To test the diagnostic performance of a deep learning-based system for the detection of clinically significant pulmonary nodules/masses on chest radiographs. MATERIALS AND METHODS: Using a retrospective study of 100 patients (47 with clinically significant pulmonary nodules/masses and 53 control subjects without pulmonary nodules), two radiologists verified clinically significantly pulmonary nodules/masses according to chest computed tomography (CT) findings. A computer-aided diagnosis (CAD) software using a deep-learning approach was used to detect pulmonary nodules/masses to determine the diagnostic performance in four algorithms (heat map, abnormal probability, nodule probability, and mass probability). RESULTS: A total of 100 cases were included in the analysis. Among the four algorithms, mass algorithm could achieve a 76.6% sensitivity (36/47, 11 false negative) and 88.68% specificity (47/ 53, six false-positive) in the detection of pulmonary nodules/masses at the optimal probability score cutoff of 0.2884. Compared to the other three algorithms, mass probability algorithm had best predictive ability for pulmonary nodule/mass detection at the optimal probability score cutoff of 0.2884 (AUC Mass : 0.916 versus AUC Heat map : 0.682, p<0.001; AUC Mass : 0.916 versus AUC Abnormal : 0.810, p¼0.002; AUC Mass : 0.916 versus AUC Nodule : 0.813, p¼0.014). CONCLUSION: In conclusion, the deep-learning based computer-aided diagnosis system will likely play a vital role in the early detection and diagnosis of pulmonary nodules/masses on chest radiographs. In future applications, these algorithms could support triage workflow via double reading to improve sensitivity and specificity during the diagnostic process.
Disuse muscle wasting will likely affect everyone in his or her lifetime in response to pathologies such as joint immobilization, inactivity or bed rest. There are no good therapies to treat it. We previously found that allopurinol, a drug widely used to treat gout, protects muscle damage after exhaustive exercise and results in functional gains in old individuals. Thus, we decided to test its effect in the prevention of soleus muscle atrophy after two weeks of hindlimb unloading in mice, and lower leg immobilization following ankle sprain in humans (EudraCT: 2011-003541-17). Our results show that allopurinol partially protects against muscle atrophy in both mice and humans. The protective effect of allopurinol is similar to that of resistance exercise which is the best-known way to prevent muscle mass loss in disuse human models. We report that allopurinol protects against the loss of muscle mass by inhibiting the expression of ubiquitin ligases. Our results suggest that the ubiquitin-proteasome pathway is an appropriate therapeutic target to inhibit muscle wasting and emphasizes the role of allopurinol as a non-hormonal intervention to treat disuse muscle atrophy.
Background Currently, there is uncertainty regarding the long-term outcome of medial patellofemoral ligament reconstructions (MPFLr). Our objectives were: (1) to develop a parametric model of the patellofemoral joint (PFJ) enabling us to simulate different surgical techniques for MPFLr; (2) to determine the negative effects on the PFJ associated with each technique, which could be related to long-term deterioration of the PFJ. Methods A finite element model of the PFJ was created based on CT data from 24 knees with chronic lateral patellar instability. Patella contact pressure and maximum MPFL-graft stress at five angles of knee flexion (0, 30, 60, 90 and 120°) were analysed in three types of MPFLr: anatomic, non-anatomic with physiometric behaviour, and non-anatomic with non-physiometric behaviour. Results An increase in patella contact pressure was observed at 0 and 30° of knee flexion after both anatomic and non-anatomic MPFLr with physiometric behaviour. In both reconstructions, the ligament was tense between 0 and 30° of knee flexion, but at 60, 90 and 120°, it had no tension. In the third reconstruction, the behaviour was completely the opposite. Conclusion A parametric model of the PFJ enables us to evaluate different types of MPFLr throughout the full range of motion of the knee, regarding the effect on the patellofemoral contact pressure, as well as the kinematic behaviour of the MPFL-graft and the maximum MPFL-graft stress. Electronic supplementary material The online version of this article (10.1186/s40634-019-0200-x) contains supplementary material, which is available to authorized users.
Several image processing algorithms have emerged to cover unmet clinical needs but their application to radiological routine with a clear clinical impact is still not straightforward. Moving from local to big infrastructures, such as Medical Imaging Biobanks (millions of studies), or even more, Federations of Medical Imaging Biobanks (in some cases totaling to hundreds of millions of studies) require the integration of automated pipelines for fast analysis of pooled data to extract clinically relevant conclusions, not uniquely linked to medical imaging, but in combination to other information such as genetic profiling. A general strategy for the development of imaging biomarkers and their integration in the cloud for the quantitative management and exploitation in large databases is herein presented. The proposed platform has been successfully launched and is being validated nowadays among the early adopters' community of radiologists, clinicians, and medical imaging researchers.
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