This was a productive year for research in the Department of Radiology, with more than 100 publications and close to 30 grant applications, many of them successful. In Q4 alone, radiology primary investigators (PI) have secured more than $2.6M in direct costs. This was also a year to strengthen our research enterprise and to facilitate access to radiology research resources for collaborators at Cincinnati Children's and the University of Cincinnati by streamlining and strengthening our review process for imaging research proposals, and by overhauling our external webpage.

One of our most exciting new research frontiers is image-based artificial intelligence (AI) and machine learning models. Led within radiology by Samuel Brady, PhD, and Elan Somasundaram, PhD, radiology clinical and research faculty and staff are working to apply machine learning techniques to the institution’s vast repositories of imaging data. Machine learning has great potential in organ and tissue segmentation, classification (e.g., diagnosis of disease versus normal), and disease prediction. Use of AI can also streamline clinical workflows and improve the quality of our images.

One recent publication from the department used machine learning to predict liver stiffness, a surrogate for liver fibrosis, from conventional MRI anatomic images, obviating the need for more advanced testing (He et al., AJR. 2019). In the coming year, we will continue to build our infrastructure for this highly collaborative research area, create relevant policies and guidelines regarding data use and governance, and continue to train and validate clinically-relevant pipelines and models.

Our body imaging radiologists had more than 50 publications last year, and they continue to lead the field in research into the use of novel quantitative ultrasound and MRI techniques to detect and quantify disease in children with liver, pancreatic, and intestinal diseases. Under the guidance of Jonathan Dillman, MD, MSc; Andrew Trout, MD; and Nathan Northern, a University of Cincinnati medical student, demonstrated the clinical effectiveness of ultrasound shear wave elastography in a pediatric population of nearly 500 patients (Northern NA, et al. Pediatr Radiol. 2019). Drs. Dillman and Trout, as well as other colleagues, showed that use of rapid “sparse” MRI can obtain MR images that are essentially identical to conventional images, allowing much faster MRI examinations (Morin et al. AJR. 2018). Working with Cincinnati Children's Center for Autoimmune Liver Disease researchers, Drs. Dillman, Trout, and Jean Tkach, PhD, showed that use of MRI-derived liver and spleen stiffness can predict which children with primary sclerosing cholangitis and autoimmune hepatitis are at risk for developing portal hypertension (Dillman, et al. Pediatr Radiol. 2019). Body imagers are leading (PI or multiple PI) NIH R01 and R21-funded investigations as well as studies funded by both foundations and industry.

Radiology’s close collaboration with the Division of Pulmonary Medicine and the Center for Pulmonary Imaging Research (CPIR) continues. An article published in the most cited pulmonary research journal included four authors from radiology (Higano et al, Am J Respir Crit Care Med. 2018). This translational work highlighted the direct clinical relevance of imaging in the youngest children. In particular, quiet-breathing neonatal pulmonary MRI shows assess to structural abnormalities of bronchopulmonary dysplasia (BPD), describe disease severity, and predict short-term outcomes more accurately than any individual standard clinical measure. Importantly, implementing this nonionizing technique to phenotype disease has the potential to serially assess efficacy of individualized therapies.

Musculoskeletal radiologists involvement in a number of successful projects that includes MRI of the zone of provisional calcification as a predictor of physeal function led by Kathleen Emery, MD. This work resulted in a poster at the meeting of the Society for Pediatric Radiology with Deborah Brahee, MD, as the fellow and an internal grant submission with the Department of Orthopedics at UC. Dr. Emery is also participating in two large cooperative research projects: JUPITER (Justifying Patellar Instability Treatment by Early Results), and A Bioinspired Approach to Large Pediatric Osteochondral Injuries (OCIs). Hee Kim, MD, published some of her collaborative research on patellofemoral instability and submitted a grant application to RIP.