Markerless attenuation correction for carotid MRI surface receiver coils in combined PET/MR imaging.

The purpose of the study was to evaluate the effect of attenuation of MR coils on quantitative carotid PET/MR exams. Additionally, an automated attenuation correction method for flexible carotid MR coils was developed and evaluated.The attenuation of the carotid coil was measured by imaging a uniform water phantom injected with 37 MBq of 18F-FDG in a combined PET/MR scanner for 24 min with and without the coil. In the same session, an ultra-short echo time (UTE) image of the coil on top of the phantom was acquired. Using a combination of rigid and non-rigid registration, a CT-based attenuation map was registered to the UTE image of the coil for attenuation and scatter correction. After phantom validation, the effect of the carotid coil attenuation and the attenuation correction method were evaluated in five subjects.Phantom studies indicated that the overall loss of PET counts due to the coil was 6.3% with local region-of-interest (ROI) errors reaching up to 18.8%. Our registration method to correct for attenuation from the coil decreased the global error and local error (ROI) to 0.8% and 3.8%, respectively. The proposed registration method accurately captured the location and shape of the coil with a maximum spatial error of 2.6 mm. Quantitative analysis in human studies correlated with the phantom findings, but was dependent on the size of the ROI used in the analysis.MR coils result in significant error in PET quantification and thus attenuation correction is needed. The proposed strategy provides an operator-free method for attenuation and scatter correction for a flexible MRI carotid surface coil for routine clinical use

Cap inflammation leads to higher plaque cap strain and lower cap stress: An MRI-PET/CT-based FSI modeling approach.

Plaque rupture may be triggered by extreme stress/strain conditions. Inflammation is also implicated and can be imaged using novel imaging techniques. The impact of cap inflammation on plaque stress/strain and flow shear stress were investigated. A patient-specific MRI-PET/CT-based modeling approach was used to develop 3D fluid-structure interaction models and investigate the impact of inflammation on plaque stress/strain conditions for better plaque assessment. 18FDG-PET/CT and MRI data were acquired from 4 male patients (average age: 66) to assess plaque characteristics and inflammation. Material stiffness for the fibrous cap was adjusted lower to reflect cap weakening causing by inflammation. Setting stiffness ratio (SR) to be 1.0 (fibrous tissue) for baseline, results for SR=0.5, 0.25, and 0.1 were obtained. Thin cap and hypertension were also considered. Combining results from the 4 patients, mean cap stress from 729 cap nodes was lowered by 25.2% as SR went from 1.0 to 0.1. Mean cap strain value for SR=0.1 was 0.313, 114% higher than that from SR=1.0 model. The thin cap SR=0.1 model had 40% mean cap stress decrease and 81% cap strain increase compared with SR=1.0 model. The hypertension SR=0.1 model had 19.5% cap stress decrease and 98.6% cap strain increase compared with SR=1.0 model. Differences of flow shear stress with 4 different SR values were limited (<10%). Cap inflammation may lead to large cap strain conditions when combined with thin cap and hypertension. Inflammation also led to lower cap stress. This shows the influence of inflammation on stress/strain calculations which are closely related to plaque assessment.This work was supported in part by NIH grants NIH/NIBIB R01 EB004759, NIH/NHLBI R01 HL071021, and National Natural Sciences Foundation of China grant 11672001, 11171030

Effect of PET-MR Inconsistency in the Kernel Image Reconstruction Method

Anatomically driven image reconstruction algorithms have become very popular in positron emission tomography (PET) where they have demonstrated improved image resolution and quantification. This paper examines the effects of spatial inconsistency between MR and PET images in hot and cold regions of PET images using the hybrid kernelized expectation maximization (HKEM) machine learning method. Our evaluation was conducted on Jaszczak phantom and patient data acquired with the Biograph Siemens mMR. The results show that even a small shift can cause a significant change in activity concentration. In general, the PET-MR inconsistencies can induce the partial volume effect, more specifically the “spill-in” for cold regions and the “spill-out” for hot regions. The maximum change was about 100% for the cold region and 10% for the hot lesion using kernelized expectation maximization, against the 37% and 8% obtained with HKEM. The findings of this paper suggest that including PET information in the kernel enhances the robustness of the reconstruction in case of spatial inconsistency. Nevertheless, accurate registration and choice of the appropriate MR image for the creation of the kernel is essential to avoid artifacts, blurring, and bias

Coronary Plaque Morphology and the Anti-Inflammatory Impact of Atorvastatin: A Multicenter 18F-Fluorodeoxyglucose Positron Emission Tomographic/Computed Tomographic Study.

BACKGROUND: Nonobstructive coronary plaques manifesting high-risk morphology (HRM) associate with an increased risk of adverse clinical cardiovascular events. We sought to test the hypothesis that statins have a greater anti-inflammatory effect within coronary plaques containing HRM. METHODS AND RESULTS: In this prospective multicenter study, 55 subjects with or at high risk for atherosclerosis underwent 18F-fluorodeoxyglucose positron emission tomographic/computed tomographic imaging at baseline and after 12 weeks of treatment with atorvastatin. Coronary arterial inflammation (18F-fluorodeoxyglucose uptake, expressed as target-to-background ratio) was assessed in the left main coronary artery (LMCA). While blinded to the PET findings, contrast-enhanced computed tomographic angiography was performed to characterize the presence of HRM (defined as noncalcified or partially calcified plaques) in the LMCA. Arterial inflammation (target-to-background ratio) was higher in LMCA segments with HRM than those without HRM (mean+/-SEM: 1.95+/-0.43 versus 1.67+/-0.32 for LMCA with versus without HRM, respectively; P=0.04). Moreover, atorvastatin treatment for 12 weeks reduced target-to-background ratio more in LMCA segments with HRM than those without HRM (12 week-baseline Deltatarget-to-background ratio [95% confidence interval]: -0.18 [-0.35 to -0.004] versus 0.09 [-0.06 to 0.26]; P=0.02). Furthermore, this relationship between coronary plaque morphology and change in LMCA inflammatory activity remained significant after adjusting for baseline low-density lipoprotein and statin dose (beta=-0.27; P=0.038). CONCLUSIONS: In this first study to evaluate the impact of statins on coronary inflammation, we observed that the anti-inflammatory impact of statins is substantially greater within coronary plaques that contain HRM features. These findings suggest an additional mechanism by which statins disproportionately benefit individuals with more advanced atherosclerotic disease. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00703261

Hybrid PET-MR list-mode kernelized expectation maximization reconstruction for quantitative PET images of the carotid arteries

Ordered subsets expectation maximization (OSEM) has been widely used in PET imaging. Although Bayesian algorithms have been shown to perform better, they are still not used in the clinical practice due to the difficulty of choosing appropriate and robust regularization parameters. The recently introduced kernelized expectation maximization (KEM) has shown some promise to work successfully for different applications. Therefore, we propose a list mode hybrid KEM (LM-HKEM) for static reconstructions, which we implemented in the open source Software for Tomographic Image Reconstruction (STIR) library. The proposed algorithm uses both MR and PET update images to create a feature vector for each voxel in the image, which contains the information about the local neighborhood. So as not to over-smooth the reconstructed images a 3×3×3 voxels kernel was used. Three real datasets were acquired with the Siemens mMR: a phantom to validate the algorithm and two patient carotid artery studies to show the possible applications of the method. The reconstructed images are assessed and compared for different algorithms: OSEM, OSEM with median root prior (MRP), KEM and LM-HKEM. The results show better quantification performance for the phantom low count images with around 4% bias compared to 7% for KEM and over 11% for OSEM and OSEM with (MRP). Our results show that the proposed technique can be used to improve quantification at low- count condition and it shows promising performance in terms of stability as for different subsets, with comparable number of events, we used the same parameters values. Emphasis is given on the reconstruction of the carotid artery and the characterization of atherosclerosis

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

Hybrid PET-MR list-mode kernelized expectation maximization reconstruction

The recently introduced kernelized expectation maximization (KEM) method has shown promise across varied applications. These studies have demonstrated the benefits and drawbacks of the technique when the kernel matrix is estimated from separate anatomical information, for example from magnetic resonance (MR), or from a preliminary PET reconstruction. The contribution of this work is to propose and investigate a list-mode-hybrid KEM (LM-HKEM) reconstruction algorithm with the aim of maintaining the benefits of the anatomically-guided methods and overcome their limitations by incorporating synergistic information iteratively. The HKEM is designed to reduce negative bias associated with low-counts, the problem of PET unique feature suppression reported in the previously mentioned studies using only the MR-based kernel, and to improve contrast of lesions at different count levels. The proposed algorithm is validated using a simulation study, a phantom dataset and two clinical datasets. For each of the real datasets high and low count-levels were investigated. The reconstructed images are assessed and compared with different LM algorithms implemented in STIR. The findings obtained using simulated and real datasets show that anatomically-guided techniques provide reduced partial volume effect and higher contrast compared to standard techniques, and HKEM provides even higher contrast and reduced bias in almost all the cases. This work, therefore argues that using synergistic information, via the kernel method, increases the accuracy of the PET clinical diagnostic examination. The promising quantitative features of the HKEM method give the opportunity to explore many possible clinical applications, such as cancer and inflammation

In Vivo Mapping of Vascular Inflammation Using Multimodal Imaging

Plaque vulnerability to rupture has emerged as a critical correlate to risk of adverse coronary events but there is as yet no clinical method to assess plaque stability in vivo. In the search to identify biomarkers of vulnerable plaques an association has been found between macrophages and plaque stability--the density and pattern of macrophage localization in lesions is indicative of probability to rupture. In very unstable plaques, macrophages are found in high densities and concentrated in the plaque shoulders. Therefore, the ability to map macrophages in plaques could allow noninvasive assessment of plaque stability. We use a multimodality imaging approach to noninvasively map the distribution of macrophages in vivo. The use of multiple modalities allows us to combine the complementary strengths of each modality to better visualize features of interest. Our combined use of Positron Emission Tomography and Magnetic Resonance Imaging (PET/MRI) allows high sensitivity PET screening to identify putative lesions in a whole body view, and high resolution MRI for detailed mapping of biomarker expression in the lesions.Macromolecular and nanoparticle contrast agents targeted to macrophages were developed and tested in three different mouse and rat models of atherosclerosis in which inflamed vascular plaques form spontaneously and/or are induced by injury. For multimodal detection, the probes were designed to contain gadolinium (T1 MRI) or iron oxide (T2 MRI), and Cu-64 (PET). PET imaging was utilized to identify regions of macrophage accumulation; these regions were further probed by MRI to visualize macrophage distribution at high resolution. In both PET and MR images the probes enhanced contrast at sites of vascular inflammation, but not in normal vessel walls. MRI was able to identify discrete sites of inflammation that were blurred together at the low resolution of PET. Macrophage content in the lesions was confirmed by histology.The multimodal imaging approach allowed high-sensitivity and high-resolution mapping of biomarker distribution and may lead to a clinical method to predict plaque probability to rupture