scholarly journals Corneal confocal microscopy detects small nerve fibre damage in patients with painful diabetic neuropathy

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Alise Kalteniece ◽  
Maryam Ferdousi ◽  
Shazli Azmi ◽  
Womba M. Mubita ◽  
Andrew Marshall ◽  
...  
Keyword(s):  
Confocal Microscopy ◽  
Diabetic Neuropathy ◽  
Nerve Fibre ◽  
Painful Diabetic Neuropathy ◽  
Corneal Confocal Microscopy ◽  
Small Nerve

scholarly journals An artificial intelligence-based deep learning algorithm for the diagnosis of diabetic neuropathy using corneal confocal microscopy: a development and validation study

Diabetologia ◽  
2019 ◽  
Vol 63 (2) ◽  
pp. 419-430 ◽  
Author(s):  
Bryan M. Williams ◽  
Davide Borroni ◽  
Rongjun Liu ◽  
Yitian Zhao ◽  
Jiong Zhang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Confocal Microscopy ◽  
Diabetic Neuropathy ◽  
Nerve Fibre ◽  
Learning Algorithm ◽  
Fibre Length ◽  
Branch Points ◽  
Deep Learning Algorithm ◽  
Corneal Confocal Microscopy ◽  
Corneal Nerve

Abstract Aims/hypothesis Corneal confocal microscopy is a rapid non-invasive ophthalmic imaging technique that identifies peripheral and central neurodegenerative disease. Quantification of corneal sub-basal nerve plexus morphology, however, requires either time-consuming manual annotation or a less-sensitive automated image analysis approach. We aimed to develop and validate an artificial intelligence-based, deep learning algorithm for the quantification of nerve fibre properties relevant to the diagnosis of diabetic neuropathy and to compare it with a validated automated analysis program, ACCMetrics. Methods Our deep learning algorithm, which employs a convolutional neural network with data augmentation, was developed for the automated quantification of the corneal sub-basal nerve plexus for the diagnosis of diabetic neuropathy. The algorithm was trained using a high-end graphics processor unit on 1698 corneal confocal microscopy images; for external validation, it was further tested on 2137 images. The algorithm was developed to identify total nerve fibre length, branch points, tail points, number and length of nerve segments, and fractal numbers. Sensitivity analyses were undertaken to determine the AUC for ACCMetrics and our algorithm for the diagnosis of diabetic neuropathy. Results The intraclass correlation coefficients for our algorithm were superior to those for ACCMetrics for total corneal nerve fibre length (0.933 vs 0.825), mean length per segment (0.656 vs 0.325), number of branch points (0.891 vs 0.570), number of tail points (0.623 vs 0.257), number of nerve segments (0.878 vs 0.504) and fractals (0.927 vs 0.758). In addition, our proposed algorithm achieved an AUC of 0.83, specificity of 0.87 and sensitivity of 0.68 for the classification of participants without (n = 90) and with (n = 132) neuropathy (defined by the Toronto criteria). Conclusions/interpretation These results demonstrated that our deep learning algorithm provides rapid and excellent localisation performance for the quantification of corneal nerve biomarkers. This model has potential for adoption into clinical screening programmes for diabetic neuropathy. Data availability The publicly shared cornea nerve dataset (dataset 1) is available at http://bioimlab.dei.unipd.it/Corneal%20Nerve%20Tortuosity%20Data%20Set.htm and http://bioimlab.dei.unipd.it/Corneal%20Nerve%20Data%20Set.htm.

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

2021 ◽  
Vol 2 ◽  
Author(s):  
Ioannis N. Petropoulos ◽  
Gulfidan Bitirgen ◽  
Maryam Ferdousi ◽  
Alise Kalteniece ◽  
Shazli Azmi ◽  
...  
Keyword(s):  
Confocal Microscopy ◽  
Diabetic Neuropathy ◽  
Nerve Fiber ◽  
Clinical Intervention ◽  
Nerve Fibers ◽  
Fiber Density ◽  
Corneal Confocal Microscopy ◽  
Intraepidermal Nerve Fiber Density ◽  
Corneal Nerve ◽  
Small Nerve

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.

scholarly journals Corneal confocal microscopy identifies small fibre damage and progression of diabetic neuropathy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shaishav Dhage ◽  
Maryam Ferdousi ◽  
Safwaan Adam ◽  
Jan Hoong Ho ◽  
Alise Kalteniece ◽  
...  
Keyword(s):  
Confocal Microscopy ◽  
Diabetic Neuropathy ◽  
Nerve Fibre ◽  
Fibre Length ◽  
Autonomic Nerve ◽  
Perception Threshold ◽  
Fibre Density ◽  
Symptom Profile ◽  
Corneal Confocal Microscopy ◽  
Patients With Diabetes

AbstractAccurately quantifying the progression of diabetic peripheral neuropathy is key to identify individuals who will progress to foot ulceration and to power clinical intervention trials. We have undertaken detailed neuropathy phenotyping to assess the longitudinal utility of different measures of neuropathy in patients with diabetes. Nineteen patients with diabetes (age 52.5 ± 14.7 years, duration of diabetes 26.0 ± 13.8 years) and 19 healthy controls underwent assessment of symptoms and signs of neuropathy, quantitative sensory testing, autonomic nerve function, neurophysiology, intra-epidermal nerve fibre density (IENFD) and corneal confocal microscopy (CCM) to quantify corneal nerve fibre density (CNFD), branch density (CNBD) and fibre length (CNFL). Mean follow-up was 6.5 years. Glycated haemoglobin (p = 0.04), low-density lipoprotein-cholesterol (LDL-C) (p = 0.0009) and urinary albumin creatinine ratio (p < 0.0001) improved. Neuropathy symptom profile (p = 0.03), neuropathy disability score (p = 0.04), vibration perception threshold (p = 0.02), cold perception threshold (p = 0.006), CNFD (p = 0.03), CNBD (p < 0.0001), CNFL (p < 0.0001), IENFD (p = 0.04), sural (p = 0.02) and peroneal motor nerve conduction velocity (p = 0.03) deteriorated significantly. Change (∆) in CNFL correlated with ∆CPT (p = 0.006) and ∆Expiration/Inspiration ratio (p = 0.002) and ∆IENFD correlated with ∆CNFD (p = 0.005), ∆CNBD (p = 0.02) and ∆CNFL (p = 0.01). This study shows worsening of diabetic neuropathy across a range of neuropathy measures, especially CCM, despite an improvement in HbA1c and LDL-C. It further supports the utility of CCM as a rapid, non-invasive surrogate measure of diabetic neuropathy.

scholarly journals Diagnostic utility of corneal confocal microscopy and intra-epidermal nerve fibre density in diabetic neuropathy

PLoS ONE ◽  
2017 ◽  
Vol 12 (7) ◽  
pp. e0180175 ◽  
Author(s):  
Uazman Alam ◽  
Maria Jeziorska ◽  
Ioannis N. Petropoulos ◽  
Omar Asghar ◽  
Hassan Fadavi ◽  
...  
Keyword(s):  
Confocal Microscopy ◽  
Diabetic Neuropathy ◽  
Nerve Fibre ◽  
Diagnostic Utility ◽  
Fibre Density ◽  
Corneal Confocal Microscopy

scholarly journals Early Detection of Diabetic Peripheral Neuropathy: A Focus on Small Nerve Fibres

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 165
Author(s):  
Jamie Burgess ◽  
Bernhard Frank ◽  
Andrew Marshall ◽  
Rashaad S. Khalil ◽  
Georgios Ponirakis ◽  
...  
Keyword(s):  
Peripheral Neuropathy ◽  
Nerve Fibre ◽  
Diabetic Peripheral Neuropathy ◽  
Point Of Care ◽  
Unmet Need ◽  
Screening Tools ◽  
Nerve Fibres ◽  
Diagnostic Laboratory ◽  
Corneal Confocal Microscopy ◽  
Small Nerve

Diabetic peripheral neuropathy (DPN) is the most common complication of both type 1 and 2 diabetes. As a result, neuropathic pain, diabetic foot ulcers and lower-limb amputations impact drastically on quality of life, contributing to the individual, societal, financial and healthcare burden of diabetes. DPN is diagnosed at a late, often pre-ulcerative stage due to a lack of early systematic screening and the endorsement of monofilament testing which identifies advanced neuropathy only. Compared to the success of the diabetic eye and kidney screening programmes there is clearly an unmet need for an objective reliable biomarker for the detection of early DPN. This article critically appraises research and clinical methods for the diagnosis or screening of early DPN. In brief, functional measures are subjective and are difficult to implement due to technical complexity. Moreover, skin biopsy is invasive, expensive and lacks diagnostic laboratory capacity. Indeed, point-of-care nerve conduction tests are convenient and easy to implement however questions are raised regarding their suitability for use in screening due to the lack of small nerve fibre evaluation. Corneal confocal microscopy (CCM) is a rapid, non-invasive, and reproducible technique to quantify small nerve fibre damage and repair which can be conducted alongside retinopathy screening. CCM identifies early sub-clinical DPN, predicts the development and allows staging of DPN severity. Automated quantification of CCM with AI has enabled enhanced unbiased quantification of small nerve fibres and potentially early diagnosis of DPN. Improved screening tools will prevent and reduce the burden of foot ulceration and amputations with the primary aim of reducing the prevalence of this common microvascular complication.

scholarly journals Using corneal confocal microscopy to compare Mecobalamin intramuscular injections vs oral tablets in treating diabetic peripheral neuropathy: a RCT

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuanjin Zhang ◽  
Dongsheng Fan ◽  
Yixuan Zhang ◽  
Shuo Zhang ◽  
Haikun Wang ◽  
...  
Keyword(s):  
Peripheral Neuropathy ◽  
Confocal Microscopy ◽  
Nerve Fibre ◽  
Diabetic Peripheral Neuropathy ◽  
Controlled Study ◽  
Oral Tablet ◽  
Injection Treatment ◽  
Intramuscular Injections ◽  
Corneal Confocal Microscopy ◽  
Corneal Nerve

AbstractThis randomized controlled study used corneal confocal microscopy (CCM) to compare the efficacy of Mecobalamin intramuscular injections vs oral tablets in treating mild to moderate diabetic peripheral neuropathy (DPN) by detecting early nerve fiber repair. Enrolled patients were randomized approximately 1:1 to receive Mecobalamin intramuscular injections (0.5 mg/day, 3 times/week) or Mecobalamin oral tablets (1.5 mg/day) for 8 weeks. Primary outcome was change of inferior whorl length (IWL) from baseline. Secondary outcomes included changes of corneal nerve fibre length (CNFL), corneal nerve fibre density (CNFD), corneal nerve branch density (CNBD) and the Survey of Autonomic Symptoms (SAS). 15 (93.75%) patients in the injection group and 17 (89.47%) patients in the tablet group completed the study. The injection treatment significantly improved patients’ IWL from baseline (21.64 ± 3.00 mm/mm2 vs 17.64 ± 4.83 mm/mm2, P < 0.01) while the tablet treatment didn’t. Additionally, the injection treatment led to significantly improved CNFL, CNBD and SAS from baseline (all P < 0.05) while the tablet treatment did not. No patient experienced any adverse events. In conclusion, CCM is sensitive enough to detect the superior efficacy of 8-week Mecobalamin intramuscular injection treatment for DPN compared to the oral tablet treatment.ClinicalTrials.gov registration number: NCT04372316 (30/04/2020).

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