Limited value of ultrasound assessment in patients with poor outcome after carpal tunnel release surgerys

[EN] OBJECTIVE: To determine the value of ultrasonography in the assessment of patients with idiopathic carpal tunnel syndrome (CTS) and poor outcome after carpal tunnel release. METHODS: A total of 88 consecutive patients with CTS (104 hands) underwent open surgical release of the median nerve. Ultrasound (US) examination was performed blind to any patient's data. The median nerve area at tunnel inlet and outlet, the retinaculum distance, and the flattening ratio were measured. The main outcome variable was the patient's overall satisfaction using a five-point Likert scale (1 = worse, 2 = no change, 3 = slightly better, 4 = much better, 5 = cured) at 3 months postoperatively. Pre- and postoperative ultrasonographic findings in relation to clinical outcome were analysed. RESULTS: Improvement (scores 4 or 5 on the Likert scale) was recorded in 75 hands (72%). After carpal tunnel release, the cross-sectional area at tunnel inlet decreased from a mean of 14.2 to 13.3 mm2 in the group with clinical improvement and also from a mean of 12.5 to 11.6 mm2 in the group with no change or slight improvement. No significant changes in the cross-sectional area at tunnel outlet, retinaculum distance, and flattening ratio were observed. CONCLUSION: Reduction of the median nerve cross-sectional area at tunnel inlet at 3 months after carpal tunnel release was similar in patients reporting cure or great improvement and in those with slight or no improvement. Ultrasonography is of limited value in assessment of patients with poor outcome after median nerve release.

On the use of simple geometric descriptors provided by RGB-D sensors for re-identification

[EN]The re-identification problem has been commonly accomplished using appearance features based on salient points and color information. In this paper, we focus on the possibilities that simple geometric features obtained from depth images captured with RGB-D cameras may offer for the task, particularly working under severe illumination conditions. The results achieved for different sets of simple geometric features extracted in a top-view setup seem to provide useful descriptors for the re-identification task, which can be integrated in an ambient intelligent environment as part of a sensor network.