Rasdall Marselle A, Cho Chloe, Stahl Amy N, Tovar David A, Lavin Patrick, Kerley Cailey I, Chen Qingxia, Ji Xiangyu, Colyer Marcus H, Groves Lucas, Longmuir Reid, Chomsky Amy, Gallagher Martin J, Anderson Adam, Landman Bennett A, Rex Tonia S
Vanderbilt Eye Institute, Vanderbilt University Medical Center, Nashville, Tennessee.
Vanderbilt Medical Scientist Training Program, Vanderbilt University School of Medicine, Nashville, Tennessee.
JAMA Ophthalmol. 2025 Jan 1;143(1):33-42. doi: 10.1001/jamaophthalmol.2024.5076.
Individuals with mild traumatic brain injury (TBI) often report vision problems despite having normal visual acuity and fundus examinations. Diagnostics are needed for these patients.
To determine if a battery of assessments or machine-learning approaches can aid in diagnosing visual dysfunction in patients with mild TBI.
DESIGN, SETTING, AND PARTICIPANTS: This prospective, observational, case-control study was conducted between May 2018 and November 2021. The study setting was at a level 1 trauma research hospital. Participant eligibility included adult males and females with recorded best-corrected visual acuity and normal fundus examination. Individuals in the case group had a history of mild TBI; controls had no history of TBI. Exclusion criteria included a history of ocular, neurological, or psychiatric disease, moderate-severe TBI, recent TBI, metal implants, age younger than 18 years, and pregnancy. Cases and controls were sex- and age-matched. Data analysis was performed from July 2023 to March 2024.
History of mild TBI in the case group.
The single-session visit included the Neurobehavioral Symptom Inventory and measurements of oculomotor function, optical coherence tomography, contrast sensitivity, visual evoked potentials, visual field testing, and magnetic resonance imaging.
A total of 28 participants (mean [SD] age, 35.0 [12.8] years; 15 male [53.6%]) with mild TBI and 28 controls (mean [SD] age, 35.8 [8.5] years; 19 female [67.9%]) were analyzed. Participants with mild TBI showed reduced prism convergence test breakpoint (-8.38; 95% CI, -14.14 to -2.62; P = .008) and recovery point (-8.44; 95% CI, -13.82 to -3.06; P = .004). Participants with mild TBI also had decreased contrast sensitivity (-0.07; 95% CI, -0.13 to -0.01; P = .04) and increased visual evoked potential binocular summation index (0.32; 95% CI, 0.02-0.63; P = .02). A subset of participants exhibited reduced peripapillary retinal nerve fiber layer thickness, increased optic nerve/sheath size, and brain cortical volumes. Machine learning identified subtle differences across the primary visual pathway, including the optic radiations and occipital lobe regions, independent of visual symptoms.
Results of this case-control study suggest that the visual system was affected in individuals with mild TBI, even in those who did not self-report vision problems. These findings support the utility of a battery of assessments or machine-learning approaches to accurately diagnose this population.
轻度创伤性脑损伤(TBI)患者尽管视力和眼底检查正常,但常报告有视力问题。这些患者需要进行诊断。
确定一系列评估或机器学习方法是否有助于诊断轻度TBI患者的视觉功能障碍。
设计、设置和参与者:这项前瞻性、观察性、病例对照研究于2018年5月至2021年11月进行。研究地点为一级创伤研究医院。参与者资格包括记录了最佳矫正视力且眼底检查正常的成年男性和女性。病例组个体有轻度TBI病史;对照组无TBI病史。排除标准包括眼部、神经或精神疾病史、中度至重度TBI、近期TBI、金属植入物、年龄小于18岁和怀孕。病例组和对照组在性别和年龄上匹配。数据分析于2023年7月至2024年3月进行。
病例组的轻度TBI病史。
单次就诊包括神经行为症状量表以及动眼功能测量、光学相干断层扫描、对比敏感度、视觉诱发电位、视野测试和磁共振成像。
共分析了28名轻度TBI参与者(平均[标准差]年龄,35.0[12.8]岁;15名男性[53.6%])和28名对照组(平均[标准差]年龄,35.8[8.5]岁;19名女性[67.9%])。轻度TBI参与者的棱镜融合测试断点降低(-8.38;95%置信区间,-14.14至-2.62;P = 0.008),恢复点降低(-8.44;95%置信区间,-13.82至-3.06;P = 0.004)。轻度TBI参与者的对比敏感度也降低(-0.07;95%置信区间,-0.13至-0.01;P = 0.04),视觉诱发电位双眼总和指数增加(0.32;95%置信区间,0.02 - 0.63;P = 0.02)。一部分参与者表现出视乳头周围视网膜神经纤维层厚度降低、视神经/鞘大小增加和脑皮质体积增加。机器学习识别出初级视觉通路中的细微差异,包括视辐射和枕叶区域差异,且与视觉症状无关。
这项病例对照研究结果表明,即使是那些未自我报告视力问题的轻度TBI患者,其视觉系统也受到了影响。这些发现支持采用一系列评估或机器学习方法来准确诊断这一人群。