ORIGINAL ARTICLE

Noninvasive Measurements of Cerebral Blood Flow, OxygenExtraction Fraction, and Oxygen Metabolic Index in Humanwith Inhalation of Air and Carbogen using MagneticResonance Imaging

Hongyu An & Souvik Sen & Yasheng Chen &

William J. Powers & Weili Lin

Received: 13 September 2011 /Revised: 16 November 2011 /Accepted: 15 December 2011 /Published online: 28 December 2011# Springer Science+Business Media, LLC 2011

Abstract Noninvasive magnetic resonance (MR) methodshave been explored to provide quantitative measurements ofcerebral blood flow (CBF), oxygen extraction fraction(OEF), and oxygen metabolic index (OMI0CBF×OEF).In this study, we sought to evaluate whether MR measuredOEF, CBF, and OMI can consistently detect the expectedphysiological changes in humans under normal and hyper-oxic hypercapnic conditions. Nine healthy human subjectswere scanned while breathing through a mask, alternatinginhaled gas in a sequential order as room air, carbogen (3%CO2 mixed with 97% O2), room air, carbogen, and room air.OEF, CBF, and OMI were obtained from the whole brain,gray matter (GM), and white matter (WM) at each gasinhalation state. Similar to previous positron emission to-mography findings, our study consistently demonstrated a10–12% decrease in OEF with a 10% increase of CBF and a

stable OMI during carbogen inhalation. Moreover, GM/WMratio in CBF and OMI remained constant during air andcarbogen breathing. In addition, OEF, CBF, and OMI werehighly reproducible if the same inhaled gas was used. Insummary, our results demonstrate that noninvasive MRmeasurements can provide reproducible measurements ofOEF, CBF, and OMI in normal subjects under normal andaltered physiological conditions.

Keywords Oxygen extraction fraction . Cerebral bloodflow .MRmeasured oxygen metabolic index . Asymmetricspin echo . Arterial spin labeling . Carbogen

Introduction

Normal resting cellular activities of human brains demandhigh energy that is primarily provided by a steady ATP(adenosine 5′-triphosphate) supply generated through oxi-dative metabolism of glucose. Compromise of oxygen me-tabolism may lead to brain damage within minutes to a fewhours [1, 2]. Therefore, absolute in vivo quantitative meas-urements of cerebral oxygen metabolism are critically im-portant for understanding of brain function under bothnormal and pathological conditions.

Thus far, positron emission tomography (PET) has beenthe method of choice for quantitative in vivo measurementsof cerebral oxygen metabolism [3, 4]. In PET studies, cere-bral metabolic rate of oxygen utilization (CMRO2) is de-fined as the product of cerebral blood flow (CBF), oxygenextraction fraction (OEF), and arterial oxygen content(CaO2). CBF×CaO2 and OEF reflect the oxygen deliveryand demand, respectively. Due to the requirement of an

H. An (*) :Y. Chen :W. LinDepartment of Radiology and Biomedical Research ImagingCenter, University of North Carolina at Chapel Hill,CB#7513, Chapel Hill, NC 27599, USAe-mail: hongyuan@med.unc.edu

S. SenDepartment of Neurology,University of South Carolina,Columbia, SC, USA

W. J. Powers :W. LinDepartment of Neurology,University of North Carolina at Chapel Hill,Chapel Hill, NC 27599, USA

W. LinDepartment of Biomedical Engineering,University of North Carolina at Chapel Hill,Chapel Hill, NC 27599, USA

Transl. Stroke Res. (2012) 3:246–254DOI 10.1007/s12975-011-0142-9

onsite cyclotron owing to the extremely short half-life time of15O (2 min), CMRO2 quantification using PET is not readilyavailable to most medical centers for routine clinical usage.

Since its inception, magnetic resonance imaging (MRI)has gained preeminence owing to its excellence in soft tissuecontrasts, sensitivity to a wide range of tissue properties,flexibility, and noninvasiveness. With rapid technical devel-opments in the past several decades, MRI has become apromising modality for functional and metabolic imaging.The blood oxygenation level dependent (BOLD) contrast [5,6] provides a unique opportunity to evaluate tissue oxygen-ation. An absolute quantification of cerebral oxygen metab-olism using BOLD contrast is possible by relating MRsignal to tissue oxygenation through biophysical signalmodels. It has been demonstrated that tissue-level cerebraloxygen extraction fraction (OEF) can be obtained noninva-sively using MRI [7–9]. Moreover, validation studies havebeen performed in rats by comparing MR measurementswith arterio-venous sampling [10, 11]. In parallel, MRmethods such as dynamic susceptibility contrast (DSC)[12, 13] and arterial spin labeling method (ASL) have beendeveloped to provide quantitative measurements of cerebralblood flow (CBF) [14–16]. By combining the MR measuredOEF and CBF, it is feasible to obtain an oxygen metabolicindex (OMI0CBF×OEF) non-invasively [10, 17, 18] inboth human and rats under normal and ischemic conditions.In the previous publications, the product of CBF and OEFwere termed as MR CMRO2. To distinguish it from the PETCMRO2 (defined as OEF×CBF×CaO2), a term “MR-de-rived cerebral oxygen metabolic index” (MR_COMI) hasthen been utilized [10]. In this study, we further simplified itas OMI. While preliminary experience has demonstratedthat MR measured OEF and OMI may offer clinical utilityin stroke models/patients, it is imperative to further deter-mine whether these MR methods can provide reliable andreproducible measurements in human under normal andphysiologically altered conditions. To this end, CBF, OEF,and OMI were estimated in a group of normal subjects whounderwent repeated episodes of gas challenge using roomair and carbogen inhalation. We sought to evaluate whetherthe CBF, OEF, and OMI measurement can detect theexpected physiological changes in human brain under alter-native normal and hyperoxic hypercapnic conditions andwhether these measurements are reproducible under repeat-ed normal or hyperoxic hypercapnic conditions.

Materials and Methods

Subjects and Experimental Protocol

All experimental protocols were approved by the Institu-tional Review Board in the University of North Carolina atChapel Hill. Written informed consent was obtained from allsubjects prior to the experiments. The experimental proce-dures were in accordance with the ethical standards set bythe local institution. Nine healthy human subjects (one maleand eight females, age038±9 years) were imaged using aSiemens 3.0-T Allegra head-only scanner with a maximumgradient strength of 40 mT/m and a maximum slew rate of400 mT/m/ms (Siemens Medical Systems, Erlangen, Ger-many). Subjects were asked to refrain from intake of alcoholand caffeine 12 h prior to imaging. A full medical historywas obtained from the subjects including screening for anyuncontrolled hypertension, diabetes, smoking, cardiovascu-lar disease, cardiac arrhythmia, cerebrovascular disease, sei-zure disorder, and pulmonary disease such as asthma oremphysema.

The overall experimental scheme is demonstrated inFig. 1. During the imaging session, subjects were breath-ing via a Hudson RCI Medium Concentration-Elongated,adult face mask (CNA Medical, Royse City, TX, USA)by alternating inhaled gas mixture of either room air orcarbogen (3% CO2 mixed with 97% O2) in a sequentialorder as room air, carbogen, room air, carbogen, androom air (Fig. 1). The imaging study started after thesubjects became accustomed to breathing air through theface mask. After each adjustment of gas, 5 min wereallowed before data acquisition to achieve a stabilizedphysiological status. Pulse rate and arterial blood oxygensaturation (SaO2) were monitored by a physician desig-nee in the magnet room using a MR-compatible physio-logical monitor, Invivo Precess (Invivo Research Inc.,Gainesville, FL, USA). During each gas inhalation state,MR sequences tomeasure OEF and CBF (sequence details arein the next section) were acquired back to back. In addition,high resolution T1-weighted images were acquired usinga 3D MP-RAGE sequence prior to gas manipulation withthe imaging parameters as follows: repetition time (TR)/echo time (TE)01700/4.38 ms, TI0900 ms, field of view(FOV)0256 mm2, and an isotropic voxel size of 1×1×1 mm3.

Fig. 1 Experimental scheme

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OEF Measurements using an Asymmetric Spin Echo EPI

Deoxyhemoglobin, an endogenous magnetic susceptibilitysource in venous blood vessels and capillaries, can causemesoscopic magnetic field variations both within and be-yond the venous blood vessels [19, 20]. Assuming the signalcontribution from the intravascular compartment is negligi-ble and the blood vessels are randomly oriented, a biophys-ical model was proposed to directly relate R2′ with OEF inthe static dephasing regime [20]. In this study, an asymmet-ric spin echo (ASE) single shot echo planar imaging (EPI)sequence was utilized to acquire a set of images that have avarying degree of sensitivities to the susceptibility effectsintroduced by deoxyhemoglobin. Details of this method canbe found in a previous publication [8].

Using an ASE sequence with different π pulse time off-sets while keeping an identical TE, the measured MR signalcan be characterized as

SðtÞ ¼ ρ 1� lð Þ � e�l�fc dwtð Þ ð1Þ

where ρ is the spin density, λ is the volume fraction con-taining deoxyhemoglobin, representing cerebral venousblood volume (vCBV), and fc(δωt) can be described as

fc dwtð Þ ¼ 1=3 �Z 1

02þ uð Þ�

ffiffiffiffiffiffiffiffiffiffiffi1� u

p� 1� J0 3

2 � dwt � u� �u2

du

ð2Þ

where J0(x) is the zeroth order Bessel function and δω is thecharacteristic frequency shift and is defined as

dw ¼ 4

3pg �Δc0 � Hct � OEF � B0 ð3Þ

where Hct is the fractional hematocrit, B0 is the main mag-netic field strength, Δχ0 is the susceptibility differencebetween fully oxygenated and fully deoxygenated bloodwhich has been measured to be 0.18 ppm per unit Hct incgs units [21], and OEF is the oxygen extraction fraction. Inthis study, a constant Hct of 0.42 was employed for allsubjects and a small vessel Hct to large vessel Hct ratio of0.85 (13) was employed to convert the large vessel Hct tosmall vessel Hct. Two asymptotic forms, namely short timescale (δω |t|≤1.5) and long time scale (δω |t|>1.5) aregiven to approximate the signal equation as [20]:

SsðtÞ ¼ ρ 1� lð Þ � exp �0:3l � dwtð Þ2� �

dw � tj j � 1:5

ð4Þand

SlðtÞ ¼ ρ 1� lð Þ � exp �R20 tj j � tcð Þð Þ dw � tj j > 1:5

ð5Þ

where the subscript s and l denote the short and long timescales, respectively; tc is the critical time defined as tc01/δω.R2′ can be written as

R20 ¼ l � dw ¼ l4

3pg �Δc0 � Hct � 1� Yð Þ � B0: ð6Þ

R2′ can be estimated by fitting a linear curve of the loga-rithm of Sl(t) with t>1.5/δω. λ can be calculated as l ¼ln Sl t ¼ 0ð Þð Þ � ln Ss t ¼ 0ð Þð Þ, where Sl(t00) can be obtainedthrough an extrapolation of Eq. (5) following the estimation ofR2′. After both R2′ and λ are estimated, measurement of OEFcan be obtained from Eq. (6).

Forty asymmetric spin echoes with t ranging from 22.5 msto 42ms with an increment of 0.5 ms and ten spin echoes at t00 were acquired. The imaging parameters were as follows:TR04 s, TE062 ms, FOV0220×220 mm2, matrix size064×64, and 16 axial slices with a slice thickness of 5 mm withoutgap, average02. The total data acquisition time was 6 min and40 s. Images were low-pass filtered using a 3×3 averagingkernel to improve SNR prior to the computation of OEF.

CBF Measurement using Continuous Arterial Spin Labeling(CASL)

MR perfusion images were acquired with a continuous arterialspin labeling (CASL) approach [1, 2]. Label and controlimages were acquired alternatively using a single-shot gradi-ent echo EPI readout. An adiabatic inversion with a B1 field of2.3 μT and 1.6 mT/m gradient was employed to label arterialblood, whereas a sinusoidal amplitude-modulated pulse wasused to control the magnetic transfer effects. The total labelingand control pulse durations were 2 s, which consisted of 20repeated radiofrequency (RF) blocks with a duration of100 ms for each pulse and a 500-μs gap in between. A post-labeling delay time of 1,000 ms between the labeling orcontrol pulses and the image acquisition was utilized. Thelabeling plane was placed 80 mm inferior to the imagingcenter. FOV was 220 mm2 and matrix size will be 64×64.Sixteen slices with a slice thickness of 5 mmwithout interslicegap was acquired. TR/TE04,000/11 ms. Forty pairs of labeland control images were acquired. The total data acquisitiontime was 5 min and 20 s.

The labeling and control images were averaged separatelyand a low-pass Gaussian filter with a full width at half max-imum (FWHM) of 11.4 mm (about 3.3 pixels) was utilized toimprove signal to noise ratio (SNR). CBF maps were calcu-lated based on the following equation [16]:

CBF ¼ lp �ΔM � R1a

2a �Mcon exp �wR1að Þ � exp � t þ wð ÞR1að Þð Þ ð7Þ

where λp is the blood–tissue water partition coefficient, whichis assumed to be 0.9 ml/g; ΔM is the difference between the

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averaged control and labeling images; R1a is the longitu-dinal relaxation rate of blood at 3 T; α is the taggingefficiency, which is assumed to be 0.68 [16]; Mcon is theaveraged control image intensity; τ (2 s) is the durationof the labeling pulse; and w (1 s) is the post-labelingdelay time.

In literature, most of the studies assumed a constantarterial blood longitudinal relaxation rate (R1) in the estima-tion of CBF using the ASL approaches. This constant arte-rial blood R1 assumption may not hold true under alteredphysiological conditions. It has been reported that carbogeninhalation substantially increased blood partial pressure ofoxygen (pO2) [10, 22, 23]. Moreover, it has been reportedthat arterial blood R1 has a dependence on several physio-logical parameters including pO2 [24]. Using fresh bovineblood and a 4.7-T scanner, Silvennoinen et al. [24] havefound that blood longitudinal relaxation rate R1 is linearlyproportional to pO2 as

R1 ¼ 0:56þ 0:00041 � pO2: ð8ÞTo account for the effects of carbogen inhalation on

blood R1 and then CBF, Eq. (8) was adopted to computeR1. Based on previously published results [10, 22, 23], weassumed a pO2 of 100 mmHg and a pO2 of 400 mmHg inthe arterial blood under normal (room air breathing) andhyperoxic hypercapnia (3% CO2 and 97% O2 carbogenbreathing), respectively. R1 was then computed as 0.60 s−1

and 0.72 s−1 for normal and hyperoxic hypercapnic condi-tions, respectively. Subsequently, the computed R1 was sub-stituted into Eq. (7) to estimate CBF. After obtaining CBFand OEF, OMI maps were computed as the product of CBFand OEF.

Data Analysis

A six-parameter rigid image registration was performed toalign CASL, ASE, and T1 images from the same subjectsacross all scans using FSL 3.2 (FMRIB, Oxford, UK). T1images of each individual subject were segmented intowhite matter (WM), gray matter (GM), and CSF using theMarkov Random Field-based tissue segmentation approachprovided in FSL 3.2 [25]. Regions of interest (ROIs) weremanually defined to cover all acquired slices in both hemi-spheres. For each subject, the GM and WMmasks generatedfrom T1 segmentation were utilized to obtain CBF, OEF,and OMI from the whole brain, the GM and the WM at eachgas inhalation state. Mean values of CBF, OEF, and OMIwere compared between baseline room air and carbogeninhalation states using repeated measures ANOVA withBonferroni correction for multiple paired comparison(Graphpad Prism 5; GraphPad Software, Inc., La Jolla,CA, USA).

Results

Prior to MRI imaging session and inhalation using a facemask, the baseline characteristic were measured and sum-marized as follows. The systolic blood pressure (BP) was126.0±17.6 mmHg, diastolic BP was 79.6±9.0 mmHg,heart rate was 70.2±14.8 beats per minute (BPM), andSaO2 was 97.1±1.3%. The physiological parameters duringeach gas inhalation state through a face mask are summa-rized in Table 1.

Representative OEF, CBF, and OMI maps during eachgas inhalation state are shown in Fig. 2. From visual inspec-tion of the images, it is clear that a decrease of OEF and anincrease of CBF were detected across the whole brain whenthe inhaled gas was switched from room air to carbogen.When the gas mixture was switched back to room air, bothOEF and CBF returned to baseline values that are similar tothose of the first air breathing episode. Moreover, the secondcarbogen inhalation induced a similar degree of decreaseand increase in OEF and CBF, respectively. Finally, the lastepisode of air inhalation brought both CBF and OEF back tobaseline values again. Conversely, despite the changes ofthe inhaled gas mixtures, OMI remained rather stablethroughout the entire imaging session, suggesting that cere-bral oxygen metabolism has been maintained in a steadystate. Both CBF and OMI showed demarcation between GMand WM, while OEF were relatively uniform across thewhole brain during both air and carbogen breathing, consis-tent with previous findings using PET [26].

Quantitative measurements of OEF, CBF, and OMI aresummarized in Table 2. The repeated measures ANOVAindicated that OEF was significantly lower; CBF was sig-nificantly higher, while OMI remained essentially un-changed during two carbogen breathing episodes whencompared to room air breathing episodes. All paired com-parison of OEF between each air and carbogen breathingepisode showed statistical significance (P<0.05) in thewhole brain, gray matter, and white matter. Except thecomparison between carbogen 1 and room air 2, all pairedcomparison of CBF showed statistical significance (P<0.05) in the whole brain, GM, and WM. The GM/WM ratioof CBF was 1.25±0.05 from all subjects during the first

Table 1 Summary of the physiological parameters

Inhalation Heart rate (BPM) SaO2 (%)

Room air 69.7±14.5 97.0±0.8

3% Carbogen 69.4±15.4 97.9±1.5

Room air 67.9±9.7 97.1±1.2

3% Carbogen 68.3±12.2 98.1±1.5

Room air 68.1±12.5 97.3±1.4

SaO2 arterial blood oxygen saturation obtained from a pulse oximeter

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episode of air breathing. Despite the changes in absoluteCBF values, this ratio remained stable throughout the wholeexperimental time, suggesting that the extent to which CBFincreased is quite similar between gray matter and whitematter. Similarly, the GM/WM ratio of OMI was 1.34±0.09during the first episode of air breathing and remained stablethroughout the whole time.

As demonstrated in Fig. 3, all subjects showed decreasedOEF and increased CBF while breathing carbogen. Thesetrends of CBF and OEF changes at each gas manipulationwere consistently observed in all subjects, suggesting thatreliable measurements of CBF and OEF might be obtainedin repeated gas manipulations. The inter-subject variation isrelatively small in OEF, while a larger inter-subject variationwas observed in CBF. When compared to the baseline air 1measurement, decreases of whole brain OEF were observed

for carbogen 1 (−10.4±5.5%) and carbogen 2 (−12.7±4.6%), whereas increases of whole-brain CBF were mea-sured for carbogen 1 (9.7±6.3%) and carbogen 2 (−10.1±9.6%). The concurrent reciprocal changes of CBF and OEFled to a minimum change in OMI (<2%) throughout theentire experimental procedure.

Discussion

MR Measured OEF, CBF, and OMI Responses duringRepeated Air and Carbogen Breathing

We have found that OEF, CBF, and OMI are similar duringall three room air breathing episodes. The variations of themean OEF, CBF, and OMI are <1.7%, <2.4 m/100 g/min

Fig. 2 Representative OEF,CBF, and OMI maps from onesubject during each gas challengestate. From left to right, thesubject breathed room air,followed by carbogen (3% CO2–97% O2), room air, carbogen (3%CO2–97% O2), and room air.Color bars represented an OEFrange of 0–100%, a CBF range0–200 ml/100 g tissue/min, and aOMI range of 0–60. Originalhigh-resolution T1 image and thetissue segmentation map in thecommon registered space are alsoshown. GM and WM are repre-sented by two different grayscales in the segmented map

Table 2 Mean and standard de-viation of CBF, OEF, and OMIfrom whole brain, GM, and WMduring five air and carbogenbreathing episodes are summa-rized across all subjects

*P <0.05 between a gas inhala-tion state vs. air 1

Air 1 Carbogen 1 Air 2 Carbogen 2 Air 3

Whole brain

CBF (ml/100 g/min) 41.0±10.5 45.0±11.6* 40.2±9.6 44.9±10.8* 38.6±10.0

OEF (%) 33.3±2.5 29.8±2.4* 33.8±1.9 29.4±3.2* 35.0±3.6

OMI 13.8±3.7 13.6±3.9 13.9±4.0 13.4±3.9 13.9±4.7

GM

CBF (ml/100 g/min) 46.0±11.6 50.9±12.7* 44.8±10.4 50.3±11.8* 43.6±11.2

OEF (%) 34.7±3.3 31.2±3.0* 35.1±2.1 30.6±3.2* 36.3±3.7

OMI 15.9±4.2 15.9±4.3 15.5±4.5 15.5±4.4 16.1±5.4

WM

CBF (ml/100 g/min) 36.9±9.6 40.2±10.5 36.6±9.3 40.5±10.2* 34.8±9.3

OEF (%) 32.0±2.0 28.6±2.0* 32.8±1.9 28.4±2.8* 33.9±3.7

OMI 12.0±3.4 11.8±3.5 12.2±3.8 11.7±3.6 12.1±4.3

GM/WM ratio

CBF 1.25±0.05 1.27±0.05 1.24±0.07 1.25±0.11 1.26±0.08

OMI 1.34±0.09 1.37±0.06 1.32±0.09 1.33±0.11 1.35±0.11

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and <0.1 ml/100 g/min, respectively, for the whole brainduring room air breathing.

As demonstrated in Table 2, mean OEF is comparable forGM and WM. Table 2 also shows OEF is in the range of 32–36.3%, which is in agreement with previous PET measure-ments [26–29]. CBF ranges between 43.6 and 46ml/100 g/minfor GM and 34.8–36.9 ml/100 g/min for GM and WM, re-spectively. The GM CBF measurement in our study is at thelow end of those obtained by PET, whereas the WM CBFagrees with the previous PET results [26–29]. To compare theMR measured OMI with the absolute CMRO2 obtainedusing PET, a fixed CaO2 of 18 ml/100 ml for all subjectswas assumed to convert MR measured OMI into MR-CMRO2 [29].We found that meanMR-CMRO2 are 115μmol/

100 g/min, 132 μmol/100 g/min, and 99.4 μmol/100 g/min forthe whole brain, GM, andWM, respectively, in agreement withthe published PET CMRO2 measurements [26, 27, 30, 31].

It has been suggested that carbogen, a mixture of a smallpercent of CO2 with oxygen, can relax vessel tone that maylead to vasodilation and increased blood flow [26, 32]. Inresponse to the elevation of CBF, OEF passively decreasesin a reciprocal manner reflecting the stable oxygenationmetabolic rate as reported a few decades ago [33, 34]. Sincethen, findings with no change in CMRO2, a decrease ofCMRO2, and an increase in CMRO2 have all been reportedfor hypercapnia. Since some studies have been performed inanimals under different anesthetic agents, we will then onlyfocus our discussion on several awake human studies [26,

Fig. 3 Box plots (box025th–75th percentile; bars010th–90th percen-tile) of OEF (first row), CBF (second row), and OMI (third row) of allpatients when subjects inhaled room air (air 1), carbogen (carbogen 1),room air (air 2), carbogen (carbogen 1), and room air (air 3). The

results are summarized for the whole brain (left column), gray matter(middle column), and white matter (right column). Asterisk denotesstatistical difference between a particular gas challenge state and thefirst room air episode

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35–37]. Using a pulsed arterial spin labeling (PASL), aphase contrast imaging, and global oximetry obtainedthrough venous blood R2 in jugular veins, Chen and Pikefound no significant changes in whole-brain CMRO2 inhuman brain under hypercapnia after inhaling a mixture ofCO2 and medical air [35]. In contrast, using a phase contrastapproach to measure global CBF and a T2 relaxation underspin tagging MRI for oxygen saturation in sagittal sinus, Xuet al. found that whole-brain CMRO2 decreased by 13% innormal subjects after inhaling 5% CO2 mixed with air [37].Both methods used an ex vivo calibration to derive tissueoxygenation from T2. The discrepancy of these two meth-ods may be caused by the methodology difference in obtain-ing T2. Moreover, using a MR phase contrast to estimateglobal CBF and a phase shift method to measure arterialvenous oxygen difference in superior sagittal sinus, Jain etal. reported significantly increased CBF and SvO2, whilealmost identical CMRO2 was obtained in human brain afterthe inhalation of 5% CO2 mixed with air [36]. Of note, theseMR-based studies [35–37] all used a 5% CO2 mixed withair, while our study used a 3% carbogen (3% CO2 mixedwith 97% O2) gas mixture.

A recent PET study reported by Ashkanian et al. has dem-onstrated that a carbogen gas with 5% CO2mixed with oxygeninduced a global CBF increase of 15% and a concomitantglobal OEF reduction of similar level, resulting in an almostunchanged CMRO2 [26]. Consistent with this PETstudy using5% carbogen, our study has consistently demonstrated about10–12% decrease in OEF and 10% increase of CBF, and astable OMI during 3% CO2 carbogen inhalation episodes.Moreover, the two carbogen breathing episodes separated byan inhalation of room air also had highly reproducible OEF,CBF, and OMI results. Our results demonstrate that the non-invasive MR measurements are consistent and capable ofdetecting about 10% changes in OEF and CBF in healthysubjects under altered physiological conditions.

Furthermore, similar to the previous PET findings, wehave observed that despite the absolute OEF and CBFchanges, GM/WM ratio in CBF and OMI remained constantduring air and carbogen breathing. It suggested that relativechanges of OEF and CBF induced by carbogen might besimilar between GM and WM. Using PET to measure localregional cerebral blood volume, Greenberg et al. have foundthat the gray matter and white matter responses to CO2 werequite similar [32]. It may explain the similar relativechanges in GM and WM observed in our study.

R1 in CBF Computation using ASL Methods

Flow quantification using ASL methods highly depends onthe arterial blood R1 values as illustrated in Eq. (7). Most ofthe studies assume that the arterial R1 is a constant indepen-dent of pO2. This assumption is not valid if a subject inhales

carbogen (2–6% CO2 mixed with O2) or pure oxygen. Usingblood gas analysis, it has been demonstrated that arterialpO2 might increase 3–5-fold during carbogen breathing [22,23]. Molecular oxygen (O2) dissolved in blood is paramag-netic due to its two unpaired electrons. It has been shownthat the blood R1 increases linearly with pO2 [24, 38]. Sincethe measurement of pO2 in arterial blood using blood gasanalysis is invasive, we did not perform a direct measure-ment of arterial blood pO2, but instead adopted the linearrelationship between pO2 and R1 to account for the effect ofpO2 on R1. Of note, the linear relationship between pO2 andR1 was derived on fresh bovine blood using a 4.7-T MRscanner. It is likely that this relationship may not be accuratefor our study. We estimated R1 to be 0.60 s−1 and 0.72 s−1

for room air and carbogen breathing, respectively. The roomair breathing R1 computed in our study is similar with an exvivo R1 measurements (0.6001/1,664 ms) using a circulat-ing blood phantom [39]. To evaluate how much the arterialblood pO2 may affect the quantification of flow using CASLmethod, we calculated CBF for both air and carbogenbreathing episodes assuming a constant R1 of 0.60 s−1. Ifan incorrect R1 was used, an 11% reduction in CBF wouldhave been obtained during carbogen breathing. After R1 wasadjusted based on blood pO2, an increase of 10% in CBFcan then be obtained. Our results suggest the importance ofR1 determination for accurate perfusion quantification usingASL approaches.

Ideally, the arterial R1 should be measured along withASL method; however, only ex vivo measurements havebeen performed to measure R1 of arterial blood and in vivomeasurements have been only conducted in venous blood[40, 41]. The direct in vivo R1 measurement in arterial bloodis challenging because the flow of arterial blood is muchfaster, which leads to a larger inflow of refreshing arterialblood and a greater effect from pulsatile flow [41].

GM/WM Ratio

In our study, the GM/WM ratio of CBF is 1.25, while theGM/WM ratio of OMI is 1.34. Previous work using PEThave reported this ratio in a wide range of 1.4–2.0 [26, 42].Using a dynamic susceptibility contrast, the GM/WM ratiowas previously measured to be 2.3 for MR measured OMI[17]. The GM/WM ratio of OMI of this study is at the lowend of the PET results, mainly due to the low GM/WM ratioof CBF. We think that partial volume effects might be amajor reason that contributes to this low GM/WM ratio. Asshown in Fig. 2, high-resolution T1 images and tissue seg-mentation results showed a clear demarcation between graymatter and white matter in both cortical and subcorticalregions, while the low-resolution CBF maps obtained fromthe CASL method showed a very blurred boundary betweenGM and WM. The spatial resolution of the ASL images was

252 Transl. Stroke Res. (2012) 3:246–254

3.43×3.43×5 mm3 and a Gaussian low filter with a FWHMof 11.4 mm was utilized to improve SNR prior to theestimation of CBF. Due to the low spatial resolution, GMand WM cannot be separated well in the cortical regions ineither the CBF or the OMI maps. Since our GM and WMregions were automatically defined based on the high-resolution T1 images, regions with mixed tissue types mightdiminish the GM/WM difference in CBF or OMI.

Study Limitation and Future Work

This study was conducted in a small cohort of normalhealthy subject under both normal and physiological alteredconditions. Due to the small sample size and imbalancednumber of female and male subjects, this study cannot beused to examine the age and gender effects in the normalvascular response to hyperoxic hypercapnia. Though thisstudy demonstrates that OEF, CBF, and OMI under bothnormal and hyperoxic hypercapnia is corroborative withprevious reported PET findings, our study utilized 3% carb-ogen, while the previous PET study utilized 5% carbogen.Therefore, the accuracy of the MR methods cannot bedirectly evaluated in this study. Further studies includingdirectly validation against PET, a well-accepted imagingmethod for quantitative oxygen metabolism measurements,in the same subjects are needed to test the accuracy of theproposed MR methods. Moreover, it remains to be seenwhether this method can be utilized to provide accurateestimation of oxygen metabolism in stroke patients. Sincepatients are likely to be less cooperative, the sensitivity andreliability may decrease in a routine clinical setting due tovarious factors including patient motion. Nevertheless, thisstudy demonstrated that the cerebral oxygenation changecaused by a global gas challenge can be readily detected inhuman and the measurements are highly reproducible,which is an important step towards the goal of clinicalutility. Further technical refinement including optimizationof MR pulse sequence and estimation methods and a directcomparison against PET in patients are warranted.

Conclusions

In this study, we evaluated noninvasive MR methods inmeasuring OEF, CBF, and OMI under normal and hyperoxichypercapnic conditions. We have consistently demonstrateda 10–12% decrease in OEF with a 10% increase of CBF anda stable OMI during carbogen inhalation. Moreover, GM/WM ratio in CBF and OMI remained constant during airand carbogen breathing. In addition, OEF, CBF, and OMIwere highly reproducible if the same inhaled gas was used.Our findings agree with previous PET results, demonstrat-ing that noninvasive MR measurements can provide reliable

measurements of OEF, CBF, and OMI in normal subjectsunder normal and altered physiological conditions.

Acknowledgments This study was supported by the Department ofNeurology, University of North Carolina at Chapel Hill, grants fromNational Institute of Health (NIH 5R01NS054079, NIH 5P50NS055977)and American Heart Association (AHA 0730321N).

Disclosure/Conflict of Interest The authors declare no conflict ofinterest.

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