Prospective ECG-gated High-Pitch Photon-Counting CT Angiography: Evaluation of measurement accuracy for aortic annulus sizing in TAVR planning.

PURPOSE: In planning transcatheter aortic valve replacement (TAVR), retrospective cardiac spiral-CT is recommended to measure aortic annulus with subsequent CT-angiography (CTA) to evaluate access routes. Photon-counting detector (PCD)-CT enables to assess the aortic annulus in desired cardiac phases, using prospective ECG-gated high-pitch CTA. The aim of this study was to evaluate the measurement accuracy of aortic annulus using prospective ECG-gated high-pitch CTA against retrospective spiral-CT reference. METHOD: Thirty patients underwent cardiac spiral-CT and prospective ECG-gated (30% R-R on aortic valve level) high-pitch CTA. Using propensity score matching, another 30 patients were identified whose CTA was performed using high-pitch mode without ECG-synchronization. Two investigators measured annular diameter, perimeter, and area on cardiac spiral-CT and high-pitch CTA. RESULTS: The aortic valve was imaged in systole in 90 % of prospective ECG-gated CTA cases but only 50 % of non-ECG-gated CTA cases (p = 0.002). There was a strong correlation (r ≥ 0.94) without significant differences (p ≥ 0.09) between cardiac spiral-CT and prospective ECG-gated high-pitch CTA for all annulus measurements. In contrast, significant differences were found in annular short-axis diameter and area between cardiac spiral-CT and non-ECG-gated high-pitch CTA (p ≤ 0.03). Furthermore, prospective ECG-gated high-pitch CTA showed significantly reduced radiation exposure compared with cardiac spiral-CT (CTDI 4.52 vs. 24.10 mGy; p < 0.001). CONCLUSION: PCD-CT-based prospective ECG-gated high-pitch scans with targeted systolic acquisition at the level of the aortic valve can simultaneously visualize TAVR access routes and accurately measure systolic annulus size. This approach could aid in optimizing protocols to achieve lower radiation doses in the growing population of younger, low-risk TAVR patients.

Soft Reconstruction Kernels Improve HCC Imaging on a Photon-Counting Detector CT.

RATIONALE AND OBJECTIVES: Hepatocellular carcinoma (HCC) is the only tumor entity that allows non-invasive diagnosis based on imaging without further histological proof. Therefore, excellent image quality is of utmost importance for HCC diagnosis. Novel photon-counting detector (PCD) CT improves image quality via noise reduction and higher spatial resolution, inherently providing spectral information. The aim of this study was to investigate these improvements for HCC imaging with triple-phase liver PCD-CT in a phantom and patient population study focusing on identification of the optimal reconstruction kernel. MATERIALS AND METHODS: Phantom experiments were performed to analyze objective quality characteristics of the regular body and quantitative reconstruction kernels, each with four sharpness levels (36-40-44-48). For 24 patients with viable HCC lesions on PCD-CT, virtual monoenergetic images at 50 keV were reconstructed using these kernels. Quantitative image analysis included contrast-to-noise ratio (CNR) and edge sharpness. Three raters performed qualitative analyses evaluating noise, contrast, lesion conspicuity, and overall image quality. RESULTS: In all contrast phases, the CNR was highest using the kernels with a sharpness level of 36 (all p < 0.05), with no significant influence on lesion sharpness. Softer reconstruction kernels were also rated better regarding noise and image quality (all p < 0.05). No significant differences were found in image contrast and lesion conspicuity. Comparing body and quantitative kernels with equal sharpness levels, there was no difference in image quality criteria, neither regarding in vitro nor in vivo analysis. CONCLUSION: Soft reconstruction kernels yield the best overall quality for the evaluation of HCC in PCD-CT. As the image quality of quantitative kernels with potential for spectral post-processing is not restricted compared to regular body kernels, they should be preferred.