OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
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