Deep learning-based post-processing of real-time MRI to assess and quantify dynamic wrist movement in health and disease

While morphologic magnetic resonance imaging (MRI) is the imaging modality of choice for the evaluation of ligamentous wrist injuries, it is merely static and incapable of diagnosing dynamic wrist instability. Based on real-time MRI and algorithm-based image post-processing in terms of convolutional neural networks (CNNs), this study aims to develop and validate an automatic technique to quantify wrist movement. A total of 56 bilateral wrists (28 healthy volunteers) were imaged during continuous and alternating maximum ulnar and radial abduction. Following CNN-based automatic segmentations of carpal bone contours, scapholunate and lunotriquetral gap widths were quantified based on dedicated algorithms and as a function of wrist position. Automatic segmentations were in excellent agreement with manual reference segmentations performed by two radiologists as indicated by Dice similarity coefficients of 0.96 ± 0.02 and consistent and unskewed Bland–Altman plots. Clinical applicability of the framework was assessed in a patient with diagnosed scapholunate ligament injury. Considerable increases in scapholunate gap widths across the range-of-motion were found. In conclusion, the combination of real-time wrist MRI and the present framework provides a powerful diagnostic tool for dynamic assessment of wrist function and, if confirmed in clinical trials, dynamic carpal instability that may elude static assessment using clinical-standard imaging modalities

Factors associated with worse lung function in cystic fibrosis patients with persistent staphylococcus aureus

Background Staphylococcus aureus is an important pathogen in cystic fibrosis (CF). However, it is not clear which factors are associated with worse lung function in patients with persistent S. aureus airway cultures. Our main hypothesis was that patients with high S. aureus density in their respiratory specimens would more likely experience worsening of their lung disease than patients with low bacterial loads. Methods Therefore, we conducted an observational prospective longitudinal multi-center study and assessed the association between lung function and S. aureus bacterial density in respiratory samples, co-infection with other CF-pathogens, nasal S. aureus carriage, clinical status, antibiotic therapy, IL-6- and IgG-levels against S. aureus virulence factors. Results 195 patients from 17 centers were followed; each patient had an average of 7 visits. Data were analyzed using descriptive statistics and generalized linear mixed models. Our main hypothesis was only supported for patients providing throat specimens indicating that patients with higher density experienced a steeper lung function decline (p<0.001). Patients with exacerbations (n = 60), S. aureus small-colony variants (SCVs, n = 84) and co-infection with Stenotrophomonas maltophilia (n = 44) had worse lung function (p = 0.0068; p = 0.0011; p = 0.0103). Patients with SCVs were older (p = 0.0066) and more often treated with trimethoprim/sulfamethoxazole (p = 0.0078). IL-6 levels positively correlated with decreased lung function (p<0.001), S. aureus density in sputa (p = 0.0016), SCVs (p = 0.0209), exacerbations (p = 0.0041) and co-infections with S. maltophilia (p = 0.0195) or A. fumigatus (p = 0.0496). Conclusions In CF-patients with chronic S. aureus cultures, independent risk factors for worse lung function are high bacterial density in throat cultures, exacerbations, elevated IL-6 levels, presence of S. aureus SCVs and co-infection with S. maltophilia