Literature DB >> 28131497

Role of Imaging in the Era of Precision Medicine.

Angela Giardino1, Supriya Gupta2, Emmi Olson3, Karla Sepulveda4, Leon Lenchik5, Jana Ivanidze6, Rebecca Rakow-Penner7, Midhir J Patel8, Rathan M Subramaniam9, Dhakshinamoorthy Ganeshan10.   

Abstract

Precision medicine is an emerging approach for treating medical disorders, which takes into account individual variability in genetic and environmental factors. Preventive or therapeutic interventions can then be directed to those who will benefit most from targeted interventions, thereby maximizing benefits and minimizing costs and complications. Precision medicine is gaining increasing recognition by clinicians, healthcare systems, pharmaceutical companies, patients, and the government. Imaging plays a critical role in precision medicine including screening, early diagnosis, guiding treatment, evaluating response to therapy, and assessing likelihood of disease recurrence. The Association of University Radiologists Radiology Research Alliance Precision Imaging Task Force convened to explore the current and future role of imaging in the era of precision medicine and summarized its finding in this article. We review the increasingly important role of imaging in various oncological and non-oncological disorders. We also highlight the challenges for radiology in the era of precision medicine. Published by Elsevier Inc.

Entities:  

Keywords:  Precision medicine; imaging in oncology; task force

Mesh:

Year:  2017        PMID: 28131497     DOI: 10.1016/j.acra.2016.11.021

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  14 in total

1.  Nomogram Identifies Age as the Most Important Predictor of Overall Survival in Oral Cavity Squamous Cell Cancer After Primary Surgery.

Authors:  Supriya Gupta; Jennifer Waller; Jimmy Brown; Yolanda Elam; James V Rawson; Darko Pucar
Journal:  Indian J Otolaryngol Head Neck Surg       Date:  2019-08-16

Review 2.  An overview of clinical decision support systems: benefits, risks, and strategies for success.

Authors:  Reed T Sutton; David Pincock; Daniel C Baumgart; Daniel C Sadowski; Richard N Fedorak; Karen I Kroeker
Journal:  NPJ Digit Med       Date:  2020-02-06

Review 3.  An Assessment of Imaging Informatics for Precision Medicine in Cancer.

Authors:  C Chennubhotla; L P Clarke; A Fedorov; D Foran; G Harris; E Helton; R Nordstrom; F Prior; D Rubin; J H Saltz; E Shalley; A Sharma
Journal:  Yearb Med Inform       Date:  2017-09-11

Review 4.  Radiology, Mobile Devices, and Internet of Things (IoT).

Authors:  Supriya Gupta; Elizabeth M Johnson; Justin G Peacock; Liwei Jiang; Morgan P McBee; Michael B Sneider; Elizabeth A Krupinski
Journal:  J Digit Imaging       Date:  2020-06       Impact factor: 4.056

5.  Radiomic Quantification for MRI Assessment of Sacroiliac Joints of Patients with Spondyloarthritis.

Authors:  Ariane Priscilla Magalhães Tenório; José Raniery Ferreira-Junior; Vitor Faeda Dalto; Matheus Calil Faleiros; Rodrigo Luppino Assad; Paulo Louzada-Junior; Marcello Henrique Nogueira-Barbosa; Rangaraj Mandayam Rangayyan; Paulo Mazzoncini de Azevedo-Marques
Journal:  J Digit Imaging       Date:  2022-01-07       Impact factor: 4.056

6.  Structured reporting adds clinical value in primary CT staging of diffuse large B-cell lymphoma.

Authors:  Franziska Schoeppe; Wieland H Sommer; Dominik Nörenberg; Mareike Verbeek; Christian Bogner; C Benedikt Westphalen; Martin Dreyling; Ernst J Rummeny; Alexander A Fingerle
Journal:  Eur Radiol       Date:  2018-03-29       Impact factor: 5.315

Review 7.  Radiomics in radiation oncology for gynecological malignancies: a review of literature.

Authors:  Morgan Michalet; David Azria; Marion Tardieu; Hichem Tibermacine; Stéphanie Nougaret
Journal:  Br J Radiol       Date:  2021-05-07       Impact factor: 3.629

Review 8.  Molecular Imaging: A Useful Tool for the Development of Natural Killer Cell-Based Immunotherapies.

Authors:  Prakash Gangadaran; Byeong-Cheol Ahn
Journal:  Front Immunol       Date:  2017-09-12       Impact factor: 7.561

9.  Divide and Conquer: Stratifying Training Data by Tumor Grade Improves Deep Learning-Based Brain Tumor Segmentation.

Authors:  Michael Rebsamen; Urspeter Knecht; Mauricio Reyes; Roland Wiest; Raphael Meier; Richard McKinley
Journal:  Front Neurosci       Date:  2019-11-05       Impact factor: 4.677

Review 10.  Artificial intelligence, machine learning, computer-aided diagnosis, and radiomics: advances in imaging towards to precision medicine.

Authors:  Marcel Koenigkam Santos; José Raniery Ferreira Júnior; Danilo Tadao Wada; Ariane Priscilla Magalhães Tenório; Marcello Henrique Nogueira Barbosa; Paulo Mazzoncini de Azevedo Marques
Journal:  Radiol Bras       Date:  2019 Nov-Dec
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