Parametric Imaging of Biologic Activity of Atherosclerosis Using Dynamic Whole-Body Positron Emission Tomography

BACKGROUND

For molecular imaging of atherosclerotic vessel wall activity, tracer kinetic analysis may yield improved contrast versus blood, more robust quantitative parameters, and more reliable characterization of systems biology.

OBJECTIVES

The authors introduce a novel dynamic whole-body positron emission tomography (PET) protocol that is enabled by rapid continuous camera table motion, followed by reconstruction of parametric data sets using voxel-based Patlak graphical analysis.

METHODS

Twenty-five subjects were prospectively enrolled and underwent dynamic PET up to 90 minutes after injection of 2-[¹⁸F]fluoro-2-deoxy-D-glucose (FDG). Two sets of images were generated: 1) the established standard of static standardized uptake value (SUV) images; and 2) parametric images of the metabolic rate of FDG (MR_FDG) using the Patlak plot-derived influx rate. Arterial wall signal was measured and compared using the volume-of-interest technique, and its association with hematopoietic and lymphoid organ signal and atherosclerotic risk factors was explored.

RESULTS

Parametric MR_FDG images provided excellent arterial wall visualization, with elimination of blood-pool activity, and enhanced focus detectability and reader confidence. Target-to-background ratio (TBR) from MR_FDG images was significantly higher compared with SUV images (2.6 ± 0.8 vs 1.4 ± 0.2; P < 0.0001), confirming improved arterial wall contrast. On MR_FDG images, arterial wall signal showed improved correlation with hematopoietic and lymphoid organ activity (spleen P = 0.0009; lymph nodes P = 0.0055; and bone marrow P = 0.0202) and increased with the number of atherosclerotic risk factors (r = 0.49; P = 0.0138), where signal from SUV images (SUV_maxP = 0.9754; TBR_maxP = 0.8760) did not.

CONCLUSIONS

Absolute quantification of MR_FDG is feasible for arterial wall using dynamic whole-body PET imaging. Parametric images provide superior arterial wall contrast, and they might be better suited to explore the relationship between arterial wall activity, systemic organ networks, and cardiovascular risk. This novel methodology may serve as a platform for future diagnostic and therapeutic clinical studies targeting the biology of arterial wall disease.

caliPER: A software for blood-free parametric Patlak mapping using PET/MRI input function

Routine clinical use of absolute PET quantification techniques is limited by the need for serial arterial blood sampling for input function and more importantly by the lack of automated pharmacokinetic analysis tools that can be readily implemented in clinic with minimal effort. PET/MRI provides the ability for absolute quantification of PET probes without the need for serial arterial blood sampling using image-derived input functions (IDIFs). Here we introduce caliPER, a modular and scalable software for simplified pharmacokinetic modelling of PET probes with irreversible uptake or binding based on PET/MR IDIFs and Patlak Plot analysis. caliPER generates regional values or parametric maps of net influx rate (K_i) using reconstructed dynamic PET images and anatomical MRI aligned to PET for IDIF vessel delineation. We evaluated the performance of caliPER for blood-free region-based and pixel-wise Patlak analyses of [¹⁸F] FDG by comparing caliPER IDIF to serial arterial blood input functions and its application in imaging brain glucose hypometabolism in Frontotemporal dementia. IDIFs corrected for partial volume errors including spill-out and spill-in effects were similar to arterial blood input functions with a general bias of around 6-8%, even for arteries <5 mm. The K_i and cerebral metabolic rate of glucose estimated using caliPER IDIF were similar to estimates using arterial blood sampling (<2%) and within limits of whole brain values reported in literature. Overall, caliPER is a promising tool for irreversible PET tracer quantification and can simplify the ability to perform parametric analysis in clinical settings without the need for blood sampling.

Short 2-[18F]Fluoro-2-Deoxy-D-Glucose PET Dynamic Acquisition Protocol to Evaluate the Influx Rate Constant by Regional Patlak Graphical Analysis in Patients With Non-Small-Cell Lung Cancer

Purpose: To test a short 2-[¹⁸F]Fluoro-2-deoxy-D-glucose (2-[¹⁸F]FDG) PET dynamic acquisition protocol to calculate K_i using regional Patlak graphical analysis in patients with non-small-cell lung cancer (NSCLC).

Methods: 24 patients with NSCLC who underwent standard dynamic 2-[¹⁸F]FDG acquisitions (60 min) were randomly divided into two groups. In group 1 (n = 10), a population-based image-derived input function (pIDIF) was built using a monoexponential trend (10–60 min), and a leave-one-out cross-validation (LOOCV) method was performed to validate the pIDIF model. In group 2 (n = 14), K_i was obtained by standard regional Patlak plot analysis using IDIF (0–60 min) and tissue response (10–60 min) curves from the volume of interests (VOIs) placed on descending thoracic aorta and tumor tissue, respectively. Moreover, with our method, the Patlak analysis was performed to obtain K_i,s using IDIF_Fitted curve obtained from PET counts (0–10 min) followed by monoexponential coefficients of pIDIF (10–60 min) and tissue response curve obtained from PET counts at 10 min and between 40 and 60 min, simulating two short dynamic acquisitions. Both IDIF and IDIF_Fitted curves were modeled to assume the value of 2-[¹⁸F]FDG plasma activity measured in the venous blood sampling performed at 45 min in each patient. Spearman's rank correlation, coefficient of determination, and Passing–Bablok regression were used for the comparison between K_i and K_i,s. Finally, K_i,s was obtained with our method in a separate group of patients (group 3, n = 8) that perform two short dynamic acquisitions.

Results: Population-based image-derived input function (10–60 min) was modeled with a monoexponential curve with the following fitted parameters obtained in group 1: a = 9.684, b = 16.410, and c = 0.068 min⁻¹. The LOOCV error was 0.4%. In patients of group 2, the mean values of K_i and K_i,s were 0.0442 ± 0.0302 and 0.33 ± 0.0298, respectively (R² = 0.9970). The Passing–Bablok regression for comparison between K_i and K_i,s showed a slope of 0.992 (95% CI: 0.94–1.06) and intercept value of −0.0003 (95% CI: −0.0033–0.0011).

Conclusions: Despite several practical limitations, like the need to position the patient twice and to perform two CT scans, our method contemplates two short 2-[¹⁸F]FDG dynamic acquisitions, a population-based input function model, and a late venous blood sample to obtain robust and personalized input function and tissue response curves and to provide reliable regional K_i estimation.

Dual time point method for the quantification of irreversible tracer kinetics: A reference tissue approach applied to [18F]-FDOPA brain PET

The Patlak graphical analysis (PGA_REF) for quantification of irreversible tracer binding with a reference tissue model was approximated by a dual time point imaging approach (DTP_REF). The DTP_REF was applied to 18 [¹⁸F]-FDOPA brain scans using the occipital cortex as reference region (DTP_OCC) and compared to both PGA_OCC and striatal-to-occipital ratios (SOR). Pearson correlation analysis and Bland-Altman plots showed an excellent correlation and good agreement between DTP_OCC and PGA_OCC, while correlations between SOR and PGA_OCC were consistently lower. Linear discriminant analysis (LDA) demonstrated a similar performance for all methods in differentiating patients with Parkinson's disease (PD) from healthy controls (HC). Specifically for [¹⁸F]-FDOPA brain imaging, these findings validate DTP_OCC as an approximation for PGA_OCC, providing the same quantitative information while reducing the acquisition time to two short static scans. For PD patients, this approach can greatly improve patient comfort while reducing motion artifacts and increasing image quality. In general, DTP_REF can improve the clinical applicability of tracers with irreversible binding characteristics when a reference tissue is available.