Advancing Neurovascular Imaging: Optimization of Reconstruction Kernel and Quantum Iterative Reconstruction for Ultra-high-resolution Photon-Counting Detector CT Angiography of the Head and Neck

Abstract

Rationale and Objectives

To find the optimal reconstruction parameters for ultra-high-resolution (UHR) photon-counting detector CT (PCD-CT) angiography of the head and neck, with a special focus on imaging intracranial aneurysms.

Material and Methods

18 patients with intracranial aneurysms were prospectively enrolled in this single-center study. CT angiograms were acquired in UHR mode on a clinical PCD-CT scanner. Images were reconstructed with six strength levels of a dedicated neurovascular kernel (Hv48–89) and with quantum iterative reconstruction (QIR) levels 1–4. Image noise, contrast-to-noise ratio, and vessel sharpness were determined for all reconstructions. Qualitative image quality was assessed by three readers using a 5-point Likert scale, for the best-performing reconstructions. Aneurysm dome and neck sizes were independently measured by two readers to assess inter-reader reliability.

Results

18 patients (mean age, 64.3 years ± 15 [SD], 5 men,) were evaluated. Three kernels (Hv56, Hv64, Hv72) were identified as best performing in the quantitative analysis. The qualitative analysis demonstrated a consistent preference for QIR level 4 across all kernels in each evaluated category (P<0.001). Hv72 was the most frequently preferred, although it exhibited a higher incidence of image artifacts compared to the other kernels. Inter-reader reliability was high for dome measurements—especially on UHR images—while neck measurements showed greater variability.

Conclusion

Hv72 kernel with QIR level 4 proved to be the optimal combination of CTA parameters among the configurations evaluated. Our results could provide reference for protocol optimization on PCD-CT for neurovascular imaging.