MINC 2.0: A Flexible Format for Multi-Modal Images

Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging

Neuroimaging research requires purpose-built analysis software, which is challenging to install and may produce different results across computing environments. The community-oriented, open-source Neurodesk platform ( https://www.neurodesk.org/ ) harnesses a comprehensive and growing suite of neuroimaging software containers. Neurodesk includes a browser-accessible virtual desktop, command-line interface and computational notebook compatibility, allowing for accessible, flexible, portable and fully reproducible neuroimaging analysis on personal workstations, high-performance computers and the cloud.

Subtle white matter intensity changes on fluid-attenuated inversion recovery imaging in patients with ischaemic stroke

Leukoaraiosis is a neuroimaging marker of small-vessel disease that is characterized by high signal intensity on fluid-attenuated inversion recovery MRI. There is increasing evidence from pathology and neuroimaging suggesting that the structural abnormalities that characterize leukoaraiosis are actually present within regions of normal-appearing white matter, and that the underlying pathophysiology of white matter damage related to small-vessel disease involves blood-brain barrier damage. In this study, we aim to verify whether leukoaraiosis is associated with elevated signal intensity on fluid-attenuated inversion recovery imaging, a marker of brain tissue free-water accumulation, in normal-appearing white matter. We performed a cross-sectional study of adult patients admitted to our hospital with a diagnosis of acute ischaemic stroke or transient ischaemic attack. Leukoaraiosis was segmented using a semi-automated method involving manual outlining and signal thresholding. White matter regions were segmented based on the probabilistic tissue maps from the International Consortium for Brain Mapping 152 atlas. Also, normal-appearing white matter was further segmented based on voxel distance from leukoaraiosis borders, resulting in five normal-appearing white matter strata at increasing voxel distances from leukoaraiosis. The relationship between mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter and leukoaraiosis volume was studied in a multivariable statistical analysis using linear mixed modelling, having normal-appearing white matter strata as a clustering variable. One hundred consecutive patients meeting inclusion and exclusion criteria were selected for analysis (53% female, mean age 68 years). Mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter was higher in the vicinity of leukoaraiosis and progressively lower at increasing distances from leukoaraiosis. In a multivariable analysis, the mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter was positively associated with leukoaraiosis volume and age (B = 0.025 for each leukoaraiosis quartile increase; 95% confidence interval 0.019-0.030). This association was found similarly across normal-appearing white matter strata. Voxel maps of the mean normalized fluid-attenuated inversion recovery signal intensity on normal-appearing white matter showed an increase in signal intensity that was not adjacent to leukoaraiosis regions. Our results show that normal-appearing white matter exhibits subtle signal intensity changes on fluid-attenuated inversion recovery imaging that are related to leukoaraiosis burden. These results suggest that diffuse free-water accumulation is likely related to the aetiopathogenic processes underlying the development of white matter damage related to small-vessel disease.

Reduction of NIFTI files storage and compression to facilitate telemedicine services based on quantization hiding of downsampling approach

Magnetic resonance imaging is a medical imaging technique to create comprehensive images of the tissues and organs in the body. This study presents an advanced approach for storing and compressing neuroimaging informatics technology initiative files, a standard format in magnetic resonance imaging. It is designed to enhance telemedicine services by facilitating efficient and high-quality communication between healthcare practitioners and patients. The proposed downsampling approach begins by opening the neuroimaging informatics technology initiative file as volumetric data and then planning it into several slice images. Then, the quantization hiding technique will be applied to each of the two consecutive slice images to generate the stego slice with the same size. This involves the following major steps: normalization, microblock generation, and discrete cosine transformation. Finally, it assembles the resultant stego slice images to produce the final neuroimaging informatics technology initiative file as volumetric data. The upsampling process, designed to be completely blind, reverses the downsampling steps to reconstruct the subsequent image slice accurately. The efficacy of the proposed method was evaluated using a magnetic resonance imaging dataset, focusing on peak signal-to-noise ratio, signal-to-noise ratio, structural similarity index, and Entropy as key performance metrics. The results demonstrate that the proposed approach not only significantly reduces file sizes but also maintains high image quality.

Dosage-dependent effects of FGFR2W290R mutation on craniofacial shape and cellular dynamics of the basicranial synchondroses

Craniosynostosis is a common yet complex birth defect, characterized by premature fusion of the cranial sutures that can be syndromic or nonsyndromic. With over 180 syndromic associations, reaching genetic diagnoses and understanding variations in underlying cellular mechanisms remains a challenge. Variants of FGFR2 are highly associated with craniosynostosis and warrant further investigation. Using the missense mutation FGFR2W290R , an effective mouse model of Crouzon syndrome, craniofacial features were analyzed using geometric morphometrics across developmental time (E10.5-adulthood, n = 665 total). Given the interrelationship between the cranial vault and basicranium in craniosynostosis patients, the basicranium and synchondroses were analyzed in perinates. Embryonic time points showed minimal significant shape differences. However, hetero- and homozygous mutant perinates and adults showed significant differences in shape and size of the cranial vault, face, and basicranium, which were associated with cranial doming and shortening of the basicranium and skull. Although there were also significant shape and size differences associated with the basicranial bones and clear reductions in basicranial ossification in cleared whole-mount samples, there were no significant alterations in chondrocyte cell shape, size, or orientation along the spheno-occipital synchondrosis. Finally, shape differences in the cranial vault and basicranium were interrelated at perinatal stages. These results point toward the possibility that facial shape phenotypes in craniosynostosis may result in part from pleiotropic effects of the causative mutations rather than only from the secondary consequences of the sutural defects, indicating a novel direction of research that may shed light on the etiology of the broad changes in craniofacial morphology observed in craniosynostosis syndromes.

Organization of thalamocortical structural covariance and a corresponding 3D atlas of the mouse thalamus

For information from sensory organs to be processed by the brain, it is usually passed to appropriate areas of the cerebral cortex. Almost all of this information passes through the thalamus, a relay structure that reciprocally connects to the vast majority of the cortex. The thalamus facilitates this information transfer through a set of thalamocortical connections that vary in cellular structure, molecular profiles, innervation patterns, and firing rates. Additionally, corticothalamic connections allow for intracortical information transfer through the thalamus. These efferent and afferent connections between the thalamus and cortex have been the focus of many studies, and the importance of cortical connectivity in defining thalamus anatomy is demonstrated by multiple studies that parcellate the thalamus based on cortical connectivity profiles. Here, we examine correlated morphological variation between the thalamus and cortex, or thalamocortical structural covariance. For each voxel in the thalamus as a seed, we construct a cortical structural covariance map that represents correlated cortical volume variation, and examine whether high structural covariance is observed in cortical areas that are functionally relevant to the seed. Then, using these cortical structural covariance maps as features, we subdivide the thalamus into six non-overlapping regions (clusters of voxels), and assess whether cortical structural covariance is associated with cortical connectivity that specifically originates from these regions. We show that cortical structural covariance is high in areas of the cortex that are functionally related to the seed voxel, cortical structural covariance varies along cortical depth, and sharp transitions in cortical structural covariance profiles are observed when varying seed locations in the thalamus. Subdividing the thalamus based on structural covariance, we additionally demonstrate that the six thalamic clusters of voxels stratify cortical structural covariance along the dorsal-ventral, medial-lateral, and anterior-posterior axes. These cluster-associated structural covariance patterns are prominently detected in cortical regions innervated by fibers projecting out of their related thalamic subdivisions. Together, these results advance our understanding of how the thalamus and the cortex couple in their volumes. Our results indicate that these volume correlations reflect functional organization and structural connectivity, and further provides a novel segmentation of the mouse thalamus that can be used to examine thalamic structural variation and thalamocortical structural covariation in disease models.

Striatal Iron Deposition in Recreational MDMA (Ecstasy) Users

BACKGROUND

The common club drug MDMA (also known as ecstasy) enhances mood, sensory perception, energy, sociability, and euphoria. While MDMA has been shown to produce neurotoxicity in animal models, research on its potential neurotoxic effects in humans is inconclusive and has focused primarily on the serotonin system.

METHODS

We investigated 34 regular, largely pure MDMA users for signs of premature neurodegenerative processes in the form of increased iron load in comparison to a group of 36 age-, sex-, and education-matched MDMA-naïve control subjects. We used quantitative susceptibility mapping, a novel tool able to detect even small tissue (nonheme) iron accumulations. Cortical and relevant subcortical gray matter structures were grouped into 8 regions of interest and analyzed.

RESULTS

Significantly increased iron deposition in the striatum was evident in the MDMA user group. The effect survived correction for multiple comparisons and remained after controlling for relevant confounding factors, including age, smoking, and stimulant co-use. Although no significant linear relationship between measurements of the amounts of MDMA intake (hair analysis and self-reports) and quantitative susceptibility mapping values was observed, increased striatal iron deposition might nevertheless point to MDMA-induced neurotoxic processes. Additional factors (hyperthermia and simultaneous co-use of other substances) that possibly amplify neurotoxic effects of MDMA during the state of acute intoxication are discussed.

CONCLUSIONS

The demonstrated increased striatal iron accumulation may indicate that regular MDMA users have an increased risk potential for neurodegenerative diseases with progressing age.

A dataset of multi-contrast unbiased average MRI templates of a Parkinson's disease population

Parkinson's disease (PD) is a complex neurodegenerative disorder affecting regions such as the substantia nigra (SN), red nucleus (RN) and locus coeruleus (LC). Processing MRI data from patients with PD requires anatomical structural references for spatial normalization and structural segmentation. Extending our previous work, we present multi-contrast unbiased MRI templates using nine 3T MRI modalities: T1w, T2*w, T1-T2* fusion, R2*, T2w, PDw, fluid-attenuated inversion recovery (FLAIR), susceptibility-weighted imaging, and neuromelanin-sensitive MRI (NM). One mm isotropic voxel size templates were created, along with 0.5 mm isotropic whole brain templates and 0.3 mm isotropic templates of the midbrain. All templates were created from 126 PD patients (44 female; ages=40-87), and 17 healthy controls (13 female; ages=39-84), except the NM template, which was created from 85 PD patients and 13 controls, respectively. The dataset is available on the NIST MNI Repository via the following link: http://nist.mni.mcgill.ca/multi-contrast-pd126-and-ctrl17-templates/. The data is also available on NITRC at the following link: https://www.nitrc.org/projects/pd126/.

Neurodesk: An accessible, flexible, and portable data analysis environment for reproducible neuroimaging

Neuroimaging data analysis often requires purpose-built software, which can be challenging to install and may produce different results across computing environments. Beyond being a roadblock to neuroscientists, these issues of accessibility and portability can hamper the reproducibility of neuroimaging data analysis pipelines. Here, we introduce the Neurodesk platform, which harnesses software containers to support a comprehensive and growing suite of neuroimaging software (https://www.neurodesk.org/). Neurodesk includes a browser-accessible virtual desktop environment and a command line interface, mediating access to containerized neuroimaging software libraries on various computing platforms, including personal and high-performance computers, cloud computing and Jupyter Notebooks. This community-oriented, open-source platform enables a paradigm shift for neuroimaging data analysis, allowing for accessible, flexible, fully reproducible, and portable data analysis pipelines.

Automatic measurements of fetal intracranial volume from 3D ultrasound scans

Three-dimensional fetal ultrasound is commonly used to study the volumetric development of brain structures. To date, only a limited number of automatic procedures for delineating the intracranial volume exist. Hence, intracranial volume measurements from three-dimensional ultrasound images are predominantly performed manually. Here, we present and validate an automated tool to extract the intracranial volume from three-dimensional fetal ultrasound scans. The procedure is based on the registration of a brain model to a subject brain. The intracranial volume of the subject is measured by applying the inverse of the final transformation to an intracranial mask of the brain model. The automatic measurements showed a high correlation with manual delineation of the same subjects at two gestational ages, namely, around 20 and 30 weeks (linear fitting R2(20 weeks) = 0.88, R2(30 weeks) = 0.77; Intraclass Correlation Coefficients: 20 weeks=0.94, 30 weeks = 0.84). Overall, the automatic intracranial volumes were larger than the manually delineated ones (84 ± 16 vs. 76 ± 15 cm3; and 274 ± 35 vs. 237 ± 28 cm3), probably due to differences in cerebellum delineation. Notably, the automated measurements reproduced both the non-linear pattern of fetal brain growth and the increased inter-subject variability for older fetuses. By contrast, there was some disagreement between the manual and automatic delineation concerning the size of sexual dimorphism differences. The method presented here provides a relatively efficient way to delineate volumes of fetal brain structures like the intracranial volume automatically. It can be used as a research tool to investigate these structures in large cohorts, which will ultimately aid in understanding fetal structural human brain development.

Project, toolkit, and database of neuroinformatics ecosystem: A summary of previous studies on "Frontiers in Neuroinformatics"

In the field of neuroscience, the core of the cohort study project consists of collection, analysis, and sharing of multi-modal data. Recent years have witnessed a host of efficient and high-quality toolkits published and employed to improve the quality of multi-modal data in the cohort study. In turn, gleaning answers to relevant questions from such a conglomeration of studies is a time-consuming task for cohort researchers. As part of our efforts to tackle this problem, we propose a hierarchical neuroscience knowledge base that consists of projects/organizations, multi-modal databases, and toolkits, so as to facilitate researchers' answer searching process. We first classified studies conducted for the topic "Frontiers in Neuroinformatics" according to the multi-modal data life cycle, and from these studies, information objects as projects/organizations, multi-modal databases, and toolkits have been extracted. Then, we map these information objects into our proposed knowledge base framework. A Python-based query tool has also been developed in tandem for quicker access to the knowledge base, (accessible at https://github.com/Romantic-Pumpkin/PDT_fninf). Finally, based on the constructed knowledge base, we discussed some key research issues and underlying trends in different stages of the multi-modal data life cycle.

Multi sequence average templates for aging and neurodegenerative disease populations

Magnetic resonance image (MRI) processing pipelines use average templates to enable standardization of individual MRIs in a common space. MNI-ICBM152 is currently used as the standard template by most MRI processing tools. However, MNI-ICBM152 represents an average of 152 healthy young adult brains and is vastly different from brains of patients with neurodegenerative diseases. In those populations, extensive atrophy might cause inevitable registration errors when using an average template of young healthy individuals for standardization. Disease-specific templates that represent the anatomical characteristics of the populations can reduce such errors and improve downstream driven estimates. We present multi-sequence average templates for Alzheimer’s Dementia (AD), Fronto-temporal Dementia (FTD), Lewy Body Dementia (LBD), Mild Cognitive Impairment (MCI), cognitively intact and impaired Parkinson’s Disease patients (PD-CIE and PD-CI, respectively), individuals with Subjective Cognitive Impairment (SCI), AD with vascular contribution (V-AD), Vascular Mild Cognitive Impairment (V-MCI), Cognitively Intact Elderly (CIE) individuals, and a human phantom. We also provide separate templates for males and females to allow better representation of the diseases in each sex group.

Measurement(s)	Human Brain
Technology Type(s)	Magnetic resonance imaging
Sample Characteristic - Organism	Homo Sapiens
Sample Characteristic - Location	Canada

MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase ( www.facebase.org , https://doi.org/10.25550/3-HXMC ) and GitHub ( https://github.com/jaydevine/MusMorph ).

A Two-Stage De-Identification Process for Privacy-Preserving Medical Image Analysis

Identification and re-identification are two major security and privacy threats to medical imaging data. De-identification in DICOM medical data is essential to preserve the privacy of patients' Personally Identifiable Information (PII) and requires a systematic approach. However, there is a lack of sufficient detail regarding the de-identification process of DICOM attributes, for example, what needs to be considered before removing a DICOM attribute. In this paper, we first highlight and review the key challenges in the medical image data de-identification process. In this paper, we develop a two-stage de-identification process for CT scan images available in DICOM file format. In the first stage of the de-identification process, the patient's PII-including name, date of birth, etc., are removed at the hospital facility using the export process available in their Picture Archiving and Communication System (PACS). The second stage employs the proposed DICOM de-identification tool for an exhaustive attribute-level investigation to further de-identify and ensure that all PII has been removed. Finally, we provide a roadmap for future considerations to build a semi-automated or automated tool for the DICOM datasets de-identification.

The genetic basis of neurocranial size and shape across varied lab mouse populations

Brain and skull tissues interact through molecular signalling and mechanical forces during head development, leading to a strong correlation between the neurocranium and the external brain surface. Therefore, when brain tissue is unavailable, neurocranial endocasts are often used to approximate brain size and shape. Evolutionary changes in brain morphology may have resulted in secondary changes to neurocranial morphology, but the developmental and genetic processes underlying this relationship are not well understood. Using automated phenotyping methods, we quantified the genetic basis of endocast variation across large genetically varied populations of laboratory mice in two ways: (1) to determine the contributions of various genetic factors to neurocranial form and (2) to help clarify whether a neurocranial variation is based on genetic variation that primarily impacts bone development or on genetic variation that primarily impacts brain development, leading to secondary changes in bone morphology. Our results indicate that endocast size is highly heritable and is primarily determined by additive genetic factors. In addition, a non-additive inbreeding effect led to founder strains with lower neurocranial size, but relatively large brains compared to skull size; suggesting stronger canalization of brain size and/or a general allometric effect. Within an outbred sample of mice, we identified a locus on mouse chromosome 1 that is significantly associated with variation in several positively correlated endocast size measures. Because the protein-coding genes at this locus have been previously associated with brain development and not with bone development, we propose that genetic variation at this locus leads primarily to variation in brain volume that secondarily leads to changes in neurocranial globularity. We identify a strain-specific missense mutation within Akt3 that is a strong causal candidate for this genetic effect. Whilst it is not appropriate to generalize our hypothesis for this single locus to all other loci that also contribute to the complex trait of neurocranial skull morphology, our results further reveal the genetic basis of neurocranial variation and highlight the importance of the mechanical influence of brain growth in determining skull morphology.

Longitudinal characterization of neuroanatomical changes in the Fischer 344 rat brain during normal aging and between sexes

Animal models are widely used to study the pathophysiology of disease and to evaluate the efficacy of novel interventions, crucial steps towards improving disease outcomes in humans. The Fischer 344 (F344) wildtype rat is a common experimental background strain for transgenic models of disease and is one of the most frequently used models in aging research. Despite frequency of use, characterization of agerelated neuroanatomical change has not been performed in the F344 rat. To this end, we present a comprehensive longitudinal examination of morphometric change in 73 brain regions and at a voxel-wise level during normative aging in vivo in a mixed-sexcohort of F344 rats. We identified the greatest vulnerability to aging within the cortex, caudoputamen, hindbrain, and internal capsule, while the influence of sex was strongest in the caudoputamen, hippocampus, nucleus accumbens, and thalamus, many of which are implicated in memory and motor control circuits frequently affected by aging and neurodegenerative disease. These findings provide a baseline for neuroanatomical changes associated with aging in male and female F344 rats, to which data from transgenic models or other background strains can be compared.

Assessing the differential sensitivities of wave-CAIPI ViSTa myelin water fraction and magnetization transfer saturation for efficiently quantifying tissue damage in MS

BACKGROUND

Wave-CAIPI Visualization of Short Transverse relaxation time component (ViSTa) is a recently developed, short-T₁-sensitized MRI method for fast quantification of myelin water fraction (MWF) in the human brain. It represents a promising technique for the evaluation of subtle, early signals of demyelination in the cerebral white matter of multiple sclerosis (MS) patients. Currently however, few studies exist that robustly assess the utility of ViSTa MWF measures of myelin compared to more conventional MRI measures of myelin in the brain of MS patients. Moreover, there are no previous studies evaluating the sensitivity of ViSTa MWF for the non-invasive detection of subtle tissue damage in both normal-appearing white matter (NAWM) and white matter lesions of MS patients. As a result, a central purpose of this study was to systematically evaluate the relationship between myelin sensitivity of T₁-based ViSTa MWF mapping and a more generally recognized metric, Magnetization Transfer Saturation (MT_sat), in healthy control and MS brain white matter.

METHODS

ViSTa MWF and MT_sat values were evaluated in automatically-classified normal appearing white matter (NAWM), white matter (WM) lesion tissue, cortical gray matter, and deep gray matter of 29 MS patients and 10 healthy controls using 3T MRI. MWF and MT _sat were also assessed in a tract-specific manner using the Johns Hopkins University WM atlas. MRI-derived measures of cerebral myelin content were uniquely compared by employing non-normal distribution-specific measures of median, interquartile range and skewness. Separate analyses of variance were applied to test tissue-specific differences in MT_sat and ViSTa MWF distribution metrics. Non-parametric tests were utilized when appropriate. All tests were corrected for multiple comparisons using the False Discovery Rate method at the level, α=0.05.

RESULTS

Differences in whole NAWM MS tissue damage were detected with a higher effect size when using ViSTa MWF (q = 0.0008; ƞ² = 0.34) compared to MT_sat (q = 0.02; ƞ²= 0.24). We also observed that, as a possible measure of WM pathology, ViSTa-derived NAWM MWF voxel distributions of MS subjects were consistently skewed towards lower MWF values, while MT_sat voxel distributions showed reduced skewness values. We further identified tract-specific reductions in mean ViSTa MWF of MS patients compared to controls that were not observed with MT_sat. However, MT_sat (q = 1.4 × 10^-21; ƞ² = 0.88) displayed higher effect sizes when differentiating NAWM and MS lesion tissue. Using regression analysis at the group level, we identified a linear relationship between MT_sat and ViSTa MWF in NAWM (R² = 0.46; p = 7.8 × 10^-4) lesions (R² = 0.30; p = 0.004), and with all tissue types combined (R² = 0.71; p = 8.4 × 10^-45). The linear relationship was also observed in most of the WM tracts we investigated. ViSTa MWF in NAWM of MS patients correlated with both disease duration (p = 0.02; R² = 0.27) and WM lesion volume (p = 0.002; R² = 0.34).

CONCLUSION

Because ViSTa MWF and MT_sat metrics exhibit differential sensitivities to tissue damage in MS white matter, they can be collected in combination to provide an efficient, comprehensive measure of myelin water and macromolecular pool proton signals. These complementary measures may offer a more sensitive, non-invasive biopsy of early precursor signals in NAWM that occur prior to lesion formation. They may also aid in monitoring the efficacy of remyelination therapies.

MNI-FTD templates, unbiased average templates of frontotemporal dementia variants

Standard templates are widely used in human neuroimaging processing pipelines to facilitate group-level analyses and comparisons across subjects/populations. MNI-ICBM152 template is the most commonly used standard template, representing an average of 152 healthy young adult brains. However, in patients with neurodegenerative diseases such as frontotemporal dementia (FTD), high atrophy levels lead to significant differences between individuals' brain shapes and MNI-ICBM152 template. Such differences might inevitably lead to registration errors or subtle biases in downstream analyses and results. Disease-specific templates are therefore desirable to reflect the anatomical characteristics of the populations of interest and reduce potential registration errors. Here, we present MNI-FTD136, MNI-bvFTD70, MNI-svFTD36, and MNI-pnfaFTD30, four unbiased average templates of 136 FTD patients, 70 behavioural variant (bv), 36 semantic variant (sv), and 30 progressive nonfluent aphasia (pnfa) variant FTD patients and a corresponding age-matched template of 133 controls (MNI-CN133), along with probabilistic tissue maps for each template. Public availability of these templates will facilitate analyses of FTD cohorts and enable comparisons between different studies in an appropriate common standardized space.

A fully segmented 3D anatomical atlas of a lizard brain

As the relevance of lizards in evolutionary neuroscience increases, so does the need for more accurate anatomical references. Moreover, the use of magnetic resonance imaging (MRI) in evolutionary neuroscience is becoming more widespread; this represents a fundamental methodological shift that opens new avenues of investigative possibility but also poses new challenges. Here, we aim to facilitate this shift by providing a three-dimensional segmentation atlas of the tawny dragon brain. The tawny dragon (Ctenophorus decresii) is an Australian lizard of increasing importance as a model system in ecology and, as a member of the agamid lizards, in evolution. Based on a consensus average 3D image generated from the MRIs of 13 male tawny dragon heads, we identify and segment 224 structures visible across the entire lizard brain. We describe the relevance of this atlas to the field of evolutionary neuroscience and propose further experiments for which this atlas can provide the foundation. This advance in defining lizard neuroanatomy will facilitate numerous studies in evolutionary neuroscience. The atlas is available for download as a supplementary material to this manuscript and through the Open Science Framework (OSF; https://doi.org/10.17605/OSF.IO/UJENQ ).

The Chromatin Regulator Ankrd11 Controls Palate and Cranial Bone Development

Epigenetic and chromatin regulation of craniofacial development remains poorly understood. Ankyrin Repeat Domain 11 (ANKRD11) is a chromatin regulator that has previously been shown to control neural stem cell fates via modulation of histone acetylation. ANKRD11 gene variants, or microdeletions of the 16q24.3 chromosomal region encompassing the ANKRD11 gene, cause KBG syndrome, a rare autosomal dominant congenital disorder with variable neurodevelopmental and craniofacial involvement. Craniofacial abnormalities include a distinct facial gestalt, delayed bone age, tooth abnormalities, delayed fontanelle closure, and frequently cleft or submucosal palate. Despite this, the dramatic phenotype and precise role of ANKRD11 in embryonic craniofacial development remain unexplored. Quantitative analysis of 3D images of KBG syndromic subjects shows an overall reduction in the size of the middle and lower face. Here, we report that mice with heterozygous deletion of Ankrd11 in neural crest cells (Ankrd11nchet) display a mild midfacial hypoplasia including reduced midfacial width and a persistent open fontanelle, both of which mirror KBG syndrome patient facial phenotypes. Mice with a homozygous Ankrd11 deletion in neural crest cells (Ankrd11ncko) die at birth. They show increased severity of several clinical manifestations described for KBG syndrome, such as cleft palate, retrognathia, midfacial hypoplasia, and reduced calvarial growth. At E14.5, Ankrd11 expression in the craniofacial complex is closely associated with developing bony structures, while expression at birth is markedly decreased. Conditional deletion of Ankrd11 leads to a reduction in ossification of midfacial bones, with several ossification centers failing to expand and/or fuse. Intramembranous bones show features of delayed maturation, with bone remodeling severely curtailed at birth. Palatal shelves remain hypoplastic at all developmental stages, with a local reduction in proliferation at E13.5. Our study identifies Ankrd11 as a critical regulator of intramembranous ossification and palate development and suggests that Ankrd11nchet and Ankrd11ncko mice may serve as pre-clinical models for KBG syndrome in humans.

Wnt Signaling Drives Correlated Changes in Facial Morphology and Brain Shape

Canonical Wnt signaling plays multiple roles critical to normal craniofacial development while its dysregulation is known to be involved in structural birth defects of the face. However, when and how Wnt signaling influences phenotypic variation, including those associated with disease, remains unclear. One potential mechanism is via Wnt signaling’s role in the patterning of an early facial signaling center, the frontonasal ectodermal zone (FEZ), and its subsequent regulation of early facial morphogenesis. For example, Wnt signaling may directly alter the shape and/or magnitude of expression of the sonic hedgehog (SHH) domain in the FEZ. To test this idea, we used a replication-competent avian sarcoma retrovirus (RCAS) encoding Wnt3a to modulate its expression in the facial mesenchyme. We then quantified and compared ontogenetic changes in treated to untreated embryos in the three-dimensional (3D) shape of both the SHH expression domain of the FEZ, and the morphology of the facial primordia and brain using iodine-contrast microcomputed tomography imaging and 3D geometric morphometrics (3DGM). We found that increased Wnt3a expression in early stages of head development produces correlated variation in shape between both structural and signaling levels of analysis. In addition, altered Wnt3a activation disrupted the integration between the forebrain and other neural tube derivatives. These results show that activation of Wnt signaling influences facial shape through its impact on the forebrain and SHH expression in the FEZ, and highlights the close relationship between morphogenesis of the forebrain and midface.

Spinal Cord Morphology in Degenerative Cervical Myelopathy Patients; Assessing Key Morphological Characteristics Using Machine Vision Tools

Despite Degenerative Cervical Myelopathy (DCM) being the most common form of spinal cord injury, effective methods to evaluate patients for its presence and severity are only starting to appear. Evaluation of patient images, while fast, is often unreliable; the pathology of DCM is complex, and clinicians often have difficulty predicting patient prognosis. Automated tools, such as the Spinal Cord Toolbox (SCT), show promise, but remain in the early stages of development. To evaluate the current state of an SCT automated process, we applied it to MR imaging records from 328 DCM patients, using the modified Japanese Orthopedic Associate scale as a measure of DCM severity. We found that the metrics extracted from these automated methods are insufficient to reliably predict disease severity. Such automated processes showed potential, however, by highlighting trends and barriers which future analyses could, with time, overcome. This, paired with findings from other studies with similar processes, suggests that additional non-imaging metrics could be added to achieve diagnostically relevant predictions. Although modeling techniques such as these are still in their infancy, future models of DCM severity could greatly improve automated clinical diagnosis, communications with patients, and patient outcomes.

CIVET-Macaque: An automated pipeline for MRI-based cortical surface generation and cortical thickness in macaques

The MNI CIVET pipeline for automated extraction of cortical surfaces and evaluation of cortical thickness from in-vivo human MRI has been extended for processing macaque brains. Processing is performed based on the NIMH Macaque Template (NMT), as the reference template, with the anatomical parcellation of the surface following the D99 and CHARM atlases. The modifications needed to adapt CIVET to the macaque brain are detailed. Results have been obtained using CIVET-macaque to process the anatomical scans of the 31 macaques used to generate the NMT and another 95 macaques from the PRIME-DE initiative. It is anticipated that the open usage of CIVET-macaque will promote collaborative efforts in data collection and processing, sharing, and automated analyses from which the non-human primate brain imaging field will advance.

[68Ga]Ga-NODAGA-E[(cRGDyK)]2 PET and hyperpolarized [1-13C] pyruvate MRSI (hyperPET) in canine cancer patients: simultaneous imaging of angiogenesis and the Warburg effect

PURPOSE

Cancer has a multitude of phenotypic expressions and identifying these are important for correct diagnosis and treatment selection. Clinical molecular imaging such as positron emission tomography can access several of these hallmarks of cancer non-invasively. Recently, hyperpolarized magnetic resonance spectroscopy with [1-13C] pyruvate has shown great potential to probe metabolic pathways. Here, we investigate simultaneous dual modality clinical molecular imaging of angiogenesis and deregulated energy metabolism in canine cancer patients.

METHODS

Canine cancer patients (n = 11) underwent simultaneous [68Ga]Ga-NODAGA-E[(cRGDyK)]2 (RGD) PET and hyperpolarized [1-13C]pyruvate-MRSI (hyperPET). Standardized uptake values and [1-13C]lactate to total 13C ratio were quantified and compared generally and voxel-wise.

RESULTS

Ten out of 11 patients showed clear tumor uptake of [68Ga]Ga-NODAGA-RGD at both 20 and 60 min after injection, with an average SUVmean of 1.36 ± 0.23 g/mL and 1.13 ± 0.21 g/mL, respectively. A similar pattern was seen for SUVmax values, which were 2.74 ± 0.41 g/mL and 2.37 ± 0.45 g/mL. The [1-13C]lactate generation followed patterns previously reported. We found no obvious pattern or consistent correlation between the two modalities. Voxel-wise tumor values of RGD uptake and lactate generation analysis revealed a tendency for each canine cancer patient to cluster in separated groups.

CONCLUSION

We demonstrated combined imaging of [68Ga]Ga-NODAGA-RGD-PET for angiogenesis and hyperpolarized [1-13C]pyruvate-MRSI for probing energy metabolism. The results suggest that [68Ga]Ga-NODAGA-RGD-PET and [1-13C]pyruvate-MRSI may provide complementary information, indicating that hyperPET imaging of angiogenesis and energy metabolism is able to aid in cancer phenotyping, leading to improved therapy planning.

MR and ultrasound cardiac image dynamic visualization and synchronization over Internet for distributed heart function diagnosis

Dual-modality 4D cardiac data visualization can convey a significant amount of complementary image information from various sources into a single and meaningful display. Even though there are existing publications on combining multiple medical images into a unique representation, there has been no work on rendering a series of cardiac image sequences, acquired from multiple sources, using web browsers and synchronizing the result over the Internet in real time. The ability to display multi-modality beating heart images using Web-based technology is hampered by the lack of efficient algorithms for fusing and visualizing constantly updated multi-source images and streaming the rendering results using internet protocols. To address this practical issue, in this paper we introduce a new Internet-based algorithm and a software platform running on a Node.js server, where a series of registered cardiac images from both magnetic resonance (MR) and ultrasound are employed to display dynamic fused cardiac structures in web browsers. Taking advantage of the bidirectional WebSocket protocol and WebGL-based graphics acceleration, internal cardiac structures are dynamically displayed, and the results of rendering and data exploration are synchronized among all the connected client computers. The presented research and software have the potential to provide clinicians with comprehensive information and intuitive feedback relating to cardiac behavior and anatomy and could impact areas such as distributed diagnosis of cardiac function and collaborative treatment planning for various heart diseases.

Detection of Cerebrovascular Loss in the Normal Aging C57BL/6 Mouse Brain Using in vivo Contrast-Enhanced Magnetic Resonance Angiography

Microvascular rarefaction, or the decrease in vascular density, has been described in the cerebrovasculature of aging humans, rats, and, more recently, mice in the presence and absence of age-dependent diseases. Given the wide use of mice in modeling age-dependent human diseases of the cerebrovasculature, visualization, and quantification of the global murine cerebrovasculature is necessary for establishing the baseline changes that occur with aging. To provide in vivo whole-brain imaging of the cerebrovasculature in aging C57BL/6 mice longitudinally, contrast-enhanced magnetic resonance angiography (CE-MRA) was employed using a house-made gadolinium-bearing micellar blood pool agent. Enhancement in the vascular space permitted quantification of the detectable, or apparent, cerebral blood volume (aCBV), which was analyzed over 2 years of aging and compared to histological analysis of the cerebrovascular density. A significant loss in the aCBV was detected by CE-MRA over the aging period. Histological analysis via vessel-probing immunohistochemistry confirmed a significant loss in the cerebrovascular density over the same 2-year aging period, validating the CE-MRA findings. While these techniques use widely different methods of assessment and spatial resolutions, their comparable findings in detected vascular loss corroborate the growing body of literature describing vascular rarefaction aging. These findings suggest that such age-dependent changes can contribute to cerebrovascular and neurodegenerative diseases, which are modeled using wild-type and transgenic laboratory rodents.

CerebrA, registration and manual label correction of Mindboggle-101 atlas for MNI-ICBM152 template

Accurate anatomical atlases are recognized as important tools in brain-imaging research. They are widely used to estimate disease-specific changes and therefore, are of great relevance in extracting regional information on volumetric variations in clinical cohorts in comparison to healthy populations. The use of high spatial resolution magnetic resonance imaging and the improvement in data preprocessing methods have enabled the study of structural volume changes on a wide range of disorders, particularly in neurodegenerative diseases where different brain morphometry analyses are being broadly used in an effort to improve diagnostic biomarkers. In the present dataset, we introduce the Cerebrum Atlas (CerebrA) along with the MNI-ICBM2009c average template. MNI-ICBM2009c is the most recent version of the MNI-ICBM152 brain average, providing a higher level of anatomical details. Cerebra is based on an accurate non-linear registration of cortical and subcortical labelling from Mindboggle 101 to the symmetric MNI-ICBM2009c atlas, followed by manual editing.

A Registration and Deep Learning Approach to Automated Landmark Detection for Geometric Morphometrics

Geometric morphometrics is the statistical analysis of landmark-based shape variation and its covariation with other variables. Over the past two decades, the gold standard of landmark data acquisition has been manual detection by a single observer. This approach has proven accurate and reliable in small-scale investigations. However, big data initiatives are increasingly common in biology and morphometrics. This requires fast, automated, and standardized data collection. We combine techniques from image registration, geometric morphometrics, and deep learning to automate and optimize anatomical landmark detection. We test our method on high-resolution, micro-computed tomography images of adult mouse skulls. To ensure generalizability, we use a morphologically diverse sample and implement fundamentally different deformable registration algorithms. Compared to landmarks derived from conventional image registration workflows, our optimized landmark data show up to a 39.1% reduction in average coordinate error and a 36.7% reduction in total distribution error. In addition, our landmark optimization produces estimates of the sample mean shape and variance-covariance structure that are statistically indistinguishable from expert manual estimates. For biological imaging datasets and morphometric research questions, our approach can eliminate the time and subjectivity of manual landmark detection whilst retaining the biological integrity of these expert annotations.

Requirements of Health Data Management Systems for Biomedical Care and Research: Scoping Review

BACKGROUND

Over the last century, disruptive incidents in the fields of clinical and biomedical research have yielded a tremendous change in health data management systems. This is due to a number of breakthroughs in the medical field and the need for big data analytics and the Internet of Things (IoT) to be incorporated in a real-time smart health information management system. In addition, the requirements of patient care have evolved over time, allowing for more accurate prognoses and diagnoses. In this paper, we discuss the temporal evolution of health data management systems and capture the requirements that led to the development of a given system over a certain period of time. Consequently, we provide insights into those systems and give suggestions and research directions on how they can be improved for a better health care system.

OBJECTIVE

This study aimed to show that there is a need for a secure and efficient health data management system that will allow physicians and patients to update decentralized medical records and to analyze the medical data for supporting more precise diagnoses, prognoses, and public insights. Limitations of existing health data management systems were analyzed.

METHODS

To study the evolution and requirements of health data management systems over the years, a search was conducted to obtain research articles and information on medical lawsuits, health regulations, and acts. These materials were obtained from the Institute of Electrical and Electronics Engineers, the Association for Computing Machinery, Elsevier, MEDLINE, PubMed, Scopus, and Web of Science databases.

RESULTS

Health data management systems have undergone a disruptive transformation over the years from paper to computer, web, cloud, IoT, big data analytics, and finally to blockchain. The requirements of a health data management system revealed from the evolving definitions of medical records and their management are (1) medical record data, (2) real-time data access, (3) patient participation, (4) data sharing, (5) data security, (6) patient identity privacy, and (7) public insights. This paper reviewed health data management systems based on these 7 requirements across studies conducted over the years. To our knowledge, this is the first analysis of the temporal evolution of health data management systems giving insights into the system requirements for better health care.

CONCLUSIONS

There is a need for a comprehensive real-time health data management system that allows physicians, patients, and external users to input their medical and lifestyle data into the system. The incorporation of big data analytics will aid in better prognosis or diagnosis of the diseases and the prediction of diseases. The prediction results will help in the development of an effective prevention plan.

Impaired perfusion and capillary dysfunction in prodromal Alzheimer's disease

INTRODUCTION

Cardiovascular disease increases the risk of developing Alzheimer's disease (AD), and growing evidence suggests an involvement of cerebrovascular pathology in AD. Capillary dysfunction, a condition in which capillary flow disturbances rather than arterial blood supply limit brain oxygen extraction, could represent an overlooked vascular contributor to neurodegeneration. We examined whether cortical capillary transit-time heterogeneity (CTH), an index of capillary dysfunction, is elevated in amyloid-positive patients with mild cognitive impairment (prodromal AD [pAD]).

METHODS

We performed structural and perfusion weighted MRI in 22 pAD patients and 21 healthy controls.

RESULTS

We found hypoperfusion, reduced blood volume, and elevated CTH in the parietal and frontal cortices of pAD-patients compared to controls, while only the precuneus showed focal cortical atrophy.

DISCUSSION

We propose that microvascular flow disturbances antedate cortical atrophy and may limit local tissue oxygenation in pAD. We speculate that capillary dysfunction contributes to the development of neurodegeneration in AD.

The relationships between neuroinflammation, beta-amyloid and tau deposition in Alzheimer's disease: a longitudinal PET study

BACKGROUND

The aim of this longitudinal study was to assess with positron emission tomography (PET) the relationship between levels of inflammation and the loads of aggregated β-amyloid and tau at baseline and again after 2 years in prodromal Alzheimer's disease.

METHODS

Forty-three subjects with mild cognitive impairment (MCI) had serial 11C-PK11195 PET over 2 years to measure inflammation changes, and 11C-PiB PET to determine β-amyloid fibril load; 22 also had serial 18F-Flortaucipir PET to determine tau tangle load. Cortical surface statistical mapping was used to localise areas showing significant changes in tracer binding over time and to interrogate correlations between tracer binding of the tracers at baseline and after 2 years.

RESULTS

Those MCI subjects with high 11C-PiB uptake at baseline (classified as prodromal Alzheimer's disease) had raised inflammation levels which significantly declined across cortical regions over 2 years although their β-amyloid levels continued to rise. Those MCI cases who had low/normal 11C-PiB uptake at baseline but their levels then rose over 2 years were classified as prodromal AD with low Thal phase 1-2 amyloid deposition at baseline. They showed levels of cortical inflammation which correlated with their rising β-amyloid load. Those MCI cases with baseline low 11C-PiB uptake that remained stable were classified as non-AD, and they showed no correlated inflammation levels. Finally, MCI cases which showed both high 11C-PiB and 18F-Flortaucipir uptake at baseline (MCI due to AD) showed a further rise in their tau tangle load over 2 years with a correlated rise in levels of inflammation.

CONCLUSIONS

Our baseline and 2-year imaging findings are compatible with a biphasic trajectory of inflammation in Alzheimer's disease: MCI cases with low baseline but subsequently rising β-amyloid load show correlated levels of microglial activation which then later decline when the β-amyloid load approaches AD levels. Later, as tau tangles form in β-amyloid positive MCI cases with prodromal AD, the rising tau load is associated with higher levels of inflammation.

An MRI-Derived Neuroanatomical Atlas of the Fischer 344 Rat Brain

This paper reports the development of a high-resolution 3-D MRI atlas of the Fischer 344 adult rat brain. The atlas is a 60 μm isotropic image volume composed of 256 coronal slices with 71 manually delineated structures and substructures. The atlas was developed using Pydpiper image registration pipeline to create an average brain image of 41 four-month-old male and female Fischer 344 rats. Slices in the average brain image were then manually segmented, individually and bilaterally, on the basis of image contrast in conjunction with Paxinos and Watson's (2007) stereotaxic rat brain atlas. Summary statistics (mean and standard deviation of regional volumes) are reported for each brain region across the sample used to generate the atlas, and a statistical comparison of a chosen subset of regional brain volumes between male and female rats is presented. On average, the coefficient of variation of regional brain volumes across all rats in our sample was 4%, with no individual brain region having a coefficient of variation greater than 13%. A full description of methods used, as well as the atlas, the template that the atlas was derived from, and a masking file, can be found on Zenodo at www.zenodo.org/record/3700210. To our knowledge, this is the first MRI atlas created using Fischer 344 rats and will thus provide an appropriate neuroanatomical model for researchers working with this strain.

Changes in the intracranial volume from early adulthood to the sixth decade of life: A longitudinal study

Normal brain-aging occurs at all structural levels. Excessive pathophysiological changes in the brain, beyond the normal one, are implicated in the etiology of brain disorders such as severe forms of the schizophrenia spectrum and dementia. To account for brain-aging in health and disease, it is critical to study the age-dependent trajectories of brain biomarkers at various levels and among different age groups. The intracranial volume (ICV) is a key biological marker, and changes in the ICV during the lifespan can teach us about the biology of development, aging, and gene X environment interactions. However, whether ICV changes with age in adulthood is not resolved. Applying a semi-automatic in-house-built algorithm for ICV extraction on T1w MR brain scans in the Dutch longitudinal cohort (GROUP), we measured ICV changes. Individuals between the ages of 16 and 55 years were scanned up to three consecutive times with 3.32±0.32 years between consecutive scans (N = 482, 359, 302). Using the extracted ICVs, we calculated ICV longitudinal aging-trajectories based on three analysis methods; direct calculation of ICV differences between the first and the last scan, fitting all ICV measurements of individuals to a straight line, and applying a global linear mixed model fitting. We report statistically significant increase in the ICV in adulthood until the fourth decade of life (average change +0.03%/y, or about 0.5 ml/y, at age 20), and decrease in the ICV afterward (-0.09%/y, or about -1.2 ml/y, at age 55). To account for previous cross-sectional reports of ICV changes, we analyzed the same data using a cross-sectional approach. Our cross-sectional analysis detected ICV changes consistent with the previously reported cross-sectional effect. However, the reported amount of cross-sectional changes within this age range was significantly larger than the longitudinal changes. We attribute the cross-sectional results to a generational effect. In conclusion, the human intracranial volume does not stay constant during adulthood but instead shows a small increase during young adulthood and a decrease thereafter from the fourth decade of life. The age-related changes in the longitudinalmeasure are smaller than those reported using cross-sectional approaches and unlikely to affect structural brain imaging studies correcting for intracranial volume considerably. As to the possible mechanisms involved, this awaits further study, although thickening of the meninges and skull bones have been proposed, as well as a smaller amount of brain fluids addition above the overall loss of brain tissue.

Fully Automated Habenula Segmentation Provides Robust and Reliable Volume Estimation Across Large Magnetic Resonance Imaging Datasets, Suggesting Intriguing Developmental Trajectories in Psychiatric Disease

Studies of habenula (Hb) function and structure provided evidence of its involvement in psychiatric disorders, including schizophrenia and bipolar disorder. Previous studies using magnetic resonance imaging (manual/semiautomated segmentation) have reported conflicting results. Aiming to improve Hb segmentation reliability and the study of large datasets, we describe a fully automated protocol that was validated against manual segmentations and applied to 3 datasets (childhood/adolescence and adult bipolar disorder and schizophrenia). It achieved reliable Hb segmentation, providing robust volume estimations across a large age range and varying image acquisition parameters. Applying it to clinically relevant datasets, we found smaller Hb volumes in the adult bipolar disorder dataset and larger volumes in the adult schizophrenia dataset compared with healthy control subjects. There are indications that Hb volume in both groups shows deviating developmental trajectories early in life. This technique sets a precedent for future studies, as it allows for fast and reliable Hb segmentation and will be publicly available.

Neurologic Examination Findings Associated With Small Cerebellar Volumes After Prematurity

To help clinicians understand what to expect from small cerebellar volumes after prematurity, this study aims to characterize the specific impacts of small cerebellar volumes on the infant neurologic examination. A prospective cohort of preterm newborns (<32 weeks' gestational age) had brain magnetic resonance imaging (MRI) studies at term-equivalent age. Cerebellar volumes were compared with neurologic examination findings in follow-up, adjusting for severity of intraventricular hemorrhage, white matter injury, and cerebellar hemorrhage. Deformation-based analyses delineated regional morphometric differences in the cerebellum associated with these findings. Of 119 infants with MRI scans, 109 (92%) had follow-up at 19.0±1.7 months corrected age. Smaller cerebellar volume at term was associated with increased odds of truncal hypotonia, postural instability on standing, and patellar hyperreflexia (P < .03). Small cerebellar volume defined as <19 cm³ by 40 weeks was associated with 7.5-fold increased odds of truncal hypotonia (P < .001), 8.9-fold odds postural instability (P < .001), and 9.7-fold odds of patellar hyperreflexia (P < .001). Voxel-based deformation-based morphometry showed postural instability associated with paravermian regions. Small cerebellar volume is associated with specific abnormalities on neurologic examination by 18 months of age, including truncal tone, reflexes, and postural stability.

MEMRI-based imaging pipeline for guiding preclinical studies in mouse models of sporadic medulloblastoma

PURPOSE

Genetically engineered mouse models of sporadic cancers are critical for studying tumor biology and for preclinical testing of therapeutics. We present an MRI-based pipeline designed to produce high resolution, quantitative information about tumor progression and response to novel therapies in mouse models of medulloblastoma (MB).

METHODS

Sporadic MB was modeled in mice by inducing expression of an activated form of the Smoothened gene (aSmo) in a small number of cerebellar granule cell precursors. aSmo mice were imaged and analyzed at defined time-points using a 3D manganese-enhanced MRI-based pipeline optimized for high-throughput.

RESULTS

A semi-automated segmentation protocol was established that estimates tumor volume in a time-frame compatible with a high-throughput pipeline. Both an empirical, volume-based classifier and a linear discriminant analysis-based classifier were tested to distinguish progressing from nonprogressing lesions at early stages of tumorigenesis. Tumor centroids measured at early stages revealed that there is a very specific location of the probable origin of the aSmo MB tumors. The efficacy of the manganese-enhanced MRI pipeline was demonstrated with a small-scale experimental drug trial designed to reduce the number of tumor associated macrophages and microglia.

CONCLUSION

Our results revealed a high level of heterogeneity between tumors within and between aSmo MB models, indicating that meaningful studies of sporadic tumor progression and response to therapy could not be conducted without an imaging-based pipeline approach.

Hippocampal alterations and functional correlates in adolescents and young adults with congenital heart disease

There is a high prevalence of neurodevelopmental impairments in individuals living with congenital heart disease (CHD) and the neural correlates of these impairments are not yet fully understood. Recent studies have shown that hippocampal volume and shape differences may provide unique biomarkers for neurodevelopmental disorders. The hippocampus is vulnerable to early life injury, especially in populations at risk for hypoxemia or hemodynamic instability such as in neonates with CHD. We compared hippocampal gray and white matter volume and morphometry between youth born with CHD (n = 50) aged 16-24 years and healthy peers (n = 48). We also explored whether hippocampal gray and white matter volume and morphometry are associated with executive function and self-regulation deficits. To do so, participants underwent 3T brain magnetic resonance imaging and completed the self-reported Behavior Rating Inventory of Executive Function-Adult version. We found that youth with CHD had smaller hippocampal volumes (all statistics corrected for false discovery rate; q < 0.05) as compared to controls. We also observed significant smaller surface area bilaterally and inward displacement on the left hippocampus predominantly on the ventral side (q < 0.10) in the CHD group that were not present in the controls. Left CA1 and CA2/3 were negatively associated with working memory (p < .05). Here, we report, for the first-time, hippocampal morphometric alterations in youth born with CHD when compared to healthy peers, as well as, structure-function relationships between hippocampal volumes and executive function. These differences may reflect long lasting alterations in brain development specific to individual with CHD.

APPIAN: Automated Pipeline for PET Image Analysis

APPIAN is an automated pipeline for user-friendly and reproducible analysis of positron emission tomography (PET) images with the aim of automating all processing steps up to the statistical analysis of measures derived from the final output images. The three primary processing steps are coregistration of PET images to T1-weighted magnetic resonance (MR) images, partial-volume correction (PVC), and quantification with tracer kinetic modeling. While there are alternate open-source PET pipelines, none offers all of the features necessary for making automated PET analysis as reliably, flexibly and easily extendible as possible. To this end, a novel method for automated quality control (QC) has been designed to facilitate reliable, reproducible research by helping users verify that each processing stage has been performed as expected. Additionally, a web browser-based GUI has been implemented to allow both the 3D visualization of the output images, as well as plots describing the quantitative results of the analyses performed by the pipeline. APPIAN also uses flexible region of interest (ROI) definition—with both volumetric and, optionally, surface-based ROI—to allow users to analyze data from a wide variety of experimental paradigms, e.g., longitudinal lesion studies, large cross-sectional population studies, multi-factorial experimental designs, etc. Finally, APPIAN is designed to be modular so that users can easily test new algorithms for PVC or quantification or add entirely new analyses to the basic pipeline. We validate the accuracy of APPIAN against the Monte-Carlo simulated SORTEO database and show that, after PVC, APPIAN recovers radiotracer concentrations within 93–100% accuracy.

Does inflammation precede tau aggregation in early Alzheimer's disease? A PET study

OBJECTIVE

Our aim was to assess with positron emission tomography (PET) the temporal and spatial inter-relationships between levels of cortical microglial activation and the aggregated amyloid-β and tau load in mild cognitive impairment (MCI) and early Alzheimer's disease (AD).

METHODS

Six clinically probable AD and 20 MCI subjects had inflammation (¹¹C-(R)-PK11195), amyloid (¹¹C-PiB) and tau (¹⁸F-flortaucipir) PET, magnetic resonance imaging (MRI) and a neuropsychological assessment. Parametric images of tracer binding were interrogated at a voxel level and by region of interest analyses.

RESULTS

55% of MCI and 83% of AD subjects had a high amyloid-β load. We have previously reported that clusters of correlated amyloid and inflammation levels are present in cortex. Here we found no correlation between levels of inflammation (¹¹C-(R)-PK11195 BP_ND) and tau (¹⁸F-flortaucipir SUVR) or MMSE scores in high amyloid-β cases.

INTERPRETATION

While correlated levels of amyloid-β and inflammation can be seen in MCI, we did not detect an association between levels of cortical tau tangles and inflammation in our series of high amyloid-β cases. High levels of inflammation could be seen in amyloid-β positive MCI cases where ¹⁸F-flortaucipir signals were low suggesting microglial activation precedes tau tangle formation. Inflammation levels were higher in high amyloid-β MCI than in early AD cases, compatible with it initially playing a protective role.

Development of a Dedicated Rebinner with Rigid Motion Correction for the mMR PET/MR Scanner, and Validation in a Large Cohort of 11C-PIB Scans

Head motion occurring during brain PET studies leads to image blurring and to bias in measured local quantities. The objective of this work was to implement a correction method for PET data acquired with the mMR synchronous PET/MR scanner. Methods: A list-mode-based motion-correction approach has been designed. The developed rebinner chronologically reads the recorded events from the Siemens list-mode file, applies the estimated geometric transformations, and frames the detected counts into sinograms. The rigid-body motion parameters were estimated from an initial dynamic reconstruction of the PET data. We then optimized the correction for ¹¹C-Pittsburgh compound B (¹¹C-PIB) scans using simulated and actual data with well-controlled motion. Results: An efficient list-mode-based motion correction approach has been implemented, fully optimized, and validated using simulated and actual PET data. The average spatial resolution loss induced by inaccuracies in motion parameter estimates and by the rebinning process was estimated to correspond to a 1-mm increase in full width at half maximum with motion parameters estimated directly from the PET data with a temporal frequency of 20 s. The results show that the rebinner can be safely applied to the ¹¹C-PIB scans, allowing almost complete removal of motion-induced artifacts. The application of the correction method to a large cohort of ¹¹C-PIB scans led to the following observations: first, that more than 21% of the scans were affected by motion greater than 10 mm (39% for subjects with Mini-Mental State Examination scores below 20), and second, that the correction led to quantitative changes in Alzheimer-specific cortical regions of up to 30%. Conclusion: The rebinner allows accurate motion correction at a cost of minimal resolution reduction. Application of the correction to a large cohort of ¹¹C-PIB scans confirmed the necessity of systematically correcting for motion to obtain quantitative results.