Molecular imaging of coronary plaque vulnerability using 18F- fluorocholine PET-MRI in patients with coronary artery disease: validation with optical coherence tomography

doi:10.21203/rs.3.rs-4686936/v1

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Research Article

Molecular imaging of coronary plaque vulnerability using 18F- fluorocholine PET-MRI in patients with coronary artery disease: validation with optical coherence tomography

https://doi.org/10.21203/rs.3.rs-4686936/v1

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Purpose

¹⁸F-fluorocholine is a positron emission tomography (PET) tracer earlier found to be a marker of macrophage content in carotid plaques. We aimed to assess the feasibility of ¹⁸F-choline PET-MRI to non-invasively localize vulnerable coronary plaques, using optical coherence tomography (OCT) as reference standard.

Methods

Patients with recent myocardial infarction who were scheduled for a secondary angiography of a non-culprit vessel, underwent ¹⁸F-fluorocholine coronary PET-MRI. Subsequently, OCT was performed during the secondary angiography. Maximum target-to-background (TBRmax) values of ¹⁸F-fluorocholine uptake were determined in two vessel sections that contained either vulnerable or stable plaques as defined by OCT. The OCT-based definition of a vulnerable plaque was a fibrous cap thickness <70µm. To enhance the detectability of coronary plaques using PET, three different motion-correction strategies were used: multigate respiratory gating motion correction (MRG-MOCO), extended MR-based motion correction (eMR-MOCO), and extended MR-based motion correction with ECG gating (eMR-MOCO-ECG).

Results

Fifteen patients were included in this study, of which eleven entered final analyses. Data of the other four subjects could only be partially analysed. TBRmax values were as follows for three different reconstructions in vulnerable versus stable plaques: MRG-MOCO: mean TBRmax 1.45 vs 1.35, p=0.52; eMR-MOCO mean TBRmax 1.47 vs 1.27, p= 0.26, eMR-MOCO-ECG: mean TBRmax 1.49 vs 1.26, p= 0.21.

Conclusion

¹⁸F-fluorocholine uptake in vulnerable atherosclerotic plaques in coronary arteries was not significantly different from uptake in stable plaques even though advanced motion-correction methods were applied. That may be caused by multiple factors, such as small coronary plaque size and remaining cardiac motion.

fluorocholine

PET-MRI

optical coherence tomography

plaque imaging

atherosclerosis

Atherosclerosis is a progressive, chronic, inflammatory disease with systemic manifestations affecting large and medium-sized arteries. As a result, fatty streaks or plaques are formed inside these arteries that can narrow them over time. Such plaques can erode over time or even suddenly rupture, thereby potentially causing a thrombotic occlusion of the vessel and obstructing the blood flow. The majority of myocardial infarctions (MI) are caused by such thrombotic events.[1] Although atherosclerotic plaques have certain pathological characteristics, such as positive remodelling, micro-calcification, and a large necrotic core, identification of vulnerable plaques remains challenging.[2,3]

Previously, it was shown that implementing cardiac magnetic resonance (CMR) or computed tomography angiography (CTA) in the diagnostic process in NSTEMI patients is a safe gatekeeper for (therapeutic) invasive coronary angiography (ICA).[4] Regardless, the risk of recurrent MI remains approximately 10% within the first year and 5% in each of the subsequent 4 years.[5,6] This is most likely an underestimation, because 17-26% of recurrent plaque ruptures and MI remain clinically silent.[7] The high recurrence rate could be attributable to inaccurate angiographic identification of vulnerable plaques resulting in inadequate treatment.[8-10] The situation is worsened by the fact that vulnerable plaques tend to occur at multiple coronary sites in approximately 40% of the patients.[10] Furthermore, it is known that ‘high-risk’ lesions that are anatomically unrelated to the initial event are often responsible for recurrent ischemic events.[10,11] Thus, performing angioplasty of only a single lesion may be an insufficient preventive measure.

Non-invasive imaging techniques, such as position emission tomography (PET), have the advantage that they can be used longitudinally and allow studying the natural behaviour of vulnerable plaques. Nowadays, hybrid PET-MRI scanners exist that combine the advantages of molecular imaging using PET with the superior soft tissue contrast of magnetic resonance imaging (MRI).[12] Hybrid PET-MRI also provides a unique opportunity to apply MRI-based respiratory motion correction on both MRI and PET images. Munoz et al. showed that a non-rigid respiratory motion-compensated coronary magnetic resonance angiography approach enabled respiratory motion-correction of the hybrid MRI as well as the PET images. [13]

Among the available radioactive PET tracers, ¹⁸F-fluorodeoxyglucose (FDG) is mostly used in oncology but has also proven its value in imaging inflammatory changes of the arterial wall. However, since FDG remains a more unspecific inflammation tracer and has several drawbacks in imaging the coronary arteries, e. g. physiological uptake in the myocardium. Recent evidence suggests that other more specific tracers may be used for metabolic imaging of cell activation, especially in macrophages.[14] Earlier studies demonstrated the feasibility of radiolabeled-choline for imaging atherosclerosis, showing ¹⁸F-fluorocholine PET being able to identify the inflammatory regions in symptomatic carotid artery plaques with a significant correlation between tracer uptake and macrophage content on histology.[15]

In contrast to hybrid PET-MRI, optical coherence tomography (OCT) is an invasive imaging technique that is able to provide detailed images of coronary plaques with a resolution ranging from 10 to 20 micrometers, which is approximately 50-100 times higher than what can be achieved using MRI or intravascular ultrasound (IVUS). Due to its superior spatial resolution, OCT can identify a key feature of coronary plaque vulnerability, i.e. the presence of a thin fibrous cap [16]. OCT already proved its usefulness in numerous studies and is therefore considered a reference standard [16-18].

In the present feasibility study, we will investigate whether non-invasive ¹⁸F-fluorocholine PET-MRI can be used to identify vulnerable atherosclerotic plaques in the coronary arteries. We will test the hypothesis that vulnerable plaques show a locally increased uptake of ¹⁸F-fluorocholine on PET-MRI compared to stable plaques using invasive OCT as reference standard.

Study population

Subjects who presented with non-ST elevation myocardial infarction (NSTEMI) at the VieCuri hospital in Venlo, underwent percutaneous coronary intervention (PCI) of the culprit vessel, and were diagnosed with multivessel coronary artery disease and subsequently scheduled for a second PCI, were recruited for study participation. NSTEMI was defined as ischemic symptoms with elevated cardiac enzymes (Troponin T/I, creatin kinase-MB), however, in absence of ST-segment elevations in the ECG. Exclusion criteria were conservatively managed patients not scheduled for PCI, ongoing severe ischaemia requiring immediate PCI, hemodynamic instability, severe heart failure (Killip Class ≥ III), chest pain highly suggestive of non-cardiac origin, suspicion or evidence of acute aortic dissection, acute pulmonary embolism, acute pericarditis, life threatening arrhythmias at the cardiac emergency department or before presentation, tachycardia (>100bpm), angina pectoris secondary to anaemia, untreated hyperthyroidism or severe hypertension (>200/110 mmHg), moderate to severe aortic or mitral valve stenosis, pregnancy, breast feeding and contra-indications for MRI, including metal implants, cardiac implantable devices, claustrophobia, renal failure and allergy to gadolinium-containing contrast media. This study was approved by the local ethics committee (METC162043 / NL58752.068.16) and conducted according to the declarations of Helsinki. All subjects were 18 years or older and provided written informed consent.

PET-MR imaging

After the first PCI procedure in the acute setting and within 72 hours of the scheduled second PCI procedure, hybrid PET-MRI imaging was performed on a fully-integrated combined 3 Tesla PET-MRI system (Biograph mMR; Siemens Healthineers, Erlangen, Germany) at the Maastricht University Medical Centre. Subjects were scanned in headfirst supine position using a 6-channel body matrix and the 12-channel spine radiofrequency coils. First, an MRI-based attenuation map (µ-map) was acquired during an end-expiration breath-hold.[18] Relevant parameters of this Dixon-based µ-map include: field-of-view (FOV) = 599 x 271 x 408 mm³, acquired resolution = 2.1 x 2.1 x 2.6 mm³, flip angle = 10°, repetition time (TR) = 3.85 msec, and echo time (TE) =2.46 msec. Following the µ-map acquisition, the ¹⁸F-fluorocholine PET tracer (BV Cyclotron VU, Amsterdam, the Netherlands) was intravenously injected with a dose of 4 MBq/kg (up to a maximum dose of 360 MBq). Five minutes after PET tracer injection, a static list-mode PET acquisition was started while the respiratory signal was recorded using the respiratory belt. Previous research in the carotid artery showed stable FCH uptake from 10 minutes until 1 hour after injection in both symptomatic and asymptomatic carotid artery, as well as in vascular background. [15]

Simultaneously during PET acquisition, coronary MR angiography (CMRA) was performed 2 minutes after an intravenous contrast agent injection of 0.2 mmol/kg gadobutrol (Gadovist; Bayer Pharmaceuticals, Berlin, Germany), up to a maximum of 20 mmol. A 3D spoiled gradient-echo sequence with a fully sampled golden-step Cartesian trajectory with spiral profile ordering was used. Relevant sequence parameters include: FOV = 304 × 304 × 104 mm³, acquired resolution = 1.0 × 1.0 × 2.0 mm³, flip angle = 15°, TR = variable based on heart rate, TE = 1.7 msec, acquisition window ranging between 90 to 130 msec. Three-lead ECG registration was performed to allow for cardiac motion gating. Every heartbeat, just before each acquisition window, a 2D image navigator (iNAV) was acquired which provides a low-resolution image of the heart in coronal view to allow for subsequent motion correction. Details of this sequence have been previously described. [19]

OCT imaging

Within 72 hours after the hybrid PET-MRI scan, during the planned second PCI procedure at the VieCuri hospital in Venlo, OCT imaging of the secondary pathological vessel was performed before potential stent placement. Before entry in the coronary artery, an intracoronary injection of 100 to 200 µg nitroglycerine was provided. The tip of the OCT catheter (Dragonfly intravascular imaging catheter, St. Jude Medical, St. Paul, MN, USA) was then placed at least 5 mm distal to the distal edge of the lesion. While obtaining optimal blood clearance by flushing the coronary artery with contrast agent using an automated pump, an automatic pullback through the lesion was initiated, covering at least 5 mm of the proximal and distal parts of the vessel.

Image reconstruction

PET image reconstruction was performed with e7 Tools (Siemens Healthineers, Erlangen, Germany) using the ordinary Poisson-ordered subset expectation maximization (OP-OSEM) algorithm with 3 iterations and 21 subsets. Images were reconstructed with a voxel size of 2.08 x 2.08 x 2.03 mm³ and a matrix size of 344 x 344 x 127. For PET attenuation correction, MR-based Dixon µ-maps were used that provided separation between air, lung, fat, and soft tissue. To make up for the smaller FOV of MRI with respect to PET, the maximum likelihood reconstruction of attenuation and activity (MLAA) approach was utilized.

For CMRA motion correction,motion in the left-right (LR) and feet-head (FH) direction is estimated for each heartbeat using the apex of the heart in the iNAV images. Based on the amplitude in the FH direction, CMRA data is allocated to four respiratory phases or bins. k-space data inside each bin is corrected to the centre of the bin using the FH and LR position estimates derived from the iNav. Next, each bin is reconstructed. Using the end-expiration bin as a reference, respiratory non-rigid deformation fields are generated which are subsequently applied to transform each bin to the end-expiration position generating the motion-compensated CMRA image.[19]

Three different motion correction strategies were available to correct the PET datasets for respiratory motion: 1) Multiphase respiratory gating motion correction (MRG-MOCO), where motion correction was based solely on the respiratory belt signal as acquired during the entire PET acquisition. Only the PET data acquired during the end-expiration phase were used for image reconstruction. 2) Extended MR-based MOCO (eMR-MOCO), where both the iNav respiratory signal (as described earlier, but only available during ~ 9 minutes of CMRA imaging) and the respiratory belt signal (available entire PET acquisition) are used.[20] The time window for which both the iNav respiratory signal and respiratory belt signal was collected, was used to ensure that the binning of PET data on the iNav signal closely matches the binning on the respiratory belt signal by adjusting binning thresholds. These thresholds are then extended for respiratory motion correction of the complete duration of the PET scan. Each bin was reconstructed and combined with other bins using iNav-based motion fields to a reference position to create a respiratory motion-corrected dataset. 3) Finally, eMR-MOCO-ECG applied the combination of eMR-MOCO (strategy 2) and ECG-based cardiac gating to mitigate cardiac motion as well. Only PET data acquired during the end-diastolic phase, which was derived from CMRA sequence ,was used for eMR-MOCO-ECG reconstruction, other data was discarded.

Image analysis

The OCT data was analysed by an independent core lab (LIMIC Medical, Ridderkerk, the Netherlands) where fibrous cap thickness was determined in all plaques. Plaque vulnerability was defined as a plaque with a thin fibrous cap of ≤ 70 μm.[16] PET imaging was then co-registered with the CMRA images and analysed using MIM Vista (MIMsoftware, Cleveland, OH, USA). The OCT slice position of the vulnerable plaque was located on the 3D MRI, using vessel side branches as landmarks, by a cardiologist (BR) and nuclear medicine physician (JP). A volume of interest (VOI) was defined around the pathological vessel section. In the same vessel, a control lesion with a thick fibrous cap was selected on OCT, pinpointed on the MRI, and analysed using the same approach as described for the target lesion. The maximum standardized uptake value (SUVmax) was measured in both the target and control lesions. Target-to-background ratios (TBR) were calculated, by dividing SUVmax values of the target and control lesions by the mean standardized uptake value (SUVmean) of the blood pool in the left atrium.

Statistics

Differences in TBR ratios between vulnerable and stable plaques were tested by paired Student’s t-test (normally distributed data) or Wilcoxon signed-rank test (non-normally distributed data). Normality of data was tested using the Shapiro-Wilk test. The correlation between TBRmax and minimal fibrous cap thickness for the combined target and reference lesions was assessed using Spearman’s rho correlation coefficient for each PET reconstruction. All statistical analyses and plot generations were performed using RStudio (Integrated Development Environment for R, version 1.4.1103, Boston MA, USA). Two-tailed values of p < 0.05 were considered significant.

A total of 15 patients were included for this study. One patient was excluded from final analysis due to PET tracer extravasation. The baseline characteristics of the remaining 14 patients are described in Table 1. Three patients could only be partially analysed due to the following reasons: 1) CMRA with nondiagnostic image quality due to artifacts (excluded for TBRmax eMR-MOCO and eMR-MOCO-ECG analyses), 2) no coronary reference lesion available (excluded for target versus reference TBRmax comparison), and 3) failure to produce all PET respiratory gating reconstructions (excluded for eMR-MOCO and eMR-MOCO-ECG analyses). All analysed patients had a vessel section with a fibrous cap thinner than 70 µm. Figure 1 shows imaging examples of the acquired PET-MRI and OCT imaging.

No significant difference between TBRmax values of the vulnerable versus the stable lesions for MRG-MOCO, eMR-MOCO and eMR-MOCO-ECG were found (MRG-MOCO: mean TBRmax 1.45 vs 1.35, p=0.52; eMR-MOCO: 1.47 vs 1.27, p= 0.26; eMR-MOCO-ECG: 1.49 vs 1.26, p= 0.21). Boxplots and dot plots of vulnerable versus stable plaque TBRmax values for the different PET reconstructions are shown in Figure 2.

No significant correlation between TBRmax and minimal fibrous cap thickness was found for each of the PET reconstructions (MRG-MOCO: -0.034, p=0.87; eMR-MOCO: -0.057, p=0.80; and eMR-MOCO-ECG: -0.036, p=0.87). Scatterplots of the TBRmax and minimal fibrous cap thickness of the combined vulnerable and stable plaques for each PET reconstruction are shown in Figure 3.

A comparison of the three used PET imaging reconstructions is shown in Figure 4. A difference in noise can be visually appreciated between the different reconstructions, where MRG-MOCO reconstruction yields more noise than both eMR-MOCO and eMR-MOCO-ECG.

To the best of our knowledge, this is the first study that investigates the feasibility to identify vulnerable coronary plaques with non-invasive ¹⁸F-fluorocholine PET. Coronary imaging is challenging due to inherent motion artefacts caused by both respiratory and cardiac motion. To correct for these motion artifacts, advanced hybrid PET-MRI respiratory motion correction as well as cardiac gating methods were applied in different combinations. Nevertheless, no significant differences were found in ¹⁸F-fluorocholine PET uptake between vulnerable and stable coronary plaques as classified by invasive OCT imaging as reference standard.

The use of hybrid PET-MRI in the present study allows for nonrigid respiratory motion correction in our patient population. This PET-MRI reconstruction method allowed to estimate translational motion from a low-resolution 2D MR image navigator (iNav) acquired each heartbeat and to subsequently apply 3D nonrigid respiratory motion correction between different respiratory bins from the CMRA data. In contrast, respiratory motion correction methods in PET-CT for correction of pulmonary and upper abdominal motion artifacts, are only correcting in craniocaudal direction. This important advantage of hybrid PET-MRI imaging potentially provides a non-invasive method for analysing the coronary arteries. Another advantage is that molecular imaging on PET can be combined with functional ischemia imaging on MRI.

In contrast to ¹⁸F-FDG PET imaging, which has significant drawbacks for coronary imaging, radiolabeled-choline is highly taken up in activated macrophages and was hypothesized to be an alternative, more specific, tracer for imaging plaque inflammation.[15] Initial murine and rabbit models of atherosclerosis revealed a significantly higher uptake of radiolabeled-choline in inflamed atherosclerotic plaques in comparison to healthy vessel wall.[21-23] This rapid uptake of radiolabeled-choline in plaque macrophages seems to be linked to the upregulation of choline transporters on the cell surface, similar to that observed in macrophages from other inflammatory conditions.[14, 22] There are three published reports that retrospectively analysed choline PET in diagnosis of prostate cancer, and described a higher presence of the tracer within the atherosclerotic vessel walls.[24-26] For obvious reasons, no comparison with the gold standard, histology, has been made in these studies. Our own group earlier investigated vascular wall inflammation in a prospective study that compared ¹⁸F-fluorocholine uptake to macrophage content on histology, represented by CD68+ plaque content, in a patient population of symptomatic carotid artery stenosis.[15] That study showed a positive correlation between ¹⁸F-fluorocholine uptake and macrophage content, as well as higher uptake in the ipsilateral versus contralateral carotid vessel wall.

An explanation for the lack of ¹⁸F-fluorocholine uptake in vulnerable coronary plaques in the current study could be related to the small size of coronary plaques, compared to larger carotid artery lesions studied earlier. A certain minimum amount of tracer needs to accumulate in a plaque in order to be detected by PET. Subvoxel size of plaques does not rule out detection, but the partial volume effect can negate detectability. Studies with other tracers, notably ¹⁸F-sodiumfluoride (¹⁸F-NaF), revealed increased tracer uptake in culprit versus non-culprit coronary plaques of patients with myocardial infarction.[27] Interestingly, this study also showed that patients with ¹⁸F-NaF positive plaques in a stable angina cohort had higher ¹⁸F-NaF activity when compared to those with myocardial infarction. The patients with stable angina were older and therefore may have had a more extensive plaque burden. Thus, not only the vulnerability but also the size of the plaque determines the TBRmax value.

When investigating coronary artery plaques, no coronary artery specimens can be obtained to correlate PET outcomes to histological findings. In our study, invasive OCT imaging was used as reference standard to provide detailed images of coronary plaques with a resolution ranging from 10 to 20 µm. This is approximately 50-100 times higher than what can be achieved using MRI or intravascular ultrasound (IVUS), and OCT has been well validated in numerous studies.[16,17,28-30] The OCT parameter that we used to define a vulnerable plaque was the presence of a thin fibrous cap, since rupture of such a cap is the main underlying cause of myocardial infarction. We used a threshold of a cap thickness of less than 70 µm for a vulnerable plaque in line with previous studies.[31] While pathologists define a thin fibrous cap using a cut-off value of < 65 µm,[32] for OCT one should choose a slightly higher threshold to take into account tissue shrinkage during histological processing.[33]

The anatomical correlation of the plaques on OCT and PET relied on visually comparing vascular anatomy as displayed on angiographical imaging to the coronary MR angiography images. By carefully selecting a segment with stable plaque, sufficiently distant away from vulnerable plaques, we ensured that the stable plaque VOI did not include a section of vulnerable plaque. We also made sure that the entire plaque was included in the VOI. The advantage of TBRmax is that this parameter is not influenced by the VOI size, as long as no other ¹⁸F-fluorocholine avid structures are included. Therefore, the current negative results, cannot be explained by high uptake in stable plaques. Theoretically, a conebeam CT acquired using a state-of-the-art angiographic gantry could be better suited to co-registrate the OCT pullback trajectory with the PET images. On the other hand, such a technique would lead to extra radiation exposure.

Finally, a practical limitation concerning the analysis of ¹⁸F-fluorocholine uptake in coronary vessels is intense liver uptake, obscuring any vascular uptake located close to the liver due to spill over of liver activity. This mostly affects the distal right coronary artery, where lumen and plaques tend to be smaller and are already inherently more challenging for PET imaging in general. In our patient population, however, all vulnerable and stable plaques that were analysed were in regions not susceptible to activity overspill from the liver. Another limitation of the study is the small sample size since the study was conceived to establish proof of principle.

PET-MRI with ¹⁸F-fluorocholine, using advanced respiratory non-rigid motion correction with or without cardiac gating, did not show significantly higher uptake in vulnerable plaques compared to stable plaques using OCT as reference standard. These findings in the coronary arteries differ from previous results in the carotid arteries, where more uptake in symptomatic lesions was observed. Multiple inherent factors, such as small coronary plaque size and cardiac movement, may hamper visualization of coronary macrophage plaque content through ¹⁸F-fluorocholine binding.

Trial registration number:

NCT03252990 (ClinicalTrials.gov)

NL58752.068.16 (Dutch Medical Ethical Committee registration number)

Acknowledgements

We are grateful for all assistance in OCT analysis offered by Jurgen Ligthart (Limic Medical).

The authors would like to acknowledge Jurgen Ligthart (LIMIC Medical) for his assistance with the OCT analysis.

Funding

This project was funded by the Academic Fund of the VieCuri hospital and Maastricht University Medical Center, and the Weijerhorst foundation (Stichting de Weijerhorst).

Competing interests

The authors Jochem A.J. van der Pol, Braim Rahel, Yvonne J.M. van Cauteren, Rik P.M. Moonen, Joan G. Meeder, Suzanne C. Gerretsen, Mueez Aizaz, Claudia Prieto, René M. Botnar, Jan Bucerius, Herman van Langen, Robert J. Holtackers and Eline M. Kooi declare no conflicts of interest. Joachim. E. Wildberger reports institutional grants by Bard, Bayer, Boston, Brainlab, GE, Philips and Siemens outside of the submitted work. He reports funding via speakers bureau by Bayer, Siemens, outside of the submitted work. Jan Bucerius reports institutional funding from the International Atomic Energy Agency (IAEA) in the context of the "PIAF"-trial (core lab), outside of the submitted work.

Author contributions

Braim Rahel, Joan Meeder, Robert J. Holtackers, M. Eline Kooi, Jochem A.J. van der Pol, Jan Bucerius and Joachim E. Wildberger contributed to the study conception and design. Patient inclusion was performed by Braim Rahel and Yvonne J.M. van Cauteren. Material preparation, data collection and analyses were performed by Braim Rahel, Yvonne J.M. van Cauteren, Robert J. Holtackers, Mueez Aizaz, Rik P.M. Moonen, Herman van Langen, M. Eline Kooi, Suzanne C. Gerretsen and Jochem A.J. van der Pol. The first draft of the manuscript was written by Jochem A.J. van der Pol, with contributions in methods by Braim Rahel, Rik Moonen, Mueez Aizaz and Robert J. Holtackers. All authors commented and critically reviewed the manuscript. Tables and figures were prepared by Jochem A.J. van der Pol. All authors read and approved the final manuscript.

Ethics approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the local Ethics Committee of Maastricht University (Registration number NL58752.068.16).

Data availability

Datasets generated and analysed during current study are available from the corresponding author on reasonable request.

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Table 1 Baseline patient characteristics.

Age [years]	63.1 (10.3)
Gender (female; n,%)	3 (21.4)
Weight [kg]	81.3 (12.0)
Systolic blood pressure [mmHg]	135.2 (22.7)
Diastolic blood pressure [mmHg]	72.4 (11.7)
Hemoglobin [mmol/L]	8.5 (1.1)
LDL-cholesterol [mmol/l]	3.2 (1.6)
HDL-cholesterol [mmol/L]	1.1 (0.27)
Total cholesterol [mmol/L]	4.7 (2.0)
Triglyceride [mmol/L]	1.5 (0.6)
Hypertension (n,%)	6 (42.9)
Diabetes mellitus (n,%)	2 (14.3)
Hypercholesterolemia (n,%)	6 (42.9)
Obesity (n,%)	4 (28.6)
Smoking (n,%)
Never smoked	3 (21.4)
Former smoker	4 (28.6)
Quit smoking during current hospitalization	5 (35.7)
Still smoking	2 (14.3)
History of ischemic heart disease (n,%)	1 (7.1)

All data are indicated as mean (standard deviation), unless indicated otherwise

No competing interests reported.

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Molecular imaging of coronary plaque vulnerability using 18F- fluorocholine PET-MRI in patients with coronary artery disease: validation with optical coherence tomography

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