The long-term sequelae of coronavirus disease 2019 (COVID-19) are still unknown. Lessons from past viral epidemics reveal that, after recovery, patients with viral pulmonary infections can suffer from irreversible pulmonary dysfunction and demonstrate residual imaging or functional abnormalities. Residual ground glass opacities, consolidations, reticular and linear opacities, residual crazy paving pattern, melted sugar sign, and parenchymal fibrotic bands are several features found in the late or remission stages of COVID-19. These radiologic findings have been observed weeks after symptom onset, even after hospital discharge, and they may or may not correlate with clinical manifestations. High-resolution CT may be indicated to establish new baselines and track changes in residual impairments. In our previous review, we observed significant pulmonary sequelae in some COVID-19 survivors at follow-up. In this update, we review the current literature on the clinical and radiologic manifestations of post-recovery COVID-19 toward the end of hospital admission and after discharge.

Background: The early diagnosis and treatment of rheumatoid arthritis (RA) are essential to prevent joint damage and enhance patient outcomes. Diagnosing RA in its early stages is challenging due to the nonspecific and variable clinical signs and symptoms. Our study aimed to identify the most predictive features of hand ultrasound (US) for RA development and assess the performance of machine learning models in diagnosing preclinical RA. Methods: We conducted a prospective cohort study with 326 adults who had experienced hand joint pain for less than 12 months and no clinical arthritis. We assessed the participants clinically and via hand US at baseline and followed them for 24 months. Clinical progression to RA was defined according to the ACR/EULAR criteria. Regression modeling and machine learning approaches were used to analyze the predictive US features. Results: Of the 326 participants (45.10 ± 11.37 years/83% female), 123 (37.7%) developed clinical RA during follow-up. At baseline, 84.6% of the progressors had US synovitis, whereas 16.3% of the non-progressors did (p < 0.0001). Only 5.7% of the progressors had positive PD. Multivariate analysis revealed that the radiocarpal synovial thickness (OR = 39.8), PIP/MCP synovitis (OR = 68 and 39), and wrist effusion (OR = 12.56) on US significantly increased the odds of developing RA. ML confirmed these US features, along with the RF and anti-CCP levels, as the most important predictors of RA. Conclusions: Hand US can identify preclinical synovitis and determine the RA risk. The radiocarpal synovial thickness, PIP/MCP synovitis, wrist effusion, and RF and anti-CCP levels are associated with RA development.

Background: Plantar fasciitis (PF) is a common enthesopathy in patients with ankylosing spondylitis (AS). Shear wave elastography (SWE) and the Belgrade ultrasound enthesitis score (BUSES) may detect PF, but their comparative diagnostic performance is unclear. Objective: To compare SWE with the BUSES for identifying PF in individuals with and without AS. Methods: In this cross-sectional study, 96 participants were stratified into AS and non-AS populations, each further divided based on the presence or absence of clinical PF. Demographic data, the American Orthopedic Foot and Ankle Society Score (AOFAS), and the BASDAI score were recorded. All subjects underwent grayscale ultrasonography, the BUSES scoring, and SWE assessment of the plantar fascia. Logistic regression models were constructed for each population, controlling for age, body mass index (BMI), and fascia–skin distance. ROC curve analyses were performed to evaluate diagnostic accuracy. Results: In both AS and non-AS groups, SWE and the BUSES were significant predictors of PF (p < 0.05). SWE demonstrated slightly higher diagnostic accuracy, with area under the curve (AUC) values of 0.845 (AS) and 0.837 (non-AS), compared to the BUSES with AUCs of 0.785 and 0.831, respectively. SWE also showed stronger adjusted odds ratios in regression models. The interobserver agreement was good to excellent for both modalities. Conclusions: Both SWE and the BUSES are effective for PF detection, with SWE offering marginally superior diagnostic performance, particularly in AS patients. SWE may enhance the early identification of biomechanical changes in the plantar fascia.

Osteoarthritis (OA) is the most prevalent degenerative joint disorder worldwide, causing significant declines in quality of life. The osteochondral junction (OCJ), a critical structural interface between deep cartilage and subchondral bone, plays an essential role in OA progression but is challenging to assess using conventional magnetic resonance imaging (MRI) due to its short T2 relaxation times. This study aimed to evaluate the utility of ultrashort echo time (UTE) MRI biomarkers, including macromolecular fraction (MMF), magnetization transfer ratio (MTR), and T2*, for in vivo quantification of OCJ changes in knee OA for the first time. Forty-five patients (mean age: 53.8 ± 17.0 years, 50% female) were imaged using 3D UTE-MRI sequences on a 3T clinical MRI scanner. Patients were stratified into two OA groups based on radiographic Kellgren–Lawrence (KL) scores: normal/subtle (KL = 0–1) (n = 21) and mild to moderate (KL = 2–3) (n = 24). Quantitative analysis revealed significantly lower MMF (15.8 ± 1.4% vs. 13.6 ± 1.2%, p < 0.001) and MTR (42.5 ± 2.5% vs. 38.2 ± 2.3%, p < 0.001) in the higher KL 2–3 group, alongside a higher trend in T2* values (19.7 ± 2.6 ms vs. 21.6 ± 3.8 ms, p = 0.06). Moreover, MMF and MTR were significantly negatively correlated with KL grades (r = −0.66 and −0.59; p < 0.001, respectively), while T2* showed a weaker positive correlation (r = 0.26, p = 0.08). Receiver operating characteristic (ROC) analysis demonstrated superior diagnostic accuracy for MMF (AUC = 0.88) and MTR (AUC = 0.86) compared to T2* (AUC = 0.64). These findings highlight UTE-MT techniques (i.e., MMF and MTR) as promising imaging tools for detecting OCJ degeneration in knee OA, with potential implications for earlier and more accurate diagnosis and disease monitoring.