Cerebral blood volume (CBV) is a hemodynamic correlate of oxygen metabolism and reflects brain activity and function. High-resolution CBV maps can be generated using the steady-state gadolinium-enhanced MRI technique. Such a technique requires an intravenous injection of exogenous gadolinium based contrast agent (GBCA) and recent studies suggest that the GBCA can accumulate in the brain after frequent use. We hypothesize that endogenous sources of contrast might exist within the most conventional and commonly acquired structural MRI, potentially obviating the need for exogenous contrast. Here, we test this hypothesis by developing and optimizing a deep learning algorithm, which we call DeepContrast, in mice. We find that DeepContrast performs equally well as exogenous GBCA in mapping CBV of the normal brain tissue and enhancing glioblastoma. Together, these studies validate our hypothesis that a deep learning approach can potentially replace the need for GBCAs in brain MRI.
Cite
@article{arxiv.2001.05551,
title = {Substituting Gadolinium in Brain MRI Using DeepContrast},
author = {Haoran Sun and Xueqing Liu and Xinyang Feng and Chen Liu and Nanyan Zhu and Sabrina J. Gjerswold-Selleck and Hong-Jian Wei and Pavan S. Upadhyayula and Angeliki Mela and Cheng-Chia Wu and Peter D. Canoll and Andrew F. Laine and J. Thomas Vaughan and Scott A. Small and Jia Guo},
journal= {arXiv preprint arXiv:2001.05551},
year = {2020}
}