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      Artifact reduction in contrast-enhanced mammography

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          Abstract

          Objective

          To evaluate the effectiveness of a new algorithm developed to reduce artifacts in dual-energy subtraction (DES) contrast-enhanced mammography (CEM) images while preserving contrast enhancement of possible lesions.

          Methods

          A retrospective multi-reader paired study was performed by using 134 CEM studies obtained from the first 134 women enrolled in a prospective clinical study aiming to compare the clinical performance of CEM to those of breast MRI in screening of women at increased risk of breast cancer. Four experienced readers compared independently the standard (STD) DES images with those obtained by reprocessing the raw images by a new algorithm (NEW), expected to reduce the DES artifact intensity. The intensity of three types of artifacts (breast-in-breast, ripple, and skinfold enhancement) and the intensity of possible contrast uptake were assessed visually and rated using a categorical ordinal scale. Proportions of images rated by the majority of readers as “Absent”, “Weak”, “Medium”, “Strong” in each artifact intensity category were compared between the two algorithms. P-values lower than 0.05 were considered statistically significant.

          Results

          The NEW algorithm succeeded in eliminating 84.5% of breast-in-breast artifacts, 84.2% of ripple artifacts, and 56.9% of skinfold enhancement artifacts versus STD DES images, and reduced the artifact intensity in 12.1%, 13.0%, and 28.8% of the images, respectively. The visibility of lesion contrast uptake was the same with the STD and the NEW algorithms.

          Conclusion

          The new dual-energy subtraction algorithm demonstrated to be effective in reducing/eliminating CEM-related artifacts while preserving lesion contrast enhancement.

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          Most cited references19

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          A breast cancer prediction model incorporating familial and personal risk factors.

          Many factors determine a woman's risk of breast cancer. Some of them are genetic and relate to family history, others are based on personal factors such as reproductive history and medical history. While many papers have concentrated on subsets of these risk factors, no papers have incorporated personal risk factors with a detailed genetic analysis. There is a need to combine these factors to provide a better overall determinant of risk. The discovery of the BRCA1 and BRCA2 genes has explained some of the genetic determinants of breast cancer risk, but these genes alone do not explain all of the familial aggregation of breast cancer. We have developed a model incorporating the BRCA genes, a low penetrance gene and personal risk factors. For an individual woman her family history is used in conjuction with Bayes theorem to iteratively produce the likelihood of her carrying any genes predisposing to breast cancer, which in turn affects her likelihood of developing breast cancer. This risk was further refined based on the woman's personal history. The model has been incorporated into a computer program that gives a personalised risk estimate. Copyright 2004 John Wiley & Sons, Ltd.
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            Combined associations of genetic and environmental risk factors: implications for prevention of breast cancer.

            Genome-wide association studies (GWAS) have identified hundreds of genetic susceptibility loci for cancers and other complex diseases. However, the public health and clinical relevance of these discoveries is unclear. Evaluating the combined associations of genetic and environmental risk factors, particularly those that can be modified, will be critical in assessing the utility of genetic information for risk stratified prevention. In this commentary, using breast cancer as a model, we show that genetic information in combination with other risk factors can provide levels of risk stratification that could be useful for individual decision-making or population-based prevention programs. Our projections are theoretical and rely on a number of assumptions, including multiplicative models for the combined associations of the different risk factors, which need confirmation. Thus, analyses of epidemiological studies with high-quality risk factor information, as well as prevention trials, are needed to empirically assess the impact of genetics in risk stratified prevention.
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              Contrast Enhanced Spectral Mammography: A Review

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                Author and article information

                Contributors
                gisella.gennaro@iov.veneto.it
                Journal
                Insights Imaging
                Insights Imaging
                Insights into Imaging
                Springer Vienna (Vienna )
                1869-4101
                13 May 2022
                13 May 2022
                December 2022
                : 13
                : 90
                Affiliations
                GRID grid.419546.b, ISNI 0000 0004 1808 1697, Breast Imaging Unit, , Veneto Institute of Oncology (IOV), ; IRCCS. Via Gattamelata 64, 35128 Padua, Italy
                Author information
                http://orcid.org/0000-0003-2444-1778
                Article
                1211
                10.1186/s13244-022-01211-w
                9098782
                35554734
                e84f71f4-5893-49f2-be95-bb7c47f0267f
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 10 February 2022
                : 17 March 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100009878, Regione del Veneto;
                Award ID: RSF-2017-00000562
                Award Recipient :
                Categories
                Original Article
                Custom metadata
                © The Author(s) 2022

                Radiology & Imaging
                mammography,contrast agent,artifact
                Radiology & Imaging
                mammography, contrast agent, artifact

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