Quantitative analysis of metacarpophalangeal joints during active flexion using four-dimensional computed tomography

Quantitative Measurement of Rotation in Phalangeal Fracture Malunion Using Computed Tomography Imaging-"Linkage Simulation"

Malunion of thumb and finger fractures causes problems in the cosmetic and functional aspects of the hand. Malunion of phalangeal fractures usually manifests as a combination of rotational deformities in the coronal, sagittal, and transverse planes, and corrective osteotomy is performed on the planes that cause these problems. Quantification of the deformity is essential for precise osteotomy and is difficult to perform in the transverse plane, even with radiography or computed tomography. Thus, we developed a technique called linkage simulation for the quantitative measurement of rotational deformities for surgical planning. In this procedure, finger extension and flexion can be simulated based on the predicted rotational axis of the joint, which is useful for determining the appropriate correction. Furthermore, by performing a reduction simulation in the software, it is possible to simulate the surgery and predict the postoperative results. This paper reports the details of this technique.

Verification of acromion marker cluster and scapula spinal marker cluster methods for tracking shoulder kinematics: a comparative study with upright four-dimensional computed tomography

BACKGROUND

This study validated the accuracy of the acromion marker cluster (AMC) and scapula spinal marker cluster (SSMC) methods compared with upright four-dimensional computed tomography (4DCT) analysis.

METHODS

Sixteen shoulders of eight healthy males underwent AMC and SSMC assessments. Active shoulder elevation was tracked using upright 4DCT and optical motion capture system. The scapulothoracic and glenohumeral rotation angles calculated from AMC and SSMC were compared with 4DCT. Additionally, the motion of these marker clusters on the skin with shoulder elevation was evaluated.

RESULTS

The average differences between AMC and 4DCT during 10°-140° of humerothoracic elevation were - 2.2° ± 7.5° in scapulothoracic upward rotation, 14.0° ± 7.4° in internal rotation, 6.5° ± 7.5° in posterior tilting, 3.7° ± 8.1° in glenohumeral elevation, - 8.3° ± 10.7° in external rotation, and - 8.6° ± 8.9° in anterior plane of elevation. The difference between AMC and 4DCT was significant at 120° of humerothoracic elevation in scapulothoracic upward rotation, 50° in internal rotation, 90° in posterior tilting, 120° in glenohumeral elevation, 100° in external rotation, and 100° in anterior plane of elevation. However, the average differences between SSMC and 4DCT were - 7.5 ± 7.7° in scapulothoracic upward rotation, 2.0° ± 7.0° in internal rotation, 2.3° ± 7.2° in posterior tilting, 8.8° ± 7.9° in glenohumeral elevation, 2.0° ± 9.1° in external rotation, and 1.9° ± 10.1° in anterior plane of elevation. The difference between SSMC and 4DCT was significant at 50° of humerothoracic elevation in scapulothoracic upward rotation and 60° in glenohumeral elevation, with no significant differences observed in other rotations. Skin motion was significantly smaller in AMC (28.7 ± 4.0 mm) than SSMC (38.6 ± 5.8 mm). Although there was smaller skin motion in AMC, SSMC exhibited smaller differences in scapulothoracic internal rotation, posterior tilting, glenohumeral external rotation, and anterior plane of elevation compared to 4DCT.

CONCLUSION

This study demonstrates that AMC is more accurate for assessing scapulothoracic upward rotation and glenohumeral elevation, while SSMC is preferable for evaluating scapulothoracic internal rotation, posterior tilting, glenohumeral external rotation, and anterior plane of elevation, with smaller differences compared to 4DCT.

Dynamic evaluation of the sternoclavicular and acromioclavicular joints using an upright four-dimensional computed tomography

In the analysis of the shoulder complex, the sequential changes occurring in the sternoclavicular and acromioclavicular joints during active shoulder motion are challenging to track. This study aimed to investigate the in vivo sternoclavicular and acromioclavicular joint motions during active elevation, including the sequential changes in these joint spaces using upright four-dimensional computed tomography (4DCT). Bilateral shoulders of 12 healthy volunteers upright 4DCT were obtained during active elevation similar to a "hands up" motion. The sternoclavicular and acromioclavicular rotation angles, joint distances, and closest points on the clavicle relative to the thorax and scapula were evaluated during 10°-140° of humerothoracic elevation. During humerothoracic elevation, the clavicle elevated, retracted, and rotated posteriorly relative to the thorax, whereas the scapula rotated upwardly, internally, and posteriorly relative to the clavicle. All the sternoclavicular and acromioclavicular joint rotation angles were significantly different at ≥ 30°-50° of humerothoracic elevation compared with 10° of humerothoracic elevation. The mean sternoclavicular and acromioclavicular joint distances were 2.2 ± 1.1 mm and 1.6 ± 0.9 mm, respectively. The closest points were located on the anteroinferior part of the medial and lateral clavicle in the sternoclavicular and acromioclavicular joints, respectively. Significant differences were observed in the acromioclavicular joint distance and anterior/posterior movements of the closest points in the sternoclavicular and acromioclavicular joints compared with 10° of humerothoracic elevation. Our sternoclavicular and acromioclavicular closest point results indicate that the impingement tends to occur at the anteroinferior part of the medial and lateral aspects of the clavicle and may be related to osteoarthritis.

Three-dimensional shoulder kinematics: Upright four-dimensional computed tomography in comparison with an optical three-dimensional motion capture system

Although shoulder kinematics have been analyzed by various methods, dynamic shoulder motion is difficult to track. This study aimed to validate the shoulder kinematic analysis using upright four-dimensional computed tomography (4DCT) and to compare the results with optical three-dimensional motion capture. During active elevation, bilateral shoulders of 10 healthy volunteers were tracked using 4DCT and motion capture. The scapulothoracic and glenohumeral rotations and the scapulohumeral rhythm (SHR) at each position were calculated, and the differences between 4DCT and motion capture were compared. During 10-140° of humerothoracic elevation, the scapulothoracic joint showed upward rotation, internal rotation, and posterior tilting, and the glenohumeral joint showed elevation, external rotation, and anterior plane of elevation in both analyses. In scapulothoracic rotations, the mean differences between the two analyses were -2.6° in upward rotation, 13.9° in internal rotation, and 6.4° in posterior tilting, and became significant with humerothoracic elevation ≥110° in upward rotation, ≥50° in internal rotation, and ≥100° in posterior tilting. In glenohumeral rotations, the mean differences were 3.7° in elevation, 9.1° in internal rotation, and -8.8° in anterior plane of elevation, and became significant with humerothoracic elevation ≥110° in elevation, ≥90° in internal rotation, and ≥100° in anterior plane of elevation. The mean overall SHRs were 1.8 in 4DCT and 2.4 in motion capture, and the differences became significant with humerothoracic elevation ≥100°. The 4DCT analysis of in vivo shoulder kinematics using upright computed tomography scanner is feasible, but the values were different from those by skin-based analysis at the elevated arm positions.

Four-dimensional computed tomographic analysis of screw home movement in patients with anterior cruciate ligament deficient knee - a 3D-3D registration technique

OBJECTIVE

The tibia externally rotates to the femur during the last 20° of the knee extension motion. This kinematic phenomenon is well known as screw home movement (SHM). The purpose was to clarify the SHM in anterior cruciate ligament deficient (ACLD) knee using four-dimensional computed tomography (4DCT).

MATERIALS AND METHODS

Six patients with a unilateral isolated ACLD knee participated. In the static position, CT scan of the both limbs of the femur and tibia were performed. Then, 4DCT was performed around knee. In the CT gantry, subjects were positioned in supine position with 45° of knee flexion on a triangle pillow and were asked to extend the knee to full extension within 10 s on each limb. The CT data were accumulated in digital imaging and communication in medicine (DICOM) data format. From the static CT and 4DCT DICOM data, three-dimensional surfaces of the knee joint were reconstructed. The whole tibia surface was matched into the partial tibia surface of that frame using 3D-3D registration technique. After the assessment of coordination system of the whole leg, knee flexion, abduction, and external rotation angle were calculated.

RESULTS

Knee external rotation angle was significantly smaller on the ACLD side than on the contralateral unaffected side in 0-15° of knee flexion (P < 0.05 in 0, 5, 10, and 15 degrees), while the angle was similar during 15-60° of knee flexion.

CONCLUSION

The absence of SHM in ACLD knee was detected using 3D-3D registration technique based on 4DCT.

Research on Discrete Semantics in Continuous Hand Joint Movement Based on Perception and Expression

Continuous movements of the hand contain discrete expressions of meaning, forming a variety of semantic gestures. For example, it is generally considered that the bending of the finger includes three semantic states of bending, half bending, and straightening. However, there is still no research on the number of semantic states that can be conveyed by each movement primitive of the hand, especially the interval of each semantic state and the representative movement angle. To clarify these issues, we conducted experiments of perception and expression. Experiments 1 and 2 focused on perceivable semantic levels and boundaries of different motion primitive units from the perspective of visual semantic perception. Experiment 3 verified and optimized the segmentation results obtained above and further determined the typical motion values of each semantic state. Furthermore, in Experiment 4, the empirical application of the above semantic state segmentation was illustrated by using Leap Motion as an example. We ended up with the discrete gesture semantic expression space both in the real world and Leap Motion Digital World, containing the clearly defined number of semantic states of each hand motion primitive unit and boundaries and typical motion angle values of each state. Construction of this quantitative semantic expression will play a role in guiding and advancing research in the fields of gesture coding, gesture recognition, and gesture design.