Faculty Bibliography

BACKGROUND AND PURPOSE/OBJECTIVE:Na) MRI provides unique information about ionic homeostasis in the brain. However, in vivo quantification of regional brain sodium is highly challenging due to low SNR and limited spatial resolution. Here, we employ our novel anatomically guided reconstruction (AGR) method to overcome these challenges and enable precise quantification of regional brain total sodium concentration (TSC). MATERIALS AND METHODS/METHODS:< 0.05. RESULTS:. CONCLUSIONS:The AGR helps sodium quantification in healthy human brains by reducing the partial volume effect and variance of TSC in non-cortical brain regions. Our normative values of TSC in the brain regions set the stage to better understand derangements of sodium metabolism and homeostasis in neurological disease. ABBREVIATIONS/BACKGROUND:= sodium-potassium pump; PVC= partial volume correction; PVE= partial volume effect; TSC= total sodium concentration; VH= vitreous humor.

Sodium magnetic resonance imaging (MRI) is highly sensitive to cellular ionic balance due to tenfold difference in sodium concentration across membranes, actively maintained by the sodium-potassium (Na⁺-K⁺) pump. Disruptions in this pump or membrane integrity, as seen in neurological disorders like epilepsy, multiple sclerosis, bipolar disease, and mild traumatic brain injury, lead to increased intracellular sodium. However, this cellular-level alteration is often masked by the dominant extracellular sodium signal, making it challenging to distinguish sodium populations with mono- vs. bi-exponential transverse (T₂) decays-especially given the low signal-to-noise ratio (SNR) even at an advanced clinical field of 3 Tesla. Here, we propose a novel technique that leverages intrinsic difference in T₂ decays by acquiring single-quantum images at multiple echo times (TEs) and applying voxel-wise matrix inversion for accurate signal separation. Using numerical models, agar phantoms, and human subjects, we achieved high separation accuracy in phantoms (95.8% for mono-T₂ and 72.5-80.4% for bi-T₂) and demonstrated clinical feasibility in humans. This approach may enable early detection of neurological disorders and early assessment of treatment responses at the cellular level using sodium MRI at 3 T.

PURPOSE/OBJECTIVE:Na images. METHODS:Na TPI brain datasets of healthy controls acquired on a 3T Siemens Prisma system were reconstructed using conventional reconstruction, AGR and AGRdm. RESULTS:Our simulations show that compared to conventional reconstructions, AGR and AGRdm show improved bias-noise characteristics in several regions of the brain. Moreover, AGR and AGRdm images show more anatomical detail and less noise in the reconstructions of the experimental data sets. Compared to AGR and the conventional reconstruction, AGRdm shows higher contrast in the sodium concentration ratio between gray and white matter and between gray matter and the brain stem. CONCLUSION/CONCLUSIONS:Na MR imaging at 3T.

PURPOSE/OBJECTIVE:The accuracy of diffusion MRI tractography reconstruction decreases in the white matter regions with crossing fibers. The optic pathways in rodents provide a challenging structure to test new diffusion tractography approaches because of the small crossing volume within the optic chiasm and the unbalanced 9:1 proportion between the contra- and ipsilateral neural projections from the retina to the lateral geniculate nucleus, respectively. METHODS: RESULTS:ODF-FP outperformed by over 100% all the tested methods in terms of the ratios between the contra- and ipsilateral segments of the reconstructed optic pathways as well as the spatial overlap between tractography and MEMRI. CONCLUSION/CONCLUSIONS:In this challenging model system, ODF-Fingerprinting reduced uncertainty of diffusion tractography for complex structural formations of fiber bundles.

Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations. The results of the challenge suggest that methods selected by the 14 teams participating in the challenge can provide high correlations between estimated and ground-truth connectivity weights, in complex numerical environments. Additionally, the methods used by the participating teams were able to accurately identify the binary connectivity of the numerical dataset. However, specific false positive and false negative connections were consistently estimated across all methods. Although the challenge dataset doesn't capture the complexity of a real brain, it provided unique data with known macrostructure and microstructure ground-truth properties to facilitate the development of connectivity estimation methods.

White matter fiber reconstructions based on seeking local maxima of Orientation Distribution Functions (ODFs) typically fail to identify fibers crossing at narrow angles below 45°. ODF-Fingerprinting (ODF-FP) replaces the ODF maxima localization mechanism with pattern matching, allowing the use of all information stored in ODFs. In this work, we study the ability of ODF-FP to reconstruct fibers crossing at varied angles spanning 10°-90° in physical diffusion phantoms composed of textile tubes with 0.8μm diameter, approaching the anatomical scale of axons. Our results show that ODF-FP is able to correctly identify 80 ± 8% of the crossing fibers regardless of the crossing angle and provide the highest average reconstruction accuracy.

Fitting of the multicompartment biophysical model of white matter is an ill-posed optimization problem. One approach to make it computationally tractable is through Orientation Distribution Function (ODF) Fingerprinting. However, the accuracy of this method relies solely on ODF dictionary generation mechanisms which either sample the microstructure parameters on a multidimensional grid or draw them randomly with a uniform distribution. In this paper, we propose a stepwise stochastic adaptation mechanism to generate ODF dictionaries tailored specifically to the diffusion-weighted images in hand. The results we obtained on a diffusion phantom and in vivo human brain images show that our reconstructed diffusivities are less noisy and the separation of a free water fraction is more pronounced than for the prior (uniform) distribution of ODF dictionaries.

PURPOSE/OBJECTIVE:Orientation Distribution Function (ODF) peak finding methods typically fail to reconstruct fibers crossing at shallow angles below 40°, leading to errors in tractography. ODF-Fingerprinting (ODF-FP) with the biophysical multicompartment diffusion model allows for breaking this barrier. METHODS:A randomized mechanism to generate a multidimensional ODF-dictionary that covers biologically plausible ranges of intra- and extra-axonal diffusivities and fraction volumes is introduced. This enables ODF-FP to address the high variability of brain tissue. The performance of the proposed approach is evaluated on both numerical simulations and a reconstruction of major fascicles from high- and low-resolution in vivo diffusion images. RESULTS:ODF-FP with the suggested modifications correctly identifies fibers crossing at angles as shallow as 10 degrees in the simulated data. In vivo, our approach reaches 56% of true positives in determining fiber directions, resulting in visibly more accurate reconstruction of pyramidal tracts, arcuate fasciculus, and optic radiations than the state-of-the-art techniques. Moreover, the estimated diffusivity values and fraction volumes in corpus callosum conform with the values reported in the literature. CONCLUSION/CONCLUSIONS:The modified ODF-FP outperforms commonly used fiber reconstruction methods at shallow angles, which improves deterministic tractography outcomes of major fascicles. In addition, the proposed approach allows for linearization of the microstructure parameters fitting problem.

BACKGROUND: THE PURPOSE OF THE STUDY/OBJECTIVE:Na MRI dual echo relative to TSC imaging. METHODS:Na MRI) were assessed. RESULTS:Na MRI suppressed the sodium signal within both CSF and necrotic foci. CONCLUSION/CONCLUSIONS:Na MRI of BCS improves tissue conspicuity relative to TSC imaging.

Positron emission tomography and magnetic resonance imaging (PET/MRI) scanners cannot be qualified in the manner adopted for hybrid PET and computed tomography (CT) devices. The main hurdle with qualification in PET/MRI is that attenuation correction (AC) cannot be adequately measured in conventional PET phantoms due to the difficulty in converting the MRI images of the physical structures (e.g., plastic) into electron density maps. Over the last decade, a plethora of novel MR-based algorithms have been developed to more accurately derive the attenuation properties of the human head, including the skull. Although very promising, none of these techniques has yet emerged as an optimal and universally adopted strategy for AC in PET/MRI. In this work, we propose a path for PET/MRI qualification for multicenter brain imaging studies. Specifically, our solution is to separate the head attenuation correction from the other factors that affect PET data quantification and use a patient as a phantom to assess the former. The emission data collected on the integrated PET/MRI scanner to be qualified should be reconstructed using both MR- and CT-based AC methods and whole-brain qualitative and quantitative (both voxel-wise and regional) analyses should be performed. The MR-based approach will be considered satisfactory if the PET quantification bias is within the acceptance criteria specified herein. We have implemented this approach successfully across two PET/MRI scanner manufacturers at two sites.