The Utility of Corneal Nerve Fractal Dimension Analysis in Peripheral Neuropathies of Different Etiology

Quantification of corneal confocal microscopy (CCM) images has shown a significant reduction in corneal nerve fiber length (CNFL) in a range of peripheral neuropathies. We assessed whether corneal nerve fractal dimension (CNFrD) analysis, a novel metric to quantify the topological complexity of corneal subbasal nerves, can differentiate peripheral neuropathies of different etiology.

In patients with DPN, CIDP, CIPN, or HIV-SN compared to HCs, CNFD ( P = 0.004–0.0001) and CNFL ( P = 0.05–0.0001) were significantly lower, with a further significant reduction among subgroups. CNFrD was significantly lower in patients with CIDP compared to HCs and patients with HIV-SN ( P = 0.02–0.0009) and in patients with DPN compared to HCs and patients with HIV-SN, CIPN, or CIDP ( P = 0.001–0.0001). ACNFrD was lower in patients with CIPN, CIDP, or DPN compared to HCs ( P = 0.03–0.0001) and in patients with DPN compared to those with HIV-SN, CIPN, or CIDP ( P = 0.01–0.005).

Various peripheral neuropathies are characterized by a comparable degree of corneal nerve loss. Assessment of corneal nerve topology by CNFrD could be useful in differentiating neuropathies based on the pattern of loss.

Study Subjects CCM images from 29 subjects with type 1 diabetes mellitus and DPN (58.5 ± 12 years old), 34 patients with CIDP (59.2 ± 14.8 years old), 13 patients with CIPN (63.8 ± 10 years old), 14 patients with HIV-SN (57.7 ± 7.8 years old), and 20 age-matched healthy controls (HCs) (58.5 ± 12 years old) were used in this study. The data presented here constitute a secondary analysis of already published data, 16 – 18 , 26 but this study utilized only the data for patients with clinically diagnosed peripheral neuropathy. This study adhered to the Tenets of the declaration of Helsinki, and ethical approval was obtained by all participating institutions. Informed written consent was obtained from all subjects prior to participation. Exclusion criteria were any cause of neuropathy other than the primary cause of neuropathy (deficiency of vitamin B 12 or folate; autoimmune infectious; rheumatological disease) or having corneal dystrophies, active anterior eye infections, using contact lens on a regular basis, or having had recent (<1 year) refractive or cataract surgery.

In total, 660 CCM images from both eyes were analyzed independently using manual semiautomated, purpose-designed CCM image segmentation software (CCMetrics; M.A. Dabbah, X. Chen, J. Graham, and R.A. Malik, University of Manchester, Manchester, UK) ( Figs. 1 F– 1 J) and the automated version (ACCMetrics). 32 CCMetrics is a validated CCM image segmentation algorithm that allows measurement of corneal nerve fiber density (CNFD) (fibers/mm 2 ), the number of main nerve fibers per image divided by the area of the image; corneal nerve branch density (CNBD) (branches/mm 2 ), the number of main nerve branches; CNFL (mm/mm 2 ), the sum of the length of all nerves per image (main nerves and branches). ACCMetrics was used for the estimation of CNFrD as previously described. 26 For CNFrD estimation, all original CCM images ( Fig. 2 A) were resized to 512 × 512 pixels, as this was the image resolution used to train our machine learning-based nerve fiber detection mode. 32 CNFrD was calculated based on the binary image representing the detected nerve fibers using our previously developed machine learning approach, 32 as shown in Figure 2 B. CNFrD measures nerve complexity as the ratio of the change in detail to the change in scale in a CCM image. Box counting is a widely used and acknowledged method for fractal analysis calculation, 33 and it was applied in our study. This technique uses various sizes of n × n boxes (in our study, n = 1, 2, 4, …, 512, as 512 was the image width) to split the image into small patches. For each of the box sizes, the total number of boxes, Y i ( i is the index of the different box sizes), that contain nerve fibers are recorded. As shown in Figure 2 C, the logarithm of Y against the logarithm of n is then plotted. A first-order polynomial (i.e., red line in Fig. 2 C) is fitted to these points using the method of least squares, where the coefficient of the line fitting (i.e., slope of the line, denoted as C ) is calculated. Subsequently, –C is used as the fractal dimension value of a given CCM image (i.e., CNFrD). The CNFrD value is unitless, as it is a ratio, and increases when the number of counted small boxes increases, indicating a more complicated structure (e.g., higher CNFrD in a healthy control subject). In contrast, fewer, shorter, or disrupted nerve fibers result in a lower CNFrD value that reflects altered morphology ( Figs. 1 K– 1 O). To adjust for the severity of corneal nerve fiber loss, a ratio of CNFL/CNFrD was calculated (CNFrD adjusted for CNFL, or ACNFrD), which is also unitless. The averaged result of six images per patient was used for CNFD, CNBD, CNFL, CNFrD, and ACNFrD. Figure 2. (A) Original CMM image, (B) detected nerve fibers using a machine learning method, 32 and (C) CNFrD calculation using the box counting method.

Demographics There was no significant difference in age among the different groups of patients except for patients with CIPN, who were slightly older ( P = 0.06) compared to HCs ( Table 1 ). Patients with HIV-SN (14 males, 0 females), CIPN (19 males, 1 female), or CIDP (22 males, 12 females) were predominantly male compared to those having DPN (12 males, 17 females), for whom there was a slightly higher prevalence among females. Glycated hemoglobin (HbA1c) was within normal range, indicating no diabetes for HCs (38 ± 3.8 mmol/mol) or for patients with HIV-SN (within normal range), CIPN (34.8 ± 5.8 mmol/mol), or CIDP (35.9 ± 6.8). HbA1c was high for patients with DPN indicating diabetes (72.4 ± 19.3 mmol/mol). Disease duration was longer for HIV-SN (25.3 ± 4.7 years), CIDP (12 ± 8.6 years), and DPN (42 ± 14.4 years) but shorter for CIPN (<6 months), as expected. Table. Demographic and CCM Parameter Results Mean SD HC ( n = 20) HIV-SN ( n = 14) CIPN ( n = 34) CIDP ( n = 29) Age (y) HC 54.5 11.2 HIV-SN 57.7 7.8 0.99 CIPN 63.8 10.0 0.06 — CIDP 59.2 14.8 0.52 — — DPN 58.5 12.0 0.71 — — — CNFD (fibers/mm 2 ) HC 39.4 6.7 HIV-SN 26.7 4.2 <0.0001 CIPN 29.5 5.5 0.004 0.99 CIDP 25.1 7.7 <0.0001 0.79 0.55 DPN 17.4 9.9 <0.0001 0.002 <0.0001 0.001 CNBD (branches/mm 2 ) HC 95.9 40.2 HIV-SN 74.0 22.0 0.6 CIPN 73.6 43.3 0.61 0.99 CIDP 80.3 40.2 0.77 0.99 0.99 DPN 45.7 31.7 <0.0001 0.18 0.22 0.003 CNFL (mm/mm 2 ) HC 27.3 4.7 HIV-SN 22.2 3.4 0.16 CIPN 21.3 5.0 0.05 0.99 CIDP 19.4 6.0 0.0001 0.8 0.98 DPN 14.6 8.2 <0.0001 0.002 0.0133 0.02 CNFrD (unitless) HC 1.51 0.02 HIV-SN 1.51 0.02 0.99 CIPN 1.50 0.03 0.99 0.99 CIDP 1.46 0.04 0.0009 0.02 0.12 DPN 1.40 0.08 <0.0001 <0.0001 <0.0001 0.001 ACNFrD (unitless) HC 18.0 3.0 HIV-SN 14.7 2.2 0.07 CIPN 14.2 3.1 0.03 0.79 CIDP 13.4 4.0 0.0007 0.67 0.78 DPN 10.2 5.3 <0.0001 0.005 0.01 0.01 P < 0.05 was considered significant.

To the best of our knowledge, this is the first study to compare established measures of corneal nerve loss and CNFrD 26 in peripheral neuropathies of differing etiology. There are two main findings in this study. First, patients with DPN or CIDP showed more severe corneal nerve loss compared to patients with HIV-SN or CIPN, who had milder albeit significant loss. Our second and most important finding is that the remaining corneal nerves may have a distinct morphological pattern, as assessed by CNFrD in DPN and CIDP compared to HIV-SN and CIPN. Furthermore, even after adjustment for the overall severity of reduction in CNFL, ACNFrD differed significantly in patients with DPN compared to CIDP, HIV-SN, and CIPN. Peripheral neuropathy occurs in the setting of many common and rare neurologic disorders. It affects approximately 26% to 58% of patients with diabetes, 34 , 35 up to 50% of people living with HIV, 36 and 68% of patients with cancer after chemotherapy. 37 CIDP affects 5 out of 100,000 people. 38 , 39 The corneal subbasal nerve plexus is a dense network of unmyelinated C-fibers, which are anatomically similar to intra-epidermal nerve fibers, 40 , 41 the gold standard markers for assessing small fiber integrity. Unlike intra-epidermal innervation, which requires an invasive skin biopsy, corneal subbasal innervation can be quantified rapidly and non-invasively using in vivo CCM. We have previously shown that corneal nerve loss occurs in DPN, 2 – 9 CIDP, 16 HIV-SN, 17 and CIPN. 18 More recently, we and others have also shown corneal nerve loss in patients with Parkinson's disease, 42 multiple sclerosis, 43 – 45 and dementia. 46 These findings highlight the potential of CCM as a surrogate measure of neurodegeneration but also raise concerns regarding the clinical utility of this technique due to limited specificity. Fractal dimension analysis is a measure of tissue structural complexity, and in brain magnetic resonance imaging scans 28 – 31 it has been used to identify distinct tissue geometric patterns in different neurodegenerative diseases. In ophthalmology research, fractal dimension analysis has been used to study alterations in the retinal vascular network in diabetic retinopathy 47 and maculopathy 48 and to detect glaucoma in digital images. 49 , 50 A recent study has used spatial analysis to show increased clustering of corneal nerve loss in patients with early diabetic neuropathy 51 and we have shown altered CNFrD in patients with DPN. 26 In this context, our findings suggest that in addition to demonstrating corneal nerve loss, there may be specific imaging traits of remaining nerve fibers associated with the underlying etiology. Strengths of this study are the detailed clinical phenotyping of neuropathy and the homogeneous imaging protocol used between centers. Given that ex vivo 41 and in vivo CCM studies 52 , 53 have shown that nerves in the inferior cornea are highly tortuous with a whorl-like appearance compared to almost straight nerves in the central cornea, all measurements were performed from the central cornea using a standardized protocol. A main limitation is the use of an automated image analysis algorithm to estimate CNFrD. Because CNFrD depends on accurate nerve segmentation, it may have been underestimated compared to the true fractal dimension. 4 Another limitation is the relatively small sample size, particularly for people living with HIV and CIPN, which may have skewed the results toward milder neuropathy. Finally, as only images from the central region were quantified for CNFrD, we cannot exclude the possibility of image selection bias. Assessment of wide-field CCM images may provide additional value for the estimation of CNFrD. Nevertheless, we show that fractal dimension analysis could complement the existing toolbox of corneal nerve analysis metrics and help to differentiate peripheral neuropathies, especially CIDP and DPN. We believe the additional quantification of CNFrD enhances the clinical utility of CCM by enhancing the specificity of this technique. Future studies should assess whether corneal nerve fractal dimension can differentiate central from peripheral neurodegenerative disorders.