Economic potential of abbreviated breast MRI for screening women with dense breast tissue for breast cancer

Localization of contrast-enhanced breast lesions in ultrafast screening MRI using deep convolutional neural networks

OBJECTIVES

To develop a deep learning-based method for contrast-enhanced breast lesion detection in ultrafast screening MRI.

MATERIALS AND METHODS

A total of 837 breast MRI exams of 488 consecutive patients were included. Lesion's location was independently annotated in the maximum intensity projection (MIP) image of the last time-resolved angiography with stochastic trajectories (TWIST) sequence for each individual breast, resulting in 265 lesions (190 benign, 75 malignant) in 163 breasts (133 women). YOLOv5 models were fine-tuned using training sets containing the same number of MIP images with and without lesions. A long short-term memory (LSTM) network was employed to help reduce false positive predictions. The integrated system was then evaluated on test sets containing enriched uninvolved breasts during cross-validation to mimic the performance in a screening scenario.

RESULTS

In five-fold cross-validation, the YOLOv5x model showed a sensitivity of 0.95, 0.97, 0.98, and 0.99, with 0.125, 0.25, 0.5, and 1 false positive per breast, respectively. The LSTM network reduced 15.5% of the false positive prediction from the YOLO model, and the positive predictive value was increased from 0.22 to 0.25.

CONCLUSIONS

A fine-tuned YOLOv5x model can detect breast lesions on ultrafast MRI with high sensitivity in a screening population, and the output of the model could be further refined by an LSTM network to reduce the amount of false positive predictions.

CLINICAL RELEVANCE STATEMENT

The proposed integrated system would make the ultrafast MRI screening process more effective by assisting radiologists in prioritizing suspicious examinations and supporting the diagnostic workup.

KEY POINTS

• Deep convolutional neural networks could be utilized to automatically pinpoint breast lesions in screening MRI with high sensitivity. • False positive predictions significantly increased when the detection models were tested on highly unbalanced test sets with more normal scans. • Dynamic enhancement patterns of breast lesions during contrast inflow learned by the long short-term memory networks helped to reduce false positive predictions.

Contrast-enhanced breast imaging: Current status and future challenges

BACKGROUND

Contrast-enhanced breast MRI and recently also contrast-enhanced mammography (CEM) are available for breast imaging. The aim of the current overview is to explore existing evidence and ongoing challenges of contrast-enhanced breast imaging.

METHODS

This narrative provides an introduction to the contrast-enhanced breast imaging modalities breast MRI and CEM. Underlying principle, techniques and BI-RADS reporting of both techniques are described and compared, and the following indications and ongoing challenges are discussed: problem-solving, high-risk screening, supplemental screening in women with extremely dense breast tissue, breast implants, neoadjuvant systemic therapy (NST) response monitoring, MRI-guided and CEM- guided biopsy.

RESULTS

Technique and reporting for breast MRI are standardised, for the newer CEM standardisation is in progress. Similarly, compared to other modalities, breast MRI is well established as superior for problem-solving, screening women at high risk, screening women with extremely dense breast tissue or with implants; and for monitoring response to NST. Furthermore, MRI-guided biopsy is a reliable technique with low long-term false negative rates. For CEM, data is as yet either absent or limited, but existing results in these settings are promising.

CONCLUSION

Contrast-enhanced breast imaging achieves highest diagnostic performance and should be considered essential. Of the two contrast-enhanced modalities, evidence of breast MRI superiority is ample, and preliminary results on CEM are promising, yet CEM warrants further study.

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.

Incorporating Value-Based Decisions in Breast Cancer Treatment Algorithms

Given the excellent prognosis and availability of evidence-based treatment, patients with early-stage breast cancer are at risk of overtreatment. In this review, we summarize key opportunities to incorporate value-based decisions to optimize the delivery of high-value treatment across the breast cancer care continuum.

Challenges and Changes of the Breast Cancer Screening Paradigm

Since four decades mammography is used for early breast cancer detection in asymptomatic women and still remains the gold standard imaging modality. However, population screening programs can be personalized and women can be divided into different groups based on risk factors and personal preferences. The availability of new and evolving imaging modalities, for example, digital breast tomosynthesis, dynamic-contrast-enhanced magnetic resonance imaging (MRI), abbreviated MRI protocols, diffusion-weighted MRI, and contrast-enhanced mammography leads to new challenges and perspectives regarding the feasibility and potential harms of breast cancer screening. The aim of this review is to discuss the current guidelines for different risk groups, to analyze the recent published studies about the diagnostic performance of the imaging modalities and to discuss new developments and future perspectives. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 6.