319 research outputs found

    Towards consensus on managing high mammographic density in population breast screening?

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    In Medicine and in Radiology, impact on societal and health outcomes of a diagnostic pathway or methodology should be comprehensively investigated before implementing a screening approach for disease ..

    Radiological clinical trials: Proposal of a problem-finding questionnaire to improve study success

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    AIM To develop a survey to help define the main problems in radiological clinical trials. METHODS Since 2006, we have managed seven different radio-logical clinical trials recruiting patients in academic and non-academic centres. We developed a preliminary questionnaire using a four-round Delphi approach to identify problems occurring in radiological clinical trials run at our centre. We investigated the recruitment experience, involvement of all multi-disciplinary team members and main obstacles to completing the projects. A final round of Delphi processes elucidated solutions to the identified problems

    sj-docx-1-msc-10.1177_09691413221125320 - Supplemental material for Factors associated with women's supplemental screening intentions following dense breast notification in an online randomised experimental study

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    Supplemental material, sj-docx-1-msc-10.1177_09691413221125320 for Factors associated with women's supplemental screening intentions following dense breast notification in an online randomised experimental study by Brooke Nickel, Hankiz Dolan, Nehmat Houssami, Erin Cvejic, Meagan Brennan, Jolyn Hersch, Melanie Dorrington, Angela Verde, Lisa Vaccaro and Kirsten McCaffery in Journal of Medical Screening</p

    sj-docx-3-dhj-10.1177_20552076231191057 - Supplemental material for Australian women's judgements about using artificial intelligence to read mammograms in breast cancer screening

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    Supplemental material, sj-docx-3-dhj-10.1177_20552076231191057 for Australian women's judgements about using artificial intelligence to read mammograms in breast cancer screening by Stacy M Carter, Lucy Carolan, Yves Saint James Aquino, Helen Frazer, Wendy A Rogers, Julie Hall, Chris Degeling, Annette Braunack-Mayer and Nehmat Houssami in DIGITAL HEALTH</p

    sj-docx-2-dhj-10.1177_20552076231191057 - Supplemental material for Australian women's judgements about using artificial intelligence to read mammograms in breast cancer screening

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    Supplemental material, sj-docx-2-dhj-10.1177_20552076231191057 for Australian women's judgements about using artificial intelligence to read mammograms in breast cancer screening by Stacy M Carter, Lucy Carolan, Yves Saint James Aquino, Helen Frazer, Wendy A Rogers, Julie Hall, Chris Degeling, Annette Braunack-Mayer and Nehmat Houssami in DIGITAL HEALTH</p

    Digital breast tomosynthesis (3D-mammography) screening : A pictorial review of screen-detected cancers and false recalls attributed to tomosynthesis in prospective screening trials

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    This pictorial review highlights cancers detected only at tomosynthesis screening and screens falsely recalled in the course of breast tomosynthesis screening, illustrating both true-positive (TP) and false-positive (FP) detection attributed to tomosynthesis. Images and descriptive data were used to characterise cases of screen-detection with tomosynthesis, sourced from prospective screening trials that performed standard (2D) digital mammography (DM) and tomosynthesis (3D-mammography) in the same screening participants. Exemplar cases from four trials highlight common themes of relevance to screening practice including: the type of lesions frequently made more conspicuous or perceptible by tomosynthesis (spiculated masses, and architectural distortions); the histologic findings (both TP and FP) of tomosynthesis-only detection; and the need to extend breast work-up protocols (additional imaging including ultrasound and MRI, and tomosynthesis-guided biopsy) if tomosynthesis is adopted for primary screening

    sj-docx-1-dhj-10.1177_20552076231191057 - Supplemental material for Australian women's judgements about using artificial intelligence to read mammograms in breast cancer screening

    No full text
    Supplemental material, sj-docx-1-dhj-10.1177_20552076231191057 for Australian women's judgements about using artificial intelligence to read mammograms in breast cancer screening by Stacy M Carter, Lucy Carolan, Yves Saint James Aquino, Helen Frazer, Wendy A Rogers, Julie Hall, Chris Degeling, Annette Braunack-Mayer and Nehmat Houssami in DIGITAL HEALTH</p
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