High-spatial-resolution 3-T breast MRI of nonmasslike enhancement lesions: an analysis of their features as significant predictors of malignancy

Role of breast MRI BI-RADS descriptors in discrimination of non-mass enhancement lesion: A systematic review & meta-analysis

OBJECTIVES

To evaluate the association of BI-RADS 5th edition distribution and type of enhancement descriptors with the malignancy of non-mass enhancement (NME) lesions.

METHODS

Medline via PubMed, Scopus, Web of Science, ProQuest, and Embase databases were systematically searched from January 2013 to July 2022 for original studies, written in English, reporting the positive predictive value (PPV) of individual BI-RADS 5th edition descriptors (distribution and type of enhancement) of NME lesions. Risk of bias and quality of included studies were assessed by QUADAS 2 appraisal tool. Odds ratio (OR) of pathologically confirmed malignant results in each distribution and internal enhancement were pooled in a meta-analysis.

RESULTS

Eight studies for a total of 1095 lesions were included. The pooled OR of malignancy for linear, focal, segmental, regional, multiple region, and diffuse distributions are 0.70 (95%CI: 0.44-1.14), 0.37 (95% CI: 0.26-0.54), 2.42 (95% CI: 1.62-3.62), 0.56 (95% CI: 0.11-2.79), 2.80 (95% CI: 0.96-8.21), and 3.35 (95% CI: 0.59-19.04), respectively. The pooled OR of malignancy for homogenous, heterogeneous, clustered ring enhancement, and clumped enhancement are 0.39 (95% CI: 0.23-0.67), 0.59 (95% CI: 0.40-0.85), 2.92 (95% CI: 1.86-4.57), and 1.49 (95% CI: 0.96-2.32), respectively.

CONCLUSION

Based on a meta-analysis of 8 studies and more than one thousand non-mass enhancing lesions, diffuse, multiple regions and clustered ring descriptors of enhancement have the highest pooled OR for malignancy.

Predictive factors for non-mass enhancement occult in conventional breast imaging: The "PAMAS" study

OBJECTIVES

To identify predictive factors for malignancy in non-mass enhancement occult on conventional imaging (NMEOCI) using MRI, focusing on morphological traits and clinical contexts to refine management strategies.

MATERIALS & METHODS

This retrospective single-center study reviewed all MRI-guided biopsies performed for NMEOCI between January 2015 and October 2021 at a European oncology reference facility. Exclusion criteria were unavailability of the MRI that led to the biopsy, inability to perform control clip MRI or surgery certifying correct targeting, and clustered ring enhancement. Clinical and radiological characteristics were analyzed, and a multivariate logistic regression model assessed associations with malignancy as confirmed by pathological analysis.

RESULTS

One hundred and twenty-eight patients (median age, 58.0 years (Q1-Q3: 45.5-68.0), 128 women) were evaluated. Increased risk of malignancy was associated with older age (p = 0.013), preoperative context (p = 0.050), presence of homolateral neoplasia (p = 0.031), or axillary adenomegaly (p = 0.034). In contrast, MRIs performed without indications (p = 0.044) or as part of screening for high-risk patients (p = 0.033) were protective. NMEOCI features such as larger size (p < 0.001), segmental distribution (p < 0.001), and micronodular character (p < 0.001) were correlated with malignancy risk, whereas homogeneous enhancement suggested benignity (p < 0.001). Five of these characteristics were independently associated with lesions at risk of malignancy: preoperative context, age of patient, micronodular enhancement, axillary adenomegaly, and segmental distribution.

CONCLUSION

Morphological characteristics and clinical contexts of NMEOCIs on MRI are associated with malignancy risk. The mnemonic acronym "PAMAS" ("not a mass" in French) is a useful guide for this type of lesion: Preoperative context, Age, Micronodular enhancement, axillary Adenomegaly, and Segmental distribution, are independently associated with lesions at risk of malignancy.

CLINICAL RELEVANCE STATEMENT

This study enhances the precision of MRI for the analysis of NMEOCI by identifying key morphological and clinical predictors of malignancy, some of which have never been studied before, potentially reducing unnecessary biopsies, and optimizing patient management.

The Role of MRI in Breast Cancer and Breast Conservation Therapy

Contrast-enhanced breast MRI has an established role in aiding in the detection, evaluation, and management of breast cancer. This article discusses MRI sequences, the clinical utility of MRI, and how MRI has been evaluated for use in breast radiotherapy treatment planning. We highlight the contribution of MRI in the decision-making regarding selecting appropriate candidates for breast conservation therapy and review the emerging role of MRI-guided breast radiotherapy.

Discriminative Factors of Malignancy of Ipsilateral Nonmass Enhancement in Women With Newly Diagnosed Breast Cancer on Initial Staging Breast MRI

BACKGROUND

Nonmass enhancement (NME) on breast MRI impacts surgical planning.

PURPOSE

To evaluate positive predictive values (PPVs) and identify malignancy discriminators of NME ipsilateral to breast cancer on initial staging MRI.

STUDY TYPE

Retrospective.

SUBJECTS

Eighty-six women (median age, 48 years; range, 26-75 years) with 101 NME lesions (BI-RADS 4 and 5) ipsilateral to known cancers and confirmed histopathology.

FIELD STRENGTH/SEQUENCE

1.5 T and 3.0 T dynamic contrast-enhanced fat-suppressed T1-weighted fast spoiled gradient-echo.

ASSESSMENT

Three radiologists blinded to pathology independently reviewed MRI features (distribution, internal enhancement pattern, and enhancement kinetics) of NME, locations relative to index cancers (contiguous, non-contiguous, and different quadrants), associated mammographic calcifications, lymphovascular invasion (LVI), axillary node metastasis, and radiology-pathology correlations. Clinical factors, NME features, and cancer characteristics were analyzed for associations with NME malignancy.

STATISTICAL TESTS

Fisher's exact, Chi-square, Wilcoxon rank sum tests, and mixed-effect multivariable logistic regression were used. Significance threshold was set at P < 0.05.

RESULTS

Overall NME malignancy rate was 48.5% (49/101). Contiguous NME had a significantly higher malignancy rate (86.7%) than non-contiguous NME (25.0%) and NME in different quadrants (10.7%), but no significant difference was observed by distance from cancer for non-contiguous NME, P = 0.68. All calcified NME lesions contiguous to the calcified index cancer were malignant. NME was significantly more likely malignant when index cancers were masses compared to NME (52.9% vs. 21.4%), had mammographic calcifications (63.2% vs. 39.7%), LVI (81.8% vs. 44.4%), and axillary node metastasis (70.8% vs. 41.6%). NME features with highest PPVs were segmental distribution (85.7%), clumped enhancement (66.7%), and nonpersistent kinetics (77.1%). On multivariable analysis, contiguous NME, segmental distribution, and nonpersistent kinetics were associated with malignancy.

DATA CONCLUSION

Malignancy discriminators of ipsilateral NME on staging MRI included contiguous location to index cancers, segmental distribution, and nonpersistent kinetics.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Prognostic Molecular Biomarkers in Breast Cancer Lesions with Non-Mass Enhancement on MR

Clustered ring enhancement (CRE) is a new lexicon for non-mass enhancement (NME) of breast MR in the 5th BIRADS, indicating a high suspicion of malignancy. We wonder if the presence of CRE correlates with expression of prognostic molecular biomarkers of breast cancer. A total of 58 breast lesions, which MRI reported with NME, were collected between July 2013 and December 2018. The patterns of enhancement including CRE were reviewed and the pathological results with expression of molecular biomarkers were collected. The association between MRI NME, pathological, and IHC stain findings were investigated under univariate analysis. A total of 58 breast lesions were pathologically proven to have breast cancer, comprising 31 lesions with CRE and 27 lesions without CRE on breast MRI. The expression of the estrogen receptor (ER) (p = 0.017) and the progesterone receptor (PR) (p = 0.017) was significantly lower in lesions with CRE as compared with those without CRE. The expression of Ki-67 (≥25%) was significantly higher in lesions with CRE (p = 0.046). The lesions with CRE had a lower expression ratio of ER (50.71 ± 45.39% vs. 74.26 ± 33.59%, p = 0.028). Our study indicated that lesions with CRE may possess different features from those without CRE in molecular expression, bearing a more aggressive behavior.

Combination of Breast Ultrasound With Magnetic Resonance Imaging in the Diagnosis of Non-mass-like Breast Lesions Detected on Ultrasound: A New Integrated Strategy to Improve Diagnostic Performance

OBJECTIVE

The aim of the work described here was to evaluate the diagnostic performance of a new integrated strategy using breast ultrasound (US) combined with magnetic resonance imaging (MRI) to differentiate benign and malignant breast non-mass-like lesions (NMLs) detected on US.

METHODS

From October 2017 to January 2021, 183 NMLs detected on US that had undergone MRI examinations were included in this respective study. Pathological results were used as the reference standard. The integrated diagnostic strategy of breast US combined with MRI based on a combination of MRI Breast Imaging Reporting and Data System (BI-RADS) with discriminant sonographic indicators highly associated with malignancy was established and validated in a cohort of 61 women. The diagnostic performances of US, MRI and the combined method were calculated and compared.

RESULTS

In the training set, the area under the receiver operating characteristic curve (AUC), sensitivity and specificity of US, MRI and the integrated diagnostic strategy using US combined with MRI for NMLs were 0.730, 93.7% and 52.3%; 0.849, 94.7% and 75.0%; and 0.901, 92.6% and 87.5%, respectively. Compared with US or MRI alone, the integrated diagnostic strategy significantly increased the AUC (p < 0.001, p = 0.007) and specificity (p < 0.001, p = 0.034) while maintaining high sensitivity (p = 0.774, p = 0.551). In the validation set, the integrated strategy of US combined with MRI (AUC = 0.899) also had good performance compared with US (AUC = 0.728) or MRI (AUC = 0.838).

CONCLUSION

The integrated diagnostic strategy of US combined with MRI exhibited good performance for breast NMLs compared with either modality used alone, which can improve the diagnostic specificity while maintaining high sensitivity.

Subcategorization of suspicious non-mass-like enhancement lesions(BI-RADS-MRI Category4)

BACKGROUND

This study aims to providing a reliable method that has good compliance and is easy to master to improve the accuracy of NMLE diagnosis.

METHODS

This study retrospectively analyzed 122 cases of breast non-mass-like enhancement (NMLE) lesions confirmed by postoperative histology. MRI features and clinical features of benign and malignant non-mass enhancement breast lesions were compared by using independent sample t test, χ2test and Fisher exact test. P < 0.05 was considered statistically significant. Statistically significant parameters were then included in logistic regression analysis to build a multiparameter differential diagnosis modelto subdivide the BI-RADS Category 4.

RESULTS

The distribution (odds ratio (OR) = 8.70), internal enhancement pattern (OR = 6.29), ADC value (OR = 5.56), and vascular sign (OR = 2.84) of the lesions were closely related to the benignity and malignancy of the lesions. These signs were used to build the MRI multiparameter model for differentiating benign and malignant non-mass enhancement breast lesions. ROC analysis revealed that its optimal diagnostic cut-off value was 5. The diagnostic specificity and sensitivity were 87.01% and 82.22%, respectively. Lesions with 1-6 points were considered BI-RADS category 4 lesions, and the positive predictive values of subtypes 4a, 4b, and 4c lesions were15.79%, 31.25%, and 77.78%, respectively.

CONCLUSIONS

Comprehensively analyzing the features of MRI of non-mass enhancement breast lesions and building the multiparameter differential diagnosis model could improve the differential diagnostic performance of benign and malignant lesions.

Idiopathic Granulomatous Mastitis or Breast Cancer? A Comparative MRI Study in Patients Presenting with Non-Mass Enhancement

OBJECTIVE

To compare and determine discriminative magnetic resonance imaging (MRI) findings of idiopathic granulomatous mastitis (IGM) and breast cancer (BC) that present as non-mass enhancement.

MATERIALS AND METHODS

This retrospective study includes 68 IGM and 75 BC cases that presented with non-mass enhancement on breast MRI. All patients with a previous history of breast surgery, radiotherapy, or chemotherapy due to BC or a previous history of mastitis were excluded. On MRI images, presence of architectural distortion skin thickening, edema, hyperintense ducts containing protein, dilated fat-containing ducts and axillary adenopathies were noted. Cysts with enhancing walls, lesion size, lesion location, fistulas, distribution, internal enhancement pattern and kinetic features of non-mass enhancement were recorded. Apparent diffusion coefficient (ADC) values were calculated. Pearson chi-square test, Fisher's exact test, independent t test and Mann-Whitney U test were used as needed for statistical analysis and comparison. Multivariate logistic regression model was used to determine the independent predictors.

RESULTS

IGM patients were significantly younger than BC patients (p < 0.001). Cysts with thin (p < 0.05) or thick walls (p = 0.001), multiple cystic lesions, (p < 0.001), cystic lesions draining to the skin (p < 0.001), and skin fistulas (p < 0.05) were detected more often in IGM. Central (p < 0.05) and periareolar (p < 0.001) location and focal skin thickening (p < 0.05) were significantly more common in IGM. Architectural distortion (p = 0.001) and diffuse skin thickening (p < 0.05) were associated with BC. Multiple regional distribution was more common in IGM, whereas diffuse distribution and clumped enhancement were more common in BC (p < 0.05). In kinetic analysis, persistent enhancement was more common in IGM, whereas plateau and wash-out types were more common in BC (p < 0.001). Independent predictors for BC were age, diffuse skin thickening and kinetic curve types. There was no significant difference in the diffusion characteristics. Based on these findings, MRI had a sensitivity, specificity and accuracy of 88%, 67.65%, and 78.32%, respectively, in differentiating IGM from BC.

CONCLUSIONS

In conclusion, for non-mass enhancement, MRI can rule out malignancy with a considerably high sensitivity; however, specificity is still low, as many IGM patients have overlapping findings. Final diagnosis should be complemented with histopathology whenever necessary.

Contrast-Enhanced Cone-Beam Breast CT: An Analysis of Diagnostic Value in Predicting Breast Lesion With Rim Enhancement Malignancy

Background

The objective of the current study was to investigate the diagnostic value of contrast-enhanced cone-beam breast computed tomography (CE-CBBCT) for breast lesion with rim enhancement (RE).

Methods

All 36 patients were examined by non-contrast (NC-CBBCT) and contrast-enhanced CBBCT (CE-CBBCT) after contrast media (CM) injection. Qualitative morphological enhancement parameters and quantitative enhancement parameters were compared between malignant and benign groups. Multivariable logistic regression analysis was performed to identify independent factors that could predict breast lesion with RE malignancy. Receiver operating curve (ROC) was used to evaluate prediction performance.

Results

A total of 36 patients with 40 lesions underwent breast CE-CBBCT were enrolled. There were significant differences in most qualitative morphological enhancement parameters between the two groups. A multivariate logistic regression model showed that △standardized HU (INR_{phase 2}−INR_preCM) [odds ratio (OR) = 1.148, 95% CI = 1.034–1.276, p = 0.01] and △standardized HU (RP_{phase 2} − RP_{phase 1}) (OR = 0.891, 95% CI = 0.814–0.976, p = 0.013) were independent indicators in predicting breast lesion with RE malignancy. △standardized HU (INR_{phase 2} − INR_preCM) combined with △standardized HU (RP_{phase 2} − RP_{phase 1}) showed significant larger area under the receiver operating curve (AUC) and higher sensitivity than each alone (p < 0.001, AUC = 0.932, sensitivity = 92.59%, specificity = 92.31%). The regression equation of the prediction model was as follows: Logit (p) = 0.351 + 0.138X × △standardized HU (INR_{phase 2} − INR_preCM) − 0.115 × △standardized HU (RP_{phase 2} − RP_{phase 1}).

Conclusion

With the observation of qualitative morphological enhancement parameters and the comparison of quantitative enhancement parameters of CBBCT, a reliable basis for the diagnostic accuracy in predicting breast lesion with RE could be provided. These conclusions should be verified in large, well-designed studies.

An artificial intelligence system using maximum intensity projection MR images facilitates classification of non-mass enhancement breast lesions

OBJECTIVES

To build an artificial intelligence (AI) system to classify benign and malignant non-mass enhancement (NME) lesions using maximum intensity projection (MIP) of early post-contrast subtracted breast MR images.

METHODS

This retrospective study collected 965 pure NME lesions (539 benign and 426 malignant) confirmed by histopathology or follow-up in 903 women. The 754 NME lesions acquired by one MR scanner were randomly split into the training set, validation set, and test set A (482/121/151 lesions). The 211 NME lesions acquired by another MR scanner were used as test set B. The AI system was developed using ResNet-50 with the axial and sagittal MIP images. One senior and one junior radiologist reviewed the MIP images of each case independently and rated its Breast Imaging Reporting and Data System category. The performance of the AI system and the radiologists was evaluated using the area under the receiver operating characteristic curve (AUC).

RESULTS

The AI system yielded AUCs of 0.859 and 0.816 in the test sets A and B, respectively. The AI system achieved comparable performance as the senior radiologist (p = 0.558, p = 0.041) and outperformed the junior radiologist (p < 0.001, p = 0.009) in both test sets A and B. After AI assistance, the AUC of the junior radiologist increased from 0.740 to 0.862 in test set A (p < 0.001) and from 0.732 to 0.843 in test set B (p < 0.001).

CONCLUSION

Our MIP-based AI system yielded good applicability in classifying NME lesions in breast MRI and can assist the junior radiologist achieve better performance.

KEY POINTS

• Our MIP-based AI system yielded good applicability in the dataset both from the same and a different MR scanner in predicting malignant NME lesions. • The AI system achieved comparable diagnostic performance with the senior radiologist and outperformed the junior radiologist. • This AI system can assist the junior radiologist achieve better performance in the classification of NME lesions in MRI.

Non-Mass Enhancements on DCE-MRI: Development and Validation of a Radiomics-Based Signature for Breast Cancer Diagnoses

Purpose

We aimed to assess the additional value of a radiomics-based signature for distinguishing between benign and malignant non-mass enhancement lesions (NMEs) on dynamic contrast-enhanced breast magnetic resonance imaging (breast DCE-MRI).

Methods

In this retrospective study, 232 patients with 247 histopathologically confirmed NMEs (malignant: 191; benign: 56) were enrolled from December 2017 to October 2020 as a primary cohort to develop the discriminative models. Radiomic features were extracted from one post-contrast phase (around 90s after contrast injection) of breast DCE-MRI images. The least absolute shrinkage and selection operator (LASSO) regression model was adapted to select features and construct the radiomics-based signature. Based on clinical and routine MR features, radiomics features, and combined information, three discriminative models were built using multivariable logistic regression analyses. In addition, an independent cohort of 72 patients with 72 NMEs (malignant: 50; benign: 22) was collected from November 2020 to April 2021 for the validation of the three discriminative models. Finally, the combined model was assessed using nomogram and decision curve analyses.

Results

The routine MR model with two selected features of the time-intensity curve (TIC) type and MR-reported axillary lymph node (ALN) status showed a high sensitivity of 0.942 (95%CI, 0.906 - 0.974) and low specificity of 0.589 (95%CI, 0.464 - 0.714). The radiomics model with six selected features was significantly correlated with malignancy (P<0.001 for both primary and validation cohorts). Finally, the individual combined model, which contained factors including TIC types and radiomics signatures, showed good discrimination, with an acceptable sensitivity of 0.869 (95%CI, 0.816 to 0.916), improved specificity of 0.839 (95%CI, 0.750 to 0.929). The nomogram was applied to the validation cohort, reaching good discrimination, with a sensitivity of 0.820 (95%CI, 0.700 to 0.920), specificity of 0.864 (95%CI,0.682 to 1.000). The combined model was clinically helpful, as demonstrated by decision curve analysis.

Conclusions

Our study added radiomics signatures into a conventional clinical model and developed a radiomics nomogram including radiomics signatures and TIC types. This radiomics model could be used to differentiate benign from malignant NMEs in patients with suspicious lesions on breast MRI.

Clumped vs non-clumped internal enhancement patterns in linear non-mass enhancement on breast MRI

OBJECTIVE

To compare positive predictive values (PPVs) of clumped vs non-clumped (homogenous and heterogeneous) internal enhancement on MRI detected linear non-mass enhancement (NME) on MRI-guided vacuum-assisted breast biopsy (MRI-VABB).

METHODS

With IRB (Institutional Review Board) approval, we retrospectively reviewed 598 lesions undergoing MRI-VABB from January 2015 to April 2018 that showed linear NME. We reviewed the electronic medical records for MRI-VABB pathology, any subsequent surgery and clinical follow-up. The X² test was performed for univariate analysis.

RESULTS

There were 120/598 (20%) linear NME MRI-VABB lesions with clumped (52/120, 43%) vs non-clumped (68/120, 57%) internal enhancement, average size 1.8 cm (range 0.6-7.6 cm). On MRI-VABB, cancer was identified in 22/120 (18%) lesions, ductal carcinoma in situ (DCIS) was found in 18/22 (82%) and invasive cancer in 4 (18%). 3/31 (10%) high-risk lesions upgraded to DCIS at surgery, for a total of 25/120 (21%) malignancies. Malignancy was found in 12/52 (23%) clumped lesions and in 13/68 (19%) of non-clumped lesions that showed heterogeneous (5/13, 38%) or homogenous (8/13, 62%) internal enhancement. The PPV of linear NME with clumped internal enhancement (23.1%) was not significantly different from the PPV of non-clumped linear NME (19.1%) (p = 0.597). The PPV of linear NME lesions <1 cm (33.3%) was not significantly different from the PPV of lesions ≥1 cm (18.6%) (p = 0.157).

CONCLUSIONS

Linear NME showed malignancy in 21% of our series. Linear NME with clumped or non-clumped internal enhancement patterns, regardless of lesion size, might need to undergo MRI-VABB in appropriate populations.

ADVANCES IN KNOWLEDGE

Evaluation of linear NME lesions on breast MRI focuses especially on internal enhancement pattern.

Idiopathic Granulomatous Mastitis and its Mimics on Magnetic Resonance Imaging: A Pictorial Review of Cases from India

Objectives:

Idiopathic granulomatous mastitis (IGM) is a rare inflammatory disease of the breast, which is benign but potentially morbid. Mammographic and sonographic findings have been well characterized, but magnetic resonance imaging (MRI) findings have been less thoroughly documented. The objective of this study was to demonstrate characteristic findings for IGM and its mimics via a retrospective review.

Material and Methods:

Breast MRI examinations performed at Sir Ganga Ram Hospital in New Delhi, India between 2014 and 2019 were retrospectively reviewed to identify cases in which a pattern suggestive of granulomatous mastitis was seen. Cases of known malignancy were excluded. Any available breast pathology results were then obtained, and cases with presumptive or definitive diagnoses were compiled for analysis.

Results:

Overall, cases identified with characteristic imaging findings and confirmed diagnosis included seven cases of IGM, four cases of invasive ductal carcinoma, two cases of tuberculous mastitis, one case of non- tuberculous infectious mastitis, one case of foreign body mastitis, and one case of eosinophilc mastitis. One case of IGM with masses rather than of non-mass enhancement was also identified.

Conclusion:

In our review, cases with clustered ring enhancement were found to have inflammatory, idiopathic, infectious and malignant etiologies. While, these etiologies can only be reliably differentiated on pathology, familiarity with the pattern and an awareness of the differential may lead to decreased morbidity due to delays in diagnosis.

Scoring System to Predict Malignancy for MRI-Detected Lesions in Breast Cancer Patients: Diagnostic Performance and Effect on Second-Look Ultrasonography

Purpose

To design a scoring system to predict malignancy of additional MRI-detected lesions in breast cancer patients.

Materials and Methods

Eighty-six lesions (64 benign and 22 malignant) detected on preoperative MRI of 68 breast cancer patients were retrospectively included. The clinico-radiologic features were correlated with the histopathologic results using the Student's t-test, Fisher's exact test, and logistic regression analysis. The scoring system was designed based on the significant predictive features of malignancy, and its diagnostic performance was compared with that of the Breast Imaging-Reporting and Data System (BI-RADS) category.

Results

Lesion size ≥ 8 mm (p < 0.001), location in the same quadrant as the primary cancer (p = 0.005), delayed plateau kinetics (p = 0.010), T2 isointense (p = 0.034) and hypointense (p = 0.024) signals, and irregular mass shape (p = 0.028) were associated with malignancy. In comparison with the BI-RADS category, the scoring system based on these features with suspicious non-mass internal enhancement increased the diagnostic performance (area under the receiver operating characteristic curve: 0.918 vs. 0.727) and detected three false-negative cases. With this scoring system, 22 second-look ultrasound examinations (22/66, 33.3%) could have been avoided.

Conclusion

The scoring system based on the lesion size, location relative to the primary cancer, delayed kinetic features, T2 signal intensity, mass shape, and non-mass internal enhancement can provide a more accurate approach to evaluate MRI-detected lesions in breast cancer patients.

Differentiation between Clinically Noninflammatory Granulomatous Lobular Mastitis and Noncalcified Ductal Carcinoma in situ Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging

<b><i>Introduction:</i></b> Challenges in differentiation between clinically noninflammatory granulomatous lobular mastitis (GLM) and noncalcified ductal carcinoma in situ (DCIS) remain. <b><i>Objective:</i></b> To identify the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) characteristics contributing to their differential diagnosis. <b><i>Methods:</i></b> A total of 33 clinically noninflammatory GLM and 36 noncalcified DCIS were retrospectively analyzed in the study. Internal enhancement of a nonmass enhancement (NME) lesion was divided into clustered enhanced ring (absence/presence), and clustered enhanced ring (presence) was further classified as small and large ring based on the optimal cutoff value. The 5th Breast Imaging and Data System MRI descriptors were used for assessing the other DCE-MRI characteristics. Multivariate analysis including variables with significant differences in univariate analyses was conducted to identify the independent predictors. The discriminative abilities of different predictors and their combination were compared by area under the receiver-operating characteristic curves (AUCs). <b><i>Results:</i></b> An NME lesion was seen more commonly in clinically noninflammatory GLM than in noncalcified DCIS (<i>p</i> = 0.003). DCE-MRI characteristics with significant differences in univariate analyses included NME size, clustered enhanced ring (absence/presence), ring size, initial increase and kinetic characteristics for the differentiation between these two entities presenting as NME lesion. Clustered enhanced ring (presence) was further classified as small (≤7 mm) or large ring (&#x3e;7 mm). Multivariate analysis revealed that internal enhancement and initial increase were identified as significant independent predictors, and the AUC of their combination achieved the highest value of 0.867 (95% CI, 0.748–0.943). <b><i>Conclusions:</i></b> An NME lesion with a large ring is more highly suggestive of clinically noninflammatory GLM.

Interobserver variability and likelihood of malignancy for fifth edition BI-RADS MRI descriptors in non-mass breast lesions

Objective

Non-mass enhancement (NME) in breast MRI is the most common feature of ductal carcinoma in situ (DCIS). We sought to evaluate the interobserver variability and positive predictive value (PPV) for malignancy of NME descriptors using the fifth edition BI-RADS lexicon focusing on the newly introduced “clustered ring enhancement” pattern.

Materials and methods

Breast MRIs of 129 patients who had undergone MRI-guided vacuum-assisted biopsy (VAB) in our institution were reviewed. Studies assessed as NME were classified according to the fifth edition BI-RADS lexicon by two breast radiologists. Consensus was reached by involving a third radiologist. Interobserver variability and PPV for malignancy were assessed.

Results

Seventy-two of 129 studies were assessed as NME. The disagreement rate in the first assessment step (mass vs. NME) was low at 9.3% (ĸ = 0.81, 95% confidence interval [CI] 0.71–0.91). The disagreement rate for distribution patterns was 23.6% (ĸ = 0.67, 95% CI 0.54–0.80) and 22.2% (ĸ = 0.69, 95% CI 0.56–0.81) for internal enhancement patterns. Clustered ring enhancement (PPV 53.85, p = 0.038) and segmental distribution (PPV 62.5%, p = 0.028) had the highest malignancy rates among internal enhancement and distribution patterns with a significant result; the combination of clustered ring enhancement and segmental distribution raised the malignancy rate by approximately 4% (PPV 66.67%, p = 0.049).

Conclusion

There was a high agreement rate among readers when differentiating NME from mass lesions. The agreement rate was lower when assessing the distribution and internal enhancement pattern descriptors, but still substantial. The descriptors clustered ring enhancement and segmental distribution were significant predictors of malignancy.

Key Points

• Non-mass enhancement is a common morphological feature of non-invasive breast cancer (DCIS) in MRI. Differentiation between potentially malignant and benign changes may be very challenging.

• Since clustered ring enhancement and segmental distribution are both significant predictors of malignancy, the awareness of this important finding, combined with high-quality image interpretation skills, may improve the tumor detection rate.

• The combination of clustered ring enhancement and segmental distribution increases the positive predictive value for malignancy, which may be relevant for clinical practice.

The MRI characteristics of non-mass enhancement lesions of the breast: associations with malignancy

OBJECTIVE:

The American College of Radiology updated the terms used for expressing the imaging characteristics of non-mass enhancement (NME) lesions in the fifth edition of the breast imaging-reporting data system (BI-RADS) lexicon. Both the distribution and internal enhancement descriptors were revised for NME lesions. Our aim was to determine the MRI characteristics of NME lesions and to investigate their association with malignancy.

METHODS:

The MRI results of 129 NME lesions were retrospectively evaluated. The medical files, biopsy results and follow-up findings of lesions were recorded. Patients who had benign biopsy and those who had stable or regressed lesions during follow-up were classified as benign. All MRI results had been obtained with a 1.5 Tesla Signa HDx MR system (GE Healthcare).

RESULTS:

Segmental and diffuse distribution along with clustered-ring internal enhancement were significantly associated with malignancy, while linear distribution and homogeneous enhancement pattern were associated with benignancy. Additionally, the plateau type (Type II) curve was significantly more frequent in malignant lesions. There was no association between the presence of cystic structures and the benign/malignant nature of the lesion. However, multivariate logistic regression showed that only segmental distribution and diffusion restriction were associated with malignancy.

CONCLUSION:

In the current study, segmental distribution, clustered-ring enhancement, Type II dynamic curve and the presence of diffusion restriction were found to be associated with malignancy. There is a requirement for multicenter studies which include higher numbers of patients in order to better evaluate lesions with rarer characteristics for distribution and enhancement pattern.

ADVANCES IN KNOWLEDGE:

Our aim in this study was to investigate the MRI characteristics of NME lesions. We have reported the MRI findings of NME lesions and have found that segmental distribution and clustered-ring enhancement patterns are significantly more frequent in malignant lesions.

Grading system to categorize breast MRI using BI-RADS 5th edition: a statistical study of non-mass enhancement descriptors in terms of probability of malignancy

PURPOSE

To analyze the association of breast non-mass enhancement descriptors in the BI-RADS 5th edition with malignancy, and to establish a grading system and categorization of descriptors.

MATERIALS AND METHODS

This study was approved by our institutional review board. A total of 213 patients were enrolled. Breast MRI was performed with a 1.5-T MRI scanner using a 16-channel breast radiofrequency coil. Two radiologists determined internal enhancement and distribution of non-mass enhancement by consensus. Corresponding pathologic diagnoses were obtained by either biopsy or surgery. The probability of malignancy by descriptor was analyzed using Fisher's exact test and multivariate logistic regression analysis. The probability of malignancy by category was analyzed using Fisher's exact and multi-group comparison tests.

RESULTS

One hundred seventy-eight lesions were malignant. Multivariate model analysis showed that internal enhancement (homogeneous vs others, p < 0.001, heterogeneous and clumped vs clustered ring, p = 0.003) and distribution (focal and linear vs segmental, p < 0.001) were the significant explanatory variables. The descriptors were classified into three grades of suspicion, and the categorization (3, 4A, 4B, 4C, and 5) by sum-up grades showed an incremental increase in the probability of malignancy (p < 0.0001).

CONCLUSION

The three-grade criteria and categorization by sum-up grades of descriptors appear valid for non-mass enhancement.

Contrast Enhancement in Breast Cancer and Background Mammary-Gland Tissue During the Super-Early Phase of Dynamic Breast Magnetic Resonance Imaging

RATIONALE AND OBJECTIVES

We aimed to compare the contrast enhancement between tumor and mammary-gland tissue to distinguish lesions in the super-early phase, during which minimal contrast media uptake is observed in mammary-gland tissue.

MATERIALS AND METHODS

Dynamic magnetic resonance imaging, including the super-early phase with bolus tracking (BT) method (to determine the optimal imaging start time), was performed by using identical parameters to obtain transverse fat-suppressed T1-weighted images of both breasts. The percent enhancement (PE) and the contrast ratio (CR) indicators for tumor and mammary-gland tissue were assessed in each dynamic phase.

RESULTS

The PE values of the tumor were 62.4% and 151.6%, and those of the mammary gland were 0.3% and 20.7% in the super-early and early phases, respectively. Therefore, virtually no background parenchymal enhancement was observed in the super-early phase. The variation in the PE values during the super-early phase was significantly smaller when the values were determined with the BT method (P < .05). The CR was highest in the early phase, and the CR in the super-early phase was lower than in the other phases. Early-phase PE and CR were significantly higher in invasive cancer cases than in noninvasive cancer cases (P < .01). A significant difference in the imaging start time was observed for the anatomic side factor by the BT method.

CONCLUSION

Background parenchymal enhancement almost never appeared in the super-early phase, but the CR was lower in the super-early phase than in the early phase. The BT method allowed for an optimal imaging start time for the super-early phase and yielded images with less deviation of contrast enhancement.

Magnetic resonance imaging characteristics of granulomatous mastitis

Granulomatous mastitis (GM) is a benign chronic inflammatory condition of the breast. This study was performed to determine the utility of magnetic resonance imaging (MRI) in differentiating GM from malignancy. MRI findings in 12 women with clinical or histopathologically-proven GM were retrospectively reviewed. Non-mass enhancement on MRI was present in all 12 patients with clustered ring enhancement being the most common pattern (n=7, 58%). Architectural distortion (n=10, 83%), skin thickening (n=10, 83%) and focal skin enhancement (n=10, 83%) were also very common. MRI features of GM are often identical to features considered suspicious for malignancy on MRI.

Significant MRI indicators of malignancy for breast non-mass enhancement

OBJECTIVE

To explore and evaluate new malignant predictors of breast non-mass enhancement lesions using the new BI-RADS MRI lexicon.

METHODS

A dataset involving 422 consecutive women underwent breast 3.0 T MRI between January 2014 and July 2016 was assembled for this study. Each case was retrospectively reviewed by 3 radiologists. Eighty-four lesions that present non-mass enhancement in 79 patients were identified in the study. Dynamic contrast-enhanced MRI features were analyzed using univariate and multivariate analyses to identify significant indicators of malignancy.

RESULTS

Of 84 non-mass enhancement lesions, 52 (61.9%) were malignant and 32 (38.1%) were benign. Segmental distribution (P = 0.015 from univariate analysis; OR = 4.739, P = 0.008 from multivariate analysis), cluster ring enhancement (P = 0.017 from univariate analysis; OR = 3.601, P = 0.032 from multivariate analysis), time-intensity curve of plateau (P = 0.002 from univariate analysis; OR = 3.525, P = 0.027 from multivariate analysis) and phase to peak (P = 0.06 from univariate analysis; OR = 6.327, P = 0.015 from multivariate analysis) were significantly different between malignant and benign lesions.

CONCLUSIONS

This study demonstrated that segmental distribution, clustered ring enhancement, and short time to peak could act as new malignant predictors for breast non-mass enhancement detected on 3.0 T MRI.

Descriptors of Malignant Non-mass Enhancement of Breast MRI: Their Correlation to the Presence of Invasion

RATIONALE AND OBJECTIVES

This study aims to investigate the clinical significance of malignant non-mass enhancement (NME) descriptors in breast magnetic resonance images by assessing their correlation to the presence of invasion or lymph node metastasis.

MATERIALS AND METHODS

Three radiologists independently reviewed magnetic resonance images with malignant NMEs between January 2008 and December 2009. Distribution was assessed first, and then each of four internal enhancement patterns-clumped, clustered ring, branching, and hypointense area-was evaluated dichotomously (yes or no). Because clustered rings and hypointense areas were thought to be major structural elements of heterogeneous NMEs, they were also evaluated by integrating them into one collective descriptor we called the "heterogeneous structures." Chi-square test, Fisher exact test, or Student t test was used to analyze differences of variables by each reviewer. Positive predictive values (PPVs) of descriptors in predicting presence of invasion or lymph node metastasis were calculated. P < 0.05 was considered significant.

RESULTS

We included 131 malignant NMEs (76 in situ and 55 invasive) in 129 patients (two bilateral). All three observers' results showed clustered rings (PPVs 54.5%, 54.5%, 50.0%) (P = 0.0005, 0.038, 0.029) and hypointense areas (PPVs 63.6%, 61.5%, 73.9%) (P = 0.004, 0.024, 0.0006) to be significantly associated with invasion. When clustered rings and hypointense areas were integrated into heterogeneous structures, they were significantly associated with invasion (PPVs 54.3%, 53.3%, 51.8%) (P = 0.0003, 0.016, 0.003).

CONCLUSIONS

The NME descriptors clustered rings, hypoechoic areas, and heterogeneous structures, assessed collectively, were associated with invasive breast cancer.

Significance of Additional Non-Mass Enhancement in Patients with Breast Cancer on Preoperative 3T Dynamic Contrast Enhanced MRI of the Breast

Background

In preoperative assessment of breast cancer, MRI has been shown to identify more additional breast lesions than are detectable using conventional imaging techniques. The characterization of additional lesions is more important than detection for optimal surgical treatment. Additional breast lesions can be included in focus, mass, and non-mass enhancement (NME) on MRI. According to the fifth edition of the breast imaging reporting and data system (BI-RADS®), which includes several changes in the NME descriptors, few studies to date have evaluated NME in preoperative assessment of breast cancer.

Objectives

We investigated the diagnostic accuracy of BI-RADS descriptors in predicting malignancy for additional NME lesions detected on preoperative 3T dynamic contrast enhanced MRI (DCE-MRI) in patients with newly diagnosed breast cancer.

Patients and Methods

Between January 2008 and December 2012, 88 patients were enrolled in our study, all with NME lesions other than the index cancer on preoperative 3T DCE-MRI and all with accompanying histopathologic examination. The MRI findings were analyzed according to the BI-RADS MRI lexicon. We evaluated the size, distribution, internal enhancement pattern, and location of NME lesions relative to the index cancer (i.e., same quadrant, different quadrant, or contralateral breast).

Results

On histopathologic analysis of the 88 NME lesions, 73 (83%) were malignant and 15 (17%) were benign. Lesion size did not differ significantly between malignant and benign lesions (P = 0.410). Malignancy was more frequent in linear (P = 0.005) and segmental (P = 0.011) distributions, and benignancy was more frequent in focal (P = 0.004) and regional (P < 0.001) NME lesions. The highest positive predictive value (PPV) for malignancy occurred in segmental (96.8%), linear (95.1%), clustered ring (100%), and clumped (92.0%) enhancement. Asymmetry demonstrated a high positive predictive value of 85.9%. The frequency of malignancy was higher for NME lesions located in the same quadrant with the index cancer (P = 0.006), and benignancy was higher in the contralateral breast (P = 0.015). On multivariate analysis, linear (P = 0.001) and segmental (P = 0.005) distributions were significant predictors of malignancy.

Conclusion

The possibility of malignancy is strongly indicated when additional NME lesions show linear or segmental enhancement on preoperative 3T DCE-MRI in patients with recently diagnosed breast cancer.

Morphology evaluation of nonmass enhancement on breast MRI: Effect of a three-step interpretation model for readers' performances and biopsy recommendations

OBJECTIVE

To evaluate and compare the use of a newly introduced interpretation model for breast nonmass enhancement (NME, defined as an area of enhancement without a three-dimensional, space-occupying lesion) with the use of the standard interpretation method based on BI-RADS.

MATERIALS AND METHODS

Two expert and two less-experienced breast imaging radiologists performed reading sessions of 86 malignant and 64 benign NME lesions twice. First, radiologists characterized NME using BI-RADS descriptors and assessed the likelihood of malignancy and need for a biopsy. Second, the likelihood of malignancy and need for a biopsy were assessed with the use of the model, in which three-step characterization of morphological features were performed: (1) selection of distribution modifiers, (2) homogeneous vs. heterogeneous internal enhancement (IE) pattern, and (3) evaluation of presence of "clumped", "clustered ring enhancement (CRE)", and "branching" IE signs. Multireader-multicase receiver operating characteristic analysis was used to evaluate observers' performances. Univariate and multivariate logistic regression analyses were performed for morphology descriptors.

RESULTS

With use of the model, average Az of less-experienced radiologists (0.77-0.83; p=0.013) and average sensitivity of all radiologists (96.2-98.2%; p=0.007) improved significantly. NPV also improved but nonsignificantly (81.1-91.9%; p=0.055). Multivariate analyses of the second reading showed branching, clumped, and CRE signs to be significant predictors of malignancy in the results of 3, 2, and 2 readers, respectively.

CONCLUSION

The three-step interpretation model for NME has the potential to improve less-experienced radiologists' performances, making them comparable to expert breast imagers.

Interpretation of Breast MRI Utilizing the BI-RADS Fifth Edition Lexicon: How Are We Doing and Where Are We Headed?

The Breast Imaging Reporting and Data System (BI-RADS) was first initiated in the late 1980s in order to standardize reporting, improve report organization, and to monitor outcomes for more clear, concise, and uniform communication of breast imaging findings. In the BI-RADS 5th edition, several changes and new additions have been made to the magnetic resonance imaging (MRI) lexicon, reflecting increased utilization and availability of breast MRI in clinical practice. Understanding the role and appropriate utilization of breast MRI and the BI-RADS lexicon could help with interpretation and effective communication of MRI findings as well as preparing for incorporation of more advanced imaging techniques. In this comprehensive review of the changes and new descriptors in the MRI section of the fifth edition of BI-RADS with pictorial examples, the reader would be able to achieve improved understanding of the MRI BI-RADS lexicon and its appropriate applications.

Real-time virtual sonography examination and biopsy for suspicious breast lesions identified on MRI alone

OBJECTIVES

The purpose of our study was to assess whether there is a potential additional value of real-time virtual sonography (RVS) to second-look ultrasound (US) examination and biopsy for breast lesions identified on MRI alone.

METHODS

A retrospective review of the records of 70 consecutive patients (78 lesions) with breast abnormalities identified on MRI alone was performed. All suspicious enhancing lesions were subsequently evaluated with second-look US. Lesions not observed on second-look US underwent RVS. Pathological findings were confirmed by subsequent percutaneous biopsy or excision.

RESULTS

Of the 78 MRI-detected lesions, second-look US correlation was made in 50 (64 %), including 22 malignant and 28 benign lesions. The remaining 28 lesions (36 %) were scheduled to undergo RVS. Four lesions were not visible on the second breast MRI. The remaining 24 lesions were RVS correlated and underwent RVS-guided biopsy; these included seven malignant and 17 benign lesions. Overall, 74 of 74 (100 %) true MRI-detected lesions were confirmed by histological results without using MRI-guided breast biopsy. The cancer rate was 29 %.

CONCLUSIONS

RVS can increase the sonographic detection and biopsy rate of lesions identified on breast MRI alone.

KEY POINTS

• All 74 MRI-detected lesions were confirmed without using MRI-guided biopsy. • Four lesions were not visible on second breast MRI. • RVS can increase sonographic detection of lesions identified on breast MRI alone. • RVS-guided breast biopsy can be an alternative to MRI-guided biopsy.

BI-RADS update

The updated American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) has been newly released. This article summarizes the changes and updates that have been made to BI-RADS. The goal of the revised edition continues to be the same: to improve clarification in image interpretation, maintain reporting standardization, and simplify the monitoring of outcomes. The new BI-RADS also introduces new terminology to provide a more universal lexicon across all 3 imaging modalities.

Earlier and better high-resolution single breast imaging during bilateral breast dynamic scans at 3-T MRI: comparison with post dynamic high-resolution imaging

BACKGROUND

Breast MRI protocols have been improved by using a combination of dynamic scans for bilateral breasts and high-resolution imaging for a single breast which can be obtained during dynamic scans by recent technological advances. The purpose of this study was to compare high-resolution imaging during dynamic scans (HR-intra) with high-resolution imaging obtained post dynamic scans (HR-post).

METHODS

Fifty-five women with pathologically proven breast cancer who underwent breast dynamic scans at 3-T MRI from February to September 2009 were enrolled in this study. Tumoral contrasts to the background breast tissue were compared by three radiologists independently in a blinded fashion. Results of visual assessment were categorized into three groups as follows: HR-intra being better (IB), equal (E), and HR-post being better (PB). The contrast to noise ratio (CNR) of the tumor and the signal to noise ratio of the normal breast gland (SNR) were compared between HR-intra and HR-post.

RESULTS

Two patients were excluded because of poor MR imaging quality. Three radiologists separately categorized 64.2, 79.2, and 77.4 % of lesions as IB. The CNR of the tumor of HR-intra (mean ± SD = 6.9 ± 4.0) was significantly higher than that of HR-post (6.0 ± 3.7, p < 0.0001). The SNR of the normal breast gland of HR-intra (9.5 ± 1.7) was significantly lower than that of HR-post (10.0 ± 1.9, p < 0.0001).

CONCLUSION

HR-intra during dynamic MRI provided earlier and better tumor to normal breast gland contrast than HR-post.

Real-time virtual sonography (RVS)-guided vacuum-assisted breast biopsy for lesions initially detected with breast MRI

PURPOSE

To report on our initial experiences with a new method of real-time virtual sonography (RVS)-guided 11-gauge vacuum-assisted breast biopsy for lesions that were initially detected with breast MRI.

MATERIALS AND METHODS

RVS-guided 11-gauge vacuum-assisted biopsy is performed when a lesion with suspicious characteristics is initially detected with breast MRI and is occult on mammography, sonography, and physical examination. Live sonographic images were co-registered to the previously loaded second-look spine contrast-enhanced breast MRI volume data to correlate the sonography and MR images.

RESULTS

Six lesions were examined in six consecutive patients scheduled to undergo RVS-guided 11-gauge vacuum-assisted biopsy. One patient was removed from the study because of non-visualization of the lesion in the second-look spine contrast-enhanced breast MRI. Five patients with non-mass enhancement lesions were biopsied. The lesions ranged in size from 9 to 13 mm (mean 11 mm). The average procedural time, including the sonography and MR image co-registration time, was 25 min. All biopsies resulted in tissue retrieval. One was fibroadenomatous nodules, and those of four were fibrocystic changes. There were no complications during or after the procedures.

CONCLUSION

RVS-guided 11-gauge vacuum-assisted breast biopsies provide a safe and effective method for the examination of suspicious lesions initially detected with MRI.

Updates and revisions to the BI-RADS magnetic resonance imaging lexicon

This article summarizes the updates and revisions to the second edition of the BI-RADS MRI lexicon. A new feature in the lexicon is background parenchymal enhancement and its descriptors. Another major focus is on revised terminology for masses and non-mass enhancement. A section on breast implants and associated lexicon terms has also been added. Because diagnostic breast imaging increasingly includes multimodality evaluation, the new edition of the lexicon also contains revised recommendations for combined reporting with mammography and ultrasound if these modalities are included as comparison, and clarification on the use of final assessment categories in MR imaging.

3T-MRI, elastography, digital mammography, and FDG-PET CT findings of subcutaneous panniculitis-like T-cell lymphoma (SPTCL) of the breast

Subcutaneous panniculitis-like T-cell lymphoma (SPTCL) is a rare subtype of cutaneous lymphoma, which is characterized by infiltration of neoplastic cytotoxic T cells into the subcutaneous tissue. We here report the case of a 66-year-old woman with SPTCL of the breast, which is a very uncommon location. Multiple suspicious irregular small masses in the subcutaneous fat were detected by mammography, and sonograms revealed hyperechoic masses. Elastography was useful to improve depiction and delineation of SPTCL in the hyperechoic subcutaneous fat, and dynamic contrast-enhanced MRI examinations showed multiple irregular rim enhanced masses with persistent enhancement. FDG-PET CT images showed hypermetabolism in areas corresponding to other imaging techniques. MRI can be useful for diagnosis of fat necrosis, which is a primary radiologic feature of SPTCL. However, fat necrosis has multitude of appearances by various imaging techniques, which typically indicate a benign disease, but may indicate a malignancy. Therefore, an ultrasonographically guided core needle biopsy is useful for a diagnosis of SPTCL of the breast. The presence of multiple subcutaneous nodules throughout the body on CT imaging may be an important finding that suggests a diagnosis of SPTCL.