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New 4-D Imaging for Real-Time Intraoperative MRI: Adaptive 4-D Scan

  • Junichi Tokuda
  • Shigehiro Morikawa
  • Hasnine A. Haque
  • Tetsuji Tsukamoto
  • Kiyoshi Matsumiya
  • Hongen Liao
  • Ken Masamune
  • Takeyoshi Dohi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4190)

Abstract

Aiming at real-time 3-D visualization of organ motion to navigate surgical procedures in MRI-guided surgery, a new 4-D MR imaging technique called “Adaptive 4-D Scan” has been proposed. The technique is designed to acquire a time series of volumetric 3-D images (4-D image) of cyclically moving organ, even in a low-field open-configuration MR scanner. A pre-operative 4-D image is acquired with respiratory phase parameter, which is monitored by using navigator-echo-based real-time tracking of the liver and diaphragm. During operation, the respiratory phase is again monitored in real-time, and a 3-D image, reflecting the current state of the target organ, is extracted from the pre-operative 4-D image and provided to physicians as a pseudo real-time 3-D image. We implemented Adaptive 4-D Scan into a 0.5 Tesla open-configuration clinical MRI system for intervention. Phantom and volunteer studies were performed to assess feasibility of this technique, in terms of image quality, imaging time and position accuracy of the imaged subject. A 4-D image (matrix: 256×128×10×8) of cyclically moving phantom was acquired in 719 s, and RMS position error between the imaged subject and the real subject was 2.3 mm, where the range of motion was 50 mm. 4-D image of the moving liver was also successfully acquired under near clinical condition. In conclusion, the study shows that the proposed method is feasible and has capability to provide real-time dynamic 3-D atlas for surgical navigation.

Keywords

Position Error Imaging Time Phantom Study Volunteer Study Surgical Navigation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Junichi Tokuda
    • 1
  • Shigehiro Morikawa
    • 2
  • Hasnine A. Haque
    • 3
  • Tetsuji Tsukamoto
    • 3
  • Kiyoshi Matsumiya
    • 1
  • Hongen Liao
    • 4
  • Ken Masamune
    • 1
  • Takeyoshi Dohi
    • 1
  1. 1.Graduate School of Information Science and TechnologyThe University of TokyoTokyoJapan
  2. 2.Biomedical MR Science CenterShiga University of Medical ScienceShigaJapan
  3. 3.GE Yokogawa Medical Systems Ltd.TokyoJapan
  4. 4.Graduate School of EngineeringThe University of TokyoTokyoJapan

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