Background: Ankylosing spondylitis (AS) is a chronic, painful, progressive disease usually seen in the spine. Traditional diagnostic methods have limitations in detecting the early stages of AS. The early diagnosis of AS can improve patients’ quality of life. This study aims to diagnose AS with a pre-trained hybrid model using magnetic resonance imaging (MRI). Materials and Methods: In this research, we collected a new MRI dataset comprising three cases. Furthermore, we introduced a novel deep feature engineering model. Within this model, we utilized three renowned pretrained convolutional neural networks (CNNs): DenseNet201, ResNet50, and ShuffleNet. Through these pretrained CNNs, deep features were generated using the transfer learning approach. For each pretrained network, two feature vectors were generated from an MRI. Three feature selectors were employed during the feature selection phase, amplifying the number of features from 6 to 18 (calculated as 6 × 3). The k-nearest neighbors (kNN) classifier was utilized in the classification phase to determine classification results. During the information phase, the iterative majority voting (IMV) algorithm was applied to secure voted results, and our model selected the output with the highest classification accuracy. In this manner, we have introduced a self-organized deep feature engineering model. Results: We have applied the presented model to the collected dataset. The proposed method yielded 99.80%, 99.60%, 100%, and 99.80% results for accuracy, recall, precision, and F1-score for the collected axial images dataset. The collected coronal image dataset yielded 99.45%, 99.20%, 99.70%, and 99.45% results for accuracy, recall, precision, and F1-score, respectively. As for contrast-enhanced images, accuracy of 95.62%, recall of 80.72%, precision of 94.24%, and an F1-score of 86.96% were attained. Conclusions: Based on the results, the proposed method for classifying AS disease has demonstrated successful outcomes using MRI. The model has been tested on three cases, and its consistently high classification performance across all cases underscores the model’s general robustness. Furthermore, the ability to diagnose AS disease using only axial images, without the need for contrast-enhanced MRI, represents a significant advancement in both healthcare and economic terms.

The musculoskeletal system plays a crucial role in our daily lives, and the accurate diagnosis of musculoskeletal issues is essential for providing effective healthcare. However, the classification of musculoskeletal system radiographs is a complex task, requiring both accuracy and efficiency. This study addresses this challenge by introducing and evaluating a pyramid deep feature extraction model for the automatic classification of musculoskeletal system radiographs. The primary goal of this research is to develop a reliable and efficient solution to classify different upper extremity regions in musculoskeletal radiographs. To achieve this goal, we conducted an end-to-end training process using a pre-trained EfficientNet B0 convolutional neural network (CNN) model. This model was trained on a dataset of radiographic images that were divided into patches of various sizes, including 224 × 224, 112 × 112, 56 × 56, and 28 × 28. From the trained CNN model, we extracted a total of 85,000 features. These features were subsequently subjected to selection using the neighborhood component analysis (NCA) feature selection algorithm and then classified using a support vector machine (SVM). The results of our experiments are highly promising. The proposed model successfully classified various upper extremity regions with high accuracy rates: 92.04% for the elbow region, 91.19% for the finger region, 92.11% for the forearm region, 91.34% for the hand region, 91.35% for the humerus region, 89.49% for the shoulder region, and 92.63% for the wrist region. These results demonstrate the effectiveness of our deep feature extraction model as a potential auxiliary tool in the automatic analysis of musculoskeletal system radiographs. By automating the classification of musculoskeletal radiographs, our model has the potential to significantly accelerate clinical diagnostic processes and provide more precise results. This advancement in medical imaging technology can ultimately lead to better healthcare services for patients. However, future studies are crucial to further refine and test the model for practical clinical applications, ensuring that it integrates seamlessly into medical diagnosis and treatment processes, thus improving the overall quality of healthcare services.

Background and Objectives: We aimed to compare the effectiveness of ESWT (Extracorporeal Shock Wave Therapy) and RFA (Radiofrequency Thermal Ablation) on pain, disability, and activity limitation in the treatment of plantar fasciitis in patients with calcaneal spurs. Materials and Methods: Patients who apply to Orthopedics and Traumatology and Physical Medicine and Rehabilitation departments with a complaint of heel pain are included in this retrospective study. We included patients diagnosed with calcaneal spurs who received treatment with ESWT (n = 80) and RFA (n = 79) between 1 August 2021 and 1 September 2022. All patients were evaluated using the Visual Analog Scale (VAS), Foot Function Index (FFI), and the Roles and Maudsley score (RM) before and after treatment. An evaluation was performed on average 6 months after treatment. Results: This study included 79 RFA patients (34 females and 45 males) with a mean age of 55.8 ± 9.6 years and 80 ESWT patients (20 females and 60 males) with a mean age of 49.1 ± 9.5 years. There was a significant decrease in VAS scores after treatment in both the RFA and ESWT groups (z: −4.98, z: −5.18, respectively, p < 0.001). The reductions in FFI pain, FFI activity restriction, FFI disability, and RM scores were significant in both groups, although the scores after treatment were lower in the RFA group. Conclusions: This study demonstrates that ESWT and RFA significantly reduced pain, disability, and activity restriction in the treatment of plantar fasciitis in patients with calcaneal spurs. ESWT proved particularly effective in alleviating pain, whereas RFA had more pronounced effects on reducing disability and activity limitations. The choice of treatment should be based on the patient’s specific complaints.

Treatment of extra-articular distal tibial fractures is problematic owing to limited soft tissue cover, poor vascularity of the location, and adjacency to the ankle, and thus continues to be controversial. This study aimed to compare clinical and radiological outcomes in 69 patients with extra-articular distal tibia fractures treated with minimally invasive plate osteosynthesis (MIPO) and an interlocking intramedullary nail (IMN). Sixty-nine patients, with mean of age 39.8±18.3 years, were retrospectively evaluated. Thirty-five patients were treated with IMN, and 34 patients were treated with MIPO. Clinical and radiological outcomes were evaluated. The average follow-up was 13.3±6 months and union time was 16.2±5.4 weeks. Nonunion was observed in only 4.3% of patients treated with MIPO (P=0.114). Non-acceptable malalignment of extremity was observed in 4.3% of patients with IMN and 7.2% of patients with MIPO. There were no significant differences in union time, nonunion, surgical timing, operating time, malalignment, and complications between groups (P>0.05). The mean American Orthopaedic Foot and Ankle Society (AOFAS) surgery score was 95.8±5 in IMN and 91.9±14.3 in MIPO. AOFAS, Tenny-Wiss radiological, and Ovadia-Beals clinical scores were better in IMN than MIPO (P=0.019, P=0.03, P=0.02, respectively). Mean time of full weight-bearing and of return to daily life with IMN was significantly shorter than with MIPO (P<0.001). IMN and MIPO methods are reliable and effective methods with similar good results in the surgical treatment of extra-articular distal tibia fractures. However, IMN may be preferred for early full weight-bearing and early return to daily life (P<0.001).

Objective: The treatment of acromioclavicular joint (ACJ) dislocations offers numerous options, and ongoing debates persist regarding their comparative effectiveness. Among these options, the suspensory loop device (SLD) is one of the most favored treatment modalities. Despite the observed high reduction loss rate associated with SLD, the treatment yields favorable clinical outcomes. This study aimed to investigate the clinical outcomes of patients with acute type 3 and 5 ACJ dislocations who underwent open and arthroscopic procedures using a single‐bundle SLD, and to evaluate the effect of clavicular tunnel position on reduction loss.Methods: Thirty‐seven eligible patients diagnosed with acute type 3 and type 5 ACJ dislocation who underwent open and arthroscopic surgery with a single‐bundle SLD between January 2015 and March 2022 were evaluated retrospectively. Demographic data and radiological measurements including coracoclavicular (CC) interval, clavicle length (CL), and implant distance (ID) were recorded. The ID/CL ratio was calculated and a value between 0.17 and 0.24 was considered as “acceptable implant position”. Reduction loss and other complications were noted. Patients were divided into two groups: open (Group 1) and arthroscopic (Group 2). Constant Murray Score (CMS) and Visual Analog Scale (VAS) were used for clinical and functional outcomes. Non‐parametric tests were used for statistical analysis of variables.Results: The study included six females (16.2%) and 31 males (83.8%) with a mean age of 40.2 ± 14.7 years (range: 20–75). The mean follow‐up period was 22.3 ± 16.7 months (range: 6–72). The average time from trauma to surgery was 6.3 ± 5.3 days (range: 1–18). At the last follow‐up, the CMS was 89.3 ± 8.8 and the VAS score was 2.1 ± 0.9. The mean ID/CL ratio was 0.19 ± 0.1 and 19 patients (51.4%) were between 0.17 and 0.24. Reduction loss was observed in nine patients (24.3%). There were no significant differences between Group 1 and Group 2 regarding operation time (p = 0.998), ID/CL ratio (p = 0.442), reduction loss (p = 0.458), CMS (p = 0.325), and VAS score (p = 0.699). Of the 28 patients without reduction loss, 16 had an ID/CL ratio between 0.17 and 0.24 (p = 0.43). Furthermore, within the 0.17–0.24 interval, CMS was higher with an average of 91.8 ± 5.1 compared to the other intervals (p = 0.559).Conclusion: The clinical and functional outcomes of acute type 3 and type 5 ACJ dislocation operated open and arthroscopically with single‐bundle SLD are similar and satisfactory. A clavicular tunnel position in the range of 0.17–0.24 (ID/CL ratio) is recommended to maintain postoperative reduction.