Jonathan R. Dillman, MD, MSc
- Associate Chief of Research, Department of Radiology
- Medical Director, Imaging Research Center, Division of Radiology
- jonathan.dillman@cchmc.org
- Board Certified
About
Biography
I’ve always enjoyed working with children and find it immensely rewarding to have a lifelong impact on patients. Radiology is my clinical specialty with a particular interest in imaging the pediatric abdomen, inflammatory bowel diseases (including Crohn's disease) and chronic liver diseases. I frequently work collaboratively with multi-disciplinary teams, including gastroenterologists, hepatologists and cardiologists.
My research areas include novel quantitative imaging methods for diagnosis and staging severity of Crohn's disease and chronic liver diseases (such as fatty liver disease and autoimmune liver disease). My work aims to measure tissue and organ injury noninvasively and turn anatomic images into quantitative biomarkers.
I am honored to have received the Best Paper award from the Pediatric Radiology journal (2020), Best Gastrointestinal (GI) Scientific Presentation, Society of Abdominal Radiology (2020) and Department of Radiology Outstanding Clinician (2020). I have also received multiple grants, including funding from the Cincinnati Children's Foundation and the National Institutes of Health (NIH). I am board certified in Radiology (2008), with subspecialty certification in Pediatric Radiology (2011) by the American Board of Radiology.
MD: Indiana University School of Medicine, Indianapolis, IN, 2003.
Residency: Diagnostic Radiology Residency Program, University of Michigan Health System, Ann Arbor, MI, 2008.
Fellowship: Pediatric Radiology Fellowship Program, University of Michigan Health System, Ann Arbor, MI, 2009; Abdominal Imaging Radiology Fellowship Program, University of Michigan Health System, Ann Arbor, MI, 2010.
Certification: American Board of Radiology, 2008; Subspecialty Certification in Pediatric Radiology, 2011.
MSc: Clinical Research Design and Statistical Analysis, University of Michigan School of Public Health, Ann Arbor, MI, 2015.
Interests
Pediatric radiology; imaging of the pediatric gastrointestinal tract (including bowel, liver, and pancreas); imaging of the pediatric genitourinary tract
Interests
Ultrasound and MRI evaluation of Crohn's disease; ultrasound and MRI detection and measurement of liver fibrosis
Publications
MRI and Blood-based Biomarkers Are Associated With Surgery in Children and Adults With Ileal Crohn's Disease. Inflammatory Bowel Diseases. 2024; 30:2181-2190.
Prospective characterization of intestinal MRI intravoxel incoherent motion in pediatric and young adult patients with newly diagnosed small bowel Crohn's disease. Abdominal Radiology. 2024; 49:3325-3336.
Imaging and clinical predictors of surgery in stricturing ileal Crohn's disease: a retrospective study from a large pediatric hospital. Abdominal Radiology. 2024; 49:3354-3363.
MR enterography radiologic ulcers in newly diagnosed ileal Crohn disease in children: frequency, inter-radiologist agreement, and clinical correlation. Pediatric Radiology: roentgenology, nuclear medicine, ultrasonics, CT, MRI. 2024; 54:1842-1849.
Deep Learning Models for Abdominal CT Organ Segmentation in Children: Development and Validation in Internal and Heterogeneous Public Datasets. American Journal of Roentgenology. 2024; 223:e2430931.
Association Between MR Elastography Liver Stiffness and Histologic Liver Fibrosis in Children and Young Adults With Autoimmune Liver Disease. American Journal of Roentgenology. 2024; 223:e2431108.
MRI-Based Characterization of Intestinal Motility in Children and Young Adults With Newly Diagnosed Ileal Crohn Disease Treated by Biologic Therapy: A Controlled Prospective Study. American Journal of Roentgenology. 2022; 219:655-664.
Velocity-Encoded Phase-Contrast MRI for Measuring Mesenteric Blood Flow in Patients With Newly Diagnosed Small-Bowel Crohn Disease. American Journal of Roentgenology. 2022; 219:132-141.
Transparency and Variability in Pricing for Pediatric Outpatient Imaging in US Children's Hospitals. JAMA network open. 2022; 5:e220736.
DeepLiverNet: a deep transfer learning model for classifying liver stiffness using clinical and T2-weighted magnetic resonance imaging data in children and young adults. Pediatric Radiology: roentgenology, nuclear medicine, ultrasonics, CT, MRI. 2021; 51:392-402.
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