The Reference Distribution of Annual Change in Corneal Nerve Fibre Length in Diabetes

AimsTo evaluate bilateral morphometric changes of corneal sub-basal nerve plexus (CSNP) occurring after unilateral cataract surgery by in vivo confocal microscopy (IVCM) images analysed with automated software.MethodsIVCM was performed before (V0) and 1 month after surgery (V1) in both operated eyes (OEs) and unoperated eyes (UEs) of 30 patients. Thirty age and sex-matched subjects acted as controls. Corneal nerve fibre density (CNFD), corneal nerve branch density (CNBD), corneal nerve fibre length (CNFL), corneal nerve total branch density (CTBD), corneal nerve fibre area (CNFA), corneal nerve fibre width, corneal nerve fractal dimension (CNFrD) and dendritic cells density were calculated.ResultsMean CNFD, CNBD, CNFL, CTBD, CNFA and CNFrD significantly decreased at V1 versus V0 in both eyes (respectively, 15.35±7.00 vs 21.21±6.56 n/mm2 in OEs and 20.11±6.69 vs 23.20±7.26 in UEs; 13.57±12.16 vs 26.79±16.91 n/mm2 in OEs and 24.28±14.88 vs 29.76±15.25 in UEs; 9.67±3.44 mm/mm2 vs 13.49±3.42 in OEs and 12.53±3.60 vs 14.02±3.82 in UEs; 22.81±18.77 vs 42.25±24.64 n/mm2 in OEs and 38.06±20.52 vs 43.93±22.27 in UEs; 0.0040±0.0021 vs 0.0058±0.0020 mm2/mm2 in OEs and 0.0049±0.0016 vs 0.0057±0.0019 in UEs; 1.418±0.058 vs 1.470±0.037 in OEs and 1.466±0.040 vs 1.477±0.036 in UEs; always p<0.049).ConclusionPatients undergoing cataract surgery exhibit bilateral alterations of CSNP. This finding could have broad implications in the setting of sequential cataract surgery.

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Reduced corneal nerve fibre length in prediabetes and type 2 diabetes: The Maastricht Study

Acta Ophthalmologica ◽

10.1111/aos.14359 ◽

2020 ◽

Vol 98 (5) ◽

pp. 485-491 ◽

Cited By ~ 1

Author(s):

Eline E.B. De Clerck ◽

Jan S.A.G. Schouten ◽

Tos T.J.M. Berendschot ◽

Renée S. Koolschijn ◽

Rudy M.M.A. Nuijts ◽

...

Keyword(s):

Type 2 Diabetes ◽

Nerve Fibre ◽

Fibre Length ◽

Corneal Nerve

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Exploring the optimal diagnostic threshold value of corneal nerve fibre length (CNFL) for diabetic neuropathy (DN) identification

Canadian Journal of Diabetes ◽

10.1016/j.jcjd.2017.08.172 ◽

2017 ◽

Vol 41 (5) ◽

pp. S62

Author(s):

Leif E. Lovblom ◽

Vera Bril ◽

Andrej Orszag ◽

Katie Edwards ◽

Nicola Pritchard ◽

...

Keyword(s):

Diabetic Neuropathy ◽

Nerve Fibre ◽

Fibre Length ◽

Threshold Value ◽

Diagnostic Threshold ◽

Corneal Nerve

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Corneal confocal microscopy identifies corneal nerve fibre loss and increased dendritic cells in patients with long COVID

British Journal of Ophthalmology ◽

10.1136/bjophthalmol-2021-319450 ◽

2021 ◽

pp. bjophthalmol-2021-319450

Author(s):

Gulfidan Bitirgen ◽

Celalettin Korkmaz ◽

Adil Zamani ◽

Ahmet Ozkagnici ◽

Nazmi Zengin ◽

...

Keyword(s):

Confocal Microscopy ◽

Nerve Fibre ◽

Fibre Length ◽

Neurological Symptoms ◽

University Hospital ◽

Nerve Branch ◽

Cross Sectional ◽

Corneal Confocal Microscopy ◽

Corneal Nerve ◽

Fibre Loss

Background/AimsLong COVID is characterised by a range of potentially debilitating symptoms which develop in at least 10% of people who have recovered from acute SARS-CoV-2 infection. This study has quantified corneal sub-basal nerve plexus morphology and dendritic cell (DC) density in patients with and without long COVID.MethodsForty subjects who had recovered from COVID-19 and 30 control participants were included in this cross-sectional comparative study undertaken at a university hospital. All patients underwent assessment with the National Institute for Health and Care Excellence (NICE) long COVID, Douleur Neuropathique 4 (DN4) and Fibromyalgia questionnaires, and corneal confocal microscopy (CCM) to quantify corneal nerve fibre density (CNFD), corneal nerve branch density (CNBD), corneal nerve fibre length (CNFL), and total, mature and immature DC density.ResultsThe mean time after the diagnosis of COVID-19 was 3.7±1.5 months. Patients with neurological symptoms 4 weeks after acute COVID-19 had a lower CNFD (p=0.032), CNBD (p=0.020), and CNFL (p=0.012), and increased DC density (p=0.046) compared with controls, while patients without neurological symptoms had comparable corneal nerve parameters, but increased DC density (p=0.003). There were significant correlations between the total score on the NICE long COVID questionnaire at 4 and 12 weeks with CNFD (ρ=−0.436; p=0.005, ρ=−0.387; p=0.038, respectively) and CNFL (ρ=−0.404; p=0.010, ρ=−0.412; p=0.026, respectively).ConclusionCorneal confocal microscopy identifies corneal small nerve fibre loss and increased DCs in patients with long COVID, especially those with neurological symptoms. CCM could be used to objectively identify patients with long COVID.

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Diagnosis of neuropathy and risk factors for corneal nerve loss in type 1 and type 2 diabetes: A corneal confocal microscopy study

10.2337/figshare.13020023.v1 ◽

2020 ◽

Author(s):

Maryam Ferdousi ◽

Alise Kalteniece ◽

Shazli Azmi ◽

Ioannis N Petropoulos ◽

Georgios Ponirakis ◽

...

Keyword(s):

Risk Factors ◽

Type 2 Diabetes ◽

Type 1 Diabetes ◽

Peripheral Neuropathy ◽

Nerve Fibre ◽

Fibre Length ◽

Corneal Confocal Microscopy ◽

Corneal Nerve

Purpose: To assess the diagnostic utility of corneal confocal microscopy (CCM) for diabetic peripheral neuropathy (DPN) and the risk factors for corneal nerve loss. Methods: 490 participants including 72 healthy controls, 149 with type 1 diabetes and 269 with type 2 diabetes underwent detailed assessment of peripheral neuropathy and CCM in relation to risk factors. Results: Corneal nerve fibre density (CNFD) (P<0.0001, P<0.0001), branch density (CNBD) (P<0.0001, P<0.0001) and length (CNFL) (P<0.0001, P=0.02) were significantly lower in patients with type 1 and type 2 diabetes, compared to controls. CNFD (P<0.0001), CNBD (P<0.0001) and CNFL (P<0.0001) were lower in type 1 diabetes compared to type 2 diabetes. Receiver operating characteristics (ROC) curve analysis for the diagnosis of DPN demonstrated a good area under the curve (AUC) for CNFD=0.81, CNBD=0.74 and CNFL=0.73. Multivariable regression analysis showed a significant association between reduced corneal nerve fibre length with age (β=-0.27, P=0.007), HbA1c (β=-1.1, P=0.01) and weight (β=-0.14, P=0.03) in patients with type 2 diabetes and with duration of diabetes (β=-0.13, P=0.02), LDL cholesterol (β=1.8, P=0.04), and triglycerides (β=-2.87, P=0.009) in patients with type 1 diabetes. Conclusion: CCM identifies more severe corneal nerve loss in patients with type 1 compared to type 2 diabetes and shows good diagnostic accuracy for DPN. Furthermore, the risk factors for a reduction in corneal nerve fibre length differ between type 1 and type 2 diabetes.

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Distal Corneal Small Nerve Fibre Damage in Subjects With Obesity

10.21203/rs.3.rs-846102/v1 ◽

2021 ◽

Author(s):

Zohaib Iqbal ◽

Maryam Ferdousi ◽

Alise Kalteniece ◽

Safwaan Adam ◽

Jan H. Ho ◽

...

Keyword(s):

Nerve Fibre ◽

Fibre Length ◽

Relative Reduction ◽

Symptom Profile ◽

Corneal Confocal Microscopy ◽

Corneal Nerves ◽

Obese Subjects ◽

Corneal Nerve ◽

Vibration Perception ◽

Dying Back

Abstract Background: We have previously shown that subjects with obesity have elevated vibration and thermal perception thresholds and central corneal nerve loss and patients with diabetic neuropathy have greater corneal nerve loss at the inferior whorl compared to the central cornea. In the current study, we assessed whether there is evidence for a dying-back neuropathy in subjects with obesity with and without diabetes. Methods: 57 obese subjects, with and without diabetes (DM+, n=30; DM-, n=27 respectively) and age- and sex‑matched controls (n=21) underwent venous blood sampling and assessment of the neuropathy symptom profile (NSP), neuropathy disability score (NDS), vibration, cold and warm threshold testing, cardiac autonomic function, and corneal confocal microscopy (CCM).Results: NSP and NDS were significantly elevated in obese DM+ (p<0.0001; p=0.001) and DM- (p<0.0001; p=0.001) subjects compared to controls. Vibration perception threshold was significantly higher in DM+ (p=0.001), but not in DM- (p=0.06), compared to controls, whilst cold (p = 0.87) and warm (p = 0.52) perception thresholds did not differ between groups. Deep breathing heart rate variability was significantly lower in DM+ (p=0.01), but not DM- (p=0.9) subjects compared to controls. Corneal nerve fibre density [26.8 ±6.22 vs 26.8 ±6.01 vs 35.3 ±7.41, p<0.0001], branch density [55.4 ±28.2 vs 58.4 ±28.5 vs 88.2 ±31.1, p<0.001], fibre length (CNFL) [17.6 ±4.43 vs 19.9 ±5.43 vs 26.7 ±5.31, p <0.0001], inferior whorl length (IWL) [17.9 ±6.10 vs 18.6 ±7.42 vs 35.3 ±9.70, p<0.0001] and total nerve fibre length (TNFL) [35.5 ±9.58 vs 38.5 ±11.0 vs 62.0 ±12.3, p<0.0001] were significantly lower in obese subjects without and with diabetes compared to controls. In comparison to controls, there was a greater relative reduction in IWL compared to CNFL in DM+ (47.3% vs 25.5%) and DM- (49.3% vs 34.1%).Conclusion: We demonstrate evidence of peripheral neuropathy characterised by neuropathic symptoms, neurological deficits, elevated vibration perception and autonomic dysfunction with a dying-back neuropathy affecting the corneal nerves in obese subjects with and without type 2 diabetes.

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

Diabetologia ◽

10.1007/s00125-019-05023-4 ◽

2019 ◽

Vol 63 (2) ◽

pp. 419-430 ◽

Cited By ~ 10

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.

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15 - Prediction of Future Neuropathy Onset Using Corneal Nerve Fibre Length (CNFL): A Longitudinal Multinational Consortium Study

Canadian Journal of Diabetes ◽

10.1016/j.jcjd.2019.07.022 ◽

2019 ◽

Vol 43 (7) ◽

pp. S7

Author(s):

Leif Erik Lovblom ◽

Bruce A. Perkins ◽

Vera Bril ◽

Maryam Ferdousi ◽

Andrej Orszag ◽

...

Keyword(s):

Nerve Fibre ◽

Fibre Length ◽

Corneal Nerve

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Diagnosis of neuropathy and risk factors for corneal nerve loss in type 1 and type 2 diabetes: A corneal confocal microscopy study

10.2337/figshare.13020023 ◽

2020 ◽

Author(s):

Maryam Ferdousi ◽

Alise Kalteniece ◽

Shazli Azmi ◽

Ioannis N Petropoulos ◽

Georgios Ponirakis ◽

...

Keyword(s):

Risk Factors ◽

Type 2 Diabetes ◽

Type 1 Diabetes ◽

Peripheral Neuropathy ◽

Nerve Fibre ◽

Fibre Length ◽

Corneal Confocal Microscopy ◽

Corneal Nerve

Purpose: To assess the diagnostic utility of corneal confocal microscopy (CCM) for diabetic peripheral neuropathy (DPN) and the risk factors for corneal nerve loss. Methods: 490 participants including 72 healthy controls, 149 with type 1 diabetes and 269 with type 2 diabetes underwent detailed assessment of peripheral neuropathy and CCM in relation to risk factors. Results: Corneal nerve fibre density (CNFD) (P<0.0001, P<0.0001), branch density (CNBD) (P<0.0001, P<0.0001) and length (CNFL) (P<0.0001, P=0.02) were significantly lower in patients with type 1 and type 2 diabetes, compared to controls. CNFD (P<0.0001), CNBD (P<0.0001) and CNFL (P<0.0001) were lower in type 1 diabetes compared to type 2 diabetes. Receiver operating characteristics (ROC) curve analysis for the diagnosis of DPN demonstrated a good area under the curve (AUC) for CNFD=0.81, CNBD=0.74 and CNFL=0.73. Multivariable regression analysis showed a significant association between reduced corneal nerve fibre length with age (β=-0.27, P=0.007), HbA1c (β=-1.1, P=0.01) and weight (β=-0.14, P=0.03) in patients with type 2 diabetes and with duration of diabetes (β=-0.13, P=0.02), LDL cholesterol (β=1.8, P=0.04), and triglycerides (β=-2.87, P=0.009) in patients with type 1 diabetes. Conclusion: CCM identifies more severe corneal nerve loss in patients with type 1 compared to type 2 diabetes and shows good diagnostic accuracy for DPN. Furthermore, the risk factors for a reduction in corneal nerve fibre length differ between type 1 and type 2 diabetes.

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