To evaluate the diagnostic utility of second-look ultrasonography (US) in the assessment of lesions identified at breast magnetic resonance (MR) imaging.
A systematic review of the PubMed database ...for articles published up to January 6, 2013, was performed by using predefined search terms applied in a standardized manner. Second-look US studies for the assessment of breast lesions identified at MR imaging were eligible for this meta-analysis. Two independent reviewers performed the literature review and data extraction. Eligible studies presented data on the number of lesions examined and the number of lesions detected at second-look US. The reference standard for lesion diagnosis was either histopathologic or follow-up examination. Sources of bias were assessed by using the Quality Assessment of Diagnostic Accuracy Studies 2, or QUADAS-2 Quality Assessment of Diagnostic Accuracy Studies 2 , tool. Statistical analysis included data pooling, heterogeneity testing, and meta-regression.
Seventeen studies that included benign and malignant lesions met the inclusion criteria. The general lesion detection rate at second-look US was very heterogeneous and ranged between 22.6% and 82.1% (pooled rate, 57.5% 1266 of 2201; 95% confidence interval CI confidence interval : 50.0%, 64.1% random-effects model; I(2) = 90.9%; P < .0001). The highest second-look US detection rates were observed for mass lesions (as opposed to nonmass lesions) and malignant (vs benign) lesions (P < .001 for both). Pooled positive and negative predictive values (positive or negative second-look US correlates of MR imaging-detected malignant or benign lesions) were calculated as 30.7% (95% CI confidence interval : 25.3%, 36.4%; I(2) = 75.4%; P < .0001) and 87.8% (95% CI confidence interval : 82.0%, 92.7%; I(2) = 82.1%; P < .0001), respectively, by using random-effects models.
The results of this study demonstrated variable utility of second-look US in MR imaging-detected lesions, as lesion detection rates were very heterogeneous. Subgroup analysis showed that malignant and mass lesions were more likely to be detected at second-look US. Furthermore, malignancy was not excluded if a lesion was not detected at second-look US.
Breast density is an independent risk factor for the development of breast cancer and also decreases the sensitivity of mammography for screening. Consequently, women with extremely dense breasts ...face an increased risk of late diagnosis of breast cancer. These women are, therefore, underserved with current mammographic screening programs. The results of recent studies reporting on contrast-enhanced breast MRI as a screening method in women with extremely dense breasts provide compelling evidence that this approach can enable an important reduction in breast cancer mortality for these women and is cost-effective. Because there is now a valid option to improve breast cancer screening, the European Society of Breast Imaging (EUSOBI) recommends that women should be informed about their breast density. EUSOBI thus calls on all providers of mammography screening to share density information with the women being screened. In light of the available evidence, in women aged 50 to 70 years with extremely dense breasts, the EUSOBI now recommends offering screening breast MRI every 2 to 4 years. The EUSOBI acknowledges that it may currently not be possible to offer breast MRI immediately and everywhere and underscores that quality assurance procedures need to be established, but urges radiological societies and policymakers to act on this now. Since the wishes and values of individual women differ, in screening the principles of shared decision-making should be embraced. In particular, women should be counselled on the benefits and risks of mammography and MRI-based screening, so that they are capable of making an informed choice about their preferred screening method.
Key Points
•
The recommendations in Figure 1 summarize the key points of the manuscript
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.
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
mm
/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.
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).
An ADC cutoff of ≥1.5 × 10
mm
/second allows downgrading of lesions classified as BI-RADS 4 on breast CE-MRI. One-third of unnecessary biopsies could thus be avoided.
Available data proving the value of DWI for breast cancer diagnosis is mainly for enhancing masses; DWI may be less sensitive and specific in non-mass enhancement (NME) lesions. The objective of this ...study was to assess the diagnostic accuracy of DWI using different ROI measurement approaches and ADC metrics in breast lesions presenting as NME lesions on dynamic contrast-enhanced (DCE) MRI.
In this retrospective study, 95 patients who underwent multiparametric MRI with DCE and DWI from September 2007 to July 2013 and who were diagnosed with a suspicious NME (BI-RADS 4/5) were included. Twenty-nine patients were excluded for lesion non-visibility on DWI (n = 24: 12 benign and 12 malignant) and poor DWI quality (n = 5: 1 benign and 4 malignant). Two readers independently assessed DWI and DCE-MRI findings in two separate randomized readings using different ADC metrics and ROI approaches. NME lesions were classified as either benign (> 1.3 × 10
mm
/s) or malignant (≤ 1.3 × 10
mm
/s). Histopathology was the standard of reference. ROC curves were plotted, and AUCs were determined. Concordance correlation coefficient (CCC) was measured.
There were 39 malignant (59%) and 27 benign (41%) lesions in 66 (65 women, 1 man) patients (mean age, 51.8 years). The mean ADC value of the darkest part of the tumor (Dptu) achieved the highest diagnostic accuracy, with AUCs of up to 0.71. Inter-reader agreement was highest with Dptu ADC max (CCC 0.42) and lowest with the point tumor (Ptu) ADC min (CCC = - 0.01). Intra-reader agreement was highest with Wtu ADC mean (CCC = 0.44 for reader 1, 0.41 for reader 2), but this was not associated with the highest diagnostic accuracy.
Diagnostic accuracy of DWI with ADC mapping is limited in NME lesions. Thirty-one percent of lesions presenting as NME on DCE-MRI could not be evaluated with DWI, and therefore, DCE-MRI remains indispensable. Best results were achieved using Dptu 2D ROI measurement and ADC mean.
OBJECTIVESThe aim of this study was to assess the potential of noncontrast magnetic resonance imaging (NC-MRI) with diffusion-weighted imaging (DWI) in characterization of breast lesions in ...comparison to dynamic contrast-enhanced MRI (DCE-MRI) at 3 T.
MATERIALS AND METHODSConsecutive patients with conventional imaging (mammography, ultrasound) BI-RADS 4/5 findings were included in this institutional review board–approved single-center study. All underwent 3 T breast MRI including readout-segmented DWI, DCE, and T2-weighted sequences. Final diagnosis was defined by histopathology or follow-up (>24 months). Two experienced radiologists (R1, R2) independently assigned lesion conspicuity (0 = minimal to 3 = excellent) and BI-RADS scores to NC-MRI (readout-segmented DWI including apparent diffusion coefficient maps) and DCE-MRI (DCE and T2-weighted). Receiver operating characteristics, κ statistics, and visual grading characteristics analysis were applied.
RESULTSSixty-seven malignant and 56 benign lesions were identified in 113 patients (mean age, 54 ± 14 years). Areas under the receiver operating characteristics curves were similarDCE-MRI0.901 (R1), 0.905 (R2); NC-MRI0.882 (R1), 0.854 (R2); P > 0.05, respectively. The κ agreement was 0.968 (DCE-MRI) and 0.893 (NC-MRI). Visual grading characteristics analysis revealed superior lesion conspicuity by DCE-MRI (0.661, P < 0.001).
CONCLUSIONSDiagnostic performance and interreader agreement of both NC-MRI and DCE-MRI is high, indicating a potential use of NC-MRI as an alternative to DCE-MRI. However, inferior lesion conspicuity and lower interreader agreement of NC-MRI need to be considered.
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.
Purpose
To investigate the impact of a scoring system (
Tree
) on inter-reader agreement and diagnostic performance in breast MRI reading.
Materials and methods
This IRB-approved, single-centre study ...included 100 patients with 121 consecutive histopathologically verified lesions (52 malignant, 68 benign). Four breast radiologists with different levels of MRI experience and blinded to histopathology retrospectively evaluated all examinations. Readers independently applied two methods to classify breast lesions: BI-RADS and
Tree
. BI-RADS provides a reporting lexicon that is empirically translated into likelihoods of malignancy;
Tree
is a scoring system that results in a diagnostic category. Readings were compared by ROC analysis and kappa statistics.
Results
Inter-reader agreement was substantial to almost perfect (kappa: 0.643–0.896) for
Tree
and moderate (kappa: 0.455–0.657) for BI-RADS. Diagnostic performance using
Tree
(AUC: 0.889–0.943) was similar to BI-RADS (AUC: 0.872–0.953). Less experienced radiologists achieved AUC: improvements up to 4.7 % using
Tree
(
P
-values: 0.042–0.698); an expert’s performance did not change (
P
= 0.526). The least experienced reader improved in specificity using
Tree
(16 %,
P
= 0.001). No further sensitivity and specificity differences were found (
P
> 0.1).
Conclusion
The
Tree
scoring system improves inter-reader agreement and achieves a diagnostic performance similar to that of BI-RADS. Less experienced radiologists, in particular, benefit from
Tree
.
Key Points
•
The Tree scoring system shows high diagnostic accuracy in mass and non-mass lesions
.
•
The Tree scoring system reduces inter-reader variability related to reader experience
.
•
The Tree scoring system improves diagnostic accuracy in non-expert readers
.
We sought to compare the diagnostic performance of apparent diffusion coefficient (ADC) mapping with the Kaiser score (KS) to distinguish benign from malignant breast lesions and to assess the ...potential of this approach to help avoid unnecessary biopsies.
MATERIALS AND METHODSIn 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).
RESULTSA 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 mm/s for ADC). However, the rate of potentially avoidable biopsies was higher when using the KS (specificity65.4% for KS vs 32.9% for ADC; P < 0.0001). The KS was superior to the KS+ in avoiding unnecessary biopsies.
CONCLUSIONSBoth 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.
Objectives
To assess whether using the
Tree
flowchart obviates unnecessary magnetic resonance imaging (MRI)-guided biopsies in breast lesions only visible on MRI.
Methods
This retrospective ...IRB-approved study evaluated consecutive suspicious (BI-RADS 4) breast lesions only visible on MRI that were referred to our institution for MRI-guided biopsy. All lesions were evaluated according to the
Tree
flowchart for breast MRI by experienced readers. The
Tree
flowchart is a decision rule that assigns levels of suspicion to specific combinations of diagnostic criteria. Receiver operating characteristic (ROC) curve analysis was used to evaluate diagnostic accuracy. To assess reproducibility by kappa statistics, a second reader rated a subset of 82 patients.
Results
There were 454 patients with 469 histopathologically verified lesions included (98 malignant, 371 benign lesions). The area under the curve (AUC) of the
Tree
flowchart was 0.873 (95% CI: 0.839–0.901). The inter-reader agreement was almost perfect (kappa: 0.944; 95% CI 0.889–0.998). ROC analysis revealed exclusively benign lesions if the
Tree
node was ≤2, potentially avoiding unnecessary biopsies in 103 cases (27.8%).
Conclusions
Using the
Tree
flowchart in breast lesions only visible on MRI, more than 25% of biopsies could be avoided without missing any breast cancer.
Key Points
•
The Tree
flowchart may obviate >25% of unnecessary MRI-guided breast biopsies.
• This decrease in MRI-guided biopsies does not cause any false-negative cases.
•
The Tree
flowchart predicts 30.6% of malignancies with >98% specificity.
•
The Tree’s
high specificity aids in decision-making after benign biopsy results.
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