Treatment of Plantar Fasciitis in Patients with Calcaneal Spurs: Radiofrequency Thermal Ablation or Extracorporeal Shock Wave Therapy?

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.

ASNET: A Novel AI Framework for Accurate Ankylosing Spondylitis Diagnosis from MRI.

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.

Unusual unilateral presentation of pachydermodactyly: a case report.

Pachydermodactyly is a rare digital fibromatosis characterized by asymptomatic fusiform soft-tissue swellings of the proximal interphalangeal joints of the hands. It usually affects healthy adolescent males with a negative family history. As a rule, clinical presentation of the disease is bilateral and symmetrical enlargement of the joints. So it can be misdiagnosed with inflammatory rheumatic diseases, especially with juvenile chronic arthritis. A prompt clinical diagnosis of the disease would prevent inappropriate treatment with immunosuppressive agents or steroids and unnecessary expensive diagnostic procedures such as biopsy or magnetic resonance imaging. Once diagnosed, patients should be advised in order to avoid repetitive traumas of the hands, rubbing and cracking of the fingers, obsessive-compulsive use of computer and video games. The joint outcome is always benign. Here, we report a case of pachydermodactyly differs from the typical clinical picture of pachydermodactyly in the unilateral distribution of the lesions.