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Differences and similarities of high-resolution computed tomography features between pneumocystis pneumonia and cytomegalovirus pneumonia in AIDS patients.

ABSTRACT: BACKGROUND:Accurately differentiating pneumocystis from cytomegalovirus pneumonia is crucial for correct therapy selection in AIDS patients. Hence, the goal of this study was to compare the computerized tomography (CT) features of pneumocystis pneumonia and cytomegalovirus pneumonia in AIDS patients and identify clinical hallmarks to accurately distinguish these two pathologies. METHODS:A total of 112 AIDS patients (78 with pneumocystis pneumonia and 34 cytomegalovirus pneumonia) at Beijing Ditan Hospital from January 2017 to May 2019 were included in this study. Two experienced chest radiologists retrospectively reviewed CT images for 17 features including ground-glass opacity, consolidation, nodules, and halo sign. Binary logistic regression analyses were conducted to identify the significant parameters that distinguished pneumocystis pneumonia from cytomegalovirus pneumonia. Correlations were analyzed by Pearson or Spearman correlation analyses. Result were considered significant if P??0.05) were common in both groups. CONCLUSIONS:Analysis of consolidation, nodules, and halo signs may contribute to the differential diagnosis of pneumocystis pneumonia or cytomegalovirus pneumonia. However, some CT features considered typical in one or other diseases appear with similar frequency in both cohorts of AIDS patients. CT features are potentially useful for the differential diagnosis of pneumocystis pneumonia and cytomegalovirus pneumonia in AIDS patients.

SUBMITTER: Du CJ

PROVIDER: S-EPMC7586649 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Differences and similarities of high-resolution computed tomography features between pneumocystis pneumonia and cytomegalovirus pneumonia in AIDS patients.

Du Chun-Jing CJ Liu Jing-Yuan JY Chen Hui H Yan Shuo S Pu Lin L Xiong Hao-Feng HF Xiang Pan P Li Chuan-Sheng CS Zhang Ming M Xie Ru-Ming RM Chen Bu-Dong BD Li Ang A

Infectious diseases of poverty 20201026 1

<h4>Background</h4>Accurately differentiating pneumocystis from cytomegalovirus pneumonia is crucial for correct therapy selection in AIDS patients. Hence, the goal of this study was to compare the computerized tomography (CT) features of pneumocystis pneumonia and cytomegalovirus pneumonia in AIDS patients and identify clinical hallmarks to accurately distinguish these two pathologies.<h4>Methods</h4>A total of 112 AIDS patients (78 with pneumocystis pneumonia and 34 cytomegalovirus pneumonia) ...[more]

PMID: 33106188

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Project description:ObjectiveThe aim of our study was to assess the effect of a short-term treatment with low-moderate corticosteroid (CS) doses by both a quantitative and qualitative assessment of chest HRCT of COVID-19 pneumonia.MethodsCORTICOVID is a single-center, cross-sectional, retrospective study involving severe/critical COVID-19 patients with mild/moderate ARDS. Lung total severity score was obtained according to Chung and colleagues. Moreover, the relative percentages of lung total severity score by ground glass opacities, consolidations, crazy paving, and linear bands were computed. Chest HRCT scores, P/F ratio, and laboratory parameters were evaluated before (pre-CS) and 7-10 days after (post-CS) methylprednisolone of 0.5-0.8 mg/kg/day.FindingsA total of 34 severe/critical COVID-19 patients were included in the study, of which 17 received Standard of Care (SoC) and 17 CS therapy in add-on. CS treatment disclosed a significant decrease in HRCT total severity score [median = 6 (IQR: 5-7.5) versus 10 (IQR: 9-13) in SoC, p < 0.001], as well in single consolidations [median = 0.33 (IQR: 0-0.92) versus 6.73 (IQR: 2.49-8.03) in SoC, p < 0.001] and crazy paving scores [mean = 0.19 (SD = 0.53) versus 1.79 (SD = 2.71) in SoC, p = 0.010], along with a significant increase in linear bands [mean = 2.56 (SD = 1.65) versus 0.97 (SD = 1.30) in SoC, p = 0.006]. GGO score instead did not significantly differ at the end of treatment between the two groups. Most post-CS GGO, however, derived from previous consolidations and crazy paving [median = 1.5 (0.35-3.81) versus 2 (1.25-3.8) pre-CS; p = 0.579], while pre-CS GGO significantly decreased after methylprednisolone therapy [median = 0.66 (0.05-1.33) versus 1.5 (0.35-3.81) pre-CS; p = 0.004]. CS therapy further determined a significant improvement in P/F levels [median P/F = 310 (IQR: 235.5-370) versus 136 (IQR: 98.5-211.75) in SoC; p < 0.001], and a significant increase in white blood cells, lymphocytes, and neutrophils absolute values.ConclusionThe improvement of all chest HRCT findings further supports the role of CS adjunctive therapy in severe/critical COVID-19 pneumonia.

Project description:BackgroundPneumocystis jirovecii pneumonia (PCP) could be fatal to patients without human immunodeficiency virus (HIV) infection. Current diagnostic methods are either invasive or inaccurate. We aimed to establish an accurate and non-invasive radiomics-based way to identify the risk of PCP infection in non-HIV patients with computed tomography (CT) manifestation of pneumonia.MethodsThis is a retrospective study including non-HIV patients hospitalized for suspected PCP from January 2010 to December 2022 in one hospital. The patients were randomized in a 7:3 ratio into training and validation cohorts. Computed tomography (CT)-based radiomics features were extracted automatically and used to construct a radiomics model. A diagnostic model with traditional clinical and CT features was also built. The area under the curve (AUC) were calculated and used to evaluate the diagnostic performance of the models. The combination of the radiomics features and serum β-D-glucan levels was also evaluated for PCP diagnosis.ResultsA total of 140 patients (PCP: N = 61, non-PCP: N = 79) were randomized into training (N = 97) and validation (N = 43) cohorts. The radiomics model consisting of nine radiomic features performed significantly better (AUC = 0.954; 95% CI: 0.898-1.000) than the traditional model consisting of serum β-D-glucan levels (AUC = 0.752; 95% CI: 0.597-0.908) in identifying PCP (P = 0.002). The combination of radiomics features and serum β-D-glucan levels showed an accuracy of 95.8% for identifying PCP infection (positive predictive value: 95.7%, negative predictive value: 95.8%).ConclusionsRadiomics showed good diagnostic performance in differentiating PCP from other types of pneumonia in non-HIV patients. A combined diagnostic method including radiomics and serum β-D-glucan has the potential to provide an accurate and non-invasive way to identify the risk of PCP infection in non-HIV patients with CT manifestation of pneumonia.Trial registrationClinicalTrials.gov (NCT05701631).

Project description:BackgroundAsbestosis and fibrotic hypersensitivity pneumonitis (FHP) share the pathogenetic mechanisms induced bronchiolocentric fibrotic process secondary to inhalation exposure. Under the occupational and environmental mixed exposures, asbestosis and FHP are needed to make the differential diagnoses on high-resolution computed tomography (HRCT), especially in the countries still using asbestos. The study aimed to analyze the HRCT features of asbestosis versus FHP.MethodsThe patients with asbestosis or with HP were sequentially recruited in this comparative study at Beijing Chaoyang Hospital between January 2006 and December 2016. Patients' clinical data were obtained from a predesigned charts. The international classification of HRCT for occupational and environmental respiratory diseases was used to categorize chest imaging findings in patients. The calculation of test statistics was used to compare the imaging features of asbestosis and FHP.Results341 patients with asbestosis and 158 patients with HP were sequentially recruited, among which 204 patients with asbestosis and 74 patients with FHP were eligible for data analysis. Patients with asbestosis were older and had a longer latent period until disease manifestation than those with FHP. Asbestosis was characterized by irregular and/or linear opacities, with lower lung preponderance, accompanied by ground-glass opacities and mosaic attenuation. Notably, 98.5% of patients with asbestosis showed benign pleural abnormalities, and 39.7% of these patients had diffuse pleural thickening with parenchymal bands and/or rounded atelectasis. Abnormalities of the mediastinal and diaphragmatic pleura were observed only in cases of asbestosis, and this finding showed high specificity for the diagnosis for asbestosis compared with that for FHP. Subpleural dots or diaphragmatic pleural abnormalities showed moderate sensitivity and high specificity for diagnosis of asbestosis compared with that for FHP. Interobserver reliability was good for evaluation of imaging findings including honeycombing, pleural calcification, lymphadenectasis, and lymph node calcification.ConclusionsHRCT-based imaging findings can distinguish between asbestosis and FHP to a certain extent, particularly with regard to subpleural dots and diaphragmatic pleural abnormalities that characterize the former.

Project description:OBJECTIVES:We propose a novel computational approach for the automated classification of classic versus atypical usual interstitial pneumonia (UIP). MATERIALS AND METHODS:Thirty-three patients with UIP were enrolled in this study. They were classified as classic versus atypical UIP by a consensus of 2 thoracic radiologists with more than 15 years of experience using the American Thoracic Society evidence-based guidelines for computed tomography diagnosis of UIP. Two cardiothoracic fellows with 1 year of subspecialty training provided independent readings. The system is based on regional characterization of the morphological tissue properties of lung using volumetric texture analysis of multiple-detector computed tomography images. A simple digital atlas with 36 lung subregions is used to locate texture properties, from which the responses of multidirectional Riesz wavelets are obtained. Machine learning is used to aggregate and to map the regional texture attributes to a simple score that can be used to stratify patients with UIP into classic and atypical subtypes. RESULTS:We compared the predictions on the basis of regional volumetric texture analysis with the ground truth established by expert consensus. The area under the receiver operating characteristic curve of the proposed score was estimated to be 0.81 using a leave-one-patient-out cross-validation, with high specificity for classic UIP. The performance of our automated method was found to be similar to that of the 2 fellows and to the agreement between experienced chest radiologists reported in the literature. However, the errors of our method and the fellows occurred on different cases, which suggests that combining human and computerized evaluations may be synergistic. CONCLUSIONS:Our results are encouraging and suggest that an automated system may be useful in routine clinical practice as a diagnostic aid for identifying patients with complex lung disease such as classic UIP, obviating the need for invasive surgical lung biopsy and its associated risks.

Dataset Information

Differences and similarities of high-resolution computed tomography features between pneumocystis pneumonia and cytomegalovirus pneumonia in AIDS patients.

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Differences and similarities of high-resolution computed tomography features between pneumocystis pneumonia and cytomegalovirus pneumonia in AIDS patients.

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