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. 2021 Jun 24;1:100019. doi: 10.1016/j.nbas.2021.100019

Vertebral artery hypoplasia influences age-related differences in blood flow of the large intracranial arteries

Kathleen B Miller a, Samuel J Gallo a, Leonardo A Rivera-Rivera b,d, Adam T Corkery a, Anna J Howery a, Sterling C Johnson d,e, Howard A Rowley c,d, Oliver Wieben b,c, Jill N Barnes a,⁎
PMCID: PMC9997135  PMID: 36911510

Abstract

Our purpose was to compare cerebral blood flow in the large intracranial vessels between healthy adults with (VAH+) and without (No VAH) vertebral artery hypoplasia. We also evaluated age-related differences in regional blood flow through the large cerebral arteries. Healthy young (n = 20; age = 25 ± 3 years) and older adults (n = 19; age = 61 ± 5 years) underwent 4D flow MRI scans to evaluate blood flow in the internal carotid arteries (ICA) and basilar artery (BA). VAH was determined retrospectively from 4D flow MRI using both structural (vessel diameter ≤ 2 mm) and flow criteria (flow ≤ 50 mL/min). We identified 5 young and 5 older adults with unilateral VAH (prevalence = 26%). ICA flow was lower in the VAH+ group compared with the No VAH group (367 ± 75 mL/min vs. 432 ± 92 mL/min, respectively; p < 0.05). There was no difference in BA flow between VAH+ and No VAH (110 ± 20 mL/min vs. 126 ± 40 mL/min, respectively; p = 0.24). When comparing age-related differences in blood flow in the No VAH group, older adults demonstrated lower BA flow compared with young adults (111 ± 38 mL/min vs. 140 ± 38 mL/min, respectively; p < 0.05) but not ICA flow (428 ± 89 mL/min vs. 436 ± 98 mL/min, respectively; p = 0.82). In contrast, in the VAH+ group, older adults had lower ICA flow compared with young adults (312 ± 65 mL/min vs. 421 ± 35 mL/min, respectively; p < 0.01), but not BA flow (104 ± 16 mL/min vs. 117 ± 23 mL/min, respectively; p = 0.32). Our results suggest that the presence of VAH is associated with lower ICA blood flow. Furthermore, VAH may contribute to the variability in the age-related differences in cerebral blood flow in healthy adults.

Keywords: Cerebral anatomy, Aging, Brain blood flow, Posterior circulation, Stroke risk

1. Introduction

Cerebral blood flow (CBF) is critical for maintaining optimal brain function and lower global CBF is associated with higher risk of all-cause mortality [43]. Previous studies have shown declines in global CBF across the lifespan [3], [4], [17], [21], [24], [27], [29], [31], [33], [45], [52], which are independent of regional gray matter atrophy [9]. Despite the lower CBF reported with advancing age, there is substantial variability in the time course and magnitude of this decline.

Vertebral artery hypoplasia (VAH) is a congenital anatomical variation common in healthy asymptomatic individuals. Although there is no consensus definition of VAH, a vessel diameter of 2 mm or less, accompanied with lower flow in the posterior cerebral circulation, is often used to define VAH [10], [19], [39]. VAH will likely affect regional blood flow distribution in the brain, causing markedly lower blood flow in the posterior inferior cerebellar territory [50], which could increase the risk of posterior stroke [10], [23], [36], [39], [53]. Recent studies suggest the prevalence of VAH is 15–35% [23], [37], [39], [40], [50]. Yet, the broader impacts of VAH on CBF are unclear. Furthermore, the influence of VAH on age-related differences in CBF is unknown.

Aging affects regional cerebral blood flow, but there is conflicting information regarding whether anterior or posterior cerebral blood flow is negatively impacted. While there are reports of age-related declines in both the anterior and posterior circulation [7], other studies have reported age-related differences in the anterior circulation [29], [32], [33], or only in the posterior circulation [3], [12], [38], [54]. Importantly, many of the studies that reported greater relative age-related declines in the posterior circulation utilized duplex ultrasonography [3], [12], [38] or 2D phase contrast (PC) magnetic resonance angiography (MRA) [54] to evaluate blood flow in the large intracranial vessels. Many of these studies 1) only evaluated the extracranial portion of the large cerebral arteries; 2) only measured one internal carotid artery (ICA) or vertebral artery (VA), which may not account for potential flow asymmetry between the right and left sides; and 3) did not consider the impact of anatomical variations. Therefore, it is unclear how VAH may impact age-related differences in regional cerebral blood flow.

The purpose of this retrospective study was twofold. Our first aim was to compare global and regional cerebral blood flow in adults with (VAH+) and without VAH (No VAH). We retrospectively determined VAH using 4D flow phase contrast magnetic resonance imaging (MRI). We hypothesized that the VAH+ group would have lower global blood flow, with lower blood flow in both the anterior and posterior intracranial vessels compared with the No VAH group. Due to the regional variability in age-related differences in cerebral blood flow, our second aim was to determine how VAH may influence age-related differences in regional blood flow in the large intracranial arteries. Within the No VAH group, we hypothesized that blood flow in the large posterior intracranial vessels would be lower in older compared with young adults, with no age-related differences in anterior intracranial vessels. In contrast, in the VAH+ group, we hypothesized that there would not be age-related differences in blood flow in the posterior vessels (due to the anatomical variation in the posterior circulation), but older adults in the VAH+ group would demonstrate lower blood flow in the anterior intracranial vessels compared with young adults in the VAH+ group.

2. Materials and methods

2.1. Participants

Healthy adults were recruited from South Central Wisconsin in the United States using recruitment flyers. Twenty young (age range = 21–32 years) and 20 older adults (age range = 50–68 years) participated in the study. All young participants were between 20 and 34 years of age and older participants were between 50 and 69 years of age. Both young and older participants met physical activity guidelines (performing >150 min of moderate to vigorous intensity exercise per week). In addition, participants had a body mass index (BMI) <30 kg/m2, and were excluded if they 1) were current smokers; 2) were diagnosed with hypertension or taking anti-hypertensive medications; 3) presented with a history or evidence of hepatic or renal disease, hematological disease, peripheral vascular disease, stroke, neurovascular disease, cardiovascular disease, diabetes; or 4) had any contraindication for doing an MRI scan (as determined by a health history questionnaire and MRI screening form). A neuroradiologist (HAR) reviewed all MRI scans for incidental findings. Selected demographic and MRI data on these participants have been previously published [34]. MRI scans were used to retrospectively identify VAH for the current study (n = 10; Supplemental Fig. 1). All study procedures were approved by the Institutional Review Board of the University of Wisconsin–Madison (IRB:2016–0403) and were performed according to the Declaration of Helsinki, including obtaining written informed consent from each participant.

2.2. Study procedures

Upon study enrollment participants attended a familiarization session. Participants then completed a laboratory visit and an MRI scan in a randomized order. The laboratory visit included cardiovascular measurements. Prior to each study visit, participants arrived after a 4 h fast (water only) and 24 h without caffeine, vigorous exercise, and alcohol. Because non-steroidal anti-inflammatory drugs (NSAIDs) may influence CBF [13], participants refrained from taking NSAIDs for at least 5 days. Premenopausal women were studied on days 2–6 of the menstrual cycle.

2.3. Cardiovascular measurements

Cardiovascular measurements were collected to characterize cardiovascular health in the laboratory with a controlled ambient temperature between 22 and 24 °C. Brachial blood pressure was measured in triplicate after 10 min of supine rest using a non-invasive oscillometric cuff blood pressure monitor (Datex Ohmeda, GE Healthcare, Chicago, IL, United States). To assess central arterial stiffness, carotid-femoral pulse wave velocity (PWV) was measured using applanation tonometry (Sphygmocor, AtcorMedical, Sydney, NSW, Australia). High-fidelity pressure waveforms were measured at the carotid and femoral arteries for an average of 3 trials in succession as previously described [18].

To assess carotid intima-media thickness (IMT), the left common carotid artery was longitudinally imaged 1–2 cm below the carotid bifurcation with a 11L ultrasound probe with a transmission frequency of 4.5–12 MHz on a GE LOGIQ S8 ultrasound machine by the same observer (GE Healthcare, Chicago, IL, United States). Carotid IMT was measured over approximately 6 cardiac cycles using a semi-automated tracking software offline (Carotid Analyzer for Research, Medical Imaging Applications, Coralville, IA, United States) [30].

2.4. MRI scan

MRI scans were performed at the Wisconsin Institutes for Medical Research. Participants were scanned using a 3 T clinical MRI system (MR750, GE Healthcare, Waukesha, WI, United States) and a 32-channel head coil (Nova Medical Head Coil, Nova Medical, Wilmington, MA, United States) with a gradient strength of 50 mT/m, and a gradient slew rate of 200 mT/m/ms. Participants were instrumented with a pulse oximeter to measure heart rate and oxygen saturation, a nasal cannula to measure end-tidal carbon dioxide (ETCO2), and a brachial blood pressure cuff on the left arm to measure brachial mean arterial blood pressure (MAP), as previously described, for participant safety monitoring [34]. All devices were connected to an MRI compatible monitor (Medrad Veris MR Vital Signs Patient Monitor, Bayer Healthcare, Whippany, NJ, United States).

Brain volumes were determined using a T1-weighted structural sequence (BRAVO) with the following scan parameters: fast spoiled gradient echo sequence, inversion time = 450 ms, repetition time (TR) = 8.1 ms, echo time (TE) = 3.2 ms, flip angle = 12°, acquisition matrix = 256 × 256, field of view (FOV) = 256 mm, slice thickness = 1.0 mm, and scan time ∼8 min. A 3D time of flight (TOF) MRA of the Circle of Willis was used for visualization of the large intracranial vessels with the following scan parameters: TE = 2.5 ms, TR: 23 ms, flip angle = 20°, acquisition matrix = 448 × 224, FOV = 512 mm, slice thickness = 1.0 mm, pixel bandwidth = 162.78 kHz, spacing between slices = 0.5 mm, and scan time ∼4 min 30 sec. Blood flow and angiographic data of the large intracranial vessels were determined with 4D flow MRI using a 3D radially undersampled sequence (PC-VIPR) with the following scan parameters: velocity encoding (Venc) = 80 cm/s, imaging volume = 22 × 22 × 16 cm3, acquired isotropic spatial resolution = 0.7 mm × 0.7 mm × 0.7 mm, TR = 7.8 ms, TE = 2.7 ms, flip angle = 8°, bandwidth = 83.3 kHz, 14,000 projection angles and scan time ∼7 min [20] as previously described [34], [41].

2.5. Determination of VAH

Unilateral VAH was retrospectively defined using both structural and flow criteria from 4D flow MRI scans independently by two investigators. Although there is no consensus for VAH diagnosis, standard criteria were followed including vessel diameter less than or equal to 2 mm and flow less than or equal to 50 mL/min [10], [19], [39]. VAH was also confirmed from the TOF angiogram. Several studies have suggested using flow criteria <30–40 mL/min to define VAH [1], [44], [46], [48]; however, most studies relied on ultrasound which may underestimate flow values [6], [8]. In addition, many of these studies included adults with confounding vascular risk factors that are associated with reduced CBF. All participants with VAH also had an asymmetry ratio of 2.0 or greater flow between the right and left VA; thus, none of the participants in this study had bilateral VAH.

2.6. MRI data analysis

Total brain volume was derived from the T1-weighted scans. Scans were segmented in Statistical Parametric Mapping version 12 (SMP12) into gray matter (GM), white matter (WM), and cerebral spinal fluid (CSF). Total brain volume was calculated as the sum of GM and WM volume. Intracranial volume (ICV) was calculated as the sum of GM, WM, and CSF. Normalized total brain volume was calculated as total brain volume divided by ICV.

For the 4D flow MRI scans, time-resolved velocity and magnitude data were reconstructed offline by retrospectively gating into 20 cardiac phases using temporal interpolation [26]. Flow was calculated from the velocity and diameter measurements for each of the 20 cardiac phases. All scans underwent background phase offset correction, eddy current correction, [47] and automatic phase unwrapping to minimize potential for velocity aliasing [28]. Individual vessel segmentation of right and left ICAs, basilar artery (BA), and right and left VAs were performed in MATLAB using an in-house tool as previously described for semi-automated cerebrovascular flow analysis [47]. Blood flow was averaged along the length of each vessel. The ICAs were measured below the carotid siphon along the cervical and petrous portions. ICA cerebrovascular variables were calculated as the sum of the right ICA and the left ICA. The BA was measured above the bifurcation of the VAs and below the superior cerebellar artery. The VA segments were measured approximately 2 mm below the junction with the BA. Pulsatility index was calculated as (maximum flow – minimum flow)/mean flow. Global blood flow was calculated as the sum of the right and left ICAs and the BA. In order to account for differences in brain volume that may influence the global cerebral blood flow measurement, normalized cerebral blood flow was calculated as global cerebral blood flow/total brain volume.

2.7. Statistical analysis

Statistical testing was completed using Sigma Plot for Windows version 13.0 (Systat Software, San Jose, CA, United States). Prior to all analyses, normality and equal variance was assessed using the Shapiro-Wilk test and Brown-Forsythe test respectively. For the first aim, blood flow and pulsatility index were compared between No VAH and VAH+ groups using an unpaired, two-tailed t-test. For the second aim, participant demographics and blood flow characteristics were compared between age groups (young and older) in the No VAH group using unpaired, two-tailed t-tests. Similarly, participant demographics and blood flow characteristics were compared between age groups (young and older) in the VAH+ group using unpaired, two-tailed t-tests. Effect sizes were calculated using Cohen’s D. Statistical significance was set a priori at p < 0.05.

3. Results

3.1. Prevalence of VAH

Data from one older female was not usable due to motion artifact during the MRI scan.

Out of the 39 total participants, VAH was identified in n = 10 (5 young and 5 older; 26% prevalence). Representative 4D flow MRI scans are shown in Fig. 1. In the VAH+ group, the hypoplastic artery was most common on the right side (n = 8). The average diameter of the hypoplastic vertebral artery was 1.9 ± 0.1 mm, compared with the 3.5 ± 0.5 mm diameter of the contralateral, non-hypoplastic vertebral artery. The average flow was 32 ± 11 mL/min in the hypoplastic vertebral artery and 104 ± 25 mL/min in the contralateral, non-hypoplastic vertebral artery.

Fig. 1.

Fig. 1

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These are example images of the large intracranial arteries from the 4D flow MRI scan. Fig. 1A shows an example of a participant without vertebral artery hypoplasia (No VAH). Fig. 1B shows an example of a participant with VAH on the right side (VAH+). VAH was determined using both structural (hypoplastic vessel diameter less than or equal to 2.0 mm) and flow criteria (hypoplastic vessel flow less than or equal to 50 mL/min). Warmer colors reflect higher blood velocity. BA, basilar artery, L, left, R, right, VA, vertebral artery, VAH, vertebral artery hypoplasia.

3.2. Comparison between No VAH and VAH+

The VAH+ group had lower ICA flow (Fig. 2B) compared with the No VAH group, but the difference in global cerebral blood flow did not reach significance (Fig. 2A, p = 0.06). There was no difference in BA flow between VAH+ and No VAH groups (Fig. 2C, p = 0.24). There were also no differences in ICA (Fig. 2D, p = 0.45) or BA pulsatility index (Fig. 2E, p = 0.33) between VAH+ and No VAH groups.

Fig. 2.

Fig. 2

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Blood flow (A, B, C) and pulsatility index (D, E) data from the large intracranial arteries in participants with (VAH+) and without vertebral artery hypoplasia (No VAH) are shown here. A shows global blood flow, B shows internal carotid artery (ICA) blood flow and C shows basilar artery (BA) blood flow. D shows ICA pulsatility index and E shows BA pulsatility index. Bar graphs demonstrate group means ± standard deviation. Group means of No VAH are shown in black and individual data are shown in white circles (n = 29). Group means of VAH+ are shown in white and individual data are shown in white triangles (n = 10). *p < 0.05 compared with No VAH.

3.3. Age group comparisons in No VAH

Participant characteristics of the No VAH group are displayed in Table 1. Cardiovascular variables reported were collected during the laboratory visit. Within the No VAH group, there were no differences between young and older adults for BMI, heart rate at rest, and systolic blood pressure. However, older adults demonstrated higher diastolic blood pressure, mean arterial pressure, carotid-femoral PWV, and carotid IMT compared with young participants (Table 1). Total brain volume was larger in young participants compared with older adults, and this finding remained when total brain volume was normalized to ICV (Young: 0.83 ± 0.02 L vs. Older: 0.76 ± 0.03 L; p < 0.001).

Table 1.

Characteristics of participants without vertebral artery hypoplasia.

Variable Young
No VAH
N = 15		 Older
No VAH
N = 14		 P-value
Men/Women 10 / 5 9 / 5
Age (years) 24 ± 3 62 ± 5 <0.001
Height (cm) 176 ± 6 173 ± 8 0.25
Weight (kg) 74 ± 9 72 ± 13 0.65
Body Mass Index (kg/m2) 24 ± 2 24 ± 3 0.90
Heart Rate at Rest (beats per minute) 54 ± 8 54 ± 7 0.82
Systolic Blood Pressure (mmHg) 123 ± 10 124 ± 9 0.77
Diastolic Blood Pressure (mmHg) 70 ± 5 76 ± 5 <0.01
Mean Arterial Pressure (mmHg) 87 ± 6 93 ± 7 0.04
Carotid-Femoral PWV (m/s) 6.2 ± 1.0 7.8 ± 1.7 <0.01
Carotid Intima-Media Thickness (mm) 0.50 ± 0.09 0.74 ± 0.10 <0.001
Total Brain Volume (L) 1.23 ± 0.11 1.13 ± 0.10 0.02
Intracranial Volume (L) 1.48 ± 0.13 1.48 ± 0.14 0.95
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Data are mean ± SD in participants without vertebral artery hypoplasia (No VAH). PWV, pulse wave velocity, VAH, vertebral artery hypoplasia.

During the MRI scan, ETCO2 levels were not different between age groups (Young: 40 ± 4 mmHg vs. Older: 41 ± 4 mmHg; p = 0.81). Global cerebral blood flow was not different between age groups (Fig. 3A, p = 0.43) and this finding remained when global cerebral blood flow was normalized to brain volume (Young: 469 ± 97 mL/min/L vs. Older: 479 ± 102 mL/min/L; p = 0.79). There were no age group differences in ICA flow (Fig. 3A, p = 0.82); however, older participants demonstrated lower BA flow (Fig. 3A), compared with young participants. BA pulsatility index was higher in older participants compared with young participants (Fig. 4A). There was no age-related difference in pulsatility index of the ICAs (Fig. 4A, p = 0.13).

Fig. 3.

Fig. 3

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Blood flow of the large intracranial arteries in young and older participants without (No VAH; A) and with vertebral artery hypoplasia (VAH+; B) are shown here. In the top panels, group means of young No VAH are shown in grey and individual data is shown in grey circles (n = 15). Group means of older No VAH are shown in white and individual data is shown in white circles (n = 14). In the bottom panels, group means of young VAH+ are shown in grey and individual data is shown in grey triangles (n = 5). Group means of older VAH+ are shown in white and individual data is shown in white triangles (n = 5). BA, basilar artery, ICA, internal carotid arteries. *p < 0.05, **p < 0.01 compared with young.

Fig. 4.

Fig. 4

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Pulsatility index of large intracranial arteries in young and older participants without (No VAH; A) and with vertebral artery hypoplasia (VAH+; B) are shown here. In the top panels, group means of young No VAH are shown in grey and individual data is shown in grey circles (n = 15). Group means of older No VAH are shown in white and individual data is shown in white circles (n = 14). In the bottom panels, group means of young VAH+ are shown in grey and individual data is shown in grey triangles (n = 5). Group means of older VAH+ are shown in white and individual data is shown in white triangles (n = 5). BA, basilar artery, ICA, internal carotid arteries. *p < 0.05, **p < 0.01 compared with young.

3.4. Age group comparisons in VAH+

Participant characteristics of the VAH+ group are displayed in Table 2. Cardiovascular variables reported were collected during the laboratory visit. Of note, there were no differences in diastolic blood pressure, mean arterial pressure or carotid-femoral PWV between age groups (Table 2). There were also no age-associated differences in total brain volume; however, when normalized to ICV, brain volume was lower in older adults (Young: 0.84 ± 0.04 L vs. Older: 0.74 ± 0.03 L; p < 0.01) compared with young adults.

Table 2.

Characteristics of participants with vertebral artery hypoplasia.

Variable Young
VAH+
N = 5		 Older
VAH+
N = 5		 P-value
Men/Women 0 / 5 1 / 4 <0.001
Age (years) 24 ± 4 61 ± 6
Height (cm) 166 ± 9 170 ± 12 0.50
Weight (kg) 62 ± 7 65 ± 19 0.76
Body Mass Index (kg/m2) 23 ± 1 22 ± 4 0.73
Heart Rate at Rest (beats per minute) 51 ± 7 56 ± 8 0.37
Systolic Blood Pressure (mmHg) 113 ± 9 116 ± 16 0.76
Diastolic Blood Pressure (mmHg) 68 ± 7 69 ± 11 0.90
Mean Arterial Pressure (mmHg) 83 ± 7 84 ± 13 0.89
Carotid-Femoral PWV (m/s) n = 8 6.2 ± 1.1 8.0 ± 2.6 0.22
Carotid Intima-Media Thickness (mm) 0.48 ± 0.06 0.63 ± 0.06 0.01
Total Brain Volume (L) 1.12 ± 0.11 1.04 ± 0.15 0.38
Intracranial Volume (L) 1.33 ± 0.10 1.40 ± 0.15 0.40
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Data are mean ± SD in participants with vertebral artery hypoplasia (VAH+). PWV, pulse wave velocity, VAH, vertebral artery hypoplasia. For carotid-femoral PWV measurements, n = 8.

During the MRI scan, ETCO2 levels were not different between age groups (Young: 40 ± 2 mmHg vs. Older: 37 ± 2 mmHg; p = 0.19). Young participants had higher global cerebral blood flow (Fig. 3B) and normalized global cerebral blood flow (Young: 482 ± 23 mL/min/L vs. Older: 399 ± 39 mL/min/L; p < 0.01) compared with older participants. Older participants had lower ICA blood flow (Fig. 3B) compared with young participants. There were no age-associated differences in BA flow (Fig. 3B, p = 0.32). Furthermore, there were no age-related differences in ICA (p = 0.21) or BA pulsatility index (p = 0.93) (Fig. 4B).

3.5. Summary of findings and effect sizes

In the No VAH group, there was no effect of age on ICA blood flow (p = 0.82, d = 0.08), but a moderate effect of age on BA blood flow (p < 0.05, d = 0.75). In contrast, in the VAH+ group, there was a large effect of age on ICA blood flow (p < 0.05, d = 2.10); however, the effect of age on BA flow in the VAH+ group was not significant (p = 0.32, d = 0.67).

4. Discussion

4.1. Summary and discussion of findings

In our retrospective analysis, 26% of participants met criteria for unilateral VAH. Participants with VAH had lower ICA blood flow compared to participants without VAH. Furthermore, aging was associated with lower ICA blood flow only in the VAH+ group. In the No VAH group, aging was associated with lower BA blood flow. Taken together, these data suggest that the presence of VAH may contribute to variability in the age-related differences in cerebral blood flow in healthy adults. As the published prevalence of VAH in healthy adults is 15–35%, identification and further evaluation of this anatomical variation is warranted in larger cohorts.

Because of the lower blood flow within the VAs, adults with VAH are at a higher risk for posterior stroke [10], [15], [36], [39], [49], [53]. Yet, the impact of VAH on CBF regulation, especially in the context of aging, in unclear. In the present study, we leveraged recent MRI scans to address this research question and utilized 4D flow MRI to identify VAH and assess blood flow of the large intracranial arteries. 4D flow MRI allows for unique, in-vivo acquisition of both volumetric flow and vascular area with high spatial resolution and without a contrast agent. It also allows for the assessment of multiple vessels from a single acquisition. Using this novel technique addresses some of the limitations of previous techniques to determine VAH. For example, 2D PC MRI relies on user-dependent placement of measurement planes which may be difficult to reproduce, B-mode ultrasound assessment relies on user-dependent insonation of the vessels extracranially, and manual inspection of the cerebral anatomy requires post-mortem evaluation. Also, in an effort to reduce confounding vascular risk factors and isolate the effects of primary aging, we included only participants that were healthy, normotensive, met physical activity guidelines, and were without underlying cardiometabolic disease. Using 4D flow MRI, we observed lower ICA blood flow in the VAH+ group compared with the No VAH group, which suggests that VAH may affect the anterior cerebral circulation. However, contrary to our hypothesis, there were no differences in BA blood flow between the VAH+ and No VAH group. Future studies could utilize 4D flow MRI to further investigate the longitudinal effects of VAH on CBF regulation and its implications for cognitive function, especially in cohorts of older adults.

In the present study, older participants in the VAH+ group demonstrated approximately 35% lower ICA blood flow compared with young participants in the VAH+ group, but similar BA blood flow values. Although we did not report differences in BA blood flow between VAH+ and No VAH groups, the pattern of age-related differences in blood flow depended on whether the anatomical variation VAH was present. In the VAH+ group, BA blood flow may be preserved with age, at the expense of blood flow of the anterior cerebral circulation. In this context, preserving BA blood flow could be a way of protecting vulnerable posterior areas such as the brainstem from hypoperfusion. Future studies could evaluate the mechanism by which anterior flow declines with aging in individuals with posterior anatomical variations such as VAH.

Older participants in the No VAH group demonstrated approximately 26% lower BA blood flow compared with young participants in the No VAH group. There were no age-related differences in ICA blood flow in participants without VAH. This suggests that in healthy adults, early age-related declines in relative blood flow may be localized to the posterior circulation and not in the anterior circulation. These findings are consistent with previous cross-sectional studies of adults with normal cerebral anatomy that reported the age-related difference in VA flow is larger than ICA flow [3], [12], [38], [54]. In fact, Olesen et al., reported the magnitude of the age-associated difference in VA flow was four times greater than ICA flow when they cross-sectionally compared young adults (age = 24 ± 3 years) with older adults (age = 70 ± 5 years) [38]. In the study by Albayrak et. al., 2007, the relationship between ICA flow and age was stronger than VA flow and age; however, the relative difference in flow between the youngest (20–39 years) and oldest (60–79 years) age groups were approximately 16% in the ICAs and approximately 25% in the VAs [3]. Our findings are in contrast with Scheel et. al., 2000 who reported significant age-related differences in ICA flow with no observed relationship between VA flow and age in adults aged 20–85 years [45]. There have also been reports of age-related differences in middle cerebral artery velocity in adults with various vascular risk factors [2], [5], [11], [14], [22]. However, these studies are difficult to compare with our findings because: 1) they do not report cerebral anatomical variations such as VAH; 2) one middle cerebral artery only contributes to about 21% of total CBF as opposed to the sum of the ICAs contributing to 72% of total CBF [52]; and 3) it is possible that the regional pattern of age-related declines in CBF may change beyond the 6th decade of life, as the older participants in our study averaged ∼ 61 years of age and many previous studies included adults up to 85 years of age. The age of the older participants, and the fact that they had low vascular risk, may contribute to why we did not observe a difference in global CBF between No VAH age groups. Collectively, the relative age-related differences in CBF of the large intracranial arteries may be region-specific. The results of the present study show posterior brain areas and the brain stem may be more vulnerable to age-related hypoperfusion, at least in the context of healthy, physically active adults without VAH. Furthermore, anatomical variations may explain some of the variability in age-related differences in global cerebral blood flow in healthy adults.

In addition to lower blood flow, older participants in the No VAH group demonstrated higher BA pulsatility index compared with young participants in our study. Higher pulsatility index is often interpreted as increased distal cerebrovascular resistance and decreased compliance of the cerebral arterial bed [16], [25]. Although pulsatility does not directly measure cerebrovascular resistance, the higher pulsatility could suggest an age-associated alteration of blood flow hemodynamics in the BA, possibly because of elevated vascular stiffness. Indeed, we observed higher carotid-femoral PWV and carotid IMT in older participants, indicating elevated vascular stiffness in central arteries. Higher central vascular stiffness reduces the dampening function of the aorta and large central arteries from the heart traveling to the cerebral circulation [35]. In a post-mortem study, posterior cerebral arteries had a higher prevalence of elastin loss, concentric intima thickening, wall thickening and nonatherosclerotic stenosis compared to anterior cerebral arteries [42]. Thus, the combination of higher pulsatility index and lower BA blood flow may augment risk of hypoperfusion in posterior brain areas of older adults. However, we did not observe differences in pulsatility index between the VAH+ and No VAH groups. It should be noted the clinical consequences of high pulsatility index and lower blood flow in posterior brain areas warrant further investigation.

4.2. Limitations and methodological considerations

Because this study was retrospective, there are inherent limitations to our approach. We leveraged existing data to determine the effect of VAH on age-related differences in the cerebral circulation. In order to conduct a prospective study to test our hypothesis, an MRI scan would be required to identify VAH prior to study enrollment. Nevertheless, these results provide rationale to further investigate the impact of VAH on CBF regulation. A second limitation is that we assessed the effect of age using a cross-sectional approach. While this is a common approach to understand aging physiology, we are unable to determine the timing and trajectory of the changes in CBF without a longitudinal follow-up over years or decades. We attempted to isolate the effects of primary aging by only including healthy young participants between 21 and 32 years and older participants between 50 and 68 years with low cardiometabolic risk; thus, we cannot comment about the effect of aging beyond those ranges. The wider age range in the older participant group could also be considered a limitation. A third limitation is the small number of participants with VAH in this study and they were primarily women. This is likely a coincidence, as other studies in larger cohorts have not reported sex differences in VAH prevalence [23], [39]. Because of the small sample size, we may be at risk for type 2 errors, and did not perform additional comparisons to evaluate the effect of sex or adjust the results for multiple comparisons. There are also methodological considerations. In this study, we used 4D flow MRI, which allows simultaneous acquisition of angiographic and blood flow data, making it an ideal scan to measure blood flow in the large intracranial arteries and to identify VAH. Using 4D flow MRI to identify VAH addresses some of the limitations of commonly used methods such as ultrasound and 2D PC MRI which both require user-dependent scanning or placement of measurements planes. However, it is possible that other perfusion scans such as arterial spin labeling (ASL) or blood-oxygen-level-dependent imaging (BOLD) may unveil additional regional blood flow differences that we are unable to capture by limiting our analysis to large major arteries. Our calculation of global cerebral blood flow was based off the contributions of the large intracranial arteries (BA and ICAs), therefore we did not include the contribution of cerebellar arteries. Because we were interested in how VAH may affect blood flow in the large major arteries, we did not evaluate the effect of other anatomical variations of the Circle of Willis such as fetal origin posterior cerebral arteries (PCA) or hypoplastic anterior cerebral arteries. Fetal origin PCA may produce flow asymmetry on perfusion imaging [51]. Evaluation of regional cerebral perfusion using additional techniques may provide insight into the relative perfusion of different vascular territories and the existence of collaterals in people with VAH. Future studies could utilize multiple scan sequences to address regional differences in CBF and perfusion in adults with VAH.

5. Conclusion

Individuals with VAH had lower ICA blood flow compared with individuals without VAH. Aging was associated with lower ICA blood flow, but only in individuals with VAH. In contrast, in individuals without VAH, aging was associated with lower BA blood flow. Collectively, these data suggest that the presence of VAH may contribute to variability in the age-related differences in cerebral blood flow in healthy adults. Future studies could evaluate the effect that VAH and other cerebral anatomical variations have on CBF regulation in the context of healthy aging in larger cohorts. Furthermore, VAH may be an additional risk factor for an accelerated decline in CBF which could impact the risk of stroke as well as the risk of developing cognitive impairment.

Funding sources

Funded by the Wisconsin Alumni Research Foundation (JNB), NIH HL118154 (JNB), NS117746 (JNB), HL007936 (KBM).

CRediT authorship contribution statement

Kathleen B. Miller: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Visualization, Writing - original draft. Samuel J. Gallo: Data curation, Formal analysis, Investigation, Methodology, Writing - original draft. Leonardo A. Rivera-Rivera: Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing - review & editing. Adam T. Corkery: Data curation, Formal analysis, Investigation, Methodology, Writing - review & editing. Anna J. Howery: Data curation, Formal analysis, Investigation, Project administration, Writing - review & editing. Sterling C. Johnson: Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Writing - review & editing. Howard A. Rowley: Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Writing - review & editing. Oliver Wieben: Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Writing - review & editing. Jill N. Barnes: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Visualization, Writing - original draft, Writing - review & editing.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

We would like to thank Jenelle Grogan, Sara John, Haley Cilliers and Martha Garcia for their help with data collection. We would also like to thank Erika Quesada for MRI scheduling and Chuck Illingworth for MRI data management.

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.nbas.2021.100019.

Contributor Information

Kathleen B. Miller, Email: kathleen.miller@wisc.edu.

Samuel J. Gallo, Email: samuel.gallo@midwestern.edu.

Leonardo A. Rivera-Rivera, Email: larivera@wisc.edu.

Adam T. Corkery, Email: acorkery@wisc.edu.

Anna J. Howery, Email: ahowery@wisc.edu.

Sterling C. Johnson, Email: scj@medicine.wisc.edu.

Howard A. Rowley, Email: hrowley@uwhealth.org.

Oliver Wieben, Email: owieben@wisc.edu.

Jill N. Barnes, Email: jnbarnes@wisc.edu.

Appendix A. Supplementary data

The following are the Supplementary data to this article:

Supplementary figure 1.

Supplementary figure 1

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