Size Distribution Imaging by Non-Uniform Oscillating-Gradient Spin Echo (NOGSE) MRI

Abstract

Objects making up complex porous systems in Nature usually span a range of sizes. These size distributions play fundamental roles in defining the physicochemical, biophysical and physiological properties of a wide variety of systems – ranging from advanced catalytic materials to Central Nervous System diseases. Accurate and noninvasive measurements of size distributions in opaque, three-dimensional objects, have thus remained long-standing and important challenges. Herein we describe how a recently introduced diffusion-based magnetic resonance methodology, Non-Uniform-Oscillating-Gradient-Spin-Echo (NOGSE), can determine such distributions noninvasively. The method relies on its ability to probe confining lengths with a (length)6 parametric sensitivity, in a constant-time, constant-number-of-gradients fashion; combined, these attributes provide sufficient sensitivity for characterizing the underlying distributions in μm-scaled cellular systems. Theoretical derivations and simulations are presented to verify NOGSE’s ability to faithfully reconstruct size distributions through suitable modeling of their distribution parameters. Experiments in yeast cell suspensions – where the ground truth can be determined from ancillary microscopy – corroborate these trends experimentally. Finally, by appending to the NOGSE protocol an imaging acquisition, novel MRI maps of cellular size distributions were collected from a mouse brain. The ensuing micro-architectural contrasts successfully delineated distinctive hallmark anatomical sub-structures, in both white matter and gray matter tissues, in a non-invasive manner. Such findings highlight NOGSE’s potential for characterizing aberrations in cellular size distributions upon disease, or during normal processes such as development.

Quantum Sensing of Noisy and Complex Systems under Dynamical Control

“…Such probes may operate at nanoscales, as magnetometers, thermometers, sensors for imaging or monitoring chemical and biological processes [9,[14][15][16][17][18][19].…”

“…Furthermore, this control may be optimized based on quantum estimation theory to infer the bath characteristics with the ultimate precision that this theory allows [9] and to selectively address key parameters by filtering out other sources of decoherence [14][15][16][17][18][19].…”

“…We therefore nicknamed the method "selective dynamical recoupling" (SDR) [14,16]. We have already implemented SDR to selectively monitor diffusion processes characterized by Equation (35) with α = 2 and A α = π −1 , so as to determine the probe-environment coupling strengths [18] and the environmental correlation time, as well as diffusion restriction lengths [16,17,19] in systems of biological and chemical interest.…”

“…This, however, is a laborious and time-consuming undertaking. Instead, it may suffice to record only a few parameters of the noise that provide a distinct signature of the bath: the bath structure and the dynamics of the underlying processes (e.g., diffusion, collisions and thermal fluctuations [9,[14][15][16][17][18][19]). We show here that such tasks may be accomplished with high fidelity or success probability by subjecting the probe to an appropriate dynamical control that may turn a sub-optimal into a fully optimal probing/sensing process.…”

“…Noise-spectrum information obtainable by quantum probing/sensing is particularly important not only for QI processing [10][11][12][20][21][22] and quantum metrology [23][24][25][26][27] but also for the design of quantum thermal (heat) machines [28][29][30][31][32][33] and, most intriguingly, for biomedical diagnostics based on NMR and MRI [11,[14][15][16][17][18][19].…”