Aortic valve stenosis-multimodality assessment with PET/CT and PET/MRI

Aortic valve disease is the most common form of heart valve disease in developed countries and a growing healthcare burden with an ageing population. Transthoracic and transoesophageal echocardiography remains central to the diagnosis and surveillance of patients with aortic stenosis, providing gold standard assessments of valve haemodynamics and myocardial performance. However, other multimodality imaging techniques are being explored for the assessment of aortic stenosis, including combined PET/CT and PET/MR. Both approaches provide unique information with respect to disease activity in the valve alongside more conventional anatomic assessments of the valve and myocardium in this condition. This review investigates the emerging use of PET/CT and PET/MR to assess patients with aortic stenosis, examining how the complementary data provided by each modality may be used for research applications and potentially in future clinical practice

Improved identification of abdominal aortic aneurysm using the Kernelized Expectation Maximization algorithm

Abdominal aortic aneurysm (AAA) monitoring and risk of rupture is currently assumed to be correlated with the aneurysm diameter. Aneurysm growth, however, has been demonstrated to be unpredictable. Using PET to measure uptake of [18F]-NaF in calcified lesions of the abdominal aorta has been shown to be useful for identifying AAA and to predict its growth. The PET low spatial resolution, however, can affect the accuracy of the diagnosis. Advanced edge-preserving reconstruction algorithms can overcome this issue. The kernel method has been demonstrated to provide noise suppression while retaining emission and edge information. Nevertheless, these findings were obtained using simulations, phantoms and a limited amount of patient data. In this study, the authors aim to investigate the usefulness of the anatomically guided kernelized expectation maximization (KEM) and the hybrid KEM (HKEM) methods and to judge the statistical significance of the related improvements. Sixty-one datasets of patients with AAA and 11 from control patients were reconstructed with ordered subsets expectation maximization (OSEM), HKEM and KEM and the analysis was carried out using the target-to-blood-pool ratio, and a series of statistical tests. The results show that all algorithms have similar diagnostic power, but HKEM and KEM can significantly recover uptake of lesions and improve the accuracy of the diagnosis by up to 22% compared to OSEM. The same improvements are likely to be obtained in clinical applications based on the quantification of small lesions, like for example cancer

Positron Emission Tomography and Magnetic Resonance Imaging of Cellular Inflammation in Patients with Abdominal Aortic Aneurysms.

OBJECTIVES: Inflammation is critical in the pathogenesis of abdominal aortic aneurysm (AAA) disease. Combined (18)F-fludeoxyglucose ((18)F-FDG) positron emission tomography with computed tomography (PET-CT) and ultrasmall superparamagnetic particles of iron oxide (USPIO)-enhanced magnetic resonance imaging (MRI) are non-invasive methods of assessing tissue inflammation. The aim of this study was to compare these techniques in patients with AAA. MATERIALS AND METHODS: Fifteen patients with asymptomatic AAA with diameter 46 ± 7 mm underwent PET-CT with (18)F-FDG, and T2*-weighted MRI before and 24 hours after administration of USPIO. The PET-CT and MRI data were then co-registered. Standardised uptake values (SUVs) were calculated to measure (18)F-FDG activity, and USPIO uptake was determined using the change in R2*. Comparisons between the techniques were made using a quadrant analysis and a voxel-by-voxel evaluation. RESULTS: When all areas of the aneurysm were evaluated, there was a modest correlation between the SUV on PET-CT and the change in R2* on USPIO-enhanced MRI (n = 70,345 voxels; r = .30; p < .0001). Although regions of increased (18)F-FDG and USPIO uptake co-localised on occasion, this was infrequent (kappa statistic 0.074; 95% CI 0.026-0.122). (18)F-FDG activity was commonly focused in the shoulder region whereas USPIO uptake was more apparent in the main body of the aneurysm. Maximum SUV was lower in patients with mural USPIO uptake. CONCLUSIONS: Both (18)F-FDG PET-CT and USPIO-MRI uptake identify vascular inflammation associated with AAA. Although they demonstrate a modest correlation, there are distinct differences in the pattern and distribution of uptake, suggesting a differential detection of macrophage glycolytic and phagocytic activity respectively.This research was supported by grants from the National Institutes of Health Research (NIHR) Efficacy and Mechanism Evaluation Programme (11/20/03), the British Heart Foundation (PG/09/083) and the Evelyn Trust (09/22). Dr. McBride is supported by the Academic Department of Military Surgery and Trauma, Royal Centre for Defence Medicine. Dr. Joshi is supported by Chief Scientist Office (ETM/160). Dr. van Beek is supported by the Scottish Imaging Network e a Platform of Scientific Excellence. The work of Dr. Rudd is part-supported by the NIHR Cambridge Biomedical Research Centre, the British Heart Foundation and the Wellcome Trust. Dr. Newby is supported by the British Heart Foundation (CH/09/002). The Wellcome Trust Clinical Research Facility and the Clinical Research Imaging Centre are supported by National Health Service Research Scotland through National Health Service Lothian.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ejvs.2015.12.01

Comparison of Correction Techniques for the Spill in Effect in Emission Tomography

In positron emission tomography (PET) imaging, accurate clinical assessment is often affected by the partial volume effect (PVE) leading to overestimation (spill-in) or underestimation (spill-out) of activity in various small regions. The spill-in correction, in particular, can be very challenging when the target region is close to a hot background region. Therefore, this study evaluates and compares the performance of various recently developed spill-in correction techniques, namely: background correction (BC), local projection (LP), and hybrid kernelized (HKEM) methods. We used a simulated digital phantom and 18F-NaF PET data of three patients with abdominal aortic aneurysms (AAA) acquired with Siemens Biograph mMRTM and mCTTM scanners respectively. Region of Interest (ROI) analysis was performed and the extracted SUVmean, SUVmax and target-to-background ratio (TBR) scores were compared. Results showed substantial spill-in effects from hot regions to targeted regions, which are more prominent in small structures. The phantom experiment demonstrated the feasibility of spill-in correction with all methods. For the patient data, large differences in SUVmean, SUVmax and TBRmax scores were observed between the ROIs drawn over the entire aneurysm and ROIs excluding some regions close to the bone. Overall, BC yielded the best performance in spill-in correction in both phantom and patient studies

Multimodality Quantitative Assessments of Myocardial Perfusion Using Dynamic Contrast Enhanced Magnetic Resonance and 15O-Labeled Water Positron Emission Tomography Imaging

Kinetic modeling of myocardial perfusion imaging data allows the absolute quantification of myocardial blood flow (MBF) and can improve the diagnosis and clinical assessment of coronary artery disease (CAD). Positron emission tomography (PET) imaging is considered the reference standard technique for absolute quantification, whilst oxygen-15 (15O)-water has been extensively implemented for MBF quantification. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has also been used for MBF quantification and showed comparable diagnostic performance against (¹⁵ O)-water PET studies. We investigated for the first time the diagnostic performance of two different PET MBF analysis softwares PMOD and Carimas, for obstructive CAD detection against invasive clinical standard methods in 20 patients with known or suspected CAD. Fermi and distributed parameter modeling-derived MBF quantification from DCE-MRI was also compared against (15O)-water PET, in a subgroup of six patients. The sensitivity and specificity for PMOD was significantly superior for obstructive CAD detection in both per vessel (0.83, 0.90) and per patient (0.86, 0.75) analysis, against Carimas (0.75, 0.65) and (0.81, 0.70), respectively. We showed strong, significant correlations between MR and PET MBF quantifications (r = 0.83 - 0.92). However, DP and PMOD analysis demonstrated comparable and higher hemodynamic differences between obstructive versus (no, minor, or non)-obstructive CAD, against Fermi and Carimas analysis. Our MR method assessments against the optimum PET reference standard technique for perfusion analysis showed promising results in per segment level and can support further multimodality assessments in larger patient cohorts. Further MR against PET assessments may help to determine their comparative diagnostic performance for obstructive CAD detection

Ferumoxytol-enhanced MRI in patients with prior cardiac transplantation.

Objectives: Ultra-small superparamagnetic particles of iron oxide (USPIO)-enhanced MRI can detect cellular inflammation within tissues and may help non-invasively identify cardiac transplant rejection. Here, we aimed to determine the normal reference values for USPIO-enhanced MRI in patients with a prior cardiac transplant and examine whether USPIO-enhanced MRI could detect myocardial inflammation in patients with transplant rejection. Methods: Ten volunteers and 11 patients with cardiac transplant underwent T2, T2* and late gadolinium enhancement 1.5T MRI, with further T2* imaging at 24 hours after USPIO (ferumoxytol, 4 mg/kg) infusion, at baseline and 3 months. Results: Ten patients with clinically stable cardiac transplantation were retained for analysis. Myocardial T2 values were higher in patients with cardiac transplant versus healthy volunteers (53.8±5.2 vs 48.6±1.9 ms, respectively; p=0.003). There were no differences in the magnitude of USPIO-induced change in R2* in patients with transplantation (change in R2*, 26.6±7.3 vs 22.0±10.4 s-1 in healthy volunteers; p=0.28). After 3 months, patients with transplantation (n=5) had unaltered T2 values (52.7±2.8 vs 52.12±3.4 ms; p=0.80) and changes in R2* following USPIO (29.42±8.14 vs 25.8±7.8 s-1; p=0.43). Conclusion: Stable patients with cardiac transplantation have increased myocardial T2 values, consistent with resting myocardial oedema or fibrosis. In contrast, USPIO-enhanced MRI is normal and stable over time suggesting the absence of chronic macrophage-driven cellular inflammation. It remains to be determined whether USPIO-enhanced MRI may be able to identify acute cardiac transplant rejection. Trial registration number: NCT02319278349 (https://clinicaltrials.gov/ct2/show/NCT02319278) Registered 03.12.2014 EUDraCT 2013-002336-24

Optimization and Reproducibility of Aortic Valve 18F-Fluoride Positron Emission Tomography in Patients With Aortic Stenosis

$\textbf{BACKGROUND}$: 18F-Fluoride positron emission tomography (PET) and computed tomography (CT) can measure disease activity and progression in aortic stenosis. Our objectives were to optimize the methodology, analysis, and scan-rescan reproducibility of aortic valve 18F-fluoride PET-CT imaging. $\textbf{METHODS AND RESULTS}$: Fifteen patients with aortic stenosis underwent repeated 18F-fluoride PET-CT. We compared nongated PET and noncontrast CT, with a modified approach that incorporated contrast CT and ECG-gated PET. We explored a range of image analysis techniques, including estimation of blood-pool activity at differing vascular sites and a most diseased segment approach. Contrast-enhanced ECG-gated PET-CT permitted localization of 18F-fluoride uptake to individual valve leaflets. Uptake was most commonly observed at sites of maximal mechanical stress: the leaflet tips and the commissures. Scan-rescan reproducibility was markedly improved using enhanced analysis techniques leading to a reduction in percentage error from ±63% to ±10% (tissue to background ratio MDS mean of 1.55, bias -0.05, limits of agreement -0·20 to +0·11). $\textbf{CONCLUSIONS}$: Optimized 18F-fluoride PET-CT allows reproducible localization of calcification activity to different regions of the aortic valve leaflet and commonly to areas of increased mechanical stress. This technique holds major promise in improving our understanding of the pathophysiology of aortic stenosis and as a biomarker end point in clinical trials of novel therapies. $\textbf{CLINICAL TRIAL REGISTRATION}$ - URL: http://www.clinicaltrials.gov. Unique identifier: NCT02132026.The study was funded by the British Heart Foundation (FS/14/78/31020). Drs Pawade, Cartlidge, Jenkins, Dweck, and Newby are supported by the British Heart Foundation (SS/CH/09/002/26360, FS/13/77/30488, SS/CH/09/002/2636, FS/14/78/31020, and CH/09/002). Dr Newby is the recipient of a Wellcome Trust Senior Investigator Award (WT103782AIA). Dr Dweck is the recipient of the Sir Jules Thorn Award for Biomedical Research 2015. Dr Adamson is supported by New Zealand Overseas Training and Research Fellowship (1607) and Edinburgh and Lothians Health Foundation (50–534). The Wellcome Trust Clinical Research Facility and the Clinical Research Imaging Centre are supported by NHS Research Scotland (NRS) through NHS Lothian. Dr Rudd is partly supported by the NIHR Cambridge Biomedical Research Centre, the British Heart Foundation, and the Wellcome Trust

A novel cardiovascular magnetic resonance risk score for predicting mortality following surgical aortic valve replacement

The increasing prevalence of patients with aortic stenosis worldwide highlights a clinical need for improved and accurate prediction of clinical outcomes following surgery. We investigated patient demographic and cardiovascular magnetic resonance (CMR) characteristics to formulate a dedicated risk score estimating long-term survival following surgery. We recruited consecutive patients undergoing CMR with gadolinium administration prior to surgical aortic valve replacement from 2003 to 2016 in two UK centres. The outcome was overall mortality. A total of 250 patients were included (68 ± 12 years, male 185 (60%), with pre-operative mean aortic valve area 0.93 ± 0.32cm2, LVEF 62 ± 17%) and followed for 6.0 ± 3.3 years. Sixty-one deaths occurred, with 10-year mortality of 23.6%. Multivariable analysis showed that increasing age (HR 1.04, P = 0.005), use of antiplatelet therapy (HR 0.54, P = 0.027), presence of infarction or midwall late gadolinium enhancement (HR 1.52 and HR 2.14 respectively, combined P = 0.12), higher indexed left ventricular stroke volume (HR 0.98, P = 0.043) and higher left atrial ejection fraction (HR 0.98, P = 0.083) associated with mortality and developed a risk score with good discrimination. This is the first dedicated risk prediction score for patients with aortic stenosis undergoing surgical aortic valve replacement providing an individualised estimate for overall mortality. This model can help clinicians individualising medical and surgical care. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT00930735 and ClinicalTrials.gov Identifier: NCT01755936