gui chul Lee - Seoul National University Bundang Hospital, Department of Radiology, Department of Healthcare, Graduate School ,Eulji University, Republic of Korea
Dongkyoon Han - Department of Radiological Science, Seongnam-si, Gyeonggi-do, Republic of Korea
Joowan Hong - Department of Radiological Science, Seongnam-si, Gyeonggi-do, Republic of Korea

Introduction: While various algorithms are applied in acquiring diagnostic information during computed tomography, such algorithms may affect image quality. The present study aimed to investigate the changes in image quality according to the application of the metal reduction algorithm and monoenergetic image in standard imaging.Material and Methods: Spectral computed tomography was used to acquire images with the application of standard, metal artifact reduction, monoenergetic, and monoenergetic+metal artifact reduction under the same conditions according to without or with of metal in ACR phantom. ImageJ program was used to measure the HU, noise, and SNR of polyethylene, bone, and acrylic located inside the ACR phantom using the same-sized ROIs.Results: HU measurement results showed changes in all materials, except acrylic with metal artifacts in the images. Moreover, the results showed a decrease in HU in images with the application of monoenergetic. Noise measurement results also showed changes in all materials, except acrylic with metal artifacts in the images. Moreover, the results showed a decrease in noise in images with the application of monoenergetic. For SNR measured relative to standard images, the results showed degradation of image quality due to a decrease of ۳۶.۵–۷۷.۷% in SNR and an increase in error value in all materials except acrylic. Whereas, acrylic showed an increase of ۳.۲–۴.۱% and a decrease in error values, resulting in improved image quality.Conclusion: Therefore, it is believed that the accuracy of reading could be increased by considering the changes in image quality and characteristics when applying algorithms for acquiring clinical information from CT.

Spectral CT, Hounsfield Unit, SNR, metal reduction, monoenergetic imaging