Center for Autonomic Medicine in Pediatrics (CAMP), Ann & Robert H. Lurie Children's Hospital of Chicago and Stanley Manne Children's Research Institute , Chicago, Illinois.
Northwestern University Feinberg School of Medicine , Chicago, Illinois.
J Appl Physiol (1985). 2018 Sep 1;125(3):755-762. doi: 10.1152/japplphysiol.01086.2017. Epub 2018 Jun 7.
The thermoregulatory sweat test (TST) can be central to the identification and management of disorders affecting sudomotor function and small sensory and autonomic nerve fibers, but the cumbersome nature of the standard testing protocol has prevented its widespread adoption. A high-resolution, quantitative, clean and simple assay of sweating could significantly improve identification and management of these disorders. Images from 89 clinical TSTs were analyzed retrospectively using two novel techniques. First, using the standard indicator powder, skin surface sweat distributions were determined algorithmically for each patient. Second, a fundamentally novel method using thermal imaging of forced evaporative cooling was evaluated through comparison with the standard technique. Correlation and receiver operating characteristic analyses were used to determine the degree of match between these methods, and the potential limits of thermal imaging were examined through cumulative analysis of all studied patients. Algorithmic encoding of sweating and nonsweating regions produces a more objective analysis for clinical decision-making. Additionally, results from the forced cooling method correspond well with those from indicator powder imaging, with a correlation across spatial regions of -0.78 (confidence interval: -0.84 to -0.71). The method works similarly across body regions, and frame-by-frame analysis suggests the ability to identify sweating regions within ~1 s of imaging. Although algorithmic encoding can enhance the standard sweat testing protocol, thermal imaging with forced evaporative cooling can dramatically improve the TST by making it less time consuming and more patient friendly than the current approach. NEW & NOTEWORTHY The thermoregulatory sweat test (TST) can be central to the identification and management of several common neurological disorders, but the cumbersome nature of the standard testing protocol has prevented its widespread adoption. In this study, images from 89 clinical TSTs were analyzed retrospectively using two novel techniques. Our results suggest that these improved methods could make sweat testing more reliable and acceptable for screening and management of a range of neurological disorders.
体温调节发汗试验(TST)对于识别和管理影响汗腺功能以及小感觉和自主神经纤维的疾病至关重要,但标准测试方案繁琐,阻碍了其广泛应用。一种高分辨率、定量、清洁和简单的发汗检测方法,可以显著改善这些疾病的识别和管理。使用两种新方法对 89 例临床 TST 的图像进行了回顾性分析。首先,使用标准指示剂粉末,为每位患者计算皮肤表面汗分布的算法。其次,通过与标准技术进行比较,评估了一种使用强制蒸发冷却的热成像的全新基本方法。通过相关性和接收者操作特征分析来确定这些方法之间的匹配程度,并通过对所有研究患者的累积分析来检查热成像的潜在局限性。算法编码的出汗和不出汗区域为临床决策提供了更客观的分析。此外,强制冷却方法的结果与指示剂粉末成像的结果非常吻合,空间区域的相关性为-0.78(置信区间:-0.84 至-0.71)。该方法在身体区域之间效果相似,逐帧分析表明,在成像后约 1 秒内就能够识别出汗区域。虽然算法编码可以增强标准发汗测试方案,但与当前方法相比,强制蒸发冷却的热成像可以通过减少测试时间和提高患者舒适度,显著改善 TST。新发现和值得注意的地方:体温调节发汗试验(TST)对于识别和管理几种常见的神经疾病至关重要,但标准测试方案繁琐,阻碍了其广泛应用。在这项研究中,使用两种新方法对 89 例临床 TST 的图像进行了回顾性分析。我们的结果表明,这些改进的方法可以使发汗测试更可靠、更易被接受,从而用于一系列神经疾病的筛查和管理。