Magnetic resonance imaging in breast cancer

Occult breast cancer in an older woman: A case report

Occult breast cancer (OBC) is a relatively rare clinical condition that can complicate differential diagnosis efforts and delay the administration of specific treatments. The individualized therapy of patients with OBC should be performed based on their clinical symptoms, imaging findings and pathological diagnosis. The present case study describes a 51-year-old woman with a painless left axillary tumor. The axillary lymph nodes of the patient were affected by invasive ductal carcinoma, as determined by histological analysis. However, the primary lesion was missed by numerous testing. The patient underwent surgery and testing for positron emission tomography/computed tomography (PET/CT). The present study comprehensively examined this case and offered a systematic analysis of the relevant scholarly works on the diagnosis, treatment and prognosis of OBC. Ultrasonography revealed the presence of three homogenous hypoechoic masses with irregular margins in the left axilla of the patient. PET/CT scanning identified multiple enlarged left axillary hypermetabolic lymph nodes. After that, the patient underwent a nipple-sparing mastectomy and an axillary lymphadenectomy. With the lymph nodes showing metastatic, infiltrating ductal carcinoma from the breast, ductal carcinoma in situ of the breast diagnosis was supported by a histological examination. Immunohistochemical staining revealed that resected lymph nodes were positive for both estrogen and progesterone receptors, consistent with the status of the breast as the primary tumor site. Following surgery, the patient underwent adjuvant chemotherapy treatment. At 12 months post-surgery, the patient remained well without evidence of disease. OBC cases lack the typical clinical and imaging findings associated with breast cancer, and a combination of axillary lymph node examination and immunohistochemistry is essential for accurately diagnosing affected patients. Ensuring the best patient outcomes necessitates accurate and prompt diagnosis, achieved by thorough physical examination, cautious utilization of diagnostic tools, personalized surgical interventions and histological investigation.

Prototype Learning Guided Hybrid Network for Breast Tumor Segmentation in DCE-MRI

Automated breast tumor segmentation on the basis of dynamic contrast-enhancement magnetic resonance imaging (DCE-MRI) has shown great promise in clinical practice, particularly for identifying the presence of breast disease. However, accurate segmentation of breast tumor is a challenging task, often necessitating the development of complex networks. To strike an optimal trade-off between computational costs and segmentation performance, we propose a hybrid network via the combination of convolution neural network (CNN) and transformer layers. Specifically, the hybrid network consists of a encoder-decoder architecture by stacking convolution and deconvolution layers. Effective 3D transformer layers are then implemented after the encoder subnetworks, to capture global dependencies between the bottleneck features. To improve the efficiency of hybrid network, two parallel encoder subnetworks are designed for the decoder and the transformer layers, respectively. To further enhance the discriminative capability of hybrid network, a prototype learning guided prediction module is proposed, where the category-specified prototypical features are calculated through online clustering. All learned prototypical features are finally combined with the features from decoder for tumor mask prediction. The experimental results on private and public DCE-MRI datasets demonstrate that the proposed hybrid network achieves superior performance than the state-of-the-art (SOTA) methods, while maintaining balance between segmentation accuracy and computation cost. Moreover, we demonstrate that automatically generated tumor masks can be effectively applied to identify HER2-positive subtype from HER2-negative subtype with the similar accuracy to the analysis based on manual tumor segmentation. The source code is available at https://github.com/ZhouL-lab/PLHN.

Clinicopathologic and genomic features of lobular like invasive mammary carcinoma: is it a distinct entity?

This study describes "lobular-like invasive mammary carcinomas" (LLIMCas), a group of low- to intermediate-grade invasive mammary carcinomas with discohesive, diffusely infiltrative cells showing retained circumferential membranous immunoreactivity for both E-cadherin and p120. We analyzed the clinical-pathologic features of 166 LLIMCas compared to 104 classical invasive lobular carcinomas (ILCs) and 100 grade 1 and 2 invasive ductal carcinomas (IDCs). Tumor size and pT stage of LLIMCas were intermediate between IDCs and ILCs, and yet often underestimated on imaging and showed frequent positive margins on the first resection. Despite histomorphologic similarities to classical ILC, the discohesion in LLIMCa was independent of E-cadherin/p120 immunophenotypic alteration. An exploratory, hypothesis-generating analysis of the genomic features of 14 randomly selected LLIMCas and classical ILCs (7 from each category) was performed utilizing an FDA-authorized targeted capture sequencing assay (MSK-IMPACT). None of the seven LLIMCas harbored CDH1 loss-of-function mutations, and none of the CDH1 alterations detected in two of the LLIMCas was pathogenic. In contrast, all seven ILCs harbored CDH1 loss-of-function mutations coupled with the loss of heterozygosity of the CDH1 wild-type allele. Four of the six evaluable LLIMCas were positive for CDH1 promoter methylation, which may partially explain the single-cell infiltrative morphology seen in LLIMCa. Further studies are warranted to better define the molecular basis of the discohesive cellular morphology in LLIMCa. Until more data becomes available, identifying LLIMCas and distinguishing them from typical IDCs and ILCs would be justified. In patients with LLIMCas, preoperative MRI should be entertained to guide surgical management.

Magnetic resonance imaging using a nonuniform Bo (NuBo) field-cycling magnet

Magnetic resonance imaging (MRI) is a powerful noninvasive diagnostic tool with superior soft tissue contrast. However, access to MRI is limited since current systems depend on homogeneous, high field strength main magnets (B0-fields), with strong switchable gradients which are expensive to install and maintain. In this work we propose a new approach to MRI where imaging is performed in an inhomogeneous field using radiofrequency spatial encoding, thereby eliminating the need for uniform B0-fields and conventional cylindrical gradient coils. The proposed technology uses an innovative data acquisition and reconstruction approach by integrating developments in field cycling, parallel imaging and non-Fourier based algebraic reconstruction. The scanner uses field cycling to image in an inhomogeneous B0-field; in this way magnetization is maximized during the high field polarization phase, and B0 inhomogeneity effects are minimized by using a low field during image acquisition. In addition to presenting the concept, this work provides experimental verification of a long-lived spin echo signal, spatially varying resolution, as well as both simulated and experimental 2D images. Our initial design creates an open MR system that can be installed in a patient examination table for body imaging (e.g., breast or liver) or built into a wall for weighted-spine imaging. The proposed system introduces a new class of inexpensive, open, silent MRIs that could be housed in doctor's offices much like ultrasound is today, making MRI more widely accessible.

Radiogenomic association of deep MR imaging features with genomic profiles and clinical characteristics in breast cancer

BACKGROUND

It has been believed that traditional handcrafted radiomic features extracted from magnetic resonance imaging (MRI) of tumors are normally shallow and low-ordered. Recent advancement in deep learning technology shows that the high-order deep radiomic features extracted automatically from tumor images can capture tumor heterogeneity in a more efficient way. We hypothesize that MRI-based deep radiomic phenotypes have significant associations with molecular profiles of breast cancer tumors. We aim to identify deep radiomic features (DRFs) from MRI, evaluate their significance in predicting breast cancer (BC) clinical characteristics and explore their associations with multi-level genomic factors.

METHODS

A denoising autoencoder was built to retrospectively extract 4,096 DRFs from 110 BC patients' MRI. Visualization and clustering were applied to these DRFs. Linear Mixed Effect models were used to test their associations with multi-level genomic features (GFs) (risk genes, gene signatures, and biological pathway activities) extracted from the same patients' mRNA expression profile. A Least Absolute Shrinkage and Selection Operator model was used to identify the most predictive DRFs for each clinical characteristic (tumor size (T), lymph node metastasis (N), estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status).

RESULTS

Thirty-six conventional radiomic features (CRFs) for 87 of the 110 BC patients provided by a previous study were used for comparison. More than 1,000 DRFs were associated with the risk genes, gene signatures, and biological pathways activities (adjusted P-value < 0.05). DRFs produced better performance in predicting T, N, ER, PR, and HER2 status (AUC > 0.9) using DRFs. These DRFs showed significant powers of stratifying patients, linking to relevant biological and clinical characteristics. As a contrast, only eight risk genes were associated with CRFs. The RFs performed worse in predicting clinical characteristics than DRFs.

CONCLUSIONS

The deep learning-based auto MRI features perform better in predicting BC clinical characteristics, which are more significantly associated with GFs than traditional semi-auto MRI features. Our radiogenomic approach for identifying MRI-based imaging signatures may pave potential pathways for the discovery of genetic mechanisms regulating specific tumor phenotypes and may enable a more rapid innovation of novel imaging modalities, hence accelerating their translation to personalized medicine.

A novel integrative computational framework for breast cancer radiogenomic biomarker discovery

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Bayesian tensor factorization is used to integrate multiomics data for radiogenomics analysis.

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A regression framework is proposed to handle the unmatched data issue in radiogenomics analysis.

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Deep learning is used to identify prognostic meaningful radiogenomic biomarkers for cancer.

In precise medicine, it is with great value to develop computational frameworks for identifying prognostic biomarkers which can capture both multi-genomic and phenotypic heterogeneity of breast cancer (BC). Radiogenomics is a field where medical images and genomic measurements are integrated and mined to solve challenging clinical problems. Previous radiogenomic studies suffered from data incompleteness, feature subjectivity and low interpretability. For example, the majority of the radiogenomic studies miss one or two of medical imaging data, genomic data, and clinical outcome data, which results in the data incomplete issue. Feature subjectivity issue comes from the extraction of imaging features with significant human involvement. Thus, there is an urgent need to address above-mentioned limitations so that fully automatic and transparent radiogenomic prognostic biomarkers could be identified for BC.

We proposed a novel framework for BC prognostic radiogenomic biomarker identification. This framework involves an explainable DL model for image feature extraction, a Bayesian tensor factorization (BTF) processing for multi-genomic feature extraction, a leverage strategy to utilize unpaired imaging, genomic, and survival outcome data, and a mediation analysis to provide further interpretation for identified biomarkers. This work provided a new perspective for conducting a comprehensive radiogenomic study when only limited resources are given. Compared with baseline traditional radiogenomic biomarkers, the 23 biomarkers identified by the proposed framework performed better in indicating patients’ survival outcome. And their interpretability is guaranteed by different levels of build-in and follow-up analyses.

Theranostic Advances in Breast Cancer in Nuclear Medicine

The implication of 'theranostic' refers to targeting an identical receptor for diagnostic and therapeutic purposes, by the same radioligand, simultaneously or separately. In regard to extensive efforts, many considerable theranostic tracers have been developed in recent years. Emerging evidence strongly demonstrates the tendency of nuclear medicine towards therapies based on a diagnosis. This review is focused on the examples of targeted radiopharmaceuticals for the imaging and therapy of breast cancer.

The Impact of Preoperative Breast MRI on Surgical Margin Status in Breast Cancer Patients Recalled at Biennial Screening Mammography: An Observational Cohort Study

Background

This study aimed to examine the association between preoperative magnetic resonance imaging (MRI) and surgical margin involvement, as well as to determine the factors associated with positive resection margins in screen-detected breast cancer patients undergoing breast-conserving surgery (BCS).

Methods

Breast cancer patients eligible for BCS and diagnosed after biennial screening mammography in the south of The Netherlands (2008–2017) were retrospectively included. Missing values were imputed and multivariable regression analyses were performed to analyze whether preoperative MRI was related to margin involvement after BCS, as well as to examine what factors were associated with positive resection margins, defined as more than focally (>4 mm) involved.

Results

Overall, 2483 patients with invasive breast cancer were enrolled, of whom 123 (5.0%) had more than focally involved resection margins. In multivariable regression analyses, preoperative MRI was associated with a reduced risk of positive resection margins after BCS (adjusted odds ratio [OR] 0.56, 95% confidence interval [CI] 0.33–0.96). Lobular histology (adjusted OR 2.86, 95% CI 1.68–4.87), large tumor size (per millimeter increase, adjusted OR 1.05, 95% CI 1.03–1.07), high (>75%) mammographic density (adjusted OR 3.61, 95% CI 1.07–12.12), and the presence of microcalcifications (adjusted OR 4.45, 95% CI 2.69–7.37) and architectural distortions (adjusted OR 1.85, 95% CI 1.01–3.40) were independently associated with positive resection margins after BCS.

Conclusions

Preoperative MRI was associated with lower risk of positive resection margins in patients with invasive breast cancer eligible for BCS using multivariable analysis. Furthermore, specific mammographic characteristics and tumor characteristics were independently associated with positive resection margins after BCS.

Integrated Multiparametric Radiomics and Informatics System for Characterizing Breast Tumor Characteristics with the OncotypeDX Gene Assay

Optimal use of multiparametric magnetic resonance imaging (mpMRI) can identify key MRI parameters and provide unique tissue signatures defining phenotypes of breast cancer. We have developed and implemented a new machine-learning informatic system, termed Informatics Radiomics Integration System (IRIS) that integrates clinical variables, derived from imaging and electronic medical health records (EHR) with multiparametric radiomics (mpRad) for identifying potential risk of local or systemic recurrence in breast cancer patients. We tested the model in patients (n = 80) who had Estrogen Receptor positive disease and underwent OncotypeDX gene testing, radiomic analysis, and breast mpMRI. The IRIS method was trained using the mpMRI, clinical, pathologic, and radiomic descriptors for prediction of the OncotypeDX risk score. The trained mpRad IRIS model had a 95% and specificity was 83% with an Area Under the Curve (AUC) of 0.89 for classifying low risk patients from the intermediate and high-risk groups. The lesion size was larger for the high-risk group (2.9 ± 1.7 mm) and lower for both low risk (1.9 ± 1.3 mm) and intermediate risk (1.7 ± 1.4 mm) groups. The lesion apparent diffusion coefficient (ADC) map values for high- and intermediate-risk groups were significantly (p < 0.05) lower than the low-risk group (1.14 vs. 1.49 × 10-3 mm2/s). These initial studies provide deeper insight into the clinical, pathological, quantitative imaging, and radiomic features, and provide the foundation to relate these features to the assessment of treatment response for improved personalized medicine.

Preoperative Magnetic Resonance Imaging Features Associated with Positive Resection Margins in Patients with Invasive Lobular Carcinoma

OBJECTIVE

To investigate preoperative magnetic resonance imaging (MRI) findings associated with resection margin status in patients with invasive lobular carcinoma (ILC) who underwent breast-conserving surgery.

MATERIALS AND METHODS

One hundred and one patients with ILC who underwent preoperative MRI were included. MRI (tumor size, multifocality, type of enhancing lesion, distribution of non-mass enhancement [NME], and degree of background parenchymal enhancement) and clinicopathological features (age, pathologic tumor size, presence of ductal carcinoma in situ [DCIS] or lobular carcinoma in situ, presence of lymph node metastases, and estrogen receptor/progesterone receptor/human epidermal growth factor receptor type 2 status) were analyzed. A positive resection margin was defined as the presence of invasive cancer or DCIS at the inked surface. Logistic regression analysis was performed to determine pre- and postoperative variables associated with positive resection margins.

RESULTS

Among the 101 patients, 21 (20.8%) showed positive resection margins. In the univariable analysis, NME, multifocality, axillary lymph node metastasis, and pathologic tumor size were associated with positive resection margins. With respect to preoperative MRI findings, multifocality (odds ratio [OR] = 3.977, p = 0.009) and NME (OR = 2.741, p = 0.063) were associated with positive resection margins in the multivariable analysis, although NME showed borderline significance.

CONCLUSION

In patients with ILC, multifocality and the presence of NME on preoperative breast MRI were associated with positive resection margins.

Autoantibodies as Potential Biomarkers in Breast Cancer

Breast cancer is a major cause of mortality in women; however, technologies for early stage screening and diagnosis (e.g., mammography and other imaging technologies) are not optimal for the accurate detection of cancer. This creates demand for a more effective diagnostic means to replace or be complementary to existing technologies for early discovery of breast cancer. Cancer neoantigens could reflect tumorigenesis, but they are hardly detectable at the early stage. Autoantibodies, however, are biologically amplified and hence may be measurable early on, making them promising biomarkers to discriminate breast cancer from healthy tissue accurately. In this review, we summarized the recent findings of breast cancer specific antigens and autoantibodies, which may be useful in early detection, disease stratification, and monitoring of treatment responses of breast cancer.

Benefits of preoperative MRI in breast cancer surgery studied in a large population-based cancer registry

Background

Although evidence for the benefits of preoperative MRI in breast cancer is lacking, use of MRI is increasing and characterized by large interhospital variation. The aim of the study was to evaluate MRI use and surgical outcomes retrospectively.

Methods

Women with invasive breast cancer (pT1–3) or ductal carcinoma in situ (DCIS), diagnosed in 2011–2013, were selected from the Netherlands Cancer Registry and subdivided into the following groups: invasive cancer, high-grade DCIS, non-palpable cancer, age 40 years or less, and invasive lobular cancer. Associations between preoperative MRI use and initial mastectomy, resection margin after breast-conserving surgery (BCS), re-excision after BCS, and final mastectomy were analysed.

Results

In total, 5514 women were included in the study; 1637 (34·1 per cent) of 4801 women with invasive cancer and 150 (21·0 per cent) of 713 with DCIS had preoperative MRI. Positive resection margins were found in 18·1 per cent women who had MRI and in 15·1 per cent of those who did not (adjusted odds ratio (OR) 1·20, 95 per cent c.i. 1·00 to 1·45), with no differences in subgroups. Re-excision rates were 9·8 per cent in the MRI group and 7·2 per cent in the no-MRI group (adjusted OR 1·33, 1·04 to 1·70), with no differences in subgroups. In the MRI group, 38·8 per cent of patients ultimately underwent mastectomy, compared with 24·2 per cent in the no-MRI group (adjusted OR 2·13, 1·87 to 2·41). This difference was not found for patients aged 40 years or less, or for those diagnosed with lobular cancer.

Conclusion

No subgroup was identified in which preoperative MRI influenced the risk of margin involvement or re-excision rate after BCS. MRI was significantly associated with more extensive surgery, except in patients aged 40 years or less and those with invasive lobular cancer. These results suggest that use of preoperative MRI should be more targeted, and that general, widespread use be discouraged.

Breast Cancer: Conventional Diagnosis and Treatment Modalities and Recent Patents and Technologies

Breast cancer is the most prevalent cancer among women worldwide. However, increased survival is due to the dramatic advances in the screening methods, early diagnosis, and breakthroughs in treatments. Over the course of the last decade, many acquisitions have taken place in this critical field of research in the pharmaceutical industry. Advances in molecular biology and pharmacology aided in better understanding of breast cancer, enabling the design of smarter therapeutics able to target cancer and respond to its microenvironment efficiently. Patents and research papers investigating diagnosis and treatment strategies for breast cancer using novel technologies have been surveyed for the past 15 years. Various nanocarriers have been introduced to improve the therapeutic efficacy of anticancer drugs, including liposomes, polymeric micelles, quantum dots, nanoparticles, and dendrimers. This review provides an overview of breast cancer, conventional therapy, novel technologies in the management of breast cancer, and rational approaches for targeting breast cancer.

HIGHLIGHTS

Breast cancer is the most common cancer in women worldwide. However, survival rates vary widely, optimistically heading toward a positive trend. Increased survival is due to the drastic shift in the screening methods, early diagnosis, and breakthroughs in treatments.Different strategies of breast cancer classification and staging have evolved over the years. Intrinsic (molecular) subtyping is essential in clinical trials and well understanding of the disease.Many novel technologies are being developed to detect distant metastases and recurrent disease as well as to assess response to breast cancer management.Intensive research efforts are actively ongoing to take novel breast cancer therapeutics to potential clinical application.Most of the recent research papers and patents discuss one of the following strategies: the development of new drug entities that specifically target the breast tumor cells; tailor designing a novel carrier system that can multitask and multifunction as a drug carrier, targeting vehicle and even as a diagnostic tool, direct conjugation of a therapeutic drug moiety with a targeting moiety, diagnostic moiety or pharmacokinetics altering moiety; or the use of innovative nontraditional approaches such as genetic engineering, stem cells, or vaccinations.

Limitations of mammography in the diagnosis of breast diseases compared with ultrasonography: a single-center retrospective analysis of 274 cases

BACKGROUND

The aim of this study is to compare X-ray mammography (MG) and ultrasonography (US) in the diagnosis of breast diseases in Chinese women.

METHODS

We retrospectively analyzed X-ray mammograms of 274 patients with US and surgical/pathological results of breast diseases diagnosed at The Second Affiliated Hospital of Anhui Medical University (Hefei, China) between March 2011 and November 2014. The MG and US data were compared to surgical records using the results from post-surgical pathological examinations as the gold standard.

RESULTS

The overall sensitivity, specificity, accuracy, false-positive, false-negative, positive predictive value, and negative predictive value for the detection of breast cancer were 88.5%, 57.9%, 73.7%, 42.1%, 11.5%, 69.2%, and 82.5%, respectively, for MG and 95.9%, 66.7%, 81.8%, 33.3%, 4.1%, 75.5%, and 93.8%, respectively, for US. Of the 274 cases, lesion size by MG agreed with surgery in 133 (48.5%) patients compared with 216 (78.8%) by US (P < 0.01). Lesion location by MG agreed with surgery in 146 (53.3%) patients compared with 257 (93.8%) by US (P < 0.01). These values were then stratified according to age, menstrual status, breast density, and breast volume, and the agreement rates of MG with surgery were lower than that of US (all P < 0.01), except when the lesion size was >5 cm (P > 0.05).

CONCLUSIONS

US was better than MG in the preoperative evaluation of breast diseases of Chinese women. These results suggest that US could be more useful for detecting breast lesions in China, especially for younger women with dense breasts.

Wait times for breast cancer surgery: effect of magnetic resonance imaging and preoperative investigations on the diagnostic pathway

PURPOSE

Women with breast cancer often require an extensive diagnostic work-up. We sought to determine the overall wait time, from the patient's perspective, from identification of an imaging abnormality to definitive treatment. The objective was to identify which factors contribute to overall wait time in women with breast cancer.

METHODS

A retrospective chart review in a tertiary care center was performed to identify all women who had breast surgery for invasive carcinoma and ductal carcinoma in situ. We recorded the dates of first imaging abnormality, first biopsy, subsequent imaging and biopsy, first consultation with any physician at the cancer center, first surgical consultation, and date of surgery. Clinical data that might influence these dates were then extracted. Wait times were calculated and factors associated with wait times were described.

RESULTS

Eligible consecutive women with a cancer diagnosis (n = 264) were identified. The median time between first imaging abnormality and definitive surgery was 79 days. The median time from first surgical consultation to surgery was significantly longer in women who underwent magnetic resonance imaging and in women who underwent initial imaging outside of our tertiary care center (P < .05). On multivariable analysis, the modifiable factors associated with prolonged wait times included number of preoperative clinic visits, number of visits to radiology, and initial imaging outside of our center (P < .05).

CONCLUSION

Extensive diagnostic work-up is an important factor that affects the time to definitive surgery. A more integrated approach using a rapid diagnostic clinic for tissue diagnosis initially, followed by facilitated preoperative evaluation, may potentially decrease wait times in breast evaluation.

The quality of tumor size assessment by contrast-enhanced spectral mammography and the benefit of additional breast MRI

Background - Contrast-enhanced spectral mammography (CESM) is a promising new breast imaging modality that is superior to conventional mammography for breast cancer detection. We aimed to evaluate correlation and agreement of tumor size measurements using CESM. As additional analysis, we evaluated whether measurements using an additional breast MRI exam would yield more accurate results.

Methods - Between January 1^st 2013 and April 1^st 2014, 87 consecutive breast cancer cases that underwent CESM were collected and data on maximum tumor size measurements were gathered. In 57 cases, tumor size measurements were also available for breast MRI. Histopathological results of the surgical specimen served as gold standard in all cases.

Results - The Pearson's correlation coefficients (PCC) of CESM versus histopathology and breast MRI versus histopathology were all >0.9, p<0.0001. For the agreement between measurements, the mean difference between CESM and histopathology was 0.03 mm. The mean difference between breast MRI and histopathology was 2.12 mm. Using a 2x2 contingency table to assess the frequency distribution of a relevant size discrepancy of >1 cm between the two imaging modalities and histopathological results, we did not observe any advantage of performing an additional breast MRI after CESM in any of the cases.

Conclusion - Quality of tumor size measurement using CESM is good and matches the quality of these measurement assessed by breast MRI. Additional measurements using breast MRI did not improve the quality of tumor size measurements.

Can breast cancer molecular subtype help to select patients for preoperative MR imaging?

PURPOSE

To assess whether breast cancer molecular subtype classified by surrogate markers can be used to predict the extent of clinically relevant disease with preoperative breast magnetic resonance (MR) imaging.

MATERIALS AND METHODS

In this HIPAA-compliant, institutional review board-approved study, informed consent was waived. Preoperative breast MR imaging reports from 441 patients were reviewed for multicentric and/or multifocal disease, lymph node involvement, skin and/or nipple invasion, chest wall and/or pectoralis muscle invasion, or contralateral disease. Pathologic reports were reviewed to confirm the MR imaging findings and for hormone receptors (estrogen and progesterone subtypes), human epidermal growth factor receptor type 2 (HER2 subtype), tumor size, and tumor grade. Surrogates were used to categorize tumors by molecular subtype: hormone receptor positive and HER2 negative (luminal A subtype); hormone receptor positive and HER2 positive (luminal B subtype); hormone receptor negative and HER2 positive (HER2 subtype); hormone receptor negative and HER2 negative (basal subtype). All patients included in the study had a histologic correlation with MR imaging findings or they were excluded. χ(2) analysis was used to compare differences between subtypes, with multivariate logistic regression analysis used to assess for variable independence.

RESULTS

Identified were 289 (65.5%) luminal A, 45 (10.2%) luminal B, 26 (5.9%) HER2, and 81 (18.4%) basal subtypes. Among subtypes, significant differences were found in the frequency of multicentric and/or multifocal disease (luminal A, 27.3% [79 of 289]; luminal B, 53.3% [24 of 45]; HER2, 65.4% [17 of 26]; basal, 27.2% [22 of 81]; P < .001) and lymph node involvement (luminal A, 17.3% [50 of 289]; luminal B, 35.6% [26 of 45]; HER2, 34.6% [nine of 26]; basal 24.7% [20 of 81]; P = .014). Multivariate analysis showed that molecular subtype was independently predictive of multifocal and/or multicentric disease.

CONCLUSION

Preoperative breast MR imaging is significantly more likely to help detect multifocal and/or multicentric disease and lymph node involvement in luminal B and HER2 molecular subtype breast cancers. Molecular subtype may help to select patients for preoperative breast MR imaging.

Partial–breast irradiation: towards a replacement for whole–breast irradiation?

Largely thanks to all of the investigators and patients who have participated in randomized breast-conservation trials, many women facing a diagnosis of breast cancer today can conserve their breast with the help of adjuvant radiation therapy. A standard course of radiation consists of 5-7 weeks of daily radiation treatments delivered to the whole breast. The success of this treatment has led investigators to attempt to determine whether the same control can be achieved while decreasing the volume of breast tissue irradiated, thus allowing treatment to be delivered in a shorter period of time. This approach could alleviate time and logistical problems faced by patients during their course of treatment as well as improving overall cost-effectiveness. It can also allow complete avoidance of the adjacent heart and lung tissue in the radiation treatment portal. Partial-breast irradiation (the delivery of radiation to the resection cavity, plus a safety margin) delivered in just hours or days, is currently under investigation. Although relatively new, its use is growing rapidly and many institutional and cooperative group trials are quickly enlisting patients, while physicians are gaining experience in a variety of partial-breast irradiation techniques.

PET/MR: a paradigm shift

More than a decade ago, multimodality imaging was introduced into clinical routine with the development of the positron emission tomography (PET)/computed tomography (CT) technique. Since then, PET/CT has been widely accepted in clinical imaging and has emerged as one of the main cancer imaging modalities. With the recent development of combined PET/magnetic resonance (MR) systems for clinical use, a promising new hybrid imaging modality is now becoming increasingly available. The combination of functional information delivered by PET with the morphologic and functional imaging of MR imaging (e.g., diffusion-weighted imaging, dynamic contrast-enhanced MR imaging and MR spectroscopy) offers exciting possibilities for clinical applications as well as basic research. However, the differences between CT and MR imaging are fundamental. This also leads to distinct differences between PET/CT and PET/MR not only regarding image interpretation but also concerning data acquisition, data processing and image reconstruction. This article provides an overview of the principal differences between PET/CT and PET/MR in terms of scanner design and technology, attenuation correction, speed, acquisition protocols, radiation exposure and safety aspects. PET/MR is expected to show advantages over PET/CT in clinical applications in which MR is known to be superior to CT due to its high intrinsic soft tissue contrast. However, as of now, only assumptions can be made about the future clinical role of PET/MR, as data about the performance of PET/MR in the clinical setting are still limited. The possible future clinical use of PET/MR in oncology, neurology and neurooncology, cardiology and imaging of inflammation is discussed.

High-risk breast lesions at imaging-guided needle biopsy: usefulness of MRI for treatment decision

OBJECTIVE

The purpose of this study is to evaluate the role of MRI for characterization of high-risk breast lesions diagnosed at imaging-guided needle biopsy.

MATERIALS AND METHODS

In this retrospective analysis of 220 patients, 227 high-risk lesions (94 papillomas, 64 radial sclerosing lesions, 46 lobular neoplasias, and 23 atypical ductal hyperplasias) found at 11-gauge vacuum-assisted or 14-gauge needle biopsy were studied with dynamic MRI (time resolution, 84 or 88 seconds; gadopentetate dimeglumine or gadobenate dimeglumine, 0.1 mmol/kg). When lesions showed contrast enhancement on subtracted images, they were considered suspicious for malignancy. The reference standard was histopathologic examination after surgical excision in 190 of 227 (84%) lesions and negative follow-up (≥ 24 months) in 37 of 227 (16%) lesions. Predictive values and likelihood ratios were calculated.

RESULTS

Of 227 lesions, 155 (68%) were contrast enhancing and 72 (32%) were not. Of 155 contrast-enhancing lesions, 28 (18%) were upgraded to malignancy after surgical excision (nine papillomas, one radial sclerosing lesion, 11 lobular neoplasias, and seven atypical ductal hyperplasias); there were 11 invasive carcinomas and 17 ductal carcinomas in situ, four of the latter being G3. Of 72 non-contrast-enhancing lesions, two (3%) were upgraded to malignancy after surgical excision (one radial sclerosing lesion and one lobular neoplasia), both of which were G1 ductal carcinoma in situ. Cancer probability was significantly higher for contrast-enhancing (18%) than for non-contrast-enhancing (3%) lesions (p = 0.001) and for nonmasslike (43%) than for masslike (14%) lesions (p = 0.005). The positive predictive value was 18% (28/155; 95% CI, 13-24%), the negative predictive value was 97% (70/72; 95% CI, 94-99%), the positive likelihood ratio was 1.448 (95% CI, 1.172-1.788), and the negative likelihood ratio was 0.188 (95% CI, 0.152-0.232).

CONCLUSION

The absence of enhancement at dynamic MRI allowed reliable exclusion of invasive cancers among high-risk lesions diagnosed at needle biopsy.

Assessment of grating-based X-ray phase-contrast CT for differentiation of invasive ductal carcinoma and ductal carcinoma in situ in an experimental ex vivo set-up

OBJECTIVE

Limited contrast between healthy and tumour tissue is a limiting factor in mammography and CT of the breast. Phase-contrast computed tomography (PC-CT) provides improved soft-tissue contrast compared with absorption-based techniques. In this study, we assessed the technical feasibility of grating-based PC-CT imaging of the breast for characterisation of ductal carcinoma in situ (DCIS).

METHODS

Grating-based PC-CT was performed on one breast specimen containing an invasive ductal carcinoma and DCIS using monochromatic radiation of 23 keV. Phase-contrast and absorption-based images were compared qualitatively and quantitatively with histopathology in a blinded fashion.

RESULTS

Grating-based PC-CT showed improved differentiation of soft-tissue components. Circular structures of high phase-shift contrast corresponding to the walls of the dilated ductuli of the DCIS were visualised with a contrast-to-noise ratio (CNR) of 9.6 using PC-CT but were not detectable on absorption-based images (CNR = 0.27). The high phase-shift structures of the dilated ductuli were identifiable in the PC-CT volume data set allowing for 3D characterisation of DCIS.

CONCLUSIONS

Our results indicate that unlike conventional CT, grating-based PC-CT may allow the differentiation between invasive carcinoma and intraductal carcinoma and healthy breast tissue and provide 3D visualisation of DCIS.

Discrimination of benign and malignant breast lesions by using shutter-speed dynamic contrast-enhanced MR imaging

PURPOSE

To assess the accuracy of the shutter-speed approach compared with standard approach dynamic contrast material-enhanced magnetic resonance (MR) imaging pharmacokinetic analysis for breast cancer diagnosis.

MATERIALS AND METHODS

This study was approved by the institutional review board and was HIPAA compliant. Informed consent was obtained from 89 high-risk women (age range, 28-83 years) who had 92 suspicious lesions with negative findings at mammography (but visible at MR imaging). Each underwent a research dynamic contrast-enhanced MR imaging examination just prior to a clinical MR imaging-guided interventional procedure. Tumor region of interest (ROI) averaged and (for some) pixel-by-pixel dynamic contrast-enhanced time-course data, together with mean arterial input function, were subjected to serial standard and shutter-speed approach analyses to extract pharmacokinetic parameters, including rate constant for passive contrast reagent transfer between plasma and interstitium (K(trans)) and interstitial space volume fraction, or v(e). Pathologic findings were used as reference standards. Diagnostic accuracy was assessed with receiver operating characteristic analyses.

RESULTS

The pathologic analyses revealed 20 malignant and 72 benign lesions. Positive predictive value of the institutional clinical breast MR imaging protocol was 22%. At 100% sensitivity, ROI-averaged shutter-speed approach K(trans) had significantly (P = .008) higher diagnostic specificity than standard approach K(trans): 86.1% versus 77.8%. The difference in the ROI-averaged K(trans) parameter value, or ΔK(trans) (≡ K(trans) [shutter-speed approach] - K(trans) [standard approach]), had even higher specificity (88.9%). Combined use of ROI analysis and pixel-by-pixel mapping of ΔK(trans) achieved 98.6% specificity at 100% sensitivity.

CONCLUSION

The use of the shutter-speed dynamic contrast-enhanced MR imaging method has the potential to improve breast cancer diagnostic accuracy and reduce putatively unnecessary biopsy procedures that yield benign pathologic findings.

SUPPLEMENTAL MATERIAL

http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11102413/-/DC1.

Meta-analysis of quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesions

Background

To determine, in a meta-analysis, the diagnostic performance of quantitative diffusion-weighted (DW) MR imaging in patients with breast lesions.

Methods

English and Chinese studies published prior to June 2009 to assess the diagnostic performance of quantitative DWI in patients with breast lesions were reviewed and summarized with reference to the inclusion and exclusion criteria. Methodological quality was assessed by using the quality assessment of diagnostic studies (QUADAS) instrument. Publication bias analysis was performed by using Comprehensive Meta-analysis version 2. Meta-Disc version 1.4 was used to describe primary results and explore homogeneity by Chi-square test and inconsistency index; to explore threshold effect by receiver operator characteristic (ROC) space and Spearman correlation coefficient; and to pool weighted sensitivity and specificity by fixed or random effect model. A summary ROC (sROC) curve was constructed to calculate the area under the curve (AUC).

Results

Of 65 eligible studies, 13 with 615 malignant and 349 benign lesions were included in the original meta-analysis, among which heterogeneity arising from factors other than threshold effect and publication bias was explored. Methodological quality was moderate. The pooled weighted sensitivity and specificity with corresponding 95% confidence interval (CI) in one homogenous subgroup of studies using maximum b = 1000 s/mm² were 0.84 (0.80, 0.87) and 0.84 (0.79, 0.88) respectively. AUC of sROC was 0.9085. Sensitivity analysis demonstrated that the pooled estimates were stable and reliable.

Conclusions

Quantitative DWI has a higher specificity to differentiate between benign and malignant breast lesions compared to that of contrast-enhanced MRI. However, large scale randomized control trials (RCTs) are necessary to assess its clinical value because of disunified diffusion gradient factor b and diagnosis threshold.

Diagnostic accuracy of fused positron emission tomography/magnetic resonance mammography: initial results

OBJECTIVES

The aim of this study was to evaluate the diagnostic accuracy of fused fluoro-deoxy-D-glucose positron emission tomography/magnetic resonance mammography (FDG-PET/MRM) in breast cancer patients and to compare FDG-PET/MRM with MRM.

METHODS

27 breast cancer patients (mean age 58.9±9.9 years) underwent MRM and prone FDG-PET. Images were fused software-based to FDG-PET/MRM images. Histopathology served as the reference standard to define the following parameters for both MRM and FDG-PET/MRM: sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy for the detection of breast cancer lesions. Furthermore, the number of patients with correctly determined lesion focality was assessed. Differences between both modalities were assessed by McNemaŕs test (p<0.05). The number of patients in whom FDG-PET/MRM would have changed the surgical approach was determined.

RESULTS

58 breast lesions were evaluated. The sensitivity, specificity, PPV, NPV and accuracy were 93%, 60%, 87%, 75% and 85% for MRM, respectively. For FDG-PET/MRM they were 88%, 73%, 90%, 69% and 92%, respectively. FDG-PET/MRM was as accurate for lesion detection (p = 1) and determination of the lesions' focality (p = 0.7722) as MRM. In only 1 patient FDG-PET/MRM would have changed the surgical treatment.

CONCLUSION

FDG-PET/MRM is as accurate as MRM for the evaluation of local breast cancer. FDG-PET/MRM defines the tumours' focality as accurately as MRM and may have an impact on the surgical treatment in only a small portion of patients. Based on these results, FDG-PET/MRM cannot be recommended as an adjunct or alternative to MRM.

Molecular and Functional Imaging of Breast Cancer

Background

Significant efforts have been directed toward developing and enhancing imaging methods for the early detection, diagnosis, and characterization of small breast tumors. Molecular and functional imaging sets the stage for enhancement of current methodology.

Methods

Current imaging modalities are described based on the molecular characteristics of normal and malignant tissue. New molecular imaging methods that have the potential for clinical use are also discussed.

Results:

Dynamic contrast-enhanced magnetic resonance imaging is more sensitive than mammography in BRCA1 carriers. It is used in screening and in the early evaluation of neoadjuvant therapy. Positron emission mammography is 91% sensitive and 93% specific in detecting primary breast cancers. Sentinel node scintigraphy is a key component of axillary lymph node evaluation. Other imaging modalities being studied include Tc99m sestamibi, radiolabeled thymidine or uridine, estrogen receptor imaging, magnetic resonance spectroscopy, and diffusion magnetic resonance imaging.

Conclusions

Molecular and functional imaging of the breast will likely alter clinical practice in diagnosing and staging primary breast cancer and assessing response to therapy since it will provide earlier information regarding the underlying biology of individual breast cancers, tumor stage, potential treatment strategies, and biomarkers for early evaluation of treatment effects.

Magnetic resonance imaging screening of the contralateral breast in women with newly diagnosed breast cancer: systematic review and meta-analysis of incremental cancer detection and impact on surgical management

PURPOSE

Preoperative magnetic resonance imaging (MRI) is increasingly used for staging women with breast cancer, including screening for occult contralateral cancer. This article is a review and meta-analysis of studies reporting contralateral MRI in women with newly diagnosed invasive breast cancer.

METHODS

We systematically reviewed the evidence on contralateral MRI, calculating pooled estimates for positive predictive value (PPV), true-positive:false-positive ratio (TP:FP), and incremental cancer detection rate (ICDR) over conventional imaging. Random effects logistic regression examined whether estimates were associated with study quality or clinical variables.

RESULTS

Twenty-two studies reported contralateral malignancies detected only by MRI in 131 of 3,253 women. Summary estimates were as follows: MRI-detected suspicious findings (TP plus FP), 9.3% (95% CI, 5.8% to 14.7%); ICDR, 4.1% (95% CI, 2.7% to 6.0%), PPV, 47.9% (95% CI, 31.8% to 64.6%); TP:FP ratio, 0.92 (95% CI, 0.47 to 1.82). PPV was associated with the number of test positives and baseline imaging. Few studies included consecutive women, and few ascertained outcomes in all subjects. Where reported, 35.1% of MRI-detected cancers were ductal carcinoma in situ (mean size = 6.9 mm), 64.9% were invasive cancers (mean size = 9.3 mm), and the majority were stage pTis or pT1 and node negative. Effect on treatment was inconsistently reported, but many women underwent contralateral mastectomy.

CONCLUSION

MRI detects contralateral lesions in a substantial proportion of women, but does not reliably distinguish benign from malignant findings. Relatively high ICDR may be due to selection bias and/or overdetection. Women must be informed of the uncertain benefit and potential harm, including additional investigations and surgery.

Novel nanomedicine-based MRI contrast agents for gynecological malignancies

Gynecological cancers result in significant morbidity and mortality in women despite advances in treatment and diagnosis. This is due to detection of the disease in the late stages following metastatic spread in which treatment options become limited and may not result in positive outcomes. In addition, traditional contrast agents are not very effective in detecting primary metastatic tumors and cells due to a lack of specificity and sensitivity of the diagnostic tools, which limits their effectiveness. Recently, the field of nanomedicine-based contrast agents offers a great opportunity to develop highly sophisticated devices that can overcome many traditional hurdles of contrast agents including solubility, cell-specific targeting, toxicities, and immunological responses. These nanomedicine-based contrast agents including liposomes, micelles, dendrimers, multifunctional magnetic polymeric nanohybrids, fullerenes, and nanotubes represent improvements over their traditional counterparts, which can significantly advance the field of molecular imaging.

Combined PET/MRI: a new dimension in whole-body oncology imaging?

INTRODUCTION

Hybrid imaging systems providing morphological and functional data in a single session have been available for oncological imaging for some time. So far, computed tomography (CT) has been the morphological method-of-choice for inclusion into these hybrid imaging systems. However, recently, research has focused on hardware-based fusion of function with magnetic resonance imaging (MRI) rather than CT.

OBJECTIVES

Now that the first head-only positron emission tomography (PET)/MRI systems have been installed and whole-body systems are to be expected in the near future, potential indications in clinical oncology have to be addressed.

DISCUSSION

This article discusses potential indications of PET/MRI in whole-body oncology imaging. Potential advantages and disadvantages compared with currently available hybrid imaging systems will be reviewed.

Treatment for patients with unknown primary cancer and favorable prognostic factors

Patients with carcinoma of unknown primary site are heterogeneous with respect to clinical and pathologic features. Within this diverse group, specific clinical and/or pathologic features can be used to define several subsets with favorable prognoses. Specific subsets include women with peritoneal carcinomatosis, women with isolated axillary lymph node metastases, adenocarcinoma presenting as a single metastatic lesion, young men with features of extragonadal germ cell tumor, squamous carcinoma involving cervical or inguinal lymph nodes, and neuroendocrine carcinoma. Prospective identification of patients in these favorable subgroups allows the most effective treatment to be selected. This review summarizes current recommendations for the evaluation and treatment of patients in each of these favorable prognostic subsets.

Clinical utility of breast-specific gamma imaging for evaluating disease extent in the newly diagnosed breast cancer patient

BACKGROUND

Breast-specific gamma imaging (BSGI) is a functional imaging modality that has comparable sensitivity but superior specificity compared with magnetic resonance imaging, yielding fewer false-positive results and thereby improving clinical management of the newly diagnosed breast cancer patient.

METHODS

A retrospective review was performed from 2 community-based breast imaging centers of newly diagnosed breast cancer patients in whom BSGI was performed as part of the imaging work-up.

RESULTS

A total of 138 patients (69 invasive ductal carcinoma, 20 invasive lobular carcinoma, 32 ductal carcinoma in situ, and 17 mixtures of invasive ductal carcinoma, invasive lobular carcinoma, or ductal carcinoma in situ and other) were reviewed. Twenty-five patients (18.1%) had a positive BSGI study at a site remote from their known cancer or more extensive disease than detected from previous imaging. Fifteen patients (10.9%) were positive for a synchronous or more extensive malignancy in the same or contralateral breast. Five patients had benign findings on pathology, 5 benign on ultrasound follow-up (false-positive rate, 7.2%). Findings converted 7 patients to mastectomy, 1 patient to neoadjuvant chemotherapy, and 7 patients were found to have previously undetected contralateral cancer. The positive predictive value for BSGI was 92.9%.

CONCLUSIONS

BSGI detected additional or more extensive malignancy in the same or contralateral breast in 10.9% of newly diagnosed breast cancer patients. Only 7.2% incurred an additional work-up. BSGI provides accurate evaluation of remaining breast tissue in newly diagnosed breast cancer patients with few false-positive readings.

Recent advances in breast MRI and MRS

Breast MRI is an area of intense research and is fast becoming an important tool for the diagnosis of breast cancer. This review covers recent advances in breast MRI, MRS, and image post-processing and analysis. Several studies have explored a multi-parametric approach to breast imaging that combines analysis of traditional contrast enhancement patterns and lesion architecture with novel methods such as diffusion, perfusion, and spectroscopy to increase the specificity of breast MRI studies. Diffusion-weighted MRI shows some potential for increasing the specificity of breast lesion diagnosis and is even more promise for monitoring early response to therapy. MRS also has great potential for increasing specificity and for therapeutic monitoring. A limited number of studies have evaluated perfusion imaging based on first-pass contrast bolus tracking, and these clearly identify that vascular indices have great potential to increase specificity. The review also covers the relatively new acquisition technique of MR elastography for breast lesion characterization. A brief survey of image processing algorithms tailored for breast MR, including registration of serial dynamic images, segmentation and extraction of morphological features of breast lesions, and contrast uptake modeling, is also included. Recent advances in MRI, MRS, and automated image analysis have increased the utility of breast MR in diagnosis, screening, management, and therapy monitoring of breast cancer.

Magnetic resonance imaging identifies multifocal and multicentric disease in breast cancer patients who are eligible for partial breast irradiation

BACKGROUND

In this retrospective study, the authors hypothesized that magnetic resonance imaging (MRI) would alter partial breast irradiation (PBI) eligibility by identifying cancers outside the PBI volume compared with mammography alone.

METHODS

Since 2002, MRI was used nonselectively at the authors' institution for the staging of patients with nonmetastatic breast cancer. Of 450 consecutive patients with invasive breast cancer, 110 patients who were eligible for PBI were identified by using criteria outlined by National Surgical Adjuvant Breast and Bowel Project B-39/Radiation Oncology Group trial 0413 based on mammography, ultrasonography, and initial pathology. In that trial, patients were randomized (stage I/II invasive cancers that measured <or=3 cm and <or=3 positive lymph nodes) to receive either whole-breast radiotherapy or PBI. MRI reports were reviewed to determine whether MRI identified secondary lesions 1) within the same quadrant (multifocal), 2) in a different quadrant (multicentric), or 3) in the contralateral breast. These lesions were pathologically proven carcinoma and would have rendered the patient ineligible for PBI.

RESULTS

MRI identified secondary lesions in 10% of patients (95% confidence interval [CI], 4.4%-15.6%). Multifocal disease was identified in 3.6% (95% CI, 1.4%-9%), multicentric disease was identified in 4.5% (95% CI, 2%-10.2%), and contralateral disease was identified in 1.8% (95% CI, 0.5%-6.4%). The proportion of patients with false-positive MRI findings was 4.5% (95% CI, 2%-10.2%). The positive predictive value of MRI was 72.2% (95% CI, 46.4%-89.3%).

CONCLUSIONS

MRI identified frequent secondary cancers that would not be removed routinely by surgery or targeted in the radiation field if treated with PBI. The current data suggest that MRI should be considered to assess PBI eligibility to minimize potential local failures.

Magnetic Resonance Imaging (MRI) and Spectroscopy (MRS) in Breast Cancer

Breast cancer is a major health problem in women and early detection is of prime importance. Breast magnetic resonance imaging (MRI) provides both physical and physiologic tissue features that are useful in discriminating malignant from benign lesions. Contrast enhanced MRI is valuable for diagnosis of small tumors in dense breast and the structural and kinetic parameters improved the specificity of diagnosing benign from malignant lesions. It is a complimentary modality for preoperative staging, to follow response to therapy, to detect recurrences and for screening high risk women. Diffusion, perfusion and MR elastography have been applied to breast lesion characterization and show promise.

In-vivo MR spectroscopy (MRS) is a valuable method to obtain the biochemical status of normal and diseased tissues. Malignant tissues contain high concentration of choline containing compounds that can be used as a biochemical marker. MRS helps to increase the specificity of MRI in lesions larger than 1cm and to monitor the tumor response. Various MR techniques show promise primarily as adjunct to the existing standard detection techniques, and its acceptability as a screening method will increase if specificity can be improved. This review presents the progress made in different MRI and MRS techniques in beast cancer management.

Contrast-enhanced magnetic resonance imaging of the breast: the value of pharmacokinetic parameters derived from fast dynamic imaging during initial enhancement in classifying lesions

The value of pharmacokinetic parameters derived from fast dynamic imaging during initial enhancement in characterizing breast lesions on magnetic resonance imaging (MRI) was evaluated. Sixty-eight malignant and 34 benign lesions were included. In the scanning protocol, high temporal resolution imaging was combined with high spatial resolution imaging. The high temporal resolution images were recorded every 4.1 s during initial enhancement (fast dynamic analysis). The high spatial resolution images were recorded at a temporal resolution of 86 s (slow dynamic analysis). In the fast dynamic evaluation pharmacokinetic parameters (K^trans, V_e and k_ep) were evaluated. In the slow dynamic analysis, each lesion was scored according to the BI-RADS classification. Two readers evaluated all data prospectively. ROC and multivariate analysis were performed. The slow dynamic analysis resulted in an AUC of 0.85 and 0.83, respectively. The fast dynamic analysis resulted in an AUC of 0.83 in both readers. The combination of both the slow and fast dynamic analyses resulted in a significant improvement of diagnostic performance with an AUC of 0.93 and 0.90 (P = 0.02). The increased diagnostic performance found when combining both methods demonstrates the additional value of our method in further improving the diagnostic performance of breast MRI.

Who Should Have Breast Magnetic Resonance Imaging Evaluation?

During the last two decades, tremendous advances have been made in the performance and interpretation of breast magnetic resonance imaging (MRI) examinations. Technical requirements for optimal breast imaging including the requirement for a breast MRI biopsy system are now being defined as part of a voluntary American College of Radiology (ACR) breast MRI accreditation program. The ACR BI-RADS (Breast Imaging Reporting and Data System) lexicon for breast MRI has brought uniformity to the interpretation of breast MRI examinations. With these advances in imaging technique, interpretation guidelines, and increasing availability of MR-compatible breast biopsy systems, MRI of the breast is rapidly gaining popularity in clinical practice in both the diagnostic setting and, more recently, in the screening setting. The clinical indications for breast MRI, however, remain to be defined. There are clinical indications that have emerged where MRI, as an adjunct to mammography, seems to be the imaging study of choice. There are other indications, specifically breast cancer staging, in which MRI is being utilized with increasing frequency, but in which controversy persists.