Abstract

Preterm infants have a high incidence of brain lesions that may lead to long-term disabilities. Early diagnosis of cerebral ischemia and hemorrhage may enable protection of the brain by prevention or neuroprotective treatment. Our recently developed time-domain near-infrared optical tomography (TD NIROT) system provides images to diagnose neonatal brain injury. Our aim is to study the image quality achievable from the TD NIROT signals perturbed by noise for two common cases: ischemia and hemorrhage. We implemented simulations on a spherical model of diameter 60 mm representing a typical neonatal head where the absorption μa=0.08 cm-1and the reduced scattering μ's=4.1 cm-1. Injury-mimicking spherical inclusions of various diameters (1~10mm) were placed at depths of 10~20 mm in the ischemia case (2.5×μa) and 14~30 mm for the hemorrhage case (50×μa). TD data were generated from a large number of source-detector pairs, i.e., 208 detectors placed within a circle of diameter 40 mm on the surface surrounded by 18 sources. Up to 5% Gaussian noise was added in the simulations. 3D images were reconstructed with the modified Tikhonov minimization with the initial guess of a homogeneous phantom, and the images were evaluated by positional error and Dice similarity. The inclusions were localized correctly with low positional errors (<1mm), and the segmented images share a high Dice similarity with the ground truth for both the ischemia and the hemorrhage case, even for tiny inclusions of 1 mm in deep tissue. The hemorrhage case with a high contrast tolerates a substantial level of noise even though the performance drops with higher noise as expected. The large amount of data provided by our novel TD NIROT system provides rich enough information for correctly locating hemorrhage and ischemia in the neonatal brain.

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