A New Challenge for Radiologists: Radiomics in Breast Cancer.

Biomed Res Int

Department of Clinical and Experimental Medicine, Institute of Radiological Sciences, University of Sassari, Sassari, Italy.

Published: February 2019

Introduction: Over the last decade, the field of medical imaging experienced an exponential growth, leading to the development of radiomics, with which innumerable quantitative features are obtained from digital medical images, providing a comprehensive characterization of the tumor. This review aims to assess the role of this emerging diagnostic tool in breast cancer, focusing on the ability of radiomics to predict malignancy, response to neoadjuvant chemotherapy, prognostic factors, molecular subtypes, and risk of recurrence.

Evidence Acquisition: A literature search on PubMed and on Cochrane database websites to retrieve English-written systematic reviews, review articles, meta-analyses, and randomized clinical trials published from August 2013 up to July 2018 was carried out.

Results: Twenty papers (19 retrospective and 1 prospective studies) conducted with different conventional imaging modalities were included.

Discussion: The integration of quantitative information with clinical, histological, and genomic data could enable clinicians to provide personalized treatments for breast cancer patients. Current limitations of a routinely application of radiomics are represented by the limited knowledge of its basics concepts among radiologists and by the lack of efficient and standardized systems of feature extraction and data sharing.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6196984PMC
http://dx.doi.org/10.1155/2018/6120703DOI Listing

Publication Analysis

Top Keywords

breast cancer
12
challenge radiologists
4
radiomics
4
radiologists radiomics
4
radiomics breast
4
cancer introduction
4
introduction decade
4
decade field
4
field medical
4
medical imaging
4

Similar Publications

Objective: This study aims to explore the role of exosome-related genes in breast cancer (BRCA) metastasis by integrating RNA-seq and single-cell RNA-seq (scRNA-seq) data from BRCA samples and to develop a reliable prognostic model.

Methods: Initially, a comprehensive analysis was conducted on exosome-related genes from the BRCA cohort in The Cancer Genome Atlas (TCGA) database. Three prognostic genes (JUP, CAPZA1 and ARVCF) were identified through univariate Cox regression and Lasso-Cox regression analyses, and a metastasis-related risk score model was established based on these genes.

View Article and Find Full Text PDF

Introduction: Breast cancer resistance protein (BCRP) is an efflux membrane transporter that controls the pharmacokinetics of a large number of drugs. Its activity may change when taking some endo- and exogenous substances, thus making it a link in drug interactions.

Aim: The aim of the study was to develop a methodology for testing drugs for belonging to BCRP substrates and inhibitors in vitro.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!