Clinical validation of enhanced CT imaging for distal radius fractures through conditional Generative Adversarial Networks (cGAN).

BACKGROUND/PURPOSE: Distal radius fractures (DRFs) account for approximately 18% of fractures in patients 65 years and older. While plain radiographs are standard, the value of high-resolution computed tomography (CT) for detailed imaging crucial for diagnosis, prognosis, and intervention planning, and increasingly recognized. High-definition 3D reconstructions from CT scans are vital for applications like 3D printing in orthopedics and for the utility of mobile C-arm CT in orthopedic diagnostics. However, concerns over radiation exposure and suboptimal image resolution from some devices necessitate the exploration of advanced computational techniques for refining CT imaging without compromising safety. Therefore, this study aims to utilize conditional Generative Adversarial Networks (cGAN) to improve the resolution of 3 mm CT images (CT enhancement). METHODS: Following institutional review board approval, 3 mm-1 mm paired CT data from 11 patients with DRFs were collected. cGAN was used to improve the resolution of 3 mm CT images to match that of 1 mm images (CT enhancement). Two distinct methods were employed for training and generating CT images. In Method 1, a 3 mm CT raw image was used as input with the aim of generating a 1 mm CT raw image. Method 2 was designed to emphasize the difference value between the 3 mm and 1 mm images; using a 3 mm CT raw image as input, it produced the difference in image values between the 3 mm and 1 mm CT scans. Both quantitative metrics, such as peak signal-to-noise ratio (PSNR), mean squared error (MSE), and structural similarity index (SSIM), and qualitative assessments by two orthopedic surgeons were used to evaluate image quality by assessing the grade (1~4, which low number means high quality of resolution). RESULTS: Quantitative evaluations showed that our proposed techniques, particularly emphasizing the difference value in Method 2, consistently outperformed traditional approaches in achieving higher image resolution. In qualitative evaluation by two clinicians, images from method 2 showed better quality of images (grade: method 1, 2.7; method 2, 2.2). And more choice was found in method 2 for similar image with 1 mm slice image (15 vs 7, p = 201). CONCLUSION: In our study utilizing cGAN for enhancing CT imaging resolution, the authors found that the method, which focuses on the difference value between 3 mm and 1 mm images (Method 2), consistently outperformed.

Improved Acromiohumeral Distance Independently Predicts Better Outcomes After Arthroscopic Superior Capsular Reconstruction Graft Tears.

PURPOSE: To identify independent factors responsible for the poor outcomes after a graft tear after arthroscopic superior capsular reconstruction (ASCR). METHODS: Patients who underwent ASCR for massive rotator cuff tears between January 2013 and July 2021were reviewed. Based on the achievement of the minimal clinically important differences for clinical outcome measures at the final follow up, patients were divided into the good outcome (GO) and poor outcome (PO) groups. The minimal clinically important differences were calculated as the values equal to one-half of the standard deviation of the changes in outcome scores between the preoperative baseline and the latest follow-up. Pre- and final follow-up variables included demographics, American Shoulder and Elbow Surgeons (ASES) score, Constant score, visual analog scale (VAS) score, range of motion, Preoperative and postoperative 1-year radiological variables were analyzed using MRIs, including anteroposterior (AP) and mediolateral (ML) tear sizes, subscapularis tear, acromiohumeral distance (AHD), and degree of fatty degeneration. Logistic regression analysis was performed to identify the significant predictors of poor outcomes. RESULTS: A total of 33 patients who underwent ASCR presented with graft tears, which were confirmed by postoperative 1-year magnetic resonance imaging (MRI), and had a minimum follow-up duration of 2 years after surgery were enrolled. The GO group demonstrated significantly greater improvements in functional outcomes compared with the PO group (ASES: 83.5 ± 11.8 vs. 64.0 ± 20.4, P = 0.004; Constant: 67.6 ± 5.7 vs. 57.1 ± 9.8, P <0.001; and VAS: 0.9 ± 1.2 vs. 2.4 ± 2.0, P = 0.026). The postoperative 1-year AHD showed significant improvement in the GO group (3.1 ± 1.2 vs. 6.1 ± 1.4, P <0.001) but no change in the PO group (3.4 ± 1.3 vs. 4.2 ± 0.9, P = 0.074) postoperatively. Multivariate logistic regression analysis indicated that a decreased postoperative 1-year AHD (OR, 0.145; P = 0.019) was associated with a poor outcome after a graft tear. CONCLUSION: A narrow postoperative 1-year AHD was identified as the most importantindependent risk factor indicating poor clinical outcomes after a graft tear post-ASCR, which was related to a larger tear and loss of integrity between the grafts and infraspinatus at 1 year postoperatively. LEVEL OF EVIDENCE: Level IV.

Effect of age and gender in rates of achieving minimal clinically important difference and patient-acceptable symptom state 2 years after arthroscopic superior capsular reconstruction.

PURPOSE: This study aimed to evaluate patient-reported outcome measures (PROMs) and the effects of gender and age on achieving clinically significant outcomes in patients undergoing arthroscopic superior capsular reconstruction (ASCR) with a minimum 2-year follow-up. METHODS: Patients undergoing ASCR for irreparable rotator cuff tear between 2013 and 2020 were reviewed. Preoperative and minimum 2-year postoperative PROMs were collected, including American Shoulder and Elbow Surgeons (ASES), Constant, single assessment numeric evaluation (SANE), and visual analog scale (VAS) scores. Minimal clinically important difference (MCID) and patient-acceptable symptomatic state (PASS) were calculated for each functional score and analyzed according to age and gender. The percentages of patients achieving MCID and PASS were recorded. RESULTS: The study included 83 patients, with a mean follow-up of 3.5 ± 1.4 years. Significant improvements were found in ASES, Constant, SANE, and VAS for all groups based on gender and age. Based on receiver-operating characteristic curves, all scores had acceptable areas under the curve for PASS. Values for PASS and MCID were 81.5 and 10.3 for ASES; 61.5 and 6.2 for Constant; 82.5 and 11.5 for SANE and 1.5 and 1.1 for VAS, respectively. Analysis of achieving MCID and PASS showed no difference between the groups in the majority of outcome measures. However, female patients achieved the SANE thresholds for PASS at significantly higher rates than male patients. Patients ≥65 years old achieved ASES and Constant thresholds for MCID at significantly higher rates than patients ˂65 years old. CONCLUSION: Most patients achieved MCID and PASS at a 2-year follow-up. Patients showed comparable rates of MCID and PASS achievement on most outcome tools based on age and gender. Female patients achieved PASS on SANE at significantly higher rates than male patients and older patients achieved MCID on ASES and Constant at higher rates than young patients. Thus, age is a stronger factor for achieving MCID than gender. LEVEL OF EVIDENCE: Level II.

Preoperative magnetic resonance imaging rotator cuff tendon stump classification correlates with the surgical outcomes following superior capsular reconstruction.

HYPOTHESIS: This study aimed to investigate the correlation between rotator cuff stump classification and postoperative outcomes after superior capsular reconstruction (SCR). METHODS: A total of 75 patients who underwent SCR between June 2013 and May 2021 were included in this study. Based on stump classification using the signal intensity ratio of the tendon rupture site to the deltoid muscle in the coronal view of preoperative T2-weighted, fat-suppressed magnetic resonance imaging scans, the patients were classified into types 1, 2, and 3 with ratios of <0.8, 0.8-1.3, and >1.3 (44, 17, and 14 patients, respectively). The American Shoulder and Elbow Surgeons (ASES), Constant, and visual analog scale (VAS) scores for pain and range of motion were evaluated at a minimum of 1 year of follow-up postoperatively. The acromiohumeral distance and rotator cuff arthropathy according to the Hamada classification were assessed on plain radiography. The graft integrity was evaluated by magnetic resonance imaging at 3 and 12 months postoperatively and annually thereafter. RESULTS: Clinical and radiological outcomes were significantly improved after SCR. In comparison with type 2 and 3 patients, type 1 patients had significantly higher ASES scores (type 1, 2, and 3 = 84 ± 10, 75 ± 15, and 76 ± 14; all P = .014), Constant scores (type 1, 2, and 3 = 65 ± 5, 61 ± 9, and 56 ± 13; all P = .005), and forward flexion (type 1, 2, and 3 = 155 ± 10, 154 ± 15, and 145 ± 13; all P = .013). However, these statistical differences between groups were below the established minimum clinically important difference values for the ASES and Constant scores after rotator cuff repair. The graft failure rate after surgery was lower in the type 1 group than that in the other 2 groups; however, the difference was not statistically significant (P = .749). CONCLUSION: Patients with stump classification type 1 showed significantly better functional scores (ASES and VAS scores) and forward flexion; however, the clinical importance of these differences may be limited. Stump classification may be useful for predicting postoperative clinical outcomes.

Time required to achieve clinically significant outcomes after arthroscopic superior capsular reconstruction.

PURPOSE: To investigate the time-dependent nature of clinically significant outcomes, including the minimal clinically important difference (MCID), substantial clinical benefit, and Patient Acceptable Symptomatic State (PASS) after arthroscopic superior capsular reconstruction, and the factors contributing to the achievement of early clinically significant outcomes. METHODS: Patients who underwent ASCR between March 2015 and September 2020 with complete preoperative and postoperative 6-month, 1-year, and 2-year patient-reported outcome measures (PROMs) were retrospectively analysed. Threshold values for MCID, substantial clinical benefit, and PASS were obtained from the previous literature for the PROMs. The time required to achieve clinically significant outcomes was calculated using Kaplan-Meier analysis. Multivariate Cox regression was performed to evaluate the variables predictive of an earlier or delayed achievement of MCID. RESULTS: Fifty-nine patients with a mean age of 64.5 ± 8.7 years old were included. The time of mean achievement of MCID, substantial clinical benefit, and PASS for VAS was 11.2 ± 0.9, 16.3 ± 1.1, and 16.6 ± 0.9 months, respectively. The time of mean achievement of MCID, substantial clinical benefit, and PASS for ASES was 13.2 ± 1.0, 16.8 ± 1.0, and 18.3 ± 0.9 months, respectively. The time of mean achievement of MCID, substantial clinical benefit, and PASS for the Constant score was 11.6 ± 0.9, 15.1 ± 1.0, and 14.7 ± 0.9 months, respectively. The time of mean achievement of MCID, substantial clinical benefit, and PASS for SANE was 14.4 ± 1.0, 16.1 ± 1.0, and 15.5 ± 0.8 months, respectively. Patients with a higher preoperative VAS score achieved an earlier MCID for VAS (P = 0.014). However, patients with a higher preoperative ASES and SANE scores achieved delayed MCID for ASES and SANE (P = 0.026, and P < 0.001, respectively). CONCLUSION: Most patients achieved MCIDs around 1 year after arthroscopic superior capsular reconstruction. A higher preoperative VAS score favours faster MCID achievement, while higher preoperative ASES and SANE scores contribute to delayed MCID achievement. STUDY DESIGN: Cohort study LEVEL OF EVIDENCE: Level IV.

Overcoming the Challenges in the Development and Implementation of Artificial Intelligence in Radiology: A Comprehensive Review of Solutions Beyond Supervised Learning.

Artificial intelligence (AI) in radiology is a rapidly developing field with several prospective clinical studies demonstrating its benefits in clinical practice. In 2022, the Korean Society of Radiology held a forum to discuss the challenges and drawbacks in AI development and implementation. Various barriers hinder the successful application and widespread adoption of AI in radiology, such as limited annotated data, data privacy and security, data heterogeneity, imbalanced data, model interpretability, overfitting, and integration with clinical workflows. In this review, some of the various possible solutions to these challenges are presented and discussed; these include training with longitudinal and multimodal datasets, dense training with multitask learning and multimodal learning, self-supervised contrastive learning, various image modifications and syntheses using generative models, explainable AI, causal learning, federated learning with large data models, and digital twins.

Diagnosis of osteoporotic vertebral compression fractures and fracture level detection using multitask learning with U-Net in lumbar spine lateral radiographs.

Recent studies of automatic diagnosis of vertebral compression fractures (VCFs) using deep learning mainly focus on segmentation and vertebral level detection in lumbar spine lateral radiographs (LSLRs). Herein, we developed a model for simultaneous VCF diagnosis and vertebral level detection without using adjacent vertebral bodies. In total, 1102 patients with VCF, 1171 controls were enrolled. The 1865, 208, and 198 LSLRS were divided into training, validation, and test dataset. A ground truth label with a 4-point trapezoidal shape was made based on radiological reports showing normal or VCF at some vertebral level. We applied a modified U-Net architecture, in which decoders were trained to detect VCF and vertebral levels, sharing the same encoder. The multi-task model was significantly better than the single-task model in sensitivity and area under the receiver operating characteristic curve. In the internal dataset, the accuracy, sensitivity, and specificity of fracture detection per patient or vertebral body were 0.929, 0.944, and 0.917 or 0.947, 0.628, and 0.977, respectively. In external validation, those of fracture detection per patient or vertebral body were 0.713, 0.979, and 0.447 or 0.828, 0.936, and 0.820, respectively. The success rates were 96 % and 94 % for vertebral level detection in internal and external validation, respectively. The multi-task-shared encoder was significantly better than the single-task encoder. Furthermore, both fracture and vertebral level detection was good in internal and external validation. Our deep learning model may help radiologists perform real-life medical examinations.

Screening of adolescent idiopathic scoliosis using generative adversarial network (GAN) inversion method in chest radiographs.

OBJECTIVE: Conventional computer-aided diagnosis using convolutional neural networks (CNN) has limitations in detecting sensitive changes and determining accurate decision boundaries in spectral and structural diseases such as scoliosis. We devised a new method to detect and diagnose adolescent idiopathic scoliosis in chest X-rays (CXRs) employing the latent space's discriminative ability in the generative adversarial network (GAN) and a simple multi-layer perceptron (MLP) to screen adolescent idiopathic scoliosis CXRs. MATERIALS AND METHODS: Our model was trained and validated in a two-step manner. First, we trained a GAN using CXRs with various scoliosis severities and utilized the trained network as a feature extractor using the GAN inversion method. Second, we classified each vector from the latent space using a simple MLP. RESULTS: The 2-layer MLP exhibited the best classification in the ablation study. With this model, the area under the receiver operating characteristic (AUROC) curves were 0.850 in the internal and 0.847 in the external datasets. Furthermore, when the sensitivity was fixed at 0.9, the model's specificity was 0.697 in the internal and 0.646 in the external datasets. CONCLUSION: We developed a classifier for Adolescent idiopathic scoliosis (AIS) through generative representation learning. Our model shows good AUROC under screening chest radiographs in both the internal and external datasets. Our model has learned the spectral severity of AIS, enabling it to generate normal images even when trained solely on scoliosis radiographs.

Automated diagnosis of flatfoot using cascaded convolutional neural network for angle measurements in weight-bearing lateral radiographs.

OBJECTIVES: Diagnosis of flatfoot using a radiograph is subject to intra- and inter-observer variabilities. Here, we developed a cascade convolutional neural network (CNN)-based deep learning model (DLM) for an automated angle measurement for flatfoot diagnosis using landmark detection. METHODS: We used 1200 weight-bearing lateral foot radiographs from young adult Korean males for the model development. An experienced orthopedic surgeon identified 22 radiographic landmarks and measured three angles for flatfoot diagnosis that served as the ground truth (GT). Another orthopedic surgeon (OS) and a general physician (GP) independently identified the landmarks of the test dataset and measured the angles using the same method. External validation was performed using 100 and 17 radiographs acquired from a tertiary referral center and a public database, respectively. RESULTS: The DLM showed smaller absolute average errors from the GT for the three angle measurements for flatfoot diagnosis compared with both human observers. Under the guidance of the DLM, the average errors of observers OS and GP decreased from 2.35° ± 3.01° to 1.55° ± 2.09° and from 1.99° ± 2.76° to 1.56° ± 2.19°, respectively (both p < 0.001). The total measurement time decreased from 195 to 135 min in observer OS and from 205 to 155 min in observer GP. The absolute average errors of the DLM in the external validation sets were similar or superior to those of human observers in the original test dataset. CONCLUSIONS: Our CNN model had significantly better accuracy and reliability than human observers in diagnosing flatfoot, and notably improved the accuracy and reliability of human observers. KEY POINTS: • Development of deep learning model (DLM) that allows automated angle measurements for landmark detection based on 1200 weight-bearing lateral radiographs for diagnosing flatfoot. • Our DLM showed smaller absolute average errors for flatfoot diagnosis compared with two human observers. • Under the guidance of the model, the average errors of two human observers decreased and total measurement time also decreased from 195 to 135 min and from 205 to 155 min.

Automated landmark identification for diagnosis of the deformity using a cascade convolutional neural network (FlatNet) on weight-bearing lateral radiographs of the foot.

Landmark detection in flatfoot radiographs is crucial in analyzing foot deformity. Here, we evaluated the accuracy and efficiency of the automated identification of flatfoot landmarks using a newly developed cascade convolutional neural network (CNN) algorithm, Flatfoot Landmarks AnnoTating Network (FlatNet). A total of 1200 consecutive weight-bearing lateral radiographs of the foot were acquired. The first 1050 radiographs were used as the training and tuning, and the following 150 radiographs were used as the test sets, respectively. An expert orthopedic surgeon (A) manually labeled ground truths for twenty-five anatomical landmarks. Two orthopedic surgeons (A and B, each with eight years of clinical experience) and a general physician (GP) independently identified the landmarks of the test sets using the same method. After two weeks, observers B and GP independently identified the landmarks once again using the developed deep learning CNN model (DLm). The X- and Y-coordinates and the mean absolute distance were evaluated. The average differences (mm) from the ground truth were 0.60 ± 0.57, 1.37 ± 1.28, and 1.05 ± 1.23 for the X-coordinate, and 0.46 ± 0.59, 0.97 ± 0.98, and 0.73 ± 0.90 for the Y-coordinate in DLm, B, and GP, respectively. The average differences (mm) from the ground truth were 0.84 ± 0.73, 1.90 ± 1.34, and 1.42 ± 1.40 for the absolute distance in DLm, B, and GP, respectively. Under the guidance of the DLm, the overall differences (mm) from the ground truth were enhanced to 0.87 ± 1.21, 0.69 ± 0.74, and 1.24 ± 1.31 for the X-coordinate, Y-coordinate, and absolute distance, respectively, for observer B. The differences were also enhanced to 0.74 ± 0.73, 0.57 ± 0.63, and 1.04 ± 0.85 for observer GP. The newly developed FlatNet exhibited better accuracy and reliability than the observers. Furthermore, under the FlatNet guidance, the accuracy and reliability of the human observers generally improved.

Prevalence of flatfoot among young Korean males and the correlation among flatfoot angles measured in weight-bearing lateral radiographs.

Flatfoot causes significant fatigue and pain while walking, and even asymptomatic flatfoot may increase the risk of metatarsal stress fracture during long-distance walking. While most studies have used physical examination or plantar footprints to diagnose flatfoot, a weight-bearing radiograph of the foot provides more objective data. However, data on the prevalence of flatfoot in Asian populations gathered in a nationwide cohort of a specific age group is lacking. We examined the prevalence of flatfoot among 19-year-old male Korean army recruits using a weight-bearing lateral radiograph and evaluated the correlation among flatfoot angles. A total of 560,141 19-year-old Korean males were examined at the regional Military Manpower Administration offices between April 2018 and April 2020. Weight-bearing lateral radiographs of the foot were obtained using an X-ray system while the subjects were standing on a table with their feet in a neutral position. Based on these radiographs, military orthopedic surgeons and radiologists measured the talo-first metatarsal angle (TMA) and calcaneal pitch angle (CPA) for flatfoot diagnosis. Mild flatfoot was diagnosed when the TMA ranged from 6 to 15° or the CPA was <17°, and moderate-to-severe flatfoot was diagnosed when the TMA was 15° or greater or the CPA was <10°. Pearson correlation coefficients and scatter plot matrix were used to evaluate the correlation among the flatfoot angles. Finally, we evaluated the relationship between body mass index (BMI) and flatfoot angles and compared the BMI in subjects with or without self-checked foot deformities including flatfoot and pes cavus. Of the 560,141 subjects, 16,102 (2.9%) were diagnosed as flatfoot, and 5265 (0.9%) were diagnosed with moderate-to-severe flatfoot. The coefficients between TMA and CPA ranged from 0.342 to 0.449 (all P values < 0.001), and those between the 2 sides of TMA and CPA were 0.709 and 0.746 (all P values < 0.001), respectively. BMI had a significant correlation with both TMA and CPA in subjects with flatfoot, and those with self-checked foot deformities had a significantly higher BMI than the group without foot deformities. The prevalence of total flatfoot and moderate-to-severe flatfoot in 19-year-old Korean males based on a weight-bearing lateral radiograph was 2.9% and 0.9%, respectively. The correlation coefficients between TMAs and CPAs showed a low degree of positive correlation. Higher BMI was associated with the likelihood of the presence of flatfoot.

Enhancement of evaluating flatfoot on a weight-bearing lateral radiograph of the foot with U-Net based semantic segmentation on the long axis of tarsal and metatarsal bones in an active learning manner.

Robust labeling for semantic segmentation in radiographs is labor-intensive. No study has evaluated flatfoot-related deformities using semantic segmentation with U-Net on weight-bearing lateral radiographs. Here, we evaluated the robustness, accuracy enhancement, and efficiency of automated measurements for flatfoot-related angles using semantic segmentation in an active learning manner. A total of 300 consecutive weight-bearing lateral radiographs of the foot were acquired. The first 100 radiographs were used as the test set, and the following 200 radiographs were used as the training and validation sets, respectively. An expert orthopedic surgeon manually labeled ground truths. U-Net was used for model training. The Dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to evaluate the segmentation results. In addition, angle measurement errors with a minimum moment of inertia (MMI) and ellipsoidal fitting (EF) based on the segmentation results were compared between active learning and learning with a pooled dataset. The mean values of DSC, HD, MMI, and EF of the average of all bones were 0.967, 1.274 mm, 0.792°, and 1.147° in active learning, and 0.964, 1.292 mm, 0.828°, and 1.186° in learning with a pooled dataset, respectively. The mean DSC and HD were significantly better in active learning than in learning with a pooled dataset. Labeling of all bones required 0.82 min in active learning and 0.88 min in learning with a pooled dataset. The accuracy and angle errors generally converged in both learning. However, the accuracies based on DSC and HD were significantly better in active learning. Moreover, active learning took less time for labeling, suggesting that active learning could be an accurate and efficient learning strategy for developing flatfoot classifiers based on semantic segmentation.

[Danger in the pocket: explosive e-cigarette]. / Gefahr in der Hosentasche ­ explosive E-Zigarette.

INTRODUCTION: Be it as a nicotine replacement or a fashionable seduction for young people or casual smokers with or without nicotine additives - the popularity of e-cigarettes in Europe has increased during the past decade. In addition to the potential of long-term pulmonary damage, which is still largely unknown to date, there is a risk of battery explosion with specific injury patterns. Most users are unaware of the danger in their pockets. MATERIAL AND METHODS: Between February and July 2019, four patients were treated with burns from exploded e-cigarettes in the burn centre at Sana Hospital in Offenbach am Main (Germany). This article describes the cause and extent of the injury and its treatment. RESULTS: In all patients, the cause of the explosion was what is called "thermal runaway" (very rapid discharge of the battery). The average age of the patients, who were exclusively male, was 37 (25-50) years. The combustion depth ranged from grade I to deep grade IIb. The burnt body surface averaged 3 % (0.5-4.5 %) TBSA and affected the body regions that are typically in direct contact with the e-cigarette: thighs, genitals and hands. Conservative treatment was successful in one case and surgical treatment in two cases (two alloplastic covers, one meshed split-skin transplant). One patient discharged himself from hospital against medical advice after initial treatment. The average time in hospital for the three remaining patients was 15.6 days (6-17). CONCLUSION: Burns from an exploding e-cigarette represent a rare new entity. The force of the explosion of the battery body leads to injury patterns that require treatment in specialised centres with the entire spectrum of burn care. Mixed injuries with deep burns occur at the predilection sites due to thermal action, colliquative necrosis due to leaking electrolyte fluid and contamination by foreign bodies (metallic lithium, splinters of the destroyed housing) and require special initial measures. The extinction of fire caused by e-cigarettes also requires special measures. Proper handling of CE-certified devices is essential. Manipulation of the device in the event of defective functions or defective batteries is highly dangerous and should be strictly prohibited. General security requirements must be observed.

Causes and treatment outcomes of revision surgery after open reduction and internal fixation of tibial plateau fractures.

PURPOSE: Treatment of a tibial plateau fracture (TPF) remains controversial and is generally challenging. Many authors report good results after conventional open reduction and internal fixation in TPF, but complications still occur. This study analyzed causes and outcomes of revision surgery for TPF. The usefulness of a flow chart for revision surgery in TPF was also evaluated. METHODS: We reviewed all patients who underwent more than two operations for a TPF between 2008 and 2015. Finally, 24 cases were selected and retrospectively investigated. The medial tibial plateau angle and proximal posterior tibial angle were radiologically evaluated. The American Knee Society Score (AKSS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), range of motion (ROM), and bone union time were investigated after surgery. RESULTS: Revision surgery for infection was performed in eight cases, for nonunion in six cases, for posttraumatic arthritis (with total knee arthroplasty) in six cases, and for other reasons in four cases. The mean clinical AKSS at final follow-up was 87.3 ± 5.3 (range, 75-95), the functional AKSS was 81.9 ± 5.5 (range, 70-90), the WOMAC score was 9.9 ± 3.1 (range, 5-16), the flexion ROM was 119.8 ± 16.5° (range, 100-150°), and the extension ROM was 2.5 ± 3.3° (range, 0-10°). CONCLUSIONS: Although complications cannot be avoided in some cases, good clinical outcomes are possible when patients are divided according to the presence or absence of infection, with selection of appropriate revision surgery as shown in the flow chart. If an infection is present, treatment should be based on the presence or absence of bone union. If there is no infection, treatment should be based on the presence or absence of nonunion, post-traumatic arthritis, malunion, or immediate post-operative malreduction.

Treatment of Modified Mason Type III or IV Radial Head Fracture: Open Reduction and Internal Fixation versus Arthroplasty.

BACKGROUND: The treatment of modified Mason Type III or IV fractures is controversial. Many authors report open reduction and internal fixation (ORIF) with reconstruction of the radial head, but others advocate radial head arthroplasty (RHA). This study compares the clinical and radiological outcomes of ORIF and RHA in modified Mason Type III or IV radial head fracture and evaluates correlations between prognostic factors and postoperative clinical outcomes. MATERIALS AND METHODS: 42 patients with modified Mason Type III or IV radial head fractures who were surgically treated between January 2010 and January 2014 were retrospectively analyzed (20 patients with RHA and 22 patients with ORIF group were selected). Clinically, the patient rated elbow evaluation (PREE), the disabilities of the arm, shoulder and hand (DASH), and the range of motion (ROM) were measured. Radiologically, plain radiographs and computed tomography scans were taken. RESULTS: The mean PREE scores were 13.9 for the RHA group and 13.0 for the ORIF group, and mean DASH scores were 9.5 and 10.7, respectively. The differences were not statistically significant. When comparing ROM, the patients in the RHA group showed greater movement at all measured angles. In multiple regression analysis, age was the only variable significantly associated with both PREE and DASH. CONCLUSION: Overall, there were no significant differences in clinical outcomes of modified Mason Type III or IV radial head fractures treated with ORIF or RHA. However, a subgroup of younger patients had better clinical outcomes with ORIF treatment. Therefore, ORIF should be the First line of treatment, particularly if the reduction is possible.

Effect of water glass coating of tricalcium phosphate granules on in vivo bone formation.

BACKGROUND: Recently, some authors introduced a water glass (WG, sodium-silicate glass; Na2O·SiO2·nH2O) coating over tricalcium phosphate (TCP) bioceramic to modulate its resorption rate and enhance the bone cell behaviors. In this study, four different types of granular samples were prepared to evaluate the ability of new bone formation in vivo using micro-computed tomography and histology. METHODS: Four types sample groups: group A (pure HA as a negative resorption control); group B (pure TCP as a positive resorption control); group C (WG-coated TCP as an early resorption model); and group D (same as group C but heat-treated at 500°C as a delayed resorption model). Cylindrical tube-type carriers with holes were fabricated with HA by extrusion and sintering. Each carrier was filled densely with each granular sample. Four types of tubes were implanted into the medial femoral condyle and medial tibial condyle of New Zealand White rabbits. RESULTS: The HA group (A) showed the lowest amount of new bone formation. All the TCP sample groups (B, C, and D) showed more new bone formation. On the other hand, among the TCP groups, group C (early resorption model) showed slightly more bone formation. The amount of residual bioceramics was most abundant in the HA group (A). All the TCP sample groups showed less residual bioceramics than group A. Among the TCP groups, group C showed slightly more residual bioceramics. Group B showed the lowest amount of residual bioceramics. CONCLUSIONS: The WG-coated TCP sample (group C) is the best bone substitute candidate because of its proper biodegradation rate and the Si ions release because the WG-coated layer reduces the material resorption and enhances the new bone formation. That is, the WG-coated TCP is believed to be the best material for the application of an artificial bone substitute material.

Clinical and Radiographic Outcomes of Pediatric Radial Head Fractures.

BACKGROUND: The treatment of pediatric radial head fracture (RHF) is controversial, and the outcome is unpredictable. We aimed to evaluate the long term clinical and radiographic outcomes of patients with pediatric RHF. MATERIALS AND METHODS: 24 patients with pediatric RHFs operated between January 2004 and 2012 were included in this retrospective study. 17 patients had extra articular radial head (EARH) fractures and 7 had intraarticular radial head (IARH) fractures. The Mayo Elbow Performance Score (MEPS), Tibone and Stoltz classification, range of motion (ROM), and carrying angle (CA) were evaluated. The radial head diameter (RHD) and radial head height (RHH), neck shaft angle (NSA), and distance from the radial head to the radial tuberosity (RHRT) were measured and compared with the other side in simple anteroposterior views of elbow radiographs. RESULTS: At the last followup, the mean MEPS was 100 and 97.9 in groups EARH and IARH, respectively. There were no clinically and radiographically significant differences between the groups. The injured elbows showed smaller ROMs than the uninjured elbows in flexion, supination, and pronation with statistically significant differences. However, the injured elbows showed larger extension ranges than the uninjured elbows with a statistical significance (all P = 0.000). CA, RHD, and RHH were higher in the injured elbows than in the uninjured elbows with statistically significant differences (P = 0.006, 0.000, and 0.011) However, NSA and RHRT of both elbows were similar, with no statistically significant difference (P = 0.810 and 0.752). CONCLUSION: All patients with pediatric RHF were satisfied with the long term clinical results. The injured elbows showed restricted ROMs compared with the uninjured elbows; however, the extension range increased.

Effect of water glass coating of tricalcium phosphate on in vitro cellular proliferation and osteogenic differentiation.

Background In this study, the properties of the water glass (WG, sodium-silicate glass) were utilized to control the biodegradability of the beta tricalcium phosphate materials by the WG coating on the tricalcium phosphate disc surface with various coating thickness, chemistry, and heat-treatment. Methods Four types of disc specimens were prepared. A sample group A consisted of pure hydroxyapatite (HA) as a negative resorption control; a sample group B consisted of pure beta tricalcium phosphate as a positive resorption control; a sample group C consisted of beta tricalcium phosphate coated with WG as an early resorption model; and a sample group D consisted beta tricalcium phosphate coated with WG and heat-treated at 500°C as a delayed resorption model. Using human bone marrow-derived mesenchymal stem cells, for the analysis of cellular attachment and proliferative activity, 4-6-Diamidino-2-Phenylindole fluorescence technique was used. For the analysis of osteteogenic differentiation, alkaline phospastase (ALP) activity was measured. Results The mean z-scores of four groups (A, B, C, and D) in cellular attachment at 4 h after seeding were -1.21, -0.15, 0.42, and 0.94, respectively, and statistically significantly different in all groups respectively. Seven days after seeding, the mean z-scores of cellular proliferation were 1.97, 0.71, 1.48, and 1.83 in the four groups, respectively. The mean z-scores of the ALP activity per the mean z-scores of cell numbers of respective groups on the seventh day were 0.40, -1.51, 0.12, and 0.06, respectively, in four groups. Conclusion Initial cellular attachment is better on beta tricalcium phosphate than on HA and is enhanced by WG coating, especially with sintering at the high temperature. Cellular proliferation is considered to be increased by maintaining its attachment site through reduced dissolution of beta tricalcium phosphate by WG coating. Osteogenic differentiation in in-vitro study on the WG-coated beta tricalcium phosphate is thought to be as the result of increased silicon ion release from the WG.

New Skeletal Muscle Mass Index in Diagnosis of Sarcopenia.

BACKGROUND: We sought to develop a novel index based on the skeletal muscle mass that reflects the change of quality of life (QOL), and is the most appropriate index for the body composition of the elderly in Korea. Whether lower extremity skeletal muscle mass index (LESMI) is an appropriate novel new index to diagnose patients with sarcopenia was also evaluated. A cut-off value for each index was reported to facilitate the diagnosis of patients with sarcopenia in a Korean population. METHODS: We used the 5th Korean National Health and Nutrition Examination Survey data from 2010. We analyzed 409 elderly patients, including 231 men and 178 women, aged ≥65 years. Patients were diagnosed by calculating their skeletal muscle index based on the skeletal muscle mass measured using dual energy X-ray absorptiometry. Obesity and osteoporosis were used to screen data and EuroQOL-5 dimension as a health questionnaire. RESULTS: The prevalence of sarcopenia in each index was obtained based on its cut-off value for diagnosing sarcopenia. There was a significant difference between the obesity rate of elderly patients diagnosed with sarcopenia and those who were not based on each index. There was no significant difference in the prevalence of osteoporosis between the groups. Sarcopenia diagnosis based on the LESMI was significantly correlated with QOL. CONCLUSIONS: LESMI, a novel index based on skeletal muscle mass, reflects changes in QOL and is appropriate for the body composition of elderly people in Korea.