Purpose To investigate relationships between computer-extracted breast magnetic resonance (MR) imaging phenotypes with multigene assays of MammaPrint, Oncotype DX, and PAM50 to assess the role of ...radiomics in evaluating the risk of breast cancer recurrence. Materials and Methods Analysis was conducted on an institutional review board-approved retrospective data set of 84 deidentified, multi-institutional breast MR examinations from the National Cancer Institute Cancer Imaging Archive, along with clinical, histopathologic, and genomic data from The Cancer Genome Atlas. The data set of biopsy-proven invasive breast cancers included 74 (88%) ductal, eight (10%) lobular, and two (2%) mixed cancers. Of these, 73 (87%) were estrogen receptor positive, 67 (80%) were progesterone receptor positive, and 19 (23%) were human epidermal growth factor receptor 2 positive. For each case, computerized radiomics of the MR images yielded computer-extracted tumor phenotypes of size, shape, margin morphology, enhancement texture, and kinetic assessment. Regression and receiver operating characteristic analysis were conducted to assess the predictive ability of the MR radiomics features relative to the multigene assay classifications. Results Multiple linear regression analyses demonstrated significant associations (R
= 0.25-0.32, r = 0.5-0.56, P < .0001) between radiomics signatures and multigene assay recurrence scores. Important radiomics features included tumor size and enhancement texture, which indicated tumor heterogeneity. Use of radiomics in the task of distinguishing between good and poor prognosis yielded area under the receiver operating characteristic curve values of 0.88 (standard error, 0.05), 0.76 (standard error, 0.06), 0.68 (standard error, 0.08), and 0.55 (standard error, 0.09) for MammaPrint, Oncotype DX, PAM50 risk of relapse based on subtype, and PAM50 risk of relapse based on subtype and proliferation, respectively, with all but the latter showing statistical difference from chance. Conclusion Quantitative breast MR imaging radiomics shows promise for image-based phenotyping in assessing the risk of breast cancer recurrence.
RSNA, 2016 Online supplemental material is available for this article.
Purpose
The second International Consensus Conference on B3 lesions was held in Zurich, Switzerland, in March 2018, organized by the International Breast Ultrasound School to re-evaluate the ...consensus recommendations.
Methods
This study (1) evaluated how management recommendations of the first Zurich Consensus Conference of 2016 on B3 lesions had influenced daily practice and (2) reviewed current literature towards recommendations to biopsy.
Results
In 2018, the consensus recommendations for management of B3 lesions remained almost unchanged: For flat epithelial atypia (FEA), classical lobular neoplasia (LN), papillary lesions (PL) and radial scars (RS) diagnosed on core-needle biopsy (CNB) or vacuum-assisted biopsy (VAB), excision by VAB in preference to open surgery, and for atypical ductal hyperplasia (ADH) and phyllodes tumors (PT) diagnosed at VAB or CNB, first-line open surgical excision (OE) with follow-up surveillance imaging for 5 years. Analyzing the Database of the Swiss Minimally Invasive Breast Biopsies (MIBB) with more than 30,000 procedures recorded, there was a significant increase in recommending more frequent surveillance of LN 65% in 2018 vs. 51% in 2016 (
p
= 0.004), FEA (72% in 2018 vs. 62% in 2016 (
p
= 0.005)), and PL (76% in 2018 vs. 70% in 2016 (
p
= 0.04) diagnosed on VAB. A trend to more frequent surveillance was also noted also for RS 77% in 2018 vs. 67% in 2016 (
p
= 0.07).
Conclusions
Minimally invasive management of B3 lesions (except ADH and PT) with VAB continues to be appropriate as an alternative to first-line OE in most cases, but with more frequent surveillance, especially for LN.
With the genomic revolution in the early 1990s, medical research has been driven to study the basis of human disease on a genomic level and to devise precise cancer therapies tailored to the specific ...genetic makeup of a tumor. To match novel therapeutic concepts conceived in the era of precision medicine, diagnostic tests must be equally sufficient, multilayered, and complex to identify the relevant genetic alterations that render cancers susceptible to treatment. With significant advances in training and medical imaging techniques, image analysis and the development of high‐throughput methods to extract and correlate multiple imaging parameters with genomic data, a new direction in medical research has emerged. This novel approach has been termed radiogenomics. Radiogenomics aims to correlate imaging characteristics (ie, the imaging phenotype) with gene expression patterns, gene mutations, and other genome‐related characteristics and is designed to facilitate a deeper understanding of tumor biology and capture the intrinsic tumor heterogeneity. Ultimately, the goal of radiogenomics is to develop imaging biomarkers for outcome that incorporate both phenotypic and genotypic metrics. Due to the noninvasive nature of medical imaging and its ubiquitous use in clinical practice, the field of radiogenomics is rapidly evolving and initial results are encouraging. In this article, we briefly discuss the background and then summarize the current role and the potential of radiogenomics in brain, liver, prostate, gynecological, and breast tumors.
Level of Evidence: 5
Technical Efficacy: Stage 2
J. Magn. Reson. Imaging 2017;47:604–620.
To develop guideline recommendations concerning optimal neoadjuvant therapy for breast cancer.
ASCO convened an Expert Panel to conduct a systematic review of the literature on neoadjuvant therapy ...for breast cancer and provide recommended care options.
A total of 41 articles met eligibility criteria and form the evidentiary basis for the guideline recommendations.
Patients undergoing neoadjuvant therapy should be managed by a multidisciplinary care team. Appropriate candidates for neoadjuvant therapy include patients with inflammatory breast cancer and those in whom residual disease may prompt a change in therapy. Neoadjuvant therapy can also be used to reduce the extent of local therapy or reduce delays in initiating therapy. Although tumor histology, grade, stage, and estrogen, progesterone, and human epidermal growth factor receptor 2 (HER2) expression should routinely be used to guide clinical decisions, there is insufficient evidence to support the use of other markers or genomic profiles. Patients with triple-negative breast cancer (TNBC) who have clinically node-positive and/or at least T1c disease should be offered an anthracycline- and taxane-containing regimen; those with cT1a or cT1bN0 TNBC should not routinely be offered neoadjuvant therapy. Carboplatin may be offered to patients with TNBC to increase pathologic complete response. There is currently insufficient evidence to support adding immune checkpoint inhibitors to standard chemotherapy. In patients with hormone receptor (HR)-positive (HR-positive), HER2-negative tumors, neoadjuvant chemotherapy can be used when a treatment decision can be made without surgical information. Among postmenopausal patients with HR-positive, HER2-negative disease, hormone therapy can be used to downstage disease. Patients with node-positive or high-risk node-negative, HER2-positive disease should be offered neoadjuvant therapy in combination with anti-HER2-positive therapy. Patients with T1aN0 and T1bN0, HER2-positive disease should not be routinely offered neoadjuvant therapy.Additional information is available at www.asco.org/breast-cancer-guidelines.
Precision medicine is medicine optimized to the genotypic and phenotypic characteristics of an individual and, when present, his or her disease. It has a host of targets, including genes and their ...transcripts, proteins, and metabolites. Studying precision medicine involves a systems biology approach that integrates mathematical modeling and biology genomics, transcriptomics, proteomics, and metabolomics. Moreover, precision medicine must consider not only the relatively static genetic codes of individuals, but also the dynamic and heterogeneous genetic codes of cancers. Thus, precision medicine relies not only on discovering identifiable targets for treatment and surveillance modification, but also on reliable, noninvasive methods of identifying changes in these targets over time. Imaging via radiomics and radiogenomics is poised for a central role. Radiomics, which extracts large volumes of quantitative data from digital images and amalgamates these together with clinical and patient data into searchable shared databases, potentiates radiogenomics, which is the combination of genetic and radiomic data. Radiogenomics may provide voxel-by-voxel genetic information for a complete, heterogeneous tumor or, in the setting of metastatic disease, set of tumors and thereby guide tailored therapy. Radiogenomics may also quantify lesion characteristics, to better differentiate between benign and malignant entities, and patient characteristics, to better stratify patients according to risk for disease, thereby allowing for more precise imaging and screening. This report provides an overview of precision medicine and discusses radiogenomics specifically in breast cancer.
RSNA, 2018.
Summary Background New research criteria for preclinical Alzheimer's disease have been proposed, which include stages for cognitively normal individuals with abnormal amyloid markers (stage 1), ...abnormal amyloid and neuronal injury markers (stage 2), or abnormal amyloid and neuronal injury markers and subtle cognitive changes (stage 3). We aimed to investigate the prevalence and long-term outcome of preclinical Alzheimer's disease according to these criteria. Methods Participants were cognitively normal (clinical dementia rating CDR=0) community-dwelling volunteers aged at least 65 years who were enrolled between 1998 and 2011 at the Washington University School of Medicine (MO, USA). CSF amyloid-β1–42 and tau concentrations and a memory composite score were used to classify participants as normal (both markers normal), preclinical Alzheimer's disease stage 1–3, or suspected non-Alzheimer pathophysiology (SNAP, abnormal injury marker without abnormal amyloid marker). The primary outcome was the proportion of participants in each preclinical AD stage. Secondary outcomes included progression to CDR at least 0·5, symptomatic Alzheimer's disease (score of at least 0·5 for memory and at least one other domain and cognitive impairments deemed to be due to Alzheimer's disease), and mortality. We undertook survival analyses using subdistribution and standard Cox hazards models and linear mixed models. Findings Of 311 participants, 129 (41%) were classed as normal, 47 (15%) as stage 1, 36 (12%) as stage 2, 13 (4%) as stage 3, 72 (23%) as SNAP, and 14 (5%) remained unclassified. The 5-year progression rate to CDR at least 0·5, symptomatic Alzheimer's disease was 2% for participants classed as normal, 11% for stage 1, 26% for stage 2, 56% for stage 3, and 5% for SNAP. Compared with individuals classed as normal, participants with preclinical Alzheimer's disease had an increased risk of death after adjusting for covariates (hazard ratio 6·2, 95% CI 1·1–35·0; p=0·040). Interpretation Preclinical Alzheimer's disease is common in cognitively normal elderly people and is associated with future cognitive decline and mortality. Thus, preclinical Alzheimer's disease could be an important target for therapeutic intervention. Funding National Institute of Aging of the National Institutes of Health (P01-AG003991, P50-AG05681, P01-AG02676), Internationale Stichting Alzheimer Onderzoek, the Center for Translational Molecular Medicine project LeARN, the EU/EFPIA Innovative Medicines Initiative Joint Undertaking, and the Charles and Joanne Knight Alzheimer Research Initiative.
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.
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.
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.
This study validated a radiomics classifier combining radiomics with molecular subtypes that accurately classifies pCR on MRI post-NAC.
MRI is an essential tool in breast imaging, with multiple established indications. Dynamic contrast-enhanced MRI (DCE-MRI) is the backbone of any breast MRI protocol and has an excellent sensitivity ...and good specificity for breast cancer diagnosis. DCE-MRI provides high-resolution morphological information, as well as some functional information about neoangiogenesis as a tumour-specific feature. To overcome limitations in specificity, several other functional MRI parameters have been investigated and the application of these combined parameters is defined as multiparametric MRI (mpMRI) of the breast. MpMRI of the breast can be performed at different field strengths (1.5-7 T) and includes both established (diffusion-weighted imaging, MR spectroscopic imaging) and novel MRI parameters (sodium imaging, chemical exchange saturation transfer imaging, blood oxygen level-dependent MRI), as well as hybrid imaging with positron emission tomography (PET)/MRI and different radiotracers. Available data suggest that multiparametric imaging using different functional MRI and PET parameters can provide detailed information about the underlying oncogenic processes of cancer development and progression and can provide additional specificity. This article will review the current and emerging functional parameters for mpMRI of the breast for improved diagnostic accuracy in breast cancer.
Global climate change includes rising temperatures and increased pCO2 concentrations in the ocean, with potential deleterious impacts on marine organisms. In this case study we conducted a four-week ...climate change incubation experiment, and tested the independent and combined effects of increased temperature and partial pressure of carbon dioxide (pCO2), on the microbiomes of a foundation species, the giant kelp Macrocystis pyrifera, and the surrounding water column. The water and kelp microbiome responded differently to each of the climate stressors. In the water microbiome, each condition caused an increase in a distinct microbial order, whereas the kelp microbiome exhibited a reduction in the dominant kelp-associated order, Alteromondales. The water column microbiomes were most disrupted by elevated pCO2, with a 7.3 fold increase in Rhizobiales. The kelp microbiome was most influenced by elevated temperature and elevated temperature in combination with elevated pCO2. Kelp growth was negatively associated with elevated temperature, and the kelp microbiome showed a 5.3 fold increase Flavobacteriales and a 2.2 fold increase alginate degrading enzymes and sulfated polysaccharides. In contrast, kelp growth was positively associated with the combination of high temperature and high pCO2 'future conditions', with a 12.5 fold increase in Planctomycetales and 4.8 fold increase in Rhodobacteriales. Therefore, the water and kelp microbiomes acted as distinct communities, where the kelp was stabilizing the microbiome under changing pCO2 conditions, but lost control at high temperature. Under future conditions, a new equilibrium between the kelp and the microbiome was potentially reached, where the kelp grew rapidly and the commensal microbes responded to an increase in mucus production.
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