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.
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.
Study Type
OBSERVATIONAL
Enrollment
140
Radiomic model for PCP diagnosis
Chinese PLA General Hospital
Beijing, Beijing Municipality, China
the diagnostic performance of radiomic model in the PCP diagnosis
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.
Time frame: 6 months
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