Neural Correlates of Hand-Object Congruency Effects during Action Planning.

Selecting hand actions to manipulate an object is affected both by perceptual factors and by action goals. Affordances may contribute to "stimulus-response" congruency effects driven by habitual actions to an object. In previous studies, we have demonstrated an influence of the congruency between hand and object orientations on response times when reaching to turn an object, such as a cup. In this study, we investigated how the representation of hand postures triggered by planning to turn a cup was influenced by this congruency effect, in an fMRI scanning environment. Healthy participants were asked to reach and turn a real cup that was placed in front of them either in an upright orientation or upside-down. They were instructed to use a hand orientation that was either congruent or incongruent with the cup orientation. As expected, the motor responses were faster when the hand and cup orientations were congruent. There was increased activity in a network of brain regions involving object-directed actions during action planning, which included bilateral primary and extrastriate visual, medial, and superior temporal areas, as well as superior parietal, primary motor, and premotor areas in the left hemisphere. Specific activation of the dorsal premotor cortex was associated with hand-object orientation congruency during planning and prior to any action taking place. Activity in that area and its connectivity with the lateral occipito-temporal cortex increased when planning incongruent (goal-directed) actions. The increased activity in premotor areas in trials where the orientation of the hand was incongruent to that of the object suggests a role in eliciting competing representations specified by hand postures in lateral occipito-temporal cortex.

Beyond negative valence: 2-week administration of a serotonergic antidepressant enhances both reward and effort learning signals.

To make good decisions, humans need to learn about and integrate different sources of appetitive and aversive information. While serotonin has been linked to value-based decision-making, its role in learning is less clear, with acute manipulations often producing inconsistent results. Here, we show that when the effects of a selective serotonin reuptake inhibitor (SSRI, citalopram) are studied over longer timescales, learning is robustly improved. We measured brain activity with functional magnetic resonance imaging (fMRI) in volunteers as they performed a concurrent appetitive (money) and aversive (effort) learning task. We found that 2 weeks of citalopram enhanced reward and effort learning signals in a widespread network of brain regions, including ventromedial prefrontal and anterior cingulate cortex. At a behavioral level, this was accompanied by more robust reward learning. This suggests that serotonin can modulate the ability to learn via a mechanism that is independent of stimulus valence. Such effects may partly underlie SSRIs' impact in treating psychological illnesses. Our results highlight both a specific function in learning for serotonin and the importance of studying its role across longer timescales.

Medical Mobile App Classification Using the National Institute for Health and Care Excellence Evidence Standards Framework for Digital Health Technologies: Interrater Reliability Study.

BACKGROUND: Clinical governance of medical mobile apps is challenging, and there is currently no standard method for assessing the quality of such apps. In 2018, the National Institute for Health and Care Excellence (NICE) developed a framework for assessing the required level of evidence for digital health technologies (DHTs), as determined by their clinical function. The framework can potentially be used to assess mobile apps, which are a subset of DHTs. To be used reliably in this context, the framework must allow unambiguous classification of an app's clinical function. OBJECTIVE: The objective of this study was to determine whether mobile health apps could be reliably classified using the NICE evidence standards framework for DHTs. METHODS: We manually extracted app titles, screenshots, and content descriptions for all apps listed on the National Health Service (NHS) Apps Library website on July 12, 2019; none of the apps were downloaded. Using this information, 2 mobile health (mHealth) researchers independently classified each app to one of the 4 functional tiers (ie, 1, 2, 3a, and 3b) described in the NICE digital technologies evaluation framework. Coders also answered contextual questions from the framework to identify whether apps were deemed to be higher risk. Agreement between coders was assessed using Cohen κ statistic. RESULTS: In total, we assessed 76 apps from the NHS Apps Library. There was classification agreement for 42 apps. Of these, 0 apps were unanimously classified into Tier 1; 24, into Tier 2; 15, into Tier 3a; and 3, into Tier 3b. There was disagreement between coders in 34/76 cases (45%); interrater agreement was poor (Cohen κ=0.32, 95% CI 0.16-0.47). Further investigation of disagreements highlighted 5 main explanatory themes: apps that did not correspond to any tier, apps that corresponded to multiple tiers, ambiguous tier descriptions, ambiguous app descriptions, and coder error. CONCLUSIONS: The current iteration of the NICE evidence standards framework for DHTs did not allow mHealth researchers to consistently and unambiguously classify digital health mobile apps listed on the NHS app library according to their functional tier.

Functional Changes in the Language Network in Response to Increased Amyloid ß Deposition in Cognitively Intact Older Adults.

Word finding symptoms are frequent early in the course of Alzheimer's disease and relate principally to functional changes in left posterior temporal cortex. In cognitively intact older adults, we examined whether amyloid load affects the network for language and associative-semantic processing. Fifty-six community-recruited subjects (52-74 years), stratified for apolipoprotein E and brain-derived neurotrophic factor genotype, received a neurolinguistic assessment, (18)F-flutemetamol positron emission tomography, and a functional MRI of the associative-semantic system. The primary measure of amyloid load was the cerebral-to-cerebellar gray matter standardized uptake value ratio in a composite cortical volume of interest (SUVR(comp)). The primary outcome analysis consisted of a whole-brain voxelwise linear regression between SUVR(comp) and fMRI response during associative-semantic versus visuoperceptual processing. Higher activity in one region, the posterior left middle temporal gyrus, correlated positively with increased amyloid load. The correlation remained significant when only the word conditions were contrasted but not for pictures. According to a stepwise linear regression analysis, offline naming reaction times correlated positively with SUVR(comp). A binary classification into amyloid-positive and amyloid-negative cases confirmed our findings. The left posterior temporal activity increase may reflect higher demands for semantic control in the presence of a higher amyloid burden.

The Good, the Bad, and the Irrelevant: Neural Mechanisms of Learning Real and Hypothetical Rewards and Effort.

Natural environments are complex, and a single choice can lead to multiple outcomes. Agents should learn which outcomes are due to their choices and therefore relevant for future decisions and which are stochastic in ways common to all choices and therefore irrelevant for future decisions between options. We designed an experiment in which human participants learned the varying reward and effort magnitudes of two options and repeatedly chose between them. The reward associated with a choice was randomly real or hypothetical (i.e., participants only sometimes received the reward magnitude associated with the chosen option). The real/hypothetical nature of the reward on any one trial was, however, irrelevant for learning the longer-term values of the choices, and participants ought to have only focused on the informational content of the outcome and disregarded whether it was a real or hypothetical reward. However, we found that participants showed an irrational choice bias, preferring choices that had previously led, by chance, to a real reward in the last trial. Amygdala and ventromedial prefrontal activity was related to the way in which participants' choices were biased by real reward receipt. By contrast, activity in dorsal anterior cingulate cortex, frontal operculum/anterior insula, and especially lateral anterior prefrontal cortex was related to the degree to which participants resisted this bias and chose effectively in a manner guided by aspects of outcomes that had real and more sustained relationships with particular choices, suppressing irrelevant reward information for more optimal learning and decision making. SIGNIFICANCE STATEMENT: In complex natural environments, a single choice can lead to multiple outcomes. Human agents should only learn from outcomes that are due to their choices, not from outcomes without such a relationship. We designed an experiment to measure learning about reward and effort magnitudes in an environment in which other features of the outcome were random and had no relationship with choice. We found that, although people could learn about reward magnitudes, they nevertheless were irrationally biased toward repeating certain choices as a function of the presence or absence of random reward features. Activity in different brain regions in the prefrontal cortex either reflected the bias or reflected resistance to the bias.

Amyloid imaging in cognitively normal older adults: comparison between (18)F-flutemetamol and (11)C-Pittsburgh compound B.

PURPOSE: Preclinical, or asymptomatic, Alzheimer's disease (AD) refers to the presence of positive AD biomarkers in the absence of cognitive deficits. This research concept is being applied to define target populations for clinical drug development. In a prospective community-recruited cohort of cognitively intact older adults, we compared two amyloid imaging markers within subjects: (18)F-flutemetamol and (11)C-Pittsburgh compound B (PIB). METHODS: In 32 community-recruited cognitively intact older adults aged between 65 and 80 years, we determined the concordance between binary classification based on (18)F-flutemetamol versus (11)C-PIB according to semiquantitative assessment (standardized uptake value ratio in composite cortical volume, SUVRcomp) and, alternatively, according to visual reads. We also determined the correlation between (18)F-flutemetamol and (11)C-PIB SUVR and evaluated how this was affected by the reference region chosen (cerebellar grey matter versus pons) and the use of partial volume correction (PVC) in this population. RESULTS: Binary classification based on semiquantitative assessment was concordant between (18)F-flutemetamol and (11)C-PIB in 94 % of cases. Concordance of blinded binary visual reads between tracers was 84 %. The Spearman correlation between (18)F-flutemetamol and (11)C-PIB SUVRcomp with cerebellar grey matter as reference region was 0.84, with a slope of 0.98. Correlations in neocortical regions were significantly lower with the pons as reference region. PVC improved the correlation in striatum and medial temporal cortex. CONCLUSION: For the definition of preclinical AD based on (18)F-flutemetamol, concordance with (11)C-PIB was highest using semiquantitative assessment with cerebellar grey matter as reference region.

Frontal and parietal cortical interactions with distributed visual representations during selective attention and action selection.

Using multivoxel pattern analysis (MVPA), we studied how distributed visual representations in human occipitotemporal cortex are modulated by attention and link their modulation to concurrent activity in frontal and parietal cortex. We detected similar occipitotemporal patterns during a simple visuoperceptual task and an attention-to-working-memory task in which one or two stimuli were cued before being presented among other pictures. Pattern strength varied from highest to lowest when the stimulus was the exclusive focus of attention, a conjoint focus, and when it was potentially distracting. Although qualitatively similar effects were seen inside regions relatively specialized for the stimulus category and outside, the former were quantitatively stronger. By regressing occipitotemporal pattern strength against activity elsewhere in the brain, we identified frontal and parietal areas exerting top-down control over, or reading information out from, distributed patterns in occipitotemporal cortex. Their interactions with patterns inside regions relatively specialized for that stimulus category were higher than those with patterns outside those regions and varied in strength as a function of the attentional condition. One area, the frontal operculum, was distinguished by selectively interacting with occipitotemporal patterns only when they were the focus of attention. There was no evidence that any frontal or parietal area actively inhibited occipitotemporal representations even when they should be ignored and were suppressed. Using MVPA to decode information within these frontal and parietal areas showed that they contained information about attentional context and/or readout information from occipitotemporal cortex to guide behavior but that frontal regions lacked information about category identity.

Binary classification of ¹8F-flutemetamol PET using machine learning: comparison with visual reads and structural MRI.

(18)F-flutemetamol is a positron emission tomography (PET) tracer for in vivo amyloid imaging. The ability to classify amyloid scans in a binary manner as 'normal' versus 'Alzheimer-like', is of high clinical relevance. We evaluated whether a supervised machine learning technique, support vector machines (SVM), can replicate the assignments made by visual readers blind to the clinical diagnosis, which image components have highest diagnostic value according to SVM and how (18)F-flutemetamol-based classification using SVM relates to structural MRI-based classification using SVM within the same subjects. By means of SVM with a linear kernel, we analyzed (18)F-flutemetamol scans and volumetric MRI scans from 72 cases from the (18)F-flutemetamol phase 2 study (27 clinically probable Alzheimer's disease (AD), 20 amnestic mild cognitive impairment (MCI), 25 controls). In a leave-one-out approach, we trained the (18)F-flutemetamol based classifier by means of the visual reads and tested whether the classifier was able to reproduce the assignment based on visual reads and which voxels had the highest feature weights. The (18)F-flutemetamol based classifier was able to replicate the assignments obtained by visual reads with 100% accuracy. The voxels with highest feature weights were in the striatum, precuneus, cingulate and middle frontal gyrus. Second, to determine concordance between the gray matter volume- and the (18)F-flutemetamol-based classification, we trained the classifier with the clinical diagnosis as gold standard. Overall sensitivity of the (18)F-flutemetamol- and the gray matter volume-based classifiers were identical (85.2%), albeit with discordant classification in three cases. Specificity of the (18)F-flutemetamol based classifier was 92% compared to 68% for MRI. In the MCI group, the (18)F-flutemetamol based classifier distinguished more reliably between converters and non-converters than the gray matter-based classifier. The visual read-based binary classification of (18)F-flutemetamol scans can be replicated using SVM. In this sample the specificity of (18)F-flutemetamol based SVM for distinguishing AD from controls is higher than that of gray matter volume-based SVM.

A European multicentre PET study of fibrillar amyloid in Alzheimer's disease.

PURPOSE: Amyloid PET tracers have been developed for in vivo detection of brain fibrillar amyloid deposition in Alzheimer's disease (AD). To serve as an early biomarker in AD the amyloid PET tracers need to be analysed in multicentre clinical studies. METHODS: In this study 238 [(11)C]Pittsburgh compound-B (PIB) datasets from five different European centres were pooled. Of these 238 datasets, 18 were excluded, leaving [(11)C]PIB datasets from 97 patients with clinically diagnosed AD (mean age 69 ± 8 years), 72 patients with mild cognitive impairment (MCI; mean age 67.5 ± 8 years) and 51 healthy controls (mean age 67.4 ± 6 years) available for analysis. Of the MCI patients, 64 were longitudinally followed for 28 ± 15 months. Most participants (175 out of 220) were also tested for apolipoprotein E (ApoE) genotype. RESULTS: [(11)C]PIB retention in the neocortical and subcortical brain regions was significantly higher in AD patients than in age-matched controls. Intermediate [(11)C]PIB retention was observed in MCI patients, with a bimodal distribution (64 % MCI PIB-positive and 36 % MCI PIB-negative), which was significantly different the pattern in both the AD patients and controls. Higher [(11)C]PIB retention was observed in MCI ApoE ε4 carriers compared to non-ApoE ε4 carriers (p < 0.005). Of the MCI PIB-positive patients, 67 % had converted to AD at follow-up while none of the MCI PIB-negative patients converted. CONCLUSION: This study demonstrated the robustness of [(11)C]PIB PET as a marker of neocortical fibrillar amyloid deposition in brain when assessed in a multicentre setting. MCI PIB-positive patients showed more severe memory impairment than MCI PIB-negative patients and progressed to AD at an estimated rate of 25 % per year. None of the MCI PIB-negative patients converted to AD, and thus PIB negativity had a 100 % negative predictive value for progression to AD. This supports the notion that PIB-positive scans in MCI patients are an indicator of prodromal AD.

Noninvasive associative plasticity induction in a corticocortical pathway of the human brain.

Coincident pairing of presynaptic and postsynaptic activity selectively strengthens synaptic connections, a key mechanism underlying cortical plasticity. Using paired associative transcranial magnetic stimulation (TMS), we demonstrate selective potentiation of physiological connectivity between two human brain regions, ventral premotor cortex (PMv) and primary motor cortex (M1) after repeated paired-pulse TMS of PMv and M1. The effect was anatomically specific: paired stimulation of the presupplementary motor area and M1 did not induce changes in PMv-M1 pathway connectivity. The effect was dependent on stimulation order: repeated stimulation of PMv before M1 led to strengthening of the PMv-M1 pathway, while repeated stimulation of M1 before PMv diminished the strength of the PMv-M1 pathway. The expression of the change in the pathway depended on the cognitive state of the subject at the time of testing: when the subject was tested at rest, paired PMv-M1 stimulation led to an increased inhibitory influence of PMv over M1, but when the subject was tested while engaged in a visuomotor task, PMv-M1 stimulation led to an increased facilitatory influence of PMv over M1. Plasticity evolved rapidly, lasted for at least 1 h, and began to reverse 3 h after intervention.

Gesture discrimination in primary progressive aphasia: the intersection between gesture and language processing pathways.

The issue of the relationship between language and gesture processing and the partial overlap of their neural representations is of fundamental importance to neurology, psychology, and social sciences. Patients suffering from primary progressive aphasia, a clinical syndrome characterized by comparatively isolated language deficits, may provide direct evidence for anatomical and functional association between specific language deficits and gesture discrimination deficits. A consecutive series of 16 patients with primary progressive aphasia and 16 matched control subjects participated. Our nonverbal gesture discrimination task consisted of 19 trials. In each trial, participants observed three video clips showing the same gesture performed correctly in one clip and incorrectly in the other two. Subjects had to indicate which of the three versions was correct. Language and gesture production were evaluated by means of conventional tasks. All participants underwent high-resolution structural and diffusion tensor magnetic resonance imaging. Ten of the primary progressive aphasia patients showed a significant deficit on the nonverbal gesture discrimination task. A factor analysis revealed that this deficit clustered with gesture imitation, word and pseudoword repetition, and writing-to-dictation. Individual scores on this cluster correlated with volume in the left anterior inferior parietal cortex extending into the posterior superior temporal gyrus. Probabilistic tractography indicated this region comprised the cortical relay station of the indirect pathway connecting the inferior frontal gyrus and the superior temporal cortex. Thus, the left perisylvian temporoparietal area may underpin verbal imitative behavior, gesture imitation, and gesture discrimination indicative of a partly shared neural substrate for language and gesture resonance.

18F-flutemetamol amyloid imaging in Alzheimer disease and mild cognitive impairment: a phase 2 trial.

OBJECTIVE: The most widely studied positron emission tomography ligand for in vivo beta-amyloid imaging is (11)C-Pittsburgh compound B ((11)C-PIB). Its availability, however, is limited by the need for an on-site cyclotron. Validation of the (18)F-labeled PIB derivative (18)F-flutemetamol could significantly enhance access to this novel technology. METHODS: Twenty-seven patients with early-stage clinically probable Alzheimer disease (AD), 20 with amnestic mild cognitive impairment (MCI), and 15 cognitively intact healthy volunteers (HVs) above and 10 HVs below 55 years of age participated. The primary endpoint was the efficacy of blinded visual assessments of (18)F-flutemetamol scans in assigning subjects to a raised versus normal uptake category, with clinical diagnosis as the standard of truth (SOT). As secondary objectives, we determined the correlation between the regional standardized uptake value ratios (SUVRs) for (18)F-flutemetamol and its parent molecule (11)C-PIB in 20 of the AD subjects and 20 of the MCI patients. We also determined test-retest variability of (18)F-flutemetamol SUVRs in 5 of the AD subjects. RESULTS: Blinded visual assessments of (18)F-flutemetamol scans assigned 25 of 27 scans from AD subjects and 1 of 15 scans from the elderly HVs to the raised category, corresponding to a sensitivity of 93.1% and a specificity of 93.3% against the SOT. Correlation coefficients between cortical (18)F-flutemetamol SUVRs and (11)C-PIB SUVRs ranged from 0.89 to 0.92. Test-retest variabilities of regional SUVRs were 1 to 4%. INTERPRETATION: (18)F-Flutemetamol performs similarly to the (11)C-PIB parent molecule within the same subjects and provides high test-retest replicability and potentially much wider accessibility for clinical and research use.

Quantity and type of peer-reviewed evidence for popular free medical apps: Cross-sectional review.

INTRODUCTION: - Mobile apps are being increasingly used as a tool to deliver clinical care. Evidence of efficacy for such apps varies, and appropriate levels of evidence may depend on the app's intended use. The UK's National Institute for Health and Care Excellence (NICE) recently developed an evidence standards framework, aiming to explicitly set out the required standards of evidence for different categories of digital health technologies. To determine current compliance with the evidence standards framework, the current study quantified the amount and type of peer-reviewed evidence associated with a cross-section of popular medical apps. METHODS: - Apps were identified by selecting the top 100 free medical apps in the Apple App Store and all free apps in the NHS Apps Library. Each app was assigned to one of the four tiers (1, 2, 3a, 3b) in the NICE evidence standards framework. For each app, we conducted searches in Ovid-MEDLINE, Web of Science, Google Scholar, and via manufacturer websites to identify any published articles that assessed the app. This allowed us to determine our primary outcome, whether apps in tiers 3a/3b were more likely than apps in tier 1/2 to be associated with academic peer-reviewed evidence. RESULTS: - We reviewed 125 apps in total (Apple App Store (n = 72), NHS Apps Library (n = 45), both (n = 8), of which 54 were categorized into the higher evidence standards framework tiers, 3a/3b. After screening, we extracted 105 relevant articles which were associated with 25 of the apps. Only 6 articles, pertaining to 3 apps, were reports of randomised controlled trials. Apps in tiers 3a/3b were more likely to be associated with articles than apps in lower tiers (χ2 = 5.54, p = .01). The percentage of tier 3a/3b apps with associated articles was similar for both the NHS Apps Library (10/28) and Apple App store (7/24), (χ2 = 0.042, p = .84). DISCUSSION: - Apps that were in higher tiers 3a and 3b, indicating higher clinical risk, were more likely to have an associated article than those in lower categories. However, even in these tiers, supporting peer-reviewed evidence was missing in the majority of instances. In our sample, Apps from the NHS Apps Library were more no more likely to have supporting evidence than popular Apple App Store apps. This is of concern, given that NHS approval may influence uptake of app usage.

Baseline cognition is the best predictor of 4-year cognitive change in cognitively intact older adults.

BACKGROUND: We examined in cognitively intact older adults the relative weight of cognitive, genetic, structural and amyloid brain imaging variables for predicting cognitive change over a 4-year time course. METHODS: One hundred-eighty community-recruited cognitively intact older adults (mean age 68 years, range 52-80 years, 81 women) belonging to the Flemish Prevent Alzheimer's Disease Cohort KU Leuven (F-PACK) longitudinal observational cohort underwent a baseline evaluation consisting of detailed cognitive assessment, structural MRI and 18F-flutemetamol PET. At inclusion, subjects were stratified based on Apolipoprotein E (APOE) ε4 and Brain-Derived Neurotrophic Factor (BDNF) val66met polymorphism according to a factorial design. At inclusion, 15% were amyloid-PET positive (Centiloid >23.4). All subjects underwent 2-yearly follow-up of cognitive performance for a 4-year time period. Baseline cognitive scores were analysed using factor analysis. The slope of cognitive change over time was modelled using latent growth curve analysis. Using correlation analysis, hierarchical regression and mediation analysis, we examined the effect of demographic (age, sex, education) and genetic variables, baseline cognition, MRI volumetric (both voxelwise and region-based) as well as amyloid imaging measures on the longitudinal slope of cognitive change. RESULTS: A base model of age and sex explained 18.5% of variance in episodic memory decline. This increased to 41.6% by adding baseline episodic memory scores. Adding amyloid load or volumetric measures explained only a negligible additional amount of variance (increase to 42.2%). A mediation analysis indicated that the effect of age on episodic memory scores was partly direct and partly mediated via hippocampal volume. Amyloid load did not play a significant role as mediator between age, hippocampal volume and episodic memory decline. CONCLUSION: In cognitively intact older adults, the strongest baseline predictor of subsequent episodic memory decline was the baseline episodic memory score. When this score was included, only very limited explanatory power was added by brain volume or amyloid load measures. The data warn against classifications that are purely biomarker-based and highlight the value of baseline cognitive performance levels in predictive models.

A dynamic microsimulation model for epidemics.

A large evidence base demonstrates that the outcomes of COVID-19 and national and local interventions are not distributed equally across different communities. The need to inform policies and mitigation measures aimed at reducing the spread of COVID-19 highlights the need to understand the complex links between our daily activities and COVID-19 transmission that reflect the characteristics of British society. As a result of a partnership between academic and private sector researchers, we introduce a novel data driven modelling framework together with a computationally efficient approach to running complex simulation models of this type. We demonstrate the power and spatial flexibility of the framework to assess the effects of different interventions in a case study where the effects of the first UK national lockdown are estimated for the county of Devon. Here we find that an earlier lockdown is estimated to result in a lower peak in COVID-19 cases and 47% fewer infections overall during the initial COVID-19 outbreak. The framework we outline here will be crucial in gaining a greater understanding of the effects of policy interventions in different areas and within different populations.

Multivariate analysis reveals anatomical correlates of naming errors in primary progressive aphasia.

Primary progressive aphasia (PPA) is an overarching term for a heterogeneous group of neurodegenerative diseases which affect language processing. Impaired picture naming has been linked to atrophy of the anterior temporal lobe in the semantic variant of PPA. Although atrophy of the anterior temporal lobe proposedly impairs picture naming by undermining access to semantic knowledge, picture naming also entails object recognition and lexical retrieval. Using multivariate analysis, we investigated whether cortical atrophy relates to different types of naming errors generated during picture naming in 43 PPA patients (13 semantic, 9 logopenic, 11 nonfluent, and 10 mixed variant). Omissions were associated with atrophy of the anterior temporal lobes. Semantic errors, for example, mistaking a rhinoceros for a hippopotamus, were associated with atrophy of the left mid and posterior fusiform cortex and the posterior middle and inferior temporal gyrus. Semantic errors and atrophy in these regions occurred in each PPA subtype, without major between-subtype differences. We propose that pathological changes to neural mechanisms associated with semantic errors occur across the PPA spectrum.

The NASSS-CAT Tools for Understanding, Guiding, Monitoring, and Researching Technology Implementation Projects in Health and Social Care: Protocol for an Evaluation Study in Real-World Settings.

BACKGROUND: Projects to implement health care and social care innovations involving technologies are typically ambitious and complex. Many projects fail. Greenhalgh et al's nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework was developed to analyze the varied outcomes of such projects. OBJECTIVE: We sought to extend the NASSS framework to produce practical tools for understanding, guiding, monitoring, and researching technology projects in health care or social care settings. METHODS: Building on NASSS and a complexity assessment tool (CAT), the NASSS-CAT tools were developed (in various formats) in seven co-design workshops involving 50 stakeholders (industry executives, technical designers, policymakers, managers, clinicians, and patients). Using action research, they were and are being tested prospectively on a sample of case studies selected for variety in conditions, technologies, settings, scope and scale, policy context, and project goals. RESULTS: The co-design process resulted in four tools, available as free downloads. NASSS-CAT SHORT is a taster to introduce the instrument and gauge interest. NASSS-CAT LONG is intended to support reflection, due diligence, and preliminary planning. It maps complexity through stakeholder discussion across six domains, using free-text open questions (designed to generate a rich narrative and surface uncertainties and interdependencies) and a closed-question checklist; this version includes an action planning section. NASSS-CAT PROJECT is a 35-item instrument for monitoring how subjective complexity in a technology implementation project changes over time. NASSS-CAT INTERVIEW is a set of prompts for conducting semistructured research or evaluation interviews. Preliminary data from empirical case studies suggest that the NASSS-CAT tools can potentially identify, but cannot always help reconcile, contradictions and conflicts that block projects' progress. CONCLUSIONS: The NASSS-CAT tools are a useful addition to existing implementation tools and frameworks. Further support of the implementation projects is ongoing. We are currently producing digital versions of the tools, and plan (subject to further funding) to establish an online community of practice for people interested in using and improving the tools, and hold workshops for building cross-project collaborations. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/16861.

Whole-body biodistribution and radiation dosimetry of 18F-GE067: a radioligand for in vivo brain amyloid imaging.

UNLABELLED: We have characterized the biodistribution and dosimetry of (18)F-3'-F-6-OH-BTA1 ((18)F-GE067), a newly developed radioligand to visualize and quantify amyloid burden, in healthy elderly human subjects. METHODS: Six subjects (5 men and 1 woman; age range, 51-74 y) underwent dynamic whole-body PET/CT for 6 h after a bolus injection of (18)F-GE067. Source organs were delineated on PET/CT. Individual organ doses and effective doses were determined. RESULTS: No adverse events or clinically significant changes were observed. (18)F-GE067 is excreted predominantly through the hepatobiliary system. The gallbladder, upper large intestine, and small intestine are the organs with the highest absorbed dose (average, 287, 173, and 155 microGy/MBq, respectively). The mean effective dose was 33.8 +/- 3.4 microSv/MBq, a dose comparable to that of many other (18)F-labeled radiopharmaceuticals. CONCLUSION: The estimated effective dose of (18)F-GE067 for PET amyloid imaging was acceptable (class II-b defined by the World Health Organization), and relatively low variability between subjects was observed.

Phase 1 study of the Pittsburgh compound B derivative 18F-flutemetamol in healthy volunteers and patients with probable Alzheimer disease.

UNLABELLED: (11)C-Pittsburgh compound B (PiB) marks Abeta amyloidosis, a key pathogenetic process in Alzheimer disease (AD). The use of (11)C-PiB is limited to centers with a cyclotron. Development of the (18)F-labeled thioflavin derivative of PiB, (18)F-flutemetamol, could hugely increase the availability of this new technology. The aims of this phase 1 study were to perform brain kinetic modeling of (18)F-flutemetamol, optimize the image acquisition procedure, and compare methods of analysis (step 1) and to compare (18)F-flutemetamol brain retention in AD patients versus healthy controls in a proof-of-concept study (steps 1 and 2). METHODS: In step 1, 3 AD patients (Mini-Mental State Examination, 22-24) and 3 elderly healthy controls were scanned dynamically during windows of 0-90, 150-180, and 220-250 min after injection of approximately 180 MBq of (18)F-flutemetamol, with arterial sampling. We compared different analysis methods (compartmental modeling, Logan graphical analysis, and standardized uptake value ratios) and determined the optimal acquisition window for step 2. In step 2, 5 AD patients (Mini-Mental State Examination, 20-26) and 5 elderly healthy controls were scanned from 80 to 170 min after injection. To determine overall efficacy, steps 1 and 2 were pooled and standardized uptake value ratios were calculated using cerebellar cortex as a reference region. RESULTS: No adverse events were reported. There was a strong correlation between uptake values obtained with the different analysis methods. From 80 min after injection onward, the ratio of neocortical to cerebellar uptake was maximal and only marginally affected by scan start time or duration. AD patients showed significantly increased standardized uptake value ratios in neocortical association zones and striatum, compared with healthy controls, whereas uptake in white matter, cerebellum, and pons did not differ between groups. Two AD patients were (18)F-flutemetamol-negative and 1 healthy control was (18)F-flutemetamol-positive. CONCLUSION: (18)F-flutemetamol uptake can be readily quantified. This phase 1 study warrants further studies to validate this (18)F-labeled derivative of PiB as a biomarker for Abeta amyloidosis.