Design and Development of an Intelligent Clinical Decision Support System Applied to the Evaluation of Breast Cancer Risk

Breast cancer is currently one of the main causes of death and tumoral diseases in women. Even if early diagnosis processes have evolved in the last years thanks to the popularization of mammogram tests, nowadays, it is still a challenge to have available reliable diagnosis systems that are exempt of variability in their interpretation. To this end, in this work, the design and development of an intelligent clinical decision support system to be used in the preventive diagnosis of breast cancer is presented, aiming both to improve the accuracy in the evaluation and to reduce its uncertainty. Through the integration of expert systems (based on Mamdani-type fuzzy-logic inference engines) deployed in cascade, exploratory factorial analysis, data augmentation approaches, and classification algorithms such as k-neighbors and bagged trees, the system is able to learn and to interpret the patient's medical-healthcare data, generating an alert level associated to the danger she has of suffering from cancer. For the system's initial performance tests, a software implementation of it has been built that was used in the diagnosis of a series of patients contained into a 130-cases database provided by the School of Medicine and Public Health of the University of Wisconsin-Madison, which has been also used to create the knowledge base. The obtained results, characterized as areas under the ROC curves of 0.95-0.97 and high success rates, highlight the huge diagnosis and preventive potential of the developed system, and they allow forecasting, even when a detailed and contrasted validation is still pending, its relevance and applicability within the clinical field.

The P.I.N.K. Study Approach for Supporting Personalized Risk Assessment and Early Diagnosis of Breast Cancer

Breast cancer is a clear example of excellent survival when it is detected and properly treated in the early stage. Currently, screening of this cancer relies on mammography, which may be integrated by new imaging techniques for more exhaustive evaluation. The Personalized, Integrated, Network, Knowledge (P.I.N.K.) study is a longitudinal multicentric study involving several diagnostic centres across Italy, co-ordinated by the Italian National Research Council and co-funded by the Umberto Veronesi Foundation. Aim of the study is to evaluate the increased diagnostic accuracy in detecting cancers obtained with different combinations of imaging technologies, and find the most effective diagnostic pathway matching the characteristics of an individual patient. The study foresees the enrolment of 50,000 women over the age of 40 years presenting for breast examination and providing informed consent to data handling. So far, the 15 participating centres across Italy have recruited a total of 22,848 patients. Based on the analyses of the first 175 histopathological-proven breast cancers, mammographic sensitivity was estimated to be 61.7% (n = 108 cancers), whereas diagnostic accuracy increased by 35.5% (n = 44 cancers) when mammography was integrated with other imaging modalities (ultrasound and/or digital breast tomosynthesis). Increase was mainly determined by ultrasound alone. Given the ongoing data collection and recruitment, the number of cancers detected is too low to allow any further in-depth analysis to explore links to patient characteristics. Past studies show that the uniform approach of population screening guidelines should be revised in favour of more personalised regimens, where known standards are integrated by imaging techniques most suitable for the individual's characteristics. With the ultimate goal of identifying early breast cancer detection strategies, our preliminary results suggest that integrated diagnostic approach could lead to a paradigm shift from an age-based regimen toward more specific and effective risk-based personalised screening regimens, in order to reduce mortality from breast cancer.

Breast cancer screening controversies: who, when, why, and how?

Mammographic screening is effective in reducing mortality from breast cancer. The issue is not whether mammography is effective, but whether the false positive rate and false negative rates can be reduced. This review will discuss controversies including the reduction in breast cancer mortality, overdiagnosis, the ideal screening candidate, and the optimal imaging modality for breast cancer screening. The article will compare and contrast screening mammography, tomosynthesis, whole-breast screening ultrasound, magnetic resonance imaging, and molecular breast imaging. Though supplemental imaging modalities are being utilized to improve breast cancer diagnosis, mammography still remains the gold standard for breast cancer screening.

Real and artificial controversies in breast cancer screening

SUMMARY We review the apparent disparities between different reviews of the effects of mammographic screening on mortality from breast cancer and overdiagnosis. When results of each review are expressed with respect to a common population and a common baseline, all find a substantial mortality benefit and variation among estimates is minor. There are genuine disagreements about overdiagnosis, but methods that take account of lead time and underlying incidence trends yield estimates of overdiagnosis that are modest and are outweighed by the mortality benefit. There is potential for individualized screening regimens, particularly with respect to breast density.

Long-term benefits of breast screening

SUMMARY A series of prospective randomized controlled trials of breast cancer screening convincingly demonstrated the efficacy of an invitation to mammography to reduce breast cancer deaths. Evaluation efforts since then have focused on the absolute benefit of breast cancer screening overall and in age-specific subgroups, with various measures of benefit versus harm, and an interest in the degree to which improvements in therapy and women’s improved reporting of symptoms have eclipsed some or all of the benefit of detection of occult disease by mammography. In this article we describe the summary measures of the efficacy of mammography demonstrated by the randomized controlled trials, the importance of long-term follow-up to measure the absolute benefit of mammography and the balance of benefits and harms, including the number needed to screen to save one life and overdiagnosis.