Introduction

Quantitative positron emission tomography (PET) studies of neurodegenerative diseases typically require the measurement of arterial input functions (AIF), an invasive and risky procedure. This study aims to assess the reproducibility of [¹¹C]DPA-713 PET kinetic analysis using population-based input function (PBIF). The final goal is to possibly eliminate the need for AIF.

Materials and methods

Eighteen subjects including six healthy volunteers (HV) and twelve Parkinson disease (PD) subjects from two [¹¹C]-DPA-713 PET studies were included. Each subject underwent 90 min of dynamic PET imaging. Five healthy volunteers underwent a test-retest scan within the same day to assess the repeatability of the kinetic parameters. Kinetic modeling was carried out using the Logan total volume of distribution (V_T) model. For each data set, kinetic analysis was performed using a patient-specific AIF (PSAIF, ground-truth standard) and then repeated using the PBIF. PBIF was generated using the leave-one-out method for each subject from the remaining 17 subjects and after normalizing the PSAIFs by 3 techniques: (a) Weight_subject×Dose_Injected, (b) area under AIF curve (AUC), and (c) Weight_subject×AUC. The variability in the V_T measured with PSAIF, in the test-retest study, was determined for selected brain regions (white matter, cerebellum, thalamus, caudate, putamen, pallidum, brainstem, hippocampus, and amygdala) using the Bland-Altman analysis and for each of the 3 normalization techniques. Similarly, for all subjects, the variabilities due to the use of PBIF were assessed.

Results

Bland-Altman analysis showed systematic bias between test and retest studies. The corresponding mean bias and 95% limits of agreement (LOA) for the studied brain regions were 30% and ± 70%. Comparing PBIF- and PSAIF-based V_T estimate for all subjects and all brain regions, a significant difference between the results generated by the three normalization techniques existed for all brain structures except for the brainstem (P-value = 0.095). The mean % difference and 95% LOA is -10% and ±45% for Weight_subject×Dose_Injected; +8% and ±50% for AUC; and +2% and ± 38% for Weight_subject×AUC. In all cases, normalizing by Weight_subject×AUC yielded the smallest % bias and variability (% bias = ±2%; LOA = ±38% for all brain regions). Estimating the reproducibility of PBIF-kinetics to PSAIF based on disease groups (HV/PD) and genotype (MAB/HAB), the average V_T values for all regions obtained from PBIF is insignificantly higher than PSAIF (%difference = 4.53%, P-value = 0.73 for HAB; and %difference = 0.73%, P-value = 0.96 for MAB). PBIF also tends to overestimate the difference between PD and HV for HAB (% difference = 32.33% versus 13.28%) and underestimate it in MAB (%difference = 6.84% versus 20.92%).

Conclusions

PSAIF kinetic results are reproducible with PBIF, with variability in V_T within that obtained for the test-retest studies. Therefore, V_T assessed using PBIF-based kinetic modeling is clinically feasible and can be an alternative to PSAIF.

Objectives

This study sought to develop an integrative positron emission tomography (PET) with magnetic resonance imaging (MRI) procedure for accurate atherosclerotic plaque phenotyping, facilitated by clinically approved and nanobody radiotracers.

Background

Noninvasive characterization of atherosclerosis remains a challenge in clinical practice. The limitations of current diagnostic methods demonstrate that, in addition to atherosclerotic plaque morphology and composition, disease activity needs to be evaluated.

Methods

We screened 3 nanobody radiotracers targeted to different biomarkers of atherosclerosis progression, namely vascular cell adhesion molecule (VCAM)-1, lectin-like oxidized low-density lipoprotein receptor (LOX)-1, and macrophage mannose receptor (MMR). The nanobodies, initially radiolabeled with copper-64 (⁶⁴Cu), were extensively evaluated in Apoe^-/- mice and atherosclerotic rabbits using a combination of in vivo PET/MRI readouts and ex vivo radioactivity counting, autoradiography, and histological analyses.

Results

The 3 nanobody radiotracers accumulated in atherosclerotic plaques and displayed short circulation times due to fast renal clearance. The MMR nanobody was selected for labeling with gallium-68 (⁶⁸Ga), a short-lived radioisotope with high clinical relevance, and used in an ensuing atherosclerosis progression PET/MRI study. Macrophage burden was longitudinally studied by ⁶⁸Ga-MMR-PET, plaque burden by T2-weighted MRI, and neovascularization by dynamic contrast-enhanced (DCE) MRI. Additionally, inflammation and microcalcifications were evaluated by fluorine-18 (¹⁸F)-labeled fluorodeoxyglucose (¹⁸F-FDG) and ¹⁸F-sodium fluoride (¹⁸F-NaF) PET, respectively. We observed an increase in all the aforementioned measures as disease progressed, and the imaging signatures correlated with histopathological features.

Conclusions

We have evaluated nanobody-based radiotracers in rabbits and developed an integrative PET/MRI protocol that allows noninvasive assessment of different processes relevant to atherosclerosis progression. This approach allows the multiparametric study of atherosclerosis and can aid in early stage anti-atherosclerosis drug trials.