Features of Undiagnosed Breast Cancers at Screening Breast MR Imaging and Potential Utility of Computer-Aided Evaluation

AI-based selection of individuals for supplemental MRI in population-based breast cancer screening: the randomized ScreenTrustMRI trial

Screening mammography reduces breast cancer mortality, but studies analyzing interval cancers diagnosed after negative screens have shown that many cancers are missed. Supplemental screening using magnetic resonance imaging (MRI) can reduce the number of missed cancers. However, as qualified MRI staff are lacking, the equipment is expensive to purchase and cost-effectiveness for screening may not be convincing, the utilization of MRI is currently limited. An effective method for triaging individuals to supplemental MRI screening is therefore needed. We conducted a randomized clinical trial, ScreenTrustMRI, using a recently developed artificial intelligence (AI) tool to score each mammogram. We offered trial participation to individuals with a negative screening mammogram and a high AI score (top 6.9%). Upon agreeing to participate, individuals were assigned randomly to one of two groups: those receiving supplemental MRI and those not receiving MRI. The primary endpoint of ScreenTrustMRI is advanced breast cancer defined as either interval cancer, invasive component larger than 15 mm or lymph node positive cancer, based on a 27-month follow-up time from the initial screening. Secondary endpoints, prespecified in the study protocol to be reported before the primary outcome, include cancer detected by supplemental MRI, which is the focus of the current paper. Compared with traditional breast density measures used in a previous clinical trial, the current AI method was nearly four times more efficient in terms of cancers detected per 1,000 MRI examinations (64 versus 16.5). Most additional cancers detected were invasive and several were multifocal, suggesting that their detection was timely. Altogether, our results show that using an AI-based score to select a small proportion (6.9%) of individuals for supplemental MRI after negative mammography detects many missed cancers, making the cost per cancer detected comparable with screening mammography. ClinicalTrials.gov registration: NCT04832594 .

'Earlier than Early' Detection of Breast Cancer in Israeli BRCA Mutation Carriers Applying AI-Based Analysis to Consecutive MRI Scans

Female BRCA1/BRCA2 (=BRCA) pathogenic variants (PVs) carriers are at a substantially higher risk for developing breast cancer (BC) compared with the average risk population. Detection of BC at an early stage significantly improves prognosis. To facilitate early BC detection, a surveillance scheme is offered to BRCA PV carriers from age 25-30 years that includes annual MRI based breast imaging. Indeed, adherence to the recommended scheme has been shown to be associated with earlier disease stages at BC diagnosis, more in-situ pathology, smaller tumors, and less axillary involvement. While MRI is the most sensitive modality for BC detection in BRCA PV carriers, there are a significant number of overlooked or misinterpreted radiological lesions (mostly enhancing foci), leading to a delayed BC diagnosis at a more advanced stage. In this study we developed an artificial intelligence (AI)-network, aimed at a more accurate classification of enhancing foci, in MRIs of BRCA PV carriers, thus reducing false-negative interpretations. Retrospectively identified foci in prior MRIs that were either diagnosed as BC or benign/normal in a subsequent MRI were manually segmented and served as input for a convolutional network architecture. The model was successful in classification of 65% of the cancerous foci, most of them triple-negative BC. If validated, applying this scheme routinely may facilitate 'earlier than early' BC diagnosis in BRCA PV carriers.

Breast MRI: False-Negative Results and Missed Opportunities

Breast MRI is the most sensitive modality for the detection of breast cancer. However, false-negative cases may occur, in which the cancer is not visualized at MRI and is instead diagnosed with another imaging modality. The authors describe the causes of false-negative breast MRI results, which can be categorized broadly as secondary to perceptual errors or cognitive errors, or nonvisualization secondary to nonenhancement of the tumor. Tips and strategies to avoid these errors are discussed. Perceptual errors occur when an abnormality is not prospectively identified, yet the examination is technically adequate. Careful development of thorough search patterns is critical to avoid these errors. Cognitive errors occur when an abnormality is identified but misinterpreted or mischaracterized as benign. The radiologist may avoid these errors by utilizing all available prior examinations for comparison, viewing images in all planes to better assess the margins and shapes of abnormalities, and appropriately integrating all available information from the contrast-enhanced, T2-weighted, and T1-weighted images as well as the clinical history. Despite this, false-negative cases are inevitable, as certain subtypes of breast cancer, including ductal carcinoma in situ, invasive lobular carcinoma, and certain well-differentiated invasive cancers, may demonstrate little to no enhancement at MRI, owing to differences in angiogenesis and neovascularity. MRI is a valuable diagnostic tool in breast imaging. However, MRI should continue to be used as a complementary modality, with mammography and US, in the detection of breast cancer. ^©RSNA, 2021.

Magnetic Resonance Imaging Features in Different Types of Invasive Breast Cancer: A Systematic Review of the Literature

Breast cancer is the most common malignancy affecting women worldwide, and early diagnosis of breast cancer is the key to its successful and effective treatment. Traditional imaging techniques such as mammography and ultrasound are used to detect and configure breast abnormalities; unfortunately, these modalities have low sensitivity and specificity, particularly in young patients with dense breast tissue, breast implants, or post-surgical scar/architecture distortions. Therefore, breast magnetic resonance imaging (MRI) has been superior in the characterization and detection of breast cancer, especially that with invasive features. This review article explores the importance of breast MRI in the early detection of invasive breast cancer versus traditional tools, including mammography and ultrasound, while also analyzing the use of MRI as a screening tool for high-risk women. We will also discuss the different MRI features for invasive ductal carcinoma and lobular carcinoma and the role of breast MRI in the detection of ductal carcinoma in situ with a focus on the utilization of new techniques, including MR spectroscopy and diffusion-weighted imaging.

Breast Cancer Screening with Abbreviated Breast MRI: 3-year Outcome Analysis

Background Data are limited regarding the performance of abbreviated screening breast MRI during consecutive years and the characteristics of breast cancers missed and detected with it. Purpose To assess the longitudinal diagnostic performance of abbreviated screening MRI and to determine whether the screening outcomes of abbreviated MRI differed between yearly time periods for 3 consecutive years. Materials and Methods This retrospective study included 1975 consecutive women who underwent abbreviated screening MRI between September 2015 and August 2018. Breast Imaging Reporting and Data System (BI-RADS) categories 3-5 defined positive results, and BI-RADS categories 1-2 defined negative results. Cancer detection rate (CDR), sensitivity, specificity, positive predictive value (PPV), abnormal interpretation rate (AIR), and interval cancer rate were assessed annually. Yearly performance measures were compared with the Fisher exact test by using the permutation method. Clinical-pathologic and imaging characteristics of the missed and detected cancers were compared by using the Fisher exact test and the Wilcoxon rank sum test. Results A total of 1975 women (median age, 49 years; interquartile range, 44-56 years) underwent 3037 abbreviated MRI examinations over 3 years. CDR (year 1 to year 3, 6.9-10.7 per 1000 examinations), positive predictive value for recall (9.7% [six of 62] to 15.6% [12 of 77]), positive predictive value for biopsy (31.6% [six of 19] to 63.2% [12 of 19]), sensitivity (75.0% [six of eight] to 80.0% [12 of 15]), and specificity (93.5% [807 of 863] to 94.1% [1041 of 1106]) were highest in year 3, and AIR (7.1% [62 of 871] to 6.9% [77 of 1121]) was lowest in year 3. However, all outcome measures did not differ statistically between years 1, 2, and 3 (all P > .05). The interval cancer rate was 0.66 per 1000 examinations (two of 3037). Thirty-eight breast cancers were identified in 36 women; 29 were detected with abbreviated MRI, but nine were missed. Of these, seven were detected with other imaging modalities after negative results at the last screening MRI examination, and two were interval cancers. All missed cancers were node-negative early-stage invasive cancers and were smaller (median size, 0.8 cm vs 1.2 cm; P = .01) than detected cancers. Conclusion Screening outcome measures of abbreviated MRI were sustained without significant differences between 3 consecutive years. All cancers missed at abbreviated MRI were node-negative invasive cancers and tended to be smaller than detected cancers. © RSNA, 2021 See also the editorial by Lee in this issue. Online supplemental material is available for this article.

Identification of Preoperative Magnetic Resonance Imaging Features Associated with Positive Resection Margins in Breast Cancer: A Retrospective Study

Objective

To determine which preoperative breast magnetic resonance imaging (MRI) findings and clinicopathologic features are associated with positive resection margins at the time of breast-conserving surgery (BCS) in patients with breast cancer.

Materials and Methods

We reviewed preoperative breast MRI and clinicopathologic features of 120 patients (mean age, 53.3 years; age range, 27–79 years) with breast cancer who had undergone BCS in 2015. Tumor size on MRI, multifocality, patterns of enhancing lesions (mass without non-mass enhancement [NME] vs. NME with or without mass), mass characteristics (shape, margin, internal enhancement characteristics), NME (distribution, internal enhancement patterns), and breast parenchymal enhancement (BPE; weak, strong) were analyzed. We also evaluated age, tumor size, histology, lymphovascular invasion, T stage, N stage, and hormonal receptors. Univariate and multivariate logistic regression analyses were used to determine the correlation between clinicopathological features, MRI findings, and positive resection margins.

Results

In univariate analysis, tumor size on MRI, multifocality, NME with or without mass, and segmental distribution of NME were correlated with positive resection margins. Among the clinicopathological factors, tumor size of the invasive breast cancer and in situ components were significantly correlated with a positive resection margin. Multivariate analysis revealed that NME with or without mass was an independent predictor of positive resection margins (odds ratio [OR] = 7.00; p < 0.001). Strong BPE was a weak predictor of positive resection margins (OR = 2.59; p = 0.076).

Conclusion

Non-mass enhancement with or without mass is significantly associated with a positive resection margin in patients with breast cancer. In patients with NME, segmental distribution was significantly correlated with positive resection margins.

Abbreviated MRI Protocols for Detecting Breast Cancer in Women with Dense Breasts

Objective

To evaluate the validity of two abbreviated protocols (AP) of MRI in breast cancer screening of dense breast tissue.

Materials and Methods

This was a retrospective study in 356 participants with dense breast tissue and negative mammography results. The study was approved by the Nanjing Medical University Ethics Committee. Patients were imaged with a full diagnostic protocol (FDP) of MRI. Two APs (AP-1 consisting of the first post-contrast subtracted [FAST] and maximum-intensity projection [MIP] images, and AP-2 consisting of AP-1 combined with diffusion-weighted imaging [DWI]) and FDP images were analyzed separately, and the sensitivities and specificities of breast cancer detection were calculated.

Results

Of the 356 women, 67 lesions were detected in 67 women (18.8%) by standard MR protocol, and histological examination revealed 14 malignant lesions and 53 benign lesions. The average interpretation time of AP-1 and AP-2 were 37 seconds and 54 seconds, respectively, while the average interpretation time of the FDP was 3 minutes and 25 seconds. The sensitivities of the AP-1, AP-2, and FDP were 92.9, 100, and 100%, respectively, and the specificities of the three MR protocols were 86.5, 95.0, and 96.8%, respectively. There was no significant difference among the three MR protocols in the diagnosis of breast cancer (p > 0.05). However, the specificity of AP-1 was significantly lower than that of AP-2 (p = 0.031) and FDP (p = 0.035), while there was no difference between AP-2 and FDP (p > 0.05).

Conclusion

The AP may be efficient in the breast cancer screening of dense breast tissue. FAST and MIP images combined with DWI of MRI are helpful to improve the specificity of breast cancer detection.

Estimation of T2* Relaxation Time of Breast Cancer: Correlation with Clinical, Imaging and Pathological Features

OBJECTIVE

The purpose of this study was to estimate the T2* relaxation time in breast cancer, and to evaluate the association between the T2* value with clinical-imaging-pathological features of breast cancer.

MATERIALS AND METHODS

Between January 2011 and July 2013, 107 consecutive women with 107 breast cancers underwent multi-echo T2*-weighted imaging on a 3T clinical magnetic resonance imaging system. The Student's t test and one-way analysis of variance were used to compare the T2* values of cancer for different groups, based on the clinical-imaging-pathological features. In addition, multiple linear regression analysis was performed to find independent predictive factors associated with the T2* values.

RESULTS

Of the 107 breast cancers, 92 were invasive and 15 were ductal carcinoma in situ (DCIS). The mean T2* value of invasive cancers was significantly longer than that of DCIS (p = 0.029). Signal intensity on T2-weighted imaging (T2WI) and histologic grade of invasive breast cancers showed significant correlation with T2* relaxation time in univariate and multivariate analysis. Breast cancer groups with higher signal intensity on T2WI showed longer T2* relaxation time (p = 0.005). Cancer groups with higher histologic grade showed longer T2* relaxation time (p = 0.017).

CONCLUSION

The T2* value is significantly longer in invasive cancer than in DCIS. In invasive cancers, T2* relaxation time is significantly longer in higher histologic grades and high signal intensity on T2WI. Based on these preliminary data, quantitative T2* mapping has the potential to be useful in the characterization of breast cancer.

Features of Pure Lobular Carcinoma In Situ on Magnetic Resonance Imaging Associated with Immediate Re-Excision after Lumpectomy

Purpose

To evaluate imaging features of pure lobular carcinoma in situ (LCIS) on magnetic resonance imaging (MRI) in patients who underwent immediate re-excision after lumpectomy.

Methods

Twenty-six patients (46.1±6.7 years) with 28 pure LCIS lesions, who underwent preoperative MRI and received curative surgery at our institution between 2005 and 2013, were included in this study. Clinicopathologic features associated with immediate re-excision were reviewed and analyzed using Fisher exact test or the Wilcoxon signed rank test.

Results

Of the 28 lesions, 21.4% (6/28, six patients) were subjected to immediate re-excision due to resection margin involvement by LCIS. Nonmass lesions and moderate-to-marked background parenchymal enhancement on MRI were more frequently found in the re-excision group than in the single operation group (100% [6/6] vs. 40.9% [9/22], p=0.018; 83.3% [5/6] vs. 31.8% [7/22], p=0.057, respectively). The median lesion size discrepancy observed between magnetic resonance images and histopathology was greater in the re-excision group than in the single operation group (-0.82 vs. 0.13, p=0.018). There were no differences in the mammographic or histopathologic findings between the two groups.

Conclusion

Nonmass LCIS lesions or moderate-to-marked background parenchymal enhancements on MRI can result in an underestimation of the extent of the lesions and are associated with subsequent re-excision due to resection margin involvement.