Bodyweight and other correlates of symptom detected breast cancers in a population offered screening

Objective: To determine factors associated with symptom detected breast cancers in a population offered screening. Methods We interviewed 1,459 Australian women aged 40–69, 946 with symptom detected and 513 with mammogram detected invasive breast cancers ≥1.1 cm in diameter, about their personal, mammogram and breast histories before diagnosis and reviewed medical records for tumour characteristics and mammogram dates, calculating ORs and 95% confidence intervals (CIs) for symptom- vs mammogram-detected cancers in logistic regression models. Results: Lack of regular mammograms (<2 mammograms in the 4.5 years before diagnosis) was the strongest correlate of symptom detected breast cancer (OR=3.04 for irregular or no mammograms). In women who had regular mammograms (≥2 mammograms in the 4.5 years before diagnosis), the independent correlates of symptom detected cancers were low BMI (OR <25kg/m2 vs ≥30kg/m2=2.18, 95% CI 1.23-3.84; p=0.008), increased breast density (available in 498 women) (OR highest quarter vs lowest =3.50, 95% CI 1.76-6.97; ptrend=0.004), high grade cancer and a larger cancer (each p<0.01). In women who did not have regular mammograms, the independent correlates were age <50 years, a first cancer and a ≥2cm cancer. Smoking appeared to modify the association of symptom detected cancer with low BMI (higher ORs for low BMI in current smokers) and estrogen receptor (ER) status (higher ORs for low BMI in ER− cancers). Conclusion: Women with low BMI may benefit from a tailored approach to breast cancer detection, particularly if they smoke.

Systematic review of the psychological consequences of false-positive screening mammograms

- Background In the UK, women aged 50–73 years are invited for screening by mammography every 3 years. In 2009–10, more than 2.24 million women in this age group in England were invited to take part in the programme, of whom 73% attended a screening clinic. Of these, 64,104 women were recalled for assessment. Of those recalled, 81% did not have breast cancer; these women are described as having a false-positive mammogram. - Objective The aim of this systematic review was to identify the psychological impact on women of false-positive screening mammograms and any evidence for the effectiveness of interventions designed to reduce this impact. We were also looking for evidence of effects in subgroups of women. - Data sources MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, EMBASE, Health Management Information Consortium, Cochrane Central Register for Controlled Trials, Cochrane Database of Systematic Reviews, Centre for Reviews and Dissemination (CRD) Database of Abstracts of Reviews of Effects, CRD Health Technology Assessment (HTA), Cochrane Methodology, Web of Science, Science Citation Index, Social Sciences Citation Index, Conference Proceedings Citation Index-Science, Conference Proceeding Citation Index-Social Science and Humanities, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, Sociological Abstracts, the International Bibliography of the Social Sciences, the British Library's Electronic Table of Contents and others. Initial searches were carried out between 8 October 2010 and 25 January 2011. Update searches were carried out on 26 October 2011 and 23 March 2012. - Review methods Based on the inclusion criteria, titles and abstracts were screened independently by two reviewers. Retrieved papers were reviewed and selected using the same independent process. Data were extracted by one reviewer and checked by another. Each included study was assessed for risk of bias. - Results Eleven studies were found from 4423 titles and abstracts. Studies that used disease-specific measures found a negative psychological impact lasting up to 3 years. Distress increased with the level of invasiveness of the assessment procedure. Studies using instruments designed to detect clinical levels of morbidity did not find this effect. Women with false-positive mammograms were less likely to return for the next round of screening [relative risk (RR) 0.97; 95% confidence interval (CI) 0.96 to 0.98] than those with normal mammograms, were more likely to have interval cancer [odds ratio (OR) 3.19 (95% CI 2.34 to 4.35)] and were more likely to have cancer detected at the next screening round [OR 2.15 (95% CI 1.55 to 2.98)]. - Limitations This study was limited to UK research and by the robustness of the included studies, which frequently failed to report quality indicators, for example failure to consider the risk of bias or confounding, or failure to report participants' demographic characteristics. - Conclusions We conclude that the experience of having a false-positive screening mammogram can cause breast cancer-specific psychological distress that may endure for up to 3 years, and reduce the likelihood that women will return for their next round of mammography screening. These results should be treated cautiously owing to inherent weakness of observational designs and weaknesses in reporting. Future research should include a qualitative interview study and observational studies that compare generic and disease-specific measures, collect demographic data and include women from different social and ethnic groups.

Psychological consequences of false-positive screening mammograms in the UK

- Objectives To identify the psychological effects of false-positive screening mammograms in the UK. - Methods Systematic review of all controlled studies and qualitative studies of women with a false-positive screening mammogram. The control group participants had normal mammograms. All psychological outcomes including returning for routine screening were permitted. All studies had a narrative synthesis. - Results The searches returned seven includable studies (7/4423). Heterogeneity was such that meta-analysis was not possible. Studies using disease-specific measures found that, compared to normal results, there could be enduring psychological distress that lasted up to 3 years; the level of distress was related to the degree of invasiveness of the assessment. At 3 years the relative risks were, further mammography, 1.28 (95% CI 0.82 to 2.00), fine needle aspiration 1.80 (95% CI 1.17 to 2.77), biopsy 2.07 (95% CI 1.22 to 3.52) and early recall 1.82 (95% CI 1.22 to 2.72). Studies that used generic measures of anxiety and depression found no such impact up to 3 months after screening. Evidence suggests that women with false-positive mammograms have an increased likelihood of failing to reattend for routine screening, relative risk 0.97 (95% CI 0.96 to 0.98) compared with women with normal mammograms. - Conclusions Having a false-positive screening mammogram can cause breast cancer-specific distress for up to 3 years. The degree of distress is related to the invasiveness of the assessment. Women with false-positive mammograms are less likely to return for routine assessment than those with normal ones.

Fatores determinantes do absenteísmo das mulheres de Piraí, estado do Rio de Janeiro, ao exame de mamografia.

O trabalho buscou conhecer os motivos que levaram mulheres do município de Piraí, estado do Rio de Janeiro, agendadas para realizar o exame de mamografia, a não comparecer ao mesmo

On Combining Morphological Component Analysis and Concentric Morphology Model for Mammographic Mass Detection

Mammographic mass detection is an important task for the early diagnosis of breast cancer. However, it is difficult to distinguish masses from normal regions because of their abundant morphological characteristics and ambiguous margins. To improve the mass detection performance, it is essential to effectively preprocess mammogram to preserve both the intensity distribution and morphological characteristics of regions. In this paper, morphological component analysis is first introduced to decompose a mammogram into a piecewise-smooth component and a texture component. The former is utilized in our detection scheme as it effectively suppresses both structural noises and effects of blood vessels. Then, we propose two novel concentric layer criteria to detect different types of suspicious regions in a mammogram. The combination is evaluated based on the Digital Database for Screening Mammography, where 100 malignant cases and 50 benign cases are utilized. The sensitivity of the proposed scheme is 99% in malignant, 88% in benign, and 95.3% in all types of cases. The results show that the proposed detection scheme achieves satisfactory detection performance and preferable compromises between sensitivity and false positive rates.

Model-based detection of spiculated lesions in mammograms

R. Zwiggelaar, T.C. Parr, J.E. Schumm. I.W. Hutt, S.M. Astley, C.J. Taylor and C.R.M. Boggis, 'Model-based detection of spiculated lesions in mammograms', Medical Image Analysis 3 (1), 39-62 (1999)

Screening-detected non-symptomatic breast cancer: a case history

Alice is a 65 year-old woman who was recalled for further investigations following a routine screening mammogram, which showed a 25 mm mass in her left breast. This case history will report on the further investigations and surgery required to manage this infiltrating ductal carcinoma. The histopathology report will be analysed to provide a rationale for future treatment with radiotherapy, and Alice's expected prognosis will be presented using the Nottingham Prognostic Index. Alice's psychological support needs will identified and the appropriate interventions will be discussed with a particular focus on Alice's history of depression. The supportive and educational role of the breast care nurse and the multidisciplinary team will be highlighted throughout the study.

Efeito de um resultado falso positivo da leitura da mamografia na não participação no rastreio do cancro da mama : estudo de coorte histórico de um rastreio de base populacional da região de saúde do centro em Portugal

RESUMO - Introdução: O cancro da mama é uma das principais causas de mortalidade por doença oncológica. O rastreio contribui para o aumento da sobrevivência, mas apresenta riscos como a obtenção de um resultado falso positivo com efeitos controversos sobre a participação subsequente. Métodos: Realizou-se um estudo de coorte histórico (2006-2012) de 170.835 mulheres com 45-67 anos, elegíveis para o programa de rastreio do cancro da mama da ARSC,IP. Calcularam-se as medidas de efeito de um falso positivo da leitura na não participação na volta consecutiva de rastreio do cancro da mama, e a associação entre o evento em estudo e factores sociodemográficos, relacionados com o rastreio e com a anamnese, através de análise de regressão de Poisson. Resultados: A incidência de não participação foi 12,13%. A exposição a falso positivo da leitura aumentou 8,01% o risco absoluto de não participação. O falso positivo da leitura da mamografia revelou-se um factor de risco para a não participação (RRa=1,17; IC 1,10-1,25). O efeito protector da existência de participações anteriores foi superior ao efeito dos factores de risco identificados. Identificaram-se outros factores de risco e de protecção. Discussão: De acordo com os factores de risco e de protecção identificados recomendaram-se alterações à operacionalização do programa de rastreio, a manutenção das estatégias adequadas e a realização de estudos futuros para avaliar o efeito de outros factores não incluídos neste estudo. A comunicação do risco associado a um resultado anormal da mamografia é importante para diminuir a ansiedade consequente ao rastreio, devendo ser oferecidas intervenções que promovam a participação no rastreio.

Les inégalités sociales dans le dépistage du cancer du sein, quand le système s'en mêle...

Réalisé en cotutelle avec Dr. Béatrice Godard, Professeure titulaire à l'Université de Montréal.

Fractal based techniques for classification of mammograms and identification of microcalcifications

After skin cancer, breast cancer accounts for the second greatest number of cancer diagnoses in women. Currently the etiologies of breast cancer are unknown, and there is no generally accepted therapy for preventing it. Therefore, the best way to improve the prognosis for breast cancer is early detection and treatment. Computer aided detection systems (CAD) for detecting masses or micro-calcifications in mammograms have already been used and proven to be a potentially powerful tool , so the radiologists are attracted by the effectiveness of clinical application of CAD systems. Fractal geometry is well suited for describing the complex physiological structures that defy the traditional Euclidean geometry, which is based on smooth shapes. The major contribution of this research include the development of • A new fractal feature to accurately classify mammograms into normal and normal (i)With masses (benign or malignant) (ii) with microcalcifications (benign or malignant) • A novel fast fractal modeling method to identify the presence of microcalcifications by fractal modeling of mammograms and then subtracting the modeled image from the original mammogram. The performances of these methods were evaluated using different standard statistical analysis methods. The results obtained indicate that the developed methods are highly beneficial for assisting radiologists in making diagnostic decisions. The mammograms for the study were obtained from the two online databases namely, MIAS (Mammographic Image Analysis Society) and DDSM (Digital Database for Screening Mammography.

classification and content based retrieval of digital mammograms and placental sonograms

Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians’ assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology.

Enhancement of Calcifications in Mammograms using Volterra Series based Quadratic Filter

The paper summarizes the design and implementation of a quadratic edge detection filter, based on Volterra series, for enhancing calcifications in mammograms. The proposed filter can account for much of the polynomial nonlinearities inherent in the input mammogram image and can replace the conventional edge detectors like Laplacian, gaussian etc. The filter gives rise to improved visualization and early detection of microcalcifications, which if left undetected, can lead to breast cancer. The performance of the filter is analyzed and found superior to conventional spatial edge detectors

Classification of Mammograms and DW T based Detection of Microcalcification

Cancer treatment is most effective when it is detected early and the progress in treatment will be closely related to the ability to reduce the proportion of misses in the cancer detection task. The effectiveness of algorithms for detecting cancers can be greatly increased if these algorithms work synergistically with those for characterizing normal mammograms. This research work combines computerized image analysis techniques and neural networks to separate out some fraction of the normal mammograms with extremely high reliability, based on normal tissue identification and removal. The presence of clustered microcalcifications is one of the most important and sometimes the only sign of cancer on a mammogram. 60% to 70% of non-palpable breast carcinoma demonstrates microcalcifications on mammograms [44], [45], [46].WT based techniques are applied on the remaining mammograms, those are obviously abnormal, to detect possible microcalcifications. The goal of this work is to improve the detection performance and throughput of screening-mammography, thus providing a ‘second opinion ‘ to the radiologists. The state-of- the- art DWT computation algorithms are not suitable for practical applications with memory and delay constraints, as it is not a block transfonn. Hence in this work, the development of a Block DWT (BDWT) computational structure having low processing memory requirement has also been taken up.