Related Experiment Video
Updated: Mar 3, 2026

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
Published on: October 27, 2023
Registration error of the liver CT using deformable image registration of MIM Maestro and Velocity AI
Nobuyoshi Fukumitsu1, Kazunori Nitta2, Toshiyuki Terunuma3
1Proton Medical Research Center, University of Tsukuba, 1-1-1, Tennoudai, Tsukuba, Japan. fukumitsun@yahoo.co.jp.
Background:
Understanding the irradiated area and dose correctly is important for the reirradiation of organs that deform after irradiation, such as the liver. We investigated the spatial registration error using the deformable image registration (DIR) software products MIM Maestro (MIM) and Velocity AI (Velocity).
Methods:
Image registration of pretreatment computed tomography (CT) and posttreatment CT was performed in 24 patients with liver tumors. All the patients received proton beam therapy, and the follow-up period was 4-14 (median: 10) months. We performed DIR of the pretreatment CT and compared it with that of the posttreatment CT by calculating the dislocation of metallic markers (implanted close to the tumors).
Results:
The fiducial registration error was comparable in both products: 0.4-32.9 (9.3 ± 9.9) mm for MIM and 0.5-38.6 (11.0 ± 10.0) mm for Velocity, and correlated with the tumor diameter for MIM (r = 0.69, P = 0.002) and for Velocity (r = 0.68, P = 0.0003). Regarding the enhancement effect, the fiducial registration error was 1.0-24.9 (7.4 ± 7.7) mm for MIM and 0.3-29.6 (8.9 ± 7.2) mm for Velocity, which is shorter than that of plain CT (P = 0.04, for both).
Conclusions:
The DIR performance of both MIM and Velocity is comparable with regard to the liver. The fiducial registration error of DIR depends on the tumor diameter. Furthermore, contrast-enhanced CT improves the accuracy of both MIM and Velocity.
Institutional Review Board Approval:
H28-102; July 14, 2016 approved.
More Related Videos
06:09Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI
Published on: July 21, 2023
06:59Improved Registration of 3D CT Angiography with X-ray Fluoroscopy for Image Fusion During Transcatheter Aortic Valve Implantation
Published on: June 3, 2018