Discovery of the Biomarker Signature for Neuropathic Corneal Pain

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PROJECT ABSTRACT Neuropathic corneal pain (NCP) is an ocular type of neuropathic pain. It causes patients to have severe discomfort and a severely compromised quality of life (QoL). The lack of signs observed by standard examination has resulted in misdiagnosis as dry eye disease (DED) resulting in an inefficient use of healthcare funds. The identification of a diagnostic biomarker for NCP and development of a detection method would allow adequate and timely treatment, improve patients’ QoL, and decrease the health care system’s financial burden. An optical biopsy can be performed using laser in vivo confocal microscopy (IVCM), which allows for visualization of subbasal corneal nerves at a quasi-histological level. Preliminary data has shown that IVCM identified microneuromas (a bulb at the end of a severed nerve caused by build-up of molecular constituents) are present in NCP, but not DED, patients. We propose to validate microneuromas as a novel biomarker for NCP. In Aim 1 we will use our database of over 2,000 DED/NCP subjects and over 500,000 IVCM images to confirm that the presence of microneuromas is an appropriate biomarker for NCP by comparing the sensitivity and specificity of identification of NCP patients via microneuromas to other IVCM parameters. Three observers will each grade images twice for this confirmed biomarker to assess inter- and intra-observer precision, and descriptive statistics of the IVCM datasets will allow for determination of the minimum number of images necessary for high precision of microneuroma detection. Aim 2 will provide biological validation of microneuromas. Both the intensity of ocular pain and the compromise to QoL caused by ocular pain as assessed by the Ocular Pain Assessment Survey (OPAS) will be compared between those with microneuromas and those without. Further, the change in ocular pain/discomfort in response to instillation of hyperosmolar saline into the eyes will be compared between those with microneuromas and those without. In Aim 3 we will develop a validated artificial intelligence (AI) program for automated identification of microneuromas to allow rapid and wide-scale adoption by clinicians. Accuracy of the program will be determined by evaluating the agreement of the AI program’s assessment of IVCM images with the assessment of 2 observers. A similar assessment of accuracy will be assessed using images obtained from an independent site so that inter-site precision can be evaluated. The AI program will also be assessed for its specificity and sensitivity in NCP identification. Aim 4 will establish the clinical utility of microneuromas observed by IVCM as a biomarker for NCP in a prospective, multi-center study. The biomarker’s precision, reference intervals, and harmonization of performance between sites as well as the sensitivity and specificity of NCP diagnosis will be determined using this prospective cohort. Next, the microneuroma findings will be correlated with the OPAS and hyperosmolar functional tests for biological validation. Finally, the AI program’s ability to provide a diagnosis of NCP will be tested using the IVCM images from this study.