A boundary element approach for image‐guided near‐infrared absorption and scatter estimation

Multimodality NIR spectroscopy systems offer the possibility of region‐based vascular and molecular characterization of tissue in vivo . However, computationally efficient 3D image reconstruction algorithms specific to these image‐guided systems currently do not exist. Image reconstruction is often based on finite‐element methods (FEMs), which require volume discretization. Here, a boundary element method (BEM) is presented using only surface discretization to recover the optical properties in an image‐guided setting. The reconstruction of optical properties using BEM was evaluated in a domain containing a 30 mm inclusion embedded in two layer media with different noise levels and initial estimates. For 5 % noise in measurements, and background starting values for reconstruction, the optical properties were recovered to within a mean error of 6.8 % . When compared with FEM for this case, BEM showed a 28 % improvement in computational time. BEM was also applied to experimental data collected from a gelatin phantom with a 25 mm inclusion and could recover the true absorption to within 6 % of expected values using less time for computation compared with FEM. When applied to a patient‐specific breast mesh generated using MRI, with a 2 cm ductal carcinoma, BEM showed successful recovery of optical properties with less than 5 % error in absorption and 1 % error in scattering, using measurements with 1 % noise. With simpler and faster meshing schemes required for surface grids as compared with volume grids, BEM offers a powerful and potentially more feasible alternative for high‐resolution 3D image‐guided NIR spectroscopy.