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

Multivariable model to predict breast cancer in non-mass enhancement lesions: a study on contrast-enhanced mammography

BACKGROUND

To explore morphology and enhancement features of malignant non-mass enhancement (NME) lesions in contrast-enhanced mammography (CEM), and to develop a multivariable model that can accurately predict the probability of malignancy in NME lesions.

METHODS

A total of 162 patients with 206 NME lesions were enrolled. The ratio of 7:3 was randomly divided into a training data set and a test data set. Differences between benign and malignant NME diseases were compared using statistical analysis in the training data set. A logistic regression analysis was used to develop a multivariable model for predicting the probability of malignancy in the training data set. The predictive value of the model was assessed by calculating the area under the curve (AUC) in both training and test data sets.

RESULTS

The incidence of malignancy was higher in cases with malignant microcalcification (32.35%), segmental and linear distribution (55.88%), clumped and clustered ring enhancement pattern (70.59%), and Type III curve (64.71%) (all p < 0.002). The sensitivity, specificity, and AUC of the multivariable model in the training data set and the test data set were 79.41-80.77%, 94.44-97.37%, and 0.920-0.946, respectively.

CONCLUSIONS

When combining microcalcification and enhancement features, the multivariable model for CEM demonstrated acceptable sensitivity and high specificity in predicting malignant NME lesions.

KEY POINTS

Question CEM has gained momentum as an innovative and clinically useful method, but it has not been identified for the discrimination efficacy of NME lesions. Findings The multivariable model of CEM can improve the diagnostic efficiency of breast malignancy NME lesions, with acceptable sensitivity and high specificity. Clinical relevance CEM is an innovative advancement in breast imaging technology. This multivariable model of CEM integrates factors such as microcalcifications, enhancement morphological distribution, internal enhancement patterns, and time-signal intensity curves, thereby enabling accurate diagnosis of NME lesions.

The Predictive Role of Mammography, Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging and Diffusion-Weighted Imaging in Hormone Receptor Status of Pure Ductal Carcinoma In Situ Lesions

Objective

The aim of this retrospective study was to analyze the predictive capabilities of preoperative mammography, dynamic contrast-enhanced-magnetic resonance imaging (DCE-MRI), and diffusion-weighted imaging (DWI) in determining hormone receptor (HRc) status for pure ductal carcinoma in situ (DCIS) lesions.

Materials and Methods

The study included a total of 79 patients who underwent preoperative mammography (MG) and MRI between December 2018 and December 2023 and were subsequently diagnosed with pure DCIS after surgery. The correlation between MG, DCE-MRI, and DWI features and estrogen receptor (ER) and progesterone receptor (PR) status was examined.

Results

Among the lesions, 44 were double HRc-positive (ER and PR-positive), 13 were single HRc-positive (ER-positive and PR-negative or ER-negative and PR-positive) and 22 were double HRc-negative (ER and PR-negative). The presence of symptom (p = 0.029), the presence of comedo necrosis (p = 0.005) and high histological grade (p<0.001) were found to be associated with ER and PR negativity. Amorphous microcalcifications were more commonly observed in the double HRc-negative group, while linear calcifications were more prevalent in both double and single HRc-positive groups (p = 0.020). Non-mass enhancement (NME) with a linear distribution was significantly more common in double HRc-negative lesions (38%), and NME with a segmental distribution in both double (43%) and single (50%) receptor-positive lesions (p = 0.042). Evaluation of DWI findings revealed that a higher lesion-to-normal breast parenchyma apparent diffusion coefficient (ADC) ratio statistically increased the probability of HRc positivity (p = 0.033).

Conclusion

Certain clinicopathological, mammography, and MRI features, along with the lesion-to-normal breast parenchyma ADC ratio, can serve as predictors for HRc status in DCIS lesions.

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.

Magnetic resonance imaging diagnosis of non-mass enhancement of the breast

Breast Imaging Reporting and Data System magnetic resonance imaging (BI-RADS-MRI) classifies lesions as mass, non-mass enhancement (NME), or focus. BI-RADS ultrasound does not currently have the concept of non-mass. Additionally, knowing the concept of NME in MRI is significant. Thus, this study aimed to provide a narrative review of NME diagnosis in breast MRI. Lexicons are defined with distribution (focal, linear, segmental, regional, multiple regions, and diffuse) and internal enhancement patterns (homogenous, heterogeneous, clumped, and clustered ring) in the case of NME. Among these, linear, segmental, clumped, clustered ring, and heterogeneous are the terms that suggest malignancy. Hence, a hand search was conducted for reports of malignancy frequencies. The malignancy frequency in NME is widely distributed, ranging from 25 to 83.6%, and the frequency of each finding varies. Latest techniques, such as diffusion-weighted imaging and ultrafast dynamic MRI, are attempted to differentiate NME. Additionally, attempts are made in the preoperative setting to determine the concordance of lesion spread based on findings and the presence of invasion.

BI-RADS 3 Assessment on MRI: A Lesion-Based Review for Breast Radiologists

Unlike mammography and US, limited data exist to establish well-defined criteria for MRI findings that have a ≤2% likelihood of malignancy. Therefore, determining which findings are appropriate for a BI-RADS 3 assessment on MRI remains challenging and variable among breast radiologists. Emerging data suggest that BI-RADS 3 should be limited to baseline MRI examinations (or examinations with less than two years of prior comparisons) performed for high-risk screening and only used for masses with all of the typical morphological and kinetic features suggestive of a fibroadenoma or dominant enhancing T2 hypointense foci that is distinct from background parenchymal enhancement and without suspicious kinetics. This article presents an updated discussion of BI-RADS 3 assessment (probably benign) for breast MRI using current evidence.

Management of Non-Mass Enhancement at Breast Magnetic Resonance in Screening Settings Referred for Magnetic Resonance-Guided Biopsy

Rationale and Objectives

According to the Breast Imaging and Reporting Data System (BI-RADS), one of the main limitations of MRI is diagnosing the non-mass enhancement (NME). The NME lesion is challenging since it is unique to the MRI lexicon. This study aims to report our experience with NME lesions diagnosed by MRI referred for MRI-guided biopsies and discuss the management and follow-up of these lesions.

Materials and Methods

We retrospectively evaluated all MRI-guide breast biopsies. We included all patients referred for NME breast MRI-guided biopsy in screening settings. All patients had a negative second-look mammography or ultrasonography. We correlated the distribution and internal enhancement pattern (IEP) of the NME lesions with histology. Invasive ductal carcinomas (IDC) of no special type and ductal carcinoma in situ (DCIS) were considered malignant lesions.

Results

From January-2018 to July-2021, we included 96 women with a total of 96 lesions in the study. There were 90 benign and 6 malignant lesions with DCIS prevalence (5/6 cancers). The most frequent benign lesion type was fibrocystic changes. There were no NME lesions with diffuse or multiple area distribution features referred to MRI-guided biopsy. The positive-predictive values (PPV) were respectively 0.0%, 2.5%, 9.0%, and 11.0% for linear, focal, regional, and segmental distribution describers, and 0.0, 3.0%, 7.9%, and 50% for homogenous, heterogeneous, clumped, and clustered-ring enhancement patterns.

Conclusion

We observe the high potential risk for malignancy in the clustered-ring enhancement followed by the clumped pattern. Segmental distribution presented the highest predictive-positive values.