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Noninvasive Characterisation of Foot Reflexology Areas by Swept Source-Optical Coherence Tomography in Patients with Low Back Pain

机译:低疼痛源 - 光源 - 光学相干性断层扫描患者止痛源 - 光学相干性断层扫描的非侵袭性特征

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Objective. When exploring the scientific basis of reflexology techniques, elucidation of the surface and subsurface features of reflexology areas (RAs) is crucial. In this study, the subcutaneous features of RAs related to the lumbar vertebrae were evaluated by swept source-optical coherence tomography (SS-OCT) in subjects with and without low back pain (LBP). Methods. Volunteers without LBP (n = 6 (male: female = 1:1)) and subjects with LBP (n = 15 (male: female = 2:3)) were clinically examined in terms of skin colour (visual perception), localised tenderness (visual analogue scale) and structural as well as optical attributes as per SS-OCT. From each subject, 6 optical tomograms were recorded from equidistant transverse planes along the longitudinal axis of the RAs, and from each tomogram, 25 different spatial locations were considered for recording SS-OCT image attributes. The images were analysed with respect to the optical intensity distributions and thicknesses of different skin layers by using Axio Vision Rel. 4.8.2 software. The SS-OCT images could be categorised into 4 pathological grades (i.e., 0,1;, and 3) according to distinctness in the visible skin layers. Results. Three specific grades for abnormalities in SS-OCT images were identified considering gradual loss of distinctness and increase in luminosity of skin layers. Almost 90.05% subjects were of mixed type having predominance in certain grades. Conclusion. The skin SS-OCT system demonstrated a definite association of the surface features of healthy/unhealthy RAs with cutaneous features and the clinical status of the lumbar vertebrae.
机译:客观的。在探索重构技术的科学依据时,阐明反射措施区域(RAS)的表面和地下特征至关重要。在该研究中,通过扫描源 - 光学相干断层扫描(SS-OCT)在具有和不低疼痛(LBP)的受试者中评估与腰椎相关的RA的皮下特征。方法。没有LBP的志愿者(n = 6(男性:雌性= 1:1))和具有LBP的受试者(n = 15(男性:女性= 2:3))在肤色(视觉感知),局部压痛方面临床检查(视觉模拟刻度)和结构以及根据SS-OCT的光学属性。从每个受试者沿着RA的纵向轴线,从等距横截面记录6个光学断层图像,并且从每个断层照片中,考虑了25个不同的空间位置用于记录SS-OCT图像属性。通过使用Axio Vision Rel,相对于不同皮肤层的光学强度分布和厚度分析图像。 4.8.2软件。根据可见皮肤层中的明显性,SS-OCT图像可以分为4个病理学等级(即,0,1;,和3)。结果。考虑逐渐丧失明显的明显和皮肤层的亮度增加,确定了SS-OCT图像异常的三种特异性等级。近90.05%的受试者是在某些等级中具有优势的混合型。结论。皮肤SS-OCT系统显示了健康/不健康RAS的明确关联,皮肤特征和腰椎的临床状态。

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