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Overview of radiomics in breast cancer diagnosis and prognostication
- Source :
- The Breast : official journal of the European Society of Mastology, Breast, Vol 49, Iss, Pp 74-80 (2020), The Breast
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- 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.<br />Highlights • In the screening setting, radiology sensitivity is suboptimal. • Artificial intelligence hold promise in cancer diagnosis and prognostication. • Radiomics include feature extraction from clinical images.
- Subjects :
- Artificial intelligence
medicine.medical_specialty
Treatment response
Biopsy
Breast Neoplasms
lcsh:RC254-282
Digital breast tomosynthesis
1117 Public Health and Health Services
Workflow
Machine Learning
03 medical and health sciences
Magnetic resonance imaging
Breast cancer
0302 clinical medicine
Radiomics
Image Interpretation, Computer-Assisted
medicine
Medical imaging
Humans
1112 Oncology and Carcinogenesis
Breast
030212 general & internal medicine
Early Detection of Cancer
Tumor size
medicine.diagnostic_test
business.industry
Disease progression
General Medicine
Virtual special issue: Artificial Intelligence in Breast Cancer Care
Edited by Nehmat Houssami, Maria João Cardoso, Giuseppe Pozzi and Brigitte Seroussi
lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Prognosis
medicine.disease
Magnetic Resonance Imaging
030220 oncology & carcinogenesis
Female
Surgery
Ultrasonography, Mammary
Radiology
Prediction
business
Mammography
Subjects
Details
- ISSN :
- 09609776
- Volume :
- 49
- Database :
- OpenAIRE
- Journal :
- The Breast
- Accession number :
- edsair.doi.dedup.....3a09d39ee06df085e2bfeebc80eb074d