Noninvasive multimodal imaging to predict recovery of locomotion after extended limb ischemia

Jason S. Radowsky, Joseph D. Caruso, Rajiv Luthra, Matthew J. Bradley, Eric A. Elster, Jonathan A. Forsberg, Nicole J. Crane

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Acute limb ischemia is a common cause of morbidity and mortality following trauma both in civilian centers and in combat related injuries. Rapid determination of tissue viability and surgical restoration of blood flow are desirable, but not always possible. We sought to characterize the response to increasing periods of hind limb ischemia in a porcine model such that we could define a period of critical ischemia (the point after which irreversible neuromuscular injury occurs), evaluate non-invasive methods for characterizing that ischemia, and establish a model by which we could predict whether or not the animal's locomotion would return to baselines levels post-operatively. Ischemia was induced by either application of a pneumatic tourniquet or vessel occlusion (performed by clamping the proximal iliac artery and vein at the level of the inguinal ligament). The limb was monitored for the duration of the procedure with both 3-charge coupled device (3CCD) and infrared (IR) imaging for tissue oxygenation and perfusion, respectively. The experimental arms of this model are effective at inducing histologically evident muscle injury with some evidence of expected secondary organ damage, particularly in animals with longer ischemia times. Noninvasive imaging data shows excellent correlation with post-operative functional outcomes, validating its use as a non-invasive means of viability assessment, and directly monitors postocclusive reactive hyperemia. A classification model, based on partial-least squares discriminant analysis (PLSDA) of imaging variables only, successfully classified animals as "returned to normal locomotion" or "did not return to normal locomotion" with 87.5%sensitivity and 66.7% specificity after cross-validation. PLSDA models generated from non-imaging data were not as accurate (AUC of 0.53) compared the PLSDA model generated from only imaging data (AUC of 0.76). With some modification, this limb ischemia model could also serve as a means on which to test therapies designed to prolong the time before critical ischemia.

Original languageEnglish
Article numbere0137430
JournalPLoS ONE
Volume10
Issue number9
DOIs
StatePublished - 14 Sep 2015
Externally publishedYes

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