Three‐dimensional frequency‐domain optical anisotropy imaging of biological tissues with near‐infrared light. Issue 9 (5th July 2019)

• Record Type: Journal Article
• Authors: Addoum, Ahmad; Contassot‐Vivier, Sylvain; Asllanaj, Fatmir
• Is Part Of: Medical physics. Volume 46:Issue 9(2019)
• Page Start: 4057
• Page End: 4069
• Publication Date: 2019-07-05
• Subjects: anisotropy factor -- cancer diagnosis -- optical image reconstruction -- radiative transfer equation; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.13636
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: Near‐infrared optical imaging aims to reconstruct the absorption μ a and scattering μ s coefficients in order to detect tumors at early stage. However, the reconstructions have only been limited to μ a and μ s due to theoretical and computational limitations. The authors propose an efficient method of the reconstruction, in three‐dimensional geometries, of the anisotropy factor g of the Henyey–Greenstein phase function as a new optical imaging biomarker. Methods: The light propagation in biological tissues is accurately modeled by the radiative transfer equation (RTE) in the frequency‐domain. The reconstruction algorithm is based on a gradient‐based updating scheme. The adjoint method is used to efficiently compute the gradient of the objective function which represents the discrepancy between simulated and measured boundary data. A parallel implementation is carried out to reduce the computational time. Results: We show that by illuminating only one surface of a tissue‐like phantom, the algorithm is able to accurately reconstruct optical values and different shapes (spherical and cylindrical) that characterize small tumor‐like inclusions. Numerical simulations show the robustness of the algorithm to reconstruct the anisotropy factor with different contrast levels, inclusion depths, initial guesses, heterogeneous background, noise levels, and two‐layered medium. The crosstalk problem when reconstructing simultaneously μ s and g has been reported and achieved with a reasonable quality. Conclusions: The proposed RTE‐based reconstruction algorithm is robust to spatially retrieve and localize small tumoral inclusions. Heterogeneities in g ‐factor have been accurately reconstructed which makes the new algorithm a candidate of choice to image this factor as new intrinsic contrast biomarker for optical imaging.