Literature DB >> 27742112

Radiomics in Brain Tumors: An Emerging Technique for Characterization of Tumor Environment.

Aikaterini Kotrotsou1, Pascal O Zinn2, Rivka R Colen3.   

Abstract

The role of radiomics in the diagnosis, monitoring, and therapy planning of brain tumors is becoming increasingly clear. Incorporation of quantitative approaches in radiology, in combination with increased computer power, offers unique insights into macroscopic tumor characteristics and their direct association with the underlying pathophysiology. This article presents the most recent findings in radiomics and radiogenomics with respect to identifying potential imaging biomarkers with prognostic value that can lead to individualized therapy. In addition, a brief introduction to the concept of big data and its significance in medicine is presented.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Big data; Brain tumors; Radiogenomics; Radiomics; Texture analysis

Mesh:

Year:  2016        PMID: 27742112     DOI: 10.1016/j.mric.2016.06.006

Source DB:  PubMed          Journal:  Magn Reson Imaging Clin N Am        ISSN: 1064-9689            Impact factor:   2.266


  27 in total

Review 1.  Novel Quantitative Imaging for Predicting Response to Therapy: Techniques and Clinical Applications.

Authors:  Kaustav Bera; Vamsidhar Velcheti; Anant Madabhushi
Journal:  Am Soc Clin Oncol Educ Book       Date:  2018-05-23

2.  MRI radiomics analysis of molecular alterations in low-grade gliomas.

Authors:  Ben Shofty; Moran Artzi; Dafna Ben Bashat; Gilad Liberman; Oz Haim; Alon Kashanian; Felix Bokstein; Deborah T Blumenthal; Zvi Ram; Tal Shahar
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-12-21       Impact factor: 2.924

3.  Preoperative Differentiation of Uterine Sarcoma from Leiomyoma: Comparison of Three Models Based on Different Segmentation Volumes Using Radiomics.

Authors:  Huihui Xie; Xiaodong Zhang; Shuai Ma; Yi Liu; Xiaoying Wang
Journal:  Mol Imaging Biol       Date:  2019-12       Impact factor: 3.488

Review 4.  Evolving Role and Translation of Radiomics and Radiogenomics in Adult and Pediatric Neuro-Oncology.

Authors:  M Ak; S A Toll; K Z Hein; R R Colen; S Khatua
Journal:  AJNR Am J Neuroradiol       Date:  2021-10-14       Impact factor: 4.966

Review 5.  Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches.

Authors:  M Zhou; J Scott; B Chaudhury; L Hall; D Goldgof; K W Yeom; M Iv; Y Ou; J Kalpathy-Cramer; S Napel; R Gillies; O Gevaert; R Gatenby
Journal:  AJNR Am J Neuroradiol       Date:  2017-10-05       Impact factor: 3.825

6.  Radiomics-based neural network predicts recurrence patterns in glioblastoma using dynamic susceptibility contrast-enhanced MRI.

Authors:  Ka Young Shim; Sung Won Chung; Jae Hak Jeong; Inpyeong Hwang; Chul-Kee Park; Tae Min Kim; Sung-Hye Park; Jae Kyung Won; Joo Ho Lee; Soon-Tae Lee; Roh-Eul Yoo; Koung Mi Kang; Tae Jin Yun; Ji-Hoon Kim; Chul-Ho Sohn; Kyu Sung Choi; Seung Hong Choi
Journal:  Sci Rep       Date:  2021-05-11       Impact factor: 4.379

7.  A Comprehensive Nomogram Combining CT Imaging with Clinical Features for Prediction of Lymph Node Metastasis in Stage I-IIIB Non-small Cell Lung Cancer.

Authors:  Xingxing Zheng; Jingjing Shao; Linli Zhou; Li Wang; Yaqiong Ge; Gaoren Wang; Feng Feng
Journal:  Ther Innov Regul Sci       Date:  2021-10-26       Impact factor: 1.778

8.  Glioblastoma and primary central nervous system lymphoma: differentiation using MRI derived first-order texture analysis - a machine learning study.

Authors:  Sarv Priya; Caitlin Ward; Thomas Locke; Neetu Soni; Ravishankar Pillenahalli Maheshwarappa; Varun Monga; Amit Agarwal; Girish Bathla
Journal:  Neuroradiol J       Date:  2021-03-03

Review 9.  Magnetic Resonance Spectroscopy, Positron Emission Tomography and Radiogenomics-Relevance to Glioma.

Authors:  Gloria C Chiang; Ilhami Kovanlikaya; Changho Choi; Rohan Ramakrishna; Rajiv Magge; Dikoma C Shungu
Journal:  Front Neurol       Date:  2018-02-05       Impact factor: 4.003

10.  Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine.

Authors:  Kooresh I Shoghi; Cristian T Badea; Stephanie J Blocker; Thomas L Chenevert; Richard Laforest; Michael T Lewis; Gary D Luker; H Charles Manning; Daniel S Marcus; Yvonne M Mowery; Stephen Pickup; Ann Richmond; Brian D Ross; Anna E Vilgelm; Thomas E Yankeelov; Rong Zhou
Journal:  Tomography       Date:  2020-09
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