White matter has impaired resting oxygen delivery in sickle cell patients

Abstract

Although modern medical management has lowered overt stroke occurrence in patients with sickle cell disease (SCD), progressive white matter (WM) damage remains common. It is known that cerebral blood flow (CBF) increases to compensate for anemia, but sufficiency of cerebral oxygen delivery, especially in the WM, has not been systematically investigated. Cerebral perfusion was measured by arterial spin labeling in 32 SCD patients (age range: 10–42 years old, 14 males, 7 with HbSC, 25 HbSS) and 25 age and race-matched healthy controls (age range: 15–45 years old, 10 males, 12 with HbAS, 13 HbAA); 8/24 SCD patients were receiving regular blood transfusions and 14/24 non-transfused SCD patients were taking hydroxyurea. Imaging data from control subjects were used to calculate maps for CBF and oxygen delivery in SCD patients and their T-score maps. Whole brain CBF was increased in SCD patients with a mean T-score of 0.5 and correlated with lactate dehydrogenase (r² = 0.58, P < 0.0001). When corrected for oxygen content and arterial saturation, whole brain and gray matter (GM) oxygen delivery were normal in SCD, but WM oxygen delivery was 35% lower than in controls. Age and hematocrit were the strongest predictors for WM CBF and oxygen delivery in patients with SCD. There was spatial co-localization between regions of low oxygen delivery and WM hyperintensities on T2 FLAIR imaging. To conclude, oxygen delivery is preserved in the GM of SCD patients, but is decreased throughout the WM, particularly in areas prone to WM silent strokes.

1 |. INTRODUCTION

Stroke is the most devastating complication in patients with sickle cell disease (SCD). It is not only a leading cause of death, but also impairs mobility, cognitive function and quality of life in these patients. The cooperative study of SCD demonstrated that 11% of patients had an overt stroke by age 20 and a cumulative lifetime stroke risk of 40%.^1,2 Routine transcranial Doppler (TCD) screening and blood transfusion therapy have lowered this risk 10-fold.^3–5 Despite this, risk of cerebral silent infarction (SCI) in SCD patients increases linearly with age, with a prevalence of 50% by the age of 30.^6,7

Non-invasive neuroimaging has been a powerful tool to improve the selection of patients with high stroke risk for treatment.⁸ Nonspecific white matter (WM) atrophy, including volumetric decrease and microscopic derangement has been demonstrated in SCD using magnetic resonance imaging (MRI).^9–11 Although recent studies have reported that WM, cerebral blood flow (CBF) is lowest in the regions of highest SCI density,¹² and that SCI occur in regions of increased oxygen extraction fraction,¹³ no one has actually determined whether WM oxygen delivery is impaired to WM regions at risk. We reported that SCD and other anemic patients preserve resting whole brain O₂ delivery, despite their impaired O₂ carrying capacity, by increasing their CBF.^14,15 However, it is unknown whether O₂ delivery is preserved regionally, across the brain. Characterization of O₂ delivery and its spatial association with WM lesions might help to identify brain regions that are most vulnerable to overt stroke.

Arterial spin labeling (ASL) is a non-invasive and contrast-free MRI imaging method to measure CBF, from which cerebral O₂ delivery can be derived. In this work, we compare CBF and O₂ delivery between 32 patients with SCD and 25 healthy age and race-matched control subjects. Imaging data from control subjects were used to calculate T-score maps of CBF and O₂ delivery in SCD patients. We used regression analysis to identify clinical and laboratory predictors of impaired O₂ delivery in white and gray matter (GM), and tested whether silent cerebral infarctions occurred in regions of poor O₂ delivery.

2 |. METHODS

2.1 |. Population

The study was approved by the Institutional Review Board (CCI11–00083) at Children’s Hospital Los Angeles (CHLA). All participants were recruited from June 2016 to August 2017, with consent or assent. Two cohorts were studied: the first consisted of SCD subjects with hemoglobin SS (N = 25) and SC (N = 7) genotypes. Exclusion criteria included previous overt stroke, pregnancy and hospitalization within the month prior to the study visit. Children younger than 9 years of age were excluded because of inability to cooperate with study procedures but there was no upper limit for age. All the SCD patients at our institution are regularly screened by TCD ultrasonography to identify patients at risk of stroke. The patients who have a blood flow velocity > 200 cm/sec are placed on monthly blood transfusions to suppress hemoglobin S% to less than 30%, according to standard clinical practice. Patients with normal Doppler velocities are placed on hydroxyurea and titrated to maximum tolerated dose.¹⁶ The second cohort was composed of age-matched healthy controls, with or without sickle cell trait. Most were first or second-degree relatives of the patients studied or recruited from friends of patients’ families, so that two cohorts are ethnically and socioeconomically matched. Controls were excluded if they had developmental delay, a prior history of neurologic insult, or serious, uncontrolled, chronic illness.

2.2 |. Data acquisition

On the same day as the imaging study, complete blood count, hemoglobin electrophoresis, and cell free hemoglobin levels were analyzed in the clinical laboratory. Brain MRI was performed on the same day using a Philips Achieva 3 Tesla scanner with an 8-channel head coil. Arterial O₂ saturation was measured from a fingertip pulse oximeter during the MRI scan. In the patients undergoing blood transfusion therapy, MRI was performed immediately prior to the blood transfusion. For each subject, a 3D T1-weighted image (echo time (TE) = 3.8 ms, repetition time (TR) = 8.3 ms, resolution 1 mm³ with a SENSE factor 2) and T2-weighted fluid attenuated inversion recovery (FLAIR) image (TE = 2.5 ms, TR = 4.8 ms, resolution = 1.3 × 1.0 × 1.0 mm³) were acquired for co-registration and screening for WM lesions. High resolution time of flight MR angiography (resolution = 0.5 × 0.5 × 1.5 mm³) was also performed at the Circle of Willis to screen for arterial stenosis. The field of view also spanned the supraclinoid, cavernous, petrous and 1 to 2 cm of the cervical portions of the internal carotid artery. Extracerebral vessels were also profiled by 3D angiography collected at a resolution of 1.5 × 1.7 × 3 mm³.

Pseudo continuous arterial spin labeling (PCASL) scans were performed using an unbalanced, Hanning shaped RF pules labeling train (mean gradient of 1 G/cm, interpulse interval of 1 ms and pulse duration of 0.5 ms), and a 3D GRASE two-shot readout (TE = 9.8 ms, TR = 3800 ms, resolution = 3.7 × 3.7 × 10 mm³, labeling duration of 2000 s, post labeling delay of 1600 s with 10 dynamics, EPI factor of 5). Two timed inversion pulses for background suppression following labeling were used, with an inversion efficiency of each background suppression pulse of 95%.

2.3 |. Pre-processing and WMH segmentation

We co-registered T1-weighted and T2-weighted images to the 2 mm³ Montreal Neurological Institute (MNI) atlas using FLIRT and FNIRT.¹⁷ The probability maps of WM and GM were obtained using FMRIB’s Automated Segmentation Tool from registered T1 images.¹⁸ The T2 FLAIR images were read for white matter hyperintensities (WMHs) by a licensed neuroradiologist who was blinded to disease status. A WMH was considered significant if it was greater or equal to three millimeters in two orthogonal planes.¹⁹ Although some WMH were observed in the control population, we limited WMH atlas generation to SCD patients. We used our in-house MATLAB toolbox published previously to semi-manually segment WMHs²⁰ from several subjects. These lesions, and transformations of these lesions, were used to train a deep learning based method²¹ capable of detecting all of the WMH in the remaining patients. While the sensitivity of the deep learning method was excellent, all detected lesions were manually edited using ITK-SNAP²² to remove false alarms; final lesion morphometry was confirmed by a neuroradiologist (BT). WMH maps for each SCD subject were transformed to the MNI atlas, and fused to create a binary mask that localized WMHs across all the SCD subjects.

Regional CBF was calculated using the PCASL images, rigidly co-registered to the T1 images and then to MNI space using FLIRT.¹⁷ Voxel-wise gray and WM probability maps were derived at the same resolution as the PCASL images in order to quantify tissue CBF in native space as well as to perform partial volume effect correction.²³ Finally, we applied the whole brain CBF to the cerebral arterial territory masks to measure regional CBF in three major cerebral arterial territories: anterior cerebral artery (ACA), middle cerebral artery (MCA) and posterior cerebral artery (PCA). The mask of major vascular territories was based on a published template of vascular territories in both hemispheres.²⁴ The territories were drawn based on an extensive overview of anatomic studies of cerebral vascularization, and evaluated on the biocommissural plane.

2.4 |. CBF quantifications

CBF quantification was performed using a modified two-compartment kinetic quantification model proposed by Wang et al.²⁵ The parameters in the equation for quantification used in this work were previously described in detail by Bush et al²⁶ for a smaller cohort, using identical imaging protocols and quantification parameters.²⁵ Briefly, we calculated labeling efficiency on a patient-by-patient basis, correcting for uneven radio-frequency excitation and differences in blood flow velocity.^26,27 Flow quantitation also employed disease specific estimation of blood T1, and patient and tissue specific arterial transit time estimates.^28,29 Complex difference was performed between tag and control images, so the norm of the signal difference was always positive. The median of 10 CBF dynamics was used for quantification and comparison. To alleviate the blurring due to the point spread function and mixing of tissue-specific signals, we performed partial volume effect correction, using a 3 × 3 × 3 regression model.²³ During registration to common atlas space, rare peripheral voxels would be designated Not-a-Number (NaN) by FLIRT. We converted these flow values to zero.

2.5 |. Oxygen delivery maps

CBF maps were converted into cerebral O₂ delivery maps to correct for patient-specific differences in hemoglobin and O₂ saturation. The following equations show the relationship of hemoglobin, O₂ content and O₂ delivery:³⁰

$$\text{Oxygen}\text{Delivery}=\text{CBF}\times \text{Oxygen}\text{Content}$$ (1)

$$\text{Oxygen}\text{Content}=1.34\times \text{Hemoglobin}\times {\text{SpO}}_2+0.003\times {\text{pO}}_2$$ (2)

where SpO₂ is the arterial O₂ saturation, and pO₂ is the partial pressure of O₂, which is assumed to be 100 Torr for room air.

2.6 |. Statistical analysis

We used two-tailed, two sample t tests to compare CBF and O₂ delivery in SCD and control subjects across the cerebral vascular territories. Predictors of whole brain, total GM and total WM CBF/O₂ delivery were identified using univariate and stepwise multivariate regression. Test statistics with two-sided P < 0.05 were considered to be statistically significant. All statistical analyses were performed using JMP Pro 11 (SAS, Cary, NC).

Systematic spatial differences in CBF and O₂ delivery were identified using T-maps. The voxelwise mean and SD, μ and σ, were first calculated from the control subjects. Voxel-wise 3D T-score maps were calculated for both CBF and O₂ delivery by calculating t = (X-μ)/σ on a voxelwise basis where t is the T-score value of each voxel, and X is the group average of CBF (or O₂ delivery) value in patients with SCD.

To determine the spatial concordance of CBF and O₂ delivery between areas with white WMHs and normal appearing white matter (NAWM), we performed a permutation analysis of WM lesions on the CBF maps and O₂ delivery maps. We created a WM lesion risk map by summating all the WMH segmented from T2-FLAIR images in 17 patients with SCD. The test distribution consisted of CBF values associated with each lesion, generating a distribution of CBF values in regions known to be at high risk from strokes. To create the corresponding null statistic, we randomly positioned each WM lesion 100 times within the NAWM regions and recalculated the CBF. The shape of the two distributions was compared by the Kolmogorov-Smirnov test, while the mean and variance of the distributions were compared by t test and ratio test, respectively. The permutation test on O₂ delivery map followed the same procedure. This was done using our in-house MATLAB code.

3 |. RESULTS

3.1 |. Demographics

Patient demographic information is summarized in Supporting Information Table S1. There is no significant difference in age and sex between two cohorts. The healthy control (CTL) group included 12 participants with sickle cell trait (hemoglobin AS) and 13 with hemoglobin AA. The sickle trait subjects did not differ in any detectable way from the control subjects (hemoglobin AA) other than their hemoglobin electrophoresis. The SCD group consisted of seven patients with hemoglobin SC, and 25 hemoglobin SS. Eight of the SS patients were receiving chronic transfusion therapy for a history of abnormal TCD (N = 6) or recurrent acute chest syndrome (N = 2). Chronically transfused patients were maintained with a pre-transfusion hemoglobin S level below 30% and had relatively low hemoglobin F%, reflecting good suppression of endogenous erythropoiesis. Chronically transfused patients were studied at their hemoglobin nadir to better match their hemoglobin levels with non-transfused subjects. Hydroxyurea was being taken by 12/17 non-transfused SS patients and 2/7 SC patients. In addition to having decreased hemoglobin and hematocrit, SCD patients were mildly desaturated compared to healthy controls; three SCD patients has O₂ saturations below 93% while the rest had O₂ saturations from 97% to 95%.

MR angiography images were read by a licensed neuroradiologist for all participants. All subjects had normal MRA except one 37-yearold patient with bilateral ACA stenosis; this patient was excluded from the analysis. Small, WMH were found in 12/24 non-transfused SCD patients and 5/8 transfused SCD patients. Five of 17 WMH+ patients were HbSC phenotype.

3.2 |. CBF and oxygen delivery

The top panel of Supporting Information Figure S1 compares the spatial distribution of CBF in CTL and SCD patients. In both groups, CBF is greater in GM than WM, but appears to be particularly increased in SCD patients. To facilitate a comparison across groups, the top-right panel of Supporting Information Figure S1 demonstrates a T-score map of regional CBF between SCD and control subjects. CBF is equally elevated in GM structures (T-score > 2) but is normal or decreased in WM. The average T-score value for whole brain CBF is 0.5. Table 1 shows the quantitative summary of all whole brain and regional CBF measurements for two groups. CBF in both whole brain and three territories are significantly higher for SCD patients than healthy controls (P < 0.01). In GM, CBF is elevated across the brain, while in WM, there was no significant difference.

TABLE 1.

Global/regional CBF and oxygen delivery. Measurements presented as global (GM/WM) with mean ± SD, values in bold indicates significant difference with P < 0.01

Regions		CTL (N = 25)	SCD (N = 32)	P-value (adjusted)
CBF (mL/100 g/min)
Whole brain	Total	54.7 ± 12.9	72.2 ± 21.0	0.0006
	GM	63.0 ± 14.7	84.0 ± 26.5	0.0006
	WM	41.2 ± 11.6	37.62 ± 9.6	0.2
ACA	Total	46.5 ± 9.7	74.7 ± 27.3	<0.0001
	GM	53.4 ± 11.5	87.0 ± 33.8	<0.0001
	WM	34.9 ± 8.4	38.8 ± 12.4	0.2
MCA	Total	58.4 ± 14.0	79.1 ± 23.5	0.0003
	GM	67.0 ± 16.7	92.1 ± 29.6	0.0004
	WM	44.0 ± 12.1	41.3 ± 11.0	0.4
PCA	Total	56.4 ± 12.5	74.3 ± 22.9	0.0009
	GM	64.7 ± 12.9	86.5 ± 28.9	0.001
	WM	42.5 ± 14.7	38.6 ± 9.7	0.2
Oxygen delivery (mL Oxygen/100 g/min)
Whole brain	Total	11.3 ± 3.0	10.4 ± 2.2	0.2
	GM	12.9 ± 3.5	12.0 ± 2.8	0.3
	WM	8.5 ± 2.7	5.5 ± 1.3	<0.0001
ACA	Total	9.6 ± 2.2	10.6 ± 2.9	0.1
	GM	11.0 ± 2.6	12.3 ± 3.6	0.1
	WM	7.2 ± 2.0	5.6 ± 1.5	0.001
MCA	Total	12.1 ± 3.4	11.2 ± 2.4	0.3
	GM	13.8 ± 4.0	13.1 ± 3.1	0.4
	WM	9.1 ± 2.9	5.9 ± 1.4	<0.0001
PCA	Total	11.6 ± 2.9	10.6 ± 2.3	0.1
	GM	13.4 ± 3.5	12.3 ± 3.0	0.2
	WM	8.8 ± 2.7	5.5 ± 1.2	<0.0001

Abbreviations: CTL, controls; SCD, sickle cell disease; CBF, cerebral blood flow; ACA, anterior cerebral artery; MCA, middle cerebral artery; PCA, posterior cerebral artery.

To control for the significant differences in O₂ content between the two groups, we converted CBF maps into O₂ delivery maps following Equation 1. The bottom panel of Supplemental Figure S1 compares regional O₂ delivery maps between the two groups; the rightmost panel depicts the corresponding T-score map. The WM areas exhibit cooler color on the T-score map, indicating decreased O₂ delivery in SCD group; while in GM, the T-score is around zero, meaning the O₂ delivery in GM is quite similar between SCD and CTL groups. The average value of the T-score for WM O₂ delivery was −0.4 (0.4 standard deviations below the mean). The quantitative whole brain and regional O₂ delivery results are summarized in the bottom panel of Table 1. Whole brain and GM O₂ delivery in SCD was completely normal (P = 0.2 and 0.3, respectively, using one-way ANOVA test), but was 35% lower in the WM (P < 0.001, using one-way ANOVA test), consistent with what was observed on the T-score map.

To further investigate the relative contributions to CBF and O₂ delivery, we performed univariate and multivariate regressions using demographic factors and blood test results (Table 2). In the SCD group, whole brain CBF and GM CBF were inversely correlated with O₂ content, hemoglobin, and hematocrit, but positively correlated with lactate dehydrogenase (LDH), cell-free hemoglobin, reticulocytes, mean platelet volume (MPV) and heart rate on univariate analysis. On multivariate analysis, only LDH remained in the model for both whole brain (r² = 0.58, P < 0.001) and GM CBF (r² = 0.54, P < 0.001). The WM CBF had similar univariate correlates except that cell-free hemoglobin, reticulocytes, and MPV did not reach statistical significance, and WM CBF decreased significantly with age (r² = 0.20, P = 0.01). On multivariate analysis, LDH, age, and hematocrit predicted WM CBF with a combined r² of 0.45 (P < 0.001).

TABLE 2.

Univariate predictors of SCD brain perfusion and oxygen delivery

Brain perfusion sickle cell disease patients
Predictor	Total perfusion	GM perfusion	WM perfusion
Plasma hemoglobin	r2 = 0.38, P = 0.0002	r2 = 0.38, P = 0.0002	-
Lactate dehydrogenase	r2 = 0.58, P < 0.0001	r2 = 0.54, P = <0.0001	r2 = 0.23, P = 0.006
Reticulocyte count	r2 = 0.27, P = 0.002	r2 = 0.27, P = 0.002	-
Mean platelet volume	r2 = 0.23, P = 0.005	r2 = 0.22, P = 0.007	-
Heart rate	r2 = 0.29, P = 0.002	r2 = 0.24, P = 0.004	r2 = 0.19, P = 0.01
Weight	-	-	r2 = 0.16, P = 0.02
Age	-	-	r2 = 0.20, P = 0.01
MCHC	r2 = 0.12, P = 0.05	r2 = 0.12, P = 0.05	-
Oxygen content	r2 = 0.37 P = 0.0002	r2 = 0.34 P = 0.0004	r2 = 0.14, P = 0.03
Hemoglobin	r2 = 0.36, P = 0.0003	r2 = 0.33, P = 0.0006	r2 = 0.17, P = 0.03
Hematocrit	r2 = 0.37, P = 0.0002	r2 = 0.33, P = 0.0006	r2 = 0.22, P = 0.007
RDW	r2 = 0.09, P = 0.09	r2 = 0.10, P = 0.07	r2 = 0.14, P = 0.03
White blood cell count	r2 = 0.12, P = 0.05	r2 = 0.11, P = 0.06	-
Oxygen delivery in sickle cell disease patients
Predictor	Total O2 delivery	GM O2 delivery	WM O2 delivery
Plasma hemoglobin	r2 = 0.30, P = 0.001	r2 = 0.33, P = 0.0007	-
Lactate dehydrogenase	r2 = 0.10, P = 0.07	r2 = 0.11, P = 0.07	-
Mean platelet volume	r2 = 0.17, P = 0.02	r2 = 0.17, P = 0.02	-
Hemoglobin S%	r2 = 0.10, P = 0.07	r2 = 0.11, P = 0.06	-
Age	-	-	r2 = 0.24, P = 0.005
MCHC	-	-	r2 = 0.22, P = 0.007
Oxygen content	-	-	r2 = 0.18, P = 0.02
Hemoglobin	-	-	r2 = 0.15, P = 0.03
Hematocrit	-	-	r2 = 0.09, P = 0.09
RDW	-	-	r2 = 0.14, P = 0.03
Reticulocyte count	-	-	r2 = 0.14, P = 0.04

Abbreviations: MCHC, mean corpuscular hemoglobin concentration; RDW: red cell distribution width; GM: gray matter; WM: white matter; O₂: oxygen.Bold letter indicates retention on multivariate analysis.

When O₂ delivery was examined instead of CBF, many factors related to anemia were no longer significant for whole brain and GM O₂ delivery. Cell-free hemoglobin and MPV were the only significant predictors, with only cell-free hemoglobin surviving multivariate analysis (Table 2). WM O₂ delivery was positively correlated with hemoglobin, hematocrit, O₂ content, and mean corpuscular hemoglobin concentration (MCHC) and inversely correlated with age, red cell distribution width (RDW) and reticulocytes. Age, O₂ content, and hematocrit remained in multivariate analysis with a combined r² of 0.46.

Figure 1 compares the spatial relationship between CBF, O₂ delivery and WMH. The color-bar represents the T-score and Z indicates the position of the axial slice in the atlas. The lesion mask was gray-scaled and shown in white. WMH was all distributed in areas having negative T-values on the O₂ delivery map. Figure 2A,B (dashed lines) summarizes the CBF and O₂ delivery in the WMH prone regions, compared with values in NAWM (solid lines). The average value for CBF in WMH prone regions was 30.0 compared with 38.9 mL/100 g/min in NAWM (P < 0.001). The average value for O₂ delivery in WMH prone regions was 4.3 mL/100 g/min compared with 5.9 mL/100 g/min in NAWM regions (P < 0.001). Figure 2C,D depicts the same relationships but converts them into T-scores. The mean CBF T-scores were 0.3 and 0.4 (P < 0.001) in WMH prone and NAWM respectively, while the corresponding mean T-scores for O₂ delivery were −0.5 and −0.3 (P < 0.001), respectively.

FIGURE 1.

White matter lesion mask overlaid on T-score map. The scaled WM lesion mask in its axial view is overlaid on top of the T-score for CBF (top row) and O2 delivery (bottom row). The number z indicates the coordinates in the standard atlas

FIGURE 2.

WMH permutation results. The CBF and oxygen delivery distribution (top row) and T-score of CBF and oxygen delivery distribution (bottom row) in the normal appearing white matter (NAWM) and in the white matter hyperintensity (WMH) prone regions

4 |. DISCUSSION

There have been several studies focusing on quantifying CBF using ASL in SCD cohorts;^26,31,32 however, we are the first to quantify O₂ delivery in both healthy controls and SCD populations. We found that whole brain and GM CBF was increased in SCD patients, as a result of cerebral vasodilation to meet GM metabolic demands. Surprisingly, we did not observe a similar compensatory hyperemia in the WM. As a result, whole brain and GM O₂ delivery were preserved in SCD patients, but WM O₂ delivery was only 2/3 as high as for control subjects. Regions commonly associated with WMH had lower O₂ delivery than NAWM. After performing univariate and multivariate regression, age and O₂ content were the strongest predictors for WM O₂ delivery in SCD patients.

Increased CBF in patients with SCD has also been described in other studies using MRI,¹⁵ PET,³³ and Xenon Computed Tomography.³⁴ The elevated CBF was found to be in part due to cerebral vasodilation in response of low hematocrit levels and high hemoglobin S concentration.³⁵ The mechanism by which anemia mediates increased CBF is not entirely known. Although blood viscosity decreases linearly with hematocrit, CBF increase cannot be explained by passive alterations in arterial blood viscosity.^36,37 Anemia, whether caused by SCD or acute hemodilution, produces cerebral tissue hypoxia.^38,39 In turn, cerebral hypoxia triggers arterial vasodilation acutely, and promotes capillary proliferation in GM through hypoxia inducible factor mediated signaling to shorten O₂ diffusion distances and lower cerebrovascular resistance.^40,41

On a whole organ basis, the increased CBF completely compensates for the inadequate O₂ carrying capacity.^15,42 However, compensatory vasodilation was not observed in WM, causing WM O₂ delivery to be directly proportional to hemoglobin concentration. Hematocrit-dependent cerebral O₂ delivery has been described in subjects with cardiovascular disease, with optimal delivery for a hematocrit of 40 to 45%.⁴³ WM O₂ delivery also declined dramatically with age. The etiology of this decline is unclear, but likely reflects accelerated geometric and morphologic alterations, or even destruction of the microvascular network.⁴⁴ Our observed decline in WM O₂ delivery with age parallels the prevalence of WMH in SCD patients observed by Kassim et al⁷ and DeBaun et al.⁴⁵

In contrast, GM O₂ delivery is normal in patients with SCD, reflecting the powerful inverse relationship between CBF and O₂ carrying capacity.^15,45 The preserved GM O₂ delivery we observed is consistent with the lack of GM atrophy we observed in our previous reports.¹¹ GM O₂ delivery was stable with age; however, the median age of our SCD cohort was only 21.4 years of age. Thus, we may have been underpowered to observe age-related reductions in GM O₂ delivery.

Surprisingly, cell-free hemoglobin was the strongest predictor of GM O₂ delivery. Cell free hemoglobin is a toxic byproduct of hemolysis and is associated with impaired nitric oxide metabolism⁴⁶ and endothelial dysfunction.⁴⁷ However, its impact on cerebral nitric oxide generation and cerebral endothelial function has not been reported. A healthy microvasculature is necessary for matching O₂ supply and consumption. Bush et al have previously documented evidence of arterio-venous shunting and impaired O₂ unloading in SCD patients,^48,49 both suggestive O₂ supply-demand mismatch. Alternatively, cell-free hemoglobin could have a more direct vasodilatory effect. Cell free hemoglobin is metabolized by heme oxygenase, producing free iron and carbon monoxide, a potent cerebral vasodilator.^46,50 In a parallel vascular circuit, excessive vasodilation of one bed could produce ischemia in another. Whether the decreased WM O₂ delivery represents vascular stealing by the GM, or simply inadequate neovascularization in response to chronic hypoxia could not be determined.

The WMHs and O₂ delivery map overlay demonstrates two important points. First, CBF and O₂ delivery were lower in regions prone to WMH, than in those with NAWM, independent of disease state (Figure 2C,D). It implies that WMHs are occurring in borderzone regions where perfusion is inherently decreased in anyone. Studies from Numaguchi, Baldeweg, Guilliams and Ford^12,34,51,52 in SCD patients also support that conclusion. Our O₂ delivery T-score maps agrees with the observations of Fields et al., who demonstrated increased O₂ extraction fraction in watershed areas.⁵³ However, the T-score for O₂ delivery was lower in regions at risk for WM stroke (T = −0.5) than in NAWM (T = −0.3) as shown in Figure 2D. The use of a T-score between groups and permutation corrections for the expected reduction in O₂ delivery based upon a watershed effect alone. Therefore, O₂ delivery is disproportionately impaired with WMH prone regions, as exhibited in Figure 1.

Our study has several limitations. First, measurement of WM CBF and O₂ delivery could be complicated by differences in blood transit time and longitudinal relaxation of blood, GM, and WM.^23,54,55 While we used velocity-based corrections for transit time derived from previous studies in SCD patients,²⁹ patient-wise measurement of transit times might improve the accuracy of the CBF estimation. Blood magnetic properties (T1 relaxation) are different in SS patients. While we used values appropriate for SCD patients, patient specific T₁ blood measurements could the CBF accuracy in SCD patients.⁵⁶ Blood T1 in SC patients has never been reported.

Second, the intrinsic low resolution of ASL images and the use of a 3D ASL acquisition, produce admixture of CBF values from gray and WM, known as partial volume effects. Our partial volume correction may not be sufficient performed to eliminate GM and WM cross-contamination. This will cause underestimation of GM CBF and overestimation of WM CBF, leading to a low GM/WM flow ratio; the thin, convoluted cerebral cortex (GM) is particularly vulnerable to CBF underestimation from this mixing effect. However, partial volume effects cannot explain low WM O₂ delivery observed in SCD patients. Nor can it explain the dependence of WM O₂ delivery on age and O₂ content because those effects were not observed in GM. The use of T-scores for group comparison controls for most of the partial volume biases because both SCD patients and healthy controls suffer from comparable GM/WM admixture.

Third, hematocrit and O₂ delivery at the microvascular level are different than in conduit vessels. It is possible that actual O₂ delivery could be slightly better, or worse, than our calculations based on venous hematocrit values. However, use a global, venous hematocrit value nonetheless yields intuitive results that provide important insights into WM disease in SCD patients. Our sample size was too small to explore important covariates such as the role of blood transfusion therapy or the compliance with hydroxyurea, nor could we explore links between O₂ delivery, brain volumes, and neurocognitive outcomes.

Lastly, our SCD population was heterogeneous with respect to genotype and treatment. The goal of the parent study (CCI-11–00083) was to examine the impact of hemoglobin level and hemoglobin S% on CBF and oxygenation, requiring a cohort having a broad range in those variables. We accomplished this objective, but at the cost of cohort homogeneity. While we were careful to control for possible group effects during statistical analysis, our subgroups were too small to make any inferences about the impact of transfusions, hydroxyurea, or genotype. Our study would have been strengthened if we could have studied chronically transfused patients prior to and following their transfusion visit but it was not feasible with our study budget.

In conclusion, we demonstrated that WM O₂ delivery is impaired in SCD patients. Cerebral compensatory mechanisms appear optimized to protect GM O₂ delivery, even while WM remains hypoxic. WMH occur in watershed areas, where CBF and O₂ delivery are intrinsically low, but O₂ delivery in these regions is even lower than uniquely predicted by watershed effects. Taken together, compensatory hyperemia preserves O₂ delivery to the GM in SCD patients but is insufficient to maintain O₂ delivery to the WM, explaining the distribution and progressive evolution of SCIs in SCD patients.