Meetings

Rashed Sobhan(1), Donnie Cameron(1,2) (1)Norwich Medical School, University of East Anglia, Norwich, United Kingdom; (2) C.J. Gorter Centre for High Field MRI, Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands

Title:

Brain imaging with Gadolinium-based contrast agents: Applications to cerebral perfusion and blood-brain-barrier permeability

Abstract:

Contrast-agent-based brain MRI involves injecting Gadolinium-based contrast agents (GBCA) into the blood stream and tracking their passage in the brain. There are two main variants for GBCA-based MRI: dynamic susceptibility contrast (DSC)- and dynamic contrast enhanced (DCE)-MRI. This presentation will cover our research on both of these modalities.

In DSC-MRI, T2/T2*-weighted imaging is used to quantify cerebral perfusion parameters to provide crucial information for diagnosis, assessment, treatment planning, and monitoring of glioma, ischaemic stroke, multiple sclerosis, and Alzheimer’s disease. DCE-MRI, on the other hand, uses T1-weighted imaging to capture extravasation of GBCA from the ‘leaky’ blood brain barrier (BBB), and can be used to assess the severity and progression of Alzheimer’s disease and cerebral small vessel diseases, and monitor treatment effectiveness in these conditions.

Typical DSC-MRI analysis can be time-consuming and subjective, with inconsistent outcomes due to dependence on manual Radiologist input and a noise-prone analysis. In our work, we aimed to mitigate these drawbacks through automation and model-dependent analysis. We evaluated the most effective time-series features for automatic arterial voxel detection; explored feature-based time-series clustering for automatic region segmentation; and compared the utility of four possible models for DSC-MRI analysis.

In our DCE-MRI research, we compared subtle BBB leakage in two groups representing early indicators of Alzheimer’s and dementia: mild cognitive impairment (MCI) and subjective memory impairment (SMI). Our aim was to investigate whether permeability in SMI can provide an early indication of BBB damage. Further, we investigated the influence of an omega-3 fatty acid flavonoid (OM3FLAV) supplement on BBB leakage for SMI patients. Our results show that SMI and MCI participants tend to have similar BBB permeability, and the intervention tended to decrease BBB leakage.

Further improvements to our exploratory investigations can assist in establishing an end-to-end automated DSC-MRI analysis pipeline and indicate the potential of permeability measures as early markers of MCI.

Luca Vizioli, The Center for Magnetic Resonance Research (CMRR) , University of Minnesota. As Luca is based in the US, this was an online meeting.

Title:

Suppressing Thermal Noise in fMRI using NORDIC

Abstract:

Functional Magnetic Resonance Imaging (fMRI) based on Blood Oxygenation Level Dependent (BOLD) contrast is an indispensable tool for studying the human brain. At ultrahigh field (UHF), it is possible to acquire submillimeter BOLD images, allowing studying mesoscopic scale neuronal organizations. However, fMRI’s signal-to-noise (SNR) and functional contrast-to-noise ratios (fCNR) remain quite low, especially for high resolution images, significantly limiting its applications. We tackle SNR and fCNR limitations using a denoising technique, Noise Reduction with Distribution Corrected (NORDIC) PCA, which operates on repetitively acquired imaging data. NORDIC removes components that cannot be distinguished from zero-mean Gaussian distributed noise, such as thermal noise, inherent in the MR measurement and a dominant noise source in submillimeter fMRI data at 7T (also significantly impairing 3Tesla studies with 1-3 mm isotropic voxels dimensions). We evaluated NORDIC on a variety of fMRI acquisition protocols (such as those of the Human Connectome Project) varying in spatio-temporal resolutions (ranging spatially from 2 mm to .5 mm iso voxels; temporally from 800 ms to 3652 ms TRs), experimental paradigms (visual and auditory block and event related designs) and field strengths (3T and 7T). Our data confirm that, regardless of field strength, experimental paradigm and acquisition protocol, NORDIC denoising removes thermal noise and markedly improves metrics of functional activation detection, while crucially preserving spatial functional precision. We further show that using NORDIC, we can record reliable BOLD functional maps with unprecedented spatial precision (e.g. 0.5 mm iso voxels), unachievable otherwise. Moreover, NORDIC’s larger cross-validated R2 reflects higher prediction accuracy for unseen data and therefore increased reproducibility. The cumulative gains that can be realized by employing NORDIC denoising will enable transformative improvements in fMRI, permitting more precise quantification of functional responses, robust studies of mesoscopic scale organizations, faster acquisitions rates, and/or significantly shorter scan times.