Holoprosencephaly

The application of AI in obstetric ultrasound includes three aspects: structure identification, automatic and standardized measurements, and classification diagnosis. Since obstetric ultrasound is time-consuming, the use of AI could also reduce examination time and improve workflow. Study design: this is a multicenter retrospective observational cohort study and subsequent prospective cohort study. The study design will be organized in two different phases. The first phase, the feasibility retrospective study, has the objective to develop and train AI-Algorithm with normal and abnormal images retrospectively acquired during second trimester ultrasound scan from various international fetal medicine centers. The second phase, a prospective clinical validation, has the objective to test the AI-Algorithm in the assessment of basic fetal brain anatomy in a real clinic setting with real patients from each of the participating fetal medicine centers. Setting: Three (3) fetal medicine centers. Participants: singleton pregnant population who underwent ultrasound examination between 19 - 22 weeks of gestation in the participating centers. Primary endpoint: to validate a novel AI-based technology for the automated assessment of the basic anatomy of the fetal brain which could potentially be used to support second trimester screening scan. Secondary endpoints: To improve the performance of the standard second trimester screening of fetal brain anatomy ensuring its reliable sonographic assessment within a shorter time of execution. To detect higher repeatability and reproducibility, allowing to implement the ultrasound screening also in terms of efficiency on a vast scale, optimizing healthcare resources In the first phase of the study, participating fetal medicine centers will search their electronic databases for images of singleton pregnant women who underwent ultrasound imaging at 19+0 - 22+6 weeks of gestation with any fetal brain anomaly. Normal images of the fetal brain at the same gestational age will be provided by the promoting centers - i.e., Fondazione Policlinico A. Gemelli, IRCCS and University of Parma. Clinical, ultrasound, prenatal and postnatal information of each case will be retrieved from patient's medical records and entered an electronic database collection file by the principal investigator from each participating center. The acquired images will be anonymized, saved as DICOM and shared through a dedicated cloud storage system which will be set up by the bioengineering team. Each center will be able to access the web system using a personal ID and password. In the second phase of the study, the algorithm will be prospectively tested and validated in a real clinical setting with real patients from each of the participating fetal medicine centers. Inclusion and exclusion criteria, imaging protocol and data collection will be the same carried out during the retrospective phase.

The application of AI in obstetric ultrasound includes three aspects: structure identification, automatic and standardized measurements, and classification diagnosis. Since obstetric ultrasound is time-consuming, the use of AI could also reduce examination time and improve workflow. Study design: this is a multicenter retrospective observational cohort study and subsequent prospective cohort study. The study design will be organized in two different phases. The first phase, the feasibility retrospective study, has the objective to develop and train AI-Algorithm with normal and abnormal images retrospectively acquired during first trimester ultrasound scan from ten international fetal medicine centers. The second phase, a prospective clinical validation, has the objective to test the AI-Algorithm in the assessment of the fetal posterior fossa anatomy in a real clinic setting with real patients from each of the participating fetal medicine centers. Setting: Three (3) fetal medicine centers. Participants: singleton pregnant population who underwent ultrasound examination between 11 - 14 weeks of gestation in ten fetal medicine centers. Primary endpoint: To validate a novel AI-based technology, which could potentially be used as a screening tool for fetal brain abnormal findings in the first trimester. Secondary endpoints: To improve the performance of the standard first trimester screening of fetal posterior fossa ensuring its reliable sonographic assessment within a shorter time of execution. To detect higher repeatability and reproducibility, allowing to implement the ultrasound screening also in terms of efficiency on a vast scale, optimizing healthcare resources In the first phase of the study, participating fetal medicine centers will search their electronic databases for midsagittal images of singleton pregnant women who underwent ultrasound imaging at 11+0 - 13+6 weeks of gestation with any fetal posterior fossa anomaly, such as open spinal dysraphism, DWM or BPC. Normal images of the fetal posterior fossa at the same gestational age will be provided by the promoting centers - i.e., Fondazione Policlinico A. Gemelli, IRCCS and University of Parma. Clinical, ultrasound, prenatal and postnatal information of each case will be retrieved from patient's medical records and entered an electronic database collection file by the principal investigator from each participating center. The acquired images will be anonymized, saved as DICOM and shared through a dedicated cloud storage system which will be set up by the bioengineering team. Each center will be able to access the web system using a personal ID and password. In the second phase of the study, the algorithm will be prospectively tested and validated in a real clinical setting with real patients from each of the participating fetal medicine centers. Inclusion and exclusion criteria, imaging protocol and data collection will be the same carried out during the retrospective phase.

This Biobank is comprised of: 1) medical, social, obstetrical and ultrasonographic data, 2) human biological samples (maternal plasma, serum and buffy coat, maternal urine, cord blood) and 3) the results derived from these (biochemical or ultrasonographic markers, genetics, risk calculations ...)

Meditation has been linked to improved brain health and lower brain age. Brain age has been successfully estimated from structural MRI and more recently, EEG Sleep data using Brain Age Index (BAI) derived by machine learning algorithms. Patients with significant neurological or psychiatric disease exhibit a mean excess BAI of about 4 years. Higher BAI is a predictor of mortality. Long term meditation has been associated with lower Brain Age in MRI studies. However, the EEG sleep measure of Brain Age has not been reported in meditators. This project aims to quantify the progressive impact of meditation on brain age. If established objectively, meditation-based interventions could offer safe, affordable and accessible solutions to promote younger and healthier brains and will have invaluable health and financial implications. The goal of this project is twofold: 1. In alignment with the recent NCCIH emphasis, we propose this study to combine neuroimaging with other non-neural modalities to delineate the impact of meditation on brain health and overall physiology and to identify objective neural biomarkers to assess meditation-based interventions which could be further used in clinical applications. 2. It is estimated that by 2050, an unprecedented 18% of the world's population will be above 65 years of age. According to the National Institute on Aging (NIA), aging is the most significant risk factor of many chronic conditions including age-related neurodegenerative diseases, which severely impact the quality of life, healthcare and social costs. The total healthcare cost of Alzheimer's disease in 2020 was estimated at $305 billion and expected to rise to $1 trillion soon. NIA's 5 year strategy highlights the crucial need to better understand the aging brain and develop interventions to address age-related neurological conditions. The study intervention is a multi-component 21-minute meditation called Shambhavi Mahamudra Kriya. It is taught at the Inner Engineering program offered by non-profit Isha Foundation as online as well as in-person formats. It incorporates a combination of different breathing patterns and meditative components. The intervention training provides precise, step by step and easy to follow instructions on how to perform this practice. Performed in a seated posture, this is a simple, safe and accessible intervention that requires no previous experience of meditation. The intervention selected for this study was shown to significantly reduce perceived stress, enhance self-reported general well-being, improve positive emotions, mindfulness, sleep, engagement, relationships and may promote enhanced Heart Rate Variability and Sympathovagal balance. The control group will be selected to be age, gender and education level matched with the intervention group and will be asked to continue their daily routine.

The last months of pregnancy are particularly important for the development of the child's brain, and the consequences of premature birth on its development can be substantial. Prematurely born children are at higher risk of various cognitive impairments and exhibits more behavioral disorders than full-term born children. Thus early detection and management of at risk children are essential. There is growing evidence of significant volumetric abnormalities in subcortical structures of premature neonates, which may be associated to negative long-term neurodevelopmental outcomes. Understanding these abnormalities could help elucidate the underlying pathophysiology and enable early determination of at-risk patients, both of which would inform the design of novel treatment strategies. However, to date there is still a lack of sensitive, reliable, and accessible algorithms capable of characterizing the influence of prematurity on the anatomy of neonatal brain subcortical structures. In addition, few studies have looked directly at the long-term neurodevelopmental implications of these neonatal subcortical structures abnormalities. Predicting long-term neurodevelopmental outcomes early on - and preferably at neonatal ages - is likely to have a transformative effect on their outcome. Our preliminary data indicate significant morphological differences in the putamen, ventricles, corpus callosum, and thalamus between preterm and term neonates. Investigators propose to develop biomarkers of prematurity by statistically comparing the morphological and diffusion properties of subcortical structures between preterm and term neonates using brain MRI. These results will further be used in a sparse learning framework to predict long-term neurodevelopmental outcomes of prematurity. Hypotheses: By combining subcortical morphological and diffusion properties, we will be able to: (1) delineate specific correlative relationships between structures regionally and differentially affected by normal maturation and different patterns of white matter injury, and (2) improve the specificity of neuroimaging to predict neurodevelopmental outcomes earlier. Aim 1: Build a new toolbox for neonatal subcortical structures analyses that combine 1) a group lasso-based analysis of significant regions of shape changes, 2) a structural correlation network analysis, 3) a neonatal tractography, and 4) tensor-based analysis on tracts. Aim 2: Ascertain biomarkers of prematurity in neonates with different patterns of abnormalities. Aim 3: Assess the predictive potential of imaging and clinical features on neurodevelopmental outcomes among premature children at 9 and 18 months and 6-8 years of age. Impact: This application will provide the first complete subcortical network analysis in both term and preterm neonates. In the first study of its kind for prematurity, investigators will use sparse and multi-task learning to determine which of the biomarkers of prematurity at birth are the best predictors of long-term outcome. The expected findings could improve the ability to predict these outcomes and enable the design of early treatments - before years of pathological brain development and symptoms occur.

The MOBILE project is part of the dynamic European collaboration of the Human Brain Project (HBP). The overall aim of the project is to characterize brain structure and function in healthy subjects and patients with epilepsy, using a quantitative multimodal approach involving both neuroimaging (MRI, PET) and electrophysiology (EEG/MEG). The project is funded by the European HBP consortium, and the data acquired will ultimately be made available to the scientific community formed by this international collaboration. Several aspects of the project have already been initiated on the basis of extensions to previous authorizations, or as part of care activities. As part of this overall project, the present MOBILE-PET application concerns exclusively the performance of 18F-FDG PET (Positron Emission Tomography) imaging in the 30 healthy adult subjects in the protocol (aged 18 to 65, with inclusion parity for gender). This cerebral examination, performed at rest on a 45-minute 3D volume acquisition, enables quantitative measurement of the metabolic consumption of glucose underlying global synaptic activity, and to determine the associated connectivity. Around 1,500 examinations of this type are carried out each year in our department as part of care for patients with brain pathology, and over 10,000 for patients with cancer. This examination requires intravenous injection of a weakly radioactive tracer corresponding to a radiopharmaceutical which has been approved for marketing for over 20 years. We also carried out and finalized a similar project in 2007 on 60 healthy subjects, using a previous-generation PET camera (NCT00484523). The Nuclear Medicine Department holds clinical research authorizations for imaging in patients and healthy subjects (including early phase and first-in-man, although the present project does not fall into this research categarogy).

Epilepsy is responsible for tremendous long-term healthcare costs. Analysis of inherited epilepsy conditions has allowed for identification of several key genes active in the developing brain. Although many genetic abnormalities of the brain are rare and lethal, rapidly advancing knowledge of the structure of the human genome makes it a realistic goal to identify genes responsible for other epileptic conditions, related brain malformations and disorders of cognition. The purpose of this study is to identify genes responsible for epilepsy and disorders of human cognition (EDHC). The Walsh Laboratory at Boston Children's Hospital is looking for genes involved in brain development. Conditions that we study include brain malformations, such as polymicrogyria, lissencephaly, pachygyria, heterotopias, microcephaly and cerebellar hypoplasia, and inherited disorders of cognition, such as familial intellectual disability and familial autism. People with these conditions also often have epilepsy. The structural brain abnormalities are usually diagnosed by brain MRI or sometimes CT scans. Adults and children with these conditions, and their family members, are invited to participate in our study. By comparing the DNA of individuals or families that carry EDHC to the DNA of people in the general population, it may be possible to learn more about the genetic bases of certain forms of EDHC. Study participants must have a brain malformation or disorder of cognition, such as familial intellectual disability or autism, in order to take part in this research.

Study Description: This is a prospective natural history study of individuals who have MEHMO syndrome or eIF2-pathway related conditions, or who are carriers of EIF2S3-related conditions to generate hypotheses for further understanding of disease pathophysiology, diagnosis, prognosis, management, and treatment. The protocol aims to enroll and follow affected or carrier individuals longitudinally to establish a repository of concurrent evaluations and biomaterials, as well as to enroll unaffected individuals for collection of informative comparable data and samples. Objectives: Primary Objective: Characterize the presentation of MEHMO syndrome and eIF2 pathway related conditions. Secondary Objectives: 1. Identify disease-reflective fluid biomarkers 2. Develop a disease severity rating scale or classification algorithm 3. Assess tolerability and feasibility of study evaluations 4. Establish a repository of participant data and samples for future research Endpoints: Primary Endpoint: Frequency and time-to-event of signs and symptoms. Secondary Endpoints: 1. Mean difference of candidate fluid biomarkers level in affected versus carrier versus unaffected individuals 2. Correlation of rating scale or classification algorithm to age, genotype, or other variables 3. Frequency of completed evaluations and reasons for noncompletion

Autism spectrum disorders (ASD) are a set of neurodevelopmental disorders characterized by social communication/interaction impairments and restricted/repetitive behaviors. ASD associated with germline heterozygous PTEN mutations (PTEN ASD) is a genetically defined sub-group that, may be one of the more prevalent genetic disorders contributing to ASD (0.5-2%). The purpose of this research study is to carefully track the phenotypic and molecular characteristics of PTEN ASD and identify biomarkers for intervention studies. Individuals with PTEN ASD, with macrocephalic ASD without a PTEN mutation (macro-ASD), healthy controls, and individuals with PTEN mutations without ASD (PTEN no-ASD) will be asked to participate in this study if they are 18 months and older. Both males and females will be asked to participate. Additionally, to be eligible for study participation, individuals' primary communicative language must be English. The study involves 3 on site visits over the course of two years. Study visits will vary in length from about 4 hours to 6 hours. Study visits involve a physical exam, medical history questions, neuropsychological assessments, and a blood draw done for laboratory studies. A subset of participants between the ages of 2 and 11 years old will take part in the EEG portion of the study. Individuals who have a clinically indicated MRI will have an option to provide routine clinical scans for analysis.

Primary objective of the study is the evaluation of sleep-disordered breathing (SDB) in two distinct pediatric populations of patients with Chiari Malformation Type 1 (CM-I) and Chiari Malformation Type 2 (CM-II). Secondary objectives: Stratify the presence of SDB into central and obstructive origins in the two study populations. Assess the volume of posterior cranial fossae, airway volume, and area of cranial base foramina in both groups. Determine the relationships between SDB and morphological-quantitative anomalies associated with CM.