Evaluation of Arterial Spin Labeling MRI-Comparison with 15O-Water PET on an Integrated PET/MR Scanner

[18F]MK-6240 Radioligand Delivery Indices as Surrogates of Cerebral Perfusion: Bias and Correlation Against [15O]Water

[18F]MK-6240 PET (where MK-6240 is 6-(fluoro)-3-(1H-pyrrolo[2,3-c]pyridin-1-yl)isoquinolin-5-amine) is used to assess in vivo tau deposition across the Alzheimer disease (AD) spectrum. We aimed to quantify the associations and bias of early-frame [18F]MK-6240 PET as surrogates for cerebral perfusion against gold standard [15O]water PET and the potential impact of cerebral perfusion on [18F]MK-6240 tau quantification across aging and the AD spectrum. Methods: Fourteen cognitively normal (CN, 4 young CN and 10 old CN) and 3 AD participants underwent dynamic [18F]MK-6240 PET, with 9 undergoing arterial sampling. A subset (n = 11) underwent [15O]water PET. [18F]MK-6240 perfusion indices were estimated as radiotracer delivery indices K 1 (using 2-tissue-compartment models), and relative perfusion indices were estimated as R1 (using compartmental and reference tissue models, cerebellar gray matter reference region) and early-frame SUV ratio (0-3 min). [15O]water K 1 and R1 were estimated using 1-tissue-compartment models). [18F]MK-6240 tau burden was estimated using distribution volume ratio and SUV ratio at 90-110 min. Spearman correlations, linear mixed-effect models, and Bland-Altman analyses examined relationships between [18F]MK-6240 perfusion indices against [15O]water and between estimates of perfusion and tau burden in tau-relevant regions. The impact of partial-volume correction was examined. Results: Significant correlations were observed between [18F]MK-6240 K 1 and [15O]water K 1 (ρ = 0.57); However, [18F]MK-6240 K 1 underestimated [15O]water K 1 by up to 50%, with a strong negative proportional bias. Significant correlations were observed between [18F]MK-6240 relative perfusion and [15O]water R1 (ρ > 0.84), with minimal bias. In 2 AD participants, significant correlations were observed between perfusion and [18F]MK-6240 retention. Applying partial-volume correction did not significantly impact the correlations or improve the underestimations in [18F]MK-6240 K 1 Conclusion: Using head-to-head [18F]MK-6240 and [15O]water data, we showed that [18F]MK-6240 exhibited a relatively low extraction fraction, leading to underestimation of cerebral perfusion. Our results provide further support for [18F]MK-6240 R1 as a reliable estimate of relative cerebral perfusion, with strong associations and minimal bias compared with [15O]water. In addition, lower perfusion may be associated with higher [18F]MK-6240 retention in tau-relevant regions in AD. These findings further support the use of dynamic [18F]MK-6240 in dual-imaging assessments of tau burden and vascular health.

Compartmental modeling for blood flow quantification from dynamic 15 O-water PET images of humans: a systematic review

Dynamic positron emission tomography (PET) can be used to non-invasively estimate the blood flow of different organs via compartmental modeling. Out of different PET tracers, water labeled with the radioactive15 O isotope of oxygen (half-life of 2.04 min) is freely diffusable, and therefore, very well-suited for blood flow quantification. While the earlier15 O-water PET research has primarily focused on cerebral or myocardial blood flow quantification, the recent emergence of total-body PET scanners has enabled greater application possibilities for both PET imaging in general and also15 O-water PET based blood flow quantification in particular. However, to validate new methods, it is necessary to compare them to earlier research. To help in this process, we systematically review 53 articles quantifying blood flow via compartmental modeling. We introduce the articles organized within subcategories of cerebral, myocardial, renal, pulmonary, pancreatic, hepatic, muscle, and tumor blood flow and summarize their results so that they can easily be evaluated in terms of population characteristics of the patients such as age or sex ratio and their potential diagnoses. We compare how both the compartment model used and the potential corrections for arterial blood volume, non-perfusable tissue, spill-over from the heart cavities, and time delay caused while the tracer travels between different areas of interest are generally implemented in the articles. We also analyze the differences in the data pre-processing techniques. According to our results, the estimates of cerebral and tumor blood flow vary considerably more between the articles than those of myocardial blood flow. This might be caused by differences in the model approaches or the study populations. We also note that the choice of the unit for these estimates is quite inconsistent as certain researchers seem to prefer mL/min/g over mL/min/mL even if no weight or density parameter is present in the modeling. We encourage more research on sex- and age-based differences in blood flow estimates and organ-specific blood flow quantification studies for kidneys, lungs, liver, and other important organs besides brain and heart.

Advances in neuroimaging in disorders of consciousness

Disorders of consciousness (DoC) are a heterogeneous spectrum of clinical conditions, including coma, unresponsive wakefulness syndrome, and minimally conscious state. DoC are clinically defined on the basis of behavioral cues expressed by the patients, on the assumption that such behavioral responses of the patient are representative of the patient's degree of consciousness impairment. However, many studies have highlighted the issues arising from formulating a DoC diagnosis merely on behavioral assessment. Overcoming the limitations of behavioral assessment, neuroimaging provides a direct window on the cerebral activity of the patient, bypassing the motor, perceptual, or cognitive deficits that might hamper the patient's ability to produce an appropriate behavioral response. This chapter provides an overview of available molecular, functional, and structural neuroimaging evidence in patients with DoC. This chapter introduces the neuroimaging tools available in the clinical settings of nuclear medicine and neuroradiology and presents the evidence on the role of neuroimaging tools to improve the clinical management of DoC patients, from the standpoint of differential diagnosis and prognosis. Last, we outline the open questions in the field, and point at actions that are urgently needed to fully exploit neuroimaging tools to advance scientific understanding and clinical management of DoC.

Evaluation of [11C]UCB-A positron emission tomography in human brains

BACKGROUND

In preclinical studies, the positron emission tomography (PET) imaging with [11C]UCB-A provided promising results for imaging synaptic vesicle protein 2A (SV2A) as a proxy for synaptic density. This paper reports the first-in-human [11C]UCB-A PET study to characterise its kinetics in healthy subjects and further evaluate SV2A-specific binding.

RESULTS

Twelve healthy subjects underwent 90-min baseline [11C]UCB-A scans with PET/MRI, with two subjects participating in an additional blocking scan with the same scanning procedure after a single dose of levetiracetam (1500 mg). Our results indicated abundant [11C]UCB-A brain uptake across all cortical regions, with slow elimination. Kinetic modelling of [11C]UCB-A PET using various compartment models suggested that the irreversible two-tissue compartment model best describes the kinetics of the radioactive tracer. Accordingly, the Patlak graphical analysis was used to simplify the analysis. The estimated SV2A occupancy determined by the Lassen plot was around 66%. Significant specific binding at baseline and comparable binding reduction as grey matter precludes the use of centrum semiovale as reference tissue.

CONCLUSIONS

[11C]UCB-A PET imaging enables quantifying SV2A in vivo. However, its slow kinetics require a long scan duration, which is impractical with the short half-life of carbon-11. Consequently, the slow kinetics and complicated quantification methods may restrict its use in humans.

Cerebral blood flow in schizophrenia: A systematic review and meta-analysis of MRI-based studies

INTRODUCTION

Schizophrenia-spectrum disorders (SSD) represent one of the leading causes of disability worldwide and are usually underpinned by neurodevelopmental brain abnormalities observed on a structural and functional level. Nuclear medicine imaging studies of cerebral blood flow (CBF) have already provided insights into the pathophysiology of these disorders. Recent developments in non-invasive MRI techniques such as arterial spin labeling (ASL) have allowed broader examination of CBF across SSD prompting us to conduct an updated literature review of MRI-based perfusion studies. In addition, we conducted a focused meta-analysis of whole brain studies to provide a complete picture of the literature on the topic.

METHODS

A systematic OVID search was performed in Embase, MEDLINEOvid, and PsycINFO. Studies eligible for inclusion in the review involved: 1) individuals with SSD, first-episode psychosis or clinical-high risk for psychosis, or; 2) had healthy controls for comparison; 3) involved MRI-based perfusion imaging methods; and 4) reported CBF findings. No time span was specified for the database queries (last search: 08/2022). Information related to participants, MRI techniques, CBF analyses, and results were systematically extracted. Whole-brain studies were then selected for the meta-analysis procedure. The methodological quality of each included studies was assessed.

RESULTS

For the systematic review, the initial Ovid search yielded 648 publications of which 42 articles were included, representing 3480 SSD patients and controls. The most consistent finding was that negative symptoms were linked to cortical fronto-limbic hypoperfusion while positive symptoms seemed to be associated with hyperperfusion, notably in subcortical structures. The meta-analysis integrated results from 13 whole-brain studies, across 426 patients and 401 controls, and confirmed the robustness of the hypoperfusion in the left superior and middle frontal gyri and right middle occipital gyrus while hyperperfusion was found in the left putamen.

CONCLUSION

This updated review of the literature supports the implication of hemodynamic correlates in the pathophysiology of psychosis symptoms and disorders. A more systematic exploration of brain perfusion could complete the search of a multimodal biomarker of SSD.

Medical Radiation Exposure Reduction in PET via Super-Resolution Deep Learning Model

In positron emission tomography (PET) imaging, image quality correlates with the injected [18F]-fluorodeoxyglucose (FDG) dose and acquisition time. If image quality improves from short-acquisition PET images via the super-resolution (SR) deep learning technique, it is possible to reduce the injected FDG dose. Therefore, the aim of this study was to clarify whether the SR deep learning technique could improve the image quality of the 50%-acquisition-time image to the level of that of the 100%-acquisition-time image. One-hundred-and-eight adult patients were enrolled in this retrospective observational study. The supervised data were divided into nine subsets for nested cross-validation. The mean peak signal-to-noise ratio and structural similarity in the SR-PET image were 31.3 dB and 0.931, respectively. The mean opinion scores of the 50% PET image, SR-PET image, and 100% PET image were 3.41, 3.96, and 4.23 for the lung level, 3.31, 3.80, and 4.27 for the liver level, and 3.08, 3.67, and 3.94 for the bowel level, respectively. Thus, the SR-PET image was more similar to the 100% PET image and subjectively improved the image quality, as compared to the 50% PET image. The use of the SR deep-learning technique can reduce the injected FDG dose and thus lower radiation exposure.