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

Breast lesions on MRI in mass and non-mass enhancement: Kaiser score and modified Kaiser score + for readers of variable experience

OBJECTIVES

To compare the diagnostic performance of three readers using BI-RADS and Kaiser score (KS) based on mass and non-mass enhancement (NME) lesions.

METHODS

A total of 630 lesions, 393 malignant and 237 benign, 458 mass and 172 NME, were analyzed. Three radiologists with 3 years, 6 years, and 13 years of experience made diagnoses. 596 cases had diffusion-weighted imaging, and the apparent diffusion coefficient (ADC) was measured. For lesions with ADC > 1.4 × 10-3 mm2/s, the KS was reduced by 4 as the modified KS +, and the benefit was assessed.

RESULTS

When using BI-RADS, AUC was 0.878, 0.915, and 0.941 for mass, and 0.771, 0.838, 0.902 for NME for Reader-1, 2, and 3, respectively, better for mass than for NME. The diagnostic accuracy of KS was improved compared to BI-RADS for less experienced readers. For Reader-1, AUC was increased from 0.878 to 0.916 for mass (p = 0.005) and from 0.771 to 0.822 for NME (p = 0.124). Based on the cut-off value of BI-RADS ≥ 4B and KS ≥ 5 as malignant, the sensitivity of KS by Readers-1 and -2 was significantly higher for both Mass and NME. When ADC was considered to change to modified KS +, the AUC and the accuracy for all three readers were improved, showing higher specificity with slightly degraded sensitivity.

CONCLUSION

The benefit of KS compared to BI-RADS was most noticeable for the less experienced readers in improving sensitivity. Compared to KS, KS + can improve specificity for all three readers. For NME, the KS and KS + criteria need to be further improved.

CLINICAL RELEVANCE STATEMENT

KS provides an intuitive method for diagnosing lesions on breast MRI. BI-RADS and KS face greater difficulties in evaluating NME compared to mass lesions. Adding ADC to the KS can improve specificity with slightly degraded sensitivity.

KEY POINTS

KS provides an intuitive method for interpreting breast lesions on MRI, most helpful for novice readers. KS, compared to BI-RADS, improved sensitivity in both mass and NME groups for less experienced readers. NME lesions were considered during the development of the KS flowchart, but may need to be better defined.

Multiparametric MRI model with synthetic MRI, DWI multi-quantitative parameters, and differential sub-sampling with cartesian ordering enables BI-RADS 4 lesions diagnosis with high accuracy

Objective

To assess the feasibility and diagnostic performances of synthetic magnetic resonance imaging (SyMRI) combined with diffusion-weighted imaging (DWI) and differential subsampling with cartesian ordering (DISCO) in breast imaging reporting and data system (BI-RADS) 4 lesions.

Methods

A total of 98 BI-RADS 4 patients, including 68 cases assigned to a malignant group and 33 cases assigned to a benign group, were prospectively enrolled, and their MRI and clinical information were collected. Two physicians jointly analyzed the characteristics of conventional MRI. T1, T2, proton density (PD), and ADC values were obtained from three different regions of interest (ROIs). Logistic regression analyses were used to select features and build models, and a nomogram was constructed with the best model.

Results

Using the ROI delineation method at the most obvious enhancement to measure the ADC value revealed the best diagnostic performance in diagnosing BI-RADS type 4 mass lesions. The diagnostic efficiency of the maximum level drawing method of the quantitative relaxation model was better than that of the whole drawing method and the most obvious enhancement method. The best relaxation model (model A) was composed of two parameters: T2stand and ΔT1%stand (AUC=0.887), and the BI-RADS model (model B) was constructed by two MRI features of edge and TIC curve (AUC=0.793). Using the quantitative parameters of SyMRI and DWI of the best ROC method combined with DISCO enhanced MRI features to establish a joint diagnostic model (model C: edge, TIC curve type, ADClocal, T2stand, ΔT1%stand) showed the best diagnostic efficiency (AUC=0.953). The nomogram also had calibration curves with good overlap.

Conclusions

The combined diagnosis model of SyMRI and DWI quantitative parameters combined with DISCO can improve the diagnostic efficiency of BI-RADS 4 types of mass lesions. Also, the line diagram based on this model can be used as an auxiliary diagnostic tool.

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.

Impact of Imaging Biomarkers and AI on Breast Cancer Management: A Brief Review

Breast cancer stands out as the most frequently identified malignancy, ranking as the fifth leading cause of global cancer-related deaths. The American College of Radiology (ACR) introduced the Breast Imaging Reporting and Data System (BI-RADS) as a standard terminology facilitating communication between radiologists and clinicians; however, an update is now imperative to encompass the latest imaging modalities developed subsequent to the 5th edition of BI-RADS. Within this review article, we provide a concise history of BI-RADS, delve into advanced mammography techniques, ultrasonography (US), magnetic resonance imaging (MRI), PET/CT images, and microwave breast imaging, and subsequently furnish comprehensive, updated insights into Molecular Breast Imaging (MBI), diagnostic imaging biomarkers, and the assessment of treatment responses. This endeavor aims to enhance radiologists' proficiency in catering to the personalized needs of breast cancer patients. Lastly, we explore the augmented benefits of artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications in segmenting, detecting, and diagnosing breast cancer, as well as the early prediction of the response of tumors to neoadjuvant chemotherapy (NAC). By assimilating state-of-the-art computer algorithms capable of deciphering intricate imaging data and aiding radiologists in rendering precise and effective diagnoses, AI has profoundly revolutionized the landscape of breast cancer radiology. Its vast potential holds the promise of bolstering radiologists' capabilities and ameliorating patient outcomes in the realm of breast cancer management.

Preoperative Breast Magnetic Resonance Imaging: An Ontario Health (Cancer Care Ontario) Clinical Practice Guideline

BACKGROUND

The use of preoperative breast magnetic resonance imaging (MRI) after the diagnosis of breast cancer by mammography and/or ultrasound is inconsistent.

METHODS

After conducting a systematic review and meta-analysis comparing preoperative breast MRI versus no MRI, we reconvened to prepare a clinical practice guideline on this topic.

RESULTS

Based on the evidence that MRI improved recurrence, decreased the rates of reoperations (re-excisions or conversion mastectomy), and increased detection of synchronous contralateral breast cancer, we recommend that preoperative breast MRI should be considered on a case-by-case basis in patients diagnosed with breast cancer for whom additional information about disease extent could influence treatment. Based on stronger evidence, preoperative breast MRI is recommended in patients diagnosed with invasive lobular carcinoma for whom additional information about disease extent could influence treatment. For both recommendations, the decision to proceed with MRI would be conditional on shared decision-making between care providers and the patient, taking into account the benefits and risks of MRI as well as patient preferences. Based on the opinion of the Working Group, preoperative breast MRI is also recommended in the following more specific situations: (a) to aid in surgical planning of breast conserving surgery in patients with suspected or known multicentric or multifocal disease; (b) to identify additional lesions in patients with dense breasts; (c) to determine the presence of pectoralis major muscle/chest wall invasion in patients with posteriorly located tumours or when invasion of the pectoralis major muscle or chest wall is suspected; (d) to aid in surgical planning for skin/nipple-sparing mastectomies, autologous reconstruction, oncoplastic surgery, and breast conserving surgery with suspected nipple/areolar involvement; and (e) in patients with familial/hereditary breast cancer but who have not had recent breast MRI as part of screening or diagnosis.

The Fallacies of the Breast MRI: A Case Study

Magnetic resonance imaging (MRI) of breasts using diffusion-weighted imaging and dynamic contrast enhancement is now well-established imaging for the evaluation and characterization of suspicious breast lesions, where it has become a problem-solving tool. Breast lesions are characterized according to their morphological features and enhancement characteristics. Breast MRI is helpful in the evaluation of breast lesions in patients with dense breasts and women with breast implants and to differentiate scars and recurrence. However, this technique has its own limitations, a few of which are elucidated in the present case report.

Evaluation of breast lesions based on modified BI-RADS using high-resolution readout-segmented diffusion-weighted echo-planar imaging and T2/T1-weighted image

PURPOSE

To evaluate the diagnostic performance of a non-contrast magnetic resonance imaging (MRI) protocol combining high-resolution diffusion-weighted images (HR-DWI) using readout-segmented echo planar imaging, T1-weighted imaging (T1WI), and T2-weighted imaging (T2WI), using our modified Breast Imaging-Reporting and Data System (modified BI-RADS).

METHODS

Two experienced radiologists, blinded to the final pathological diagnosis, categorized a total of 108 breast lesions (61 malignant and 47 benign) acquired with the above protocol using the modified BI-RADS with a diagnostic decision tree. The decision tree included subcategories of category 4, as in mammography (categories 2, 3, 4A, 4B, 4C, and 5). These results were compared with the pathological diagnoses.

RESULTS

The area under the ROC curve (AUC) was 0.89 (95% confidence interval [CI]: 0.83-0.95) for reader 1, and 0.89 (95% CI: 0.82-0.96) for reader 2. When categories 4C and above were classified as malignant, the sensitivity, specificity, and accuracy were 73.8%, 93.6%, and 82.4%, for reader 1; and 82.0%, 89.4%, and 85.2% for reader 2, respectively.

CONCLUSION

Our results suggest that using HR-DWI, T1WI/T2WI analyzed with a modified BI-RADS and a decision tree showed promising diagnostic performance in breast lesions, and is worthy of further study.

Advanced Diffusion-Weighted Imaging Sequences for Breast MRI: Comprehensive Comparison of Improved Sequences and Ultra-High B-Values to Identify the Optimal Combination

This study investigated the image quality and choice of ultra-high b-value of two DWI breast-MRI research applications. The study cohort comprised 40 patients (20 malignant lesions). In addition to s-DWI with two m-b-values (b50 and b800) and three e-b-values (e-b1500, e-b2000, and e-b2500), z-DWI and IR m-b1500 DWI were applied. z-DWI was acquired with the same measured b-values and e-b-values as the standard sequence. For IR m-b1500 DWI, b50 and b1500 were measured, and e-b2000 and e-b2500 were mathematically extrapolated. Three readers used Likert scales to independently analyze all ultra-high b-values (b1500-b2500) for each DWI with regards to scan preference and image quality. ADC values were measured in all 20 lesions. z-DWI was the most preferred (54%), followed by IR m-b1500 DWI (46%). b1500 was significantly preferred over b2000 for z-DWI and IR m-b1500 DWI (p = 0.001 and p = 0.002, respectively). Lesion detection was not significantly different among sequences or b-values (p = 0.174). There were no significant differences in measured ADC values within lesions between s-DWI (ADC: 0.97 [±0.09] × 10^-3 mm²/s) and z-DWI (ADC: 0.99 [±0.11] × 10^-3 mm²/s; p = 1.000). However, there was a trend toward lower values in IR m-b1500 DWI (ADC: 0.80 [±0.06] × 10^-3 mm²/s) than in s-DWI (p = 0.090) and z-DWI (p = 0.110). Overall, image quality was superior and there were fewer image artifacts when using the advanced sequences (z-DWI + IR m-b1500 DWI) compared with s-DWI. Considering scan preferences, we found that the optimal combination was z-DWI with a calculated b1500, especially regarding examination time.

Diagnostic performance of DCE-MRI, multiparametric MRI and multimodality imaging for discrimination of breast non-mass-like enhancement lesions

OBJECTIVE

The aim of this study was to investigate and compare the diagnostic performance of dynamic contrast-enhanced (DCE)-MRI, multiparametric MRI (mpMRI), and multimodality imaging (MMI) combining mpMRI and mammography (MG) for discriminating breast non-mass-like enhancement (NME) lesions.

METHODS

This retrospective study enrolled 193 patients with 199 lesions who underwent 3.0 T MRI and MG from January 2017 to December 2019. The features of DCE-MRI, turbo inversion recovery magnitude (TIRM), and diffusion-weighted imaging (DWI) were assessed by two breast radiologists. Then, all lesions were divided into microcalcification and non-microcalcification groups to assess the features of MG. Comparisons were performed between groups using univariate analyses. Then, multivariate analyses were performed to construct diagnostic models for distinguishing NME lesions. Diagnostic performance was evaluated by using the area under the curve (AUC) and the differences between AUCs were evaluated by using the DeLong test.

RESULTS

Overall (n = 199), mpMRI outperformed DCE-MRI alone (AUCmpMRI = 0.924 vs. AUCDCE-MRI = 0.884; p = 0.007). Furthermore, MMI outperformed both mpMRI and MG (the microcalcification group [n = 140]: AUCMMI = 0.997 vs. AUCmpMRI = 0.978, p = 0.018 and AUCMMI = 0.997 vs. AUCMG = 0.912, p < 0.001; the non-microcalcification group [n = 59]: AUCMMI = 0.857 vs. AUCmpMRI = 0.768, p = 0.044 and AUCMMI = 0.857 vs. AUCMG = 0.759, p = 0.039).

CONCLUSION & ADVANCES IN KNOWLEDGE

DCE-MRI combined with DWI and TIRM information could improve the diagnostic performance for discriminating NME lesions compared with DCE-MRI alone. Furthermore, MMI combining mpMRI and MG showed better discrimination than both mpMRI and MG.

Comparison between second-look ultrasound and second-look digital breast tomosynthesis in the detection of additional lesions with presurgical CESM

OBJECTIVES

To compare second-look ultrasound (SL-ultrasound) with second-look digital breast tomosynthesis (SL-DBT) in the detection of additional lesions (ALs) with presurgical contrast-enhanced spectral mammography (CESM).

METHODS

We retrospectively included 121 women with 128 ALs from patients who underwent CESM for presurgical staging at our centre from September 2016 to December 2018. These ALs underwent SL-ultrasound and a retrospective review of DBT (SL-DBT) performed 1-3 weeks prior to CESM to evaluate the performance of each technique individually and in combination. ALs in CESM images were evaluated according to enhancement type (focus, mass, or non-mass), size (<10 mm or >10 mm) and level of suspicion (BI-RADS 2, 3, 4 or 5). Our gold-standard was post-biopsy histology, post-surgical specimen or >24 month negative follow-up. McNemar's test was used for the statistical analysis.

RESULTS

Out of the 128 ALs, an imaging correlate was found for 71 (55.5 %) with ultrasound, 79 (61.7%) with DBT, 53 (41.4 %) with DBT and ultrasound, and 97 (75.8%) with ultrasound and/or DBT. SL-DBT demonstrated a higher detection rate vs SL-ultrasound in non-mass enhancement (NME) pattern (p: 0.0325) and ductal carcinoma in situ histological type (p: 0.0081). Adding SL-DBT improved the performance vs SL-ultrasound alone in the overall sample (p: <0.0001) and in every subcategory identified; adding SL-ultrasound to SL-DBT improved the detectability of ALs in the overall sample and in every category except for NME (p: 0.0833), foci (p: 0.0833) and B3 lesions (p: 0.3173).

CONCLUSION

Combined second-look imaging (SL-DBT+ SL-ultrasound) for CESM ALs is superior to SL-DBT alone and SL-ultrasound alone. In B3 lesions, NME, and foci, the analysis of a larger sample could determine whether adding SL-ultrasound to SL-DBT is necessary or not.

ADVANCES IN KNOWLEDGE

Thanks to its high sensitivity, CESM is a useful tool in presurgical staging to detect the extent of the disease burden and identify ALs not detected with conventional imaging. Since CESM-guided biopsy systems are still scarcely available in clinical practice, it is necessary to look for other approaches to histologically characterize ALs detected with CESM. In our study, combined second-look imaging (SL-DBT + SL-ultrasound) showed better performance in terms of detectability of ALs, than either SL-DBT or SL-ultrasound alone, and allowed us to identify 91.2% of ALs that turned out to be malignant at final histology; for the remaining 8.8% it was still necessary to perform MRI or MRI-guided biopsy. However, this issue could be solved once CESM-guided biopsies spread in clinical practice. SL-DBT demonstrated a higher detection rate than SL-ultrasound in NME and ductal carcinoma in situ histology.

Non-mass enhancement breast lesions: MRI findings and associations with malignancy

Background

Magnetic resonance imaging (MRI) is a multi-sequence imaging technique. Although MRI is the most sensitive method for detecting breast cancer, it is limited in evaluating the malignant possibility of non-mass enhanced (NME) breast lesions. It is also rarely reported whether MRI can further indicate the invasion of the lesions. In this article, we explore the differentiation of MRI characteristics between benign and malignant NME lesions and determine which features are associated with invasion.

Methods

The MRI findings of 118 NME lesions were evaluated retrospectively to explore the characteristics of the benign and malignant NME lesions in different MRI sequences including dynamic contrast-enhanced (DCE) MRI and diffusion-weighted imaging (DWI). The difference of MRI findings between benign and malignant NME lesions were determined by Pearson χ2 test or Fisher's exact test, and the diagnostic value of features for malignancy was evaluated by receiver operating characteristic (ROC) curve.

Results

This study included 118 NME lesions (62 benign and 56 malignant) in 118 patients. We found a segmental distribution, clustered-ring enhancement, wash-out dynamic curve, and lower apparent diffusion coefficient (ADC) value (P=0.01, <0.001, 0.02, 0.001) were associated with malignancy. Wash-out dynamic curves, diffusion restriction on DWI, lower ADC values were more advantageous in distinguishing invasive NME cancer from benign lesions than ductal carcinoma in situ (DCIS) (P<0.001, <0.001, 0.027). Further analysis showed that there were statistical differences between invasive carcinoma and carcinoma in situ in terms of wash-out dynamic curves, diffusion restriction on DWI and lower ADC values (P=0.001, 0.014, 0.024).

Conclusions

MRI is a valuable way to identify malignant NME lesions and could predict the invasion of the lesions. Compared with carcinoma in situ, some sequences have more advantages in distinguishing invasive carcinoma from benign lesions.

Added value of contrast-enhanced spectral mammogram in assessment of suspicious microcalcification and grading of DCIS

Background

Breast microcalcifications are one of the most difficult mammographic findings to assess. The purpose of this study is to assess the ability of contrast-enhanced spectral mammography in the assessment of suspicious microcalcification and in predicting the grade of DCIS.

Methods

Three hundred and forty cases with suspicious microcalcification were reviewed in this study. We excluded 160 cases associated with masses. We enrolled 180 cases for analysis of suspicious microcalcification on mammograms with no underlying masses. We reviewed the microcalcification for their morphology, distribution, and associated pathological enhancement according to BI-RADS lexicon with pathology results reviewed and classified into benign and malignant which subdivided into low, intermediate, or high-grade DCIS or invasive carcinoma.

Results

Three hundred and forty cases with suspicious microcalcification were reviewed in this study. We excluded 160 cases associated with masses. Forty-five of 180 cases were benign, and 135/180 cases were malignant. Twenty-five of 135 cases were diagnosed as invasive breast carcinomas while 110/135 were ductal carcinoma in situ. From the latter, 110 patients with DCIS, 22/110 cases were low grade, 11/110 cases were intermediate grade, and 77/110 cases were high grade (44 with micro-invasion). A total of 25 invasive carcinomas showed pathological non-mass enhancement, 76/77 cases of high-grade DCIS, and 6/11 cases of intermediate-grade DCIS. No abnormal enhancement appeared with benign entities, low-grade DCIS, and 5/11 cases of intermediate DCIS. The diagnostic performance of CESM in anticipation of high grade in DCIS patients was sensitivity of 98%, specificity of 81.8%, and accuracy of 93.1%. CESM sensitivity, specificity, and accuracy in prediction of invasiveness or high-grade DCIS were 98.5%, 81.8%, and 87.5%, respectively.

Conclusion

CESM can provide a fundamental contribution in the evaluation of suspicious microcalcification as high-grade DCIS or invasive component can present by non-mass enhancement, but enhancement paucity is favorable to diagnose benign lesion or non-invasive/low-grade DCIS.

Value of breast MRI omics features and clinical characteristics in Breast Imaging Reporting and Data System (BI-RADS) category 4 breast lesions: an analysis of radiomics-based diagnosis

Background

The Breast Imaging Reporting and Data System (BI-RADS) category 4 breast lesions is categorized into 4A, 4B, and 4C, which reflect an increasing malignancy potential from low (2–10%) moderate (10–50%) and high (50–95%). Determining the benign and malignant of BI-RADS category 4 breast lesions is very important for accurate diagnosis and follow-up treatment. This study aimed to explore the value of breast magnetic resonance imaging (MRI) omics features and clinical characteristics in the assessment of BI-RADS category 4 breast lesions.

Methods

This retrospective study analyzed 96 lesions (39 benign and 57 malignant) from 92 patients diagnosed with MRI BI-RADS category 4 lesions in the Second Affiliated Hospital of Dalian Medical University between May 2017 and December 2019. The lesions were sub-categorized as BI-RADS 4A, 4B, or 4C based on the MRI findings. An imaging omics analysis model was applied to extract the MRI features. The positive predictive value (PPV) of each subcategory was calculated, and the area under the curve (AUC) was used to describe the efficiency for different diagnoses. Moreover, we analyzed 17 clinical indicators to assess their diagnostic value for BI-RADS category 4 breast lesions.

Results

The PPVs of BI-RADS 4A, 4B, and 4C were 7.1% (2/28), 41.2% (7/17), and 94.1% (48/51), respectively. The AUC, sensitivity, and specificity were 0.919, 84.2%, and 92.3%, respectively. The combination of T₁-weighted images (T₁WI) with dynamic contrast-enhanced (DCE) MRI yielded the best diagnostic results among all dual sequences. Two clinical indicators [progesterone receptor (PR) and Ki-67 expression] achieved an AUC almost equal to 1.0. The radiomics and redundancy reduction methods reduced the clinical data features from 1,233 to 14.

Conclusions

High diagnostic performance can be achieved in distinguishing malignant breast BI-RADS category 4 lesions using the combination of T₁WI and DCE in MRI. Combining the PR and Ki-67 expression variables can further improve MRI accuracy for breast BI-RADS category 4 lesions.

Diffusion weighted imaging for evaluation of breast lesions: Comparison between high b-value single-shot and routine readout-segmented sequences at 3 T

PURPOSE

In this study, we compare readout-segmented echo-planar imaging (rs-EPI) Diffusion Weighted Imaging (DWI) to a work-in-progress single-shot EPI with modified Inversion Recovery Background Suppression (ss-EPI-mIRBS) sequence at 3 T using a b-value of 2000 s/mm² on image quality, lesion visibility and evaluation time.

METHOD

From September 2017 to December 2018, 23 women (one case used for training) with known breast cancer were included in this study, after providing signed informed consent. Women were scanned with the conventional rs-EPI sequence and the work-in-progress ss-EPI-mIRBS during the same examination. Four breast radiologists (4-13 years of experience) independently scored both series for overall image quality (1: extremely poor to 9: excellent). All lesions (47 in total, 36 malignant, and 11 benign and high-risk) were evaluated for visibility (1: not visible, 2: visible if location is given, 3: visible) and probability of malignancy (BI-RADS 1 to 5). ADC values were determined by measuring signal intensity in the lesions using dynamic contrast-enhanced (DCE) images for reference. Evaluation times for all assessments were automatically recorded. Results were analyzed using the visual grading characteristics (VGC) and the resulting area under the curve (AUC_VGC) method. Statistical analysis was performed in SPSS, with McNemar tests, and paired t-tests used for comparison.

RESULTS

No significant differences were detected between the two sequences in image quality (AUC_VGC: 0.398, p = 0.087) and lesion visibility (AUC_VGC: 0.534, p = 0.336) scores. Lesion characteristics (e.g benign and high-risk, versus malignant; small (≤10 mm) vs. larger (>10 mm)) did not result in different image quality or lesion visibility between sequences. Sensitivity (rs-EPI: 72.2% vs. ss-EPImIRBS: 78.5%, p = 0.108) and specificity (70.5% vs. 56.8%, p = 0.210, respectively) were comparable. In both sequences the mean ADC value was higher for benign and high-risk lesions than for malignant lesions (ss-EPI-mIRBS: p = 0.022 and rs-EPI: p = 0.055). On average, ss-EPI-mIRBS resulted in decreased overall reading time by 7.7 s/case (p = 0.067); a reduction of 17%. For malignant lesions, average reading time was significantly shorter using ss-EPI-mIRBS compared to rs-EPI (64.0 s/lesion vs. 75.9 s/lesion, respectively, p = 0.039).

CONCLUSION

Based on this study, the ss-EPI sequence using a b-value of 2000 s/mm² enables for a mIRBS acquisition with quality and lesion conspicuity that is comparable to conventional rs-EPI, but with a decreased reading time.

Additive value of texture analysis based on breast MRI for distinguishing between benign and malignant non-mass enhancement in premenopausal women

BACKGROUND

Non-mass enhancement (NME) is a diagnostic dilemma and highly reliant on the experience of the radiologists. Texture analysis (TA) could serve as an objective method to quantify lesion characteristics. However, it remains unclear what role TA plays in a predictive model based on routine MRI characteristics. The purpose of this study was to explore the value of TA in distinguishing between benign and malignant NME in premenopausal women.

METHODS

Women in whom NME was histologically proven (n = 147) were enrolled (benign: 58; malignant: 89) was retrospective. Then, 102 and 45 patients were classified as the training and validation groups, respectively. Scanning sequences included Fat-suppressed T2-weighted and fat-suppressed contrast-enhanced T1-weighted which were acquired on a 1.5T MRI system. Clinical and routine MR characteristics (CRMC) were evaluated by two radiologists according to the Breast Imaging and Reporting and Data system (2013). Texture features were extracted from all post-contrast sequences in the training group. The combination model was built and then assessed in the validation group. Pearson's chi-square test and Mann-Whitney U test were used to compare categorical variables and continuous variables, respectively. Logistic regression analysis and receiver operating characteristic curve were employed to assess the diagnostic performance of CRMC, TA, and their combination model in NME diagnosis.

RESULTS

The combination model showed superior diagnostic performance in differentiating between benign and malignant NME compared to that of CRMC or TA alone (AUC, 0.887 vs 0.832 vs 0.74). Moreover, compared to CRMC, the model showed high specificity (72.5% vs 80%). The results obtained in the validation group confirmed the model was promising.

CONCLUSIONS

With the combined use of TA and CRMC could afford an improved diagnostic performance in differentiating between benign and malignant NME.

Comparison of simultaneous multi-slice single-shot DWI to readout-segmented DWI for evaluation of breast lesions at 3T MRI

PURPOSE

To compare diffusion-weighted imaging of the breast performed with a conventional readout-segmented echo-planar imaging (rs-EPI) sequence to when using a prototype simultaneous multi-slice single-shot EPI (SMS-ss-EPI) acquisition.

METHOD

From September 2017 to December 2018, 26 women with histologically proven breast cancer were scanned with the conventional rs-EPI and the SMS-ss-EPI at 3 T during the same imaging examination. Four breast radiologists (4-13 years of experience) independently scored both acquired series of 25 women (one case was used for training) for overall image quality (1: extremely poor to 9: excellent) and artifacts (1: very disturbing to 5: not present). All lesions (n = 52; 40 malignant, 12 benign) were also evaluated for visibility (1: not visible, 2: visible if location is given, 3: visible). In addition, lesion characteristics were rated, and a BI-RADS score was given. Results were analyzed using visual grading characteristics and the resulting area under the curve (AUC_VGC), weighted kappa, McNemar test, and dependent-samples t-test when appropriate.

RESULTS

Overall, radiologists significantly preferred the image quality in rs-EPI over that of SMS-ss-EPI (AUC_VGC: 0.698, P = 0.002). Infolding and ghosting, and distortion artifacts were significantly less apparent in the rs-EPI (AUC_VGC: 0.660, P = 0.022 and AUC_VGC: 0.700 P = 0.002, respectively). Lesions were, however, significantly better visible on the SMS-ss-EPI images (AUC_VGC: 0.427, P = 0.016). Malignant lesions had significantly higher visibility with SMS-ss-EPI (P = 0.035). Sensitivity and specificity were comparable between both sequences (P = 0.760 and P = 0.549, respectively).

CONCLUSIONS

Despite the perceived lower image quality and the increased presence of artifacts in the SMS-ss-EPI sequence, malignant lesions are better visualized using this sequence.

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.

[Kaiser score for diagnosis of breast lesions presenting as non-mass enhancement on MRI]

OBJECTIVE

To evaluate the diagnostic efficacy of Kaiser score for breast lesions presenting as non-mass enhancement.

METHODS

We collected data from patients with breast lesions presenting as non-mass enhancement on preoperative DCE-MRI between January, 2014 and June, 2019. All the cases were confirmed by surgical pathology or puncture biopsy. With pathology results as the gold standard, we evaluated the diagnostic efficacy of Kaiser score and MRI BI-RADS classification and the consistency between the diagnostic results by the two methods and the pathological results.

RESULTS

A total of 90 lesions were detected in 88 patients, including 28 benign lesions (31.1%) and 62 malignant lesions (68.9%). For diagnosis of the lesions, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy of Kaiser Score were 100%, 75%, 89.9%, 100% and 92%, as compared with 93.5%, 46.4%, 79.5%, 76.5% and 78.9% of MRI BI-RADS, respectively. The diagnostic specificity of Kaiser score was significantly higher than that of BI-RADS classification (P=0.021).

CONCLUSIONS

The Kaiser score system provides a diagnostic strategy for BI-RADS classification of breast lesions with non-mass enhancement and has a better diagnostic efficacy than BI-RADS classification alone. The use of Kaiser score can significantly improve the diagnostic specificity of such breast lesions for inexperienced radiologists.

Reliability of MRI tumor size measurements for minimal invasive treatment selection in small breast cancers

INTRODUCTION

Due to the shift towards minimal invasive treatment, accurate tumor size estimation is essential for small breast cancers. The purpose of this study was to determine the reliability of MRI-based tumor size measurements with respect to clinical, histological and radiomics characteristics in small invasive or in situ carcinomas of the breast to select patients for minimal invasive therapy.

MATERIALS AND METHODS

All consecutive cases of cT1 invasive breast carcinomas that underwent pre-operative MRI, treated in two hospitals between 2005 and 2016, were identified retrospectively from the Dutch cancer registry and cross-correlated with local databases. Concordance between MRI-based measurements and final pathological size was analyzed. The influence of clinical, histological and radiomics characteristics on the accuracy of MRI size measurements were analyzed.

RESULTS

Analysis included 343 cT1 breast carcinomas in 336 patients (mean age, 55 years; range, 25-81 years). Overall correlation of MRI measurements with pathology was moderately strong (ρ = 0.530, P < 0.001), in 42 cases (12.2%) MRI underestimated the size with more than 5 mm. Underestimation occurs more often in grade 2 and grade 3 disease than in low grade invasive cancers. In DCIS the frequency of underestimation is higher than in invasive breast cancer. Unfortunately, none of the patient, imaging or biopsy characteristics appeared predictive for underestimation.

CONCLUSION

Size measurements of small breast cancers on breast MRI are within 5 mm of pathological size in 88% of patients. Nevertheless, underestimation cannot be adequately predicted, particularly for grade 2 and grade 3 tumors, which may hinder patient selection for minimal invasive therapy.

Magnetic Resonance Imaging Texture Analysis in Differentiating Benign and Malignant Breast Lesions of Breast Imaging Reporting and Data System 4: A Preliminary Study

RATIONALE AND OBJECTIVES

This novel study aims to investigate texture parameters in distinguishing malignant and benign breast lesions classified as Breast Imaging Reporting and Data System 4 in dynamic contrast-enhanced magnetic resonance imaging (MRI).

MATERIALS AND METHODS

This retrospective study included 203 patients with 136 breast cancer and 67 benign lesions who underwent breast MRI between November 23, 2016, and August 27, 2018. Co-occurrence matrix-based texture features were extracted from each lesion on T1-weighted contrast-enhanced MRI using MatLab software. The association between texture parameters and breast lesions was analyzed, and the diagnostic model for breast cancer was created. Classification performance was evaluated by the area under the receiver operating characteristic curve, sensitivity, and specificity.

RESULTS

Significant differences were seen between malignant and benign lesions for a number of textural features, including contrast, correlation, autocorrelation, dissimilarity, cluster shade, and cluster performance (P < 0.05). After the analysis of the multicollinearity, 5 texture features (contrast, correlation, dissimilarity, cluster shade, and cluster performance) were included for the next principal component analysis. The differentiation accuracy of breast cancer based on the diagnostic model was 0.948 (95% confidence interval, 0.908-0.974).

CONCLUSIONS

Texture features that measure randomness, heterogeneity, or homogeneity may reflect underlying growth patterns of breast lesions and show great difference in malignant and benign lesions. Therefore, texture analysis may be a valuable assisted tool for diagnostic analysis on breast.

Differentiating benign and malignant mass and non-mass lesions in breast DCE-MRI using normalized frequency-based features

PURPOSE

In this study, we propose a new computer-aided diagnosis (CADx) to distinguish between malign and benign mass and non-mass lesions in breast DCE-MRI. For this purpose, we introduce new frequency textural features.

METHODS

In this paper, we propose novel normalized frequency-based features. These are obtained by applying the dual-tree complex wavelet transform to MRI slices containing a lesion for specific decomposition levels. The low-pass and band-pass frequency coefficients of the dual-tree complex wavelet transform represent the general shape and texture features, respectively, of the lesion. The extraction of these features is computationally efficient. We employ a support vector machine to classify the lesions, and investigate modified cost functions and under- and oversampling strategies to handle the class imbalance.

RESULTS

The proposed method has been tested on a dataset of 80 patients containing 103 lesions. An area under the curve of 0.98 for the mass and 0.94 for the non-mass lesions is obtained. Similarly, accuracies of 96.9% and 89.8%, sensitivities of 93.8% and 84.6% and specificities of 98% and 92.3% are obtained for the mass and non-mass lesions, respectively.

CONCLUSION

Normalized frequency-based features can characterize benign and malignant lesions efficiently in both mass- and non-mass-like lesions. Additionally, the combination of normalized frequency-based features and three-dimensional shape descriptors improves the CADx performance.

Amount of fibroglandular tissue FGT and background parenchymal enhancement BPE in relation to breast cancer risk and false positives in a breast MRI screening program : A retrospective cohort study

Objectives

The purpose of this study is to evaluate the predictive value of the amount of fibroglandular tissue (FGT) and background parenchymal enhancement (BPE), measured at baseline on breast MRI, for breast cancer development and risk of false-positive findings in women at increased risk for breast cancer.

Methods

Negative baseline MRI scans of 1533 women participating in a screening program for women at increased risk for breast cancer between January 1, 2003, and January 1, 2014, were selected. Automated tools based on deep learning were used to obtain quantitative measures of FGT and BPE. Logistic regression using forward selection was used to assess relationships between FGT, BPE, cancer detection, false-positive recall, and false-positive biopsy.

Results

Sixty cancers were detected in follow-up. FGT was only associated to short-term cancer risk; BPE was not associated with cancer risk. High FGT and BPE did lead to more false-positive recalls at baseline (OR 1.259, p = 0.050, and OR 1.475, p = 0.003) and to more frequent false-positive biopsies at baseline (OR 1.315, p = 0.049, and OR 1.807, p = 0.002), but were not predictive for false-positive findings in subsequent screening rounds.

Conclusions

FGT and BPE, measured on baseline MRI, are not predictive for overall breast cancer development in women at increased risk. High FGT and BPE lead to more false-positive findings at baseline.

Key Points

• Amount of fibroglandular tissue is only predictive for short-term breast cancer risk in women at increased risk.

• Background parenchymal enhancement measured on baseline MRI is not predictive for breast cancer development in women at increased risk.

• High amount of fibroglandular tissue and background parenchymal enhancement lead to more false-positive findings at baseline MRI.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06020-2) contains supplementary material, which is available to authorized users.

Magnetic resonance imaging and molecular features associated with tumor-infiltrating lymphocytes in breast cancer

Background

We sought to investigate associations between dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) features and tumor-infiltrating lymphocytes (TILs) in breast cancer, as well as to study if MRI features are complementary to molecular markers of TILs.

Methods

In this retrospective study, we extracted 17 computational DCE-MRI features to characterize tumor and parenchyma in The Cancer Genome Atlas cohort (n = 126). The percentage of stromal TILs was evaluated on H&E-stained histological whole-tumor sections. We first evaluated associations between individual imaging features and TILs. Multiple-hypothesis testing was corrected by the Benjamini-Hochberg method using false discovery rate (FDR). Second, we implemented LASSO (least absolute shrinkage and selection operator) and linear regression nested with tenfold cross-validation to develop an imaging signature for TILs. Next, we built a composite prediction model for TILs by combining imaging signature with molecular features. Finally, we tested the prognostic significance of the TIL model in an independent cohort (I-SPY 1; n = 106).

Results

Four imaging features were significantly associated with TILs (P < 0.05 and FDR < 0.2), including tumor volume, cluster shade of signal enhancement ratio (SER), mean SER of tumor-surrounding background parenchymal enhancement (BPE), and proportion of BPE. Among molecular and clinicopathological factors, only cytolytic score was correlated with TILs (ρ = 0.51; 95% CI, 0.36–0.63; P = 1.6E-9). An imaging signature that linearly combines five features showed correlation with TILs (ρ = 0.40; 95% CI, 0.24–0.54; P = 4.2E-6). A composite model combining the imaging signature and cytolytic score improved correlation with TILs (ρ = 0.62; 95% CI, 0.50–0.72; P = 9.7E-15). The composite model successfully distinguished low vs high, intermediate vs high, and low vs intermediate TIL groups, with AUCs of 0.94, 0.76, and 0.79, respectively. During validation (I-SPY 1), the predicted TILs from the imaging signature separated patients into two groups with distinct recurrence-free survival (RFS), with log-rank P = 0.042 among triple-negative breast cancer (TNBC). The composite model further improved stratification of patients with distinct RFS (log-rank P = 0.0008), where TNBC with no/minimal TILs had a worse prognosis.

Conclusions

Specific MRI features of tumor and parenchyma are associated with TILs in breast cancer, and imaging may play an important role in the evaluation of TILs by providing key complementary information in equivocal cases or situations that are prone to sampling bias.

Electronic supplementary material

The online version of this article (10.1186/s13058-018-1039-2) contains supplementary material, which is available to authorized users.

The added value of mammography in different age-groups of women with and without BRCA mutation screened with breast MRI

Background

Breast magnetic resonance imaging (MRI) is the most sensitive imaging method for breast cancer detection and is therefore offered as a screening technique to women at increased risk of developing breast cancer. However, mammography is currently added from the age of 30 without proven benefits. The purpose of this study is to investigate the added cancer detection of mammography when breast MRI is available, focusing on the value in women with and without BRCA mutation, and in the age groups above and below 50 years.

Methods

This retrospective single-center study evaluated 6553 screening rounds in 2026 women at increased risk of breast cancer (1 January 2003 to 1 January 2014). Risk category (BRCA mutation versus others at increased risk of breast cancer), age at examination, recall, biopsy, and histopathological diagnosis were recorded. Cancer yield, false positive recall rate (FPR), and false positive biopsy rate (FPB) were calculated using generalized estimating equations for separate age categories (< 40, 40–50, 50–60, ≥ 60 years). Numbers of screens needed to detect an additional breast cancer with mammography (NSN) were calculated for the subgroups.

Results

Of a total of 125 screen-detected breast cancers, 112 were detected by MRI and 66 by mammography: 13 cancers were solely detected by mammography, including 8 cases of ductal carcinoma in situ. In BRCA mutation carriers, 3 of 61 cancers were detected only on mammography, while in other women 10 of 64 cases were detected with mammography alone. While 77% of mammography-detected-only cancers were detected in women ≥ 50 years of age, mammography also added more to the FPR in these women. Below 50 years the number of mammographic examinations needed to find an MRI-occult cancer was 1427.

Conclusions

Mammography is of limited added value in terms of cancer detection when breast MRI is available for women of all ages who are at increased risk. While the benefit appears slightly larger in women over 50 years of age without BRCA mutation, there is also a substantial increase in false positive findings in these women.

The correlation of background parenchymal enhancement in the contralateral breast with patient and tumor characteristics of MRI-screen detected breast cancers

PURPOSE

Higher background parenchymal enhancement (BPE) could be used for stratification of MRI screening programs since it might be related to a higher breast cancer risk. Therefore, the purpose of this study is to correlate BPE to patient and tumor characteristics in women with unilateral MRI-screen detected breast cancer who participated in an intermediate and high risk screening program. As BPE in the affected breast may be difficult to discern from enhancing cancer, we assumed that BPE in the contralateral breast is a representative measure for BPE in women with unilateral breast cancer.

MATERIALS AND METHODS

This retrospective study was approved by our local institutional board and a waiver for consent was granted. MR-examinations of women with unilateral breast cancers screen-detected on breast MRI were evaluated by two readers. BPE in the contralateral breast was rated according to BI-RADS. Univariate analyses were performed to study associations. Observer variability was computed.

RESULTS

Analysis included 77 breast cancers in 76 patients (age: 48±9.8 years), including 62 invasive and 15 pure ductal carcinoma in-situ cases. A negative association between BPE and tumor grade (p≤0.016) and a positive association with progesterone status (p≤0.021) was found. The correlation was stronger when only considering invasive disease. Inter-reader agreement was substantial.

CONCLUSION

Lower BPE in the contralateral breast in women with unilateral breast cancer might be associated to higher tumor grade and progesterone receptor negativity. Great care should be taken using BPE for stratification of patients to tailored screening programs.

Heterogeneous Enhancement Patterns of Tumor-adjacent Parenchyma at MR Imaging Are Associated with Dysregulated Signaling Pathways and Poor Survival in Breast Cancer

Purpose To identify the molecular basis of quantitative imaging characteristics of tumor-adjacent parenchyma at dynamic contrast material-enhanced magnetic resonance (MR) imaging and to evaluate their prognostic value in breast cancer. Materials and Methods In this institutional review board-approved, HIPAA-compliant study, 10 quantitative imaging features depicting tumor-adjacent parenchymal enhancement patterns were extracted and screened for prognostic features in a discovery cohort of 60 patients. By using data from The Cancer Genome Atlas (TCGA), a radiogenomic map for the tumor-adjacent parenchymal tissue was created and molecular pathways associated with prognostic parenchymal imaging features were identified. Furthermore, a multigene signature of the parenchymal imaging feature was built in a training cohort (n = 126), and its prognostic relevance was evaluated in two independent cohorts (n = 879 and 159). Results One image feature measuring heterogeneity (ie, information measure of correlation) was significantly associated with prognosis (false-discovery rate < 0.1), and at a cutoff of 0.57 stratified patients into two groups with different recurrence-free survival rates (log-rank P = .024). The tumor necrosis factor signaling pathway was identified as the top enriched pathway (hypergeometric P < .0001) among genes associated with the image feature. A 73-gene signature based on the tumor profiles in TCGA achieved good association with the tumor-adjacent parenchymal image feature (R² = 0.873), which stratified patients into groups regarding recurrence-free survival (log-rank P = .029) and overall survival (log-rank P = .042) in an independent TCGA cohort. The prognostic value was confirmed in another independent cohort (Gene Expression Omnibus GSE 1456), with log-rank P = .00058 for recurrence-free survival and log-rank P = .0026 for overall survival. Conclusion Heterogeneous enhancement patterns of tumor-adjacent parenchyma at MR imaging are associated with the tumor necrosis signaling pathway and poor survival in breast cancer. ^© RSNA, 2017 Online supplemental material is available for this article.

Preoperative MRI features associated with lymphovascular invasion in node-negative invasive breast cancer: A propensity-matched analysis

PURPOSE

In node-negative disease, the presence of lymphovascular invasion (LVI) is reported to be an unfavorable prognostic factor. Thus, the aim of this study was to evaluate whether preoperative breast MRI features are associated with LVI in patients with node-negative invasive breast cancer by a propensity-matched analysis.

MATERIALS AND METHODS

Among 389 patients with node-negative invasive ductal breast cancer who had preoperative breast 3.0 Tesla MRI with precontrast T2-weighted fat-suppressed, pre- and dynamic postcontrast T1-weighted fat-suppressed sequences, 61 patients with LVI (LVI group) were matched with 183 patients without LVI (no LVI group) at a ratio of 1:3 in terms of age, histologic grade, tumor size, and hormone receptor status. Two radiologists reviewed the MRI features, following profiles of focal breast edema (peritumoral, prepectoral, subcutaneous), intratumoral T2 signal intensity, adjacent vessel sign, and increased ipsilateral whole-breast vascularity, in addition to 2013 Breast Imaging Reporting and Data System lexicon.

RESULTS

The presence of peritumoral edema (45.9% [28/61] versus 30.6% [56/183], P = 0.030) and adjacent vessel sign (82.0% [50/61] versus 68.3% [125/183], P = 0.041) was significantly associated with LVI. Prepectoral edema was also more frequently observed in the LVI group than in the no LVI group with borderline significance (26.2% [16/61] versus 15.3% [28/183], P = 0.055). In cases of nonmass enhancement, regional enhancement was more frequently found in the LVI group than in the no LVI group (60.0% [3/4] versus 5.9% [1/4], P = 0.042).

CONCLUSION

Preoperative breast MRI features may be associated with LVI in patients with node-negative invasive breast cancer.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1037-1044.

Identifying relations between imaging phenotypes and molecular subtypes of breast cancer: Model discovery and external validation

PURPOSE

To determine whether dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) characteristics of the breast tumor and background parenchyma can distinguish molecular subtypes (ie, luminal A/B or basal) of breast cancer.

MATERIALS AND METHODS

In all, 84 patients from one institution and 126 patients from The Cancer Genome Atlas (TCGA) were used for discovery and external validation, respectively. Thirty-five quantitative image features were extracted from DCE-MRI (1.5 or 3T) including morphology, texture, and volumetric features, which capture both tumor and background parenchymal enhancement (BPE) characteristics. Multiple testing was corrected using the Benjamini-Hochberg method to control the false-discovery rate (FDR). Sparse logistic regression models were built using the discovery cohort to distinguish each of the three studied molecular subtypes versus the rest, and the models were evaluated in the validation cohort.

RESULTS

On univariate analysis in discovery and validation cohorts, two features characterizing tumor and two characterizing BPE were statistically significant in separating luminal A versus nonluminal A cancers; two features characterizing tumor were statistically significant for separating luminal B; one feature characterizing tumor and one characterizing BPE reached statistical significance for distinguishing basal (Wilcoxon P < 0.05, FDR < 0.25). In discovery and validation cohorts, multivariate logistic regression models achieved an area under the receiver operator characteristic curve (AUC) of 0.71 and 0.73 for luminal A cancer, 0.67 and 0.69 for luminal B cancer, and 0.66 and 0.79 for basal cancer, respectively.

CONCLUSION

DCE-MRI characteristics of breast cancer and BPE may potentially be used to distinguish among molecular subtypes of breast cancer.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1017-1027.

Focal transitional mastitis in MR-Mammography: Preliminary findings

Purpose

During clinical routine, we retrospectively discovered diagnostic criteria for “focal mastitis” in MR-Mammography (MRM). The aim of this study was to prospectively evaluate these criteria.

Methods

1975 consecutive patients were examined between 01/2010 and 12/2011. 29 patients fit the diagnostic criteria of focal mastitis.

Results

In follow-up scans, 28 patients showed a complete remission of the previous findings. One patient was followed-up with persisting findings, which could histologically be correlated to an area of DCIS after biopsy.

Conclusion

The morphologic, kinetic and follow-up criteria we discovered seem to be a reliable diagnostic indicator for focal mastitis.

Concordance of BI-RADS Assessments and Management Recommendations for Breast MRI in Community Practice

OBJECTIVE

The purpose of this study was to evaluate concordance between BI-RADS assessments and management recommendations for breast MRI in community practice.

MATERIALS AND METHODS

Breast MRI data were collected from four regional Breast Cancer Surveillance Consortium registries from 2005 to 2011 for women who were 18-79 years old. Assessments and recommendations were compared to determine concordance according to BI-RADS guidelines. Concordance was compared by assessment category as well as by year of examination and clinical indication.

RESULTS

In all, 8283 MRI examinations were included in the analysis. Concordance was highest (93% [2475/2657]) in examinations with a BI-RADS category 2 (benign) assessment. Concordance was also high in examinations with category 1 (negative) (87% [1669/1909]), category 0 (incomplete) (83% [348/417]), category 5 (highly suggestive of malignancy) (83% [208/252]), and category 4 (suspicious) (74% [734/993]) assessments. Examinations with categories 3 (probably benign) and 6 (known biopsy-proven malignancy) assessments had the lowest concordance rates (36% [302/837] and 56% [676/1218], respectively). The most frequent discordant recommendation for a category 3 assessment was routine follow-up. The most frequent discordant recommendation for a category 6 assessment was biopsy. Concordance of assessments and management recommendations differed across clinical indications (p < 0.0001), with the lowest concordance in examinations to assess disease extent.

CONCLUSION

Breast MRI BI-RADS management recommendations were most concordant for assessments of negative, incomplete, suspicious, and highly suggestive of malignancy. Lower concordance for assessments of probably benign and known biopsy-proven malignancy and for examinations performed to assess disease extent highlight areas for interventions to improve breast MRI reporting.

Dynamic contrast-enhanced breast MRI at 7T and 3T: an intra-individual comparison study

The aim of this study is to compare the current state of lesion identification, the BI-RADS classification and the contrast-enhancement behavior at 7T and 3T breast MRI in the same patient group. Twenty-seven patients with thirty suspicious lesions were selected for this prospective study and underwent both 7T and 3T MRI. All examinations were rated by two radiologists (R1 and R2) independently on image quality, lesion identification and BI-RADS classification. We assessed sensitivity, specificity, NPV and PPV, observer agreement, lesion sizes, and contrast-enhancement-to-noise ratios (CENRs) of mass lesions. Fifteen of seventeen histopathological proven malignant lesions were detected at both field strengths. Image quality of the dynamic series was good at 7T, and excellent at 3T (P = 0.001 for R1 and P = 0.88 for R2). R1 found higher rates of specificity, NPV and PPV at 7T when compared to 3T, while R2 found the same results for sensitivity, specificity, NPV and PPV for both field strengths. The observers showed excellent agreement for BI-RADS categories at 7T (κ = 0.86) and 3T (κ = 0.93). CENRs were higher at 7T (P = 0.015). Lesion sizes were bigger at 7T according to R2 (P = 0.039). Our comparison study shows that 7T MRI allows BI-RADS conform analysis. Technical improvements, such as acquisition of T2w sequences and adjustment of B1+ field inhomogeneity, are still necessary to allow clinical use of 7T breast MRI.

Perirenal Edema as a potential hint towards primary hypertension—Preliminary findings in MRI breast cancer staging

Purpose

To demonstrate our primary findings, indicating perirenal edema as a first imaging sign towards primary hypertension.

Methods

Out of 3190 consecutive MR-Mammography (MRM) examinations, 777 were performed with an additional body array coil. Incidentally, “perirenal edema” could be linked to a patient history of hypertension. We Therefore specifically further observed the correlation.

Results

Of 777 patients 86 (11%) patients showed the perirenal edema sign (PES). Upon inquiry all of these cases (100%) confirmed a past or present history of hypertensive disease (i.e. blood pressure above 140/90 and/or anti-hypertensive treatment).

Conclusion

Our preliminary results strongly indicate a strong correlation between perirenal edema and primary hypertension.

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.

Breast Cancer: Influence of Taxanes on Response Assessment with Dynamic Contrast-enhanced MR Imaging

PURPOSE

To prospectively investigate the influence of taxane-containing neoadjuvant chemotherapy (T-NACT) versus non-taxane-containing NACT (NT-NACT) on the contrast material enhancement of breast cancers, benign enhancing lesions (BELs), and background parenchymal enhancement (BPE) at dynamic contrast-enhanced magnetic resonance (MR) imaging.

MATERIALS AND METHODS

This institutional review board-approved study was performed in 62 patients with invasive breast cancer who underwent multiagent NACT with (n = 49) or without (n = 13) taxanes between 2008 and 2011. Written informed consent was obtained. Patients underwent dynamic contrast-enhanced MR imaging according to a standardized protocol before and 2 weeks after completing NACT. The percentage reduction of enhancement of breast cancers, BELs, and BPEs was calculated for patients undergoing NT-NACT versus those undergoing T-NACT. Final surgical pathologic results served as standard of reference. Changes in mean enhancement of breast cancers, BELs, and BPEs between the regimens were compared by using the Student t test for unpaired samples; for intraindividual comparison, the Student t test for paired samples was used.

RESULTS

Similar rates of complete pathologic response were observed after T-NACT and NT-NACT (28 [57.2%] of 49 vs eight [61.5%] of 13). T-NACT was associated with an almost complete suppression of enhancement in not only breast cancers but also BELs and BPE in the same patients, with an average reduction of enhancement of -89.9% ± 9.3, -90.2% ± 11.8, and -91.2% ± 7.5, respectively. After T-NACT, cancers with partial (n = 21) or complete (n = 28) pathologic response exhibited a similar reduction of enhancement (-81.8% ± 17.5 vs -93.9% ± 2.3; P = .22). The reduction of enhancement of cancers after NT-NACT was significantly less pronounced than that after T-NACT (-41.1% ± 22.8 vs 88.1% ± 13.9; P < .0001), and effects on enhancement of BELs and BPE were significantly less pronounced compared with effects on enhancement of cancers in the same women (P < .0001). MR imaging led to an overestimation of response (yielded false-negative results for residual disease) in 66.7% (14 of 21) of patients after T-NACT, versus in 20% (one of five) of patients after NT-NACT.

CONCLUSION

The reduction of enhancement observed in breast cancers after T-NACT is, in part, unrelated to their oncologic response. MR imaging-detectable effects of taxanes represent a combination of specific antimitotic and nonspecific antiangiogenic effects. This impacts the accuracy with which dynamic contrast-enhanced MR imaging helps predict complete pathologic response to T-NACT. (©) RSNA, 2015 Online supplemental material is available for this article.

Background Parenchymal Enhancement of the Contralateral Normal Breast: Association with Tumor Response in Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

PURPOSE: This study investigated the association between background parenchymal enhancement (BPE) and pathologic response to neoadjuvant chemotherapy (NAC). METHODS: A total of 46 patients diagnosed with invasive breast cancer were analyzed. Each patient had three magnetic resonance imaging (MRI) studies, one pre-treatment and two follow-up (F/U) MRI studies. BPE was measured as the averaged enhancement of the whole fibroglandular tissues. The pre-treatment BPE and the changes in the F/U MRI were compared between patients achieving pathologic complete response (pCR) versus those not. Subgroup analyses based on age, estrogen receptor (ER), and human epidermal growth factor receptor 2 (HER2) status of their cancers were also performed. RESULTS: The pre-treatment BPE was higher in the pCR group than that in the non-pCR group. Compared to baseline, BPE at F/U-1 was significantly decreased in the pCR group but not in the non-pCR group. In subgroup analysis based on age, these results were seen only in the younger group (< 55 years old), not in the older group (≥ 55 years old). Older patients had a significantly lower pre-treatment BPE than younger patients. In analysis based on molecular biomarkers, a significantly decreased BPE at F/U-1 was only found in the ER-negative pCR group but not in the non-pCR, nor in the ER-positive groups. CONCLUSIONS: A higher pre-treatment BPE showing a significant decrease early after starting NAC was related to pCR in pre/peri-menopausal patients.

DCE-MRI of the breast in a stand-alone setting outside a complementary strategy - results of the TK-study

OBJECTIVES

To evaluate the accuracy of MRI of the breast (DCE-MRI) in a stand-alone setting with extended indications.

MATERIALS AND METHODS

According to the inclusion criteria, breast specialists were invited to refer patients to our institution for DCE-MRI. Depending on the MR findings, patients received either a follow-up or biopsy. Between 04/2006 and 12/2011 a consecutive total of 1,488 women were prospectively examined.

RESULTS

Of 1,488 included patients, 393 patients were lost to follow-up, 1,095 patients were evaluated. 124 patients were diagnosed with malignancy by DCE-MRI (76 TP, 48 FP, 971 TN, 0 FN cases). Positive cases were confirmed by histology, negative cases by MR follow-ups or patient questionnaires over the next 5 years in 1,737 cases (sensitivity 100 %; specificity 95.2 %; PPV 61.3 %; NPV 100 %; accuracy 95.5 %). For invasive cancers only (DCIS excluded), the results were 63 TP; 27 FP; 971 TP and 0 FN (sensitivity 100 %; specificity 97.2 %; PPV 70 %; NPV 100 %; accuracy 97.5 %).

CONCLUSION

The DCE-MRI indications tested imply that negative results in DCE-MRI reliably exclude cancer. The results were achieved in a stand-alone setting (single modality diagnosis). However, these results are strongly dependent on reader experience and adequate technical standards as prerequisites for optimal diagnoses.

KEY POINTS

• DCE-MRI of the breast has a high accuracy in finding breast cancer. • The set of indications for DCE-MRI of the breast is still very limited. • DCE-MRI can achieve a high accuracy in a 'screening-like' setting. • Accuracy of breast DCE-MRI is strongly dependent on technique and reader experience. • A negative DCE-MRI effectively excludes cancer.

Lesion type and reader experience affect the diagnostic accuracy of breast MRI: a multiple reader ROC study

PURPOSE

To evaluate the influence of lesion type (mass versus non-mass) and reader experience on the diagnostic performance of breast MRI (BMRI) in a non-screening setting.

MATERIALS AND METHODS

Consecutive patients (mean age, 55 ± 12 years) with breast lesions that were verified by biopsy or surgery, and who had had BMRI as part of their diagnostic workup, were eligible for this retrospective single-center study. Cancers diagnosed by biopsy before BMRI were excluded to eliminate biological and interpretation bias due to biopsy or chemotherapy effects (n=103). Six blinded readers (experience level, high (HE, n=2); intermediate (IE, n=2); and low (LE, n=2)) evaluated all examinations and assigned independent MRI BI-RADS ratings. Lesion type (mass, non-mass, focal) was noted. Receiver operating characteristics (ROC) and logistic regression analysis was performed to compare diagnostic accuracies.

RESULTS

There were 259 histologically verified lesions (123 malignant, 136 benign) investigated. There were 169 mass (103 malignant, 66 benign) and 48 non-mass lesions (19 malignant, 29 benign). Another 42 lesions that met the inclusion criteria were biopsied due to conventional findings (i.e., microcalcifications, architectural distortions), but did not enhance on MRI (41 benign, one DCIS). ROC analysis revealed a total area under the curve (AUC) between 0.834 (LE) and 0.935 (HI). Logistic regression identified a significant effect of non-mass lesions (P<0.0001) and reader experience (P=0.005) on diagnostic performance.

CONCLUSIONS

Non-mass lesion type and low reader experience negatively affect the diagnostic performance of breast MRI in a non-screening setting.

Auditing a breast MRI practice: performance measures for screening and diagnostic breast MRI

PURPOSE

Breast MRI is increasingly used for both screening and diagnostic purposes. Although performance benchmarks for screening and diagnostic mammography have been published, performance benchmarks for breast MRI have yet to be established. The purpose of this study was to comprehensively evaluate breast MRI performance measures, stratified by screening and diagnostic indications, from a single academic institution.

METHODS

Institutional review board approval was acquired for this HIPAA-compliant study. Informed consent was not required. Retrospective review of the institutional database identified all breast MRI examinations performed from April 1, 2007, to March 31, 2008. After application of exclusion criteria, the following performance measures for screening and diagnostic indications were calculated: cancer detection rate, positive predictive value (PPV), and abnormal interpretation rates.

RESULTS

The study included 2,444 examinations, 1,313 for screening and 1,131 for diagnostic indications. The cancer detection rates were 14 per 1,000 screening breast MRI examinations and 47 per 1,000 diagnostic examinations (P < .00001). The abnormal interpretation rate was 12% (152 of 1,313) for screening and 17% (194 of 1,131) for diagnostic indications (P = .00008). The PPVs of MRI were lower for screening [PPV1 (abnormal findings) = 12%, PPV2 (biopsy recommended) = 24%, PPV3 (biopsy performed) = 27%] compared with diagnostic indications (PPV1 (abnormal findings) = 28%, PPV2 (biopsy recommended) = 36%, PPV3 (biopsy performed) = 38%].

CONCLUSIONS

Breast MRI performance measures differ significantly between screening and diagnostic MRI indications. Medical audits for breast MRI should calculate performance measures for screening and diagnostic breast MRI separately, as recommended for mammography.

Breast implant-associated anaplastic large cell lymphoma: sensitivity, specificity, and findings of imaging studies in 44 patients

Breast implant-associated anaplastic large cell lymphoma (BIA ALCL) is a newly described clinicopathologic entity. The purpose of this study is to describe the imaging findings of patients with BIA ALCL and determine their sensitivity and specificity in the detection of the presence of an effusion or a mass related to BIA ALCL. A retrospective search was performed of our files as well as of the world literature for patients with pathologically proven BIA ALCL who had been assessed by any imaging study including ultrasound (US), computerized tomography (CT), magnetic resonance imaging (MRI), or positron emission tomography (PET)-CT, as well as mammography. The sensitivity and specificity of each imaging modality in the detection of an effusion or a mass around breast implants was determined. We identified 44 patients who had BIA ALCL and imaging studies performed between 1997 and 2013. The sensitivity for detecting an effusion was 84, 55, 82, and 38 %, and for detecting a mass was 46, 50, 50, and 64 %, by US, CT, MRI, and PET, respectively. The sensitivity of mammography in the detection of an abnormality without distinction of effusion or mass was 73 %, and specificity 50 %. Progression-free survival was worse in patients with an implant-associated mass (p = 0.001).

CONCLUSIONS

Current imaging with US, CT, MR, and PET appears suboptimal in the detection of an imaging abnormality associated with BIA ALCL. This under diagnosis may reflect a lack of awareness of this rare entity suggesting the need for better understanding of the spectrum of imaging findings associated with BIA ALCL by breast imagers.