Magnetic Resonance Mammography Research Articles

Sensitivity and specificity of unenhanced MR mammography (DWI combined with T2-weighted TSE imaging, ueMRM) for the differentiation of mass lesions

This study was performed to assess the sensitivity and specificity for malignant and benign mass lesions of a diagnostic approach combining DWI with T2-weighted images (unenhanced MR mammography, ueMRM) and compare the results with contrast-enhanced MR mammography (ceMRM). Consecutive patients undergoing histopathological verification of mass lesions after MR mammography without prior breast interventions (contrast-enhanced T1-weighted, T2-weighted and DWI sequences) were eligible for this retrospective investigation. Two blinded observers first rated ueMRM and then ceMRM according to the BIRADS scale. Lesion size, ADC values and T2-weighted TSE descriptors were assessed. This study examined 81 lesions (27 benign, 54 malignant). Sensitivity of ueMRM was 93% (observer 1) and 86% (observer 2), respectively. Sensitivity of ceMRM was 96.5% (observer 1) and 98.3% (observer 2). Specificity was 85.2% (ueMRM) and 92.6% (ceMRM) for both observers. The differences between both methods and observers were not significant (P > or = 0.09). Lesion size measurements did not differ significantly among all sequences analyzed. Tumor visibility was worse using ueMRM for both benign (P < 0.001) and malignant lesions (P = 0.004). Sensitivity and specificity of ueMRM in mass lesions equal that of ceMRM. However, a reduced lesion visibility in ueMRM may lead to more false-negative findings.

Can Color-Coded Parametric Maps Improve Dynamic Enhancement Pattern Analysis in MR Mammography?

Post-contrast enhancement characteristics (PEC) are a major criterion for differential diagnosis in MR mammography (MRM). Manual placement of regions of interest (ROIs) to obtain time/signal intensity curves (TSIC) is the standard approach to assess dynamic enhancement data. Computers can automatically calculate the TSIC in every lesion voxel and combine this data to form one color-coded parametric map (CCPM). Thus, the TSIC of the whole lesion can be assessed. This investigation was conducted to compare the diagnostic accuracy (DA) of CCPM with TSIC for the assessment of PEC. 329 consecutive patients with 469 histologically verified lesions were examined. MRM was performed according to a standard protocol (1.5 T, 0.1 mmol/kgbw Gd-DTPA). ROIs were drawn manually within any lesion to calculate the TSIC. CCPMs were created in all patients using dedicated software (CAD Sciences). Both methods were rated by 2 observers in consensus on an ordinal scale. Receiver operating characteristics (ROC) analysis was used to compare both methods. The area under the curve (AUC) was significantly (p=0.026) higher for CCPM (0.829) than TSIC (0.749). The sensitivity was 88.5% (CCPM) vs. 82.8% (TSIC), whereas equal specificity levels were found (CCPM: 63.7%, TSIC: 63.0%). The color-coded parametric maps (CCPMs) showed a significantly higher DA compared to TSIC, in particular the sensitivity could be increased. Therefore, the CCPM method is a feasible approach to assessing dynamic data in MRM and condenses several imaging series into one parametric map.

Bildgebende Diagnostik des invasiv lobulären Mammakarzinoms

Early diagnosis of invasive lobular breast carcinoma by physical examination and mammography is often difficult. It is thus often diagnosed only at an advanced tumor stage. Sonography of the breast can increase the sensitivity for diagnosis of invasive lobular breast cancer, but this modality has its limitations even when performed by experienced investigators. The combination of mammography and sonography also has limitations, particularly with regard to the staging of the invasive lobular cancer, as tumor dimensions are often underestimated and multifocality or multicentricity often not recognized. At present, MR mammography is the most sensitive modality for the diagnosis and staging of invasive lobular breast cancer. It has therefore been recommended for local staging of invasive lobular carcinoma in the updated stage 3 guidelines for the early detection of breast cancer in Germany 2008.

Cancers inBRCA1andBRCA2Carriers and in Women at High Risk for Breast Cancer: MR Imaging and Mammographic Features

To review imaging features of screening-detected cancers on images from diagnostic and prior examinations to identify specific abnormalities to aid earlier detection of or facilitate differentiation of cancers in BRCA1 and BRCA2 carriers and in women with a high risk for breast cancer. Informed consent and multicenter and local research ethics committee approval were obtained. Women (mean age, 40.1 years; range, 27-55 years) who had at least a 50% risk of being a BRCA1, BRCA2, or TP53 gene mutation carrier were recruited from August 1997 to March 2003 into the United Kingdom Magnetic Resonance Imaging in Breast Screening Study Group trial and were offered annual magnetic resonance (MR) imaging and two-view mammography (total number of screenings, 2065 and 1973; mean, 2.38 and 2.36, respectively). Images in all 39 cancer cases were reread in consensus to document the morphologic and enhancement imaging features on MR and mammographic images in screening and prior examinations. Cases were grouped into genetic subtypes. With MR imaging, there was no difference in morphologic or enhancement characteristics between the genetic subgroups. Cancers on images from prior examinations were of smaller size, showed less enhancement, and were more likely to have a type 1 enhancement curve compared with those cancers in the subsequent diagnostic screening examinations. The tumor sizes detected by using MR imaging and mammography were not significantly different (P = .46). The cancers in BRCA1 carriers found by using MR imaging tended to be smaller than those detected by using mammography (median, 17 mm vs 30 mm; P = .37), whereas the opposite was true for cancers found in BRCA2 carriers (MR imaging median size = 12.5 mm vs mammographic median size = 6 mm; P = .067); the difference was not significant. Tumors with prior MR imaging abnormalities grew at an average of 5.1 mm/y. When undertaking MR imaging surveillance in high-risk women, small enhancing lesions should be regarded with suspicion and biopsied or patients should be followed up at 6 months.

Whole-Body Magnetic Resonance Imaging of Healthy Volunteers: Pilot Study Results from the Population-Based SHIP Study

Approximately 4000 volunteers will undergo whole-body magnetic resonance imaging (WB-MRI) within the next 3 years in the population-based Study of Health in Pomerania (SHIP). Here we present a pilot study conducted (a) to determine the feasibility of adding a WB-MRI protocol to a large-scale population-based study, (b) to evaluate the reliability of standardized MRI interpretation, and (c) to establish an approach for handling pathological findings. The institutional review board approved the study, and oral and written informed consent was obtained from each participant. Two hundred healthy volunteers (99 women, 101 men; mean age 48.3 years) underwent a standardized WB-MRI protocol. The protocol was supplemented by contrast-enhanced cardiac MRI and magnetic resonance (MR) angiography in 61 men (60.4%) and cardiac MRI and MR mammography in 44 women (44.4%). MR scans were evaluated independently by two readers. Abnormalities were discussed by an advisory board and classified according to the need for further clinical work-up. One hundred ninety-four (97.0%) WB-MRI examinations were successfully completed in a mean scan time per subject of 90 minutes. There were 431 pathological findings in 176 (88%) of the participants. Of those 45 (10.4%) required further clinical work-up and 386 (89.6%) characterized as benign lesions did not. The interobserver agreement for the detection of pathological findings was excellent (kappa = 0.799). The preliminary results presented here indicate that a large prospective, population-based study using WB-MRI is feasible and that the results of image analysis are reproducible. A variety of positive findings provide valuable information regarding disease prevalence in a general adult population.

Accuracy of the Fischer scoring system and the Breast Imaging Reporting and Data System in identification of malignant breast lesions

Fischer developed a scoring system in 1999 that made identifying malignant lesions much easier for inexperienced radiologists. Our study was performed to assess whether this scoring system would help beginners to accurately diagnose breast lesions on magnetic resonance (MR) imaging and to assess the correlation between the magnetic resonance mammography Breast Imaging Reporting and Data System (MRM BI-RADS) grade and the final diagnosis. The lesion morphology and contrast kinetics of 63 masses in 41 patients were evaluated on MRI and accorded a MRM BI-RADS final assessment category using the Fischer scoring system. The accuracy was evaluated after the final diagnosis was obtained by tissue sampling and follow-up imaging. There were 25 malignant and 30 benign lesions. Eight lesions were seen by MRI only and we could not verify their pathology since we did not have MR-guided biopsy facilities at the time of the study. On MR mammography, the proven carcinomatous lesions were characterized as BI-RADS category V in 16 (64%), category IV in 7 (28%), and category III in 2 (8%) lesions. Benign lesions were graded as category V in 3 (10%), category IV in 6 (20%), and category III in 3 (10%), category II in 10 (33%) and category I in 8 (27%) lesions. The MRM BI-RADS category accurately predicted malignancy in 92% and a benign pathology in 70% of the lesions. The overlap between the MRM features of chronic inflammatory lesions and carcinomas resulted in a lower accuracy in diagnosing benign as compared to malignant lesions. The MRM BI-RADS lexicon using the Fischer scoring system is useful and has a high predictive value, especially for malignant breast lesions, and is easy to apply. Overlapping features between benign inflammatory and malignant lesions might yield a reduced accuracy in inflammatory pathologies.

Accuracy of the Fischer scoring system and the Breast Imaging Reporting and Data System in identification of malignant breast lesions

BACKGROUND AND OBJECTIVES:Fischer developed a scoring system in 1999 that made identifying malignant lesions much easier for inexperienced radiologists. Our study was performed to assess whether this scoring system would help beginners to accurately diagnose breast lesions on magnetic resonance (MR) imaging and to assess the correlation between the magnetic resonance mammography Breast Imaging Reporting and Data System (MRM BI-RADS) grade and the final diagnosis.PATIENTS AND METHODS:The lesion morphology and contrast kinetics of 63 masses in 41 patients were evaluated on MRI and accorded a MRM BI-RADS final assessment category using the Fischer scoring system. The accuracy was evaluated after the final diagnosis was obtained by tissue sampling and follow-up imaging.RESULTS:There were 25 malignant and 30 benign lesions. Eight lesions were seen by MRI only and we could not verify their pathology since we did not have MR-guided biopsy facilities at the time of the study. On MR mammography, the proven carcinomatous lesions were characterized as BI-RADS category V in 16 (64%), category IV in 7 (28%), and category III in 2 (8%) lesions. Benign lesions were graded as category V in 3 (10%), category IV in 6 (20%), and category III in 3 (10%), category II in 10 (33%) and category I in 8 (27%) lesions. The MRM BI-RADS category accurately predicted malignancy in 92% and a benign pathology in 70% of the lesions. The overlap between the MRM features of chronic inflammatory lesions and carcinomas resulted in a lower accuracy in diagnosing benign as compared to malignant lesions.CONCLUSION:The MRM BI-RADS lexicon using the Fischer scoring system is useful and has a high predictive value, especially for malignant breast lesions, and is easy to apply. Overlapping features between benign inflammatory and malignant lesions might yield a reduced accuracy in inflammatory pathologies.

Signal intensity of normal breast tissue at MR mammography midfield: applying a random coefficient model evaluating the effect of doubling the contrast dose

To prospectively investigate the effect on signal intensity (SI) of healthy breast parenchyma on magnetic resonance mammography (MRM) when doubling the contrast dose from 0.1 to 0.2 mmol/kg body weight.

Clinical MR-Mammography: Are Computer-Assisted Methods Superior to Visual or Manual Measurements for Curve Type Analysis? A Systematic Approach

Enhancement characteristics after administration of a contrast agent are regarded as a major criterion for differential diagnosis in magnetic resonance mammography (MRM). However, no consensus exists about the best measurement method to assess contrast enhancement kinetics. This systematic investigation was performed to compare visual estimation with manual region of interest (ROI) and computer-aided diagnosis (CAD) analysis for time curve measurements in MRM. A total of 329 patients undergoing surgery after MRM (1.5 T) were analyzed prospectively. Dynamic data were measured using visual estimation, including ROI as well as CAD methods, and classified depending on initial signal increase and delayed enhancement. Pathology revealed 469 lesions (279 malignant, 190 benign). Kappa agreement between the methods ranged from 0.78 to 0.81. Diagnostic accuracies of 74.4% (visual), 75.7% (ROI), and 76.6% (CAD) were found without statistical significant differences. According to our results, curve type measurements are useful as a diagnostic criterion in breast lesions irrespective of the method used.

Application of Computer-aided Diagnosis (CAD) in MR-Mammography (MRM): Do We Really Need Whole Lesion Time Curve Distribution Analysis?

The identification of the most suspect enhancing part of a lesion is regarded as a major diagnostic criterion in dynamic magnetic resonance mammography. Computer-aided diagnosis (CAD) software allows the semi-automatic analysis of the kinetic characteristics of complete enhancing lesions, providing additional information about lesion vasculature. The diagnostic value of this information has not yet been quantified. Consecutive patients from routine diagnostic studies (1.5 T, 0.1 mmol gadopentetate dimeglumine, dynamic gradient-echo sequences at 1-minute intervals) were analyzed prospectively using CAD. Dynamic sequences were processed and reduced to a parametric map. Curve types were classified by initial signal increase (not significant, intermediate, and strong) and the delayed time course of signal intensity (continuous, plateau, and washout). Lesion enhancement was measured using CAD. The most suspect curve, the curve-type distribution percentage, and combined dynamic data were compared. Statistical analysis included logistic regression analysis and receiver-operating characteristic analysis. Fifty-one patients with 46 malignant and 44 benign lesions were enrolled. On receiver-operating characteristic analysis, the most suspect curve showed diagnostic accuracy of 76.7 +/- 5%. In comparison, the curve-type distribution percentage demonstrated accuracy of 80.2 +/- 4.9%. Combined dynamic data had the highest diagnostic accuracy (84.3 +/- 4.2%). These differences did not achieve statistical significance. With appropriate cutoff values, sensitivity and specificity, respectively, were found to be 80.4% and 72.7% for the most suspect curve, 76.1% and 83.6% for the curve-type distribution percentage, and 78.3% and 84.5% for both parameters. The integration of whole-lesion dynamic data tends to improve specificity. However, no statistical significance backs up this finding.

Imaging Studies for the Early Detection of Breast Cancer: MRI Not Considered

The article does not consider the substantial diagnostic added value of modern methods, such as magnetic resonance mammography (MRM). The authors don’t mention that The sensitivity of x-ray mammography is below 50% according to the most recent publications (1) X-ray mammography overlooks at least 10 times more cancers than MRM. One should not create the impression that x-ray mammography is the gold standard. Too many patients suffer and die from breast cancer because it is detected too late. The diagnostic added value of a technically and methodologically well conducted MRM is undeniably overwhelming. MRM is obviously laborious and quite expensive (€ 420), and it requires a steep learning curve. However, in the hands of experienced experts, it is certainly a very promising modality. Breast cancer is a life threatening disease, the most common cancer, and up to the 55th year of life the most common cause of death in women. Patients therefore have a right to this information. The authors report that they were involved in the initial description of magnetic resonance tomography and thus create the impression that they discovered the procedure. With all due respect, it should not be forgotten that other studies pre-dating and post-dating theirs have enabled fundamental advances in coil development, investigative techniques, and image interpretation. A greater degree of objectivity and detachment seems advisable.

Accuracy of MRI volume measurements of breast lesions: comparison between automated, semiautomated and manual assessment

The aim of this study was to investigate the efficacy of a dedicated software tool for automated and semiautomated volume measurement in contrast-enhanced (CE) magnetic resonance mammography (MRM). Ninety-six breast lesions with histopathological workup (27 benign, 69 malignant) were re-evaluated by different volume measurement techniques. Volumes of all lesions were extracted automatically (AVM) and semiautomatically (SAVM) from CE 3D MRM and compared with manual 3D contour segmentation (manual volume measurement, MVM, reference measurement technique) and volume estimates based on maximum diameter measurement (MDM). Compared with MVM as reference method MDM, AVM and SAVM underestimated lesion volumes by 63.8%, 30.9% and 21.5%, respectively, with significantly different accuracy for benign (102.4%, 18.4% and 11.4%) and malignant (54.9%, 33.0% and 23.1%) lesions (p < 0.05). Inter- and intraobserver reproducibility was best for AVM (mean difference +/- 2SD, 1.0 +/- 9.7% and 1.8 +/- 12.1%) followed by SAVM (4.3 +/- 25.7% and 4.3 +/- 7.9%), MVM (2.3 +/- 38.2% and 8.6 +/- 31.8%) and MDM (33.9 +/- 128.4% and 9.3 +/- 55.9%). SAVM is more accurate for volume assessment of breast lesions than MDM and AVM. Volume measurement is less accurate for malignant than benign lesions.

Evaluation of Suspicious Nipple Discharge by Magnetic Resonance Mammography Based on Breast Imaging Reporting and Data System Magnetic Resonance Imaging Descriptors

To evaluate the findings of magnetic resonance mammography for suspicious nipple discharge based on breast imaging-reporting and data system magnetic resonance imaging (MRI) descriptors and establish any correlations with the histopathologic diagnoses. Forty-seven patients with suspicious nipple discharge underwent MRI using a 1.5-T system. Images were evaluated for a signal of abnormal discharge, related abnormal enhancement according to the breast imaging-reporting and data system MRI descriptors, and the presence of clustered ring enhancement and were compared with the histopathologic diagnoses established in 39 lesions. The most common finding in patients with suspicious nipple discharge was non-masslike enhancement. Seventeen malignant and 22 benign lesions were detected. The most frequent findings in the malignant lesions were "segmental" (59%), "heterogeneous" (57%), and plateau pattern (40%). Clustered ring enhancement was found in 60% of the enhanced malignant lesions (P = 0.002). The combination of segmental distribution and clustered ring enhancement showed a significant association with malignant lesions (P = 0.004). Magnetic resonance imaging provides clinically useful information in patients with suspicious nipple discharge.

Small Lesions Evaluation Based on Unsupervised Cluster Analysis of Signal-Intensity Time Courses in Dynamic Breast MRI

An application of an unsupervised neural network-based computer-aided diagnosis (CAD) system is reported for the detection and characterization of small indeterminate breast lesions, average size 1.1 mm, in dynamic contrast-enhanced MRI. This system enables the extraction of spatial and temporal features of dynamic MRI data and additionally provides a segmentation with regard to identification and regional subclassification of pathological breast tissue lesions. Lesions with an initial contrast enhancement ≥50% were selected with semiautomatic segmentation. This conventional segmentation analysis is based on the mean initial signal increase and postinitial course of all voxels included in the lesion. In this paper, we compare the conventional segmentation analysis with unsupervised classification for the evaluation of signal intensity time courses for the differential diagnosis of enhancing lesions in breast MRI. The results suggest that the computerized analysis system based on unsupervised clustering has the potential to increase the diagnostic accuracy of MRI mammography for small lesions and can be used as a basis for computer-aided diagnosis of breast cancer with MR mammography.

MR mammography at 7 Tesla: Preliminary results

MR mammography at 7 Tesla: Preliminary results

Practical application of contrast-enhanced magnetic resonance mammography [CE-MRM] by an algorithm combining morphological and enhancement patterns

The purpose of this article is to report our practical utilization of dynamic contrast-enhanced magnetic resonance mammography [DCE-MRM] in the diagnosis of breast lesions. In many European centers, was preferred a high-temporal acquisition of both breasts simultaneously in a large FOV. We preferred to scan single breasts, with the aim to combine the analysis of the contrast intake and washout with the morphological evaluation of breast lesions. We followed an interpretation model, based upon a diagnostic algorithm, which combined contrast enhancement with morphological evaluation, in order to increase our confidence in diagnosis. DCE-MRM with our diagnostic algorithm has identified 179 malignant and 41 benign lesions; final outcome has identified 178 malignant and 42 benign lesions, 3 false positives and 2 false negatives. Sensitivity of CE-MRM was 98.3%; specificity, 95.1%; positive predictive value, 98.9%; negative predictive value, 92.8% and accuracy, 97.7%.

Contrast-Enhanced MR Mammography: Improved Lesion Detection and Differentiation with Gadobenate Dimeglumine

The objective of our study was to intraindividually compare 0.1 mmol/kg doses of gadobenate dimeglumine and gadopentetate dimeglumine for contrast-enhanced breast MRI. Forty-seven women (mean age +/- SD, 50.8 +/- 12.9 years) with breast lesions classified as BI-RADS category 3, 4, or 5 for suspicion of malignancy underwent two identical MR examinations at 1.5 T separated by 48-72 hours. T1-weighted gradient-echo images were acquired before contrast administration and at 2-minute intervals after the randomized injection of gadopentetate dimeglumine or gadobenate dimeglumine at 2 mL/s. Two blinded readers evaluated randomized image sets for lesion detection and differentiation as benign or malignant compared with histology. The McNemar exact test and the generalized estimating equation (GEE) were used to compare lesion detection rates and diagnostic performance in terms of sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV). Histopathology data were available for 78 lesions. Significantly more lesions overall (75/78 [96%] vs 62/78 [79%], respectively; p = 0.0002) and significantly more malignant lesions (49/50 [98%] vs 38/50 [76%]; p = 0.0009) were detected with gadobenate dimeglumine than gadopentetate dimeglumine. All detected malignant lesions were correctly diagnosed with both agents. More detected benign lesions were correctly diagnosed with gadobenate dimeglumine than with gadopentetate dimeglumine (20/26 [77%] vs 17/24 [71%], respectively). Differentiation of lesions was significantly (p = 0.0001) better with gadobenate dimeglumine. Significantly better diagnostic performance was noted with gadobenate dimeglumine than with gadopentetate dimeglumine, respectively, for sensitivity (98.0% vs 76.0%; p = 0.0064), accuracy (88.5% vs 69.2%; p = 0.0004), PPV (86.0% vs 76.0%; p = 0.0321), and NPV (95.2% vs 57.1%; p = 0.0003). Lesion detection and malignant-benign differentiation is significantly better with 0.1 mmol/kg gadobenate dimeglumine than 0.1 mmol/kg gadopentetate dimeglumine.

Diagnosis of ductal carcinoma in situ using contrast-enhanced magnetic resonance mammography compared with conventional mammography

Purpose The objective of this study is to compare mammography with magnetic resonance mammography (MRM) in the diagnosis of histopathologically verified subtypes of ductal carcinoma in situ (DCIS). Materials and Methods All patients with verified pure DCIS lesions (no signs of invasion or microinvasion) after surgery were identified between 2004 and 2006. Selection criteria were performed mammography and MRM at our institute prior to surgery resulting in a cohort of 33 patients (mean patient age, 60 years; mean lesion size, 15 mm). Results Magnetic resonance mammography enabled identification of DCIS in 29 of 33 patients with histopathologically verified pure DCIS (7 G1, 13 G2, and 9 G3 subtypes), giving an overall sensitivity of 87.9% for this patient cohort. Four DCIS lesions (two G1 and two G2) up to 5 mm diameter or smaller were not detected by MRM. In mammography, 21 of the 33 patients revealed suspicious outcome (including all lesions not detected by MRM), demonstrating an overall sensitivity of 63.6%. The remaining 12 mammographically occult DCIS lesions (three G1 subtypes, four G2 subtypes, five G3 subtypes) were all identified in MRM. Conclusion Magnetic resonance mammography can diagnose mammographically visible and also occult DCIS lesions without microcalcifications. Only small DCIS foci with microcalcifications could additionally be verified by mammography supposing MRM as a diagnostic approach.

Quantitative 2- and 3-dimensional analysis of pharmacokinetic model-derived variables for breast lesions in dynamic, contrast-enhanced MR mammography

Purpose: Two- (2D) and three-dimensional (3D) evaluation of quantitative pharmacokinetic parameters derived from the Tofts model modeling dynamic contrast enhancement of lesions in MR mammography.

Klinische Wertigkeit computergestützter Analysen in der MR-Mammografie. Ein Vergleich zwischen zwei Systemen und drei Untersuchern mit unterschiedlicher Erfahrung

The value of computer-assisted detection (CAD) used in magnetic resonance (MR) mammography in a clinical setting is currently a subject of controversy. This study evaluated the extent to which color-coded CAD systems aid radiologists with different levels of experience in their reading of MR mammographies. In this prospective study, 48 patients with a total of 88 lesions (43 malignant, 45 benign) were included. All examinations were performed on a 1.5 Tesla MR scanner with intravenous application of 0.1 mmol gadopentetate dimeglumine/kg body weight. Three readers independently analyzed the images without knowledge of the clinical data; radiologists 1 and 2 were much more experienced in the interpretation of MR mammographies than radiologist 3. Initially, the observers visually categorized the lesions as benign or malignant following classification of BI-RADS (Breast Imaging Reporting and Data System). The readers also scored their own confidence level using a dichotome score (1: unsure vs. 2: sure) according to the BI-RADS classification. The images were then analyzed in a blinded manner with two technically different CAD systems: the full-time point (FTP) method (Cadsciences; White Plains, NY, USA) and the Dynacad version 1.1 (Invivo; Pewaukee, WI, USA). After CAD, all three readers classified more malignant lesions as BI-RADS 4 or 5 (suspicious or highly suggestive of malignancy). However, this increase in sensitivity revealed only statistical significance for observer 3 (p < 0.05). After CAD, the two experienced readers categorized about the same quantity of benign lesions correctly as BI-RADS 2. Observer 3 classified less benign lesions as BI-RADS 2 after both CAD analyses; i. e. the specificity decreased. The subjective confidence of all observers increased after analysis with Dynacad. Observer 3 also reported to be more confident after the FTP method. Computer-assisted detection can be a useful additional diagnostic tool for the radiologist in the interpretation of MR mammographies, but does not have the potential to replace the professional experience of a radiologist.