Unraveling Lifelong Brain Morphometric Dynamics: A Protocol for Systematic Review and Meta-Analysis in Healthy Neurodevelopment and Ageing

A high incidence and prevalence of neurodegenerative diseases and neurodevelopmental disorders justify the necessity of well-defined criteria for diagnosing these pathologies from brain imaging findings. No easy-to-apply quantitative markers of abnormal brain development and ageing are available. We aim to find the characteristic features of non-pathological development and degeneration in distinct brain structures and to work out a precise descriptive model of brain morphometry in age groups. We will use four biomedical databases to acquire original peer-reviewed publications on brain structural changes occurring throughout the human life-span. Selected publications will be uploaded to Covidence systematic review software for automatic deduplication and blinded screening. Afterwards, we will manually review the titles, abstracts, and full texts to identify the papers matching eligibility criteria. The relevant data will be extracted to a ‘Summary of findings’ table. This will allow us to calculate the annual rate of change in the volume or thickness of brain structures and to model the lifelong dynamics in the morphometry data. Finally, we will adjust the loss of weight/thickness in specific brain areas to the total intracranial volume. The systematic review will synthesise knowledge on structural brain change across the life-span.

[1]  S. DeKosky,et al.  Mediation of Reduced Hippocampal Volume by Cerebral Amyloid Angiopathy in Pathologically Confirmed Patients with Alzheimer's Disease. , 2023, Journal of Alzheimer's disease : JAD.

[2]  M. Ljubisavljevic,et al.  Patterns of structure-function association in normal aging and in Alzheimer's disease: Screening for mild cognitive impairment and dementia with ML regression and classification models , 2023, Frontiers in Aging Neuroscience.

[3]  R. Perneczky,et al.  Anti-amyloid antibody therapies in Alzheimer's disease. , 2023, Brain : a journal of neurology.

[4]  O. Witte,et al.  Cortical and subcortical grey matter atrophy in Amyotrophic Lateral Sclerosis correlates with measures of disease accumulation independent of disease aggressiveness , 2022, NeuroImage: Clinical.

[5]  M. L. Cordeiro,et al.  Autism Spectrum Disorder Diagnoses: A Comparison of Countries with Different Income Levels , 2022, Clinical epidemiology.

[6]  S. Brenner,et al.  Newborn screening for neurodevelopmental diseases: Are we there yet? , 2022, American journal of medical genetics. Part C, Seminars in medical genetics.

[7]  C. Lockwood,et al.  JBI Series Paper 2: Tailored evidence synthesis approaches are required to answer diverse questions: a pragmatic evidence synthesis toolkit from JBI. , 2022, Journal of clinical epidemiology.

[8]  M. Ljubisavljevic,et al.  Brain Morphometry and Cognitive Performance in Normal Brain Aging: Age- and Sex-Related Structural and Functional Changes , 2022, Frontiers in Aging Neuroscience.

[9]  M. Ljubisavljevic,et al.  Proportional Changes in Cognitive Subdomains During Normal Brain Aging , 2021, Frontiers in Aging Neuroscience.

[10]  Nazar Zaki,et al.  MRI and cognitive tests-based screening tool for dementia , 2021, Journal of the Neurological Sciences.

[11]  M. Szólics,et al.  Ai models of age-associated changes in CNS composition identified by MRI , 2021, Journal of the Neurological Sciences.

[12]  M. Szólics,et al.  Predicting cognitive age for screening for neurodegeneration , 2021, Journal of the Neurological Sciences.

[13]  T. Habuza Models of brain cognitive and morphological changes across the life: machine learning-based approach , 2021 .

[14]  Phillip G. D. Ward,et al.  Factors associated with brain ageing - a systematic review , 2021, BMC Neurology.

[15]  G. Baylis,et al.  Predicting Age From Behavioral Test Performance for Screening Early Onset of Cognitive Decline , 2021, Frontiers in Aging Neuroscience.

[16]  Dan J Stein,et al.  Brain charts for the human lifespan , 2021, Nature.

[17]  S. Minoshima,et al.  Brain [F-18]FDG PET for Clinical Dementia Workup: Differential Diagnosis of Alzheimer's Disease and Other Types of Dementing Disorders. , 2021, Seminars in nuclear medicine.

[18]  Nazar Zaki,et al.  Applying the Inverse Efficiency Score to Visual–Motor Task for Studying Speed-Accuracy Performance While Aging , 2020, Frontiers in Aging Neuroscience.

[19]  Natalie L. Colich,et al.  Biological aging in childhood and adolescence following experiences of threat and deprivation: A systematic review and meta-analysis. , 2020, Psychological bulletin.

[20]  F. Panza,et al.  Anti-amyloid-β protein agents for the treatment of Alzheimer’s disease: an update on emerging drugs , 2020, Expert opinion on emerging drugs.

[21]  Femitha Pournami,et al.  Disability Prediction by Early Hammersmith Neonatal Neurological Examination: A Diagnostic Study , 2020, Journal of child neurology.

[22]  M. Levine,et al.  A roadmap to build a phenotypic metric of ageing: insights from the Baltimore Longitudinal Study of Aging , 2020, Journal of internal medicine.

[23]  J. Polanin,et al.  Methodological Guidance Paper: High-Quality Meta-Analysis in a Systematic Review , 2019, Review of Educational Research.

[24]  S. Hasselbalch,et al.  Ageing as a risk factor for neurodegenerative disease , 2019, Nature Reviews Neurology.

[25]  O. Wolkowitz,et al.  Accelerated aging in serious mental disorders. , 2019, Current opinion in psychiatry.

[26]  A. Cerasa,et al.  Radiomics approach in the neurodegenerative brain , 2019, Aging Clinical and Experimental Research.

[27]  P. Maurya,et al.  Oxidative Stress and Accelerated Aging in Neurodegenerative and Neuropsychiatric Disorder. , 2019, Current pharmaceutical design.

[28]  B. Miller,et al.  Discriminative Accuracy of [18F]flortaucipir Positron Emission Tomography for Alzheimer Disease vs Other Neurodegenerative Disorders , 2018, JAMA.

[29]  T. Luck,et al.  Is dementia incidence declining in high-income countries? A systematic review and meta-analysis , 2018, Clinical epidemiology.

[30]  Melissa J. Krauss,et al.  Trends in Adult Alcohol Use and Binge Drinking in the Early 21st‐Century United States: A Meta‐Analysis of 6 National Survey Series , 2018, Alcoholism, clinical and experimental research.

[31]  M. Mattson,et al.  Hallmarks of Brain Aging: Adaptive and Pathological Modification by Metabolic States. , 2018, Cell metabolism.

[32]  Myria Petrou,et al.  How to Perform a Systematic Review and Meta-analysis of Diagnostic Imaging Studies. , 2018, Academic radiology.

[33]  D. Harvey,et al.  Brain Volume Change and Cognitive Trajectories in Aging , 2018, Neuropsychology.

[34]  John H. Gilmore,et al.  Imaging structural and functional brain development in early childhood , 2018, Nature Reviews Neuroscience.

[35]  J. Piven,et al.  Brain and behavior development in autism from birth through infancy , 2017, Dialogues in clinical neuroscience.

[36]  Sean C. L. Deoni,et al.  Quantifying cortical development in typically developing toddlers and young children, 1–6 years of age , 2017, NeuroImage.

[37]  L. Nyberg,et al.  Longitudinal association between hippocampus atrophy and episodic-memory decline , 2017, Neurobiology of Aging.

[38]  C. Ghosh,et al.  Basics of aging theories and disease related aging-an overview , 2017 .

[39]  P. Bosco,et al.  Brain atrophy in Alzheimer’s Disease and aging , 2016, Ageing Research Reviews.

[40]  B. Copnell,et al.  A Guide to Writing a Qualitative Systematic Review Protocol to Enhance Evidence-Based Practice in Nursing and Health Care. , 2016, Worldviews on evidence-based nursing.

[41]  Juha Koikkalainen,et al.  Differential diagnosis of neurodegenerative diseases using structural MRI data , 2016, NeuroImage: Clinical.

[42]  G. Cioni,et al.  Early intervention in neurodevelopmental disorders: underlying neural mechanisms , 2016, Developmental medicine and child neurology.

[43]  S. McNaughton,et al.  Dietary patterns and successful ageing: a systematic review , 2015, European Journal of Nutrition.

[44]  Michael A. Bruno,et al.  Understanding and Confronting Our Mistakes: The Epidemiology of Error in Radiology and Strategies for Error Reduction. , 2015, Radiographics : a review publication of the Radiological Society of North America, Inc.

[45]  Sarah J. Locke,et al.  Evaluating temporal trends from occupational lead exposure data reported in the published literature using meta-regression. , 2014, The Annals of occupational hygiene.

[46]  M. Miller,et al.  Traumatic stress, oxidative stress and posttraumatic stress disorder: neurodegeneration and the accelerated-aging hypothesis , 2014, Molecular Psychiatry.

[47]  L. Westlye,et al.  Differential Longitudinal Changes in Cortical Thickness, Surface Area and Volume across the Adult Life Span: Regions of Accelerating and Decelerating Change , 2014, The Journal of Neuroscience.

[48]  B. Tang,et al.  Genetics of hereditary neurological disorders in children. , 2014, Translational pediatrics.

[49]  S. Kushwaha,et al.  Differential Diagnosis of Neurodegenerative Dementias Using Metabolic Phenotypes on F-18 FDG PET/CT , 2014, The neuroradiology journal.

[50]  A. Dale,et al.  Critical ages in the life course of the adult brain: nonlinear subcortical aging , 2013, Neurobiology of Aging.

[51]  Sabine C. Mueller,et al.  A blood based 12-miRNA signature of Alzheimer disease patients , 2013, Genome Biology.

[52]  J. Kaye,et al.  Neuropathologic basis of age-associated brain atrophy. , 2013, JAMA neurology.

[53]  Shuyu Li,et al.  Age-related changes in brain structural covariance networks , 2013, Front. Hum. Neurosci..

[54]  George Richardson,et al.  Brain development and aging: Overlapping and unique patterns of change , 2013, NeuroImage.

[55]  C. Jack,et al.  Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers , 2013, The Lancet Neurology.

[56]  L. Nyberg,et al.  Genetic and Lifestyle Predictors of 15‐Year Longitudinal Change in Episodic Memory , 2012, Journal of the American Geriatrics Society.

[57]  Y. Stern Cognitive reserve in ageing and Alzheimer's disease , 2012, The Lancet Neurology.

[58]  Hisao Nishijo,et al.  Developmental Trajectories of Amygdala and Hippocampus from Infancy to Early Adulthood in Healthy Individuals , 2012, PloS one.

[59]  Ronald M. Summers,et al.  Machine learning and radiology , 2012, Medical Image Anal..

[60]  Y. Kawasaki,et al.  A follow-up MRI study of the fusiform gyrus and middle and inferior temporal gyri in schizophrenia spectrum , 2011, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[61]  C. Lebel,et al.  Longitudinal Development of Human Brain Wiring Continues from Childhood into Adulthood , 2011, The Journal of Neuroscience.

[62]  Denise C. Park,et al.  Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.

[63]  Anders M. Dale,et al.  Consistent neuroanatomical age-related volume differences across multiple samples , 2011, Neurobiology of Aging.

[64]  M. Albert,et al.  Introduction to the recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.

[65]  Guangyu Zhang,et al.  Beyond age and gender: Relationships between cortical and subcortical brain volume and cognitive-motor abilities in school-age children , 2011, NeuroImage.

[66]  C. Jack,et al.  Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade , 2010, The Lancet Neurology.

[67]  P. Areán,et al.  The Sensitivity and Specificity of Cognitive Screening Instruments to Detect Cognitive Impairment in Older Adults With Severe Psychiatric Illness , 2010, Journal of geriatric psychiatry and neurology.

[68]  A. Dale,et al.  One-Year Brain Atrophy Evident in Healthy Aging , 2009, The Journal of Neuroscience.

[69]  D. Krainc,et al.  Gene expression changes in blood as a putative biomarker for Huntington's disease , 2009, Movement disorders : official journal of the Movement Disorder Society.

[70]  Daniel P. Kennedy,et al.  Mapping Early Brain Development in Autism , 2007, Neuron.

[71]  K. Marder,et al.  A screening assessment of cognitive impairment in patients with ALS , 2007, Amyotrophic lateral sclerosis : official publication of the World Federation of Neurology Research Group on Motor Neuron Diseases.

[72]  Cheryl L. Dahle,et al.  Regional brain changes in aging healthy adults: general trends, individual differences and modifiers. , 2005, Cerebral cortex.

[73]  A. Dale,et al.  Effects of age on volumes of cortex, white matter and subcortical structures , 2005, Neurobiology of Aging.

[74]  T. Gera,et al.  Effect of iron supplementation on mental and motor development in children: systematic review of randomised controlled trials , 2005, Public Health Nutrition.

[75]  D. Altman,et al.  Measuring inconsistency in meta-analyses , 2003, BMJ : British Medical Journal.

[76]  Nick C Fox,et al.  A longitudinal study of brain volume changes in normal aging using serial registered magnetic resonance imaging. , 2003, Archives of neurology.

[77]  M. Ljubisavljevic,et al.  Reliability of Machine Learning in Eliminating Data Redundancy of Radiomics and Reflecting Pathophysiology in COVID-19 Pneumonia: Impact of CT Reconstruction Kernels on Accuracy , 2022, IEEE Access.

[78]  N. Zaki,et al.  Deviation From Model of Normal Aging in Alzheimer’s Disease: Application of Deep Learning to Structural MRI Data and Cognitive Tests , 2022, IEEE Access.

[79]  Nazar Zaki,et al.  AI applications in robotics, diagnostic image analysis and precision medicine: Current limitations, future trends, guidelines on CAD systems for medicine , 2021 .

[80]  Sebastião Gobbi,et al.  Physical exercise modulates peripheral levels of brain-derived neurotrophic factor (BDNF): a systematic review of experimental studies in the elderly. , 2013, Archives of gerontology and geriatrics.

[81]  Rebecca C. Knickmeyer,et al.  Longitudinal development of cortical and subcortical gray matter from birth to 2 years. , 2012, Cerebral cortex.