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)

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Summary

Introduction

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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