Visual loss has been recognized for decades as one of the most common and disabling clinical manifestations of multiple sclerosis (MS). It was not until a decade ago, however, that MS clinical trials began to include sensitive measures of visual function. Inspired by the effective use of contrast sensitivity (Pelli-Robson charts) to demonstrate visual abnormalities in the Optic Neuritis Treatment Trial (ONTT) (1–6), low-contrast letter acuity was introduced into MS trials as an exploratory outcome to better capture the often subtle visual symptoms experienced by patients with acute optic neuritis (ON) (7–10).
Visual symptoms can result from a variety of pathological processes, including inflammation, demyelination, and axonal degeneration in the afferent visual pathway (retina, optic nerves, chiasm, and tracts) (11–15). During the past decade, the contributions of axonal and neuronal loss to disability in MS have been increasingly recognized (12,16–19). Developed initially as a noninvasive tool to monitor retinal disease and glaucoma, optical coherence tomography (OCT) was first applied to cohorts of patients with MS and ON over a decade ago to provide validation of clinical visual outcomes and to capture anterior visual pathway axonal loss (15,20–25). As a result of these early studies and >100 subsequent published investigations of OCT in MS and ON (26), the visual pathway is now recognized as a model for structure-function correlation in MS for studying the pathophysiology of disease and for testing both novel and standard therapies that involve neuroprotection and repair. OCT can be used noninvasively to capture reductions in axonal loss that may be associated with neuroprotective or myelin repair therapies; this information can be correlated with visual function and quality of life (QOL) data to further establish the clinical relevance of these structural outcomes.
OCT enables investigators to rapidly and reproducibly evaluate the structural composition of the retina. Ultimately, OCT could substantially increase our understanding of the mechanisms of tissue injury in MS, ON, and other optic neuropathies.
A decade after publication of the first studies of low-contrast acuity in MS, this test and OCT measures are commonly used in MS clinical trials. They have formed the foundation for new trials that use acute ON as a model for identifying novel compounds for neurorepair (27–32).
This review describes a number of advancements in the development of visual function outcomes in MS and OCT as a novel technology that enables objective analysis of the processes of neurodegeneration. In addition, we present representative group data from studies that have examined visual function, OCT measures, and QOL scales in patients with MS and ON and disease-free controls (Table 1). These data may be used to provide initial reference values and should be viewed in the context of 1) the continually evolving field of vision in MS, 2) the potential challenge inherent in applying group data to individual patients, and 3) the perspective that even the small observed differences in mean OCT values have been shown to correlate with clinically meaningful changes in visual function and QOL in MS patients.
VISION IN MS: THE STORY
In the late 1990s, the National Multiple Sclerosis Society Clinical Outcomes Assessment Task Force developed the Multiple Sclerosis Functional Composite (MSFC) in response to the need for more sensitive neurologic outcome scale (33,34). Designed to be a battery of performance measures complementary to the Expanded Disability Status Scale (EDSS), the MSFC includes the 25-Foot Timed Walk, the 9-Hole Peg Test, and Paced Auditory Serial Addition Test (35–38). While multidimensional, the MSFC did not include a measure of visual function. In the evaluation of candidate MSFC visual components from MS clinical trial data used to develop the MSFC, Snellen high-contrast visual acuity (VA) did not change over time or demonstrate concurrent changes with EDSS scores (33). Contrast sensitivity, as tested by line gratings and letter charts in MS and by Pelli-Robson charts in the ONTT, had been shown to be a sensitive measure of afferent visual function, even among patient with Snellen acuities of 20/20 or better (1–6,39–43). Importantly, measures of low-contrast vision are predictive of “real-world” visual tasks, such as reading rate, facial recognition, and driving (44).
Low-Contrast Letter Acuity
While used successfully in the ONTT to demonstrate persistent visual abnormalities beyond recovery of high-contrast VA, Pelli-Robson contrast sensitivity charts were not available for purchase in 1998, when the first MS clinical trial to incorporate a low-contrast visual measure as an exploratory outcome was begun. This trial, International MS Progressive Avonex Clinical Trial (IMPACT), incorporated low-contrast Sloan letter charts (7,8,45,46). These charts are the low-contrast (gray letters on white) “cousin” of the Early Treatment Diabetic Retinopathy Study (ETDRS) high-contrast VA charts used in ophthalmology clinical trials (Fig. 1). Sloan charts have a standardized format based on the ETDRS VA charts. Three contrast levels have been used in MS trials and research studies, including 100% (high-contrast, used to measure VA as a descriptor of the study cohorts), 2.5%, and 1.25% (lightest contrast level). Charts are scored letter by letter, and numbers of letters identified correctly constitute the score for each chart (Table 1). Most recently, visual improvement and loss by the low-contrast acuity chart has been defined as a 7-letter change in score, while 5-letter changes in high-contrast VA are now considered clinically significant for patients with good VA (47). This threshold represents a change that exceeds that which would be expected from repeated testing when there was no real change (45,48) and to correlate with retinal nerve fiber layer (RNFL) axonal loss in patients with MS (47). As shown in Table 1, differences in mean letter scores for MS vs disease-free control groups are consistently ≥5 letters for VA and ≥7 letters for low-contrast acuity. Since the 5- and 7-letter criteria are meant to be applied to individual eye or patient differences, differences in mean scores of such magnitude are therefore likely to be clinically meaningful. Furthermore, these 5- and 7-letter mean changes have been shown to correlate significantly with vision-specific and overall QOL, as well as structural measures of OCT RNFL thickness. These associations of OCT and QOL measures with clinically meaningful changes in visual function provide perspective for the data in Table 1, despite the seemingly small magnitudes of differences in means for OCT values.
In the IMPACT trial and in heterogeneous MS cohorts (7,8,45), low-contrast letter acuity was shown to be a highly reliable (high intraclass correlations of 0.86–0.95) and practical method that was superior in identifying MS-related visual loss compared to other available tests (Fig. 2). Correlations of Sloan chart scores with MSFC and EDSS in these studies were significant and moderate in magnitude (r s = 0.56 vs MSFC; r s = −0.43 vs EDSS, P < 0.0001). These studies provided the first ever data demonstrating that low-contrast acuity scores capture unique aspects of dysfunction not captured by standard neurologic scales of EDSS or the MSFC and suggested that adding a visual component to the MSFC would increase the applicability of this measure.
In the AFFIRM trial of natalizumab vs placebo for relapsing-remitting MS, low-contrast letter acuity was able to demonstrate treatment effects and changes over time both with respect to reduction of the cumulative probability of sustained visual loss (by 47%, P < 0.001 for 2.5% contrast level) and sustained clinically meaningful visual improvement (by 57%, P = 0.01) in the treatment group (9,10). Similar to previous studies and to MS trial datasets used originally to develop the MSFC, high-contrast VA did not show treatment differences or detect sustained visual loss or improvement over time. The analyses of visual loss in AFFIRM used initially a 2-line (10-letter) criterion for clinically significant change; subsequent ophthalmologic studies for VA, however, suggested use of a 1-line (5-letter cut-off). Examination of interrater and test-retest reliability data for low-contrast acuity revealed 7 letters to represent 2 SDs on the interrater differences; this 7-letter criterion was subsequently incorporated into the AFFIRM analyses of visual improvement and subsequent longitudinal studies of OCT.
Vision-Specific QOL Measures
The relevance of low-contrast letter acuity measurements to patient functioning has been underscored by studies linking these scores to vision-specific QOL. Scores for the 25-Item National Eye Institute Visual Functioning Questionnaire (NEI-VFQ-25) are reduced among patients with MS (Table 1) (49–51). A 10-Item Neuro-Ophthalmic Supplement to the NEI-VFQ-25 has also been designed using MS cohorts to capture symptoms relevant to neurologic disease. In a recent study of 167 patients with MS, 2-line differences in visual function by low-contrast acuity are associated, on average, with >4-point worsening (6.7 – 10.9 points, P < 0.001 accounting for age) in NEI-VFQ-25 composite (overall) score, reductions that are considered to be clinically meaningful based on ophthalmic epidemiologic studies (52–55). In Table 1, the differences in mean scores between MS patients and disease-free controls were ≥4 points; such differences may be considered clinically significant for both individual changes and group data. Binocular scores for low-contrast acuity also correlated significantly with score for the 10-Item Neuro-Ophthalmic Supplement (P < 0.001), the Impact of Visual Impairment Scale (P < 0.001), and the SF-36 Physical Component Summary (P < 0.001) in this MS cohort. Collectively, these data demonstrated that low-contrast acuity testing provides information on patient-reported aspects of vision. This is a key feature for clinical measures and a prerequisite for their use as primary outcomes in clinical trials.
Binocular Summation of Acuity
While the earliest studies of low-contrast acuity and QOL examined binocular vision scores (vision testing with both eyes together), monocular measurements (with each eye separately) have more recently been introduced into MS trials and vision research with the inclusion of OCT scanning as a structural correlate to vision (Table 1). Given the importance of both of these types of acuity to measurements of function, analyses of MS cohort data, including both binocular and monocular scores, were performed to examine the relation between the two and to determine the potential roles for binocular summation and inhibition (56). Binocular summation of acuity occurs when vision is improved under binocular viewing conditions (binocular score is greater than the scores for either eye alone) (57). In contrast, patients with binocular inhibition have worse binocular vision compared to the better eye alone. Among 1,007 patients with MS and 324 disease-free controls, binocular summation was substantial (5- to 7-letter increases over better eye acuity, 28%–52% with >7 letters, P < 0.001) for low-contrast acuity at the 2.5% and 1.25% levels. For high-contrast VA, only 3.0%–3.4% of patients showed similar degrees of summation. Increasing age (P < 0.0001), greater interocular differences in acuity (P < 0.0001), and history of ON (P = 0.015) were associated with lower magnitudes of binocular summation; in fact, some of these patients had binocular inhibition. Importantly, greater degrees of binocular summation were predictive of better QOL by the NEI-VFQ-25 (P = 0.02) and 10-Item Supplement (P = 0.03), indicating that the capacity to use both eyes together is an important factor in determining how well patients with MS can perform daily activities (56).
Relation of Vision to MRI and Visual-Evoked Potentials
Correlation with biological markers and electrophysiological measures of disease is one of the most important factors in the evaluation of clinical outcome measures such as low-contrast letter acuity. The first such study determined the relation of binocular low-contrast scores to brain MRI measures of T2 lesion burden (58). This study of 45 patients with MS found that those with worse low-contrast acuity scores had greater T2 lesion volumes in whole brain (3 mm3 increase for every 1-line worsening, P = 0.002–0.004, accounting for age and disease duration). Area 17 and optic radiation white matter lesion burden specifically correlated with visual function, but non–vision-related white matter did not show associations. These findings were important in providing a structural correlate to low-contrast acuity scores and also in emphasizing a potential postgeniculate pathway component to binocular low-contrast vision.
Standard brain MRI techniques have provided information regarding disease burden in MS. However, the capacity for these techniques to precisely quantify axonal and neuronal loss, particularly in the anterior visual pathway, has been limited. Electrophysiologic markers such as the visual-evoked potential (VEP) can provide additional information on anterior visual pathway integrity. Recent studies have combined assessments of vision loss with VEP. Conventional VEPs measure the cortical response to monocular stimulation in the central 30° of the visual field. In MS, the latency characteristically is delayed with normal amplitude. Axonal loss, however, can reduce this amplitude (59). Abnormal VEPs in unaffected eyes provided evidence for clinically silent lesions in the optic nerve that might help identify dissemination in space and help establish the diagnosis of MS (60). Various studies have shown that contrast sensitivity can be measured by VEP (43), and in MS, low-contrast stimuli VEPs show increased latencies or absent waveforms when compared with high-contrast stimuli VEPs. Low-contrast VEP may prove to be helpful in identifying demyelination (61). Other studies have concluded that multifocal VEP provides higher sensitivity and specificity in detecting abnormalities in visual function in MS and in ON (62).
Naismith et al (63) systematically evaluated the utility of OCT and VEPs to detect the presence of clinical and subclinical ON and examined the relation of these measures to visual function. This retrospective cross-sectional study evaluated 65 subjects (n = 96 eyes) with MS (n = 40), clinically isolated syndrome (CIS, n = 1), neuromyelitis optica (n = 20), and idiopathic demyelination (n = 4). Patients had at least one episode of ON ≥6 months prior to enrollment. VEPs detected ON in 81% of patients (32% of subclinical ON in unaffected eyes and 75% of all subclinical ON). In contrast, using their criteria, they found that OCT identified 60% of eyes with ON and less than 20% of subclinically affected eyes. The authors concluded that OCT is less sensitive than VEPs in ON. On the other hand, to the extent that this study focused on patients with relatively poor vision, there were likely floor effects with regard to OCT RNFL thickness.
STRUCTURE-FUNCTION CORRELATIONS: OCT
Although acute ON and demyelination are important contributors to visual dysfunction, irreversible axonal and neuronal degeneration are also final common pathways to permanent visual loss (12–14,24,64). While the relationship between visual loss and brain MRI lesion burden discussed above is a relatively new finding, the extremely high predilection for MS to involve the optic nerves is well-documented and was initially observed long before the advent of advanced optical and neuroimaging. Autopsy studies have shown that up to 94%–99% of MS patients have detectable optic nerve lesions (65,66). Subclinical changes related to visual loss may involve the optic nerves or chiasm, or postchiasmal regions of the optic tract (13,67–69).
Features and Advantages of OCT Imaging
OCT provides a noninvasive technique to measure axonal and neuronal loss in the anterior visual pathways (24,28–32). As the optical analog of ultrasound B-mode imaging, OCT allows us to image the RNFL (15,20–32,47,59,70–82). Since, within the retina, these axons are nonmyelinated, the RNFL is an ideal structure to visualize the processes of neurodegeneration, neuroprotection, and potentially even neurorepair. In contrast to the peripapillary RNFL, which contains axons, the macula contains a large proportion of retinal ganglion cell neurons (about 34% of total macular volume) (81). The development of Fourier-domain (or spectral-domain [SD]) detection has in particular enhanced ophthalmic OCT technology. While many of the studies cited in this review utilized time-domain (TD) OCT, some have incorporated the newer SD-OCT technologies. Table 1 presents some representative group data for OCT measures in patients with MS, ON, and disease-free controls. Since OCT measures have been shown to correlate with clinically meaningful changes in visual function and QOL (see above), the differences in mean values between groups shown in Table 1 are likely to have clinical significance. Larger studies and additional meta-analyses will allow us to further refine the precision of these representative average values.
OCT Investigations in MS and ON
The earliest application of OCT technology to the study of MS was reported by Parisi et al in 1999 (15). In this study, which utilized first-generation OCT technology, 14 patients with MS who had completely recovered from a previous event of acute ON were analyzed. The thickness of the RNFL was shown to be reduced by 46% in the affected eyes of the patients with MS vs the control eyes (P < 0.01) and by 28% when affected eyes were compared with the “unaffected” eyes of the same patient (P < 0.01). Even in the clinically unaffected eyes of patients, however, there was a 26% reduction in RNFL thickness when compared with control eyes (P < 0.01).
In 2005, Trip et al (21) reported their observations with OCT in 11 patients with MS and 14 patients with CIS, all of which individuals had a history of a single episode of ON. The study was a cross-sectional analysis with follow-up ranging from 1 to 9 years after the ON event. Corroborating the previous findings by Parisi et al (15), the investigators found a 33% reduction in RNFL thickness in the eyes of the patients when compared with the eyes of matched controls and a 27% reduction when the affected and unaffected eyes of the same patient were compared (P < 0.001). Trip et al (21) extended the utility of OCT by also showing that the macular volume (a reflection of retinal ganglion cell neuronal integrity) was reduced by 11% in the eyes of patients with a history of ON when compared with control eyes (P < 0.001) and by 9% in the affected vs the unaffected eye of the same patient (P < 0.001).
In 2006, Costello et al (20) reported that the majority of patients with MS who have ON (approximately 75%) will sustain 10–40 μm of RNFL loss within a period of approximately 3–6 months. This finding is striking given that the RNFL is only about 110–120 μm thick by the age of 15 years and that most individuals (without a history of glaucoma or macular degeneration) will lose only about 0.017% per year in retinal thickness, which equates to approximately 10–20 μm over 60 years (25,83). Costello et al (20) also provided compelling evidence identifying an injury threshold within the RNFL of about 75 μm; thinning of the RNFL below this level led to a corresponding decline in visual function, as measured by automated perimetry. Using low-contrast letter acuity in MS eyes with a history of acute ON, we have found a similar threshold for abnormal visual function and axonal loss at 80 μm (Fig. 3).
The trajectory and time course of RNFL axonal loss following an episode of acute ON are important for determining the “window of opportunity” within which a neuroprotective or repair agent should be administered in a treatment trial. Sample size calculations for a proposed ON trial are also likely to be based on such data. Henderson et al (84) recently addressed both of these questions in a study of 23 patients with acute clinically isolated unilateral ON. Patients underwent TD-OCT assessment of RNFL thickness and total macular volume; visual function testing with high-contrast VA, low-contrast acuity (Sloan charts at 1.25%), Farnsworth-Munsell 100 color testing, and automated visual fields; and pattern VEP testing. The mean time to 90% loss from the initial RNFL thickness values for affected eyes (initial median 116.5 μm—likely reflecting slight edema) was 2.38 months (95% confidence interval [CI], 1.95–2.77; P < 0.05). Ninety-nine percent of the loss from the initial value to the asymptotic value (lowest point where loss leveled off) occurred by a mean of 4.75 months (95% CI, 3.90–5.54; P < 0.05). The time of first detectable RNFL atrophy compared to the baseline fellow eye value was 1.64 months (95% CI, 0.96–2.32; P < 0.05). Eyes with poor recovery (n = 5), defined as logarithm of the minimum angle of resolution VA > 0.1, had a significantly greater decline of RNFL from baseline to 3 months (P = 0.002). Macular volumes also declined significantly to the time of last follow-up. Sample size estimates using their models showed that, assuming 80% power, approximately 100–150 patients would be needed to detect a 30% decrease in RNFL loss between the treatment and placebo groups at a 3- to 6-month endpoint. These findings are critical in setting the stage for use of acute ON as a model for neuroprotection and repair trials (84).
One of the most important findings that has resulted from the use of OCT MS studies is the correlation between RNFL thinning and visual loss, as measured by low-contrast letter acuity. In 2006, Fisher et al (22) conducted a cross-sectional study that compared RNFL thickness among MS eyes with a history of ON (MS ON eyes), MS eyes without a history of ON (MS non-ON eyes), and disease-free controls. In addition to OCT measurement of OCT, they conducted low-contrast visual assessments with low-contrast letter acuity, contrast sensitivity (Pelli-Robson charts), and high-contrast VA (ETDRS charts). The authors found that RNFL thickness was reduced significantly among MS patients (92 μm) vs controls (105 μm, P < 0.001) and particularly reduced in MS ON eyes (85 μm, P < 0.001). Furthermore, lower visual function scores were associated with reduced average overall RNFL thickness in MS eyes; for every 1 line decrease in low-contrast letter acuity or contrast sensitivity score, the mean RNFL thickness decreased by 4 μm. These findings not only supported the validity of low-contrast visual assessment as a secondary clinical outcome measure in MS trials, they also suggested a potential role for OCT in trials that examine neuroprotective and other disease-modifying therapies. Several other investigations have demonstrated correlations between RNFL thinning and visual loss (21,25,77,85–87).
While the above studies used cross-sectional studies to examine relationships between biomarkers measured with OCT and visual function, the first longitudinal study to study the relationship between RNFL thickness and visual loss was carried out by Talman et al in 2010 (47). These investigators used OCT to measure RNFL thickness at baseline and at 6-month intervals during a mean follow-up of 18 months at 3 centers. Low-contrast letter acuity (2.5% and 1.25%) and high-contrast VA were tested. The results indicated that among 299 patients (593 eyes) with at least 6 month follow-up, eyes with visual loss showed greater RNFL thinning compared to eyes with stable vision (low-contrast acuity, 2.5%: P < 0.001; VA: P = 0.005). RNFL thinning increased over time, with average losses of 2.9 μm at 2–3 years and 6.1 μm at 3–4.5 years (P < 0.001 vs 0.5–1 year follow-up). The authors concluded that progressive RNFL thinning occurs as a function of time in some patients with MS, even in the absence of ON (47). Studies such as this draw the important connection between structure (RNFL thickness and macular volume, as measured by OCT) and function (visual performance as measured by low-contrast acuity) and are likely to be instrumental in improving our understanding of the MS disease process.
Recently, OCT has also been used to show the capacity of RNFL thinning to distinguish MS disease subtypes. Costello et al (85) found that RNFL comparisons involving eyes without ON yielded greater differences between MS subtypes than ON-affected eyes. Overall RNFL values in nonaffected eyes were reduced in patients with secondary progressive multiple sclerosis (SPMS) (83.4 μm), relative to ON as a CIS (101.2 μm) (P = 0.0009), and patients with relapsing-remitting multiple sclerosis (RRMS) (103.7 μm) (P = 0.001); and temporal RNFL atrophy was greater in RRMS (64.4 μm) eyes as compared to CIS eyes (73.2 μm, P = 0.02). In ON-affected eyes, RNFL atrophy was greater in patients with SPMS (39.5 μm) than those with CIS (58.1 μm, P = 0.03) and in patients with RRMS (48.2 μm) relative to those with CIS (P = 0.05). These authors concluded that RNFL thickness might represent an important MS structural marker because RNFL thinning reflects disease progression.
While RNFL thinning is most marked in patients with SPMS, those with benign MS, traditionally defined as EDSS ≤3 and ≥15 years of disease duration, are thought to follow a milder course (88). We recently conducted an analysis of a longitudinal MS cohort to determine the extent of visual pathway axonal loss by OCT RNFL thickness. At 3 academic centers, a subset of patients with EDSS scores, visual function, OCT, and QOL assessments was analyzed. Low- and high-contrast letter acuities were performed to assess visual function. RNFL thickness was determined using OCT-3. QOL scales included the NEI-VFQ-25 and SF-36. Among 68 patients (135 eyes) studied longitudinally, 13 (26 eyes) had benign MS using criteria of EDSS ≤3 and ≥15 years of disease duration. Benign MS eyes had as much RNFL thinning (−3.6 μm, P = 0.0008 vs baseline, paired t test) as typical MS eyes (−3.3 μm, P < 0.0001). Both groups had significant low-contrast acuity loss over time. History of ON was more frequent in benign MS (69% vs 33% of eyes). History of ON distinguished benign vs typical MS (P = 0.002) and correlated with RNFL thickness at baseline (P = 0.002) and disease duration (P = 0.03) but not EDSS (P = 0.32, logistic regression). NEI-VFQ-25 scores were also worse for benign MS, accounting for age (75 ± 21 vs 88 ± 11, P = 0.005). These findings demonstrated that patients with benign MS have RNFL axonal loss that is as marked as that of typical MS and have reduced vision and QOL. While overall neurologic impairment is mild, visual dysfunction, not well-captured by the EDSS, accounts for a substantial degree of disability in benign MS.
The Future of OCT in MS: Retinal Segmentation
In addition to axonal degeneration, neuronal loss is increasingly recognized as a correlate of disability in MS (16–19,89–91). While investigations of TD-OCT have shown reductions in total macular volume as a potential marker for neuronal loss in MS eyes, more specific measurement of the retinal ganglion cell layer (GCL) and other layers by segmentation has only recently emerged following the introduction of high-resolution and high-speed-domain (SD) OCT techniques to study MS (Table 1) (25–27,82,92–100). Earlier studies of total macular volume using TD-OCT suggested that retinal ganglion cell neuronal loss occurs in MS eyes and that this correlates with visual function (81). These observations were necessarily based on the structural assumption that approximately 34% of the total macular volume is comprised of ganglion cells.
Using SD-OCT, some of the first observations of specific retinal GCL loss in MS eyes were generated by a study that involved manual delineation of the GCL on a Spectralis OCT platform (Fig. 4) (97). In this pilot investigation, eyes of patients with MS (n = 16) had significantly lower GCL volumes than control eyes (P < 0.001, accounting for age and within-patient intereye correlations). Lower volumes were noted among MS eyes with a history of ON (n = 4) compared with MS non-ON eyes (P < 0.001). Reduced GCL volumes were not associated with worse high-contrast VA (P = 0.14), but did predict visual loss by low-contrast acuity (P = 0.003).
While manual OCT retinal segmentation demonstrated important findings in these studies, the labor-intensive nature of this technique (approximately 2 hours per eye) limits its large scale use in MS cohorts. Computerized segmentation algorithms have been used successfully in studies of glaucoma (99,100) and have provided the basis for 2 recent investigations in MS cohorts. Saidha et al (96) used a segmentation method developed commercially to study patients with a macular thinning predominant (MTP) MS phenotype. These patients have peripapillary RNFL thickness that is within the normal ranges but exhibit severe <5th percentile thinning of the macular region on SD-OCT. This group of patient eyes demonstrated thinning of the outer retinal layers (P < 0.001 for inner and outer nuclear layers in MTP vs MS eyes), with relative sparing of the GCL. Patients with the MTP phenotype also had relatively greater degrees of overall neurologic disability, suggesting that these individuals may have a distinct or primary process underlying their neuronal loss.
Recent pathologic studies of postmortem eyes from heterogeneous MS cohorts (n = 82) demonstrated that the GCL is a site of neuronal dropout in 79% of eyes (101). Retinal ganglion cell loss has also been shown to occur in vivo in mouse models of relapsing-remitting experimental autoimmune encephalomyelitis with optic nerve involvement and to be reduced by neuroprotective therapies, such as resveratrol, in these models (102). To examine GCL loss in MS in vivo in patients with MS, our collaborative MS vision research group has used a novel computerized segmentation algorithm developed at the University of Pittsburgh (103). In this study, patients with MS (n = 122 subjects, 239 eyes) and disease-free controls (n = 31 subjects, 61 eyes) underwent Cirrus SD-OCT (Carl Zeiss-Meditec, Dublin, CA). Images were captured using Macular Cube (200 × 200 or 512 × 128) and ONH Cube 200 × 200 scanning protocols. Retinal layer segmentation was performed using algorithms originally designed for studies of glaucoma. Thicknesses of the GCL/inner plexiform layer (GCL+IPL), RNFL, outer plexiform/inner nuclear layer, and outer nuclear/photoreceptor layer were measured and compared in MS vs control eyes as well as MS ON vs non-ON eyes. Since the IPL is a thin layer that is currently inseparable from the GCL using OCT, the combination GCL+IPL is used to estimate GCL thickness. Macular RNFL and GCL+IPL were significantly decreased in MS subjects vs controls (P < 0.001, P = 0.001) and in MS ON eyes vs non-ON eyes (P < 0.001 for both measures). Peripapillary RNFL, macular RNFL, and GCL+IPL were all significantly correlated with VA (P ≤ 0.001), 2.5% low-contrast acuity (P < 0.001), and 1.25% low-contrast acuity (P ≤ 0.001). Among OCT measurements, reductions in GCL+IPL (P < 0.001) and macular RNFL (P = 0.006) were the most strongly associated with lower (worse) NEI-VFQ-25 and 10-Item Supplement composite scores for QOL; GCL+IPL thinning was significant even accounting simultaneously for macular RNFL thickness (P = 0.03 for GCL+IPL and P = 0.39 for macular RNFL). These data demonstrate that GCL+IPL thinning is most significantly correlated with both visual function and vision-specific QOL in MS. GCL thickness is likely to emerge as a useful structural marker of disease. These findings parallel those of MRI studies that show gray matter disease as a marker of neurologic disability in MS.
Vision and OCT in MS Clinical Trials: Role for Reading Centers
The incorporation of OCT and visual outcome measures into MS clinical trials has benefited from the presence of OCT reading centers. The University of California Davis Reading Center recently published the results of Stratus (TD) OCT quality control in 2 multicenter MS clinical trials (104). The authors evaluated 19,961 OCT scans from 981 patients with the goal of determining the influence of OCT quality control procedures on error rate. In Trial 1 (design and therapeutic agent not specified in publication), there was no ophthalmic technician certification and data were obtained by the Reading Center retrospectively. However, in Trial 2, technicians were certified and submitted data prospectively according to the study protocol. OCT scans in Trial 2 had higher signal strengths, fewer errors, and more usable data compared to Trial 1 scans. This study showed that certified technicians and prompt transmission of data for ongoing quality control monitoring provide higher data quality; these factors and the use of Reading Centers should be considered in the design of clinical trials for MS and other neuro-ophthalmologic disorders.
Visual dysfunction is not only an important contributor to impairment and disability in MS but represents a unique opportunity for studying disease mechanisms and for testing new therapies that involve neuroprotection and repair. The advent of ocular imaging with OCT has allowed investigators to examine in vivo the morphological changes that accompany visual loss. Sensitive visual function tests, including low-contrast letter acuity, have been shown to correlate with OCT measures of axonal and neuronal loss as well as with patient-reported assessments of QOL. These observations have been instrumental in the establishment of a structure-function paradigm for using the anterior visual pathway as a model in MS. Low-contrast letter acuity, vision-specific QOL measures (NEI-VFQ-25 and 10-Item Neuro-Ophthalmic Supplement), and OCT measures have been incorporated into recent MS clinical trials. It is likely that these emerging data will yield important findings for therapeutics in MS, ON, and other neuro-ophthalmologic causes of visual loss.
1. Optic Neuritis Study Group. . Visual function 15 years after optic neuritis: a final follow-up report from the Optic Neuritis Treatment Trial. Ophthalmology. 2008;115:1079–1082
2. Beck RW, Gal RL, Bhatti MT, Brodsky MC, Buckley EG, Chrousos GA, Corbett J, Eggenberger E, Goodwin JA, Katz B, Kaufman DI, Keltner JL, Kupersmith MJ, Miller NR, Moke PS, Nazarian S, Orengo-Nania S, Savino PJ, Shults WT, Smith CH, Trobe JD, Wall M, Xing DOptic Neuritis Study Group. . Visual function more than 10 years after optic neuritis: experience of the optic neuritis treatment trial. Am J Ophthalmol. 2004;137:77–83
3. Cleary PA, Beck RW, Anderson MM Jr, Kenny DJ, Backlund JY, Gilbert PR. Design, methods, and conduct of the Optic Neuritis Treatment Trial. Control Clin Trials. 1993;14:123–142
4. Trobe JD, Beck RW, Moke PS, Cleary PA. Contrast sensitivity and other vision tests in the optic neuritis treatment trial. Am J Ophthalmol. 1996;121:547–553
5. Volpe NJ. The optic neuritis treatment trial: a definitive answer and profound impact with unexpected results. Arch Ophthalmol. 2008;126:996–999
6. Keltner JL, Johnson CA, Cello KE, Dontchev M, Gal RL, Beck RWOptic Neuritis Study Group. . Visual field profile of optic neuritis: a final follow-up report from the optic neuritis treatment trial from baseline through 15 years. Arch Ophthalmol. 2010;128:330–337
7. Balcer LJ, Baier ML, Cohen JA, Kooijmans MF, Sandrock AW, Nano-Schiavi ML, Pfohl DC, Mills M, Bowen J, Ford C, Heidenreich FR, Jacobs DA, Markowitz CE, Stuart WH, Ying GS, Galetta SL, Maguire MG, Cutter GR. Contrast letter acuity as a visual component for the Multiple Sclerosis Functional Composite. Neurology. 2003;61:1367–1373
8. Baier ML, Cutter GR, Rudick RA, Miller D, Cohen JA, Weinstock-Guttman B, Mass M, Balcer LJ. Low-contrast letter acuity testing captures visual dysfunction in patients with multiple sclerosis. Neurology. 2005;64:992–995
9. Balcer LJ, Galetta SL, Calabresi PA, Confavreux C, Giovannoni G, Havrdova E, Hutchinson M, Kappos L, Lublin FD, Miller DH, O'Connor PW, Phillips JT, Polman CH, Radue EW, Rudick RA, Stuart WH, Wajgt A, Weinstock-Guttman B, Wynn DR, Lynn F, Panzara MA. Natalizumab reduces visual loss in patients with relapsing multiple sclerosis. Neurology. 2007;68:1299–1304
10. Balcer LJ, Galetta SL, Polman PH, Eggenberger E, Calabresi PA, Zhang A, Scanlon JV, Hyde R. Low-contrast acuity measures visual improvement in a phase 3 trial of natalizumab in relapsing MS. Mult Scler. 2010;16:S183
11. Graves J, Balcer LJ. Eye disorders in patients with multiple sclerosis: natural history and management. Clin Ophthalmol. 2010;4:1409–1422
12. Trapp BD, Peterson J, Ransohoff RM, Rudick R, Mörk S, Bö L. Axonal transection in the lesions of multiple sclerosis. N Engl J Med. 1998;338:278–285
13. Evangelou N, Konz D, Esiri MM, Smith S, Palace J, Matthews PM. Size-selective neuronal changes in the anterior optic pathways suggest a differential susceptibility to injury in multiple sclerosis. Brain. 2001;124:1813–1820
14. DeLuca GC, Williams K, Evangelou N, Ebers GC, Esiri MM. The contribution of demyelination to axonal loss in multiple sclerosis. Brain. 2006;129:1507–1516
15. Parisi V, Manni G, Spadaro M, Colacino G, Restuccia R, Marchi S, Bucci MG, Pierelli F. Correlation between morphological and functional retinal impairment in multiple sclerosis patients. Invest Ophthalmol Vis Sci. 1999;40:2520–2527
16. Fisher E, Lee JC, Nakamura K, Rudick RA. Gray matter atrophy in multiple sclerosis: a longitudinal study. Ann Neurol. 2008;64:255–265
17. Pirko I, Lucchinetti CF, Sriram S, Bakshi R. Gray matter involvement in multiple sclerosis. Neurology. 2007;68:634–642
18. Fisniku LK, Chard DT, Jackson JS, Anderson VM, Altmann DR, Miszkiel KA, Thompson AJ, Miller DH. Gray matter atrophy is related to long-term disability in multiple sclerosis. Ann Neurol. 2008;64:247–254
19. Chard D, Miller D. Grey matter pathology in clinically early multiple sclerosis: evidence from magnetic resonance imaging. J Neurol Sci. 2009;282:5–11
20. Costello F, Coupland S, Hodge W, Lorello GR, Koroluk J, Pan YI, Freedman MS, Zackon DH, Kardon RH. Quantifying axonal loss after optic neuritis with optical coherence tomography. Ann Neurol. 2006;59:963–969
21. Trip SA, Schlottmann PG, Jones SJ, Altmann DR, Garway-Heath DF, Thompson AJ, Plant GT, Miller DH. Retinal nerve fiber layer axonal loss and visual dysfunction in optic neuritis. Ann Neurol. 2005;58:383–391
22. Fisher JB, Jacobs DA, Markowitz CE, Galetta SL, Volpe NJ, Nano-Schiavi ML, Baier ML, Frohman EM, Winslow H, Frohman TC, Calabresi PA, Maguire MG, Cutter GR, Balcer LJ. Relation of visual function to retinal nerve fiber layer thickness in multiple sclerosis. Ophthalmology. 2006;113:324–332
23. Frohman E, Costello F, Zivadinov R, Stuve O, Conger A, Winslow H, Trip A, Frohman T, Balcer L. Optical coherence tomography in multiple sclerosis. Lancet Neurol. 2006;5:853–863
24. Frohman EM, Fujimoto JG, Frohman TC, Calabresi PA, Cutter G, Balcer LJ. Optical coherence tomography: a window into the mechanisms of multiple sclerosis. Nat Clin Pract Neurol. 2008;4:664–665
25. Galetta KM, Calabresi PA, Frohman EM, Balcer LJ. Optical coherence tomography (OCT): imaging the visual pathway as a model for neurodegeneration. Neurotherapeutics. 2011;8:117–132
26. Petzold A, de Boer JF, Schippling S, Vermersch P, Kardon R, Green A, Calabresi PA, Polman C. Optical coherence tomography in multiple sclerosis: a systematic review and meta-analysis. Lancet Neurol. 2010;9:921–932
27. Barkhof F, Calabresi PA, Miller DH, Reingold SC. Imaging outcomes for neuroprotection and repair in multiple sclerosis trials. Nat Rev Neurol. 2009;5:256–266
28. Jindahra P, Hedges TR, Mendoza-Santiesteban CE, Plant GT. Optical coherence tomography of the retina: applications in neurology. Curr Opin Neurol. 2010;23:16–23
29. Lameril C, Newman N, Biousse V. The use of optical coherence tomography in neurology. Rev Neurol Dis. 2009;6:E105–E120
30. Sakata LM, Deleon-Ortega J, Sakata V, Girkin CA. Optical coherence tomography of the retina and optic nerve—a review. Clin Exp Ophthalmol. 2009;37:90–99
31. Glisson CC, Galetta SL. Nonconventional optic nerve imaging in multiple sclerosis. Neuroimag Clin N Am. 2009;19:71–79
32. Kallenbach K, Frederiksen J. Optical coherence tomography in optic neuritis and multiple sclerosis: a review. Eur J Neurol. 2007;14:841–849
33. Rudick R, Antel J, Confavreux C, Cutter G, Ellison G, Fischer J, Lublin F, Miller A, Petkau J, Rao S, Reingold S, Syndulko K, Thompson A, Wallenberg J, Weinshenker B, Willoughby E. Recommendations from the National Multiple Sclerosis Society Clinical Outcomes Assessment Task Force. Ann Neurol. 1997;42:379–382
34. Rudick R, Antel J, Confavreux C, Cutter G, Ellison G, Fischer J, Lublin F, Miller A, Petkau J, Rao S, Reingold S, Syndulko K, Thompson A, Wallenberg J, Weinshenker B, Willoughby E. Clinical outcomes assessment in multiple sclerosis. Ann Neurol. 1996;40:469–479
35. Miller DM, Rudick RA, Cutter G, Baier M, Fischer JS. Clinical significance of the multiple sclerosis functional composite: relationship to patient-reported quality of life. Arch Neurol. 2000;57:1319–1324
36. Rudick RA, Cutter G, Reingold S. The multiple sclerosis functional composite: a new clinical outcome measure for multiple sclerosis trials. Mult Scler. 2002;8:359–365
37. Ozakbas S, Ormeci B, Akdede BB, Alptekin K, Idiman E. Utilization of the auditory consonant trigram test to screen for cognitive impairment in patients with multiple sclerosis: comparison with the paced auditory serial addition test. Mult Scler. 2004;10:686–689
38. Rudick RA, Polman CH, Cohen JA, Walton MK, Miller AE, Confavreux C, Lublin FD, Hutchinson M, O'Connor PW, Schwid SR, Balcer LJ, Lynn F, Panzara MA, Sandrock AW. Assessing disability progression with the Multiple Sclerosis Functional Composite. Mult Scler. 2009;15:984–997
39. Ashworth B, Aspinall PA, Mitchell JD. Visual function in multiple sclerosis. Doc Ophthalmol. 1989;73:209–224
40. Bodis-Wollner I, Brannan JR. Hidden visual loss in optic neuropathy is revealed using Gabor patch contrast perimetry. Clin Neurosci. 1997;4:284–291
41. Regan D, Raymond J, Ginsburg AP, Murray TJ. Contrast sensitivity, visual acuity and the discrimination of Snellen letters in multiple sclerosis. Brain. 1981;104:333–350
42. Wender M. Value of Pelli-Robson contrast sensitivity chart for evaluation of visual system in multiple sclerosis patients. Neurol Neurochir Pol. 2007;41:141–143
43. Kupersmith MJ, Seiple WH, Nelson JI, Carr RE. Contrast sensitivity loss in multiple sclerosis. Selectivity by eye, orientation, and spatial frequency measured with the evoked potential. Invest Ophthalmol Vis Sci. 1984;25:632–639
44. Leat SJ, Legge GE, Bullimore MA. What is low vision? A re-evaluation of definitions. Optom Vis Sci. 1999;76:198–211
45. Balcer LJ, Baier ML, Pelak VS, Fox RJ, Shuwairi S, Galetta SL, Cutter GR, Maguire MG. New low-contrast vision charts: reliability and test characteristics in patients with multiple sclerosis. Mult Scler. 2000;6:163–171
46. Balcer LJ, Frohman EM. Evaluating loss of visual function in multiple sclerosis as measured by low-contrast letter acuity. Neurology. 2010;74(suppl 3):S16–S23
47. Talman LS, Bisker ER, Sackel DJ, Long DA Jr, Galetta KM, Ratchford JN, Lile DJ, Farrell SK, Loguidice MJ, Remington G, Conger A, Frohman TC, Jacobs DA, Markowitz CE, Cutter GR, Ying GS, Dai Y, Maguire MG, Galetta SL, Frohman EM, Calabresi PA, Balcer LJ. Longitudinal study of vision and retinal nerve fiber layer thickness in multiple sclerosis. Ann Neurol. 2010;67:749–760
48. Rosser DA, Cousens SN, Murdoch IE, Fitzke FW, Laidlaw DA. How sensitive to clinical change are ETDRS and logMAR visual acuity measurements? Invest Ophthalmol Vis Sci. 2003;44:3278–3281
49. Ma SL, Shea JA, Galetta SL, Jacobs DA, Markowitz CE, Maguire MG, Balcer LJ. Self-reported visual dysfunction in multiple sclerosis: new data from the VFQ-25 and development of an MS-specific vision questionnaire. Am J Ophthalmol. 2002;133:686–692
50. Raphael BA, Galetta KM, Jacobs DA, Markowitz CE, Liu GT, Nano-Schiavi ML, Galetta SL, Maguire MG, Mangione CM, Globe DR, Balcer LJ. Validation and test characteristics of a 10-item neuro-ophthalmic supplement to the NEI-VFQ-25. Am J Ophthalmol. 2006;142:1026–1035
51. Mowry EM, Loguidice MJ, Daniels AB, Jacobs DA, Markowitz CE, Galetta SL, Nano-Schiavi ML, Cutter GR, Maguire MG, Balcer LJ. Vision related quality of life in multiple sclerosis: correlation with new measures of low and high contrast letter acuity. J Neurol Neurosurg Psychiatry. 2009;80:767–772
52. Submacular Surgery Trials Research Group. . Evaluation of minimum clinically meaningful changes in scores on the National Eye Institute Visual Function Questionnaire (NEI-VFQ) SST Report Number 19. Ophthalmic Epidemiol. 2007;14:205–215
53. Submacular Surgery Trials Research Group. . Responsiveness of the National Eye Institute Visual Function Questionnaire to changes in visual acuity: findings in patients with subfoveal choroidal neovascularization—SST Report Number 1. Arch Ophthalmol. 2003;121:531–539
54. McKean-Cowdin R, Varma R, Wu J, Hays RD, Azen SPLos Angeles Latino Eye Study Group. . Severity of visual field loss and health-related quality of life. Am J Ophthalmol. 2007;143:1013–1023
55. Globe DR, Wu J, Azen SP, Varma RLos Angeles Latino Eye Study Group. . The impact of visual impairment on self-reported visual functioning in Latinos: The Los Angeles Latino Eye Study. Ophthalmology. 2004;111:1141–1149
56. Pineles SL, Birch EE, Talman LS, Sackel DJ, Frohman EM, Calabresi PA, Galetta SL, Maguire MG, Balcer LJ. One eye or two: a comparison of binocular and monocular low-contrast acuity testing in multiple sclerosis. Am J Ophthalmol. 2011;152:133–140
57. Newman NJ, Wolfe JM, Stewart MI, Lessell S. Binocular visual function in patients with a history of monocular optic neuritis. Clin Vis Sci. 1991;6:95–107
58. Wu GF, Schwartz ED, Lei T, Souza A, Mishra S, Jacobs DA, Markowitz CE, Galetta SL, Nano-Schiavi ML, Desiderio LM, Cutter GR, Calabresi PA, Udupa JK, Balcer LJ. Relation of vision to global and regional brain MRI in multiple sclerosis. Neurology. 2007;69:2128–2135
59. Kolappan M, Henderson AP, Jenkins TM, Wheeler-Kingshott CA, Plant GT, Thompson AJ, Miller DH. Assessing structure and function of the afferent visual pathway in multiple sclerosis and associated optic neuritis. J Neurol. 2009;256:305–319
60. Halliday AM, McDonald WI, Mushin J. Visual evoked response in diagnosis of multiple sclerosis. BMJ. 1973;4:661–664
61. Thurtell MJ, Bala E, Yaniglos SS, Rucker JC, Peachey NS, Leigh RJ. Evaluation of optic neuropathy in multiple sclerosis using low-contrast visual evoked potentials. Neurology. 2009;73:1849–1857
62. Laron M, Cheng H, Zhang B, Schiffman JS, Tang RA, Frishman LJ. Assessing visual pathway function in multiple sclerosis patients with multifocal visual evoked potentials. Mult Scler. 2009;15:1431–1441
63. Naismith RT, Tutlam NT, Xu J, Shepherd JB, Klawiter EC, Song SK, Cross AH. Optical coherence tomography is less sensitive than visual evoked potentials in optic neuritis. Neurology. 2009;73:46–52
64. Sepulcre J, Goñi J, Masdeu JC, Bejarano B, Vélez de Mendizábal N, Toledo JB, Villoslada P. Contribution of white matter lesions to gray matter atrophy in multiple sclerosis: evidence from voxel-based analysis of T1 lesions in the visual pathway. Arch Neurol. 2009;66:173–179
65. Ikuta F, Zimmerman HM. Distribution of plaques in seventy autopsy cases of multiple sclerosis in the United States. Neurology. 1976;26:26–28
66. Toussaint D, Périer O, Verstappen A, Bervoets S. Clinicopathological study of the visual pathways, eyes, and cerebral hemispheres in 32 cases of disseminated sclerosis. J Clin Neuro-Ophthalmol. 1983;3:211–220
67. Sisto D, Trojano M, Vetrugno M, Trabucco T, Iliceto G, Sborgia C. Subclinical visual involvement in multiple sclerosis: a study by MRI, VEPs, frequency-doubling perimetry, standard perimetry, and contrast sensitivity. Invest Ophthalmol Vis Sci. 2005;46:1264–1268
68. Lycke J, Tollesson PO, Frisén L. Asymptomatic visual loss in multiple sclerosis. J Neurol. 2001;248:1079–1086
69. Engell T, Trojaborg W, Raun NE. Subclinical optic neuropathy in multiple sclerosis. A neuro-ophthalmological investigation by means of visually evoked response, Farnworth-Munsell 100 Hue test and Ishihara test and their diagnostic value. Acta Ophthalmol (Copenh). 1987;65:735–740
70. Cheng H, Laron M, Schiffman JS, Tang RA, Frishman LJ. The relationship between visual field and retinal nerve fiber layer measurements in patients with multiple sclerosis. Invest Ophthalmol Vis Sci. 2007;48:5798–5805
71. Pulicken M, Gordon-Lipkin E, Balcer LJ, Frohman E, Cutter G, Calabresi PA. Optical coherence tomography and disease subtype in multiple sclerosis. Neurology. 2007;69:2085–2092
72. Costello F, Hodge W, Pan YI, Freedman M, DeMeulemeester C. Differences in retinal nerve fiber layer atrophy between multiple sclerosis subtypes. J Neurol Sci. 2009;281:74–79
73. Henderson AP, Trip SA, Schlottmann PG, Altmann DR, Garway-Heath DF, Plant GT, Miller DH. An investigation of the retinal nerve fibre layer in progressive multiple sclerosis using optical coherence tomography. Brain. 2008;131:277–287
74. Gordon-Lipkin E, Chodkowski B, Reich DS, Smith SA, Pulicken M, Balcer LJ, Frohman EM, Cutter G, Calabresi PA. Retinal nerve fiber layer is associated with brain atrophy in multiple sclerosis. Neurology. 2007;69:1603–1609
75. Sepulcre J, Murie-Fernandez M, Salinas-Alaman A, García-Layana A, Bejarano B, Villoslada P. Diagnostic accuracy of retinal abnormalities in predicting disease activity in MS. Neurology. 2007;68:1488–1494
76. Cettomai D, Pulicken M, Gordon-Lipkin E, Salter A, Frohman TC, Conger A, Zhang X, Cutter G, Balcer LJ, Frohman EM, Calabresi PA. Reproducibility of optical coherence tomography in multiple sclerosis. Arch Neurol. 2008;65:1218–1222
77. Zaveri MS, Conger A, Salter A, Frohman TC, Galetta SL, Markowitz CE, Jacobs DA, Cutter GR, Ying GS, Maguire MG, Calabresi PA, Balcer LJ, Frohman EM. Retinal imaging by laser polarimetry and optical coherence tomography evidence of axonal degeneration in multiple sclerosis. Arch Neurol. 2008;65:924–928
78. Salter AR, Conger A, Frohman TC, Zivadinov R, Eggenberger E, Calabresi P, Cutter G, Balcer L, Frohman EM. Retinal architecture predicts pupillary reflex metrics in MS. Mult Scler. 2008;15:479–486
79. Pueyo V, Ara JR, Almarcegui C, Martin J, Güerri N, García E, Pablo LE, Honrubia FM, Fernandez FJ. Sub-clinical atrophy of the retinal nerve fibre layer in multiple sclerosis. Acta Ophthalmol. 2010;88:748–752
80. Costello F, Hodge W, Pan YI, Metz L, Kardon RH. Retinal nerve fiber layer and future risk of multiple sclerosis. Can J Neurol Sci. 2008;35:482–487
81. Burkholder BM, Osborne B, Loguidice MJ, Bisker E, Frohman TC, Conger A, Ratchford JN, Warner C, Markowitz CE, Jacobs DA, Galetta SL, Cutter GR, Maguire MG, Calabresi PA, Balcer LJ, Frohman EM. Macular volume determined by optical coherence tomography as a measure of neuronal loss in multiple sclerosis. Arch Neurol. 2009;66:1366–1372
82. Syc SB, Warner CV, Hiremath GS, Farrell SK, Ratchford JN, Conger A, Frohman T, Cutter G, Balcer LJ, Frohman EM, Calabresi PA. Reproducibility of high-resolution optical coherence tomography in multiple sclerosis. Mult Scler. 2010;16:829–839
83. Kanamori A, Escano MF, Eno A, Nakamura M, Maeda H, Seya R, Ishibashi K, Negi A. Evaluation of the effect of aging on retinal nerve fiber layer thickness measured by optical coherence tomography. Ophthalmologica. 2003;217:273–278
84. Henderson APD, Altmann DR, Trip AS, Kallis C, Jones SJ, Schlottmann PG, Garway-Heath DF, Plant GT, Miller DH. A serial study of retinal changes following optic neuritis with sample size estimates for acute neuroprotection trials. Brain. 2010;133:2592–2602
85. Costello F, Hodge W, Pan YI, Eggenberger E, Freedman MS. Using retinal architecture to help characterize multiple sclerosis patients. Can J Ophthalmol. 2010;45:520–526
86. Bock M, Brandt AU, Kuchenbecker J, Dörr J, Pfueller CF, Weinges-Evers N, Gaede G, Zimmermann H, Bellmann-Strobl J, Ohlraun S, Zipp F, Paul F. Impairment of contrast visual acuity as a functional correlate of retinal nerve fibre layer thinning and total macular volume reduction in multiple sclerosis. Br J Ophthalmol. [published online ahead of print March 3, 2011] doi:10.1136/bjo.2010.193581
87. Merle H, Olindo S, Donnio A, Beral L, Richer R, Smadja D, Cabre P. Retinal nerve fiber layer thickness and spatial and temporal contrast sensitivity in multiple sclerosis. Eur J Ophthalmol. 2010;20:158–166
88. Galetta KM, Graves J, Talman LS, Lile DJ, Frohman EM, Calabresi PA, Galetta SL, Balcer LJ. Visual pathway loss in benign multiple sclerosis: a longitudinal study. J Neuroophthalmol. 2011 In press
89. Shiee N, Bazin PL, Ozturk A, Reich DS, Calabresi PA, Pham DL. A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions. NeuroImage. 2010;49:1524–1535
90. Filippi M, Rocca MA, Calabrese M, Sormani MP, Rinaldi F, Perini P, Comi G, Gallo P. Intracortical lesions: relevance for new MRI diagnostic criteria for multiple sclerosis. Neurology. 2010;75:1988–1994
91. Pitt D, Boster A, Pei W, Wohleb E, Jasne A, Zachariah CR, Rammohan K, Knopp MV, Schmalbrock P. Imaging cortical lesions in multiple sclerosis with ultra-high-field magnetic resonance imaging. Arch Neurol. 2010;67:812–818
92. Watson GM, Keltner JL, Chin EK, Harvey D, Nguyen A, Park SS. Comparison of retinal nerve fiber layer and central macular thickness measurements among five different optical coherence tomography instruments in patients with multiple sclerosis and optic neuritis. J Neuroophthalmol. 2011;31:110–116
93. Garcia-Martin E, Pinilla I, Idoipe M, Fuertes I, Pueyo V. Intra and inter-operator reproducibility of retinal nerve fiber and macular thickness measurements using Cirrus Fourier-domain OCT. Acta Ophthalmol. 2011;89:e23–e29
94. Sull AC, Vuong LN, Price LL, Srinivasan VJ, Gorczynska I, Fujimoto JG, Schuman JS, Duker JS. Comparison of spectral domain optical coherence tomography instruments for assessment of normal macular thickness. Retina. 2010;30:235–245
95. Wollstein G, Kagemann L, Bilonick RA, Ishikawa H, Folio LS, Gabriele ML, Ungar AK, Duker JS, Fujimoto JG, Schuman JS. Retinal nerve fibre layer and visual function loss in glaucoma: the tipping point. Br J Ophthalmol. [published online ahead of print April 8, 2011] doi:10.1136/bjo.2010.196907
96. Saidha S, Syc SB, Ibrahim MA, Eckstein C, Warner CV, Farrell SK, Oakley JD, Durbin MK, Meyer SA, Balcer LJ, Frohman EM, Rosenzweig JM, Newsome SD, Ratchford JN, Nguyen QD, Calabresi PA. Primary retinal pathology in multiple sclerosis as detected by optical coherence tomography. Brain. 2011;134:518–533
97. Davies EC, Galetta KM, Sackel DJ, Talman LS, Frohman EM, Calabresi PA, Galetta SL, Balcer LJ. Retinal ganglion cell layer volumetric assessment by spectral-domain optical coherence tomography in multiple sclerosis: application of a high-precision manual estimation technique. J Neuroophthalmol. 2011;31:260–264
98. Tan O, Li G, Lu AT, Varma R, Huang DAdvanced Imaging for Glaucoma Study Group. . Mapping of macular substructures with optical coherence tomography for glaucoma diagnosis. Ophthalmology. 2008;115:949–956
99. Tan O, Chopra V, Lu AT, Schuman JS, Ishikawa H, Wollstein G, Varma R, Huang D. Detection of macular ganglion cell loss in glaucoma by Fourier-domain optical coherence tomography. Ophthalmology. 2009;116:2305–2314
100. Ishikawa H, Stein DM, Wollstein G, Beaton S, Fujimoto JG, Schuman JS. Macular segmentation with optical coherence tomography. Invest Ophthalmol Vis Sci. 2005;46:2012–2017
101. Green A, McQuaid S, Hauser SL, Allen IV, Lyness R. Ocular pathology in multiple sclerosis: retinal atrophy and inflammation irrespective of disease duration. Brain. 2010;133:1591–1601
102. Shindler KS, Ventura E, Dutt M, Elliott P, Fitzgerald DC, Rostami A. Oral resveratrol reduces neuronal damage in a model of multiple sclerosis. J Neuroophthalmol. 2010;30:328–339
103. Walter SD, Ishikawa H, Galetta KM, Sakai RE, Feller DJ, Wilson JA, Maguire MG, Galetta SL, Frohman E, Calabresi PA, Schuman JS, Balcer LJ. Ganglion cell loss in relation to visual disability in multiple sclerosis. Mult Scler. Nov 2011 Suppl Abstract. In press
104. Keltner JL, Cello KE, Balcer LJ, Calabresi PA, Markowitz CE, Werner JS. Stratus OCT quality control in two multi-centre multiple sclerosis clinical trials. J Neuroophthalmol. 2011;35:57–64
105. Werner JS, Keltner JL, Zawadzki RJ, Choi SS. Outer retinal abnormalities associated with inner retinal pathology in nonglaucomatous and glaucomatous optic neuropathies. Eye. 2011;25:279–289