Orthopedic Biomechanics Laboratory, Division of Orthopedic Research, Mayo Clinic, 200 First St SW, Rochester, MN 55905 USA.
J Ultrasound Med. 2012 Jul;31(7):1091-8. doi: 10.7863/jum.2012.31.7.1091.
The aim of this study was to image both tendon and subsynovial connective tissue movement in patients with carpal tunnel syndrome and healthy control volunteers, using sonography with speckle tracking. To estimate accuracy of this tracking method, we used in vivo measurements during surgery to validate the motion estimated with sonography.
We recruited 22 healthy volunteers and 18 patients with carpal tunnel syndrome. Longitudinal sonograms of the middle finger flexor digitorum superficialis tendon and subsynovial connective tissue were obtained during finger flexion and extension. The images were analyzed with a speckle-tracking algorithm. The ratio of the subsynovial connective tissue velocity to tendon velocity was calculated as the maximum velocity ratio, and the shear index, the ratio of tendon to subsynovial connective tissue motion, was calculated. For validation, we recorded flexor digitorum superficialis tendon motion during open carpal tunnel release.
The shear index was higher in patients than controls (P < .05), whereas the maximum velocity ratio in extension was lower in patients than controls (P < .05). We found good intraclass correlation coefficients (>0.08) for shear index and maximum velocity ratio measurements between speckle-tracking and in vivo measurements. Bland-Altman analyses showed that all measurements remained within the limits of agreement.
Speckle tracking is a potentially useful method to assess the biomechanics within the carpal tunnel and to distinguish between healthy individuals and patients with carpal tunnel syndrome. This method, however, needs to be further developed for clinical use, with the shear index and maximum velocity ratio as possible differentiating parameters between patients with carpal tunnel syndrome and healthy individuals.
本研究旨在使用超声斑点追踪技术对腕管综合征患者和健康对照志愿者进行肌腱和滑膜下结缔组织运动的成像。为了评估这种跟踪方法的准确性,我们使用术中的体内测量来验证超声估计的运动。
我们招募了 22 名健康志愿者和 18 名腕管综合征患者。在手指屈伸过程中获得中指屈指浅肌肌腱和滑膜下结缔组织的长轴超声图像。使用斑点跟踪算法对图像进行分析。计算滑膜下结缔组织速度与肌腱速度的比值作为最大速度比,计算肌腱与滑膜下结缔组织运动的比值即剪切指数。为了验证,我们记录了开放性腕管松解术中屈指浅肌肌腱的运动。
患者的剪切指数高于对照组(P <.05),而患者在伸展时的最大速度比低于对照组(P <.05)。我们发现,在斑点跟踪和体内测量之间,剪切指数和最大速度比的测量具有良好的组内相关系数(>0.08)。Bland-Altman 分析表明,所有测量值均在可接受范围内。
斑点跟踪是一种评估腕管内生物力学并区分健康个体和腕管综合征患者的潜在有用方法。然而,这种方法需要进一步开发,以便在临床上使用,剪切指数和最大速度比可能是腕管综合征患者和健康个体之间的区分参数。