Early differential diagnosis model for acute radiation pneumonitis based on multiple parameters

Area of Science:

• Oncology
• Radiotherapy
• Pulmonology
• Medical Diagnostics

Background:

• Distinguishing acute radiation pneumonitis (ARP) from infectious pneumonitis (IP) is crucial for effective patient management following radiotherapy.
• Current diagnostic methods may lack the specificity and sensitivity required for early and accurate differentiation.
• Developing a robust diagnostic model can improve treatment strategies and patient outcomes.

Purpose of the Study:

• To construct and validate a diagnostic model for the early differentiation of acute radiation pneumonitis (ARP) and infectious pneumonitis (IP).
• To identify key radiophysical, imaging, and serological parameters predictive of ARP.
• To assess the diagnostic performance of the developed model compared to individual indicators.

Main Methods:

• Retrospective analysis of 152 patients diagnosed with ARP (91) or IP (61) after radiotherapy.
• Collection of radiophysical parameters, imaging characteristics, and serological indicators.
• Application of logistic univariate and multivariate analyses to identify independent diagnostic factors and construct a predictive model (nomogram).

Main Results:

• Univariate analysis identified positional relation between lesions and V20 area (PRLV), procalcitonin (PCT), C-reactive protein (CRP), mean lung dose (MLD), and V20 as correlated with ARP.
• Multivariate analysis revealed PRLV, PCT, white blood cell (WBC), and MLD as independent diagnostic factors.
• The developed nomogram model demonstrated high diagnostic accuracy (AUC 0.849) with sensitivity (82.4%) and specificity (82.0%), outperforming single indicators.

Conclusions:

• The constructed diagnosis model shows significant value in the differential diagnosis between ARP and IP.
• The model's high sensitivity and specificity suggest its utility for early and accurate patient stratification.
• Further validation in diverse clinical settings is warranted to confirm its broad applicability.