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MicroCT optimisation for imaging fascicular anatomy in peripheral nerves.

ABSTRACT: BACKGROUND:Due to the lack of understanding of the fascicular organisation, vagus nerve stimulation (VNS) leads to unwanted off-target effects. Micro-computed tomography (microCT) can be used to trace fascicles from periphery and image fascicular anatomy. NEW METHOD:In this study, we present a simple and reproducible method for imaging fascicles in peripheral nerves with iodine staining and microCT for the determination of fascicular anatomy and organisation. RESULTS:At the determined optimal pre-processing steps and scanning parameters, the microCT protocol allowed for segmentation and tracking of fascicles within the nerves. This was achieved after 24 hours and 120 hours of staining with Lugol's solution (1% total iodine) for rat sciatic and pig vagus nerves, respectively, and the following scanning parameters: 4 ?m voxel size, 35 kVp energy, 114 ?A current, 4 W power, 0.25 fps in 4 s exposure time, 3176 projections and a molybdenum target. COMPARISON WITH EXISTING METHOD(S):This optimised method for imaging fascicles provides high-resolution, three-dimensional images and full imaging penetration depth not obtainable with methods typically used such as histology, magnetic resonance imaging and optical coherence tomography whilst obviating time-consuming pre-processing methods, the amount of memory required, destruction of the samples and the cost associated with current microCT methods. CONCLUSION:The optimised microCT protocol facilitates segmentation and tracking of the fascicles within the nerve. The resulting segmentation map of the functional anatomical organisation of the vagus nerve will enable selective VNS ultimately allowing for the avoidance of the off-target effects and improving its therapeutic efficacy.

SUBMITTER: Thompson N

PROVIDER: S-EPMC7181190 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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MicroCT optimisation for imaging fascicular anatomy in peripheral nerves.

Thompson Nicole N Ravagli Enrico E Mastitskaya Svetlana S Iacoviello Francesco F Aristovich Kirill K Perkins Justin J Shearing Paul R PR Holder David D

Journal of neuroscience methods 20200313

<h4>Background</h4>Due to the lack of understanding of the fascicular organisation, vagus nerve stimulation (VNS) leads to unwanted off-target effects. Micro-computed tomography (microCT) can be used to trace fascicles from periphery and image fascicular anatomy.<h4>New method</h4>In this study, we present a simple and reproducible method for imaging fascicles in peripheral nerves with iodine staining and microCT for the determination of fascicular anatomy and organisation.<h4>Results</h4>At the ...[more]

PMID: 32179090

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Project description:Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is a molecular imaging method that can be used to elucidate the small-molecule composition of tissues and map their spatial information using two-dimensional ion images. This technique has been used to investigate the molecular profiles of variety of tissues, including within the central nervous system, specifically the brain and spinal cord. To our knowledge, this technique has yet to be applied to tissues of the peripheral nervous system (PNS). Data generated from such analyses are expected to advance the characterization of these structures. The study aimed to: (i) establish whether DESI-MSI can discriminate the molecular characteristics of peripheral nerves and distinguish them from surrounding tissues and (ii) assess whether different peripheral nerve subtypes are characterized by unique molecular profiles. Four different nerves for which are known to carry various nerve fiber types were harvested from a fresh cadaveric donor: mixed, motor and sensory (sciatic and femoral); cutaneous, sensory (sural); and autonomic (vagus). Tissue samples were harvested to include the nerve bundles in addition to surrounding connective tissue. Samples were flash-frozen, embedded in optimal cutting temperature compound in cross-section, and sectioned at 14 μm. Following DESI-MSI analysis, identical tissue sections were stained with hematoxylin and eosin. In this proof-of-concept study, a combination of multivariate and univariate statistical methods was used to evaluate molecular differences between the nerve and adjacent tissue and between nerve subtypes. The acquired mass spectral profiles of the peripheral nerve samples presented trends in ion abundances that seemed to be characteristic of nerve tissue and spatially corresponded to the associated histology of the tissue sections. Principal component analysis (PCA) supported the separation of the samples into distinct nerve and adjacent tissue classes. This classification was further supported by the K-means clustering analysis, which showed separation of the nerve and background ions. Differences in ion expression were confirmed using ANOVA which identified statistically significant differences in ion expression between the nerve subtypes. The PCA plot suggested some separation of the nerve subtypes into four classes which corresponded with the nerve types. This was supported by the K-means clustering. Some overlap in classes was noted in these two clustering analyses. This study provides emerging evidence that DESI-MSI is an effective tool for metabolomic profiling of peripheral nerves. Our results suggest that peripheral nerves have molecular profiles that are distinct from the surrounding connective tissues and that DESI-MSI may be able to discriminate between nerve subtypes. DESI-MSI of peripheral nerves may be a valuable technique that could be used to improve our understanding of peripheral nerve anatomy and physiology. The ability to utilize ambient mass spectrometry techniques in real time could also provide an unprecedented advantage for surgical decision making, including in nerve-sparing procedures in the future.

Dataset Information

MicroCT optimisation for imaging fascicular anatomy in peripheral nerves.

Publications

MicroCT optimisation for imaging fascicular anatomy in peripheral nerves.

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