scholarly journals Automatic Tortuosity Estimation of Nerve Fibers and Retinal Vessels in Ophthalmic Images

2020 ◽  
Vol 10 (14) ◽  
pp. 4788
Author(s):  
Honghan Chen ◽  
Bang Chen ◽  
Dan Zhang ◽  
Jiong Zhang ◽  
Jiang Liu ◽  
...  
Keyword(s):  
Nerve Fiber ◽  
Estimation Method ◽  
Weighted Average ◽  
Retinal Vessel ◽  
Ground Truth ◽  
Nerve Fibers ◽  
Public Access ◽  
Close Relationship ◽  
Enhancement Method ◽  
Corneal Nerve

The tortuosity changes of curvilinear anatomical organs such as nerve fibers or vessels have a close relationship with a number of diseases. Therefore, the automatic estimation and representation of the tortuosity is desired in medical image for such organs. In this paper, an automated framework for tortuosity estimation is proposed for corneal nerve and retinal vessel images. First, the weighted local phase tensor-based enhancement method is employed and the curvilinear structure is extracted from raw image. For each curvilinear structure with a different position and orientation, the curvature is measured by the exponential curvature estimation in the 3D space. Then, the tortuosity of an image is calculated as the weighted average of all the curvilinear structures. Our proposed framework has been evaluated on two corneal nerve fiber datasets and one retinal vessel dataset. Experiments on three curvilinear organ datasets demonstrate that our proposed tortuosity estimation method achieves a promising performance compared with other state-of-the-art methods in terms of accuracy and generality. In our nerve fiber dataset, the method achieved overall accuray of 0.820, and 0.734, 0.881 for sensitivity and specificity, respectively. The proposed method also achieved Spearman correlation scores 0.945 and 0.868 correlated with tortuosity grading ground truth for arteries and veins in the retinal vessel dataset. Furthermore, the manual labeled 403 corneal nerve fiber images with different levels of tortuosity, and all of them are also released for public access for further research.

scholarly journals Corneal Nerve Fiber Structure, Its Role in Corneal Function, and Its Changes in Corneal Diseases

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Hiroshi Eguchi ◽  
Akio Hiura ◽  
Hiroshi Nakagawa ◽  
Shunji Kusaka ◽  
Yoshikazu Shimomura
Keyword(s):  
Nerve Fiber ◽  
Trp Channels ◽  
Nerve Fibers ◽  
Corneal Epithelial Cell ◽  
Transient Receptor Potential Vanilloid ◽  
Eye Drops ◽  
Fiber Morphology ◽  
Corneal Nerves ◽  
Corneal Nerve ◽  
Neurotrophic Keratopathy

Recently, in vivo confocal microscopy is used to examine the human corneal nerve fibers morphology. Corneal nerve fiber architecture and its role are studied in healthy and pathological conditions. Corneal nerves of rats were studied by nonspecific acetylcholinesterase (NsAchE) staining. NsAchE-positive subepithelial (stromal) nerve fiber has been found to be insensitive to capsaicin. Besides, NsAchE-negative but capsaicin-sensitive subbasal nerve (leash) fibers formed thick mesh-like structure showing close interconnections and exhibit both isolectin B4- and transient receptor potential vanilloid channel 1- (TRPV1-) positive. TRPV1, TRPV3, TRPA (ankyrin) 1, and TRPM (melastatin) 8 are expressed in corneal nerve fibers. Besides the corneal nerve fibers, the expressions of TRPV (1, 3, and 4), TRPC (canonical) 4, and TRPM8 are demonstrated in the corneal epithelial cell membrane. The realization of the importance of TRP channels acting as polymodal sensors of environmental stresses has identified potential drug targets for corneal disease. The pathophysiological conditions of corneal diseases are associated with disruption of normal tissue innervation, especially capsaicin-sensitive small sensory nerve fibers. The relationships between subbasal corneal nerve fiber morphology and neurotrophic keratopathy in corneal diseases are well studied. The recommended treatment for neurotrophic keratopathy is administration of preservative free eye drops.

scholarly journals Early detection of diabetic neuropathy by investigating CNFL and IENFD in thy1-YFP mice

2016 ◽  
Vol 231 (2) ◽  
pp. 147-157 ◽  
Author(s):  
Janine Leckelt ◽  
Pedro Guimarães ◽  
Annett Kott ◽  
Alfredo Ruggeri ◽  
Oliver Stachs ◽  
...  
Keyword(s):  
Diabetic Neuropathy ◽  
Nerve Fiber ◽  
Blood Glucose Concentration ◽  
Ex Vivo ◽  
Surrogate Marker ◽  
Nerve Fibers ◽  
Fiber Density ◽  
Corneal Confocal Microscopy ◽  
Intraepidermal Nerve Fiber Density ◽  
Corneal Nerve

Small fiber neuropathy is one of the most common and painful long-term complications of diabetes mellitus. Examination of the sub-basal corneal nerve plexus is a promising surrogate marker of diabetic neuropathy. To investigate the efficacy, reliability and reproducibility of in vivo corneal confocal microscopy (IVCCM), we used thy1-YFP mice, which express yellow fluorescence protein (YFP) in nerve fibers. 4 weeks after multiple low-dose injections of streptozotocin, thy1-YFP mice showed manifest diabetes. Subsequent application of insulin-releasing pellets for 8 weeks resulted in a significant reduction of blood glucose concentration and HbA1c, a significant increase in body weight and no further increase in advanced glycation end products (AGEs). IVCCM, carried out regularly over 12 weeks and analyzed both manually and automatically, revealed a significant loss of corneal nerve fiber length (CNFL) during diabetes manifestation and significant recovery after insulin therapy. Ex vivo analyses of CNFL by YFP-based microscopy confirmed the IVCCM results (with high sensitivity between manual and automated approaches) but demonstrated that the changes were restricted to the central cornea. Peripheral areas, not accessible by IVCCM in mice, remained virtually unaffected. Because parallel assessment of intraepidermal nerve fiber density revealed no changes, we conclude that IVCCM robustly captures early signs of diabetic neuropathy.

scholarly journals Automatic corneal nerve fiber segmentation and geometric biomarker quantification

2020 ◽  
Vol 135 (2) ◽  
Author(s):  
Dan Zhang ◽  
Fan Huang ◽  
Maziyar Khansari ◽  
Tos T. J. M. Berendschot ◽  
Xiayu Xu ◽  
...  
Keyword(s):  
Nerve Fiber ◽  
Extraction Methods ◽  
Nerve Fibers ◽  
Convolutional Network ◽  
Fiber Network ◽  
Fiber Extraction ◽  
Topological Features ◽  
Corneal Nerve ◽  
Fully Automatic ◽  
Microscopy Images

Abstract Geometric and topological features of corneal nerve fibers in confocal microscopy images are important indicators for the diagnosis of common diseases such as diabetic neuropathy. Quantitative analysis of these important biomarkers requires an accurate segmentation of the nerve fiber network. Currently, most of the analysis are performed based on manual annotations of the nerve fiber segments, while a fully automatic corneal nerve fiber extraction and analysis framework is still needed. In this paper, we establish a fully convolutional network method to precisely enhance and segment corneal nerve fibers in microscopy images. Based on the segmentation results, automatic tortuosity measurement and branching detection modules are established to extract valuable geometric and topological biomarkers. The proposed segmentation method is validated on a dataset with 142 images. The experimental results show that our deep learning-based framework outperforms state-of-the-art segmentation approaches. The biomarker extraction methods are validated on two different datasets, demonstrating high effectiveness and reliability of the proposed methods.

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 Deep Learning-Based Analysis of Macaque Corneal Sub-Basal Nerve Fibers in Confocal Microscopy Images

2019 ◽  
Author(s):  
Jonathan D. Oakley ◽  
Daniel B. Russakoff ◽  
Megan E. McCarron ◽  
Rachel L. Weinberg ◽  
Jessica M. Izzi ◽  
...  
Keyword(s):  
Deep Learning ◽  
Confocal Microscopy ◽  
Nerve Fiber ◽  
Ground Truth ◽  
Automated Analysis ◽  
Nerve Fibers ◽  
Fiber Analysis ◽  
Quantitative Measurements ◽  
Nerve Fiber Analysis

AbstractPurposeTo describe and assess different deep learning-based methods for automated measurement of macaque corneal sub-basal nerves using in vivo confocal microscopy (IVCM).MethodsThe automated assessment of corneal nerve fiber length (CNFL) in IVCM images is of increasing clinical interest. These measurements are important biomarkers in a number of diseases including diabetes mellitus, human immunodeficiency virus, Parkinson’s disease and multiple sclerosis. Animal models of these and other diseases play an important role in understanding the disease processes as efforts toward developing new and effective therapeutics are made. And while automated methods exist for nerve fiber analysis in clinical data, differences in anatomy and image quality make the macaque data more challenging and has motivated the work reported here.Toward this goal, nerves in macaque corneal IVCM images were manually labelled using an ImageJ plugin (NeuronJ). Different deep convolutional neural network (CNN) architectures were evaluated for accuracy relative to the ground truth manual tracings. The best performing model was used on separately acquired macaque ICVM images to additionally compare inter-reader variability.ConclusionsDeep learning-based segmentation of sub-basal nerves in IVCM images shows excellent correlation to manual segmentations in macaque data. The technique is indistinguishable across readers and paves the way for more widespread adoption of objective automated analysis of sub-basal nerves in IVCM.Translational RelevanceQuantitative measurements of corneal sub-basal nerves are important biomarkers for disease screening and management. This work reports on different approaches that, in using deep learning-based techniques, leverage state of the art analysis methods to demonstrate performance akin to human graders. In application, the approach is robust, rapid and objective, offering utility to a variety of clinical studies using IVCM.

scholarly journals Augmented Corneal Nerve Fiber Branching in Painful Compared With Painless Diabetic Neuropathy

2019 ◽  
Vol 104 (12) ◽  
pp. 6220-6228
Author(s):  
Sonja Püttgen ◽  
Gidon J Bönhof ◽  
Alexander Strom ◽  
Karsten Müssig ◽  
Julia Szendroedi ◽  
...  
Keyword(s):  
Nerve Fiber ◽  
Rating Scale ◽  
Nerve Fibers ◽  
Control Group ◽  
Fiber Density ◽  
Nerve Branch ◽  
Perception Threshold ◽  
Cross Sectional ◽  
Corneal Confocal Microscopy ◽  
Corneal Nerve

AbstractContextThe factors that determine the development of diabetic sensorimotor polyneuropathy (DSPN) as a painful or painless entity are unknown.ObjectiveWe hypothesized that corneal nerve pathology could be more pronounced in painful DSPN, indicating predominant small nerve fiber damage.Design and MethodsIn this cross-sectional study, we assessed 53 patients with painful DSPN, 63 with painless DSPN, and 46 glucose-tolerant volunteers by corneal confocal microscopy (CCM), nerve conduction (NC), and quantitative sensory testing. DSPN was diagnosed according to modified Toronto Consensus criteria. A cutoff at 4 points on the 11-point rating scale was used to differentiate between painful and painless DSPN.ResultsAfter adjustment for age, sex, body mass index, and smoking, corneal nerve fiber density, corneal nerve fiber length, and corneal nerve branch density (CNBD) were reduced in both DSPN types compared with the control group (P < 0.05). Only CNBD differed between the groups; it was greater in patients with painful DSPN compared with those with painless DSPN [55.8 (SD, 29.9) vs 43.8 (SD, 28.3) branches/mm2; P < 0.05]. Several CCM measures were associated with NC and cold perception threshold in patients with painless DSPN (P < 0.05) but not those with painful DSPN.ConclusionDespite a similarly pronounced peripheral nerve dysfunction and corneal nerve fiber loss in patients with painful and painless DSPN, corneal nerve branching was enhanced in those with painful DSPN, pointing to some susceptibility of corneal nerve fibers toward regeneration in this entity, albeit possibly not to a sufficient degree.

scholarly journals Assessment and comparison of the morphology and function of the corneal sub-basal nerve plexus in type-1 diabetes mellitus patients and in healthy subjects

2016 ◽  
Vol 1 (1) ◽  
pp. 51-63
Author(s):  
Irmante Derkac ◽  
Ingrida Januleviciene ◽  
Kirwan Asselineau ◽  
Dzilda Velickiene
Keyword(s):  
Nerve Fiber ◽  
Healthy Subjects ◽  
Nerve Fibers ◽  
Corneal Sensitivity ◽  
Fiber Density ◽  
Corneal Confocal Microscopy ◽  
Corneal Nerve ◽  
Type 1 Dm ◽  
Nerve Fiber Density

Aim/purpose: It is believed that small nerve bundles are damaged in the earliest stages of neuropathy caused by diabetes mellitus (DM). Our goal was to evaluate and compare anatomical characteristics of corneal nerve fibers and corneal sensitivity in type-1 DM patients and in healthy control subjects.Design: A prospective, masked, controlled cross-sectional clinical study.Method: Thirty patients with type-1 DM and ten non-diabetic healthy subjects underwent a corneal confocal microscopy to evaluate the corneal sub-basal nerve fibers (density, number of nerves and branches, total nerve length) and contact corneal esthesiometry.Results: Diabetic patients had significantly lower corneal nerve fiber density density (14.32 ± 5.87 vs. 19.71 ± 5.59 mm/mm2; p = 0.023 ) nerve branches number (4.57 ± 3,91 vs. 9.90 ± 5.8 n°/image; p = 0.006) , nerve fiber length (2.28 ± 0.94 vs. 3.13 ± 0.89 mm; p = 0.032) and corneal sensitivity (1.13 ± 0.29 vs. 0.98 ± 0.058 gr/mm2 p = 0.02), as compared with controls. A negative correlation was found between corneal nerve fiber length, corneal nerve number, corneal nerve fiber density and disease duration (p < 0.05).Conclusion: Corneal confocal microscopy and corneal sensitivity evaluation are noninvasive techniques helping to detect early changes in the sub-basal nerve plexus characteristic for diabetic neuropathy (DN) in patients with type-1 DM. Further studies are required to investigate the role of corneal neuropathy assessment using these novel techniques as a toll to detect early DN. 

scholarly journals Corneal confocal microscopy differentiates inflammatory from diabetic neuropathy

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Michael Fleischer ◽  
Inn Lee ◽  
Friedrich Erdlenbruch ◽  
Lena Hinrichs ◽  
Ioannis N. Petropoulos ◽  
...  
Keyword(s):  
Dendritic Cell ◽  
Confocal Microscopy ◽  
Diabetic Neuropathy ◽  
Nerve Fiber ◽  
Cell Density ◽  
Chronic Inflammatory Demyelinating Polyneuropathy ◽  
Basal Layer ◽  
Nerve Fibers ◽  
Corneal Confocal Microscopy ◽  
Corneal Nerve

Abstract Background Immune-mediated neuropathies, such as chronic inflammatory demyelinating polyneuropathy (CIDP) are treatable neuropathies. Among individuals with diabetic neuropathy, it remains a challenge to identify those individuals who develop CIDP. Corneal confocal microscopy (CCM) has been shown to detect corneal nerve fiber loss and cellular infiltrates in the sub-basal layer of the cornea. The objective of the study was to determine whether CCM can distinguish diabetic neuropathy from CIDP and whether CCM can detect CIDP in persons with coexisting diabetes. Methods In this multicenter, case-control study, participants with CIDP (n = 55) with (n = 10) and without (n = 45) diabetes; participants with diabetes (n = 58) with (n = 28) and without (n = 30) diabetic neuropathy, and healthy controls (n = 58) underwent CCM. Corneal nerve fiber density (CNFD), corneal nerve fiber length (CNFL), corneal nerve branch density (CNBD), and dendritic and non-dendritic cell density, with or without nerve fiber contact were quantified. Results Dendritic cell density in proximity to corneal nerve fibers was significantly higher in participants with CIDP with and without diabetes compared to participants with diabetic neuropathy and controls. CNFD, CNFL, and CNBD were equally reduced in participants with CIDP, diabetic neuropathy, and CIDP with diabetes. Conclusions An increase in dendritic cell density identifies persons with CIDP. CCM may, therefore, be useful to differentiate inflammatory from non-inflammatory diabetic neuropathy.

scholarly journals Verification of Finger Joint Stiffness Estimation Method With Soft Robotic Actuator

2020 ◽  
Vol 8 ◽  
Author(s):  
Xiang Qian Shi ◽  
Ho Lam Heung ◽  
Zhi Qiang Tang ◽  
Kai Yu Tong ◽  
Zheng Li
Keyword(s):  
Estimation Method ◽  
Joint Stiffness ◽  
Ground Truth ◽  
Clinical Score ◽  
Metacarpophalangeal Joint ◽  
Finger Joint ◽  
Joint Torque ◽  
Hand Rehabilitation ◽  
Stiffness Characteristic ◽  
Modified Ashworth Scale

Stroke has been the leading cause of disability due to the induced spasticity in the upper extremity. The constant flexion of spastic fingers following stroke has not been well described. Accurate measurements for joint stiffness help clinicians have a better access to the level of impairment after stroke. Previously, we conducted a method for quantifying the passive finger joint stiffness based on the pressure-angle relationship between the spastic fingers and the soft-elastic composite actuator (SECA). However, it lacks a ground-truth to demonstrate the compatibility between the SECA-facilitated stiffness estimation and standard joint stiffness quantification procedure. In this study, we compare the passive metacarpophalangeal (MCP) joint stiffness measured using the SECA with the results from our designed standalone mechatronics device, which measures the passive metacarpophalangeal joint torque and angle during passive finger rotation. Results obtained from the fitting model that concludes the stiffness characteristic are further compared with the results obtained from SECA-Finger model, as well as the clinical score of Modified Ashworth Scale (MAS) for grading spasticity. These findings suggest the possibility of passive MCP joint stiffness quantification using the soft robotic actuator during the performance of different tasks in hand rehabilitation.

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