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PhD Thesis Proposal: Yue Tang

May

17

Friday
1:00pm - 3:00pm ET

Borwell 658W, DHMC/Online

Optional ZOOM LINK

"Intraoperative dynamic contrast-enhanced fluorescence imaging for navigating orthopedic surgeries"

Abstract

Infection following trauma is one of the most prevalent and challenging complications faced by orthopedic surgeons. Inadequate tissue perfusion plays a critical role in this complication, as poorly perfused bone can be a nidus for bacterial biofilm formation, creating resistance to antibiotics. Because of this, management of open fractures and fracture-related infection relies on aggressive and thorough debridement to remove all poorly perfused bone. However, there is a limited number of imaging tools to objectively inform bone perfusion and navigate the surgeries. To address this, indocyanine green (ICG)-based dynamic contrast-enhanced fluorescence imaging (DCE-FI) has been developed at Dartmouth to objectively measure bone perfusion during open orthopedic surgeries and guide surgical debridement of devitalized bone.

While fluorescence imaging systems and image processing procedures have been studied by many research groups, adapting DCE-FI for intraoperative bone imaging is new and facing specific challenges related to bone. In my thesis study, methods for image processing and analysis have been developed to improve the accuracy of bone blood perfusion assessment. When these methods were applied to the images of infection/open fracture patients, low perfusion areas were identified by reduced maximum fluorescence intensity and blood flow, and showed strong correlations with early infections that occurred within 3 months after the surgery. In addition, a portable compact fluorescence imaging system (cBPI) has also been developed to work in austere environments and/or forward operating units close to the battlefield. Proposed work includes finishing outcome analysis to evaluate the association between post-debridement bone perfusion and the risk of infection recurrence and treatment failure, optimizing the imaging analysis workflow to reduce computation time, and implementing cBPI in animal and patient studies for comprehensive system validation, with streamlined analytic tools and user interface developed.

Thesis Committee

  • Shudong Jiang (Chair)
  • Jonathan Elliott
  • Ida Leah Gitajn
  • Brian Pogue (University of Wisconsin-Madison)

Contact

For more information, contact Thayer Registrar at thayer.registrar@dartmouth.edu.