Breast MRI used as a problem-solving tool reliably excludes malignancy

Optimizing ultrafast dynamic contrast-enhanced MRI scan duration in the differentiation of benign and malignant breast lesions

OBJECTIVE

To determine the optimal scan duration for ultrafast DCE-MRI in effectively differentiating benign from malignant breast lesions.

METHODS

The study prospectively recruited participants who underwent breast ultrafast DCE-MRI from September 2021 to March 2023. A 30-phase breast ultrafast DCE-MRI on a 3.0-T MRI system was conducted with a 4.5-s temporal resolution. Scan durations ranged from 40.5 s to 135.0 s, during which the analysis is performed at three-phase intervals, forming eight dynamic sets (scan duration [SD]40.5s: 40.5 s, SD54s: 54.0 s, SD67.5s: 67.5 s, SD81s: 81.0 s, SD94.5s: 94.5 s, SD108s: 108.0 s, SD121.5s: 121.5 s, and SD135s: 135.0 s). Two ultrafast DCE-MRI parameters, maximum slope (MS) and initial area under the curve in 60 s (iAUC), were calculated for each dynamic set and compared between benign and malignant lesions. Areas under the receiver operating characteristic curve (AUCs) were used to assess their diagnostic performance.

RESULTS

A total of 140 women (mean age, 47 ± 11 years) with 151 lesions were included. MS and iAUC from eight dynamic sets exhibited significant differences between benign and malignant lesions (all p < 0.05), except iAUC at SD40.5s. The AUC of MS (AUC = 0.804) and iAUC (AUC = 0.659) at SD67.5s were significantly higher than their values at SD40.5s (AUC = 0.606 and 0.516; corrected p < 0.05). No significant differences in AUCs for MS and iAUC were observed from SD67.5s to SD135s (all corrected p > 0.05).

CONCLUSIONS

Ultrafast DCE-MRI with a 67.5-s scan duration appears optimal for effectively differentiating malignant from benign breast lesions.

CRITICAL RELEVANCE STATEMENT

By evaluating scan durations (40.5-135 s) and analyzing two ultrafast DCE-MRI parameters, we found a scan duration of 67.5 s optimal for discriminating between these lesions and offering a balance between acquisition time and diagnostic efficacy.

KEY POINTS

Ultrafast DCE-MRI can effectively differentiate malignant from benign breast lesions. A minimum of 67.5-sec ultrafast DCE-MRI scan duration is required to differentiate benign and malignant lesions. Extending the scan duration beyond 67.5 s did not significantly improve diagnostic accuracy.

Problem Solving MRI to Reduce False-Positive Biopsy Related to Breast US: Conductivity vs. DWI vs. Abbreviated Contrast-Enhanced MRI

BACKGROUND

While breast ultrasound (US) is a useful tool for diagnosing breast masses, it can entail false-positive biopsy results because of some overlapping features between benign and malignant breast masses and subjective interpretation.

PURPOSE

To evaluate the performance of conductivity imaging for reducing false-positive biopsy results related to breast US, as compared to diffusion-weighted imaging (DWI) and abbreviated MRI consisting of one pre- and one post-contrast T1-weighted imaging.

STUDY TYPE

Prospective.

SUBJECTS

Seventy-nine women (median age, 44 years) with 86 Breast Imaging Reporting and Data System (BI-RADS) category 4 masses as detected by breast US.

FIELD STRENGTH/SEQUENCE

3-T, T2-weighted turbo spin echo sequence, DWI, and abbreviated contrast-enhanced MRI (T1-weighted gradient echo sequence).

ASSESSMENT

US-guided biopsy (reference standard) was obtained on the same day as MRI. The maximum and mean conductivity parameters from whole and single regions of interest (ROIs) were measured. Apparent diffusion coefficient (ADC) values were obtained from an area with the lowest signal within a lesion on the ADC map. The performance of conductivity, ADC, and abbreviated MRI for reducing false-positive biopsies was evaluated using the following criteria: lowest conductivity and highest ADC values among malignant breast lesions and BI-RADS categories 2 or 3 on abbreviated MRI.

STATISTICAL TESTS

One conductivity parameter with the maximum area under the curve (AUC) from receiver operating characteristics was selected. A P-value <0.05 was considered statistically significant.

RESULTS

US-guided biopsy revealed 65 benign lesions and 21 malignant lesions. The mean conductivity parameter of the single ROI method was selected (AUC = 0.74). Considering conductivity (≤0.10 S/m), ADC (≥1.60 × 10-3  mm2 /sec), and BI-RADS categories 2 or 3 reduced false-positive biopsies by 23% (15 of 65), 38% (25 of 65), and 43% (28 of 65), respectively, without missing malignant lesions.

DATA CONCLUSION

Conductivity imaging may show lower performance than DWI and abbreviated MRI in reducing unnecessary biopsies.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

The diagnostic performance of ultrafast MRI to differentiate benign from malignant breast lesions: a systematic review and meta-analysis

OBJECTIVES

To assess the diagnostic performance of ultrafast magnetic resonance imaging (UF-DCE MRI) in differentiating benign from malignant breast lesions.

MATERIALS AND METHODS

A comprehensive search was conducted until September 1, 2023, in Medline, Embase, and Cochrane databases. Clinical studies evaluating the diagnostic performance of UF-DCE MRI in breast lesion stratification were screened and included in the meta-analysis. Pooled summary estimates for sensitivity, specificity, diagnostic odds ratio (DOR), and hierarchic summary operating characteristics (SROC) curves were pooled under the random-effects model. Publication bias and heterogeneity between studies were calculated.

RESULTS

A final set of 16 studies analyzing 2090 lesions met the inclusion criteria and were incorporated into the meta-analysis. Using UF-DCE MRI kinetic parameters, the pooled sensitivity, specificity, DOR, and area under the curve (AUC) for differentiating benign from malignant breast lesions were 83% (95% CI 79-88%), 77% (95% CI 72-83%), 18.9 (95% CI 13.7-26.2), and 0.876 (95% CI 0.83-0.887), respectively. We found no significant difference in diagnostic accuracy between the two main UF-DCE MRI kinetic parameters, maximum slope (MS) and time to enhancement (TTE). DOR and SROC exhibited low heterogeneity across the included studies. No evidence of publication bias was identified (p = 0.585).

CONCLUSIONS

UF-DCE MRI as a stand-alone technique has high accuracy in discriminating benign from malignant breast lesions.

CLINICAL RELEVANCE STATEMENT

UF-DCE MRI has the potential to obtain kinetic information and stratify breast lesions accurately while decreasing scan times, which may offer significant benefit to patients.

KEY POINTS

• Ultrafast breast MRI is a novel technique which captures kinetic information with very high temporal resolution. • The kinetic parameters of ultrafast breast MRI demonstrate a high level of accuracy in distinguishing between benign and malignant breast lesions. • There is no significant difference in accuracy between maximum slope and time to enhancement kinetic parameters.

Investigation of imaging features in contrast-enhanced magnetic resonance imaging of benign and malignant breast lesions

PURPOSE

This study aimed to enhance the diagnostic accuracy of contrast-enhanced breast magnetic resonance imaging (MRI) using gadobutrol for differentiating benign breast lesions from malignant ones. Moreover, this study sought to address the limitations of current imaging techniques and criteria based on the Breast Imaging Reporting and Data System (BI-RADS).

MATERIALS AND METHODS

In a multicenter retrospective study conducted in Japan, 200 women were included, comprising 100 with benign lesions and 100 with malignant lesions, all classified under BI-RADS categories 3 and 4. The MRI protocol included 3D fast gradient echo T1- weighted images with fat suppression, with gadobutrol as the contrast agent. The analysis involved evaluating patient and lesion characteristics, including age, size, location, fibroglandular tissue, background parenchymal enhancement (BPE), signal intensity, and the findings of mass and non-mass enhancement. In this study, univariate and multivariate logistic regression analyses were performed, along with decision tree analysis, to identify significant predictors for the classification of lesions.

RESULTS

Differences in lesion characteristics were identified, which may influence malignancy risk. The multivariate logistic regression model revealed age, lesion location, shape, and signal intensity as significant predictors of malignancy. Decision tree analysis identified additional diagnostic factors, including lesion margin and BPE level. The decision tree models demonstrated high diagnostic accuracy, with the logistic regression model showing an area under the curve of 0.925 for masses and 0.829 for non-mass enhancements.

CONCLUSION

This study underscores the importance of integrating patient age, lesion location, and BPE level into the BI-RADS criteria to improve the differentiation between benign and malignant breast lesions. This approach could minimize unnecessary biopsies and enhance clinical decision-making in breast cancer diagnostics, highlighting the effectiveness of gadobutrol in breast MRI evaluations.

Problem-solving Breast MRI

Breast MRI has high sensitivity and negative predictive value, making it well suited to problem solving when other imaging modalities or physical examinations yield results that are inconclusive for the presence of breast cancer. Indications for problem-solving MRI include equivocal or uncertain imaging findings at mammography and/or US; suspicious nipple discharge or skin changes suspected to represent an abnormality when conventional imaging results are negative for cancer; lesions categorized as Breast Imaging Reporting and Data System 4, which are not amenable to biopsy; and discordant radiologic-pathologic findings after biopsy. MRI should not precede or replace careful diagnostic workup with mammography and US and should not be used when a biopsy can be safely performed. The role of MRI in characterizing calcifications is controversial, and management of calcifications should depend on their mammographic appearance because ductal carcinoma in situ may not appear enhancing on MR images. In addition, ductal carcinoma in situ detected solely with MRI is not associated with a higher likelihood of an upgrade to invasive cancer compared with ductal carcinoma in situ detected with other modalities. MRI for triage of high-risk lesions is a subject of ongoing investigation, with a possible future role for MRI in decreasing excisional biopsies. The accuracy of MRI is likely to increase with the use of advanced techniques such as deep learning, which will likely expand the indications for problem-solving MRI. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

The value of MRI for downgrading of breast suspicious lesions detected on ultrasound

BACKGROUND

Most of suspicious lesions classified as breast imaging reporting and data system (BI-RADS) 4A and 4B categories on ultrasound (US) were benign, resulting in unnecessary biopsies. MRI has a high sensitivity to detect breast cancer and high negative predictive value (NPV) to exclude malignancy. The purpose of this study was to investigate the value of breast MRI for downgrading of suspicious lesions with BI-RADS 4A and 4B categories on US.

METHODS

Patients who underwent breast MRI for suspicious lesions classified as 4A and 4B categories were included in this retrospective study. Two radiologists were aware of the details of suspicious lesions detected on US and evaluated MR images. MRI BI-RADS categories were given by consensus on the basis on dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI). Pathological results and imaging follow-up at least 12 months were used as a reference standard. Sensitivity, specificity, positive predictive value (PPV), NPV and their 95% confidence interval (CI) were calculated for MRI findings.

RESULTS

One sixty seven patients with 186 lesions (US 4A category: 145, US 4B category: 41) consisted of the study cohort. The malignancy rate was 34.9% (65/186). On MRI, all malignancies showed true-positive results and 92.6% (112/121) benign lesions were correctly diagnosed. MRI increased PPV from 34.9% (65/186) to 87.8% (65/74) and reduced the false-positive biopsies by 92.6% (112/121). The sensitivity, specificity, PPV and NPV of MRI were 100% (95% CI: 94.5%-100%), 92.6% (95% CI: 86.3%-96.5%), 87.8% (95% CI: 78.2%-94.3%) and 100% (95% CI: 96.8%-100%), respectively. 2.2% (4/186) of suspicious lesions were additionally detected on MRI, 75% (3/4) of which were malignant.

CONCLUSION

MRI could downgrade suspicious lesions classified as BI-RADS 4A and 4B categories on US and avoided unnecessary benign biopsies without missing malignancy. Additional suspicious lesions detected on MRI needed further work-up.

Pathologic Outcomes in Single Versus Multiple Areas of Architectural Distortion on Digital Breast Tomosynthesis

BACKGROUND. Digital breast tomosynthesis (DBT) has led to increased detection of architectural distortion (AD). Management of patients with multiple areas of AD is not established. OBJECTIVE. The purpose of this article is to compare pathologic outcomes between single and multiple areas of AD identified on DBT. METHODS. This retrospective study included 402 patients (mean age, 56 years) who underwent image-guided core needle biopsy of AD visualized on DBT between April 7, 2017, and April 16, 2019. Patients were classified as having a single or multiple areas of AD according to the presence of distinct areas of AD described in the clinical radiology reports. The pathologic diagnosis for each AD was on the basis of the most aggressive pathology identified on either biopsy or surgical excision, if performed. Patients with single and multiple areas of AD were compared. RESULTS. The sample included 372 patients with a single AD (145 benign, 121 high risk, 105 malignant, one other) and 30 patients with multiple visualized ADs, including 66 biopsied ADs (10 benign, 35 high risk, 21 malignant). At pathologic assessment on a per-lesion basis, multiple compared with single ADs showed higher frequency of high-risk pathology (53.0% vs 32.5%, p = .002) but no difference in frequency of malignancy (31.8% vs 28.2%, p = .56). In multivariable analysis of a range of patient-related characteristics, the presence of single versus multiple areas of AD was not independently associated with malignancy (p = .51). In patients with multiple areas of AD, the most aggressive pathology (benign, high risk, or malignant) across all ADs was not associated with the number of ADs (p = .73). In 8 of 24 patients with at least two ipsilateral biopsied ADs, the ipsilateral areas varied in terms of most aggressive pathology; in 5 of 10 patients with contralateral biopsied ADs, the contralateral areas varied in most aggressive pathology. CONCLUSION. The presence of multiple areas of AD, compared with a single AD, was significantly more likely to yield high-risk pathology but was not significantly different in yield of malignancy. In patients with multiple ADs, multiple ipsilateral or contralateral ADs commonly varied in pathologic classification (benign, high risk, or malignant). CLINICAL IMPACT. These findings may help guide management of AD visualized by DBT, including multiple ADs. For patients with multiple areas of AD, biopsy of all areas may be warranted given variation in pathologic diagnoses.

Limited value of multiparametric MRI with dynamic contrast-enhanced and diffusion-weighted imaging in non-mass enhancing breast tumors

PURPOSE

To investigate the diagnostic value of multiparametric MRI (mpMRI) including dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) in non-mass enhancing breast tumors.

METHOD

Patients who underwent mpMRI, who were diagnosed with a suspicious non-mass enhancement (NME) on DCE-MRI (BI-RADS 4/5), and who subsequently underwent image-guided biopsy were retrospectively included. Two radiologists independently evaluated all NMEs, on both DCE-MR images and high-b-value DW images. Different mpMRI reading approaches were evaluated: 1) with a fixed apparent diffusion coefficient (ADC) threshold (<1.3 malignant, ≥1.3 benign) based on the recommendation by the European Society of Breast Imaging (EUSOBI); 2) with a fixed ADC threshold (<1.5 malignant, ≥1.5 benign) based on recently published trial data; 3) with an ADC threshold adapted to the assigned BI-RADS classification using a previously published reading method; and 4) with individually determined best thresholds for each reader.

RESULTS

The final study sample consisted of 66 lesions in 66 patients. DCE-MRI alone had the highest sensitivity for breast cancer detection (94.8-100 %), outperforming all mpMRI reading approaches (R1 74.4-87.1 %, R2 71.7-94.8 %) and DWI alone (R1 74.4 %, R2 79.4 %). The adapted approach achieved the best specificity for both readers (85.1 %), resulting in the best diagnostic accuracy for R1 (86.5 %) but a moderate diagnostic accuracy for R2 (77.2 %).

CONCLUSION

mpMRI has limited added diagnostic value to DCE-MRI in the assessment of NME.

MRI Breast: Current Imaging Trends, Clinical Applications, and Future Research Directions

Magnetic Resonance Imaging (MRI) is the most sensitive and advanced imaging technique in diagnosing breast cancer and is essential in improving cancer detection, lesion characterization, and determining therapy response. In addition to the dynamic contrast-enhanced (DCE) technique, functional techniques such as magnetic resonance spectroscopy (MRS), diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), and intravoxel incoherent motion (IVIM) further characterize and differentiate benign and malignant lesions thus, improving diagnostic accuracy. There is now an increasing clinical usage of MRI breast, including screening in high risk and supplementary screening tools in average-risk patients. MRI is becoming imperative in assisting breast surgeons in planning breast-conserving surgery for preoperative local staging and evaluation of neoadjuvant chemotherapy response. Other clinical applications for MRI breast include occult breast cancer detection, investigation of nipple discharge, and breast implant assessment. There is now an abundance of research publications on MRI Breast with several areas that still remain to be explored. This review gives a comprehensive overview of the clinical trends of MRI breast with emphasis on imaging features and interpretation using conventional and advanced techniques. In addition, future research areas in MRI breast include developing techniques to make MRI more accessible and costeffective for screening. The abbreviated MRI breast procedure and an area of focused research in the enhancement of radiologists' work with artificial intelligence have high impact for the future in MRI Breast.

Improving breast cancer diagnostics with deep learning for MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has a high sensitivity in detecting breast cancer but often leads to unnecessary biopsies and patient workup. We used a deep learning (DL) system to improve the overall accuracy of breast cancer diagnosis and personalize management of patients undergoing DCE-MRI. On the internal test set (n = 3936 exams), our system achieved an area under the receiver operating characteristic curve (AUROC) of 0.92 (95% CI: 0.92 to 0.93). In a retrospective reader study, there was no statistically significant difference (P = 0.19) between five board-certified breast radiologists and the DL system (mean ΔAUROC, +0.04 in favor of the DL system). Radiologists' performance improved when their predictions were averaged with DL's predictions [mean ΔAUPRC (area under the precision-recall curve), +0.07]. We demonstrated the generalizability of the DL system using multiple datasets from Poland and the United States. An additional reader study on a Polish dataset showed that the DL system was as robust to distribution shift as radiologists. In subgroup analysis, we observed consistent results across different cancer subtypes and patient demographics. Using decision curve analysis, we showed that the DL system can reduce unnecessary biopsies in the range of clinically relevant risk thresholds. This would lead to avoiding biopsies yielding benign results in up to 20% of all patients with BI-RADS category 4 lesions. Last, we performed an error analysis, investigating situations where DL predictions were mostly incorrect. This exploratory work creates a foundation for deployment and prospective analysis of DL-based models for breast MRI.

Outcomes of Canceled Tomosynthesis-Guided Biopsy of Architectural Distortion Due to Nonvisualization

Objective

Architectural distortion without a sonographic correlate is an indication for digital breast tomosynthesis–guided vacuum-assisted biopsy (DBT-VAB). However, when the finding is not visualized on the day of biopsy, the procedure is canceled. This study reports the outcomes of canceled DBT-VAB of architectural distortion due to nonvisualization.

Methods

In this IRB-approved retrospective study, chart review was performed to identify DBT-VABs of architectural distortion at our institution between June 1, 2017, and November 1, 2020, that were canceled because of nonvisualization at the time of biopsy. Cases without follow-up imaging were excluded. Statistical analysis, including the frequency of cases yielding malignancy by the end of the study period, was performed.

Results

In total, 7.2% (39/544) of architectural distortions recommended for biopsy during the study period were canceled because of nonvisualization, 30 of which had follow-up imaging and were included in the study. Mean patient age was 56 years (standard deviation [SD], 9.6 years) and mean follow-up time was 26.7 months (SD, 11.2 months; range, 8.4–50.9 months). During the follow-up period, 16.7% (5/30) underwent repeat biopsy attempt, with one malignant result (1/30, 3.3%; SD, 18%; 95% confidence interval: 0.6%–16.7%). In total, 86.7% (26/30) of cases were declared benign during the follow-up period and 10% (3/30) remained stable with a BI-RADS 3 assessment category.

Conclusion

During available follow-up, there was a low likelihood that distortions not visualized at the time of DBT-VAB represented malignancy (3.3%, 1/30). While this low malignancy rate is reassuring, imaging follow-up is warranted.

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.

Association between breast cancer's prognostic factors and 3D textural features of non-contrast-enhanced T1 weighted breast MRI

OBJECTIVES

The aim of this exploratory study was to evaluate whether three-dimensional texture analysis (3D-TA) features of non-contrast-enhanced T₁ weighted MRI associate with traditional prognostic factors and disease-free survival (DFS) of breast cancer.

METHODS

3D-T₁ weighted images from 78 patients with 81 malignant histopathologically verified breast lesions were retrospectively analysed using standard-size volumes of interest. Grey-level co-occurrence matrix (GLCM)-based features were selected for statistical analysis. In statistics the Mann-Whitney U and the Kruskal-Wallis tests, the Cox proportional hazards model and the Kaplan-Meier method were used.

RESULTS

Tumours with higher histological grade were significantly associated with higher contrast (1 voxel: p = 0.033, 2 voxels: p = 0.036). All the entropy parameters showed significant correlation with tumour grade (p = 0.015-0.050) but there were no statistically significant associations between other TA parameters and tumour grade. The Nottingham Prognostic Index (NPI) was correlated with contrast and sum entropy parameters. A higher sum variance TA parameter was a significant predictor of shorter DFS.

CONCLUSION

Texture parameters, assessed by 3D-TA from non-enhanced T₁ weighted images, indicate tumour heterogeneity but have limited independent prognostic value. However, they are associated with tumour grade, NPI, and DFS. These parameters could be used as an adjunct to contrast-enhanced TA parameters.

ADVANCES IN KNOWLEDGE

3D-TA of non-contrast enhanced T₁ weighted breast MRI associates with tumour grade, NPI, and DFS. The use of non-contrast 3D-TA parameters in adjunct with contrast-enhanced 3D-TA parameters warrants further research.

Meta-analysis: Architectural distortion and breast MRI

BACKGROUND

The implementation of digital breast tomosynthesis has increased the detection of architectural distortion (AD). Managing this finding may be experienced as a clinical dilemma in daily practice. Breast Contrast-Enhanced MRI (CE-BMR) is a known modality in case of problem-solving tool for mammographic abnormalities. However, the data about AR and CE-BMR are scant.

OBJECTIVE

The purpose was to estimate the benefit of CE-BMR in the setting of architectural distortion detected mammographically through a systematic review and meta-analysis of the literature.

METHODS

A search of MEDLINE and EMBASE databases were conducted in 2020. Based on the PRISMA guidelines, an analysis was performed using the chi-square test of independence to determine if there was a significant association between the result of the test (positive or negative) and the participant condition (malignant or non-malignant).

RESULTS

Four studies were available. The negative predictive value (NPV) was 98.3% to 100%. The result of the chi-square indicated that there was significant association between the participant test result and the participant condition for the included publications (X(1,175)2= 84.051, p = 0.0001).

CONCLUSIONS

The high NPV could allow for deferral of a biopsy in favor of a short-interval imaging follow-up in the setting of a negative CE-BMR.

Breast magnetic resonance imaging as a problem solving tool in women recalled at biennial screening mammography: A population-based study in the Netherlands

Purpose

Problem solving magnetic resonance imaging (MRI) is used to exclude malignancy in women with equivocal findings on conventional imaging. However, recommendations on its use for women recalled after screening are lacking. This study evaluates the impact of problem solving MRI on diagnostic workup among women recalled from the Dutch screening program, as well as time trends and inter-hospital variation in its use.

Methods

Women who were recalled at screening mammography in the South of the Netherlands (2008–2017) were included. Two-year follow-up data were collected. Diagnostic-workup and accuracy of problem solving MRI were evaluated and time trends and inter-hospital variation in its use were examined.

Results

In the study period 16,175 women were recalled, of whom 906 underwent problem solving MRI. Almost half of the women (45.4%) who underwent problem solving MRI were referred back to the screening program without further workup. The sensitivity, specificity, and positive and negative predictive values of problem solving MRI were 98.2%, 70.0%, 31.1%, and 99.6%, respectively. The percentage of recalled women receiving problem solving MRI fluctuated over time (4.7%–7.2%) and significantly varied among hospitals (2.2%–7.0%).

Conclusion

The use of problem solving MRI may exclude malignancy in recalled women. The use of problem solving MRI varied over time and among hospitals, which indicates the need for guidelines on problem solving MRI.

•

Problem solving MRI did correctly refer back women to the screening program.

•

The sensitivity and specificity of problem solving MRI were 98.2% and 70.0%.

•

Positive and negative predictive values of problem solving MRI were 31.1% and 99.6%.

•

By excluding malignancy, problem solving MRI may reduce invasive diagnostic workup.

Magnetic resonance imaging in diagnosis of indeterminate breast (BIRADS 3 & 4A) in a general population

OBJECTIVE

Currently, mammography and ultrasonography are the most used imaging techniques for breast cancer screening. However, these examinations report many indeterminate studies with a low probability of being malignant, i.e., BIRADS 3 and 4A. This prospective study aims to evaluate the value of breast magnetic resonance imaging (MRI) to clarify the BIRADS categorization of indeterminate mammography or ultrasonography studies.

METHODS

MRI studies acquired prospectively from 105 patients previously classified as BIRADS 3 or 4A were analyzed independently by four radiologists with different experience levels. Interobserver agreement was determined by the first-order agreement coefficient (AC1), and divergent results were re-analyzed for consensus. The possible correlation between the MRI and the mammography/ultrasound findings was evaluated, and each study was independently classified in one of the five BIRADS categories (BIRADS 1 to 5). In lesions categorized as BIRADS 4 or 5 at MRI, histopathological diagnosis was established by image-guided biopsy; while short-term follow-up was performed in lesions rated as BIRADS 3.

RESULTS

Breast MRI was useful in diagnosing three invasive ductal carcinomas, upgraded from BIRADS 4A to BIRADS 5. It also allowed excluding malignancy in 86 patients (81.9%), avoiding 22 unnecessary biopsies and 64 short-term follow-ups. The MRI showed good diagnostic performance with the area under roc curve, sensitivity, specificity, PPV, and NPV of 0.995, 100%, 83.5%, 10.5%, and 100%, respectively.

CONCLUSIONS

MRI showed to be useful as a problem-solving tool to clarify indeterminate findings in breast cancer screening and avoiding unnecessary short-follow-ups and percutaneous biopsies.

[Artificial intelligence in breast imaging : Areas of application from a clinical perspective]

Klinisches/methodisches Problem

Bei der Mammadiagnostik gilt es, klinische sowie multimodal bildgebende Informationen mit perkutanen und operativen Eingriffen zu koordinieren. Aus dieser Komplexität entsteht eine Reihe von Problemen: übersehene Karzinome, Überdiagnose, falsch-positive Befunde, unnötige weiterführende Bildgebung, Biopsien und Operationen.

Radiologische Standardverfahren

Folgende Untersuchungsverfahren werden in der Mammadiagnostik eingesetzt: Röntgenmammographie, Tomosynthese, kontrastangehobene Mammographie, (multiparametrischer) Ultraschall, Magnetresonanztomographie, Computertomographie, nuklearmedizinische Verfahren sowie deren Hybridvarianten.

Methodische Innovationen

Künstliche Intelligenz (KI) verspricht Abhilfe bei praktisch allen Problemen der Mammadiagnostik. Potenziell lassen sich Fehlbefunde vermeiden, bildgebende Verfahren effizienter einsetzen und möglicherweise auch biologische Phänotypen von Mammakarzinomen definieren.

Leistungsfähigkeit

Auf KI basierende Software wird für zahlreiche Anwendungen entwickelt. Am weitesten fortgeschritten sind Systeme für das Screening mittels Mammographie. Probleme sind monozentrische sowie kurzfristig am finanziellen Erfolg orientierte Ansätze.

Bewertung

Künstliche Intelligenz (KI) verspricht eine Verbesserung der Mammadiagnostik. Durch die Vereinfachung von Abläufen, die Reduktion monotoner und ergebnisloser Tätigkeiten und den Hinweis auf mögliche Fehler ist eine Beschleunigung von dann weitgehend fehlerfreien Abläufen denkbar.

Empfehlung für die Praxis

In diesem Beitrag werden die Anforderungen der Mammadiagnostik und mögliche Einsatzgebiete der der KI beleuchtet. Je nach Definition gibt es bereits praktisch anwendbare Softwaretools für die Mammadiagnostik. Globale Lösungen stehen allerdings noch aus.

Application of the Kaiser score to increase diagnostic accuracy in equivocal lesions on diagnostic mammograms referred for MR mammography

INTRODUCTION

We aimed to interpret MR mammography (MRM) using the Kaiser scores for equivocal or inconclusive lesions on mammography (MG).

METHODS

Retrospective IRB-approved evaluation of 3623 MG for which MRM was deployed as a problem-solving tool, after inclusion-exclusion criteria were met. Three readers with different levels of experience assigned a final score from 1 to 11 based on the previously established tree classification system. Area under the curve (AUC) derived from receiver operating characteristic (ROC) analysis was used to determine the overall diagnostic performance for all lesions and separately for mass and non-mass enhancement. Sensitivity, specificity, and likelihood ratio values were obtained at different cut-off values of >4, > 5, and > 8 to rule in and rule out malignancy.

RESULT

Histopathology of 183 mass and 133 non-mass enhancement (NME) lesions show benign etiology in 95 and malignant in 221. The AUC was 0.796 [0.851 for mass and 0.715 for NME]. Applying the Kaiser score upgraded 202 lesions with correct prediction in 77 %, and downgraded 28 lesions with correct prediction in 60.8 %. Using a score <5 instead of <4 to rule out malignancy improved our diagnostic ability to correctly identify 100 % benign lesions. Applying Kaiser score correctly downgraded 60.8 % (17/28) lesions; thus avoiding biopsies in these. Using a high cut-off value>8 to rule-in malignancy, we correctly identified 59.7 % of lesions with 80 % specificity and positive likelihood ratio of 3.

CONCLUSION

The Kaiser score has clinical translation benefits when used as a problem-solving tool for inconclusive MG findings.

Deep-learning approach with convolutional neural network for classification of maximum intensity projections of dynamic contrast-enhanced breast magnetic resonance imaging

PURPOSE

We aimed to evaluate deep learning approach with convolutional neural networks (CNNs) to discriminate between benign and malignant lesions on maximum intensity projections of dynamic contrast-enhanced breast magnetic resonance imaging (MRI).

METHODS

We retrospectively gathered maximum intensity projections of dynamic contrast-enhanced breast MRI of 106 benign (including 22 normal) and 180 malignant cases for training and validation data. CNN models were constructed to calculate the probability of malignancy using CNN architectures (DenseNet121, DenseNet169, InceptionResNetV2, InceptionV3, NasNetMobile, and Xception) with 500 epochs and analyzed that of 25 benign (including 12 normal) and 47 malignant cases for test data. Two human readers also interpreted these test data and scored the probability of malignancy for each case using Breast Imaging Reporting and Data System. Sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) were calculated.

RESULTS

The CNN models showed a mean AUC of 0.830 (range, 0.750-0.895). The best model was InceptionResNetV2. This model, Reader 1, and Reader 2 had sensitivities of 74.5%, 72.3%, and 78.7%; specificities of 96.0%, 88.0%, and 80.0%; and AUCs of 0.895, 0.823, and 0.849, respectively. No significant difference arose between the CNN models and human readers (p > 0.125).

CONCLUSION

Our CNN models showed comparable diagnostic performance in differentiating between benign and malignant lesions to human readers on maximum intensity projection of dynamic contrast-enhanced breast MRI.

Architectural Distortion on Digital Breast Tomosynthesis: Management Algorithm and Pathological Outcome

Architectural distortion on digital breast tomosynthesis (DBT) can occur due to benign and malignant causes. With DBT, there is an increase in the detection of architectural distortion compared with 2D digital mammography, and the positive predictive value is high enough to justify tissue sampling when imaging findings are confirmed. Workup involves supplemental DBT views and ultrasound, with subsequent image-guided percutaneous biopsy using the modality on which it is best visualized. If architectural distortion is subtle and/or questionable on diagnostic imaging, MRI may be performed for problem solving, with subsequent biopsy of suspicious findings using MRI or DBT guidance, respectively. If no suspicious findings are noted on MRI, a six-month follow-up DBT may be performed. On pathology, malignant cases are noted in 6.8%-50.7% of the cases, most commonly due to invasive ductal carcinoma, followed by invasive lobular carcinoma. Radial scars are the most common benign cause, with stromal fibrosis and sclerosing adenosis being much less common. As there is an increase in the number of benign pathological outcomes for architectural distortion on DBT compared with 2D digital mammography, concordance should be based on the level of suspicion of imaging findings. As discordant cases have upgrade rates of up to 25%, surgical consultation is recommended for discordant radiologic-pathologic findings.

A Brief Review on Breast Carcinoma and Deliberation on Current Non Invasive Imaging Techniques for Detection

BACKGROUND

Breast carcinoma is a life threatening disease that accounts for 25.1% of all carcinoma among women worldwide. Early detection of the disease enhances the chance for survival.

DISCUSSION

This paper presents comprehensive report on breast carcinoma disease and its modalities available for detection and diagnosis, as it delves into the screening and detection modalities with special focus placed on the non-invasive techniques and its recent advancement work done, as well as a proposal on a novel method for the application of early breast carcinoma detection.

CONCLUSION

This paper aims to serve as a foundation guidance for the reader to attain bird's eye understanding on breast carcinoma disease and its current non-invasive modalities.

Can Follow-up be Avoided for Probably Benign US Masses with No Enhancement on MRI?

OBJECTIVES

To assess whether no enhancement on pre-treatment MRI can rule out malignancy of additional US mass(es) initially assessed as BI-RADS 3 or 4 in women with newly diagnosed breast cancer.

METHODS

This retrospective study included consecutive women from 2010-2018 with newly diagnosed breast cancer; at least one additional breast mass (distinct from index cancer) assigned a BI-RADS 3 or 4 on US; and a bilateral contrast-enhanced breast MRI performed within 90 days of US. All malignant masses were pathologically proven; benign masses were pathologically proven or defined as showing at least 2 years of imaging stability. Incidence of malignant masses and NPV were calculated on a per-patient level using proportions and exact 95% CIs.

RESULTS

In 230 patients with 309 additional masses, 140/309 (45%) masses did not enhance while 169/309 (55%) enhanced on MRI. Of the 140 masses seen in 105 women (mean age, 54 years; range 28-82) with no enhancement on MRI, all had adequate follow-up and 140/140 (100%) were benign, of which 89/140 (63.6%) were pathologically proven and 51/140 (36.4%) demonstrated at least 2 years of imaging stability. Pre-treatment MRI demonstrating no enhancement of US mass correlate(s) had an NPV of 100% (95% CI 96.7-100.0).

CONCLUSIONS

All BI-RADS 3 and 4 US masses with a non-enhancing correlate on pre-treatment MRI were benign. The incorporation of MRI, when ordered by the referring physician, may decrease unnecessary follow-up imaging and/or biopsy if the initial US BI-RADS assessment and management recommendation were to be retrospectively updated.

KEY POINTS

• Of 309 BI-RADS 3 or 4 US masses with a corresponding mass on MRI, 140/309 (45%) demonstrated no enhancement whereas 169/309 (55%) demonstrated enhancement • All masses classified as BI-RADS 3 or 4 on US without enhancement on MRI were benign • MRI can rule out malignancy in non-enhancing US masses with an NPV of 100.

Detection and Diagnosis of Breast Cancer Using Artificial Intelligence Based assessment of Maximum Intensity Projection Dynamic Contrast-Enhanced Magnetic Resonance Images. Diagnostics (Basel). 2020;10. [PMID: 32443922 PMCID: PMC7277981 DOI: 10.3390/diagnostics10050330]

We aimed to evaluate an artificial intelligence (AI) system that can detect and diagnose lesions of maximum intensity projection (MIP) in dynamic contrast-enhanced (DCE) breast magnetic resonance imaging (MRI). We retrospectively gathered MIPs of DCE breast MRI for training and validation data from 30 and 7 normal individuals, 49 and 20 benign cases, and 135 and 45 malignant cases, respectively. Breast lesions were indicated with a bounding box and labeled as benign or malignant by a radiologist, while the AI system was trained to detect and calculate possibilities of malignancy using RetinaNet. The AI system was analyzed using test sets of 13 normal, 20 benign, and 52 malignant cases. Four human readers also scored these test data with and without the assistance of the AI system for the possibility of a malignancy in each breast. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were 0.926, 0.828, and 0.925 for the AI system; 0.847, 0.841, and 0.884 for human readers without AI; and 0.889, 0.823, and 0.899 for human readers with AI using a cutoff value of 2%, respectively. The AI system showed better diagnostic performance compared to the human readers (p = 0.002), and because of the increased performance of human readers with the assistance of the AI system, the AUC of human readers was significantly higher with than without the AI system (p = 0.039). Our AI system showed a high performance ability in detecting and diagnosing lesions in MIPs of DCE breast MRI and increased the diagnostic performance of human readers.

Can second-look ultrasound downgrade MRI-detected lesions? A retrospective study

PURPOSE

To determine whether MRI-detected suspicious (BIRADS 4 & 5) breast lesions can be downgraded using second-look ultrasound (SLU) and thus reduce unnecessarily performed breast biopsies.

MATERIALS METHODS

A retrospective single-center review of consecutive patients, who underwent breast MRI studies during a 12-month time period was performed. 94 patients with 103 lesions undergoing SLU of incidentally detected MRI BI-RADS 4&5 lesions which were not identified on previous ultrasound were included in the study. The SLU detection rate and SLU features of the lesions were assessed. Histology (91/103) or two year follow up (n = 12) were defined as the reference standard for lesion diagnosis.

RESULTS

57 (55.3 %) of the 103 lesions were identified on SLU. 17 of the identified lesions were malignant (29.8 %). Lesions detected on ultrasound presented on MRI as masses in 66.7 % (38/57) and non-mass in 33.3 % (19/57). Our findings showed that it is possible to distinguish between malignant and benign lesions with SLU. The results were significant (p < 0.05) for the following morphological features: shape, orientation, margins, architectural distortion, hyperechoic rim/ edema. All lesions classified as SLU BI-RADS 2 in our study were benign and thus, 30 % of all unnecessary biopsies could potentially have been avoided. Including SLU BI-RADS 3 lesions, this rate increased to 60 %, while yielding one (of 17, 5.8 %) false negative result. All three BI-RADS 5 lesions detected by SLU presented as malignant on ultrasound.

CONCLUSION

SLU can potentially downgrade incidental MRI BIRADS 4 lesions. This may reduce the number of unnecessarily performed biopsies by 30-60 %, thus simplifying patient management.

The role of magnetic resonance imaging in patients with palpable breast abnormalities and negative mammographic and sonographic findings

OBJECTIVE OR PURPOSE OF STUDY

The objective of this retrospective study was to determine the frequency of positive findings on breast magnetic resonance imaging (MRI) in patients with palpable breast abnormalities in the setting of negative mammographic and sonographic evaluations.

MATERIALS, METHODS, AND PROCEDURES

Consecutive patients undergoing breast MRI for palpable abnormalities from January 1, 2005 to December 31, 2015 were identified for this retrospective study. Those with preceding imaging (mammograms or ultrasounds) demonstrating positive findings related to the palpable abnormalities were excluded. The location and the duration of the symptoms, the type and the location of the abnormal MRI findings, and their relationships to the symptoms were recorded. Clinical and imaging follow-up as well as the type and the resultant biopsies were recorded. Patients with less than two years of imaging or clinical follow-up were excluded from the study.

RESULTS

22 004 women presented with palpable abnormalities at one breast imaging center between January 1, 2005 and December 31, 2015. Nine thousand and three hundred and thirty-four patients had negative or benign findings on mammography, ultrasound, or mammography plus ultrasound. Thirty-one patients underwent MRI with the complaint of palpable abnormalities despite negative or benign mammographic and/or sonographic findings. Their age range was between 32 and 74 years, and their mean age was 49 years. Of those who had MRI, twenty-one patients had negative MRI findings. Six patients had negative concordant results for the palpable abnormalities and benign incidental findings. Three patients had benign concordant results for the palpable abnormalities, and one patient had incidental atypia. Twenty-eight patients had negative MRI results in the area of the palpable abnormality, and none of these patients underwent biopsy. Of the 31 cases, four patients (13%) underwent additional examinations (three second-look ultrasounds and one bone scan) after MRI. Five patients (16%) underwent MRI-guided biopsies, two patients (6%) underwent ultrasound-guided biopsies, and one patient (3%) had an excision. All biopsies showed benign results. The Gail risk score was calculated for 22 of them and the mean 5-year risk was 1.64 and the mean lifetime risk was 12.51.

CONCLUSION

Breast MRI to evaluate palpable abnormalities after negative mammography and ultrasound results in a low yield for malignancy. The majority of patients (67.7%) had negative MRI examinations, and there were no malignancies detected. Our findings lead us to believe that there are no data to encourage the use of MRI in patients with palpable abnormalities and negative mammographic and/or ultrasound studies.

Can breast MRI accurately exclude malignancy in mammographic architectural distortion?

OBJECTIVES

To investigate the diagnostic accuracy of problem-solving breast magnetic resonance imaging (MRI) in excluding malignancy in a cohort of patients diagnosed with mammographic architectural distortion (MAD).

METHODS

The Institutional Review Board approved the study. Imaging database with 40,245 breast MRIs done between January 2008 and September 2018 was retrospectively reviewed. The study included all exams considered problem-solving MRI for MAD. Two radiologists reviewed the imaging data. Outcome was determined by the pathology results of biopsy/surgical excision or at least 1 year of clinical and radiological follow-up. Predictors for malignancy were examined, and appropriate statistical tests were applied.

RESULTS

One hundred seventy-five patients (median age 53 years) fulfilled the inclusion criteria and formed the study cohort. No cancers were diagnosed in 106 patients with a negative MRI. Out of 69 women with positive MRI findings, 48 (70%) had benign outcome defined either by pathology result or by negative follow-up, and 21 (30%) yielded malignancy. Malignancy was significantly associated with positive MRI (p < 0.001) and older age (p = 0.014). Falsely positive MRIs were frequently found in women with radial scars. The sensitivity, specificity, negative predictive value, positive predictive value, and overall accuracy of breast MRI were 100% (95% CI 84 to 100%), 68% (CI 61 to 76%), 100% (CI 95 to 100%), 30% (CI 26 to 36%), and 73% (95% CI 66-79), respectively.

CONCLUSION

A negative breast MRI in patients with MAD was reliable in excluding malignancy in this cohort and may have a role as a precision medicine tool for avoiding unnecessary interventions.

KEY POINTS

• MRI shows a high negative predictive value in MAD cases. • MRI displays low accuracy in differentiating malignancy from RS. • MRI is a reliable non-invasive method to exclude malignancy in women with mammographic architectural distortion, potentially avoiding unnecessary biopsies and surgeries.

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.

Attributes, Performance, and Gaps in Current & Emerging Breast Cancer Screening Technologies

Background:

Early detection of breast cancer, combined with effective treatment, can reduce mortality. Millions of women are diagnosed with breast cancer and many die every year globally. Numerous early detection screening tests have been employed. A wide range of current breast cancer screening methods are reviewed based on a series of searchers focused on clinical testing and performance. </P><P> Discussion: The key factors evaluated centre around the trade-offs between accuracy (sensitivity and specificity), operator dependence of results, invasiveness, comfort, time required, and cost. All of these factors affect the quality of the screen, access/eligibility, and/or compliance to screening programs by eligible women. This survey article provides an overview of the working principles, benefits, limitations, performance, and cost of current breast cancer detection techniques. It is based on an extensive literature review focusing on published works reporting the main performance, cost, and comfort/compliance metrics considered.

Conclusion:

Due to limitations and drawbacks of existing breast cancer screening methods there is a need for better screening methods. Emerging, non-invasive methods offer promise to mitigate the issues particularly around comfort/pain and radiation dose, which would improve compliance and enable all ages to be screened regularly. However, these methods must still undergo significant validation testing to prove they can provide realistic screening alternatives to the current accepted standards.

Problem-solving breast MRI: useful or a source of new problems?

PURPOSE

We aimed to evaluate the findings and results from breast magnetic resonance imaging (MRI) examinations performed for problem-solving purposes due to inconclusive conventional imaging findings.

METHODS

Imaging findings, biopsy and follow-up results were retrospectively evaluated for breast MRI performed for problem-solving purposes at our department between January 2011 and December 2016 for cases whose mammography, tomosynthesis, or ultrasonography findings were inconclusive.

RESULTS

Lesions were identified in 414 of 986 problem-solving MRI examinations, and 13.3% of these lesions were diagnosed as malignant. A total of 124 lesions were additionally found by MRI, and 9.7% of these lesions were diagnosed as malignant. MRI produced false-negative results in four cases. In cases whose conventional imaging methods yielded indefinite results, the sensitivity, specificity, negative and positive predictive values of MRI were found to be 96.3%, 83%, 99.3%, and 46.5%, respectively. For the additional lesions identified, the sensitivity, specificity, negative and positive predictive values of MRI were found to be 91.7%, 69%, 98.7%, and 24%, respectively.

CONCLUSION

Breast MRI is a reliable problem-solving method for excluding malignancy that cannot be confirmed by conventional imaging. In such cases, additional findings from MRI may help identify new cancers that cannot be detected with conventional methods. However, it has moderately low specificity which may cause unnecessary biopsies, follow-ups, and anxiety to patients.

Understanding indications and defining guidelines for breast magnetic resonance imaging

Magnetic resonance imaging (MRI) of the breast is the most sensitive imaging modality for detecting cancer. With improved scan resolution and correctly applied clinical indications, the specificity of breast MRI has markedly improved in recent years. Current literature indicates an overall sensitivity for breast MRI of 98% - 100% and specificity of 88%. By comparison, the sensitivity and specificity for mammography is in the region of 71% and 98%, respectively. In particular, the very high negative predictive value (NPV) of breast MRI, which approaches 100%, is hugely useful in establishing absence of disease. Furthermore, the ability to accurately delineate viable cancer by way of combining both morphological and functional (contrast enhancement) capabilities means that MRI is the best tool we have in terms of local cancer staging and identifying residual or recurrent disease. The high NPV also means that breast MRI is uniquely capable of ruling out cancer or high-grade ductal carcinoma in situ in appropriate circumstances. I hope that the following guidelines that are based on those of the American College of Radiology and the European Society of Breast Imaging in addition to multiple review articles will provide some assistance to radiologists in terms of the correct indications for breast MRI. There are few formal guidelines in South Africa for the usage of breast MRI. In fact, there is a general paucity of guidelines in the international radiology world. The role of breast MRI in high-risk screening and identification of the primary in occult breast cancer is universally accepted. Thereafter, there is little consensus. By using some general guidelines, and bringing MRI into the discussion of multidisciplinary breast cancer management, good clinical practice and consistent decision-making can be established.

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.

Problem-Solving MR Imaging for Equivocal Imaging Findings and Indeterminate Clinical Symptoms of the Breast

Breast MR imaging is commonly used for high-risk screening and for assessing the extent of disease in patients with newly diagnosed breast cancer, but its utility for assessing suspicious symptoms and equivocal imaging findings is less widely accepted. The authors review current literature and guidelines regarding the use of breast MR imaging for these indications. Overall, problem-solving breast MR imaging is best reserved for pathologic nipple discharge and sonographically occult architectural distortion with limited biopsy options. Further study is necessary to define the role of problem-solving MR imaging for calcifications, mammographic asymmetries, and surgical scarring.

3 Tesla breast MR imaging as a problem-solving tool: Diagnostic performance and incidental lesions

PURPOSE

To investigate the diagnostic performance and incidental lesion yield of 3T breast MRI if used as a problem-solving tool.

METHODS

This retrospective, IRB-approved, cross-sectional, single-center study comprised 302 consecutive women (mean: 50±12 years; range: 20-79 years) who were undergoing 3T breast MRI between 03/2013-12/2014 for further workup of conventional and clinical breast findings. Images were read by experienced, board-certified radiologists. The reference standard was histopathology or follow-up ≥ two years. Sensitivity, specificity, PPV, and NPV were calculated. Results were stratified by conventional and clinical breast findings.

RESULTS

The reference standard revealed 53 true-positive, 243 true-negative, 20 false-positive, and two false-negative breast MRI findings, resulting in a sensitivity, specificity, PPV, and NPV of 96.4% (53/55), 92.4% (243/263), 72.6% (53/73), and 99.2% (243/245), respectively. In 5.3% (16/302) of all patients, incidental MRI lesions classified BI-RADS 3-5 were detected, 37.5% (6/16) of which were malignant. Breast composition and the imaging findings that had led to referral had no significant influence on the diagnostic performance of breast MR imaging (p>0.05).

CONCLUSION

3T breast MRI yields excellent diagnostic results if used as a problem-solving tool independent of referral reasons. The number of suspicious incidental lesions detected by MRI is low, but is associated with a substantial malignancy rate.

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.

Preliminary Results of a Simplified Breast MRI Protocol to Characterize Breast Lesions: Comparison with a Full Diagnostic Protocol and a Review of the Current Literature

RATIONALE AND OBJECTIVES

This study aimed to investigate whether a simplified breast magnetic resonance imaging (MRI) protocol consisting of a localizer, one precontrast sequence, and three time-point postcontrast sequences (at 28 seconds, 84 seconds and 252 seconds after the contrast agent administration) is suitable for the characterization of breast lesions as compared to a full diagnostic protocol (FDP). This study also aimed to review the current literature concerning abbreviated breast MRI protocols and offer an alternative protocol.

MATERIALS AND METHODS

Breast magnetic resonance (MR) examinations with detected breast lesions of 98 patients were retrospectively evaluated. Two expert radiologists in consensus reviewed the simplified breast protocol (SBP) first and only thereafter the regular FDP, recording a diagnosis for each detected lesion for both protocols. Receiver operating characteristic curve analysis was performed to determine the diagnostic performance of the SBP compared to the standard FDP. A revision of the previously reported abbreviated breast magnetic resonance protocols was also carried out.

RESULTS

A total of 180 lesions were identified; of these, 110 (61%) were malignant and 70 (39%) were benign. Of the 110 malignant lesions, 86 (78%) were invasive ductal carcinoma, 18 (16%) were invasive lobular carcinoma, and 6 (6%) were ductal carcinoma in situ. Areas under the curve for the receiver operating characteristic curves for the SBP vs the FDP were equivalent (0.98 vs 0.99, respectively; P = 0.76). The SBP could be performed in approximately 6 minutes and 58 seconds, compared to 14 minutes and 48 seconds for the FDP.

CONCLUSIONS

An SBP protocol including a late postcontrast time point is accurate for the characterization of breast lesions and was comparable to the standard FDP protocol, allowing a potential reduction of the total acquisition and interpretation times.

MRI in the Assessment of BI-RADS® 4 lesions

The American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BI-RADS) lexicon, which is used ubiquitously to standardize reporting of breast magnetic resonance imaging (MRI), provides 7 BI-RADS assessment categories to indicate the level of suspicion of malignancy and guide further management. A BI-RADS category 4 assessment is assigned when an imaging abnormality does not fulfill the typical criteria for malignancy, but is suspicious enough to warrant a recommendation for biopsy. The BI-RADS category 4 assessment covers a wide range of probability of malignancy, from >2 to <95%. MRI is an essential noninvasive technique in breast imaging and the role of MRI in the assessment of ACR BI-RADS 4 lesions is manifold. In lesions classified as suspicious on imaging with mammography, digital breast tomosynthesis, and sonography, MRI can aid in the noninvasive differentiation of benign and malignant lesions and obviate unnecessary breast biopsies. When the suspicion of cancer is confirmed with MRI, concurrent staging of disease for treatment planning can be accomplished. This article will provide a comprehensive overview of the role of breast MRI in the assessment of ACR BI-RADS 4 lesions. In addition, we will discuss strategies to decrease false positives and avoid false negative results when reporting MRI of the breast.

MRI fused with prone FDG PET/CT improves the primary tumour staging of patients with breast cancer

OBJECTIVE

Our aim was to evaluate the diagnostic accuracy of magnetic resonance imaging (MRI) fused with prone 2-[fluorine-18]-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) in primary tumour staging of patients with breast cancer.

METHODS

This retrospective study evaluated 45 women with 49 pathologically proven breast carcinomas. MRI and prone PET-CT scans with time-of-flight and point-spread-function reconstruction were performed with the same dedicated breast coil. The studies were assessed by a radiologist and a nuclear medicine physician, and evaluation of fused images was made by consensus. The final diagnosis was based on pathology (90 lesions) or follow-up ≥ 24 months (17 lesions).

RESULTS

The study assessed 72 malignant and 35 benign lesions with a median size of 1.8 cm (range 0.3-8.4 cm): 31 focal, nine multifocal and nine multicentric cases. In lesion-by-lesion analysis, sensitivity, specificity, positive and negative predictive values were 97%, 80%, 91% and 93% for MRI, 96%, 71%, 87%, and 89% for prone PET, and 97%. 94%, 97% and 94% for MRI fused with PET. Areas under the curve (AUC) were 0.953, 0.850, and 0.983, respectively (p < 0.01).

CONCLUSIONS

MRI fused with FDG-PET is more accurate than FDG-PET in primary tumour staging of breast cancer patients and increases the specificity of MRI.

KEY POINTS

• FDG PET-CT may improve the specificity of MRI in breast cancer staging. • MRI fused with prone 2-[fluorine-18]-fluoro-2-deoxy-D-glucose PET-CT has better overall diagnostic performance than MRI. • The clinical role of fused PET-MRI has not yet been established.

Diagnostic Performance of Breast Magnetic Resonance Imaging in Non-Calcified Equivocal Breast Findings: Results from a Systematic Review and Meta-Analysis

OBJECTIVES

To evaluate the performance of MRI for diagnosis of breast cancer in non-calcified equivocal breast findings.

MATERIALS AND METHODS

We performed a systematic review and meta-analysis of peer-reviewed studies in PubMed from 01/01/1986 until 06/15/2015. Eligible were studies applying dynamic contrast-enhanced breast MRI as an adjunct to conventional imaging (mammography, ultrasound) to clarify equivocal findings without microcalcifications. Reference standard for MRI findings had to be established by histopathological sampling or imaging follow-up of at least 12 months. Number of true or false positives and negatives and other characteristics were extracted, and possible bias was determined using the QUADAS-2 applet. Statistical analyses included data pooling and heterogeneity testing.

RESULTS

Fourteen out of 514 studies comprising 2,316 lesions met our inclusion criteria. Pooled diagnostic parameters were: sensitivity (99%, 95%-CI: 93-100%), specificity (89%, 95%-CI: 85-92%), PPV (56%, 95%-CI: 42-70%) and NPV (100%, 95%-CI: 99-100%). These estimates displayed significant heterogeneity (P<0.001).

CONCLUSIONS

Breast MRI demonstrates an excellent diagnostic performance in case of non-calcified equivocal breast findings detected in conventional imaging. However, considering the substantial heterogeneity with regard to prevalence of malignancy, problem solving criteria need to be better defined.

Breast MR Imaging for Equivocal Mammographic Findings: Help or Hindrance?

Breast magnetic resonance (MR) imaging, because of its extremely high sensitivity in detecting invasive breast cancers, is sometimes used as a diagnostic tool to evaluate equivocal mammographic findings. However, breast MR imaging should never substitute for a complete diagnostic evaluation or for biopsy of suspected, localizable suspicious mammographic lesions, whenever possible. The modality's high cost, in addition to only moderate specificity, mandate that radiologists use it sparingly and with discrimination for problematic mammographic findings. It is rare that the reality or significance of a noncalcified mammographic finding remains equivocal or problematic at diagnostic mammography evaluation, which usually includes targeted ultrasonography (US). There are several reasons for this infrequent occurrence: (a) an asymmetry may persist on diagnostic views but be visible only on craniocaudal or mediolateral oblique projections, precluding three-dimensional localization for US or biopsy, or a lesion may persist on some diagnostic spot views but dissipate or efface on others; (b) uncertainty may exist as to whether apparent change is clinically important or owing to technical factors such as compression or positioning differences; or (c) a lesion may be suspected but biopsy options are limited owing to lack of a US correlate and lesion inaccessibility for stereotactic biopsy, or biopsy of a vague or questionably real lesion has been attempted unsuccessfully. This article will discuss the indications for problem-solving MR imaging for equivocal mammographic findings, present cases illustrating appropriate and inappropriate uses of problem-solving MR imaging, and present false-positive and false-negative cases affecting the specificity of breast MR imaging. (©)RSNA, 2016.

Influence of fat-water separation and spatial resolution on automated volumetric MRI measurements of fibroglandular breast tissue

The aim of this study was to investigate the influence of fat-water separation and spatial resolution in MRI on the results of automated quantitative measurements of fibroglandular breast tissue (FGT). Ten healthy volunteers (age range, 28-71 years; mean, 39.9 years) were included in this Institutional Review Board-approved prospective study. All measurements were performed on a 1.5-T scanner (Siemens, AvantoFit) using an 18-channel breast coil. The protocols included isotropic (Di) [TR/TE1 /TE2  = 6.00 ms/2.45 ms/2.67 ms; flip angle, 6.0°; 256 slices; matrix, 360 × 360; 1 mm isotropic; field of view, 360°; acquisition time (TA) = 3 min 38 s] and anisotropic (Da) (TR/TE1 /TE2  = 10.00 ms/2.39 ms/4.77 ms; flip angle, 24.9°; 80 slices; matrix 360 × 360; voxel size, 0.7 × 0.7 × 2.0 mm(3) ; field of view, 360°; TA = 1 min 25 s) T1 three-dimensional (3D) fast low-angle shot (FLASH) Dixon sequences, and a T1 3D FLASH sequence with the same resolution (T1 ) without (TR/TE = 11.00 ms/4.76 ms; flip angle, 25.0°; 80 slices; matrix, 360 × 360; voxel size, 0.7 × 0.7 × 2.0 mm(3) ; field of view, 360°; TA = 50 s) and with (TR/TE = 29.00 ms/4.76 ms; flip angle, 25.0°; 80 slices; matrix, 360 × 360; voxel size, 0.7 × 0.7 × 2.0 mm(3) ; field of view, 360°; TA = 2 min 35 s) fat saturation. Repeating volunteer measurements after 20 min and repositioning were used to assess reproducibility. An automated and quantitative volumetric breast density measurement system was used for FGT calculation. FGT with Di, Da and T1 measured 4.6-63.0% (mean, 30.6%), 3.2-65.3% (mean, 32.5%) and 1.7-66.5% (mean, 33.7%), respectively. The highest correlation between different MRI sequences was found with the Di and Da sequences (R(2)  = 0.976). Coefficients of variation (CVs) for FGT calculation were higher in T1 (CV = 21.5%) compared with Dixon (Di, CV = 5.1%; Da, CV = 4.2%) sequences. Dixon-type sequences worked well for FGT measurements, even at lower resolution, whereas the conventional T1 -weighted sequence was more sensitive to decreasing resolution. The Dixon fat-water separation technique showed superior repeatability of FGT measurements compared with conventional sequences. A standard dynamic protocol using Dixon fat-water separation is best suited for combined diagnostic purposes and prognostic measurements of FGT. Copyright © 2016 John Wiley & Sons, Ltd.