Comparison of analytical methods of brain [18F]FDG-PET after severe traumatic brain injury

A short 18F-FDG imaging window triple injection neuroimaging protocol for parametric mapping in PET

BACKGROUND

In parametric PET, kinetic parameters are extracted from dynamic PET images. It is not commonly used in clinical practice because of long scan times and the requirement for an arterial input function (AIF). To address these limitations, we designed an 18F-fluorodeoxyglucose (18F-FDG) triple injection dynamic PET protocol for brain imaging with a standard field of view PET scanner using a 24-min imaging window and an input function modeled using measurements from a region of interest placed over the left ventricle.

METHODS

To test the protocol in 6 healthy participants, we examined the quality of voxel-based maps of kinetic parameters in the brain generated using the two-tissue compartment model and compared estimated parameter values with previously published values. We also utilized data from a 36-min validation imaging window to compare (1) the modeled AIF against the input function measured in the validation window; and (2) the net influx rate ([Formula: see text]) computed using parameter estimates from the short imaging window against the net influx rate obtained using Patlak analysis in the validation window.

RESULTS

Compared to the AIF measured in the validation window, the input function estimated from the short imaging window achieved a mean area under the curve error of 9%. The voxel-wise Pearson's correlation between [Formula: see text] estimates from the short imaging window and the validation imaging window exceeded 0.95.

CONCLUSION

The proposed 24-min triple injection protocol enables parametric 18F-FDG neuroimaging with noninvasive estimation of the AIF from cardiac images using a standard field of view PET scanner.

Prediction of voluntary movements of the upper extremities by resting state-brain regional glucose metabolism in patients with chronic severe brain injury: A pilot study

Confirmation of the exact voluntary movements of patients with disorder of consciousness following severe traumatic brain injury (TBI) is difficult because of the associated communication disturbances. In this pilot study, we investigated whether regional brain glucose metabolism assessed by ¹⁸ F-fluorodeoxyglucose positron emission tomography (FDG-PET) at rest could predict voluntary movement in severe TBI patients, particularly those with sufficient upper limb capacity to use communication devices. We visually and verbally instructed patients to clasp or open their hands. After video capture, three independent rehabilitation therapists determined whether the patients' movements were voluntary or involuntary. The results were compared with the standardized uptake value in the primary motor cortex, referring to the Penfield's homunculus, by resting state by FDG-PET imaged 1 year prior. Results showed that glucose uptake in the left (p = 0.0015) and right (p = 0.0121) proximal limb of the primary motor cortex, based on Penfield's homunculus on cerebral cartography, may reflect contralateral voluntary movement. Receiver operating characteristic curve analysis showed that a mean cutoff standardized uptake value of 5.47 ± 0.08 provided the best sensitivity and specificity for differentiating between voluntary and involuntary movements in each area. FDG-PET may be a useful and robust biomarker for predicting long-term recovery of motor function in severe TBI patients with disorders of consciousness.

Brain Trauma Imaging

Imaging of mild traumatic brain injury (TBI) using conventional techniques such as CT or MRI often results in no specific imaging correlation that would explain cognitive and clinical symptoms. Molecular imaging of mild TBI suggests that secondary events after injury can be detected using PET. However, no single specific pattern emerges that can aid in diagnosing the injury or determining the prognosis of the long-term behavioral profiles, indicating the heterogeneous and diffuse nature of TBI. Chronic traumatic encephalopathy, a primary tauopathy, has been shown to be strongly associated with repetitive TBI. In vivo data on the available tau PET tracers, however, have produced mixed results and overall low retention profiles in athletes with a history of repetitive mild TBI. Here, we emphasize that the lack of a mechanistic understanding of chronic TBI has posed a challenge when interpreting the results of molecular imaging biomarkers. We advocate for better target identification, improved analysis techniques such as machine learning or artificial intelligence, and novel tracer development.

Non-invasive quantification of cerebral glucose metabolism using Gjedde-Patlak plot and image-derived input function from the aorta

INTRODUCTION

We aimed at evaluating a Gjedde-Patlak plot and non-invasive image-derived input functions (IDIF) from the aorta to quantify cerebral glucose metabolic rate (CMRglc) in comparison to the reference standard based on sampling the arterial input function (AIF).

METHOD

Six healthy subjects received 200 MBq [¹⁸F]FDG simultaneously with the initiation of a three-part dynamic PET recording consisting of a 15 min-recording of the aorta, a 40 min-recording of the brain and finally 2 min-recording of the aorta. Simultaneously, the arterial ¹⁸F concentration was measured via arterial cannulation. Regions of interest were drawn in the aorta and the brain and time-activity curves extracted. The IDIF was obtained by fitting a triple exponential function to the aorta time-activity curve after the initial peak including the late aorta frame, thereby interpolating the arterial blood activity concentration during the brain scan. CMRglc was calculated from Gjedde-Patlak plots using AIF and IDIF, respectively and the predictive value was examined. Results from frontal cortex, insula, hippocampus and cerebellum were compared by paired t-test and agreement between the methods was analyzed by Bland-Altman plot statistics.

RESULTS

There was a strong linear relationship and an excellent agreement between the methods (mean±SD of CMRglcIDIF (μmol 100 g^-1 min^-1), mean difference, mean relative difference, 95% limits of agreement): frontal cortex: 30.8 ± 3.3, 0.5, 2.2%, [-1,6:2.5], insula: 25.4 ± 2.2, 0.4, 2.4%, [-1.4:2.2], hippocampus: 16.9 ± 1.2, 0.4, 3.8%, [-1.1:2.0] and cerebellum: 23.4 ± 1.9, 0.5, 3.1%, [-1.4:2.5]).

CONCLUSION

We found excellent agreement between CMRglc obtained with an IDIF from the aorta and the reference standard with AIF. A non-invasive three-part dynamic [¹⁸F]FDG PET recording is feasible as a non-invasive alternative for reliable quantification of cerebral glucose metabolism in all scanner systems. This is useful in patients with presumed global cerebral changes owing to systemic disease or for the monitoring of treatment effects.

In vivo synaptic density relates to glucose metabolism at rest in healthy subjects, but is strongly modulated by regional differences

Preclinical and postmortem studies have suggested that regional synaptic density and glucose consumption (CMRGlc) are strongly related. However, the relation between synaptic density and cerebral glucose metabolism in the human brain has not directly been assessed in vivo. Using [¹¹C]UCB-J binding to synaptic vesicle glycoprotein 2 A (SV2A) as indicator for synaptic density and [¹⁸F]FDG for measuring cerebral glucose consumption, we studied twenty healthy female subjects (age 29.6 ± 9.9 yrs) who underwent a single-day dual-tracer protocol (GE Signa PET-MR). Global measures of absolute and relative CMRGlc and specific binding of [¹¹C]UCB-J were indeed highly significantly correlated (r > 0.47, p < 0.001). However, regional differences in relative [¹⁸F]FDG and [¹¹C]UCB-J uptake were observed, with up to 19% higher [¹¹C]UCB-J uptake in the medial temporal lobe (MTL) and up to 17% higher glucose metabolism in frontal and motor-related areas and thalamus. This pattern has a considerable overlap with the brain regions showing different levels of aerobic glycolysis. Regionally varying energy demands of inhibitory and excitatory synapses at rest may also contribute to this difference. Being unaffected by astroglial and/or microglial energy demands, changes in synaptic density in the MTL may therefore be more sensitive to early detection of pathological conditions compared to changes in glucose metabolism.