Skip to main content
Journal cover image

Indocyanine green dye angiography accurately predicts survival in the zone of ischemia in a burn comb model.

Publication ,  Journal Article
Fourman, MS; Phillips, BT; Crawford, L; McClain, SA; Lin, F; Thode, HC; Dagum, AB; Singer, AJ; Clark, RA
Published in: Burns
August 2014

INTRODUCTION: Surgical evaluation of burn depth is performed via clinical observation, with only moderate reliability. While perfusion analysis has been proposed to enhance accuracy, no perfusion study has attempted to predict burn extension into the area of ischemia surrounding the original insult. We examined whether laser Doppler imaging (LDI) and indocyanine green (ICG) angiography predicted survival in the zone of ischemia in a porcine hot comb burn model. METHODOLOGY: Six full-thickness wounds were created on 5 female Yorkshire swine using a validated porcine hot comb burn model. 4 full-thickness burns were created separated by 3 unburned interspaces that represent the zone of ischemia. The interspaces between each comb burn were monitored using LDI and ICG Angiography at 1, 4, 24, and 48 h after burn. Interspace survival was assessed via gross observation and blinded histological readings 7 days after injury. RESULTS: ICG Angiographic assessments of burn perfusion were significantly different in viable vs. non-viable interspace perfusion at 1 h, 4 h, and 48 h. Temporal plotting of a trend-line derived from quantitative perfusion measurements rendered two distinct graphs, allowing for the derivation of a predictive algorithm to separate viable and non-viable interspaces. LDI revealed no such prognostic trend. CONCLUSION: Results from a validated porcine burn comb model suggest that ICG angiography has significant potential in the prediction of burn progression early after burn. However, the full potential of this technology cannot be determined until completion of clinical trials.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Burns

DOI

EISSN

1879-1409

Publication Date

August 2014

Volume

40

Issue

5

Start / End Page

940 / 946

Location

Netherlands

Related Subject Headings

  • Tissue Survival
  • Swine
  • Skin
  • Perfusion Imaging
  • Laser-Doppler Flowmetry
  • Ischemia
  • Indocyanine Green
  • Female
  • Emergency & Critical Care Medicine
  • Disease Models, Animal
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Fourman, M. S., Phillips, B. T., Crawford, L., McClain, S. A., Lin, F., Thode, H. C., … Clark, R. A. (2014). Indocyanine green dye angiography accurately predicts survival in the zone of ischemia in a burn comb model. Burns, 40(5), 940–946. https://doi.org/10.1016/j.burns.2013.10.017
Fourman, Mitchell S., Brett T. Phillips, Laurie Crawford, Steve A. McClain, Fubao Lin, Henry C. Thode, Alexander B. Dagum, Adam J. Singer, and Richard A. Clark. “Indocyanine green dye angiography accurately predicts survival in the zone of ischemia in a burn comb model.Burns 40, no. 5 (August 2014): 940–46. https://doi.org/10.1016/j.burns.2013.10.017.
Fourman MS, Phillips BT, Crawford L, McClain SA, Lin F, Thode HC, et al. Indocyanine green dye angiography accurately predicts survival in the zone of ischemia in a burn comb model. Burns. 2014 Aug;40(5):940–6.
Fourman, Mitchell S., et al. “Indocyanine green dye angiography accurately predicts survival in the zone of ischemia in a burn comb model.Burns, vol. 40, no. 5, Aug. 2014, pp. 940–46. Pubmed, doi:10.1016/j.burns.2013.10.017.
Fourman MS, Phillips BT, Crawford L, McClain SA, Lin F, Thode HC, Dagum AB, Singer AJ, Clark RA. Indocyanine green dye angiography accurately predicts survival in the zone of ischemia in a burn comb model. Burns. 2014 Aug;40(5):940–946.
Journal cover image

Published In

Burns

DOI

EISSN

1879-1409

Publication Date

August 2014

Volume

40

Issue

5

Start / End Page

940 / 946

Location

Netherlands

Related Subject Headings

  • Tissue Survival
  • Swine
  • Skin
  • Perfusion Imaging
  • Laser-Doppler Flowmetry
  • Ischemia
  • Indocyanine Green
  • Female
  • Emergency & Critical Care Medicine
  • Disease Models, Animal