Localization of Fluorescent Targets in Deep Tissue with Expanded Beam Illumination for Studies of Cancer and the Brain

Brian Z. Bentz, Sakkarapalayam M. Mahalingam, Daniel Ysselstein, Paola C. Montenegro Larrea, Jason R. Cannon, Jean Christophe Rochet, Philip S. Low, Kevin Webb

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Imaging fluorescence through millimeters or centimeters of tissue has important in vivo applications, such as guiding surgery and studying the brain. Often, the important information is the location of one of more optical reporters, rather than the specifics of the local geometry, motivating the need for a localization method that provides this information. We present an optimization approach based on a diffusion model for the fast localization of fluorescent inhomogeneities in deep tissue with expanded beam illumination that simplifies the experiment and the reconstruction. We show that the position of a fluorescent inhomogeneity can be estimated while assuming homogeneous tissue parameters and without having to model the excitation profile, reducing the computational burden and improving the utility of the method. We perform two experiments as a demonstration. First, a tumor in a mouse is localized using a near infrared folate-targeted fluorescent agent (OTL38). This result shows that localization can quickly provide tumor depth information, which could reduce damage to healthy tissue during fluorescence-guided surgery. Second, another near infrared fluorescent agent (ATTO647N) is injected into the brain of a rat, and localized through the intact skull and surface tissue. This result will enable studies of protein aggregation and neuron signaling.

Original languageEnglish (US)
Article number8985382
Pages (from-to)2472-2481
Number of pages10
JournalIEEE Transactions on Medical Imaging
Issue number7
StatePublished - Jul 2020


  • Fluorescence imaging
  • brain
  • inverse problems
  • localization
  • tumors
  • turbid media

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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