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A Window to Beyond the Orbit: the value of optical coherence tomography in non-ocular disease James R. Cameron 1 Andrew J. Tatham 2 1 Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK 2 Princess Alexandra Eye Pavilion, Edinburgh, UK Corresponding Author: Dr. James R Cameron MSc FRCOphth Anne Rowling Regenerative Neurology Clinic University of Edinburgh Chancellor’s Building 49 Little France Crescent Edinburgh EH16 4SB UK Tel: +44 (0)131 465 9500 Email: [email protected] Abstract: Optical coherence tomography (OCT) imaging of the eye has become an essential tool for the ophthalmologist, aiding diagnosis and assisting with treatment decisions, in many ocular diseases. However, there is an evolving role for OCT in informing on non-ocular diseases, which ophthalmologists should be aware of. The purpose of this review is to examine recent evidence for the role of ocular OCT imaging to evaluate disease beyond the orbit and to discuss possible opportunities and challenges arising from this, from the perspective of the ophthalmologist. Keywords: optical coherence tomography - retinal imaging - systemic disease – neurodegeneration – biomarker – glaucoma 1 Introduction Since first used to image the eye in 1991, optical coherence tomography (OCT) has become an integral tool for the diagnosis and management of a diverse range of ocular diseases, with the versatility of OCT providing the means to obtain quantitative information about the optic nerve head, macula and anterior segment. (Huang et al. 1991) The original technology of time domain OCT (TD-OCT) has been surpassed by newer generation spectral domain OCT (SD-OCT), which benefits from enhanced image quality due to improved spatial resolution and averaging of multiple images within each scan, made possible by a much faster scan speed. Increasingly sophisticated SD-OCT segmentation software has also become available that produces more accurate automated segmentation of inner retinal layers. (Mwanza et al. 2012) Although ophthalmologists are familiar with the many uses of OCT in ophthalmic disease, not all may be aware that OCT imaging of the eye is increasingly explored as a possible tool for identifying ocular biological markers of predominantly non-ophthalmic diseases, ranging from multiple sclerosis to cardiovascular disease. The purpose of this review is to examine recent evidence for the role of ocular OCT imaging to evaluate disease beyond the orbit and to discuss possible opportunities and challenges arising from this from the perspective of the ophthalmologist. 2 Methods A PubMed and Medline database search was performed on 20 September 2015 using the following search terms: ((((((((((“optical coherence tomography”[Title/Abstract]) NOT ("Eye Diseases"[Mesh])) AND English[Language]) NOT Review[Publication Type]) NOT Comment[Publication Type]) NOT animals[MeSH Terms]) NOT mice[MeSH Terms])))) AND ((eye OR retina OR macula OR "retinal nerve fiber layer")). This search yielded 2,059 results. Although searching with Medical Subject headings (MeSH terms) may exclude newer citations and articles that do not yet include MeSH subject terms, we avoided this problem by excluding rather than including articles based on MeSH terms. Therefore a manuscript describing an animal study without a MeSH term for animal would not have been excluded at this stage. Article titles were then manually reviewed and those relating primarily to ocular diseases (such as glaucoma or age-related macular degeneration) or studies in healthy subjects were excluded. Studies relating to use of OCT for non-ocular imaging or anterior segment imaging were also excluded. We also purposefully excluded animal studies, letters, comments, review articles and articles not published in English. We also excluded articles describing OCT in systemic diseases with well know ocular manifestations such as hypertension, diabetes and albinism. References of the articles retrieved from the above search were also manually scanned to identify additional studies. Details of the studies remaining after the search are summarised in Table 1. 3 Table 1. Summary of papers reporting OCT studies in non-ocular diseases from initial Pubmed search. Case Report Case-control / Cohort-study Random allocation Meta-analysis Multiple sclerosis 6 132 0 0 Neuromyelitis Optica 3 18 0 0 Dementia 0 12 0 3 Parkinson’s Disease 2 27 0 1 Multiple System Atrophy 0 5 0 0 Motor Neurone Disease 0 2 0 0 Autism 0 1 0 0 Traumatic brain injury 1 3 0 0 Chiasmal compression 2 6 0 0 Optic pathway glioma 0 2 0 0 Schizophrenia 0 2 0 0 Neurosarcoid 0 1 0 0 Stroke 0 3 0 0 Migraine 0 6 0 1 Cluster headache 0 1 0 0 Systemic lupus erythematosus 0 1 0 0 A selection process was used to determine which articles were suitable for inclusion in the review. Abstracts were retrieved for all studies collected in Table 1. Abstracts were reviewed for the quality of study design using the levels of evidence hierarchy described by the Oxford Centre for Evidence Based Medicine (OCEBM Levels of Evidence Working Group*. “The Oxford Levels of Evidence 2”. Oxford Centre for Evidence-Based Medicine. http://www.cebm.net/index.aspx?o=5653). Only the studies with the highest level of evidence for each disease category were retained. These were then compared for representative studies, across appropriate comparisons and correlations, to give the reader a fair consensus opinion of the current state of knowledge in this rapidly evolving subject area. For example, priority was given to papers utilising newer generation spectral-domain OCT, over previous generations. 4 Although retinal nerve fibre layer (RNFL) thickness is typically measured in the circumpapillary region, with the exact location dependant on the OCT device, more recently segmentation of the RNFL in the macula is possible. For simplicity throughout this article, when referring to RNFL thickness we refer to the circumpapillary RNFL. Review of Diseases It is in the field of neurodegenerative diseases that the use of OCT is seeing rapid uptake, as the technology has arrived at a time when there is a great unmet need for reliable and sensitive biomarkers of disease status. Not only do several of these conditions feature anterior visual pathway involvement - thus making OCT of the neuroretina a logical investigation but there is an increasing belief that many diseases of the brain will reflect their pathology in the eye, thus making it a unique entry point to directly visualise the central nervous system, both neural and vascular tissue. The concept of the retina being an anatomical and functional surrogate of the central brain is increasingly recognised. (MacGillivray et al. 2014) Therefore it is not only the neurodegenerative diseases of the central nervous system (CNS) that are under investigation, but diseases where either a retinopathy is described, or where there is a plausible hypothesis for retinal metrics to provide surrogate measures of CNS status. Multiple Sclerosis Multiple Sclerosis (MS) is a common neurological disease, characterised by recurrent inflammatory episodes within the CNS, causing demyelination with associated relapse symptoms, and ultimately neuronal loss and permanent functional disability. Existing radiological and clinical markers of disease assist in phenotypic diagnosis and disease course to a degree. However, the wide heterogeneity in the disease group necessitates a search for 5 better biomarkers of individuals, to more precisely track the gradient of disease, and provide an important metric of impact of disease-modifying treatments. With 138 publications, MS was by far the leading disease identified in our literature search. The first paper to investigate OCT as a potentially useful biomarker in the assessment of MS, alongside functional measures of vision, was published in 2006. (Fisher et al. 2006) This study reported reduced RNFL thickness in patient with MS - with and without a history of optic neuritis (ON) - with RNFL thickness correlated to visual acuity and contrast sensitivity. The same group have been leaders in this field, with a series of publications since. Important findings have included demonstration of a relationship between thinner RNFL and reduced magnetic resonance imaging (MRI)-measured brain parenchymal fraction (BPF) (GordonLipkin et al. 2007). Patients with MS have also been shown in longitudinal studies to experience progressive thinning of the RNFL with or without a prior history of ON, although patients with visual deterioration during follow-up seem to have greater loss of RNFL than those with stable vision. (Talman et al. 2010) Correlations with spinal cord MRI (Oh et al. 2015), and visual evoked potentials (VEPs) (Sriram et al. 2014) have further validated the importance of measuring RNFL thickness in these patients, and a recent review of vision-related outcome measures from a key author in the field has cemented the importance of OCT structural measures as a surrogate outcome in MS trials. (Balcer et al. 2015) The evolution of OCT technology has led to a surge of studies in MS over recent years, with more confidence and statistical certainty, thanks to the improved resolution and segmentation software. The ability to also measure the retinal ganglion cell layer has provided new insights into the temporal relationship of damage following ON. (Syc et al. 2012; Costello et al. 2015) In addition, longitudinal studies are confirming that progressive neuronal loss continues despite no clinically evident inflammation. (Narayanan et al. 2014) This is an excellent 6 example of clinical research now informing on the pathophysiology of disease, assisting in understanding the disease and suggesting new areas for basic research. Neuromyelitis Optica The second condition identified by our search was Neuromyelitis Optica (NMO), a clinical variant of MS, which has long been observed to frequently cause a more damaging insult to the optic nerve than the typical demyelinating optic neuritis seen in relapsing-remitting MS. (Ratchford et al. 2009; Monteiro et al. 2012) OCT has rapidly gained importance as a tool to quantify optic nerve damage in this condition, to the extent that it has been recommended by expert consensus, along with MRI of the brain and spinal cord, as an essential imaging modality. (Trebst et al. 2014) Dementia We identified 12 case-control/cohort studies and 3 meta-analyses examining the use of OCT in dementia. The dementias have a complex heterogeneous aetiology and are the focus of intense international research attention, with ocular imaging of particular interest. A recent meta-analysis on the utility of OCT in dementia concluded that measurement of RNFL thickness has potential utility in the diagnosis and discrimination of dementia types. (Thomson et al. 2015) To this end, there have been studies of OCT in Alzheimer’s Disease (Marziani et al. 2013; Polo et al. 2014) and Mild Cognitive Impairment (Shen et al. 2014), generally demonstrating retinal thinning, and in particular RNFL thinning associated with the disease. However, as has been learnt from glaucoma research, it is important to differentiate observed RNFL changes over time associated with disease from normal age-related decline. Of particular importance, a recent study has suggested that retinal changes may be visible before memory becomes affected, raising the possibility that OCT might be used to identify 7 patients that may benefit from early use of future neuroprotective treatments. (Garcia-Martin et al. 2014) Parkinson’s Disease Parkinson’s disease (PD) was the second most common condition identified by our literature search. However, evidence to support the use of OCT in PD is scanty. The earliest studies of OCT in PD reported no difference in RNFL thickness between cases and controls, but patients with PD were found to have thinner maculas, predominantly thought to be due to thinning of the outer retinal layers. (Aaker et al. 2010) Subsequent studies provided somewhat contradictory results with some reporting macular but not RNFL thinning (Mailankody et al. 2015) and others also finding thinner RNFL. (Satue et al. 2013; Satue et al. 2014) To complicate matters, a large case-control study which included 108 patients and 165 controls found no difference in RNFL or macula volume. (Bittersohl et al. 2015) Nevertheless, a recent meta-analysis concluded that OCT might be useful for monitoring PD progression. (Yu et al. 2014) Interestingly, one study has suggested that OCT might be useful for differentiating the atypical Parkinsonian syndromes, with 96% sensitivity and 70% specificity for differentiating between PD and progressive supranuclear palsy (PSP). (Albrecht et al. 2012) 8 The remaining conditions had relatively few published studies, with less than 10 articles identified for each. Multiple System Atrophy A recent paper described a case-control study of 24 patients with MSA and 35 controls. (Mendoza-Santiesteban et al. 2015) RNFL and GCL thicknesses were reduced in MSA compared to controls, particularly in the inferior quadrant, where the mean difference was around 10 microns. The same paper also included patients with PD, and found no significant difference between MSA and PD on OCT, except in the macula where the GCL thickness tended to be more reduced in PD than in MSA. Motor Neurone Disease Motor neurone disease (also known as amyotrophic lateral sclerosis) is traditionally understood to spare the anterior visual pathways, although non-motor neurone manifestations of the disease, such as cognitive change, are increasingly recognised. At present, there is no clear evidence for the utility of OCT in motor neurone disease, with two studies revealing contrasting results about whether or not there is any detectable retinal thinning associated with the disease. (Roth et al. 2013; Ringelstein et al. 2014) Although interestingly, the two studies used different OCT machines, and had slightly different criteria for selecting their patients. Autism Autism is a complex area of study, but one where there is again need for biomarkers of structural abnormality. A single paper (Emberti Gialloreti et al. 2014) looked at subjects with 9 high functioning autism (HFA) or Asperger Syndrome (AS), and found reduced global RNFL thickness in HFA compared with both AS subjects and controls. In addition, they found that the cognitive assessments of Verbal-IQ/performance-IQ discrepancy correlated with RNFL thickness. Traumatic brain injury Shaken Baby Syndrome (SBS) is well known to be associated with multi-layered retinal haemorrhages, but recently OCT studies have also revealed findings of vitreoretinal traction and macular hole. (Sturm et al. 2008; Scott et al. 2009) Hand-held OCT shows potential in being a useful clinical tool in this group, and may reveal more specific findings in the future. (Avery et al. 2014) Chiasmal compression Traditionally, pathologies causing compression of the chiasm (for example, pituitary adenoma, craniopharyngioma, suprasellar meningioma) have been monitored via radiological imaging and visual field testing. Recent work has suggested that RNFL and retinal ganglion cell (RGC) layer thinning assessed with SD-OCT correlate with the visual field (VF) loss. (Monteiro et al. 2014) OCT may therefore provide a more objective measure of disease status. In addition, it has been proposed that measuring RNFL thickness pre-operatively could be used to assess the prognosis of visual field recovery post-operatively, with a better visual prognosis for patients with a closer to normal RNFL thickness. (Garcia et al. 2014; DaneshMeyer et al. 2015; Park et al. 2015) 10 Optic pathway gliomas Whilst the natural history of OCT changes in optic pathway glioma has not been described, one report has suggested that RNFL analysis assessment using SD-OCT is superior to visual function assessment and optic disc evaluation as a clinical screening tool for optic pathway gliomas, in paediatric patients with neurofibromatosis-1. (Parrozzani et al. 2013) This was followed by a more recent paper supporting this view, reporting that children experiencing vision loss from optic pathway gliomas frequently demonstrated a ≥10% decline of RNFL thickness in 1 or more anatomic sectors. (Avery et al. 2015) Schizophrenia Psychiatric brain diseases have not been traditionally viewed as neurodegenerative in nature, but with MRI investigations now reporting some degree of gray and white matter atrophy in conditions like schizophrenia, a few groups have investigated OCT measures, as a surrogate measure of this. The first group looked at macula volume and RNFL thickness comparing schizophrenia and healthy controls. They found no overall difference between the groups, but within the patient group, there was an association between ‘positive symptom’ severity and reduced macular volume. (Chu et al. 2012) Another group, which recruited similar subjects, did find reduced RNFL thickness in schizophrenia, particularly in those with a longer duration of illness. (Lee et al. 2013) Neurosarcoid Ophthalmologists will be familiar with using OCT in the clinical assessment of ocular sarcoid, to visualise granulomas and markers of inflammation in the retina and choroid. (Wong et al. 2009; Gungor et al. 2014) However, even in the absence of ocular signs or 11 symptoms, RNFL and macula thinning has been reported in patients with neurosarcoid. (Eckstein et al. 2012) Stroke Much has been written about retinal manifestations of cerebrovascular disease, with recent work including findings of localised RNFL defects in patients with previous or acute stroke (Wang et al. 2014) and RNFL thinning after internal carotid artery (ICA) occlusion and middle cerebral artery (MCA) infarction. (Gunes et al. 2014) In addition, reduced macula ganglion cell complex layer thickness has been described in patients with homonymous hemianopia following PCA infarction. (Yamashita et al. 2012) Migraine Migraine has long been recognised as a risk factor for normal tension glaucoma. A recent study has examined the RNFL in patients with migraine without a diagnosis of glaucoma, and found some patients have a significant degree of RNFL thinning in the superior quadrant, compared with normal. (Gipponi et al. 2013) This is thought to be due to recurrent vasoconstriction in the supply to this area of the retina, causing permanent structural change. A meta-analysis of six case-control studies found a significant reduction in global RNFL thickness in migraine patients. (Feng et al. 2015) Cluster Headache We identified a single study examining OCT and cluster headache (CH), which included 107 patients with CH and 65 controls. Patients with CH were found to have significantly thinner temporal RNFL (mean difference 6 µm). (Ewering et al. 2015) The authors suggested that this observation might be due to the temporal RGC axons being more vulnerable to hypoxia, 12 as they are thinner - thus giving rise to this pattern of temporal loss, also seen in mitochondrial optic neuropathies. Systemic Lupus Erythematosus A single small study compared RNFL thickness in patients with systemic lupus erythematosus (SLE) (with and without neuropsychiatric symptoms) to healthy controls. Although there was no difference in RNFL between the SLE groups, both showed retinal thinning (full thickness and RNFL) compared to controls. (Liu et al. 2015) Patients with SLE had an average macular volume 0.30 mm3 less than controls, with an average 8µm thinner global RNFL thickness. The authors did not offer any hypothesis suggested for this observation. Discussion Our literature search and review has demonstrated a plethora of studies examining the possible application of OCT in neurological and systemic disease. RNFL thinning is a recurring theme, but few clear phenotypic patterns have emerged thus far. Most evidence exists for MS, with almost 140 studies identified. These have consistently shown temporal thinning, which has emerged as a sensitive biomarker of disease status, and now being used as an endpoint in trials of new treatments. It should however be emphasised that high quality studies are largely lacking, particularly given the multiple confounders known to influence quantitative measurements of retinal layers such as axial length, age and scan quality amongst others. Despite the limitations of current studies, interest in imaging the 13 eye, as a window to beyond the orbit, is likely to grow, with important implications for the ophthalmologist. Many ophthalmologists may have already had requests from neurologists for OCT in patients with MS and other conditions. As demonstrated by the wide range of diseases identified in this review, future requests may be forthcoming from other specialties. However, as the evidence-base for OCT grows, neurologists are increasingly seeking greater access to OCT, with some units purchasing their own device. With imaging training provided to nonophthalmologists by device manufacturers, there will be less dependence on ophthalmology departments for access to OCT. However, the use of OCT by non-ophthalmic trained individuals is likely to lead to an increase in referrals to ophthalmic services for investigation of incidental findings, a phenomenon already encountered with increasing use of OCT in the community by optometrists. There is however enormous potential for collaborative work between neurologists and ophthalmologists, with ophthalmologists already experienced in using OCT for diagnosis and monitoring progression in a good position to knowledge share. The growing number of studies providing evidence of abnormal retinal structural measurements in diseases viewed as predominantly non-ocular also has important implications for the management of ophthalmic disease. For example, RNFL thinning due to systemic or neurological diseases may complicate the management of glaucoma in which measurement of change in RNFL thickness over time is commonly used to detect progression. Particularly in the elderly population where comorbidity is common, a condition such as dementia, which has been reported to be associated with RNFL thinning, may introduce a potentially confounding factor to the assessment of glaucoma progression. On the other hand, the observation that diseases such as glaucoma and dementia have shared features raises the possibility that neuroprotective treatments effective for one disease may be utilised 14 for another. For example, neuroprotective and neuroregenerative treatments that aim to protect existing and regenerate damaged cells respectively may be effective for a range of diseases with heterogeneous mechanisms from Alzheimer’s disease to glaucoma. (Gupta & Yucel 2007; Johnson et al. 2011; Chang & Goldberg 2012) The ability to identify ocular biomarkers of systemic disease is an attractive prospect as the optical properties of the eye permit visualisation of vascular and neural tissues that is not possible in any other part of the body. The identification of ocular biomarkers of systemic and predominantly non-ocular disease is not a new concept and it is clear that many ocular diseases, such as diabetic retinopathy and arteritic ischemic optic neuropathy are a direct consequence of systemic pathology. In fact the diabetic retinopathy grading system is an excellent example of the use of ocular biomarkers for monitoring a systemic disease, with other useful diabetes biomarkers including HbA1c and blood pressure. The introduction of OCT has however, led to the realisation that an increasing number of conditions can have ocular manifestations, and it is possible to quantify these changes using imaging devices. There is therefore the possibility that OCT imaging might reduce the need for more invasive, time consuming or costly tests, for example reducing the need for MRI imaging of the brain to monitor for disease progression in multiple sclerosis. Measurements from OCT may be used for diagnoses, assessing disease progression, for predicting clinical outcomes, or for providing more acceptable and cost-effective ways to assess the effect of new treatments. In clinical trials, appropriately used biomarkers have the potential to replace or supplement conventional endpoints with something that can be measured earlier, more easily and more frequently. (Medeiros 2014) We should though exercise caution when considering introducing new biological markers, particularly if considering them for inclusion as endpoints in clinical trials or to base 15 decision-making regarding effectiveness of treatment. Few biomarkers fully capture the full effect of treatment, and this is particularly likely to be true for ocular biomarkers of systemic diseases. (Lesko & Atkinson 2001) Nevertheless, there is great hope that quantification of retinal parameters using OCT may be a useful surrogate for the assessment of a wide range of predominantly non-ocular dieases. Limitations of optical coherence tomography It is important to appreciate the limitations of OCT, which despite improvements in technology is still subject to poor scan quality, artefact and segmentation errors. Without appropriate training, non-ophthalmic specialists may refer patients to ophthalmologists based on anomalous OCT findings alone. For example, failures in accurate segmentation of retinal layers may lead to the erroneous conclusion that a patient has an ocular abnormality. However, this situation is the same for any imaging device or investigational procedure, any of which can lead to false positive referrals. Incidental abnormalities may also be identified in asymptomatic individuals. To aid diagnosis, imaging device software is often used to categorize patients as within normal limits, borderline, or outside normal limits. However, there are limitations of applying the built in normative databases to heterogeneous populations with complex systemic disease. The normative databases used to determine whether a patient is outside normal limits are comprised of relatively small numbers of patients and often specifically excludes those with other diseases. The databases also differ in size, eligibility criteria and ethnic makeup between manufacturers. (Realini et al. 2014) Normative databases are improving, however many consist primarily of Caucasian subjects, within a narrow age range and with limited refractive error. 16 Conclusion The growing interest among non-ophthalmic clinicians in ocular biomarkers derived from OCT has potential implications for ophthalmologists. There are exciting opportunities for collaborative work in this evolving arena, provided the limitations are understood. 17 References Aaker GD, Myung JS, Ehrlich JR, Mohammed M, Henchcliffe C & Kiss S (2010): Detection of retinal changes in Parkinson's disease with spectral-domain optical coherence tomography. Clin Ophthalmol 4: 1427-1432. Albrecht P, Muller AK, Sudmeyer M, Ferrea S, Ringelstein M, Cohn E, Aktas O, Dietlein T, Lappas A, Foerster A, Hartung HP, Schnitzler A & Methner A (2012): Optical coherence tomography in parkinsonian syndromes. PLoS One 7: e34891. Avery RA, Cnaan A, Schuman JS, Chen C-L, Glaug NC, Packer RJ, Quinn GE & Ishikawa H (2014): Reproducibility of Circumpapillary Retinal Nerve Fiber Layer Measurements Using Handheld Optical Coherence Tomography in Sedated Children. American Journal of Ophthalmology 158: 780-787.e781. Avery RA, Cnaan A, Schuman JS, Trimboli-Heidler C, Chen CL, Packer RJ & Ishikawa H (2015): Longitudinal Change of Circumpapillary Retinal Nerve Fiber Layer Thickness in Children With Optic Pathway Gliomas. Am J Ophthalmol 10.1016/j.ajo.2015.07.036. Balcer LJ, Miller DH, Reingold SC & Cohen JA (2015): Vision and vision-related outcome measures in multiple sclerosis. Brain 138: 11-27. Bittersohl D, Stemplewitz B, Keseru M, Buhmann C, Richard G & Hassenstein A (2015): Detection of retinal changes in idiopathic Parkinson's disease using high-resolution optical coherence tomography and heidelberg retina tomography. Acta Ophthalmol 10.1111/aos.12757. Chang EE & Goldberg JL (2012): Glaucoma 2.0: neuroprotection, neuroregeneration, neuroenhancement. Ophthalmology 119: 979-986. Chu EM, Kolappan M, Barnes TR, Joyce EM & Ron MA (2012): A window into the brain: an in vivo study of the retina in schizophrenia using optical coherence tomography. Psychiatry Res 203: 89-94. 18 Costello F, Pan YI, Yeh EA, Hodge W, Burton JM & Kardon R (2015): The temporal evolution of structural and functional measures after acute optic neuritis. J Neurol Neurosurg Psychiatry 10.1136/jnnp-2014-309704. Danesh-Meyer HV, Wong A, Papchenko T, Matheos K, Stylli S, Nichols A, Frampton C, Daniell M, Savino PJ & Kaye AH (2015): Optical coherence tomography predicts visual outcome for pituitary tumors. J Clin Neurosci 22: 1098-1104. Eckstein C, Saidha S, Sotirchos ES, Byraiah G, Seigo M, Stankiewicz A, Syc SB, Ford E, Sharma S, Calabresi PA & Pardo CA (2012): Detection of clinical and subclinical retinal abnormalities in neurosarcoidosis with optical coherence tomography. J Neurol 259: 1390-1398. Emberti Gialloreti L, Pardini M, Benassi F, Marciano S, Amore M, Mutolo MG, Porfirio MC & Curatolo P (2014): Reduction in retinal nerve fiber layer thickness in young adults with autism spectrum disorders. J Autism Dev Disord 44: 873-882. Ewering C, Hasal N, Alten F, Clemens CR, Eter N, Oberwahrenbrock T, Kadas EM, Zimmermann H, Brandt AU, Osada N, Paul F & Marziniak M (2015): Temporal retinal nerve fibre layer thinning in cluster headache patients detected by optical coherence tomography. Cephalalgia 35: 946-958. Feng YF, Guo H, Huang JH, Yu JG & Yuan F (2015): Retinal Nerve Fiber Layer Thickness Changes in Migraine: A Meta-Analysis of Case-Control Studies. Curr Eye Res: 1-9. 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 (2006): Relation of visual function to retinal nerve fiber layer thickness in multiple sclerosis. Ophthalmology 113: 324-332. Garcia-Martin ES, Rojas B, Ramirez AI, de Hoz R, Salazar JJ, Yubero R, Gil P, Trivino A & Ramirez JM (2014): Macular thickness as a potential biomarker of mild Alzheimer's disease. Ophthalmology 121: 1149-1151.e1143. Garcia T, Sanchez S, Litre CF, Radoi C, Delemer B, Rousseaux P, Ducasse A & Arndt C (2014): Prognostic value of retinal nerve fiber layer thickness for postoperative 19 peripheral visual field recovery in optic chiasm compression. J Neurosurg 121: 165169. Gipponi S, Scaroni N, Venturelli E, Forbice E, Rao R, Liberini P, Padovani A & Semeraro F (2013): Reduction in retinal nerve fiber layer thickness in migraine patients. Neurol Sci 34: 841-845. Gordon-Lipkin E, Chodkowski B, Reich DS, Smith SA, Pulicken M, Balcer LJ, Frohman EM, Cutter G & Calabresi PA (2007): Retinal nerve fiber layer is associated with brain atrophy in multiple sclerosis. Neurology 69: 1603-1609. Gunes A, Demirci S & Umul A (2014): Vision Loss and RNFL Thinning after Internal Carotid Arter Occlusion and Middle Cerebral Artery Infarction. Acta Inform Med 22: 413-414. Gungor SG, Akkoyun I, Reyhan NH, Yesilirmak N & Yilmaz G (2014): Choroidal thickness in ocular sarcoidosis during quiescent phase using enhanced depth imaging optical coherence tomography. Ocul Immunol Inflamm 22: 287-293. Gupta N & Yucel YH (2007): Glaucoma as a neurodegenerative disease. Curr Opin Ophthalmol 18: 110-114. Huang D, Swanson EA, Lin CP, Schuman JS, Stinson WG, Chang W, Hee MR, Flotte T, Gregory K, Puliafito CA & et al. (1991): Optical coherence tomography. Science 254: 1178-1181. Johnson TV, Bull ND & Martin KR (2011): Neurotrophic factor delivery as a protective treatment for glaucoma. Exp Eye Res 93: 196-203. Lee WW, Tajunisah I, Sharmilla K, Peyman M & Subrayan V (2013): Retinal nerve fiber layer structure abnormalities in schizophrenia and its relationship to disease state: evidence from optical coherence tomography. Invest Ophthalmol Vis Sci 54: 77857792. Lesko LJ & Atkinson AJ, Jr. (2001): Use of biomarkers and surrogate endpoints in drug development and regulatory decision making: criteria, validation, strategies. Annu Rev Pharmacol Toxicol 41: 347-366. 20 Liu GY, Utset TO & Bernard JT (2015): Retinal nerve fiber layer and macular thinning in systemic lupus erythematosus: an optical coherence tomography study comparing SLE and neuropsychiatric SLE. Lupus 24: 1169-1176. MacGillivray TJ, Trucco E, Cameron JR, Dhillon B, Houston JG & van Beek EJ (2014): Retinal imaging as a source of biomarkers for diagnosis, characterization and prognosis of chronic illness or long-term conditions. Br J Radiol 87: 20130832. Mailankody P, Battu R, Khanna A, Lenka A, Yadav R & Pal PK (2015): Optical coherence tomography as a tool to evaluate retinal changes in Parkinson's disease. Parkinsonism Relat Disord 21: 1164-1169. Marziani E, Pomati S, Ramolfo P, Cigada M, Giani A, Mariani C & Staurenghi G (2013): Evaluation of retinal nerve fiber layer and ganglion cell layer thickness in Alzheimer's disease using spectral-domain optical coherence tomography. Invest Ophthalmol Vis Sci 54: 5953-5958. Medeiros FA (2014): Biomarkers and surrogate endpoints in glaucoma clinical trials. Br J Ophthalmol 10.1136/bjophthalmol-2014-305550. Mendoza-Santiesteban CE, Palma JA, Martinez J, Norcliffe-Kaufmann L, Hedges TR, 3rd & Kaufmann H (2015): Progressive retinal structure abnormalities in multiple system atrophy. Mov Disord 10.1002/mds.26360. Monteiro ML, Fernandes DB, Apostolos-Pereira SL & Callegaro D (2012): Quantification of retinal neural loss in patients with neuromyelitis optica and multiple sclerosis with or without optic neuritis using Fourier-domain optical coherence tomography. Invest Ophthalmol Vis Sci 53: 3959-3966. Monteiro ML, Hokazono K, Fernandes DB, Costa-Cunha LV, Sousa RM, Raza AS, Wang DL & Hood DC (2014): Evaluation of inner retinal layers in eyes with temporal hemianopic visual loss from chiasmal compression using optical coherence tomography. Invest Ophthalmol Vis Sci 55: 3328-3336. Mwanza JC, Durbin MK, Budenz DL, Sayyad FE, Chang RT, Neelakantan A, Godfrey DG, Carter R & Crandall AS (2012): Glaucoma diagnostic accuracy of ganglion cell-inner 21 plexiform layer thickness: comparison with nerve fiber layer and optic nerve head. Ophthalmology 119: 1151-1158. Narayanan D, Cheng H, Bonem KN, Saenz R, Tang RA & Frishman LJ (2014): Tracking changes over time in retinal nerve fiber layer and ganglion cell-inner plexiform layer thickness in multiple sclerosis. Mult Scler 10.1177/1352458514523498. Oh J, Sotirchos ES, Saidha S, Whetstone A, Chen M, Newsome SD, Zackowski K, Balcer LJ, Frohman E, Prince J, Diener-West M, Reich DS & Calabresi PA (2015): Relationships between quantitative spinal cord MRI and retinal layers in multiple sclerosis. Neurology 10.1212/wnl.0000000000001257. Park HH, Oh MC, Kim EH, Kim CY, Kim SH, Lee KS & Chang JH (2015): Use of optical coherence tomography to predict visual outcome in parachiasmal meningioma. J Neurosurg 10.3171/2014.12.jns141549: 1-11. Parrozzani R, Clementi M, Kotsafti O, Miglionico G, Trevisson E, Orlando G, Pilotto E & Midena E (2013): Optical coherence tomography in the diagnosis of optic pathway gliomas. Invest Ophthalmol Vis Sci 54: 8112-8118. Polo V, Garcia-Martin E, Bambo MP, Pinilla J, Larrosa JM, Satue M, Otin S & Pablo LE (2014): Reliability and validity of Cirrus and Spectralis optical coherence tomography for detecting retinal atrophy in Alzheimer's disease. Eye (Lond) 28: 680-690. Ratchford JN, Quigg ME, Conger A, Frohman T, Frohman E, Balcer LJ, Calabresi PA & Kerr DA (2009): Optical coherence tomography helps differentiate neuromyelitis optica and MS optic neuropathies. Neurology 73: 302-308. Realini T, Zangwill LM, Flanagan JG, Garway-Heath D, Patella VM, Johnson CA, Artes PH, Gaddie IB & Fingeret M (2014): Normative Databases for Imaging Instrumentation. J Glaucoma 10.1097/ijg.0000000000000152. Ringelstein M, Albrecht P, Sudmeyer M, Harmel J, Muller AK, Keser N, Finis D, Ferrea S, Guthoff R, Schnitzler A, Hartung HP, Methner A & Aktas O (2014): Subtle retinal pathology in amyotrophic lateral sclerosis. Ann Clin Transl Neurol 1: 290-297. 22 Roth NM, Saidha S, Zimmermann H, Brandt AU, Oberwahrenbrock T, Maragakis NJ, Tumani H, Ludolph AC, Meyer T, Calabresi PA & Paul F (2013): Optical coherence tomography does not support optic nerve involvement in amyotrophic lateral sclerosis. Eur J Neurol 20: 1170-1176. Satue M, Garcia-Martin E, Fuertes I, Otin S, Alarcia R, Herrero R, Bambo MP, Pablo LE & Fernandez FJ (2013): Use of Fourier-domain OCT to detect retinal nerve fiber layer degeneration in Parkinson's disease patients. Eye (Lond) 27: 507-514. Satue M, Seral M, Otin S, Alarcia R, Herrero R, Bambo MP, Fuertes MI, Pablo LE & Garcia-Martin E (2014): Retinal thinning and correlation with functional disability in patients with Parkinson's disease. Br J Ophthalmol 98: 350-355. Scott AW, Farsiu S, Enyedi LB, Wallace DK & Toth CA (2009): Imaging the Infant Retina with a Hand-held Spectral-Domain Optical Coherence Tomography Device. American Journal of Ophthalmology 147: 364-373.e362. Shen Y, Liu L, Cheng Y, Feng W, Shi Z, Zhu Y, Wu W & Li C (2014): Retinal Nerve Fiber Layer Thickness is Associated with Episodic Memory Deficit in Mild Cognitive Impairment Patients. Curr Alzheimer Res. Sriram P, Wang C, Yiannikas C, Garrick R, Barnett M, Parratt J, Graham SL, Arvind H & Klistorner A (2014): Relationship between optical coherence tomography and electrophysiology of the visual pathway in non-optic neuritis eyes of multiple sclerosis patients. PLoS One 9: e102546. Sturm V, Landau K & Menke MN (2008): Optical Coherence Tomography Findings in Shaken Baby Syndrome. American Journal of Ophthalmology 146: 363-368. Syc SB, Saidha S, Newsome SD, Ratchford JN, Levy M, Ford E, Crainiceanu CM, Durbin MK, Oakley JD, Meyer SA, Frohman EM & Calabresi PA (2012): Optical coherence tomography segmentation reveals ganglion cell layer pathology after optic neuritis. Brain 135: 521-533. 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 23 PA & Balcer LJ (2010): Longitudinal study of vision and retinal nerve fiber layer thickness in multiple sclerosis. Ann Neurol 67: 749-760. Thomson KL, Yeo JM, Waddell B, Cameron JR & Pal S (2015): A systematic review and meta-analysis of retinal nerve fiber layer change in dementia, using optical coherence tomography. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring 1: 136-143. Trebst C, Jarius S, Berthele A, Paul F, Schippling S, Wildemann B, Borisow N, Kleiter I, Aktas O & Kumpfel T (2014): Update on the diagnosis and treatment of neuromyelitis optica: recommendations of the Neuromyelitis Optica Study Group (NEMOS). J Neurol 261: 1-16. Wang D, Li Y, Wang C, Xu L, You QS, Wang YX, Zhao L, Wei WB, Zhao X & Jonas JB (2014): Localized retinal nerve fiber layer defects and stroke. Stroke 45: 1651-1656. Wong M, Janowicz M, Tessler HH & Goldstein DA (2009): High-resolution optical coherence tomography of presumed sarcoid retinal granulomas. Retina 29: 15451546. Yamashita T, Miki A, Iguchi Y, Kimura K, Maeda F & Kiryu J (2012): Reduced retinal ganglion cell complex thickness in patients with posterior cerebral artery infarction detected using spectral-domain optical coherence tomography. Jpn J Ophthalmol 56: 502-510. Yu JG, Feng YF, Xiang Y, Huang JH, Savini G, Parisi V, Yang WJ & Fu XA (2014): Retinal nerve fiber layer thickness changes in Parkinson disease: a meta-analysis. PLoS One 9: e85718. 24