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Optimizing Quantitative Methods in Murine Pulmonary Imaging with UTE 1H MR

Stecker, Ian
http://orcid.org/0000-0002-0507-7109
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592135581719325

Abstract Details

2020, MS, University of Cincinnati, Engineering and Applied Science: Biomedical Engineering.
Pathophysiology in progressive lung diseases, such as pulmonary fibrosis, is invariably spatially heterogeneous. Thus, there is a pressing need for spatially explicit information to elucidate the underlying biological mechanisms that drive the initiation and progression of these disorders. While animal models, particularly mice, are ubiquitously used to investigate these biological pathways, the experimental tools commonly available to quantify disease burden are highly invasive. As such, conventional histology and lung functional measurements typically require cross-sectional study designs. These terminal studies limit the ability to observe disease progression and require a large number of animals to achieve statistical significance, thus increasing experimental complexity and expense. To reduce animal numbers and achieve more robust statistical results, spatially resolved, longitudinal data are acquired. To this end, non-invasive imaging modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI) are promising technics to probe the regional dynamics in preclinical models of fibrotic lung disease. However, CT involves non-trivial doses of ionizing radiation, making human translation of some preclinical images’ protocols challenging. While free from radiation, pulmonary MRI has historically been difficult to implement due to a variety of technical challenges such as low proton tissue density (10-20% that of other solid organs), rapid apparent transverse relaxation (T2*) of 0.5 ms or less at preclinically relevant field strengths (4.5–9.4 T), and inherent rapid physiological motion (> 250 breaths per minute and > 400 heartbeats per minute). To overcome the constraints imposed by rapid T2*, radial ultrashort echo time (UTE) sequences have been developed that have effective echo times on the order of 10 µs. In addition, the center-out encoding strategies employed in UTE also help to mitigate motion by heavily oversampling the center of k-space (k0). As such, UTE sequences provide a general solution to the most prevalent challenges in preclinical lung MRI. This thesis describes 1) UTE-based methods used to investigate the dynamic changes in mouse lung, 2) approaches used to optimize radial sequences to maximize the utility of pulmonary imaging in mouse models, and 3) experimental results obtained using these optimized protocols. In the first research project, preliminary results are described characterizing longitudinal disease trajectories in a previously uncharacterized, transgenic mouse model of lung fibrosis. This work was carried out by developing broadly application image acquisition and quantitative analysis approaches. For the second research project, the relationship between radial undersampling and quantitative MR analysis (specifically T2* mapping) is described. This was done by acquiring fully sampled radial multi-TE images and then pseudorandomly undersampling these data repeatedly to quantify undersampling-induced challenges associated with image signal-to-noise-ratio and T2* distribution. Combined, these projects highlight the potential for preclinical lung MRI to become an efficient, quantitative, and cost-effective tool to provide long-term, in vivo data for translational lung disease research.
Zackary Cleveland, Ph.D. (Committee Chair)
Jing-Huei Lee, Ph.D. (Committee Member)
Jason Woods, Ph.D. (Committee Member)
99 p.
Biomedical Research
MRI; Quantitative; Mouse; Lung; UTE; Preclincal

Recommended Citations

Citations

  • Stecker, I. (2020). Optimizing Quantitative Methods in Murine Pulmonary Imaging with UTE 1H MR [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592135581719325

    APA Style (7th edition)

  • Stecker, Ian. Optimizing Quantitative Methods in Murine Pulmonary Imaging with UTE 1H MR. 2020. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592135581719325.

    MLA Style (8th edition)

  • Stecker, Ian. "Optimizing Quantitative Methods in Murine Pulmonary Imaging with UTE 1H MR." Master's thesis, University of Cincinnati, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592135581719325

    Chicago Manual of Style (17th edition)

ucin1592135581719325
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This open access ETD is published by University of Cincinnati and OhioLINK.