Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study.
Journal:
The Lancet. Digital health
Published Date:
Oct 20, 2021
Abstract
BACKGROUND: Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after repeated GBCA administration with yet unknown clinical significance. We aimed to assess the feasibility and diagnostic value of synthetic post-contrast T1-weighted MRI generated from pre-contrast MRI sequences through deep convolutional neural networks (dCNN) for tumour response assessment in neuro-oncology.
Authors
Keywords
Algorithms
Brain
Brain Neoplasms
Contrast Media
Deep Learning
Diffusion Magnetic Resonance Imaging
Disease Progression
Feasibility Studies
Gadolinium
Germany
Glioblastoma
Humans
Magnetic Resonance Imaging
Middle Aged
Neoplasms
Neural Networks, Computer
Prognosis
Radiology
Retrospective Studies
Tumor Burden