Hybrid iterative reconstruction algorithm in brain CT: a radiation dose reduction and image quality assessment study

Abstract

Background Iterative reconstruction (IR) algorithms improve image quality and allow for radiation dose reduction in CT. Dose reduction is particularly challenging in brain CT where good low-contrast resolution is essential. Ideally, evaluation of image quality combines objective measurements and subjective assessment of clinically relevant quality criteria. Subjective assessment is associated with various pitfalls and biases. Purpose To evaluate the potential of the hybrid IR algorithm iDOSE4 to preserve image quality in phantom and clinical brain CT acquired with 30% reduced radiation dose, and to discuss the image quality assessment methods. Material and Methods Forty patients underwent two consecutive brain CTs with normal radiation dose (ND) and 30% reduced dose (RD). Both ND and RD were reconstructed with FBP. In addition the reduced dose CTs were reconstructed with two levels of IR (ID2, ID4). Three image quality criteria (grey-white-matter discrimination, basal ganglia delineation, general image quality) were graded and ranked by six neuroradiologists. Noise levels and contrast-to-noise ratios (CNR) were measured in clinical data. Noise, signal-to-noise ratio (SNR), spatial resolution, and noise-power spectrum (NPS) were also assessed in a phantom. Results Subjective image quality was considered adequate for clinical use for all reconstructions, graded good or excellent in 93% of cases for ND, 83% for ID4, 79% for ID2, and 67% for RD. For all quality parameters, ID4 and ID2 were graded better than RD ( P < 0.0055 and P < 0.035), but worse than ND ( P < 0.001). In clinical images, objective measurements showed lower noise and significantly higher CNR in ID4 compared with ND and RD ( P < 0.001). CNR was similar for ID2 and ND. In the phantom, IR reduced noise while maintaining spatial resolution and NPS. Conclusion: The IR algorithm improves image quality of reduced dose CTs and consistently delivers sufficient image quality for clinical purposes. Pitfalls related to subjective assessment can be addressed with careful study design.