Predicting cancer outcomes with radiomics and artificial intelligence in radiology

K Bera, N Braman, A Gupta, V Velcheti… - Nature reviews Clinical …, 2022 - nature.com
The successful use of artificial intelligence (AI) for diagnostic purposes has prompted the
application of AI-based cancer imaging analysis to address other, more complex, clinical …

Radiomics and radiogenomics in gliomas: a contemporary update

G Singh, S Manjila, N Sakla, A True, AH Wardeh… - British journal of …, 2021 - nature.com
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 …

Biomass seaweed-derived nitrogen self-doped porous carbon anodes for sodium-ion batteries: Insights into the structure and electrochemical activity

C Senthil, JW Park, N Shaji, GS Sim, CW Lee - Journal of Energy Chemistry, 2022 - Elsevier
Sustainable transformation and efficient utilization of biomasses and their derived materials
are environmentally as well as economically compliant strategies. Biomass seaweed …

Introduction to radiomics and radiogenomics in neuro-oncology: implications and challenges

N Beig, K Bera, P Tiwari - Neuro-Oncology Advances, 2020 - academic.oup.com
Neuro-oncology largely consists of malignancies of the brain and central nervous system
including both primary as well as metastatic tumors. Currently, a significant clinical …

MR elastography in cancer

J Guo, LJ Savic, KH Hillebrandt, I Sack - Investigative Radiology, 2023 - journals.lww.com
The mechanical traits of cancer include abnormally high solid stress as well as drastic and
spatially heterogeneous changes in intrinsic mechanical tissue properties. Whereas solid …

Structural connectome quantifies tumour invasion and predicts survival in glioblastoma patients

Y Wei, C Li, Z Cui, RC Mayrand, J Zou, ALKC Wong… - Brain, 2023 - academic.oup.com
Glioblastoma is characterized by diffuse infiltration into the surrounding tissue along white
matter tracts. Identifying the invisible tumour invasion beyond focal lesion promises more …

Multi-modal learning for predicting the genotype of glioma

Y Wei, X Chen, L Zhu, L Zhang… - … on Medical Imaging, 2023 - ieeexplore.ieee.org
The isocitrate dehydrogenase (IDH) gene mutation is an essential biomarker for the
diagnosis and prognosis of glioma. It is promising to better predict glioma genotype by …

Prediction of survival of glioblastoma patients using local spatial relationships and global structure awareness in FLAIR MRI brain images

MT Tran, HJ Yang, SH Kim, GS Lee - IEEE Access, 2023 - ieeexplore.ieee.org
This article introduces a framework for predicting the survival of brain tumor patients by
analyzing magnetic resonance images. The prediction of brain tumor survival is challenging …

Pretreatment MR-based radiomics in patients with glioblastoma: A systematic review and meta-analysis of prognostic endpoints

Y Choi, J Jang, B Kim, KJ Ahn - European Journal of Radiology, 2023 - Elsevier
Purpose Recent studies have shown promise of MR-based radiomics in predicting the
survival of patients with untreated glioblastoma. This study aimed to comprehensively collate …

Predicting survival of glioblastoma from automatic whole-brain and tumor segmentation of MR images

S Pálsson, S Cerri, HS Poulsen, T Urup, I Law… - Scientific Reports, 2022 - nature.com
Survival prediction models can potentially be used to guide treatment of glioblastoma
patients. However, currently available MR imaging biomarkers holding prognostic …