Nicolas Karakatsanis

Hybrid Magnetic Resonance Imaging and Positron Emission Tomography With Fluorodeoxyglucose to Diagnose Active Cardiac Sarcoidosis

OBJECTIVESnThe purpose of this study was to explore the diagnostic usefulness of hybrid cardiac magnetic resonance (CMR) and positron emission tomography (PET) using 18F-fluorodeoxyglucose (FDG) for active cardiac sarcoidosis.nnnBACKGROUNDnActive cardiac sarcoidosis (aCS) is underdiagnosed and has a high mortality.nnnMETHODSnPatients with clinical suspicion of aCS underwent hybrid CMR/PET with late gadolinium enhancement (LGE) and FDG to assess the pattern of injury and disease activity, respectively. Patients were categorized visually as magnetic resonance (MR)+PET+ (characteristic LGE aligning exactly with increased FDG uptake), MR+PET- (characteristic LGE but no increased FDG), MR-PET- (neither characteristic LGE nor increased FDG), and MR-PET+ (increased FDG uptake in absence of characteristic LGE) and further characterized as aCS+ (MR+PET+) or aCS- (MR+PET-, MR-PET-, MR-PET+). FDG uptake was quantified using maximum target-to-normal-myocardium ratio and the net uptake rate (Ki) from dynamic Patlak analysis. Receiver-operating characteristic methods were used to identify imaging biomarkers for aCS. FDG PET was assessed using computed tomography/PET in 19 control subjects with healthy myocardium.nnnRESULTSnA total of 25 patients (12 males; 54.9 ± 9.8 years of age) were recruited prospectively; 8 were MR+PET+, suggestive of aCS; 1 was MR+PET-, consistent with inactive cardiac sarcoidosis; and 8 were MR-PET-, with no imaging evidence of cardiac sarcoidosis. Eight patients were MR-PET+ (6 with global myocardial FDG uptake, 2 with focal-on-diffuse uptake); they demonstrated distinct Ki values and hyperintense maximum standardized uptake value compared with MR+PET+ patients. Similar hyperintense patterns of global (nxa0= 9) and focal-on-diffuse (nxa0= 2) FDG uptake were also observed in control patients, suggesting physiological myocardial uptake. Maximum target-to-normal-myocardium ratio values were higher in the aCS+ group (pxa0< 0.001), demonstrating an area under the curve of 0.98 on receiver-operating characteristic analysis for the detection of aCS, with an optimal maximum target-to-normal myocardium ratio threshold of 1.2 (Youden index: 0.94).nnnCONCLUSIONSnCMR/PET imaging holds major promise for the diagnosis of aCS, providing incremental information about both the pattern of injury and disease activity in a single scan. (Inxa0Vivo Molecular Imaging [MRI] of Atherothrombotic Lesions; NCT01418313).

Coronary Artery PET/MR Imaging: Feasibility, Limitations, and Solutions

OBJECTIVESnThe aims of this study were to describe the authors initial experience with combined coronary artery positron emission tomographic (PET) and magnetic resonance (MR) imaging using 18F-fluorodeoxyglucose (18F-FDG) and 18F-sodium fluoride (18F-NaF) radiotracers, describe common problems and their solutions, and demonstrate the feasibility of coronary PET/MR imaging in appropriate patients.nnnBACKGROUNDnRecently, PET imaging has been applied to the aortic valve and regions of atherosclerosis. 18F-FDG PET imaging has become established for imaging inflammation in atherosclerosis in the aorta and carotid arteries. Moreover, 18F-NaF has emerged as a novel tracer of active microcalcification in the aortic valve and coronary arteries. Coronary PETxa0imaging remains challenging because of the small caliber of the vessels and their complex motion. Currently, mostxa0coronary imaging uses combined PET and computed tomographic imaging, but there is increasing enthusiasm for PET/MR imaging because of its reduced radiation, potential to correct for motion, and the complementary informationxa0available from cardiac MR in a single scan.nnnMETHODSnTwenty-three patients with diagnosed or documented risk factors for coronary artery disease underwent either 18F-FDG or 18F-NaF PET/MR imaging. Standard breath-held MR-based attenuation correction was compared with a novel free-breathing approach. The impact on PET image artifacts and the interpretation of vascular uptake were evaluated semiquantitatively by expert readers. Moreover, PET reconstructions with more algorithm iterations were compared visually and by target-to-background ratio.nnnRESULTSnImage quality was significantly improved by novel free-breathing attenuation correction. Moreover, conspicuity of coronary uptake was improved by increasing the number of algorithm iterations from 3 to 6. Elevated radiotracer uptake could be localized to individual coronary lesions using both 18F-FDG (nxa0= 1, maximal target-to-background ratioxa0=xa01.61) and 18F-NaF (nxa0= 7, maximal target-to-background ratioxa0= 1.55 ± 0.37), including in 1 culprit plaque post-myocardial infarction confirmed by myocardial late gadolinium enhancement.nnnCONCLUSIONSnThe authors provide the first demonstration of successful, low-radiation (7.2 mSv) PET/MR imaging of inflammation and microcalcification activity in the coronary arteries. However, this requires specializedxa0approaches tailored to coronary imaging for both attenuation correction and PET reconstruction.

Clinical Utility of Combined FDG-PET/MR to Assess Myocardial Disease

The assessment of both the pattern and activity of myocardial injury has important implications for the clinical management of patients with cardiovascular disease. Comprehensive evaluation of these has previously been challenging using a single imaging modality.nnCardiac magnetic resonance (CMR)

18F-Sodium Fluoride PET/MR for the Assessment of Cardiac Amyloidosis

Cardiac amyloidosis exists in 2 predominant forms: acquired monoclonal immunoglobulin light-chain (AL) and transthyretin-related (familial and wild-type/senile) amyloid (ATTR). Differentiation is important because they have different prognoses and are amenable to different treatment strategies.

Efficacy and safety assessment of a TRAF6-targeted nanoimmunotherapy in atherosclerotic mice and non-human primates

Macrophage accumulation in atherosclerosis is directly linked to the destabilization and rupture of plaque, causing acute atherothrombotic events. Circulating monocytes enter the plaque and differentiate into macrophages, where they are activated by CD4+ T lymphocytes through CD40–CD40 ligand signalling. Here, we report the development and multiparametric evaluation of a nanoimmunotherapy that moderates CD40–CD40 ligand signalling in monocytes and macrophages by blocking the interaction between CD40 and tumour necrosis factor receptor-associated factor 6 (TRAF6). We evaluated the biodistribution characteristics of the nanoimmunotherapy in apolipoprotein E-deficient (Apoe–/–) mice and in non-human primates by in vivo positron-emission tomography imaging. In Apoe–/– mice, a 1-week nanoimmunotherapy treatment regimen achieved significant anti-inflammatory effects, which was due to the impaired migration capacity of monocytes, as established by a transcriptome analysis. The rapid reduction of plaque inflammation by the TRAF6-targeted nanoimmunotherapy and its favourable toxicity profiles in both mice and non-human primates highlights the translational potential of this strategy for the treatment of atherosclerosis.A nanoparticle-based immunotherapy targeted to a protein responsible for signalling between monocytes and macrophages reduces plaque inflammation in atherosclerotic mice and appears to be safe in non-human primates.

Quantitative PET image reconstruction employing nested expectation-maximization deconvolution for motion compensation

Bulk body motion may randomly occur during PET acquisitions introducing blurring, attenuation-emission mismatches and, in dynamic PET, discontinuities in the measured time activity curves between consecutive frames. Meanwhile, dynamic PET scans are longer, thus increasing the probability of bulk motion. In this study, we propose a streamlined 3D PET motion-compensated image reconstruction (3D-MCIR) framework, capable of robustly deconvolving intra-frame motion from a static or dynamic 3D sinogram. The presented 3D-MCIR methods need not partition the data into multiple gates, such as 4D MCIR algorithms, or access list-mode (LM) data, such as LM MCIR methods, both associated with increased computation or memory resources. The proposed algorithms can support compensation for any periodic and non-periodic motion, such as cardio-respiratory or bulk motion, the latter including rolling, twisting or drifting. Inspired from the widely adopted point-spread function (PSF) deconvolution 3D PET reconstruction techniques, here we introduce an image-based 3D generalized motion deconvolution method within the standard 3D maximum-likelihood expectation-maximization (ML-EM) reconstruction framework. In particular, we initially integrate a motion blurring kernel, accounting for every tracked motion within a frame, as an additional MLEM modeling component in the image space (integrated 3D-MCIR). Subsequently, we replaced the integrated model component with a nested iterative Richardson-Lucy (RL) image-based deconvolution method to accelerate the MLEM algorithm convergence rate (RL-3D-MCIR). The final method was evaluated with realistic simulations of whole-body dynamic PET data employing the XCAT phantom and real human bulk motion profiles, the latter estimated from volunteer dynamic MRI scans. In addition, metabolic uptake rate Ki parametric images were generated with the standard Patlak method. Our results demonstrate significant improvement in contrast-to-noise ratio (CNR) and noise-bias performance in both dynamic and parametric images. The proposed nested RL-3D-MCIR method is implemented on the Software for Tomographic Image Reconstruction (STIR) open-source platform and is scheduled for public release.

Whole body parametric imaging on clinical scanner: Direct 4D reconstruction with simultaneous attenuation estimation and time-dependent normalization

Whole body dynamic PET imaging has the potential to enhance detectability and quantification when assessing disease stage or progress. The same body region is repeatedly scanned within relatively short acquisition frames and with delays between time samples. Repeated scanning is sensitive to patient motion, which may cause mismatches between attenuation and activity maps and thus erroneous correction factors. Moreover, since count rates change with time, standard software correction factors can be time dependent. The generation of parametric images requires proper physiological modeling and has been shown to benefit from so-called direct 4D reconstruction methods. In this work we extend the MLACF/MLAA algorithms for application to dynamic direct reconstruction. Handling time-dependent normalization requires a redesign of the existing algorithm as well. The reconstruction methodology was verified on Siemens mCT scanner patient data using the standard Patlak model. Different number of frames and scan initiation time points were investigated. Initial results showed that direct 4D reconstruction outperformed the indirect approach. Available CT attenuation information can be corrected based on emission data.

Generalized PSF modeling for optimized quantitation in PET imaging

Point-spread function (PSF) modeling offers the ability to account for resolution degrading phenomena within the PET image generation framework. PSF modeling improves resolution and enhances contrast, but at the same time significantly alters image noise properties and induces edge overshoot effect. Thus, studying the effect of PSF modeling on quantitation task performance can be very important. Frameworks explored in the past involved a dichotomy of PSF versus no-PSF modeling. By contrast, the present work focuses on quantitative performance evaluation of standard uptake value (SUV) PET images, while incorporating a wide spectrum of PSF models, including those that under- and over-estimate the true PSF, for the potential of enhanced quantitation of SUVs. The developed framework first analytically models the true PSF, considering a range of resolution degradation phenomena (including photon non-collinearity, inter-crystal penetration and scattering) as present in data acquisitions with modern commercial PET systems. In the context of oncologic liver FDG PET imaging, we generated 200 noisy datasets per image-set (with clinically realistic noise levels) using an XCAT anthropomorphic phantom with liver tumours of varying sizes. These were subsequently reconstructed using the OS-EM algorithm with varying PSF modelled kernels. We focused on quantitation of both SUVmean and SUVmax, including assessment of contrast recovery coefficients, as well as noise-bias characteristics (including both image roughness and coefficient of-variability), for different tumours/iterations/PSF kernels. It was observed that overestimated PSF yielded more accurate contrast recovery for a range of tumours, and typically improved quantitative performance. For a clinically reasonable number of iterations, edge enhancement due to PSF modeling (especially due to over-estimated PSF) was in fact seen to lower SUVmean bias in small tumours. Overall, the results indicate that exactly matched PSF modeling does not offer optimized PET quantitation, and that PSF overestimation may provide enhanced SUV quantitation. Furthermore, generalized PSF modeling may provide a valuable approach for quantitative tasks such as treatment-response assessment and prognostication.

Novel quantitative whole-body parametric PET imaging utilizing multiple clustering realizations

Whole-body parametric PET imaging along with Patlak graphical analysis has the potential to provide improved diagnosis. However, a voxel-based fitting approach for a short dynamic scan protocol results in high statistical noise in the parametric images. The objective of our study is to present the framework of a novel multiple clustering realizations (MCR) method for estimating parametric images with improved image quality. The method relies primarily on using standard k-means clustering for segmenting the time-activity curves within the whole-body volume. In addition, in order to obtain improved accuracy without increasing noise, multiple realizations of clustering were performed. During each realization, cluster centers were selected from a unique ordered set of time-activity curves within the whole body volume. All the remaining data were classified into the cluster centers based on minimum Eucledian distance measure. Patlak analysis was performed on the cluster average to form the slope and intercept images. Parametric images thus obtained for all realizations were averaged. An XCAT phantom based simulations for the torso were performed using dynamic time-activity curves to model FDG uptake. Five dynamic images each representing 1 min scan time with 7 min intervals were created starting 60 minutes post injection. In addition, 5 whole-body dynamic FDG patient datasets with image-derived blood input function and whole-body dynamic data measurements were also used. All dynamic data were reconstructed using OSEM applying corrections for image-degrading factors. Slope and intercept parametric images were obtained for the voxel-fitting and MCR method. Noise in a liver region of interest increased as a function of the number of clusters for the simulated data. On the other hand, bias decreased with increasing number of clusters. However, as number of clustering realizations increased, noise reduced and Ki estimates stabilized. The parametric images obtained with MCR method showed better image quality compared to voxel-based fitting method for the patient and simulated datasets. Multiple clustering realizations method has the potential to provide improved parametric image quality for short scan whole-body parametric PET imaging.

Author Correction: Efficacy and safety assessment of a TRAF6-targeted nanoimmunotherapy in atherosclerotic mice and non-human primates

In the version of this Article originally published, the surname of the author Edward A. Fisher was spelt incorrectly as ‘Fischer’. This has now been corrected.