Multiparametric cardiac18F-FDG PET in humans: pilot comparison of FDG delivery rate with82Rb myocardial blood flow

Optimization-derived blood input function using a kernel method and its evaluation with total-body PET for brain parametric imaging

Dynamic PET allows quantification of physiological parameters through tracer kinetic modeling. For dynamic imaging of brain or head and neck cancer on conventional PET scanners with a short axial field of view, the image-derived input function (ID-IF) from intracranial blood vessels such as the carotid artery (CA) suffers from severe partial volume effects. Alternatively, optimization-derived input function (OD-IF) by the simultaneous estimation (SIME) method does not rely on an ID-IF but derives the input function directly from the data. However, the optimization problem is often highly ill-posed. We proposed a new method that combines the ideas of OD-IF and ID-IF together through a kernel framework. While evaluation of such a method is challenging in human subjects, we used the uEXPLORER total-body PET system that covers major blood pools to provide a reference for validation.

METHODS

The conventional SIME approach estimates an input function using a joint estimation together with kinetic parameters by fitting time activity curves from multiple regions of interests (ROIs). The input function is commonly parameterized with a highly nonlinear model which is difficult to estimate. The proposed kernel SIME method exploits the CA ID-IF as a priori information via a kernel representation to stabilize the SIME approach. The unknown parameters are linear and thus easier to estimate. The proposed method was evaluated using 18F-fluorodeoxyglucose studies with both computer simulations and 20 human-subject scans acquired on the uEXPLORER scanner. The effect of the number of ROIs on kernel SIME was also explored.

RESULTS

The estimated OD-IF by kernel SIME showed a good match with the reference input function and provided more accurate estimation of kinetic parameters for both simulation and human-subject data. The kernel SIME led to the highest correlation coefficient (R = 0.97) and the lowest mean absolute error (MAE = 10.5 %) compared to using the CA ID-IF (R = 0.86, MAE = 108.2 %) and conventional SIME (R = 0.57, MAE = 78.7 %) in the human-subject evaluation. Adding more ROIs improved the overall performance of the kernel SIME method.

CONCLUSION

The proposed kernel SIME method shows promise to provide an accurate estimation of the blood input function and kinetic parameters for brain PET parametric imaging.

Total-Body Positron Emission Tomography: Adding New Perspectives to Cardiovascular Research

The recent advent of positron emission tomography (PET) scanners that can image the entire human body opens up intriguing possibilities for cardiovascular research and future clinical applications. These new systems permit radiotracer kinetics to be measured in all organs simultaneously. They are particularly well suited to study cardiovascular disease and its effects on the entire body. They could also play a role in quantitatively measuring physiologic, metabolic, and immunologic responses in healthy individuals to a variety of stressors and lifestyle interventions, and may ultimately be instrumental for evaluating novel therapeutic agents and their molecular effects across different tissues. In this review, we summarize recent progress in PET technology and methodology, discuss several emerging cardiovascular applications for total-body PET, and place this in the context of multiorgan and systems medicine. Finally, we discuss opportunities that will be enabled by the technology, while also pointing to some of the challenges that still need to be addressed.

Normal values for 18F-FDG uptake in organs and tissues measured by dynamic whole body multiparametric FDG PET in 126 patients

BACKGROUND

Dynamic whole-body (D-WB) FDG PET/CT is a recently developed technique that allows direct reconstruction of multiparametric images of metabolic rate of FDG uptake (MR_FDG) and "free" FDG (DV_FDG). Multiparametric images have a markedly different appearance than the conventional SUV images obtained by static PET imaging, and normal values of MR_FDG and DV_FDG in frequently used reference tissues and organs are lacking. The aim of this study was therefore to: (1) provide an overview of normal MR_FDG and DV_FDG values and range of variation in organs and tissues; (2) analyse organ time-activity curves (TACs); (3) validate the accuracy of directly reconstructed MR_FDG tissue values versus manually calculated K_i (and MR_FDG) values; and (4) explore correlations between demographics, blood glucose levels and MR_FDG values. D-WB data from 126 prospectively recruited patients (100 without diabetes and 26 with diabetes) were retrospectively analysed. Participants were scanned using a 70-min multiparametric PET acquisition protocol on a Siemens Biograph Vision 600 PET/CT scanner. 13 regions (bone, brain grey and white matter, colon, heart, kidney, liver, lung, skeletal muscle of the back and thigh, pancreas, spleen, and stomach) as well as representative pathological findings were manually delineated, and values of static PET (SUV), D-WB PET (K_i, MR_FDG and DV_FDG) and individual TACs were extracted. Multiparametric values were compared with manual TAC-based calculations of K_i and MR_FDG, and correlations with blood glucose, age, weight, BMI, and injected tracer dose were explored.

RESULTS

Tissue and organ MR_FDG values showed little variation, comparable to corresponding SUV variation. All regional TACs were in line with previously published FDG kinetics, and the multiparametric metrics correlated well with manual TAC-based calculations (r² = 0.97, p < 0.0001). No correlations were observed between glucose levels and MR_FDG in tissues known not to be substrate driven, while tissues with substrate driven glucose uptake had significantly correlated glucose levels and MR_FDG values.

CONCLUSION

The multiparametric D-WB PET scan protocol provides normal MR_FDG values with little inter-subject variation and in agreement with manual TAC-based calculations and literature values. The technique therefore facilitates both accurate clinical reports and simpler acquisition of quantitative estimates of whole-body tissue glucose metabolism.

Multiparametric Evaluation of Post-MI Small Animal Models Using Metabolic ([18F]FDG) and Perfusion-Based (SYN1) Heart Viability Tracers

Cardiovascular diseases (CVD), with myocardial infarction (MI) being one of the crucial components, wreak havoc in developed countries. Advanced imaging technologies are required to obtain quick and widely available diagnostic data. This paper describes a multimodal approach to in vivo perfusion imaging using the novel SYN1 tracer based on the fluorine-18 isotope. The NOD-SCID mice were injected intravenously with SYN1 or [¹⁸F] fluorodeoxyglucose ([¹⁸F]-FDG) radiotracers after induction of the MI. In all studies, the positron emission tomography–computed tomography (PET/CT) technique was used. To obtain hemodynamic data, mice were subjected to magnetic resonance imaging (MRI). Finally, the biodistribution of the SYN1 compound was performed using Wistar rat model. SYN1 showed normal accumulation in mouse and rat hearts, and MI hearts correctly indicated impaired cardiac segments when compared to [¹⁸F]-FDG uptake. In vivo PET/CT and MRI studies showed statistical convergence in terms of the size of the necrotic zone and cardiac function. This was further supported with RNAseq molecular analyses to correlate the candidate function genes’ expression, with Serpinb1c, Tnc and Nupr1, with Trem2 and Aldolase B functional correlations showing statistical significance in both SYN1 and [¹⁸F]-FDG. Our manuscript presents a new fluorine-18-based perfusion radiotracer for PET/CT imaging that may have importance in clinical applications. Future research should focus on confirmation of the data elucidated here to prepare SYN1 for first-in-human trials.