Modeling the Effect of Hyperoxia on the Spin-Lattice Relaxation Rate R1 of Tissues.

PURPOSE: Inducing hyperoxia in tissues is common practice in several areas of research, including oxygen-enhanced MRI (OE-MRI), which attempts to use the resulting signal changes to detect regions of tumor hypoxia or pulmonary disease. The linear relationship between PO2 and R1 has been reproduced in phantom solutions and body fluids such as vitreous fluid; however, in tissue and blood experiments, factors such as changes in deoxyhemoglobin levels can also affect the ΔR1. THEORY AND METHODS: This manuscript proposes a three-compartment model for estimating the hyperoxia-induced changes in R1 of tissues depending on B0, SO2 , blood volume, hematocrit, oxygen extraction fraction, and changes in blood and tissue PO2 . The model contains two blood compartments (arterial and venous) and a tissue compartment. This model has been designed to be easy for researchers to tailor to their tissue of interest by substituting their preferred model for tissue oxygen diffusion and consumption. A specific application of the model is demonstrated by calculating the resulting ΔR1 expected in healthy, hypoxic and necrotic tumor tissues. In addition, the effect of sex-based hematocrit differences on ΔR1 is assessed. RESULTS: The ΔR1 values predicted by the model are consistent with reported literature OE-MRI results: with larger positive changes in the vascular periphery than hypoxic and necrotic regions. The observed sex-based differences in ΔR1 agree with findings by Kindvall et al. suggesting that differences in hematocrit levels may sometimes be a confounding factor in ΔR1. CONCLUSION: This model can be used to estimate the expected tissue ΔR1 in oxygen-enhanced MRI experiments.

A simplified empirical model to estimate oxygen relaxivity at different magnetic fields.

The change in longitudinal relaxation rate (R1 ) produced by oxygen has been used as a means of inferring oxygenation levels in magnetic resonance imaging in numerous applications. The relationship between oxygen partial pressure (pO2 ) and R1 is linear and reproducible, and the slope represents the relaxivity of oxygen (r1Ox ) in that material. However, there is considerable variability in the values of r1Ox reported, and they have been shown to vary by field strength and temperature. Therefore, we have compiled 28 reported empirical values of the relaxivity of oxygen as a resource for researchers. Furthermore, we provide an empirical model for estimating the relaxivity of oxygen in water, saline, plasma, and vitreous fluids, accounting for magnetic field strength and temperature. The model agrees well (R2  = 0.93) with the data gathered from the literature for fields ranging from 0.011 to 8.45 T and temperatures of 21-40 °C. This provides a useful resource for researchers seeking to quantify pO2 in simple fluids in their studies, such as water and saline phantoms, or bodily fluids such as vitreous fluids, cerebrospinal fluids, and amniotic fluids.

A General Model to Calculate the Spin-Lattice Relaxation Rate (R1) of Blood, Accounting for Hematocrit, Oxygen Saturation, Oxygen Partial Pressure, and Magnetic Field Strength Under Hyperoxic Conditions.

BACKGROUND: Under normal physiological conditions, the spin-lattice relaxation rate (R1) in blood is influenced by many factors, including hematocrit, field strength, and the paramagnetic effects of deoxyhemoglobin and dissolved oxygen. In addition, techniques such as oxygen-enhanced magnetic resonance imaging (MRI) require high fractions of inspired oxygen to induce hyperoxia, which complicates the R1 signal further. A quantitative model relating total blood oxygen content to R1 could help explain these effects. PURPOSE: To propose and assess a general model to estimate the R1 of blood, accounting for hematocrit, SO2 , PO2 , and B0 under both normal physiological and hyperoxic conditions. STUDY TYPE: Mathematical modeling. POPULATION: One hundred and twenty-six published values of R1 from phantoms and animal models. FIELD STRENGTH/SEQUENCE: 5-8.45 T. ASSESSMENT: We propose a two-compartment nonlinear model to calculate R1 as a function of hematocrit, PO2 , and B0. The Akaike Information Criterion (AIC) was used to select the best-performing model with the fewest parameters. A previous model of R1 as a function of hematocrit, SO2 , and B0 has been proposed by Hales et al, and our work builds upon this work to make the model applicable under hyperoxic conditions (SO2  > 0.99). Models were assessed using the AIC, mean squared error (MSE), coefficient of determination (R2 ), and Bland-Altman analysis. The effect of volume fraction constants WRBC and Wplasma was assessed by the SD of resulting R1. The range of the model was determined by the maximum and minimum B0, hematocrit, SO2 , and PO2 of the literature data points. STATISTICAL TESTS: Bland-Altman, AIC, MSE, coefficient of determination (R2 ), SD. RESULTS: The model estimates agreed well with the literature values of R1 of blood (R2  = 0.93, MSE = 0.0013 s-2 ), and its performance was consistent across the range of parameters: B0 = 1.5-8.45 T, SO2  = 0.40-1, PO2  = 30-700 mmHg. DATA CONCLUSION: Using the results from this model, we have quantified and explained the contradictory decrease in R1 reported in oxygen-enhanced MRI and oxygen-delivery experiments. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 1.

Pancreas MRI Segmentation Into Head, Body, and Tail Enables Regional Quantitative Analysis of Heterogeneous Disease.

BACKGROUND: Quantitative imaging studies of the pancreas have often targeted the three main anatomical segments, head, body, and tail, using manual region of interest strategies to assess geographic heterogeneity. Existing automated analyses have implemented whole-organ segmentation, providing overall quantification but failing to address spatial heterogeneity. PURPOSE: To develop and validate an automated method for pancreas segmentation into head, body, and tail subregions in abdominal MRI. STUDY TYPE: Retrospective. SUBJECTS: One hundred and fifty nominally healthy subjects from UK Biobank (100 subjects for method development and 50 subjects for validation). A separate 390 UK Biobank triples of subjects including type 2 diabetes mellitus (T2DM) subjects and matched nondiabetics. FIELD STRENGTH/SEQUENCE: A 1.5 T, three-dimensional two-point Dixon sequence (for segmentation and volume assessment) and a two-dimensional axial multiecho gradient-recalled echo sequence. ASSESSMENT: Pancreas segments were annotated by four raters on the validation cohort. Intrarater agreement and interrater agreement were reported using Dice overlap (Dice similarity coefficient [DSC]). A segmentation method based on template registration was developed and evaluated against annotations. Results on regional pancreatic fat assessment are also presented, by intersecting the three-dimensional parts segmentation with one available proton density fat fraction (PDFF) image. STATISTICAL TEST: Wilcoxon signed rank test and Mann-Whitney U-test for comparisons. DSC and volume differences for evaluation. A P value < 0.05 was considered statistically significant. RESULTS: Good intrarater (DSC mean, head: 0.982, body: 0.940, tail: 0.961) agreement and interrater (DSC mean, head: 0.968, body: 0.905, tail: 0.943) agreement were observed. No differences (DSC, head: P = 0.4358, body: P = 0.0992, tail: P = 0.1080) were observed between the manual annotations and our method's segmentations (DSC mean, head: 0.965, body: 0.893, tail: 0.934). Pancreatic body PDFF was different between T2DM and nondiabetics matched by body mass index. DATA CONCLUSION: The developed segmentation's performance was no different from manual annotations. Application on type 2 diabetes subjects showed potential for assessing pancreatic disease heterogeneity. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 3.

Determination of oxygen relaxivity in oxygen nanobubbles at 3 and 7 Tesla.

OBJECTIVE: Oxygen-loaded nanobubbles have shown potential for reducing tumour hypoxia and improving treatment outcomes, however, it remains difficult to noninvasively measure the changes in partial pressure of oxygen (PO2) in vivo. The linear relationship between PO2 and longitudinal relaxation rate (R1) has been used to noninvasively infer PO2 in vitreous and cerebrospinal fluid, and therefore, this experiment aimed to investigate whether R1 is a suitable measurement to study oxygen delivery from such oxygen carriers. METHODS: T1 mapping was used to measure R1 in phantoms containing nanobubbles with varied PO2 to measure the relaxivity of oxygen (r1Ox) in the phantoms at 7 and 3 T. These measurements were used to estimate the limit of detection (LOD) in two experimental settings: preclinical 7 T and clinical 3 T MRI. RESULTS: The r1Ox in the nanobubble solution was 0.00057 and 0.000235 s-1/mmHg, corresponding to a LOD of 111 and 103 mmHg with 95% confidence at 7 and 3 T, respectively. CONCLUSION: This suggests that T1 mapping could provide a noninvasive method of measuring a > 100 mmHg oxygen delivery from therapeutic nanobubbles.

PyPlr: A versatile, integrated system of hardware and software for researching the human pupillary light reflex.

We introduce PyPlr-a versatile, integrated system of hardware and software to support a broad spectrum of research applications concerning the human pupillary light reflex (PLR). PyPlr is a custom Python library for integrating a research-grade video-based eye-tracker system with a light source and streamlining stimulus design, optimisation and delivery, device synchronisation, and extraction, cleaning, and analysis of pupil data. We additionally describe how full-field, homogenous stimulation of the retina can be realised with a low-cost integrating sphere that serves as an alternative to a more complex Maxwellian view setup. Users can integrate their own light source, but we provide full native software support for a high-end, commercial research-grade 10-primary light engine that offers advanced control over the temporal and spectral properties of light stimuli as well as spectral calibration utilities. Here, we describe the hardware and software in detail and demonstrate its capabilities with two example applications: (1) pupillometer-style measurement and parametrisation of the PLR to flashes of white light, and (2) comparing the post-illumination pupil response (PIPR) to flashes of long and short-wavelength light. The system holds promise for researchers who would favour a flexible approach to studying the PLR and the ability to employ a wide range of temporally and spectrally varying stimuli, including simple narrowband stimuli.

Delayed ventilation assessment using fast dynamic hyperpolarised Xenon-129 magnetic resonance imaging.

OBJECTIVES: To investigate the use of a fast dynamic hyperpolarised 129Xe ventilation magnetic resonance imaging (DXeV-MRI) method for detecting and quantifying delayed ventilation in patients with chronic obstructive pulmonary disease (COPD). METHODS: Three male participants (age range 31-43) with healthy lungs and 15 patients (M/F = 12:3, age range = 48-73) with COPD (stages II-IV) underwent spirometry tests, quantitative chest computed tomography (QCT), and DXeV-MRI at 1.5-Tesla. Regional delayed ventilation was captured by measuring the temporal signal change in each lung region of interest (ROI) in comparison to that in the trachea. In addition to its qualitative assessment through visual inspection by a clinical radiologist, delayed ventilation was quantitatively captured by calculating a covariance measurement of the lung ROI and trachea signals, and quantified using both the time delay, and the difference between the integrated areas covered by the signal-time curves of the two signals. RESULTS: Regional temporal ventilation, consistent with the expected physiological changes across a free breathing cycle, was demonstrated with DXeV-MRI in all patients. Delayed ventilation was observed in 13 of the 15 COPD patients and involved variable lung ROIs. This was in contrast to the control group, where no delayed ventilation was demonstrated (p = 0.0173). CONCLUSIONS: DXeV-MRI offers a non-invasive way of detecting and quantifying delayed ventilation in patients with COPD, and provides physiological information on regional pulmonary function during a full breathing cycle. KEY POINTS: • Dynamic xenon MRI allows for the non-invasive detection and measurement of delayed ventilation in COPD patients. • Dynamic xenon MRI during a free breathing cycle can provide unique information about pulmonary physiology and pulmonary disease pathophysiology. • With further validation, dynamic xenon MRI could offer a non-invasive way of measuring collateral ventilation which can then be used to guide lung volume reduction therapy (LVRT) for certain COPD patients.

Multiparametric measurement of cerebral physiology using calibrated fMRI.

The ultimate goal of calibrated fMRI is the quantitative imaging of oxygen metabolism (CMRO2), and this has been the focus of numerous methods and approaches. However, one underappreciated aspect of this quest is that in the drive to measure CMRO2, many other physiological parameters of interest are often acquired along the way. This can significantly increase the value of the dataset, providing greater information that is clinically relevant, or detail that can disambiguate the cause of signal variations. This can also be somewhat of a double-edged sword: calibrated fMRI experiments combine multiple parameters into a physiological model that requires multiple steps, thereby providing more opportunity for error propagation and increasing the noise and error of the final derived values. As with all measurements, there is a trade-off between imaging time, spatial resolution, coverage, and accuracy. In this review, we provide a brief overview of the benefits and pitfalls of extracting multiparametric measurements of cerebral physiology through calibrated fMRI experiments.

Fast dynamic ventilation MRI of hyperpolarized 129 Xe using spiral imaging.

PURPOSE: To develop and optimize a rapid dynamic hyperpolarized 129 Xe ventilation (DXeV) MRI protocol and investigate the feasibility of capturing pulmonary signal-time curves in human lungs. THEORY AND METHODS: Spiral k-space trajectories were designed with the number of interleaves Nint = 1, 2, 4, and 8 corresponding to voxel sizes of 8 mm, 5 mm, 4 mm, and 2.5 mm, respectively, for field of view = 15 cm. DXeV images were acquired from a gas-flow phantom to investigate the ability of Nint = 1, 2, 4, and 8 to capture signal-time curves. A finite element model was constructed to investigate gas-flow dynamics corroborating the experimental signal-time curves. DXeV images were also carried out in six subjects (three healthy and three chronic obstructive pulmonary disease subjects). RESULTS: DXeV images and numerical modelling of signal-time curves permitted the quantification of temporal and spatial resolutions for different numbers of spiral interleaves. The two-interleaved spiral (Nint = 2) was found to be the most time-efficient to obtain DXeV images and signal-time curves of whole lungs with a temporal resolution of 624 ms for 13 slices. Signal-time curves were well matched in three healthy volunteers. The Spearman's correlations of chronic obstructive pulmonary disease subjects were statistically different from three healthy subjects (P < 0.05). CONCLUSION: The Nint = 2 spiral demonstrates the successful acquisition of DXeV images and signal-time curves in healthy subjects and chronic obstructive pulmonary disease patients. Magn Reson Med 79:2597-2606, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Monitoring cardiac and respiratory physiology during FMRI.

This article will consider how physiological monitoring can be used both as an intrinsic part of an experiment, or for removing unwanted physiological signals from the FMRI time series. As functional MRI is used for a wide variety of applications beyond the identification of regions involved in a task, different sources of noise in the time series become important. The use of arterial spin labelling sequences, either in isolation or combined with BOLD imaging, means that temporal noise must be dealt with differently. Moreover, when these are combined with global cerebrovascular stimuli, such as respiratory challenges, the standard analysis tools must be employed with great care so as not to detrimentally distort the data. Acquiring and analysing physiological data is sometimes more art than science, and this article attempts to provide some insight into common techniques as well as advice on identifying and correcting some of the problems that may be encountered.

Rapid cerebrovascular reactivity mapping: Enabling vascular reactivity information to be routinely acquired.

Cerebrovascular reactivity mapping (CVR), using magnetic resonance imaging (MRI) and carbon dioxide as a stimulus, provides useful information on how cerebral blood vessels react under stress. This information has proven to be useful in the study of vascular disorders, dementia and healthy ageing. However, clinical adoption of this form of CVR mapping has been hindered by relatively long scan durations of 7-12 min. By replacing the conventional block presentation of carbon dioxide enriched air with a sinusoidally modulated stimulus, the aim of this study was to investigate whether more clinically acceptable scan durations are possible. Firstly, the conventional block protocol was compared with a sinusoidal protocol of the same duration of 7 min. Estimates of the magnitude of the CVR signal (CVR magnitude) were found to be in good agreement between the stimulus protocols, but estimates of the relative timing of the CVR response (CVR phase) were not. Secondly, data from the sinusoidal protocol was reanalysed using decreasing amounts of data in the range 1-6 min. The CVR magnitude was found to tolerate this reduction in scan duration better than CVR phase. However, these analyses indicate that scan durations in the range of 3-5 min produce robust data.

Investigating the dependence of the calibration parameter M on echo time.

PURPOSE: The calculation of the calibration parameter M, which represents the maximum theoretically possible blood oxygen level dependent (BOLD) signal increase, is an essential intermediate step in any calibrated fMRI experiment. To better compare M values obtained across different studies, it is common to scale M values from their original BOLD echo time (TE) to a different echo time according to the theory that M is directly proportional to TE. To the best of our knowledge, this relationship has never been directly tested. THEORY AND METHODS: A pseudocontinuous arterial spin labeling sequence with five readouts (TE ranging from 20 to 78 ms) was implemented to test the relationship between M and TE, both with and without the application of flow crushing gradients. RESULTS: Both M and the BOLD signal were found to be linear functions of TE, but with a nonzero intercept. This intercept was reduced when crusher gradients were added, suggesting that the deviation from theory is a result of nonnegligible intravascular signal. CONCLUSION: The linear scaling method introduces some error when comparing M values acquired with different BOLD echo times. However, this error is small compared with other considerations, and would generally not preclude the continued use of this scaling method.

Hyperoxia and Functional MRI.

Oxygen plays a fundamental role in functional magnetic resonance imaging (FMRI). Blood oxygenation level-dependent (BOLD) imaging is the foundation stone of all FMRI and is still the essential workhorse of the vast majority of FMRI procedures. Hemoglobin may provide the magnetic properties that allow the technique to work, but it is oxygen that allows the contrast to effectively be switched on or off, and it is oxygen that we are interested in tracking in order to observe the oxygen metabolism changes. In general the changes in venous oxygen saturation are observed in order to infer changes in the correlated mechanisms, which can include changes in cerebral blood flow, metabolism, and the fraction of inspired oxygen. By independently manipulating the fraction of inspired oxygen it is possible to alter the amount of dissolved oxygen in the plasma, the venous saturation, or even the blood flow. The effects that these changes have on the observed MRI signal can be either a help or a hindrance depending on how well the changes induced are understood. The administration of supplemental inspired oxygen is in a unique position to provide a flexible, noninvasive, inexpensive, patient-friendly addition to the MRI toolkit to enable investigations to look beyond statistics and regions of interest, and actually produce calibrated, targeted measurements of blood flow, metabolism or pathology.

Sources of systematic error in calibrated BOLD based mapping of baseline oxygen extraction fraction.

Recently a new class of calibrated blood oxygen level dependent (BOLD) functional magnetic resonance imaging (MRI) methods were introduced to quantitatively measure the baseline oxygen extraction fraction (OEF). These methods rely on two respiratory challenges and a mathematical model of the resultant changes in the BOLD functional MRI signal to estimate the OEF. However, this mathematical model does not include all of the effects that contribute to the BOLD signal, it relies on several physiological assumptions and it may be affected by intersubject physiological variability. The aim of this study was to investigate these sources of systematic error and their effect on estimating the OEF. This was achieved through simulation using a detailed model of the BOLD signal. Large ranges for intersubject variability in baseline physiological parameters such as haematocrit and cerebral blood volume were considered. Despite this the uncertainty in the relationship between the measured BOLD signals and the OEF was relatively low. Investigations of the physiological assumptions that underlie the mathematical model revealed that OEF measurements are likely to be overestimated if oxygen metabolism changes during hypercapnia or cerebral blood flow changes under hyperoxia. Hypoxic hypoxia was predicted to result in an underestimation of the OEF, whilst anaemic hypoxia was found to have only a minimal effect.

Investigating the field-dependence of the Davis model: Calibrated fMRI at 1.5, 3 and 7T.

Gas calibrated fMRI in its most common form uses hypercapnia in conjunction with the Davis model to quantify relative changes in the cerebral rate of oxygen consumption (CMRO2) in response to a functional stimulus. It is most commonly carried out at 3T but, as 7T research scanners are becoming more widespread and the majority of clinical scanners are still 1.5T systems, it is important to investigate whether the model used remains accurate across this range of field strengths. Ten subjects were scanned at 1.5, 3 and 7T whilst performing a bilateral finger-tapping task as part of a calibrated fMRI protocol, and the results were compared to a detailed signal model. Simulations predicted an increase in value and variation in the calibration parameter M with field strength. Two methods of defining experimental regions of interest (ROIs) were investigated, based on (a) BOLD signal and (b) BOLD responses within grey matter only. M values from the latter ROI were in closer agreement with theoretical predictions; however, reassuringly, ROI choice had less impact on CMRO2 than on M estimates. Relative changes in CMRO2 during motor tasks at 3 and 7T were in good agreement but were over-estimated at 1.5T as a result of the lower signal to noise ratio. This result is encouraging for future studies at 7T, but also highlights the impact of imaging and analysis choices (such as ASL sequence and ROI definition) on the calibration parameter M and on the calculation of CMRO2.

Reduced cerebrovascular reactivity in young adults carrying the APOE ε4 allele.

BACKGROUND: Functional magnetic resonance imaging (MRI) studies have shown that APOE ε2- and ε4-carriers have similar patterns of blood-oxygenation-level-dependent (BOLD) activation suggesting that we need to look beyond the BOLD signal to link APOE's effect on the brain to Alzheimer's disease (AD)-risk. METHODS: We evaluated APOE-related differences in BOLD activation in response to a memory task, cerebrovascular reactivity using a CO2-inhalation challenge (CO2-CVR), and the potential contribution of CO2-CVR to the BOLD signal. RESULTS: APOE ε4-carriers had the highest task-related hippocampal BOLD signal relative to non-carriers. The largest differences in CO2-CVR were between ε2- and ε4-carriers, with the latter having the lowest values. Genotype differences in CO2-CVR accounted for ∼70% of hippocampal BOLD differences between groups. CONCLUSION: Because CO2-CVR gauges vascular health, the differential effect of APOE in young adults may reflect a vascular contribution to the vulnerability of ε4-carriers to late-life pathology. Studies confirming our findings are warranted.

MRI measurement of oxygen extraction fraction, mean vessel size and cerebral blood volume using serial hyperoxia and hypercapnia.

Functional magnetic resonance imaging measures signal increases arising from a variety of interrelated effects and physiological sources. Recently there has been some success in disentangling this signal in order to quantify baseline physiological parameters, including the resting oxygen extraction fraction (OEF), cerebral blood volume (CBV) and mean vessel size. However, due to the complicated nature of the signal, each of these methods relies on certain physiological assumptions to derive a solution. In this work we present a framework for the simultaneous, voxelwise measurement of these three parameters. The proposed method removes the assumption of a fixed vessel size from the quantification of OEF and CBV, while simultaneously removing the need for an assumed OEF in the calculation of vessel size. The new framework is explored through simulations and validated with a pilot study in healthy volunteers. The MRI protocol uses a combined hyperoxia and hypercapnia paradigm with a modified spin labelling sequence collecting multi-slice gradient echo and spin echo data.

An analysis of the use of hyperoxia for measuring venous cerebral blood volume: comparison of the existing method with a new analysis approach.

Hyperoxia is known to cause an increase in the blood oxygenation level dependent (BOLD) signal that is primarily localised to the venous vasculature. This contrast mechanism has been proposed as a way to measure venous cerebral blood volume (CBVv) without the need for more invasive contrast media. In the existing method the analysis modelled the data as a dynamic contrast agent experiment, with the assumption that the BOLD signal of tissue was dominated by intravascular signal. The effects on the accuracy of the method due to extravascular BOLD signal changes, as well as signal modulation by intersubject differences in baseline physiology, such as haematocrit and oxygen extraction fraction, have so far been unexplored. In this study the effect of extravascular signal and intersubject physiological variability was investigated by simulating the hyperoxia CBVv experiment using a detailed BOLD signal model. This analysis revealed substantial uncertainty in the measurement of CBVv using the existing analysis based on dynamic contrast agent experiments. Instead, the modelling showed a simple and direct relationship between the BOLD signal change and CBVv, and an alternative analysis method with much reduced uncertainty was proposed based on this finding. Both methods were tested experimentally, with the new method producing results that are consistent with the limited literature in this area.

The impact of Alzheimer's disease risk factors on the pupillary light response.

Alzheimer's disease (AD) is the leading cause of dementia, and its prevalence is increasing and is expected to continue to increase over the next few decades. Because of this, there is an urgent requirement to determine a way to diagnose the disease, and to target interventions to delay and ideally stop the onset of symptoms, specifically those impacting cognition and daily livelihood. The pupillary light response (PLR) is controlled by the sympathetic and parasympathetic branches of the autonomic nervous system, and impairments to the pupillary light response (PLR) have been related to AD. However, most of these studies that assess the PLR occur in patients who have already been diagnosed with AD, rather than those who are at a higher risk for the disease but without a diagnosis. Determining whether the PLR is similarly impaired in subjects before an AD diagnosis is made and before cognitive symptoms of the disease begin, is an important step before using the PLR as a diagnostic tool. Specifically, identifying whether the PLR is impaired in specific at-risk groups, considering both genetic and non-genetic risk factors, is imperative. It is possible that the PLR may be impaired in association with some risk factors but not others, potentially indicating different pathways to neurodegeneration that could be distinguished using PLR. In this work, we review the most common genetic and lifestyle-based risk factors for AD and identify established relationships between these risk factors and the PLR. The evidence here shows that many AD risk factors, including traumatic brain injury, ocular and intracranial hypertension, alcohol consumption, depression, and diabetes, are directly related to changes in the PLR. Other risk factors currently lack sufficient literature to make any conclusions relating directly to the PLR but have shown links to impairments in the parasympathetic nervous system; further research should be conducted in these risk factors and their relation to the PLR.