[HTML][HTML] Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology
Medical image processing and analysis (also known as Radiomics) is a rapidly growing
discipline that maps digital medical images into quantitative data, with the end goal of …
discipline that maps digital medical images into quantitative data, with the end goal of …
Quantitative imaging of cancer in the postgenomic era: Radio (geno) mics, deep learning, and habitats
Although cancer often is referred to as “a disease of the genes,” it is indisputable that the
(epi) genetic properties of individual cancer cells are highly variable, even within the same …
(epi) genetic properties of individual cancer cells are highly variable, even within the same …
Radiomics-based machine learning model for efficiently classifying transcriptome subtypes in glioblastoma patients from MRI
Background In the field of glioma, transcriptome subtypes have been considered as an
important diagnostic and prognostic biomarker that may help improve the treatment efficacy …
important diagnostic and prognostic biomarker that may help improve the treatment efficacy …
MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma
L Zhao, J Gong, Y Xi, M Xu, C Li, X Kang, Y Yin… - European …, 2020 - Springer
Objectives To establish and validate a radiomics nomogram for prediction of induction
chemotherapy (IC) response and survival in nasopharyngeal carcinoma (NPC) patients …
chemotherapy (IC) response and survival in nasopharyngeal carcinoma (NPC) patients …
The rise of radiomics and implications for oncologic management
V Verma, CB Simone, S Krishnan, SH Lin… - JNCI: Journal of the …, 2017 - academic.oup.com
Clinical medicine, particularly oncology, is progressing toward personalized care. Whereas
the terms genomics, proteomics, transcriptomics, and metabolomics have dominated …
the terms genomics, proteomics, transcriptomics, and metabolomics have dominated …
Radiomics in radiooncology–challenging the medical physicist
Purpose Noticing the fast growing translation of artificial intelligence (AI) technologies to
medical image analysis this paper emphasizes the future role of the medical physicist in this …
medical image analysis this paper emphasizes the future role of the medical physicist in this …
High-order radiomics features based on T2 FLAIR MRI predict multiple glioma immunohistochemical features: a more precise and personalized gliomas management
J Li, S Liu, Y Qin, Y Zhang, N Wang, H Liu - PLoS One, 2020 - journals.plos.org
Objective To investigate the performance of high-order radiomics features and models
based on T2-weighted fluid-attenuated inversion recovery (T2 FLAIR) in predicting the …
based on T2-weighted fluid-attenuated inversion recovery (T2 FLAIR) in predicting the …
[HTML][HTML] Radiomics in glioblastoma: current status, challenges and potential opportunities
Gliomas are tumors which develop in the brain, the most aggressive of which is glioblastoma
multiforme (GBM). Despite extensive research to better understand the underlying biology of …
multiforme (GBM). Despite extensive research to better understand the underlying biology of …
Advanced MRI techniques in the monitoring of treatment of gliomas
Opinion statement With advances in treatments and survival of patients with glioblastoma
(GBM), it has become apparent that conventional imaging sequences have significant …
(GBM), it has become apparent that conventional imaging sequences have significant …
Spatiotemporal heterogeneity in multiparametric physiologic MRI is associated with patient outcomes in IDH-wildtype glioblastoma
JE Park, HS Kim, NY Kim, SY Park, YH Kim… - Clinical Cancer Research, 2021 - AACR
Purpose: Heterogeneity in glioblastomas is associated with poorer outcomes, and
physiologic heterogeneity can be quantified with noninvasive imaging. We developed …
physiologic heterogeneity can be quantified with noninvasive imaging. We developed …