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Registration error of the liver CT using deformable image registration of MIM Maestro and Velocity AI

Authors :
Nobuyoshi Fukumitsu
Kazunori Nitta
Toshiyuki Terunuma
Toshiyuki Okumura
Haruko Numajiri
Yoshiko Oshiro
Kayoko Ohnishi
Masashi Mizumoto
Teruhito Aihara
Hitoshi Ishikawa
Koji Tsuboi
Hideyuki Sakurai
Source :
BMC Medical Imaging, Vol 17, Iss 1, Pp 1-9 (2017)
Publication Year :
2017
Publisher :
BMC, 2017.

Abstract

Abstract 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.

Details

Language :
English
ISSN :
14712342 and 78247918
Volume :
17
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Medical Imaging
Publication Type :
Academic Journal
Accession number :
edsdoj.b782479188c4426c91d3c7c88b8cfff1
Document Type :
article
Full Text :
https://doi.org/10.1186/s12880-017-0202-z