Impaired median nerve mobility in patients with carpal tunnel syndrome: a systematic review and meta-analysis

Successful evaluation of a new image-based parameter for the diagnosis of carpal tunnel syndrome: ultrasound assessment of longitudinal median nerve gliding in patients, healthy volunteers, and cadavers

BACKGROUND

Reduced longitudinal median nerve gliding is a new promising diagnostic feature in carpal tunnel syndrome (CTS). However, the complexity of existing ultrasound analysis protocols undermines the application in routine clinical practice.

AIM

To provide a simple method for assessing longitudinal gliding with ultrasound, without the need for post-hoc image analysis.

DESIGN

1) Retrospective cohort study, validation by external blinded reviewers; 2) proof of concept in body donors.

SETTING

1) Outpatient clinic; 2) anatomy department.

POPULATION

The population included 48 patients with idiopathic CTS diagnosed by electrodiagnostic testing and ultrasound, as well as 15 healthy controls. Twelve, non-frozen, non-embalmed body donors were enrolled.

METHODS

Longitudinal gliding of the median nerve in the carpal tunnel was visualized in all patients with idiopathic CTS and healthy controls. All ultrasound videos were pseudonymized, equipped with a scale, and randomized. Videos were analyzed by four independent radiologists, all blinded to clinical characteristics. The endpoint was gliding rated as millimeters. Validity of the technique was tested by using speckle tracking software, and in body donors, directly measuring nerve excursion in situ, simultaneously to ultrasound.

RESULTS

Gliding differed significantly between controls and patients with CTS, decreasing with incremental CTS severity. A cut-off value of 3.5 mm to identify patients with CTS, yielded 93.8% sensitivity and 93.3% specificity. Intraclass correlation coefficient among senior author and raters was 0.798 (95% CI 0.513 to 0.900, P<0.001), indicating good reliability. Speckle tracking and especially direct validation in body donors correlated well with ultrasound findings.

CONCLUSIONS

First, longitudinal median nerve gliding can reliably be assessed using this simple technique without the need for complicated procedures. Second, a decrease in gliding was found with progressive severity of CTS. Reproducibility for measured distances is good among raters.

CLINICAL REHABILITATION IMPACT

An easy to apply sonography parameter would bolster the diagnostic ability of specialists in physical medicine and rehabilitation in daily routine.

Natural evolution of idiopathic carpal tunnel syndrome with respect to wrist and hand anthropometry: A prospective cohort study

OBJECTIVE

A greater wrist depth/width ratio and wrist depth/palm length ratio are known risk factors for carpal tunnel syndrome. We hypothesized that these parameters might also predict progression in patients who were not surgically treated.

METHODS

Seventy-eight patients with moderately severe idiopathic carpal tunnel syndrome of at least 10 months duration at recruitment, who declined surgical treatment and steroid injection, underwent repeated neurophysiological assessments after 3 years. A > 10% increase in median SNAP latency was taken as evidence of significant deterioration.

RESULTS

Patients with a wrist ratio ≥ 0.72 showed a statistically significant deterioration in SNAP latency from 5.46 (SD 2.09) to 7.16 (SD 1.56) ms and in SNAP amplitude from 30.19 (SD 13.8) to 16.62 (SD 14.42) µv. For those with a wrist-to-palm ratio ≥ 0.42, SNAP latency deteriorated from 5.27 (SD 1.21) to 7.1 (SD 1.52) ms, and amplitude from 32.78 (SD 13.76) to 19.45 (SD 16.62) µv. Patients with lower ratios did not show significant changes in any neurophysiological parameter. The relative risk of significant deterioration in SNAP latency in patients with a wrist ratio ≥ 0.72 was 2.04 (95% CI 1.27-3.27).

CONCLUSION

In untreated idiopathic carpal tunnel syndrome, patients with larger wrist and wrist-to-palm ratios are more likely to show neurophysiological progression.

Real-Time Automated Segmentation of Median Nerve in Dynamic Ultrasonography Using Deep Learning

OBJECTIVE

The morphological dynamics of the median nerve across the level extracted from dynamic ultrasonography are valuable for the diagnosis and evaluation of carpal tunnel syndrome (CTS), but the data extraction requires tremendous labor to manually segment the nerve across the image sequence. Our aim was to provide visually real-time, automated median nerve segmentation and subsequent data extraction in dynamic ultrasonography.

METHODS

We proposed a deep-learning model modified from SOLOv2 and tailored for median nerve segmentation. Ensemble strategies combining several state-of-the-art models were also employed to examine whether the segmentation accuracy could be improved. Image data were acquired from nine normal participants and 59 patients with idiopathic CTS.

DISCUSSION

Our model outperformed several state-of-the-art models with respect to inference speed, whereas the segmentation accuracy was on a par with that achieved by these models. When evaluated on a single 1080Ti GPU card, our model achieved an intersection over union score of 0.855 and Dice coefficient of 0.922 at 28.9 frames/s. The ensemble models slightly improved segmentation accuracy.

CONCLUSION

Our model has great potential for use in the clinical setting, as the real-time, automated extraction of the morphological dynamics of the median nerve allows clinicians to diagnose and treat CTS as the images are acquired.