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.
Highlights
Cellular morphologies are intimately linked with biological functions in general, and with a tissue’s capacity to perform its physiological role in-vivo in particular
As a test of NOGSE’s ability to extract simple parameters to characterize size distributions– including their mean, peak and widths– signals were first simulated for five lognormal distributions P(l) distributed around a biologically-relevant size of lc = 2 μm, and possessing different distribution widths σ (Fig 1B; see Materials and Methods for details)
Excellent correspondence was observed when synthetic NOGSE data are given as input, and the originating size distributions are recovered by fitting (Fig 1C)
Summary
Cellular morphologies are intimately linked with biological functions in general, and with a tissue’s capacity to perform its physiological role in-vivo in particular. PLOS ONE | DOI:10.1371/journal.pone.0133201 July 21, 2015
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