Comparison of Model-Based Iterative Reconstruction, Adaptive Statistical Iterative Reconstruction, and Filtered Back
Jung Hee Son1, Seung Ho Kim, Jung-Hee Yoon
1From the *Department of Radiology, Inje University College of Medicine, Haeundae Paik Hospital, Haeundae-gu, Busan; and †Department of Radiology, Myongji Hospital, Deogyang-gu, Goyang-si, Gyeonggi-do, South Korea.
Objective:
The aim of the study was to compare the diagnostic performance of model-based iterative reconstruction (MBIR), adaptive statistical iterative reconstruction (ASIR), and filtered back projection (FBP) on submillisievert low-dose computed tomography (LDCT) for detecting hepatic metastases.
Methods:
Thirty-eight patients having hepatic metastases underwent abdomen CT. Computed tomography protocol consisted of routine standard-dose portal venous phase scan (120 kVp) and 90-second delayed low-dose scan (80 kVp). The LDCT images were reconstructed with FBP, ASIR, and MBIR, respectively. Two readers recorded the number of hepatic metastases on each image set.
Results:
A total of 105 metastatic lesions were analyzed. For reader 1, sensitivity for detecting metastases was stationary between FBP (49%) and ASIR (52%, P = 0.0697); however, sensitivity increased in MBIR (66%, P = 0.0035). For reader 2, it was stationary for all the following sets: FBP (65%), ASIR (68%), and MBIR (67%, P > 0.05).
Conclusions:
The MBIR and ASIR showed a limited sensitivity for detecting hepatic metastases in submillisievert LDCT.
More Related Videos
11:43Advanced Animal Model of Colorectal Metastasis in Liver: Imaging Techniques and Properties of Metastatic Clones
Published on: November 30, 2016
08:41Novel In Vivo Micro-Computed Tomography Imaging Techniques for Assessing the Progression of Non-Alcoholic Fatty Liver Disease
Published on: March 24, 2023
