Objectives
To evaluate the potential of artificial intelligence (AI) to identify normal mammograms in a screening population.
Methods
In this retrospective study, 9581 double-read mammography ...screening exams including 68 screen-detected cancers and 187 false positives, a subcohort of the prospective population-based Malmö Breast Tomosynthesis Screening Trial, were analysed with a deep learning–based AI system. The AI system categorises mammograms with a cancer risk score increasing from 1 to 10. The effect on cancer detection and false positives of excluding mammograms below different AI risk thresholds from reading by radiologists was investigated. A panel of three breast radiologists assessed the radiographic appearance, type, and visibility of screen-detected cancers assigned low-risk scores (≤ 5). The reduction of normal exams, cancers, and false positives for the different thresholds was presented with 95% confidence intervals (CI).
Results
If mammograms scored 1 and 2 were excluded from screen-reading, 1829 (19.1%; 95% CI 18.3–19.9) exams could be removed, including 10 (5.3%; 95% CI 2.1–8.6) false positives but no cancers. In total, 5082 (53.0%; 95% CI 52.0–54.0) exams, including 7 (10.3%; 95% CI 3.1–17.5) cancers and 52 (27.8%; 95% CI 21.4–34.2) false positives, had low-risk scores. All, except one, of the seven screen-detected cancers with low-risk scores were judged to be clearly visible.
Conclusions
The evaluated AI system can correctly identify a proportion of a screening population as cancer-free and also reduce false positives. Thus, AI has the potential to improve mammography screening efficiency.
Key Points
• Retrospective study showed that AI can identify a proportion of mammograms as normal in a screening population.
• Excluding normal exams from screening using AI can reduce false positives.
Objective
To assess the performance of one-view digital breast tomosynthesis (DBT) in breast cancer screening.
Methods
The Malmö Breast Tomosynthesis Screening Trial is a prospective population-based ...one-arm study with a planned inclusion of 15000 participants; a random sample of women aged 40–74 years eligible for the screening programme. This is an explorative analysis of the first half of the study population (n = 7500). Participants underwent one-view DBT and two-view digital mammography (DM), with independent double reading and scoring. Primary outcome measures were detection rate, recall rate and positive predictive value (PPV). McNemar's test with 95 % confidence intervals was used.
Results
Breast cancer was found in sixty-eight women. Of these, 46 cases were detected by both modalities, 21 by DBT alone and one by DM alone. The detection rate for one-view DBT was 8.9/1000 screens (95 % CI 6.9 to 11.3) and 6.3/1000 screens (4.6 to 8.3) for two-view DM (p < 0.0001). The recall rate after arbitration was 3.8 % (3.3 to 4.2) for DBT and 2.6 % (2.3 to 3.0) for DM (p < 0.0001). The PPV was 24 % for both DBT and DM.
Conclusion
Our results suggest that one-view DBT might be feasible as a stand-alone screening modality.
Key Points
•
One-view DBT as a stand-alone breast cancer screening modality has not been investigated.
•
One-view DBT increased the cancer detection rate significantly.
•
The recall rate increased significantly but was still low.
•
Breast cancer screening with one-view DBT as a stand-alone modality seems feasible.
Breast density is an independent risk factor for the development of breast cancer and also decreases the sensitivity of mammography for screening. Consequently, women with extremely dense breasts ...face an increased risk of late diagnosis of breast cancer. These women are, therefore, underserved with current mammographic screening programs. The results of recent studies reporting on contrast-enhanced breast MRI as a screening method in women with extremely dense breasts provide compelling evidence that this approach can enable an important reduction in breast cancer mortality for these women and is cost-effective. Because there is now a valid option to improve breast cancer screening, the European Society of Breast Imaging (EUSOBI) recommends that women should be informed about their breast density. EUSOBI thus calls on all providers of mammography screening to share density information with the women being screened. In light of the available evidence, in women aged 50 to 70 years with extremely dense breasts, the EUSOBI now recommends offering screening breast MRI every 2 to 4 years. The EUSOBI acknowledges that it may currently not be possible to offer breast MRI immediately and everywhere and underscores that quality assurance procedures need to be established, but urges radiological societies and policymakers to act on this now. Since the wishes and values of individual women differ, in screening the principles of shared decision-making should be embraced. In particular, women should be counselled on the benefits and risks of mammography and MRI-based screening, so that they are capable of making an informed choice about their preferred screening method.
Key Points
•
The recommendations in Figure 1 summarize the key points of the manuscript
Sweden has a population-based mammography screening programme for women aged 40–74. The objective of this study was to examine the association between mammography screening attendance and ...sociodemographic factors in 15 of Sweden's 21 health care regions. Register-based information was collected on all mammography screening invitations and attendance during 2017 and 2018, and linked to individual-level sociodemographic data from Statistics Sweden. Odds ratios (ORs) and 95% confidence intervals (CIs) for attendance were computed by sociodemographic factor. The study sample included 1.5 million women, aged 40–75, with an overall screening attendance of 81.3%. The lowest odds of attending were found for women living without a partner (OR = 0.52, 95% CI: 0.52–0.53), low-income women (OR = 0.57, 95% CI: 0.56–0.57), and non-Nordic women born in Europe (OR = 0.60, 95% CI: 0.59–0.61). Other groups with lower odds of attending were women whose main source of income was social assistance or benefits (OR = 0.62, 95% CI: 0.62–0.63), those not owning their home (OR = 0.66, 95% CI: 0.66–0.67), and those with low level of education (OR = 0.72, 95% CI: 0.71–0.73). Having multiple of these sociodemographic characteristics further lowered the odds of attending. Although overall mammography screening attendance in Sweden is high, sociodemographic inequalities exist, and efforts should be made to address these. Particular attention should be given to low-income women who live without a partner.
•Mammography screening attendance in Sweden was 81% in 2017–2018.•Sociodemographic inequalities were found for screening attendance.•Having multiple low attendance risk factors further decreased the odds of attending.•Lowest attendance among low-income women who live without a partner.
Purpose
To assess the change in mammography screening attendance in Sweden—overall and in sociodemographic groups at risk of low attendance—after removal of the out-of-pocket fee in 2016.
Methods
...Individual-level data on all screening invitations and attendance between 2014 and 2018 were linked to sociodemographic data from Statistics Sweden. Odds ratios and 95% confidence intervals (CIs) for attendance by time period and sociodemographic factor were computed using mixed logistic regression to account for repeated measures within women. The study sample included 1.4 million women, aged 40–75, who had a mammography screening appointment in 2014–2015 and/or 2017–2018 in 14 of Sweden’s 21 health care regions.
Results
Overall screening attendance was 83.8% in 2014–2015 and 84.1% in 2017–2018 (+ 0.3 percentage points, 95% CI 0.2–0.4). The greatest increase in attendance was observed in non-Nordic women with the lowest income, where attendance rose from 62.9 to 65.8% (+ 2.9 points, 95% CI 2.3–3.6), and among women with four or more risk factors for low attendance, where attendance rose from 59.2 to 62.0% (+ 2.8 points, 95% CI 2.2–3.4).
Conclusion
Screening attendance did not undergo any important increase after implementing free screening, although attendance among some sociodemographic groups increased by almost three percentage points after the policy change.
Purpose
High-performing imaging and predictive markers are warranted to minimize surgical overtreatment of the axilla in breast cancer (BC) patients receiving neoadjuvant chemotherapy (NACT). Here we ...have investigated whether axillary ultrasound (AUS) could identify axillary lymph node (ALN) metastasis (ALNM) pre-NACT and post-NACT for BC. The association of tumor, AUS features and mammographic density (MD) with axillary-pathological complete response (axillary-pCR) post-NACT was also assessed.
Methods
The NeoDense-study cohort (
N
= 202, NACT during 2014–2019), constituted a pre-NACT cohort, whereas patients whom had a cytology verified ALNM pre-NACT and an axillary dissection performed (
N
= 114) defined a post-NACT cohort. AUS characteristics were prospectively collected pre- and post-NACT. The diagnostic accuracy of AUS was evaluated and stratified by histological subtype and body mass index (BMI). Predictors of axillary-pCR were analyzed, including MD, using simple and multivariable logistic regression models.
Results
AUS demonstrated superior performance for prediction of ALNM pre-NACT in comparison to post-NACT, as reflected by the positive predictive value (PPV) 0.94 (95% CI 0.89–0.97) and PPV 0.76 (95% CI 0.62–0.87), respectively. We found no difference in AUS performance according to neither BMI nor histological subtype. Independent predictors of axillary-pCR were: premenopausal status, ER-negativity, HER2-overexpression, and high MD.
Conclusion
Baseline AUS could, to a large extent, identify ALNM; however, post-NACT, AUS was insufficient to determine remaining ALNM. Thus, our results support the surgical staging of the axilla post-NACT. Baseline tumor biomarkers and patient characteristics were predictive of axillary-pCR. Larger, multicenter studies are needed to evaluate the performance of AUS post-NACT.
Abstract
Background
The diagnostic accuracy of digital breast tomosynthesis (DBT) and digital mammography (DM) in breast cancer screening may vary per breast density subgroup. The purpose of this ...study was to evaluate which women, based on automatically assessed breast density subgroups, have the greatest benefit of DBT compared with DM in the prospective Malmö Breast Tomosynthesis Screening Trial.
Materials and methods
The prospective European, Malmö Breast Tomosynthesis Screening Trial (
n
= 14,848, Jan. 27, 2010–Feb. 13, 2015) compared one-view DBT and two-view DM, with consensus meeting before recall. Breast density was assessed in this secondary analysis with the automatic software Laboratory for Individualized Breast Radiodensity Assessment. DBT and DM’s diagnostic accuracies were compared by breast density quintiles of breast percent density (PD) and absolute dense area (DA) with confidence intervals (CI) and McNemar’s test. The association between breast density and cancer detection was analyzed with logistic regression, adjusted for ages < 55 and ≥ 55 years and previous screening participation.
Results
In total, 14,730 women (median age: 58 years; inter-quartile range = 16) were included in the analysis. Sensitivity was higher and specificity lower for DBT compared with DM for all density subgroups. The highest breast PD quintile showed the largest difference in sensitivity and specificity at 81.1% (95% CI 65.8–90.5) versus 43.2% (95% CI 28.7–59.1),
p
< .001 and 95.5% (95% CI 94.7–96.2) versus 97.2% (95% CI 96.6–97.8),
p
< 0.001, respectively. Breast PD quintile was also positively associated with cancer detected via DBT at odds ratio 1.24 (95% CI 1.09–1.42,
p
= 0.001).
Conclusion
Women with the highest breast density had the greatest benefit from digital breast tomosynthesis compared with digital mammography with increased sensitivity at the cost of slightly lower specificity. These results may influence digital breast tomosynthesis’s use in an individualized screening program stratified by, for instance, breast density.
Trial registration
. Trial registration at
https://www.ClinicalTrials.gov
: NCT01091545, registered March 24, 2010.
Objectives
Breast Imaging-Reporting and Data System (BI-RADS) mammographic density categories are associated with considerable interobserver variability. Automated methods of measuring volumetric ...breast density may reduce variability and be valuable in risk and mammographic screening stratification. Our objective was to assess agreement of mammographic density by a volumetric method with the radiologists’ classification.
Methods
Eight thousand seven hundred and eighty-two examinations from the Malmö Breast Tomosynthesis Screening Trial were classified according to BI-RADS, 4th Edition. Volumetric breast density was assessed using automated software for 8433 examinations. Agreement between volumetric breast density and BI-RADS was descriptively analyzed. Agreement between radiologists and between categorical volumetric density and BI-RADS was calculated, rendering kappa values.
Results
The observed agreement between BI-RADS scores of different radiologists was 80.9 % kappa 0.77 (0.76–0.79). A spread of volumetric breast density for each BI-RADS category was seen. The observed agreement between categorical volumetric density and BI-RADS scores was 57.1 % kappa 0.55 (0.53-0.56).
Conclusions
There was moderate agreement between volumetric density and BI-RADS scores from European radiologists indicating that radiologists evaluate mammographic density differently than software. The automated method may be a robust and valuable tool; however, differences in interpretation between radiologists and software require further investigation.
Key Points
•
Agreement between qualitative and software density measurements has not been frequently studied.
•
There was substantial agreement between different radiologists´ qualitative density assessments.
•
There was moderate agreement between software and radiologists’ density assessments.
•
Differences in interpretation between software and radiologists require further investigation.
Mammographic tumour appearance may provide prognostic useful information. For example, spiculation indicates invasiveness, but also better survival compared to tumours with other appearances. We ...aimed to study the relationship between mammographic tumour appearance and established clinicopathological factors, including surrogate molecular breast cancer subtypes, in the large Malmö Diet and Cancer Study. A total of 1116 women with invasive breast cancer, diagnosed between 1991 and 2014, were included. Mammographic tumour appearance in relation to status for oestrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2, histological grade, Ki67 and molecular subtype was analysed using various regression models. All models were adjusted for relevant confounders, including breast density, which can affect mammographic appearance. The results consistently showed that spiculated tumours are indicative of favourable characteristics, as they are more likely to be ER and PR positive, and more often exhibit lower histological grade and lower Ki67 expression. Furthermore, spiculated tumours tend to be of luminal A-like subtype, which is associated with a good prognosis. The establishment of associations between mammographic tumour appearance and clinico-pathological factors may aid in characterizing breast cancer at an earlier stage. This could contribute to more individualized breast cancer treatment in the future.
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