Examining short interval intracortical inhibition with different transcranial magnetic stimulation-induced current directions in ALS.

Objective: To establish if induced current direction across the motor cortex alters the sensitivity of transcranial magnetic stimulation (TMS)-evoked short-interval intracortical inhibition (SICI) as an ALS biomarker. Methods: Threshold tracking-TMS was undertaken in 35 people with ALS and 39 controls. Using a coil orientation which induces posterior-anterior (PA)-directed current across the motor cortex, SICI (1 ms and 3 ms interstimulus intervals) and intracortical facilitation (ICF, 10 ms interstimulus interval) were recorded. SICI3ms was also recorded using a coil orientation which induces anterior-posterior (AP)-directed current across the motor cortex. Results: At group level, SICI3ms-PA (AUROC = 0.7), SICI3ms-AP (AUROC = 0.8) and SICI1ms (AUROC = 0.66) were substantially lower in those with ALS, although there was considerable interindividual heterogeneity. Averaging across interstimulus intervals (ISIs) marginally improved SICIPA sensitivity (AUROC = 0.76). Averaging SICI values across ISIs and orientations into a single SICI measure did not substantially improve sensitivity (AUROC = 0.81) compared to SICI3ms-AP alone. SICI3ms-AP and SICI3ms-PA did not significantly correlate (rho = 0.19, p = 0.313), while SICI1ms-PA and SICI3ms-PA did (rho = 0.37, p = 0.006). Further, those with ALS with the lowest SICI3ms-PA were not those with the lowest SICI3ms-AP. ICF was similar between groups (AUROC = 0.50). Conclusions: SICIPA and SICIAP are uncorrelated measures of motor cortical inhibitory functions which are useful as distinct, unequally affected, measures of disinhibition in ALS. Significance: Examining both SICIPA and SICIAP may facilitate more comprehensive characterisation of motor cortical disinhibition in ALS.

Synaptic density patterns in early Alzheimer's disease assessed by independent component analysis.

Synaptic loss is a primary pathology in Alzheimer's disease and correlates best with cognitive impairment as found in post-mortem studies. Previously, we observed in vivo reductions of synaptic density with [11C]UCB-J PET (radiotracer for synaptic vesicle protein 2A) throughout the neocortex and medial temporal brain regions in early Alzheimer's disease. In this study, we applied independent component analysis to synaptic vesicle protein 2A-PET data to identify brain networks associated with cognitive deficits in Alzheimer's disease in a blinded data-driven manner. [11C]UCB-J binding to synaptic vesicle protein 2A was measured in 38 Alzheimer's disease (24 mild Alzheimer's disease dementia and 14 mild cognitive impairment) and 19 cognitively normal participants. [11C]UCB-J distribution volume ratio values were calculated with a whole cerebellum reference region. Principal components analysis was first used to extract 18 independent components to which independent component analysis was then applied. Subject loading weights per pattern were compared between groups using Kruskal-Wallis tests. Spearman's rank correlations were used to assess relationships between loading weights and measures of cognitive and functional performance: Logical Memory II, Rey Auditory Verbal Learning Test-long delay, Clinical Dementia Rating sum of boxes and Mini-Mental State Examination. We observed significant differences in loading weights among cognitively normal, mild cognitive impairment and mild Alzheimer's disease dementia groups in 5 of the 18 independent components, as determined by Kruskal-Wallis tests. Only Patterns 1 and 2 demonstrated significant differences in group loading weights after correction for multiple comparisons. Excluding the cognitively normal group, we observed significant correlations between the loading weights for Pattern 1 (left temporal cortex and the cingulate gyrus) and Clinical Dementia Rating sum of boxes (r = -0.54, P = 0.0019), Mini-Mental State Examination (r = 0.48, P = 0.0055) and Logical Memory II score (r = 0.44, P = 0.013). For Pattern 2 (temporal cortices), significant associations were demonstrated between its loading weights and Logical Memory II score (r = 0.34, P = 0.0384). Following false discovery rate correction, only the relationship between the Pattern 1 loading weights with Clinical Dementia Rating sum of boxes (r = -0.54, P = 0.0019) and Mini-Mental State Examination (r = 0.48, P = 0.0055) remained statistically significant. We demonstrated that independent component analysis could define coherent spatial patterns of synaptic density. Furthermore, commonly used measures of cognitive performance correlated significantly with loading weights for two patterns within only the mild cognitive impairment/mild Alzheimer's disease dementia group. This study leverages data-centric approaches to augment the conventional region-of-interest-based methods, revealing distinct patterns that differentiate between mild cognitive impairment and mild Alzheimer's disease dementia, marking a significant advancement in the field.

Population-based deep image prior for dynamic PET denoising: A data-driven approach to improve parametric quantification.

The high noise level of dynamic Positron Emission Tomography (PET) images degrades the quality of parametric images. In this study, we aim to improve the quality and quantitative accuracy of Ki images by utilizing deep learning techniques to reduce the noise in dynamic PET images. We propose a novel denoising technique, Population-based Deep Image Prior (PDIP), which integrates population-based prior information into the optimization process of Deep Image Prior (DIP). Specifically, the population-based prior image is generated from a supervised denoising model that is trained on a prompts-matched static PET dataset comprising 100 clinical studies. The 3D U-Net architecture is employed for both the supervised model and the following DIP optimization process. We evaluated the efficacy of PDIP for noise reduction in 25%-count and 100%-count dynamic PET images from 23 patients by comparing with two other baseline techniques: the Prompts-matched Supervised model (PS) and a conditional DIP (CDIP) model that employs the mean static PET image as the prior. Both the PS and CDIP models show effective noise reduction but result in smoothing and removal of small lesions. In addition, the utilization of a single static image as the prior in the CDIP model also introduces a similar tracer distribution to the denoised dynamic frames, leading to lower Ki in general as well as incorrect Ki in the descending aorta. By contrast, as the proposed PDIP model utilizes intrinsic image features from the dynamic dataset and a large clinical static dataset, it not only achieves comparable noise reduction as the supervised and CDIP models but also improves lesion Ki predictions.

Deficits in force production during multifinger tasks demarcate cognitive dysfunction.

BACKGROUND: The multifinger force deficit (MFFD) is the decline in force generated by each finger as the number of fingers contributing to an action is increased. It has been shown to associate with cognitive status. AIMS: The aim was to establish whether a particularly challenging form of multifinger grip dynamometry, that provides minimal tactile feedback via cutaneous receptors and requires active compensation for reaction forces, will yield an MFFD that is more sensitive to cognitive status. METHODS: Associations between measures of motor function, and cognitive status (Montreal Cognitive Assessment [MoCA]) and latent components of cognitive function (derived from 11 tests using principal component analysis), were estimated cross-sectionally using generalized partial rank correlations. The participants (n = 62) were community dwelling, aged 65-87. RESULTS: Approximately half the participants were unable to complete the dynamometry task successfully. Cognitive status demarcated individuals who could perform the task from those who could not. Among those who complied with the task requirements, the MFFD was negatively correlated with MoCA scores-those with the highest MoCA scores tended to exhibit the smallest deficits, and vice versa. There were corresponding associations with latent components of cognitive function. DISCUSSION: The results support the view that neurodegenerative processes that are a feature of normal and pathological aging exert corresponding effects on expressions of motor coordination-in multifinger tasks, and cognitive sufficiency, due to their dependence on shared neural systems. CONCLUSIONS: The outcomes add weight to the assertion that deficits in force production during multifinger tasks are sensitive to cognitive dysfunction.

Consensus for experimental design in electromyography (CEDE) project: Checklist for reporting and critically appraising studies using EMG (CEDE-Check).

The diversity in electromyography (EMG) techniques and their reporting present significant challenges across multiple disciplines in research and clinical practice, where EMG is commonly used. To address these challenges and augment the reproducibility and interpretation of studies using EMG, the Consensus for Experimental Design in Electromyography (CEDE) project has developed a checklist (CEDE-Check) to assist researchers to thoroughly report their EMG methodologies. Development involved a multi-stage Delphi process with seventeen EMG experts from various disciplines. After two rounds, consensus was achieved. The final CEDE-Check consists of forty items that address four critical areas that demand precise reporting when EMG is employed: the task investigated, electrode placement, recording electrode characteristics, and acquisition and pre-processing of EMG signals. This checklist aims to guide researchers to accurately report and critically appraise EMG studies, thereby promoting a standardised critical evaluation, and greater scientific rigor in research that uses EMG signals. This approach not only aims to facilitate interpretation of study results and comparisons between studies, but it is also expected to contribute to advancing research quality and facilitate clinical and other practical applications of knowledge generated through the use of EMG.

Synaptic loss and its association with symptom severity in Parkinson's disease.

Parkinson's disease (PD) is the fastest growing neurodegenerative disease, but at present there is no cure, nor any disease-modifying treatments. Synaptic biomarkers from in vivo imaging have shown promise in imaging loss of synapses in PD and other neurodegenerative disorders. Here, we provide new clinical insights from a cross-sectional, high-resolution positron emission tomography (PET) study of 30 PD individuals and 30 age- and sex-matched healthy controls (HC) with the radiotracer [11C]UCB-J, which binds to synaptic vesicle glycoprotein 2A (SV2A), and is therefore, a biomarker of synaptic density in the living brain. We also examined a measure of relative brain perfusion from the early part of the same PET scan. Our results provide evidence for synaptic density loss in the substantia nigra that had been previously reported, but also extend this to other early-Braak stage regions known to be affected in PD (brainstem, caudate, olfactory cortex). Importantly, we also found a direct association between synaptic density loss in the nigra and severity of symptoms in patients. A greater extent and wider distribution of synaptic density loss in PD patients with longer illness duration suggests that [11C]UCB-J PET can be used to measure synapse loss with disease progression. We also demonstrate lower brain perfusion in PD vs. HC groups, with a greater extent of abnormalities in those with longer duration of illness, suggesting that [11C]UCB-J PET can simultaneously provide information on changes in brain perfusion. These results implicate synaptic imaging as a useful PD biomarker for future disease-modifying interventions.

First-in-Human Study of 18F-SynVesT-2: An SV2A PET Imaging Probe with Fast Brain Kinetics and High Specific Binding.

PET imaging of synaptic vesicle glycoprotein 2A allows for noninvasive quantification of synapses. This first-in-human study aimed to evaluate the kinetics, test-retest reproducibility, and extent of specific binding of a recently developed synaptic vesicle glycoprotein 2A PET ligand, (R)-4-(3-(18F-fluoro)phenyl)-1-((3-methylpyridin-4-yl)methyl)pyrrolidine-2-one (18F-SynVesT-2), with fast brain kinetics. Methods: Nine healthy volunteers participated in this study and were scanned on a High Resolution Research Tomograph scanner with 18F-SynVesT-2. Five volunteers were scanned twice on 2 different days. Five volunteers were rescanned with preinjected levetiracetam (20 mg/kg, intravenously). Arterial blood was collected to calculate the plasma free fraction and generate the arterial input function. Individual MR images were coregistered to a brain atlas to define regions of interest for generating time-activity curves, which were fitted with 1- and 2-tissue-compartment (1TC and 2TC) models to derive the regional distribution volume (V T). The regional nondisplaceable binding potential (BP ND) was calculated from 1TC V T, using the centrum semiovale (CS) as the reference region. Results: 18F-SynVesT-2 was synthesized with high molar activity (187 ± 69 MBq/nmol, n = 19). The parent fraction of 18F-SynVesT-2 in plasma was 28% ± 8% at 30 min after injection, and the plasma free fraction was high (0.29 ± 0.04). 18F-SynVesT-2 entered the brain quickly, with an SUVpeak of 8 within 10 min after injection. Regional time-activity curves fitted well with both the 1TC and the 2TC models; however, V T was estimated more reliably using the 1TC model. The 1TC V T ranged from 1.9 ± 0.2 mL/cm3 in CS to 7.6 ± 0.8 mL/cm3 in the putamen, with low absolute test-retest variability (6.0% ± 3.6%). Regional BP ND ranged from 1.76 ± 0.21 in the hippocampus to 3.06 ± 0.29 in the putamen. A 20-min scan was sufficient to provide reliable V T and BP ND Conclusion: 18F-SynVesT-2 has fast kinetics, high specific uptake, and low nonspecific uptake in the brain. Consistent with the nonhuman primate results, the kinetics of 18F-SynVesT-2 is faster than the kinetics of 11C-UCB-J and 18F-SynVesT-1 in the human brain and enables a shorter dynamic scan to derive physiologic information on cerebral blood flow and synapse density.

Electroencephalographic ß-band oscillations in the sensorimotor network reflect motor symptom severity in amyotrophic lateral sclerosis.

BACKGROUND AND PURPOSE: Resting-state electroencephalography (EEG) holds promise for assessing brain networks in amyotrophic lateral sclerosis (ALS). We investigated whether neural ß-band oscillations in the sensorimotor network could serve as an objective quantitative measure of progressive motor impairment and functional disability in ALS patients. METHODS: Resting-state EEG was recorded in 18 people with ALS and 38 age- and gender-matched healthy controls. We estimated source-localized ß-band spectral power in the sensorimotor cortex. Clinical evaluation included lower (LMN) and upper motor neuron scores, Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised score, fine motor function (FMF) subscore, and progression rate. Correlations between clinical scores and ß-band power were analysed and corrected using a false discovery rate of q = 0.05. RESULTS: ß-Band power was significantly lower in people with ALS than controls (p = 0.004), and correlated with LMN score (R = -0.65, p = 0.013), FMF subscore (R = -0.53, p = 0.036), and FMF progression rate (R = 0.52, p = 0.036). CONCLUSIONS: ß-Band spectral power in the sensorimotor cortex reflects clinically evaluated motor impairment in ALS. This technology merits further investigation as a biomarker of progressive functional disability.

TDP-43-stratified single-cell proteomics of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis.

A limitation of conventional bulk-tissue proteome studies in amyotrophic lateral sclerosis (ALS) is the confounding of motor neuron (MN) signals by admixed non-MN proteins. Here, we leverage laser capture microdissection and nanoPOTS single-cell mass spectrometry-based proteomics to query changes in protein expression in single MNs from postmortem ALS and control tissues. In a follow-up analysis, we examine the impact of stratification of MNs based on cytoplasmic transactive response DNA-binding protein 43 (TDP-43)+ inclusion pathology on the profiles of 2,238 proteins. We report extensive overlap in differentially abundant proteins identified in ALS MNs with or without overt TDP-43 pathology, suggesting early and sustained dysregulation of cellular respiration, mRNA splicing, translation, and vesicular transport in ALS. Together, these data provide insights into proteome-level changes associated with TDP-43 proteinopathy and begin to demonstrate the utility of pathology-stratified trace sample proteomics for understanding single-cell protein dynamics in human neurologic diseases.

A pilot study to evaluate the effect of CT1812 treatment on synaptic density and other biomarkers in Alzheimer's disease.

BACKGROUND: Effective, disease-modifying therapeutics for the treatment of Alzheimer's disease (AD) remain a large unmet need. Extensive evidence suggests that amyloid beta (Aß) is central to AD pathophysiology, and Aß oligomers are among the most toxic forms of Aß. CT1812 is a novel brain penetrant sigma-2 receptor ligand that interferes with the binding of Aß oligomers to neurons. Preclinical studies of CT1812 have demonstrated its ability to displace Aß oligomers from neurons, restore synapses in cell cultures, and improve cognitive measures in mouse models of AD. CT1812 was found to be generally safe and well tolerated in a placebo-controlled phase 1 clinical trial in healthy volunteers and phase 1a/2 clinical trials in patients with mild to moderate dementia due to AD. The unique objective of this study was to incorporate synaptic positron emission tomography (PET) imaging as an outcome measure for CT1812 in AD patients. METHODS: The present phase 1/2 study was a randomized, double-blind, placebo-controlled, parallel-group trial conducted in 23 participants with mild to moderate dementia due to AD to primarily evaluate the safety of CT1812 and secondarily its pharmacodynamic effects. Participants received either placebo or 100 mg or 300 mg per day of oral CT1812 for 24 weeks. Pharmacodynamic effects were assessed using the exploratory efficacy endpoints synaptic vesicle glycoprotein 2A (SV2A) PET, fluorodeoxyglucose (FDG) PET, volumetric MRI, cognitive clinical measures, as well as cerebrospinal fluid (CSF) biomarkers of AD pathology and synaptic degeneration. RESULTS: No treatment differences relative to placebo were observed in the change from baseline at 24 weeks in either SV2A or FDG PET signal, the cognitive clinical rating scales, or in CSF biomarkers. Composite region volumetric MRI revealed a trend towards tissue preservation in participants treated with either dose of CT1812, and nominally significant differences with both doses of CT1812 compared to placebo were found in the pericentral, prefrontal, and hippocampal cortices. CT1812 was safe and well tolerated. CONCLUSIONS: The safety findings of this 24-week study and the observed changes on volumetric MRI with CT1812 support its further clinical development. TRIAL REGISTRATION: The clinical trial described in this manuscript is registered at clinicaltrials.gov (NCT03493282).

The regional pattern of age-related synaptic loss in the human brain differs from gray matter volume loss: in vivo PET measurement with [11C]UCB-J.

PURPOSE: Aging is a major societal concern due to age-related functional losses. Synapses are crucial components of neural circuits, and synaptic density could be a sensitive biomarker to evaluate brain function. [11C]UCB-J is a positron emission tomography (PET) ligand targeting synaptic vesicle glycoprotein 2A (SV2A), which can be used to evaluate brain synaptic density in vivo. METHODS: We evaluated age-related changes in gray matter synaptic density, volume, and blood flow using [11C]UCB-J PET and magnetic resonance imaging (MRI) in a wide age range of 80 cognitive normal subjects (21-83 years old). Partial volume correction was applied to the PET data. RESULTS: Significant age-related decreases were found in 13, two, and nine brain regions for volume, synaptic density, and blood flow, respectively. The prefrontal cortex showed the largest volume decline (4.9% reduction per decade: RPD), while the synaptic density loss was largest in the caudate (3.6% RPD) and medial occipital cortex (3.4% RPD). The reductions in caudate are consistent with previous SV2A PET studies and likely reflect that caudate is the site of nerve terminals for multiple major tracts that undergo substantial age-related neurodegeneration. There was a non-significant negative relationship between volume and synaptic density reductions in 16 gray matter regions. CONCLUSION: MRI and [11]C-UCB-J PET showed age-related decreases of gray matter volume, synaptic density, and blood flow; however, the regional patterns of the reductions in volume and SV2A binding were different. Those patterns suggest that MR-based measures of GM volume may not be directly representative of synaptic density.

Evaluation of a First PET Tracer Suitable for Imaging the Sigma-2 Receptor in the Brain of Nonhuman Primates.

The sigma-2 receptor (σ2R), recently identified as transmembrane protein 97, is expressed in many cell types and mediates important functions in both the peripheral and central nervous systems. Over the years, σ2R has emerged as a potential therapeutic target for cancer and neurological disorders such as Alzheimer's disease (AD). The currently available σ2R radiotracers have been developed primarily for cancer imaging with limited brain uptake. Here, we report the evaluation of the first brain penetrant 18F-labeled radiotracer suitable for positron emission tomography (PET) imaging of σ2R in nonhuman primate brain.

Improving SUVR quantification by correcting for radiotracer clearance in tissue.

Standardized Uptake Value Ratio (SUVR) is a widely reported semi-quantitative positron emission tomography (PET) outcome measure, partly because of its ease of measurement from short scan durations. However, in brain, SUVR is often a biased estimator of the gold-standard distribution volume ratio (DVR) due to non-equilibrium conditions, i.e., clearance of the radiotracer in relevant tissues. Factors that affect radiotracer metabolism and clearance such as medication or subject groups could lead to artificial differences in SUVR. This work developed a correction that reduces the bias in SUVR (estimated from a short 15-30 min PET imaging session) by accounting for the effects of tracer clearance observed during the late SUVR time window. The proposed correction takes the form of a one-step non-linear algebraic transform of SUVR that is a function of radiotracer dependent parameters such as clearance rates from the reference and target tissues, and population averaged reference region clearance rate (k2,ref). An important observation was the need for accurate estimation of radiotracer clearance rate in target tissue, which was addressed with a regression based model. Simulations and human data from two different radiotracers (healthy controls for [11C]LSN3172176, healthy controls and Parkinson's disease subjects for [18F]FE-PE2I) were used to validate the correction and evaluate its benefits and limitations. SUVR correction in human data significantly reduced mean SUVR bias across brain regions and subjects (from ∼25% for SUVR to <10% for corrected SUVR). This correction also significantly reduced the variability of this bias across brain regions for both tracers (approximately 50% for [11C]LSN3172176, 20% for [18F]FE-PE2I). Future work should investigate the benefits of using corrected SUVR in other populations and with different tracers.

Assessment of Gray Matter Microstructure and Synaptic Density in Alzheimer's Disease: A Multimodal Imaging Study With DTI and SV2A PET.

OBJECTIVE: Multimodal imaging techniques have furthered our understanding of how different aspects of Alzheimer's disease (AD) pathology relate to one another. Diffusion tensor imaging (DTI) measures such as mean diffusivity (MD) may be a surrogate measure of the changes in gray matter structure associated with AD. Positron emission tomography (PET) imaging of synaptic vesicle glycoprotein 2A (SV2A) has been used to quantify synaptic loss, which is the major pathological correlate of cognitive impairment in AD. In this study, we investigated the relationship between gray matter microstructure and synaptic density. METHODS: DTI was used to measure MD and [11C]UCB-J PET to measure synaptic density in 33 amyloid-positive participants with AD and 17 amyloid-negative cognitively normal (CN) participants aged 50-83. Univariate regression analyses were used to assess the association between synaptic density and MD in both the AD and CN groups. RESULTS: Hippocampal MD was inversely associated with hippocampal synaptic density in participants with AD (r = -0.55, p <0.001, df = 31) but not CN (r = 0.13, p = 0.62, df = 15). Exploratory analyses across other regions known to be affected in AD suggested widespread inverse associations between synaptic density and MD in the AD group. CONCLUSION: In the setting of AD, an increase in gray matter MD is inversely associated with synaptic density. These co-occurring changes may suggest a link between synaptic loss and gray matter microstructural changes in AD. Imaging studies of gray matter microstructure and synaptic density may allow important insights into AD-related neuropathology.

Perceptions of the seriousness of major public health problems during the COVID-19 pandemic in seven middle-income countries.

INTRODUCTION: Public perception of the seriousness of the COVID-19 pandemic compared to six other major public health problems (alcoholism and drug use, HIV/AIDS, malaria, tuberculosis, lung cancer and respiratory diseases caused by air pollution and smoking, and water-borne diseases like diarrhea) is unclear. We designed a survey to examine this issue using YouGov's internet panels in seven middle-income countries in Africa, Asia, and Latin America in early 2022. METHODS: Respondents rank ordered the seriousness of the seven health problems using a repeated best-worst question format. Rank-ordered logit models allow comparisons within and across countries and assessment of covariates. RESULTS: In six of the seven countries, respondents perceived other respiratory illnesses to be a more serious problem than COVID-19. Only in Vietnam was COVID-19 ranked above other respiratory illnesses. Alcoholism and drug use was ranked the second most serious problem in the African countries. HIV/AIDS ranked relatively high in all countries. Covariates, particularly a COVID-19 knowledge scale, explained differences within countries; statistics about the pandemic were highly correlated with differences in COVID-19's perceived seriousness. CONCLUSIONS: People in the seven middle-income countries perceived COVID-19 to be serious (on par with HIV/AIDS) but not as serious as other respiratory illnesses. In the African countries, respondents perceived alcoholism and drug use as more serious than COVID-19. Our survey-based approach can be used to quickly understand how the threat of a newly emergent disease, like COVID-19, fits into the larger context of public perceptions of the seriousness of health problems.

We were curious what people in different countries thought about the seriousness of COVID-19 compared to other health problems. We designed a survey, and hired YouGov, a survey research firm, to administer it in seven countries in Africa, Asia, and Latin America in early 2022. Respondents answered the questions on their computer, tablets, or smart phones. Their answers revealed that in most countries respiratory illnesses were perceived to be a more serious problem than COVID-19. In Africa people felt that alcoholism and drug use were also more serious than COVID-19. These findings are important because they show that people still care about the health problems they were facing before the pandemic, which is useful information for healthcare providers.

An update on the use of image-derived input functions for human PET studies: new hopes or old illusions?

BACKGROUND: The need for arterial blood data in quantitative PET research limits the wider usability of this imaging method in clinical research settings. Image-derived input function (IDIF) approaches have been proposed as a cost-effective and non-invasive alternative to gold-standard arterial sampling. However, this approach comes with its own limitations-partial volume effects and radiometabolite correction among the most important-and varying rates of success, and the use of IDIF for brain PET has been particularly troublesome. MAIN BODY: This paper summarizes the limitations of IDIF methods for quantitative PET imaging and discusses some of the advances that may make IDIF extraction more reliable. The introduction of automated pipelines (both commercial and open-source) for clinical PET scanners is discussed as a way to improve the reliability of IDIF approaches and their utility for quantitative purposes. Survey data gathered from the PET community are then presented to understand whether the field's opinion of the usefulness and validity of IDIF is improving. Finally, as the introduction of next-generation PET scanners with long axial fields of view, ultra-high sensitivity, and improved spatial and temporal resolution, has also brought IDIF methods back into the spotlight, a discussion of the possibilities offered by these state-of-the-art scanners-inclusion of large vessels, less partial volume in small vessels, better description of the full IDIF kinetics, whole-body modeling of radiometabolite production-is included, providing a pathway for future use of IDIF. CONCLUSION: Improvements in PET scanner technology and software for automated IDIF extraction may allow to solve some of the major limitations associated with IDIF, such as partial volume effects and poor temporal sampling, with the exciting potential for accurate estimation of single kinetic rates. Nevertheless, until individualized radiometabolite correction can be performed effectively, IDIF approaches remain confined at best to a few tracers.

Intrathecal delivery of nanoparticle PARP inhibitor to the cerebrospinal fluid for the treatment of metastatic medulloblastoma.

The morbidity associated with pediatric medulloblastoma, in particular in patients who develop leptomeningeal metastases, remains high in the absence of effective therapies. Administration of substances directly into the cerebrospinal fluid (CSF) is one approach to circumvent the blood-brain barrier and focus delivery of drugs to the site of tumor. However, high rates of CSF turnover prevent adequate drug accumulation and lead to rapid systemic clearance and toxicity. Here, we show that PLA-HPG nanoparticles, made with a single-emulsion, solvent evaporation process, can encapsulate talazoparib, a PARP inhibitor (BMN-673). These degradable polymer nanoparticles improve the therapeutic index when delivered intrathecally and lead to sustained drug retention in the tumor as measured with PET imaging and fluorescence microscopy. We demonstrate that administration of these particles into the CSF, alone or in combination with systemically administered temozolomide, is a highly effective therapy for tumor regression and prevention of leptomeningeal spread in xenograft mouse models of medulloblastoma. These results provide a rationale for harnessing nanoparticles for the delivery of drugs limited by brain penetration and therapeutic index and demonstrate important advantages in tolerability and efficacy for encapsulated drugs delivered locoregionally.

Markerless head motion tracking and event-by-event correction in brain PET.

Objective.Head motion correction (MC) is an essential process in brain positron emission tomography (PET) imaging. We have used the Polaris Vicra, an optical hardware-based motion tracking (HMT) device, for PET head MC. However, this requires attachment of a marker to the subject's head. Markerless HMT (MLMT) methods are more convenient for clinical translation than HMT with external markers. In this study, we validated the United Imaging Healthcare motion tracking (UMT) MLMT system using phantom and human point source studies, and tested its effectiveness on eight18F-FPEB and four11C-LSN3172176 human studies, with frame-based region of interest (ROI) analysis. We also proposed an evaluation metric, registration quality (RQ), and compared it to a data-driven evaluation method, motion-corrected centroid-of-distribution (MCCOD).Approach.UMT utilized a stereovision camera with infrared structured light to capture the subject's real-time 3D facial surface. Each point cloud, acquired at up to 30 Hz, was registered to the reference cloud using a rigid-body iterative closest point registration algorithm.Main results.In the phantom point source study, UMT exhibited superior reconstruction results than the Vicra with higher spatial resolution (0.35 ± 0.27 mm) and smaller residual displacements (0.12 ± 0.10 mm). In the human point source study, UMT achieved comparable performance as Vicra on spatial resolution with lower noise. Moreover, UMT achieved comparable ROI values as Vicra for all the human studies, with negligible mean standard uptake value differences, while no MC results showed significant negative bias. TheRQevaluation metric demonstrated the effectiveness of UMT and yielded comparable results to MCCOD.Significance.We performed an initial validation of a commercial MLMT system against the Vicra. Generally, UMT achieved comparable motion-tracking results in all studies and the effectiveness of UMT-based MC was demonstrated.