دورية أكاديمية
Overview of radiomics in breast cancer diagnosis and prognostication.
| العنوان: | Overview of radiomics in breast cancer diagnosis and prognostication. |
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| المؤلفون: | Tagliafico, Alberto S, Piana, Michele, Schenone, Daniela, Lai, Rita, Massone, Anna Maria, Houssami, Nehmat |
| المصدر: | The Breast |
| بيانات النشر: | Elsevier Faculty of Medicine and Health, Sydney School of Public Health |
| سنة النشر: | 2020 |
| المجموعة: | The University of Sydney: Sydney eScholarship Repository |
| مصطلحات موضوعية: | Breast cancer, Prediction, Digital breast tomosynthesis, Radiomics, Magnetic resonance imaging, Artificial intelligence, 1112 Oncology and Carcinogenesis, 1117 Public Health and Health Services |
| الوصف: | Diagnosis of early invasive breast cancer relies on radiology and clinical evaluation, supplemented by biopsy confirmation. At least three issues burden this approach: a) suboptimal sensitivity and suboptimal positive predictive power of radiology screening and diagnostic approaches, respectively; b) invasiveness of biopsy with discomfort for women undergoing diagnostic tests; c) long turnaround time for recall tests. In the screening setting, radiology sensitivity is suboptimal, and when a suspicious lesion is detected and a biopsy is recommended, the positive predictive value of radiology is modest. Recent technological advances in medical imaging, especially in the field of artificial intelligence applied to image analysis, hold promise in addressing clinical challenges in cancer detection, assessment of treatment response, and monitoring disease progression. Radiomics include feature extraction from clinical images; these features are related to tumor size, shape, intensity, and texture, collectively providing comprehensive tumor characterization, the so-called radiomics signature of the tumor. Radiomics is based on the hypothesis that extracted quantitative data derives from mechanisms occurring at genetic and molecular levels. In this article we focus on the role and potential of radiomics in breast cancer diagnosis and prognostication. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| العلاقة: | https://hdl.handle.net/2123/25904Test |
| DOI: | 10.1016/j.breast.2019.10.018 |
| الإتاحة: | https://doi.org/10.1016/j.breast.2019.10.018Test https://hdl.handle.net/2123/25904Test |
| حقوق: | Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 |
| رقم الانضمام: | edsbas.A2E71479 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1016/j.breast.2019.10.018 |
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