Magnetic resonance imaging of the breast: recommendations from the EUSOMA working group

Applications of T1 and T2 relaxation time calculation in tissue differentiation and cancer diagnostics-a systematic literature review

INTRODUCTION

The purpose of this review was to summarize current applications of non-contrast-enhanced quantitative magnetic resonance imaging (qMRI) in tissue differentiation, considering healthy tissues as well as comparisons of malignant and benign samples. The analysis concentrates mainly on the epithelium and epithelial breast tissue, especially breast cancer.

METHODS

A systematic review has been performed based on current recommendations by publishers and foundations. An exhaustive overview of currently used techniques and their potential in medical sciences was obtained by creating a search strategy and explicit inclusion and exclusion criteria.

RESULTS AND DISCUSSION

PubMed and Elsevier (Scopus & Science Direct) search was narrowed down to studies reporting T1 or T2 values of human tissues, resulting in 404 initial candidates, out of which roughly 20% were found relevant and fitting the review criteria. The nervous system, especially the brain, and connective tissue such as cartilage were the most frequently analyzed, while the breast remained one of the most uncommon subjects of studies. There was little agreement between published T1 or T2 values, and methodologies and experimental setups differed strongly. Few contemporary (after 2000) resources have been identified that were dedicated to studying the relaxation times of tissues and their diagnostic applications. Most publications concentrate on recommended diagnostic standards, for example, breast acquisition of T1- or T2-weighted images using gadolinium-based contrast agents. Not enough data is available yet to decide how repeatable or reliable analysis of relaxation times is in diagnostics, so it remains mainly a research topic. So far, qMRI might be recommended as a diagnostic help providing general insight into the nature of lesions (benign vs. malignant). However, additional means are generally necessary to differentiate between specific lesion types.

Staging Breast Cancer with MRI, the T. A Key Role in the Neoadjuvant Setting

Breast cancer (BC) is the most common cancer among women worldwide. Neoadjuvant chemotherapy (NACT) indications have expanded from inoperable locally advanced to early-stage breast cancer. Achieving a pathological complete response (pCR) has been proven to be an excellent prognostic marker leading to better disease-free survival (DFS) and overall survival (OS). Although diagnostic accuracy of MRI has been shown repeatedly to be superior to conventional methods in assessing the extent of breast disease there are still controversies regarding the indication of MRI in this setting. We intended to review the complex literature concerning the tumor size in staging, response and surgical planning in patients with early breast cancer receiving NACT, in order to clarify the role of MRI. Morphological and functional MRI techniques are making headway in the assessment of the tumor size in the staging, residual tumor assessment and prediction of response. Radiomics and radiogenomics MRI applications in the setting of the prediction of response to NACT in breast cancer are continuously increasing. Tailored therapy strategies allow considerations of treatment de-escalation in excellent responders and avoiding or at least postponing breast surgery in selected patients.

Precision Medicine in Breast Cancer: Do MRI Biomarkers Identify Patients Who Truly Benefit from the Oncotype DX Recurrence Score® Test?

The aim of this study was to combine breast MRI-derived biomarkers with clinical-pathological parameters to identify patients who truly need an Oncotype DX Breast Recurrence Score® (ODXRS) genomic assay, currently used to predict the benefit of adjuvant chemotherapy in ER-positive/HER2-negative early breast cancer, with the ultimate goal of customizing therapeutic decisions while reducing healthcare costs. Patients who underwent a preoperative multiparametric MRI of the breast and ODXRS tumor profiling were retrospectively included in this study. Imaging sets were evaluated independently by two breast radiologists and classified according to the 2013 American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) lexicon. In a second step of the study, a combined oncologic and radiologic assessment based on clinical-pathological and radiological data was performed, in order to identify patients who may need adjuvant chemotherapy. Results were correlated with risk levels expressed by ODXRS, using the decision made on the basis of the ODXRS test as a gold standard. The χ2 test was used to evaluate associations between categorical variables, and significant ones were further investigated using logistic regression analyses. A total of 58 luminal-like, early-stage breast cancers were included. A positive correlation was found between ODXRS and tumor size (p = 0.003), staging (p = 0.001) and grading (p = 0.005), and between BI-RADS categories and ODXRS (p < 0.05 for both readers), the latter being confirmed at multivariate regression analysis. Moreover, BI-RADS categories proved to be positive predictors of the therapeutic decision taken after performing an ODXRS assay. A statistically significant association was also found between the therapeutic decision based on the ODXRS and the results of combined onco-radiologic assessment (p < 0.001). Our study suggests that there is a correlation between BI-RADS categories at MRI and ODXRS and that a combined onco-radiological assessment may predict the decision made on the basis of the results of ODXRS genomic test.

Digital Breast Tomosynthesis versus MRI as an Adjunct to Full-Field Digital Mammography for Preoperative Evaluation of Breast Cancer according to Mammographic Density

OBJECTIVE

To compare digital breast tomosynthesis (DBT) and MRI as an adjunct to full-field digital mammography (FFDM) for the preoperative evaluation of women with breast cancer based on mammographic density.

MATERIALS AND METHODS

This retrospective study enrolled 280 patients with breast cancer who had undergone FFDM, DBT, and MRI for preoperative local tumor staging. Three radiologists independently sought the index cancer and additional ipsilateral and contralateral breast cancers using either FFDM alone, DBT plus FFDM, or MRI plus FFDM. Diagnostic performances across the three radiologists were compared among the reading modes in all patients and subgroups with dense (n = 186) and non-dense breasts (n = 94) according to mammographic density.

RESULTS

Of 280 patients, 46 (16.4%) had 48 additional (39 ipsilateral and nine contralateral) cancers in addition to the index cancer. For index cancers, both DBT plus FFDM and MRI plus FFDM showed sensitivities of 100% in the non-dense group. In the dense group, DBT plus FFDM showed lower sensitivity than that of MRI plus FFDM (94.6% vs. 99.6%, p < 0.001). For additional ipsilateral cancers, DBT plus FFDM showed specificity and positive predictive value (PPV) of 100% in the non-dense group, but sensitivity and negative predictive value (NPV) were not statistically different from those of MRI plus FFDM (p > 0.05). In the dense group, DBT plus FFDM showed higher specificity (98.2% vs. 94.1%, p = 0.005) and PPV (83.1% vs. 65.4%; p = 0.036) than those of MRI plus FFDM, but lower sensitivity (59.9% vs. 75.3%; p = 0.049). For contralateral cancers, DBT plus FFDM showed higher specificity than that of MRI plus FFDM (99.0% vs. 96.7%, p = 0.014), however, the other values did not differ (all p > 0.05) in the dense group.

CONCLUSION

DBT plus FFDM showed an overall higher specificity than that of MRI plus FFDM regardless of breast density, perhaps without substantial loss in sensitivity and NPV in the diagnosis of additional cancers. Thus, DBT may have the potential to be used as a preoperative breast cancer staging tool.

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.

Simplified intravoxel incoherent motion DWI for differentiating malignant from benign breast lesions

Background

To evaluate simplified intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for differentiating malignant versus benign breast lesions as (i) stand-alone tool and (ii) add-on to dynamic contrast-enhanced magnetic resonance imaging.

Methods

1.5-T DWI data (b = 0, 50, 250, 800 s/mm²) were retrospectively analysed for 126 patients with malignant or benign breast lesions. Apparent diffusion coefficient (ADC) ADC (0, 800) and IVIM-based parameters D₁′ = ADC (50, 800), D₂′ = ADC (250, 800), f₁′ = f (0, 50, 800), f₂′ = f (0, 250, 800) and D*′ = D* (0, 50, 250, 800) were voxel-wise calculated without fitting procedures. Regions of interest were analysed in vital tumour and perfusion hot spots. Beside the single parameters, the combined use of D₁′ with f₁′ and D₂′ with f₂′ was evaluated. Lesion differentiation was investigated for lesions (i) with hyperintensity on DWI with b = 800 s/mm² (n = 191) and (ii) with suspicious contrast-enhancement (n = 135).

Results

All lesions with suspicious contrast-enhancement appeared also hyperintense on DWI with b = 800 s/mm². For task (i), best discrimination was reached for the combination of D₁′ and f₁′ using perfusion hot spot regions-of-interest (accuracy 93.7%), which was higher than that of ADC (86.9%, p = 0.003) and single IVIM parameters D₁′ (88.0%) and f₁′ (87.4%). For task (ii), best discrimination was reached for single parameter D₁′ using perfusion hot spot regions-of-interest (92.6%), which were slightly but not significantly better than that of ADC (91.1%) and D₂′ (88.1%). Adding f₁′ to D₁′ did not improve discrimination.

Conclusions

IVIM analysis yielded a higher accuracy than ADC. If stand-alone DWI is used, perfusion analysis is of special relevance.

Do body composition parameters correlate with response to targeted therapy in ER+/HER2- metastatic breast cancer patients? Role of sarcopenia and obesity

Purpose

To investigate the association between body composition parameters, sarcopenia, obesity and prognosis in patients with metastatic ER+/HER2- breast cancer under therapy with cyclin-dependent kinase (CDK) 4/6 inhibitors.

Methods

92 patients with biopsy-proven metastatic ER+/HER2- breast cancer, treated with CDK 4/6 inhibitors between 2018 and 2021 at our center, were included in this retrospective analysis. Visceral Adipose Tissue (VAT), Subcutaneous Adipose Tissue (SAT) and Skeletal Muscle Index (SMI) were measured before starting therapy with CDK 4/6 inhibitors (Palbociclib, Abemaciclib or Ribociclib). Measurements were performed on a computed tomography-derived abdominal image at third lumbar vertebra (L3) level by an automatic dedicated software (Quantib body composition^®, Rotterdam, Netherlands). Visceral obesity was defined as a VAT area > 130 cm². Sarcopenia was defined as SMI < 40 cm²/m². Changes in breast lesion size were evaluated after 6 months of treatment. Response to therapy was assessed according to RECIST 1.1 criteria. Spearman’s correlation and χ² analyses were performed.

Results

Out of 92 patients, 30 were included in the evaluation. Of the 30 patients (mean age 53 ± 12 years), 7 patients were sarcopenic, 16 were obese, while 7 patients were neither sarcopenic nor obese. Statistical analyses showed that good response to therapy was correlated to higher SMI values (p < 0.001), higher VAT values (p = 0.008) and obesity (p = 0.007); poor response to therapy was correlated to sarcopenia (p < 0.001). Moreover, there was a significant association between sarcopenia and menopause (p = 0.021) and between sarcopenia and the persistence of axillary lymphadenopathies after treatment (p = 0.003), while the disappearance of axillary lymphadenopathies was associated with obesity (p = 0.028).

Conclusions

There is a growing interest in body composition, especially in the field of breast cancer. Our results showed an interesting correlation between sarcopenia and progression of disease, and demonstrated that VAT can positively influence the response to targeted therapy with CDK 4/6 inhibitors. Larger-scale studies are needed to confirm these preliminary results.

Clinical Relevance

Sarcopenia and obesity seem to predict negative outcomes in many oncologic entities. Their prevalence and impact in current breast cancer care are promising but still controversial.

A Score to Predict the Malignancy of a Breast Lesion Based on Different Contrast Enhancement Patterns in Contrast-Enhanced Spectral Mammography

Background: To create a predictive score of malignancy of a breast lesion based on the main contrast enhancement features ascertained by contrast-enhanced spectral mammography (CESM). Methods: In this single-centre prospective study, patients with suspicious breast lesions (BIRADS > 3) were enrolled between January 2013 and February 2022. All participants underwent CESM prior to breast biopsy, and eventually surgery. A radiologist with 20 years’ experience in breast imaging evaluated the presence or absence of enhancement and the following enhancement descriptors: intensity, pattern, margin, and ground glass. A score of 0 or 1 was given for each descriptor, depending on whether the enhancement characteristic was predictive of benignity or malignancy (both in situ and invasive). Then, an overall enhancement score ranging from 0 to 4 was obtained. The histological results were considered the gold standard in the evaluation of the relationship between enhancement patterns and malignancy. Results: A total of 321 women (median age: 51 years; range: 22−83) with 377 suspicious breast lesions were evaluated. Two hundred forty-nine lesions (66%) have malignant histological results (217 invasive and 32 in situ). Considering an overall enhancement score ≥ 2 as predictive of malignancy, we obtain an overall sensitivity of 92.4%; specificity of 89.8%; positive predictive value of 94.7%; and negative predictive value of 85.8%. Conclusions: Our proposed predictive score on the enhancement descriptors of CESM to predict the malignancy of a breast lesion shows excellent results and can help in early breast cancer diagnosis and in avoiding unnecessary biopsies.

Understanding Breast Cancers through Spatial and High-Resolution Visualization Using Imaging Technologies

Breast cancer is the most common cancer affecting women worldwide. Although many analyses and treatments have traditionally targeted the breast cancer cells themselves, recent studies have focused on investigating entire cancer tissues, including breast cancer cells. To understand the structure of breast cancer tissues, including breast cancer cells, it is necessary to investigate the three-dimensional location of the cells and/or proteins comprising the tissues and to clarify the relationship between the three-dimensional structure and malignant transformation or metastasis of breast cancers. In this review, we aim to summarize the methods for analyzing the three-dimensional structure of breast cancer tissue, paying particular attention to the recent technological advances in the combination of the tissue-clearing method and optical three-dimensional imaging. We also aimed to identify the latest methods for exploring the relationship between the three-dimensional cell arrangement in breast cancer tissues and the gene expression of each cell. Finally, we aimed to describe the three-dimensional imaging features of breast cancer tissues using noninvasive photoacoustic imaging methods.

The potential of predictive and prognostic breast MRI (P2-bMRI)

Magnetic resonance imaging (MRI) is an important part of breast cancer diagnosis and multimodal workup. It provides unsurpassed soft tissue contrast to analyse the underlying pathophysiology, and it is adopted for a variety of clinical indications. Predictive and prognostic breast MRI (P2-bMRI) is an emerging application next to these indications. The general objective of P2-bMRI is to provide predictive and/or prognostic biomarkers in order to support personalisation of breast cancer treatment. We believe P2-bMRI has a great clinical potential, thanks to the in vivo examination of the whole tumour and of the surrounding tissue, establishing a link between pathophysiology and response to therapy (prediction) as well as patient outcome (prognostication). The tools used for P2-bMRI cover a wide spectrum: standard and advanced multiparametric pulse sequences; structured reporting criteria (for instance BI-RADS descriptors); artificial intelligence methods, including machine learning (with emphasis on radiomics data analysis); and deep learning that have shown compelling potential for this purpose. P2-bMRI reuses the imaging data of examinations performed in the current practice. Accordingly, P2-bMRI could optimise clinical workflow, enabling cost savings and ultimately improving personalisation of treatment. This review introduces the concept of P2-bMRI, focusing on the clinical application of P2-bMRI by using semantic criteria.

Machine learning for multi-parametric breast MRI: radiomics-based approaches for lesion classification

In the artificial intelligence era, machine learning (ML) techniques have gained more and more importance in the advanced analysis of medical images in several fields of modern medicine. Radiomics extracts a huge number of medical imaging features revealing key components of tumor phenotype that can be linked to genomic pathways. The multi-dimensional nature of radiomics requires highly accurate and reliable machine-learning methods to create predictive models for classification or therapy response assessment.

Multi-parametric breast magnetic resonance imaging (MRI) is routinely used for dense breast imaging as well for screening in high-risk patients and has shown its potential to improve clinical diagnosis of breast cancer. For this reason, the application of ML techniques to breast MRI, in particular to multi-parametric imaging, is rapidly expanding and enhancing both diagnostic and prognostic power. In this review we will focus on the recent literature related to the use of ML in multi-parametric breast MRI for tumor classification and differentiation of molecular subtypes. Indeed, at present, different models and approaches have been employed for this task, requiring a detailed description of the advantages and drawbacks of each technique and a general overview of their performances.

Efficacy Evaluation of Neoadjuvant Chemotherapy in Breast Cancer by MRI

Breast cancer is a highly harmful malignancy, which often causes great distress to patients and seriously affects their physical and mental health. Breast cancer causes patients to experience decreased appetite, decreased eating, and indigestion, which in turn leads to malnutrition, body wasting, resistance, immune compromise, progressive anemia, cachexia, and, as a result, severe secondary infections. To investigate the efficacy evaluation of neoadjuvant chemotherapy in breast cancer by MRI, forty-eight subjects treated at the hospital from June 2014 to August 2019 were recruited. After the neoadjuvant chemotherapy, the patients were divided into two groups based on the results of histopathological examination, namely, the ineffective group (n = 14) and the effective group (n = 34). Changes in MRI indicators were compared between the two groups before and after the neoadjuvant chemotherapy. The maximum diameter of lesions decreased significantly after the neoadjuvant chemotherapy than before. The apparent diffusion coefficient (ADC) increased considerably, and the time-intensity curve (TIC) showed a transition from type III to type II/I and from type II to type I. MRI can indicate the maximum diameter of the breast cancer lesion, ADC, and TIC type. Therefore, it can be used to evaluate the efficacy of neoadjuvant chemotherapy for breast cancer and be widely applied in clinical practice.

Global guidelines for breast cancer screening: A systematic review

Objectives

Breast cancer screening guidelines could provide valuable tools for clinical decision making by reviewing the available evidence and providing recommendations. Little information is known about how many countries have issued breast cancer screening guidelines and the differences among existing guidelines. We systematically reviewed current guidelines and summarized corresponding recommendations, to provide references for good clinical practice in different countries.

Methods

Systematic searches of MEDLINE, EMBASE, Web of Science, and Scopus from inception to March 27th, 2021 were conducted and supplemented by reviewing the guideline development organizations. The quality of screening guidelines was assessed from six domains of the Appraisal of Guidelines for Research and Evaluation Ⅱ (AGREE Ⅱ) instrument by two appraisers. The basic information and recommendations of the issued guidelines were extracted and summarized.

Results

A total of 23 guidelines issued between 2010 and 2021 in 11 countries or regions were identified for further review. The content and quality varied across the guidelines. The average AGREE Ⅱ scores of the guidelines ranged from 33.3% to 87.5%. The highest domain score was "clarity of presentation" while the domain with the lowest score was "applicability". For average-risk women, most of the guidelines recommended mammographic screening for those aged 40–74 years, specifically, those aged 50–69 years were regarded as the optimal age group for screening. Nine of 23 guidelines recommended against an upper age limit for breast cancer screening. Mammography (MAM) was recommended as the primary screening modality for average-risk women by all included guidelines. Most guidelines suggested annual or biennial mammographic screening. Risk factors of breast cancer identified in the guidelines mainly fell within five categories which could be broadly summarized as the personal history of pre-cancerous lesions and/or breast cancer; the family history of breast cancer; the known genetic predisposition of breast cancer; the history of mantle or chest radiation therapy; and dense breasts. For women at higher risk, there was a consensus among most guidelines that annual MAM or annual magnetic resonance imaging (MRI) should be given, and the screening should begin earlier than the average-risk group.

Conclusions

The majority of 23 included international guidelines were issued by developed countries which contained roughly the same but not identical recommendations on breast cancer screening age, methods, and intervals. Most guidelines recommended annual or biennial mammographic screening between 40 and 74 years for average-risk populations and annual MAM or annual MRI starting from a younger age for high-risk populations. Current guidelines varied in quality and increased efforts are needed to improve the methodological quality of guidance documents. Due to lacking clinical practice guidelines tailored to different economic levels, low- and middle-income countries (LMICs) should apply and implement the evidence-based guidelines with higher AGREE Ⅱ scores considering local adaption.

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This systematic review comprehensively maps the recommendations of the latest international breast screening guidelines, providing valuable tools for clinical decision making in different settings.

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Most guidelines recommend annual or biennial mammographic screening between 40 and 74 years for the average-risk populations and annual MAM or annual MRI starting from a younger age for the high-risk populations. However, there are indeed discrepancies in screening age, methods, and intervals among countries.

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High-quality evidence and rigorous methodology are the keys to guidance development, but current guidelines vary in methodological quality.

Breast MRI: does a clinical decision algorithm outweigh reader experience?

Objectives

Due to its high sensitivity, DCE MRI of the breast (MRIb) is increasingly used for both screening and assessment purposes. The Kaiser score (KS) is a clinical decision algorithm, which formalizes and guides diagnosis in breast MRI and is expected to compensate for lesser reader experience. The aim was to evaluate the diagnostic performance of untrained residents using the KS compared to off-site radiologists experienced in breast imaging using only MR BI-RADS.

Methods

Three off-site, board-certified radiologists, experienced in breast imaging, interpreted MRIb according to the MR BI-RADS scale. The same studies were read by three residents in radiology without prior training in breast imaging using the KS. All readers were blinded to clinical information. Histology was used as the gold standard. Statistical analysis was conducted by comparing the AUC of the ROC curves.

Results

A total of 80 women (median age 52 years) with 93 lesions (32 benign, 61 malignant) were included. The individual within-group performance of the three expert readers (AUC 0.723–0.742) as well as the three residents was equal (AUC 0.842–0.928), p > 0.05, respectively. But, the rating of each resident using the KS significantly outperformed the experts’ ratings using the MR BI-RADS scale (p ≤ 0.05).

Conclusion

The KS helped residents to achieve better results in reaching correct diagnoses than experienced radiologists empirically assigning MR BI-RADS categories in a clinical “problem solving MRI” setting. These results support that reporting breast MRI benefits more from using a diagnostic algorithm rather than expert experience.

Key Points

• Reporting breast MRI benefits more from using a diagnostic algorithm rather than expert experience in a clinical “problem solving MRI” setting.

• The Kaiser score, which provides a clinical decision algorithm for structured reporting, helps residents to reach an expert level in breast MRI reporting and to even outperform experienced radiologists using MR BI-RADS without further formal guidance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-022-09015-8.

MRI for Evaluation of Complications of Breast Augmentation

Breast augmentation is one of the most common aesthetic procedures performed in the United States. Several techniques of breast augmentation have been developed, including the implantation of breast prostheses and the injection of autologous fat and other materials. The most common method of breast augmentation is to implant a prosthesis. There are different types of breast implants that vary in shape, composition, and the number of lumina. The rupture of breast implants is the leading cause of implant removal. The rupture rate increases substantially with the increasing age of the implant. Most implant ruptures are asymptomatic. Implant complications can be grouped into two categories: local complications in the breast and adjacent soft tissue, and systemic complications associated with rheumatologic or neurologic symptoms. The onset of local complications may be early (infection and periprosthetic collections including seromas, hematomas, or abscesses) or late (capsular contraction, implant rupture, gel bleed, or breast implant-associated anaplastic large cell lymphoma). Although mammography is the imaging modality for breast cancer screening, noncontrast breast MRI is the imaging modality of choice for evaluation of the integrity of breast implants and the complications of breast augmentation, for equivocal findings at conventional imaging, and as a supplement to mammography in patients with free injectable materials. The fifth edition of the Breast Imaging Reporting and Data System (BI-RADS) provides a systematic outline for MRI evaluation of patients with breast implants. Silicone- and water-selective sequences provide useful supplemental information to confirm intracapsular and extracapsular rupture. Breast MRI for evaluation of implant integrity does not require intravenous contrast material. The use of MRI contrast material in patients with breast augmentation is indicated when infection or malignancy is suspected. Radiologists should have a thorough understanding of the different techniques for breast augmentation, normal imaging features, and complications specific to breast augmentation. An invited commentary by Ojeda-Fournier is available online. ^©RSNA, 2022.

Association of breast cancer risk, density, and stiffness: global tissue stiffness on breast MR elastography (MRE)

PURPOSE

Quantify in vivo biomechanical tissue properties in various breast densities and in average risk and high-risk women using Magnetic Resonance Imaging (MRI)/MRE and examine the association between breast biomechanical properties and cancer risk based on patient demographics and clinical data.

METHODS

Patients with average risk or high-risk of breast cancer underwent 3.0 T breast MR imaging and elastography. Breast parenchymal enhancement (BPE), density (from most recent mammogram), stiffness, elasticity, and viscosity were recorded. Within each breast density group (non-dense versus dense), stiffness, elasticity, and viscosity were compared across risk groups (average versus high). Separately for stiffness, elasticity, and viscosity, a multivariable logistic regression model was used to evaluate whether the MRE parameter predicted risk status after controlling for clinical factors.

RESULTS

50 average risk and 86 high-risk patients were included. Risk groups were similar in age, density, and menopausal status. Among patients with dense breasts, mean stiffness, elasticity, and viscosity were significantly higher in high-risk patients (N = 55) compared to average risk patients (N = 34; all p < 0.001). Stiffness remained a significant predictor of risk status (OR = 4.26, 95% CI [1.96, 9.25]) even after controlling for breast density, BPE, age, and menopausal status. Similar results were seen for elasticity and viscosity.

CONCLUSION

A structurally based, quantitative biomarker of tissue stiffness obtained from MRE is associated with differences in breast cancer risk in dense breasts. Tissue stiffness could provide a novel prognostic marker to help identify high-risk women with dense breasts who would benefit from increased surveillance and/or risk reduction measures.

Use of Diagnostic Imaging Modalities in Modern Screening, Diagnostics and Management of Breast Tumours 1st Central-Eastern European Professional Consensus Statement on Breast Cancer

Breast radiologists and nuclear medicine specialists updated their previous recommendation/guidance at the 4th Hungarian Breast Cancer Consensus Conference in Kecskemét. A recommendation is hereby made that breast tumours should be screened, diagnosed and treated according to these guidelines. These professional guidelines include the latest technical developments and research findings, including the role of imaging methods in therapy and follow-up. It includes details on domestic development proposals and also addresses related areas (forensic medicine, media, regulations, reimbursement). The entire material has been agreed with the related medical disciplines.

Second-Look Ultrasound Using Shear-Wave Elastography in MRI-Suspected Locoregional Recurrence of Breast Carcinoma

PURPOSE

To investigate if second-look US using shear-wave elastography (SWE) can help to differentiate between benign and malignant changes in the postoperative breast after surgical treatment of breast carcinoma.

MATERIALS AND METHODS

SWE and related sonographic features were reviewed in 90 female patients with a history of surgical treatment of breast carcinoma and a suspicious lesion detected on a follow-up MRI scan. A single experienced radiologist performed all second-look US exams with SWE measurements placing a circular region of interest measuring 2 mm in diameter over the stiffest part of the lesion. Tissue samples for histopathological analysis were obtained during the same US examination via core-needle biopsy.

RESULTS

Out of 90 lesions, 39 were proven malignant on histopathological analysis. 50 % of malignant lesions had El_max values ranging from 128 to 199 kPa, and 50 % of benign lesions had El_max values ranging from 65 to 169 kPa. The cut-off value of 171.2 kPa for El_max shows a sensitivity of 59 % and specificity of 78.4 % for carcinoma recurrence, area under the curve 0.706 (CI95 % 0.6-0.81), P = 0.001. In univariate logistic models, restricted diffusion and stiffness on SWE, El_max > 171.2 kPa, were shown as significant recurrence predictors. In the multivariate model, restricted diffusion remains significant independent recurrence predictor. With a recurrence prevalence of 43 %, the test sensitivity is 95 % (CI95 % 81-99 %) and the specificity is 75 % (CI95 % 60-85 %).

CONCLUSION

Stiffer lesions should be considered suspicious on second-look US in the postoperative breast and SWE can be a helpful tool in identifying malignant lesions, especially if this is related to restricted diffusion on MRI exam. Lesion stiffness, however, should not be considered as an independent predictor of lesion malignancy in the postoperative breast, because of benign changes that can appear stiff on SWE, as well as carcinoma recurrences that may appear soft.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

ADVANCES IN KNOWLEDGE

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

Diagnostic Challenge of Invasive Lobular Carcinoma of the Breast: What Is the News? Breast Magnetic Resonance Imaging and Emerging Role of Contrast-Enhanced Spectral Mammography

Invasive lobular carcinoma is the second most common histologic form of breast cancer, representing 5% to 15% of all invasive breast cancers. Due to an insidious proliferative pattern, invasive lobular carcinoma remains clinically and radiologically elusive in many cases. Breast magnetic resonance imaging (MR) is considered the most accurate imaging modality in detecting and staging invasive lobular carcinoma and it is strongly recommended in pre-operative planning for all ILC. Contrast-enhanced spectral mammography (CESM) is a new diagnostic method that enables the accurate detection of malignant breast lesions similar to that of breast MR. CESM is also a promising breast imaging method for planning surgeries. In this study, we compare the ability of contrast-enhanced spectral mammography (CESM) with breast MR in the preoperative assessment of the extent of invasive lobular carcinoma. All patients with proven invasive lobular carcinoma treated in our breast cancer center underwent preoperative breast MRI and CESM. Images were reviewed by two dedicated breast radiologists and results were compared to the reference standard histopathology. CESM was similar and in some cases more accurate than breast MR in assessing the extent of disease in invasive lobular cancers. Further evaluation in larger prospective randomized trials is needed to validate our preliminary results.

Evidence-Based and Structured Diagnosis in Breast MRI using the Kaiser Score

BACKGROUND

 Breast MRI is the most sensitive method for the detection of breast cancer and is an integral part of modern breast imaging. On the other hand, interpretation of breast MRI exams is considered challenging due to the complexity of the available information. Clinical decision rules that combine diagnostic criteria in an algorithm can help the radiologist to read breast MRI by supporting objective and largely experience-independent diagnosis.

METHOD

 Narrative review. In this article, the Kaiser Score (KS) as a clinical decision rule for breast MRI is introduced, its diagnostic criteria are defined, and strategies for clinical decision making using the KS are explained and discussed.

RESULTS

 The KS is based on machine learning and has been independently validated by international research. It is largely independent of the examination technique that is used. It allows objective differentiation between benign and malignant contrast-enhancing breast MRI findings using diagnostic BI-RADS criteria taken from T2w and dynamic contrast-enhanced T1w images. A flowchart guides the reader in up to three steps to determine a score corresponding to the probability of malignancy that can be used to assign a BI-RADS category. Individual decision making takes the clinical context into account and is illustrated by typical scenarios.

KEY POINTS

· The KS as an evidence-based decision rule to objectively distinguish benign from malignant breast lesions is based on information contained in T2w und dynamic contrast-enhanced T1w sequences and is largely independent of specific examination protocols.. · The KS diagnostic criteria are in line with the MRI BI-RADS lexicon. We focused on defining a default category to be applied in the case of equivocal imaging criteria.. · The KS reflects increasing probabilities of malignancy and, together with the clinical context, assists individual decision making..

CITATION FORMAT

· Baltzer PA, Krug KB, Dietzel M. Evidence-Based and Structured Diagnosis in Breast MRI using the Kaiser Score. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1829-5985.

Sensitivity of Contrast-Enhanced Breast MRI vs X-ray Mammography Based on Cancer Histology, Tumor Grading, Receptor Status, and Molecular Subtype: A Supplemental Analysis of 2 Large Phase III Studies

Background:

The impact of certain tumor parameters on the sensitivity of imaging tools is unknown. The purpose was to study the impact of breast cancer histology, tumor grading, single receptor status, and molecular subtype on the sensitivity of contrast-enhanced breast magnetic resonance imaging (CE-BMRI) vs X-ray mammography (XRM) to detect breast cancer.

Materials and Methods:

We ran a supplemental analysis of 2 global Phase III studies which recruited patients with histologically proven breast cancers. The sensitivity of CE-BMRI vs XRM to detect cancer lesions with different histologies, tumor grading, single receptor status, and molecular subtype was compared. Six blinded readers for each study evaluated the images. Results were summarized as the “Mean Reader.” For each reader, sensitivity was defined as the proportion of detected lesions vs the total number of lesions identified by the standard of reference. Two-sided 95% confidence intervals were calculated for within-group proportions, and for the difference between CE-BMRI and XRM, using a normal approximation to the binomial distribution.

Results:

In 778 patients, 1273 cancer lesions were detected. A total of 435 patients had 1 lesion, 254 had 2 lesions, and 77 had 3 or more lesions. The sensitivity of CE-BMRI was significantly higher compared with XRM irrespective of the histology. The largest difference was seen for invasive lobular carcinoma (22.3%) and ductal carcinoma in situ (19%). Across all 3 tumor grades, the sensitivity advantage of CE-BMRI over XRM ranged from 15.7% to 18.5%. Contrast-enhanced breast magnetic resonance imaging showed higher sensitivity compared with XRM irrespective of single receptor expressions (15.3%-19.4%). The sensitivities for both imaging methods were numerically higher for the more aggressive ER– (estrogen receptor), PR– (progesterone receptor), and HER2+ (human epidermal growth factor receptor 2) tumors. Irrespective of molecular subtype, sensitivity of CE-BMRI was 14.8% to 18.9% higher compared with XRM.

Conclusions:

Contrast-enhanced breast magnetic resonance imaging showed significantly higher sensitivity compared with XRM independent of tumor histology, tumor grading, single receptor status, and molecular subtype.

Trial Registration: ClinicalTrials.gov: NCT01067976 and NCT01104584.

Global Increase in Breast Cancer Incidence: Risk Factors and Preventive Measures

Breast cancer is a global cause for concern owing to its high incidence around the world. The alarming increase in breast cancer cases emphasizes the management of disease at multiple levels. The management should start from the beginning that includes stringent cancer screening or cancer registry to effective diagnostic and treatment strategies. Breast cancer is highly heterogeneous at morphology as well as molecular levels and needs different therapeutic regimens based on the molecular subtype. Breast cancer patients with respective subtype have different clinical outcome prognoses. Breast cancer heterogeneity emphasizes the advanced molecular testing that will help on-time diagnosis and improved survival. Emerging fields such as liquid biopsy and artificial intelligence would help to under the complexity of breast cancer disease and decide the therapeutic regimen that helps in breast cancer management. In this review, we have discussed various risk factors and advanced technology available for breast cancer diagnosis to combat the worst breast cancer status and areas that need to be focused for the better management of breast cancer.

Breast MRI during pregnancy and lactation: clinical challenges and technical advances

The breast experiences substantial changes in morphology and function during pregnancy and lactation which affects its imaging properties and may reduce the visibility of a concurrent pathological process. The high incidence of benign gestational-related entities may further add complexity to the clinical and radiological evaluation of the breast during the period. Consequently, pregnancy-associated breast cancer (PABC) is often a delayed diagnosis and carries a poor prognosis. This state-of-the-art pictorial review illustrates how despite currently being underutilized, technical advances and new clinical evidence support the use of unenhanced breast MRI during pregnancy and both unenhanced and dynamic-contrast enhanced (DCE) during lactation, to serve as effective supplementary modalities in the diagnostic work-up of PABC.

Role of Qualitative and Quantitative Indocyanine Green Angiography to Assess Mastectomy Skin Flaps Perfusion in Nipple/Skin-Sparing and Skin-Reducing Mastectomies with Implant-Based Breast Reconstruction

Methods

Consecutive women scheduled for nipple/skin-sparing/skin-reducing mastectomy between May 2020 and April 2021 were prospectively enrolled. Patients were divided into Group 1 in the absence of superficial and full-thickness necrosis (SN; FTN) and Group 2 in the presence of both. T1 (time between ICG injection and the initial perfusion of the least perfused MSF area), ICG-Q1, and ICG-Q% (absolute and relative perfusion values of the least vascularized area) were collected.

Results

38 breasts were considered. FTN was reported in 4 breasts (10.5%) and SN in 3 (7.9%). The two groups statistically differ in T1 (Group2 > Group1) and ICG-Q% (Group1 > Group2) (p < 0.05). T1 could statistically predict ICG-Q1 and ICG-Q%. Both quantitative values have a sensitivity of 57% and a NPV of 89%; ICG-Q% shows higher specificity (81% vs 77%) and PPV (40% vs 36%).

Conclusions

Quantitative ICG angiography may additionally reduce MSF necrosis. Moreover, longer T1 may indicate possible postoperative necrosis. Considering these factors, intraoperative changes of reconstructive strategy could be adopted to reduce reconstructive failure.

Multiparametric Magnetic Resonance Imaging in Evaluation of Benign and Malignant Breast Masses with Pathological Correlation

Background

Dynamic contrast-enhanced (DCE) MRI sequences plays a vital role in diagnosing breast masses with high sensitivity and specificity as compared to other diagnostic modalities. The addition of diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) values significantly improves diagnostic accuracy. This study aimed to study the breast masses on DCE-MRI, restricted diffusion on DWI, ADC values, and choline peak on spectroscopy in breast cancer diagnosis.

Material and methods

This study was a prospective observational study which involved subjects with breast lumps. Baseline data was collected from the patients along with pertinent clinical history and relevant laboratory investigations. MR mammography (MRM) was performed on a 1.5 Tesla MR Scanner (MAGNETOM® Avanto, Siemens AG, Munich Germany) using a dedicated double breast coil.

Results

Forty-one subjects were included with a total of 54 breast masses in them. The mean age of the study population was 47.1±14.7 years. From the MRI final diagnosis, the majority (53.70%) were diagnosed as malignant lesions and 46.30% as benign. Out of 20 lesions diagnosed as benign on histopathology, only five percent had ADC value <1.3 ×10⁻³mm²/s, and the majority (95%) had ADC value >1.3 ×10⁻³mm²/s. All 20 lesions were circumscribed, ovoid, or round in shape showing no restricted diffusion on DWI, with corresponding ADC value of >1.3×10⁻³mm²/s, homogeneous post-contrast enhancement, or with dark internal septations, type I kinetic enhancement curve, and they showed no choline peak on spectroscopy. Out of 34 malignant lesions diagnosed on histopathology, the majority (85.29%) displayed restricted diffusion on DWI and had an ADC value of <1.3×10⁻³mm²/s, most of them had spiculated margins, type II/ III kinetic curve with choline peak on spectroscopy.

Conclusion

Multiparametric MR mammography, which included DCE-MRM, DWI, ADC values, and spectroscopy, correlated well with the histopathological diagnosis of benign and malignant breast masses.

Association between breast cancer's prognostic factors and 3D textural features of non-contrast-enhanced T1 weighted breast MRI

OBJECTIVES

The aim of this exploratory study was to evaluate whether three-dimensional texture analysis (3D-TA) features of non-contrast-enhanced T₁ weighted MRI associate with traditional prognostic factors and disease-free survival (DFS) of breast cancer.

METHODS

3D-T₁ weighted images from 78 patients with 81 malignant histopathologically verified breast lesions were retrospectively analysed using standard-size volumes of interest. Grey-level co-occurrence matrix (GLCM)-based features were selected for statistical analysis. In statistics the Mann-Whitney U and the Kruskal-Wallis tests, the Cox proportional hazards model and the Kaplan-Meier method were used.

RESULTS

Tumours with higher histological grade were significantly associated with higher contrast (1 voxel: p = 0.033, 2 voxels: p = 0.036). All the entropy parameters showed significant correlation with tumour grade (p = 0.015-0.050) but there were no statistically significant associations between other TA parameters and tumour grade. The Nottingham Prognostic Index (NPI) was correlated with contrast and sum entropy parameters. A higher sum variance TA parameter was a significant predictor of shorter DFS.

CONCLUSION

Texture parameters, assessed by 3D-TA from non-enhanced T₁ weighted images, indicate tumour heterogeneity but have limited independent prognostic value. However, they are associated with tumour grade, NPI, and DFS. These parameters could be used as an adjunct to contrast-enhanced TA parameters.

ADVANCES IN KNOWLEDGE

3D-TA of non-contrast enhanced T₁ weighted breast MRI associates with tumour grade, NPI, and DFS. The use of non-contrast 3D-TA parameters in adjunct with contrast-enhanced 3D-TA parameters warrants further research.

Economic potential of abbreviated breast MRI for screening women with dense breast tissue for breast cancer

OBJECTIVES

Abbreviated breast MRI (AB-MRI) was introduced to reduce both examination and image reading times and to improve cost-effectiveness of breast cancer screening. The aim of this model-based economic study was to analyze the cost-effectiveness of full protocol breast MRI (FB-MRI) vs. AB-MRI in screening women with dense breast tissue for breast cancer.

METHODS

Decision analysis and a Markov model were designed to model the cumulative costs and effects of biennial screening in terms of quality-adjusted life years (QALYs) from a US healthcare system perspective. Model input parameters for a cohort of women with dense breast tissue were adopted from recent literature. The impact of varying AB-MRI costs per examination as well as specificity on the resulting cost-effectiveness was modeled within deterministic sensitivity analyses.

RESULTS

At an assumed cost per examination of $ 263 for AB-MRI (84% of the cost of a FB-MRI examination), the discounted cumulative costs of both MR-based strategies accounted comparably. Reducing the costs of AB-MRI below $ 259 (82% of the cost of a FB-MRI examination, respectively), the incremental cost-effectiveness ratio of FB-MRI exceeded the willingness to pay threshold and the AB-MRI-strategy should be considered preferable in terms of cost-effectiveness.

CONCLUSIONS

Our preliminary findings indicate that AB-MRI may be considered cost-effective compared to FB-MRI for screening women with dense breast tissue for breast cancer, as long as the costs per examination do not exceed 82% of the cost of a FB-MRI examination.

KEY POINTS

• Cost-effectiveness of abbreviated breast MRI is affected by reductions in specificity and resulting false positive findings and increased recall rates. • Abbreviated breast MRI may be cost-effective up to a cost per examination of 82% of the cost of a full protocol examination. • Abbreviated breast MRI could be an economically preferable alternative to full protocol breast MRI in screening women with dense breast tissue.

MRI Screening of BRCA Mutation Carriers: Comparison of Standard Protocol and Abbreviated Protocols With and Without T2-Weighted Images

Background: Increasing evidence supports the role of abbreviated MRI protocols for breast cancer detection. However, abbreviated protocols have been poorly studied in patients who are BRCA1 or BRCA2 mutation carriers. Further, the need for T2-weighted (T2W) sequences in abbreviated protocols remains controversial. Objective: To compare the diagnostic performance of a standard full breast MRI protocol and of abbreviated protocols with and without inclusion of the T2W sequence in patients with BRCA mutations. Methods: This retrospective study included a total of 292 patients (mean age, 47.9 years) who were BRCA1 or BRCA2 mutation carriers and who underwent a total of 427 screening breast MRI examinations using a standard full protocol that could be classified as having benign (n=407) or malignant (n=20) findings based on histopathology or imaging follow-up. Four readers independently assessed examinations in three separate sessions [theoretical abbreviated protocol (which included the first postcontrast acquisition), theoretical abbreviated protocol with addition of T2W sequence, and the standard full protocol], assigning BI-RADS categories. Categories of 3-5 were considered to represent positive examinations. Interreader agreement was assessed, and diagnostic performance was compared using pooled reader data. Results: Interreader agreement for BI-RADS category, expressed as kappa, was 0.55 for standard, 0.45 for abbreviated, and 0.57 for abbreviated+T2. Pooled sensitivity was 94% for standard, 92% for abbreviated, and 90% for abbreviated+T2 (all p>.001). Pooled specificity was 80% for standard, 71% for abbreviated, and 83% for abbreviated+ T2 (p<.001 for abbreviated+T2 compared with both standard and abbreviated). Pooled PPV was 19% for standard, 14% for abbreviated, and 20% for abbreviated+T2 (p<.001 for abbreviated compared with both standard and abbreviated). Pooled NPV was 100% for standard, 99% for abbreviated, and 99% for abbreviated+T2 (all p>.001). Pooled accuracy was 80% for standard, 73% for abbreviated, and 83% for abbreviated+T2 (p<.001 for abbreviated compared with both standard and abbreviated+T2). Conclusion: The abbreviated protocol without T2W images had suboptimal performance. However, addition of T2W sequence yielded comparable sensitivity and accuracy, and small increase in specificity, compared with the full protocol. Clinical Impact: The findings support implementation of abbreviated MRI with T2W imaging for breast cancer screening in patients with BRCA mutations.

Using Ultrasound-Based Multilayer Perceptron to Differentiate Early Breast Mucinous Cancer and its Subtypes From Fibroadenoma

Objectives

Mucinous breast cancer (MBC), particularly pure MBC (pMBC), often tend to be confused with fibroadenoma (FA) due to their similar images and firm masses, so some MBC cases are misdiagnosed to be FA, which may cause poor prognosis. We analyzed the ultrasonic features and aimed to identify the ability of multilayer perceptron (MLP) to classify early MBC and its subtypes and FA.

Materials and Methods

The study consisted of 193 patients diagnosed with pMBC, mMBC, or FA. The area under curve (AUC) was calculated to assess the effectiveness of age and 10 ultrasound features in differentiating MBC from FA. We used the pairwise comparison to examine the differences among MBC subtypes (pure and mixed types) and FA. We utilized the MLP to differentiate MBC and its subtypes from FA.

Results

The nine features with AUCs over 0.5 were as follows: age, echo pattern, shape, orientation, margin, echo rim, vascularity distribution, vascularity grade, and tumor size. In subtype analysis, the significant differences were obtained in 10 variables (p-value range, 0.000–0.037) among pMBC, mMBC, and FA, except posterior feature. Through MLP, the AUCs of predicting MBC and FA were both 0.919; the AUCs of predicting pMBC, mMBC, and FA were 0.875, 0.767, and 0.927, respectively.

Conclusion

Our study found that the MLP models based on ultrasonic characteristics and age can well distinguish MBC and its subtypes from FA. It may provide a critical insight into MBC preoperative clinical management.

Clinicopathologic features of breast cancers diagnosed in women treated with prior radiation therapy for Hodgkin lymphoma: Results from a population-based cohort

BACKGROUND

Childhood and young adult survivors of Hodgkin lymphoma (HL) are at elevated risk of developing breast cancer, yet little data exist on the tumor characteristics that develop in this high-risk patient population.

METHODS

The National Cancer Institute's Surveillance, Epidemiology, and End Results database was used to identify breast cancers diagnosed between 1990 and 2016 in women who had received prior radiation therapy for HL at age 30 years or younger. Clinicopathologic features of subsequent breast cancers (breast cancer after radiation therapy for HL [BC-HL]) were examined and compared with breast cancers diagnosed in women who had no prior malignancy (breast cancer with no prior malignancy [BC-NPM]).

RESULTS

In total, 321 breast cancers were identified in 257 women who had a history of radiation therapy for HL. The median age at HL diagnosis was 22 years (interquartile range, 18-26 years), and nearly all patients in the BC-HL group (97.9%) were diagnosed ≥8 years after radiation therapy. Overall, 56 patients in the BC-HL group (21.8%) developed bilateral breast cancer. Compared with women who had BC-NPM, those who had BC-HL were younger (43 vs 60 years; P < .001) and were less likely to present with ductal carcinoma in situ (8.4% vs 14.9%; P = .001). On multivariable analysis that included adjustment for age, invasive BC-HL was associated with smaller (≤2 cm) tumor size (odds ratio, 1.64; 95% CI, 1.25-2.15) and upper outer quadrant tumors (odds ratio, 1.37; 95% CI, 1.04-1.81) compared with BC-NPM. In a subset analysis of 102 women who had HER2/neu status available, the distribution of biologic subtype was not significantly different between BC-HL and BC-NPM (P = .16).

CONCLUSIONS

Breast cancers in women who previously received radiation therapy for HL are characterized by earlier onset disease, although most remain estrogen receptor-positive and have early stage disease at presentation.

LAY SUMMARY

Women who have had radiation therapy for Hodgkin lymphoma at a young age are at increased risk of developing early onset breast cancer; however, most of these breast cancers are sensitive to hormones (estrogen receptor-positive) and are diagnosed at early stages. Because these breast tumors are estrogen receptor-positive, medications that prevent breast cancer by blocking the effect of or lowering hormone levels (also termed endocrine prevention) may be useful in this group of high-risk women.

Background parenchymal enhancement and uptake as breast cancer imaging biomarkers: A state-of-the-art review

Within the past decade, background parenchymal enhancement (BPE) and background parenchymal uptake (BPU) have emerged as novel imaging-derived biomarkers in the diagnosis and treatment monitoring of breast cancer. Growing evidence supports the role of breast parenchyma vascularity and metabolic activity as probable risk factors for breast cancer development. Furthermore, in the presence of a newly-diagnosed breast cancer, added clinically-relevant data was surprisingly found in the respective imaging properties of the non-affected contralateral breast. Evaluation of the contralateral BPE and BPU have been found to be especially instrumental in predicting the prognosis of a patient with breast cancer and even anticipating their response to neoadjuvant chemotherapy. Simultaneously, further research has found a link between these two biomarkers, even though they represent different physical properties. The aim of this review is to provide an up to date summary of the current clinical applications of BPE and BPU as breast cancer imaging biomarkers with the hope that it propels their further usage in clinical practice.

Breast imaging: Beyond the detection

Breast cancer is a heterogeneous disease nowadays, including different biological subtypes with a variety of possible treatments, which aim to achieve the best outcome in terms of response to therapy and overall survival. In recent years breast imaging has evolved considerably, and the ultimate goal is to predict these strong phenotypic differences noninvasively. Indeed, breast cancer multiparametric studies can highlight not only qualitative imaging parameters, as the presence/absence of a likely malignant finding, but also quantitative parameters, suggesting clinical-pathological features through the evaluation of imaging biomarkers. A further step has been the introduction of artificial intelligence and in particular radiogenomics, that investigates the relationship between breast cancer imaging characteristics and tumor molecular, genomic and proliferation features. In this review, we discuss the main techniques currently in use for breast imaging, their respective fields of use and their technological and diagnostic innovations.

MRI of the Lactating Breast: Computer-Aided Diagnosis False Positive Rates and Background Parenchymal Enhancement Kinetic Features

RATIONALE AND OBJECTIVES

To investigate the application of computer-added diagnosis (CAD) in dynamic contrast-enhanced (DCE) MRI of the healthy lactating breast, focusing on false-positive rates and background parenchymal enhancement (BPE) coloring patterns in comparison with breast cancer features in non-lactating patients.

MATERIALS AND METHODS

The study population was composed of 58 healthy lactating patients and control groups of 113 healthy premenopausal non-lactating patients and 55 premenopausal non-lactating patients with newly-diagnosed breast cancer. Patients were scanned on 1.5-T MRI using conventional DCE protocol. A retrospective analysis of DCE-derived CAD properties was conducted using a commercial software that is regularly utilized in our routine radiological work-up. Qualitative morphological characterization and automatically-obtained quantitative parametric measurements of the BPE-induced CAD coloring were categorized and subgroups' trends and differences between the lactating and cancer cohorts were statistically assessed.

RESULTS

CAD false-positive coloring was found in the majority of lactating cases (87%). Lactation BPE coloring was characteristically non-mass enhancement (NME)-like shaped (87%), bilateral (79%) and symmetric (64%), whereas, unilateral coloring was associated with prior irradiation (p <0.0001). Inter-individual variability in CAD appearance of both scoring-grade and kinetic-curve dominance was found among the lactating cohort. When compared with healthy non-lactating controls, CAD false positive probability was significantly increased [Odds ratio 40.2, p <0001], while in comparison with the breast cancer cohort, CAD features were mostly inconclusive, even though increased size parameters were significantly associated with lactation-BPE (p <0.00001).

CONCLUSION

BPE was identified as a common source for false-positive CAD coloring on breast DCE-MRI among lactating population. Despite several typical characteristics, overlapping features with breast malignancy warrant a careful evaluation and clinical correlation in all cases with suspected lactation induced CAD coloring.

Breast magnetic resonance imaging as a problem solving tool in women recalled at biennial screening mammography: A population-based study in the Netherlands

Purpose

Problem solving magnetic resonance imaging (MRI) is used to exclude malignancy in women with equivocal findings on conventional imaging. However, recommendations on its use for women recalled after screening are lacking. This study evaluates the impact of problem solving MRI on diagnostic workup among women recalled from the Dutch screening program, as well as time trends and inter-hospital variation in its use.

Methods

Women who were recalled at screening mammography in the South of the Netherlands (2008–2017) were included. Two-year follow-up data were collected. Diagnostic-workup and accuracy of problem solving MRI were evaluated and time trends and inter-hospital variation in its use were examined.

Results

In the study period 16,175 women were recalled, of whom 906 underwent problem solving MRI. Almost half of the women (45.4%) who underwent problem solving MRI were referred back to the screening program without further workup. The sensitivity, specificity, and positive and negative predictive values of problem solving MRI were 98.2%, 70.0%, 31.1%, and 99.6%, respectively. The percentage of recalled women receiving problem solving MRI fluctuated over time (4.7%–7.2%) and significantly varied among hospitals (2.2%–7.0%).

Conclusion

The use of problem solving MRI may exclude malignancy in recalled women. The use of problem solving MRI varied over time and among hospitals, which indicates the need for guidelines on problem solving MRI.

•

Problem solving MRI did correctly refer back women to the screening program.

•

The sensitivity and specificity of problem solving MRI were 98.2% and 70.0%.

•

Positive and negative predictive values of problem solving MRI were 31.1% and 99.6%.

•

By excluding malignancy, problem solving MRI may reduce invasive diagnostic workup.

Magnetic resonance imaging before breast cancer surgery: results of an observational multicenter international prospective analysis (MIPA)

OBJECTIVES

Preoperative breast magnetic resonance imaging (MRI) can inform surgical planning but might cause overtreatment by increasing the mastectomy rate. The Multicenter International Prospective Analysis (MIPA) study investigated this controversial issue.

METHODS

This observational study enrolled women aged 18-80 years with biopsy-proven breast cancer, who underwent MRI in addition to conventional imaging (mammography and/or breast ultrasonography) or conventional imaging alone before surgery as routine practice at 27 centers. Exclusion criteria included planned neoadjuvant therapy, pregnancy, personal history of any cancer, and distant metastases.

RESULTS

Of 5896 analyzed patients, 2763 (46.9%) had conventional imaging only (noMRI group), and 3133 (53.1%) underwent MRI that was performed for diagnosis, screening, or unknown purposes in 692/3133 women (22.1%), with preoperative intent in 2441/3133 women (77.9%, MRI group). Patients in the MRI group were younger, had denser breasts, more cancers ≥ 20 mm, and a higher rate of invasive lobular histology than patients who underwent conventional imaging alone (p < 0.001 for all comparisons). Mastectomy was planned based on conventional imaging in 22.4% (MRI group) versus 14.4% (noMRI group) (p < 0.001). The additional planned mastectomy rate in the MRI group was 11.3%. The overall performed first- plus second-line mastectomy rate was 36.3% (MRI group) versus 18.0% (noMRI group) (p < 0.001). In women receiving conserving surgery, MRI group had a significantly lower reoperation rate (8.5% versus 11.7%, p < 0.001).

CONCLUSIONS

Clinicians requested breast MRI for women with a higher a priori probability of receiving mastectomy. MRI was associated with 11.3% more mastectomies, and with 3.2% fewer reoperations in the breast conservation subgroup.

KEY POINTS

• In 19% of patients of the MIPA study, breast MRI was performed for screening or diagnostic purposes. • The current patient selection to preoperative breast MRI implies an 11% increase in mastectomies, counterbalanced by a 3% reduction of the reoperation rate. • Data from the MIPA study can support discussion in tumor boards when preoperative MRI is under consideration and should be shared with patients to achieve informed decision-making.

Contrast-enhanced digital mammography and magnetic resonance imaging: reproducibility compared to pathologic anatomy

PURPOSE

To compare the reproducibility between contrast-enhanced digital mammography (CEDM) and magnetic resonance imaging (MRI) with the postsurgical pathologic examination. In addition, the applicability of the Breast Imaging-Reporting and Data System (BI-RADS) lexicon of MRI to CEDM was evaluated for mass lesions.

METHODS

A total of 62 patients with a histologically proven diagnosis of breast cancer were included in this study, for a total of 67 lesions. Fifty-nine patients underwent both methods. The reproducibility between MRI vs CEDM and the reference standard (postoperative pathology) was assessed by considering the lesion and breast size as pivotal variables. Reproducibility was evaluated by computing the concordance correlation coefficient (CCC). Bland-Altman plots were used to depict the observed pattern of agreement as well as to estimate the associated bias. Furthermore, the pattern of agreement between the investigated methods with regard to the breast lesion characterization (i.e. mass/nonmass; shape; margins; internal enhanced characteristics) was assessed by computing the Cohen kappa and its 95% confidence interval (CI).

RESULTS

The reproducibility between MRI and the reference standard and between CEDM and the reference standard showed substantial agreement, with a CCC value of 0.956 (95% CI, 0.931-0.972) and 0.950 (95% CI, 0.920-0.969), respectively. By looking at the Bland-Altman analysis, bias values of 2.344 and 1.875 mm were observed for MRI and CEDM vs reference evaluation, respectively. The agreement between MRI and CEDM is substantial with a CCC value of 0.969 (95% CI, 0.949-0.981). The Bland-Altman analysis showed bias values of -0.469 mm when comparing CEDM vs MRI. Following the Landis and Koch classification criteria, moderate agreement was observed between the two methods in describing BI-RADS descriptors of mass lesions.

CONCLUSION

CEDM is able to measure and describe tumor masses comparably to MRI and can be used for surgical planning.

Analysis of breast cancer subtypes and their correlations with receptors and ultrasound

The study aim was to evaluate the ultrasound (US) signs of the mammary lesions classified in the Breast Imaging-Reporting and Data System (BI-RADS) score category 3, 4, and 5, corresponding to US BI-RADS. It also followed the correlation between US changes of lesions suggestive for malignancy with the histopathological results and evaluated the proper management of those lesions. There were correlations of breast cancer (BC) subtypes with the receptors [estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2)], and Ki67 index, and the signs of conventional ultrasonography and US elastography. We selected 108 female patients examined with US, mammography and fine-needle biopsy who presented suspicions for malignancy lesions. Following the immunohistochemical analysis, they were classified in one of the BC subtypes. According to chi-squared analysis of molecular cancer subtypes correlation to receptors and Ki67 index, we found significant associations between both luminal A and luminal B HER2-negative subtypes and hormone receptors (ER, PR). These have an inverse relationship with Ki67 index elevated values; luminal B HER2-positive subtype has a direct association with HER2 presence; HER2-enriched subtype was statistically significant associated to HER2 presence and elevated Ki67 index values but had an inverse relationship to hormone receptors (ER, PR); triple-negative subtype was strongly associated to Ki67 index values and inversely correlated to ER and PR. We found luminal A subtype as being the most common and luminal B HER2-positive subtype as having the fewer cases.

Quantitative Three-Dimensional Assessment of the Pharmacokinetic Parameters of Intra- and Peri-tumoural Tissues on Breast Dynamic Contrast-Enhanced Magnetic Resonance Imaging

We aimed to assess the feasibility of three-dimensional (3D) segmentation and to investigate whether semi-quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters are associated with traditional prognostic factors for breast cancer. In addition, we evaluated whether both intra-tumoural and peri-tumoural DCE parameters can differentiate the breast cancers that are more aggressive from those that are less aggressive. Consecutive patients with newly diagnosed invasive breast cancer and structural breast MRI (3.0 T) were included after informed consent. Fifty-six patients (mean age, 57 years) with mass lesions of > 7 mm in diameter were included. A semi-automatic image post-processing algorithm was developed to measure 3D pharmacokinetic information from the DCE-MRI images. The kinetic parameters were extracted from time-signal curves, and the absolute tissue contrast agent concentrations were calculated with a reference tissue model. Markedly, higher intra-tumoural and peri-tumoural tissue concentrations of contrast agent were found in high-grade tumours (n = 44) compared to low-grade tumours (n = 12) at every time point (P = 0.006-0.040), providing positive predictive values of 90.6-92.6% in the classification of high-grade tumours. The intra-tumoural and peri-tumoural signal enhancement ratios correlated with tumour grade, size, and Ki67 activity. The intra-observer reproducibility was excellent. We developed a model to measure the 3D intensity data of breast cancers. Low- and high-grade tumours differed in their intra-tumoural and peri-tumoural enhancement characteristics. We anticipate that pharmacokinetic parameters will be increasingly used as imaging biomarkers to model and predict tumour behavior, prognoses, and responses to treatment.

Diagnostic Performance of Digital Breast Tomosynthesis, Unenhanced MRI, and Their Combination in the Preoperative Assessment of Breast Cancer: A Multi-reader Study

RATIONALE AND OBJECTIVES

To compare the diagnostic performance of digital breast tomosynthesis (DBT) and unenhanced magnetic resonance imaging (UMRI) in the preoperative assessment of breast cancer.

MATERIALS AND METHODS

We retrospectively included 59 patients with 74 pathology-proven cancers who underwent DBT and preoperative 1.5 T magnetic resonance imaging between January 2016 and February 2017. Four residents with 2-3 years of experience, blinded to pathology, independently reviewed DBT and UMRI (diffusion-weighted and unenhanced T1-weighted sequences), using the breast imaging reporting and data system (BI-RADS) and a 0-5 Likert score, respectively. We calculated per-lesion sensitivity and positive predictive value of DBT, UMRI, and combined DBT+UMRI, as well as the agreement between DBT and UMRI vs. pathology in assessing cancer size (Bland-Altman analysis). Logistic regression was performed to assess clinical features predictive of missing cancer.

RESULTS

Of 74 lesions, 84% were invasive ductal carcinoma, 27% of which with an in situ component; 31% of cancers were ≤10 mm large. Sensitivity of UMRI (74-85%) was equal or higher than that of DBT (68-82%), with similar positive predictive value (93-97% vs. 98-100%, respectively). DBT+UMRI increased the sensitivity up to 88%. UMRI showed closer limits of agreement with pathological size than DBT. Missing cancer was independently predicted by size ≤10 mm on DBT, UMRI, and DBT+UMRI (odds ratio 18.7, 5.1, and 13.3, respectively), and by increased breast density on DBT alone (odds ratio 3.50).

CONCLUSION

UMRI was equal or better than DBT in the preoperative assessment of breast cancer. Combined imaging achieved up to 88% per-lesion sensitivity, suggesting potential use in clinical practice.

Ultrasound-Based Nomogram for Distinguishing Malignant Tumors from Nodular Sclerosing Adenoses in Solid Breast Lesions

OBJECTIVES

Nodular sclerosing adenoses (NSAs) and malignant tumors (MTs) may coexist and are often classified into the same Breast Imaging Reporting and Data System (BI-RADS) category. We aimed to build and validate an ultrasound-based nomogram to distinguish MT from NSA for building a precise sequence of biopsies.

MATERIALS AND METHODS

The training cohort included 156 patients (156 masses) with NSA or MT at one study institution. We used best subset regression to determine the predictors for building a nomogram from ultrasonic characteristics and patients' age. Model performance and clinical utility were evaluated using Brier score, concordance (C)-index, calibration curve, and decision curve analysis. The independent validation cohort consisted of 162 patients (162 masses) from a separate institution.

RESULTS

Through best subset regression, we selected 6 predictors to develop nomogram: age, calcification, echogenic rim, vascularity distribution, tumor size, and thickness of breast parenchyma. Brier score and C-index of the nomogram in the training cohort were 0.068 and 0.967 (95% confidence interval [CI]: 0.941-0.993), respectively. In addition, calibration curve demonstrated good agreement between prediction and pathological result. In the validation cohort, the nomogram still obtained a favorable C-index score of 0.951 (95% CI: 0.919-0.983) and fine calibration. Decision curve analysis showed that the model was clinically useful.

CONCLUSIONS

If multiple NSA and MT masses are present in the same patient and are classified into the same BI-RADS category, our nomogram can be used as a supplement to the BI-RADS category for accurate biopsy of the mass most likely to be MT.

Cost-Effectiveness of MR-Mammography in Breast Cancer Screening of Women With Extremely Dense Breasts After Two Rounds of Screening

Objectives

To evaluate the cost-effectiveness of MR-mammography (MRM) vs. x-ray based mammography (XM) in two-yearly screening women of intermediate risk for breast cancer in the light of recent literature.

Methods

Decision analysis and Markov modelling were used to compare cumulative costs (in US-$) and outcomes (in QALYs) of MRM vs. XM over the model runtime of 20 years. The perspective of the U.S. healthcare system was selected. Incremental cost-effectiveness ratios (ICER) were calculated and related to a willingness to pay-threshold of $ 100,000 per QALY in order to evaluate the cost-effectiveness. Deterministic and probabilistic sensitivity analyses were conducted to test the impact of variations of the input parameters. In particular, variations of the rate of false positive findings beyond the first screening round and their impact on cost-effectiveness were assessed.

Results

Breast cancer screening with MRM resulted in increased costs and superior effectiveness. Cumulative average costs of $ 6,081 per woman and cumulative effects of 15.12 QALYs were determined for MRM, whereas screening with XM resulted in costs of $ 5,810 and 15.10 QALYs, resulting in an ICER of $ 13,493 per QALY gained. When the specificity of MRM in the second and subsequent screening rounds was varied from 92% to 99%, the ICER resulted in a range from $ 38,849 to $ 5,062 per QALY.

Conclusions

Based on most recent data on the diagnostic performance beyond the first screening round, MRM may remain the economically preferable alternative in screening women of intermediate risk for breast cancer due to their dense breast tissue.

Recalibrating the decision for MRI-directed breast ultrasound in patients with newly diagnosed breast cancer, factors predicting sonographic success

OBJECTIVE

Evaluate utilization of MRI-directed breast ultrasound (US) in patients with newly diagnosed breast cancer and refine practices to increase success of sonographic lesion detection.

METHODS

This retrospective single-institution review was restricted to women with breast cancer who underwent MRI from November 2006 to January 2017. Enhancing breast lesions, separate from the index tumor, recommended for MRI-directed US were assessed to see which were detected and which characteristics predicted success in detection. Univariate mixed-effects logistic modeling predicted likelihood of finding breast lesions with US, with odds ratios reported. All tests were two-sided with p < 0.05 considered significant.

RESULTS

A total of 275 patients underwent MRI-directed US for 361 breast lesions, of which 187 (51.8%) were found on US. Of those detected, 171 (91.4%) were masses and 16 (8.6%) were nonmass enhancement (NME), with masses 14 times more likely to be seen (p < 0.001). Size alone was not a significant predictor but achieved significance when associated with lesion type (mass size, p < 0.001). Masses with irregular shapes or margins and invasive carcinomas were more frequently detected. Patient age, internal enhancement pattern, and distribution of NME were not significant predictors in sonographic detection. A presumed sonographic correlate for NME was found for 16 (16.2%) of 99 attempted lesions.

CONCLUSION

As MRI access expands, utilization of MRI-directed US should be scrutinized to avoid downstream practice inefficiencies. Sonographic detection rates for NME remain low for women undergoing MRI for disease extent, with NME often better suited for MRI-guided biopsy.