Radiomics-driven personalized radiotherapy for primary and recurrent tumors: A general review with a focus on reirradiation.

PURPOSE: This review systematically investigates the role of radiomics in radiotherapy, with a particular emphasis on the use of quantitative imaging biomarkers for predicting clinical outcomes, assessing toxicity, and optimizing treatment planning. While the review encompasses various applications of radiomics in radiotherapy, it particularly highlights its potential for guiding reirradiation of recurrent cancers. METHODS: A systematic review was conducted based on a Medline search with the search engine PubMed using the keywords "radiomics or radiomic" and "radiotherapy or reirradiation". Out of 189 abstracts reviewed, 147 original articles were included in the analysis. These studies were categorized by tumor localization, imaging modality, study objectives, and performance metrics, with a particular emphasis on the inclusion of external validation and adherence to a standardized radiomics pipeline. RESULTS: The review identified 14 tumor localizations, with the majority of studies focusing on lung (33 studies), head and neck (27 studies), and brain (15 studies) cancers. CT was the most frequently employed imaging modality (77 studies) for radiomics, followed by MRI (46 studies) and PET (13 studies). The overall AUC across all studies, primarily focused on predicting the risk of recurrence (94 studies) or toxicity (41 studies), was 0.80 (SD=0.08). However, only 24 studies (16.3%) included external validation, with a slightly lower AUC compared to those without it. For studies using CT versus MRI or PET, both had a median AUC of 0.79, with IQRs of 0.73-0.86 for CT and 0.76-0.855 for MRI/PET, showing no significant differences in performance. Five studies involving reirradiation reported a median AUC of 0.81 (IQR: 0.73-0.825). CONCLUSION: Radiomics demonstrates considerable potential in personalizing radiotherapy by improving treatment precision through better outcome prediction and treatment planning. However, its clinical adoption is hindered by the lack of external validation and variability in study designs. Future research should focus on implementing rigorous validation methods and standardizing imaging protocols to enhance the reliability and generalizability of radiomics in clinical radiotherapy, with particular attention to its application in reirradiation.

Treatment-wise Glioblastoma Survival Inference with Multi-parametric Preoperative MRI.

In this work, we aim to predict the survival time (ST) of glioblastoma (GBM) patients undergoing different treatments based on preoperative magnetic resonance (MR) scans. The personalized and precise treatment planning can be achieved by comparing the ST of different treatments. It is well established that both the current status of the patient (as represented by the MR scans) and the choice of treatment are the cause of ST. While previous related MR-based glioblastoma ST studies have focused only on the direct mapping of MR scans to ST, they have not included the underlying causal relationship between treatments and ST. To address this limitation, we propose a treatment-conditioned regression model for glioblastoma ST that incorporates treatment information in addition to MR scans. Our approach allows us to effectively utilize the data from all of the treatments in a unified manner, rather than having to train separate models for each of the treatments. Furthermore, treatment can be effectively injected into each convolutional layer through the adaptive instance normalization we employ. We evaluate our framework on the BraTS20 ST prediction task. Three treatment options are considered: Gross Total Resection (GTR), Subtotal Resection (STR), and no resection. The evaluation results demonstrate the effectiveness of injecting the treatment for estimating GBM survival.

EXPLORING BACKDOOR ATTACKS IN OFF-THE-SHELF UNSUPERVISED DOMAIN ADAPTATION FOR SECURING CARDIAC MRI-BASED DIAGNOSIS.

The off-the-shelf model for unsupervised domain adaptation (OSUDA) has been introduced to protect patient data privacy and intellectual property of the source domain without access to the labeled source domain data. Yet, an off-the-shelf diagnosis model, deliberately compromised by backdoor attacks during the source domain training phase, can function as a parasite-host, disseminating the backdoor to the target domain model during the OSUDA stage. Because of limitations in accessing or controlling the source domain training data, OSUDA can make the target domain model highly vulnerable and susceptible to prominent attacks. To sidestep this issue, we propose to quantify the channel-wise backdoor sensitivity via a Lipschitz constant and, explicitly, eliminate the backdoor infection by overwriting the backdoor-related channel kernels with random initialization. Furthermore, we propose to employ an auxiliary model with a full source model to ensure accurate pseudo-labeling, taking into account the controllable, clean target training data in OSUDA. We validate our framework using a multi-center, multi-vendor, and multi-disease (M&M) cardiac dataset. Our findings suggest that the target model is susceptible to backdoor attacks during OSUDA, and our defense mechanism effectively mitigates the infection of target domain victims.

Free-breathing 3D cardiac extracellular volume (ECV) mapping using a linear tangent space alignment (LTSA) model.

PURPOSE: To develop a new method for free-breathing 3D extracellular volume (ECV) mapping of the whole heart at 3 T. METHODS: A free-breathing 3D cardiac ECV mapping method was developed at 3 T. T1 mapping was performed before and after contrast agent injection using a free-breathing electrocardiogram-gated inversion recovery sequence with spoiled gradient echo readout. A linear tangent space alignment model-based method was used to reconstruct high-frame-rate dynamic images from (k,t)-space data sparsely sampled along a random stack-of-stars trajectory. Joint T1 and transmit B1 estimation were performed voxel-by-voxel for pre- and post-contrast T1 mapping. To account for the time-varying T1 after contrast agent injection, a linearly time-varying T1 model was introduced for post-contrast T1 mapping. ECV maps were generated by aligning pre- and post-contrast T1 maps through affine transformation. RESULTS: The feasibility of the proposed method was demonstrated using in vivo studies with six healthy volunteers at 3 T. We obtained 3D ECV maps at a spatial resolution of 1.9 × 1.9 × 4.5 mm3 and a FOV of 308 × 308 × 144 mm3, with a scan time of 10.1 ± 1.4 and 10.6 ± 1.6 min before and after contrast agent injection, respectively. The ECV maps and the pre- and post-contrast T1 maps obtained by the proposed method were in good agreement with the 2D MOLLI method both qualitatively and quantitatively. CONCLUSION: The proposed method allows for free-breathing 3D ECV mapping of the whole heart within a practically feasible imaging time. The estimated ECV values from the proposed method were comparable to those from the existing method.

The role of parvalbumin interneuron dysfunction across neurodegenerative dementias.

Parvalbumin-positive (PV+) basket neurons are fast-spiking, non-adapting inhibitory interneurons whose oscillatory activity is essential for regulating cortical excitation/inhibition balance. Their dysfunction results in cortical hyperexcitability and gamma rhythm disruption, which have recently gained substantial traction as contributing factors as well as potential therapeutic targets for the treatment of Alzheimer's Disease (AD). Recent evidence indicates that PV+ cells are also impaired in Frontotemporal Dementia (FTD) and Dementia with Lewy bodies (DLB). However, no attempt has been made to integrate these findings into a coherent pathophysiological framework addressing the contribution of PV+ interneuron dysfunction to the generation of cortical hyperexcitability and gamma rhythm disruption in FTD and DLB. To fill this gap, we epitomized the most recent evidence on PV+ interneuron impairment in AD, FTD, and DLB, focusing on its contribution to the generation of cortical hyperexcitability and gamma oscillatory disruption and their interplay with misfolded protein accumulation, neuronal death, and clinical symptoms' onset. Our work deepens the current understanding concerning the role of PV+ interneuron dysfunction across neurodegenerative dementias, highlighting commonalities and differences among AD, FTD, and DLB, thus paving the way for identifying novel biomarkers and potential therapeutic targets for the treatment of these diseases.

Design Optimisation of a Flat-Panel, Limited-Angle TOF-PET Scanner: A Simulation Study.

In time-of-flight positron emission tomography (TOF-PET), a coincidence time resolution (CTR) below 100 ps reduces the angular coverage requirements and, thus, the geometric constraints of the scanner design. Among other possibilities, this opens the possibility of using flat-panel PET detectors. Such a design would be more cost-accessible and compact and allow for a higher degree of modularity than a conventional ring scanner. However, achieving adequate CTR is a considerable challenge and requires improvements at every level of detection. Based on recent results in the ongoing development of optimised TOF-PET photodetectors and electronics, we expect that within a few years, a CTR of about 75 ps will be be achievable at the system level. In this work, flat-panel scanners with four panels and various design parameters were simulated, assessed and compared to a reference scanner based on the Siemens Biograph Vision using NEMA NU 2-2018 metrics. Point sources were also simulated, and a method for evaluating spatial resolution that is more appropriate for flat-panel geometry is presented. We also studied the effects of crystal readout strategies, comparing single-crystal and module readout levels. The results demonstrate that with a CTR below 100 ps, a flat-panel scanner can achieve image quality comparable to that of a reference clinical scanner, with considerable savings in scintillator material.

Speech Motion Anomaly Detection via Cross-Modal Translation of 4D Motion Fields from Tagged MRI.

Understanding the relationship between tongue motion patterns during speech and their resulting speech acoustic outcomes-i.e., articulatory-acoustic relation-is of great importance in assessing speech quality and developing innovative treatment and rehabilitative strategies. This is especially important when evaluating and detecting abnormal articulatory features in patients with speech-related disorders. In this work, we aim to develop a framework for detecting speech motion anomalies in conjunction with their corresponding speech acoustics. This is achieved through the use of a deep cross-modal translator trained on data from healthy individuals only, which bridges the gap between 4D motion fields obtained from tagged MRI and 2D spectrograms derived from speech acoustic data. The trained translator is used as an anomaly detector, by measuring the spectrogram reconstruction quality on healthy individuals or patients. In particular, the cross-modal translator is likely to yield limited generalization capabilities on patient data, which includes unseen out-of-distribution patterns and demonstrates subpar performance, when compared with healthy individuals. A one-class SVM is then used to distinguish the spectrograms of healthy individuals from those of patients. To validate our framework, we collected a total of 39 paired tagged MRI and speech waveforms, consisting of data from 36 healthy individuals and 3 tongue cancer patients. We used both 3D convolutional and transformer-based deep translation models, training them on the healthy training set and then applying them to both the healthy and patient testing sets. Our framework demonstrates a capability to detect abnormal patient data, thereby illustrating its potential in enhancing the understanding of the articulatory-acoustic relation for both healthy individuals and patients.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

PET image denoising based on denoising diffusion probabilistic model.

PURPOSE: Due to various physical degradation factors and limited counts received, PET image quality needs further improvements. The denoising diffusion probabilistic model (DDPM) was a distribution learning-based model, which tried to transform a normal distribution into a specific data distribution based on iterative refinements. In this work, we proposed and evaluated different DDPM-based methods for PET image denoising. METHODS: Under the DDPM framework, one way to perform PET image denoising was to provide the PET image and/or the prior image as the input. Another way was to supply the prior image as the network input with the PET image included in the refinement steps, which could fit for scenarios of different noise levels. 150 brain [[Formula: see text]F]FDG datasets and 140 brain [[Formula: see text]F]MK-6240 (imaging neurofibrillary tangles deposition) datasets were utilized to evaluate the proposed DDPM-based methods. RESULTS: Quantification showed that the DDPM-based frameworks with PET information included generated better results than the nonlocal mean, Unet and generative adversarial network (GAN)-based denoising methods. Adding additional MR prior in the model helped achieved better performance and further reduced the uncertainty during image denoising. Solely relying on MR prior while ignoring the PET information resulted in large bias. Regional and surface quantification showed that employing MR prior as the network input while embedding PET image as a data-consistency constraint during inference achieved the best performance. CONCLUSION: DDPM-based PET image denoising is a flexible framework, which can efficiently utilize prior information and achieve better performance than the nonlocal mean, Unet and GAN-based denoising methods.