Development and internal validation of a CT radiomics-based model for severity classification in HIV-associated...

Severity assessment of human immunodeficiency virus (HIV)-associated Pneumocystis jirovecii pneumonia (PJP) is clinically important because arterial blood gas indices are standard but may not fully capture the heterogeneity of lung involvement on chest computed tomography (CT). We aimed to develop and internally validate a CT radiomics model for classifying severity in adults with confirmed HIV-associated PJP.

This retrospective single-center study included 96 adult patients with confirmed HIV-associated PJP who underwent chest CT at presentation. Disease severity was classified as mild or moderate-to-severe according to room-air arterial blood gas criteria, with moderate-to-severe disease defined as arterial partial pressure of oxygen (PaO₂) <70 mmHg or an alveolar-arterial oxygen gradient (A-aDO₂) ≥35 mmHg. Clinical variables were retrospectively collected from medical records. Patients were randomly divided into training and test cohorts at a ratio of 7:3. Radiomics features were extracted from the bilateral lung parenchyma. After least absolute shrinkage and selection operator regression, features with non-zero coefficients were included in the final radiomics model. In parallel, a clinical logistic model incorporating serum lactate dehydrogenase, β-D-glucan, and CD4 count was developed in the training cohort and tested in the test cohort. Model performance was assessed using the area under the receiver operating characteristic curve (AUC) with 95% confidence intervals (CIs), calibration analysis, decision curve analysis, and pairwise DeLong test comparisons.

Of the 96 patients, 38 were classified as mild and 58 as moderate-to-severe. Patients with moderate-to-severe disease had a higher frequency of dyspnea, higher levels of inflammatory markers, and lower CD4 count. The final radiomics model included 10 features. In the training cohort, the radiomics model achieved an AUC of 0.92 (95% CI: 0.85-0.97), compared with 0.65 (95% CI: 0.51-0.78) for the clinical logistic model. In the test cohort, the radiomics model showed a numerically higher AUC of 0.89 (95% CI: 0.72-1.00), followed by the clinical logistic model at 0.84 (95% CI: 0.68-0.97). Using their respective classification thresholds, the radiomics model yielded a sensitivity of 0.778 (95% CI: 0.548-0.910) and a specificity of 0.818 (95% CI: 0.523-0.949) in the test cohort, while the clinical logistic model yielded a sensitivity of 0.722 (95% CI: 0.491-0.875) and a specificity of 0.909 (95% CI: 0.623-0.984). Pairwise DeLong tests in the test cohort showed no statistically significant difference between the radiomics model and the clinical logistic model.

In this small single-center study, the CT radiomics model showed promising discrimination for severity classification in HIV-associated PJP, but these findings are preliminary and require external multicenter validation before clinical use.