Tuberculosis of the knee masquerading as pigmented villonodular synovitis: Report of two cases

Tuberculosis Presenting as Chronic Monoarthritis: A Case Study

Mycobacterium tuberculosis infection remains a common disease in developing countries with the potential to involve the osteoarticular system. The authors report a case of knee arthritis due to tuberculosis (TB) in a 34-year-old woman. The patient presented with pain and swelling of the right knee as major complaints, without a history of respiratory symptoms. Magnetic resonance imaging (MRI) demonstrated a marked joint effusion, involving synovial tissue with cartilaginous lesion compatible with pigmented villonodular synovitis (PVNS). After several physiotherapy courses without significant relief, total knee arthroplasty was proposed. Two months after surgery and rehabilitation, symptoms did not completely resolve, with limited active range of motion. Microbial bone biopsy culture at the time of the arthroplasty revealed a TB infection. Due to the rarity and clinical nonspecificity of TB bone manifestations, early diagnosis may be challenging. Yet, attempted diagnosis and prompt pharmacological intervention are paramount to improve outcomes.

Deep Learning-Based Multimodal 3 T MRI for the Diagnosis of Knee Osteoarthritis

The objective of this study was to investigate the application effect of deep learning model combined with different magnetic resonance imaging (MRI) sequences in the evaluation of cartilage injury of knee osteoarthritis (KOA). Specifically, an image superresolution algorithm based on an improved multiscale wide residual network model was proposed and compared with the single-shot multibox detector (SSD) algorithm, superresolution convolutional neural network (SRCNN) algorithm, and enhanced deep superresolution (EDSR) algorithm. Meanwhile, 104 patients with KOA diagnosed with cartilage injury were selected as the research subjects and underwent MRI scans, and the diagnostic performance of different MRI sequences was analyzed using arthroscopic results as the gold standard. It was found that the image reconstructed by the model in this study was clear enough, with minimum noise and artifacts, and the overall quality was better than that processed by other algorithms. Arthroscopic analysis found that grade I and grade II lesions concentrated on patella (26) and femoral trochlear (15). In addition to involving the patella and femoral trochlea, grade III and grade IV lesions gradually developed into the medial and lateral articular cartilage. The 3D-DS-WE sequence was found to be the best sequence for diagnosing KOA injury, with high diagnostic accuracy of over 95% in grade IV lesions. The consistency test showed that the 3D-DESS-WE sequence and T2∗ mapping sequence had a strong consistency with the results of arthroscopy, and the Kappa consistency test values were 0.748 and 0.682, respectively. In conclusion, MRI based on deep learning could clearly show the cartilage lesions of KOA. Of different MRI sequences, 3D-DS-WE sequence and T2∗ mapping sequence showed the best diagnosis results for different degrees of KOA injury.