Statsenko Yauhen, Habuza Tetiana, Smetanina Darya, Simiyu Gillian Lylian, Meribout Sarah, King Fransina Christina, Gelovani Juri G, Das Karuna M, Gorkom Klaus N-V, Zaręba Kornelia, Almansoori Taleb M, Szólics Miklós, Ismail Fatima, Ljubisavljevic Milos
Radiology Department, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates.
Medical Imaging Platform, ASPIRE Precision Medicine Research Institute Abu Dhabi, Al Ain P.O. Box 15551, United Arab Emirates.
Biomedicines. 2023 Jul 14;11(7):1999. doi: 10.3390/biomedicines11071999.
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.
神经退行性疾病和神经发育障碍的高发病率和患病率证明了从脑成像结果诊断这些疾病的明确标准的必要性。目前尚无易于应用的异常脑发育和衰老的定量标志物。我们旨在发现不同脑结构中非病理性发育和退化的特征,并制定一个精确的各年龄组脑形态测量描述模型。我们将使用四个生物医学数据库来获取关于人类整个生命周期中发生的脑结构变化的经同行评审的原始出版物。选定的出版物将上传到Covidence系统评价软件进行自动重复数据删除和盲法筛选。之后,我们将人工审阅标题、摘要和全文,以识别符合入选标准的论文。相关数据将被提取到一个“结果总结”表中。这将使我们能够计算脑结构体积或厚度的年变化率,并对形态测量数据中的终身动态进行建模。最后,我们将特定脑区的重量/厚度损失调整为总颅内体积。该系统评价将综合关于整个生命周期脑结构变化的知识。