System analysis of spatial frequency domain imaging for quantitative mapping of surgically resected breast tissues. Academic Article uri icon

Overview

abstract

  • The feasibility of spatial frequency domain imaging (SFDI) for breast surgical margin assessment was evaluated in tissue-simulating phantoms and in fully intact lumpectomy specimens at the time of surgery. Phantom data was evaluated according to contrast-detail resolution, quantitative accuracy and model-data goodness of fit, where optical parameters were estimated by minimizing the residual sum of squares between the measured modulation amplitude and its solutions, modeled according to diffusion and scaled-Monte Carlo simulations. In contrast-detail phantoms, a 1.25-mm-diameter surface inclusion was detectable for scattering contrast >28%; a fraction of this scattering contrast (7%) was detectable for a 10 mm surface inclusion and at least 33% scattering contrast was detected up to 1.5 mm below the phantom surface, a probing depth relevant to breast surgical margin assessment. Recovered hemoglobin concentrations were insensitive to changes in scattering, except for overestimation at visible wavelengths for total hemoglobin concentrations <15  μM. The scattering amplitude increased linearly with scattering concentration, but the scattering slope depended on both the particle size and number density. Goodness of fit was comparable for the diffusion and scaled-Monte Carlo models of transport in spatially modulated, near-infrared reflectance acquired from 47 lumpectomy tissues, but recovered absorption parameters varied more linearly with expected hemoglobin concentration in liquid phantoms for the scaled-Monte Carlo forward model. SFDI could potentially reduce the high secondary excision rate associated with breast conserving surgery; its clinical translation further requires reduced image reconstruction time and smart inking strategies.

authors

  • Laughney, Ashley
  • Krishnaswamy, Venkataramanan
  • Rice, Tyler B
  • Cuccia, David J
  • Barth, Richard J
  • Tromberg, Bruce J
  • Paulsen, Keith D
  • Pogue, Brian W
  • Wells, Wendy A

publication date

  • March 1, 2013

Research

keywords

  • Breast
  • Breast Neoplasms
  • Image Processing, Computer-Assisted
  • Mastectomy, Segmental
  • Spectroscopy, Near-Infrared

Identity

PubMed Central ID

  • PMC3605471

Scopus Document Identifier

  • 84880813666

Digital Object Identifier (DOI)

  • 10.1117/1.JBO.18.3.036012

PubMed ID

  • 23525360

Additional Document Info

volume

  • 18

issue

  • 3