Three-dimensional corrective osteotomy for cubitus varus deformity using patient-matched instruments.

Background: Various methods of two or three-dimensional (3D) corrective osteotomy for cubitus varus deformity have been reported. However, whether 3D correction of cubitus varus deformity is necessary is controversial because of technical difficulties and surgical complications. This study introduced 3D simulations and printing technology for corrective osteotomy against cubitus varus deformities. Moreover, recent studies on the application of these technologies were reviewed. Methods: The amount of 3D deformity was calculated based on the difference in 3D shape between the affected side and the contralateral normal side. Patient-matched instruments were created to perform the actual surgery as simulated. Further, a 3D corrective osteotomy was performed using patient-matched instruments for cubitus varus deformity in pediatric and adolescent patients. The humerus-elbow-wrist angle, tilting angle, and elbow ranges of motion were evaluated. Results: Humerus-elbow-wrist angle and tilting angle were corrected from -21° to 14° and from 30° to 43°, respectively, in the pediatric patient and from -18° to 10° and from 20° to 40°, respectively, in the adolescent patient. The elbow flexion and extension angles changed from 130° to 140° and from 20° to 10°, respectively, in the pediatric patient and from 120° to 130° and from 15° to 0°, respectively, in the adolescent patient. Conclusion: The 3D computer simulations and the use of patient-matched instruments for cubitus varus deformity are reliable and can facilitate an accurate and safe correction. These technologies can simplify the complexity of 3D surgical procedures and contribute to the standardization of treatment for cubitus varus deformity.

Quantitative 3-D CT Demonstrates Distal Row Pronation and Translation and Radiolunate Arthritis in the SNAC Wrist.

BACKGROUND: In scaphoid nonunion advanced collapse (SNAC) wrist arthritis, we analyzed the 3-dimensional (3-D) deformity patterns of carpal alignment secondary to scaphoid nonunion and quantified subchondral arthritis by investigating alterations in bone density. METHODS: We constructed 3-D models of the carpal bones and radius from 51 patients with scaphoid nonunion (nonunion group) and 50 healthy controls (control group). We quantified the differences in 3-D geometric position of the distal carpal row relative to the distal radius in SNAC wrists versus controls. In addition, we assessed the bone density of anatomic regions of interest in the radiocarpal and capitolunate joints relative to the pisiform bone density to characterize degenerative changes in SNAC wrists. RESULTS: The distal carpal row pronated by a difference of 14° (7.2° versus -6.7°; p < 0.001), deviated ulnarly by a difference of 19° (7.7° versus -11.2°; p < 0.001), shifted dorsally by a difference of 17% of the dorsovolar width of the distal radius (21.0% versus 4.4%; p < 0.001), shifted radially by a difference of 8% of the radioulnar width of the distal radius (13.2% versus 5.3%; p < 0.001), and migrated proximally by a difference of 12% of the lunate height (96.3% versus 108.8%; p < 0.001) in the nonunion group compared with the control group. Additionally, it was found that bone density was greater at the capitolunate joint (capitate head: 140.4% versus 123.7%; p < 0.001; distal lunate: 159.9% versus 146.3%; p < 0.001), the radial styloid (157.0% versus 136.3%; p < 0.001), and the radiolunate joint (proximal lunate: 134.8% versus 122.7%; p < 0.001; lunate fossa: 158.6% versus 148.1%; p = 0.005) in the nonunion group compared with the control group. CONCLUSIONS: Scaphoid nonunion exhibited a unique deformity pattern and alteration in bone-density distributions. The distal carpal row not only shifted dorsally and migrated proximally but also pronated, deviated ulnarly, and shifted radially. Bone density was greater at the capitolunate joint, the radial styloid, and surprisingly, the radiolunate joint. Our findings give insight into the natural history and progression of arthritis of the SNAC wrist. Additionally, future studies may give insight into whether successful treatment of scaphoid nonunion arrests the progression of arthritis. LEVEL OF EVIDENCE: Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Artificial intelligence to diagnosis distal radius fracture using biplane plain X-rays.

BACKGROUND: Although the automatic diagnosis of fractures using artificial intelligence (AI) has recently been reported to be more accurate than those by orthopedics specialists, big data with at least 1000 images or more are required for deep learning of the convolutional neural network (CNN) to improve diagnostic accuracy. The aim of this study was to develop an AI system capable of diagnosing distal radius fractures with high accuracy even when learning with relatively small data by learning to use bi-planar X-rays images. METHODS: VGG16, a learned image recognition model, was used as the CNN. It was modified into a network with two output layers to identify the fractures in plain X-ray images. We augmented 369 plain X-ray anteroposterior images and 360 lateral images of distal radius fractures, as well as 129 anteroposterior images and 125 lateral images of normal wrists to conduct training and diagnostic tests. Similarly, diagnostic tests for fractures of the styloid process of the ulna were conducted using 189 plain X-ray anteroposterior images of fractures and 302 images of the normal styloid process. The distal radius fracture is determined by entering an anteroposterior image of the wrist for testing into the trained AI. If it identifies a fracture, it is diagnosed as the same. However, if the anteroposterior image is determined as normal, the lateral image of the same patient is entered. If a fracture is identified, the final diagnosis is fracture; if the lateral image is identified as normal, the final diagnosis is normal. RESULTS: The diagnostic accuracy of distal radius fractures and fractures of the styloid process of the ulna were 98.0 ± 1.6% and 91.1 ± 2.5%, respectively. The areas under the receiver operating characteristic curve were 0.991 {n = 540; 95% confidence interval (CI), 0.984-0.999} and 0.956 (n = 450; 95% CI 0.938-0.973). CONCLUSIONS: Our method resulted in a good diagnostic rate, even when using a relatively small amount of data.

Utility of a 3-dimensionally printed color-coded bone model to visualize impinging osteophytes for arthroscopic débridement arthroplasty in elbow osteoarthritis.

BACKGROUND: The identification and precise removal of bony impingement lesions during arthroscopic débridement arthroplasty for elbow osteoarthritis require a high level of experience and surgical skill. We have developed a new technique to identify impinging osteophytes on a computer display by simulating elbow motion using the multiple positions of 3-dimensional (3D) elbow models created from computed tomography data. Moreover, an actual color-coded 3D model indicating the impinging osteophytes was created with a 3D printer and was used as an intraoperative reference tool. This study aimed to verify the efficacy of these new technologies in arthroscopic débridement for elbow osteoarthritis. METHODS: We retrospectively studied 16 patients treated with arthroscopic débridement for elbow osteoarthritis after a preoperative computer simulation. Patients who underwent surgery with only the preoperative simulation were assigned to group 1 (n = 8), whereas those on whom we operated using a color-coded 3D bone model created from the preoperative simulation were assigned to group 2 (n = 8). Elbow extension and flexion range of motion (ROM), the Mayo Elbow Performance Score (MEPS), and the severity of osteoarthritis were compared between the groups. RESULTS: Although preoperative elbow flexion and MEPS values were not significantly different between the groups, preoperative extension was significantly more restricted in group 2 than in group 1 (P = .0131). Group 2 tended to include more severe cases according to the Hastings-Rettig classification (P = .0693). ROM and MEPS values were improved in all cases. No significant differences in postoperative ROM or MEPS values were observed between the groups. There were no significant differences in the improvement in ROM or MEPS values between the 2 groups. CONCLUSIONS: The use of preoperative simulation and a color-coded bone model could help to achieve as good postoperative ROM and MEPS values for advanced elbow osteoarthritis as those for early and intermediate stages.

Arthroscopic Debridement of Elbow Osteoarthritis Using CT-Based Computer-Aided Navigation Systems Is Accurate.

PURPOSE: To evaluate whether the bony impingement lesion in elbow osteoarthritis can be removed accurately, as planned during arthroscopy, by using the computer-aided navigation system and performing mock surgery using 3-dimensional (3D)-printed bone models for clinical applications. METHODS: We performed mock surgery using 3D-printed plaster bone models of the humerus of 15 actual patients with elbow osteoarthritis. Two types of experiments were conducted to evaluate the surgical accuracy. Three surgeons performed the mock surgery, each with 15 bone models (total, 45 trials). Surgical accuracy was based on the mean of 45 trials. The differences in surgical accuracy among the 3 surgeons were also evaluated (mean 15 trials). The same surgeon performed 30 trials, and the difference in surgical accuracy between the first and the second halves was also evaluated (mean 15 trials). RESULTS: The spatial error in the entire elbow joint was 1.13 mm. In terms of resection volume, a mean of 8% more volume was resected than was planned, and 85% of the planned area was resected. In our experiments, the surgical accuracy was significantly lower in the anterior than in the posterior joint. Intrarater reliability was intraclass correlation (ICC)2,1 0.81 and inter-rater reliability was ICC1,1 0.87. CONCLUSIONS: Surgery using computer-aided navigation systems for arthroscopic debridement of the elbow provided accuracy comparable to that in other joints. CLINICAL RELEVANCE: Arthroscopic debridement of elbow osteoarthritis requires advanced surgical skills because accurate identification of the bony impingement legion is difficult during surgery. Surgery using computer-aided navigation systems for arthroscopic debridement of the elbow will provide real-time tracking of both the surgical instruments and bony impingement lesions as well as solve the technical difficulties of arthroscopic surgery of the elbow joint.

Tether Creation Between the Second and Third Extensor Digitorum Communis for Third Extensor Tendon Subluxation at the Metacarpophalangeal Joint.

We developed a substitution technique for a sagittal band reconstruction for subluxation of the third extensor tendon at the metacarpophalangeal joint. Through this procedure, we attempted to supply a tether between the second and third extensor digitorum communis (EDC) tendons. A half-slip of the second EDC was interlaced to the third EDC tendon at the level of the third metacarpal head with the metacarpophalangeal joint in full flexion position; this ensured that the interlace of the graft serves as a direct stabilizer against ulnar subluxation. A key advantage of our procedure is the strong and reliable interlace of the graft that does not require postoperative immobilization and allows unprotected motion protocol.