Project Summary Pediatric patients are more vulnerable to radiation exposure when compared to adults. Each year, 2.2 million pediatric head computed tomography (CT) scans utilizing ionizing radiation are performed in the United States. Head trauma and craniosynostosis are two of the most common pediatric conditions requiring head CT scans. Multiple CT scans are often performed during clinical follow-up, exacerbating the cumulative risk of radiation exposure. Head trauma is common in children, frequently resulting in a skull fracture. Craniosynostosis is a congenital disability defined by a prematurely fused cranial suture. Standard clinical care for pediatric patients with head trauma or craniosynostosis employs 3D high-resolution cranial CT images to identify cranial fractures or cranial suture patency. The National Cancer Institute reported that radiation exposure from multiple head CT scans in children has the potential to triple the risk of leukemia and brain cancer due to radiosensitivity of their bone marrow and brain tissue. Magnetic resonance imaging (MRI) is a safe alternative without ionizing radiation. Existing “black bone” MRI methods rely on a diminished bone signal in a standard gradient echo scan to image the skull. Though these methods have shown encouraging results, they have not translated into clinical practice due to several challenges: motion artifacts, long acquisition time, and subjective manual image processing. Since pediatric patient movement is very common, sedation has been routinely used to minimize motion artifacts in an MR scan. Unfortunately, sedation is associated with risks including developmental delay and cardiopulmonary complications. It takes several minutes to acquire high-resolution MR images, which can be challenging for pediatric subject compliance and limits clinical adoption. Due to poor signal contrast between bone and its surrounding tissues in MR images, existing manual signal intensity-based approaches are challenging and not suitable for clinical translation. Our primary goal is to develop novel MR techniques to provide CT-equivalent 3D high-resolution cranial bone imaging. Four specific aims are proposed: 1) develop motion correction to address head motion in unsedated pediatric patients; 2) develop an MR image reconstruction method regularized by a deep-learning prior to reduce MR acquisition time to 1 minute or below; 3) develop a 3D Bayesian neural network to estimate pseudo-CT (pCT) and uncertainty maps from MRI for robust and automated image post-processing; and 4) determine the clinical utility of pCT in identifying cranial fractures and cranial suture patency. This study will have a profound impact on pediatric health by removing the risks associated with radiation and sedation.

Project Narrative Head CT has been widely used in pediatric patients for the diagnosis of cranial fractures in head trauma and cranial suture patency in craniosynostosis, a congenital disability defined by a prematurely fused cranial suture. Unfortunately, these pediatric patients are particularly vulnerable to ionizing radiation from CT scans. Moreover, sedation is commonly used to reduce motion artifacts in children. Our proposal will develop a motion-robust, fast, and fully automated approach to perform high resolution 3D cranial bone imaging using MR as a safe alternative. The proposed research is relevant to public health as it will have a profound impact on pediatric patients by reducing the risks associated with ionizing radiation and sedation for cranial bone imaging. If successful, this study will achieve a goal set by the National Cancer Institute, American College of Radiology, and US Food and Drug Administration (FDA) by reducing radiation exposure in children from head CT scans.