The biology of malignant breast tumors has an impact on the presentation in ultrasound: an analysis of 315 cases

BACKGROUND: The aim of this study was to evaluate the relation of some ultrasound morphological parameters to biological characteristics in breast carcinoma. METHODS: Ultrasound data from 315 breast masses were collected. We analyzed the ultrasound features of the tumors according to the ACR BI-RADS®-US classification system stratified by hormone receptor status, HER2 status, histology grade, tumor type (ductal versus lobular), triple-negativity, breast density, tumor size, lymph node involvement and patient’s age. RESULTS: We found a variety of ultrasound features that varied between the groups. Invasive lobular tumors were more likely to have an angulated margin (39% versus 22%, p = 0.040) and less likely to show posterior acoustic enhancement (3% versus 16%, p = 0.023) compared to invasive ductal carcinoma. G3 tumors were linked to a higher chance of posterior acoustic enhancement and less shadowing and the margin of G3 tumors was more often described as lobulated or microlobulated compared to G1/G2 tumors (67% versus 46%, p = 0.001). Tumors with an over-expression of HER2 exhibited a higher rate of architectural distortions in the surrounding tissue, but there were no differences regarding the other features. Hormone receptor negative tumors were more likely to exhibit a lobulated or microlobulated margin (67% versus 50%, p = 0.037) and less likely to have an echogenic halo (39% versus 64%, p = 0.001). Furthermore, the posterior acoustic feature was more often described as enhancement (33% versus 13%, p = 0.001) and less often as shadowing (20% versus 47%, p < 0.001) compared to hormone receptor positive tumors. CONCLUSION: Depending on their biological and clinical profile, breast cancers are more or less likely to exhibit the typical criteria for malignancy in ultrasound. Moreover, certain types of breast cancer tend to possess criteria that are usually associated with benign masses. False-negative diagnosis may result in serious consequences for the patient. For the sonographer it is essential to be well aware of potential variations in the ultrasound morphology of breast tumors, as described in this paper

The cost-effectiveness of follow-up strategies after cancer treatment: a systematic literature review

Introduction: The cost of treatment and follow-up of cancer patients in the UK is substantial. In a budget-constrained system such as the NHS, it is necessary to consider the cost-effectiveness of the range of management strategies at different points on cancer patients' care pathways to ensure that they provide adequate value for money. Sources of data: We conducted a systematic literature review to explore the cost-effectiveness of follow-up strategies of patients previously treated for cancer with the aim of informing UK policy. All papers that were considered to be economic evaluations in the subject areas described above were extracted. Areas of agreement: The existing literature suggests that intensive follow-up of patients with colorectal disease is likely to be cost-effective, but the opposite holds for breast cancer. Areas of controversy: Interventions and strategies for follow-up in cancer patients were variable across type of cancer and setting. Drawing general conclusions about the cost-effectiveness of these interventions/strategies is difficult. Growing points: The search identified 2036 references but applying inclusion/exclusion criteria a total of 44 articles were included in the analysis. Breast cancer was the most common (n = 11) cancer type followed by colorectal (n = 10) cancer. In general, there were relatively few studies of cost-effectiveness of follow-up that could influence UK guidance. Where there was evidence, in the most part, NICE guidance broadly reflected this evidence. Areas timely to develop research: In terms of future research around the timing, frequency and composition of follow-ups, this is dependent on the type of cancer being considered. Nevertheless, across most cancers, the possibility of remote follow-up (or testing) by health professionals other than hospital consultants in other settings appears to warrant further work

What scans we will read: imaging instrumentation trends in clinical oncology

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non- invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/ CT), advanced MRI, optical or ultrasound imaging. This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now. Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by progress in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as “data”, and – through the wider adoption of advanced analysis, including machine learning approaches and a “big data” concept – move to the next stage of non-invasive tumor phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi- dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging