Automated lung texture analysis for assessing interstitial lung disease in systemic sclerosis: Diagnostic accuracy in photon-counting-detector and conventional energy-integrating-detector CT

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.