Objective: To summarize the original CT features of Pneumocystis Jirovecii pneumonia in patients with hematological diseases. Methods: A retrospective analysis was carried out in 46 patients with proven pneumocystis pneumonia (PJP) in the Hospital of Hematology, Chinese Academy of Medical Sciences between January 2014 and December 2021. All patients had multiple chests CT and related laboratory examinations, imaging typing were conducted based on the initial CT presentation, and the distinct imaging types were analyzed against the clinical data. Results: In the analysis, there were 46 patients with proven pathogenesis, 33 males, and 13 females, with a median age of 37.5 (2-65) years. The diagnosis was validated by bronchoalveolar lavage fluid (BALF) hexamine silver staining in 11 patients and clinically diagnosed in 35 cases. Of the 35 clinically diagnosed patients, 16 were diagnosed by alveolar lavage fluid macrogenomic sequencing (BALF-mNGS) and 19 by peripheral blood macrogenomic sequencing (PB-mNGS) . The initial chest CT presentation was categorized into 4 types, including ground glass (GGO) type in 25 cases (56.5%) , nodular type in 10 cases (21.7%) , fibrosis type in 4 cases (8.7%) , and mixed type in 5 cases (13.0%) . There was no substantial discrepancy in CT types among confirmed patients, BALF-mNGS diagnosed patients and PB-mNGS diagnosed patients (χ(2)=11.039, P=0.087) . The CT manifestations of confirmed patients and PB-mNGS diagnosed patients were primarily GGO type (67.6%, 73.7%) , while that of BALF-mNGS diagnosed patients were nodular type (37.5%) . Of the 46 patients, 63.0% (29/46) had lymphocytopenia in the peripheral blood, 25.6% (10/39) with positive serum G test, and 77.1% (27/35) with elevated serum lactate dehydrogenase (LDH) . There were no great discrepancies in the rates of lymphopenia in peripheral blood, positive G-test, and increased LDH among different CT types (all P>0.05) . Conclusion: The initial chest CT findings of PJP in patients with hematological diseases were relatively prevalent with multiple GGO in both lungs. Nodular and fibrosis types were also the initial imaging findings for PJP.
Male ; Female ; Humans ; Adult ; Middle Aged ; Aged ; Pneumonia, Pneumocystis/diagnostic imaging* ; Retrospective Studies ; Pneumocystis carinii ; Hematologic Diseases/complications* ; Tomography, X-Ray Computed ; Fibrosis

BACKGROUND: Pneumonia-like primary pulmonary lymphoma (PPL) was commonly misdiagnosed as infectious pneumonia, leading to delayed treatment. The purpose of this study was to establish a computed tomography (CT)-based radiomics model to differentiate pneumonia-like PPL from infectious pneumonia. METHODS: In this retrospective study, 79 patients with pneumonia-like PPL and 176 patients with infectious pneumonia from 12 medical centers were enrolled. Patients from center 1 to center 7 were assigned to the training or validation cohort, and the remaining patients from other centers were used as the external test cohort. Radiomics features were extracted from CT images. A three-step procedure was applied for radiomics feature selection and radiomics signature building, including the inter- and intra-class correlation coefficients (ICCs), a one-way analysis of variance (ANOVA), and least absolute shrinkage and selection operator (LASSO). Univariate and multivariate analyses were used to identify the significant clinicoradiological variables and construct a clinical factor model. Two radiologists reviewed the CT images for the external test set. Performance of the radiomics model, clinical factor model, and each radiologist were assessed by receiver operating characteristic, and area under the curve (AUC) was compared. RESULTS: A total of 144 patients (44 with pneumonia-like PPL and 100 infectious pneumonia) were in the training cohort, 38 patients (12 with pneumonia-like PPL and 26 infectious pneumonia) were in the validation cohort, and 73 patients (23 with pneumonia-like PPL and 50 infectious pneumonia) were in the external test cohort. Twenty-three radiomics features were selected to build the radiomics model, which yielded AUCs of 0.95 (95% confidence interval [CI]: 0.94-0.99), 0.93 (95% CI: 0.85-0.98), and 0.94 (95% CI: 0.87-0.99) in the training, validation, and external test cohort, respectively. The AUCs for the two readers and clinical factor model were 0.74 (95% CI: 0.63-0.83), 0.72 (95% CI: 0.62-0.82), and 0.73 (95% CI: 0.62-0.84) in the external test cohort, respectively. The radiomics model outperformed both the readers' interpretation and clinical factor model ( P <0.05). CONCLUSIONS The CT-based radiomics model may provide an effective and non-invasive tool to differentiate pneumonia-like PPL from infectious pneumonia, which might provide assistance for clinicians in tailoring precise therapy.
Humans ; Retrospective Studies ; Pneumonia/diagnostic imaging* ; Analysis of Variance ; Tomography, X-Ray Computed ; Lymphoma/diagnostic imaging*

The coronavirus disease 2019 (COVID-19) is typically diagnosed by specific assays that detect viral nucleic acid from the upper respiratory tract; however, this may miss infections involving only the lower airways. Computed tomography (CT) has been described as a diagnostic modality in the COVID-19 diagnosis and treatment plan. We present a case series with virologically confirmed COVID-19 pneumonia. Variable CT features were observed: consolidation with ground-glass opacities, ground-glass opacities with subpleural reticular bands, and an anterior-posterior gradient of lung abnormalities resembling that of acute respiratory distress syndrome. Evolution of CT findings was observed in one patient, where there was interval resolution of bilateral lung consolidation with development of bronchiolectasis and subpleural fibrotic bands. While sensitive for detecting lung parenchymal abnormalities in COVID-19 pneumonia, the use of CT for initial diagnosis is discouraged and should be reserved for specific clinical indications. Interpretation of chest CT findings should be correlated with duration of symptoms to better determine the disease stage and aid in patient management.
Aged ; Betacoronavirus ; Coronavirus Infections ; diagnosis ; Diagnosis, Differential ; Female ; Humans ; Lung ; diagnostic imaging ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral ; diagnosis ; Tomography, X-Ray Computed ; methods

Betacoronavirus ; Coronavirus Infections ; diagnosis ; Diagnosis, Differential ; Diagnostic Imaging ; methods ; Humans ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral ; diagnosis ; virology ; Radiography, Thoracic ; methods ; Tomography, X-Ray Computed ; methods

Betacoronavirus ; Coronavirus Infections ; diagnosis ; epidemiology ; Diagnostic Imaging ; methods ; Humans ; Pandemics ; Pneumonia, Viral ; diagnosis ; epidemiology ; Radiology Department, Hospital ; organization & administration

Coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 and was declared a global pandemic by the World Health Organization on 11 March 2020. A definitive diagnosis of COVID-19 is made after a positive result is obtained on reverse transcription-polymerase chain reaction assay. In Singapore, rigorous contact tracing was practised to contain the spread of the virus. Nasal swabs and chest radiographs (CXR) were also taken from individuals who were suspected to be infected by COVID-19 upon their arrival at a centralised screening centre. From our experience, about 40% of patients who tested positive for COVID-19 had initial CXR that appeared "normal". In this case series, we described the temporal evolution of COVID-19 in patients with an initial "normal" CXR. Since CXR has limited sensitivity and specificity in COVID-19, it is not suitable as a first-line diagnostic tool. However, when CXR changes become unequivocally abnormal, close monitoring is recommended to manage potentially severe COVID-19 pneumonia.
Adult ; Betacoronavirus ; Clinical Laboratory Techniques ; Coronavirus Infections ; complications ; diagnosis ; diagnostic imaging ; Female ; Humans ; Lung ; diagnostic imaging ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral ; complications ; diagnostic imaging ; Radiography ; Sensitivity and Specificity

BACKGROUND: The 2019 novel coronavirus (2019-nCoV) causing an outbreak of pneumonia in Wuhan, Hubei province of China was isolated in January 2020. This study aims to investigate its epidemiologic history, and analyze the clinical characteristics, treatment regimens, and prognosis of patients infected with 2019-nCoV during this outbreak. METHODS: Clinical data from 137 2019-nCoV-infected patients admitted to the respiratory departments of nine tertiary hospitals in Hubei province from December 30, 2019 to January 24, 2020 were retrospectively collected, including general status, clinical manifestations, laboratory test results, imaging characteristics, and treatment regimens. RESULTS: None of the 137 patients (61 males, 76 females, aged 20-83 years, median age 57 years) had a definite history of exposure to Huanan Seafood Wholesale Market. Major initial symptoms included fever (112/137, 81.8%), coughing (66/137, 48.2%), and muscle pain or fatigue (44/137, 32.1%), with other, less typical initial symptoms observed at low frequency, including heart palpitations, diarrhea, and headache. Nearly 80% of the patients had normal or decreased white blood cell counts, and 72.3% (99/137) had lymphocytopenia. Lung involvement was present in all cases, with most chest computed tomography scans showing lesions in multiple lung lobes, some of which were dense; ground-glass opacity co-existed with consolidation shadows or cord-like shadows. Given the lack of effective drugs, treatment focused on symptomatic and respiratory support. Immunoglobulin G was delivered to some critically ill patients according to their conditions. Systemic corticosteroid treatment did not show significant benefits. Notably, early respiratory support facilitated disease recovery and improved prognosis. The risk of death was primarily associated with age, underlying chronic diseases, and median interval from the appearance of initial symptoms to dyspnea. CONCLUSIONS The majority of patients with 2019-nCoV pneumonia present with fever as the first symptom, and most of them still showed typical manifestations of viral pneumonia on chest imaging. Middle-aged and elderly patients with underlying comorbidities are susceptible to respiratory failure and may have a poorer prognosis.
Adult ; Aged ; Aged, 80 and over ; Betacoronavirus ; China ; Coronavirus Infections ; complications ; diagnostic imaging ; Female ; Fever ; etiology ; Humans ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral ; complications ; diagnostic imaging ; Tertiary Care Centers ; Tomography, X-Ray Computed ; Young Adult

BACKGROUND: Human infections with zoonotic coronaviruses (CoVs), including severe acute respiratory syndrome (SARS)-CoV and Middle East respiratory syndrome (MERS)-CoV, have raised great public health concern globally. Here, we report a novel bat-origin CoV causing severe and fatal pneumonia in humans. METHODS: We collected clinical data and bronchoalveolar lavage (BAL) specimens from five patients with severe pneumonia from Wuhan Jinyintan Hospital, Hubei province, China. Nucleic acids of the BAL were extracted and subjected to next-generation sequencing. Virus isolation was carried out, and maximum-likelihood phylogenetic trees were constructed. RESULTS: Five patients hospitalized from December 18 to December 29, 2019 presented with fever, cough, and dyspnea accompanied by complications of acute respiratory distress syndrome. Chest radiography revealed diffuse opacities and consolidation. One of these patients died. Sequence results revealed the presence of a previously unknown β-CoV strain in all five patients, with 99.8% to 99.9% nucleotide identities among the isolates. These isolates showed 79.0% nucleotide identity with the sequence of SARS-CoV (GenBank NC_004718) and 51.8% identity with the sequence of MERS-CoV (GenBank NC_019843). The virus is phylogenetically closest to a bat SARS-like CoV (SL-ZC45, GenBank MG772933) with 87.6% to 87.7% nucleotide identity, but is in a separate clade. Moreover, these viruses have a single intact open reading frame gene 8, as a further indicator of bat-origin CoVs. However, the amino acid sequence of the tentative receptor-binding domain resembles that of SARS-CoV, indicating that these viruses might use the same receptor. CONCLUSION A novel bat-borne CoV was identified that is associated with severe and fatal respiratory disease in humans.
Adult ; Aged ; Betacoronavirus ; genetics ; isolation & purification ; Coronavirus Infections ; diagnostic imaging ; therapy ; virology ; Female ; Humans ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral ; diagnostic imaging ; therapy ; virology ; Tomography, X-Ray ; Treatment Outcome

The aim of this study was to investigate the clinical characteristics of neonates born to SARS-CoV-2 infected mothers and increase the current knowledge on the perinatal consequences of COVID-19. Nineteen neonates were admitted to Tongji Hospital from January 31 to February 29, 2020. Their mothers were clinically diagnosed or laboratory-confirmed with COVID-19. We prospectively collected and analyzed data of mothers and infants. There are 19 neonates included in the research. Among them, 10 mothers were confirmed COVID-19 by positive SARS-CoV-2 RT-PCR in throat swab, and 9 mothers were clinically diagnosed with COVID-19. Delivery occurred in an isolation room and neonates were immediately separated from the mothers and isolated for at least 14 days. No fetal distress was found. Gestational age of the neonates was 38.6 ± 1.5 weeks, and average birth weight was 3293 ± 425 g. SARS-CoV-2 RT-PCR in throat swab, urine, and feces of all neonates were negative. SARS-CoV-2 RT-PCR in breast milk and amniotic fluid was negative too. None of the neonates developed clinical, radiologic, hematologic, or biochemical evidence of COVID-19. No vertical transmission of SARS-CoV-2 and no perinatal complications in the third trimester were found in our study. The delivery should occur in isolation and neonates should be separated from the infected mothers and care givers.
Adult ; Betacoronavirus ; Coronavirus Infections ; diagnostic imaging ; transmission ; Female ; Humans ; Infant, Newborn ; Infectious Disease Transmission, Vertical ; Mothers ; Pandemics ; Pneumonia, Viral ; diagnostic imaging ; transmission ; Pregnancy ; Prospective Studies ; Tomography, X-Ray Computed

Coronavirus disease 2019 (COVID-19) has spread rapidly around the world. In order to diagnose COVID-19 more quickly, in this paper, a depthwise separable DenseNet was proposed. The paper constructed a deep learning model with 2 905 chest X-ray images as experimental dataset. In order to enhance the contrast, the contrast limited adaptive histogram equalization (CLAHE) algorithm was used to preprocess the X-ray image before network training, then the images were put into the training network and the parameters of the network were adjusted to the optimal. Meanwhile, Leaky ReLU was selected as the activation function. VGG16, ResNet18, ResNet34, DenseNet121 and SDenseNet models were used to compare with the model proposed in this paper. Compared with ResNet34, the proposed classification model of pneumonia had improved 2.0%, 2.3% and 1.5% in accuracy, sensitivity and specificity respectively. Compared with the SDenseNet network without depthwise separable convolution, number of parameters of the proposed model was reduced by 43.9%, but the classification effect did not decrease. It can be found that the proposed DWSDenseNet has a good classification effect on the COVID-19 chest X-ray images dataset. Under the condition of ensuring the accuracy as much as possible, the depthwise separable convolution can effectively reduce number of parameters of the model.
Betacoronavirus ; Coronavirus Infections ; diagnostic imaging ; Deep Learning ; Humans ; Pandemics ; Pneumonia, Viral ; diagnostic imaging ; X-Rays