Radiomics and radiogenomics in gliomas: a contemporary update
The natural history and treatment landscape of primary brain tumours are complicated by the
varied tumour behaviour of primary or secondary gliomas (high-grade transformation of low …
varied tumour behaviour of primary or secondary gliomas (high-grade transformation of low …
Beyond imaging: the promise of radiomics
The domain of investigation of radiomics consists of large-scale radiological image analysis
and association with biological or clinical endpoints. The purpose of the present study is to …
and association with biological or clinical endpoints. The purpose of the present study is to …
A radiomics nomogram for the preoperative prediction of lymph node metastasis in bladder cancer
S Wu, J Zheng, Y Li, H Yu, S Shi, W Xie, H Liu… - Clinical Cancer …, 2017 - AACR
Purpose: To develop and validate a radiomics nomogram for the preoperative prediction of
lymph node (LN) metastasis in bladder cancer. Experimental Design: A total of 118 eligible …
lymph node (LN) metastasis in bladder cancer. Experimental Design: A total of 118 eligible …
Multiclass magnetic resonance imaging brain tumor classification using artificial intelligence paradigm
GS Tandel, A Balestrieri, T Jujaray, NN Khanna… - Computers in Biology …, 2020 - Elsevier
Motivation Brain or central nervous system cancer is the tenth leading cause of death in men
and women. Even though brain tumour is not considered as the primary cause of mortality …
and women. Even though brain tumour is not considered as the primary cause of mortality …
Radiomics in brain tumor: image assessment, quantitative feature descriptors, and machine-learning approaches
Radiomics describes a broad set of computational methods that extract quantitative features
from radiographic images. The resulting features can be used to inform imaging diagnosis …
from radiographic images. The resulting features can be used to inform imaging diagnosis …
An ensemble learning approach for brain cancer detection exploiting radiomic features
Abstract Background and Objective The brain cancer is one of the most aggressive tumour:
the 70% of the patients diagnosed with this malignant cancer will not survive. Early detection …
the 70% of the patients diagnosed with this malignant cancer will not survive. Early detection …
[HTML][HTML] Novel, non-invasive imaging approach to identify patients with advanced non-small cell lung cancer at risk of hyperprogressive disease with immune …
Purpose Hyperprogression is an atypical response pattern to immune checkpoint inhibition
that has been described within non-small cell lung cancer (NSCLC). The paradoxical …
that has been described within non-small cell lung cancer (NSCLC). The paradoxical …
Multicenter study demonstrates radiomic features derived from magnetic resonance perfusion images identify pseudoprogression in glioblastoma
Pseudoprogression (PsP) is a diagnostic clinical dilemma in cancer. In this study, we
retrospectively analyse glioblastoma patients, and using their dynamic susceptibility contrast …
retrospectively analyse glioblastoma patients, and using their dynamic susceptibility contrast …
Machine learning for the prediction of molecular markers in glioma on magnetic resonance imaging: a systematic review and meta-analysis
BACKGROUND Molecular characterization of glioma has implications for prognosis,
treatment planning, and prediction of treatment response. Current histopathology is limited …
treatment planning, and prediction of treatment response. Current histopathology is limited …
Pediatric brain tumor genetics: what radiologists need to know
J AlRayahi, M Zapotocky, V Ramaswamy… - Radiographics, 2018 - pubs.rsna.org
Brain tumors are the most common solid tumors in the pediatric population. Pediatric neuro-
oncology has changed tremendously during the past decade owing to ongoing genomic …
oncology has changed tremendously during the past decade owing to ongoing genomic …