Visual Structure and Function in Collision Sport Athletes

Vision-based measures have been shown to be useful markers in multiple sclerosis (MS), Alzheimer and Parkinson disease. Therefore, these testing paradigms may have applications to populations explaining repetitive head trauma that has been associated with long-term neurodegenerative sequelae. We investigated retinal structure and visual function in professional collision sport athletes compared to age- and race-matched control participants. In this cross-sectional study, participants underwent spectral-domain optical coherence tomography (OCT) measurements of peripapillary retinal nerve fiber layer (RNFL) and macular ganglion cell complex (GCC = ganglion cell + inner plexiform layers) thickness. High-contrast visual acuity (100% level), low-contrast letter acuity (LCLA) (1.25% and 2.5% levels), and King-Devick Test of rapid number naming performance were administered. Vision-specific quality of life (QOL) measures were assessed. Among 46 collision sport athletes (boxing, n = 14; football, n = 29; ice hockey, n = 3) and 104 control participants, average RNFL thickness was a significant predictor of athlete vs control status with athletes demonstrating 4.8-μm of thinning compared to controls (P = 0.01, generalized estimating equation [GEE] models accounting for age and within-subject, intereye correlations). Athlete vs control status was not a predictor of RNFL thickness for the subgroup of football players in this cohort (P = 0.60). Binocular (P = 0.001) and monocular (P = 0.02) LCLA at 2.5% contrast and vision-specific QOL (P = 0.04) were significant predictors of athlete vs control status (GEE models accounting for age and within-subject, intereye correlations). Rapid number naming performance times were not significantly different between the control and athlete groups. This study showed that retinal axonal and neuronal loss is present among collision sport athletes, with most notable differences seen in boxers. These findings are accompanied by reductions in visual function and QOL, similar to patterns observed in multiple sclerosis, Alzheimer and Parkinson diseases. Vision-based changes associated with head trauma exposure that have the potential to be detected in vivo represent a unique opportunity for further study to determine if these changes in collision sport athletes are predictive of future neurodegeneration.

Original Contribution Visual Structure and Function in Collision Sport Athletes Danielle Leong, OD, PhD, Christina Morettin, OD, Leonard V. Messner, OD, Robert J. Steinmetz, OD, Yi Pang, MD, OD, PhD, Steven L. Galetta, MD, Laura J. Balcer, MD, MSCE Background: Vision-based measures have been shown to be useful markers in multiple sclerosis (MS), Alzheimer and Parkinson disease. Therefore, these testing paradigms may have applications to populations explaining repetitive head trauma that has been associated with long-term neurodegenerative sequelae. We investigated retinal structure and visual function in professional collision sport athletes compared to age- and race-matched control participants. Methods: In this cross-sectional study, participants underwent spectral-domain optical coherence tomography (OCT) measurements of peripapillary retinal nerve fiber layer (RNFL) and macular ganglion cell complex (GCC = ganglion cell + inner plexiform layers) thickness. High-contrast visual acuity (100% level), low-contrast letter acuity (LCLA) (1.25% and 2.5% levels), and King-Devick Test of rapid number naming performance were administered. Vision-specific quality of life (QOL) measures were assessed. Results: Among 46 collision sport athletes (boxing, n = 14; football, n = 29; ice hockey, n = 3) and 104 control participants, average RNFL thickness was a significant predictor of athlete vs control status with athletes demonstrating 4.8-mm of thinning compared to controls (P = 0.01, generalized estimating equation [GEE] models accounting for age and within-subject, intereye correlations). Athlete vs control status was not a predictor of RNFL thickness for the subgroup of football players in this cohort (P = 0.60). Binocular (P = 0.001) and monocular (P = 0.02) LCLA at 2.5% contrast and vision-specific QOL (P = 0.04) were significant predictors of athlete vs control status (GEE models accounting for age and within-subject, intereye correlations). Rapid number naming performance times were not significantly different between the control and athlete groups. Illinois Eye Institute (DL, CM, LVM, RJS, YP), Illinois College of Optometry, Chicago, Illinois; and Departments of Neurology, Ophthalmology, Population Health (SLG, LJB), New York University, New York, New York. This study was funded with a research grant from the Illinois Society for the Prevention of Blindness. Dr. D. Leong is employed by King-Devick technologies, Inc as a director of research. The remaining authors report no conflict of interests. Address correspondence to Danielle Leong, OD, PhD, Illinois Eye Institute, Illinois College of Optometry, 3241 South Michigan Avenue, Chicago, IL 60622; E-mail: [e-mail] Leong et al: J Neuro-Ophthalmol 2018; 38: 285-291 Conclusions: This study showed that retinal axonal and neuronal loss is present among collision sport athletes, with most notable differences seen in boxers. These findings are accompanied by reductions in visual function and QOL, similar to patterns observed in multiple sclerosis, Alzheimer and Parkinson diseases. Vision-based changes associated with head trauma exposure that have the potential to be detected in vivo represent a unique opportunity for further study to determine if these changes in collision sport athletes are predictive of future neurodegeneration. Journal of Neuro-Ophthalmology 2018;38:285-291 doi: 10.1097/WNO.0000000000000572 © 2017 by North American Neuro-Ophthalmology Society S ports-related concussion has received increasing attention due to research suggesting associations between repeated head trauma and the development of neurodegenerative conditions and chronic traumatic encephalopathy (CTE). Visual pathways are affected by neurodegenerative disorders such as Parkinson disease (1-4), Alzheimer disease (5,6), and multiple sclerosis (MS) (7-11). Extensive research in MS patients has demonstrated that optical coherence tomography (OCT) captures evidence of visual pathway axonal and neuronal loss (7-11). In terms of visual function, low-contrast letter acuity (LCLA) is a sensitive measure that is now incorporated into MS clinical trials for examining dysfunction of the anterior and posterior visual pathways (12). Given that vision-based measures are associated with some neurodegenerative conditions, these testing paradigms may have application to traumatic brain injury (TBI) populations. In rodent models of blast-mediated TBI, retinal changes are evident on OCT and postmortem histology (13). Similar changes are seen in investigations of veterans with TBI with abnormal retinal thinning (14). To date, there are limited investigations of afferent vision-based markers of head trauma exposure, particularly for active and retired collision sport athletes. This study 285 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution aimed to characterize the visual pathway and investigate if vision testing has the potential to capture neurologic dysfunction among active and retired professional level collision sport athletes. Identifying in vivo markers may aid in quantification of head trauma and detect long-term structural and functional changes that are critical for future developments of diagnostic, therapeutic, and rehabilitative tools. are scored based on the number of letters correctly identified (maximum score of 70 letters per chart). METHODS Vision-Specific Quality of Life (QOL) Our study included active and retired professional athletes from collision sports recruited from retired associations in Chicago, IL. Age- and race-matched healthy control participants who had not played collegiate or professional level collision sports were recruited from among clinic staff or friends and relatives of participants. Exclusion criteria were age ,18 years, diagnosis by history of ocular pathology other than corrected refractive error, or known neurodegenerative conditions. The following measurements were obtained in a single study visit: spectral-domain OCT, high-contrast visual acuity (HCVA), LCLA, rapid number naming (King-Devick [K-D] Test), and vision-specific quality of life (QOL) questionnaire scores. Demographic data (age, sex, race, highest educational level attained) were recorded. The following sport exposure-specific data also were collected: duration, levels of play, and self-reported numbers of concussions. For boxers, professional records available on public websites provided additional estimates of exposure: numbers of fights, win/loss records, rounds boxed, and knockout percentages. Written informed consent was obtained from each study participant. All study procedures were approved by the Illinois College of Optometry and New York University Institutional Review Boards. Optical Coherence Tomography Scans of the macula and peripapillary retinal nerve fiber layer (RNFL) were obtained using Cirrus spectral-domain OCT. Auto segmentation was used and checked for accuracy. Signal strength $7 was required for data to be used and none were excluded on this basis. Measures of average RNFL, RNFL by quadrant, and ganglion cell complex (ganglion cell + inner plexiform layers, GCC) average thicknesses were recorded. Intereye symmetry for average RNFL and GCC thicknesses was calculated as the absolute value for the difference between the right and left eyes. Letter Acuity Measurements HCVA was measured using retro-illuminated ETDRS charts at 3.2 m (Lighthouse Low Vision Products, Long Island, NY). LCLA at 2.5% and 1.25% was determined using the retro-illuminated low-contrast Sloan letter charts at 2 m (Precision Vision, La Salle, IL) (12). Monocular and binocular best-corrected acuities were obtained. Both chart types have a standardized format with 5 letters per line and 286 King-Devick (K-D) Test The K-D Test is a quick (,2 minute) test that requires saccades and other eye movements such as convergence (15). Participants were instructed to complete 2 trials using standardized instructions; time and errors were recorded. The 25-Item National Eye Institute Visual Functioning Questionnaire (NEI-VFQ-25) and the 10-Item NeuroOphthalmic Supplement to the NEI-VFQ-25 (10-Item Supplement) were administered; subscale and summary scores were determined for each questionnaire following standardized instructions (16,17). Statistical Analysis Generalized estimating equation (GEE) models accounting for age and adjusting for within-participant, intereye correlations were used to examine the capacity for athlete vs control status to predict monocular measurements as continuous variables. Linear regression models, accounting for age, were utilized to predict binocular or participantlevel measures. Type I error a = 0.05 was used for statistical significance. RESULTS Among 46 athletes (92 eyes, Table 1), 3 collision sports were represented: boxing (n = 14, 28 eyes), football (n = 29, 58 eyes), and ice hockey (n = 3, 6 eyes). Ice hockey players were included in main comparisons between controls and athletes; however, they were excluded in exploratory subgroup analysis by sport due to small sample size (n = 3). Athletes reported, on average, a greater number of years of sport participation; this was a significant predictor of control vs athlete status (athletes: 18.8 ± 8.2 years vs controls: 2.3 ± 3.8, P , 0.001, linear regression accounting for age, Table 1). Average RNFL thickness was a significant predictor of athlete vs control status overall, with athletes having, on average, a 4.8 mm thinner RNFL compared to controls (P = 0.01, GEE models accounting for age and withinparticipant, intereye correlations, Fig. 1A). Average RNFL thickness was reduced in boxers, with an average of 10.8 mm of thinning compared to controls (83.5 ± 2.8 mm vs 94.3 ± 0.9 mm, P , 0.001, GEE models accounting for age and within-participant intereye correlations, Table 2). Boxers also had a 6.8· greater odds of a ,fifth percentile result for RNFL thickness on Cirrus OCT age-based normative database (P = 0.005, GEE models accounting for within-participant, intereye correlations). RNFL thickness in all quadrants (temporal P , 0.001, Leong et al: J Neuro-Ophthalmol 2018; 38: 285-291 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution TABLE 1. Demographic and clinical data of athletes and healthy controls Controls vs Athletes Age, yr, mean (SD) Male (%) Race (%) White African-American Collision sport exposure, yr, mean (SD) Concussive episodes, count, mean (SD), median (range) Total fights, count, mean (SD), range Professional fights, count, mean (SD), range Wins, count, mean (SD) Losses, count, mean (SD) Rounds boxed, round, mean (SD), range KO percent, %, mean (SD) Football vs Boxing Athletes Controls (n = 104, 208 Eyes) Athletes (n = 46, 92 Eyes) Football Athletes (n = 29, 58 Eyes) Boxing Athletes (n = 14, 28 Eyes) 43.9 (1.3) 61.5 46.1 (12.2) 97.8 47.7 (12.8) 100 43.9 (11.4) 92.9 66.4 28.9 2.3 (3.8) 63.0 37.0 18.8 (8.2)*,† 58.6 41.4 16.1 (5.0) 64.3 35.7 21.6 (10.7) 0.1 (0.2), 0 (0-1) 8.5 (7.1), 7 (0-20) 10.5 (7.0), 10 (1-20) 3.1 (4.0), 1 (1-10) - - - 60.4 (49.8), (5-175) - - - 49.8 (35.0), (5-123) - - - - - - - - - 42.9 (44.9) 6.5 (4.9) 241.8 (246.5), (10-882) - - - 44.4 (21.6) *P , 0.001. † Comparison to control using linear regression accounting for age. KO, knockout; SD, standard deviation. nasal P = 0.002, inferior P = 0.001, superior P = 0.02) was also significantly reduced in boxers compared to controls (Table 2). Athlete vs control status was not a predictor of RNFL thickness for our subgroup of professional football players (P = 0.60). Average GCC thickness was not a significant predictor of athlete vs control status overall (P = 0.11, Fig. 1B). However, average GCC thickness was reduced in boxers, with boxers averaging a 5.0 mm degree of thinning compared to controls (76.7 ± 2.1 mm vs 81.6 ± 0.5 mm, P = 0.02, GEE models accounting for within-participant, intereye correlations, Table 2). Boxers also had a 7.5· greater odds of having a ,fifth percentile on Cirrus OCT agebased normative database (P = 0.01, GEE models accounting for within-participant intereye correlations). Average GCC thickness in football players was not significantly different from controls. Boxers had significantly less intereye asymmetry in average RNFL than controls (21.9 mm, P = 0.002, GEE models accounting for age and withinparticipant, intereye correlations); however, the athlete and control groups did not differ significantly in asymmetry of average GCC. Binocular HCVA did not differ between controls and athletes; however, subgroup analysis by sport demonstrated that binocular HCVA was reduced in boxers compared to controls (55.8 ± 1.5 letters [Snellen equivalent 20/25] vs 60.4 ± 0.4 letters [Snellen equivalent 20/30], P = 0.003, linear regression accounting for age, Table 3). Monocular Leong et al: J Neuro-Ophthalmol 2018; 38: 285-291 HCVA was similarly reduced in boxers compared to controls (52.4 ± 1.3 letters [Snellen equivalent 20/32] vs 56.4 ± 0.5 letters [Snellen equivalent 20/25], P = 0.003, linear regression accounting for age, Table 3). Binocular LCLA at 2.5% was a significant predictor of athlete vs control status (P = 0.001, GEE models accounting for age and within-participant, intereye correlations, Fig. 1C). Specifically, athletes had, on average, 3.6 letters' (nearly one line) reduction of acuity. Upon athlete-type subgroup analysis, binocular LCLA at 2.5% was reduced in boxers compared to controls (31.7 ± 2.1 letters vs 38.6 ± 0.5 letters, P = 0.002, linear regression accounting for age, Table 3). Monocular LCLA at 2.5% was similarly a significant predictor of athlete vs control status (P = 0.02, GEE models accounting for age and within-participant, intereye correlations, Fig. 1D). On subgroup analysis by sport, boxers had on average 6.2 letters worse 2.5% LCLA than controls (P = 0.003, GEE model accounting for age and within-participant, intereye correlations, Table 3) and 4.6 letters worse acuity compared to controls on 1.25% contrast charts (P = 0.03, GEE model accounting for age and within-participant, intereye correlations, Table 3). Rapid number naming performance times were not significantly different between the control and athlete groups. However, on subgroup analyses by sport, football players had faster (better) K-D Test performance times compared to controls (37.5 ± 0.9 seconds vs 40.0 ± 0.6 287 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution FIG. 1. Box plots comparing controls vs athletes show median scores for OCT measures of average RNFL (A) and GCC (B) thickness demonstrating RNFL thinning in athletes, LCLA demonstrating worse binocular (C) and monocular (D) LCLA at 2.5% contrast in athletes, and visual QOL measures demonstrating worse NEI-VFQ-25 (E) and 10-Item Supplement (F) scores in athletes. The horizontal lines in the boxes represent the medians, and boxes delineate the interquartile ranges (25th to 75th percentiles). Whiskers represent the ranges of observations (represented as circles). P-values are based on GEE or linear regression models, accounting for age (and within-participant, intereye corrections for monocular measures). GCC, ganglion cell complex; NEI-VFQ-25, 25-Item National Eye Institute Visual Functioning Questionnaire; 10-Item Supplement, 10-Item Neuro-Ophthalmic Supplement to the NEI-VFQ-25; RNFL, retinal nerve fiber layer. seconds, P = 0.02, linear regression accounting for age, Table 2). The performance time for boxers was not significantly different from controls. Health-related vision-specific QOL using the NEI-VFQ25 was a significant predictor of athlete vs control status; athletes had an average of 3.1 points worse scores compared to controls (P = 0.04, linear regression accounting for age, Fig. 1E). Football athletes scored lower compared to controls (89.0 ± 1.9 vs 93.3 ± 0.6, P = 0.04, GEE models accounting for age, Table 3). Boxers did not score TABLE 2. Retinal structure measurements by optical coherence tomography Controls (n = 104, 208 Eyes) Average RNFL, mm, mean (SD) Temporal RNFL, mm, mean (SD) Superior RNFL, mm, mean (SD) Nasal RNFL, mm, mean (SD) Inferior RNFL, mm, mean (SD) Average GCC thickness, mm, mean (SD) Average minimum GCC thickness, mm, mean (SD) 94.3 61.8 116.8 74.1 124.4 81.6 80.1 (0.9) (0.9) (1.5) (1.0) (1.6) (0.5) (0.6) Football Athletes (n = 29, 58 Eyes) 93.0 59.8 116.3 74.3 122.1 81.2 78.7 (1.9) (1.5) (2.9) (2.3) (2.8) (1.2) (2.1) Boxing Athletes (n = 14, 28 Eyes) 83.5 52.2 105.0 67.1 109.3 76.7 74.3 (2.8)***,† (1.9)***,† (4.7)*,† (2.1)**,† (4.1)**,† (2.1)*,† (2.1)**,† *P , 0.05, **P , 0.01, ***P , 0.001. Comparison to control using GEE models accounting for age and within-subject intereye correlations. GCC, ganglion cell complex; RNFL, retinal nerve fiber layer; SD, standard deviation. † 288 Leong et al: J Neuro-Ophthalmol 2018; 38: 285-291 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution TABLE 3. Visual function measurements Controls (n = 104, 208 Eyes) Football Athletes (n = 29, 58 Eyes) Boxing Athletes (n = 14, 28 Eyes) 60.4 (0.4) letters 38.6 (0.5) letters 29.8 (0.6) letters 56.4 (0.5) letters 30.8 (0.6) letters 21.2 (0.8) letters 40.0 (0.6) 93.3 (0.6) 93.1 (0.7) 59.7 (0.8) letters 36.6 (1.0) letters 29.8 (0.8) letters 56.5 (0.8) letters 29.2 (1.1) letters 21.1 (1.2) letters 37.5 (0.9)*,‡ 89.0 (1.9)*,‡ 84.9 (2.3)**,‡ 55.8 (1.5) letters**,‡ 31.7 (2.1) letters**,‡ 26.4 (2.0) letters 52.4 (1.3) letters**,k 24.4 (2.0) letters**,k 16.3 (2.0) letters*,k 42.4 (2.1) 91.5 (1.6) 85.5 (3.4)*,‡ Binocular HCVA,† mean (SD) Binocular 2.5% LCLA,§ mean (SD) Binocular 1.25% LCLA,§ mean (SD) Monocular HCVA,† mean (SD) Monocular 2.5% LCLA,§ mean (SD) Monocular 1.25% LCLA,§ mean (SD) K-D Test, s, mean (SD) NEI-VFQ-25 composite, mean (SD) 10-Item supplement, mean (SD) *P , 0.05, **P , 0.01, ***P , 0.001. † Number of letters seen correctly (out of 70) on the Early Treatment Diabetic Retinopathy Study chart at 3.2 m. ‡ Comparison to control using linear regression models accounting for age. § Number of letters seen correctly (out of 70) on the Sloan Low-contrast Letter Acuity charts at 2.0 m. k Comparison to control using GEE models accounting for age and within-subject intereye correlations. 10-Item Supplement, 10-item Neuro-Ophthalmic Supplement to the NEI-VFQ-25; HCVA, high contrast visual acuity; K-D, King-Devick; LCLA, Low-contrast letter acuity; NEI-VFQ-25, 25-item National Eye Institute Visual Function Questionnaire; SD, standard deviation. significantly different than controls on the NEI-VFQ-25 (P = 0.30). The 10-Item Supplement was a significant predictor of athlete vs control status; athletes scored an average of 7.6 points worse compared to controls (P , 0.001, linear regression accounting for age, Fig. 1F). Football athletes scored on average 8.2 points worse than controls (P = 0.001, linear regression accounting for age, Table 3). Boxers scored on average 7.6 points worse than controls (P = 0.031, linear regression accounting for age, Table 3). Reductions in LCLA at 2.5% were associated with RNFL thinning (P = 0.02, GEE models accounting for age and within-participant, intereye correlations). RNFL and GCC measurements were not significantly associated with HCVA or LCLA, K-D Test, or NEI-VFQ-25. Vision-specific QOL was associated with K-D Test performance (P = 0.009, GEE models accounting for age and within-subject intereye correlations) however was not associated with LCLA or HCVA among the cohort. Years of sport participation was not significantly associated with any visual structure or function measures. There also were no associations between clinical measures and professional boxing records (total fights, win count, loss count, rounds boxed, knock-out percentage) with the exception of the boxers' draw record, which was significantly associated with RNFL thinning (9.5 mm thinner for every one draw decision, P = 0.008, GEE model accounting for age and within-participant intereye correlations). DISCUSSION This is a first study to assess vision-related clinical measures as potential markers of repetitive head trauma. Clinically significant vision-based differences were observed in collision sport athletes, with the most notable differences seen in boxers. Specifically, there were reductions of LCLA and Leong et al: J Neuro-Ophthalmol 2018; 38: 285-291 retinal thinning in the boxing cohort while the football players experienced a reduction of their visual quality of life. Although studies of retinal thinning in TBI cohorts are limited, studies of neurodegenerative conditions have demonstrated findings that are similar to those of our overall athlete cohort (10). In terms of retinal thinning, our football athletes were not significantly different from the control group. This may be due to fewer years of sport exposure, the variety of team positions represented (leading to a wide range of head trauma exposure), the type of head blows suffered, or other biomechanical and physiological factors. It also is possible that the football helmet conveys some level of protection against repetitive head trauma when compared to boxing. Nonetheless, more detailed studies of dose and intensity of trauma in larger cohorts of collision sport athletes are needed to determine if similar retinal changes are present or not. Since detailed eye examinations were not performed for this study, we cannot exclude the effects of direct ocular trauma (common in boxing) for differences between sport groups. However, the intereye symmetry in OCT findings among athletes suggests trans-synaptic degeneration as a possible mechanism of retinal thinning. This finding and potential mechanism should be investigated in future studies. Reductions in LCLA among boxers were similar to observations made in cohorts of patients with MS. Boxers had approximately one line worse acuity scores than controls for both low-contrast levels. In studies of MS, differences in mean letter scores compared to healthy controls have been reported to be 5 letters or more for HCVA and 7 letters or more for LCLA (18). The observation that football athletes had faster K-D Test times compared to boxers was perhaps not an unexpected finding given other deficits evident in boxers and that athletes typically do quite well on the rapid number naming test at baseline in the absence of acute 289 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution concussion. Previous studies of Parkinson disease and MS have shown worse K-D Test times (3,11) and also have demonstrated associations of thinner RNFL and GCC with worse LCLA scores (11). There are other factors that may affect rapid number naming performance such as educational level and age (19). Future and ongoing studies will include larger cohorts to study these effects and to examine differences in sport types. The NEI-VFQ-25 and 10-Item Supplement scores were able to differentiate controls and athletes. Previous studies of MS have reported a .4 point average NEI-VFQ-25 score difference between MS patients and disease-free controls, with patients having worse scores (depending on history of acute optic neuritis) (18). The current study found approximately 3-point difference in athletes compared to controls and 7-point difference on the 10-Item Supplement. The 10-Item Supplement previously has been evaluated in veterans with a history of blast-associated TBI (20) averaging 75 points on the NEI-VFQ-25 and 67 points on the 10-Item Supplement (20). These scores are much lower than those of patients with MS and athletes in our study. Such differences may represent variability in the mechanisms of TBI, injury severity, exposure or presence of other comorbidities common to military veterans. In contrast to previous reports of patients with MS (7,8,10,11,18), our results did not show consistent LCLA and OCT associations. This may be due to differences in mechanisms of neuronal injury in MS and neurodegenerative disease compared to those occurring in repetitive head trauma. Associations of reduced vision-specific QOL and worse K-D Test performance parallel studies of MS (11). Collectively, these findings highlight the value of using multiple measures of vision to capture dysfunction and subjective deficits. Interestingly, there was a significant association between boxers' draw records and RNFL thickness (greater numbers of draw decisions for boxers with thinner RNFL). In boxing, draws occur when the bout goes the entire distance, goes to the scorecards and the officials cannot determine a winner. This implies a longer fight duration with the potential for greater exposure to head blows and potential axonal injury. Limitations of our study include a small-sized convenience sample and limited sports represented. Future and ongoing investigations will include larger cohorts across a variety of sports. In particular, a larger sample and more heterogeneous cohort of football athletes will ensure position-specific data to sufficiently examine higher- vs lower-risk positions. This study also was limited due to cross-sectional design and retrospective ascertainment of head trauma exposure data. Ongoing studies will examine longitudinal changes and, hopefully, provide more insight into the natural history of these findings. Lastly, there are a variety of additional ophthalmic measures, as well as cognitive and brain imaging techniques, that 290 future studies should consider to provide insight into pathophysiology. Importantly, visual dysfunction and structural changes associated with participation in sports with head injury that can be detected in vivo represent a unique opportunity to study related mechanisms of neurodegeneration. 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Lemke S, Cockerham GC, Glynn-Milley C, Cockerham KP. Visual quality of life in veterans with blast-induced traumatic brain injury. JAMA Ophthalmol. 2013;131:1602-1609. Images in Neuro-Ophthalmology Traumatic four nerve palsy. A 58 year-old man accidentally fell, striking the right side of his head and losing consciousness. During his recovery, he complained that "things look slanted" and his exam was consistent with a left fourth nerve palsy. Brain MRI including diffusion-weighted (A) and fluid-attenuated inversion recovery (B) sequences show changes consistent with axonal injury to the right fourth nerve nucleus (arrowhead) and an asymptomatic lesion in the right temporal lobe (arrow). (Courtesy of Alex McGaughy MD, Michael Vaphiades DO, and Lanning Kline MD, Birmingham, Alabama). Leong et al: J Neuro-Ophthalmol 2018; 38: 285-291 291 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited.