Journal article
High success rates of sedation-free brain MRI scanning in young children using simple subject preparation protocols with and without a commercial mock scanner–the Diabetes Research in Children Network (DirecNet) experience
Pediatric radiology, Vol.44(2), pp.181-186
02/2014
DOI: 10.1007/s00247-013-2798-7
PMCID: PMC3946760
PMID: 24096802
Abstract
Background
The ability to lie still in an MRI scanner is essential for obtaining usable image data. To reduce motion, young children are often sedated, adding significant cost and risk.
Objective
We assessed the feasibility of using a simple and affordable behavioral desensitization program to yield high-quality brain MRI scans in sedation-free children.
Materials and methods
222 children (4–9.9 years), 147 with type 1 diabetes and 75 age-matched non-diabetic controls, participated in a multi-site study focused on effects of type 1 diabetes on the developing brain. T1-weighted and diffusion-weighted imaging (DWI) MRI scans were performed. All children underwent behavioral training and practice MRI sessions using either a commercial MRI simulator or an inexpensive mock scanner consisting of a toy tunnel, vibrating mat, and video player to simulate the sounds and feel of the MRI scanner.
Results
205 children (92.3%), mean age 7 ± 1.7 years had high-quality T1-W scans and 174 (78.4%) had high-quality diffusion-weighted scans after the first scan session. With a second scan session, success rates were 100% and 92.5% for T1-and diffusion-weighted scans, respectively. Success rates did not differ between children with type 1 diabetes and children without diabetes, or between centers using a commercial MRI scan simulator and those using the inexpensive mock scanner.
Conclusion
Behavioral training can lead to a high success rate for obtaining high-quality T1-and diffusion-weighted brain images from a young population without sedation.
Details
- Title: Subtitle
- High success rates of sedation-free brain MRI scanning in young children using simple subject preparation protocols with and without a commercial mock scanner–the Diabetes Research in Children Network (DirecNet) experience
- Creators
- Naama Barnea-Goraly - Department of Psychiatry and Behavioral Sciences, Center for Interdisciplinary Brain Sciences Research, Stanford, CA, USAStuart A Weinzimer - Pediatric Endocrinology, Yale University, New Haven, CT, USAKatrina J Ruedy - Jaeb Center for Health Research, 15310 Amberly Drive, Ste. 350, Tampa, FL 33647, USANelly Mauras - Pediatric Endocrinology, Nemours Children’s Clinic, Jacksonville, FL, USARoy W Beck - Jaeb Center for Health Research, 15310 Amberly Drive, Ste. 350, Tampa, FL 33647, USAMatt J Marzelli - Department of Psychiatry and Behavioral Sciences, Center for Interdisciplinary Brain Sciences Research, Stanford, CA, USAPaul K Mazaika - Department of Psychiatry and Behavioral Sciences, Center for Interdisciplinary Brain Sciences Research, Stanford, CA, USATandy Aye - Department of Pediatrics, Stanford University, Stanford, CA, USANeil H White - Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, USAEva Tsalikian - Pediatric Endocrinology, University of Iowa, Iowa City, IA, USALarry Fox - Pediatric Endocrinology, Nemours Children’s Clinic, Jacksonville, FL, USACraig Kollman - Jaeb Center for Health Research, 15310 Amberly Drive, Ste. 350, Tampa, FL 33647, USAPeiyao Cheng - Jaeb Center for Health Research, 15310 Amberly Drive, Ste. 350, Tampa, FL 33647, USAAllan L Reiss - Department of Psychiatry and Behavioral Sciences, Center for Interdisciplinary Brain Sciences Research, Stanford, CA, USADiabetes Research in Children Network (DirecNet)
- Resource Type
- Journal article
- Publication Details
- Pediatric radiology, Vol.44(2), pp.181-186
- DOI
- 10.1007/s00247-013-2798-7
- PMID
- 24096802
- PMCID
- PMC3946760
- NLM abbreviation
- Pediatr Radiol
- ISSN
- 0301-0449
- eISSN
- 1432-1998
- Language
- English
- Date published
- 02/2014
- Academic Unit
- Stead Family Department of Pediatrics; Fraternal Order of Eagles Diabetes Research Center
- Record Identifier
- 9984093360302771
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