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Proceedings Paper

Modelling and validation of diffuse reflectance of the adult human head for fNIRS: scalp sub-layers definition
Author(s): Javier Herrera-Vega; Samuel Montero-Hernández; Ilias Tachtsidis; Carlos G. Treviño-Palacios; Felipe Orihuela-Espina
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Paper Abstract

Accurate estimation of brain haemodynamics parameters such as cerebral blood flow and volume as well as oxygen consumption i.e. metabolic rate of oxygen, with funcional near infrared spectroscopy (fNIRS) requires precise characterization of light propagation through head tissues. An anatomically realistic forward model of the human adult head with unprecedented detailed specification of the 5 scalp sublayers to account for blood irrigation in the connective tissue layer is introduced. The full model consists of 9 layers, accounts for optical properties ranging from 750nm to 950nm and has a voxel size of 0.5mm. The whole model is validated comparing the predicted remitted spectra, using Monte Carlo simulations of radiation propagation with 108 photons, against continuous wave (CW) broadband fNIRS experimental data. As the true oxy- and deoxy-hemoglobin concentrations during acquisition are unknown, a genetic algorithm searched for the vector of parameters that generates a modelled spectrum that optimally fits the experimental spectrum. Differences between experimental and model predicted spectra was quantified using the Root mean square error (RMSE). RMSE was 0.071 ± 0.004, 0.108 ± 0.018 and 0.235±0.015 at 1, 2 and 3cm interoptode distance respectively. The parameter vector of absolute concentrations of haemoglobin species in scalp and cortex retrieved with the genetic algorithm was within histologically plausible ranges. The new model capability to estimate the contribution of the scalp blood flow shall permit incorporating this information to the regularization of the inverse problem for a cleaner reconstruction of brain hemodynamics.

Paper Details

Date Published: 17 November 2017
PDF: 8 pages
Proc. SPIE 10572, 13th International Conference on Medical Information Processing and Analysis, 1057206 (17 November 2017); doi: 10.1117/12.2285918
Show Author Affiliations
Javier Herrera-Vega, Instituto Nacional de Astrofísica Óptica y Electrónica (Mexico)
Samuel Montero-Hernández, Instituto Nacional de Astrofísica Óptica y Electrónica (Mexico)
Ilias Tachtsidis, Univ. College London (United Kingdom)
Carlos G. Treviño-Palacios, Instituto Nacional de Astrofísica, Óptica y Electrónica (Mexico)
Felipe Orihuela-Espina, Instituto Nacional de Astrofísica, Óptica y Electrónica (Mexico)


Published in SPIE Proceedings Vol. 10572:
13th International Conference on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva; Juan David García, Editor(s)

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