Towards nationally curated data archives for clinical radiology image analysis at scale: Learnings from national data collection in response to a pandemic.

The prevalence of the coronavirus SARS-CoV-2 disease has resulted in the unprecedented collection of health data to support research. Historically, coordinating the collation of such datasets on a national scale has been challenging to execute for several reasons, including issues with data privacy, the lack of data reporting standards, interoperable technologies, and distribution methods. The coronavirus SARS-CoV-2 disease pandemic has highlighted the importance of collaboration between government bodies, healthcare institutions, academic researchers and commercial companies in overcoming these issues during times of urgency.

International survey on residency programs in radiology: similarities and differences among 17 countries.

Objective: With the initiative of the ACR International Economics Committee, a multinational survey was conducted to evaluate radiology residency programs around the world.

Methods: A 31-question survey was developed. It included: economic issues, program size and length, resident's activities during daytime and call, academic aspects including syllabus and examinations.

Breast ultrasound region of interest detection and lesion localisation.

In current breast ultrasound computer aided diagnosis systems, the radiologist preselects a region of interest (ROI) as an input for computerised breast ultrasound image analysis. This task is time consuming and there is inconsistency among human experts. Researchers attempting to automate the process of obtaining the ROIs have been relying on image processing and conventional machine learning methods.

An International Survey of Quality and Safety Programs in Radiology.

Purpose: The aim of this study was to determine the status of radiology quality improvement programs in a variety of selected nations worldwide.

Methods: A survey was developed by select members of the International Economics Committee of the American College of Radiology on quality programs and was distributed to committee members. Members responded on behalf of their country.

Breast ultrasound lesions recognition: end-to-end deep learning approaches.

Multistage processing of automated breast ultrasound lesions recognition is dependent on the performance of prior stages. To improve the current state of the art, we propose the use of end-to-end deep learning approaches using fully convolutional networks (FCNs), namely FCN-AlexNet, FCN-32s, FCN-16s, and FCN-8s for semantic segmentation of breast lesions. We use pretrained models based on ImageNet and transfer learning to overcome the issue of data deficiency.

Deep learning in mammography and breast histology, an overview and future trends.

Recent improvements in biomedical image analysis using deep learning based neural networks could be exploited to enhance the performance of Computer Aided Diagnosis (CAD) systems. Considering the importance of breast cancer worldwide and the promising results reported by deep learning based methods in breast imaging, an overview of the recent state-of-the-art deep learning based CAD systems developed for mammography and breast histopathology images is presented. In this study, the relationship between mammography and histopathology phenotypes is described, which takes biological aspects into account.

Classification of micro-calcification in mammograms using scalable linear Fisher discriminant analysis.

Breast cancer is one of the major causes of death in women. Computer Aided Diagnosis (CAD) systems are being developed to assist radiologists in early diagnosis. Micro-calcifications can be an early symptom of breast cancer.

Provision of out-of-hours services for acute upper gastrointestinal bleeding in England: results of the 2014-2015 BSG/NHS England national survey.

Background: There has been a drive to raise the standard of management of acute upper gastrointestinal bleeding (AUGIB) in the UK, including three previous audits, sponsored by the British Society of Gastroenterology (BSG).

Objective: To review the results of the latest BSG/National Health Service (NHS) England national survey of endoscopy services in England between 2014 and 2015.

Method: All NHS hospitals accepting acute admissions in England (168) were invited to respond to the survey.

Impact of errors in recorded compressed breast thickness measurements on volumetric density classification using volpara v1.5.0 software.

Purpose: Mammographic density has been demonstrated to predict breast cancer risk. It has been proposed that it could be used for stratifying screening pathways and recommending additional imaging. Volumetric density tools use the recorded compressed breast thickness (CBT) of the breast measured at the x-ray unit in their calculation; however, the accuracy of the recorded thickness can vary.

Breast image pre-processing for mammographic tissue segmentation.

During mammographic image acquisition, a compression paddle is used to even the breast thickness in order to obtain optimal image quality. Clinical observation has indicated that some mammograms may exhibit abrupt intensity change and low visibility of tissue structures in the breast peripheral areas. Such appearance discrepancies can affect image interpretation and may not be desirable for computer aided mammography, leading to incorrect diagnosis and/or detection which can have a negative impact on sensitivity and specificity of screening mammography.

Breast cancer screening and diagnosis in the 21st century within the U.K.

In the UK, breast cancer represents the most commonly diagnosed cancer in females and carries with it a significant morbidity and mortality. An established national screening programme is in place to identify those with the disease at an early stage in order to optimise treatment and prognosis. This article provides an overview for the non-breast specialist clinician whose practice regularly deals with women who may be the subject of the screening programme.

A Review on Automatic Mammographic Density and Parenchymal Segmentation.

Breast cancer is the most frequently diagnosed cancer in women. However, the exact cause(s) of breast cancer still remains unknown. Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective way to tackle breast cancer.

Topological modeling and classification of mammographic microcalcification clusters.

Goal: The presence of microcalcification clusters is a primary sign of breast cancer; however, it is difficult and time consuming for radiologists to classify microcalcifications as malignant or benign. In this paper, a novel method for the classification of microcalcification clusters in mammograms is proposed.

Methods: The topology/connectivity of individual microcalcifications is analyzed within a cluster using multiscale morphology.

A reporter-targeted approach to reducing the use of the term "superficial femoral vein" in ultrasound reports for deep vein thrombosis.

Background: The term "superficial femoral vein" is felt to be potentially misleading and dangerous in the context of deep venous thrombosis (DVT) of the lower limb, with the preferred term now being "femoral vein." The purpose of this work was to identify a means of reducing its use in reports of lower limb sonographic scans for DVT.

Methods: A retrospective search of the reports for all lower limb sonographic scans for the detection of DVT in 2011 was performed using the Radiology Information System to identify the baseline rate of use of the term.

The clinical and functional outcomes of ultrasound-guided vs landmark-guided injections for adults with shoulder pathology--a systematic review and meta-analysis.

Objective: To compare the clinical and functional outcomes of US-guided (USG) vs landmark-guided (LMG) injection for the treatment of adults with shoulder pathology.

Method: MEDLINE, AMED and Embase in addition to unpublished literature databases were searched from 1950 to August 2011. Studies were included if they were randomized or non-randomized controlled trials comparing USG vs LSG injections for the treatment of adults with shoulder pathology.

The changing NHS and imaging services: impact on musculoskeletal imaging.

Objective: This article describes some of the major influences that have improved the way health services in England are delivered over the past 10 years and the impact this has had on imaging services. In particular, we will describe the impact of these changes on the delivery of musculoskeletal imaging services.

Conclusion: The National Health Service (NHS) is reaping the benefits of these changes, with waiting times at the lowest ever recorded.

A review of automatic mass detection and segmentation in mammographic images.

The aim of this paper is to review existing approaches to the automatic detection and segmentation of masses in mammographic images, highlighting the key-points and main differences between the used strategies. The key objective is to point out the advantages and disadvantages of the various approaches. In contrast with other reviews which only describe and compare different approaches qualitatively, this review also provides a quantitative comparison.

Tackling climate change close to home: mobile breast screening as a model.

Objective: Health services contribute significantly to carbon dioxide (CO(2)) emissions and, while services in the UK are beginning to address this, the focus has been on reducing energy consumption rather than road transport, a major component of emissions. We aimed to compare the distances travelled by patients attending mobile breast screening clinics compared to the distance they would need to travel if screening services were centralized.

Methods: Anonymized postcode records were analysed to determine driving distances potentially saved through attendance at 20 mobile breast screening clinics rather than at two centralized locations.

A statistical approach for breast density segmentation.

Studies reported in the literature indicate that the increase in the breast density is one of the strongest indicators of developing breast cancer. In this paper, we present an approach to automatically evaluate the density of a breast by segmenting its internal parenchyma in either fatty or dense class. Our approach is based on a statistical analysis of each pixel neighbourhood for modelling both tissue types.

Eigendetection of masses considering false positive reduction and breast density information.

The purpose of this article is to present a novel algorithm for the detection of masses in mammographic computer-aided diagnosis systems. Four key points provide the novelty of our approach: (1) the use of eigenanalysis for describing variation in mass shape and size; (2) a Bayesian detection methodology providing a mathematical sound framework, flexible enough to include additional information; (3) the use of a two-dimensional principal components analysis approach to facilitate false positive reduction; and (4) the incorporation of breast density information, a parameter correlated with the performance of most mass detection algorithms and which is not considered in existing approaches. To study the performance of the system two experiments were carried out.

Associations among mammographic density, circulating sex hormones, and polymorphisms in sex hormone metabolism genes in postmenopausal women.

Mammographic density and serum sex hormone levels are important risk factors for breast cancer, but their associations with one another are unclear. We studied these phenotypes, together with single nucleotide polymorphisms (SNP) in genes related to sex hormone metabolism, in a cross-sectional study of 1,413 postmenopausal women from the European Prospective Investigation into Cancer and Nutrition-Norfolk. All women were >1 year postmenopausal and had not taken hormone replacement therapy for >3 months before sampling.