Breast cancers not detected at MRI: review of false-negative lesions

Diagnostic performance of Kaiser score in the evaluation of breast cancer using MRI: A systematic review and meta-analysis

PURPOSE

To assess the performance of Kaiser score (KS) in detecting and characterizing breast cancer on magnetic resonance imaging (MRI).

METHODS

The protocol was pre-registered at (https://osf.io/83c6j/). We performed a comprehensive search in PubMed, Embase, Cochrane Library, and Web of Science until 30 October 2024 for studies that used KS for detection of breast cancer on MRI. The risk of bias in the included studies was evaluated utilizing Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Diagnostic values of area under the curve (AUC), sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio were calculated using a random-effects bivariate model. Meta-regression was used to explore the source of heterogeneity when I2 was ≥ 50 %. P-value < 0.05 was considered statistically significant.

RESULTS

A total of 29 studies with 7918 patients and 8451 breast lesions were included. The pooled sensitivity, specificity, and AUC of KS for detecting malignant breast lesions on MRI were 95 % (95 % CI = 94 % to 96 %), 70 % (95 % CI = 64 % to 75 %), and 0.94 (95 % CI = 0.91 to 0.96), while for Breast Imaging Reporting and Data System (BI-RADS), they were 97 % (95 % CI = 92 % to 99 %), 46 % (95 % CI = 30 % to 62 %), and 0.89 (95 % CI = 0.86 to 0.91). Sensitivity difference was not statistically significant (p-value = 0.803), but specificity difference was significant (p-value = 0.001). Also, KS demonstrated slightly better diagnostic accuracy for mass lesions with a sensitivity of 96 % (95 % CI = 94 % to 97 %), specificity of 69 % (95 % CI = 60 % to 77 %), and AUC of 0.96 (95 % CI = 0.94 to 0.97) compared to non-mass lesions with 93 % (95 % CI = 88 % to 96 %), 68 % (95 % CI = 58 % to 77 %), and 0.91 (95 % CI = 0.88 to 0.94) values, respectively. KS showed better performance in larger lesions.

CONCLUSION

The KS's superior diagnostic performance compared to BI-RADS, particularly its ability to avoid unnecessary biopsies, makes it valuable for diagnostic and clinical decision-making.

Contrast-Enhanced Chest Computed Tomography for In-Breast Recurrence Detection: Clinical and Imaging Predictors of Visibility

Purpose: Routine surveillance chest CT is not recommended by current guidelines; however, its use has been increasing with improved accessibility. This study aimed to evaluate the utility of surveillance contrast-enhanced chest computed tomography (CT) in detecting in-breast recurrence among survivors, focusing on imaging and clinicopathological features that enhance tumor visibility. Additionally, this study sought to determine which patient populations may derive benefit from contrast-enhanced chest CT. Materials and Methods: A retrospective analysis was conducted on records of patients diagnosed with in-breast recurrence through biopsy during follow-up after breast cancer surgery between January 2016 and August 2022. Patients who underwent contrast-enhanced chest CT within one month of diagnosis were included. Two radiologists reviewed the chest CT scans for breast cancer lesions by consensus, and their findings were validated by two other radiologists blinded to tumor locations. Statistical analyses were performed to evaluate associations among clinicopathological factors, image features, and visibility. Results: Eighty-nine recurrent tumors in 85 patients were included. Fifty-eight recurrent tumors were identified by radiologists who were not blinded. The blinded radiologists independently identified 50 and 56 recurrences, with substantial inter-observer agreement (κ-value = 0.768, p < 0.001). The visible group had a significantly higher rate of invasive ductal carcinoma (IDC) compared to the non-visible group (81.0% vs. 54.8%, p = 0.002). Additionally, the visible group exhibited larger tumors than the non-visible group (mean ± SD: 1.9 ± 1.5 cm vs. 1.3 ± 0.6 cm, p = 0.018). Tumors located in fatty backgrounds demonstrated significantly greater visibility on chest CT than those in glandular backgrounds (67.2% vs. 16.1%, p < 0.001). Recurrent breast cancer was also more frequently visible on chest CT in patients who had undergone mastectomy compared to those who had received breast-conserving surgery (p < 0.001). Conclusions: Contrast-enhanced chest CT can aid in the detection of in-breast recurrence, particularly in patients who have undergone mastectomy, as a complementary imaging modality. Tumors in fatty backgrounds, large tumors, mass-type tumors, and IDCs are better visible on chest CT.

Injecting hope: the potential of intratumoral immunotherapy for locally advanced and metastatic cancer

Despite enormous progress, advanced cancers are still one of the most serious medical problems in current society. Although various agents and therapeutic strategies with anticancer activity are known and used, they often fail to achieve satisfactory long-term patient outcomes and survival. Recently, immunotherapy has shown success in patients by harnessing important interactions between the immune system and cancer. However, many of these therapies lead to frequent side effects when administered systemically, prompting treatment modifications or discontinuation or, in severe cases, fatalities. New therapeutic approaches like intratumoral immunotherapy, characterized by reduced side effects, cost, and systemic toxicity, offer promising prospects for future applications in clinical oncology. In the context of locally advanced or metastatic cancer, combining diverse immunotherapeutic and other treatment strategies targeting multiple cancer hallmarks appears crucial. Such combination therapies hold promise for improving patient outcomes and survival and for promoting a sustained systemic response. This review aims to provide a current overview of immunotherapeutic approaches, specifically focusing on the intratumoral administration of drugs in patients with locally advanced and metastatic cancers. It also explores the integration of intratumoral administration with other modalities to maximize therapeutic response. Additionally, the review summarizes recent advances in intratumoral immunotherapy and discusses novel therapeutic approaches, outlining future directions in the field.

Kaiser score diagnosis of breast MRI lesions: Factors associated with false-negative and false-positive results

PURPOSE

We sought factors associated with false-negative and false-positive results in the diagnosis of breast lesions using the Kaiser score (KS) on breast magnetic resonance imaging (MRI).

METHODS

We retrospectively analyzed 1058 patients with 1058 breast lesions who underwent preoperative breast MRI with successful histopathologic results. Two radiologists assessed each lesion according to KS criteria, and clinicopathologic features and MRI findings were analyzed. Multivariate regression analysis was conducted to identify factors associated with false-negative and false-positive KS results.

RESULTS

Of the 1058 lesions, 859 were malignant and 199 were benign. Particularly high misdiagnosis rates were observed for intraductal papilloma, inflammatory lesion, and mucinous carcinoma. For breast cancer, KS yielded 821 (95.6 %) true-positive and 38 (4.4 %) false-negative results. Multivariate analysis showed that smaller lesion size (≤1 cm) (OR, 3.698; 95 %CI, 1.430-9.567; p = 0.007), absence of ipsilateral breast hypervascularity (OR, 3.029; 95 %CI, 1.370-6.693; p = 0.006), and presence of hyperintensity on T2WI (OR, 2.405; 95 %CI, 1.121-5.162; p = 0.024) were significantly associated with false-negative breast cancer results. For benign lesions, KS yielded 141 (70.9 %) true-negative and 58 (29.1 %) false-positive results. Multivariate regression analysis revealed that non-mass enhancement lesions (OR, 4.660; 95 %CI, 2.018-10.762; p＜0.001), moderate/high background parenchymal enhancement (OR, 2.402; 95 %CI, 1.180-4.892; p = 0.016), and the presence of hyperintensity on T2WI (OR, 2.986; 95 %CI, 1.386-6.433; p = 0.005) were significantly associated with false-positive KS results.

CONCLUSION

Several clinicopathologic and MRI features influence the accuracy of KS diagnosis. Understanding these factors may facilitate appropriate use of KS and guide alternative diagnostic approaches, ultimately improving diagnostic accuracy in the evaluation of breast lesions.

False-Positive and False-Negative Contrast-enhanced Mammograms: Pitfalls and Strategies to Improve Cancer Detection

Contrast-enhanced mammography (CEM) is a relatively new breast imaging modality that uses intravenous contrast material to increase detection of breast cancer. CEM combines the structural information of conventional mammography with the functional information of tumor neovascularity. Initial studies have demonstrated that CEM and MRI perform with similar accuracies, with CEM having a slightly higher specificity (fewer false positives), although larger studies are needed. There are various reasons for false positives and false negatives at CEM. False positives at CEM can be caused by benign lesions with vascularity, including benign tumors, infection or inflammation, benign lesions in the skin, and imaging artifacts. False negatives at CEM can be attributed to incomplete or inadequate visualization of lesions, marked background parenchymal enhancement (BPE) obscuring cancer, lack of lesion contrast enhancement due to technical issues or less-vascular cancers, artifacts, and errors of lesion perception or characterization. When possible, real-time interpretation of CEM studies is ideal. If additional views are necessary, they may be obtained while contrast material is still in the breast parenchyma. Until recently, a limitation of CEM was the lack of CEM-guided biopsy capability. However, in 2020, the U.S. Food and Drug Administration cleared two devices to support CEM-guided biopsy using a stereotactic biopsy technique. The authors review various causes of false-positive and false-negative contrast-enhanced mammograms and discuss strategies to reduce these diagnostic errors to improve cancer detection while mitigating unnecessary additional imaging and procedures. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Caveat Emptor: Commercialized Manganese Oxide Nanoparticles Exhibit Unintended Properties

Nano-encapsulated manganese oxide (NEMO) particles are noteworthy contrast agents for magnetic resonance imaging (MRI) due to their bright, pH-switchable signal ("OFF" to "ON" at low pH), high metal loading, and targeting capability for increased specificity. For the first time, we performed a head-to-head comparison of NEMO particles from In-house and commercialized sources (US Nano vs Nanoshel) to assess their potential as bright T₁ MRI contrast agents. Manganese oxide nanocrystals (MnO, Mn₂O₃, and Mn₃O₄) were systematically evaluated for size, chemistry, release of manganese ions, and MRI signal pre- and post-encapsulation within poly(lactic-co-glycolic acid) (PLGA). Suprisingly, a majority of the commercialized formulations were not as advertised by displaying unintended sizes, morphologies, chemistry, dissolution profiles, and/or MRI signal that precludes in vivo use. US Nano's Mn₃O₄ and Mn₂O₃ nanocrystals contained impurities that impacted Mn ion release as well as micron-sized rodlike structures. Nanoshel's MnO and Mn₂O₃ nanoparticles had very large hydrodynamic sizes (>600 nm). In-house MnO and Nanoshel's Mn₃O₄ nanoparticles demonstrated the best characteristics with brighter T₁ MRI signals, small hydrodynamic sizes, and high encapsulation efficiencies. Our findings highlight that researchers must confirm the properties of purchased nanomaterials before utilizing them in desired applications, as their experimental success may be impacted.

In Search of Calcifications : Histologic Analysis and Diagnostic Yield of Stereotactic Core Needle Breast Biopsies

OBJECTIVES

Stereotactic core needle biopsy (SCNB) is used in the diagnostic assessment of suspicious mammographic calcifications to rule out breast ductal carcinoma in situ (DCIS). With advances in imaging technology and increased biopsy tissue volume, the detection rate of calcifications and DCIS in SCNB is unclear.

METHODS

This retrospective study included 916 consecutive SCNBs for calcifications performed on 893 patients in a 2-year period.

RESULTS

We found the cancer detection rate was 27.1% (DCIS, 23.7%; invasive, 3.4%). The detection rate for calcifications was 74.8% with the standard 3 levels. Additional leveling of calcification-negative cases further increased the detection of both calcifications (to 99.4% of cases) and DCIS (to 32.9% of cases). Lobular neoplasia (LN) was diagnosed in 41 cases. Twenty-five (61.0%) cases of LN were incidental without associated calcification. Of 32 invasive carcinomas detected on SCNB, 87.5% were T1a or less, and calcifications were associated with atypical ductal hyperplasia/DCIS or LCIS. The common benign lesions associated with calcifications were fibrocystic change (32.5%), fibroadenomatous change (30.2%), and columnar cell change and hyperplasia (8.2%).

CONCLUSIONS

We determined the up-to-date detection rates of calcification and DCIS in SCNB, as well as the common benign and malignant breast lesions associated with calcifications. Additional levels significantly increase the detection rate when standard levels show only stromal or scant/absent calcifications. Lobular neoplasia is often an incidental finding in SCNB for calcifications. When calcifications are present with LN, they are commonly florid, pleomorphic LCIS, or with concurrent invasive carcinoma.

Non-enhancing malignant lesions of the breast: A case report and review of literature

Due to the elusive nature of invasive lobular carcinoma, mammography, ultrasound, and magnetic resonance imaging have their limitations in early detection. A 67-year-old woman presented for mammography and found retraction of breast parenchyma of the right breast. Magnetic resonance imaging and contrast mammography showed no contrast uptake in the region in question. Magnetic resonance imaging and ultrasound were found to be superior for the detection of invasive lobular carcinoma, with a sensitivity of more than 90%. On ultrasound examination, invasive lobular carcinoma may occur only with posterior acoustic shadowing. On breast magnetic resonance imaging, it is commonly described as an irregular mass and less commonly as non-mass enhancement. An additional advantage of magnetic resonance imaging is the higher detection rate of multifocal, multicentric, and contralateral breast lesions. The reason for no contrast enhancement in this particular tumor before neoadjuvant chemotherapy followed by enhancement after neoadjuvant chemotherapy is most likely at the molecular and histologic level and requires further investigation in similar cases.

Contrast enhanced mammography: focus on frequently encountered benign and malignant diagnoses

Contrast-enhanced mammography (CEM) is becoming a widely adopted modality in breast imaging over the past few decades and exponentially so over the last few years, with strong evidence of high diagnostic performance in cancer detection. Evidence is also growing indicating comparative performance of CEM to MRI in sensitivity with fewer false positive rates. As application of CEM ranges from potential use in screening dense breast populations to staging of known breast malignancy, increased familiarity with the modality and its implementation, and disease processes encountered becomes of great clinical significance. This review emphasizes expected normal findings on CEM followed by a focus on examples of the commonly encountered benign and malignant pathologies on CEM.

MRI Breast: Current Imaging Trends, Clinical Applications, and Future Research Directions

Magnetic Resonance Imaging (MRI) is the most sensitive and advanced imaging technique in diagnosing breast cancer and is essential in improving cancer detection, lesion characterization, and determining therapy response. In addition to the dynamic contrast-enhanced (DCE) technique, functional techniques such as magnetic resonance spectroscopy (MRS), diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), and intravoxel incoherent motion (IVIM) further characterize and differentiate benign and malignant lesions thus, improving diagnostic accuracy. There is now an increasing clinical usage of MRI breast, including screening in high risk and supplementary screening tools in average-risk patients. MRI is becoming imperative in assisting breast surgeons in planning breast-conserving surgery for preoperative local staging and evaluation of neoadjuvant chemotherapy response. Other clinical applications for MRI breast include occult breast cancer detection, investigation of nipple discharge, and breast implant assessment. There is now an abundance of research publications on MRI Breast with several areas that still remain to be explored. This review gives a comprehensive overview of the clinical trends of MRI breast with emphasis on imaging features and interpretation using conventional and advanced techniques. In addition, future research areas in MRI breast include developing techniques to make MRI more accessible and costeffective for screening. The abbreviated MRI breast procedure and an area of focused research in the enhancement of radiologists' work with artificial intelligence have high impact for the future in MRI Breast.

The Frequency and Causes of Not-Detected Breast Malignancy in Dynamic Contrast-Enhanced MRI

Breast MR is the most sensitive imaging modality, but there are cases of malignant tumors that are not detected in MR. This study evaluated the frequency and main causes of malignant breast lesions not detected in dynamic contrast-enhanced (DCE) MR. A total of 1707 cases of preoperative breast MR performed between 2020 and 2021 were included. Three radiologists individually reviewed the DCE MRs and found not-detected malignancy cases in the MRs. The final cases were decided through consensus. For the selected cases, images other than DCE MRIs, such as mammography, ultrasounds, diffusion-weighted MRs, and, if possible, contrast-enhanced chest CTs, were analyzed. In the final sample, 12 cases were not detected in DCE MR, and the frequency was 0.7% (12/1707). Six cases were not detected due to known non-enhancing histologic features. In four cases, tumors were located in the breast periphery and showed no enhancement in MR. In the remaining two cases, malignant lesions were not identified due to underlying marked levels of BPE. The frequency of not-detected malignancy in DCE MR is rare. Knowing the causes of each case and correlating it with other imaging modalities could be helpful in the diagnosis of breast malignancy in DCE MR.

Diagnostic Strategies for Breast Cancer Detection: From Image Generation to Classification Strategies Using Artificial Intelligence Algorithms

Breast cancer is one the main death causes for women worldwide, as 16% of the diagnosed malignant lesions worldwide are its consequence. In this sense, it is of paramount importance to diagnose these lesions in the earliest stage possible, in order to have the highest chances of survival. While there are several works that present selected topics in this area, none of them present a complete panorama, that is, from the image generation to its interpretation. This work presents a comprehensive state-of-the-art review of the image generation and processing techniques to detect Breast Cancer, where potential candidates for the image generation and processing are presented and discussed. Novel methodologies should consider the adroit integration of artificial intelligence-concepts and the categorical data to generate modern alternatives that can have the accuracy, precision and reliability expected to mitigate the misclassifications.

Comparison of Diagnostic Test Accuracy of Cone-Beam Breast Computed Tomography and Digital Breast Tomosynthesis for Breast Cancer: A Systematic Review and Meta-Analysis Approach

BACKGROUND

Cone-beam breast computed tomography (CBBCT) and digital breast tomosynthesis (DBT) remain the main 3D modalities for X-ray breast imaging. This study aimed to systematically evaluate and meta-analyze the comparison of diagnostic accuracy of CBBCT and DBT to characterize breast cancers.

METHODS

Two independent reviewers identified screening on diagnostic studies from 1 January 2015 to 30 December 2021, with at least reported sensitivity and specificity for both CBBCT and DBT. A univariate pooled meta-analysis was performed using the random-effects model to estimate the sensitivity and specificity while other diagnostic parameters like the area under the ROC curve (AUC), positive likelihood ratio (LR+), and negative likelihood ratio (LR-) were estimated using the bivariate model.

RESULTS

The pooled sensitivity specificity, LR+ and LR- and AUC at 95% confidence interval are 86.7% (80.3-91.2), 87.0% (79.9-91.8), 6.28 (4.40-8.96), 0.17 (0.12-0.25) and 0.925 for the 17 included studies in DBT arm, respectively, while, 83.7% (54.6-95.7), 71.3% (47.5-87.2), 2.71 (1.39-5.29), 0.20 (0.04-1.05), and 0.831 are the pooled sensitivity specificity, LR+ and LR- and AUC for the five studies in the CBBCT arm, respectively.

CONCLUSIONS

Our study demonstrates that DBT shows improved diagnostic performance over CBBCT regarding all estimated diagnostic parameters; with the statistical improvement in the AUC of DBT over CBBCT. The CBBCT might be a useful modality for breast cancer detection, thus we recommend more prospective studies on CBBCT application.

Missed Breast Cancers on MRI in High-Risk Patients: A Retrospective Case–Control Study

Purpose: To determine if MRI features and molecular subtype influence the detectability of breast cancers on MRI in high-risk patients. Methods and Materials: Breast cancers in a high-risk population of 104 patients were diagnosed following MRI describing a BI-RADS 4–5 lesion. MRI characteristics at the time of diagnosis were compared with previous MRI, where a BI-RADS 1–2–3 lesion was described. Results: There were 77 false-negative MRIs. A total of 51 cancers were overlooked and 26 were misinterpreted. There was no association found between MRI characteristics, the receptor type and the frequency of missed cancers. The main factors for misinterpreted lesions were multiple breast lesions, prior biopsy/surgery and long-term stability. Lesions were mostly overlooked because of their small size and high background parenchymal enhancement. Among missed lesions, 50% of those with plateau kinetics on initial MRI changed for washout kinetics, and 65% of initially progressively enhancing lesions then showed plateau or washout kinetics. There were more basal-like tumours in BRCA1 carriers (50%) than in non-carriers (13%), p = 0.0001, OR = 6.714, 95% CI = [2.058–21.910]. The proportion of missed cancers was lower in BRCA carriers (59%) versus non-carriers (79%), p < 0.05, OR = 2.621, 95% CI = [1.02–6.74]. Conclusions: MRI characteristics or molecular subtype do not influence breast cancer detectability. Lesions in a post-surgical breast should be assessed with caution. Long-term stability does not rule out malignancy and multimodality evaluation is of added value. Lowering the biopsy threshold for lesions with an interval change in kinetics for a type 2 or 3 curve should be considered. There was a higher rate of interval cancers in BRCA 1 patients attributed to lesions more aggressive in nature.

[Non-genetic indications for risk reducing mastectomies: Guidelines of the National College of French Gynecologists and Obstetricians (CNGOF)]

OBJECTIVE

To determine the value of performing a risk-reducting mastectomy (RRM) in the absence of a deleterious variant of a breast cancer susceptibility gene, in 4 clinical situations at risk of breast cancer.

DESIGN

The CNGOF Commission of Senology, composed of 26 experts, developed these recommendations. A policy of declaration and monitoring of links of interest was applied throughout the process of making the recommendations. Similarly, the development of these recommendations did not benefit from any funding from a company marketing a health product. The Commission of Senology adhered to the AGREE II (Advancing guideline development, reporting and evaluation in healthcare) criteria and followed the Grading of Recommendations Assessment, Development and Evaluation (GRADE) method to assess the quality of the evidence on which the recommendations were based. The potential drawbacks of making recommendations in the presence of poor quality or insufficient evidence were highlighted.

METHODS

The Commission of Senology considered 8 questions on 4 topics, focusing on histological, familial (no identified genetic abnormality), radiological (of unrecognized cancer), and radiation (history of Hodgkin's disease) risk. For each situation, it was determined whether performing RRM compared with surveillance would decrease the risk of developing breast cancer and/or increase survival.

RESULTS

The Commission of Senology synthesis and application of the GRADE method resulted in 11 recommendations, 6 with a high level of evidence (GRADE 1±) and 5 with a low level of evidence (GRADE 2±).

CONCLUSION

There was significant agreement among the Commission of Senology members on recommendations to improve practice for performing or not performing RRM in the clinical setting.

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.

Discrimination of Breast Cancer from Healthy Breast Tissue Using a Three-component Diffusion-weighted MRI Model

PURPOSE

Diffusion-weighted MRI (DW-MRI) is a contrast-free modality that has demonstrated ability to discriminate between predefined benign and malignant breast lesions. However, how well DW-MRI discriminates cancer from all other breast tissue voxels in a clinical setting is unknown. Here we explore the voxelwise ability to distinguish cancer from healthy breast tissue using signal contributions from the newly developed three-component multi-b-value DW-MRI model.

EXPERIMENTAL DESIGN

Patients with pathology-proven breast cancer from two datasets (n = 81 and n = 25) underwent multi-b-value DW-MRI. The three-component signal contributions C 1 and C 2 and their product, C 1 C 2, and signal fractions F 1, F 2, and F 1 F 2 were compared with the image defined on maximum b-value (DWI max), conventional apparent diffusion coefficient (ADC), and apparent diffusion kurtosis (K app). The ability to discriminate between cancer and healthy breast tissue was assessed by the false-positive rate given a sensitivity of 80% (FPR80) and ROC AUC.

RESULTS

Mean FPR80 for both datasets was 0.016 [95% confidence interval (CI), 0.008-0.024] for C 1 C 2, 0.136 (95% CI, 0.092-0.180) for C 1, 0.068 (95% CI, 0.049-0.087) for C 2, 0.462 (95% CI, 0.425-0.499) for F 1 F 2, 0.832 (95% CI, 0.797-0.868) for F 1, 0.176 (95% CI, 0.150-0.203) for F 2, 0.159 (95% CI, 0.114-0.204) for DWI max, 0.731 (95% CI, 0.692-0.770) for ADC, and 0.684 (95% CI, 0.660-0.709) for K app. Mean ROC AUC for C 1 C 2 was 0.984 (95% CI, 0.977-0.991).

CONCLUSIONS

The C 1 C 2 parameter of the three-component model yields a clinically useful discrimination between cancer and healthy breast tissue, superior to other DW-MRI methods and obliviating predefining lesions. This novel DW-MRI method may serve as noncontrast alternative to standard-of-care dynamic contrast-enhanced MRI.

Fusion of high b-value diffusion-weighted and unenhanced T1-weighted images to diagnose invasive breast cancer: factors associated with false-negative results

OBJECTIVES

We sought factors associated with false-negative results in the diagnosis of invasive breast cancer via non-contrast breast magnetic resonance imaging (MRI) using fused high b-value diffusion-weighted imaging (DWI) and unenhanced T1-weighted images (T1WI).

METHODS

Between 2018 and 2019, 316 consecutive women (mean age, 54.6 years) with invasive breast cancer who underwent preoperative breast MRI, including fused high b-value DWI and unenhanced T1WI, were retrospectively evaluated. Malignancy confidence ratings of the most suspicious breast lesions evident on fused DWI were derived by two radiologists using a 6-point Likert-type scale. Both clinicopathological and imaging features were analyzed. Multivariate regression analysis was performed to identify factors associated with false-negative DWI results in the diagnosis of invasive breast cancer.

RESULTS

Of the 316 breast cancers, fused DWI yielded 289 (91.5%) true-positive and 27 (8.5%) false-negative results. Multivariate analysis showed that small tumor size (≤ 1 cm) (odds ratio [OR], 5.95; 95% confidence interval [CI], 2.11, 16.81; p = 0.001), presence of calcifications in the tumor (OR, 3.41; 95% CI, 1.27, 9.15; p = 0.015), and a moderate/marked background diffusion signal (ORs, 4.23 and 19.18; 95% CI, 1.31, 13.67 and 6.51, 56.46; p = 0.016 and p < 0.001, respectively) were significantly associated with false-negative results. In subgroup analysis of 141 screening-detected cancers, a marked background diffusion signal (OR, 7.94; 95% CI, 2.30, 27.35; p = 0.001) remained significantly associated with false-negative results in the multivariate analysis.

CONCLUSIONS

In addition to histopathological features, a higher background diffusion signal was associated with false-negative results in the diagnosis of invasive breast cancer via non-contrast MRI using fused high b-value DWI and unenhanced T1WI.

KEY POINTS

• Subcentimeter tumors and presence of calcifications in the tumor are associated with false-negative diffusion-weighted imaging results in the diagnosis of invasive breast cancer. • A higher degree of background diffusion signal may lead to false-negative interpretation of diffusion-weighted imaging in patients with invasive breast cancer.

Can Follow-up be Avoided for Probably Benign US Masses with No Enhancement on MRI?

OBJECTIVES

To assess whether no enhancement on pre-treatment MRI can rule out malignancy of additional US mass(es) initially assessed as BI-RADS 3 or 4 in women with newly diagnosed breast cancer.

METHODS

This retrospective study included consecutive women from 2010-2018 with newly diagnosed breast cancer; at least one additional breast mass (distinct from index cancer) assigned a BI-RADS 3 or 4 on US; and a bilateral contrast-enhanced breast MRI performed within 90 days of US. All malignant masses were pathologically proven; benign masses were pathologically proven or defined as showing at least 2 years of imaging stability. Incidence of malignant masses and NPV were calculated on a per-patient level using proportions and exact 95% CIs.

RESULTS

In 230 patients with 309 additional masses, 140/309 (45%) masses did not enhance while 169/309 (55%) enhanced on MRI. Of the 140 masses seen in 105 women (mean age, 54 years; range 28-82) with no enhancement on MRI, all had adequate follow-up and 140/140 (100%) were benign, of which 89/140 (63.6%) were pathologically proven and 51/140 (36.4%) demonstrated at least 2 years of imaging stability. Pre-treatment MRI demonstrating no enhancement of US mass correlate(s) had an NPV of 100% (95% CI 96.7-100.0).

CONCLUSIONS

All BI-RADS 3 and 4 US masses with a non-enhancing correlate on pre-treatment MRI were benign. The incorporation of MRI, when ordered by the referring physician, may decrease unnecessary follow-up imaging and/or biopsy if the initial US BI-RADS assessment and management recommendation were to be retrospectively updated.

KEY POINTS

• Of 309 BI-RADS 3 or 4 US masses with a corresponding mass on MRI, 140/309 (45%) demonstrated no enhancement whereas 169/309 (55%) demonstrated enhancement • All masses classified as BI-RADS 3 or 4 on US without enhancement on MRI were benign • MRI can rule out malignancy in non-enhancing US masses with an NPV of 100.

Which clinical, radiological, histological, and molecular parameters are associated with the absence of enhancement of known breast cancers with Contrast Enhanced Digital Mammography (CEDM)?

Background

CEDM has demonstrated a diagnostic performance similar to MRI and could have similar limitations in breast cancer (BC) detection.

Purpose

The aim of our study was to systematically analyze the characteristics of the lesions with the absence of enhancement with CEDMs, called false-negatives (FNs), in order to identify which clinical, radiological, histological and molecular parameters are associated with the absence of enhancement of known BCs with CEDMs, and which types of BC are most likely to cause FNs in CEDMs. We also tried to evaluate which parameters instead increased the probability of showing enhancement in the same context.

Materials and methods

Included in our study group were 348 women with 348 diagnosed BCs performing CEDM as preoperative staging. Two breast-imaging radiologists reviewed the CEDM exams. The absence of perceptible contrast enhancement at the index cancer site was indicative of an FN CEDM, whereas cases with appreciable enhancement were considered true positives (TPs). Dichotomic variables were analyzed with Fisher’s exact probability test or, when applicable, the chi-square test. Binary logistic regression was performed on variables shown to be significant by the univariate analysis in order to assess the relationship between predictors (independent variables) and TFNs (outcome).

Results

Enhancement was observed in 317 (91.1%) of the 348 BCs. From the 31 (8.9%) lesions which were FNs, we excluded 12 (38.7%) which showed an artifact generated by the post biopsy hematoma and 6 (19.4%) which were outside the CEDM field of vision. We thus obtained 13 (41.9%) BCs considered “True False Negatives” (TFNs), i.e. BCs which showed no enhancement despite being within the CEDM field of vision and failed to show post biopsy hematoma artifacts. We found that the TFNs frequently have a unifocal disease extension, diameter <10 mm, a lower number of luminal B HER2-subtypes, a higher number of DCIS, and an index lesion with microcalcifications.

Conclusions

The parameters we found to be associated with no enhancement of known BCs with CEDMs were: unifocal disease extension, DCIS histotype, lesion dimensions <10 mm, and index lesion with microcalcifications. The characteristics that instead increase the probability of showing enhancement were US mass, Luminal B HER2 negative molecular subtype, the presence of an invasive ductal component, and lesion dimensions ≥10 mm.

•

The variables associated with an increased risk of no enhancement were unifocal disease extension, non-classifiable molecular subtype, DCIS histotype, lesion dimensions <10 mm, index lesion represented by microcalcifications.

•

A greater probability of showing enhancement entailed the presence of an invasive ductal component, index lesion represented by ultrasound mass, Luminal B HER2 negative molecular subtype, lesion dimensions ≥10 mm, multifocal disease extension.

Fully automatic classification of breast MRI background parenchymal enhancement using a transfer learning approach

Marked enhancement of the fibroglandular tissue on contrast-enhanced breast magnetic resonance imaging (MRI) may affect lesion detection and classification and is suggested to be associated with higher risk of developing breast cancer. The background parenchymal enhancement (BPE) is qualitatively classified according to the BI-RADS atlas into the categories "minimal," "mild," "moderate," and "marked." The purpose of this study was to train a deep convolutional neural network (dCNN) for standardized and automatic classification of BPE categories.This IRB-approved retrospective study included 11,769 single MR images from 149 patients. The MR images were derived from the subtraction between the first post-contrast volume and the native T1-weighted images. A hierarchic approach was implemented relying on 2 dCNN models for detection of MR-slices imaging breast tissue and for BPE classification, respectively. Data annotation was performed by 2 board-certified radiologists. The consensus of the 2 radiologists was chosen as reference for BPE classification. The clinical performances of the single readers and of the dCNN were statistically compared using the quadratic Cohen's kappa.Slices depicting the breast were classified with training, validation, and real-world (test) accuracies of 98%, 96%, and 97%, respectively. Over the 4 classes, the BPE classification was reached with mean accuracies of 74% for training, 75% for the validation, and 75% for the real word dataset. As compared to the reference, the inter-reader reliabilities for the radiologists were 0.780 (reader 1) and 0.679 (reader 2). On the other hand, the reliability for the dCNN model was 0.815.Automatic classification of BPE can be performed with high accuracy and support the standardization of tissue classification in MRI.

Can Magnetic Resonance Imaging Replace Mammography and Ultrasonography for the Detection of Breast Lesions?

Objective We aimed to evaluate the role of magnetic resonance imaging (MRI) in the visualization of breast lesions and to estimate whether MRI can be a reliable alternative to mammography (MG) and ultrasonography (USG) for this purpose. Materials and methods In this retrospective, single-center study, an analysis of medical files of 260 patients with breast masses as breast imaging reports and data system (BI-RADS) 4 and 5 at MRI was performed. The features of the breast lump, such as the side, location, multi foci or multicentricity, histopathological diagnosis, contrast-enhancement characteristics, radiological, and pathological axillary involvement, were noted. Consistency between MRI-BIRADS and MG+USG-BIRADS, as well as the association between lesion characteristics, was sought. Results The agreement ratio between the BI-RADS categories of MRI and MG+USG was 0.654 while consistency between histopathological diagnosis and MRI BI-RADS category was 0.838. The agreement between the BI-RADS category of MG+USG and histopathological diagnosis was 0.819. The consistency between MRI BI-RADS and MG+USG BI-RADS increased remarkably with the advancement of age. Similarly, the consistency between MRI BI-RADS and histopathological diagnosis tends to increase with the advancement of age. Nonmass contrast enhancement yielded the highest agreement ratios between MRI BI-RADS and MG+USG BI-RADS, histopathological diagnosis and MRI BI-RADS, and histopathological diagnosis and MG+USG BI-RADS. Conclusion Dynamic MRI is a useful and reliable method for imaging breast neoplasms. However, it is not devoid of disadvantages such as cost, attainability, and contrast use and it should be reserved as a problem-solving technique to be used in conjunction with conventional methods including MG and USG.

Impact of Background Parenchymal Enhancement on Diagnostic Performance in Screening Breast MRI

RATIONALE AND OBJECTIVES

To evaluate the impact of background parenchymal enhancement (BPE) on diagnostic performance in screening breast magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Consecutive screening breast MRIs performed at our institution from 2011 to 2014 were reviewed in a HIPAA-compliant manner with institutional review board approval. BPE was extracted from radiology reports and examinations grouped into minimal/mild (lower) or moderate/marked (higher) BPE. Performance measures were compared between the two groups with Pearson's χ2 test and with logistic regression to adjust for possible confounders of age, screening indication, mammographic density, available prior MRI, and examination year, using lower BPE as the reference group.

RESULTS

For 4686 screening MRIs performed in 2446 women, BPE was reported as minimal or mild for 3975 (85%) examinations and moderate or marked for 711(15%). Following logistic regression to adjust for multiple confounders, abnormal interpretation rate (AIR) significantly differed between the two BPE groups. AIR was 13% (89/711) in the higher BPE group versus 7% (295/3975) in the lower BPE group with an adjusted odds ratio of 1.37 (95% confidence interval: 1.03, 1.82). After adjustment, all other performance metrics, including cancer detection rate, positive predictive value, sensitivity, and specificity did not significantly differ between the two BPE groups (P > 0.05).

CONCLUSION

Higher BPE on screening MRI is associated with higher abnormal interpretation rate, with no impact on cancer detection rate, sensitivity, or specificity.

Diagnostic value of molybdenum target combined with DCE-MRI in different types of breast cancer

This study compared the diagnostic value of molybdenum target and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in different types of breast cancer. A retrospective analysis was performed on 120 female patients with breast cancer admitted to The First Affiliated Hospital of Zhengzhou University from February 2015 to October 2017. All of them underwent DCE-MRI and molybdenum target examination. Postoperatively, the pathological tissues were examined to determine their molecular typing. The sensitivity and diagnostic coincidence rates of Luminal-B breast cancer with different molecular types diagnosed by molybdenum target combined with DCE-MRI were significantly higher than those of molybdenum target or DCE-MRI alone. There were no statistical differences in sensitivity and diagnostic coincidence rates of breast cancer with different molecular types diagnosed by molybdenum target or DCE-MRI alone between the two groups (P>0.05). Molybdenum target combined with DCE-MRI in the diagnosis of different molecular types of breast cancer is better than the single imaging screening, which is of great clinical significance in the development of individualized comprehensive treatment for breast cancer patients and worthy of wide promotion in clinical practice.

Use of Contrast-Enhanced MRI in Management of Discordant Core Biopsy Results

OBJECTIVE. Evaluating concordance between core biopsy results and imaging findings is an integral component of breast intervention. Pathologic results deemed benign discordant reflect concern that a malignancy may have been incorrectly sampled. Standard of care currently is surgical excision, although a large percentage of these lesions will be benign at final pathologic analysis. The purpose of this study was to determine whether inclusion of contrast-enhanced MRI would optimize patient care. MATERIALS AND METHODS. Forty-five patients with 46 lesions were identified who underwent contrast-enhanced MRI after receiving discordant ultrasound or stereotactic biopsy results between 2012 and mid 2018. These findings were classified BI-RADS category 4 at diagnostic imaging. Disease-positive was defined as all malignancies and borderline lesions. RESULTS. Fourteen patients had suspicious MRI findings; 31 patients did not. Negative or benign MRI findings were validated by stability at imaging follow-up of at least 1 year in 27 patients (28 lesions) and at least 6 months in four patients. Eight of the total of 46 discordant lesions were ultimately malignant, a rate of 17.3%, an expected result for BI-RADS 4 lesions. Sensitivity, specificity, positive predictive value, and negative predictive value of MRI calculated in the group of 41 patients (42 lesions) with documented stability for at least 1 year were 100%, 93.3%, 85.7%, and 100%. The false-negative rate of MRI was 0%; the false-positive rate was 2 of 30 (6.7%). CONCLUSION. In the management of discordant benign core biopsy results, contrast-enhanced MRI facilitated successful triage of patients to surgery; 31 of the original 45 patients (68.9%) avoided surgery.

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.

Large Non-enhancing Breast Cancer on Breast Magnetic Resonance Imaging: A Case Report

A 55-year-old female presented with vague symptoms in the lateral left breast. Digital breast tomosynthesis and breast ultrasound showed no focal lesion, and magnetic resonance imaging (MRI) was subsequently performed. No suspicious enhancement was seen on MRI; in particular, no suspicious lesion was seen in the area of clinical concern. In view of persisting focal mastalgia and vague parenchymal changes in the symptomatic area on repeat targeted ultrasound, a core biopsy was performed. Final pathology after left mastectomy with axillary clearance showed a 42 mm grade 2 invasive ductal carcinoma. Ten out of 15 lymph nodes contained metastatic carcinoma. This case report presents a large ductal breast cancer with no enhancement on breast MRI. Factors that may contribute to the non-detection of breast cancers on MRI studies will be discussed.

The frequency of missed breast cancers in women participating in a high-risk MRI screening program

Purpose

To evaluate the frequency of missed cancers on breast MRI in women participating in a high-risk screening program.

Methods

Patient files from women who participated in an increased risk mammography and MRI screening program (2003–2014) were coupled to the Dutch National Cancer Registry. For each cancer detected, we determined whether an MRI scan was available (0–24 months before cancer detection), which was reported to be negative. These negative MRI scans were in consensus re-evaluated by two dedicated breast radiologists, with knowledge of the cancer location. Cancers were scored as invisible, minimal sign, or visible. Additionally, BI-RADS scores, background parenchymal enhancement, and image quality (IQ; perfect, sufficient, bad) were determined. Results were stratified by detection mode (mammography, MRI, interval cancers, or cancers in prophylactic mastectomies) and patient characteristics (presence of BRCA mutation, age, menopausal state).

Results

Negative prior MRI scans were available for 131 breast cancers. Overall 31% of cancers were visible at the initially negative MRI scan and 34% of cancers showed a minimal sign. The presence of a BRCA mutation strongly reduced the likelihood of visible findings in the last negative MRI (19 vs. 46%, P < 0.001). Less than perfect IQ increased the likelihood of visible findings and minimal signs in the negative MRI (P = 0.021).

Conclusion

This study shows that almost one-third of cancers detected in a high-risk screening program are already visible at the last negative MRI scan, and even more in women without BRCA mutations. Regular auditing and double reading for breast MRI screening is warranted.

Effect of Background Parenchymal Enhancement on Breast MR Imaging Interpretive Performance in Community-based Practices

Purpose To evaluate the effect of background parenchymal enhancement (BPE) on breast magnetic resonance (MR) imaging interpretive performance in a large multi-institutional cohort with independent analysis of screening and diagnostic MR studies. Materials and Methods Analysis of 3770 breast MR studies was conducted. Examinations were performed in 2958 women at six participating facilities in the San Francisco Bay Area from January 2010 to October 2012. Findings were recorded prospectively in the San Francisco Mammography Registry. Performance measures were compared between studies with low BPE (mild or minimal) and those with high BPE (moderate or marked) by using binomial tests of proportions. Results Of 1726 MR imaging studies in the screening group, 1301 were classified as having low BPE and 425 were classified as having high BPE (75% vs 25%, respectively; P < .001). Of 2044 MR imaging studies in the diagnostic group, 1443 were classified as having low BPE and 601 were classified as having high BPE (71% vs 29%, respectively; P < .001). For low versus high BPE groups at screening, abnormal interpretation rate was 157 of 1301 versus 111 of 424 (12% vs 26%, P < .001); biopsy recommendation rate was 85 of 1301 versus 54 of 424 (7% vs 13%, P < .001); and specificity was 89% (95% confidence interval [CI]: 87, 91) versus 75% (95% CI: 71, 80) (P = .01). For the low versus high BPE groups at diagnostic MR imaging, biopsy recommendation rate was 325 of 1443 versus 195 of 601 (23% vs 32%, P < .001); and specificity was 86% (95% CI: 84, 88) versus 75% (95% CI: 74, 82) (P < .001). There were no significant differences between studies with low versus high BPE in sensitivity for screening (76% [95% CI: 55, 91] vs 83% [95% CI: 52, 98]; P = .94) or diagnostic (93% [95% CI: 87, 97] vs 96% [95% CI: 87, 99]; P = .69) MR imaging, nor were there significant differences in cancer detection rate per 1000 patients between the low BPE versus high BPE groups for screening (15 per 1000 vs 24 per 1000, P = .30) or diagnostic (78 per 1000 vs 85 per 1000, P = .64) MR imaging. Conclusion Relative to MR studies with minimal or mild BPE, those with moderate or marked BPE were associated with higher abnormal interpretation and biopsy rates and lower specificity, with no difference in cancer detection rate. ^© RSNA, 2017 Online supplemental material is available for this article.

Discrepancies Between Pathological Tumor Responses and Estimations of Complete Response by Magnetic Resonance Imaging After Neoadjuvant Chemotherapy Differ by Breast Cancer Subtype

INTRODUCTION

The influence of breast cancer (BC) subtype in discrepancies between pathologic complete response (pCR) and complete response by magnetic resonance imaging (MRI-CR) after neoadjuvant chemotherapy (NAC) have not been discussed well. We evaluated the association between BC subtype and pCR or only residual in situ lesion without invasive cancer (pCR/in situ⁺) in patients with MRI-CR (positive predictive value [PPV]).

MATERIAL AND METHODS

From the data of 716 patients with primary BC who were diagnosed with invasive cancer and treated with NAC and then surgery from January 2009 to May 2014 at St. Luke's International Hospital, 180 patients were determined to have MRI-CR by retrospective chart review. BC subtypes at baseline were classified into 6 subtypes, as strong estrogen receptor (ER⁺⁺), moderately positive ER (ER⁺), negative ER (ER^-), and HER2 status expression.

RESULTS

Three subtypes had PPV (pCR) ≥ 50%: ER^-/HER2⁺ (56.3%, 27/48), ER^-/HER2^- (57.6%, 34/59), and ER⁺/HER2⁺ (56.2%, 9/16). However, PPV (pCR) for the ER⁺⁺/HER2^- and ER⁺⁺/HER2⁺ subtypes was < 30%; notably, only 12.0% (3/25) for the ER⁺⁺/HER2^- subtype, which was significantly low (P < .001) compared with ER⁺⁺/HER2^- and other subtypes. PPV (pCR/in situ⁺) was significantly low at 20.0% in the ER⁺⁺/HER2^- subtype (P < .001 compared with other subtypes). PPV (pCR/in situ⁺) in other subtypes was collectively greater than 60%, and was 91.7% in the ER^-/HER2⁺ subtype.

CONCLUSION

We should interpret carefully MRI-CR of NAC to evaluate residual disease for ER⁺⁺/HER2^- BC.

False-negative contrast-enhanced spectral mammography: use of more than one imaging modality and application of the triple test avoids misdiagnosis

A 50-year-old woman presented with chest tenderness. On examination, both breasts were lumpy. Bilateral mammography showed heterogeneously dense parenchyma, with possible stromal distortion laterally on the right at the 0900 position. On ultrasound (US), a corresponding 13×9×10 mm irregular hypoechoic mass with internal vascularity was noted and both breasts had a complex heterogeneous fibroglandular background pattern. US-guided core biopsy with marker clip insertion was performed with the diagnosis of a grade 2 invasive ductal carcinoma (IDC). In view of the parenchymal pattern on mammography and US, contrast-enhanced spectral mammography (CESM) was performed for local staging. Mild background enhancement was noted, but there was no enhancement at the lesion site. The patient elected to have bilateral mastectomies and sentinel node biopsies. Final histopathology showed a node negative 11 mm grade 2 oestrogen and progesterone receptor positive, IDC.

A comparison study between gross tumor volumes defined by preoperative magnetic resonance imaging, postoperative specimens, and tumor bed for radiotherapy after breast-conserving surgery

BACKGROUND

The identification and contouring of target volume is important for breast-conserving therapy. The aim of the study was to compare preoperative magnetic resonance imaging (MRI), postoperative pathology, excised specimens' (ES) size, and tumor bed (TB) delineation as methods for determining the gross tumor volume (GTV) for radiotherapy after breast-conserving surgery (BCS).

METHODS

Thirty-three patients with breast cancer who underwent preoperative MRI and radiotherapy after BCS were enrolled. The GTVs determined by MRI, pathology, and the ES were defined as GTVMRI, GTVPAT, and GTVES, respectively. GTVMRI+1 was defined as a 1.0-cm margin around the GTVMRI. The radiation oncologist delineated GTV of the TB (GTVTB) using planning computed tomography according to ≥5 surgical clips placed in the lumpectomy cavity (LC).

RESULTS

The median GTVMRI, GTVMRI+1, GTVPAT, GTVES, and GTVTB were 0.97 cm (range, 0.01-6.88), 12.58 cm (range, 3.90-34.13), 0.97 cm (range, 0.01-6.36), 15.46 cm (range, 1.15-70.69), and 19.24 cm (range, 4.72-54.33), respectively. There were no significant differences between GTVMRI and GTVPAT, GTVMRI+1 and GTVES, GTVES and GTVTB (P = 0.188, 0.070, and 0.264, respectively). GTVMRI is positively related with GTVPAT. However, neither GTVES nor GTVTB correlated with GTVMRI (P = 0.071 and 0.378, respectively). Furthermore, neither GTVES nor GTVTB correlated with GTVMRI+1 (P = 0.068 and 0.375, respectively).

CONCLUSION

When ≥5 surgical clips were placed in the LC for BCS, the volume of TB was consistent with the volume of ES. Neither the volume of TB nor the volume of ES correlated significantly with the volume of tumor defined by preoperative MRI.

An integrated cell line-based discovery strategy identified follistatin and kallikrein 6 as serum biomarker candidates of breast carcinoma

Secreted proteins constitute a relevant source of putative cancer biomarkers. Here, we compared the secretome of a series of four genetically-related breast cancer cell lines as a model of aggressiveness using quantitative mass spectrometry. 537 proteins (59.5% of the total identified proteins) predicted to be released or shed from cells were identified. Using a scoring system based on i) iTRAQ value, ii) breast cancer tissue mRNA expression levels, and iii) immunohistochemical staining (public database), a short list of 10 candidate proteins was selected. Using specific ELISA assays, the expression level of the top five proteins was measured in a verification set of 56 patients. The four significantly differentially expressed proteins were then validated in a second independent set of 353 patients. Finally, follistatin (FST) and kallikrein 6 (KLK6) in serum were significantly higher (p-value < 0.0001) in invasive breast cancer patients compared with non-cancerous controls. Using specific cut-off values, FST distinguished breast cancer samples from healthy controls with a sensitivity of 65% and an accuracy of 68%, whereas KLK6 achieved a sensitivity of 55% and an accuracy of 61%. Therefore, we concluded that FST and KLK6 may have significance in breast cancer detection.

BIOLOGICAL SIGNIFICANCE

Discovery of new serum biomarkers that exhibit increased sensitivity and specificity compared to current biomarkers appears to be an essential field of research in cancer. Most biological markers show insufficient diagnostic sensitivity for early breast cancer detection and, for the majority of them, their concentrations are elevated only in metastatic forms of the disease. It is therefore essential to identify clinically reliable biomarkers and develop effective approaches for cancer diagnosis. One promising approach in this field is the study of secreted proteins through proteomic analysis of in vitro progression breast cancer models. Here we have shown that FST and KLK6 are elevated in breast cancer patient serum compared to healthy controls. We expect that our discovery strategy will help to identify cancer-specific and body-fluid-accessible biomarkers.

Breast Background Parenchymal Enhancement on Screening Magnetic Resonance Imaging in Women Who Received Chest Radiotherapy for Childhood Hodgkin's Lymphoma

RATIONALE AND OBJECTIVES

Breast magnetic resonance imaging (MRI) is recommended for the screening of women with a history of chest radiotherapy and consequent increased breast cancer risk. The purpose of this study was to evaluate the impact of prior chest radiotherapy on breast tissue background parenchymal enhancement (BPE) at screening breast MRI.

MATERIALS AND METHODS

A departmental database was reviewed to identify asymptomatic women with either a history of chest radiotherapy for Hodgkin's lymphoma or age-matched controls who underwent screening breast MRI between 2009 and 2013. MRI studies were analyzed on an automated breast MRI viewing platform to calculate breast BPE and breast density.

RESULTS

A total of 61 cases (mean age 41.6 ± 6.75 years) and 61 controls (mean age 40.8 ± 6.99 years) were included. The age of patients at the time of chest radiotherapy was 22.6 ± 8.17 years. Screening MRI was performed 19.0 ± 7.43 years after chest radiotherapy. BPE was significantly higher in patients who received chest radiotherapy (50% vs. 37%, P <0.01). A weak to moderate positive correlation (r > 0.3; P < 0.03) was found between BPE and number of years post radiotherapy. There was a trend toward significant difference between the two groups in the correlation of BPE and age (P = 0.05). Breast density was not significantly different between the two groups.

CONCLUSIONS

BPE is significantly greater in women who receive chest radiotherapy for childhood Hodgkin's lymphoma, and unexpectedly, it positively correlates with the number of years passed after radiation therapy. Long-term biological effects of radiation therapy on breast parenchyma need further research.

Comparative accuracy of preoperative tumor size assessment on mammography, sonography, and MRI: Is the accuracy affected by breast density or cancer subtype?

PURPOSE

To compare the accuracy of preoperative breast tumor size measurements obtained on three imaging modalities (mammography [MM], sonography [US], and MRI) with those obtained on final pathologic examination for different breast densities and various tumor types.

METHODS

Records from patients who underwent breast cancer lumpectomy between 2008 and 2012 and in whom tumor was seen on all three imaging modalities were retrospectively reviewed for maximum tumor size measurements. Patients with positive tumor margins and those who had undergone neoadjuvant chemotherapy were excluded. Tumor size measurements obtained on the three imaging modalities were compared for accuracy with those obtained during the final pathologic examination. Differences were analyzed for the whole group and for subgroups according to breast density and tumor type.

RESULTS

In total, 57 patients were included, in whom wire-localization lumpectomy was performed without neoadjuvant chemotherapy; negative surgical margins for tumor were obtained, and tumor was preoperatively visualized on all three imaging modalities. The mean (± SEM) tumor size measured on MRI was significantly greater than that measured on pathology (p < 0.001), whereas the sizes measured on US and MM were not statistically significantly different from that measured on pathology (p = 0.62 and p = 0.57). Tumor size measured on MRI was greater than that measured on both US and MM (p = 0.003 and p < 0.001). Compared with the measurements obtained on pathology, that obtained on US showed moderate agreement (Lin concordance correlation coefficient [CCC], 0.71; 95% confidence interval [CI], 0.56-0.82); poorer agreement was found for the sizes obtained on MM (CCC, 0.58; 95% CI, 0.38-0.72) and MRI (CCC, 0.50; 95% CI, 0.31-0.65). No difference in comparative accuracy of size measurement was noted between dense and nondense breast tissue. MRI overestimated tumor size in ductal cancers (p < 0.001) and slightly underestimated it in lobular cancers.

CONCLUSIONS

Preoperative MRI significantly overestimated tumor size. Measurements obtained on US and MM were more accurate irrespective of breast density, with US measurements being slightly more accurate than MM measurements.

Computerized breast mass detection using multi-scale Hessian-based analysis for dynamic contrast-enhanced MRI

This study aimed to investigate a computer-aided system for detecting breast masses using dynamic contrast-enhanced magnetic resonance imaging for clinical use. Detection performance of the system was analyzed on 61 biopsy-confirmed lesions (21 benign and 40 malignant lesions) in 34 women. The breast region was determined using the demons deformable algorithm. After the suspicious tissues were identified by kinetic feature (area under the curve) and the fuzzy c-means clustering method, all breast masses were detected based on the rotation-invariant and multi-scale blob characteristics. Subsequently, the masses were further distinguished from other detected non-tumor regions (false positives). Free-response operating characteristics (FROC) curve and detection rate were used to evaluate the detection performance. Using the combined features, including blob, enhancement, morphologic, and texture features with 10-fold cross validation, the mass detection rate was 100 % (61/61) with 15.15 false positives per case and 91.80 % (56/61) with 4.56 false positives per case. In conclusion, the proposed computer-aided detection system can help radiologists reduce inter-observer variability and the cost associated with detection of suspicious lesions from a large number of images. Our results illustrated that breast masses can be efficiently detected and that enhancement and morphologic characteristics were useful for reducing non-tumor regions.

Does background parenchymal enhancement on MRI affect the rate of positive resection margin in breast cancer patients?

OBJECTIVE

The purpose of our study was to evaluate whether strong background parenchymal enhancement (BPE) would be a significant independent factor associated with positive resection margin in patients treated initially with breast-conserving surgery (BCS).

METHODS

Retrospective evaluation of breast MRI examinations of 314 patients with breast cancer was carried out. Breast cancer was histologically confirmed in all patients who underwent BCS from January 2008 to December 2010. BPE was dichotomized into weak (minimal or mild) and strong (moderate or marked) enhancement for statistical analysis. Histopathological features of attained specimens were evaluated by an experienced pathologist and were also dichotomized for statistical analysis.

RESULTS

On univariate analysis, positive extensive intraductal component (p < 0.001), strong BPE (p = 0.001) and human epidermal growth factor receptor 2 (HER2) positivity (p = 0.08) had significant association with positive surgical margin. Tumour size, axillary lymph node metastasis, nuclear grade, histological grade, lymphovascular invasion, oestrogen receptor and progesterone receptor did not show significant correlation with positive surgical margin. On multivariate analysis, the significant independent predictors were extensive intraductal component [odds ratio, 5.68; 95% confidence interval (CI), 2.72-11.82] and strong BPE (odds ratio, 2.39; 95% CI, 1.20-4.78).

CONCLUSION

Strong BPE is a significant independent factor for positive resection margin along with positive extensive intraductal component, and performing MRI during the period of lower parenchymal enhancement is needed in patients with strong BPE.

ADVANCES IN KNOWLEDGE

As far as we know, this is the first study to reveal that BPE is a significant independent factor associated with positive resection margin.

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.

A multiparametric serum marker panel as a complementary test to mammography for the diagnosis of node-negative early-stage breast cancer and DCIS in young women

BACKGROUND

The sensitivity of mammography for the detection of small lesions, including node-negative early-stage (T1N0) primary breast cancer (PBC) and ductal carcinoma in situ (DCIS), is significantly decreased in young patients. From a clinical standpoint, an inconclusive mammogram reflects the inability of clinicians to confidently decide whether patients should be referred for biopsy or for follow-up with repeat imaging.

METHODS

Specific ELISAs were developed for a panel of 13 well-recognized breast autoantigens (HSP60, FKBP52, PRDX2, PPIA, MUC1, GAL3, PAK2, P53, CCNB1, PHB2, RACK1, RUVBL1, and HER2). Circulating autoantibody levels were measured in a cohort of 396 serum samples from histologically confirmed DCIS (n = 87) or T1N0 PBC (n = 153) and healthy controls (n = 156).

RESULTS

Individually, antibodies against CCNB1, FKBP52, GAL3, PAK2, PRDX2, PPIA, P53, and MUC1 demonstrated discriminatory power between breast cancer and healthy control groups. At 90% sensitivity, the overall combined specificity of the autoantibody serum screening test was 42%. Adjustment for higher sensitivities of 95% and 99% resulted in 30% and 21% specificities, respectively (33% and 18% in T1N0 PBC and 28% and 21% in DCIS). Finally, in patients with node-negative early-stage breast cancer younger than 50 years, the autoantibody assay exhibited 59% specificity with a fixed sensitivity at 90%.

CONCLUSIONS

Our autoantibody panel allows accurate detection of early breast cancer and DCIS, notably in younger patients.

IMPACT

Clinical assessment of this autoantibody panel displays a potential to facilitate clinical management of early-stage breast cancer detection in cases of inconclusive mammogram.

Evaluation of the role of dynamic contrast-enhanced MR imaging for patients with BI-RADS 3-4 microcalcifications

Objective

The purpose of study was to prospectively evaluate the diagnostic performance of dynamic contrast-enhanced MR imaging in the differentiation of malignant lesions from benign ones in patients with BI-RADS 3–4 microcalcifications detected by mammography.

Materials and Methods

93 women with 100 microcalcifications had undergone breast MRI from June 2010 to July 2013. Subsequently, 91 received open biopsy and 2 received stereotactic vacuum-assisted biopsy. All results were compared with histological findings. The PPV, NPV and area under curve (AUC) of the mammography and breast MRI were calculated.

Results

There were 31 (31.0%) BI-RADS 3 microcalcifications and 69 (69.0%) BI-RADS 4. The PPV and NPV of mammography is 65.2% (45/69) and 90.3% (28/31). The PPV and NPV of breast MRI was 90.2% (46/51) and 95.9% (47/49). Among 31 BI-RADS 3 microcalcifications, the PPV and NPV of breast MRI was 100% (3/3) and 100% (28/28). Among 69 BI-RADS 4 microcalcifications, the PPV and NPV of breast MRI was 89.6% (43/48) and 90.5% (19/21). The AUC of mammography and breast MRI assessment were 0.738 (95% CI, 0.639–0.837) and 0.931 (95% CI, 0.874–0.988) (p<0.05).

Conclusion

Dynamic contrast-enhanced MR imaging of breast is able to be applied to predict the risk of malignance before follow-up for BI-RADS 3 microcalcifications and biopsy for BI-RADS 4 microcalcifications.

A new user-friendly visual environment for breast MRI data analysis

In this paper a novel, user friendly visual environment for Breast MRI Data Analysis is presented (BreDAn). Given planar MRI images before and after IV contrast medium injection, BreDAn generates kinematic graphs, color maps of signal increase and decrease and finally detects high risk breast areas. The advantage of BreDAn, which has been validated and tested successfully, is the automation of the radiodiagnostic process in an accurate and reliable manner. It can potentially facilitate radiologists' workload.

Pearls and pitfalls in breast MRI

At our academic institution, we have noticed repeated examples of both false-positive and false-negative MR diagnoses in breast cancer. The most common diagnostic errors in interpreting MRI of the breast are discussed in this review and experience-based advice is provided to avoid similar mistakes. The most common reasons for false-positive diagnoses are misinterpretation of artefacts, confusion between normal enhancing structures and tumours and, above all, insufficient use of the American College of Radiology breast imaging reporting and data system lexicon, whereas false-negative diagnoses are made as a result of missed tiny enhancement, a background-enhancing breast, or enhancement interpreted as benign rather than malignant.