Accelerated 3D metabolite T1 mapping of the brain using variable-flip-angle SPICE.

PURPOSE: To develop a practical method to enable 3D T1 mapping of brain metabolites. THEORY AND METHODS: Due to the high dimensionality of the imaging problem underlying metabolite T1 mapping, measurement of metabolite T1 values has been currently limited to a single voxel or slice. This work achieved 3D metabolite T1 mapping by leveraging a recent ultrafast MRSI technique called SPICE (spectroscopic imaging by exploiting spatiospectral correlation). The Ernst-angle FID MRSI data acquisition used in SPICE was extended to variable flip angles, with variable-density sparse sampling for efficient encoding of metabolite T1 information. In data processing, a novel generalized series model was used to remove water and subcutaneous lipid signals; a low-rank tensor model with prelearned subspaces was used to reconstruct the variable-flip-angle metabolite signals jointly from the noisy data. RESULTS: The proposed method was evaluated using both phantom and healthy subject data. Phantom experimental results demonstrated that high-quality 3D metabolite T1 maps could be obtained and used for correction of T1 saturation effects. In vivo experimental results showed metabolite T1 maps with a large spatial coverage of 240 × 240 × 72 mm3 and good reproducibility coefficients (< 11%) in a 14.5-min scan. The metabolite T1 times obtained ranged from 0.99 to 1.44 s in gray matter and from 1.00 to 1.35 s in white matter. CONCLUSION: We successfully demonstrated the feasibility of 3D metabolite T1 mapping within a clinically acceptable scan time. The proposed method may prove useful for both T1 mapping of brain metabolites and correcting the T1-weighting effects in quantitative metabolic imaging.

Head-to-head comparison of [18F]-Flortaucipir, [18F]-MK-6240 and [18F]-PI-2620 postmortem binding across the spectrum of neurodegenerative diseases.

We and others have shown that [18F]-Flortaucipir, the most validated tau PET tracer thus far, binds with strong affinity to tau aggregates in Alzheimer's (AD) but has relatively low affinity for tau aggregates in non-AD tauopathies and exhibits off-target binding to neuromelanin- and melanin-containing cells, and to hemorrhages. Several second-generation tau tracers have been subsequently developed. [18F]-MK-6240 and [18F]-PI-2620 are the two that have garnered most attention. Our recent data indicated that the binding pattern of [18F]-MK-6240 closely parallels that of [18F]-Flortaucipir. The present study aimed at the direct comparison of the autoradiographic binding properties and off-target profile of [18F]-Flortaucipir, [18F]-MK-6240 and [18F]-PI-2620 in human tissue specimens, and their potential binding to monoamine oxidases (MAO). Phosphor-screen and high resolution autoradiographic patterns of the three tracers were studied in the same postmortem tissue material from AD and non-AD tauopathies, cerebral amyloid angiopathy, synucleopathies, transactive response DNA-binding protein 43 (TDP-43)-frontotemporal lobe degeneration and controls. Our results show that the three tracers show nearly identical autoradiographic binding profiles. They all strongly bind to neurofibrillary tangles in AD but do not seem to bind to a significant extent to tau aggregates in non-AD tauopathies pointing to their limited utility for the in vivo detection of non-AD tau lesions. None of them binds to lesions containing ß-amyloid, α-synuclein or TDP-43 but they all show strong off-target binding to neuromelanin and melanin-containing cells, as well as weaker binding to areas of hemorrhage. The autoradiographic binding signals of the three tracers are only weakly displaced by competing concentrations of selective MAO-B inhibitor deprenyl but not by MAO-A inhibitor clorgyline suggesting that MAO enzymes do not appear to be a significant binding target of any of them. These findings provide relevant insights for the correct interpretation of the in vivo behavior of these three tau PET tracers.

Advances and Insights in Positron Emission Tomography Tracers for Metabotropic Glutamate Receptor 4 Imaging.

Positron emission tomography (PET) imaging employs positron-emitting radioisotopes to visualize biological processes in living subjects with high sensitivity and quantitative accuracy. As the most translational molecular imaging modality, PET can detect and image a wide range of radiotracers with minimal or no modification to parent drugs or targeting molecules. This Perspective provides a comprehensive analysis of developing PET radioligands using allosteric modulators for the metabotropic glutamate receptor subtype 4 (mGluR4) as a therapeutic target for neurological disorders. We focus on the selection of lead compounds from various chemotypes of mGluR4 positive allosteric modulators (PAMs) and discuss the challenges and systematic characterization required in developing brain-penetrant PET tracers specific for mGluR4. Through this analysis, we offer insights into the development and evaluation of PET ligands. Our review concludes that further research and development in this field hold great promise for discovering effective treatments for neurological disorders.

Cross noise level PET denoising with continuous adversarial domain generalization.

Objective.Performing positron emission tomography (PET) denoising within the image space proves effective in reducing the variance in PET images. In recent years, deep learning has demonstrated superior denoising performance, but models trained on a specific noise level typically fail to generalize well on different noise levels, due to inherent distribution shifts between inputs. The distribution shift usually results in bias in the denoised images. Our goal is to tackle such a problem using a domain generalization technique.Approach.We propose to utilize the domain generalization technique with a novel feature space continuous discriminator (CD) for adversarial training, using the fraction of events as a continuous domain label. The core idea is to enforce the extraction of noise-level invariant features. Thus minimizing the distribution divergence of latent feature representation for different continuous noise levels, and making the model general for arbitrary noise levels. We created three sets of 10%, 13%-22% (uniformly randomly selected), or 25% fractions of events from 9718F-MK6240 tau PET studies of 60 subjects. For each set, we generated 20 noise realizations. Training, validation, and testing were implemented using 1400, 120, and 420 pairs of 3D image volumes from the same or different sets. We used 3D UNet as the baseline and implemented CD to the continuous noise level training data of 13%-22% set.Main results.The proposed CD improves the denoising performance of our model trained in a 13%-22% fraction set for testing in both 10% and 25% fraction sets, measured by bias and standard deviation using full-count images as references. In addition, our CD method can improve the SSIM and PSNR consistently for Alzheimer-related regions and the whole brain.Significance.To our knowledge, this is the first attempt to alleviate the performance degradation in cross-noise level denoising from the perspective of domain generalization. Our study is also a pioneer work of continuous domain generalization to utilize continuously changing source domains.

Associations of Physical Activity Engagement with Cerebral Amyloid-ß and Tau from Midlife.

Background: Higher midlife physical activity engagement has been associated with lower dementia risk in late life. However, the underlying mechanisms contributing to the protective effect remain unclear. Objective: The goal of the current study was to evaluate the associations of physical activity with cerebral amyloid-ß (Aß) and tau in a predominately middle-aged community-based cohort, as well as to explore whether the associations differ by sex or age. Methods: Participants from the Framingham Heart Study underwent 11C-Pittsburgh Compound B amyloid and 18F-Flortaucipir tau positron emission tomography (PET) imaging. Total physical activity levels were evaluated by self-report using the Physical Activity Index (PAI). Cross-sectional associations between total PAI with regional Aß and tau PET retention were evaluated using linear regression models adjusted for demographic and cardiovascular risk factors. Interactions with sex and age group were examined and stratified analyses were performed when significant. FDR-correction for multiple comparisons was applied. Results: The sample included 354 participants (mean age 53±8 years, 51% female). Higher total PAI scores were associated with lower entorhinal cortex tau PET binding (ß (SE) = -0.021(0.008), p = 0.049). There were significant interactions with sex. In men alone, total PAI inversely associated with entorhinal cortex (ß (SE) = -0.035(0.009), p = 0.001), inferior temporal (ß (SE) = -0.029(0.010), p = 0.012), and rhinal cortex tau(ß (SE) = -0.033(0.010), p = 0.002). Conclusions: The results suggest that higher midlife physical activity engagement may confer resistance to tau pathology. However, the effects may vary based on sex, highlighting the importance of better understanding and tailoring lifestyle interventions to address sex disparities.

Association of Sleep Duration and Change Over Time With Imaging Biomarkers of Cerebrovascular, Amyloid, Tau, and Neurodegenerative Pathology.

BACKGROUND AND OBJECTIVES: Both short and long sleep duration were previously associated with incident dementia, but underlying mechanisms remain unclear. We evaluated how self-reported sleep duration and its change over time associate with (A)myloid, (T)au, (N)eurodegeneration, and (V)ascular neuroimaging markers of Alzheimer disease. METHODS: Two Framingham Heart Study overlapping samples were studied: participants who underwent 11C-Pittsburg Compound B amyloid and 18F-flortaucipir tau PET imaging and participants who underwent an MRI. MRI metrics estimated neurodegeneration (total brain volume) and cerebrovascular injuries (white matter hyperintensities [WMHs] volume, covert brain infarcts, free-water [FW] fraction). Self-reported sleep duration was assessed and split into categories both at the time of neuroimaging testing and approximately 13 years before: short ≤6 hours. average 7-8 hours, and long ≥9 hours. Logistic and linear regression models were used to examine sleep duration and neuroimaging metrics. RESULTS: The tested cohort was composed of 271 participants (age 53.6 ± 8.0 years; 51% male) in the PET imaging sample and 2,165 participants (age 61.3 ± 11.1 years; 45% male) in the MRI sample. No fully adjusted association was observed between cross-sectional sleep duration and neuroimaging metrics. In fully adjusted models compared with consistently sleeping 7-8 hours, groups transitioning to a longer sleep duration category over time had higher FW fraction (short to average ß [SE] 0.0062 [0.0024], p = 0.009; short to long ß [SE] 0.0164 [0.0076], p = 0.031; average to long ß [SE] 0.0083 [0.0022], p = 0.002), and those specifically going from average to long sleep duration also had higher WMH burden (ß [SE] 0.29 [0.11], p = 0.007). The opposite associations (lower WMH and FW) were observed in participants consistently sleeping ≥9 hours as compared with people consistently sleeping 7-8 hours in fully adjusted models (ß [SE] -0.43 [0.20], p = 0.028; ß [SE] -0.019 [0.004], p = 0.020). Each hour of increasing sleep (continuous, ß [SE] 0.12 [0.04], p = 0.003; ß [SE] 0.002 [0.001], p = 0.021) and extensive increase in sleep duration (≥2 hours vs 0 ± 1 hour change; ß [SE] 0.24 [0.10], p = 0.019; ß [SE] 0.0081 [0.0025], p = 0.001) over time was associated with higher WMH burden and FW fraction in fully adjusted models. Sleep duration change was not associated with PET amyloid or tau outcomes. DISCUSSION: Longer self-reported sleep duration over time was associated with neuroimaging biomarkers of cerebrovascular pathology as evidenced by higher WMH burden and FW fraction. A longer sleep duration extending over time may be an early change in the neurodegenerative trajectory.

The role of 18F-FDG PET in minimizing variability in gross tumor volume delineation of soft tissue sarcomas.

BACKGROUND: Accurate gross tumor volume (GTV) delineation is a critical step in radiation therapy treatment planning. However, it is reader dependent and thus susceptible to intra- and inter-reader variability. GTV delineation of soft tissue sarcoma (STS) often relies on CT and MR images. PURPOSE: This study investigates the potential role of 18F-FDG PET in reducing intra- and inter-reader variability thereby improving reproducibility of GTV delineation in STS, without incurring additional costs or radiation exposure. MATERIALS AND METHODS: Three readers performed independent GTV delineation of 61 patients with STS using first CT and MR followed by CT, MR, and 18F-FDG PET images. Each reader performed a total of six delineation trials, three trials per imaging modality group. Dice Similarity Coefficient (DSC) score and Hausdorff distance (HD) were used to assess both intra- and inter-reader variability using generated simultaneous truth and performance level estimation (STAPLE) GTVs as ground truth. Statistical analysis was performed using a Wilcoxon signed-ranked test. RESULTS: There was a statistically significant decrease in both intra- and inter-reader variability in GTV delineation using CT, MR 18F-FDG PET images vs. CT and MR images. This was translated by an increase in the DSC score and a decrease in the HD for GTVs drawn from CT, MR and 18F-FDG PET images vs. GTVs drawn from CT and MR for all readers and across all three trials. CONCLUSION: Incorporation of 18F-FDG PET into CT and MR images decreased intra- and inter-reader variability and subsequently increased reproducibility of GTV delineation in STS.

Radiosynthesis automation, non-human primate biodistribution and dosimetry of K+ channel tracer [11C]3MeO4AP.

BACKGROUND: 4-Aminopyridine (4AP) is a medication for the symptomatic treatment of multiple sclerosis. Several 4AP-based PET tracers have been developed for imaging demyelination. In preclinical studies, [11C]3MeO4AP has shown promise due to its high brain permeability, high metabolic stability, high plasma availability, and high in vivo binding affinity. To prepare for the translation to human studies, we developed a cGMP-compatible automated radiosynthesis protocol and evaluated the whole-body biodistribution and radiation dosimetry of [11C]3MeO4AP in non-human primates (NHPs). METHODS: Automated radiosynthesis was carried out using a GE TRACERlab FX-C Pro synthesis module. One male and one female adult rhesus macaques were used in the study. A high-resolution CT from cranial vertex to knee was acquired. PET data were collected using a dynamic acquisition protocol with four bed positions and 13 passes over a total scan time of ~ 150 min. Based on the CT and PET images, volumes of interest (VOIs) were manually drawn for selected organs. Non-decay corrected time-activity curves (TACs) were extracted for each VOI. Radiation dosimetry and effective dose were calculated from the integrated TACs using OLINDA software. RESULTS: Fully automated radiosynthesis of [11C]3MeO4AP was achieved with 7.3 ± 1.2% (n = 4) of non-decay corrected radiochemical yield within 38 min of synthesis and purification time. [11C]3MeO4AP distributed quickly throughout the body and into the brain. The organs with highest dose were the kidneys. The average effective dose of [11C]3MeO4AP was 4.0 ± 0.6 µSv/MBq. No significant changes in vital signs were observed during the scan. CONCLUSION: A cGMP-compatible automated radiosynthesis of [11C]3MeO4AP was developed. The whole-body biodistribution and radiation dosimetry of [11C]3MeO4AP was successfully evaluated in NHPs. [11C]3MeO4AP shows lower average effective dose than [18F]3F4AP and similar average effective dose as other carbon-11 tracers.

PET imaging of M4 muscarinic acetylcholine receptors in rhesus macaques using [11C]MK-6884: Quantification with kinetic modeling and receptor occupancy by CVL-231 (emraclidine), a novel positive allosteric modulator.

Stimulation of the M4 muscarinic acetylcholine receptor reduces striatal hyperdopaminergia, suggesting its potential as a therapeutic target for schizophrenia. Emraclidine (CVL-231) is a novel, highly selective, positive allosteric modulator (PAM) of M4 muscarinic acetylcholine receptors i.e. acts as a modulator that increases the response of these receptors. First, we aimed to further characterize the positron emission tomography (PET) imaging and quantification performance of a recently developed M4 PAM radiotracer, [11C]MK-6884, in non-human primates (NHPs). Second, we applied these results to determine the receptor occupancy of CVL-231 as a function of dose. Using paired baseline-blocking PET scans, we quantified total volume of distribution, binding potential, and receptor occupancy. Both blood-based and reference region-based methods quantified M4 receptor levels across brain regions. The 2-tissue 4-parameter kinetic model best fitted regional [11C]MK-6884-time activity curves. Only the caudate nucleus and putamen displayed statistically significant [11C]MK-6884 uptake and dose-dependent blocking by CVL-231. For binding potential and receptor occupancy quantification, the simplified reference tissue model using the grey cerebellum as a reference region was employed. CVL-231 demonstrated dose-dependent M4 receptor occupancy in the striatum of the NHP brain and shows promise for further development in clinical trials.

Associations of Plasma Tau with Amyloid and Tau PET: Results from the Community-Based Framingham Heart Study.

Background: Associations of plasma total tau levels with future risk of AD have been described. Objective: To examine the extent to which plasma tau reflects underlying AD brain pathology in cognitively healthy individuals. Methods: We examined cross-sectional associations of plasma total tau with 11C-Pittsburgh Compound-B (PiB)-PET and 18F-Flortaucipir (FTP)-PET in middle-aged participants at the community-based Framingham Heart Study. Results: Our final sample included 425 participants (mean age 57.6± 9.9, 50% F). Plasma total tau levels were positively associated with amyloid-ß deposition in the precuneus region (ß±SE, 0.11±0.05; p = 0.025). A positive association between plasma total tau and tau PET in the rhinal cortex was suggested in participants with higher amyloid-PET burden and in APOEɛ4 carriers. Conclusions: Our study highlights that plasma total tau is a marker of amyloid deposition as early as in middle-age.

Acute Stress Increases Striatal Connectivity With Cortical Regions Enriched for µ and κ Opioid Receptors.

BACKGROUND: Understanding the neurobiological effects of stress is critical for addressing the etiology of major depressive disorder (MDD). Using a dimensional approach involving individuals with differing degree of MDD risk, we investigated 1) the effects of acute stress on cortico-cortical and subcortical-cortical functional connectivity (FC) and 2) how such effects are related to gene expression and receptor maps. METHODS: Across 115 participants (37 control, 39 remitted MDD, 39 current MDD), we evaluated the effects of stress on FC during the Montreal Imaging Stress Task. Using partial least squares regression, we investigated genes whose expression in the Allen Human Brain Atlas was associated with anatomical patterns of stress-related FC change. Finally, we correlated stress-related FC change maps with opioid and GABAA (gamma-aminobutyric acid A) receptor distribution maps derived from positron emission tomography. RESULTS: Results revealed robust effects of stress on global cortical connectivity, with increased global FC in frontoparietal and attentional networks and decreased global FC in the medial default mode network. Moreover, robust increases emerged in FC of the caudate, putamen, and amygdala with regions from the ventral attention/salience network, frontoparietal network, and motor networks. Such regions showed preferential expression of genes involved in cell-to-cell signaling (OPRM1, OPRK1, SST, GABRA3, GABRA5), similar to previous genetic MDD studies. CONCLUSIONS: Acute stress altered global cortical connectivity and increased striatal connectivity with cortical regions that express genes that have previously been associated with imaging abnormalities in MDD and are rich in µ and κ opioid receptors. These findings point to overlapping circuitry underlying stress response, reward, and MDD.

Association of T-cell subtypes with macrophage-specific arterial infiltration in PWH.

People with human immunodeficiency virus (HIV, PWH) face an increased risk of cardiovascular disease (CVD) compared to the general population. We previously demonstrated that people with (versus without) HIV have higher macrophage-specific arterial infiltration in relation to systemic monocyte activation. We now show that select T lymphocyte subpopulations (naïve CD4+, effector memory CD4+, and central memory CD8+) are differentially associated with macrophage-specific arterial infiltration among participants with versus without HIV, with evidence of interaction by HIV status. Our results suggest that among PWH, circulating T lymphocytes associate with macrophage-specific arterial infiltration, of relevance to atherogenesis and CVD risk. CLINICAL TRIALS REGISTRATION: NCT02542371.

Incremental Learning for Heterogeneous Structure Segmentation in Brain Tumor MRI.

Deep learning (DL) models for segmenting various anatomical structures have achieved great success via a static DL model that is trained in a single source domain. Yet, the static DL model is likely to perform poorly in a continually evolving environment, requiring appropriate model updates. In an incremental learning setting, we would expect that well-trained static models are updated, following continually evolving target domain data-e.g., additional lesions or structures of interest-collected from different sites, without catastrophic forgetting. This, however, poses challenges, due to distribution shifts, additional structures not seen during the initial model training, and the absence of training data in a source domain. To address these challenges, in this work, we seek to progressively evolve an "off-the-shelf" trained segmentation model to diverse datasets with additional anatomical categories in a unified manner. Specifically, we first propose a divergence-aware dual-flow module with balanced rigidity and plasticity branches to decouple old and new tasks, which is guided by continuous batch renormalization. Then, a complementary pseudo-label training scheme with self-entropy regularized momentum MixUp decay is developed for adaptive network optimization. We evaluated our framework on a brain tumor segmentation task with continually changing target domains-i.e., new MRI scanners/modalities with incremental structures. Our framework was able to well retain the discriminability of previously learned structures, hence enabling the realistic life-long segmentation model extension along with the widespread accumulation of big medical data.

Speech Audio Synthesis from Tagged MRI and Non-Negative Matrix Factorization via Plastic Transformer.

The tongue's intricate 3D structure, comprising localized functional units, plays a crucial role in the production of speech. When measured using tagged MRI, these functional units exhibit cohesive displacements and derived quantities that facilitate the complex process of speech production. Non-negative matrix factorization-based approaches have been shown to estimate the functional units through motion features, yielding a set of building blocks and a corresponding weighting map. Investigating the link between weighting maps and speech acoustics can offer significant insights into the intricate process of speech production. To this end, in this work, we utilize two-dimensional spectrograms as a proxy representation, and develop an end-to-end deep learning framework for translating weighting maps to their corresponding audio waveforms. Our proposed plastic light transformer (PLT) framework is based on directional product relative position bias and single-level spatial pyramid pooling, thus enabling flexible processing of weighting maps with variable size to fixed-size spectrograms, without input information loss or dimension expansion. Additionally, our PLT framework efficiently models the global correlation of wide matrix input. To improve the realism of our generated spectrograms with relatively limited training samples, we apply pair-wise utterance consistency with Maximum Mean Discrepancy constraint and adversarial training. Experimental results on a dataset of 29 subjects speaking two utterances demonstrated that our framework is able to synthesize speech audio waveforms from weighting maps, outperforming conventional convolution and transformer models.