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Breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) is a rare but increasingly important diagnosis as the incidence of breast implant placement, both elective and reconstructive, continues to rise. When detected and treated early, this indolent disease carries an excellent prognosis. However, because the clinical presentation is often nonspecific, it is crucial for radiologists to accurately identify the imaging findings associated with BIA-ALCL to facilitate a timely diagnosis. This article will provide radiologists with an overview of the diagnosis, imaging findings, and management of BIA-ALCL.

Background For breast cancer patients undergoing neoadjuvant chemotherapy (NAC), pathologic complete response (pCR; no invasive or in situ) cannot be assessed non-invasively so all patients undergo surgery. The aim of our study was to develop and validate a radiomics classifier that classifies breast cancer pCR post-NAC on MRI prior to surgery. Methods This retrospective study included women treated with NAC for breast cancer from 2014 to 2016 with (1) pre- and post-NAC breast MRI and (2) post-NAC surgical pathology report assessing response. Automated radiomics analysis of pre- and post-NAC breast MRI involved image segmentation, radiomics feature extraction, feature pre-filtering, and classifier building through recursive feature elimination random forest (RFE-RF) machine learning. The RFE-RF classifier was trained with nested five-fold cross-validation using (a) radiomics only (model 1) and (b) radiomics and molecular subtype (model 2). Class imbalance was addressed using the synthetic minority oversampling technique. Results Two hundred seventy-three women with 278 invasive breast cancers were included; the training set consisted of 222 cancers (61 pCR, 161 no-pCR; mean age 51.8 years, SD 11.8), and the independent test set consisted of 56 cancers (13 pCR, 43 no-pCR; mean age 51.3 years, SD 11.8). There was no significant difference in pCR or molecular subtype between the training and test sets. Model 1 achieved a cross-validation AUROC of 0.72 (95% CI 0.64, 0.79) and a similarly accurate (P = 0.1) AUROC of 0.83 (95% CI 0.71, 0.94) in both the training and test sets. Model 2 achieved a cross-validation AUROC of 0.80 (95% CI 0.72, 0.87) and a similar (P = 0.9) AUROC of 0.78 (95% CI 0.62, 0.94) in both the training and test sets. Conclusions This study validated a radiomics classifier combining radiomics with molecular subtypes that accurately classifies pCR on MRI post-NAC.

To evaluate the impact of comorbid conditions and age on mammography use.We used data from the 2011 to 2015 Medical Expenditure Panel Survey, which contained records for 40,752 women over the age of 40. Use was defined as a mammogram within the previous 1 or 2 years, analyzed separately. A logit model was employed to evaluate associations between use and comorbidities and age. Statistical significance was defined by a P.05 by two-sided test.Of the 36,575 women in our study sample, 45.9%, 43.6%, 3.9%, and 5.7% reported a history of hypertension (HTN), hyperlipidemia (HLD), prior heart attack (MI), and prior stroke, respectively. Among women without a comorbid condition, there was 47.3% annual mammography use. HTN and HLD were associated with increased use (2.5 and 6.8 percentage points [pp], P.01). In comparison, prior MI was associated with decreased annual use (-8.2 pp, P.01). Prior stroke was not significantly associated with annual mammography (-1.5 pp, P = .42). Results were similar for biennial use. The age trend in use showed that the age with maximum screening use was approximately 60 years.Mammography use was higher in patients with HTN and HLD and lower in patients with prior MI and stroke, which may reflect differences in comorbidity-related general health care use. Use increased until it peaked around age 60. An understanding of how mammography use naturally evolves as people age may help better target specific populations and improve overall use of preventive care.

This study aims to evaluate ultrafast DCE-MRI-derived kinetic parameters that reflect contrast agent inflow effects in differentiating between subcentimeter BI-RADS 4–5 breast carcinomas and benign lesions. We retrospectively reviewed consecutive 3-T MRI performed from February to October 2017, during which ultrafast DCE-MRI was performed as part of a hybrid clinical protocol with conventional DCE-MRI. In total, 301 female patients with 369 biopsy-proven breast lesions were included. Ultrafast DCE-MRI was acquired continuously over approximately 60 s (temporal resolution, 2.7–7.1 s/phase) starting simultaneously with the start of contrast injection. Four ultrafast DCE-MRI-derived kinetic parameters (maximum slope [MS], contrast enhancement ratio [CER], bolus arrival time [BAT], and initial area under gadolinium contrast agent concentration [IAUGC]) and one conventional DCE-MRI-derived kinetic parameter (signal enhancement ratio [SER]) were calculated for each lesion. Wilcoxon rank sum test or Fisher’s exact test was performed to compare kinetic parameters, volume, diameter, age, and BI-RADS morphological descriptors between subcentimeter carcinomas and benign lesions. Univariate/multivariate logistic regression analyses were performed to determine predictive parameters for subcentimeter carcinomas. In total, 125 lesions (26 carcinomas and 99 benign lesions) were identified as BI-RADS 4–5 subcentimeter lesions. Subcentimeter carcinomas demonstrated significantly larger MS and SER and shorter BAT than benign lesions (p = 0.0117, 0.0046, and 0.0102, respectively). MS, BAT, and age were determined as significantly predictive for subcentimeter carcinoma (p = 0.0208, 0.0023, and

OBJECTIVE. The objective of our study was to assess the utility of targeted breast ultrasound and mammography in evaluating palpable lumps in the mastectomy bed. MATERIALS AND METHODS. This retrospective study identified postmastectomy patients who presented for initial imaging evaluation of palpable lumps between January 2009 and December 2015. Clinical, imaging, and pathology results were reviewed. Surgical reconstruction type and percutaneous sampling data were collected. Patients were excluded if they had known malignancy at imaging presentation, if the palpable lump was not at the mastectomy site, or if there was less than 1 year clinical or imaging follow-up in the absence of biopsy. Each palpable site was assigned as a case, and analyses were performed at the case level. RESULTS. Among the 101 patients with a history of prophylactic or therapeutic mastectomy who presented during the study period, 118 palpable cases met the inclusion criteria. All 118 cases were evaluated with ultrasound and 43 with mammography. Among the 75 cases evaluated with ultrasound alone, nine cancers were detected. Among the 43 cases evaluated with both ultrasound and mammography, three cancers were sonographically detected, of which two were mammographically visible and one was mammographically occult. There were two false-negative ultrasound cases; both underwent sampling because of the level of clinical suspicion. In total, 14 palpable lumps in 12 patients were malignant, and 104 palpable lumps in 89 patients were nonmalignant. Targeted ultrasound yielded a negative predictive value (NPV) of 97% and a positive predictive value 2 of 27%. CONCLUSION. Our data suggest that targeted breast ultrasound, with its high NPV, should be the initial imaging test of choice for palpable lumps after mastectomy. Mammography yielded no additional cancers but was helpful in confirming benign diagnoses. The two false-negative ultrasound cases support palpation-guided sampling for imaging-occult and clinically suspicious palpable lumps.

Rationale and objectives We sought to incorporate a new teaching module into the traditional medical student radiology clerkship, to improve the necessary skills for future referring physicians. Materials and methods A new required and graded module was introduced in 2014 into the radiology clerkship in year three of medical school: the Mystery Case. Each student was provided a unique and undifferentiated case from a dedicated teaching file containing de-identified images and requisition data. Students were expected to complete three serial tasks over one week: 1) prepare a voice recognition-derived, structured radiological report utilizing appropriate and relevant vocabulary; 2) discuss pertinent additional clinical information; and 3) discuss appropriate follow-up imaging, in addition to information on how to best prepare patients for these potential patient exams (e.g., with or without contrast, bowel preparation, and length of study). Students were provided written examples and dedicated class instruction with interactive discussions covering specific cases and associated related cases through random pairing with radiology resident and attending mentors. At the close of the week, students gave brief oral presentations of their cases and submitted the tasks for a written evaluation. Upon completion of the clerkship, the students completed a Likert-type six-item survey to evaluate the perceived improvement in select skills. Results The survey was completed by 82% (54/66) of the enrolled students, with 85% finding the Mystery Case an effective use of time. Medical students perceived an improved awareness of the patient care process (77%), awareness of the medical imaging resources available (89%), ability to understand a radiology report (74%), and ability to advise patients (69%). Conclusion Introduction of the Mystery Case as a graded exercise in the medical school radiology clerkship was perceived by students as effective use of time, with an improvement in the skills essential for future referring physicians.

Purpose To use features extracted from magnetic resonance (MR) images and a machine-learning method to assist in differentiating breast cancer molecular subtypes. Materials and Methods This retrospective Health Insurance Portability and Accountability Act (HIPAA)-compliant study received Institutional Review Board (IRB) approval. We identified 178 breast cancer patients between 2006–2011 with: 1) ERPR + (n = 95, 53.4%), ERPR–/HER2 + (n = 35, 19.6%), or triple negative (TN, n = 48, 27.0%) invasive ductal carcinoma (IDC), and 2) preoperative breast MRI at 1.5T or 3.0T. Shape, texture, and histogram-based features were extracted from each tumor contoured on pre- and three postcontrast MR images using in-house software. Clinical and pathologic features were also collected. Machine-learning-based (support vector machines) models were used to identify significant imaging features and to build models that predict IDC subtype. Leave-one-out cross-validation (LOOCV) was used to avoid model overfitting. Statistical significance was determined using the Kruskal–Wallis test. Results Each support vector machine fit in the LOOCV process generated a model with varying features. Eleven out of the top 20 ranked features were significantly different between IDC subtypes with P < 0.05. When the top nine pathologic and imaging features were incorporated, the predictive model distinguished IDC subtypes with an overall accuracy on LOOCV of 83.4%. The combined pathologic and imaging model's accuracy for each subtype was 89.2% (ERPR+), 63.6% (ERPR–/HER2+), and 82.5% (TN). When only the top nine imaging features were incorporated, the predictive model distinguished IDC subtypes with an overall accuracy on LOOCV of 71.2%. The combined pathologic and imaging model's accuracy for each subtype was 69.9% (ERPR+), 62.9% (ERPR–/HER2+), and 81.0% (TN). Conclusion We developed a machine-learning-based predictive model using features extracted from MRI that can distinguish IDC subtypes with significant predictive power. J. Magn. Reson. Imaging 2016;44:122–129.

We present a segmentation approach that combines GrowCut (GC) with cancer-specific multi-parametric Gaussian Mixture Model (GCGMM) to produce accurate and reproducible segmentations. We evaluated GCGMM using a retrospectively collected 75 invasive ductal carcinoma with ERPR+ HER2− (n = 15), triple negative (TN) (n = 9), and ER-HER2+ (n = 57) cancers with variable presentation (mass and non-mass enhancement) and background parenchymal enhancement (mild and marked). Expert delineated manual contours were used to assess the segmentation performance using Dice coefficient (DSC), mean surface distance (mSD), Hausdorff distance, and volume ratio (VR). GCGMM segmentations were significantly more accurate than GrowCut (GC) and fuzzy c-means clustering (FCM). GCGMM’s segmentations and the texture features computed from those segmentations were the most reproducible compared with manual delineations and other analyzed segmentation methods. Finally, random forest (RF) classifier trained with leave-one-out cross-validation using features extracted from GCGMM segmentation resulted in the best accuracy for ER-HER2+ vs. ERPR+/TN (GCGMM 0.95, expert 0.95, GC 0.90, FCM 0.92) and for ERPR + HER2− vs. TN (GCGMM 0.92, expert 0.91, GC 0.77, FCM 0.83).

Although guidelines such as those of the National Comprehensive Cancer Network consider 18F-FDG PET/CT for systemic staging of newly diagnosed stage III breast cancer patients, factors in addition to stage may influence the utility of PET/CT. Because invasive lobular carcinoma (ILC) is less conspicuous than invasive ductal carcinoma (IDC) on 18F-FDG PET, we hypothesized that tumor histology may be one such factor. We evaluated PET/CT systemic staging of patients newly diagnosed with ILC compared with IDC. Methods: In this Institutional Review Board–approved retrospective study, our Hospital Information System was screened for ILC patients who underwent PET/CT in 2006–2013 before systemic or radiation therapy. Initial stage was determined from examination, mammography, ultrasound, MR, or surgery. PET/CT was performed to identify unsuspected distant metastases. A sequential cohort of stage III IDC patients was evaluated for comparison. Upstaging rates were compared using the Pearson χ2 test. Results: The study criteria were fulfilled by 146 ILC patients. PET/CT revealed unsuspected distant metastases in 12 (8%): 0 of 8 with initial stage I, 2 of 50 (4%) stage II, and 10 of 88 (11%) stage III. Upstaging to IV by PET/CT was confirmed by biopsy in all cases. Three of 12 upstaged patients were upstaged only by the CT component of the PET/CT, as the metastases were not 18F-FDG–avid. In the comparison stage III IDC cohort, 22% (20/89) of patients were upstaged to IV by PET/CT. All 20 demonstrated 18F-FDG–avid metastases. The relative risk of PET/CT revealing unsuspected distant metastases in stage III IDC patients was 1.98 times (95% confidence interval, 0.98–3.98) that of stage III ILC patients (P = 0.049). For 18F-FDG–avid metastases, the relative risk of PET/CT revealing unsuspected 18F-FDG–avid distant metastases in stage III IDC patients was 2.82 times (95% confidence interval, 1.26–6.34) that of stage III ILC patients (P = 0.007). Conclusion:18F-FDG PET/CT was more likely to reveal unsuspected distant metastases in stage III IDC patients than in stage III ILC patients. In addition, some ILC patients were upstaged by non–18F-FDG-avid lesions visible only on the CT images. Overall, the impact of PET/CT on systemic staging may be lower for ILC patients than for IDC patients.

Due to an increasing number of breast cancer diagnoses in younger women anecdotally noted at our institution, we conceived of this study %was to retrospectively review the records of women diagnosed with breast cancer under the age of 40 for potentially alterable versus unalterable risk factors in their history. Between 2007 and 2013, there were 52 patients less than 40 years of age with breast cancer at our institution: 79% (41/52) presented with a clinical abnormality (palpable mass, nipple discharge or inversion) and 21% (11/52) were asymptomatic but diagnosed on early screening mammograms. Seventy-five percent (39/52) of the cancers had an invasive component and 87% (45/52) were intermediate to high grade. Sixty percent (31/52) of subjects had stage 0 or I disease, but 40% (21/52) had later stage disease (stage II or greater). The vast majority of the cancers were ER+ (82%) and PR+ (78%). Fifty-six percent (28/50; 2 unknown) of the subjects had a documented history of hormonal contraception. Fifty-three percent (27/51; 1 unknown) of had no family history of breast cancer whatsoever, and 80% (41/51) had no family history of breast cancer in a first degree relative. Six were positive for BRCA 1, 2, or a variant (6/52 = 12%).

Breast cancer subtypes are increasingly classified based on tumor genotype, which is often predictive of outcome, and molecular characterization is now often used to guide targeted therapy. Luminal A subtype is defined by immunohistochemistry surrogates, including positive estrogen receptor (ER+) and/or positive progesterone receptor (PR+), negative HER2 receptor (HER2−), and a low Ki67 level. This subtype of ER-positive breast cancer is the most common subtype and correlates with the highest probability of long-term disease-free and overall survival compared to luminal B, HER2-overexpressing, and basal-like subtypes.1 However, there is significant intertumoral and intratumoral variability in biological aggressiveness within the luminal A subtype, which has motivated a search for biomarkers and predictive models to more effectively personalize treatment regimes.2–4 The Oncotype Dx (Genomic Health, Redwood City, CA) breast cancer assay incorporates the mRNA expression of 21 genes, resulting in the so-called Recurrence Score (RS), that has been shown to be predictive and prognostic in early-stage ER-positive/HER2-negative invasive breast cancer.5–12 The American Society of Clinical Oncology (ASCO) recommended its clinical use based on data showing that RS correlates with the magnitude of chemotherapy benefit as well as the 10-year risk of distant recurrence, both increasing with higher RS scores.13 Oncotype Dx RS (hereafter, ODxRS) is used clinically to influence decision-making, sometimes preventing unnecessary chemotherapy.5 Correlating imaging phenotype with genomic information (often referred to as “radiogenomics”), in order to better understand genetic variability and the ability to predict prognosis or response to therapy, is a new field of research.14 The overlap between image-based breast cancer phenotype features and genomic characteristics is not currently well established. Breast magnetic resonance imaging (MRI) is the most sensitive imaging modality for tumor characterization and accurate size measurement. Clinical indication includes preoperative evaluation to define extent of disease in newly diagnosed breast cancer.15,16 Tumors are characterized clinically using the Breast Imaging-Reporting and Data System (BI-RADS) Lexicon. However, image features extracted through computer-based automated image analysis are quantitative and may include characteristics that are imperceptible to the eye. Such efforts to discover and use quantitative features are termed “radiomics.” Types of radiomics features that are often extracted include texture-based features (ie, characteristics associated with “roughness” or “smoothness” and the like). Previous applications of texture analysis for breast cancer have predominantly been for differentiating between benign and malignant lesions as well as differentiating between ductal and lobular breast cancers.17–20 Sophisticated methods using gray-scale correlation matrix (GLCM) textures or variations of the same textures computed from Gabor edge images and temporal kinetics,21 as well as fractal-based textures,22 have been employed for classifying malignant from benign breast tumors. The purpose of this study was to investigate the association between ODxRS and image analysis-based features extracted from MRI scans.

A radiology teaching file (TF) is a system containing a collection of cases with teaching value. Given the wide variety of TF solutions available, we conducted a national survey to better understand the need for TFs, TF features desired by users and their current implementation. A 28-question survey was created which explored TF implementation, utilization, and preferences among respondents. The survey was emailed to residents and faculty throughout the USA, with a request for program coordinators to forward the survey to their departments. The survey was completed by 396 respondents from 115 different institutions. These respondents included 60 % residents, 21 % attendings (non-program directors), 12 % program directors, 5 % fellows, and 1 % medical students. TFs were assigned to one of three categories: personal TFs, shared in-house TFs, and public TFs. Seventy-six percent of respondents kept a personal TF using a variety of media, and 67 % used a shared in-house TF. Of the public TFs used, the most popular were those requiring paid subscriptions. The features respondents valued most provided efficient querying of cases, simulated basic PACS functionality, enabled self-directed learning, and facilitated case submissions. There is a trend toward utilizing electronic media for TFs. The media utilized should be understood and reviewed to ensure PHI is properly secured. Contemporary users demand a high degree of functionality from TF solutions, and use both in-house and commercial products to meet their needs.

PURPOSE Evaluate the clinical presentation and imaging findings of breast implant-associated anaplastic large cell lymphoma (BIA ALCL) at a large US cancer center. MATERIALS AND METHODS HIPAA-compliant IRB approved retrospective study, for which informed consent was waived. The Hospital Information System was screened for women who underwent implant reconstruction and were diagnosed with BIA ALCL between 2010 and 2016. Two radiologists reviewed images in consensus. Clinical and imaging characteristics were summarized using means and ranges for continuous variables and percentages for categorical variables. RESULTS Patient cohort included 11 women with BIA ALCL (mean age at diagnosis = 54 years, range: 35-77), including women with (9/11) and without (2/11) history of breast cancer. Mean time from breast implant placement to diagnosis was 10 years (range: 6-14). BIA ALCL was identified in patients with saline (4/11) and silicone (5/11) implants. Implants were textured in 7/11 (63%) and unknown in 4/11 (36%) cases. All patients presented with a peri-implant seroma, (9/11 documented on imaging). Two of 11 patients had a mass within this seroma. Ten of 11 patients (91%) presented with symptoms. CONCLUSIONS Saline and silicone breast implants may predispose patients to a rare lymphoma subtype, BIA ALCL, which presents on imaging as a peri-implant fluid collection ± mass.

Purpose To evaluate whether the disease status of the pre-neoadjuvant chemotherapy (NAC) core biopsied lymph node (preNACBxLN) in patients with node positive breast cancer corresponds to nodal status of all surgically retrieved lymph nodes (LNs) post-NAC and whether wire localization of this LN is feasible. Materials and methods HIPPA compliant IRB approved retrospective study including breast cancer patients (a.) with preNACBxLN confirmed metastases, (b.) who received NAC, and (c.) underwent wire localization of the preNACBxLN. Electronic medical records were reviewed. Fisher's exact test was used to compare differences in residual disease post-NAC among breast cancer subtypes. Results 28 women with node positive breast cancer underwent ultrasound guided wire localization of the preNACBxLN, without complication. There was no evidence of residual nodal disease for 16 patients, with mean 4.4 (median 4) LNs resected. 12 patients had residual nodal metastases, with mean 9.2 (median 7) LNs resected and mean 2.3 (median 2) LNs with tumor involvement. 11 patients had metastases detected within the localized LN. One patient had micrometastasis in a sentinel LN, despite no residual disease in the preNACBxLN. Patients with luminal A/B breast cancer more often had residual nodal metastases (86%) at pathology, as compared to patients with HER2 + (20%) and Triple Negative breast cancer (50%), though not quite achieving statistical significance (p = 0.055). Conclusion Ultrasound guided wire localization of the preNACBxLN is feasible and may improve detection of residual tumor in patients post-NAC.

Purpose TNM Stage 3B encompasses a wide range of primary tumor and nodal metastatic tumor burden. This study aimed to evaluate the prognostic value of quantitative FDG PET/CT parameters in patients with newly diagnosed Stage 3B Non-Small Cell Lung Cancer (NSCLC). Materials and Methods Institutional review board approved retrospective study identified patients diagnosed with Stage 3B NSCLC (8th edition TNM classification) on baseline FDG PET/CT at two medical centers (Medical centers A and B), between Feb 2004 and Dec 2014. Patients were excluded if they had prior NSCLC treatment or recent diagnosis of a second primary cancer. Quantitative FDG PET/CT parameters including whole body metabolic tumor volume (MTVwb), total lesion glycolysis (TLGwb), and maximum standardized uptake value (SUVmaxwb) were measured from baseline PET/CT using Edge method with Mimvista software. The primary endpoint was overall survival (OS). Cox proportional hazard regression and Kaplan-Meier overall survival analyses were used to test for an association between OS and quantitative FDG PET/CT parameters. The distributions of MTVwb, TLGwb, SUVmaxwb were skewed, so a natural logarithm transformation was applied and the transformed variables [(ln(MTVwb), ln(TLGwb), and ln(SUVmaxwb)] were used in the analysis. Results The training set included 110 patients from center A with Stage 3B NSCLC. 78.2% of patients expired during follow-up. Median OS was 14 months. 1-year, 2-year, and 5-year OS was 56.5%, 34.6% and 13.9%, respectively. Univariate Cox regression analysis showed no significant difference in OS on the basis of age, gender, histology, ln(TLGwb), or ln(SUVmaxwb). ln(MTVwb) was positively associated with OS [hazard ratio (HR) of 1.23, p = 0.037]. This association persisted on multivariate Cox regression analysis (HR 1.28, p = 0.043), with adjustments for age, gender, treatment and tumor histology. External validation with 44 patients from center B confirmed increasing MTVwb was associated significantly worse OS. An MTVwb cut-off point of 85.6 mL significantly stratified Stage 3B NSCLC patient prognosis. Conclusion MTVwb is a prognostic marker for OS in patients with Stage 3B NSCLC, independent of age, gender, treatment, and tumor histology.

Rationale and Objectives Here we review the current state of multicenter radiology research (MRR), and utilize a survey of experienced researchers to identify common advantages, barriers, and resources to guide future investigators. Materials and Methods The Association of University Radiologists established a Radiology Research Alliance task force, Multi-center Research Studies in Radiology, composed of 12 society members to review MRR. A REDCap survey was designed to gain more insight from experienced researchers. Recipients were authors identified from a PubMed database search, utilizing search terms “multicenter” or “multisite” and “radiology.” The survey included investigator background information, reasons why, barriers to, and resources that investigators found helpful in conducting or participating in MRR. Results The survey was completed by 23 of 80 recipients (29%), the majority (76%) of whom served as a primary investigator on at least one MRR project. Respondents reported meeting collaborators at national or international (74%) and society (39%) meetings. The most common perceived advantages of MRR were increased sample size (100%) and improved generalizability (91%). External funding was considered the most significant barrier to MRR, reported by 26% of respondents. Institutional funding, setting up a central picture archiving and communication system, and setting up a central database were considered a significant barrier by 30%, 22%, and 22% of respondents, respectively. Resources for overcoming barriers included motivated staff (74%), strong leadership (70%), regular conference calls (57%), and at least one face-to-face meeting (57%). Conclusions Barriers to MRR include funding and establishing a central database and a picture archiving and communication system. Upon embarking on an MRR project, forming a motivated team who meets and speaks regularly is essential.

Pathologic evaluation of breast specimens requires a fixation and staining procedure of at least 12 hours duration, delaying diagnosis and post-operative planning. Here we introduce an MRI technique with a custom-designed radiofrequency resonator for imaging breast and lymph tissue with sufficient spatial resolution and speed to guide pathologic interpretation and offer value in clinical decision making. In this study, we demonstrate the ability to image breast and lymphatic tissue using 7.0 Tesla MRI, achieving a spatial resolution of 59 × 59 × 94 μm3 with a signal-to-noise ratio of 15–20, in an imaging time of 56 to 70 minutes. These are the first MR images to reveal characteristic pathologic features of both benign and malignant breast and lymph tissue, some of which were discernible by blinded pathologists who had no prior training in high resolution MRI interpretation.

To determine if the histology of a breast malignancy influences the appearance of untreated osseous metastases on FDG PET/CT. This retrospective study was performed under IRB waiver. Our Hospital Information System was screened for breast cancer patients who presented with osseous metastases, who underwent FDG PET/CT prior to systemic therapy or radiotherapy from 2009 to 2012. Patients with invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), or mixed ductal/lobular (MDL) histology were included. Patients with a history of other malignancies were excluded. PET/CT was evaluated, blinded to histology, to classify osseous metastases on a per-patient basis as sclerotic, lytic, mixed lytic/sclerotic, or occult on CT, and to record SUVmax for osseous metastases on PET. Following screening, 95 patients who met the inclusion criteria (74 IDC, 13 ILC, and 8 MDL) were included. ILC osseous metastases were more commonly sclerotic and demonstrated lower SUVmax than IDC metastases. In all IDC and MDL patients with osseous metastases, at least one was FDG-avid. For ILC, all patients with lytic or mixed osseous metastases demonstrated at least one FDG-avid metastasis; however, in only three of seven patients were sclerotic osseous metastases apparent on FDG PET. The histologic subtype of breast cancer affects the appearance of untreated osseous metastases on FDG PET/CT. In particular, non-FDG-avid sclerotic osseous metastases were more common in patients with ILC than in patients with IDC. Breast cancer histology should be considered when interpreting non-FDG-avid sclerotic osseous lesions on PET/CT, which may be more suspicious for metastases (rather than benign lesions) in patients with ILC.

To investigate the association between a validated, gene-expression-based, aggressiveness assay, Oncotype Dx RS, and morphological and texture-based image features extracted from magnetic resonance imaging (MRI).This retrospective study received Internal Review Board approval and need for informed consent was waived. Between 2006-2012, we identified breast cancer patients with: 1) ER+, PR+, and HER2- invasive ductal carcinoma (IDC); 2) preoperative breast MRI; and 3) Oncotype Dx RS test results. Extracted features included morphological, histogram, and gray-scale correlation matrix (GLCM)-based texture features computed from tumors contoured on pre- and three postcontrast MR images. Linear regression analysis was performed to investigate the association between Oncotype Dx RS and different clinical, pathologic, and imaging features. P 0.05 was considered statistically significant.Ninety-five patients with IDC were included with a median Oncotype Dx RS of 16 (range: 0-45). Using stepwise multiple linear regression modeling, two MR-derived image features, kurtosis in the first and third postcontrast images and histologic nuclear grade, were found to be significantly correlated with the Oncotype Dx RS with P = 0.0056, 0.0005, and 0.0105, respectively. The overall model resulted in statistically significant correlation with Oncotype Dx RS with an R-squared value of 0.23 (adjusted R-squared = 0.20; P = 0.0002) and a Spearman's rank correlation coefficient of 0.49 (P 0.0001).A model for IDC using imaging and pathology information correlates with Oncotype Dx RS scores, suggesting that image-based features could also predict the likelihood of recurrence and magnitude of chemotherapy benefit.

The objective of our study was to review screening mammography examinations performed at our institution from 2007 through 2010 with the primary endpoint of determining the incidence of breast cancer and associated histologic and prognostic features in women in their 40s.Patients who presented for screening mammography who ultimately (i.e., after additional imaging, including diagnostic mammographic views and ultrasound) received a BI-RADS assessment of a category 4 or 5 for a suspicious abnormality were followed retrospectively through completion of care and were analyzed with respect to pathology results after biopsy, treatment, and family history.During the study period, 43,351 screening mammography examinations were performed; 1227 biopsies were recommended on the basis of those studies and yielded 205 breast cancers (cancer detection rate of 4.7 per 1000 screening examinations). These screening examinations included 14,528 (33.5%) screening examinations of patients in their 40s; 413 biopsies were recommended and yielded 39 breast cancers (39/205 = 19%) (cancer detection rate of 2.7 per 1000 screening examinations). More than 50% (21/39) of the cancers in women in their 40s were invasive. Only 8% (3/39) of the women in their 40s with screening-detected breast cancer had a first-degree relative with breast cancer.From 2007 through 2010, patients in their 40s accounted for one third of the population undergoing screening mammography and for nearly 20% of the screening-detected breast cancers--more than half of which were invasive. This information should be a useful contribution to counseling women in this age group when discussing whether or not to pursue regular screening mammography.