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SU‐E‐J‐212: Real‐Time Treatment Failure Detection for Moving Tumor with Image Guidance
Author(s) -
Wu H,
Zhao Q,
Das I
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 - 10.1118/1.4735052
Subject(s) - fiducial marker , image guided radiation therapy , tracking (education) , correlation , signal (programming language) , medical imaging , nuclear medicine , mathematics , artificial intelligence , computer vision , computer science , physics , medicine , geometry , psychology , programming language , pedagogy
Purpose: Respiratory motion can cause misalignment of the radiation beam and will greatly degrade the effectiveness of cancer radiation treatment. Failure of radiation treatment can be detected by real‐time image. The efficiency of both internal tracking and external tracking has been assessed in this. Methods: Both 3D internal fiducial marker motion and 1D external abdominal surface motion data of 11 patients were collected simultaneously. Linear and quadratic functions have been applied to correlate the internal and external motion signal. To detect tracking failure of external imaging, three approaches have been proposed: (i) correlation only: which will compare directly between the tracked and the based curve. (2) fixed baseline shift: which interferes the treatment by adjusting the baseline of tracked signal to compensate target motion for each treatment fraction. (3) dynamic baseline shift: dynamically interfere with treatment for each breathing cycle. (4) dynamic baseline with base curve update, is the third approach with base curve for each fraction. Results: Generally, the quadratic function produced better correlation results than the linear correlation. With more historical data available, the quadratic prediction gives better correlation outcomes. The tracking frequency of 30, 10, 5, 2, 1, and 0.2Hz has been evaluated. Although high imaging frequency usually results in better correlation, imaging rate of 1 Hz will results acceptable results. For the failure detection, the average Euclidean misalignment is 3.46, 2.42, 2.21, 1.80 for the above four approach. With treatment interference, the beam‐on‐time percentages are 54.03, 58.26, 63.94, and 60.48 respectively. Conclusion: High imaging frequency is not required. approaches with baseline shift and base curve update will improve the treatment efficiency and treatment accuracy. Guidance using hybrid imaging with high‐frequency of external imaging and low internal imaging is needed to compensate tumor respiratory motion.