Cost-Effectiveness of Digital Breast Tomosynthesis vs. Abbreviated Breast MRI for Screening Women with Intermediate Risk of Breast Cancer-How Low-Cost Must MRI Be?

Optimized, Person-Centered Workflow Design for a High-Throughput Breast MRI Screening Facility-A Simulation Study

OBJECTIVES

This project aims to model an optimal scanning environment for breast magnetic resonance imaging (MRI) screening based on real-life data to identify to what extent the logistics of breast MRI can be optimized.

MATERIALS AND METHODS

A novel concept for a breast MRI screening facility was developed considering layout of the building, workflow steps, used resources, and MRI protocols. The envisioned screening facility is person centered and aims for an efficient workflow-oriented design. Real-life data, collected from existing breast MRI screening workflows, during 62 scans in 3 different hospitals, were imported into a 3D simulation software for designing and testing new concepts. The model provided several realistic, virtual, logistical pathways for MRI screening and their outcome measures: throughput, waiting times, and other relevant variables.

RESULTS

The total average appointment time in the baseline scenario was 25:54 minutes, with 19:06 minutes of MRI room occupation. Simulated improvements consisted of optimizing processes and resources, facility layout, and scanning protocol. In the simulation, time spent in the MRI room was reduced by introducing an optimized facility layout, dockable tables, and adoption of an abbreviated MRI scanning protocol. The total average appointment time was reduced to 19:36 minutes, and in this scenario, the MRI room was occupied for 06:21 minutes. In the most promising scenario, screening of about 68 people per day (10 hours) on a single MRI scanner could be feasible, compared with 36 people per day in the baseline scenario.

CONCLUSIONS

This study suggests that by optimizing workflow MRI for breast screening total appointment duration and MRI occupation can be reduced. A throughput of up to 6 people per hour may be achieved, compared with 3 people per hour in the current setup.

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.

New Approaches and Recommendations for Risk-Adapted Breast Cancer Screening

Population-based breast cancer screening using mammography as the gold standard imaging modality has been in clinical practice for over 40 years. However, the limitations of mammography in terms of sensitivity and high false-positive rates, particularly in high-risk women, challenge the indiscriminate nature of population-based screening. Additionally, in light of expanding research on new breast cancer risk factors, there is a growing consensus that breast cancer screening should move toward a risk-adapted approach. Recent advancements in breast imaging technology, including contrast material-enhanced mammography (CEM), ultrasound (US) (automated-breast US, Doppler, elastography US), and especially magnetic resonance imaging (MRI) (abbreviated, ultrafast, and contrast-agent free), may provide new opportunities for risk-adapted personalized screening strategies. Moreover, the integration of artificial intelligence and radiomics techniques has the potential to enhance the performance of risk-adapted screening. This review article summarizes the current evidence and challenges in breast cancer screening and highlights potential future perspectives for various imaging techniques in a risk-adapted breast cancer screening approach. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 5.

Breast MRI - The champion in the millimeter league: MIO breast MRI - The method of choice in women with dense breasts

We perform MRI of the breast as a first pass technique. We successfully established 10-minute-protocols (including T2 images) with a fixed dosage of 5 ml 1 M CM. A high spatial resolution of 526 × 526, better 672 × 672 or maximum (1.024 × 1.024, MIO MRI) is vital to achieve best results. We use fixation tools to avoid motion artifacts. Motion correction algorithms can, however, often eliminate such artifacts when they are present. In initial breast MRI exams, morphologic features are the most important criteria for lesion evaluation. If previous exams are available for comparison, the main criteria indicating a suspicious lesion are an increase in lesion size or the depiction of new lesions. High quality HR MRI of the breast is the method of choice in women with dense or extremely dense breasts in all cases (screening, assessment, follow up). In density type A or B, MRI can be helpful in defined constellations, e.g. when MX and US are limited or contraindicated. According to our experience, 95% or more of all carcinomas of the breast are detectable on MRI. The remaining 5% of MRI-occult lesions are intraductal tumors or very small invasive carcinomas depicted with mammography due to associated microcalcifications. MRI is, however, superior to all other imaging modalities in the detection of the clinically relevant DCIS (high risk DCIS, intermediate type). Consecutive MRI examinations in intervals of 12 to 24 months allow a reliable detection of invasive breast cancer with an average size of 7-8 mm. This corresponds to a rate of metastasis-free locoregional lymph nodes in >95% of cases. The rate of interval cancers is <2%. In conclusion, this strategy may increase the overall-lifetime survival of breast cancer patients to more than 95%. Inversely, mortality may be reduced to <5%. Taking these improvements in early breast cancer detection and survival that can be achieved through the implementation of QA HR MRI of the breast into account, it should be discussed to modify oncologic guidelines for the treatment of breast cancer. MRI is the best diagnostic tool we have and according to our experience, a first pass, quality-assured high-resolution breast MRI protocol provides best diagnostic results at minimal procedural effort.

Breast MRI: does a clinical decision algorithm outweigh reader experience?

Objectives

Due to its high sensitivity, DCE MRI of the breast (MRIb) is increasingly used for both screening and assessment purposes. The Kaiser score (KS) is a clinical decision algorithm, which formalizes and guides diagnosis in breast MRI and is expected to compensate for lesser reader experience. The aim was to evaluate the diagnostic performance of untrained residents using the KS compared to off-site radiologists experienced in breast imaging using only MR BI-RADS.

Methods

Three off-site, board-certified radiologists, experienced in breast imaging, interpreted MRIb according to the MR BI-RADS scale. The same studies were read by three residents in radiology without prior training in breast imaging using the KS. All readers were blinded to clinical information. Histology was used as the gold standard. Statistical analysis was conducted by comparing the AUC of the ROC curves.

Results

A total of 80 women (median age 52 years) with 93 lesions (32 benign, 61 malignant) were included. The individual within-group performance of the three expert readers (AUC 0.723–0.742) as well as the three residents was equal (AUC 0.842–0.928), p > 0.05, respectively. But, the rating of each resident using the KS significantly outperformed the experts’ ratings using the MR BI-RADS scale (p ≤ 0.05).

Conclusion

The KS helped residents to achieve better results in reaching correct diagnoses than experienced radiologists empirically assigning MR BI-RADS categories in a clinical “problem solving MRI” setting. These results support that reporting breast MRI benefits more from using a diagnostic algorithm rather than expert experience.

Key Points

• Reporting breast MRI benefits more from using a diagnostic algorithm rather than expert experience in a clinical “problem solving MRI” setting.

• The Kaiser score, which provides a clinical decision algorithm for structured reporting, helps residents to reach an expert level in breast MRI reporting and to even outperform experienced radiologists using MR BI-RADS without further formal guidance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-022-09015-8.

Using deep learning to safely exclude lesions with only ultrafast breast MRI to shorten acquisition and reading time

OBJECTIVES

To investigate the feasibility of automatically identifying normal scans in ultrafast breast MRI with artificial intelligence (AI) to increase efficiency and reduce workload.

METHODS

In this retrospective analysis, 837 breast MRI examinations performed on 438 women from April 2016 to October 2019 were included. The left and right breasts in each examination were labelled normal (without suspicious lesions) or abnormal (with suspicious lesions) based on final interpretation. Maximum intensity projection (MIP) images of each breast were then used to train a deep learning model. A high sensitivity threshold was calculated based on the detection trade - off (DET) curve on the validation set. The performance of the model was evaluated by receiver operating characteristic analysis of the independent test set. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with the high sensitivity threshold were calculated.

RESULTS

The independent test set consisted of 178 examinations of 149 patients (mean age, 44 years ± 14 [standard deviation]). The trained model achieved an AUC of 0.81 (95% CI: 0.75-0.88) on the independent test set. Applying a threshold of 0.25 yielded a sensitivity of 98% (95% CI: 90%; 100%), an NPV of 98% (95% CI: 89%; 100%), a workload reduction of 15.7%, and a scan time reduction of 16.6%.

CONCLUSION

This deep learning model has a high potential to help identify normal scans in ultrafast breast MRI and thereby reduce radiologists' workload and scan time.

KEY POINTS

• Deep learning in TWIST may eliminate the necessity of additional sequences for identifying normal breasts during MRI screening. • Workload and scanning time reductions of 15.7% and 16.6%, respectively, could be achieved with the cost of 1 (1 of 55) false negative prediction.

Evidence-Based and Structured Diagnosis in Breast MRI using the Kaiser Score

BACKGROUND

 Breast MRI is the most sensitive method for the detection of breast cancer and is an integral part of modern breast imaging. On the other hand, interpretation of breast MRI exams is considered challenging due to the complexity of the available information. Clinical decision rules that combine diagnostic criteria in an algorithm can help the radiologist to read breast MRI by supporting objective and largely experience-independent diagnosis.

METHOD

 Narrative review. In this article, the Kaiser Score (KS) as a clinical decision rule for breast MRI is introduced, its diagnostic criteria are defined, and strategies for clinical decision making using the KS are explained and discussed.

RESULTS

 The KS is based on machine learning and has been independently validated by international research. It is largely independent of the examination technique that is used. It allows objective differentiation between benign and malignant contrast-enhancing breast MRI findings using diagnostic BI-RADS criteria taken from T2w and dynamic contrast-enhanced T1w images. A flowchart guides the reader in up to three steps to determine a score corresponding to the probability of malignancy that can be used to assign a BI-RADS category. Individual decision making takes the clinical context into account and is illustrated by typical scenarios.

KEY POINTS

· The KS as an evidence-based decision rule to objectively distinguish benign from malignant breast lesions is based on information contained in T2w und dynamic contrast-enhanced T1w sequences and is largely independent of specific examination protocols.. · The KS diagnostic criteria are in line with the MRI BI-RADS lexicon. We focused on defining a default category to be applied in the case of equivocal imaging criteria.. · The KS reflects increasing probabilities of malignancy and, together with the clinical context, assists individual decision making..

CITATION FORMAT

· Baltzer PA, Krug KB, Dietzel M. Evidence-Based and Structured Diagnosis in Breast MRI using the Kaiser Score. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1829-5985.

Screening MRI in Women at Intermediate Breast Cancer Risk: An Update of the Recent Literature

Guidelines issued by the American Cancer Society (ACS) in 2007 recommend neither for nor against screening MRI in women at intermediate breast cancer risk (15%–20%), including those with dense breast tissue, a history of lobular neoplasia or atypical ductal hyperplasia (ADH), or a prior breast cancer, because of scarce supporting evidence about the utility of MRI in these specific patient populations. However, since the issuance of the ACS guidelines in 2007, multiple investigations have found that women at intermediate risk may be suitable candidates for screening MRI, given the high detection rates of early-stage cancers and acceptable false-positive rates. For women with dense breast tissue, the Dense Tissue and Early Breast Neoplasm Screening trial reported that the incremental cancer detection rate (CDR) by MRI exceeded 16 cancers per 1000 examinations but decreased in the second round of screening; this decrease in CDR, however, occurred alongside a marked decrease in the false-positive rate. For women with lobular neoplasia or ADH, single-institution retrospective analyses have shown CDRs mostly ranging from 11 to 16 cancers per 1000 MRI examinations, with women with lobular carcinoma in situ benefitting more than women with atypical lobular hyperplasia or ADH. For patients with a prior breast cancer, the cancer yield by MRI varies widely but mostly ranges from 8 to 20 cancers per 1000 examinations, with certain subpopulations more likely to benefit, such as those with dense breasts. This article reviews and summarizes more recent studies on MRI screening of intermediate-risk women.

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

OBJECTIVES

Abbreviated breast MRI (AB-MRI) was introduced to reduce both examination and image reading times and to improve cost-effectiveness of breast cancer screening. The aim of this model-based economic study was to analyze the cost-effectiveness of full protocol breast MRI (FB-MRI) vs. AB-MRI in screening women with dense breast tissue for breast cancer.

METHODS

Decision analysis and a Markov model were designed to model the cumulative costs and effects of biennial screening in terms of quality-adjusted life years (QALYs) from a US healthcare system perspective. Model input parameters for a cohort of women with dense breast tissue were adopted from recent literature. The impact of varying AB-MRI costs per examination as well as specificity on the resulting cost-effectiveness was modeled within deterministic sensitivity analyses.

RESULTS

At an assumed cost per examination of $ 263 for AB-MRI (84% of the cost of a FB-MRI examination), the discounted cumulative costs of both MR-based strategies accounted comparably. Reducing the costs of AB-MRI below $ 259 (82% of the cost of a FB-MRI examination, respectively), the incremental cost-effectiveness ratio of FB-MRI exceeded the willingness to pay threshold and the AB-MRI-strategy should be considered preferable in terms of cost-effectiveness.

CONCLUSIONS

Our preliminary findings indicate that AB-MRI may be considered cost-effective compared to FB-MRI for screening women with dense breast tissue for breast cancer, as long as the costs per examination do not exceed 82% of the cost of a FB-MRI examination.

KEY POINTS

• Cost-effectiveness of abbreviated breast MRI is affected by reductions in specificity and resulting false positive findings and increased recall rates. • Abbreviated breast MRI may be cost-effective up to a cost per examination of 82% of the cost of a full protocol examination. • Abbreviated breast MRI could be an economically preferable alternative to full protocol breast MRI in screening women with dense breast tissue.

Optimal Breast Density Characterization Using a Three-Dimensional Automated Breast Densitometry System

Dense breasts are a risk factor for breast cancer. Assessment of breast density is important and radiologist-dependent. We objectively measured mammographic density using the three-dimensional automatic mammographic density measurement device Volpara™ and examined the criteria for combined use of ultrasonography (US). Of 1227 patients who underwent primary breast cancer surgery between January 2019 and April 2021 at our hospital, 441 were included. A case series study was conducted based on patient age, diagnostic accuracy, effects of mammography (MMG) combined with US, size of invasion, and calcifications. The mean density of both breasts according to the Volpara Density Grade (VDG) was 0–3.4% in 2 patients, 3.5–7.4% in 55 patients, 7.5–15.4% in 173 patients, and ≥15.5% in 211 patients. Breast density tended to be higher in younger patients. Diagnostic accuracy of MMG tended to decrease with increasing breast density. US detection rates were not associated with VDG on MMG and were favorable at all densities. The risk of a non-detected result was high in patients without malignant suspicious calcifications. Supplementary use of US for patients without suspicious calcifications on MMG and high breast density, particularly ≥25.5%, could improve the breast cancer detection rate.

Cost-effectiveness of abbreviated-protocol MRI screening for women with mammographically dense breasts in a national breast cancer screening program

Introduction

Magnetic resonance imaging (MRI) has shown the potential to improve the screening effectiveness among women with dense breasts. The introduction of fast abbreviated protocols (AP) makes MRI more feasible to be used in a general population. We aimed to investigate the cost-effectiveness of AP-MRI in women with dense breasts (heterogeneously/extremely dense) in a population-based screening program.

Methods

A previously validated model (SiMRiSc) was applied, with parameters updated for women with dense breasts. Breast density was assumed to decrease with increased age. The base scenarios included six biennial AP-MRI strategies, with biennial mammography from age 50–74 as reference. Fourteen alternative scenarios were performed by varying screening interval (triennial and quadrennial) and by applying a combined strategy of mammography and AP-MRI. A 3% discount rate for both costs and life years gained (LYG) was applied. Model robustness was evaluated using univariate and probabilistic sensitivity analyses.

Results

The six biennial AP-MRI strategies ranged from 132 to 562 LYG per 10,000 women, where more frequent application of AP-MRI was related to higher LYG. The optimal strategy was biennial AP-MRI screening from age 50–65 for only women with extremely dense breasts, producing an incremental cost-effectiveness ratio of € 18,201/LYG. At a threshold of € 20,000/LYG, the probability that the optimal strategy was cost-effective was 79%.

Conclusion

Population-based biennial breast cancer screening with AP-MRI from age 50–65 for women with extremely dense breasts might be a cost-effective alternative to mammography, but is not an option for women with heterogeneously dense breasts.

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AP-MRI can be cost-effective for screening women with extremely dense breast.

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The more frequent the use of AP-MRI, the more life years will be gained.

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Biennial AP-MRI for women with extremely dense breast up to age 65 is optimal.

Cost-Effectiveness of MR-Mammography in Breast Cancer Screening of Women With Extremely Dense Breasts After Two Rounds of Screening

Objectives

To evaluate the cost-effectiveness of MR-mammography (MRM) vs. x-ray based mammography (XM) in two-yearly screening women of intermediate risk for breast cancer in the light of recent literature.

Methods

Decision analysis and Markov modelling were used to compare cumulative costs (in US-$) and outcomes (in QALYs) of MRM vs. XM over the model runtime of 20 years. The perspective of the U.S. healthcare system was selected. Incremental cost-effectiveness ratios (ICER) were calculated and related to a willingness to pay-threshold of $ 100,000 per QALY in order to evaluate the cost-effectiveness. Deterministic and probabilistic sensitivity analyses were conducted to test the impact of variations of the input parameters. In particular, variations of the rate of false positive findings beyond the first screening round and their impact on cost-effectiveness were assessed.

Results

Breast cancer screening with MRM resulted in increased costs and superior effectiveness. Cumulative average costs of $ 6,081 per woman and cumulative effects of 15.12 QALYs were determined for MRM, whereas screening with XM resulted in costs of $ 5,810 and 15.10 QALYs, resulting in an ICER of $ 13,493 per QALY gained. When the specificity of MRM in the second and subsequent screening rounds was varied from 92% to 99%, the ICER resulted in a range from $ 38,849 to $ 5,062 per QALY.

Conclusions

Based on most recent data on the diagnostic performance beyond the first screening round, MRM may remain the economically preferable alternative in screening women of intermediate risk for breast cancer due to their dense breast tissue.