Marco Piccirelli^{1}, Christiaan Hendrik Bas van Niftrik^{2}, Oliver Bozinov^{2}, Athina Pangalu^{1}, Antonio Valavanis^{1}, Luca Regli^{2}, and Jorn Fierstra^{2}

^{1}Department of Neuroradiology, University Hospital Zurich, Zurich, Switzerland, ^{2}Department of Neurosurgery, University Hospital Zurich, Zurich, Switzerland

### Synopsis

**Our iterative algorithm evaluates transient
phases of BOLD fMRI signal dynamics during a CO2 pseudo-square wave challenge
and optimizes CO2 arrival time determination to increase sensitivity and
reliability of cerebrovascular reactivity analysis.
On 25 healthy controls and unilateral
internal carotid occlusion patients, all BOLD-derived parameters maps are normalized
in MNI space and combined for reference atlases and assess alterations within single
patient.
The transient phase durations, temporal
delay maps and dynamic and static CVR maps were calculated.
We determined the optimal CO2 arrival time
and found that excluding the transient phases resulted in the best fit to the physiological
data.**### PURPOSE – “Why was this study/research
performed?"

The BOLD cerebrovascular reactivity
response to a CO2 challenge of neuro-vascular Patients is clinically relevant and
has a complex temporal dynamic. This neurovascular response-function differs
greatly from the commonly used canonical HRF. (Poublanc et al., 2015)
Therefore,
we present here a novel model-free iterative analysis for evaluating transient
phase duration parameters describing BOLD fMRI signal dynamics during a
monitored CO2 pseudo- square wave challenge. We aim to optimize the CO2 arrival
time description to increase sensitivity and reliability of cerebrovascular
reactivity analysis, test our algorithm for its clinical relevance on patient data
and thereby gain further pathophysiological insight.

### METHODS – “How has this problem been
studied?”

The algorithm explained in Fig1 is
illustrated using datasets of Patients with unilateral internal carotid
occlusion and healthy Controls. Secondly, BOLD-fMRI derived normalized maps of
25 healthy subjects in MNI standard space are combined for reference atlases of
all BOLD-derived parameters to better assess alterations within a single
subject. All subjects underwent a standardized CO2 pseudo square wave increase
of ± 8.3±1.6mmHg of partial pressure of end-tidal CO2 (PetCO2)
from a calibrated baseline of 40.1±1.2mmHg PetCO2,
executed by a custom built computer controlled gas blender (RepirActTM,
Thornhill Research Institute, Toronto, Canada) using the prospective gas
targeting algorithms. (Slessarev et al., 2007)
The iterative algorithm was then applied to
the data to calculate both the transient phase durations, temporal delay maps
and dynamic and static CVR maps. We compared our algorithm to the state-of-the-art
methods used in the literature: the maximum correlation method.

### RESULTS – “Principal data and statistical
analysis”

BOLD time series vs CO2 time series are
presented with different CO2 arrival times applied to the data. We determined
the most optimal CO2 arrival time and found that the parametric decomposition
resulted in the best description of the physiological data for white and grey
matter (Fig2). The linear fit of the BOLD vs. CO2 scatter plot shows clearly that
only our algorithm removes the transition phases between the two static states
correctly.
Our algorithm corrected the too long CVR
response delay obtained with the maximum correlation method: WM: 40 s, GM: 10 s;
to the more realistic delay of WM 18 s, GM: 2 s.
Fig2.4 shows the respective duration of the
DTP: Delay to Plateau and of the DTB: Delay to Baseline for GM and WM with the
dynamic (CVRcorr) and static (CVRstat) CVR maps.
The CVR maps obtained with our algorithm
differed significantly from previous CVR maps obtained with not correct delays.
The new parametric maps obtained: DTP, DTB have
a good SNR and clinically plausible.

### DISCUSSION – “What is the interpretation of
the data?”

Improved pathophysiological insight could
be gained with the decomposition of the dynamic response: the separation of the
arterial arrival time of CO2 from the CO2-BOLD relationship improved the
sensitivity and reliability of CVR measurements.
Further, knowing the transient phase
durations allows calculation of a static CVR which can be used to compare the
MRI data to static CVR data obtained from the clinical gold-standard imaging
modalities like Positron-Emission-Tomography or Xenon enhanced-Computed-Tomography,
.(Vagal, et al
2009)

### CONCLUSION – “What is the relevance to clinical practice or future research?”

The improved quantification of monitored CVR fMRI data increased sensitivity of DYNAMIC BOLD-CVR measurements by excluding the CO2 arrival time fMRI and might allow the replacement of clinical static CVR measurements.

### Acknowledgements

MP and CHBVN: equal first Author contribution### References

Poublanc, J.,
Crawley, A., Sobzcyk, O., Sam, K., Mandell, D., Venkatravaghan, L., Fisher, J. (2015). Measuring cerebrovascular reactivity: the dynamic response
to a step hypercapnic stimulus.

Slessarev, M., Han, J., Mardimae, A., Prisman, E., Preiss, D.,
Volgyesi, G., Fisher, J. A. (2007). Prospective targeting and control of
end-tidal CO2 and O2 concentrations. J
Physiol, 581(Pt 3), 1207-1219. doi: 10.1113/jphysiol.2007.129395

Vagal, A. S., Leach, J. L., Fernandez-Ulloa, M., & Zuccarello,
M. (2009). The acetazolamide challenge: techniques and applications in the
evaluation of chronic cerebral ischemia. AJNR
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