Literature DB >> 29782246

Precision Medicine and Radiogenomics in Breast Cancer: New Approaches toward Diagnosis and Treatment.

Katja Pinker1, Joanne Chin1, Amy N Melsaether1, Elizabeth A Morris1, Linda Moy1.   

Abstract

Precision medicine is medicine optimized to the genotypic and phenotypic characteristics of an individual and, when present, his or her disease. It has a host of targets, including genes and their transcripts, proteins, and metabolites. Studying precision medicine involves a systems biology approach that integrates mathematical modeling and biology genomics, transcriptomics, proteomics, and metabolomics. Moreover, precision medicine must consider not only the relatively static genetic codes of individuals, but also the dynamic and heterogeneous genetic codes of cancers. Thus, precision medicine relies not only on discovering identifiable targets for treatment and surveillance modification, but also on reliable, noninvasive methods of identifying changes in these targets over time. Imaging via radiomics and radiogenomics is poised for a central role. Radiomics, which extracts large volumes of quantitative data from digital images and amalgamates these together with clinical and patient data into searchable shared databases, potentiates radiogenomics, which is the combination of genetic and radiomic data. Radiogenomics may provide voxel-by-voxel genetic information for a complete, heterogeneous tumor or, in the setting of metastatic disease, set of tumors and thereby guide tailored therapy. Radiogenomics may also quantify lesion characteristics, to better differentiate between benign and malignant entities, and patient characteristics, to better stratify patients according to risk for disease, thereby allowing for more precise imaging and screening. This report provides an overview of precision medicine and discusses radiogenomics specifically in breast cancer. © RSNA, 2018.

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Year:  2018        PMID: 29782246     DOI: 10.1148/radiol.2018172171

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  69 in total

Review 1.  Physician centred imaging interpretation is dying out - why should I be a nuclear medicine physician?

Authors:  Roland Hustinx
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-06-07       Impact factor: 9.236

2.  Radiomics signature for the preoperative assessment of stage in advanced colon cancer.

Authors:  Yu Li; Aydin Eresen; Yun Lu; Jia Yang; Junjie Shangguan; Yury Velichko; Vahid Yaghmai; Zhuoli Zhang
Journal:  Am J Cancer Res       Date:  2019-07-01       Impact factor: 6.166

3.  Beyond Breast Density: Radiomic Phenotypes Enhance Assessment of Breast Cancer Risk.

Authors:  Katja Pinker
Journal:  Radiology       Date:  2018-10-30       Impact factor: 11.105

Review 4.  Potentials of radiomics for cancer diagnosis and treatment in comparison with computer-aided diagnosis.

Authors:  Hidetaka Arimura; Mazen Soufi; Kenta Ninomiya; Hidemi Kamezawa; Masahiro Yamada
Journal:  Radiol Phys Technol       Date:  2018-10-29

5.  Renal cell carcinoma: predicting RUNX3 methylation level and its consequences on survival with CT features.

Authors:  Dongzhi Cen; Li Xu; Siwei Zhang; Zhiguang Chen; Yan Huang; Ziqi Li; Bo Liang
Journal:  Eur Radiol       Date:  2019-03-15       Impact factor: 5.315

Review 6.  Digital Analysis in Breast Imaging.

Authors:  Giovanna Negrão de Figueiredo; Michael Ingrisch; Eva Maria Fallenberg
Journal:  Breast Care (Basel)       Date:  2019-06-04       Impact factor: 2.860

Review 7.  Radiomics: an Introductory Guide to What It May Foretell.

Authors:  Stephanie Nougaret; Hichem Tibermacine; Marion Tardieu; Evis Sala
Journal:  Curr Oncol Rep       Date:  2019-06-25       Impact factor: 5.075

Review 8.  Artificial Intelligence for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future Perspectives.

Authors:  Krzysztof J Geras; Ritse M Mann; Linda Moy
Journal:  Radiology       Date:  2019-09-24       Impact factor: 11.105

Review 9.  Background, applications and challenges of radiogenomics in genitourinary tumor.

Authors:  Longfei Liu; Xiaoping Yi; Can Lu; Yingxian Pang; Xiongbing Zu; Minfeng Chen; Xiao Guan
Journal:  Am J Cancer Res       Date:  2021-05-15       Impact factor: 6.166

Review 10.  Natural products targeting cancer cell dependency.

Authors:  Changxiang Shi; Eun Ju Yang; Shishi Tao; Guowen Ren; Pui Kei Mou; Joong Sup Shim
Journal:  J Antibiot (Tokyo)       Date:  2021-06-23       Impact factor: 2.649

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