Parker T Maxwell, Farrell Nathan, Otero-Millan Jorge, Kheradmand Amir, McClenney Ayodele, Newman-Toker David E
Division of Neuro-Visual and Vestibular Disorders, Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Optometry and Vision Science, University of California, Berkeley, Berkeley, California, USA.
Digit Biomark. 2020 Dec 30;5(1):1-8. doi: 10.1159/000511287. eCollection 2021 Jan-Apr.
Differentiating benign from dangerous causes of dizziness or vertigo presents a major diagnostic challenge for many clinicians. Bedside presentations of peripheral vestibular disorders and posterior fossa strokes are often indistinguishable other than by a few subtle vestibular eye movements. The most challenging of these to interpret is the head impulse test (HIT) of vestibulo-ocular reflex (VOR) function. There have been major advances in portable video-oculography (VOG) quantification of the video HIT (vHIT), but these specialized devices are not routinely available in most clinical settings. As a first step towards smartphone-based diagnosis of strokes in patients presenting vestibular symptoms, we sought proof of concept that we could use a smartphone application ("app") to accurately record the vHIT.
This was a cross-sectional agreement study comparing a novel index test (smartphone-based vHIT app) to an accepted reference standard test (VOG-based vHIT) for measuring VOR function. We recorded passive (examiner-performed) vHIT sequentially with both methods in a convenience sample of patients visiting an otoneurology clinic. We quantitatively correlated VOR gains (ratio of eye to head movements during the HIT) from each side/ear and experts qualitatively assessed the physiologic traces by the two methods.
We recruited 11 patients; 1 patient's vHIT could not be reliably quantified with either device. The novel and reference test VOR gain measurements for each ear ( = 20) were highly correlated (Pearson's = 0.9, = 0.0000001) and, qualitatively, clinically equivalent.
This preliminary study provides proof of concept that an "eyePhone" app could be used to measure vHIT and eventually developed to diagnose vestibular strokes by smartphone.
对许多临床医生而言,区分头晕或眩晕的良性与危险病因是一项重大的诊断挑战。除了一些细微的前庭眼动外,外周前庭疾病和后颅窝卒中的床边表现通常难以区分。其中最难解释的是前庭眼反射(VOR)功能的摇头试验(HIT)。便携式视频眼震图(VOG)对视频摇头试验(vHIT)的量化取得了重大进展,但这些专业设备在大多数临床环境中并非常规可用。作为基于智能手机诊断前庭症状患者卒中的第一步,我们寻求概念验证,即能否使用智能手机应用程序(“应用”)准确记录vHIT。
这是一项横断面一致性研究,将一种新型指标测试(基于智能手机的vHIT应用)与一种公认的参考标准测试(基于VOG的vHIT)进行比较,以测量VOR功能。我们在一家耳神经科诊所就诊的患者便利样本中,依次用两种方法记录被动(由检查者进行)vHIT。我们对每侧/耳的VOR增益(HIT期间眼动与头动的比率)进行定量相关分析,并由专家对两种方法的生理痕迹进行定性评估。
我们招募了11名患者;1名患者的vHIT用两种设备都无法可靠量化。每只耳朵( = 20)的新型测试和参考测试VOR增益测量值高度相关(Pearson相关系数 = 0.9, = 0.0000001),并且在定性上临床等效。
这项初步研究提供了概念验证,即“眼机”应用可用于测量vHIT,并最终开发用于通过智能手机诊断前庭卒中。