N, Consejo Superior de Investigaciones icas (CSIC), Spain Cienti Reviewed by: Harini Veeraraghavan, Cornell University, United states of america Rui Vasco Simoes, Champalimaud Foundation, Portugal Correspondence: Hong Zhu [email protected] Pixian Shui [email protected] authors have contributed equally to this function Specialty section: This short article was submitted to Cancer Imaging and Image-directed Interventions, a section of the journal Frontiers in Oncology Received: 08 June 2020 Accepted: 08 December 2020 Published: 26 JanuaryWith the speedy development of new technologies, which includes artificial intelligence and genome sequencing, radiogenomics has emerged as a state-of-the-art PKCĪ· Compound science in the field of individualized medicine. Radiogenomics combines a large volume of quantitative information extracted from health-related pictures with individual genomic phenotypes and constructs a prediction model through deep learning to stratify patients, guide therapeutic methods, and evaluate clinical outcomes. Current research of many varieties of tumors demonstrate the predictive value of radiogenomics. And a few of the issues in the radiogenomic analysis as well as the solutions from prior operates are presented. Even though the workflow criteria and international agreed guidelines for statistical methods have to be confirmed, radiogenomics represents a repeatable and cost-effective approach for the detection of continuous changes and is actually a promising surrogate for invasive interventions. For that reason, radiogenomics could facilitate computer-aided diagnosis, treatment, and prediction from the prognosis in sufferers with tumors inside the routine clinical setting. Here, we summarize the integrated approach of radiogenomics and introduce the important strategies and statistical algorithms involved in existing studies.Keyword phrases: precision medicine, deep mastering, artificial intelligence, radiogenomics, radiological imagingCitation: Shui L, Ren H, Yang X, Li J, Chen Z, Yi C, Zhu H and Shui P (2021) The Era of Radiogenomics in Precision Medicine: An Emerging Method to Support Diagnosis, Treatment Decisions, and Prognostication in Oncology. Front. Oncol. 10:570465. doi: 10.3389/fonc.2020.BACKGROUNDAdvances in genomics plus the far-reaching effects of precision medicine have synergistically accelerated research by integrating the person qualities of sufferers (1). Compared with traditional medical treatment, the nNOS medchemexpress notion of precision medicine follows a “one-size-fits-one” philosophy and sets out a tailored therapeutic program as outlined by the genotypic and phenotypic data of individual individuals (two).Frontiers in Oncology | www.frontiersin.orgJanuary 2021 | Volume 10 | ArticleShui et al.Radiogenomics for Tumor Diagnosis/TherapyCancer can be a disease that includes genetic abnormalities triggered by hereditary or environmental elements. When genes undergo the error-prone method of replication and alterations, including nucleotide substitution, insertions, deletions, and chromosomal rearrangements, the activation of oncogenes and loss of tumor suppressor genes could induce oncogenesis (three). Furthermore, epigenetic alterations, including histone modification, DNA methylation, and altered expression levels of non-coding RNAs, have also been confirmed to be vital contributors to the development of cancer (4). Over current decades, there happen to be important advances in our understanding of the genetic alterations involved in oncogenesis. One example is, mutations with the Kirsten rat sarcoma viral oncogene (KRAS), epidermal growth.
