arXiv subjects

Ying-Chia Lin

Publications and source records attributed to Ying-Chia Lin.

4 recordsLinked to original sources

arXiv2026

Quantum Sensing MRI for Noninvasive Detection of Neuronal Electrical Activity in Human Brains

Neuronal electrical activity underlies human cognition including perception, attention, memory, language, and decision-making. Yet its direct, noninvasive measurement in the living human brain remains a fundamental challenge. Existing neuroimaging techniques, including electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI), are limited by trade-offs in sensitivity and spatial or temporal resolution. Here we propose quantum sensing MRI (qsMRI), a noninvasive approach that enables direct detection of neuronal firing-induced magnetic fields using a clinical MRI system. qsMRI exploits endogenous proton (1H) nuclear spins in water molecules as intrinsic quantum sensors and decodes time-resolved phase information from the free induction decay signals to infer neuronal magnetic fields. We validate qsMRI through simulations, phantom experiments, and human studies at rest and during motor tasks, and provide open experimental procedures to facilitate independent rigorous validation. We further present a case study demonstrating potential applications to neurological disorders. qsMRI represents, to our knowledge, the first-in-human application of quantum sensing on a clinical MRI platform and may lay the foundation for a non-BOLD functional imaging modality capable of probing neuronal firing dynamics in both cortical and deep brain regions.

physics.med-ph↗

arXiv2024

Multi-TE Single-Quantum Sodium (23Na) MRI: A Clinically Translatable Technique for Separation of Mono- and Bi-T2 Sodium Signals

Sodium magnetic resonance imaging (MRI) is sensitive and specific to ionic balance of cells owing to 10 fold difference in sodium concentration across membrane actively maintained by sodium potassium (Na+ K+) pump. Disruption of the pump and membrane integrity, as seen in neurological disorders such as epilepsy, multiple sclerosis, bipolar disease, and mild traumatic brain injury, leads to a large increase in intracellular sodium. Such a cellular level alteration is however overshadowed by large signal from extracellular sodium, leaving behind a long standing pursuit to separate signals from sodium exhibiting mono vs biexponential transverse (T2) decay under the inherent constraint of low signal to noise ratio even at advanced clinical field of 3 Tesla. Here we propose a novel technique that exploits intrinsic difference in their T2 decays by simply acquiring single quantum images at multiple echo times (TEs) and performing accurate matrix inversion at voxel. This approach was then investigated using numerical models, agar phantoms and human subjects, showing high accuracy of the separation in phantoms (95.8 percent for monoT2 and 72.5 to 80.4 percent for biT2) and clinical feasibility in humans. Thus, sodium MRI at 3T can now facilitate detection of neurological disorders early at cellular level and response to treatment as well. Keywords. sodium MRI, single quantum MRI, triple quantum MRI, neuroimaging, neurodegeneration

physics.med-ph↗

arXiv2019

Fingerprinting Orientation Distribution Functions in Diffusion MRI detects smaller crossing angles

Diffusion tractography is routinely used to study white matter architecture and brain connectivity in vivo. A key step for successful tractography of neuronal tracts is the correct identification of tract directions in each voxel. Here we propose a fingerprinting-based methodology to identify these fiber directions in Orientation Distribution Functions, dubbed ODF-Fingerprinting (ODF-FP). In ODF-FP, fiber configurations are selected based on the similarity between measured ODFs and elements in a pre-computed library. In noisy ODFs, the library matching algorithm penalizes the more complex fiber configurations. ODF simulations and analysis of bootstrapped partial and whole-brain in vivo datasets show that the ODF-FP approach improves the detection of fiber pairs with small crossing angles while maintaining fiber direction precision, which leads to better tractography results. Rather than focusing on the ODF maxima, the ODF-FP approach uses the whole ODF shape to infer fiber directions to improve the detection of fiber bundles with small crossing angle. The resulting fiber directions aid tractography algorithms in accurately displaying neuronal tracts and calculating brain connectivity.

physics.med-ph↗

arXiv2018

Low Rank plus Sparse Decomposition of ODFs for Improved Detection of Group-level Differences and Variable Correlations in White Matter

A novel approach is presented for group statistical analysis of diffusion weighted MRI datasets through voxelwise Orientation Distribution Functions (ODF). Recent advances in MRI acquisition make it possible to use high quality diffusion weighted protocols (multi-shell, large number of gradient directions) for routine in vivo study of white matter architecture. The dimensionality of these data sets is however often reduced to simplify statistical analysis. While these approaches may detect large group differences, they do not fully capitalize on all acquired image volumes. Incorporation of all available diffusion information in the analysis however risks biasing the outcome by outliers. Here we propose a statistical analysis method operating on the ODF, either the diffusion ODF or fiber ODF. To avoid outlier bias and reliably detect voxelwise group differences and correlations with demographic or behavioral variables, we apply the Low-Rank plus Sparse (L + S) matrix decomposition on the voxelwise ODFs which separates the sparse individual variability in the sparse matrix S whilst recovering the essential ODF features in the low-rank matrix L. We demonstrate the performance of this ODF L + S approach by replicating the established negative association between global white matter integrity and physical obesity in the Human Connectome dataset. The volume of positive findings agrees with and expands on the volume found by TBSS, Connectivity based fixel enhancement and Connectometry. In the same dataset we further localize the correlations of brain structure with neurocognitive measures such as fluid intelligence and episodic memory. The presented ODF L + S approach will aid in the full utilization of all acquired diffusion weightings leading to the detection of smaller group differences in clinically relevant settings as well as in neuroscience applications.

physics.med-ph↗