Potential of Employing a Quantum Iterative Reconstruction Algorithm for Ultra-high-resolution Photon-counting Detector CT of the Hip

Introduction: This study investigated the image quality of a new quantum iterative reconstruction algorithm (QIR) for high resolution photon-counting CT of the hip.

Methods: Using a first-generation photon-counting CT scanner, five cadaveric specimens were examined with ultra-high-resolution protocols matched for radiation dose. Images were post-processed with a sharp convolution kernel and five different strength levels of iterative reconstruction (QIR 0 - QIR 4). Subjective image quality was rated independently by three radiologists on a five-point scale. Intraclass correlation coefficients (ICC) were computed for assessing interrater agreement. Objective image quality was evaluated by means of contrast-to-noise-ratios (CNR) in bone and muscle tissue.

Results: For osseous tissue, subjective image quality was rated best for QIR 2 reformatting (median 5 [interquartile range 5-5]). Contrarily, for soft tissue, QIR 4 received the highest ratings among compared strength levels (3 [3-4]). Both ICC (0.805; 95% confidence interval 0.711-0.877; p < 0.001) and ICC (0.885; 0.824-0.929; p < 0.001) suggested good interrater agreement. CNR in bone and muscle tissue increased with ascending strength levels of iterative reconstruction with the highest results recorded for QIR 4 (CNR 29.43 ± 2.61; CNR 8.09 ± 0.77) and lowest results without QIR (CNR 3.90 ± 0.29; CNR 1.07 ± 0.07) (all p < 0.001).

Conclusion: Reconstructing photon-counting CT data with an intermediate QIR strength level appears optimal for assessment of osseous tissue, whereas soft tissue analysis benefitted from applying the highest strength level available.

Implications For Practice: Quantum iterative reconstruction technique can enhance image quality by significantly reducing noise and improving CNR in ultra-high resolution CT imaging of the hip.