Initial experience with a next-generation low-field MRI scanner: Potential for breast imaging?

PURPOSE

Broader clinical adoption of breast magnetic resonance imaging (MRI) faces challenges such as limited availability and high procedural costs. Low-field technology has shown promise in addressing these challenges. We report our initial experience using a next-generation scanner for low-field breast MRI at 0.55T.

METHODS

This initial cases series was part of an institutional review board-approved prospective study using a 0.55T scanner (MAGNETOM Free.Max, Siemens Healthcare, Erlangen/Germany: height < 2 m, weight < 3.2 tons, no quench pipe) equipped with a seven-channel breast coil (Noras, Höchberg/Germany). A multiparametric breast MRI protocol consisting of dynamic T1-weighted, T2-weighted, and diffusion-weighted sequences was optimized for 0.55T. Two radiologists with 12 and 20 years of experience in breast MRI evaluated the examinations.

RESULTS

Twelve participants (mean age: 55.3 years, range: 36-78 years) were examined. The image quality was diagnostic in all examinations and not impaired by relevant artifacts. Typical imaging phenotypes were visualized. The scan time for a complete, non-abbreviated breast MRI protocol ranged from 10:30 to 18:40 min.

CONCLUSION

This initial case series suggests that low-field breast MRI is feasible at diagnostic image quality within an acceptable examination time.

Identification of impactful imaging biomarker: Clinical applications for breast and prostate carcinoma

BACKGROUND

 Imaging biomarkers are quantitative parameters from imaging modalities, which are collected noninvasively, allow conclusions about physiological and pathophysiological processes, and may consist of single (monoparametric) or multiple parameters (bi- or multiparametric).

METHOD

 This review aims to present the state of the art for the quantification of multimodal and multiparametric imaging biomarkers. Here, the use of biomarkers using artificial intelligence will be addressed and the clinical application of imaging biomarkers in breast and prostate cancers will be explained. For the preparation of the review article, an extensive literature search was performed based on Pubmed, Web of Science and Google Scholar. The results were evaluated and discussed for consistency and generality.

RESULTS AND CONCLUSION

 Different imaging biomarkers (multiparametric) are quantified based on the use of complementary imaging modalities (multimodal) from radiology, nuclear medicine, or hybrid imaging. From these techniques, parameters are determined at the morphological (e. g., size), functional (e. g., vascularization or diffusion), metabolic (e. g., glucose metabolism), or molecular (e. g., expression of prostate specific membrane antigen, PSMA) level. The integration and weighting of imaging biomarkers are increasingly being performed with artificial intelligence, using machine learning algorithms. In this way, the clinical application of imaging biomarkers is increasing, as illustrated by the diagnosis of breast and prostate cancers.

KEY POINTS

· Imaging biomarkers are quantitative parameters to detect physiological and pathophysiological processes.. · Imaging biomarkers from multimodality and multiparametric imaging are integrated using artificial intelligence algorithms.. · Quantitative imaging parameters are a fundamental component of diagnostics for all tumor entities, such as for mammary and prostate carcinomas..

CITATION FORMAT

· Bäuerle T, Dietzel M, Pinker K et al. Identification of impactful imaging biomarker: Clinical applications for breast and prostate carcinoma. Fortschr Röntgenstr 2024; 196: 354 - 362.

METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII

PURPOSE

To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research quality of radiomics studies.

METHODS

We conducted an online modified Delphi study with a group of international experts. It was performed in three consecutive stages: Stage#1, item preparation; Stage#2, panel discussion among EuSoMII Auditing Group members to identify the items to be voted; and Stage#3, four rounds of the modified Delphi exercise by panelists to determine the items eligible for the METRICS and their weights. The consensus threshold was 75%. Based on the median ranks derived from expert panel opinion and their rank-sum based conversion to importance scores, the category and item weights were calculated.

RESULT

In total, 59 panelists from 19 countries participated in selection and ranking of the items and categories. Final METRICS tool included 30 items within 9 categories. According to their weights, the categories were in descending order of importance: study design, imaging data, image processing and feature extraction, metrics and comparison, testing, feature processing, preparation for modeling, segmentation, and open science. A web application and a repository were developed to streamline the calculation of the METRICS score and to collect feedback from the radiomics community.

CONCLUSION

In this work, we developed a scoring tool for assessing the methodological quality of the radiomics research, with a large international panel and a modified Delphi protocol. With its conditional format to cover methodological variations, it provides a well-constructed framework for the key methodological concepts to assess the quality of radiomic research papers.

CRITICAL RELEVANCE STATEMENT

A quality assessment tool, METhodological RadiomICs Score (METRICS), is made available by a large group of international domain experts, with transparent methodology, aiming at evaluating and improving research quality in radiomics and machine learning.

KEY POINTS

• A methodological scoring tool, METRICS, was developed for assessing the quality of radiomics research, with a large international expert panel and a modified Delphi protocol. • The proposed scoring tool presents expert opinion-based importance weights of categories and items with a transparent methodology for the first time. • METRICS accounts for varying use cases, from handcrafted radiomics to entirely deep learning-based pipelines. • A web application has been developed to help with the calculation of the METRICS score ( https://metricsscore.github.io/metrics/METRICS.html ) and a repository created to collect feedback from the radiomics community ( https://github.com/metricsscore/metrics ).

Added value of clinical decision rules for the management of enhancing breast MRI lesions: A systematic comparison of the Kaiser score and the Göttingen score

PURPOSE

We investigated the added value of two internationally used clinical decision rules in the management of enhancing lesions on breast MRI.

METHODS

This retrospective, institutional review board approved study included consecutive patients from two different populations. Patients received breast MRI according to the recommendations of the European Society of Breast Imaging (EUSOBI). Initially, all examinations were assessed by expert readers without using clinical decision rules. All lesions rated as category 4 or 5 according to the Breast Imaging Reporting and Data System were histologically confirmed. These lesions were re-evaluated by an expert reader blinded to the histology. He assigned each lesion a Göttingen score (GS) and a Kaiser score (KS) on different occasions. To provide an estimate on inter-reader agreement, a second fellowship-trained reader assessed a subset of these lesions. Subgroup analyses based on lesion type (mass vs. non-mass), size (>1 cm vs. ≤ 1 cm), menopausal status, and significant background parenchymal enhancement were conducted. The areas under the ROC curves (AUCs) for the GS and KS were compared, and the potential to avoid unnecessary biopsies was determined according to previously established cutoffs (KS > 4, GS > 3) RESULTS: 527 lesions in 506 patients were included (mean age: 51.8 years, inter-quartile-range: 43.0-61.0 years). 131/527 lesions were malignant (24.9 %; 95 %-confidence-interval: 21.3-28.8). In all subgroups, the AUCs of the KS (median = 0.91) were higher than those of the GS (median = 0.83). Except for "premenopausal patients" (p = 0.057), these differences were statistically significant (p ≤ 0.01). Kappa agreement was higher for the KS (0.922) than for the GS (0.358).

CONCLUSION

Both the KS and the GS provided added value for the management of enhancing lesions on breast MRI. The KS was superior to the GS in terms of avoiding unnecessary biopsies and showed superior inter-reader agreement; therefore, it may be regarded as the clinical decision rule of choice.

Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI database

OBJECTIVES

To develop an intuitive and generally applicable system for the reporting, assessment, and documentation of ADC to complement standard BI-RADS criteria.

METHODS

This was a multicentric, retrospective analysis of 11 independently conducted institutional review board-approved studies from seven institutions performed between 2007 and 2019. Breast Apparent Diffusion coefficient (ADC-B) categories comprised ADC-B0 (ADC non-diagnostic), ADC-B1 (no enhancing lesion), and ADC-B2-5. The latter was defined by plotting ADC versus cumulative malignancy rates. Statistics comprised ANOVA with post hoc testing and ROC analysis. p values ≤ 0.05 were considered statistically significant.

RESULTS

A total of 1625 patients (age: 55.9 years (± 13.8)) with 1736 pathologically verified breast lesions were included. The mean ADC (× 10-3 mm2/s) differed significantly between benign (1.45, SD .40) and malignant lesions (.95, SD .39), and between invasive (.92, SD .22) and in situ carcinomas (1.18, SD .30) (p < .001). The following ADC-B categories were identified: ADC-B0-ADC cannot be assessed; ADC-B1-no contrast-enhancing lesion; ADC-B2-ADC ≥ 1.9 (cumulative malignancy rate < 0.1%); ADC-B3-ADC 1.5 to < 1.9 (0.1-1.7%); ADC-B4-ADC 1.0 to < 1.5 (10-24.5%); and ADC-B5-ADC < 1.0 (> 24.5%). At the latter threshold, a positive predictive value of 95.8% (95% CI 0.94-0.97) for invasive versus non-invasive breast carcinomas was reached.

CONCLUSIONS

The breast apparent diffusion coefficient system (ADC-B) provides a simple and widely applicable categorization scheme for assessment, documentation, and reporting of apparent diffusion coefficient values in contrast-enhancing breast lesions on MRI.

CLINICAL RELEVANCE STATEMENT

The ADC-B system, based on diverse MRI examinations, is clinically relevant for stratifying breast cancer risk via apparent diffusion coefficient measurements, and complements BI-RADS for improved clinical decision-making and patient outcomes.

KEY POINTS

• The breast apparent diffusion coefficient category system (ADC-B) is a simple tool for the assessment, documentation, and reporting of ADC values in contrast-enhancing breast lesions on MRI. • The categories comprise ADC-B0 for non-diagnostic examinations, ADC-B1 for examinations without an enhancing lesion, and ADC-B2-5 for enhancing lesions with an increasing malignancy rate. • The breast apparent diffusion coefficient category system may be used to complement BI-RADS in clinical decision-making.

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.

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.

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.

Potential of spiral breast computed tomography to increase patient comfort compared to DM

PURPOSE

To intra-individually compare patient comfort of spiral breast computed tomography (SBCT) versus digital mammography (DM).

METHOD

This prospective IRB approved study included 79 patients undergoing both SBCT and DM for the assessment of BI-RADS 4 - 6 lesions. Following SBCT and DM patients answered a standardized questionnaire regarding "Overall patient comfort" and "Pain" on a 5-point Likert Scale. On the same Likert Scale, experienced radiologic technicians rated the workflow of the SBCT regarding patients' "Mobility", ease of patient "Positioning", patients' adherence to the examination ("Compliance") and expected image quality. Visibility of fibroglandular tissue in SBCT was independently rated by two breast radiologists on a 10-point Likert Scale. Subgroups stratified by menopausal status and body mass index (BMI) were analyzed.

RESULTS

Patients reported significantly lower pain during SBCT (4.73 ± 0.57) compared to DM (4.09 ± 0.90; P < 0.01). This effect was independent from BMI. However, pain reduction by SBCT was most pronounced in premenopausal (SBCT vs. DM: 4.79 ± 0.50 vs. 3.89 ± 0.99) compared to postmenopausal patients (4.71 ± 0.77 vs. 4.20 ± 0.89). Overall patient comfort in premenopausal patients tended to be higher in SBCT compared to DM (P = 0.08). Radiologic technicians rated the SBCT procedure generally as positive (average: 4.62 ± 0.56). Coverage of fibroglandular tissue in SBCT was generally high (9.82 ± 0.43) and interrater agreement was good (κ = 0.77).

CONCLUSIONS

Patients experience less pain during spiral breast computed tomography compared to DM, especially in premenopausal women. Imaging is feasible at a high level of anatomical breast coverage and without problems with the clinical workflow.

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.

A Multicentric Comparison of Apparent Diffusion Coefficient Mapping and the Kaiser Score in the Assessment of Breast Lesions

MATERIALS AND METHODS

In this multicentric study, individual patient data from 3 different centers were analyzed. Consecutive patients receiving standardized multiparametric breast magnetic resonance imaging for standard nonscreening indications were included. At each center, 2 experienced radiologists with more than 5 years of experience retrospectively interpreted the examinations in consensus and applied the KS to every histologically verified lesion. The corresponding mean ADC of each lesion was measured using a Wielema type 4 region of interest. According to established methods, the KS and ADC were combined, yielding the KS+ score. Diagnostic accuracy was evaluated by the area under the receiver operating characteristics curve (AUROC) and compared between the KS, ADC, and KS+ (DeLong test). Likewise, the potential to help avoid unnecessary biopsies was compared between the KS, ADC, and KS+ based on established high sensitivity thresholds (McNemar test).

RESULTS

A total of 450 lesions in 414 patients (mean age, 51.5 years; interquartile range, 42-60.8 years) were included, with 219 lesions being malignant (48.7%; 95% confidence interval [CI], 44%-53.4%). The performance of the KS (AUROC, 0.915; CI, 0.886-0.939) was significantly better than that of the ADC (AUROC, 0.848; CI, 0.811-0.880; P < 0.001). The largest difference between these parameters was observed when assessing subcentimeter lesions (AUROC, 0.909 for KS; CI, 0.849-0.950 vs 0.811 for ADC; CI, 0.737-0.871; P = 0.02).The use of the KS+ (AUROC, 0.918; CI, 0.889-0.942) improved the performance slightly, but without any significant difference relative to a single KS or ADC reading (P = 0.64).When applying high sensitivity thresholds for avoiding unnecessary biopsies, the KS and ADC achieved equal sensitivity (97.7% for both; cutoff values, >4 for KS and ≤1.4 × 10-3 mm2/s for ADC). However, the rate of potentially avoidable biopsies was higher when using the KS (specificity: 65.4% for KS vs 32.9% for ADC; P < 0.0001). The KS was superior to the KS+ in avoiding unnecessary biopsies.

CONCLUSIONS

Both the KS and ADC may be used to distinguish benign from malignant breast lesions. However, KS proved superior in this task including, most of all, when assessing small lesions less than 1 cm. Using the KS may avoid twice as many unnecessary biopsies, and the combination of both the KS and ADS does not improve diagnostic performance.

Diffusion-weighted Imaging Allows for Downgrading MR BI-RADS 4 Lesions in Contrast-enhanced MRI of the Breast to Avoid Unnecessary Biopsy

PURPOSE

Diffusion-weighted imaging with the calculation of an apparent diffusion coefficient (ADC) has been proposed as a quantitative biomarker on contrast-enhanced MRI (CE-MRI) of the breast. There is a need to approve a generalizable ADC cutoff. The purpose of this study was to evaluate whether a predefined ADC cutoff allows downgrading of BI-RADS 4 lesions on CE-MRI, avoiding unnecessary biopsies.

EXPERIMENTAL DESIGN

This was a retrospective, multicentric, cross-sectional study. Data from five centers were pooled on the individual lesion level. Eligible patients had a BI-RADS 4 rating on CE-MRI. For each center, two breast radiologists evaluated the images. Data on lesion morphology (mass, non-mass), size, and ADC were collected. Histology was the standard of reference. A previously suggested ADC cutoff (≥1.5 × 10-3 mm2/second) was applied. A negative likelihood ratio of 0.1 or lower was considered as a rule-out criterion for breast cancer. Diagnostic performance indices were calculated by ROC analysis.

RESULTS

There were 657 female patients (mean age, 42; SD, 14.1) with 696 BI-RADS 4 lesions included. Disease prevalence was 59.5% (414/696). The area under the ROC curve was 0.784. Applying the investigated ADC cutoff, sensitivity was 96.6% (400/414). The potential reduction of unnecessary biopsies was 32.6% (92/282).

CONCLUSIONS

An ADC cutoff of ≥1.5 × 10-3 mm2/second allows downgrading of lesions classified as BI-RADS 4 on breast CE-MRI. One-third of unnecessary biopsies could thus be avoided.

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?

BACKGROUND

Digital breast tomosynthesis (DBT) and abbreviated breast MRI (AB-MRI) offer superior diagnostic performance compared to conventional mammography in screening women with intermediate risk of breast cancer due to dense breast tissue. The aim of this model-based economic evaluation was to analyze whether AB-MRI is cost-effective in this cohort compared to DBT.

METHODS

Decision analysis and Markov simulations were used to model the cumulative costs and quality-adjusted life-years (QALYs) over a time horizon of 30 years. Model input parameters were adopted from recent literature. Deterministic and probabilistic sensitivity analyses were applied to test the stability of the model.

RESULTS

In the base-case scenario, the costs of an AB-MRI examination were defined to equal the costs of a full protocol acquisition. Two-yearly screening of women with dense breasts resulted in cumulative discounted costs of $8798 and $9505 for DBT and AB-MRI, and cumulative discounted effects of 19.23 and 19.27 QALYs, respectively, with an incremental cost-effectiveness ratio of $20,807 per QALY gained in the base-case scenario. By reducing the cost of an AB-MRI examination below a threshold of $241 in sensitivity analyses, AB-MRI would become cost-saving compared to DBT.

CONCLUSION

In comparison to DBT, AB-MRI can be considered cost-effective up to a price per examination of $593 in screening patients at intermediate risk of breast cancer.

Images Are Data: A Breast Imaging Perspective on a Contemporary Paradigm

BACKGROUND

 Considering radiological examinations not as mere images, but as a source of data, has become the key paradigm in the diagnostic imaging field. This change of perspective is particularly popular in breast imaging. It allows breast radiologists to apply algorithms derived from computer science, to realize innovative clinical applications, and to refine already established methods. In this context, the terminology "imaging biomarker", "radiomics", and "artificial intelligence" are of pivotal importance. These methods promise noninvasive, low-cost (e. g., in comparison to multigene arrays), and workflow-friendly (automated, only one examination, instantaneous results, etc.) delivery of clinically relevant information.

METHODS AND RESULTS

 This paper is designed as a narrative review on the previously mentioned paradigm. The focus is on key concepts in breast imaging and important buzzwords are explained. For all areas of breast imaging, exemplary studies and potential clinical use cases are discussed.

CONCLUSION

 Considering radiological examination as a source of data may optimize patient management by guiding individualized breast cancer diagnosis and oncologic treatment in the age of precision medicine.

KEY POINTS

  · In conventional breast imaging, examinations are interpreted based on patterns perceivable by visual inspection.. · The radiomics paradigm treats breast images as a source of data, containing information beyond what is visible to our eyes.. · This results in radiomic signatures that may be considered as imaging biomarkers, as they provide diagnostic, predictive, and prognostic information.. · Radiomics derived imaging biomarkers may be used to individualize breast cancer treatment in the era of precision medicine.. · The concept and key research of radiomics in the field of breast imaging will be discussed in this narrative review..

CITATION FORMAT

· Dietzel M, Clauser P, Kapetas P et al. Images Are Data: A Breast Imaging Perspective on a Contemporary Paradigm. Fortschr Röntgenstr 2021; 193: 898 - 908.

Impact of specificity on cost-effectiveness of screening women at high risk of breast cancer with magnetic resonance imaging, mammography and ultrasound

PURPOSE

Aim of this study was to analyze the comparative cost-effectiveness of MR-mammography vs conventional imaging in a screening setting for women with high risk of breast cancer, with particular focus on the impact of specificity of MRM.

METHOD

Decision analytic modelling and Markov Modelling were applied to evaluate cumulative costs of each screening modality and their subsequent treatments as well as cumulative outcomes in quality adjusted life years (QALYs). For the selected time horizon of 30 years, false positive and false negative results were included. Model input parameters for women with high risk of breast cancer were estimated based on published data from a US healthcare system perspective. Major influence factors were identified and evaluated in a deterministic sensitivity analysis. Based on current recommendations for economic evaluations, a probabilistic sensitivity analysis was conducted to test the model stability.

RESULTS

In a base-case analysis, screening with XM vs. MRM and treatment resulted in overall costs of $36,201.57 vs. $39,050.97 and a cumulative effectiveness of 19.53 QALYs vs. 19.59 QALYs. This led to an incremental cost-effectiveness ratio (ICER) of $ 45,373.94 per QALY for MRM. US and XM + US resulted in ICER values higher than the willingness to pay (WTP). In the sensitivity analyses, MRM remained a cost-effective strategy for screening high-risk patients as long as the specificity of MRM did not drop below 86.7 %.

CONCLUSION

In high-risk breast cancer patients, MRM can be regarded as a cost-effective alternative to XM in a yearly screening setting. Specificity may be an important cost driver in settings with yearly screening intervals.

A decade of radiomics research: are images really data or just patterns in the noise?

KEY POINTS

• Although radiomics is potentially a promising approach to analyze medical image data, many pitfalls need to be considered to avoid a reproducibility crisis.• There is a translation gap in radiomics research, with many studies being published but so far little to no translation into clinical practice.• Going forward, more studies with higher levels of evidence are needed, ideally also focusing on prospective studies with relevant clinical impact.

Cost-effectiveness of MR-mammography vs. conventional mammography in screening patients at intermediate risk of breast cancer - A model-based economic evaluation

PURPOSE

The aim of this study was to analyze the cost-effectiveness of screening patients of intermediate risk of breast cancer with MR-Mammography (MRM) versus conventional mammography (XM).

METHOD

A decision model for both diagnostic modalities and a subsequent markov model for the simulation of follow-up costs and outcomes was developed. Input parameters were acquired from published literature for this markov modelling study. The expected cumulative costs and outcomes were calculated for both modalities in a 30-year timeframe in US-dollar ($) and quality-adjusted life years (QALYs). A deterministic sensitivity analysis and a probabilistic sensitivity analysis incorporating 30,000 Monte Carlo iterations were performed to investigate the model stability.

RESULTS

In total, XM with its consecutive treatments resulted in total costs of $ 5,492.68 and an average cumulative quality of life of 18.87 QALYs, compared to MRM with costs of $ 5,878.66 and 18.92 QALYs. The corresponding incremental cost-effectiveness ratio (ICER) for MRM was $ 8,797.60 per QALY - distinctly below international willingness-to-pay thresholds for cost-effectiveness. The results were confirmed within the limits of the sensitivity analyses.

CONCLUSIONS

In patients with intermediate risk for breast cancer due to their dense breast tissue, two-yearly screening with MRM may be considered as cost-effective.

Clinical relevance of total choline (tCho) quantification in suspicious lesions on multiparametric breast MRI

Purpose

To assess the additional value of quantitative tCho evaluation to diagnose malignancy and lymph node metastases in suspicious lesions on multiparametric breast MRI (mpMRI, BI-RADS 4, and BI-RADS 5).

Methods

One hundred twenty-one patients that demonstrated suspicious multiparametric breast MRI lesions using DCE, T2w, and diffusion-weighted (DW) images were prospectively enrolled in this IRB-approved study. All underwent single-voxel proton MR spectroscopy (¹H-MRS, point-resolved spectroscopy sequence, TR 2000 ms, TE 272 ms) with and without water suppression. The total choline (tCho) amplitude was measured and normalized to millimoles/liter according to established methodology by two independent readers (R1, R2). ROC-analysis was employed to predict malignancy and lymph node status by tCho results.

Results

One hundred three patients with 74 malignant and 29 benign lesions had full ¹H-MRS data. The area under the ROC curve (AUC) for prediction of malignancy was 0.816 (R1) and 0.809 (R2). A cutoff of 0.8 mmol/l tCho could diagnose malignancy with a sensitivity of > 95%. For prediction of lymph node metastases, tCho measurements achieved an AUC of 0.760 (R1) and 0.788 (R2). At tCho levels < 2.4 mmol/l, no metastatic lymph nodes were found.

Conclusion

Quantitative tCho evaluation from ¹H-MRS allowed diagnose malignancy and lymph node status in breast lesions suspicious on multiparametric breast MRI. tCho therefore demonstrated the potential to downgrade suspicious mpMRI lesions and stratify the risk of lymph node metastases for improved patient management.

Key Points

• Quantitative tCho evaluation can distinguish benign from malignant breast lesions suspicious after multiparametric MRI assessment.

• Quantitative tCho levels are associated with lymph node status in breast cancer.

• Quantitative tCho levels are higher in hormonal receptor positive compared to hormonal receptor negative lesions.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-06678-z) contains supplementary material, which is available to authorized users.

Combination of an ultrafast TWIST-VIBE Dixon sequence protocol and diffusion-weighted imaging into an accurate easily applicable classification tool for masses in breast MRI

OBJECTIVES

This study aimed to develop a tool for the classification of masses in breast MRI, based on ultrafast TWIST-VIBE Dixon (TVD) dynamic sequences combined with DWI. TVD sequences allow to abbreviate breast MRI protocols, but provide kinetic information only on the contrast wash-in, and because of the lack of the wash-out kinetics, their diagnostic value might be hampered. A special focus of this study was thus to maintain high diagnostic accuracy in lesion classification.

MATERIALS AND METHODS

Sixty-one patients who received breast MRI between 02/2014 and 04/2015 were included, with 83 reported lesions (60 malignant). Our institute's standard breast MRI protocol was complemented by an ultrafast TVD sequence. ADC and peak enhancement of the TVD sequences were integrated into a generalised linear model (GLM) for malignancy prediction. For comparison, a second GLM was calculated using ADC and conventional DCE curve type. The resulting GLMs were evaluated for standard diagnostic parameters. For easy application of the GLMs, nomograms were created.

RESULTS

The GLM based on peak enhancement of the TVD and ADC was as equally accurate as the GLM based on conventional DCE and ADC, with no significant differences (sensitivity, 93.3%/93.3%; specificity, 91.3%/87.0%; PPV, 96.6%/94.9%; NPV, 84.0%/83.3%; all, p ≥ 0.315).

CONCLUSIONS

This study presents a method to integrate ultrafast TVD sequences into a breast MRI protocol, allowing a reduction of the examination time while maintaining diagnostic accuracy. A GLM based on the combination of TVD-derived peak enhancement and ADC provides high diagnostic accuracy, and can be easily applied using a nomogram.

KEY POINTS

• Ultrafast TWIST-VIBE Dixon sequence protocols in combination with diffusion-weighted imaging allow to shorten breast MRI examinations, while diagnostic accuracy is maintained. • Integrating peak enhancement from the TWIST-VIBE Dixon sequence and the apparent diffusion coefficient into a generalised linear model provides a comprehensible image evaluation approach. • This approach is further facilitated by nomograms.

Implementation of machine learning into clinical breast MRI: Potential for objective and accurate decision-making in suspicious breast masses

We investigated whether the integration of machine learning (ML) into MRI interpretation can provide accurate decision rules for the management of suspicious breast masses. A total of 173 consecutive patients with suspicious breast masses upon complementary assessment (BI-RADS IV/V: n = 100/76) received standardized breast MRI prior to histological verification. MRI findings were independently assessed by two observers (R1/R2: 5 years of experience/no experience in breast MRI) using six (semi-)quantitative imaging parameters. Interobserver variability was studied by ICC (intraclass correlation coefficient). A polynomial kernel function support vector machine was trained to differentiate between benign and malignant lesions based on the six imaging parameters and patient age. Ten-fold cross-validation was applied to prevent overfitting. Overall diagnostic accuracy and decision rules (rule-out criteria) to accurately exclude malignancy were evaluated. Results were integrated into a web application and published online. Malignant lesions were present in 107 patients (60.8%). Imaging features showed excellent interobserver variability (ICC: 0.81–0.98) with variable diagnostic accuracy (AUC: 0.65–0.82). Overall performance of the ML algorithm was high (AUC = 90.1%; BI-RADS IV: AUC = 91.6%). The ML algorithm provided decision rules to accurately rule-out malignancy with a false negative rate <1% in 31.3% of the BI-RADS IV cases. Thus, integration of ML into MRI interpretation can provide objective and accurate decision rules for the management of suspicious breast masses, and could help to reduce the number of potentially unnecessary biopsies.

Breast MRI in the era of diffusion weighted imaging: do we still need signal-intensity time curves?

Objective

Dynamic contrast-enhanced imaging of the initial (IP) and delayed phase (DP) is an integral part of any clinical breast MRI protocol. Furthermore, DWI is increasingly used as an add-on sequence by the breast-imaging community. We investigated whether DWI could be used as a substitute DP.

Material and methods

One hundred thirty-two consecutive patients with equivocal or suspicious findings at ultrasound and/or mammography received a full diagnostic breast MRI according to international recommendations. Histopathological verification served as reference standard. We evaluated three sections of the MRI protocol: IP, DP, and apparent diffusion coefficient (ADC) maps derived from DWI. Circular ROIs (regions of interest, mean size 5–10 mm²) were drawn into the enhancing parts of the lesion (first postcontrast). ROIs were transferred to the corresponding location on ADC maps and IP and DP images. Mean ROI values were investigated signal intensity (SI): (1) Initial-phase enhancement = (SI(IP) − SI(precontrast))/SI(precontrast); (2) Delayed-phase enhancement = (SI(DP) − SI(IP))/SI(IP); (3) ADC. Multiparametric combinations were computed using logistic regression analysis: (1) IP+: Initial-phase enhancement and ADC; (2) Curve: Initial-phase enhancement and delayed-phase enhancement; (3) Curve+: Curve and ADC. The diagnostic performances of these feature combinations to diagnose malignancy were compared by the area under the receiver-operating characteristics curve (AUC).

Results

One hundred thirty-two patients (age: mean = 57.1 years, range 23–83 years) with 145 lesions were included (malignant/benign 101/44). IP+ (AUC = 0.877) outperformed Curve (AUC = 0.788, p = 0.03). Curve+ was not superior to IP+ (p = 1).

Conclusion

DWI could substitute DP. Because DWI is typically used as an add-on to IP and DP, our results might help to abbreviate and to simplify current practice of breast MRI.

Key Points

• DWI provides similar but superior diagnostic information for diagnosis of malignancy in enhancing breast lesions compared to DP.

• Adding DP to DWI does not provide incremental information to distinguish benign from malignant lesions.

• DWI could substitute DP. As DWI is typically used as an add-on to IP and DP, our findings might help to abbreviate and to simplify current breast MRI practice.

Motion artifacts, lesion type, and parenchymal enhancement in breast MRI: what does really influence diagnostic accuracy?

BACKGROUND

Motion artifacts can reduce image quality of breast magnetic resonance imaging (MRI). There is a lack of data regarding their effect on diagnostic estimates.

PURPOSE

To evaluate factors that potentially influence readers' diagnostic estimates in breast MRI: motion artifacts; amount of fibroglandular tissue; background parenchymal enhancement; lesion size; and lesion type.

MATERIAL AND METHODS

This Institutional Review Board-approved, retrospective, cross-sectional, single-center study included 320 patients (mean age = 55.1 years) with 334 histologically verified breast lesions (139 benign, 195 malignant) who underwent breast MRI. Two expert breast radiologists evaluated the images considering: motion artifacts (1 = minimal to 4 = marked); fibroglandular tissue (BI-RADS FGT); background parenchymal enhancement (BI-RADS BPE); lesion size; lesion type; and BI-RADS score. Univariate (Chi-square) and multivariate (Generalized Estimation Equations [GEE]) statistics were used to identify factors influencing sensitivity, specificity, and accuracy.

RESULTS

Lesions were: 230 mass (68.9%) and 59 non-mass (17.7%), no foci. Forty-five lesions (13.5%) did not enhance in MRI but were suspicious or unclear in conventional imaging. Sensitivity, specificity, and accuracy were 93.8%, 83.4%, and 89.8% for Reader 1 and 95.4%, 87.8%, and 91.9% for Reader 2. Lower sensitivity was observed in case of increased motion artifacts ( P = 0.007), non-mass lesions ( P < 0.001), and small lesions ≤ 10 mm ( P < 0.021). No further factors (e.g. BPE, FGT) significantly influenced diagnostic estimates. At multivariate analysis, lesion type and size were retained as independent factors influencing the diagnostic performance ( P < 0.033).

CONCLUSION

Motion artifacts can impair lesion characterization with breast MRI, but lesion type and small size have the strongest influence on diagnostic estimates.

How to use the Kaiser score as a clinical decision rule for diagnosis in multiparametric breast MRI: a pictorial essay

Due to its superior sensitivity, breast MRI (bMRI) has been established as an important additional diagnostic tool in the breast clinic and is used for screening in patients with an elevated risk for breast cancer. Breast MRI, however, is a complex tool, providing multiple images containing several contrasts. Thus, reading bMRI requires a structured approach. A lack of structure will increase the rate of false-positive findings and sacrifice most of the advantages of bMRI as additional work-up will be required. While the BI-RADS (Breast Imaging Reporting And Data System) lexicon is a major step toward standardised and structured reporting, it does not provide a clinical decision rule with which to guide diagnostic decisions. Such a clinical decision rule, however, is provided by the Kaiser score, which combines five independent diagnostic BI-RADS lexicon criteria (margins, SI-time curve type, internal enhancement and presence of oedema) in an intuitive flowchart. The resulting score provides probabilities of malignancy that can be used for evidence-based decision-making in the breast clinic. Notably, considerable benefits have been demonstrated for radiologists with initial and intermediate experience in bMRI. This pictorial essay is a practical guide to the application of the Kaiser score in the interpretation of breast MRI examinations.

TEACHING POINTS

• bMRI requires standardisation of patient-management, protocols, and reading set-up. • Reading bMRI includes the assessment of breast parenchyma, associated findings, and lesions. • Diagnostic decisions should be made according to evidence-based clinical decision rules. • The evidence-based Kaiser score is applicable independent of bMRI protocol and scanner. • The Kaiser score provides high diagnostic accuracy with low inter-observer variability.

MRI for the assessment of malignancy in BI-RADS 4 mammographic microcalcifications

Purpose

Assess the performance of breast MRI to diagnose breast cancer in BI-RADS 4 microcalcifications detected by mammography.

Materials and methods

This retrospective, IRB-approved study included 248 consecutive contrast-enhanced breast MRI (1.5T, protocol in accordance with EUSOBI recommendations) performed to further diagnose BI-RADS 4 microcalcifications detected at mammography during a 3-year period. Standard of reference had to be established by histopathology. Routine consensus reading results by two radiologists were dichotomized as positive or negative and compared with the reference standard (benign vs malignant) to calculate diagnostic parameters.

Results

There were 107 malignant and 141 benign microcalcifications. Malignancy rates were 18.3% (23/126 BI-RADS 4a), 41.7% (25/60 BI-RADS 4b) and 95% (59/62 BI-RADS 4c). There were 103 true-positive, 116 true-negative, 25 false-positive, and 4 false-negative (one invasive cancer, three DCIS; 2 BI-RADS 4c, 1 BI-RADS 4b on mammography) breast MRI findings, effecting a sensitivity, specificity, PPV, and NPV of 96.3% (95%-CI 90.7–99.0%), 82.3% (95%-CI 75.0–88.2%), 80.5% (95%-CI 72.5–87.0%) and 96.7% (95%-CI 91.7–99.1%), respectively.

Conclusion

MRI is an accurate tool to further diagnose BI-RADS 4a and 4b microcalcifications and may be helpful to avoid unnecessary biopsies in BI-RADS 4a and 4b lesions. BI-RADS 4c microcalcifications should be biopsied irrespective of MRI findings.

A survey by the European Society of Breast Imaging on the utilisation of breast MRI in clinical practice

OBJECTIVES

While magnetic resonance imaging (MRI) is considered a helpful diagnostic tool in breast imaging, discussions are ongoing about appropriate protocols and indications. The European Society of Breast Imaging (EUSOBI) launched a survey to evaluate the utilisation of breast MRI in clinical practice.

METHODS

An online survey reviewed by the EUSOBI board and committees was distributed amongst members. The questions encompassed: training and experience; annual breast MRI and MRI-guided-intervention workload; examination protocols; indications; reporting habits and preferences. Data were summarised and subgroups compared using χ² test.

RESULTS

Of 647 EUSOBI members, 177 (27.4%) answered the survey. The majority were radiologists (90.5%), half of them based in academic centres (51.9%). Common indications for MRI included cancer staging, treatment monitoring, high-risk screening and problem-solving, and differed significantly between countries (p≤0.03). Structured reporting and BI-RADS were mostly used. Breast radiologists with ≤10 years of experience preferred inclusion of additional techniques, such as T2/STIR (p=0.03) and DWI (p=0.08) in the scan protocol. MRI-guided interventions were performed by a minority of participants (35.4%).

CONCLUSIONS

The utilisation of breast MRI in clinical practice is generally in line with international recommendations. There are substantial differences between countries. MRI-guided interventions and functional MRI parameters are not widely available.

KEY POINTS

• MRI is commonly used for the detection and characterisation of breast lesions. • Clinical practice standards are generally in line with current recommendations. • Standardised criteria and diagnostic categories (mainly BI-RADS) are widely adopted. • Younger radiologists value additional techniques, such as T2/STIR and DWI. • MRI-guided breast biopsy is not widely available.

Differentiation of ductal carcinoma in situ versus fibrocystic changes by magnetic resonance imaging: are there pathognomonic imaging features?

Background In breast magnetic resonance imaging (MRI), the diagnosis of ductal carcinoma in situ (DCIS) remains controversial; the most challenging cause of false-positive DCIS diagnosis is fibrocystic changes (FC). Purpose To search for typical and pathognomonic patterns of DCIS and FC using a standard clinical MRI protocol. Material and Methods Consecutive patients scheduled for breast MRI (standardized protocols @ 1.5T: dynamic-T1-GRE before/after Gd-DTPA [0.1 mmol/kg body weight (BW)]; T1-TSE), with subsequent pathological sampling, were investigated. Sixteen MRI descriptors were prospectively assessed by two experienced radiologists in consensus (blinded to pathology) and explored in patients with DCIS (n = 77) or FC (n = 219). Univariate and multivariate statistics were performed to identify the accuracy of descriptors (alone, combined). Furthermore, pathognomonic descriptor-combinations with an accuracy of 100% were explored (χ² statistics; decision trees). Results Six breast MRI descriptors significantly differentiated DCIS from FC ( P_corrected < 0.05; odds ratio < 7.9). Pathognomonic imaging features were present in 33.8% (n = 100) of all cases allowing the identification of 42.9% of FC (n = 94). Conclusion Pathognomonic patterns of DCIS and FC were frequently observed in a standard clinical MRI protocol. Such imaging patterns could decrease the false-positive rate of breast MRI and hence might help to decrease the number of unnecessary biopsies in this clinically challenging subgroup.

Automated Semi-Quantitative Analysis of Breast MRI: Potential Imaging Biomarker for the Prediction of Tissue Response to Neoadjuvant Chemotherapy

BACKGROUND

We aimed to investigate an automated semi-quantitative software as an imaging biomarker for the prediction of tissue response (TR) after completion of neoadjuvant chemotherapy (NAC).

METHODS

Breast magnetic resonance imaging (MRI) (1.5T, protocol according to international recommendations) of 67 patients with biopsy-proven invasive breast cancer were examined before and after NAC. After completion of NAC, histopathologic assessments of TR were classified according to the Chevallier grading system (CG1/4: full/non-responder; CG2/C3: partial responder). A commercially available fully automatic software (CADstream) extracted MRI parameters of tumor extension (tumor diameter/volume: TD/TV). Pre- versus post-NAC values were compared (ΔTV and ΔTD). Additionally, the software performed volumetric analyses of vascularization (VAV) after NAC. Accuracy of MRI parameters to predict TR were identified (cross-tabs, ROC, AUC, Kruskal-Wallis).

RESULTS

There were 37 (34.3%) CG1, 7 (6.5%) CG2, 53 (49.1%) CG3, and 11 (10.2%) CG4 lesions. The software reached area under the curve levels of 79.5% (CG1/complete response: ΔTD), 68.6% (CG2, CG3/partial response: VAV), and 88.8% to predict TR (CG4/non-response: ΔTV).

CONCLUSION

Semi-quantitative automated analysis of breast MRI data enabled the prediction of tissue response to NAC.

The value of "constant sharpness" as a diagnostic sign in MR-Mammography

Purpose

To examine “constant lesion sharpness” as a morphological diagnostic sign in the differential diagnosis between benign and malignant lesions.

Material and methods

This prospective study had institutional review board approval and was HIPAA compliant. In total 1014 consecutive patients were examined (mean age 55 years ± 13 years) and evaluated in our University hospital towards the morphological shape of the lesion borders. The “Constant sharpness Sign” was defined as a lesion remaining continuously sharp for the duration of the dynamic scan. Inclusion criteria were unclear findings (e.g. BIRADS III/IV), Preoperative staging (BRIDAS IV/V), and referred patients from local clinic of gynecology. Exclusion criteria were MRM-examination ≤1 year before, status after surgery and/or biopsy, chemotherapy and/or radiation therapy. Reference Standard was histological verification. Images were diagnosed by two experienced radiologists in consensus, blinded to the standard of reference.

Results

1014 patients with 1084 lesions (436 benign, 648 malignant lesions) were included into the study.

41.5% of benign lesions and 6.8% (181/436) of malignant lesions displayed a constant sharpness as an accompanying morphological sign (P < 0.001). This resulted in a sensitivity of 41.5%, specificity of 93.2%, a positive likelihood ratio of 6.1%, a negative likelihood ratio of 0.63 and an odd’s ratio of 9,7%.

Summary and conclusion

The constant sharpness sign seems to be an accurate predictor of benign breast lesions, which may help to increase the accuracy of MRM as a morphological sign.

MRI Background Parenchymal Enhancement Is Not Associated with Breast Cancer

Background

Previously, a strong positive association between background parenchymal enhancement (BPE) at magnetic resonance imaging (MRI) and breast cancer was reported in high-risk populations. We sought to determine, whether this was also true for non-high-risk patients.

Methods

540 consecutive patients underwent breast MRI for assessment of breast findings (BI-RADS 0–5, non-high-risk screening (no familial history of breast cancer, no known genetic mutation, no prior chest irradiation, or previous breast cancer diagnosis)) and subsequent histological work-up. For this IRB-approved study, BPE and fibroglandular tissue FGT were retrospectively assessed by two experienced radiologists according to the BI-RADS lexicon. Pearson correlation coefficients were calculated to explore associations between BPE, FGT, age and final diagnosis of breast cancer. Subsequently, multivariate logistic regression analysis, considering covariate colinearities, was performed, using final diagnosis as the target variable and BPE, FGT and age as covariates.

Results

Age showed a moderate negative correlation with FGT (r = -0.43, p<0.001) and a weak negative correlation with BPE (r = -0.28, p<0.001). FGT and BPE correlated moderately (r = 0.35, p<0.001). Final diagnosis of breast cancer displayed very weak negative correlations with FGT (r = -0.09, p = 0.046) and BPE (r = -0.156, p<0.001) and weak positive correlation with age (r = 0.353, p<0.001). On multivariate logistic regression analysis, the only independent covariate for prediction of breast cancer was age (OR 1.032, p<0.001).

Conclusions

Based on our data, neither BPE nor FGT independently correlate with breast cancer risk in non-high-risk patients at MRI. Our model retained only age as an independent risk factor for breast cancer in this setting.

Focal transitional mastitis in MR-Mammography: Preliminary findings

Purpose

During clinical routine, we retrospectively discovered diagnostic criteria for “focal mastitis” in MR-Mammography (MRM). The aim of this study was to prospectively evaluate these criteria.

Methods

1975 consecutive patients were examined between 01/2010 and 12/2011. 29 patients fit the diagnostic criteria of focal mastitis.

Results

In follow-up scans, 28 patients showed a complete remission of the previous findings. One patient was followed-up with persisting findings, which could histologically be correlated to an area of DCIS after biopsy.

Conclusion

The morphologic, kinetic and follow-up criteria we discovered seem to be a reliable diagnostic indicator for focal mastitis.

Impact of post-processing methods on apparent diffusion coefficient values

OBJECTIVE

The apparent diffusion coefficient (ADC) is increasingly used as a quantitative biomarker in oncological imaging. ADC calculation is based on raw diffusion-weighted imaging (DWI) data, and multiple post-processing methods (PPMs) have been proposed for this purpose. We investigated whether PPM has an impact on final ADC values.

METHODS

Sixty-five lesions scanned with a standardized whole-body DWI-protocol at 3 T served as input data (EPI-DWI, b-values: 50, 400 and 800 s/mm²). Using exactly the same ROI coordinates, four different PPM (ADC_1-ADC_4) were executed to calculate corresponding ADC values, given as [10^-3 mm²/s] of each lesion. Statistical analysis was performed to intra-individually compare ADC values stratified by PPM (Wilcoxon signed-rank tests: α = 1 %; descriptive statistics; relative difference/∆; coefficient of variation/CV).

RESULTS

Stratified by PPM, mean ADCs ranged from 1.136-1.206 *10^-3 mm²/s (∆ = 7.0 %). Variances between PPM were pronounced in the upper range of ADC values (maximum: 2.540-2.763 10^-3 mm²/s, ∆ = 8 %). Pairwise comparisons identified significant differences between all PPM (P ≤ 0.003; mean CV = 7.2 %) and reached 0.137 *10^-3 mm²/s within the 25th-75th percentile.

CONCLUSION

Altering the PPM had a significant impact on the ADC value. This should be considered if ADC values from different post-processing methods are compared in patient studies.

KEY POINTS

• Post-processing methods significantly influenced ADC values. • The mean coefficient of ADC variation due to PPM was 7.2 %. • To achieve reproducible ADC values, standardization of post-processing is recommended.

Is "prepectoral edema" a morphologic sign for malignant breast tumors?

RATIONALE AND OBJECTIVES

A variety of morphologic and kinetic signs of benign or malignant breast lesions contribute to a final diagnosis and differential diagnosis in magnetic resonance (MR) mammography (MRM). As a new sign, prepectoral edema (PE) in patients without any history of previous biopsy, operation, radiation, or chemotherapy was detected during routine breast MR examinations. The purpose of this study was to retrospectively evaluate the role of this morphologic sign in the differential diagnosis of breast lesions.

MATERIALS AND METHODS

Between January 2005 and October 2006, a total of 1109 consecutive MRM examinations have been performed in our institution. In this study, only patients who would later be biopsied or operated in our own hospital were included. They had no previous operation, biopsy, intervention, chemotherapy, hormone replacement therapy, or previous mastitis. In total, 162 patients with 180 lesions were included, histologically correlated later-on by open biopsy (124 patients and 136 lesions) or core biopsy (38 patients and 44 lesions). The evaluations were performed by four experienced radiologists in consensus.

RESULTS

One hundred eighty evaluated lesions included 104 malignant lesions (93 invasive and 11 noninvasive cancers) and 76 benign lesions. PE was detected in 2.6% of benign lesions (2 of 76), in none of the Ductal cacinoma in situ (DCIS) cases (0 of 11), and in 25.8% of malignant lesions (24 of 93; P < .000). PE was found significantly more frequently in presence of malignant tumors >2 cm in diameter (48.5%, 17 of 35 vs. 13.8%, 8 of 58; P < .001). PE was not statistically associated to malignant tumor type, presence or absence of additional DCIS, and number of lesions. This resulted in the following diagnostic parameters for PE as an indicator for malignancy: sensitivity of 19.3%, specificity of 97.3%, positive predictive value (PPV) of 92.3%, negative predictive value of 48%, and accuracy of 57.7%.

CONCLUSIONS

In case of occurrence, the "PE sign" seems to be a specific indicator for malignant tumors with a high PPV, independent from its entity.

DCE-MRI of the breast in a stand-alone setting outside a complementary strategy - results of the TK-study

OBJECTIVES

To evaluate the accuracy of MRI of the breast (DCE-MRI) in a stand-alone setting with extended indications.

MATERIALS AND METHODS

According to the inclusion criteria, breast specialists were invited to refer patients to our institution for DCE-MRI. Depending on the MR findings, patients received either a follow-up or biopsy. Between 04/2006 and 12/2011 a consecutive total of 1,488 women were prospectively examined.

RESULTS

Of 1,488 included patients, 393 patients were lost to follow-up, 1,095 patients were evaluated. 124 patients were diagnosed with malignancy by DCE-MRI (76 TP, 48 FP, 971 TN, 0 FN cases). Positive cases were confirmed by histology, negative cases by MR follow-ups or patient questionnaires over the next 5 years in 1,737 cases (sensitivity 100 %; specificity 95.2 %; PPV 61.3 %; NPV 100 %; accuracy 95.5 %). For invasive cancers only (DCIS excluded), the results were 63 TP; 27 FP; 971 TP and 0 FN (sensitivity 100 %; specificity 97.2 %; PPV 70 %; NPV 100 %; accuracy 97.5 %).

CONCLUSION

The DCE-MRI indications tested imply that negative results in DCE-MRI reliably exclude cancer. The results were achieved in a stand-alone setting (single modality diagnosis). However, these results are strongly dependent on reader experience and adequate technical standards as prerequisites for optimal diagnoses.

KEY POINTS

• DCE-MRI of the breast has a high accuracy in finding breast cancer. • The set of indications for DCE-MRI of the breast is still very limited. • DCE-MRI can achieve a high accuracy in a 'screening-like' setting. • Accuracy of breast DCE-MRI is strongly dependent on technique and reader experience. • A negative DCE-MRI effectively excludes cancer.

4D co-registration of X-ray and MR-mammograms: initial clinical results and potential incremental diagnostic value

PURPOSE

4D co-registration of X-ray- and MR-mammograms (XM and MM) is a new method of image fusion. The present study aims to evaluate its clinical feasibility, radiological accuracy, and potential clinical value.

METHODS

XM and MM of 25 patients were co-registered. Results were evaluated by a blinded reader.

RESULTS

Precision of the 4D co-registration was "very good" (mean-score [ms]=7), and lesions were "easier to delineate" (ms=5). In 88.8%, "relevant additional diagnostic information" was present, accounting for a more "confident diagnosis" in 76% (ms=5).

CONCLUSION

4D co-registration is feasible, accurate, and of potential clinical value.

[Initial clinical experience in the treatment of vitreomacular traction and macular holes with ocriplasmin]

BACKGROUND

The introduction and approval of Ocriplasmin as an intravitreally applicable drug in the pharmocological treatment of vitreomacular traction represents a new therapeutic approach possibly avoiding vitreoretinal surgery. With our article we report our first experience wih Ocriplasmin in clinical practice.

METHODS

The indication for intravitreal therapy with Ocriplasmin was provided for symptomatic VMT or macular hole with VMT in 20 patients since March 2013. Surgery was planned in cases with remaining symptoms. Before IVI we performed SD-OCT. Best visual acuity (BCVA) was evaluated preoperatively, 7 and 28 days after treatment and finally every month in 14 treated eyes. SD-OCT images were analysed before treatment and later on with every follow-up examination. In addition to functional and morphological changes we analysed all side effects.

RESULTS

The mean BCVA at the beginning of treatment was 0.3 and 0.4 before injection. The indications for treatment were as follows: symptomatic VMT in 10 patients and 4 patients suffering from full thickness macular hole stage 2. In 3 patients spontaneous regression of VMT could be observed with increasing of vision from 0.3 to 0.5. In one patient his macular hole was closed and BCVA increased from 0.2 to 0.6 within 7 days. Two patients showed significant enlargement of their macular holes after 7 days and finally underwent surgery. A massive cystoid macular oedema occurred in one patient. No change in the SD-OCT image could be observed 28 days after treatment. The mean visual acuity improved to 0.6 during a follow-up period of 90 days. Photopsia and disturbing vitreous opacities up to 28 days post injection could be regarded as minor side effects.

CONCLUSION

Our first clinical experience with intravitreous injection of Ocriplasmin were performed to confirm the presumed therapeutic effect in patients suffering from VMT. Small macular holes could frequently be closed. The possibility of special side effects must be taken in consideration just as the possibility of spanteous improvement before performing IVI with Ocriplasmin. Further prospective studies must be recommended to be right about Ocriplasmin injections.

Clinical evaluation of semi-automatic landmark-based lesion tracking software for CT-scans

Background

To evaluate a semi-automatic landmark-based lesion tracking software enabling navigation between RECIST lesions in baseline and follow-up CT-scans.

Methods

The software automatically detects 44 stable anatomical landmarks in each thoraco/abdominal/pelvic CT-scan, sets up a patient specific coordinate-system and cross-links the coordinate-systems of consecutive CT-scans. Accuracy of the software was evaluated on 96 RECIST lesions (target- and non-target lesions) in baseline and follow-up CT-scans of 32 oncologic patients (64 CT-scans). Patients had to present at least one thoracic, one abdominal and one pelvic RECIST lesion. Three radiologists determined the deviation between lesions’ centre and the software’s navigation result in consensus.

Results

The initial mean runtime of the system to synchronize baseline and follow-up examinations was 19.4 ± 1.2 seconds, with subsequent navigation to corresponding RECIST lesions facilitating in real-time. Mean vector length of the deviations between lesions’ centre and the semi-automatic navigation result was 10.2 ± 5.1 mm without a substantial systematic error in any direction. Mean deviation in the cranio-caudal dimension was 5.4 ± 4.0 mm, in the lateral dimension 5.2 ± 3.9 mm and in the ventro-dorsal dimension 5.3 ± 4.0 mm.

Conclusion

The investigated software accurately and reliably navigates between lesions in consecutive CT-scans in real-time, potentially accelerating and facilitating cancer staging.