vs stage I diagnoses, stage 0 vs stage II diagnoses, and stage I vs stage II diagnoses.

CONCLUSION

Women aged 40 to 49 years had the highest proportion of in situ tumors, and stages III and IV accounted for about one-third of the cases in all age groups. There was no difference in the overall survival for stage 0 (in situ) vs stage I or II diagnoses in all age groups.

Design of a Low-Cost Diffuse Optical Mammography System for Biomedical Image Processing in Breast Cancer Diagnosis

Worldwide, breast cancer is the most common type of cancer that mainly affects women. Several diagnosis techniques based on optical instrumentation and image analysis have been developed, and these are commonly used in conjunction with conventional diagnostic devices such as mammographs, ultrasound, and magnetic resonance imaging of the breast. The cost of using these instruments is increasing, and developing countries, whose deaths indices due to breast cancer are high, cannot access conventional diagnostic methods and have even less access to newer techniques. Other studies, based on the analysis of images acquired by traditional methods, require high resolutions and knowledge of the origin of the captures in order to avoid errors. For this reason, the design of a low-cost diffuse optical mammography system for biomedical image processing in breast cancer diagnosis is presented. The system combines the acquisition of breast tissue photographs, diffuse optical reflectance (as a biophotonics technique), and the processing of digital images for the study and diagnosis of breast cancer. The system was developed in the form of a medical examination table with a 638 nm red-light source, using light-emitted diode technology (LED) and a low-cost web camera for the acquisition of breast tissue images. The system is automatic, and its control, through a graphical user interface (GUI), saves costs and allows for the subsequent analysis of images using a digital image-processing algorithm. The results obtained allow for the possibility of planning in vivo measurements. In addition, the acquisition of images every 30° around the breast tissue could be used in future research in order to perform a three-dimensional (3D) reconstruction and an analysis of the captures through deep learning techniques. These could be combined with virtual, augmented, or mixed reality environments to predict the position of tumors, increase the likelihood of a correct medical diagnosis, and develop a training system for specialists. Furthermore, the system allows for the possibility to develop analysis of optical characterization for new phantom studies in breast cancer diagnosis through bioimaging techniques.

Computational Mechanobiology Model Evaluating Healing of Postoperative Cavities Following Breast-Conserving Surgery

Breast cancer is the most commonly diagnosed cancer type worldwide. Given high survivorship, increased focus has been placed on long-term treatment outcomes and patient quality of life. While breast-conserving surgery (BCS) is the preferred treatment strategy for early-stage breast cancer, anticipated healing and breast deformation (cosmetic) outcomes weigh heavily on surgeon and patient selection between BCS and more aggressive mastectomy procedures. Unfortunately, surgical outcomes following BCS are difficult to predict, owing to the complexity of the tissue repair process and significant patient-to-patient variability. To overcome this challenge, we developed a predictive computational mechanobiological model that simulates breast healing and deformation following BCS. The coupled biochemical-biomechanical model incorporates multi-scale cell and tissue mechanics, including collagen deposition and remodeling, collagen-dependent cell migration and contractility, and tissue plastic deformation. Available human clinical data evaluating cavity contraction and histopathological data from an experimental porcine lumpectomy study were used for model calibration. The computational model was successfully fit to data by optimizing biochemical and mechanobiological parameters through the Gaussian Process. The calibrated model was then applied to define key mechanobiological parameters and relationships influencing healing and breast deformation outcomes. Variability in patient characteristics including cavity-to-breast volume percentage and breast composition were further evaluated to determine effects on cavity contraction and breast cosmetic outcomes, with simulation outcomes aligning well with previously reported human studies. The proposed model has the potential to assist surgeons and their patients in developing and discussing individualized treatment plans that lead to more satisfying post-surgical outcomes and improved quality of life.

Clinical Outcomes of Conservative Treatment for Low-Risk Ductal Carcinoma in Situ: A Systematic Review and Pooled Analysis

AIMS

The current gold standard of treatment for ductal carcinoma in situ (DCIS) is surgical resection with or without adjuvant radiotherapy. However, the increased detection and radical treatment of DCIS did not result in a declined incidence of invasive breast cancers, leading to the debate if DCIS has been overtreated. While ongoing randomised controlled trials on active surveillance of DCIS are still in progress, this systematic review aims to evaluate the best evidence on conservative treatment for DCIS from the literature.

MATERIALS AND METHODS

This systematic review was conducted in line with the PRISMA statement. We included all relevant studies published up to June 2022 for analysis. The primary outcomes were overall survival and breast cancer-specific survival (BCSS) of conservative treatment for DCIS.

RESULTS

Three studies, with a total of 34 007 women with low-risk DCIS, were included in the analysis. Active and conservative treatments both resulted in excellent 10-year BCSS, with no statistically insignificant difference (98.6% versus 96.0%, 31 478 women). One study comparing 5-year BCSS of active and conservative treatments only in subjects aged over 80 years also reported [AQ1]an insignificant difference (98.2% versus 96.0%, 2529 women). One study measuring 5- and 10-year overall survival between the treatment groups also reported [AQ1]an insignificant difference (5-year: 96.2% versus 92.4%; 10-year: 85.6% versus 86.7%, 31 106 women).

CONCLUSION

BCSS between active and conservative treatment for women with low-risk DCIS is both excellent and comparable, suggesting that conservative treatment is a possible alternative without compromising survival.

Trends in Breast Cancer Incidence and Mortality in the United States From 2004-2018: A Surveillance, Epidemiology, and End Results (SEER)-Based Study

The incidence and mortality data for patients with breast cancer in the United States are important to healthcare administrators for planning healthcare measures such as screening mammograms. In this study, we examined breast cancer incidence and incidence-based mortality in the United States from 2004-2018 using the Surveillance, Epidemiology, and End Results (SEER) database. We reviewed 915,417 cases of breast cancer diagnosed between 2004 and 2018. Overall, the data showed an increased incidence rate of breast cancer among all races and a decreased mortality rate among all races. Breast cancer incidence rates increased by 0.3% (95% CI, 0.1, 0.4, p<0.001) per year over the study period. Breast cancer incidence rates increased for all age, race, and stage groups except for stage regional, which showed a statistically significant decrease in the incidence of -0.9% (95% CI, -1.1, -0.7, p<0.001). The highest decrease in mortality was observed among white patients, with an overall statistically significant decrease in rates by -14.3% (95% CI, -18.1, -10.4, p <0.001). The highest decrease in rates was observed between 2016 and 2018: -48.6 (95% CI, -52.6, -44.3, p <0.001). In black/African American patients, the overall incidence-based mortality decreased by -11.6% (95% CI -15.9, -7.1 p <.001), with the highest decrease in rates observed between 2016 and 2018 with a decrease of -51.3% (95% CI -56.6, -45.3, p <0.001). In Hispanic Americans, the overall incidence-based mortality decreased by -12.3% (95% CI -16.9, -7.4, p <.001), which is lower than in white Americans.

Fluoroscopic Intraoperative Breast Neoplasm and Node Detection

BACKGROUND

Preoperative localization is necessary for nonpalpable breast lesions. A novel procedure, fluoroscopic intraoperative neoplasm and node detection (FIND), obviates the preoperative painful and potentially expensive localization by using intraoperative visualization of the standard clip placed during diagnostic biopsy. We hypothesized FIND would improve negative margin rates.

STUDY DESIGN

This is an IRB-approved retrospective study (September 2016 to March 2021). Electronic chart review identified breast and axillary node procedures using wire localization (WL) or FIND. Primary outcome was margin status. Secondary outcomes included re-excision rate, specimen weight, surgery time, and axillary node localization rate.

RESULTS

We identified 459 patients, of whom 116 (25.3%) underwent FIND and 343 (74.7%) WL. Of these, 68.1% of FIND and 72.0% of WL procedures were for malignant lesions. Final margin positivity was 5.1% (4 of 79) for FIND and 16.6% (41 of 247) for WL (p = 0.008). This difference lost statistical significance on multivariable logistic regression (p = 0.652). Re-excision rates were 7.6% and 14.6% for FIND and WL (p = 0.125), with an equivalent mean specimen weight (p = 0.502), and mean surgery time of 177.5 ± 81.7 and 157.1 ± 66.8 minutes, respectively (mean ± SD; p = 0.022). FIND identified all (29 of 29) targeted axillary nodes, and WL identified only 80.1% (21 of 26) (p = 0.019).

CONCLUSIONS

FIND has lower positive margin rates and a trend towards lower re-excision rates compared with WL, proving its value in localizing nonpalpable breast lesions. It also offers accurate localization of axillary nodes, valuable in the era of targeted axillary dissection. It is a method of visual localization, using a skill and equipment surgeons already have, and saves patients and medical systems an additional schedule-disruptive, painful procedure, especially valuable when using novel localization devices is cost-prohibitive.

Ultrasound for Breast Cancer Screening in Resource-Limited Settings: Current Practice and Future Directions

Breast cancer (BC) is the most prevalent cancer among women globally. Cancer screening can reduce mortality and improve women’s health. In developed countries, mammography (MAM) has been primarily utilized for population-based BC screening for several decades. However, it is usually unavailable in low-resource settings due to the lack of equipment, personnel, and time necessary to conduct and interpret the examinations. Ultrasound (US) with high detection sensitivity for women of younger ages and with dense breasts has become a supplement to MAM for breast examination. Some guidelines suggest using US as the primary screening tool in certain settings where MAM is unavailable and infeasible, but global recommendations have not yet reached a unanimous consensus. With the development of smart devices and artificial intelligence (AI) in medical imaging, clinical applications and preclinical studies have shown the potential of US combined with AI in BC screening. Nevertheless, there are few comprehensive reviews focused on the role of US in screening BC in underserved conditions, especially in technological, economical, and global perspectives. This work presents the benefits, limitations, advances, and future directions of BC screening with technology-assisted and resource-appropriate strategies, which may be helpful to implement screening initiatives in resource-limited countries.