Alzheimer’s disease (AD) is an age-related neurodegenerative disorder that compromises the memory and executive function of affected individuals [1
]. The etiology of AD is complex, with a variety of factors such as genetics [2
], the amyloid-β (Aβ) protein [7
], the microtubule tau protein [8
], and inflammation [16
], amongst others, interacting with one another to influence the pathology and progression of AD. While the amyloid cascade hypothesis and its variants [7
] remain the favored AD hypothesis, the exact cause of AD remains contentious [22
Cerebro-vascular factors have been demonstrated to both influence and to be influenced by AD pathology [26
]. These vascular effects include an increased risk of stroke in AD patients [29
]. Paradoxically, a history of strokes excludes a diagnosis of AD in favor of vascular dementia [30
]. This only muddies the waters in differentiating between these two causes of dementia and raises discordance: If an individual suffers a stroke and then presents with dementia symptoms, the dementia is likely to be differentiated as vascular dementia, yet if an AD patient suffers a stroke following diagnosis, the stroke is likely to be attributed to the AD pathology.
The various pathological factors involved in AD have allowed for the discovery of an abundance of AD biomarkers based on data obtained from medical imaging, cerebrospinal fluid and blood plasma [31
]. Medical imaging, including positron emission tomography (PET) [37
] and magnetic resonance imaging (MRI) [41
], has provided a wealth of information on the pathology of AD both in research settings and as confirmatory diagnostic tools [38
Impaired cerebral perfusion is one of the many pathological hallmarks of AD [49
] and its use as a biomarker for AD was established even before the amyloid cascade hypothesis was first posited [50
] in the early 1990s. Numerous research groups have observed a reduction in cerebral perfusion in AD patients using a variety of techniques [51
]. In one such example, Perani, et al. showed a reduction in global cerebral perfusion compared to healthy controls using technetium-99m hexamethylpropyleneamine oxime ([99mTc]HM-PAO) Single Positron Emission Tomography (SPECT) [54
]. Parkes and colleagues employed arterial spin labelling (ASL), an MRI-based technique, to demonstrate a decrease in the grey matter to white matter (GM:WM) perfusion ratio, which was attributed to the reduction in GM perfusion [55
]. Work by Du et al. and Johnson et al. localized areas of hypoperfusion to the parietal cortex [56
]. In addition to localizing impaired cerebral perfusion to the parietal cortices, Schuff, and colleagues localized impaired perfusion to the frontal cortices [56
]. ASL and phase contrast MRI have been used to detect changes in cerebral blood flow (CBF) in order to stage AD disease severity [58
In addition to detecting endogenous nuclei in the body (i.e., protons), MRI can also be used to detect exogeneous nuclei. A variety of techniques have been developed to increase the sensitivity of MRI to these exogeneous nuclei. One of these techniques involves hyperpolarizing the nuclei of a variety of elements such as 3
] and 13
], to align their nuclear spin angular momentum, providing an increase in the signal-to-noise (SNR) ratio of approximately five orders of magnitude [65
]. Because these nuclei are not ubiquitous to the body under ordinary physiological conditions, they can be detected and tracked throughout the body using MRI and magnetic resonance spectroscopy (MRS) [66
]. In particular, a hyperpolarized (HP) gas, 129
Xe, dissolves into the blood following inhalation [69
] and then travels throughout the vasculature and accumulates in highly perfused tissues such as the brain [70
]. This process is referred to as xenon wash-in. Xenon then washes out of the brain tissue, dissolving in the blood and is then exhaled following gas exchange in the lungs.
The diagnosis of AD is a diagnosis of exclusion and is primarily based upon clinical presentation [30
]. Biomarkers obtained from the cerebrospinal fluid (CSF) or from imaging may be used as confirmatory tools [72
]. One of the difficulties in using AD-associated biomarkers for AD diagnosis is the large overlap in values between AD patients and healthy individuals; while the mean values between the two populations may be statistically significant, many AD patients may have biomarker values close to the “normal” range, and vice versa [73
]. Abnormal Aβ42 levels are typically set at <550 ng/L [74
]. This overlap has motivated the search for AD biomarkers with higher diagnostic accuracy. Recently, Nakamura, et al. demonstrated convincing plasma AD biomarkers at accuracies exceeding 90% using highly sensitive immunoprecipitation and mass spectrometry [75
]. At present, biomarkers are ideally suited to quantitatively monitor disease progression over time, comparing current values to baseline values.
In the present study, we employed HP 129
Xe, MRI and MRS to probe the xenon gas exchange characteristics in the brain of AD participants [63
]. We demonstrate the preliminary results of two potential biomarkers of AD based on the washout of HP 129
Xe from the brain of AD participants, which was detected using 129
Xe MRS. The washout of the 129
Xe from the brain can be used as an indirect measure of brain perfusion. In contrast to the high degree of overlap of many existing AD biomarkers, our preliminary data demonstrate a five standard deviation difference of 129
Xe-GM signal retention at 60 s following the breath hold and a nearly two standard deviation difference in the xenon washout parameter between AD participants and healthy controls. The xenon washout parameter is calculated by fitting the xenon signal curve to a pharmacokinetic equation (see Equation (1) in results). The difference in xenon retention values between AD participants and healthy controls makes these potential biomarkers candidates for larger scale future studies.
2. Materials and Methods
2.1. Ethical Approval and Consent to Participate
This research study was approved by the research ethics boards (REB) of Lakehead University (LU) and the Thunder Bay Regional Health Sciences Centre (TBRHSC) (Reference number RP-307) and was conducted in accordance with the Tri-Council Policy Statement-2 (TCPS-2). All participants consented to their data being used for publication.
2.2. Participant Recruitment
Four participants diagnosed with mild to moderate AD were recruited from the community for participation in this study. AD patients were diagnosed using clinical criteria by a qualified neurologist or gerontologist. Additionally, four age-matched healthy volunteers were recruited to serve as controls. Age-matched control participants were all cognitively normal. Informed consent was obtained from all human participants.
2.3. 1H Magnetic Resonance Imaging
Participants were placed into a dual tuned 1H/129Xe head coil (Clinical MR Solutions LLC, Brookfield, WI, USA) in a Philips Achieva 3T clinical MRI scanner. T2-weighted 1H MRI was acquired using a turbo-spin echo (TSE) sequence with the following parameters: FOV = 250 mm × 250 mm, matrix = 256 × 256, TR/TE = 3 s/80 ms, NSA = 5, FA = 90°.
2.4. 129Xe Magnetic Resonance Spectroscopy
Enriched 129Xe was polarized to ~35% using a Xemed xenon (Xemed LLC, Durham, NH, USA) gas polarizer and dispensed into a 500 mL Tedlar bag. The participants inhaled the Xe gas and held their breath for 20 s. Sixty dynamic spectra were acquired every 2 s beginning with Xe inhalation. Xe MRS parameters were as follows: 60 dynamic scans, bandwidth 32 kHz, sample number: 4096, TR/TE = 2 s/0.17 ms, FA = 10°. The signal was a single voxel encompassing the entirety of the brain region. We used a low flip angle to maintain polarization of the 129Xe gas throughout all dynamic scans. Both Xe-GM and Xe-WM peaks were plotted as a function of time. Signal intensity was calculated by measuring the peak divided by the standard deviation of the noise.
2.5. 129Xe Magnetic Resonance Imaging
Enriched 129Xe was polarized to ~35% as described above and dispensed into two 1 L Tedlar bags. Acquisition parameters were as follows: FOV = 250 mm × 250 mm, matrix = 32 × 32, TR/TE = 250 ms/0.84 ms, NSA = 1, FA = 12.5°, Bandwidth 150 Hz/pixel. Three dynamic scans were acquired at 10 s, 20 s and 30 s following inhalation.
2.6. 129Xe Image Processing
All images were processed using a custom Matlab script that converted the raw data in k-space into an MR image using a Fast Fourier Transform (FFT) algorithm. SNR maps were created by dividing each pixel by the standard deviation of the noise. Complete details on how the SNR maps were created are contained within the supplementary information
2.7. Xenon Washout Parameter Maps Image Processing
The three dynamic 129Xe MRI were processed as described above. A custom Matlab script was used to calculate the xenon washout parameter of each pixel as described above to create a “xenon washout parameter map”. Xenon washout parameter maps from all individuals were averaged to create a mean xenon washout parameter map for all AD participants and healthy age-matched controls. A mask was created to remove noise from outside the brain region for image clarity. The xenon washout parameter maps were overlaid on T2W anatomical MRI using GIMP v.2.8 image processing software.
2.8. Statistical Analysis
Data for all participants was aggregated and the means and standard deviations were calculated. 16 data points for healthy controls and 13 data points for AD were used. (Each participant had xenon washout measured 3 or 4 times). A Welsh’s t-test (2-tail, unpaired) was conducted to establish statistical significance. For all comparisons, p < 0.01. However, due to the preliminary nature of this study and small sample size, p values were not stated.
In this work, we made two significant findings. Firstly, AD participants have significantly lower 129Xe in the GM than healthy controls. Secondly, we found that AD subjects retain 129Xe within both the GM and WM of the brain significantly longer than healthy controls. Our results support the hypothesis that cerebral perfusion may be affected by AD pathology.
AD is considered primarily a disease of grey matter; however, white matter has been implicated as well in the AD pathology [78
]. Our observed decrease in 129
Xe-GM signal between AD participants and healthy controls suggests a reduction in GM volume or a decrease in 129
Xe uptake in the GM. In contrast, the 129
Xe-WM signal was not different between AD participants and healthy controls.
While there is considerable overlap in many AD biomarkers between healthy controls and AD patients, we calculated a five standard deviation difference in the 129
Xe retention in the GM between AD patients compared to healthy controls (Table 1
, Figure 2
D and Figure 3
A). Furthermore, no AD patients had 129
Xe retention values below that of any healthy control and no healthy control had 129
Xe retention values higher than the lowest AD 129
Xe retention values.
Additionally, we introduce a potential AD biomarker that we denote as the xenon washout parameter from Equation (1). The measurement of xenon signal as a function of time (i.e., Xe washout) using 129
Xe MRS was fit to a pharmacokinetic model (Equation (1)) and the xenon washout parameter was calculated. While other pharmacokinetic models [76
] have been developed and fit our data, we utilized the model developed by Martin, et al. [77
] because it was a better fit for our data as it is only applied to the washout phase and therefore relied on fewer assumptions than the model developed by Kilian et al. [76
]. We calculated that the xenon washout parameter is nearly 2 standard deviations lower in AD participants than in healthy controls for grey matter.
In addition to our spectroscopic data, we were able to localize the xenon washout parameter to different brain regions. Our analysis of the localized xenon washout parameter from the xenon washout parameter maps indicates a lower xenon washout parameter in AD participants than in healthy controls (Figure 5
). While this observation is consistent with our spectroscopic results, the xenon washout parameter obtained from imaging is less accurate than that obtained from spectroscopy because the model was fit using only three data points (three dynamic 129
Xe images) for the imaging data compared to 60 data points for the spectroscopic data. From our qualitative observations of the sagittal β-parameter maps, we observed that the xenon washout parameter is higher in the caudal regions than it is in the frontal lobes (Figure 5
) for both healthy controls and AD participants. In AD participants, while the mean xenon washout parameter decreases throughout the brain, the xenon washout parameter remains higher in the posterior regions of the brain. This observation could possibly indicate lower perfusion in the frontal lobes than in the caudal brain regions. This observation is consistent with previous reports indicating that AD pathology begins near the rostral regions of the brain and slowly migrates towards the caudal regions of the brain [79
The cerebral perfusion, T1 of 129
Xe in the brain, and the xenon partition coefficient all influence the xenon washout parameter as expressed in Equation (2). Cerebral perfusion has long been demonstrated to be reduced in AD patients [50
]. Work by Binnewijzend et al. reported a difference of cerebral perfusion of approximately 27% which was one standard deviation lower in AD patients compared to healthy controls [58
]. In contrast, we observed a difference in the xenon washout parameter of 42% or nearly two standard deviations between AD subjects and healthy controls. Since the xenon washout parameter is a function of cerebral perfusion, our results raise the question of why the xenon washout parameter demonstrates a greater difference between AD participants and healthy controls. While ASL provides a direct measure of cerebral perfusion, our technique incorporates additional factors, such as T1 and the xenon lipid diffusion coefficient, that may be affected in AD patients.
It is possible that the xenon washout parameter is affected by a difference in T1 relaxation time values between healthy controls and AD participants. It is interesting to speculate that small changes in T1 may be caused by the abundance of trace metals in the brain of AD participants [10
An alternative hypothesis is that the partition coefficient of xenon in the brain tissues is different in AD participants compared to healthy controls. It is well established that Aβ affects the membrane properties of the brain [84
]. We speculate that because of the increased membrane permeability in AD brain tissue, the partition coefficient of xenon in the brain of AD participants is increased, creating a reservoir of xenon that causes a slower wash out. Additionally, AD is known to breakdown the blood brain barrier (BBB) [90
]. This breakdown may affect the clearance of xenon from the brain tissue into the blood. However, it is more likely that this phenomenon would cause increased xenon clearance (and hence faster washout in AD patients) rather than our observations of greater retained xenon in AD brains. This biomarker may offer some advantages over existing biomarkers, especially those relying on CSF. Our proposed biomarker does not require an invasive spinal tap and, so far in our preliminary results, shows a greater difference between AD participants and healthy controls compared to CSF Aβ values.
Like all techniques, this proposed biomarker has a number of limitations. First, it requires an expensive and highly specialized 129Xe polarizer to polarize the 129Xe gas. Secondly, this technique relies on the patient holding their breath for 20 s, a task that some individuals with dementia could have difficulty with.
Moreover, this study has notable limitations. Firstly, it relied on a small number of subjects precluding accurate determination of the sensitivity and specificity of this technique. Second, because of the small sample size, we were unable to infer the predictive power of this study or to correlate disease severity with the xenon washout parameter value. Lastly, we were unable to differentiate whether our proposed biomarkers are indicative of just AD or all dementias, or even, any neurologic disease. Regardless of these limitations, the proposed 129Xe xenon washout parameter biomarker has the potential for validation with a larger sample size study to determine both its accuracy and predictive power of impending AD. Additionally, future experiments could attempt to correlate the Montreal Cognitive Assessment (MOCA) scores to 129Xe retention and the xenon washout parameter; these biomarkers could be tested as a potential correlate to future AD risk.
In conclusion, we demonstrate a difference in the 129Xe retention between AD participants and healthy controls. Additionally, we introduce the termed xenon washout parameter which accounts for changes in cerebral perfusion, and differences in 129Xe T1 relaxation and lipid partition coefficients associated with AD pathology. The xenon washout parameter is considerably different in healthy controls and AD participants with little overlap between the two groups.