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Dmitrij Kravchenko

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Aug 2026

Optimizing Photon-counting CT for Congenital Heart Disease: The Value of Ultrasharp Kernels in Neonates and Infants.

Purpose To evaluate the image quality of kernel sharpness (KS) and iterative reconstruction (IR) settings in high-pitch photon-counting detector CT for pediatric cardiac imaging. Materials and Methods This retrospective study analyzed photon-counting detector CT data from neonates and infants with congenital heart disease that were acquired between October 2022 and August 2023 at two specialized centers. Images were reconstructed using vascular kernels with varying KS (36, 40, 44, 48, 56, and 60) and IR levels (Q1-Q4) at a 1-mm section thickness. Visual image quality was assessed by one pediatric cardiologist and two radiologists using a five-point Likert scale, with selection of the most diagnostic reconstruction per patient. Image sharpness was quantified using edge rise distance, and signal-to-noise ratio and contrast-to-noise ratio were calculated. Statistical analysis used linear mixed models, with results reported as regression estimates with 95% CIs. Results A total of 47 patients (median age, 82 days [IQR, 4-227 days]; 28 male) were included. Subjective image quality improved with increasing KS (β = 0.07 Likert points per level; 95% CI: 0.06, 0.09) and IR level (β = 0.21 Likert points per level; 95% CI: 0.19, 0.23) (both P < .001). The most preferred reconstruction was a KS of 60 (ultrasharp kernel) with an IR of Q4 (highest IR level) (77 of 141 votes). Edge-rise distance decreased with increasing KS (-0.07 mm; 95% CI: -0.08, -0.06) and IR level (-0.06 mm; 95% CI: -0.06, -0.04) (both P < .001). Signal-to-noise ratio and contrast-to-noise ratio increased significantly with higher IR levels (both P < .001). Conclusion KS and IR selection significantly affected image quality in pediatric cardiac photon-counting detector CT, with ultrasharp reconstruction providing the best quantitative and visual image quality for evaluation of complex coronary and structural heart anomalies. Keywords: Pediatrics, CT-Photon Counting, Cardiac, Pediatric Cardiac Imaging, Congenital Heart Disease, Image Quality Optimization, Kernel Sharpness Supplemental material is available for this article. © RSNA, 2026.

B. Salam, Alois M. Sprinkart, C. Hart et al. · 0 citations
Open access Jul 2026

Deep learning-based detection of acute pancreatitis on abdominal contrast-enhanced CT

DL enabled accurate CECT-based identification of AP in this retrospective multicenter cohort, with performance maintained in an independent external dataset, and showed promising performance for CECT-based acute pancreatitis detection.

Oleksandra Seidel, M. Theis, Sebastian Nowak et al. · 0 citations