This copy is for personal use only. To order printed copies, contact reprints@rsna.org I n P r e s s 2 Key Points 1. The positive rates of RT-PCR assay and chest CT imaging in our cohort were 59% (601/1014), and 88% (888/1014) for the diagnosis of suspected patients with COVID-19, respectively. 2.With RT-PCR as a reference, the sensitivity of chest CT imaging for COVID-19 was 97% (580/601). In patients with negative RT-PCR results but positive chest CT scans (n=308 patients), 48% (147/308) of patients were re-considered as highly likely cases, with 33% (103/308) as probable cases by a comprehensive evaluation. 3.With analysis of serial RT-PCR assays and CT scans, 60% to 93% of patients had initial positive chest CT consistent with COVID-19 before the initial positive RT-PCR results. 42% of patients showed improvement of follow-up chest CT scans before the RT-PCR results turning negative. Summary StatementChest CT had higher sensitivity for diagnosis of COVID-19 as compared with initial reverse-transcription polymerase chain reaction (RT-PCR) from swab samples in the epidemic area of China. Abbreviations RT-PCR = reverse transcription polymerase chain reaction NCP = novel coronavirus pneumonia PPV = positive predictive value NPV = negative predictive value I n P r e s s 3 Abstract Background: Chest CT is used for diagnosis of 2019 novel coronavirus disease (COVID-19), as an important complement to the reverse-transcription polymerase chain reaction (RT-PCR) tests. Purpose: To investigate the diagnostic value and consistency of chest CT as compared with comparison to RT-PCR assay in COVID-19. underwent both chest CT and RT-PCR tests were included. With RT-PCR as reference standard, the performance of chest CT in diagnosing COVID-19 was assessed. Besides, for patients with multiple RT-PCR assays, the dynamic conversion of RT-PCR results (negative to positive, positive to negative, respectively) was analyzed as compared with serial chest CT scans for those with time-interval of 4 days or more. Results: Of 1014 patients, 59% (601/1014) had positive RT-PCR results, and 88% (888/1014) had positive chest CT scans. The sensitivity of chest CT in suggesting COVID-19 was 97% (95%CI, 95-98%, 580/601 patients) based on positive RT-PCRresults. In patients with negative RT-PCR results, 75% (308/413) had positive chest CT findings; of 308, 48% were considered as highly likely cases, with 33% as probable cases. By analysis of serial RT-PCR assays and CT scans, the mean interval time between the initial negative to positive RT-PCR results was 5.1 ± 1.5 days; the initial positive to subsequent negative RT-PCR result was 6.9 ± 2.3 days). 60% to 93% of cases had initial positive CT consistent with COVID-19 prior (or parallel) to the initial positive RT-PCR results. 42% (24/57) cases showed improvement in follow-up chest CT scans before the RT-PCR results turning negative. Conclusion:Chest CT has a high sensitivity for diagnosis of COVID-19. Chest CT may be considered as a primary tool for the current COVID-19 detection in epidemic ar...

The severity of the pulmonary manifestations of COVID-19 can be quantitatively evaluated from chest CT using a deep-learning method. There were significant differences in lung opacification percentage, as measured by the deep learning algorithm, among patients with different clinical severity. This automated tool for quantification of lung involvement may be used to monitor the disease progression and understand the temporal evolution of COVID-19. Abbreviations ARDS = acute respiratory distress syndrome, COVID-19 = coronavirus disease 19, GGO = ground glass opacity, HRCT = high resolution computed tomography, RT-PCR = reverse transcription-polymerase chain reaction, SARS-Cov-2 = severe acute respiratory syndrome coronavirus 2, SpO2 =pulse oxygen saturation

Magnetic resonance imaging (MRI) contrast agents are pharmaceuticals used widely in MRI examinations. Gadolinium-based MRI contrast agents (GBCAs) are by far the most commonly used. To date, nine GBCAs have been commercialized for clinical use, primarily indicated in the central nervous system, vasculature, and whole body. GBCAs primarily lower the T(1) in vivo to create higher signal in T(1)-weighted MRI scans where GBCAs are concentrated. GBCAs are unique among pharmaceuticals, being water proton relaxation catalysts whose effectiveness is characterized by a rate constant known as relaxivity. The relaxivity of each GBCAs depends on a variety of factors that are discussed in terms of both the existing agents and future molecular imaging agents under study by current researchers. Current GBCAs can be divided into four different structural types (macrocyclic, linear, ionic, and nonionic) based on the chemistry of the chelating ligands whose primary purpose is to protect the body from dissociation of the relatively toxic Gd(3+) ion from the ligand. This article discusses how the chemical structure influences inherent and in vivo stability toward dissociation, and how it affects important formulation properties. Although GBCAs have a lower rate of serious adverse events than iodinated contrast agents, they still present some risk.

To analyse the high-resolution computed tomography (HRCT) early imaging features and the changing trend of coronavirus disease 2019 (COVID-19) pneumonia. Materials and Methods: Forty-six patients with COVID-19 pneumonia who had an isolated lesion on the first positive CT were enrolled in this study. The following parameters were recorded for each lesion: sites, sizes, location (peripheral or central), attenuation (ground-glass opacity or consolidation), and other abnormalities (supply pulmonary artery dilation, air bronchogram, interstitial thickening, etc.). The follow-up CT images were compared with the previous CT scans, and the development of the lesions was evaluated. Results: The lesions tended to be peripheral and subpleural. All the lesions exhibited ground-glass opacity with or without consolidation. A higher proportion of supply pulmonary artery dilation (89.13 % [41/46]) and air bronchogram (69.57 % [32/46]) were found. Other findings included thickening of the intralobular interstitium and a halo sign of ground glass around a solid nodule. Cavitation, calcification or lymphadelopathy were not observed. The reticular patterns were noted from the 14 days after symptoms onset in 7 of 20 patients (45 %). At 22-31 days, the lesions were completely absorbed only in 2 of 7 patients (28.57 %). Conclusion:The typical early CT features of COVID-19 pneumonia are ground-glass opacity, and located peripheral or subpleural location, and with supply pulmonary artery dilation. Reticulation was evident after the 2nd week and persisted in half of patients evaluated in 4 weeks after the onset. Long-term follow-up is required to determine whether the reticulation represents irreversible fibrosis.

Non-invasive prediction of isocitrate dehydrogenase (IDH) genotype plays an important role in tumor glioma diagnosis and prognosis. Recently, research has shown that radiology images can be a potential tool for genotype prediction, and fusion of multi-modality data by deep learning methods can further provide complementary information to enhance prediction accuracy. However, it still does not have an effective deep learning architecture to predict IDH genotype with three-dimensional (3D) multimodal medical images. In this paper, we proposed a novel multimodal 3D DenseNet (M3D-DenseNet) model to predict IDH genotypes with multimodal magnetic resonance imaging (MRI) data. To evaluate its performance, we conducted experiments on the BRATS-2017 and The Cancer Genome Atlas breast invasive carcinoma (TCGA-BRCA) dataset to get image data as input and gene mutation information as the target, respectively. We achieved 84.6% accuracy (area under the curve (AUC) = 85.7%) on the validation dataset. To evaluate its generalizability, we applied transfer learning techniques to predict World Health Organization (WHO) grade status, which also achieved a high accuracy of 91.4% (AUC = 94.8%) on validation dataset. With the properties of automatic feature extraction, and effective and high generalizability, M3D-DenseNet can serve as a useful method for other multimodal radiogenomics problems and has the potential to be applied in clinical decision making.

Chinese measured spirometry data. The present study also compared with other published Chinese equations for spirometry. Results: A total of 7,115 eligible individuals aged 4 to 80 years (50.9% females) were recruited. Reference equations against age and height by gender were established, including predicted values and lower limits of normal (LLNs). Validated with Chinese data, the mean percentage differences of Caucasian reference values adjusted with ethnic conversion factors were −10.2% to 1.8%, and the percentages of total subjects under LLNs were 0.1% to 8.9%. Compared with this study, the percentage differences of previous Chinese studies ranged from −17.8% to 11.4%, which were found to significantly overestimate or underestimate lung IntroductionSpirometry has been widely used for diagnosing respiratory diseases, quantifying disease severity, and assessing disease prognosis (1,2). Accurate interpretation of spirometry requires appropriate reference values derived from its own ancestry population (3), including lower limits of normal (LLNs), which could be helpful for assessment of abnormal pulmonary function in patients with pulmonary diseases.There are over 40 million overseas Chinese (4) and 1.3 billion mainland Chinese (5) in the world (about 22% of the global population), indicating the huge medical demand (6). Embarrassingly, standardized nationwide spirometric reference values for Chinese were unavailable.In 2012, Global Lung Function Initiative (3) recommended multi-ethnic reference values for African-Americans, Southeast Asians (SEA-GLI2012) and Northeast Asians (NEA-GLI2012), which were largely established with Caucasian data and adjusted with fixed ethnic conversion factors in the whole age range. In addition, other Caucasian reference values adjusted with fixed ethnic conversion factors were also applied in China (7,8), such as European Committee of Steel and Coal equations adjusted for Chinese with the suggestion of Zheng et al. (Chinese-ECSC1993) (9,10), and the third national health and nutrition examination surveys equations adjusted with 0.88 times for Asian-American (Asian-NHANESIII 0.88) (11,12). Given the dynamic changes of gene, economic, environment, nutrition and et al., it remains unknown whether those fixed ethnic conversion factors reliably reflect the difference of spirometry between Caucasians and Chinese.Although several spirometric reference values for Chinese have been published (13-22), the major disadvantages in these studies limited the nationwide use, including small samples, limited age ranges, small local regions, as well as different study protocols and quality control. Without LLNs for nationwide Chinese, a fixed 0.7 of forced expiratory volume in 1 second to forced vital capacity (FEV 1 /FVC) instead of LLNs was frequently applied for the diagnosis of "airflow limitation" in previous studies (7,23,24), leading possible underdiagnosis in younger subjects and over diagnosis in elderly. Moreover, In the nationwide questionnaire surveys on clinical application of pulmon...

SEMAC-VAT (2D) and MSVAT-SPACE (3D) demonstrated a consistent, marked reduction of metal artifacts for different metal implants and offered flexible image contrasts (T1, T2, PD and STIR) with high image quality. These techniques likely will improve the evaluation of postoperative patients with metal implants.

Objectives To investigate the association of chest CT findings with mortality in clinical management of older patients. Methods From January 21 to February 14, 2020, 98 older patients (≥ 60 years) who had undergone chest CT scans ("initial CT") on admission were enrolled. Manifestation and CT score were compared between the death group and the survival group. In each group, patients were sub-grouped based on the time interval between symptom onset and the "initial CT" scan: subgroup1 (interval ≤ 5 days), subgroup2 (interval between 6 and 10 days), and subgroup3 (interval > 10 days). Adjusted ROC curve after adjustment for age and gender was applied. Results Consolidations on CT images were more common in the death group (n = 46) than in the survival group (n = 52) (53.2% vs 32.0%, p < 0.001). For subgroup1 and subgroup2, a higher mean CT score was found for the death group (33.0 ± 17.1 vs 12.9 ± 8.7, p < 0.001; 38.8 ± 12.3 vs 24.3 ± 11.9, p = 0.002, respectively) and no significant difference of CT score was identified with respect to subgroup3 (p = 0.144). In subgroup1, CT score of 14.5 with a sensitivity of 83.3% and a specificity of 77.3% for the prediction of mortality was an optimal cutoff value, with an adjusted AUC of 0.881. In subgroup2, CT score of 27.5 with a sensitivity of 87.5% and a specificity of 70.6% for the prediction of mortality was an optimal cutoff value, with an adjusted AUC of 0.895. Conclusions "Initial CT" scores may be useful to speculate prognosis and stratify patients. Severe manifestation on CT at an early stage may indicate poor prognosis for older patients with COVID-19. Key Points• Severe manifestation on CT at an early stage may indicate poor prognosis for older patients with COVID-19.• Radiologists should pay attention to the time interval between symptom onsets and CT scans of patients with COVID-19.• Consolidations on CT images were more common in death patients than in survival patients.