Early detection of white matter hyperintensities using SHIVA-WMH detector.

White matter hyperintensities (WMHs) are well-established markers of cerebral small vessel disease, and are associated with an increased risk of stroke, dementia, and mortality. Although their prevalence increases with age, small and punctate WMHs have been reported with surprisingly high frequency even in young, neurologically asymptomatic adults. However, most automated methods to segment WMH published to date are not optimized for detecting small and sparse WMH. Here we present the SHIVA-WMH tool, a deep-learning (DL)-based automatic WMH segmentation tool that has been trained with manual segmentations of WMH in a wide range of WMH severity. We show that it is able to detect WMH with high efficiency in subjects with only small punctate WMH as well as in subjects with large WMHs (i.e., with confluency) in evaluation datasets from three distinct databases: magnetic resonance imaging-Share consisting of young university students, MICCAI 2017 WMH challenge dataset consisting of older patients from memory clinics, and UK Biobank with community-dwelling middle-aged and older adults. Across these three cohorts with a wide-ranging WMH load, our tool achieved voxel-level and individual lesion cluster-level Dice scores of 0.66 and 0.71, respectively, which were higher than for three reference tools tested: the lesion prediction algorithm implemented in the lesion segmentation toolbox (LPA: Schmidt), PGS tool, a DL-based algorithm and the current winner of the MICCAI 2017 WMH challenge (Park et al.), and HyperMapper tool (Mojiri Forooshani et al.), another DL-based method with high reported performance in subjects with mild WMH burden. Our tool is publicly and openly available to the research community to facilitate investigations of WMH across a wide range of severity in other cohorts, and to contribute to our understanding of the emergence and progression of WMH.

Handedness and its genetic influences are associated with structural asymmetries of the cerebral cortex in 31,864 individuals.

Roughly 10% of the human population is left-handed, and this rate is increased in some brain-related disorders. The neuroanatomical correlates of hand preference have remained equivocal. We resampled structural brain image data from 28,802 right-handers and 3,062 left-handers (UK Biobank population dataset) to a symmetrical surface template, and mapped asymmetries for each of 8,681 vertices across the cerebral cortex in each individual. Left-handers compared to right-handers showed average differences of surface area asymmetry within the fusiform cortex, the anterior insula, the anterior middle cingulate cortex, and the precentral cortex. Meta-analyzed functional imaging data implicated these regions in executive functions and language. Polygenic disposition to left-handedness was associated with two of these regional asymmetries, and 18 loci previously linked with left-handedness by genome-wide screening showed associations with one or more of these asymmetries. Implicated genes included six encoding microtubule-related proteins: TUBB, TUBA1B, TUBB3, TUBB4A, MAP2, and NME7-mutations in the latter can cause left to right reversal of the visceral organs. There were also two cortical regions where average thickness asymmetry was altered in left-handedness: on the postcentral gyrus and the inferior occipital cortex, functionally annotated with hand sensorimotor and visual roles. These cortical thickness asymmetries were not heritable. Heritable surface area asymmetries of language-related regions may link the etiologies of hand preference and language, whereas nonheritable asymmetries of sensorimotor cortex may manifest as consequences of hand preference.

Laterality indices consensus initiative (LICI): A Delphi expert survey report on recommendations to record, assess, and report asymmetry in human behavioural and brain research.

Laterality indices (LIs) quantify the left-right asymmetry of brain and behavioural variables and provide a measure that is statistically convenient and seemingly easy to interpret. Substantial variability in how structural and functional asymmetries are recorded, calculated, and reported, however, suggest little agreement on the conditions required for its valid assessment. The present study aimed for consensus on general aspects in this context of laterality research, and more specifically within a particular method or technique (i.e., dichotic listening, visual half-field technique, performance asymmetries, preference bias reports, electrophysiological recording, functional MRI, structural MRI, and functional transcranial Doppler sonography). Experts in laterality research were invited to participate in an online Delphi survey to evaluate consensus and stimulate discussion. In Round 0, 106 experts generated 453 statements on what they considered good practice in their field of expertise. Statements were organised into a 295-statement survey that the experts then were asked, in Round 1, to independently assess for importance and support, which further reduced the survey to 241 statements that were presented again to the experts in Round 2. Based on the Round 2 input, we present a set of critically reviewed key recommendations to record, assess, and report laterality research for various methods.

Atlas55+: Brain Functional Atlas of Resting-State Networks for Late Adulthood.

Currently, several human brain functional atlases are used to define the spatial constituents of the resting-state networks (RSNs). However, the only brain atlases available are derived from samples of young adults. As brain networks are continuously reconfigured throughout life, the lack of brain atlases derived from older populations may influence RSN results in late adulthood. To address this gap, the aim of the study was to construct a reliable brain atlas derived only from older participants. We leveraged resting-state functional magnetic resonance imaging data from three cohorts of healthy older adults (total N = 563; age = 55-95 years) and a younger-adult cohort (N = 128; age = 18-35 years). We identified the major RSNs and their subdivisions across all older-adult cohorts. We demonstrated high spatial reproducibility of these RSNs with an average spatial overlap of 67%. Importantly, the RSNs derived from the older-adult cohorts were spatially different from those derived from the younger-adult cohort (P = 2.3 × 10-3). Lastly, we constructed a novel brain atlas, called Atlas55+, which includes the consensus of the major RSNs and their subdivisions across the older-adult cohorts. Thus, Atlas55+ provides a reliable age-appropriate template for RSNs in late adulthood and is publicly available. Our results confirm the need for age-appropriate functional atlases for studies investigating aging-related brain mechanisms.

Large-Scale Phenomic and Genomic Analysis of Brain Asymmetrical Skew.

The human cerebral hemispheres show a left-right asymmetrical torque pattern, which has been claimed to be absent in chimpanzees. The functional significance and developmental mechanisms are unknown. Here, we carried out the largest-ever analysis of global brain shape asymmetry in magnetic resonance imaging data. Three population datasets were used, UK Biobank (N = 39 678), Human Connectome Project (N = 1113), and BIL&GIN (N = 453). At the population level, there was an anterior and dorsal skew of the right hemisphere, relative to the left. Both skews were associated independently with handedness, and various regional gray and white matter metrics oppositely in the two hemispheres, as well as other variables related to cognitive functions, sociodemographic factors, and physical and mental health. The two skews showed single nucleotide polymorphisms-based heritabilities of 4-13%, but also substantial polygenicity in causal mixture model analysis, and no individually significant loci were found in genome-wide association studies for either skew. There was evidence for a significant genetic correlation between horizontal brain skew and autism, which requires future replication. These results provide the first large-scale description of population-average brain skews and their inter-individual variations, their replicable associations with handedness, and insights into biological and other factors which associate with human brain asymmetry.

Novel characterization of the relationship between verbal list-learning outcomes and hippocampal subfields in healthy adults.

The relationship between hippocampal subfield volumetry and verbal list-learning test outcomes have mostly been studied in clinical and elderly populations, and remain controversial. For the first time, we characterized a relationship between verbal list-learning test outcomes and hippocampal subfield volumetry on two large separate datasets of 447 and 1,442 healthy young and middle-aged adults, and explored the processes that could explain this relationship. We observed a replicable positive linear correlation between verbal list-learning test free recall scores and CA1 volume, specific to verbal list learning as demonstrated by the hippocampal subfield volumetry independence from verbal intelligence. Learning meaningless items was also positively correlated with CA1 volume, pointing to the role of the test design rather than word meaning. Accordingly, we found that association-based mnemonics mediated the relationship between verbal list-learning test outcomes and CA1 volume. This mediation suggests that integrating items into associative representations during verbal list-learning tests explains CA1 volume variations: this new explanation is consistent with the associative functions of the human CA1.

Automated anatomical labelling atlas 3.

Following a first version AAL of the automated anatomical labeling atlas (Tzourio-Mazoyer et al., 2002), a second version (AAL2) (Rolls et al., 2015) was developed that provided an alternative parcellation of the orbitofrontal cortex following the description provided by Chiavaras, Petrides, and colleagues. We now provide a third version, AAL3, which adds a number of brain areas not previously defined, but of interest in many neuroimaging investigations. The 26 new areas in the third version are subdivision of the anterior cingulate cortex into subgenual, pregenual and supracallosal parts; subdivision of the thalamus into 15 parts; the nucleus accumbens, substantia nigra, ventral tegmental area, red nucleus, locus coeruleus, and raphe nuclei. The new atlas is available as a toolbox for SPM, and can be used with MRIcron.

Predicting hemispheric dominance for language production in healthy individuals using support vector machine.

We used a Support Vector Machine (SVM) classifier to assess hemispheric pattern of language dominance of 47 individuals categorized as non-typical for language from their hemispheric functional laterality index (HFLI) measured on a sentence minus word-list production fMRI-BOLD contrast map. The SVM classifier was trained at discriminating between Dominant and Non-Dominant hemispheric language production activation pattern on a group of 250 participants previously identified as Typicals (HFLI strongly leftward). Then, SVM was applied to each hemispheric language activation pattern of 47 non-typical individuals. The results showed that at least one hemisphere (left or right) was found to be Dominant in every, except 3 individuals, indicating that the "dominant" type of functional organization is the most frequent in non-typicals. Specifically, left hemisphere dominance was predicted in all non-typical right-handers (RH) and in 57.4% of non-typical left-handers (LH). When both hemisphere classifications were jointly considered, four types of brain patterns were observed. The most often predicted pattern (51%) was left-dominant (Dominant left-hemisphere and Non-Dominant right-hemisphere), followed by right-dominant (23%, Dominant right-hemisphere and Non-Dominant left-hemisphere) and co-dominant (19%, 2 Dominant hemispheres) patterns. Co-non-dominant was rare (6%, 2 Non-Dominant hemispheres), but was normal variants of hemispheric specialization. In RH, only left-dominant (72%) and co-dominant patterns were detected, while for LH, all types were found, although with different occurrences. Among the 10 LH with a strong rightward HFLI, 8 had a right-dominant brain pattern. Whole-brain analysis of the right-dominant pattern group confirmed that it exhibited a functional organization strictly mirroring that of left-dominant pattern group. Hum Brain Mapp 38:5871-5889, 2017. © 2017 Wiley Periodicals, Inc.

Implementation of a new parcellation of the orbitofrontal cortex in the automated anatomical labeling atlas.

An alternative parcellation of the orbitofrontal cortex is described for the automated anatomical labeling atlas of Tzourio-Mazoyer et al. (2002) (Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage 15:273-289). The new parcellation of the orbitofrontal cortex follows the description provided by Chiavaras, Petrides, and colleagues (2000, 2001). The new atlas is available as a toolbox for SPM at http://www.gin.cnrs.fr/AAL2.

Strong rightward lateralization of the dorsal attentional network in left-handers with right sighting-eye: an evolutionary advantage.

Hemispheric lateralization for spatial attention and its relationships with manual preference strength and eye preference were studied in a sample of 293 healthy individuals balanced for manual preference. Functional magnetic resonance imaging was used to map this large sample while performing visually guided saccadic eye movements. This activated a bilateral distributed cortico-subcortical network in which dorsal and ventral attentional/saccadic pathways elicited rightward asymmetrical activation depending on manual preference strength and sighting eye. While the ventral pathway showed a strong rightward asymmetry irrespective of both manual preference strength and eye preference, the dorsal frontoparietal network showed a robust rightward asymmetry in strongly left-handers, even more pronounced in left-handed subjects with a right sighting-eye. Our findings brings support to the hypothesis that the origin of the rightward hemispheric dominance for spatial attention may have a manipulo-spatial origin neither perceptual nor motor per se but rather reflecting a mechanism by which a spatial context is mapped onto the perceptual and motor activities, including the exploration of the spatial environment with eyes and hands. Within this context, strongly left-handers with a right sighting-eye may benefit from the advantage of having the same right hemispheric control of their dominant hand and visuospatial attention processing. We suggest that this phenomenon explains why left-handed right sighting-eye athletes can outperform their competitors in sporting duels and that the prehistoric and historical constancy of the left-handers ratio over the general population may relate in part on the hemispheric specialization of spatial attention.

Modulate the impact of the drowsiness on the resting state functional connectivity.

This research explores different methodologies to modulate the effects of drowsiness on functional connectivity (FC) during resting-state functional magnetic resonance imaging (RS-fMRI). The study utilized a cohort of students (MRi-Share) and classified individuals into drowsy, alert, and mixed/undetermined states based on observed respiratory oscillations. We analyzed the FC group difference between drowsy and alert individuals after five different processing methods: the reference method, two based on physiological and a global signal regression of the BOLD time series signal, and two based on Gaussian standardizations of the FC distribution. According to the reference method, drowsy individuals exhibit higher cortico-cortical FC than alert individuals. First, we demonstrated that each method reduced the differences between drowsy and alert states. The second result is that the global signal regression was quantitively the most effective, minimizing significant FC differences to only 3.3% of the total FCs. However, one should consider the risks of overcorrection often associated with this methodology. Therefore, choosing a less aggressive form of regression, such as the physiological method or Gaussian-based approaches, might be a more cautious approach. Third and last, using the Gaussian-based methods, cortico-subcortical and intra-default mode network (DMN) FCs were significantly greater in alert than drowsy subjects. These findings bear resemblance to the anticipated patterns during the onset of sleep, where the cortex isolates itself to assist in transitioning into deeper slow wave sleep phases, simultaneously disconnecting the DMN.

Prediction of dementia risk from multimodal repeated measures: The added value of brain MRI biomarkers.

Abstract: The utility of brain magnetic resonance imaging (MRI) for predicting dementia is debated. We evaluated the added value of repeated brain MRI, including atrophy and cerebral small vessel disease markers, for dementia prediction. We conducted a landmark competing risk analysis in 1716 participants of the French population-based Three-City Study to predict the 5-year risk of dementia using repeated measures of 41 predictors till year 4 of follow-up. Brain MRI markers improved significantly the individual prediction of dementia after accounting for demographics, health measures, and repeated measures of cognition and functional dependency (area under the ROC curve [95% CI] improved from 0.80 [0.79 to 0.82] to 0.83 [0.81 to 0.84]). Nonetheless, accounting for the change over time through repeated MRIs had little impact on predictive abilities. These results highlight the importance of multimodal analysis to evaluate the added predictive abilities of repeated brain MRI for dementia and offer new insights into the predictive performances of various MRI markers. Highlights: We evaluated whether repeated brain volumes and cSVD markers improve dementia prediction.The 5-year prediction of dementia is slightly improved when considering brain MRI markers.Measures of hippocampus volume are the main MRI predictors of dementia.Adjusted on cognition, repeated MRI has poor added value over single MRI for dementia prediction.We utilized a longitudinal analysis that considers error-and-missing-prone predictors, and competing death.

Atlasing white matter and grey matter joint contributions to resting-state networks in the human brain.

Over the past two decades, the study of resting-state functional magnetic resonance imaging has revealed that functional connectivity within and between networks is linked to cognitive states and pathologies. However, the white matter connections supporting this connectivity remain only partially described. We developed a method to jointly map the white and grey matter contributing to each resting-state network (RSN). Using the Human Connectome Project, we generated an atlas of 30 RSNs. The method also highlighted the overlap between networks, which revealed that most of the brain's white matter (89%) is shared between multiple RSNs, with 16% shared by at least 7 RSNs. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the communication within networks. We provide an atlas and an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage to these networks. In a first application of the software with clinical data, we were able to link stroke patients and impacted RSNs, showing that their symptoms aligned well with the estimated functions of the networks.

Patterns of hemodynamic low-frequency oscillations in the brain are modulated by the nature of free thought during rest.

During conscious rest, the mind switches into a state of wandering. Although this rich inner experience occupies a large portion of the time spent awake, how it relates to brain activity has not been well explored. Here, we report the results of a behavioral and functional magnetic resonance imaging (fMRI) study of the continuous resting state in 307 healthy participants. The analysis focused on the relationship between the nature of inner experience and the temporal correlations computed between the low-frequency blood oxygen level-dependent (BOLD) fluctuations (0.01-0.1 Hz) of five large-scale modules. The subjects' self-reported time spontaneously spent on visual mental imagery and/or inner language was used as the behavioral variable. Decreased temporal correlations between modules were revealed when subjects reported more time spent thinking in mental images and inner language. These changes segregated the three modules supporting inner-oriented activities from those associated with sensory-related and externally guided activities. Among the brain areas associated with inner-oriented processing, the module including the lateral parietal and frontal regions (commonly described as being engaged in the manipulation and maintenance of internal information) was implicated in the majority of these effects. The preponderance of segregation appears to be the signature of the spontaneous sequence of thoughts during rest that are not constrained by logic, causality, or even a rigorous temporal organization. In other words, though goal-directed tasks have been demonstrated to rely on specific regional integration, mind wandering can be characterized by widespread modular segregation. Overall, the present study provides evidence that modulation of spontaneous low-frequency fluctuations in the brain is at least partially explained by spontaneous conscious cognition while at rest.

Neural correlates of perceiving and interpreting engraved prehistoric patterns as human production: Effect of archaeological expertise.

It has been suggested that engraved abstract patterns dating from the Middle and Lower Palaeolithic served as means of representation and communication. Identifying the brain regions involved in visual processing of these engravings can provide insights into their function. In this study, brain activity was measured during perception of the earliest known Palaeolithic engraved patterns and compared to natural patterns mimicking human-made engravings. Participants were asked to categorise marks as being intentionally made by humans or due to natural processes (e.g. erosion, root etching). To simulate the putative familiarity of our ancestors with the marks, the responses of expert archaeologists and control participants were compared, allowing characterisation of the effect of previous knowledge on both behaviour and brain activity in perception of the marks. Besides a set of regions common to both groups and involved in visual analysis and decision-making, the experts exhibited greater activity in the inferior part of the lateral occipital cortex, ventral occipitotemporal cortex, and medial thalamic regions. These results are consistent with those reported in visual expertise studies, and confirm the importance of the integrative visual areas in the perception of the earliest abstract engravings. The attribution of a natural rather than human origin to the marks elicited greater activity in the salience network in both groups, reflecting the uncertainty and ambiguity in the perception of, and decision-making for, natural patterns. The activation of the salience network might also be related to the process at work in the attribution of an intention to the marks. The primary visual area was not specifically involved in the visual processing of engravings, which argued against its central role in the emergence of engraving production.

Left hemisphere lateralization for language in right-handers is controlled in part by familial sinistrality, manual preference strength, and head size.

We investigated the effects of familial sinistrality (FS+; presence of left-handedness in one's close relatives), manual preference strength (MPS), and head size on the hemispheric lateralization of language in right-handers. Functional magnetic resonance imaging was used to map 49 individuals while listening to a story in their mother tongue. We found that individuals who had both the FS+ trait and weak MPS had no left hemisphere dominance for this lexicosyntactic task, whereas others showed a leftward functional asymmetry. In addition, the smaller the brain size, the smaller the leftward asymmetry for language, independent of FS and MPS. None of these effects were observed when the same subjects performed a spatial attention task that elicited right hemispheric functional asymmetry. These results demonstrate that the left hemisphere dominance for language in right-handers is a variable controlled, in part, by a number of specific factors, including FS, MPS, and head size.

Brain activity at rest: a multiscale hierarchical functional organization.

Spontaneous brain activity was mapped with functional MRI (fMRI) in a sample of 180 subjects while in a conscious resting-state condition. With the use of independent component analysis (ICA) of each individual fMRI signal and classification of the ICA-defined components across subjects, a set of 23 resting-state networks (RNs) was identified. Functional connectivity between each pair of RNs was assessed using temporal correlation analyses in the 0.01- to 0.1-Hz frequency band, and the corresponding set of correlation coefficients was used to obtain a hierarchical clustering of the 23 RNs. At the highest hierarchical level, we found two anticorrelated systems in charge of intrinsic and extrinsic processing, respectively. At a lower level, the intrinsic system appears to be partitioned in three modules that subserve generation of spontaneous thoughts (M1a; default mode), inner maintenance and manipulation of information (M1b), and cognitive control and switching activity (M1c), respectively. The extrinsic system was found to be made of two distinct modules: one including primary somatosensory and auditory areas and the dorsal attentional network (M2a) and the other encompassing the visual areas (M2b). Functional connectivity analyses revealed that M1b played a central role in the functioning of the intrinsic system, whereas M1c seems to mediate exchange of information between the intrinsic and extrinsic systems.

Effect of familial sinistrality on planum temporale surface and brain tissue asymmetries.

The impact of having left-handers (LHs) among one's close relatives, called familial sinistrality (FS), on neuroanatomical markers of left-hemisphere language specialization was studied in 274 normal adults, including 199 men and 75 women, among whom 77 men and 27 women were positive for FS. Measurements of the surface of a phonological cortical area, the "planum temporale" (PT), and gray and white matter hemispheric volumes and asymmetries were made using brain magnetic resonance images. The size of the left PT of subjects with left-handed close relatives (FS+) was reduced by 10%, decreasing with the number of left-handed relatives, and lowest when the subject's mother was left-handed. Such findings had no counterparts in the right hemisphere, and the subject's handedness and sex were found to have no significant effect or interaction with FS on the left PT size. The FS+ subjects also exhibited increased gray matter volume, reduced hemispheric gray matter leftward asymmetry, and, in LHs, reduced strength of hand preference. These results add to the increasing body of evidence suggesting multiple and somewhat independent mechanisms for the inheritance of hand and language lateralization.

Deep Learning-based Classification of Resting-state fMRI Independent-component Analysis.

Functional connectivity analyses of fMRI data have shown that the activity of the brain at rest is spatially organized into resting-state networks (RSNs). RSNs appear as groups of anatomically distant but functionally tightly connected brain regions. Inter-RSN intrinsic connectivity analyses may provide an optimal spatial level of integration to analyze the variability of the functional connectome. Here we propose a deep learning approach to enable the automated classification of individual independent-component (IC) decompositions into a set of predefined RSNs. Two databases were used in this work, BIL&GIN and MRi-Share, with 427 and 1811 participants, respectively. We trained a multilayer perceptron (MLP) to classify each IC as one of 45 RSNs, using the IC classification of 282 participants in BIL&GIN for training and a 5-dimensional parameter grid search for hyperparameter optimization. It reached an accuracy of 92 %. Predictions for the remaining individuals in BIL&GIN were tested against the original classification and demonstrated good spatial overlap between the cortical RSNs. As a first application, we created an RSN atlas based on MRi-Share. This atlas defined a brain parcellation in 29 RSNs covering 96 % of the gray matter. Second, we proposed an individual-based analysis of the subdivision of the default-mode network into 4 networks. Minimal overlap between RSNs was found except in the angular gyrus and potentially in the precuneus. We thus provide the community with an individual IC classifier that can be used to analyze one dataset or to statistically compare different datasets for RSN spatial definitions.

Brain reactivity to humorous films is affected by insomnia.

STUDY OBJECTIVES: Emotional reactivity to negative stimuli has been investigated in insomnia, but little is known about emotional reactivity to positive stimuli and its neural representation. METHODS: We used 3 Tesla functional magnetic resonance imaging (fMRI) to determine neural reactivity during the presentation of standardized short, 10- to 40-seconds, humorous films in patients with insomnia (n = 20, 18 females, aged 27.7 +/- 8.6 years) and age-matched individuals without insomnia (n = 20, 19 females, aged 26.7 +/- 7.0 years) and assessed humor ratings through a visual analog scale. Seed-based functional connectivity was analyzed for the left and right amygdalas (lAMYG and rAMYG, respectively) networks: group-level mixed-effects analysis (FLAME; FMRIB Software Library [FSL]) was used to compare amygdala connectivity maps between groups. RESULTS: fMRI seed-based analysis of the amygdala revealed stronger neural reactivity in patients with insomnia than in controls in several brain network clusters within the reward brain network, without humor rating differences between groups (p = 0.6). For lAMYG connectivity, cluster maxima were in the left caudate (Z = 3.88), left putamen (Z = 3.79), and left anterior cingulate gyrus (Z = 4.11), whereas for rAMYG connectivity, cluster maxima were in the left caudate (Z = 4.05), right insula (Z = 3.83), and left anterior cingulate gyrus (Z = 4.29). Cluster maxima of the rAMYG network were correlated with hyperarousal scores in patients with insomnia only. CONCLUSIONS: The presentation of humorous films leads to increased brain activity in the neural reward network for patients with insomnia compared with controls, related to hyperarousal features in patients with insomnia, in the absence of humor rating group differences. These novel findings may benefit insomnia treatment interventions. CLINICAL TRIAL: The Sleepless Brain: Neuroimaging Support for a Differential Diagnosis of Insomnia (SOMNET). ClinicalTrials.gov identifier: NCT02821234; https://clinicaltrials.gov/ct2/show/NCT02821234.