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Real-time phase contrast magnetic resonance imaging for assessment of cerebral haemodynamics during breathing.
Olivier Balédent1,2, Pan Liu1, Armelle Lokossou1, Fall Sidy1, Serge Metanbou3, and Malek Makki1,4

1EA 7516 Chimère, Jules Verne university, amiens, France, 2Image Processing, Jules Verne University Hospital, Amiens, France, 3Neuro Radiology, Jules Verne University Hospital, Amiens, France, 4MRI Research GIE-IFF CHU Amiens Picardie, Amiens, France

Synopsis

To investigate cerebral blood flows by EPI Phase Contrast (EPI-PC) and Normal Phase contrast sequences, in volunteers. Cerebral arterial and venous blood flows were calculated by homemade software. Arterial cerebral blood flows measured by EPI-PC were significantly higher than those measured by normal PC. Whereas venous cerebral blood flows were not different between the two technics. Post processing of continuous EPI-PC flow signal provides blood flows curves during inspiration and expiration. Blood flows during inspiration were respectively higher than during expiration. EPI-PC flow quantify arterial and venous intracranial blood flows in few seconds without any cardiac or respiratory gating.

INTRODUCTION:

Phase contrast MRI (normal-PC)1 can quantify cerebral blood flow dynamic by using cardiac synchronization. This sequence reconstruct only one mean flow curve from all the cardiac cycles of the acquisition. It is not possible to take in account the breathing impact that can affect the blood flow. New Phase contrast MRI sequence based on Echo Planar imaging (EPI-PC) can now produce continuously velocity map, more or less every 100 ms function of the machine and of the quality wanted2. The aim of this work is to apply an EPI-PC protocol and Normal-PC to investigate total cerebral blood flow and potential respiratory effect on it.

METHODS:

The study was performed on a 3T Achieva dStream scanner with gradient strength of 40 mT/m and a 32 channels head coil (Figure 1). Fourteen adult volunteers in accordance with ethical procedure were included to investigate blood flow in their internal carotids and basilar arteries and in their straight and sagittal sinuses. (Figure 2)Two different acquisitions were used:

• 2D Cine Normal-PC using retrospective plethysmograph gating.

• 2D EPI-PC free of any synchronization.

Post processing was done by homemade software to calculate dynamic blood flow curve for each vessel during cardiac cycle. A background correction area was applied. Normal-PC provides only one flow curve to represent all the cardiac cycles of the acquisition whereas EPI-PC provides continuous flow dynamics curves. Respiratory physiological signals were recorded during the MRI acquisitions using a pneumatic belt sensor. From EPI-PC signal, each cardiac cycle was identified to reconstruct three mean cardiac flow curves from: all the cardiac cycles, the expiration periods and the inspiration periods. (Figure 3). Cerebral arterial and venous blood flows were calculated by summation of the arterial and venous flows. Measured Cerebral venous flow was artificially increased to equal mean arterial flow and generate arterio-venous flow rate and calculate cerebral blood volume change during cardiac cycle3 (figure 4). Statistical Pearson correlation and paired t-student tests were used to compare EPI-PC and Normal-PC results.

RESULTS:

A good correlation between Normal and EPI-PC measurements was found for all the arterial flows. A higher correlation was found for the venous blood flows. (Figure 5) The vessel areas of the internal carotid arteries measured in the EPI-PC images were significantly higher than those segmented in the Normal-PC images (25.7±6.1 mm2 versus 18.9±4.1) whereas area of the sagittal sinuses were not significantly different between the two sequences (35.9±9.9 mm2 versus 34.5±11.8 mm2). Arterial cerebral blood flows (864±370 ml/min) calculated by EPI-PC were significantly (p<0.01) higher than those (583±165 ml/min) measured by normal-PC. Whereas venous cerebral blood flows were not different between the two technic (416±147 ml/min for EPI-PC and 454±200 ml/min for normal-PC). Arterial and venous blood flows during inspiration were respectively higher than during expiration (10% and 8%). Duration of cardiac cycle during inspiration was significantly (p<0.01) smaller (0.80±0.10 sec) than during expiration (0.89±0.15 sec). Mean intracranial vascular blood volume change during cardiac cycle was not significantly different between expiration (0.64±0.21 ml) and inspiration (0.66±0.22 ml).

DISCUSSION:

Post processing is very important to extract quantitative and interpretable information from the large number of images and no commercial dedicated tool still exists. Due to poor spatial resolution of EPI-PC we found an important difference in the arteries area measurements between the two sequences which explain the important difference found in arterial flows between the two sequences. A better spatial resolution should limit partial volume effect in the arteries. This problem was limited in venous flows because the sinuses presented larger areas and less pulsatile flow. EPI-PC protocol presented a temporal resolution of 113 ms which is too small and explains why arterial flow curve shape was more round than normal-PC. These limitations should be partly corrected by increasing the accelerator EPI factor and decreasing the FOV. These preliminary results have shown how respiratory impact arterial and venous cerebral blood flows and the duration of the cardiac cycle. It was surprising to found that the cerebral blood volume change calculated was not impacted by breathing. But this volume is small and should be interpreted with caution.

CONCLUSION:

This new real time EPI-PC sequence is useful to investigate cerebral blood flow in few seconds without any cardiac or respiratory gating but needs a convivial and accurate post processing tool to be easily used in clinical practice. Such new flow investigations open new ways to better understand cerebral pathologies as idiopathic hydrocephalus, idiopathic hypertension, Chiari malformation and syringomyelia where cerebral fluids dynamics seems to be altered4.

Acknowledgements

Thanks to :

Garance Arbeaumont Trocme and Caroline Fournier our clever MRI technicians.

David Chechin from Phillips for his scientific support.

All the volunteers who trust us and let us working with their spins

Agence national de la recherche : ANR-18-CE45-0014-04 and Région Haut de France for the financial support.

References

1. Feinberg D.A., Mark A.S. Human brain motion and cerebrospinal fluid circulation demonstrated with MR velocity imaging. Radiology 1987 (163) : 793–799.

2. Chen L , Beckett A ,Verma A, Feinberg D. Dynamics of respiratory and cardiac CSF motion revealed with real-time simultaneous multi-slice EPI velocity phase contrast imaging. NeuroImage 2015 ; (122) : 281–287

3. Balédent O, Henry-Feugeas MC, Idy-peretti I, Cerebrospinal fluid dynamics and relation with blood flow: a magnetic resonance study with semiautomated cerebrospinal fluid segmentation. Investigative radiology (7), 368-37.

4. Skytioti M, Søvik S, Elstad M. Respiration-related cerebral blood flow variability increases during control-mode non-invasive ventilation in normovolemia and hypovolemia. Eur J Appl Physiol. 2017 Nov; (11):2237-2249

Figures

Figure 1 : MRI Acquisition parameters

Figure 2 : Intracranial acquisition planes selected for EPI-PC and Normal-PC flow sequences on 3D phase contrast angiography. Red arrows represent internal carotid arteries. Orange arrow represents basilar artery. Blue arrows represent Sagittal and Straight sinuses. The schema represents how cardiac and breathing impacts cranio-spinal fluids dynamics.

Figure 3 : Post processing of an internal carotid artery of an healthy volunteer. On the left, blood flow measured by Normal PC, was calculated over the 32 phases of a mean cardiac cycle. On the right the same artery was measured by EPI PC which produces continuously in real time the blood flows over the entire acquisition duration. Each cardiac cycle can be identified (red star). A global mean cardiac cycle was calculated “all”. Expiration and inspiration periods were identified by physiological signal to calculate a mean “Expiration” and “Inspiration” flow curves.

Figure 4 :Example of EPI PC blood flows analysis. Internal carotids and basilar arteries were summed to calculate total cerebral arterial blood flows from “all” the cardiac cycle acquired, from only the cardiac cycles present in the “expiration” period and from only the cardiac cycles present in the “inspiration” period. In the same way sinuses were summed to calculate the measured cerebral venous flows and calculated theoretical arterio-venous flow and intracranial blood volume change during cardiac cycle during normal breathing. Arterial and venous flows increase during inspiration but no difference was present in arterio-venous and intracranial blood volume change during breathing.

Figure 5 : Internal carotid and basilar arteries blood flows measured by normal PC were corelated with those measured by EP PC but some points were far the correlation line showing some limitations these measurements. The second graphic shows a better correlation of the sinuses blood flows measurements.

Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)
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