Probabilistic atlas can improve reconstruction from optical imaging of the neonatal brain

Juha Heiskala,Mika Pollari,Ilkka Nissilä,P Ellen Grant,Marjo Metsäranta

doi:10.1364/oe.17.014977

Abstract

Diffuse optical imaging is an emerging medical imaging modality based on near-infrared and visible red light. The method can be used for imaging activations in the human brain. In this study, a deformable probabilistic atlas of the distribution of tissue types within the term neonatal head was created based on MR images. The use of anatomical prior information provided by such atlas in reconstructing brain activations from optical imaging measurements was studied using Monte Carlo simulations. The results suggest that use of generic anatomical information can greatly improve the spatial accuracy and robustness of the reconstruction when noise is present in the data.

Highlights

Diffuse optical imaging is an emerging medical imaging modality which uses near-infrared (NIR) and visible red light to probe tissue physiology
In our recent study [11], we found that accurate anatomical a priori information from MR imaging can significantly improve the spatial accuracy and robustness of reconstructing absorption changes due to brain activation in the neonatal human brain
We suggest that an atlas model which provides generic anatomic a priori information without requiring MR imaging of the subject could be a valuable aid in optical imaging of the infant brain

Summary

Introduction

Diffuse optical imaging is an emerging medical imaging modality which uses near-infrared (NIR) and visible red light to probe tissue physiology. Information about optical properties within the tissue being imaged is drawn from measurements of light that has traveled through. In order to reconstruct changes in the optical properties of tissue, a model which predicts light propagation between the source and detector fibers is needed. This requires a computational model and a compatible anatomical model. Light propagation in tissue is thought to be accurately modeled by the Radiative Transfer Equation (RTE) [4]. The diffusion approximation (DA) to the RTE is considered fairly accurate in most tissues, and can be efficiently implemented using the finite element method [6]. Drawbacks of using the DA include the inability to correctly model light propagation in tissues with low scattering such as the cerebrospinal fluid (CSF), and inaccuracy close to the light sources, where the light propagation is not completely diffusive

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Conclusion