Abstract

Our first step to adapt our recently developed noncontact diffuse correlation tomography (ncDCT) system for three-dimensional (3-D) imaging of blood flow distribution in human breast tumors is reported. A commercial 3-D camera was used to obtain breast surface geometry, which was then converted to a solid volume mesh. An ncDCT probe scanned over a region of interest on the mesh surface and the measured boundary data were combined with a finite element framework for 3-D image reconstruction of blood flow distribution. This technique was tested in computer simulations and in vivo human breasts with low-grade carcinoma. Results from computer simulations suggest that relatively high accuracy can be achieved when the entire tumor is within the sensitive region of diffuse light. Image reconstruction with a priori knowledge of the tumor volume and location can significantly improve the accuracy in recovery of tumor blood flow contrasts. In vivo imaging results from two breast carcinomas show higher average blood flow contrasts (5.9- and 10.9-fold) in the tumor regions compared to the surrounding tissues, which are comparable with previous findings using diffuse correlation spectroscopy. The ncDCT system has the potential to image blood flow distributions in soft and vulnerable tissues without distorting tissue hemodynamics

Document Type

Article

Publication Date

8-2015

Notes/Citation Information

Published in Journal of Biomedical Optics, v. 20, no. 8, article 086003, p. 1-11.

Copyright 2015 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.

Lian He, Yu Lin, Chong Huang, Daniel Irwin, Margaret M. Szabunio, and Guoqiang Yu, "Noncontact diffuse correlation tomography of human breast tumor", Journal of Biomedical Optics 20(8), 086003 (2015).

http://dx.doi.org/10.1117/1.JBO.20.8.086003

Digital Object Identifier (DOI)

http://dx.doi.org/10.1117/1.JBO.20.8.086003

Funding Information

We acknowledge support from the National Institutes of Health (NIH) R01-CA149274 (G. Y.), R21-AR062356 (G. Y.), UL-1RR033173 Pilot Grant (G. Y.), and R25-CA153954 Predoctoral Traineeship (D. I.).

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