Assessment of cerebral response to exercise: effects of ageing and cardiorespiratory fitness
Andrew Hale1, Penny Gowland1, Paul Greenhaff2, and Susan Francis1

1Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom, 2Faculty of Medicine & Health Sciences, Queens Medical Centre, University of Nottingham, Nottingham, United Kingdom

Synopsis

Although there is a general relationship between age and brain function, habitual physical activity levels may also impact on brain health. We performed a MR study involving low and moderate intensity supine exercise in healthy young and older subjects. We assess the effect of exercise on CBF response in large arteries, regional perfusion and BOLD, and the relationship of grey matter volume with physical fitness and ageing. On exercise there was a clear CBF, perfusion and BOLD response to exercise in young volunteers, whilst a reduced CBF, perfusion and BOLD response to exercise was found in the older volunteers.

Purpose

Physical inactivity is linked to poor health and disease progression, particularly in older people. This has led to research focus on physical activity, ageing and brain structure and function relationships. Importantly, negative health traits generally attributed to ageing, (frailty, cognitive decline, brain atrophy), may in part result from decreased habitual physical activity levels, and be preventable with increased exercise. Using Transcranial Doppler Ultrasound (TCD) it has been shown that the increase in cerebral perfusion during submaximal and maximal exercise is lower in older volunteers than young1-4, although brain O2 uptake is similar4. However, a critical issue for TCD2,3 is the extent to which blood velocity reflects cerebral blood flow (CBF) and that values are not corrected for grey matter (GM) volume. Further, studies have suggested that higher cardiorespiratory fitness levels are associated with greater GM volume5.

Aim

Here, in healthy young and older volunteers, we assess MR measures of (1) CBF response in large arteries to low/moderate intensity steady-state exercise; (2) regional perfusion and BOLD response to low/moderate intensity steady-state exercise; (3) GM volume and the relationship with cardiorespiratory fitness and ageing.

Method

12 male subjects were recruited to healthy, young (N=5, 22-27 years, BMI 24±2) and healthy, older (N=7, 70-74 years, BMI 24.4±2.1) groups.

VO2max: Subjects underwent a continuous, incremental supine exercise test to determine maximal oxygen consumption (VO2max) using a MR compatible cycle ergometer (Lode B.V, Netherlands) and an on-line gas analysis system (Cosmed, Italy).

Exercise task: MR data was acquired at baseline and during 10min of steady-state exercise inside the scanner at workloads of 30% and 50% VO2max, and heart-rate was measured throughout. For the older group, data was also acquired during a 10min recovery period (Fig.1A).

MR acquisition: Data was acquired on a Philips Achieva 3T MR scanner using a 32-channel receive coil. Sagittal and coronal 2D PC-MRA data was acquired to locate the left (L)/right (R) internal carotid arteries (ICA) and basilar artery (BA). At baseline and each workload, blood flow (velocity and flux) in the L/R ICA and BA was measured using a vector-cardiogram (VCG) gated, 2D PC-MRA (TE/TR=6.5/15ms, FA=25°, FOV=280x77mm2, 0.75x0.75x6mm3 reconstructed, SENSE4, vENC=0 and 100 cm/s, NSA=2, duration=1min25s). For regional perfusion and BOLD data, a DABS sequence6 was used to acquire simultaneous perfusion and BOLD data (GE-EPI at TE=13ms/40ms for ASL and BOLD respectively), 10 slices of in-plane resolution 3x3mm, slice thickness 8mm, post-label delay (TI)=1550ms, TR=2600ms per label/control, duration~5min. Following the exercise protocol, a T1-weighted MPRAGE image was acquired to estimate GM volume.

Data analysis: PCA data was analysed using Q-Flow (Philips) for vessel area, velocity and flux in the L/R ICA and BA. Flux measures were summed to estimate ‘Total CBF’. DABS data were separated into BOLD and ASL time-series. BOLD data was motion corrected (FSL, fMRIB, Oxford) and motion parameters applied to ASL images. Perfusion weighted images were formed from subtraction of label and control data. BOLD data was analysed using FEAT (FSL) to identify brain areas associated with the exercise task (GLM analysis, FDR corrected Z>3.89). Image segmentation and GM volume analysis normalized for subject head size was performed on the MPRAGE images using SIENAX (FSL).

Results

Steady-state heart-rate increased with workload, but the increase was less in older versus younger volunteers (Fig.1B), as was the absolute maximum exercise workload achieved (114±17 vs. 162±20W).

PCA data: Fig.2A shows GM corrected total CBF at rest and with exercise for both younger and older subjects and Fig.2B shows the corresponding % change in CBF from baseline.

BOLD/CBF data: Fig.3 shows the perfusion change in grey matter as measured by ASL. Young subjects exhibited a clear BOLD response to exercise (6.9±2.1%, 30% VO2max; 9.5±3.8%, 50% VO2max), however no consistent BOLD response was found in older volunteers (3 older subjects removed due to motion artefacts). Fig.4 shows GM volume versus VO2max.

Discussion

At rest, there was no difference in GM corrected CBF when comparing age groups. On exercise there was a clear CBF, perfusion and BOLD response in young subjects, whilst a markedly blunted CBF and perfusion response was found in older subjects at the same relative exercise workloads. No clear BOLD response was found in older subjects, possibly due to the reduced change in CBF on exercise inhibiting a BOLD change. GM volume was positively correlated with cardiorespiratory fitness (r=0.78), however a greater range of VO2max values is required to moderate the effects of age. Exercise manifests clear deficits in brain vascular responses in older volunteers compared to young, which may be a function of reduced habitual physical activity levels.

Acknowledgements

AH holds a MRC-ARUK Centre for Musculoskeletal Ageing Research studentship

References

[1] Ide K & Secher NH, Prog Neurobiol 61, 397–414, 2000. [2] Sato et al. J Physiol 589, 2847-2856, 2011. [3] Kim YS et al. Physiol Rep 6, e12430, 2015. [4] Fisher JP et al. J Physiol 591,1859-70, 2013. [5] Erickson KI et al. Neurobiol of aging 35, 20-28, 2014. [6] Wesolowski et al. Proc. ISMRM, 2009.

Figures

Figure 1: (A) Exercise protocol performed inside scanner (older volunteer group also included a recovery period). (B) Heart rate as a function of relative exercise workload.

Figure 2: (A) GM corrected total CBF (ICA+BA) flow for each workload. (B) % change in GM corrected total CBF flow for each workload.

Figure 3: % change in GM perfusion for each workload.

Figure 4: GM volume analysis normalized for subject head size plot against cardiorespiratory fitness levels defined by VO2max (ml/kg body mass/min).



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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