Small nerve fibre quantification in the diagnosis of diabetic sensorimotor polyneuropathy: comparing corneal confocal microscopy with intraepidermal nerve fibre density

OBJECTIVE: Quantitative assessment of small fiber damage is key to the early diagnosis and assessment of progression or regression of diabetic sensorimotor polyneuropathy (DSPN). Intraepidermal nerve fiber density (IENFD) is the current gold standard, but corneal confocal microscopy (CCM), an in vivo ophthalmic imaging modality, has the potential to be a noninvasive and objective image biomarker for identifying small fiber damage. The purpose of this study was to determine the diagnostic performance of CCM and IENFD by using the current guidelines as the reference standard. RESEARCH DESIGN AND METHODS: Eighty-nine subjects (26 control subjects and 63 patients with type 1 diabetes), with and without DSPN, underwent a detailed assessment of neuropathy, including CCM and skin biopsy. RESULTS: Manual and automated corneal nerve fiber density (CNFD) (P < 0.0001), branch density (CNBD) (P < 0.0001) and length (CNFL) (P < 0.0001), and IENFD (P < 0.001) were significantly reduced in patients with diabetes with DSPN compared with control subjects. The area under the receiver operating characteristic curve for identifying DSPN was 0.82 for manual CNFD, 0.80 for automated CNFD, and 0.66 for IENFD, which did not differ significantly (P = 0.14). CONCLUSIONS: This study shows comparable diagnostic efficiency between CCM and IENFD, providing further support for the clinical utility of CCM as a surrogate end point for DSPN

Corneal Confocal Microscopy Identifies Parkinson's Disease with More Rapid Motor Progression

From Wiley via Jisc Publications RouterHistory: received 2020-12-15, rev-recd 2021-03-11, accepted 2021-03-12, pub-electronic 2021-04-07, pub-print 2021-08Article version: VoRPublication status: PublishedFunder: Michael J Fox Foundation Trust (Grant ID 12059); Id: http://dx.doi.org/10.13039/100010269ABSTRACT: Background: Corneal confocal microscopy (CCM) is a noninvasive, reproducible ophthalmic technique to quantify corneal small nerve fiber degeneration. CCM demonstrates small nerve fiber damage in Parkinson's disease (PD), but its role as a longitudinal biomarker of PD progression has not been explored. Objective: The aim of this study was to assess corneal nerve morphology using CCM in relation to disease progression in PD. Methods: Sixty‐four participants with PD were assessed at baseline and at 12‐month follow‐up. Participants underwent CCM with automated corneal nerve quantification and assessment of Movement Disorder Society Unified Parkinson's Disease Rating Scale, Hoehn and Yahr stage, and Montreal Cognitive Assessment. Results: Corneal nerve fiber density (CNFD), corneal nerve branch density, corneal nerve fiber length, corneal total branch density, and corneal nerve fiber area were significantly lower in participants with PD compared with healthy control subjects. Worsening of Movement Disorder Society Unified Parkinson's Disease Rating Scale part III score over 12 months was significantly greater in participants with a CNFD in the lowest compared with the highest quartile at baseline (mean difference: 6.0; 95% CI: 1.0–10.9; P = 0.019). There were no significant changes in CNFD, corneal nerve branch density, corneal nerve fiber length, corneal total branch density, corneal nerve fiber area, or corneal nerve fiber width between baseline and 12‐month follow‐up. Conclusions: CCM identifies neurodegeneration in patients with PD, especially those who show the greatest progression in neurological disability. CCM may be a useful tool to help enrich clinical trials with those likely to exhibit more rapid progression and reduce required sample size and cost of studies. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Societ

Artificial Intelligence Based Analysis of Corneal Confocal Microscopy Images for Diagnosing Peripheral Neuropathy: A Binary Classification Model

Diabetic peripheral neuropathy (DPN) is the leading cause of neuropathy worldwide resulting in excess morbidity and mortality. We aimed to develop an artificial intelligence deep learning algorithm to classify the presence or absence of peripheral neuropathy (PN) in participants with diabetes or pre-diabetes using corneal confocal microscopy (CCM) images of the sub-basal nerve plexus. A modified ResNet-50 model was trained to perform the binary classification of PN (PN+) versus no PN (PN-) based on the Toronto consensus criteria. A dataset of 279 participants (149 PN-, 130 PN+) was used to train (n = 200), validate (n = 18), and test (n = 61) the algorithm, utilizing one image per participant. The dataset consisted of participants with type 1 diabetes (n = 88), type 2 diabetes (n = 141), and pre-diabetes (n = 50). The algorithm was evaluated using diagnostic performance metrics and attribution-based methods (gradient-weighted class activation mapping (Grad-CAM) and Guided Grad-CAM). In detecting PN+, the AI-based DLA achieved a sensitivity of 0.91 (95%CI: 0.79-1.0), a specificity of 0.93 (95%CI: 0.83-1.0), and an area under the curve (AUC) of 0.95 (95%CI: 0.83-0.99). Our deep learning algorithm demonstrates excellent results for the diagnosis of PN using CCM. A large-scale prospective real-world study is required to validate its diagnostic efficacy prior to implementation in screening and diagnostic programmes

Diagnosing and managing diabetic somatic and autonomic neuropathy

The diagnosis and management of diabetic neuropathy can be a major challenge. Late diagnosis contributes to significant morbidity in the form of painful diabetic neuropathy, foot ulceration, amputation, and increased mortality. Both hyperglycaemia and cardiovascular risk factors are implicated in the development of somatic and autonomic neuropathy and an improvement in these risk factors can reduce their rate of development and progression. There are currently no US Food and Drug Administration (FDA)-approved disease-modifying treatments for either somatic or autonomic neuropathy, as a consequence of multiple failed phase III clinical trials. While this may be partly attributed to premature translation, there are major shortcomings in trial design and outcome measures. There are a limited number of partially effective FDA-approved treatments for the symptomatic relief of painful diabetic neuropathy and autonomic neuropathy

Optimal Utility of H-Reflex RDD as a Biomarker of Spinal Disinhibition in Painful and Painless Diabetic Neuropathy

From MDPI via Jisc Publications RouterHistory: accepted 2021-07-07, pub-electronic 2021-07-12Publication status: PublishedFunder: American Diabetes Association; Grant(s): 1-17ICTS-062Impaired rate-dependent depression of the Hoffman reflex (HRDD) is a potential biomarker of impaired spinal inhibition in patients with painful diabetic neuropathy. However, the optimum stimulus-response parameters that identify patients with spinal disinhibition are currently unknown. We systematically compared HRDD, performed using trains of 10 stimuli at five stimulation frequencies (0.3, 0.5, 1, 2 and 3 Hz), in 42 subjects with painful and 62 subjects with painless diabetic neuropathy with comparable neuropathy severity, and 34 healthy controls. HRDD was calculated using individual and mean responses compared to the initial response. At stimulation frequencies of 1, 2 and 3 Hz, HRDD was significantly impaired in patients with painful diabetic neuropathy compared to patients with painless diabetic neuropathy for all parameters and for most parameters when compared to healthy controls. HRDD was significantly enhanced in patients with painless diabetic neuropathy compared to controls for responses towards the end of the 1 Hz stimulation train. Receiver operating characteristic curve analysis in patients with and without pain showed that the area under the curve was greatest for response averages of stimuli 2–4 and 2–5 at 1 Hz, AUC = 0.84 (95%CI 0.76–0.92). Trains of 5 stimuli delivered at 1 Hz can segregate patients with painful diabetic neuropathy and spinal disinhibition, whereas longer stimulus trains are required to segregate patients with painless diabetic neuropathy and enhanced spinal inhibition

Corneal nerve loss is related to the severity of painful diabetic neuropathy

From Wiley via Jisc Publications RouterHistory: received 2021-08-04, accepted 2021-09-26, pub-electronic 2021-10-13Article version: VoRPublication status: PublishedFunder: Seventh Framework Programme; Id: http://dx.doi.org/10.13039/501100004963; Grant(s): n°602273Abstract: Background and purpose: Previously it has been shown that patients with painful diabetic neuropathy (PDN) have greater corneal nerve loss compared to patients with painless diabetic neuropathy. This study investigated if the severity of corneal nerve loss was related to the severity of PDN. Methods: Participants with diabetic neuropathy (n = 118) and healthy controls (n = 38) underwent clinical and neurological evaluation, quantitative sensory testing, nerve conduction testing and corneal confocal microscopy and were categorized into those with no (n = 43), mild (n = 34) and moderate‐to‐severe (n = 41) neuropathic pain. Results: Corneal nerve fibre density (p = 0.003), corneal nerve fibre length (p < 0.0001) and cold perception threshold (p < 0.0001) were lower and warm perception threshold was higher (p = 0.002) in patients with more severe pain, but there was no significant difference in the neuropathy disability score (p = 0.5), vibration perception threshold (p = 0.5), sural nerve conduction velocity (p = 0.3) and amplitude (p = 0.7), corneal nerve branch density (p = 0.06) and deep breathing heart rate variability (p = 0.08) between patients with differing severity of PDN. The visual analogue scale correlated significantly with corneal nerve fibre density (r = −0.3, p = 0.0002), corneal nerve branch density (r = −0.3, p = 0.001) and corneal nerve fibre length (r = −0.4, p < 0.0001). Receiver operating curve analysis showed that corneal nerve fibre density had an area under the curve of 0.78 with a sensitivity of 0.73 and specificity of 0.72 for the diagnosis of PDN. Conclusions: Corneal confocal microscopy reveals increasing corneal nerve fibre loss with increasing severity of neuropathic pain and a good diagnostic outcome for identifying patients with PDN

Small Nerve Fiber Damage and Langerhans Cells in Type 1 and Type 2 Diabetes and LADA Measured by Corneal Confocal Microscopy.

PurposeIncreased corneal and epidermal Langerhans cells (LCs) have been reported in patients with diabetic neuropathy. The aim of this study was to quantify the density of LCs in relation to corneal nerve morphology and the presence of diabetic neuropathy and to determine if this differed in patients with type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), and latent autoimmune diabetes of adults (LADA).MethodsPatients with T1DM (n = 25), T2DM (n = 36), or LADA (n = 23) and control subjects (n = 23) underwent detailed assessment of peripheral neuropathy and corneal confocal microscopy. Corneal nerve fiber density (CNFD), branch density (CNBD), length (CNFL) and total, immature and mature LC densities were quantified.ResultsLower CNFD (P ConclusionsThis study shows significant corneal nerve loss and an increase in LC density in patients with T1DM, T2DM, and LADA. Furthermore, increased LC density correlated with corneal nerve loss in patients with T1DM

Small nerve fibre quantification in the diagnosis of diabetic sensorimotor polyneuropathy: comparing corneal confocal microscopy with intraepidermal nerve fibre density

OBJECTIVE: Quantitative assessment of small fiber damage is key to the early diagnosis and assessment of progression or regression of diabetic sensorimotor polyneuropathy (DSPN). Intraepidermal nerve fiber density (IENFD) is the current gold standard, but corneal confocal microscopy (CCM), an in vivo ophthalmic imaging modality, has the potential to be a noninvasive and objective image biomarker for identifying small fiber damage. The purpose of this study was to determine the diagnostic performance of CCM and IENFD by using the current guidelines as the reference standard. RESEARCH DESIGN AND METHODS: Eighty-nine subjects (26 control subjects and 63 patients with type 1 diabetes), with and without DSPN, underwent a detailed assessment of neuropathy, including CCM and skin biopsy. RESULTS: Manual and automated corneal nerve fiber density (CNFD) (P < 0.0001), branch density (CNBD) (P < 0.0001) and length (CNFL) (P < 0.0001), and IENFD (P < 0.001) were significantly reduced in patients with diabetes with DSPN compared with control subjects. The area under the receiver operating characteristic curve for identifying DSPN was 0.82 for manual CNFD, 0.80 for automated CNFD, and 0.66 for IENFD, which did not differ significantly (P = 0.14). CONCLUSIONS: This study shows comparable diagnostic efficiency between CCM and IENFD, providing further support for the clinical utility of CCM as a surrogate end point for DSPN

Corneal Confocal Microscopy to Image Small Nerve Fiber Degeneration: Ophthalmology Meets Neurology.

Neuropathic pain has multiple etiologies, but a major feature is small fiber dysfunction or damage. Corneal confocal microscopy (CCM) is a rapid non-invasive ophthalmic imaging technique that can image small nerve fibers in the cornea and has been utilized to show small nerve fiber loss in patients with diabetic and other neuropathies. CCM has comparable diagnostic utility to intraepidermal nerve fiber density for diabetic neuropathy, fibromyalgia and amyloid neuropathy and predicts the development of diabetic neuropathy. Moreover, in clinical intervention trials of patients with diabetic and sarcoid neuropathy, corneal nerve regeneration occurs early and precedes an improvement in symptoms and neurophysiology. Corneal nerve fiber loss also occurs and is associated with disease progression in multiple sclerosis, Parkinson's disease and dementia. We conclude that corneal confocal microscopy has good diagnostic and prognostic capability and fulfills the FDA criteria as a surrogate end point for clinical trials in peripheral and central neurodegenerative diseases