Development of a Model to Aid NIRS Data
Interpretation: Results from a Hypercapnia
Study in Healthy Adults
Tracy Moroz1, Murad Banaji1, Martin Tisdall1, Chris E. Cooper2, Clare E.
Elwell1, Ilias Tachtsidis1
1Biomedical Optics Research Laboratory, Department of Medical Physics and
Bioengineering, University College London, Gower Street, London WC1E 6BT,2Department
of Biological Sciences, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK
Abstract The use of a mathematical model of cerebral physiology and metabo-
lism may aid the interpretation of experimentally measured data. In this study,
model outputs of tissue oxygen saturation (TOS) and velocity of blood in the mid-
dle cerebral artery (Vmca) were compared with experimentally measured signals
(TOS using near infrared spectroscopy and Vmca using transcranial Doppler) ac-
quired during hypercapnia in healthy volunteers. Initially, some systematic dis-
crepancies between predicted and measured values of these variables were identi-
fied. The model was optimised to best fit the measured data by adjusting model
parameters. To improve the fit, three additional model mechanisms were consid-
ered. These were: an extracerebral contribution to TOS, a change in venous vol-
ume with CO2levels, and a change in oxygen consumption with CO2levels. Each
mechanism, when used alone, improved the fit of the model to the data, although
significant parameter changes were necessary. It is likely that a combination of
these mechanisms will improve the success of modelling of TOS and Vmca
changes during hypercapnia.
Changes in carbon dioxide levels are known to alter cerebral blood flow . Hy-
percapnia studies have been carried out in healthy volunteers to characterise brain
tissue oxygenation and blood flow changes, measured with near-infrared spectros-
copy (NIRS) and transcranial Doppler (TCD) .
Here we apply the BrainSignals model , a physiological model of brain cir-
culation and metabolism, to data from a hypercapnia study in healthy adults .
The model predicts several physiological variables, including those which can be
measured with NIRS and TCD. It has previously been used successfully to de-
Fig. 3 Modelled response minus measured response for TOS vs Vmca. The response is the dif-
ference (TOS) or percentage change (Vmca) of the mean at hypercapnia from the mean at base-
line. The legend refers to the six optimisation methods described in Table 2. Series 0 represents
no optimisation. Each point within a series represents a subject. The box at the origin surrounds
all the points from optimisations 4-6, where new mechanisms were introduced.
Fig. 4. Examples of TOS, Vmca and CMRO2from one volunteer. The graphs show the measured
signal (solid black), the modelled signal after optimisation 3 (dashed) and the modelled signal af-
ter optimisation 6 (solid grey).