A semi-automated method to assess intraepidermal nerve fibre density in human skin biopsies

Automated immunohistochemistry of intra-epidermal nerve fibres in skin biopsies: A proof-of-concept study

AIMS

To develop a standardised, automated protocol for detecting protein gene product 9.5 (PGP9.5) positive intra-epidermal nerve fibres (IENFs) in skin biopsies, transitioning from the established manual technique to an automated platform. This automated method, although currently intended for research applications, may improve the accessibility of this diagnostic test for small fibre neuropathy in clinical settings.

METHODS

Skin biopsies (n = 274) from 100 participants (fibromyalgia syndrome n = 62; idiopathic small fibre neuropathy: n = 16; healthy volunteers: n = 22) were processed using an automated immunohistochemistry platform. IENF quantification was performed by blinded examiners, with reliability assessed via a two-way mixed-effects model to evaluate inter- and intra-observer variability.

RESULTS

The automated staining system reproduced intra-epidermal nerve fibre density (IENFD) counts consistent with free-floating sections (mean ± standard deviation: free-floating: 5.6 ± 3.4 fibres/mm; automated: 5.9 ± 3.2 fibres/mm). A median difference of 0.3 with a lower bound 95% Confidence Interval (CI) at -0.00005 established non-inferiority against a margin of -0.4 (p = .08). Specifically, the inter-class correlation coefficient (class denotes consistency in measured observations) was 99% (95% CI: 0.9-1), indicating excellent agreement between free-floating and automated methods. The inter- and intra-class coefficient between examiners were both 99% (95% CI: 0.9-0.1) for IENFD, demonstrating high reliability using sections stained using the automated method.

INTERPRETATION

Automated immunohistochemistry provides high-throughput reliable and reproducible intra-epidermal nerve fibre quantification. This method, although currently proof-of-concept, for research use only, may be more widely deployed in histopathology laboratories to increase the adoption of IENFD assessment for the diagnosis of peripheral neuropathies.

Density mapping of nerve endings in the skin of the palm and flexor retinaculum of the hand. Application to open carpal tunnel release

In order to re-evaluate the safest area to incise skin and the flexor retinaculum (FR) when performing a carpal tunnel release (CTR), we carried out a mapping study of the nerve endings in the skin and FR on cadaver specimens, which, unlike previous studies for the first time, includes histomorphometry and image digital analysis. After dividing the skin and FR into 20 and 12 sections, respectively, we carried out a histomorphological analysis of nerve endings. The analysis was performed by two neutral observers on 4-μm histological sections stained with hematoxylin-eosin (H-E), and Klüver-Barrera with picrosirius red (KB + PR) methods. A semi-automatic image digital analysis was also used to estimate the percentage of area occupied per nerve. We observed a lower quantity of nerve endings in the skin of the palm of the hand in line with the ulnar aspect of the 4th finger. The ulnar aspect of the FR was the most densely innervated. However, there are no statistically significant differences between sections in the percentage of area occupied per nerve both in the skin and in the FR. We concluded that there is not a safe area to incise when performing carpal tunnel surgery, but taking into account the quantity of nerve endings present in skin and FR, we recommend an incision on the axis of the ulnar aspect of 4th finger when incising skin and on the middle third of the FR for CTR.

Advantages of an Automated Method Compared With Manual Methods for the Quantification of Intraepidermal Nerve Fiber in Skin Biopsy

Intraepidermal nerve fiber density (IENFD) measurements in skin biopsy are performed manually by 1–3 operators. To improve diagnostic accuracy and applicability in clinical practice, we developed an automated method for fast IENFD determination with low operator-dependency. Sixty skin biopsy specimens were stained with the axonal marker PGP9.5 and imaged using a widefield fluorescence microscope. IENFD was first determined manually by 3 independent observers. Subsequently, images were processed in their Z-max projection and the intradermal line was delineated automatically. IENFD was calculated automatically (fluorescent images automated counting [FIAC]) and compared with manual counting on the same fluorescence images (fluorescent images manual counting [FIMC]), and with classical manual counting (CMC) data. A FIMC showed lower variability among observers compared with CMC (interclass correlation [ICC] = 0.996 vs 0.950). FIMC and FIAC showed high reliability (ICC = 0.999). A moderate-to-high (ICC = 0.705) was observed between CMC and FIAC counting. The algorithm process took on average 15 seconds to perform FIAC counting, compared with 10 minutes for FIMC counting. This automated method rapidly and reliably detects small nerve fibers in skin biopsies with clear advantages over the classical manual technique.

Orbit Image Analysis: An open-source whole slide image analysis tool

We describe Orbit Image Analysis, an open-source whole slide image analysis tool. The tool consists of a generic tile-processing engine which allows the execution of various image analysis algorithms provided by either Orbit itself or from other open-source platforms using a tile-based map-reduce execution framework. Orbit Image Analysis is capable of sophisticated whole slide imaging analyses due to several key features. First, Orbit has machine-learning capabilities. This deep learning segmentation can be integrated with complex object detection for analysis of intricate tissues. In addition, Orbit can run locally as standalone or connect to the open-source image server OMERO. Another important characteristic is its scale-out functionality, using the Apache Spark framework for distributed computing. In this paper, we describe the use of Orbit in three different real-world applications: quantification of idiopathic lung fibrosis, nerve fibre density quantification, and glomeruli detection in the kidney.

Automated PGP9.5 immunofluorescence staining: a valuable tool in the assessment of small fiber neuropathy?

BACKGROUND

In this study we explored the possibility of automating the PGP9.5 immunofluorescence staining assay for the diagnosis of small fiber neuropathy using skin punch biopsies. The laboratory developed test (LDT) was subjected to a validation strategy as required by good laboratory practice guidelines and compared to the well-established gold standard method approved by the European Federation of Neurological Societies (EFNS). To facilitate automation, the use of thinner sections. (16 µm) was evaluated. Biopsies from previously published studies were used. The aim was to evaluate the diagnostic performance of the LDT compared to the gold standard. We focused on technical aspects to reach high-quality standardization of the PGP9.5 assay and finally evaluate its potential for use in large scale batch testing.

RESULTS

We first studied linear nerve fiber densities in skin of healthy volunteers to establish reference ranges, and compared our LDT using the modifications to the EFNS counting rule to the gold standard in visualizing and quantifying the epidermal nerve fiber network. As the LDT requires the use of 16 µm tissue sections, a higher incidence of intra-epidermal nerve fiber fragments and a lower incidence of secondary branches were detected. Nevertheless, the LDT showed excellent concordance with the gold standard method. Next, the diagnostic performance and yield of the LDT were explored and challenged to the gold standard using skin punch biopsies of capsaicin treated subjects, and patients with diabetic polyneuropathy. The LDT reached good agreement with the gold standard in identifying small fiber neuropathy. The reduction of section thickness from 50 to 16 µm resulted in a significantly lower visualization of the three-dimensional epidermal nerve fiber network, as expected. However, the diagnostic performance of the LDT was adequate as characterized by a sensitivity and specificity of 80 and 64 %, respectively.

CONCLUSIONS

This study, designed as a proof of principle, indicated that the LDT is an accurate, robust and automated assay, which adequately and reliably identifies patients presenting with small fiber neuropathy, and therefore has potential for use in large scale clinical studies.