Prospects for the application of radiomics to brain tumors

Radiomics is a new branch in diagnostics based on a quantitative approach to medical imaging able to ensure more efficient use of medical equipment, optimize imaging time per patient, and increase the accuracy of differential diagnostics in various areas of medicine. Radiogenomics is a branch of radionics intended to establish a connection between the patient’s genotype and phenotypic presentation obtained from medical imaging. The review dwells on general issues for radiomics and radiogenomics in oncology with the recent study findings, focusing on the role of these methods in neurooncology and solving problems in diagnosing brain tumors. One of the current topics in neurooncology is disease prognosis in patients with unverified midline gliomas because morphological confirmation of the diagnosis and molecular genetic testing of tissues is impossible. Besides, the high spatial and temporal heterogeneity of malignant neoplasms prevents a complete assessment of the biological properties of the tumor and even using stereotactic biopsy methods. Radiomics methods can help doctors differentiate the tumor grade, acting as a “virtual biopsy” while avoiding invasive procedures. The study findings on radiomics and radiogenomics in neurooncology indicate the undeniable promise of these methods; however, as in other areas of medicine and biology, errors cannot be completely excluded, so the expert team must aim to minimize them.

Authors

Institutions

Publication Details

Journal
Digital Diagnostics
Published
2024-10-16
DOI
https://doi.org/10.17816/dd625382
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prospects for the application of radiomics to brain tumors

Р. А. Пархоменко, Н. И. Сергеев, O. S. Regentova, V. А. Solodkiy et al.
Digital Diagnostics
Radiomics and Machine Learning in Medical Imaging
article

Prospects for the application of radiomics to brain tumors

Р. А. Пархоменко, Н. И. Сергеев, O. S. Regentova, V. А. Solodkiy, P. V. Polushkin, K. V. Bozhenko
article en

Abstract

Radiomics is a new branch in diagnostics based on a quantitative approach to medical imaging able to ensure more efficient use of medical equipment, optimize imaging time per patient, and increase the accuracy of differential diagnostics in various areas of medicine. Radiogenomics is a branch of radionics intended to establish a connection between the patient’s genotype and phenotypic presentation obtained from medical imaging. The review dwells on general issues for radiomics and radiogenomics in oncology with the recent study findings, focusing on the role of these methods in neurooncology and solving problems in diagnosing brain tumors. One of the current topics in neurooncology is disease prognosis in patients with unverified midline gliomas because morphological confirmation of the diagnosis and molecular genetic testing of tissues is impossible. Besides, the high spatial and temporal heterogeneity of malignant neoplasms prevents a complete assessment of the biological properties of the tumor and even using stereotactic biopsy methods. Radiomics methods can help doctors differentiate the tumor grade, acting as a “virtual biopsy” while avoiding invasive procedures. The study findings on radiomics and radiogenomics in neurooncology indicate the undeniable promise of these methods; however, as in other areas of medicine and biology, errors cannot be completely excluded, so the expert team must aim to minimize them.

Digital DiagnosticsVol. 5(3)
Peoples' Friendship University of Russia (RU), Federal State Budgetary Institution Russian Scientific Center of Roentgenoradiology (RU), Ministry of Health of the Russian Federation (RU)
Good health and well-being
Openalex Percentile: Top 70%
Radiomics and Machine Learning in Medical Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Prospects for the application of radiomics to brain tumors — Р. А. Пархоменко, Н. И. Сергеев, et al. · Digital Diagnostics (2024) | TGRS Research Map | TGRS