Ligament and Bone Arch Partition of the Carpal Tunnel by Three-Dimensional Ultrasonography

Convolutional Neural Network Approaches in Median Nerve Morphological Assessment from Ultrasound Images

Ultrasound imaging has been used to investigate compression of the median nerve in carpal tunnel syndrome patients. Ultrasound imaging and the extraction of median nerve parameters from ultrasound images are crucial and are usually performed manually by experts. The manual annotation of ultrasound images relies on experience, and intra- and interrater reliability may vary among studies. In this study, two types of convolutional neural networks (CNNs), U-Net and SegNet, were used to extract the median nerve morphology. To the best of our knowledge, the application of these methods to ultrasound imaging of the median nerve has not yet been investigated. Spearman's correlation and Bland-Altman analyses were performed to investigate the correlation and agreement between manual annotation and CNN estimation, namely, the cross-sectional area, circumference, and diameter of the median nerve. The results showed that the intersection over union (IoU) of U-Net (0.717) was greater than that of SegNet (0.625). A few images in SegNet had an IoU below 0.6, decreasing the average IoU. In both models, the IoU decreased when the median nerve was elongated longitudinally with a blurred outline. The Bland-Altman analysis revealed that, in general, both the U-Net- and SegNet-estimated measurements showed 95% limits of agreement with manual annotation. These results show that these CNN models are promising tools for median nerve ultrasound imaging analysis.

Quantification of carpal tunnel morphology using centroid-to-boundary distance shape signatures

Morphology analysis is valuable to understanding risk factors and the etiology of carpal tunnel (CT) syndrome. The objective of this study was to investigate morphology changes along the length of the CT using shape signatures (SS). Analysis was performed on ten cadaveric specimens in neutral wrist posture. Centroid-to-boundary distance SS were generated for proximal, middle, and distal CT cross-sections. Phase shift and Euclidean distance were quantified relative to a template SS for each specimen. Medial, lateral, palmar, and dorsal peaks were identified on each SS to generate metrics of tunnel width, tunnel depth, peak amplitude, peak angle. Width and depth measures were also performed using previously reported methods to serve as a basis of comparison. The phase shift revealed twisting of 21° between the ends of the tunnel. Distance from the template and width varied significantly over the length of the tunnel, while depth did not. Measures of width and depth using the SS method were consistent with previously reported methods. The SS method afforded the advantage of peak analysis with overall trends of peak amplitude indicating flattening of the tunnel at the proximal and distal ends relative to a rounder shape in the middle.

Spatial Relationship of the Median Nerve and Transverse Carpal Ligament in Asymptomatic Hands

The spacing between the median nerve and transverse carpal ligament (TCL) within the carpal tunnel can potentially affect the nerve morphology. This study aimed to quantify the spatial relationship between the median nerve and transverse carpal ligament in asymptomatic hands. Twelve subjects were recruited to image the carpal tunnel using robot-assisted ultrasound. The median nerve and TCL were segmented from each image and three-dimensionally reconstructed using kinematic information from the robot. The TCL-median nerve distance, nerve cross-sectional area, circularity, and position were measured along the entirety of the nerve length within the carpal tunnel. Results were averaged at every 5% of nerve length. At the nerve length percentages of 0% (distal), 25%, 50%, 75%, and 100% (proximal), the TCL-median nerve distance (±SD) was 0.7 ± 0.4, 0.7 ± 0.2, 0.5 ± 0.2, 0.5 ± 0.2, and 0.6 ± 0.3 mm, respectively. The corresponding nerve cross-sectional area was 9.4 ± 1.9, 10.6 ± 2.6, 11.2 ± 2.1, 11.2 ± 1.7, and 9.7 ± 1.9 mm2. A one-way analysis of variance showed no significant differences between the respective percentages of nerve length for TCL-median nerve distance (p = 0.219) and cross-sectional area (p = 0.869). Significant (p < 0.0001) but weak correlations were observed between the TCL-median nerve distance with cross-sectional area (r = -0.247) and circularity (r = -0.244). This study shows that the healthy median nerve morphology is consistent along the continuous nerve length within the carpal tunnel, supporting the use of 2D imaging in the evaluation of the healthy nerve.

Carpal tunnel mechanics and its relevance to carpal tunnel syndrome

The carpal tunnel is an elaborate biomechanical structure whose pathomechanics plays an essential role in the development of carpal tunnel syndrome. The purpose of this article is to review the movement related biomechanics of the carpal tunnel together with its anatomical and morphological features, and to describe the pathomechanics and pathophysiology associated with carpal tunnel syndrome. Topics of discussion include biomechanics of the median nerve, flexor tendons, subsynovial tissue, transverse carpal ligament, carpal tunnel pressure, and morphological properties, as well as mechanisms for biomechanical improvement and physiological restoration. It is our hope that the biomechanical knowledge of the carpal tunnel will improve the understanding and management of carpal tunnel syndrome.

Three-Dimensional Carpal Arch Morphology Using Robot-Assisted Ultrasonography

OBJECTIVE

The morphology of the carpal arch implicates the available space for the median nerve within the carpal tunnel. The purposes of this study were to 1) reconstruct the three-dimensional (3D) carpal arch by robot-assisted ultrasonography with a linear array transducer using cadaveric hands, and 2) investigate the 3D morphological properties of the carpal arch.

METHODS

An ultrasound probe with two-dimensional (2D) linear array was integrated on a robotic arm and maneuvered over the cadaveric carpal tunnels to scan the entire transverse carpal ligament and its osseous attachments to carpal bones. The acquired series of 2D ultrasound images together with robot positioning were utilized to reconstruct the 3D carpal arch for morphometric analyses.

RESULTS

Total carpal arch volume was 1099.4 ± 163.2 mm³ with the distal, middle, and proximal regions contributing 18.2 ± 1.5%, 32.7 ± 1.2%, and 49.1 ± 2.3%, respectively. The ligament surface area was 420.1 ± 63.9 mm². The carpal arch width, height, curvature, length, area, and palmar bowing index progressively increased from the distal to proximal locations within the tunnel (p < 0.01).

CONCLUSION

The incorporation of the robot technology with the ultrasound system advanced the applications of traditional 2D ultrasound imaging for a 3D carpal arch reconstruction, allowing for comprehensive morphological assessment of the carpal arch.

SIGNIFICANCE

The developed workflow can be used for the reconstruction and analysis of other anatomical features in vivo.