Automated lung texture analysis for assessing interstitial lung disease in systemic sclerosis: Diagnostic accuracy in photon-counting-detector and conventional energy-integrating-detector CT
European Journal of Radiology, 2025
Abstract
Objectives
To evaluate the performance of automated Lung Texture Analysis (LTA) in assessing interstitial lung disease (ILD) in systemic sclerosis (SSc) using low-dose photon-counting detector CT (PCD-CT) compared to conventional low-dose energy-integrating detector CT (EID-CT).
Materials and Methods
In this study of a prospectively enrolled SSc cohort, a post-hoc analysis on 186 patients (93 PCD-CT, 93 EID-CT), matched by propensity scoring, was performed. Visual ILD assessment by three expert radiologists served as the reference standard. Image quality assessment was performed using Likert-scales by expert radiologists and signal-to-noise ratios (SNR). Quantitative ILD features and extent were extracted using LTA (Imbio, CALIPER-based). Diagnostic accuracy was assessed using ROC-AUC analysis.
Results
LTA-based assessment of ILD on PCD-CT demonstrated a higher AUC for detecting ILD presence (AUC = 0.846) compared to EID-CT (AUC = 0.772). PCD-CT also exhibited superior AUCs in identifying specific ILD features, including ground-glass opacities, reticulation, and honeycombing. However, EID-CT showed higher AUCs than PCD-CT in detecting extensive ILD (>20 % lung involvement; AUC = 0.978 vs. 0.842). Despite significantly lower radiation dose, PCD-CT achieved comparable SNR and superior image quality ratings on Likert-scale.
Conclusion
Both EID-CT and PCD-CT demonstrated acceptable to excellent AUC values, indicating their strong applicability in ILD assessment. Further, LTA using PCD-CT consistently provided excellent AUCs for detecting individual ILD features in SSc, supporting its clinical utility despite being trained on PCD-CT data. PCD-CT’s enhanced image quality and lower radiation dose make it a promising tool for longitudinal ILD assessment. Further multicenter validation is warranted.
