In this retrospective study, chest CTs of 121 symptomatic patients infected with coronavirus were reviewed for common CT findings in relationship to the time between symptom onset and the initial CT scan (i.e. early, 0-2 days (36 patients), intermediate 3-5 days (33 patients), late 6-12 days (25 patients)). The hallmarks of COVID-19 infection on imaging were bilateral and peripheral ground-glass and consolidative pulmonary opacities. Notably, 20/36 (56%) of early patients had a normal CT. With a longer time after the onset of symptoms, CT findings were more frequent, including consolidation, bilateral and peripheral disease, greater total lung involvement, linear opacities, "crazy-paving" pattern and the "reverse halo" sign. Bilateral lung involvement was observed in 10/36 early patients (28%), 25/33 intermediate patients (76%), and 22/25 late patients (88%).

For diagnosis of coronavirus disease 2019 (COVID-19), a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT-PCR) test is routinely used. However, this test can take up to 2 d to complete, serial testing may be required to rule out the possibility of false negative results and there is currently a shortage of RT-PCR test kits, underscoring the urgent need for alternative methods for rapid and accurate diagnosis of patients with COVID-19. Chest computed tomography (CT) is a valuable component in the evaluation of patients with suspected SARS-CoV-2 infection. Nevertheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infection, as some patients may have normal radiological findings at early stages of the disease. In this study, we used artificial intelligence (AI) algorithms to integrate chest CT findings with clinical symptoms, exposure history and laboratory testing to rapidly diagnose patients who are positive for COVID-19. Among a total of 905 patients tested by real-time RT-PCR assay and next-generation sequencing RT-PCR, 419 (46.3%) tested positive for SARS-CoV-2. In a test set of 279 patients, the AI system achieved an area under the curve of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist. The AI system also improved the detection of patients who were positive for COVID-19 via RT-PCR who presented with normal CT scans, correctly identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-19 negative. When CT scans and associated clinical history are available, the proposed AI system can help to rapidly diagnose COVID-19 patients. The COVID-19 pandemic has rapidly propagated due to widespread person-to-person transmission 1-6. Laboratory confirmation of SARS-CoV-2 is performed with a virus-specific RT-PCR, but the test can take up to 2 d to complete. Chest CT is a valuable component of evaluation and diagnosis in symptomatic patients with

BackgroundMyocardial fibrosis is being increasingly recognised as a common final pathway of a wide range of diseases. Thus, the development of an accurate and convenient method to evaluate myocardial fibrosis is of major importance. Although T1 mapping is a potential alternative for myocardial biopsy, validation studies are limited to small numbers and vary regarding technical facets, and include only a restricted number of disease. A systematic review and meta-analysis was conducted to objectively and comprehensively evaluate the performance of T1 mapping on the quantification of myocardial fibrosis using cardiovascular magnetic resonance (CMR).MethodsPubMed, EMBASE and the Cochrane Library databases were searched for studies applying T1 mapping to measure myocardial fibrosis and that validated the results via histological analysis. A pooled correlation coefficient between the CMR and histology measurements was used to evaluate the performance of the T1 mapping.ResultsA total of 15 studies, including 308 patients who had CMR and myocardial biopsy were included and the pooled correlation coefficient between ECV measured by T1 mapping and biopsy for the selected studies was 0.884 (95% CI: 0.854, 0.914) and was not notably heterogeneous chi-squared = 7.44; P = 0.489 for the Q test and I^2 = 0.00%).ConclusionsThe quantitative measurement of myocardial fibrosis via T1 mapping is associated with a favourable overall correlation with the myocardial biopsy measurements. Further studies are required to determine the calibration of the T1 mapping results for the biopsy findings of different cardiomyopathies.

BackgroundEarly detection of subclinical myocardial dysfunction in patients with diabetes mellitus (DM) is essential for recommending therapeutic interventions that can prevent or reverse heart failure, thereby improving the prognosis in such patients. This study aims to quantitatively evaluate left ventricular (LV) myocardial deformation and perfusion using cardiovascular magnetic resonance (CMR) imaging in patients with type 2 diabetes mellitus (T2DM), and to investigate the association between LV subclinical myocardial dysfunction and coronary microvascular perfusion.MethodsWe recruited 71 T2DM patients and 30 healthy individuals as controls who underwent CMR examination. The T2DM patients were subdivided into two groups, namely the newly diagnosed DM group (n = 31, patients with diabetes for ≤ 5 years) and longer-term DM group (n = 40, patients with diabetes > 5 years). LV deformation parameters, including global peak strain (PS), peak systolic strain rate, and peak diastolic strain rate (PSDR), and myocardial perfusion parameters such as upslope, time to maximum signal intensity (TTM), and max signal intensity (Max SI, were measured and compared among the three groups. Pearson’s correlation was used to evaluate the correlation between LV deformation and perfusion parameters.ResultsPooled data from T2DM patients showed a decrease in global longitudinal, circumferential, and radial PDSR compared to healthy individuals, apart from lower upslope. In addition, increased TTM and reduced Max SI were found in the longer-term diabetics compared to the normal subjects (p < 0.017 for all). Multivariable linear regression analysis showed that T2DM was independently associated with statistically significant CMR parameters, except for TTM (β = 0.137, p = 0.195). Further, longitudinal PDSR was significantly associated with upslope (r = − 0.346, p = 0.003) and TTM (r = 0.515, p < 0.001).ConclusionsOur results imply that a contrast-enhanced 3.0T CMR can detect subclinical myocardial dysfunction and impaired myocardial microvascular perfusion in the early stages of T2DM, and that the myocardial dysfunction is associated with impaired coronary microvascular perfusion.Electronic supplementary materialThe online version of this article (10.1186/s12933-018-0782-0) contains supplementary material, which is available to authorized users.

With the spread of novel coronavirus (2019-nCoV) pneumonia, chest high-resolution computed tomography (HRCT) has been one of the key diagnostic tools. To achieve early and accurate diagnostics, determining the radiological characteristics of the disease is of great importance. In this small scale research we retrospectively reviewed and selected six cases confirmed with 2019-nCoV infection in West China Hospital and investigated their initial and follow-up HRCT features, along with the clinical characteristics. The 2019-nCoV pneumonia basically showed a multifocal or unifocal involvement of ground-glass opacity (GGO), sometimes with consolidation and fibrosis. No pleural effusion or lymphadenopathy was identified in our presented cases. The follow-up CT generally demonstrated mild to moderate progression of the lesion, with only one case showing remission by the reducing extent and density of the airspace opacification.