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Abstract #0454

Capturing Internal Target Motion with Breathing Variability Using 3D Dynamic Lung MRI

Xiao Liang1, Li Pan2, Erez Nevo3, Steve Roys1, Hussain Soomro4, Rao P Gullapalli1, Amit Sawant4, Thomas Ernst1, and Jiachen Zhuo1
1Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States, 2Siemens Medical Solutions USA Inc, Baltimore, MD, United States, 3Robin Medical Inc., Baltimore, MD, United States, 4Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, United States

Synopsis

Keywords: MR-Guided Radiotherapy, Hybrid & Novel Systems Technology, Breathing variability

Motivation: To develop an MRI technique that captures cycle-to-cycle variability and differential motion between inhalation and exhalation to enable more accurate treatment planning and real-time beam adaptation.

Goal(s): To address the challenge of acquiring sufficient volumetric data for reconstruction of 3D dynamic lung MRI while maintaining adequate spatiotemporal resolution for radiation therapy guidance.

Approach: We utilized golden angle stack-of-star acquisition and labeled each view with the breathing state captured by a surface tracking system for sharing views with similar breathing states.

Results: 3D dynamic lung imaging captured cycle-to-cycle variability and respiratory hysteresis with a nominal temporal resolution of 60.6ms per volume.

Impact: The 3D dynamic lung imaging captured cycle-to-cycle variability and respiratory hysteresis with a nominal temporal resolution of 60.6ms. It can provide more accurate motion information than 4D-MRI for radiotherapy guidance, avoiding interplay between the tumor target and organs at risk.

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Keywords