Intracranial pressure (ICP) is an important parameter to monitor in several neuropathologies. However, because current clinically accepted methods are invasive, its monitoring is limited to patients in critical conditions. On the other hand, there are other less critical conditions for which ICP monitoring could still be useful; therefore, there is a need to develop non-invasive methods. We propose a new method to estimate ICP based on the analysis of the non-invasive measurement of pulsatile, microvascular cerebral blood flow with diffuse correlation spectroscopy. This is achieved by training a recurrent neural network using only the cerebral blood flow as the input. The method is validated using a 50% split sample method using the data from a proof-of-concept study. The study involved a population of infants (n = 6) with external hydrocephalus (initially diagnosed as benign enlargement of subarachnoid spaces) as well as a population of adults (n = 6) with traumatic brain injury. The algorithm was applied to each cohort individually to obtain a model and an ICP estimate. In both diverse cohorts, the non-invasive estimation of ICP was achieved with an accuracy of <4 mm Hg and a negligible small bias. Further, we have achieved a good correlation (Pearson's correlation coefficient >0.9) and good concordance (Lin's concordance correlation coefficient >0.9) in comparison with standard clinical, invasive ICP monitoring. This preliminary work paves the way for further investigations of this tool for the non-invasive, bedside assessment of ICP.

中文翻译：

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通过漫射光学无创估计颅内压：概念验证研究。

颅内压 (ICP) 是监测多种神经病理学的重要参数。然而，由于目前临床上接受的方法是侵入性的，其监测仅限于处于危急状态的患者。另一方面，还有其他一些不太重要的情况，ICP 监测仍然有用；因此，需要开发非侵入性方法。我们提出了一种估计 ICP 的新方法，该方法基于使用扩散相关光谱法对脉动微血管脑血流的非侵入性测量进行分析。这是通过仅使用脑血流作为输入训练循环神经网络来实现的。该方法使用 50% 拆分样本方法使用概念验证研究的数据进行验证。该研究涉及婴儿群体（n = 6) 患有外部脑积水（最初诊断为蛛网膜下腔良性扩大）以及 患有创伤性脑损伤的成年人群 ( n = 6)。该算法单独应用于每个队列以获得模型和 ICP 估计值。在两个不同的队列中，ICP 的非侵入性估计均以 <4 mm Hg 的准确度和可忽略的小偏差实现。此外，与标准临床侵入性 ICP 监测相比，我们实现了良好的相关性（Pearson 相关系数 >0.9）和良好一致性（Lin 相关性相关系数 >0.9）。这项初步工作为进一步研究该工具用于 ICP 的非侵入性床边评估铺平了道路。