Objectives Rapid and accurate diagnosis of coronavirus disease 2019 is critical during the epidemic. We aim to identify differences in CT imaging and clinical manifestations between pneumonia patients with and without COVID-19, and to develop and validate a diagnostic model for COVID-19 based on radiological semantic and clinical features alone. Methods A consecutive cohort of 70 COVID-19 and 66 non-COVID-19 pneumonia patients were retrospectively recruited from five institutions. Patients were divided into primary (n = 98) and validation (n = 38) cohorts. The chi-square test, Student's t test, and Kruskal-Wallis H test were performed, comparing 1745 lesions and 67 features in the two groups. Three models were constructed using radiological semantic and clinical features through multivariate logistic regression. Diagnostic efficacies of developed models were quantified by receiver operating characteristic curve. Clinical usage was evaluated by decision curve analysis and nomogram. Results Eighteen radiological semantic features and seventeen clinical features were identified to be significantly different. Besides ground-glass opacities (p = 0.032) and consolidation (p = 0.001) in the lung periphery, the lesion size (1-3 cm) is also significant for the diagnosis of COVID-19 (p = 0.027). Lung score presents no significant difference (p = 0.417). Three diagnostic models achieved an area under the curve value as high as 0.986 (95% CI 0.966~1.000). The clinical and radiological semantic models provided a better diagnostic performance and more considerable net benefits. Conclusions Based on CT imaging and clinical manifestations alone, the pneumonia patients with and without COVID-19 can be distinguished. A model composed of radiological semantic and clinical features has an excellent performance for the diagnosis of COVID-19.Xiaofeng Chen and Yanyan Tang contributed equally to this work.Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00330-020-06829-2) contains supplementary material, which is available to authorized users. Key Points• Based on CT imaging and clinical manifestations alone, the pneumonia patients with and without COVID-19 can be distinguished. • A diagnostic model for COVID-19 was developed and validated using radiological semantic and clinical features, which had an area under the curve value of 0.986 (95% CI 0.966~1.000) and 0.936 (95% CI 0.866~1.000) in the primary and validation cohorts, respectively.

Chemical exchange saturation transfer (CEST) MRI is sensitive to dilute proteins and peptides as well as microenvironmental properties. However, the complexity of the CEST MRI effect, which varies with the labile proton content, exchange rate and experimental conditions, underscores the need for development of quantitative CEST (qCEST) analysis. Towards this goal, it has been shown that the omega plot is capable of quantifying paramagnetic CEST (PARACEST) MRI. However, the use of omega plot is somewhat limited for diamagnetic CEST (DIACEST) MRI because it is more susceptible to direct RF saturation (spillover) effects owing to their relatively small chemical shift. Recently, it has been found that for dilute DIACEST agents that undergo slow to intermediate chemical exchange, the RF spillover effect varies little with the labile proton ratio and exchange rate. Therefore, we postulated that the omega plot analysis can be improved if RF spillover effect could be estimated and taken into account. Specifically, simulation showed that both labile proton ratio and exchange rate derived using the spillover effect-corrected omega plot are in good agreement with simulated values. In addition, the modified omega plot was confirmed experimentally, and we showed that the derived labile proton ratio increases linearly with creatine concentration (P< 0.01), with little difference in their exchange rate (P=0.32). In summary, our study extended the conventional omega plot for quantitative analysis of DIACEST MRI.

Aim:We utilized single-voxel 1 H magnetic resonance spectroscopy to determine biochemical abnormalities related to major depressive disorder (MDD) in the bilateral dorsolateral prefrontal cortex, anterior cingulate cortex (ACC), and cerebellar hemisphere before and after antidepressant treatment. Methods:Fifteen adult MDD patients and 15 ageand sex-matched healthy controls were involved. Magnetic resonance spectroscopy of the brain was conducted in all subjects at the beginning of the study and the depressed subjects were reassessed after 8 weeks of antidepressant treatment.Results: At baseline, N-acetyl aspartate (NAA), total glutamine plus glutamate (Glx) and myo-inositol (MI) levels in the bilateral ACC were significantly lower in MDD patients than in controls (P < 0.05/3). MI in the bilateral cerebellar hemisphere were also decreased in patients compared with controls. After the treatment, the lower NAA, Glx and MI in ACC were normalized in MDD patients and the NAA and Glx increased compared to baseline values. The MI levels in the bilateral cerebellar hemisphere were also normalized in patients. MI and choline levels in the right cerebellar hemisphere were elevated compared to those at baseline. Conclusion:Our study suggests that metabolic abnormalities in the ACC and cerebellar hemisphere are implicated in MDD. Antidepressants may alter the local metabolic abnormalities in these areas.

In this study, we aimed to use 3T magnetic resonance imaging (MRI), which is clinically available, to determine the extracellular pH (pHe) of liver tumors and prospectively evaluate the ability of chemical exchange saturation transfer (CEST) MRI to distinguish between benign and malignant liver tumors. Methods: Different radiofrequency irradiation schemes were assessed for ioversol-based pH measurements at 3T. CEST effects were quantified in vitro using the asymmetric magnetization transfer ratio (MTRasym) at 4.3 ppm from the corrected Z spectrum. Generalized ratiometric analysis was conducted by rationing resolved ioversol CEST effects at 4.3 ppm at a flip angle of 60 and 350°. Fifteen patients recently diagnosed with hepatic carcinoma and five patients diagnosed with hepatic hemangioma [1 male; mean age, 48.6 (range, 37-59) years] were assessed. Results: By conducting dual-power CEST MRI, the pH of solutions was determined to be 6.0-7.2 at 3T in vitro. In vivo, ioversol signal intensities in the tumor region showed that the extracellular pH in hepatic carcinoma was acidic(mean ± standard deviation, 6.66 ± 0.19), whereas the extracellular pH was more physiologically neutral in hemangioma (mean ± standard deviation, 7.34 ± 0.09).The lesion size was similar between CEST pH MRI and T2-weighted imaging. Conclusion: dual-power CEST MRI can detect extracellular pH in human liver tumors and can provide molecular-level diagnostic tools for differentiating benign and malignant liver tumors at 3T.

A correlation between the abnormal cerebral glucose metabolism and the progression of Alzheimer’s disease (AD) has been found in previous studies, suggesting that glucose alterations may be used to predict the histopathological diagnosis in AD. In this study, we investigated the dynamic changes of cerebral glucose uptake in vivo using MR glucose chemical exchange saturation transfer (glucoCEST) imaging in a rat model of AD with an intracerebroventricular (i.c.v) injection of amyloid Aβ-protein (25–35), confirmed by Morris water maze and Nissl staining. In total, 6 rats in the AD group and 6 rats in the control group that were given an injection of sterile normal saline were included. At 28 days after injection, all rats performed a 7.0 T MR exanimation, including glucoCEST, diffusion tensor imaging (DTI) and hippocampus magnetic resonance spectra (MRS), to detect the possible metabolic and structural changes in the rat brain. A significantly elevated brain glucoCEST signal in the brain of AD rats was observed, and a decreased brain glucose uptake was also explored during the progression of glucose infusion compared with those in rats of the control group. In addition, there is a significant positive correlation between glucoCEST enhancement (GCE) and myo-Inosito (Ins) in the AD group and the control group (P &lt; 0.05). A significantly reduced number of neurons in the cortex and hippocampus in AD rats combined with the significantly longer escape and a decreased number of crossings were verified at 28 days after Aβ25–35 injection by Nissl staining and Morris water maze, respectively. Our results indicated that an abnormal brain glucose mechanism in AD rats could be detected by glucoCEST imaging, suggesting a new method to explore the occurrence and progress of diabetes-related AD or dementia.