Development of a machine learning method to automa4cally quan4fy calcified intracranial atheroma on CT imaging and assess risk of future neurovascular

动脉粥样硬化或慢性病理性狭窄与这些动脉突然闭塞的风险增加以及随后的主要疾病如缺血性中风和心脏病发作有关。动脉粥样硬化形成与血管危险因素有关，（吸烟、糖尿病、高胆固醇、高血压、缺乏体育活动）和不可改变（年龄、种族、男性、家族史）。1然而，动脉粥样硬化和随后的血管狭窄的识别通常需要专门的血管成像，因此通常仅在已知或怀疑患有动脉疾病的患者中获得由于动脉粥样化通常是钙化的，因此它在CT成像上是清楚可识别的，即使该CT不是作为血管造影片采集的。冠状动脉钙评分在临床上以这种方式用于预测未来心脏病发作的风险，并在患者发生轻微冠状动脉事件之前为患者计划治疗策略，即改善其可改变的风险因素。虽然一些证据表明钙化的颅内动脉粥样硬化可能与大脑的主要疾病如认知障碍、痴呆和中风有类似的联系，但缺乏2大规模人群水平的纵向随访证据，因此颅内钙化动脉粥样硬化评分尚未用于临床实践。由于其速度、患者耐受性和可用性，CT是最常用的脑部成像方法。NHS苏格兰每年进行大约120，000次CT脑部扫描，用于治疗急性（创伤，中风）和非急性（认知能力下降，慢性头痛）适应症。苏格兰公共卫生部（PHS）负责监督对安全收集的医疗保健数据的匿名国家数据集的整理和访问，以便在安全的环境中进行研究。3这些丰富的数据集包括来自初级和二级保健、处方和国家统计数据的超过10年的成像数据，并包括使用ICD（国际疾病分类）代码的特定诊断。开发一种自动化人工智能方法，用于对非增强CT脑部扫描的钙化颅内动脉粥样硬化进行评分2。在与临床数据相关的大型国家成像数据集上使用这种自动化方法来描述钙化动脉粥样硬化和未来神经血管疾病之间的关联3。定义可用于临床实践的脑动脉钙化评分用于神经血管疾病预后。Joshua C，Joshua MI.颅内主要动脉粥样硬化引起的中风。循环研究。2017;120：502-5132.陈云春，魏晓娥，陆军，乔若华，沈晓芳，李永华.颅内动脉钙化与脑小血管病影像学表现的相关性。神经学前沿第103章. Gao C，McGilchrist M，Mumtaz S，Hall C，安德森LA，Zurowski J，et al. A national network of safe havens：Scofsh perspective.医学互联网研究杂志2022;24：e31684

Atheroma, or chronic pathological narrowing, of arteries is associated with an increased risk of sudden occlusion of these arteries and subsequent major diseases such as ischaemic stroke and heart attack. Atheroma formation is associated with vascular risk factors that are both modifiable (smoking, diabetes, high cholesterol, high blood pressure, physical inactivity) and non-modifiable (age, race, male sex, family history).1 However, identification of atheroma and subsequent vessel narrowing usually requires dedicated vascular imaging and is therefore often only acquired in patients already known or suspected to have arterial disease (e.g. following mini stroke or chest pain).Since atheroma is often calcified, it is clearly identifiable on CT imaging, even if that CT was not acquired as an angiogram. Coronary artery calcium scoring is used clinically in this way to predict future risk of heart attack and to plan treatment strategies for patients before they have even a minor coronary event, i.e. to improve their modifiable risk factors. While some evidence suggests calcified intracranial atheroma might be similarly linked to major diseases of the brain such as cognitive impairment, dementia and stroke,2 large-scale population level evidence with longitudinal follow-up is lacking, and thus intracranial calcified atheroma scoring is not yet used in clinical practice.Due to its speed, patient tolerability and availability, CT is the commonest method for imaging the brain. NHS Scotland performs approximately 120,000 CT brain scans annually for a host of acute (trauma, stroke) and non-acute (cognitive decline, chronic headache) indications. Public Health Scotland (PHS) oversees the collation of and access to pseudonymised national datasets of routinely-collected healthcare data for research in a secure environment.3 These rich datasets include >10 years of imaging linkable to data from primary and secondary care, prescribing, and national statistics and includes specific diagnoses using ICD (International Classification of Diseases) codes.Aims1. Develop an automated artificial intelligence method for scoring calcified intracranial atheroma on non-enhanced CT brain scans2. Use this automated method on a large national imaging dataset linked to clinical data to describe associations between calcified atheroma and future neurovascular disease3. Define a cranial artery calcification score for neurovascular disease prognosis that can be used in clinical practiceReferences1. Banerjee C, Chimowitz MI. Stroke caused by atherosclerosis of the major intracranial arteries. Circulation Research. 2017;120:502-5132. Chen Y-C, Wei X-E, Lu J, Qiao R-H, Shen X-F, Li Y-H. Correlation between intracranial arterial calcification and imaging of cerebral small vessel disease. Frontiers in Neurology. 2019;103. Gao C, McGilchrist M, Mumtaz S, Hall C, Anderson LA, Zurowski J, et al. A national network of safe havens: Scofsh perspective. J Med Internet Res.2022;24:e31684