Radiomics Model for the Diagnosis of Pneumocystis Jirovecii Pneumonia in Non-HIV Patients
- Conditions
- Pneumocystis Jirovecii Pneumonia
- Interventions
- Diagnostic Test: Radiomic model
- Registration Number
- NCT05701631
- Lead Sponsor
- Chinese PLA General Hospital
- Brief Summary
To evaluate the performance of radiomics in differentiating Pneumocystis jirovecii pneumonia (PCP) from other types of pneumonia and to improve the diagnostic efficacy of non-invasive tests in non-HIV patients.
- Detailed Description
Retrospective study, including non-HIV patients hospitalized for suspected PCP from January 2010 to December 2022. The included patients were randomized in a 7:3 ratio into training and validation cohorts. Radiomic features were extracted from semi-automatically identified infected areas in computed tomography (CT) scans and used to construct a radiomic model, which was then compared to a clinical-imaging model built with clinical and semantic CT features in terms of diagnostic performance of PCP. The combination of the radiomic model and serum β-D-glucan levels was also evaluated for PCP diagnosis.
Recruitment & Eligibility
- Status
- ACTIVE_NOT_RECRUITING
- Sex
- All
- Target Recruitment
- 140
- aged over eighteen years;
- presence of an underlying disease known to be associated with PCP
- symptoms of lower respiratory tract infection, such as fever, cough or dyspnea
- signs of lung infection on high resolution CT at the on-set of the disease
- received BAL examination within three days after CT scans
- underwent qPCR and IF staining tests on the BAL fluid sample.
- with HIV infection
- taking trimethoprim-sulfamethoxazole for prophylaxis
- undiagnosed by qPCR and IF staining tests
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description non-HIV patients hospitalized for suspected PCP Radiomic model non-HIV patients hospitalized for suspected PCP
- Primary Outcome Measures
Name Time Method the diagnostic performance of radiomic model in the PCP diagnosis 6 months The included patients were randomized in a 7:3 ratio into training and validation cohorts. Radiomic features were extracted from semi-automatically identified infected areas in computed tomography (CT) scans and used to construct a radiomic model. Then, the area under the curve (AUC) of the receiver operating characteristic (ROC) curves were calculated and used to evaluate the diagnostic performance (accuracy, sensitivity, specialty, positive predictive value, negative predictive value) of the model for PCP diagnosis in both training and validation cohorts.
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Chinese PLA General Hospital
🇨🇳Beijing, Beijing, China