We have developed an accurate, non-invasive, and easy-to-use method to quantify endothelial permeability and dysfunction in the arteries using Magnetic Resonance Imaging (MRI), named qMETRIC. This technique enables assessing vascular damage and cardiovascular risk associated with atherosclerosis in preclinical models and humans.
Cardiovascular diseases are the leading causes of death worldwide. A permeable/leaky and dysfunctional endothelium is considered the earliest marker of vascular damage and thought to drive atherosclerosis. A method to identify these changes in vivo would be desirable in the clinic. Magnetic resonance imaging (MRI)-based tools and other technologies have enabled a profound understanding of the role of the endothelium in cardiovascular diseases and risk in vivo. There is, however, a need for reproducible and simple approaches for extracting quantifiable data reflective of endothelial damage from a single imaging study. A non-invasive, easy-to-implement, and quantitative MRI workflow was developed to acquire and analyze images that allow the quantification of two imaging biomarkers of arterial endothelial damage (leakiness/permeability and dysfunction). Here, the protocol describes the application of this method in the brachiocephalic artery of atherosclerotic ApoE-/- mice using a clinical MRI scanner. First, late gadolinium enhancement (LGE) and Modified Look-Locker Inversion Recovery (MOLLI) T1 mapping protocols to quantify endothelial leakage using an albumin-binding probe are described. Second, anatomic, and quantitative blood flow sequences to measure endothelial dysfunction, in response to acetylcholine are described. Importantly, the method outlined here allows the acquisition of high-spatial-resolution 3D images with large volumetric coverage enabling accurate segmentation of vessel wall structures to improve inter- and intra-observer variability and to increase reliability and reproducibility. Additionally, it provides quantitative data without the need for high-temporal resolution for complex kinetic modeling, making it model-independent and even allowing for imaging of highly mobile vessels (coronary arteries). Therefore, the approach simplifies and expedites data analysis. Finally, this method can be implemented on different scanners, can be extended to image different arterial beds, and is clinically applicable for use in humans. This method could be used to diagnose and treat patients with atherosclerosis by adopting a precision-medicine approach.
Cardiovascular diseases (CVDs) remain the leading cause of mortality and morbidity worldwide, accounting for nearly one-third of deaths1, and the cause of lifelong disabilities that exert a high financial cost on the healthcare systems1. Among CVDs, ischaemic heart disease and stroke are primarily caused by atherosclerotic plaques. Atherosclerosis is a multifactorial disease; however, a common hallmark is early damage of the vascular endothelial cells that lead to the formation, progression, and eventual complications of atherosclerosis. An intact vascular endothelium has fundamental vasculo-protective properties2. The endothelium regulates vascular permeability by controlling translocation of cells and molecules between the systemic circulation and the vessel wall; controls vascular tone by balancing the production of vasodilators (e.g., nitric oxide, prostacyclin) and vasoconstrictors (e.g., endothelin-1, angiotensin II); and also has anti-coagulant properties. However, both the function and permeability of the endothelial cells can deteriorate in the presence of cardiovascular risk factors (e.g., smoking, high cholesterol, diabetes, systemic inflammation, oxidative stress) and by blood flow hemodynamic patterns. A dysfunctional endothelium has reduced vasodilation in response to stressors, consequently increasing arterial stiffness. In addition, a permeable/leaky endothelium has widened tight gap junctions between adjacent cells3,4,5,6,7. Such change occurs both on the luminal endothelium and newly-formed plaque microvessels that appear fragile, leaky, and dysmorphic8. Permeable endothelial cells act as entry points for plasma-borne molecules and cells-exacerbating the risk of cardiovascular disease.
Building on this knowledge, in the past 15 years, endothelial permeability and function has emerged as a promising imaging and therapeutic target to better diagnose subjects at risk for cardiovascular disease and to assess the effects of known or novel drugs. However, direct and quantitative imaging of endothelium function is limited9,10,11,12. Currently, much of the interpretation of endothelial function in vivo is based on studies of endothelial-dependent dilation (FMD) in peripheral vessels whose function modestly correlates with atherosclerosis burden in vascular beds that cause clinical events13,14,15. Only a limited number of imaging studies have shown a direct link between endothelial dysfunction and atherosclerosis burden in vivo9,10,11,12. Conversely, more accessible MRI-based approaches have enabled imaging endothelial permeability more widely. Using the percent vessel wall signal enhancement after administration of MRI gadolinium agents has provided a semi-quantitative measurement of endothelial permeability16,17. Later, the development of dynamic contrast-enhanced (DCE) protocols has permitted an improved and more quantitative measurement of vascular endothelial permeability. Quantitative parameters such as the contrast extravasation rate (Ktrans) and microvascular volume (Vρ) derived from kinetic modeling or the area under the curve (AUC), upslope, time to peak, and peak concentration extracted from non-modeled methods correlated not only with endothelial permeability but also plaque vascularity18,19,20. However, the application of vascular DCE remains challenging despite significant technical advances because: (i) it requires both high spatial (0.5-0.7 mm2) and temporal resolution21 for accurate delineation of the vessel wall. Sampling the concentration of contrast agent in the blood to calculate the arterial input function also requires kinetic modeling, which leads to a trade-off of either limiting anatomical coverage22,23 to gain temporal resolution or vice versa24,25; (ii) data analysis may require complex pharmacokinetic modeling (e.g., Patlak vs. Tofts); (iii) provides limited image quality, poor scan-rescan reproducibility, and average inter-observer and intra-observer variability26,27. Therefore, there is still a need for reproducible and simple approaches for extracting direct and quantifiable data of endothelial permeability and (dys)function from single imaging studies that could have better clinical utility.
Here, we have developed a non-invasive, easy-to-implement, and quantitative MRI to acquire and analyze images that allows direct quantification of two markers of arterial endothelial damage (leakiness/permeability and dysfunction) using preclinical models of atherosclerosis in a single scan. The method is named Quantitative MRI of EndoThelial peRmeabIlity and dysfunCtion (qMETRIC). It involves the acquisition of late gadolinium enhancement (LGE) and Modified Look-Locker Inversion Recovery (MOLLI) T1 mapping protocols to quantify endothelial leakage, after administration of an intravascular albumin-binding probe; and acquisition of anatomic and quantitative blood flow sequences to measure endothelial dysfunction, in response to an acetylcholine bolus. We have demonstrated that qMETRIC accurately detects: the severity of atherosclerosis and the risk of complications; treatment responses; and can be adapted for use in patients5,6,7. Importantly, the method outlined here allows the acquisition of high-spatial-resolution images to enable accurate segmentation of the vessel wall to minimize inter/intra-observer bias and to increase reliability and reproducibility with large anatomical coverage. Finally, this method can be adapted for use on different scanners and can be extended to image different arterial beds (even coronary arteries28). The straightforward workflow makes this approach more accessible to the cardiovascular imaging community.
All components of this study were carried out in accordance with the UK Animals (Scientific Procedures) Act, 1986, and with the approval of King's College London Ethical Review Panel.
The experimental workflow is summarized in Figure 1.
1. Animal preparation
2. Preparation of the MRI scanner (see Figure 1)
3. Animal positioning in the MRI scanner and monitoring (see Figure 2)
4. MRI image planning and acquisition
5. MRI segmentation and data analysis (see Figure 4)
In this report, the application of a Quantitative MRI method is demonstarted to measure EndoThelial peRmeabIlity and (dys)funCtion (qMETRIC) in the brachiocephalic artery of atherosclerotic ApoE-/- mice. This method provides direct and quantifiable data of two markers of endothelial damage – permeability and (dys)function, which can be extracted from in vivo vessel wall scans acquired within a single imaging session. First, LGE are used to measure the area of vessel wall enhancement (mm3), and T1 (or R1) maps are used to quantify the relaxation rate of the vessel wall (s-1) after administration of gadofosveset, both surrogate markers of permeability (see Figure 5 for representative results). The vessel wall R1 relaxation rate ranged from 2.42 s-1 ± 0.35 s-1 to 3.45 s-1 ± 0.54 s-1 to 3.83 s-1 ± 0.52 s-1 at 4 weeks, 8 weeks, and 12 weeks of a high-fat diet, respectively. Conversely, wild-type (R1 = 2.15 ± 0.34 s-1) and statin-treated ApoE-/- (R1 = 3.0 ± 0.65 s-1) mice showed less enhancement. In ApoE-/- mice fed with a high-fat diet for up to 12 months, the study shows with histological analysis, Evans Blue dye, and electron microscopy that endothelial permeability increases during atherosclerosis progression, which was in agreement with increased LGE vessel wall volume, increased change in vessel wall R1 relaxivity, and paradoxical vasoconstriction after acetylcholine injection5. Conversely, statin and other endothelium-targeting treatments decreased endothelial permeability and plaque size, which was reflected in smaller LGE volume, lower R1 values5,7, and improved vasodilation. Mechanistically, gadofosveset binds reversibly to serum albumin. This results in a 5-6-fold increase in the T1 relaxivity of the probe29-making it detectable by MRI with high sensitivity. Here, the study shows that bound to albumin, the uptake of the probe reflects endothelial leakiness because it correlates with the uptake of Evan's blue dye-a gold-standard ex vivo method of quantifying endothelial leakage (Figure 5) – and wider tight gap junctions5. Secondly, a simple test is demonstrated to measure endothelial (dys)function, in response to acetylcholine. In control vessels, acetylcholine causes endothelium-depended vascular relaxation leading to increased arterial area/volume and blood flow. To measure endothelial (dys)function, ECG-triggered angiography images acquired before and after administration of acetylcholine were used. The study calculates the change in the end-diastolic area (or volume) of the vessel lumen before and after the administration of acetylcholine. It was found that, unlike normal vessels that vasodilate in response to acetylcholine, atherosclerotic vessels demonstrate decreased endothelial-dependent vasodilatory function that manifests either as a reduced change in vessel area (or volume) or even paradoxical vasoconstriction of the vessel (Figure 5). Interestingly, statin treatment improved vasodilatory properties of the endothelium13.
Figure 1: Workflow to image endothelial permeability and (dys)function in atherosclerotic mice. (A–B) Mice are first anesthetized and then injected with the albumin contrast agent. (C) Mice are then transferred onto an MRI coil, where ECG pads are used to monitor cardiac activity. (D–E) MRI images are acquired to quantify endothelial permeability and (dys)function that are subsequently analyzed using an open-platform software (created with BioRender.com). Please click here to view a larger version of this figure.
Figure 2: Animal positioning and ECG monitoring to image endothelial permeability and (dys)function using a clinical 3 Tesla MRI scanner. (A–B) The animal is positioned prone on a surface coil and maintained anesthetized using inhalable isoflurane. Sandbags are used to stabilize the imaging platform. (C–D) ECG pads are placed on the paws and connected to a clinical ECG module to record cardiac activity. Please click here to view a larger version of this figure.
Figure 3: MRI planning and acquisition of images to quantify endothelial permeability and (dys)function in the brachiocephalic artery of atherosclerotic mice. (A) Scout images are acquired to identify the anatomical region between the aortic root and the carotid arteries. (B) The MR angiogram is used to visualize the vasculature and plan the subsequent scans. (C) Look-Locker images are acquired at the level of the brachiocephalic artery to determine the suitable time delay to null the signal from the blood in the subsequent later gadolinium enhancement images (LGE). (D) LGE images provide a visual assessment of vessel wall enhancement. (E) T1 mapping is used to calculate the vessel wall relaxation rate that is indicative of the concentration of gadolinium. (F) The endothelium-depended vasodilating properties of the vessel wall are quantified after the administration of acetylcholine. Please click here to view a larger version of this figure.
Figure 4: Image segmentation and analysis to quantify endothelial permeability and (dys)function in the brachiocephalic artery of atherosclerotic mice. (A) The vessel wall is manually segmented on the LGE images to quantify the area/volume of contrast uptake. (B) The vessel wall is segmented on the T1 mapping to calculate the vessel wall T1 relaxation rate. (C) The vessel wall segmented on the MR angiograms and blood flow encoded images is used to study the vasodilating properties of the vessel wall by calculating the changes in the changes in the end-
diastolic lumen area (or volume) and blood flow after administration of acetylcholine. Please click here to view a larger version of this figure.
Figure 5: Quantitative imaging of endothelial permeability and (dys)function (qMETRIC) in atherosclerotic mice. (A) LGE images and R1 relaxation maps show increased uptake of the albumin-binding contrast agent within the vessel wall during atherosclerosis progression and the improvement after statin treatment. Imaging data are corroborated by the accumulation of Evan's blue dye, an albumin-binding dye, ex vivo. (B) Changes in the vasodilating properties of the vessel wall, in response to acetylcholine administration, allow quantification of endothelial-dependent vasodilation. Control vessels vasodilate, whereas atherosclerotic vessels vasoconstrict in response to acetylcholine, suggestive of endothelial damage. Treatment with statin improves endothelial damage. The terms "wks" and "HFD" in the figure represents "weeks" and "high-fat diet", respectively. This figure has been modified from Phinikaridou, A. et al.5. Please click here to view a larger version of this figure.
Scan / Sequence | Acquisition parameters | ||
Scout / pilot scan | 3D, fast gradient echo Transverse: FOV = 50 mm x 27 mm x 14 mm, matrix = 96 x 52, in-plane resolution = 0.5 mm x 0.5 mm, slice thickness = 0.5 mm, TR/TE = 15/6.1 ms, flip angle = 30°, averages = 1 Coronal: FOV = 200 mm x 102 mm x 14 mm, matrix = 336 x 173, in-plane resolution= 0.5 mm x 0.5 mm, slice thickness = 0.5 mm, TR/TE = 12/6 ms, flip angle = 30°, averages = 1 |
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MRA scan | 3D fast gradient echo, FOV = 30 mm x 30 mm x 8 mm, matrix = 200 x 200, in-plane resolution =0.15 mm x 0.15 mm, slice thickness = 0.5 mm, TR/TE = 15/6.1 ms, flip angle = 40°, averages = 1 | ||
Look-Locker scan | 2D fast gradient echo, FOV = 30 mm x 30 mm, matrix = 80 x 80, in-plane resolution = 0.38 mm x 0.38 mm, slice thickness = 2 mm, TR/TE = 19/8.6 ms, TR between subsequent IR pulses = 1000 ms, and flip angle = 10°, averages = 1. | ||
LGE scan | 3D fast gradient echo, FOV = 30 mm x 30 mm x 8 mm, matrix = 304 x 304, in-plane resolution = 0.1mm x 0.1 mm, measured slice thickness = 0.5 mm, slices = 32, TR/TE = 28/8 ms, TR between subsequent IR pulses = 1000 ms, and flip angle = 30°, averages = 1. | ||
T1 mapping scan | 3D fast gradient echo , FOV = 36 mm x 22 mm x 8 mm, matrix = 192 x 102, in-plane resolution = 0.18 mm x 0.22 mm, measured slice thickness = 0.5 mm, slices = 16, TR/TE = 9.6/4.9 ms, flip angle = 10°, averages = 1. | ||
Phase contrast angiography scan | 2D, fast gradient echo, FOV = 40 mm x 23 mm, matrix = 132 x 77, in-plane resolution = 0.3 mm x 0.3 mm x 1 mm, TR/TE = 9.8/4.9 ms, flip angle = 30°, cardiac phases = 14, averages = 6, flow velocity (foot-head direction) = 30 cm/s. |
TABLE 1: MRI acquisition parameters
Determining vascular endothelial health is an attractive imaging biomarker that can potentially be used to diagnose atherosclerotic-related risk and to monitor treatment effects. The qMETRIC protocol outlined here can be used to reproducibly quantitate endothelial permeability/leakiness and (dys)function in a comprehensive, fast, and clinically applicable MRI protocol. Such an approach can provide a simpler alternative or complementary tool to existing DCE-MRI protocols for quantifying endothelial permeability. It can also provide a non-invasive tool for direct assessment of endothelial (dys)function in vascular beds, such as the coronary and carotid arteries, instead of using either invasive techniques or surrogate measurements in peripheral arteries that are less severely affected by the disease. Measuring endothelial permeability using this method allows coverage of the aorta, the aortic arch, and the brachiocephalic and carotid arteries at high spatial resolution (0.1 mm for the LGE images and 0.22 mm for T1 mapping) that is crucial for accurate segmentation of the vessel wall in rodents. Analysis of the images can be carried out using an open-source platform and requires only a simple segmentation of the vessel wall without the need for complex pharmacokinetic modeling. Importantly, this protocol can be adapted to be used in a number of different commercially available scanners and can be extended to be used in different animal models and also humans. Although this protocol describes the methodology using a clinical scanner setup, the MRI protocols can also be implemented when using high-field small animal scanners. These scanners frequently offer inversion recovery, T1 mapping, and angiography protocols that can be used or can be programmed in collaboration with the scanner manufacturers.
To obtain accurate and reproducible results, particular attention should be paid to some critical steps of the protocol. Firstly, when imaging small animals in a clinical scanner, suitable and custom-made receiver coils are necessary to maximize the signal-to-noise ratio for high image quality. The animal positioning on the coil is also crucial, avoiding separation and air-filled spaces between the animal and the coil to improve the signal-to-noise ratio. For this reason, the anatomical area of interest should be placed in the center of the coil, and then moved to the isocenter of the magnet to expose them to the magnetic field with maximum homogeneity. Secondly, a stable, strong, and accurate ECG signal is paramount for reliable imaging triggering/gating. This is important for consistent excitation of the magnetization and the timing of the image acquisition window at specific time points and for acquiring accurate time-resolved images that include the end-diastolic phase for the functional test. Small animal pad-based or needle-based electrodes are more suitable options when used at higher-field strength scanners, which are better shielded compared to clinical scanners. When these options are used at clinical field scanners, the ECG cables need to be warped together to avoid the formation of resonant circuits at the MRI Lamour frequency that may deteriorate the ECG signal during the pulse sequence. Alternatively, we propose the use of the ECG module and pads used for human scans with adjustment of the pad size to that of the mouse paw and extra stabilization of the pads with tape to improve conductivity. Thirdly, when acquiring LGE images while the contrast agent is still circulating in the bloodstream, it is crucial to choose the correct nulling time to efficiently suppress the blood pool to delineate the vessel wall. A Look-locker sequence must be run before every LGE sequence, and the inversion delay time needs to be adjusted accordingly. Fourthly, for accurate and precise T1 mapping using a modified look-locker inversion recovery (MOLLI) sequence, the proposed image acquisition scheme should be implemented to cover a range of inversion delays ranging at least from 20 ms to 2000 ms to capture the short and long T1 species. Lastly, segmentation of MRI data must be rigorous and strict criteria applied to avoid intra and/or inter-observer biases in the area/volume and T1 value calculations.
Unlike DCE-MRI, the procedure described here does not provide kinetic data of the wash-in and wash-out of the contrast agent in the vessel wall. Rather, it provides a snapshot of endothelial permeability at a specific time point after injection of the albumin-binding contrast agent, gadofosveset. However, the extracted quantitative data from these time-points highly correlated with other albumin-dyes, such as Evan’s blue dye, which is considered a gold-standard to measure endothelial permeability and increased endothelial gap-junction width. Mechanistically, both the albumin-bound and unbound-fraction of gadofosveset are small enough to pass through breaks in the endothelial junctions and lead to MRI signal enhancement. Additionally, it is possible that the unbound-fraction may also bind to intraplaque albumin after it enters the vessel wall and results in signal enhancement. It was observed that the relaxivity of the vessel wall is r1≈17 mmol/L/s, when gadofosveset is injected at a clinical dose. This value is closer to that reported for the albumin-bound fraction (r1≈25 mmol/L/s) compared to the free-fraction (r1≈6.6 mmol/L/s)5,29.
Future applications of this imaging method include basic science studies in different animal models and other arterial segments and the use of this method to assess for biological responses to existing or novel pharmaceutical agents. Studies can be performed either cross-sectionally or longitudinally to gather mechanistic and outcome data, respectively. The straightforward workflow makes this approach accessible and clinically applicable for use in humans also. Adaptation of this method for imaging human carotid and peripheral arteries is more imminent, but the application of this method for imaging the coronary arteries requires further advancements in image acquisition, reconstruction, and motion-correction that are currently being developed30,31.
The authors have nothing to disclose.
We are grateful for funding to the: (1) British Heart Foundation (A.P Early Career Development Fellowship, Project grant-PG/2019/34897, and R.M.B. Project and Programme grants PG/10/044/28343, RG/12/1/29262 and RG/20/1/34802); (2) the King's BHF Centre for Research Excellence RE/18/2/34213; (3) the Wellcome EPSRC Centre for Medical Engineering (NS/A000049/1); (4) the Department of Health via the National Institute for Health Research (NIHR) Cardiovascular Health Technology Cooperative (HTC) and comprehensive Biomedical Research Centre awarded to Guy's & St Thomas' NHS Foundation Trust in partnership with King's College London and King's College Hospital NHS Foundation Trust; (5) Chilean Agency for Research and Development (ANID) – Millennium Science Initiative Program – NCN17_129 and FONDECYT 1180525.
Acetylcholine | Sigma Aldrich | A6625- 100G, 16.6 mg/kg | |
Anesthesia equipment | General Anesthetic Services | General Anesthetic Services | |
Circulating heating pump | ThermoFisher Scientific, USA | BOM: 152510101 | |
ECG conductive gel (Nuprep) | Waever and Company, USA | 10-30-T | |
ECG monitoring module | Invivo, USA | REF 0700-1002 | |
Gadofosveset trisordium (Vasovist/ Ablavar) | Lantheus Medical Imaging Inc, North Billerica, MA, USA | 0.03 mmol/kg | |
High fat diet | Special Diets Services, Witham, UK | 21% fat from lard, 0.15% (wt/wt) cholesterol | |
Induction box | Vet Tech Solutions LTD | ||
Insulin syringes | BD Biosciences | 0.5 mL, 29 G | |
OsirixX software | OsiriX Foundation, Geneva, Switzerland | Open-source platform | |
Philips Achieva MRI Scanner (3 Tesla) | Philips Healthcare, Best, The Netherlands | Equipped with a clinical gradient system (30 mT m-1, 200 mT m-1 ms-1) | |
Single–loop surface microscopy receiver coil | Phillips Hamburg | Diameter = 23 mm | Custom built |
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