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A Method to Discriminate Pulmonary Contusion Severity Through Analysis of Hounsfield Unit Frequency

[+] Author Affiliations
F. Scott Gayzik, Melissa Daly, Joel Stitzel

Virginia Tech - Wake Forest University, Winston-Salem, NC

Paper No. SBC2007-176906, pp. 623-624; 2 pages
doi:10.1115/SBC2007-176906
From:
  • ASME 2007 Summer Bioengineering Conference
  • ASME 2007 Summer Bioengineering Conference
  • Keystone, Colorado, USA, June 20–24, 2007
  • Conference Sponsors: Bioengineering Division
  • ISBN: 0-7918-4798-5
  • Copyright © 2007 by ASME

abstract

This study presents a novel approach for the quantification and classification of pulmonary contusion (PC). PC is a common thoracic injury, affecting up to 25% of patients sustaining blunt chest trauma. [1] Contusion volume at the time of hospitalization has been shown to be an independent predictor for the development of Acute Respiratory Distress Syndrome (ARDS), with the risk of ARDS increasing sharply with PC in excess of 20% by volume. [1] Despite the frequency of the injury and strong positive correlation between contusion volume and outcome, there are relatively few contusion quantification methods in the current literature. One such study utilized chest x-ray film to score PC according the amount of lung appearing to be damaged. [2] The study concluded that despite the limitations in using chest x-rays, a PC scoring system may be of value in determining the need for ventilator assistance and predicting outcome. A potentially more accurate approach to quantifying the severity of PC is through the use of computed tomography (CT) chest scans. CT is the preferred modality for obtaining volumetric pulmonary contusion data since the complete three-dimensional lung anatomy is captured. In this work a semi-automated approach is used to analyze PC in an isolated model of lung contusion in the rat. [3, 4] The CT-based approach enables the PC to be precisely quantified as the lesion progresses in time. The technique distinguishes the severity of the contusion by analyzing the composition of bands in the Hounsfield Unit (HU) range of lung image masks.

Copyright © 2007 by ASME

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