Department of Surgery, Hennepin County Medical Center, Minneapolis, Minnesota.
Department of Neurosurgery, University of Minnesota, Minneapolis, Minnesota.
Clin J Sport Med. 2020 Sep;30(5):433-443. doi: 10.1097/JSM.0000000000000639.
Concussion is the most common type of brain injury in both pediatric and adult populations and can potentially result in persistent postconcussion symptoms. Objective assessment of physiologic "mild" traumatic brain injury in concussion patients remains challenging. This study evaluates an automated eye-tracking algorithm as a biomarker for concussion as defined by its symptoms and the clinical signs of convergence insufficiency and accommodation dysfunction in a pediatric population.
Cross-sectional case-control study.
Primary care.
Concussed children (N = 56; mean age = 13 years), evaluated at a mean of 22-week post-injury, compared with 83 uninjured controls.
Metrics comparing velocity and conjugacy of eye movements over time were obtained and were compared with the correlation between Acute Concussion Evaluation (ACE) scores, convergence, and accommodation dysfunction.
Subjects' eye movements recorded with an automated eye tracker while they watched a 220-second cartoon film clip played continuously while moving within an aperture.
Twelve eye-tracking metrics were significantly different between concussed and nonconcussed children. A model to classify concussion as diagnosed by its symptoms assessed using the ACE achieved an area under the curve (AUC) = 0.854 (71.9% sensitivity, 84.4% specificity, a cross-validated AUC = 0.789). An eye-tracking model built to identify near point of convergence (NPC) disability achieved 95.8% specificity and 57.1% sensitivity for an AUC = 0.810. Reduced binocular amplitude of accommodation had a Spearman correlation of 0.752(P value <0.001) with NPC.
Eye tracking correlated with concussion symptoms and detected convergence and accommodative abnormalities associated with concussion in the pediatric population. It demonstrates utility as a rapid, objective, noninvasive aid in the diagnosis of concussion.
脑震荡是小儿和成人中最常见的脑损伤类型，可能导致持续性脑震荡后症状。对脑震荡患者的生理性“轻度”创伤性脑损伤进行客观评估仍然具有挑战性。本研究评估了一种自动眼动追踪算法，作为一种生物标志物，用于定义小儿人群中的脑震荡，其定义为症状以及会聚不足和调节功能障碍的临床体征。
横断面病例对照研究。
初级保健。
脑震荡患儿（N=56；平均年龄 13 岁），在受伤后平均 22 周进行评估，与 83 名未受伤的对照组进行比较。
随着时间的推移，比较比较眼球运动的速度和共轭性的度量，并将其与急性脑震荡评估（ACE）评分、会聚和调节功能障碍之间的相关性进行比较。
受试者在观看连续播放 220 秒卡通电影片段时，使用自动眼动追踪器记录眼球运动，同时在孔径内移动。
在脑震荡和非脑震荡儿童之间，有 12 项眼动追踪指标存在显著差异。一种使用 ACE 评估诊断为脑震荡症状的模型，其曲线下面积（AUC）为 0.854（71.9%敏感性，84.4%特异性，交叉验证 AUC=0.789）。一种用于识别近点会聚（NPC）障碍的眼动追踪模型，特异性为 95.8%，敏感性为 57.1%，AUC 为 0.810。双眼调节幅度的减少与 NPC 的 Spearman 相关系数为 0.752（P 值<0.001）。
眼动追踪与脑震荡症状相关，并在小儿人群中检测到与脑震荡相关的会聚和调节异常。它证明了作为一种快速、客观、非侵入性的脑震荡诊断辅助工具的效用。
