Literature DB >> 34649914

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

M Ak1,2, S A Toll3, K Z Hein4, R R Colen1,2, S Khatua5.   

Abstract

Exponential technologic advancements in imaging, high-performance computing, and artificial intelligence, in addition to increasing access to vast amounts of diverse data, have revolutionized the role of imaging in medicine. Radiomics is defined as a high-throughput feature-extraction method that unlocks microscale quantitative data hidden within standard-of-care medical imaging. Radiogenomics is defined as the linkage between imaging and genomics information. Multiple radiomics and radiogenomics studies performed on conventional and advanced neuro-oncology image modalities show that they have the potential to differentiate pseudoprogression from true progression, classify tumor subgroups, and predict recurrence, survival, and mutation status with high accuracy. In this article, we outline the technical steps involved in radiomics and radiogenomics analyses with the use of artificial intelligence methods and review current applications in adult and pediatric neuro-oncology.
© 2022 by American Journal of Neuroradiology.

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Mesh:

Year:  2021        PMID: 34649914      PMCID: PMC9172943          DOI: 10.3174/ajnr.A7297

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   4.966


  87 in total

1.  Radiogenomics of Glioblastoma: Machine Learning-based Classification of Molecular Characteristics by Using Multiparametric and Multiregional MR Imaging Features.

Authors:  Philipp Kickingereder; David Bonekamp; Martha Nowosielski; Annekathrin Kratz; Martin Sill; Sina Burth; Antje Wick; Oliver Eidel; Heinz-Peter Schlemmer; Alexander Radbruch; Jürgen Debus; Christel Herold-Mende; Andreas Unterberg; David Jones; Stefan Pfister; Wolfgang Wick; Andreas von Deimling; Martin Bendszus; David Capper
Journal:  Radiology       Date:  2016-09-16       Impact factor: 11.105

Review 2.  Shedding Light on the 2016 World Health Organization Classification of Tumors of the Central Nervous System in the Era of Radiomics and Radiogenomics.

Authors:  Rivka R Colen; Islam Hassan; Nabil Elshafeey; Pascal O Zinn
Journal:  Magn Reson Imaging Clin N Am       Date:  2016-11       Impact factor: 2.266

3.  Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings.

Authors:  Prateek Prasanna; Jay Patel; Sasan Partovi; Anant Madabhushi; Pallavi Tiwari
Journal:  Eur Radiol       Date:  2016-10-24       Impact factor: 5.315

4.  In vivo evaluation of EGFRvIII mutation in primary glioblastoma patients via complex multiparametric MRI signature.

Authors:  Hamed Akbari; Spyridon Bakas; Jared M Pisapia; MacLean P Nasrallah; Martin Rozycki; Maria Martinez-Lage; Jennifer J D Morrissette; Nadia Dahmane; Donald M O'Rourke; Christos Davatzikos
Journal:  Neuro Oncol       Date:  2018-07-05       Impact factor: 12.300

5.  Quantitative imaging biomarkers for risk stratification of patients with recurrent glioblastoma treated with bevacizumab.

Authors:  Patrick Grossmann; Vivek Narayan; Ken Chang; Rifaquat Rahman; Lauren Abrey; David A Reardon; Lawrence H Schwartz; Patrick Y Wen; Brian M Alexander; Raymond Huang; Hugo J W L Aerts
Journal:  Neuro Oncol       Date:  2017-11-29       Impact factor: 12.300

6.  Machine Learning methods for Quantitative Radiomic Biomarkers.

Authors:  Chintan Parmar; Patrick Grossmann; Johan Bussink; Philippe Lambin; Hugo J W L Aerts
Journal:  Sci Rep       Date:  2015-08-17       Impact factor: 4.379

7.  Magnetic Resonance Imaging-Based Radiomic Profiles Predict Patient Prognosis in Newly Diagnosed Glioblastoma Before Therapy.

Authors:  Sean D McGarry; Sarah L Hurrell; Amy L Kaczmarowski; Elizabeth J Cochran; Jennifer Connelly; Scott D Rand; Kathleen M Schmainda; Peter S LaViolette
Journal:  Tomography       Date:  2016-09

8.  Radiomics analysis for predicting pembrolizumab response in patients with advanced rare cancers.

Authors:  Rivka R Colen; Christian Rolfo; Murat Ak; Mira Ayoub; Sara Ahmed; Nabil Elshafeey; Priyadarshini Mamindla; Pascal O Zinn; Chaan Ng; Raghu Vikram; Spyridon Bakas; Christine B Peterson; Jordi Rodon Ahnert; Vivek Subbiah; Daniel D Karp; Bettzy Stephen; Joud Hajjar; Aung Naing
Journal:  J Immunother Cancer       Date:  2021-04       Impact factor: 13.751

9.  3D Texture Analysis of Heterogeneous MRI Data for Diagnostic Classification of Childhood Brain Tumours.

Authors:  Ahmed E Fetit; Jan Novak; Daniel Rodriguez; Dorothee P Auer; Chris A Clark; Richard G Grundy; Tim Jaspan; Andrew C Peet; Theodoros N Arvanitis
Journal:  Stud Health Technol Inform       Date:  2015

10.  Association between Ki-67 Labeling index and Histopathological Grading of Glioma in Indonesian Population.

Authors:  Emilia Theresia; Rusdy Ghazali Malueka; Sofia Pranacipta; Bidari Kameswari; Kusumo Dananjoyo; Ahmad Asmedi; Adiguno Suryo Wicaksono; Rahmat Andi Hartanto; Ery Kus Dwianingsih
Journal:  Asian Pac J Cancer Prev       Date:  2020-04-01
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  3 in total

1.  Pre-operative MRI radiomics model non-invasively predicts key genomic markers and survival in glioblastoma patients.

Authors:  Mathew Pease; Zachary C Gersey; R R Colen; P O Zinn; Murat Ak; Ahmed Elakkad; Aikaterini Kotrotsou; Serafettin Zenkin; Nabil Elshafeey; Priyadarshini Mamindla; Vinodh A Kumar; Ashok J Kumar
Journal:  J Neurooncol       Date:  2022-10-14       Impact factor: 4.506

Review 2.  Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine.

Authors:  Sanjay Saxena; Biswajit Jena; Neha Gupta; Suchismita Das; Deepaneeta Sarmah; Pallab Bhattacharya; Tanmay Nath; Sudip Paul; Mostafa M Fouda; Manudeep Kalra; Luca Saba; Gyan Pareek; Jasjit S Suri
Journal:  Cancers (Basel)       Date:  2022-06-09       Impact factor: 6.575

3.  18F-FDG PET/CT-based radiomics nomogram could predict bone marrow involvement in pediatric neuroblastoma.

Authors:  Lijuan Feng; Xu Yang; Xia Lu; Ying Kan; Chao Wang; Dehui Sun; Hui Zhang; Wei Wang; Jigang Yang
Journal:  Insights Imaging       Date:  2022-09-04
  3 in total

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