scatterBrains: an open database of human head models and companion optode locations for realistic Monte Carlo photon simulations

Abstract

.SignificanceMonte Carlo (MC) simulations are currently the gold standard in the near-infrared and diffuse correlation spectroscopy (NIRS/DCS) communities for generating light transport paths through tissue. However, realistic and diverse models that capture complex tissue layers are not easily available to all; moreover, manually placing optodes on such models can be tedious and time consuming. Such limitations may hinder the adoption of representative models for basic simulations and the use of these models for large-scale simulations, e.g., for training machine learning algorithms.AimWe aim to provide the NIRS/DCS communities with an open-source, user-friendly database of morphologically and optically realistic head models, as well as a succinct software pipeline to prepare these models for mesh-based Monte Carlo simulations of light transport.ApproachSixteen anatomical models were created from segmented T1-weighted magnetic resonance imaging (MRI) head scans and converted to tetrahedral mesh volumes. Approximately 800 companion scalp surface locations were distributed on each model, comprising full head coverage. A pipeline was created to place custom source and optical detectors at each location, and guidance is provided on how to use these parameters to set up MC simulations.ResultsThe models, head surface locations, and all associated code are freely available under the scatterBrains project on Github.ConclusionsThe NIRS/DCS community benefits from having shared resources for conducting MC simulations on realistic head geometries. We hope this will make MRI-based head models and virtual optode placement easily accessible to all. Contributions to the database are welcome and encouraged.

Comparing the performance potential of speckle contrast optical spectroscopy and diffuse correlation spectroscopy for cerebral blood flow monitoring using Monte Carlo simulations in realistic head geometries

“…We conclude by discussing limitations of the study, including aspects of real-life measurements not considered in simulation and potential pitfalls. We made the code for generating the sensitivity, coefficient of variation (CoV), and contrast-to-noise ratio estimates from the outputs of Monte Carlo simulations run on an open-source dataset of MRI-derived head models publicly available as an example in the scatterBrains repository 20 so that researchers can evaluate the performance of a particular DCS or SCOS system with the parameters different from what has been explored in this paper.…”