Contrast-enhanced MRI Synthesis Using 3D High-Resolution ConvNets

by   Chao Chen, et al.

Gadolinium-based contrast agents (GBCAs) have been widely used to better visualize disease in brain magnetic resonance imaging (MRI). However, gadolinium deposition within the brain and body has raised safety concerns about the use of GBCAs. Therefore, the development of novel approaches that can decrease or even eliminate GBCA exposure while providing similar contrast information would be of significant use clinically. For brain tumor patients, standard-of-care includes repeated MRI with gadolinium-based contrast for disease monitoring, increasing the risk of gadolinium deposition. In this work, we present a deep learning based approach for contrast-enhanced T1 synthesis on brain tumor patients. A 3D high-resolution fully convolutional network (FCN), which maintains high resolution information through processing and aggregates multi-scale information in parallel, is designed to map pre-contrast MRI sequences to contrast-enhanced MRI sequences. Specifically, three pre-contrast MRI sequences, T1, T2 and apparent diffusion coefficient map (ADC), are utilized as inputs and the post-contrast T1 sequences are utilized as target output. To alleviate the data imbalance problem between normal tissues and the tumor regions, we introduce a local loss to improve the contribution of the tumor regions, which leads to better enhancement results on tumors. Extensive quantitative and visual assessments are performed, with our proposed model achieving a PSNR of 28.24dB in the brain and 21.2dB in tumor regions. Our results suggests the potential of substituting GBCAs with synthetic contrast images generated via deep learning.


page 1

page 3

page 4

page 6

page 7

page 8


Fully-automated deep learning-powered system for DCE-MRI analysis of brain tumors

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays an ...

Substituting Gadolinium in Brain MRI Using DeepContrast

Cerebral blood volume (CBV) is a hemodynamic correlate of oxygen metabol...

Adaptive PromptNet For Auxiliary Glioma Diagnosis without Contrast-Enhanced MRI

Multi-contrast magnetic resonance imaging (MRI)-based automatic auxiliar...

The University of California San Francisco, Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Dataset

The University of California San Francisco Brain Metastases Stereotactic...

DS3-Net: Difficulty-perceived Common-to-T1ce Semi-Supervised Multimodal MRI Synthesis Network

Contrast-enhanced T1 (T1ce) is one of the most essential magnetic resona...

Multi-task Deep Learning for Cerebrovascular Disease Classification and MRI-to-PET Translation

Accurate quantification of cerebral blood flow (CBF) is essential for th...

Faithful Synthesis of Low-dose Contrast-enhanced Brain MRI Scans using Noise-preserving Conditional GANs

Today Gadolinium-based contrast agents (GBCA) are indispensable in Magne...

Please sign up or login with your details

Forgot password? Click here to reset