Citation

Danelson KA, Stitzel JD. Biomed. Sci. Instrum. 2008; 44: 159-164.

Affiliation

Wake Forest University School of Medicine, Virginia Tech/Wake Forest University Center for Injury Biomechanics, Winston-Salem, NC, 27157, USA.

Copyright

(Copyright © 2008, Instrument Society of America)

DOI

unavailable

PMID

19141909

Abstract

The spleen is a commonly injured organ in Motor Vehicle Crash (MVC) with 22 percent of all MVC occupants receiving a spleen injury. Previous studies have been performed to investigate the correlation between the injury grading scales and the volumetric relationship of injured tissue to uninjured tissue using a semi-automated tissue thresholding in image processing software. This study develops a method for semi-automating this methodology by comparing radiopacity in the major blood vessels to that of the injured spleen. Eleven contrast enhanced computed tomography scans of trauma patients involved in MVC were selected from a medical center radiological database. Radiopacity of the tissues of interested were studied at multiple locations on each patient using a display of the Hounsfield unit profile across areas of interest. These ranges were compared across patients by calculating ratios between Hounsfield unit ranges in the arteries and Hounsfield unit ranges in the tissues of interest. Once these ranges were determined, a modified masking procedure using these ratios was adapted to create three dimensional reconstructions of the uninjured and injured splenic tissue. The percent of injured tissue in the total volume of the spleen was derived from the calculated reconstructions. The final step was comparing the injury volumes calculated in the patient to three injury scores obtained through radiology reports and coded by trauma registrars. While this small study did not show a consistent increase in injury volume with severity, the use of profile lines within one individual's scan significantly reduced the amount of manual segmentation required. A future application of this methodology will employ a larger dataset to better understand the mechanisms of splenic injury.

Language: en