Literature DB >> 29926137

Radiomics and radiogenomics of prostate cancer.

Clayton P Smith1,2, Marcin Czarniecki1, Sherif Mehralivand1,3,4, Radka Stoyanova5, Peter L Choyke1, Stephanie Harmon6, Baris Turkbey7.   

Abstract

Radiomics and radiogenomics are attractive research topics in prostate cancer. Radiomics mainly focuses on extraction of quantitative information from medical imaging, whereas radiogenomics aims to correlate these imaging features to genomic data. The purpose of this review is to provide a brief overview summarizing recent progress in the application of radiomics-based approaches in prostate cancer and to discuss the potential role of radiogenomics in prostate cancer.

Entities:  

Keywords:  Imaging; Prostate cancer; Radiogenomics; Radiomics

Year:  2019        PMID： 29926137     DOI： 10.1007/s00261-018-1660-7

Source DB:  PubMed          Journal:  Abdom Radiol (NY)


  18 in total

Review 1.  Machine learning applications in imaging analysis for patients with pituitary tumors: a review of the current literature and future directions.

Authors:  Ashirbani Saha; Samantha Tso; Jessica Rabski; Alireza Sadeghian; Michael D Cusimano
Journal:  Pituitary       Date:  2020-06       Impact factor: 4.107

2.  A rapid volume of interest-based approach of radiomics analysis of breast MRI for tumor decoding and phenotyping of breast cancer.

Authors:  Aydin Demircioglu; Johannes Grueneisen; Marc Ingenwerth; Oliver Hoffmann; Katja Pinker-Domenig; Elizabeth Morris; Johannes Haubold; Michael Forsting; Felix Nensa; Lale Umutlu
Journal:  PLoS One       Date:  2020-06-26       Impact factor: 3.240

3.  Repeatability of Multiparametric Prostate MRI Radiomics Features.

Authors:  Michael Schwier; Joost van Griethuysen; Mark G Vangel; Steve Pieper; Sharon Peled; Clare Tempany; Hugo J W L Aerts; Ron Kikinis; Fiona M Fennessy; Andriy Fedorov
Journal:  Sci Rep       Date:  2019-07-01       Impact factor: 4.379

4.  Gleason Probability Maps: A Radiomics Tool for Mapping Prostate Cancer Likelihood in MRI Space.

Authors:  Sean D McGarry; John D Bukowy; Kenneth A Iczkowski; Jackson G Unteriner; Petar Duvnjak; Allison K Lowman; Kenneth Jacobsohn; Mark Hohenwalter; Michael O Griffin; Alex W Barrington; Halle E Foss; Tucker Keuter; Sarah L Hurrell; William A See; Marja T Nevalainen; Anjishnu Banerjee; Peter S LaViolette
Journal:  Tomography       Date:  2019-03

5.  Objective risk stratification of prostate cancer using machine learning and radiomics applied to multiparametric magnetic resonance images.

Authors:  Bino Varghese; Frank Chen; Darryl Hwang; Suzanne L Palmer; Andre Luis De Castro Abreu; Osamu Ukimura; Monish Aron; Manju Aron; Inderbir Gill; Vinay Duddalwar; Gaurav Pandey
Journal:  Sci Rep       Date:  2019-02-07       Impact factor: 4.379

6.  Automated multiparametric localization of prostate cancer based on B-mode, shear-wave elastography, and contrast-enhanced ultrasound radiomics.

Authors:  Rogier R Wildeboer; Christophe K Mannaerts; Ruud J G van Sloun; Lars Budäus; Derya Tilki; Hessel Wijkstra; Georg Salomon; Massimo Mischi
Journal:  Eur Radiol       Date:  2019-10-10       Impact factor: 5.315

Review 7.  Evolution of prostate MRI: from multiparametric standard to less-is-better and different-is better strategies.

Authors:  Rossano Girometti; Lorenzo Cereser; Filippo Bonato; Chiara Zuiani
Journal:  Eur Radiol Exp       Date:  2019-01-28

8.  Evaluation of a multiparametric MRI radiomic-based approach for stratification of equivocal PI-RADS 3 and upgraded PI-RADS 4 prostatic lesions.

Authors:  Valentina Brancato; Marco Aiello; Luca Basso; Serena Monti; Luigi Palumbo; Giuseppe Di Costanzo; Marco Salvatore; Alfonso Ragozzino; Carlo Cavaliere
Journal:  Sci Rep       Date:  2021-01-12       Impact factor: 4.379

9.  Variability in accuracy of prostate cancer segmentation among radiologists, urologists, and scientists.

Authors:  Michael Y Chen; Maria A Woodruff; Prokar Dasgupta; Nicholas J Rukin
Journal:  Cancer Med       Date:  2020-08-18       Impact factor: 4.452

10.  Whole-Volume Tumor MRI Radiomics for Prognostic Modeling in Endometrial Cancer.

Authors:  Kristine E Fasmer; Erlend Hodneland; Julie A Dybvik; Kari Wagner-Larsen; Jone Trovik; Øyvind Salvesen; Camilla Krakstad; Ingfrid H S Haldorsen
Journal:  J Magn Reson Imaging       Date:  2020-11-16       Impact factor: 4.813
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