Medical Physics & Biomedical Engineering, University College London, London WC1E 6BT, UK.
Stroke Research Centre, Department of Brain repair and Rehabilitation, University College London Institute of Neurology, London WC1N 3BG, UK.
Sci Data. 2018 Jul 3;5:180112. doi: 10.1038/sdata.2018.112.
Electrical Impedance Tomography (EIT) is a non-invasive imaging technique, which has the potential to expedite the differentiation of ischaemic or haemorrhagic stroke, decreasing the time to treatment. Whilst demonstrated in simulation, there are currently no suitable imaging or classification methods which can be successfully applied to human stroke data. Development of these complex methods is hindered by a lack of quality Multi-Frequency EIT (MFEIT) data. To address this, MFEIT data were collected from 23 stroke patients, and 10 healthy volunteers, as part of a clinical trial in collaboration with the Hyper Acute Stroke Unit (HASU) at University College London Hospital (UCLH). Data were collected at 17 frequencies between 5 Hz and 2 kHz, with 31 current injections, yielding 930 measurements at each frequency. This dataset is the most comprehensive of its kind and enables combined analysis of MFEIT, Electroencephalography (EEG) and Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) data in stroke patients, which can form the basis of future research into stroke classification.
电阻抗断层成像（EIT）是一种非侵入性成像技术，有可能加速缺血性或出血性中风的鉴别，从而缩短治疗时间。虽然在模拟中得到了证明，但目前还没有合适的成像或分类方法可以成功应用于人类中风数据。这些复杂方法的发展受到缺乏高质量多频电阻抗断层成像（MFEIT）数据的阻碍。为了解决这个问题，MFEIT 数据是从 23 名中风患者和 10 名健康志愿者中收集的，作为与伦敦大学学院医院（UCLH）的超急性中风单元（HASU）合作进行的临床试验的一部分。数据在 5 Hz 到 2 kHz 之间的 17 个频率下采集，每个频率有 31 个电流注入，每个频率产生 930 个测量值。这个数据集是同类中最全面的，可以对中风患者的 MFEIT、脑电图（EEG）和计算机断层扫描（CT）或磁共振成像（MRI）数据进行联合分析，这可以为未来的中风分类研究奠定基础。
