Portions of this study were presented as a poster at the ACVR annual scientific conference held in Las Vegas, Nevada, USA, October, 2012.
AN OPTIMIZED PROTOCOL FOR MULTISLICE COMPUTED TOMOGRAPHY OF THE CANINE BRAIN
Article first published online: 10 FEB 2014
© 2014 American College of Veterinary Radiology
Veterinary Radiology & Ultrasound
Volume 55, Issue 4, pages 387–392, July/August 2014
How to Cite
Zarelli, M., Schwarz, T., Puggioni, A., Pinilla, M., O'Doherty, J. V. and McAllister, H. (2014), AN OPTIMIZED PROTOCOL FOR MULTISLICE COMPUTED TOMOGRAPHY OF THE CANINE BRAIN. Veterinary Radiology & Ultrasound, 55: 387–392. doi: 10.1111/vru.12144
- Issue published online: 16 JUL 2014
- Article first published online: 10 FEB 2014
- Manuscript Accepted: 11 NOV 2013
- Manuscript Received: 12 APR 2013
- computed tomography;
Computed tomography (CT) is commonly used in veterinary practice to evaluate dogs with suspected brain disease, however contrast resolution limitations and artifacts may reduce visualization of clinically important anatomic features. The purpose of this study was to develop an optimized CT protocol for evaluating the canine brain. The head of a 5-year-old Springer Spaniel with no neurological signs was imaged immediately following euthanasia using a 4-slice CT scanner and 282 protocols. Each protocol used a fixed tube voltage of 120 kVp and 10 cm display field of view. Other acquisition and reconstruction parameters were varied. For each protocol, four selected images of the brain were reconstructed, anonymized and saved in DICOM format. Three board-certified veterinary radiologists independently reviewed each of the four images for each protocol and recorded a numerical quality score for each image. The protocol yielding the lowest total numerical score was defined as the optimal protocol. There was overall agreement that the optimal protocol was the one with the following parameters: sequential mode, 300 mAs, 1 mm slice thickness, 1 s tube rotation time, medium image reconstruction algorithm and applied beam hardening correction. Sequential imaging provided optimal image resolution. The thin-sliced images provided a small blur due to partial volume artifacts. A high tube current resulted in a relatively low noise level. Use of a medium frequency image reconstruction algorithm provided optimal contrast resolution for brain tissue. Use of a proprietary beam hardening correction filter (Posterior Fossa Optimization) markedly reduced beam-hardening artifact.