Browsing by Subject "Spinal cord"

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Open Access
Intestinal microbiota in patients with spinal cord injury
(Public Library of Science, 2016) Gungor, B.; Adiguzel, E.; Gursel, I.; Yilmaz, B.; Gursel, M.
Human intestinal flora comprises thousands of bacterial species. Growth and composition of intestinal microbiota is dependent on various parameters, including immune mechanisms, dietary factors and intestinal motility. Patients with spinal cord injury (SCI) frequently display neurogenic bowel dysfunction due to the absence of central nervous system control over the gastrointestinal system. Considering the bowel dysfunction and altered colonic transit time in patients with SCI, we hypothesized the presence of a significant change in the composition of their gut microbiome. The objective of this study was to characterize the gut microbiota in adult SCI patients with different types of bowel dysfunction. We tested our hypothesis on 30 SCI patients (15 upper motor neuron [UMN] bowel syndrome, 15 lower motor neuron [LMN] bowel syndrome) and 10 healthy controls using the 16S rRNA sequencing. Gut microbial patterns were sampled from feces. Independent of study groups, gut microbiota of the participants were dominated by Blautia, Bifidobacterium, Faecalibacterium and Ruminococcus. When we compared all study groups, Roseburia, Pseudobutyrivibrio, Dialister, Marvinbryantia and Megamonas appeared as the genera that were statistically different between groups. In comparison to the healthy group, total bacterial counts of Pseudobutyrivibrio, Dialister and Megamonas genera were significantly lower in UMN bowel dysfunction group. The total bacterial count of Marvinbryantia genus was significantly lower in UMN bowel dysfunction group when compared to the LMN group. Total bacterial counts of Roseburia, Pseudobutyrivibrio and Megamonas genera were significantly lower in LMN bowel dysfunction group when compared to healthy groups. Our results demonstrate for the first time that butyrate-producing members are specifically reduced in SCI patients when compared to healthy subjects. The results of this study would be of interest since to our knowledge, microbiome-associated studies targeting SCI patients are non-existent and the results might help explain possible implications of gut microbiome in SCI. Copyright © 2016 Gungor et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Open Access
Phase-correcting non-local means filtering for diffusion-weighted imaging of the spinal cord
(John Wiley, 2018) Kafalı, Sevgi Gökçe; Çukur, Tolga; Sarıtaş, Emine Ülkü
Purpose: DWI suffers from low SNR when compared to anatomical MRI. To maintain reasonable SNR at relatively high spatial resolution, multiple acquisitions must be averaged. However, subject motion or involuntary physiological motion during diffusion-sensitizing gradients cause phase offsets among acquisitions. When the motion is localized to a small region, these phase offsets become particularly problematic. Complex averaging of acquisitions lead to cancellations from these phase offsets, whereas magnitude averaging results in noise amplification. Here, we propose an improved reconstruction for multi-acquisition DWI that effectively corrects for phase offsets while reducing noise. Theory and Methods: Each acquisition is processed with a refocusing reconstruction for global phase correction and a partial k-space reconstruction via projection-onto-convex-sets (POCS). The proposed reconstruction then embodies a new phase-correcting non-local means (PC-NLM) filter. PC-NLM is performed on the complex-valued outputs of the POCS algorithm aggregated across acquisitions. The PC-NLM filter leverages the shared structure among multiple acquisitions to simultaneously alleviate nuisance factors including phase offsets and noise. Results: Extensive simulations and in vivo DWI experiments of the cervical spinal cord are presented. The results demonstrate that the proposed reconstruction improves image quality by mitigating signal loss because of phase offsets and reducing noise. Importantly, these improvements are achieved while preserving the accuracy of apparent diffusion coefficient maps. Conclusion: An improved reconstruction incorporating a PC-NLM filter for multi-acquisition DWI is presented. This reconstruction can be particularly beneficial for high-resolution or high-b-value DWI acquisitions that suffer from low SNR and phase offsets from local motion.