The continual innovation of commercial PET/CT solutions in nuclear cardiology: Siemens Healthineers

Inter-Software Reproducibility of Quantitative Values of Myocardial Blood Flow and Coronary Flow Reserve Acquired by [13N]NH3 MPI PET/CT and the Effect of Motion Correction Tools

Background: The choice of software package (SP) for image processing affects the reproducibility of myocardial blood flow (MBF) values in [13N]NH3 PET/CT scans. However, the impact of motion correction (MC) tools-integrated software motion correction (ISMC) or data-driven motion correction (DDMC)-on the inter-software reproducibility of MBF has not been studied. This research aims to evaluate reproducibility among three commonly used SPs and the role of MC. Methods: Thirty-six PET/CT studies from patients without myocardial ischemia or infarction were processed using QPET, Corridor-4DM (4DM), and syngo.MBF (syngo). MBF and coronary flow reserve (CFR) values were obtained without motion correction (NMC) and with ISMC and DDMC. Intraclass correlation coefficients (ICC) and Bland-Altman (BA) plots were used to analyze agreement. Results: Good or excellent reproducibility (ICC ≥ 0.77) was found for rest-MBF values, regardless of the SPs or use of MC. In contrast, stress-MBF and CFR values presented mostly a moderate agreement when NMC was used. The RCA territory consistently had the lowest agreement in stress-MBF and CFR in the comparisons involving QPET. The use of MC, particularly DDMC, enhanced the reproducibility of most of the stress-MBF and CFR values by improving ICCs and reducing bias and limits of agreement (LoA) in BA analysis. Conclusions: MBF quantification agreement between SPs is strong for rest-MBF values but suboptimal for stress-MBF and CFR values. MC tools, especially DDMC, are recommended for improving reproducibility in stress-MBF assessments, although differences in SP reproducibility up to 0.77 mL/g/min in global stress-MBF and up to 0.88 in global CFR remain despite the use of MC.

PET Imaging of Metabolism, Perfusion, and Hypoxia: FDG and Beyond

ABSTRACT

Imaging glucose metabolism with [18F]fluorodeoxyglucose positron emission tomography has transformed the diagnostic and treatment algorithms of numerous malignancies in clinical practice. The cancer phenotype, though, extends beyond dysregulation of this single pathway. Reprogramming of other pathways of metabolism, as well as altered perfusion and hypoxia, also typifies malignancy. These features provide other opportunities for imaging that have been developed and advanced into humans. In this review, we discuss imaging metabolism, perfusion, and hypoxia in cancer, focusing on the underlying biology to provide context. We conclude by highlighting the ability to image multiple facets of biology to better characterize cancer and guide targeted treatment.

Commercialization potential of PET (polyethylene terephthalate) recycled nanomaterials: A review on validation parameters

Polyethylene Terephthalate (PET) is a polymer which is considered as one of the major contaminants to the environment. The PET waste materials can be recycled to produce value-added products. PET can be converted to nanoparticles, nanofibers, nanocomposites, and nano coatings. To extend the applications of PET nanomaterials, understanding its commercialization potential is important. In addition, knowledge about the factors affecting recycling of PET based nanomaterials is essential. The presented review is focused on understanding the PET commercialization aspects, keeping in mind market analysis, growth drivers, regulatory affairs, safety considerations, issues associated with scale-up, manufacturing challenges, economic viability, and cost-effectiveness. In addition, the paper elaborates the challenges associated with the use of PET based nanomaterials. These challenges include PET contamination to water, soil, sediments, and human exposure to PET nanomaterials. Moreover, the paper discusses in detail about the factors affecting PET recycling, commercialization, and circular economy with specific emphasis on life cycle assessment (LCA) of PET recycled nanomaterials.

Improved [18F]FDG PET/CT Diagnostic Accuracy for Infective Endocarditis Using Conventional Cardiac Gating or Combined Cardiac and Respiratory Motion Correction (CardioFreezeTM)

Infective endocarditis (IE) is a serious and diagnostically challenging condition. [18F]FDG PET/CT is valuable for evaluating suspected IE, but it is susceptible to motion-related artefacts. This study investigated the potential benefits of cardiac motion correction for [18F]FDG PET/CT. In this prospective study, patients underwent [18F]FDG PET/CT for suspected IE, combined with a conventional cardiac gating sequence, a data-driven cardiac and respiratory gating sequence (CardioFreezeTM), or both. Scans were performed in adherence to EANM guidelines and assessors were blinded to patients' clinical contexts. Final diagnosis of IE was established based on multidisciplinary consensus after a minimum of 4 months follow-up and surgical findings, whenever performed. Seven patients participated in the study, undergoing both an ungated [18F] FDG-PET/CT and a scan with either conventional cardiac gating, CardioFreezeTM, or both. Cardiac motion correction improved the interpretability of [18F]FDG PET/CT in four out of five patients with valvular IE lesions, regardless of the method of motion correction used, which was statistically significant by Wilcoxon's signed rank test: p = 0.046. In one patient the motion-corrected sequence confirmed the diagnosis of endocarditis, which had been missed on non-gated PET. The performance of the two gating sequences was comparable. In conclusion, in this exploratory study, cardiac motion correction of [18F]FDG PET/CT improved the interpretability of [18F]FDG PET/CT. This may improve the sensitivity of PET/CT for suspected IE. Further larger comparative studies are necessary to confirm the additive value of these cardiac motion correction methods.

PET respiratory motion correction: quo vadis?

Positron emission tomography (PET) respiratory motion correction has been a subject of great interest for the last twenty years, prompted mainly by the development of multimodality imaging devices such as PET/computed tomography (CT) and PET/magnetic resonance imaging (MRI). PET respiratory motion correction involves a number of steps including acquisition synchronization, motion estimation and finally motion correction. The synchronization steps include the use of different external device systems or data driven approaches which have been gaining ground over the last few years. Patient specific or generic motion models using the respiratory synchronized datasets can be subsequently derived and used for correction either in the image space or within the image reconstruction process. Similar overall approaches can be considered and have been proposed for both PET/CT and PET/MRI devices. Certain variations in the case of PET/MRI include the use of MRI specific sequences for the registration of respiratory motion information. The proposed review includes a comprehensive coverage of all these areas of development in field of PET respiratory motion for different multimodality imaging devices and approaches in terms of synchronization, estimation and subsequent motion correction. Finally, a section on perspectives including the potential clinical usage of these approaches is included.

Assessing Reliability of Myocardial Blood Flow After Motion Correction With Dynamic PET Using a Bayesian Framework

The estimation of myocardial blood flow (MBF) in dynamic PET can be biased by many different processes. A major source of error, particularly in clinical applications, is patient motion. Patient motion, or gross motion, creates displacements between different PET frames as well as between the PET frames and the CT-derived attenuation map, leading to errors in MBF calculation from voxel time series. Motion correction techniques are challenging to evaluate quantitatively and the impact on MBF reliability is not fully understood. Most metrics, such as signal-to-noise ratio (SNR), are characteristic of static images, and are not specific to motion correction in dynamic data. This study presents a new approach of estimating motion correction quality in dynamic cardiac PET imaging. It relies on calculating a MBF surrogate, K₁ , along with the uncertainty on the parameter. This technique exploits a Bayesian framework, representing the kinetic parameters as a probability distribution, from which the uncertainty measures can be extracted. If the uncertainty extracted is high, the parameter studied is considered to have high variability - or low confidence - and vice versa. The robustness of the framework is evaluated on simulated time activity curves to ensure that the uncertainties are consistently estimated at the multiple levels of noise. Our framework is applied on 40 patient datasets, divided in 4 motion magnitude categories. Experienced observers manually realigned clinical datasets with 3D translations to correct for motion. K₁ uncertainties were compared before and after correction. A reduction of uncertainty after motion correction of up to 60% demonstrates the benefit of motion correction in dynamic PET and as well as provides evidence of the usefulness of the new method presented.