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WE‐G‐213CD‐04: A Triggering System to Guide 4DMRI Image Acquisition
Author(s) -
Hu Y,
Caruthers S,
Low D,
Parikh P,
Mutic S
Publication year - 2012
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4736205
Subject(s) - exhalation , respiratory monitoring , computer science , nuclear medicine , respiratory system , scanner , medical imaging , data acquisition , medicine , computer vision , artificial intelligence , radiology , operating system
Purpose: To develop a practical triggering system based on pre‐selected respiratory amplitudes to guide prospectively the image acquisition of 4DMRI to track abdominal tumor motion for radiotherapy treatment planning. Methods: The proposed triggering scheme consists of a preparation stage and an acquisition stage. Immediately prior to MRI acquisition, the preparation stage monitors the respiration via an external respiratory belt. Based on the respiratory amplitude and status (i.e., inhalation↑ or exhalation↓), the respiration cycle is equally divided into N respiratory states. For example, in the 4‐state case, the 4 respiratory states are 5%↓″, 50%↑, 95%↑ and 50%↓. The 5%↓ and 95%↑ are used instead of 0% and 100% to improve the robustness of the triggering system. Each state is associated with a trigger which starts image acquisition for one and only one slice. A complete 4DMRI imageset requires N dynamic scans. In each dynamic scan, all slices are acquired once and each is in a specific respiratory state. In different dynamic scans, each slice is associated with different respiratory states to form a 4D dataset. For proof‐of‐principle, the triggering system was integrated into a T2‐weighted turbo spin echo sequence (TE=100ms, TR=7122ms) on a clinical 1.5T MRI (Philips Achieva) scanner. The 4‐state case was tested on a healthy subject. Results: Plots of the physiology data recorded and exported from the scanner clearly verified that triggers occurred at the expected locations. Four T2‐weighted images from a representative slice recorded the liver motion corresponding to the 4 respiratory states. Conclusions: Our results confirmed that the newly‐developed system could trigger prospectively to guide 4DMRI image acquisition to achieve T2 weighting, which has a better tumor‐tissue contrast than those offered by previous 4DMRI techniques with T1 or T2/T1 weighting. This is a first report of a pure T2‐weighted 4DMRI to track respiration induced abdominal motion.