Quality assessment of computed tomography images using a channelized hoteling observer: Optimization of protocols in clinical practice


1 Department of Radiology, Isfahan University of Medical Sciences, Isfahan, Iran

2 Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

3 Department of Radiation Engineering, Shahid Beheshti University, Tehran, Iran


Background: This study investigated the feasibility of channelized hoteling observer (CHO) model in computed tomography (CT) protocol optimization regarding the image quality and patient exposure. While the utility of using model observers such as to optimize the clinical protocol is evident, the pitfalls associated with the use of this method in practice require investigation.
Materials and Methods: This study was performed using variable tube current and adaptive statistical iterative reconstruction (ASIR) level (ASIR 10% to ASIR 100%). Various criteria including noise, high-contrast spatial resolution, CHOs model were used to compare image quality at different captured levels. For the implementation of CHO, we first tuned the model in a restricted dataset and then it to the evaluation of a large dataset of images obtained with different reconstruction ASIR and filtered back projection (FBP) levels.
Results: The results were promising in terms of CHO use for the stated purposes. Comparisons of the noise of reconstructed images with 30% ASIR and higher levels of noise in rebuilding images using the FBP approach showed a significant difference (P < 0.05). The spatial resolution obtained using various ASIR levels and tube currents were 0.8 pairs of lines per millimeter, which did not differ significantly from the FBP method (P > 0.05).
Conclusions: Based on the results, using 80% ASIR can reduce the radiation dose on lungs, abdomen, and pelvis CT scans while maintaining image quality. Furthermore using ASIR 60% only for the reconstruction of lungs, abdomen, and pelvis images at standard radiation dose leads to optimal image quality.


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