Presentation + Paper
14 March 2023 Risk prediction on orthopaedic trauma patients for fracture-associated infection using dynamic contrast enhanced-fluorescence imaging
Author Affiliations +
Abstract
Debridement of the surgical site during open fracture reduction and internal fixation is important for preventing surgical site infection; the risk of subsequent fracture-associated infection for a particular area of tissue is assessed by the surgeon based on multi-level variables, including demographics and laboratory results. Intraoperative fluorescence imaging can contribute additional information at a more localized level. Here we present a fluorescence-based predictive model using features from dynamic contrast enhanced-fluorescence imaging (DCE-FI), as well as patient-level variables associated with infection risk. Regions-of-interest were selected from thirty-eight enrolled open fracture patients. Spatial and kinetic features were extracted from DCE-FI, and combined with patient infection risk factor describing the possibility of getting surgical-site-infection. The model was evaluated for ability to predict composite outcome scores—intra-operative surgeon assessment coupled with post-operative confirmed infection outcome. This proposed model demonstrates high predictive performance with an accuracy of 0.86, evaluated with a cross-validation approach, and is a promising approach for early and quick identification of tissue prone to infection.
Conference Presentation
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xinyue Han, Logan M. Bateman, Paul M. Werth, Shudong Jiang, I. Leah Gitajn, and Jonathan Thomas Elliott "Risk prediction on orthopaedic trauma patients for fracture-associated infection using dynamic contrast enhanced-fluorescence imaging", Proc. SPIE 12361, Molecular-Guided Surgery: Molecules, Devices, and Applications IX, 123610A (14 March 2023); https://doi.org/10.1117/12.2650773
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KEYWORDS
Surgery

Tissues

Bone

Biological imaging

Machine learning

Feature extraction

Information science

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