Validation of a new fully automated software for 2D digital mammographic breast density evaluation in predicting breast cancer risk.

We compared accuracy for breast cancer (BC) risk stratification of a new fully automated system (DenSeeMammo-DSM) for breast density (BD) assessment to a non-inferiority threshold based on radiologists' visual assessment. Pooled analysis was performed on 14,267 2D mammograms collected from women aged 48-55 years who underwent BC screening within three studies: RETomo, Florence study and PROCAS. BD was expressed through clinical Breast Imaging Reporting and Data System (BI-RADS) density classification. Women in BI-RADS D category had a 2.6 (95% CI 1.5-4.4) and a 3.6 (95% CI 1.4-9.3) times higher risk of incident and interval cancer, respectively, than women in the two lowest BD categories. The ability of DSM to predict risk of incident cancer was non-inferior to radiologists' visual assessment as both point estimate and lower bound of 95% CI (AUC 0.589; 95% CI 0.580-0.597) were above the predefined visual assessment threshold (AUC 0.571). AUC for interval (AUC 0.631; 95% CI 0.623-0.639) cancers was even higher. BD assessed with new fully automated method is positively associated with BC risk and is not inferior to radiologists' visual assessment. It is an even stronger marker of interval cancer, confirming an appreciable masking effect of BD that reduces mammography sensitivity

A multicentre epidemiological study on sunbed use and cutaneous melanoma in Europe

A large European case-control study investigated the association between sunbed use and cutaneous melanoma in an adult population aged between 18 and 49 years. Between 1999 and 2001 sun and sunbed exposure was recorded in 597 newly diagnosed melanoma cases and 622 controls in Belgium, France, The Netherlands, Sweden and the UK. Fifty three precent of cases and 57% of controls ever used sunbeds. The overall adjusted odds ratio (OR) associated with ever sunbed use was 0.90 (95% CI: 0.71-1.14). There was a South-to-North gradient with high prevalence of sunbed exposure in Northern Europe and lower prevalence in the South (prevalence of use in France 20%, OR: 1.19 (0.68-2.07) compared to Sweden, prevalence 83%, relative risk 0.62 (0.26-1.46)). Dose and lag-time between first exposure to sunbeds and time of study were not associated with melanoma risk, neither were sunbathing and sunburns (adjusted OR for mean number of weeks spent in sunny climates >14 years: 1.12 (0.88-1.43); adjusted OR for any sunburn >14 years: 1.16 (0.9-1.45)). Host factors such as numbers of naevi and skin type were the strongest risk indicators for melanoma. Public health campaigns have improved knowledge regarding risk of UV-radiation for skin cancers and this may have led to recall and selection biases in both cases and controls in this study. Sunbed exposure has become increasingly prevalent over the last 20 years, especially in Northern Europe but the full impact of this exposure on skin cancers may not become apparent for many years

All-cause mortality among Belgian military radar operators: a 40-year controlled longitudinal study.

It has been suggested that exposure to radiofrequency/microwaves radiations could be associated with greater health hazards and higher mortality.Journal ArticleResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishe

A versatile knowledge-based clinical imaging annotation system for breast cancer screening

Medical information is evolving towards more complex multimedia data representation, as new imaging modalities are made available by sophisticated devices. Features such as segmented lesions can now be extracted through analysis techniques and need to be integrated into clinical patient data. The management of structured information extracted from multimedia has been addressed in knowledge based annotation systems providing methods to attach interpretative semantics to multimedia content. Building on these methods, we develop a new clinical imaging annotation system for computer aided breast cancer screening. The proposed system aims at more consistent, efficient and standardised data mark-up of digital and digitalised radiology images. The objective is to provide detailed characterisation of abnormalities as an aid in the diagnostic task through integrated annotation management. The system combines imaging analysis results and radiologist diagnostic information about suspicious findings by mapping well-established visual and low-level descriptors into pathology specific profiles. The versatile characterisation allows differentiating annotation descriptors for different types of findings. Our approach of semi-automatic integrated annotations supports increased quality assurance in screening practice. This is achieved through detailed and objective patient imaging information while providing user-friendly means for their manipulation that is oriented to relieving the radiologist's workload.Anglai

Interactive breast cancer segmentation based on relevance feedback: from user-centered design to evaluation

Computer systems play an important role in medical imaging industry since radiologists depend on it for visualization, interpretation, communication and archiving. In particular, computer-aided diagnosis (CAD) systems help in lesion detection tasks. This paper presents the design and the development of an interactive segmentation tool for breast cancer screening and diagnosis. The tool conception is based upon a user-centered approach in order to ensure that the application is of real benefit to radiologists. The analysis of user expectations, workflow and decision-making practices give rise to the need for an interactive reporting system based on the BIRADS, that would not only include the numerical features extracted from the segmentation of the findings in a structured manner, but also support human relevance feedback as well. This way, the numerical results from segmentation can be either validated by end-users or enhanced thanks to domain-experts subjective interpretation. Such a domain-expert centered system requires the segmentation to be sufficiently accurate and locally adapted, and the features to be carefully selected in order to best suit user's knowledge and to be of use in enhancing segmentation. Improving segmentation accuracy with relevance feedback and providing radiologists with a user-friendly interface to support image analysis are the contributions of this work. The preliminary result is first the tool conception, and second the improvement of the segmentation precision. © 2009 SPIE.SCOPUS: cp.pinfo:eu-repo/semantics/publishe