A geometric-sensitivity-difference method improves object depth-localization for continuous-wave fluorescence diffuse optical tomography: An in silico study in an axial outward-imaging geometry

Abstract

A geometric-sensitivity-difference (GSD) based reconstruction method is demonstrated in fluorescence diffuse optical tomography (FDOT) for improving the depth-localization of objects. The GSD method optimizes the data-model fit based on paired-measurements between source-detector pairs sharing either the source or the detector channel, as comparing to conventional methods that optimize the data-model fit based on un-paired measurements of individual source-detector pairs. This in silico study is limited to continuous-wave and 2-dimension, for a circular-array outward-imaging geometry of which the native sensitivity of measurement varies strongly with respect to the depth of the object. The outcomes of GSD method are compared to that of two conventional methods: one is the baseline method which does not involve any scheme to compensate the variation of native sensitivity; the other applies a depth-adapted weight to counteract the depth-variance of the native sensitivity. These three methods were evaluated using synthetic data corresponding to the following conditions of the object: (1) Single object with a 3-folds of positive contrast of fluorescence over the background was set at edge-depths of 0.5 mm, 5 mm and 10 mm; (2) Two objects with identical 3-folds of positive or 1/3-folds of negative contrast of fluorescence over the background were set at a fixed edge-depth of 10 mm and different azimuthal separations of 45 degree, 135 degree, and 180 degree; (3) Two objects with identical 3-folds of positive or 1/3-folds of negative contrast of fluorescence over the background were set at a fixed azimuthal separation of 90 • and at edge-depths of 0.5 mm, 5 mm and 10 mm. The GSD method outperforms the other two methods in localizing a single anomaly and resolving two anomalies, for the anomaly possessing either the 3 folds positive or 1/3-folds negative contrast of fluorescence over the background. The case of objects with negative contrast over the background has specific implications to imaging zinc-specific fluorophore uptake in prostate.

Sensitivity laplacian ratio-based optimization of the projection selection for diffuse optical tomography

“…[ 8 ] In many studies, the uniformity of the sensitivity matrix was used to evaluate different geometries. [ 9 10 11 12 ] The sensitivity matrix is derived from the sum of the Jacobian matrix rows and represents the sensitivity of the sample points for all of the source-detector pairs. The sensitivity matrix is the function of the imaging geometry and sampling strategy.…”