scholarly journals Combining In Vivo Corneal Confocal Microscopy with Deep Learning-based Analysis Reveals Sensory Nerve Fiber Loss in Acute SIV Infection

2020 ◽  
Author(s):  
Megan E. McCarron ◽  
Rachel L. Weinberg ◽  
Jessica M. Izzi ◽  
Suzanne E. Queen ◽  
Stuti L. Misra ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Deep Learning ◽  
Confocal Microscopy ◽  
Nerve Fiber ◽  
Fiber Length ◽  
Sensory Nerve ◽  
Corneal Confocal Microscopy ◽  
Siv Infection ◽  
Corneal Nerve

AbstractPurposeTo characterize corneal subbasal nerve plexus morphologic features using in vivo corneal confocal microscopy (IVCM) in normal and SIV-infected macaques and to implement automated assessments using novel deep learning-based methods customized for macaque studies.MethodsIn vivo corneal confocal microscopy images were collected from both male and female age-matched specific-pathogen free rhesus and pigtailed macaques housed at the Johns Hopkins University breeding colony using the Heidelberg HRTIII with Rostock Corneal Module. We also obtained repeat IVCM images of 12 SIV-infected animals including pre-infection and 10 day post-SIV infection time-points. All IVCM images were analyzed using a novel deep convolutional neural network architecture developed specifically for macaque studies.ResultsDeep learning-based segmentation of subbasal nerves in IVCM images from macaques demonstrated that corneal nerve fiber length (CNFL) and fractal dimension measurements did not differ between species, but pigtailed macaques had significantly higher baseline corneal nerve fiber tortuosity than rhesus macaques (P = 0.005). Neither sex nor age of macaques was associated with differences in any of the assessed corneal subbasal nerve parameters. In the SIV/macaque model of HIV, acute SIV infection induced significant decreases in both corneal nerve fiber length and fractal dimension (P= 0.01 and P= 0.008 respectively).ConclusionsThe combination of IVCM and objective, robust, and rapid deep-learning analysis serves as a powerful noninvasive research and clinical tool to track sensory nerve damage, enabling early detection of neuropathy. Adapting the deep-learning analyses to human corneal nerve assessments will refine our ability to predict and monitor damage to small sensory nerve fibers in a number of clinical settings including HIV, multiple sclerosis, Parkinson’s disease, diabetes, and chemotherapeutic neurotoxicity.

scholarly journals Early Alterations of Corneal Subbasal Plexus in Uncomplicated Type 1 Diabetes Patients

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Domenico Schiano Lomoriello ◽  
Irene Abicca ◽  
Mariacristina Parravano ◽  
Daniela Giannini ◽  
Benedetta Russo ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Diabetic Retinopathy ◽  
Confocal Microscopy ◽  
Nerve Fiber ◽  
Fiber Length ◽  
Diabetes Complications ◽  
Corneal Confocal Microscopy ◽  
Subbasal Nerve Plexus

Purpose. The purpose of our study is to describe the in vivo corneal confocal microscopy characteristics of subbasal nerve plexus in a highly selected population of patients affected by type 1 diabetes mellitus (T1DM) without any microvascular diabetes complications.Methods. We included 19 T1DM patients without diabetic peripheral neuropathy, diabetic autonomic neuropathy, diabetic retinopathy, and microalbuminuria. All patients underwent in vivo corneal confocal microscopy and blood analysis to determine subbasal nerve plexus parameters and their correlation with clinical data. We compared the results with 19 healthy controls.Results. The T1DM group showed a significant decrease of the nerve fiber length (P=0.032), the nerve fiber length density (P=0.034), the number of fibers (P=0.005), and the number of branchings (P=0.028), compared to healthy subjects. The nerve fiber length, nerve fiber length density, and number of fibers were directly related to the age at onset of diabetes and inversely to the duration of DM. BMI (body mass index) was highly related to the nerve fiber length (r = −0.6,P=0.007), to the nerve fiber length density (r = −0.6,P=0.007), and to the number of fibers (r = −0.587,P=0.008). No significant correlations were found between the corneal parameters and HbA1c.Conclusions. Early subclinical fiber corneal variation could be easily detected using in vivo corneal confocal microscopy, even in type 1 diabetes without any microvascular diabetes complications, including diabetic peripheral neuropathy, diabetic autonomic neuropathy, diabetic retinopathy, and microalbuminuria.

scholarly journals Corneal confocal microscopy demonstrates axonal loss in different courses of multiple sclerosis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ioannis N. Petropoulos ◽  
Kathryn C. Fitzgerald ◽  
Jonathan Oakley ◽  
Georgios Ponirakis ◽  
Adnan Khan ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Confocal Microscopy ◽  
Nerve Fiber ◽  
Clinically Isolated Syndrome ◽  
Axonal Loss ◽  
Fiber Density ◽  
Corneal Confocal Microscopy ◽  
Segmentation Methods ◽  
Relapsing Remitting ◽  
Corneal Nerve

AbstractAxonal loss is the main determinant of disease progression in multiple sclerosis (MS). This study aimed to assess the utility of corneal confocal microscopy (CCM) in detecting corneal axonal loss in different courses of MS. The results were confirmed by two independent segmentation methods. 72 subjects (144 eyes) [(clinically isolated syndrome (n = 9); relapsing–remitting MS (n = 20); secondary-progressive MS (n = 22); and age-matched, healthy controls (n = 21)] underwent CCM and assessment of their disability status. Two independent algorithms (ACCMetrics; and Voxeleron deepNerve) were used to quantify corneal nerve fiber density (CNFD) (ACCMetrics only), corneal nerve fiber length (CNFL) and corneal nerve fractal dimension (CNFrD). Data are expressed as mean ± standard deviation with 95% confidence interval (CI). Compared to controls, patients with MS had significantly lower CNFD (34.76 ± 5.57 vs. 19.85 ± 6.75 fibers/mm2, 95% CI − 18.24 to − 11.59, P < .0001), CNFL [for ACCMetrics: 19.75 ± 2.39 vs. 12.40 ± 3.30 mm/mm2, 95% CI − 8.94 to − 5.77, P < .0001; for deepNerve: 21.98 ± 2.76 vs. 14.40 ± 4.17 mm/mm2, 95% CI − 9.55 to − 5.6, P < .0001] and CNFrD [for ACCMetrics: 1.52 ± 0.02 vs. 1.45 ± 0.04, 95% CI − 0.09 to − 0.05, P < .0001; for deepNerve: 1.29 ± 0.03 vs. 1.19 ± 0.07, 95% − 0.13 to − 0.07, P < .0001]. Corneal nerve parameters were comparably reduced in different courses of MS. There was excellent reproducibility between the algorithms. Significant corneal axonal loss is detected in different courses of MS including patients with clinically isolated syndrome.

scholarly journals A novel investigation method for axonal damage in neuromyelitis optica spectrum disorder: In vivo corneal confocal microscopy

2021 ◽  
Vol 7 (1) ◽  
pp. 205521732199806
Author(s):  
Ayşe Altıntaş ◽  
Ayse Yildiz-Tas ◽  
Sezen Yilmaz ◽  
Betul N Bayraktutar ◽  
Melis Cansu Comert ◽  
...  
Keyword(s):  
Confocal Microscopy ◽  
Nerve Fibre ◽  
Disease Severity ◽  
Neuromyelitis Optica ◽  
Spectrum Disorder ◽  
Neuromyelitis Optica Spectrum Disorder ◽  
Rnfl Thickness ◽  
Corneal Confocal Microscopy ◽  
Corneal Nerve

Background Neuromyelitis optica spectrum disorder (NMOSD) is an inflammatory autoimmune disorder that damages optic nerves, brainstem, and spinal cord. In vivo corneal confocal microscopy (IVCM) is a noninvasive technique that provides corneal images with dendritic cells (DCs) and corneal subbasal nerve plexus (SBP), which arises from the trigeminal nerve. Objective We investigated corneal SBP changes in NMOSD and proposed IVCM as a potential new disease severity biomarker for NMOSD. Methods Seventeen age-sex matched NMOSD patients and 19 healthy participants underwent complete neurologic and ophthalmologic examinations. The duration of disease, first symptom, presence of optic neuritis attack, antibody status, Expanded Disability Status Scale(EDSS) score and disease severity score(DSS) were recorded. Retinal nerve fibre layer (RNFL) thickness was measured with optical coherence tomography, and corneal SBP images were taken with IVCM. Results NMOSD patients had significantly reduced corneal nerve fibre lenght-density and corneal nerve branch lenght-density compared with controls, while DC density was increased. NMOSD patients also showed significantly reduced RNFL thickness compared with controls. EDSS,DSS levels were inversely correlated with IVCM parameters. Conclusion We observed significant corneal nerve fibre loss in NMOSD patients in relation to disease severity. IVCM can be a candidate noninvasive imaging method for axonal damage assessment in NMOSD that warrants further investigation.

scholarly journals Corneal confocal microscopy compared with quantitative sensory testing and nerve conduction for diagnosing and stratifying the severity of diabetic peripheral neuropathy

2020 ◽  
Vol 8 (2) ◽  
pp. e001801
Author(s):  
Maryam Ferdousi ◽  
Alise Kalteniece ◽  
Shazli Azmi ◽  
Ioannis N Petropoulos ◽  
Anne Worthington ◽  
...  
Keyword(s):  
Diabetic Neuropathy ◽  
Nerve Fiber ◽  
Nerve Conduction ◽  
Fiber Length ◽  
Quantitative Sensory Testing ◽  
Sensory Testing ◽  
Perception Threshold ◽  
Corneal Confocal Microscopy ◽  
Corneal Nerve ◽  
Vibration Perception

IntroductionDiabetic neuropathy can be diagnosed and assessed using a number of techniques including corneal confocal microscopy (CCM).Research design and methodsWe have undertaken quantitative sensory testing, nerve conduction studies and CCM in 143 patients with type 1 and type 2 diabetes without neuropathy (n=51), mild neuropathy (n=47) and moderate to severe neuropathy (n=45) and age-matched controls (n=30).ResultsVibration perception threshold (p<0.0001), warm perception threshold (WPT) (p<0.001), sural nerve conduction velocity (SNCV) (p<0.001), corneal nerve fiber density (CNFD) (p<0.0001), corneal nerve branch density (CNBD) (p<0.0001), corneal nerve fiber length (CNFL) (p=0.002), inferior whorl length (IWL) (p=0.0001) and average nerve fiber length (ANFL) (p=0.0001) showed a progressive abnormality with increasing severity of diabetic neuropathy. Receiver operating characteristic curve analysis for the diagnosis of diabetic neuropathy showed comparable performance in relation to the area under the curve (AUC) but differing sensitivities and specificities for vibration perception threshold (AUC 0.79, sensitivity 55%, specificity 90%), WPT (AUC 0.67, sensitivity 50%, specificity 76%), cold perception threshold (AUC 0.64, sensitivity 80%, specificity 47%), SNCV (AUC 0.70, sensitivity 76%, specificity 54%), CNFD (AUC 0.71, sensitivity 58%, specificity 83%), CNBD (AUC 0.70, sensitivity 69%, specificity 65%), CNFL (AUC 0.68, sensitivity 64%, specificity 67%), IWL (AUC 0.72, sensitivity 70%, specificity 65%) and ANFL (AUC 0.72, sensitivity 71%, specificity 66%).ConclusionThis study shows that CCM identifies early and progressive corneal nerve loss at the inferior whorl and central cornea and has comparable utility with quantitative sensory testing and nerve conduction in the diagnosis of diabetic neuropathy.

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 In vivo corneal confocal microscopy and optical coherence tomography on eyes of participants with type 2 diabetes mellitus and obese participants without diabetes

2021 ◽  
Author(s):  
Noémi Tóth ◽  
David M. Silver ◽  
Szabolcs Balla ◽  
Miklós Káplár ◽  
Adrienne Csutak
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Optical Coherence Tomography ◽  
Type 2 Diabetes Mellitus ◽  
Confocal Microscopy ◽  
Nerve Fibers ◽  
Corneal Confocal Microscopy ◽  
Corneal Nerve

Abstract Purposes To examine corneal nerve and retinal nerve characteristics of participants with type 2 diabetes mellitus (T2DM) compared with obese participants without diabetes to discover potential nerve vulnerabilities. Methods All participants underwent a complete medical examination including a physical examination and blood sample tests. The ophthalmologic examination included best-corrected visual acuity, intraocular pressure, Schirmer test, tear film breakup time, slit-lamp examination, dilated fundus photography, in vivo corneal confocal microscopy (IVCCM), and optical coherence tomography (OCT). Results The study cohort consisted of 83 eyes of 83 individuals: a group of 44 participants with T2DM, and a control group of 39 obese participants with no history of diabetes. Comparing measurements on the two groups, participants with T2DM had lower values with statistical significance for retinal nerve fiber layer (RNFL) nasal superior thickness (p = 0.010) and three corneal nerve (CN) parameters: fiber length (p = 0.025), total branch density (p = 0.013), and fiber area (p = 0.009). There was a borderline significant difference in CN fiber width (p = 0.051) and RNFL nasal inferior thickness (p = 0.056). No other significant differences were observed in the IVCCM and OCT parameters. No statistically significant correlation was found between CN and RNFL parameters. Conclusions Progression from a pre-diabetic obese state to a T2DM condition might entail a loss or diminishment of certain corneal nerve fibers or retinal nerve fibers, but not necessarily a loss of both corneal and retinal nerve fibers simultaneously. Using IVCCM and OCT together enables monitoring of both corneal and retinal health of the eye.

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.

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