Characteristics of ductal carcinoma in situ in magnetic resonance imaging

Ultrasound diagnosis of non-mass MRI-detected lesions

Magnetic resonance imaging (MRI)-detected lesions are often category 2 or 3 lesions on initial ultrasound examination. In addition, in the case of new non-mass lesions detected on MRI, one would expect to find lesions with ductal dilatation with minimal secretory accumulation, single short lesions with ductal dilatation, cyst-like lesions less than 5 mm in size, mammary gland-like lesions less than 8 mm in size, and very indistinct lesions. Detection is expected to be even more difficult. Currently, there are no clear uniform criteria for the indication of second-look ultrasonography (US) for MRI-detected lesions, so it is not possible to make a general comparison, but recent studies have indicated that the ratio of mass to non-mass MRI-detected lesions is 7:3. And it has been pointed out that the percentage of malignancy is about 30% for each. Before about 2012, the US detection rate was about 70%, and MRI-guided biopsies of undetected lesions showed a small percentage of malignant lesions. Therefore, some observers believe that lesions not detected on US should be followed up, while others believe that MRI-guided biopsy should be performed. Recently, however, the use of surrounding anatomical structures as landmarks for second-look US has increased the detection rate to as high as 87-99%, and the percentage of malignancy remains the same. In addition, recent surveillance of high-risk breast cancer requires careful management of MRI-detected lesions. In this review, we will discuss the literature on MRI-detected lesions and describe ultrasound techniques to accurately detect small lesions and reliably reveal pale lesions based on their structural differences from their surroundings.

An Unusual Presentation of Extensive Ductal Carcinoma in Situ Accompanying Invasive Ductal Carcinoma on MRI: A Case Report

The incidence of ductal carcinoma in situ has increased with the rise in screening mammography; currently, ductal carcinoma in situ constitutes 20%-25% of all breast cancers, and up to half of them may become invasive. Its early detection is critical in improving the cure rate. Moreover, MRI has higher sensitivity for its detection than mammography. Herein, we report an unusual case of ductal carcinoma in situ presenting as a continuous, serpentine, linear enhancement with regional distribution on MRI.

The characteristics associated with upgrade on surgical pathology of conventional imaging occult DCIS diagnosed by MRI

PURPOSE

To characterize the clinical, pathological, and imaging features of DCIS occult on conventional imaging diagnosed on MRI-guided biopsy associated with increased risk of invasive disease on surgical excision.

MATERIALS AND METHODS

All consecutive patients with MRI-detected DCIS occult on conventional imaging between January 2009 and December 2018 were included. Women were divided into two groups based on final pathology: Pure DCIS or DCIS with invasive component. Clinical, imaging, and pathological risk factors for upgrade to invasion were evaluated.

RESULTS

Of 50 patients who met the inclusion criteria, 12 (24%) were upgraded to invasive malignancy in the final pathology. The only parameters that showed statistically significant association with upgrade were related to kinetic characteristics: 53% of patients with the combination of fast early upstroke and either plateau or washout curve were upgraded, compared to 12% of women without this combination (p = 0.006). The sensitivity of combined kinetic features for predicting upgrade was 67% (95% CI 35-90%), specificity was 84% (CI 95% 68-94%), positive predictive value was 57% (CI 95% 37-75%), negative predictive value was 89% (CI 95% 77-95%), and OR was 78% (64-88%).

CONCLUSION

Kinetic characteristics show the strongest association with upgrade to invasion in DCIS occult on mammogram and US. Larger studies should be encouraged to consolidate our findings, which may have implication for treatment planning.

Discriminating low-grade ductal carcinoma in situ (DCIS) from non-low-grade DCIS or DCIS upgraded to invasive carcinoma: effective texture features on ultrafast dynamic contrast-enhanced magnetic resonance imaging

PURPOSE

To investigate effective model composed of features from ultrafast dynamic contrast-enhanced magnetic resonance imaging (UF-MRI) for distinguishing low- from non-low-grade ductal carcinoma in situ (DCIS) lesions or DCIS lesions upgraded to invasive carcinoma (upgrade DCIS lesions) among lesions diagnosed as DCIS on pre-operative biopsy.

MATERIALS AND METHODS

Eighty-six consecutive women with 86 DCIS lesions diagnosed by biopsy underwent UF-MRI including pre- and 18 post-contrast ultrafast scans (temporal resolution of 3 s/phase). The last phase of UF-MRI was used to perform 3D segmentation. The time point at 6 s after the aorta started to enhance was used to obtain subtracted images. From the 3D segmentation and subtracted images, enhancement, shape, and texture features were calculated and compared between low- and non-low-grade or upgrade DCIS lesions using univariate analysis. Feature selection by least absolute shrinkage and selection operator (LASSO) algorithm and k-fold cross-validation were performed to evaluate the diagnostic performance.

RESULTS

Surgical specimens revealed 16 low-grade DCIS lesions, 37 non-low-grade lesions and 33 upgrade DCIS lesions. In univariate analysis, five shape and seven texture features were significantly different between low- and non-low-grade lesions or upgrade DCIS lesions, whereas enhancement features were not. The six features including surface/volume ratio, irregularity, diff variance, uniformity, sum average, and variance were selected using LASSO algorism and the mean area under the receiver operating characteristic curve for training and validation folds were 0.88 and 0.88, respectively.

CONCLUSION

The model with shape and texture features of UF-MRI could effectively distinguish low- from non-low-grade or upgrade DCIS lesions.

Performance Measures of Magnetic Resonance Imaging Plus Mammography in the High Risk Ontario Breast Screening Program

BACKGROUND

The Ontario Breast Screening Program expanded in July 2011 to screen high-risk women age 30-69 years with annual magnetic resonance imaging (MRI) and digital mammography. This study examined the benefits of screening with mammography and MRI by age and risk criteria.

METHODS

This prospective cohort study included 8782 women age 30-69 years referred to the High Risk Ontario Breast Screening Program from July 2011 to June 2015, with final results to December 2016. Cancer detection rates, sensitivity, and specificity of MRI and mammography combined were compared with each modality individually within risk groups stratified by age using generalized estimating equation models. Prognostic features of screen-detected breast cancers were compared by modality using Fisher exact test. All P values are two-sided.

RESULTS

Among 20 053 screening episodes, there were 280 screen-detected breast cancers (cancer detection rate = 14.0 per 1000, 95% confidence interval [CI] = 12.4 to 15.7). The sensitivity of mammography was statistically significantly lower than that of MRI plus mammography (40.8%, 95% CI = 29.3% to 53.5% vs 96.0%, 95% CI = 92.2% to 98.0%, P < .001). In mutation carriers age 30-39 years, sensitivity of the combination was comparable with MRI alone (100.0% vs 96.8%, 95% CI = 79.2% to 100.0%, P = .99) but with statistically significantly decreased specificity (78.0%, 95% CI = 74.7% to 80.9% vs 86.2%, 95% CI = 83.5% to 88.5%, P < .001). In women age 50-69 years, combining MRI and mammography statistically significantly increased sensitivity compared with MRI alone (96.3%, 95% CI = 90.6% to 98.6% vs 90.9%, 95% CI = 83.6% to 95.1%, P = .02), with a small but statistically significant decrease in specificity (84.2%, 95% CI = 83.1% to 85.2% vs 90.0%, 95% CI = 89.2% to 90.9%, P < .001).

CONCLUSIONS

Screening high risk women age 30-39 years with annual MRI only may be sufficient for cancer detection and should be evaluated further, particularly for mutation carriers. Among women age 50-69 years, detection is most effective when mammography is included with annual MRI.

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.

Role of Breast MRI in the Evaluation and Detection of DCIS: Opportunities and Challenges

Historically, breast magnetic resonance imaging (MRI) was not considered an effective modality in the evaluation of ductal carcinoma in situ (DCIS). Over the past decade this has changed, with studies demonstrating that MRI is the most sensitive imaging tool for detection of all grades of DCIS. It has been suggested that not only is breast MRI the most sensitive imaging tool for detection but it may also detect the most clinically relevant DCIS lesions. The role and outcomes of MRI in the preoperative setting for patients with DCIS remains controversial; however, several studies have shown benefit in the preoperative evaluation of extent of disease as well as predicting an underlying invasive component. The most common presentation of DCIS on MRI is nonmass enhancement (NME) in a linear or segmental distribution pattern. Maximizing breast MRI spatial resolution is therefore beneficial, given the frequent presentation of DCIS as NME on MRI. Emerging MRI techniques, such as diffusion-weighted imaging (DWI), have shown promising potential to discriminate DCIS from benign and invasive lesions. Future opportunities including advanced imaging visual techniques, radiomics/radiogenomics, and machine learning / artificial intelligence may also be applicable to the detection and treatment of DCIS. Level of Evidence: 3 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2019. J. Magn. Reson. Imaging 2020;52:697-709.

MRI in the Assessment of BI-RADS® 4 lesions

The American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BI-RADS) lexicon, which is used ubiquitously to standardize reporting of breast magnetic resonance imaging (MRI), provides 7 BI-RADS assessment categories to indicate the level of suspicion of malignancy and guide further management. A BI-RADS category 4 assessment is assigned when an imaging abnormality does not fulfill the typical criteria for malignancy, but is suspicious enough to warrant a recommendation for biopsy. The BI-RADS category 4 assessment covers a wide range of probability of malignancy, from >2 to <95%. MRI is an essential noninvasive technique in breast imaging and the role of MRI in the assessment of ACR BI-RADS 4 lesions is manifold. In lesions classified as suspicious on imaging with mammography, digital breast tomosynthesis, and sonography, MRI can aid in the noninvasive differentiation of benign and malignant lesions and obviate unnecessary breast biopsies. When the suspicion of cancer is confirmed with MRI, concurrent staging of disease for treatment planning can be accomplished. This article will provide a comprehensive overview of the role of breast MRI in the assessment of ACR BI-RADS 4 lesions. In addition, we will discuss strategies to decrease false positives and avoid false negative results when reporting MRI of the breast.

Breast MRI: EUSOBI recommendations for women's information

This paper summarizes information about breast MRI to be provided to women and referring physicians. After listing contraindications, procedure details are described, stressing the need for correct scheduling and not moving during the examination. The structured report including BI-RADS® categories and further actions after a breast MRI examination are discussed. Breast MRI is a very sensitive modality, significantly improving screening in high-risk women. It also has a role in clinical diagnosis, problem solving, and staging, impacting on patient management. However, it is not a perfect test, and occasionally breast cancers can be missed. Therefore, clinical and other imaging findings (from mammography/ultrasound) should also be considered. Conversely, MRI may detect lesions not visible on other imaging modalities turning out to be benign (false positives). These risks should be discussed with women before a breast MRI is requested/performed. Because breast MRI drawbacks depend upon the indication for the examination, basic information for the most important breast MRI indications is presented. Seventeen notes and five frequently asked questions formulated for use as direct communication to women are provided. The text was reviewed by Europa Donna-The European Breast Cancer Coalition to ensure that it can be easily understood by women undergoing MRI.

KEY POINTS

• Information on breast MRI concerns advantages/disadvantages and preparation to the examination • Claustrophobia, implantable devices, allergic predisposition, and renal function should be checked • Before menopause, scheduling on day 7-14 of the cycle is preferred • During the examination, it is highly important that the patient keeps still • Availability of prior examinations improves accuracy of breast MRI interpretation.

Differentiation of ductal carcinoma in-situ from benign micro-calcifications by dedicated breast computed tomography

PURPOSE

Compare conspicuity of ductal carcinoma in-situ (DCIS) to benign calcifications on unenhanced (bCT), contrast-enhanced dedicated breast CT (CEbCT) and mammography (DM).

METHODS AND MATERIALS

The institutional review board approved this HIPAA-compliant study. 42 women with Breast Imaging Reporting and Data System 4 or 5 category micro-calcifications had breast CT before biopsy. Three subjects with invasive disease at surgery were excluded. Two breast radiologists independently compared lesion conspicuity scores (CS) for CEbCT, to bCT and DM. Enhancement was measured in Hounsfield units (HU). Mean CS ± standard deviations are shown. Receiver operating characteristic analysis (ROC) measured radiologists' discrimination performance by comparing CS to enhancement alone. Statistical measurements were made using ANOVA F-test, Wilcoxon rank-sum test and robust linear regression analyses.

RESULTS

39 lesions (17 DCIS, 22 benign) were analyzed. DCIS (8.5 ± 0.9, n=17) was more conspicuous than benign micro-calcifications (3.6 ± 2.9, n=22; p<0.0001) on CEbCT. DCIS was equally conspicuous on CEbCT and DM (8.5 ± 0.9, 8.7 ± 0.8, n=17; p=0.85) and more conspicuous when compared to bCT (5.3 ± 2.6, n=17; p<0.001). All DCIS enhanced; mean enhancement (90HU ± 53HU, n=17) was higher compared to benign lesions (33 ± 30HU, n=22) (p<0.0001). ROC analysis of the radiologists' CS showed high discrimination performance (AUC=0.94) compared to enhancement alone (AUC=0.85) (p<0.026).

CONCLUSION

DCIS is more conspicuous than benign micro-calcifications on CEbCT. DCIS visualization on CEbCT is equal to mammography but improved compared to bCT. Radiologists' discrimination performance using CEBCT is significantly higher than enhancement values alone. CEbCT may have an advantage over mammography by reducing false positive examinations when calcifications are analyzed.

Improving the Accuracy of Computer-aided Diagnosis for Breast MR Imaging by Differentiating between Mass and Nonmass Lesions

PURPOSE

To determine suitable features and optimal classifier design for a computer-aided diagnosis (CAD) system to differentiate among mass and nonmass enhancements during dynamic contrast material-enhanced magnetic resonance (MR) imaging of the breast.

MATERIALS AND METHODS

Two hundred eighty histologically proved mass lesions and 129 histologically proved nonmass lesions from MR imaging studies were retrospectively collected. The institutional research ethics board approved this study and waived informed consent. Breast Imaging Reporting and Data System classification of mass and nonmass enhancement was obtained from radiologic reports. Image data from dynamic contrast-enhanced MR imaging were extracted and analyzed by using feature selection techniques and binary, multiclass, and cascade classifiers. Performance was assessed by measuring the area under the receiver operating characteristics curve (AUC), sensitivity, and specificity. Bootstrap cross validation was used to predict the best classifier for the classification task of mass and nonmass benign and malignant breast lesions.

RESULTS

A total of 176 features were extracted. Feature relevance ranking indicated unequal importance of kinetic, texture, and morphologic features for mass and nonmass lesions. The best classifier performance was a two-stage cascade classifier (mass vs nonmass followed by malignant vs benign classification) (AUC, 0.91; 95% confidence interval (CI): 0.88, 0.94) compared with one-shot classifier (ie, all benign vs malignant classification) (AUC, 0.89; 95% CI: 0.85, 0.92). The AUC was 2% higher for cascade (median percent difference obtained by using paired bootstrapped samples) and was significant (P = .0027). Our proposed two-stage cascade classifier decreases the overall misclassification rate by 12%, with 72 of 409 missed diagnoses with cascade versus 82 of 409 missed diagnoses with one-shot classifier.

CONCLUSION

Separately optimizing feature selection and training classifiers for mass and nonmass lesions improves the accuracy of CAD for breast MR imaging. By cascading classifiers, we achieved a significant improvement in performance with respect to the use of a one-shot classifier. Our cascaded classifier may provide an advantage for screening women at high risk for breast cancer, in whom the ability to diagnose cancers at an early stage is of primary importance.

PPV(3) of suspicious breast MRI findings

RATIONALE AND OBJECTIVES

Magnetic resonance imaging (MRI) characteristics of Breast Imaging Reporting and Data System (BI-RADS) 4 and 5 lesions were evaluated to identify characteristics that may improve the positive predictive value (PPV) of a biopsy.

MATERIALS AND METHODS

MRI BI-RADS 4 or 5 breast findings in 101 women who underwent biopsy leading to a diagnosis of cancer within 1 year (PPV3; n = 115 cases) were reviewed. Patient history, lesion morphology, enhancement pattern and kinetics, and T2 characteristics were examined.

RESULTS

The PPV3 of all BI-RADS 4 and 5 breast lesions seen on MRI was 22.6% (26 of 115). Excluding lesions with second-look imaging correlates decreased the PPV3 to 11.8% (6/51). Of the MRI-guided biopsies, 20.9% (24 of 115) yielded a high-risk lesion, altering surgical management. MRI lesion type did not significantly affect the PPV3: the PPV3 was 26.3% (15 of 57) for masses, 21.4% (9 of 42) for non mass enhancement (NME) and 12.5% (2 of 16) for suspicious foci. The PPV3 for lesions found on diagnostic MRI in women with newly diagnosed cancer was 30.8% (20 of 65) which was statistically significantly greater compared to a PPV3 of 11.9% (5 of 42) for lesions identified on high-risk screening MRI.

CONCLUSIONS

Suspicious MRI findings identified on a second-look examination are more likely malignant than those seen only on MRI. Suspicious MRI findings discovered in patients with concurrent malignancy have a greater PPV3 than those detected on high-risk screening MRIs. However, the type of MRI finding (mass vs. NME vs. foci) does not significantly affect the PPV3 and should not be used as a discriminator for determining biopsy threshold.

Breast MRI of pure ductal carcinoma in situ: sensitivity of diagnosis and influence of lesion characteristics

OBJECTIVES

The purpose of the study was to evaluate the sensitivity of breast MRI in the detection of pure DCIS and to analyze the influence of lesion type and nuclear grade.

METHODS

58 consecutive patients with pathologically proven pure DCIS and preoperatively performed breast MRI were retrospectively reviewed and analyzed. Sensitivities in the detection of DCIS were calculated for MRI and mammography (Mx). Influence of MRI lesion type and nuclear grading on DCIS diagnosis was evaluated.

RESULTS

MRI detected pure DCIS with a sensitivity of 79.3%. The sensitivity of Mx was lower (69%), but the difference was not statistically significant (p=0.345). 46.2% of the DCIS presented as enhancing mass and 53.8% as non-mass-like enhancement (NMLE). None of the masses but 21.4% (n=6) of the NMLE were underestimated as probably benign (BI-RADS 3). MRI measured lesion sizes showed a moderate correlation (r=0.74) with histopathologically measured lesion sizes. MRI detection rate of DCIS decreased significantly (p=0.0458) with increasing nuclear grade. Calculated sensitivities were 100% for low-grade DCIS, 84.6% for intermediate-grade DCIS, and 66.7% for high-grade DCIS.

CONCLUSIONS

In this study MRI could detect pure DCIS more sensitively than Mx. Despite of missing statistically significance preoperative MRI seems to be helpful in patients with DCIS who are eligible for breast conservation. This applies in particular to patients with non-high-grade DCIS because those were significantly more often positive on MRI and significantly more often negative on Mx. Misinterpretation occurs especially in cases of NMLE and high-grade DCIS and therefore a correlation with Mx is also recommended.

In vivo assessment of ductal carcinoma in situ grade: a model incorporating dynamic contrast-enhanced and diffusion-weighted breast MR imaging parameters

PURPOSE

To develop a model incorporating dynamic contrast material-enhanced (DCE) and diffusion-weighted (DW) magnetic resonance (MR) imaging features to differentiate high-nuclear-grade (HNG) from non-HNG ductal carcinoma in situ (DCIS) in vivo.

MATERIALS AND METHODS

This HIPAA-compliant study was approved by the institutional review board and requirement for informed consent was waived. A total of 55 pure DCIS lesions (19 HNG, 36 non-HNG) in 52 women who underwent breast MR imaging at 1.5 T with both DCE and DW imaging (b = 0 and 600 sec/mm(2)) were retrospectively reviewed. The following lesion characteristics were recorded or measured: DCE morphology, DCE maximum lesion size, peak initial enhancement at 90 seconds, worst-curve delayed enhancement kinetics, apparent diffusion coefficient (ADC), contrast-to-noise ratio (CNR) at DW imaging with b values of 0 and 600 sec/mm(2), and T2 signal effects (measured with CNR at b = 0 sec/mm(2)). Univariate and stepwise multivariate logistic regression modeling was performed to identify MR imaging features that optimally discriminated HNG from non-HNG DCIS. Discriminative abilities of models were compared by using the area under the receiver operating characteristic curve (AUC).

RESULTS

HNG lesions exhibited larger mean maximum lesion size (P = .02) and lower mean CNR for images with b value of 600 sec/mm(2) (P = .004), allowing discrimination of HNG from non-HNG DCIS (AUC = 0.71 for maximum lesion size, AUC = 0.70 for CNR at b = 600 sec/mm(2)). Differences in CNR for images with b value of 0 sec/mm(2) (P = .025) without corresponding differences in ADC values were observed between HNG and non-HNG lesions. Peak initial enhancement was the only kinetic variable to approach significance (P = .05). No differences in lesion morphology (P = .11) or worst-curve delayed enhancement kinetics (P = .97) were observed. A multivariate model combining CNR for images with b value of 600 sec/mm(2) and maximum lesion size most significantly discriminated HNG from non-HNG (AUC = 0.81).

CONCLUSION

The preliminary findings suggest that DCE and DW MR imaging features may aid in identifying patients with high-risk DCIS. Further study may yield a model combining MR characteristics with histopathologic data to facilitate lesion-specific targeted therapies. © RSNA, 2012.

MRI of the breast in patients with DCIS to exclude the presence of invasive disease

OBJECTIVES

Core biopsy underestimates invasion in more than 20% of patients with preoperatively diagnosed ductal carcinoma in situ (DCIS) without evidence of invasion (pure DCIS). The aim of the current study was to evaluate the efficacy of preoperative magnetic resonance imaging (MRI) to discriminate between patients with DCIS who are at high risk of invasive breast cancer and patients at low risk.

METHODS

One hundred and twenty-five patients, preoperatively diagnosed with pure DCIS (128 lesions; 3 bilateral) by core-needle biopsy, were prospectively included. Clinical, mammographic, histological (core biopsy) and MRI features were assessed. All patients underwent breast surgery. Analyses were performed to identify features associated with presence of invasion.

RESULTS

Eighteen lesions (14.1%) showed invasion on final histology. Seventy-three lesions (57%) showed suspicious enhancement on MRI with a type 1 (n = 12, 16.4%), type 2 (n = 19, 26.0%) or type 3 curve, respectively (n = 42, 57.5%). At multivariate analysis, the most predictive features for excluding presence of invasive disease were absence of enhancement or a type 1 curve on MRI (negative predictive value 98.5%; A(Z) 0.80, P = 0.00006).

CONCLUSION

Contrast medium uptake kinetics at MRI provide high negative predictive value to exclude presence of invasion and may be useful in primary surgical planning in patients with a preoperative diagnosis of pure DCIS.

KEY POINTS

It is important to determine invasion in breast DCIS. • MRI contrast medium uptake kinetics can help exclude the presence of invasion. • However, the positive predictive value for the presence of invasion is limited. • MRI features were more accurate at predicting invasion than mammographic features alone.

The role of breast MR imaging in pre-operative determination of invasive disease for ductal carcinoma in situ diagnosed by needle biopsy

OBJECTIVES

To evaluate whether magnetic resonance (MR) imaging features can predict the presence of occult invasion in cases of biopsy-proven pure ductal carcinoma in situ (DCIS).

METHODS

We retrospectively reviewed 92 biopsy-proven pure DCIS in 92 women who underwent MR imaging. The following MR imaging findings were compared between confirmed DCIS and invasive breast cancer (IBC): lesion size, type, morphological and kinetic assessments by ACR BI-RADS MRI, and findings of fat-suppressed T2-weighted (FS-T2W) imaging.

RESULTS

Sixty-eight of 92 (74%) were non-mass-like enhancements (NMLE) and 24 were mass lesions on MR imaging. Twenty-one of 68 (31%) NMLE and 13 of 24 (54%) mass lesions were confirmed as IBC. In NMLE lesions, large lesions (P = 0.007) and higher signal intensities (SI) on FS-T2W images (P = 0.032) were significantly associated with IBC. Lesion size remained a significant independent predictor of invasion in multivariate analysis (P = 0.032), and combined with FS-T2W SIs showed slightly higher observer performances (area under the curve, AUC, 0.71) than lesion size alone (AUC 0.68). There were no useful findings that enabled the differentiation of mass-type lesions.

CONCLUSIONS

Breast MR imaging is potentially useful to predict the presence of occult invasion in biopsy-proven DCIS with NMLE.

KEY POINTS

MR mammography permits more precise lesion assessment including ductal carcinoma in situ A correct diagnosis of occult invasion before treatment is important for clinicians This study showed the potential of MR mammography to diagnose occult invasion Treatment and/or aggressive biopsy can be given with greater confidence MR mammography can lead to more appropriate management of patients.

Nonmass lesions in magnetic resonance imaging of the breast: additional T2-weighted images improve diagnostic accuracy

OBJECTIVE

In magnetic resonance imaging (MRI) of the breast, contrast enhancements present as mass or nonmass (NM) lesions. This study aimed to test the usefulness of currently accepted T1-weighted Breast Imaging Reporting and Data System predictors and to determine the incremental value of new T2-weighted predictors for differentiation of benign from malignant NM lesions.

METHODS

Consecutive patients undergoing surgery after MRI (1.5-T contrast-enhanced T1- and T2-weighted images) were investigated. Lesions were rated by 2 observers in consensus. Breast Imaging Reporting and Data System criteria for NM included spatial distribution, internal enhancement, and dynamic enhancement pattern. Additional criteria on T2-weighted images were signal intensity, presence of intraductal fluid, or cysts at the enhancements location. Independent differentiation criteria (benign vs malignant) were identified by logistic regression followed by receiver operating characteristics analysis.

RESULTS

Of 316 patients, 65 demonstrated NM. The NM lesions were split almost equally into malignant (34) and benign (31) histology. Breast Imaging Reporting and Data System predictors did not differentiate benign from malignant lesions, whereas signal intensity and the presence of cysts on contrast-enhanced T2-weighted images did, with a sensitivity of 91.2% and a specificity of 64.5%.

CONCLUSIONS

Differentiation of NM can be improved using additional T2-weighted images.

Radiologic-pathologic correlation of ductal carcinoma in situ

Ductal carcinoma in situ (DCIS) accounts for 20%-25% of breast cancers detected at screening mammography. The lesions are diverse and commonly are classified on the basis of their mammographic features and histologic characteristics such as nuclear grade and presence or absence of necrosis. The most common mammographic finding in DCIS is microcalcifications, but a low-grade lesion without necrosis is less likely to manifest with calcifications than either an intermediate- or a high-grade lesion. Other mammographic findings might include a mass or architectural distortion. Magnetic resonance (MR) imaging has higher sensitivity than mammography for the detection of DCIS and greater accuracy for depicting the extent of disease. The MR imaging appearance of DCIS depends primarily on the presence and extent of abnormal periductal or stromal vascularity. Nonmasslike enhancement, the most common MR imaging finding, is often seen in association with clumped internal enhancement. The enhancement kinetics in dynamic MR studies vary, and no kinetic pattern is pathognomonic of a particular nuclear grade of DCIS. However, the kinetic pattern at delayed imaging does appear to be correlated with the mammographic findings: Mass lesions show strong washout; fine pleomorphic, fine linear, and fine linear-branching calcifications demonstrate a plateau enhancement pattern; and amorphous calcifications exhibit persistent enhancement. Multidetector computed tomography might be a useful adjunct to MR imaging for preoperative mapping.

Characterization of Pure Ductal Carcinoma In Situ on Dynamic Contrast-Enhanced MR Imaging: Do Nonhigh Grade and High Grade Show Different Imaging Features?

To characterize imaging features of pure DCIS on dynamic contrast-enhanced MR imaging (DCE-MRI), 31 consecutive patients (37-81 years old, mean 56), including 2 Grade I, 16 Grade II, and 13 Grade III, were studied. MR images were reviewed retrospectively and the morphological appearances and kinetic features of breast lesions were categorized according to the ACR BI-RADS breast MRI lexicon. DCE-MRI was a sensitive imaging modality in detecting pure DCIS. MR imaging showed enhancing lesions in 29/31 (94%) cases. Pure DCIS appeared as mass type or non-mass lesions on MRI with nearly equal frequency. The 29 MR detected lesions include 15 mass lesions (52%), and 14 lesions showing non-mass-like lesions (48%). For the mass lesions, the most frequent presentations were irregular shape (50%), irregular margin (50%) and heterogeneous enhancement (67%). For the non-mass-like lesions, the clumped internal enhancement pattern was the dominate feature, seen in 9/14 cases (64%). Regarding enhancement kinetic curve, 21/29 (78%) lesions showed suspicious malignant type kinetics. No significant difference was found in morphology (P > .05), tumor size (P = 0.21), and kinetic characteristics (P = .38) between non-high grade (I+II) and high-grade (III) pure DCIS.

Characterizing early contrast uptake of ductal carcinoma in situ with high temporal resolution dynamic contrast-enhanced MRI of the breast: a pilot study

Improvements in the reliable diagnosis of preinvasive ductal carcinoma in situ (DCIS) by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are needed. In this study, we present a new characterization of early contrast kinetics of DCIS using high temporal resolution (HiT) DCE-MRI and compare it with other breast lesions and normal parenchyma. Forty patients with mammographic calcifications suspicious for DCIS were selected for HiT imaging using T(1)-weighted DCE-MRI with ∼7 s temporal resolution for 90 s post-contrast injection. Pixel-based and whole-lesion kinetic curves were fit to an empirical mathematical model (EMM) and several secondary kinetic parameters derived. Using the EMM parameterized and fitted concentration time curve for subsequent analysis allowed for calculation of kinetic parameters that were less susceptible to fluctuations due to noise. The parameters' initial area under the curve (iAUC) and contrast concentration at 1 min (C(1 min)) provided the highest diagnostic accuracy in the task of distinguishing pathologically proven DCIS from normal tissue. There was a trend for DCIS lesions with solid architectural pattern to exhibit a negative slope at 1 min (i.e. increased washout rate) compared to those with a cribriform pattern (p < 0.04). This pilot study demonstrates the feasibility of quantitative analysis of early contrast kinetics at high temporal resolution and points to the potential for such an analysis to improve the characterization of DCIS.

Selection of diagnostic features on breast MRI to differentiate between malignant and benign lesions using computer-aided diagnosis: differences in lesions presenting as mass and non-mass-like enhancement

Purpose

To investigate methods developed for the characterisation of the morphology and enhancement kinetic features of both mass and non-mass lesions, and to determine their diagnostic performance to differentiate between malignant and benign lesions that present as mass versus non-mass types.

Methods

Quantitative analysis of morphological features and enhancement kinetic parameters of breast lesions were used to differentiate among four groups of lesions: 88 malignant (43 mass, 45 non-mass) and 28 benign (19 mass, 9 non-mass). The enhancement kinetics was measured and analysed to obtain transfer constant (K^trans) and rate constant (k_ep). For each mass eight shape/margin parameters and 10 enhancement texture features were obtained. For the lesions presenting as nonmass-like enhancement, only the texture parameters were obtained. An artificial neural network (ANN) was used to build the diagnostic model.

Results

For lesions presenting as mass, the four selected morphological features could reach an area under the ROC curve (AUC) of 0.87 in differentiating between malignant and benign lesions. The kinetic parameter (k_ep) analysed from the hot spot of the tumour reached a comparable AUC of 0.88. The combined morphological and kinetic features improved the AUC to 0.93, with a sensitivity of 0.97 and a specificity of 0.80. For lesions presenting as non-mass-like enhancement, four texture features were selected by the ANN and achieved an AUC of 0.76. The kinetic parameter k_ep from the hot spot only achieved an AUC of 0.59, with a low added diagnostic value.

Conclusion

The results suggest that the quantitative diagnostic features can be used for developing automated breast CAD (computer-aided diagnosis) for mass lesions to achieve a high diagnostic performance, but more advanced algorithms are needed for diagnosis of lesions presenting as non-mass-like enhancement.

Magnetic resonance imaging of ductal carcinoma in situ: what is its clinical application? A review

BACKGROUND

After breast-conserving surgery of ductal carcinoma in situ (DCIS) of the breast or invasive breast carcinoma with an extensive intraductal component, tumor-positive surgical margins are frequently found. Therefore, the extent of the intraductal disease needs to be accurately determined preoperatively.

METHODS

Data for this review were identified by search of PubMed. Reference lists of selected articles were cross-searched for additional literature.

RESULTS

DCIS is accurately detected with magnetic resonance imaging (MRI), but the typical malignant features are inconsistently seen and most often in high-grade DCIS or in DCIS with a small invasive component. The histopathologic extent of DCIS is more accurately demonstrated with MRI. However, overestimation due to benign proliferative lesions does frequently occur. An improved depiction of DCIS could lead to improved preoperative staging. Conversely, the identification of more extensive disease on MRI could give rise to unnecessary interventions. Therefore, MRI should be used carefully and preferable in specialized and experienced centers.

CONCLUSION

[corrected] To date, there is no evidence that the use of MRI improves outcomes (ie, decreases recurrence rates) in patients with DCIS.