| Added by | mollevi |
|---|---|
| Group name | EquipeMY |
| Item Type | Journal Article |
| Title | Radiomics: an Introductory Guide to What It May Foretell |
| Creator | Nougaret et al. |
| Author | Stephanie Nougaret |
| Author | Hichem Tibermacine |
| Author | Marion Tardieu |
| Author | Evis Sala |
| Abstract | PURPOSE OF REVIEW: To briefly review the radiomics concept, its applications, and challenges in oncology in the era of precision medicine. RECENT FINDINGS: Over the last 5 years, more than 500 studies have evaluated the role of radiomics to predict tumor diagnosis, genetic pattern, tumor response to therapy, and survival in multiple cancers. This new post-processing method is aimed at extracting multiple quantitative features from the image and converting them into mineable data. Radiomics models developed have shown promising results and may play a role in the near future in the daily patient management especially to assess tumor heterogeneity acting as a whole tumor virtual biopsy. For now, radiomics is limited by its lack of standardization; future challenges will be to provide robust and reproducible metrics extracted from large multicenter databases. |
| Publication | Current Oncology Reports |
| Volume | 21 |
| Issue | 8 |
| Pages | 70 |
| Date | 06 25, 2019 |
| Journal Abbr | Curr Oncol Rep |
| Language | eng |
| DOI | 10.1007/s11912-019-0815-1 |
| ISSN | 1534-6269 |
| Short Title | Radiomics |
| Library Catalog | PubMed |
| Extra | PMID: 31240403 |
| Tags | Artificial Intelligence, Biopsy, CT, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, MRI, Neoplasms, PET/CT, Positron-Emission Tomography, Precision Medicine, Radiation Oncology, Radiomics, Texture, Tomography, X-Ray Computed |
| Date Added | 2020/09/03 - 09:50:52 |
| Date Modified | 2020/09/03 - 09:50:52 |
| Notes and Attachments | PubMed entry (Attachment) |
Institut de Recherche en Cancérologie de
