Biological laterality and peripheral nerve DTI metrics.

Biological laterality and peripheral nerve DTI metrics.
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DOI:
10.1371/journal.pone.0260256
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发表时间:
2021
期刊:
影响因子:
3.7
通讯作者:
Borsook D
Borsook D
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Holmes SA;Staffa SJ;Karapanagou A;Lopez N;Karian V;Borra R;Zurakowski D;Lebel A;Borsook D

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Clinical comparisons do not usually take laterality into account and thus may report erroneous or misleading data. The concept of laterality, well evaluated in brain and motor systems, may also apply at the level of peripheral nerves. Therefore, we sought to evaluate the extent to which we could observe an effect of laterality in MRI-collected white matter indices of the sciatic nerve and its two branches (tibial and fibular). We enrolled 17 healthy persons and performed peripheral nerve diffusion weighted imaging (DWI) and magnetization transfer imaging (MTI) of the sciatic, tibial and fibular nerve. Participants were scanned bilaterally, and findings were divided into ipsilateral and contralateral nerve fibers relative to self-reporting of hand dominance. Generalized estimating equation modeling was used to evaluate nerve fiber differences between ipsilateral and contralateral legs while controlling for confounding variables. All findings controlled for age, sex and number of scans performed. A main effect of laterality was found in radial, axial, and mean diffusivity for the tibial nerve. Axial diffusivity was found to be lateralized in the sciatic nerve. When evaluating mean MTR, a main effect of laterality was found for each nerve division. A main effect of sex was found in the tibial and fibular nerve fiber bundles. For the evaluation of nerve measures using DWI and MTI, in either healthy or disease states, consideration of underlying biological metrics of laterality in peripheral nerve fiber characteristics need to considered for data analysis. Integrating knowledge regarding biological laterality of peripheral nerve microstructure may be applied to improve how we diagnosis pain disorders, how we track patients’ recovery and how we forecast pain chronification.
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