QdMRI: a system for a comprehensive analysis of thoracic dynamics via dynamic MRI

Yubing Tong; Jayaram K. Udupa; You Hao; Lipeng Xie; Joseph M. McDonough; Caiyun Wu; Carina Lott; Abigail Clark; Jason B. Anari; Drew A. Torigian; Patrick J. Cahill

doi:10.1117/12.2612117

4 April 2022 QdMRI: a system for a comprehensive analysis of thoracic dynamics via dynamic MRI

Yubing Tong, Jayaram K. Udupa, You Hao, Lipeng Xie, Joseph M. McDonough, Caiyun Wu, Carina Lott, Abigail Clark, Jason B. Anari, Drew A. Torigian, Patrick J. Cahill

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Proceedings Volume 12034, Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling; 120341G (2022) https://doi.org/10.1117/12.2612117
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Abstract

Quantitative thoracic dynamic magnetic resonance imaging (QdMRI), a recently developed technique, provides a potential solution for evaluating treatment effects in thoracic insufficiency syndrome (TIS). In this paper, we integrate all related algorithms and modules during our work from the past 10 years on TIS into one system, named QdMRI, to address the following questions: (1) How to effectively acquire dynamic images? For many TIS patients, subjects are unable to cooperate with breathing instructions during image acquisition. Image acquisition can only be implemented under freebreathing conditions, and it is not feasible to use a surrogate device for tracing breathing signals. (2) How to assess the thoracic structures from the acquired image, such as lungs, left and right, separately? (3) How to depict the dynamics of thoracic structures due to respiration motion? (4) How to use the structural and functional information for the quantitative evaluation of surgical TIS treatment and for the design of the surgery plan? The QdMRI system includes 4 major modules: dynamic MRI (dMRI) acquisition, 4D image construction, image segmentation (from 4D image), and visualization of segmentation results, dynamic measurements, and comparisons of measurements from TIS patients with those from normal children. Scanning/image acquisition time for one subject is ~20 minutes, 4D image construction time is ~5 minutes, image segmentation of lungs via deep learning is 70 seconds for all time points (with the average DICE 0.96 in healthy children), and measurement computation time is 2 seconds.

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Yubing Tong, Jayaram K. Udupa, You Hao, Lipeng Xie, Joseph M. McDonough, Caiyun Wu, Carina Lott, Abigail Clark, Jason B. Anari, Drew A. Torigian, and Patrick J. Cahill "QdMRI: a system for a comprehensive analysis of thoracic dynamics via dynamic MRI", Proc. SPIE 12034, Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling, 120341G (4 April 2022); https://doi.org/10.1117/12.2612117

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KEYWORDS

Image segmentation

Lung

Magnetic resonance imaging

Titanium

Chest

Surgery

Visualization

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