Contrast-enhanced MR imaging of the breast at 3.0 and 1.5 T in the same patients: initial experience

Diagnostic performance of diffusion-weighted imaging and intravoxel incoherent motion for renal lesions: a meta-analysis

AIM

To compare the diagnostic performance of diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) parameters, specifically true diffusion coefficient (D), pseudo diffusion coefficient (D∗), and perfusion fraction (f) for quantitatively differentiating benign and malignant renal lesions.

MATERIALS AND METHODS

A comprehensive search was conducted in the EMBASE and PubMed databases before September 2022 to identify studies in English investigating the diagnostic accuracy of DWI and IVIM in renal lesions. The quality of the included studies was assessed using the QUADAS-2 tool. Pooled sensitivity, specificity, and area under the curve (AUC) values were estimated for each parameter.

RESULTS

A total of 19 studies involving 1,860 renal lesions (1,160 malignant and 700 benign), met the inclusion criteria. Among these studies, 15 assessed the apparent diffusion coefficient (ADC), four assessed IVIM, and three evaluated both ADC and IVIM. The pooled sensitivity, specificity, and AUC for ADC were 0.84 (95% confidence interval [Cl], 0.79-0.88), 0.82 (95% Cl, 0.72-0.89), and 0.89 (95% Cl, 0.86-0.92), respectively. The IVIM parameter with the highest diagnostic accuracy was D, with a pooled sensitivity, specificity, and AUC of 0.89 (95% Cl, 0.74-0.96), 0.96 (95% Cl, 0.85-0.99), and 0.98 (95% Cl, 0.96-0.99), respectively. The pooled sensitivity, specificity and AUC for f were 0.67 (95% Cl, 0.55-0.77), 0.81 (95% Cl, 0.30-0.98), and 0.73 (95% Cl, 0.69-0.77), respectively. The pooled sensitivity, specificity, and AUC for D∗ were 0.87 (95% Cl, 0.81-0.91), 0.59 (95% Cl, 0.48-0.70), and 0.82 (95% Cl, 0.78-0.85), respectively.

CONCLUSION

This meta-analysis indicated that both IVIM and DWI had moderate to high diagnostic accuracy for differentiating benign and malignant renal lesions. Among the IVIM parameter, D exhibited the highest diagnostic accuracy, demonstrating higher sensitivity and specificity than ADC, D∗, and f.

Assessment of Enhancement Kinetics Improves the Specificity of Abbreviated Breast MRI: Performance in an Enriched Cohort

Objective: To investigate the added value of kinetic information for breast lesion evaluation on abbreviated breast MRI (AB-MRI). Methods: This retrospective study analyzed 207 breast lesions with Breast Imaging Reporting and Data System categories 3, 4, or 5 on AB-MRI in 198 consecutive patients who had breast MRI for screening after breast cancer surgery between January 2017 and December 2019. All lesions were pathologically confirmed or stable on follow-up images for 2 years or more. Kinetic information of the lesions regarding the degree and rate of enhancement on the first post-contrast-enhanced image and the enhancement curve type from two post-contrast-enhanced images were analyzed on a commercially available computer-assisted diagnosis system. The diagnostic performances of AB-MRI with morphological analysis alone and with the addition of kinetic information were compared using the McNemar test. Results: Of 207 lesions, 59 (28.5%) were malignant and 148 (71.5%) were benign. The addition of an enhancement degree of ≥90% to the morphological analysis significantly increased the specificity of AB-MRI (29.7% vs. 52.7%, p < 0.001) without significantly reducing the sensitivity (94.9% vs. 89.8%, p = 0.083) compared to morphological analysis alone. Unnecessary biopsy could have been avoided in 34 benign lesions, although three malignant lesions could have been missed. For detecting invasive cancer, adding an enhancement degree ≥107% to the morphological analysis significantly increased the specificity (26.5% vs. 57.6%, p < 0.001) without significantly decreasing the sensitivity (94.6% vs. 86.5%, p = 0.083). Conclusion: Adding the degree of enhancement on the first post-contrast-enhanced image to the morphological analysis resulted in higher AB-MRI specificity without compromising its sensitivity.

Diffusion tensor imaging on 3-T MRI breast: diagnostic performance in comparison to diffusion-weighted imaging

Background

Breast cancer is the most prevalent cancer among females. Dynamic contrast-enhanced MRI (DCE-MRI) breast is highly sensitive (90%) in the detection of breast cancer. Despite its high sensitivity in detecting breast cancer, its specificity (72%) is moderate. Owing to 3-T breast MRI which has the advantage of a higher signal to noise ratio and shorter scanning time rather than the 1.5-T MRI, the adding of new techniques as diffusion tensor imaging (DTI) to breast MRI became more feasible.

Diffusion-weighted imaging (DWI) which tracks the diffusion of the tissue water molecule as well as providing data about the integrity of the cell membrane has been used as a valuable additional tool of DCE-MRI to increase its specificity.

Based on DWI, more details about the microstructure could be detected using diffusion tensor imaging. The DTI applies diffusion in many directions so apparent diffusion coefficient (ADC) will vary according to the measured direction raising its sensitivity to microstructure elements and cellular density. This study aimed to investigate the diagnostic accuracy of DTI in the assessment of breast lesions in comparison to DWI.

Results

By analyzing the data of the 50 cases (31 malignant cases and 19 benign cases), the sensitivity and specificity of DWI in differentiation between benign and malignant lesions were about 90% and 63% respectively with PPV 90% and NPV 62%, while the DTI showed lower sensitivity and specificity about 81% and 51.7%, respectively, with PPV 78.9% and NPV 54.8% (P-value ≤ 0.05).

Conclusion

While the DWI is still the most established diffusion parameter, DTI may be helpful in the further characterization of tumor microstructure and differentiation between benign and malignant breast lesions.

Radiomics-based machine learning analysis and characterization of breast lesions with multiparametric diffusion-weighted MR

Background

This study aimed to evaluate the utility of radiomics-based machine learning analysis with multiparametric DWI and to compare the diagnostic performance of radiomics features and mean diffusion metrics in the characterization of breast lesions.

Methods

This retrospective study included 542 lesions from February 2018 to November 2018. One hundred radiomics features were computed from mono-exponential (ME), biexponential (BE), stretched exponential (SE), and diffusion-kurtosis imaging (DKI). Radiomics-based analysis was performed by comparing four classifiers, including random forest (RF), principal component analysis (PCA), L1 regularization (L1R), and support vector machine (SVM). These four classifiers were trained on a training set with 271 patients via ten-fold cross-validation and tested on an independent testing set with 271 patients. The diagnostic performance of the mean diffusion metrics of ME (mADC_{all b}, mADC_0–1000), BE (mD, mD^*, mf), SE (mDDC, mα), and DKI (mK, mD) were also calculated for comparison. The area under the receiver operating characteristic curve (AUC) was used to compare the diagnostic performance.

Results

RF attained higher AUCs than L1R, PCA and SVM. The AUCs of radiomics features for the differential diagnosis of breast lesions ranged from 0.80 (BE_D*) to 0.85 (BE_D). The AUCs of the mean diffusion metrics ranged from 0.54 (BE_mf) to 0.79 (ME_mADC_0–1000). There were significant differences in the AUCs between the mean values of all diffusion metrics and radiomics features of AUCs (all P < 0.001) for the differentiation of benign and malignant breast lesions. Of the radiomics features computed, the most important sequence was BE_D (AUC: 0.85), and the most important feature was FO-10 percentile (Feature Importance: 0.04).

Conclusions

The radiomics-based analysis of multiparametric DWI by RF enables better differentiation of benign and malignant breast lesions than the mean diffusion metrics.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03117-5.

Robustness of radiomic features of benign breast lesions and hormone receptor positive/HER2-negative cancers across DCE-MR magnet strengths

Radiomic features extracted from breast lesion images have shown potential in diagnosis and prognosis of breast cancer. As medical centers transition from 1.5 T to 3.0 T magnetic resonance (MR) imaging, it is beneficial to identify potentially robust radiomic features across field strengths because images acquired at different field strengths could be used in machine learning models. Dynamic contrast-enhanced MR images of benign breast lesions and hormone receptor positive/HER2-negative (HR+/HER2-) breast cancers were acquired retrospectively, yielding 612 unique cases: 150 and 99 benign lesions imaged at 1.5 T and 3.0 T, and 223 and 140 HR+/HER2- cancerous lesions imaged at 1.5 T and 3.0 T, respectively. In addition, an independent set of seven lesions imaged at both field strengths, three benign lesions and four HR+/HER2- cancers, was analyzed separately. Lesions were automatically segmented using a 4D fuzzy c-means method; thirty-eight radiomic features were extracted. Feature value distributions were compared by cancer status and imaging field strength using the Kolmogorov-Smirnov test. Features that did not demonstrate a statistically significant difference were considered to be potentially robust. The area under the receiver operating characteristic curve (AUC), for the task of classifying lesions as benign or HR+/HER2- cancer, was determined for each feature at each field strength. Three features were found to be both potentially robust across field strength and of high classification performance, i.e., AUCs statistically greater than 0.5 in the classification task: one shape feature (irregularity), one texture feature (sum average) and one enhancement variance kinetics features (enhancement variance increasing rate). In the demonstration set of lesions imaged at both field strengths, two of the three potentially robust features showed qualitative agreement across field strength. These findings may contribute to the development of computer-aided diagnosis models that are robust across field strength for this classification task.

Distinguishing between benign and malignant breast lesions using diffusion weighted imaging and intravoxel incoherent motion: A systematic review and meta-analysis

PURPOSE

We sought to evaluate the diagnostic performance of diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) for distinguishing between benign and malignant breast tumors by performing a meta-analysis.

METHODS

We comprehensively searched the electronic databases PubMed and Embase from January 2000 to April 2020 for studies in English. Studies were included if they reported the sensitivity and specificity for identifying benign and malignant breast lesions using DWI or IVIM. Studies were reviewed according to QUADAS-2. The data inhomogeneity and publication bias were also assessed. In order to explore the influence of different field strengths and different b values on diagnostic efficiency, we conducted subgroup analysis.

RESULTS

We analyzed 79 studies, which included a total of 6294 patients with 4091 malignant lesions and 2793 benign lesions. Overall, the pooled sensitivity and specificity of ADC for detecting malignant breast tumors were 0.87 (0.86-0.88) and 0.80 (0.78-0.81), respectively. The PLR was 5.09 (4.16-6.24); the NLR was 0.15 (0.13-0.18); and the DOR was 38.95 (28.87-52.54). The AUC value was 0.9297. The highest performing parameter for IVIM was tissue diffusivity (D), and the pooled sensitivity and specificity was 0.85 (0.82-0.88) and 0.87(0.83-0.90), respectively; the PLR was 5.65 (3.91-8.18); the NLR was 0.17 (0.12-0.26); and the DOR was 38.44 (23.57-62.69). The AUC value was 0.9265. Most of parameters demonstrated considerable statistically significant heterogeneity (P < 0.05, I²>50 %) except the pooled DOR, PLR of D and the pooled DOR and NLR of D*.

CONCLUSIONS

Our meta-analysis indicated that DWI and IVIM had high sensitivity and specificity in the differential diagnosis of breast lesions; and compared with DWI, IVIM could not further increase the diagnostic performance. There was no significant difference in diagnostic accuracy.

Preoperative breast magnetic resonance imaging in patients with ductal carcinoma in situ: a systematic review for the European Commission Initiative on Breast Cancer (ECIBC)

Objective

To evaluate the impact of preoperative MRI in the management of Ductal carcinoma in situ (DCIS).

Methods

We searched the PubMed, EMBASE and Cochrane Library databases to identify randomised clinical trials (RCTs) or cohort studies assessing the impact of preoperative breast MRI in surgical outcomes, treatment change or loco-regional recurrence. We provided pooled estimates for odds ratios (OR), relative risks (RR) and proportions and assessed the certainty of the evidence using the GRADE approach.

Results

We included 3 RCTs and 23 observational cohorts, corresponding to 20,415 patients. For initial breast-conserving surgery (BCS), the RCTs showed that MRI may result in little to no difference (RR 0.95, 95% CI 0.90 to 1.00) (low certainty); observational studies showed that MRI may have no difference in the odds of re-operation after BCS (OR 0.96; 95% CI 0.36 to 2.61) (low certainty); and uncertain evidence from RCTs suggests little to no difference with respect to total mastectomy rate (RR 0.91; 95% CI 0.65 to 1.27) (very low certainty). We also found that MRI may change the initial treatment plans in 17% (95% CI 12 to 24%) of cases, but with little to no effect on locoregional recurrence (aHR = 1.18; 95% CI 0.79 to 1.76) (very low certainty).

Conclusion

We found evidence of low to very low certainty which may suggest there is no improvement of surgical outcomes with pre-operative MRI assessment of women with DCIS lesions. There is a need for large rigorously conducted RCTs to evaluate the role of preoperative MRI in this population.

Key Points

• Evidence of low to very low certainty may suggest there is no improvement in surgical outcomes with pre-operative MRI.

• There is a need for large rigorously conducted RCTs evaluating the role of preoperative MRI to improve treatment planning for DCIS.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-021-07873-2.

Five-dimensional quantitative low-dose Multitasking dynamic contrast- enhanced MRI: Preliminary study on breast cancer

PURPOSE

To develop a low-dose Multitasking DCE technique (LD-MT-DCE) for breast imaging, enabling dynamic T₁ mapping-based quantitative characterization of tumor blood flow and vascular properties with whole-breast coverage, a spatial resolution of 0.9 × 0.9 × 1.1 mm³ , and a temporal resolution of 1.4 seconds using a 20% gadolinium dose (0.02 mmol/kg).

METHODS

Magnetic resonance Multitasking was used to reconstruct 5D images with three spatial dimensions, one T₁ recovery dimension for dynamic T₁ quantification, and one DCE dimension for contrast kinetics. Kinetic parameters F p , v p , K trans , and v e were estimated from dynamic T₁ maps using the two-compartment exchange model. The LD-MT-DCE repeatability and agreement against standard-dose MT-DCE were evaluated in 20 healthy subjects. In 7 patients with triple-negative breast cancer, LD-MT-DCE image quality and diagnostic results were compared with that of standard-dose clinical DCE in the same imaging session. One-way unbalanced analysis of variance with Tukey test was performed to evaluate the statistical significance of the kinetic parameters between control and patient groups.

RESULTS

The LD-MT-DCE technique was repeatable, agreed with standard-dose MT-DCE, and showed excellent image quality. The diagnosis using LD-MT-DCE matched well with clinical results. The values of F p , v p , and K trans were significantly different between malignant tumors and normal breast tissue (P < .001, < .001, and < .001, respectively), and between malignant and benign tumors (P = .020, .003, and < .001, respectively).

CONCLUSION

The LD-MT-DCE technique was repeatable and showed excellent image quality and equivalent diagnosis compared with standard-dose clinical DCE. The estimated kinetic parameters were capable of differentiating between normal breast tissue and benign and malignant tumors.

Accelerating acquisition of readout-segmented echo planar imaging with a simultaneous multi-slice (SMS) technique for diagnosing breast lesions

OBJECTIVES

To investigate the feasibility and effectiveness of SMS rs-EPI for evaluating breast lesions.

METHODS

This prospective study was approved by IRB. Ninety-six patients had 102 histopathologically verified lesions (80 malignant and 22 benign) that were evaluated. Conventional rs-EPI and SMS rs-EPI data were acquired on a 3T scanner. Mean kurtosis (MK), mean diffusion (MD), and apparent diffusion coefficient (ADC) values were quantitatively calculated for each lesion on both sequences. Images were qualitatively and quantitatively analyzed with respect to image sharpness, geometric distortion, lesion conspicuity, anatomic structure, overall image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Student's t test, Pearson correlation, receiver operating characteristic curve, Wilcoxon rank sum test, and paired-sample t tests were used for statistical analysis.

RESULTS

Compared to conventional rs-EPI, the acquisition time of SMS rs-EPI was markedly reduced (2:17 min vs 4:27 min). Pearson's correlations showed excellent linear relationships for each parameter between conventional rs-EPI and SMS rs-EPI (MK, r = 0.908; MD, r = 0.938; and ADC, r = 0.975; p < 0.01 for all). Furthermore, SMS rs-EPI had similar diagnostic performance compared with conventional rs-EPI. SMS rs-EPI had comparable visual image quality as conventional rs-EPI, with excellent inter-reader reliability (ICC = 0.851-0.940). No differences existed between conventional rs-EPI and SMS rs-EPI for either SNR or CNR (p > 0.05).

CONCLUSIONS

Applying the SMS technique can significantly reduce the acquisition time and produce similar diagnostic accuracy while generating comparable image quality as the conventional rs-EPI.

KEY POINTS

• SMS rs-EPI reduces scan time from 4:27 min to 2:17 min compared with conventional rs-EPI. • SMS rs-EPI has a comparable diagnostic performance to conventional rs-EPI in the differentiation between malignant and benign breast lesions. • SMS rs-EPI demonstrates comparable image quality to conventional rs-EPI with shorter scan time.

MR imaging-guided vacuum assisted breast biopsy: Radiological-pathological correlation and underestimation rate in pre-surgical assessment

BACKGROUND

Magnetic Resonance(MR) guided percutaneous procedures(MRgVABB) have been developed and largely employed to reduce the need of surgical biopsies for suspicious lesions which can be detected only by MR(MR-only lesion). The present study aims to investigate correlation between imaging, histological features of MRgVABB and surgical specimens of MR-only lesions.

METHODS

We retrospectively enrolled 56 patients with a total of 61 lesions. Each finding was defined as Mass-Enhancement(ME) or Non-ME(NME) and classified according to BI-RADS. MRgVABB and surgical data were collected. Concordance between MR, MRgVABB and open biopsy was calculated. Underestimation Rate(UR) of MRgVABB with surgery was obtained.

RESULTS

B2 and B5b lesions were statistically associated with NME and ME, respectively. No statistical association was found to B3 nor to B5a with radiological features. UR was 10 %; underestimated lesions were strongly associated with the presence of a ME on MR imaging. Moreover, B3 lesions are associated with higher UR.

CONCLUSION

Radiological features should influence patient management aiming to construct a correct diagnostic and therapeutic plan. When MR is prescribed for breast cancer staging for ME-MR-only lesions, we suggest surgical open biopsy instead of MRgVABB when upfront surgery is the treatment of choice.

The kinetic analysis of breast cancer: An investigation of the optimal temporal resolution for dynamic contrast-enhanced MR imaging

INTRODUCTION

There is wide agreement that morphologic features and enhancement kinetics should be evaluated for MRI of the breast, although there has been no clear consensus concerning optimal temporal resolutions. The objective of this study was to investigate the optimal temporal resolution for the kinetic analysis of breast cancers.

METHODS

Thirty-four patients with 34 enhancing lesions of breast cancer who underwent dynamic contrast-enhanced MRI (DCE-MRI) on a 3.0-T scanner were included in this retrospective study. DCE-MRI was performed with an original temporal resolution of 10-s, and the values of pharmacokinetic parameters (Ktrans, Ve, Kep, and area under the curve (AUC)) were compared with selected data of 30-s and 60-s time intervals.

RESULTS

Among the 34 lesions, 10 showed a wash out pattern, 16 showed a plateau pattern, and 8 showed a persistent enhancement pattern. The Ktrans value in the wash-out pattern was significantly higher than that of other time-intensity curve patterns (p < 0.01). The Kep and AUC also showed significant differences between the wash-out pattern and other types (p < 0.01). On comparing the perfusion parameters among different temporal resolutions, simulations showed that only the AUC differed significantly between the data acquired at a 10-s temporal resolution and that acquired at a 60-s time interval (p < 0.01). Although the comparison of the AUC between the 30-s and 60-s data also showed significant differences (p = 0.01), there was no significant difference between the 10-s and 30-s data (p = 0.17).

CONCLUSIONS

DCE-MRI with a temporal resolution of 30-s preserves the kinetic information. Further prospective studies will be needed to investigate the trade-off between temporal and spatial resolution in DCE-MRI.

Association between MRI background parenchymal enhancement and lymphovascular invasion and estrogen receptor status in invasive breast cancer

Objectives:

In magnetic resonance imaging (MRI), background parenchymal enhancement (BPE) is associated with breast cancer risk, but the associations between BPE and clinical characteristics and histological features are unknown. This study aimed to investigate the association between BPE and clinical characteristics (including age, menopausal status, and tumor histological characteristics) in patients with invasive breast cancer.

Methods:

This was a retrospective study of 163 patients with invasive breast cancer (164 lesions, 1 patient had bilateral cancer) confirmed by surgery and pathological examination, treated between January 2014 and December 2016 at our university (Kunming Medical University). The patients were divided into two groups: extremely minimal and mild enhancement (low BPE group, n = 78) vs moderate and marked enhancement (high BPE group, n = 86).

Results:

Compared with the low BPE group, the high BPE group showed higher frequencies of patients < 50 years of age (88% vs 38%, p < 0.0001), premenopausal (87% vs 29%, p < 0.0001), T1 staging (35% vs 15%, p = 0.027), Grade II (57% vs 37%, p = 0.03), lymphovascular invasion (83% vs 13%, p < 0.0001), and positive estrogen receptor (ER) (79% vs 42%, p < 0.0001). The Spearman correlation coefficients (r) between BPE and age, menopausal status, lymphovascular invasion, and ER status were −0.521 (p < 0.0001), –0.588 (p < 0.0001), 0.697 (p < 0.0001), and 0.377 (p < 0.0001), respectively.

Conclusion:

BPE is negatively associated with age and menopausal status, and is positively associated with lymphovascular invasion and positive ER status.

Advances in knowledge:

BPE is not correlated with T staging and histological classification in patients with invasive breast cancer.

Abbreviated MRI Protocols in Breast Cancer Diagnostics

Oncologic imaging focused on the detection of breast cancer is of increasing importance, with over 1.7 million new cases detected each year worldwide. MRI of the breast has been described to be one of the most sensitive imaging modalities in breast cancer detection; however, clinical use is limited due to high costs. In the past, the objective and clinical routine of oncologic imaging was to provide one extended imaging protocol covering all potential needs and clinical implications regardless of the specific clinical indication or question. Future protocols might be more focused according to a "keep it short and simple" approach, with a reduction of patient magnet time and a limited number of images to review. Rather than replacing conventional full-diagnostic breast MRI protocols, these approaches aim at introducing a new thinking in oncologic imaging using a diversification of available imaging approaches targeted to the dedicated clinical needs of the individual patient. Here we review current approaches on using abbreviated protocols that aim to increase the clinical availability and use of breast MRI for improved early detection of breast cancer. Level of Evidence: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:647-658.

Clinical role of breast MRI now and going forward

Magnetic resonance imaging (MRI) is a well-established method in breast imaging, with manifold clinical applications, including the non-invasive differentiation between benign and malignant breast lesions, preoperative staging, detection of scar versus recurrence, implant assessment, and the evaluation of high-risk patients. At present, dynamic contrast-enhanced MRI is the most sensitive imaging technique for breast cancer diagnosis, and provides excellent morphological and to some extent also functional information. To compensate for the limited functional information, and to increase the specificity of MRI while preserving its sensitivity, additional functional parameters such as diffusion-weighted imaging and apparent diffusion coefficient mapping, and MR spectroscopic imaging have been investigated and implemented into the clinical routine. Several additional MRI parameters to capture breast cancer biology are still under investigation. MRI at high and ultra-high field strength and advances in hard- and software may also further improve this imaging technique. This article will review the current clinical role of breast MRI, including multiparametric MRI and abbreviated protocols, and provide an outlook on the future of this technique. In addition, the predictive and prognostic value of MRI as well as the evolving field of radiogenomics will be discussed.

Freehand 3T MR-guided vacuum-assisted breast biopsy (VAB): a five-year experience

Background Magnetic resonance (MR) permits the detection of some malignant lesions that cannot be identified with mammography or ultrasonography. The characterization of these MR-only detectable lesions often requires a biopsy. Purpose To evaluate the technique, the feasibility and the accuracy of freehand 3T MR-guided VAB for the characterization of suspicious, MR-only detectable lesions and to compare VAB results with surgical pathology and follow-up imaging results. Material and Methods During 2010-2015, 118 women who were referred for MR-guided VAB were retrospectively reviewed. All BI-RADS MR 4 and 5 lesions and some BI-RADS MR 3 lesions (according to clinical context and patient anxiety) were scheduled to undergo biopsy. Results A total of 123 suspicious lesions were retrospectively selected. Technical failures occurred in only two cases (1.6%) due to the location of the lesions. Histopathological results revealed 59 benign lesions (48%), 27 high-risk lesions (22%), and 35 malignant lesions (28.4%). Surgical pathology results led to the reclassification of eight B3 lesions: one proved to be a ductal carcinoma in situ, while seven presented with invasive features. B3 underestimation also occurred in 29% of the cases. MR follow-up was achieved for all the benign lesions and no false-negative cases were observed. No complications, 3T-related artefacts, or difficulties were observed. Conclusion Freehand 3T MR-guided VAB was found to be a valid, safe, fast, and inexpensive alternative to surgical histology.

Preoperative dynamic breast magnetic resonance imaging kinetic features using computer-aided diagnosis: Association with survival outcome and tumor aggressiveness in patients with invasive breast cancer

Objectives

To evaluate whether preoperative breast dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging kinetic features, assessed using computer-aided diagnosis (CAD), can predict survival outcome and tumor aggressiveness in patients with invasive breast cancer.

Materials and methods

Between March and December 2011, 301 women who underwent preoperative DCE MR imaging for invasive breast cancer, with CAD data, were identified. All MR images were retrospectively evaluated using a commercially available CAD system. The following kinetic parameters were prospectively recorded for each lesion: initial peak enhancement, the proportion of early phase medium and rapid enhancement, and the proportion of delayed phase persistent, plateau, and washout enhancement. The Cox proportional hazards model was used to determine the association between the kinetic features assessed by CAD and disease-free survival (DFS). The peak signal intensity and kinetic enhancement profiles were compared with the clinical-pathological variables.

Results

There were 32 recurrences during a mean follow-up time of 55.2 months (range, 5–72 months). Multivariate analysis revealed that a higher peak enhancement (DFS hazard ratio, 1.004 [95% confidence interval (CI): 1.001, 1.006]; P = .013) on DCE MR imaging and a triple-negative subtype (DFS hazard ratio, 21.060 [95% CI: 2.675, 165.780]; P = .004) were associated with a poorer DFS. Higher peak enhancement was significantly associated with a higher tumor stage, clinical stage, and histologic grade.

Conclusions

Patients with breast cancer who showed higher CAD-derived peak enhancement on breast MR imaging had worse DFS. Peak enhancement and volumetric analysis of kinetic patterns were useful for predicting tumor aggressiveness.

Effects of MRI scanner parameters on breast cancer radiomics

PURPOSE

To assess the impact of varying magnetic resonance imaging (MRI) scanner parameters on the extraction of algorithmic features in breast MRI radiomics studies.

METHODS

In this retrospective study, breast imaging data for 272 patients were analyzed with magnetic resonance (MR) images. From the MR images, we assembled and implemented 529 algorithmic features of breast tumors and fibrograndular tissue (FGT). We divided the features into 10 groups based on the type of data used for the feature extraction and the nature of the extracted information. Three scanner parameters were considered: scanner manufacturer, scanner magnetic field strength, and slice thickness. We assessed the impact of each of the scanner parameters on each of the feature by testing whether the feature values are systematically diverse for different values of these scanner parameters. A two-sample t-test has been used to establish whether the impact of a scanner parameter on values of a feature is significant and receiver operating characteristics have been used for to establish the extent of that effect.

RESULTS

On average, higher proportion (69% FGT versus 20% tumor) of FGT related features were affected by the three scanner parameters. Of all feature groups and scanner parameters, the feature group related to the variation in FGT enhancement was found to be the most sensitive to the scanner manufacturer (AUC = 0.81 ± 0.14).

CONCLUSIONS

Features involving calculations from FGT are particularly sensitive to the scanner parameters.

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.

Bloch-Siegert B1-Mapping Improves Accuracy and Precision of Longitudinal Relaxation Measurements in the Breast at 3 T

Variable flip angle (VFA) sequences are a popular method of calculating T₁ values, which are required in a quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI). B₁ inhomogeneities are substantial in the breast at 3 T, and these errors negatively impact the accuracy of the VFA approach, thus leading to large errors in the DCE-MRI parameters that could limit clinical adoption of the technique. This study evaluated the ability of Bloch–Siegert B₁ mapping to improve the accuracy and precision of VFA-derived T₁ measurements in the breast. Test–retest MRI sessions were performed on 16 women with no history of breast disease. T₁ was calculated using the VFA sequence, and B₁ field variations were measured using the Bloch–Siegert methodology. As a gold standard, inversion recovery (IR) measurements of T₁ were performed. Fibroglandular tissue and adipose tissue from each breast were segmented using the IR images, and the mean T₁ was calculated for each tissue. Accuracy was evaluated by percent error (%err). Reproducibility was assessed via the 95% confidence interval (CI) of the mean difference and repeatability coefficient (r). After B₁ correction, %err significantly (P < .001) decreased from 17% to 8.6%, and the 95% CI and r decreased from ±94 to ±38 milliseconds and from 276 to 111 milliseconds, respectively. Similar accuracy and reproducibility results were observed in the adipose tissue of the right breast and in both tissues of the left breast. Our data show that Bloch–Siegert B₁ mapping improves accuracy and precision of VFA-derived T₁ measurements in the breast.

The potential of multiparametric MRI of the breast

MRI is an essential tool in breast imaging, with multiple established indications. Dynamic contrast-enhanced MRI (DCE-MRI) is the backbone of any breast MRI protocol and has an excellent sensitivity and good specificity for breast cancer diagnosis. DCE-MRI provides high-resolution morphological information, as well as some functional information about neoangiogenesis as a tumour-specific feature. To overcome limitations in specificity, several other functional MRI parameters have been investigated and the application of these combined parameters is defined as multiparametric MRI (mpMRI) of the breast. MpMRI of the breast can be performed at different field strengths (1.5-7 T) and includes both established (diffusion-weighted imaging, MR spectroscopic imaging) and novel MRI parameters (sodium imaging, chemical exchange saturation transfer imaging, blood oxygen level-dependent MRI), as well as hybrid imaging with positron emission tomography (PET)/MRI and different radiotracers. Available data suggest that multiparametric imaging using different functional MRI and PET parameters can provide detailed information about the underlying oncogenic processes of cancer development and progression and can provide additional specificity. This article will review the current and emerging functional parameters for mpMRI of the breast for improved diagnostic accuracy in breast cancer.

Computer-based automated estimation of breast vascularity and correlation with breast cancer in DCE-MRI images

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) with gadolinium constitutes one of the most promising protocols for boosting up the sensitivity in breast cancer detection. The aim of this study was twofold: first to design an image processing methodology to estimate the vascularity of the breast region in DCE-MRI images and second to investigate whether the differences in the composition/texture and vascularity of normal, benign and malignant breasts may serve as potential indicators regarding the presence of the disease. Clinical material comprised thirty nine cases examined on a 3.0-T MRI system (SIGNA HDx; GE Healthcare). Vessel segmentation was performed using a custom made modification of the Seeded Region Growing algorithm that was designed in order to identify pixels belonging to the breast vascular network. Two families of features were extracted: first, morphological and textural features from segmented images in order to quantify the extent and the properties of the vascular network; second, textural features from the whole breast region in order to investigate whether the nature of the disease causes statistically important changes in the texture of affected breasts. Results have indicated that: (a) the texture of vessels presents statistically significant differences (p<0.001) between normal, benign and malignant cases, (b) the texture of the whole breast region for malignant and non-malignant breasts, produced statistically significant differences (p<0.001), (c) the relative ratios of the texture between the two breasts may be used for the discrimination of non-malignant from malignant patients, and (d) an area under the receiver operating characteristic curve of 0.908 (AUC) was found when features were combined in a logistic regression prediction rule according to ROC analysis.

Accuracy of combined dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted imaging for breast cancer detection: a meta-analysis

BACKGROUND

Magnetic resonance imaging (MRI) is increasingly being used to examine patients with suspected breast cancer.

PURPOSE

To determine the diagnostic performance of combined dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) for breast cancer detection.

MATERIAL AND METHODS

A comprehensive search of the PUBMED, EMBASE, Web of Science, and Cochrane Library databases was performed up to September 2014. Statistical analysis included pooling of sensitivity and specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and diagnostic accuracy using the summary receiver operating characteristic (SROC). All analyses were conducted using STATA (version 12.0), RevMan (version 5.2), and Meta-Disc 1.4 software programs.

RESULTS

Fourteen studies were analyzed, which included a total of 1140 patients with 1276 breast lesions. The pooled sensitivity and specificity of combined DCE-MRI and DWI were 91.6% and 85.5%, respectively. The pooled sensitivity and specificity of DWI-MRI were 86.0% and 75.6%, respectively. The pooled sensitivity and specificity of DCE-MRI were 93.2% and 71.1%. The area under the SROC curve (AUC-SROC) of combined DCE-MRI and DWI was 0.94, the DCE-MRI of 0.85. Deeks testing confirmed no significant publication bias in all studies.

CONCLUSION

Combined DCE-MRI and DWI had superior diagnostic accuracy than either DCE-MRI or DWI alone for the diagnosis of breast cancer.

Apparent diffusion coefficient in differentiation between malignant and benign breast masses: does size matter?

AIM

To determine whether lesion size affects the diagnostic performance of apparent diffusion coefficient (ADC) in the evaluation of breast masses.

MATERIALS AND METHODS

Consecutive breast lesions detected at magnetic resonance imaging (MRI) from June 2010 to July 2013 were retrospectively reviewed. Differences in the ADCs of benign and malignant mass lesions were compared. Receiver operating characteristics analysis was performed to evaluate diagnostic performance of ADC regarding lesion size (≤ 1 cm or >1 cm) and their T2W signal intensities.

RESULTS

Seventy-four malignant lesions (77.9%) and 21 (22.1%) benign lesions were included. Twenty-two of the 95 (23.2%) masses measured ≤ 1 cm (mean 0.73 ± 0.4; range 0.51-0.8 cm) and 73/95 (76.9%) masses measured >1 cm (mean 2.11 ± 0.1; range 1.1-3.3 cm). The mean ADC was significantly lower for malignant than for benign lesions (mean for malignant lesion, 0.89 ± 0.29 × 10(-3) mm(2)/s; mean for benign lesions, 1.27 ± 0.42 × 10(-3) mm(2)/s; p<0.01). The optimal ADC cut-off for differentiating benign and malignant lesion was 1.088 × 10(-3) mm(2)/s with a sensitivity of 85.9% and specificity of 77% for lesions >1 cm. The sensitivity and specificity were lowered to 60% and 50%, respectively, for lesions of size ≤ 1. Maximal sensitivity and specificity were reached when the ADC value was used to evaluate T2-dark lesions.

CONCLUSION

Diffusion-weighted MRI is useful for characterizing masses that are hypointense on T2-weighted images. Lower sensitivity and specificity were found for breast lesions ≤ 1 cm.

Diffusion-Weighted Imaging in 3.0 Tesla Breast MRI: Diagnostic Performance and Tumor Characterization Using Small Subregions vs. Whole Tumor Regions of Interest

Introduction

Apparent diffusion coefficient (ADC) values are increasingly reported in breast MRI. As there is no standardized method for ADC measurements, we evaluated the effect of the size of region of interest (ROI) to diagnostic utility and correlation to prognostic markers of breast cancer.

Methods

This prospective study was approved by the Institutional Ethics Board; the need for written informed consent for the retrospective analyses of the breast MRIs was waived by the Chair of the Hospital District. We compared diagnostic accuracy of ADC measurements from whole-lesion ROIs (WL-ROIs) to small subregions (S-ROIs) showing the most restricted diffusion and evaluated correlations with prognostic factors in 112 consecutive patients (mean age 56.2±11.6 years, 137 lesions) who underwent 3.0-T breast MRI.

Results

Intra- and interobserver reproducibility were substantial (κ = 0.616–0.784; Intra-Class Correlation 0.589–0.831). In receiver operating characteristics analysis, differentiation between malignant and benign lesions was excellent (area under curve 0.957–0.962, cut-off ADC values for WL-ROIs: 0.87×10⁻³ mm²s^-1; S-ROIs: 0.69×10⁻³ mm²s^-1, P<0.001). WL-ROIs/S-ROIs achieved sensitivities of 95.7%/91.3%, specificities of 89.5%/94.7%, and overall accuracies of 89.8%/94.2%. In S-ROIs, lower ADC values correlated with presence of axillary metastases (P = 0.03), high histological grade (P = 0.006), and worsened Nottingham Prognostic Index Score (P<0.05). In both ROIs, ADC values correlated with progesterone receptors and advanced stage (P<0.01), but not with HER2, estrogen receptors, or Ki-67.

Conclusions

ADC values assist in breast tumor characterization. Small ROIs were more accurate than whole-lesion ROIs and more frequently associated with prognostic factors. Cut-off values differed significantly depending on measurement procedure, which should be recognized when comparing results from the literature. Instead of using a whole lesion covering ROI, a small ROI could be advocated in diffusion-weighted imaging.

Evaluation with 3.0-T MR imaging: predicting the pathological response of triple-negative breast cancer treated with anthracycline and taxane neoadjuvant chemotherapy

BACKGROUND

Triple-negative breast cancer (TNBC) which expresses neither hormonal receptors nor HER-2 is associated with poor prognosis and shorter survival. Several studies have suggested that TNBC patients attaining pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) show a longer survival than those without pCR.

PURPOSE

To assess the accuracy of 3.0-T breast magnetic resonance imaging (MRI) in predicting pCR and to evaluate the clinicoradiologic factors affecting the diagnostic accuracy of 3.0-T breast MRI in TNBC patients treated with anthracycline and taxane (ACD).

MATERIAL AND METHODS

This retrospective study was approved by the institutional review board; patient consent was not required. Between 2009 and 2012, 35 TNBC patients with 3.0-T breast MRI prior to (n = 26) or after (n = 35) NAC were included. MRI findings were reviewed according to pCR to chemotherapy. The diagnostic accuracy of 3.0-T breast MRI for predicting pCR and the clinicoradiological factors affecting MRI accuracy and response to NAC were analyzed.

RESULTS

3.0-T MRI following NAC with ACD accurately predicted pCR in 91.4% of TNBC patients. The residual tumor size between pathology and 3.0-T MRI in non-pCR cases showed a higher correlation in the Ki-67-positive TNBC group (r = 0.947) than in the Ki-67 negative group (r = 0.375) with statistical trends (P = 0.069). Pre-treatment MRI in the non-pCR group compared to the pCR group showed a larger tumor size (P = 0.030) and non-mass presentation (P = 0.015).

CONCLUSION

3.0-T MRI in TNBC patients following NAC with ACD showed a high accuracy for predicting pCR to NAC. Ki-67 can affect the diagnostic accuracy of 3.0-T MRI for pCR to NAC with ACD in TNBC patients.

Breast magnetic resonance imaging performance: safety, techniques, and updates on diffusion-weighted imaging and magnetic resonance spectroscopy

Dynamic contrast-enhanced breast magnetic resonance imaging (MRI) is a well-established, highly sensitive technique for the detection and evaluation of breast cancer. Optimal performance of breast MRI continues to evolve. This article addresses breast MRI applications, covers emerging breast MRI safety concerns; outlines the technical aspects of breast MRI, including equipment and protocols at 3 T and 1.5 T; and describes current promising areas of research including diffusion-weighted imaging and magnetic resonance spectroscopy.

Diagnostic accuracy of (18)F-FDG PET/CT compared with that of contrast-enhanced MRI of the breast at 3 T

PURPOSE

To compare the diagnostic accuracy of prone (18)F-FDG PET/CT with that of contrast-enhanced MRI (CE-MRI) at 3 T in suspicious breast lesions. To evaluate the influence of tumour size on diagnostic accuracy and the use of maximum standardized uptake value (SUVMAX) thresholds to differentiate malignant from benign breast lesions.

METHODS

A total of 172 consecutive patients with an imaging abnormality were included in this IRB-approved prospective study. All patients underwent (18)F-FDG PET/CT and CE-MRI of the breast at 3 T in the prone position. Two reader teams independently evaluated the likelihood of malignancy as determined by (18)F-FDG PET/CT and CE-MRI independently. (18)F-FDG PET/CT data were qualitatively evaluated by visual interpretation. Quantitative assessment was performed by calculation of SUVMAX. Sensitivity, specificity, diagnostic accuracy, area under the curve and interreader agreement were calculated for all lesions and for lesions <10 mm. Histopathology was used as the standard of reference.

RESULTS

There were 132 malignant and 40 benign lesions; 23 lesions (13.4%) were <10 mm. Both (18)F-FDG PET/CT and CE-MRI achieved an overall diagnostic accuracy of 93%. There were no significant differences in sensitivity (p = 0.125), specificity (p = 0.344) or diagnostic accuracy (p = 1). For lesions <10 mm, diagnostic accuracy deteriorated to 91% with both (18)F-FDG PET/CT and CE-MRI. Although no significant difference was found for lesions <10 mm, CE-MRI at 3 T seemed to be more sensitive but less specific than (18)F-FDG PET/CT. Interreader agreement was excellent (κ = 0.85 and κ = 0.92). SUVMAX threshold was not helpful in differentiating benign from malignant lesions.

CONCLUSION

(18)F-FDG PET/CT and CE-MRI at 3 T showed equal diagnostic accuracies in breast cancer diagnosis. For lesions <10 mm, diagnostic accuracy deteriorated, but was equal for (18)F-FDG PET/CT and CE-MRI at 3 T. For lesions <10 mm, CE-MRI at 3 T seemed to be more sensitive but less specific than (18)F-FDG PET/CT. Quantitative assessment using an SUVMAX threshold for differentiating benign from malignant lesions was not helpful in breast cancer diagnosis.

MR-Guided Near-Infrared Spectral Tomography Increases Diagnostic Performance of Breast MRI

PURPOSE

The purpose of this study was to determine the diagnostically most important molecular biomarkers quantified by magnetic resonance-guided (MR) near-infrared spectral tomography (NIRST) that distinguish malignant breast lesions from benign abnormalities when combined with outcomes from clinical breast MRI.

EXPERIMENTAL DESIGN

The study was HIPAA compliant and approved by the Dartmouth Institutional Review Board, the NIH, the United States State Department, and Xijing Hospital. MR-guided NIRST evaluated hemoglobin, water, and lipid content in regions of interest defined by concurrent dynamic contrast-enhanced MRI (DCE-MRI) in the breast. MRI plus NIRST was performed in 44 subjects (median age, 46, age range, 20-81 years), 28 of whom had subsequent malignant pathologic diagnoses, and 16 had benign conditions. A subset of 30 subject examinations yielded optical data that met minimum sensitivity requirements to the suspicious lesion and were included in the analyses of diagnostic performance.

RESULTS

In the subset of 30 subject examinations meeting minimum optical data sensitivity criterion, the MR-guided NIRST separated malignant from benign lesions using total hemoglobin (HbT; P < 0.01) and tissue optical index (TOI; P < 0.001). Combined MRI plus TOI data caused one false positive and 1 false negative, and produced the best diagnostic performance, yielding an AUC of 0.95, sensitivity of 95%, specificity of 89%, positive predictive value of 95%, and negative predictive value of 89%, respectively.

CONCLUSIONS

MRI plus NIRST results correlated well with histopathologic diagnoses and could provide additional information to reduce the number of MRI-directed biopsies.

Preoperative axillary staging with 3.0-T breast MRI: clinical value of diffusion imaging and apparent diffusion coefficient

The axillary staging in newly diagnosed breast cancer is under major evolution. The aims of this study were to define the diagnostic performance of 3.0-T diffusion-weighted imaging (DWI) in the detection of axillary metastases in newly diagnosed breast cancer, to assess apparent diffusion coefficients (ADCs) for histopathologically confirmed metastatic lymph nodes in a clinical setting. Altogether 52 consecutive breast cancer patients underwent magnetic resonance imaging and DWI in addition to axillary ultrasound. ADCs of axillary lymph nodes were analysed by two breast radiologists and ultrasound-guided core biopsies were taken. In a separate reading by one radiologist two types of region of interests were used for a smaller group of patients. Altogether 56 axillae (121 lymph nodes) were included in the statistical analysis. Metastatic axillae (51.8%) had significantly lower ADCs (p<0.001). Mean ADCs were 0.663–0.676 x 10^-3 mm²/s for the histologically confirmed metastatic LNs and 1.100–1.225 x 10^-3 mm²/s for the benign. The sensitivity, specificity, and accuracy of DWI were 72.4%, 79.6%, and 75.9%, respectively with threshold ADC 0.812 x 10^-3 mm²/s. Region of interest with information on the minimum value increased the diagnostic performance (area under the curve 0.794 vs. 0.619). Even though ADCs are significantly associated with histopathologically confirmed axillary metastases the diagnostic performance of axillary DWI remains moderate and ultrasound-guided core biopsies or sentinel lymph node biopsies cannot be omitted.

Comparison of dynamic contrast-enhanced MRI parameters of breast lesions at 1.5 and 3.0 T: a pilot study

OBJECTIVE

To compare dynamic contrast-enhanced (DCE) MRI parameters from scans of breast lesions at 1.5 and 3.0 T.

METHODS

11 patients underwent paired MRI examinations in both Philips 1.5 and 3.0 T systems (Best, Netherlands) using a standard clinical fat-suppressed, T1 weighted DCE-MRI protocol, with 70-76 s temporal resolution. Signal intensity vs time curves were fit with an empirical mathematical model to obtain semi-quantitative measures of uptake and washout rates as well as time-to-peak enhancement (TTP). Maximum percent enhancement and signal enhancement ratio (SER) were also measured for each lesion. Percent differences between parameters measured at the two field strengths were compared.

RESULTS

TTP and SER parameters measured at 1.5 and 3.0 T were similar; with mean absolute differences of 19% and 22%, respectively. Maximum percent signal enhancement was significantly higher at 3 T than at 1.5 T (p = 0.006). Qualitative assessment showed that image quality was significantly higher at 3 T (p = 0.005).

CONCLUSION

Our results suggest that TTP and SER are more robust to field strength change than other measured kinetic parameters, and therefore measurements of these parameters can be more easily standardized than measurements of other parameters derived from DCE-MRI. Semi-quantitative measures of overall kinetic curve shape showed higher reproducibility than do discrete classification of kinetic curve early and delayed phases in a majority of the cases studied.

ADVANCES IN KNOWLEDGE

Qualitative measures of curve shape are not consistent across field strength even when acquisition parameters are standardized. Quantitative measures of overall kinetic curve shape, by contrast, have higher reproducibility.

Accuracy of 3 T versus 1.5 T breast MRI for pre-operative assessment of extent of disease in newly diagnosed DCIS

OBJECTIVES

While 3T breast magnetic resonance imaging has increased in use over the past decade, there is little data comparing its use for assessing ductal carcinoma in situ (DCIS) versus 1.5 T. We sought to compare the accuracies of DCIS extent of disease measures on pre-operative 3T versus 1.5 T MRI.

METHODS

This institutional review board-approved prospective study included 20 patients with ductal carcinoma in situ diagnosed by core needle biopsy (CNB) who underwent pre-operative breast MRI at both 3T (resolution=0.5 mm×0.5 mm×1.3 mm) and 1.5 T (0.85 mm×0.85 mm×1.6 mm). All patients provided informed consent, and the study was HIPPA compliant. Lesion sizes and imaging characteristics (morphologic and kinetic enhancement) were recorded for the 3 T and 1.5 T examinations. Lesion size measures at both field strengths were correlated to final pathology, and imaging characteristics also were compared.

RESULTS

Of the initial cohort of 20 patients with CNB-diagnosed DCIS, 19 underwent definitive surgery. Median DCIS sizes of these 19 patients were 6mm (range: 0-67 mm) on 3T, 13 mm (0-60 mm) on 1.5 T, and 6mm (0-55 mm) on surgical pathology. Size correlation between MRI and pathology was higher for 3T (Spearman's ρ=0.66, p=0.002) than 1.5 T (ρ=0.36, p=0.13). In 10 women in which a residual area of suspicious enhancement was identified on both field strengths, there was agreement of morphologic description (NME vs. mass) in nine, and no significant difference in dynamic contrast enhanced kinetics at 3T compared to 1.5 T.

CONCLUSIONS

Pre-operative breast MRI at 3T provided higher correlation with final pathology size of DCIS lesions compared to 1.5 T, and may be more accurate for assessment of disease extent prior to definitive surgery.

3.0 Tesla breast magnetic resonance imaging in patients with nipple discharge when mammography and ultrasound fail

OBJECTIVES

To compare 3.0 Tesla breast magnetic resonance imaging (MRI) with galactography for detection of benign and malignant causes of nipple discharge in patients with negative mammography and ultrasound.

METHODS

We prospectively evaluated 56 breasts of 50 consecutive patients with nipple discharge who had inconspicuous mammography and ultrasound, using 3.0 Tesla breast MRI with a dedicated 16-channel breast coil, and then compared the results with galactography. Histopathological diagnoses and follow-ups were used as reference standard. Lesion size estimated on MRI was compared with the size at histopathology.

RESULTS

Sensitivity and specificity of MRI vs. galactography for detecting pathologic findings were 95.7 % vs. 85.7 % and 69.7 % vs. 33.3 %, respectively. For the supposed concrete pathology based on MRI findings, the specificity was 67.6 % and the sensitivity 77.3 % (PPV 60.7 %, NPV 82.1 %). Eight malignant lesions were detected (14.8 %). The estimated size at breast MRI showed excellent correlation with the size at histopathology (Pearson's correlation coefficient 0.95, p < 0.0001).

CONCLUSIONS

MRI of the breast at 3.0 Tesla is an accurate imaging test and can replace galactography in the workup of nipple discharge in patients with inconspicuous mammography and ultrasound.

KEY POINTS

• Breast MRI is an excellent diagnostic tool for patients with nipple discharge. • MRI of the breast reveals malignant lesions despite inconspicuous mammography and ultrasound. • MRI of the breast has greater sensitivity and specificity than galactography. • Excellent correlation of lesion size measured at MRI and histopathology was found.

[Molecular breast imaging. An update]

CLINICAL/METHODICAL ISSUE

The aim of molecular imaging is to visualize and quantify biological, physiological and pathological processes at cellular and molecular levels. Molecular imaging using various techniques has recently become established in breast imaging.

STANDARD RADIOLOGICAL METHODS

Currently molecular imaging techniques comprise multiparametric magnetic resonance imaging (MRI) using dynamic contrast-enhanced MRI (DCE-MRI), diffusion-weighted imaging (DWI), proton MR spectroscopy ((1)H-MRSI), nuclear imaging by breast-specific gamma imaging (BSGI), positron emission tomography (PET) and positron emission mammography (PEM) and combinations of techniques (e.g. PET-CT and multiparametric PET-MRI).

METHODICAL INNOVATIONS

Recently, novel techniques for molecular imaging of breast tumors, such as sodium imaging ((23)Na-MRI), phosphorus spectroscopy ((31)P-MRSI) and hyperpolarized MRI as well as specific radiotracers have been developed and are currently under investigation.

PRACTICAL RECOMMENDATIONS

It can be expected that molecular imaging of breast tumors will enable a simultaneous assessment of the multiple metabolic and molecular processes involved in cancer development and thus an improved detection, characterization, staging and monitoring of response to treatment will become possible.

A comparative study of the diagnostic value of contrast-enhanced breast MR imaging and mammography on patients with BI-RADS 3-5 microcalcifications

Objective

To retrospectively investigate the diagnostic value of breast MRI in patients with BI-RADS 3–5 microcalcifications in mammography.

Methods

Eighty-four patients with BI-RADS 3–5 microcalcifications on mammography underwent breast MR exams before surgical biopsy with a hookwire position under mammographic guidance. Two radiologists reviewed each lesion with BI-RADS by consensus. The diagnostic value of mammography and MRI was compared.

Results

Histopathological examination revealed 49 benign lesions and 42 malignant lesions. In the assessments of mammography, 21 lesions (23.1%) were assigned to category 3, 51 lesions (56.0%) to category 4, and 19 lesions (20.9%) to category 5. The area under the receiver operating characteristic(ROC) curve for mammography and MR assessment was 0.844, and 0.945, respectively (p<0.05). In cases of category 3 microcalcifications, the specificity of mammography and MR was 100%, and 95.2% (p = 1.000), respectively. In cases of category 4 microcalcifications, the specificity, PPV and accuracy of mammography was 0%, 45.1% and 45.1%; whereas those for MR was 82.1% (p<0.05), 80.8% (P = 0.003) and 86.3% (p<0.05). All microcalcifications of category 5 were correctly diagnosed by mammography and MR.

Conclusions

Breast MRI has the potential to significantly improve the diagnosis of category 4 microcalcifications on mammography. Among mammographic category 4 microcalcifications, about 82% of benign lesions can be degraded to BI-RADS 1∼3 by MRI. However for microcalcifications of category 3 and 5, MR exams do not show significant improvement over mammography.

Review of treatment assessment using DCE-MRI in breast cancer radiation therapy

As a noninvasive functional imaging technique, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is being used in oncology to measure properties of tumor microvascular structure and permeability. Studies have shown that parameters derived from certain pharmacokinetic models can be used as imaging biomarkers for tumor treatment response. The use of DCE-MRI for quantitative and objective assessment of radiation therapy has been explored in a variety of methods and tumor types. However, due to the complexity in imaging technology and divergent outcomes from different pharmacokinetic approaches, the method of using DCE-MRI in treatment assessment has yet to be standardized, especially for breast cancer. This article reviews the basic principles of breast DCE-MRI and recent studies using DCE-MRI in treatment assessment. Technical and clinical considerations are emphasized with specific attention to assessment of radiation treatment response.

Ductal carcinoma in situ of the breasts: review of MR imaging features

The incidence of ductal carcinoma in situ (DCIS) has increased over the past few decades and now accounts for over 20% of newly diagnosed cases of breast cancer. Although the detection of DCIS has increased with the advent of widespread mammography screening, it is essential to have a more accurate assessment of the extent of DCIS for successful breast conservation therapy. Recent studies evaluating the detection of DCIS with magnetic resonance (MR) imaging have used high spatial resolution techniques and have increasingly been performed to screen a high-risk population as well as to evaluate the extent of disease. This work has shown that MR imaging is the most sensitive modality currently available for identifying DCIS and is more accurate than mammography in evaluating the extent of DCIS. MR imaging is particularly sensitive for identifying high-grade and intermediate-grade DCIS. DCIS may have variable morphologic features on MR images, with non-mass enhancement morphology being the most common manifestation. Less commonly, DCIS may also manifest as a mass on MR images, in which case it is most likely to be irregular. The kinetics of DCIS are also variable, with fast uptake and a plateau curve reported as the most common kinetic pattern. Additional MR imaging tools such as diffusion-weighted imaging and quantitative kinetic analysis combined with the benefit of high field strength, such as 3 T, may increase the sensitivity and specificity of breast MR imaging in the detection of DCIS.

The added diagnostic value of dynamic contrast-enhanced MRI at 3.0 T in nonpalpable breast lesions

Objective

To investigate the added diagnostic value of 3.0 Tesla breast MRI over conventional breast imaging in the diagnosis of in situ and invasive breast cancer and to explore the role of routine versus expert reading.

Materials and Methods

We evaluated MRI scans of patients with nonpalpable BI-RADS 3–5 lesions who underwent dynamic contrast-enhanced 3.0 Tesla breast MRI. Initially, MRI scans were read by radiologists in a routine clinical setting. All histologically confirmed index lesions were re-evaluated by two dedicated breast radiologists. Sensitivity and specificity for the three MRI readings were determined, and the diagnostic value of breast MRI in addition to conventional imaging was assessed. Interobserver reliability between the three readings was evaluated.

Results

MRI examinations of 207 patients were analyzed. Seventy-eight of 207 (37.7%) patients had a malignant lesion, of which 33 (42.3%) patients had pure DCIS and 45 (57.7%) invasive breast cancer. Sensitivity of breast MRI was 66.7% during routine, and 89.3% and 94.7% during expert reading. Specificity was 77.5% in the routine setting, and 61.0% and 33.3% during expert reading. In the routine setting, MRI provided additional diagnostic information over clinical information and conventional imaging, as the Area Under the ROC Curve increased from 0.76 to 0.81. Expert MRI reading was associated with a stronger improvement of the AUC to 0.87. Interobserver reliability between the three MRI readings was fair and moderate.

Conclusions

3.0 T breast MRI of nonpalpable breast lesions is of added diagnostic value for the diagnosis of in situ and invasive breast cancer.

Breast magnetic resonance imaging technique at 1.5 T and 3 T: requirements for quality imaging and American College of Radiology accreditation

Although there are multiple variations in acquisition protocols for breast magnetic resonance (MR) imaging, there is agreement that components of high-quality technique include a bilateral acquisition obtained with a dedicated breast coil. Further, key pulse sequences should be included and spatial and temporal resolution should be sufficiently high to assess lesion morphology and kinetics. Artifacts must be recognized and avoided. The American College of Radiology Breast MRI Accreditation Program requirements provide minimum standards to guide facilities in technique. MR imaging at 3 T is increasingly available and offers signal-to-noise ratio advantages over 1.5 T but also some technical challenges.

High-quality breast MRI

Breast magnetic resonance imaging (MRI) demands the competing factors of high spatial resolution, good temporal resolution, high signal-to-noise ratios, and complete bilateral breast coverage. Achieving these competing factors requires modern MRI equipment with high magnetic field strength and homogeneity, high maximum gradient strength with short rise times, dedicated multichannel bilateral breast coils with prone patient positioning, and 3D (volume) gradient-echo MRI pulse sequences with short TR, short TE, high spatial resolution, and reasonably short acquisition times. This article discusses the equipment and pulse sequences needed to achieve high-quality breast MRI and summarizes requirements of the ACR Breast MRI Accreditation Program.