The need for sedation is a signi?cant concern for magnetic resonance imaging (MRI) of young children. This challenge arises because the typically long durations of volumetric imaging used in clinical applications are too long for infants and young children to remain still voluntarily. Without anesthesia, the motion during a scan would distort images, obscuring critical features needed for diagnosis. Breathing-related motion further reduces image quality, and breath-holds may be unrealistic for young children. This project aims to eliminate the use of sedation from the majority of pediatric MRIs using novel acquisition and reconstruction methods that accelerate the imaging process and track and compensate for motion. A pediatric MRI paradigm performed without any sedation would enable broader application of clinical MRI in young children. Other bene?ts include a shorter, less costly exam, which is easier to schedule absent anesthesiologist support. These bene?ts should make MRI a more attractive option for pediatric imaging versus an alternative such as X-ray computed tomography (CT), which is unattractive due to its high radiation dose. This distinction becomes even more important when repeated imaging is necessary, such as the monitoring of solid tumors in pediatric cancer patients. Conventional MRI data acquisition for volumetric imaging relies on a ?spin warp? approach, requiring thousands or even tens of thousands of readouts to reconstruct a volume, depending on the desired ?eld of view and spatial resolution. In total, an entire volume can take several minutes to acquire, and multiple volumes with different contrasts are generally prescribed in a typical imaging session. Patient motion during this process can distort or blur the reconstruction, rendering the images unusable. Respiratory gating techniques can reduce the effects of breathing-related motion, but such methods do not extend to patient motion. Distraction, acclimation, and parental involvement also can help young children to behave cooperatively in the scanner environment, but the typical process for acquiring diagnostic-quality MRI of young children remains sedation or partial sedation during scanning. This proposal merges complementary pulse sequence and image reconstruction algorithm design to introduce a hybrid solution to the challenging problem of fast imaging with motion. We hypothesize that combining a variable-density inter- leaved spiral acquisition (Aim 1) with self-navigating motion-compensated model-based reconstruction (Aim 2) will greatly reduce scan times and mitigate patient motion suf?ciently to enable diagnostically useful pediatric clinical imaging without any sedation, and introduce a low-risk alternative for the diagnosis and regular treatment monitoring of solid tumors in infants and young children (Aim 3).

Public Health Relevance

The overall goal of this project is to eliminate the need for sedation in pediatric magnetic resonance imaging (MRI), thus eliminating the risks of sedation to the child, reducing the length and cost of the exam, and enabling exams to be scheduled more quickly. This could signi?cantly increase the use of this powerful and safe imaging modality in children, improving diagnosis and reducing the use of x-ray computed tomography (CT), which is associated with a signi?cant dose of ionizing radiation and an increased risk of cancer. The researchers will develop new methods of acquiring MRI data and new methods of processing the data to form images, with the goal of rapid exam that can produce good images even when the child is moving.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21EB022309-01A1
Application #
9245352
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Liu, Guoying
Project Start
2016-09-01
Project End
2018-06-30
Budget Start
2016-09-01
Budget End
2017-06-30
Support Year
1
Fiscal Year
2016
Total Cost
$188,570
Indirect Cost
$63,570
Name
University of Virginia
Department
Biomedical Engineering
Type
Schools of Medicine
DUNS #
065391526
City
Charlottesville
State
VA
Country
United States
Zip Code
22904
Liang, Haoyi; Dabrowska, Natalia; Kapur, Jaideep et al. (2018) Structure-based Intensity Propagation for 3D Brain Reconstruction with Multilayer Section Microscopy. IEEE Trans Med Imaging :
Fielden, Samuel W; Feng, Xue; Zhao, Li et al. (2018) A spiral-based volumetric acquisition for MR temperature imaging. Magn Reson Med 79:3122-3127
Weller, Daniel S; Salerno, Michael; Meyer, Craig H (2018) Content-aware compressive magnetic resonance image reconstruction. Magn Reson Imaging 52:118-130
Feng, Xue; Blemker, Silvia S; Inouye, Josh et al. (2018) Assessment of velopharyngeal function with dual-planar high-resolution real-time spiral dynamic MRI. Magn Reson Med 80:1467-1474