Clements Rebecca G, Zvolanek Kristina M, Reddy Neha A, Hemmerling Kimberly J, Bayrak Roza G, Chang Catie, Bright Molly G
Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Department of Biomedical Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, USA.
bioRxiv. 2025 Mar 15:2024.11.18.624159. doi: 10.1101/2024.11.18.624159.
Cerebrovascular reactivity (CVR), the ability of cerebral blood vessels to dilate or constrict in response to a vasoactive stimulus, is a clinically useful measure of cerebrovascular health. CVR is often measured using a breath-hold task to modulate blood CO levels during an fMRI scan. Measuring end-tidal CO (PCO) with a nasal cannula during the task allows CVR amplitude to be calculated in standard units (vascular response per unit change in CO, or %BOLD/mmHg) and CVR delay to be calculated in seconds. The use of standard units allows for normative CVR ranges to be established and for CVR comparisons to be made across subjects and scan sessions. Although breath holding can be successfully performed by diverse patient populations, obtaining accurate PCO measurements requires additional task compliance; specifically, participants must breathe exclusively through their nose and exhale immediately before and after each breath hold. Meeting these requirements is challenging, even in healthy participants, and this has limited the translational potential of breath-hold fMRI for CVR mapping. Previous work has focused on using alternative regressors such as respiration volume per time (RVT), derived from respiration-belt measurements, to map CVR. Because measuring RVT does not require additional task compliance from participants, it is a more feasible measure than PCO. However, using RVT does not produce CVR amplitude in standard units. In this work, we explored how to achieve CVR amplitude maps, in standard units, and CVR delay maps, when breath-hold task PCO data quality is low. First, we evaluated whether RVT could be scaled to units of mmHg using a subset of PCO data of sufficiently high quality. Second, we explored whether a PCO timeseries predicted from RVT using deep learning allows for more accurate CVR measurements. Using a dense-mapping breath-hold fMRI dataset, we showed that both rescaled RVT and rescaled, predicted PCO can be used to produce maps of CVR amplitude in standard units and CVR delay with strong absolute agreement to ground-truth maps. The rescaled, predicted PCO regressor resulted in superior accuracy for both CVR amplitude and delay. In an individual with regions of increased CVR delay due to Moyamoya disease, the predicted PCO regressor also provided greater sensitivity to pathology than RVT. Ultimately, this work will increase the clinical applicability of CVR in populations exhibiting decreased task compliance.
脑血管反应性（CVR）是指脑血管对血管活性刺激做出扩张或收缩反应的能力，是衡量脑血管健康状况的一项具有临床应用价值的指标。CVR通常在功能磁共振成像（fMRI）扫描期间通过屏气任务来调节血液中二氧化碳（CO）水平进行测量。在任务过程中使用鼻导管测量呼气末二氧化碳分压（PCO₂），可以计算出CVR幅度的标准单位（每单位CO变化的血管反应，或%BOLD/mmHg）以及以秒为单位计算CVR延迟。使用标准单位能够建立正常的CVR范围，并能在不同受试者和扫描时段之间进行CVR比较。尽管不同患者群体都能成功完成屏气，但要获得准确的PCO₂测量值还需要额外的任务依从性；具体而言，参与者必须仅通过鼻子呼吸，并且在每次屏气前后立即呼气。即使对于健康参与者来说，满足这些要求也具有挑战性，这限制了屏气fMRI用于CVR映射的转化潜力。先前的工作主要集中在使用替代回归变量，例如从呼吸带测量得出的每分钟呼吸量（RVT）来映射CVR。由于测量RVT不需要参与者额外的任务依从性，因此它是比PCO₂更可行的测量方法。然而，使用RVT并不能得出标准单位的CVR幅度。在这项研究中，我们探索了在屏气任务的PCO₂数据质量较低时，如何获得标准单位的CVR幅度图和CVR延迟图。首先，我们评估了是否可以使用质量足够高的PCO₂数据子集将RVT缩放到mmHg单位。其次，我们探索了使用深度学习从RVT预测的PCO₂时间序列是否能实现更准确的CVR测量。通过一个密集映射的屏气fMRI数据集，我们表明重新缩放后的RVT和重新缩放后的预测PCO₂都可用于生成标准单位的CVR幅度图和CVR延迟图，并且与真实地图具有高度的绝对一致性。重新缩放后的预测PCO₂回归变量在CVR幅度和延迟方面都具有更高的准确性。在一名因烟雾病导致CVR延迟增加区域的个体中，预测的PCO₂回归变量对病变的敏感性也高于RVT。最终，这项研究将提高CVR在任务依从性降低人群中的临床适用性。
