Digital pathology for reporting histopathology samples, including cancer screening samples - definitive evidence from a multisite study.

AIMS: To conduct a definitive multicentre comparison of digital pathology (DP) with light microscopy (LM) for reporting histopathology slides including breast and bowel cancer screening samples. METHODS: A total of 2024 cases (608 breast, 607 GI, 609 skin, 200 renal) were studied, including 207 breast and 250 bowel cancer screening samples. Cases were examined by four pathologists (16 study pathologists across the four speciality groups), using both LM and DP, with the order randomly assigned and 6 weeks between viewings. Reports were compared for clinical management concordance (CMC), meaning identical diagnoses plus differences which do not affect patient management. Percentage CMCs were computed using logistic regression models with crossed random-effects terms for case and pathologist. The obtained percentage CMCs were referenced to 98.3% calculated from previous studies. RESULTS: For all cases LM versus DP comparisons showed the CMC rates were 99.95% [95% confidence interval (CI) = 99.90-99.97] and 98.96 (95% CI = 98.42-99.32) for cancer screening samples. In speciality groups CMC for LM versus DP showed: breast 99.40% (99.06-99.62) overall and 96.27% (94.63-97.43) for cancer screening samples; [gastrointestinal (GI) = 99.96% (99.89-99.99)] overall and 99.93% (99.68-99.98) for bowel cancer screening samples; skin 99.99% (99.92-100.0); renal 99.99% (99.57-100.0). Analysis of clinically significant differences revealed discrepancies in areas where interobserver variability is known to be high, in reads performed with both modalities and without apparent trends to either. CONCLUSIONS: Comparing LM and DP CMC, overall rates exceed the reference 98.3%, providing compelling evidence that pathologists provide equivalent results for both routine and cancer screening samples irrespective of the modality used.

Technical note on the exploration of COVID-19 in autopsy material.

Interrogation of immune response in autopsy material from patients with SARS-CoV-2 is potentially significant. We aim to describe a validated protocol for the exploration of the molecular physiopathology of SARS-CoV-2 pulmonary disease using multiplex immunofluorescence (mIF).The application of validated assays for the detection of SARS-CoV-2 in tissues, originally developed in our laboratory in the context of oncology, was used to map the topography and complexity of the adaptive immune response at protein and mRNA levels.SARS-CoV-2 is detectable in situ by protein or mRNA, with a sensitivity that could be in part related to disease stage. In formalin-fixed, paraffin-embedded pneumonia material, multiplex immunofluorescent panels are robust, reliable and quantifiable and can detect topographic variations in inflammation related to pathological processes.Clinical autopsies have relevance in understanding diseases of unknown/complex pathophysiology. In particular, autopsy materials are suitable for the detection of SARS-CoV-2 and for the topographic description of the complex tissue-based immune response using mIF.

Using Systemised Nomenclature of Medicine (SNOMED) codes to select digital pathology whole slide images for long-term archiving.

The archiving of whole slide images represents a hurdle to digital pathology implementation largely because of the amount of data generated. The retention of glass slides is currently recommended for a minimum of 10 years, but it is for individual departments to determine how digital images are archived and for how long. In a retrospective study, we examined the combination of Systemised Nomenclature of Medicine (SNOMED) codes allocated to cases reported between July 2011 and December 2015 and recalled more than 12 months after diagnosis in comparison to non-recalled cases.Our results show that 0.2% of cases are recalled after 12 months, and SNOMED code combinations can be used to identify which cases are likely to be recalled and which are not. This approach could reduce the number of cases archived by 62% and still ensure all cases likely to be recalled remain in the archive.

Lessons from a breast cell annotation competition series for school pupils.

Due to COVID-19 outbreaks, most school pupils have had to be home-schooled for long periods of time. Two editions of a web-based competition "Beat the Pathologists" for school age participants in the UK ran to fill up pupils' spare time after home-schooling and evaluate their ability on contributing to AI annotation. The two editions asked the participants to annotate different types of cells on Ki67 stained breast cancer images. The Main competition was at four levels with different level of complexity. We obtained annotations of four kinds of cells entered by school pupils and ground truth from expert pathologists. In this paper, we analyse school pupils' performance on differentiating different kinds of cells and compare their performance with two neural networks (AlexNet and VGG16). It was observed that children tend to get very good performance in tumour cell annotation with the best F1 measure 0.81 which is a metrics taking both false positives and false negatives into account. Low accuracy was achieved with F1 score 0.75 on positive non-tumour cells and 0.59 on negative non-tumour cells. Superior performance on non-tumour cell detection was achieved by neural networks. VGG16 with training from scratch achieved an F1 score over 0.70 in all cell categories and 0.92 in tumour cell detection. We conclude that non-experts like school pupils have the potential to contribute to large-scale labelling for AI algorithm development if sufficient training activities are organised. We hope that competitions like this can promote public interest in pathology and encourage participation by more non-experts for annotation.

Artificial intelligence for advance requesting of immunohistochemistry in diagnostically uncertain prostate biopsies.

The use of immunohistochemistry in the reporting of prostate biopsies is an important adjunct when the diagnosis is not definite on haematoxylin and eosin (H&E) morphology alone. The process is however inherently inefficient with delays while waiting for pathologist review to make the request and duplicated effort reviewing a case more than once. In this study, we aimed to capture the workflow implications of immunohistochemistry requests and demonstrate a novel artificial intelligence tool to identify cases in which immunohistochemistry (IHC) is required and generate an automated request. We conducted audits of the workflow for prostate biopsies in order to understand the potential implications of automated immunohistochemistry requesting and collected prospective cases to train a deep neural network algorithm to detect tissue regions that presented ambiguous morphology on whole slide images. These ambiguous foci were selected on the basis of the pathologist requesting immunohistochemistry to aid diagnosis. A gradient boosted trees classifier was then used to make a slide-level prediction based on the outputs of the neural network prediction. The algorithm was trained on annotations of 219 immunohistochemistry-requested and 80 control images, and tested by threefold cross-validation. Validation was conducted on a separate validation dataset of 222 images. Non IHC-requested cases were diagnosed in 17.9 min on average, while IHC-requested cases took 33.4 min over multiple reporting sessions. We estimated 11 min could be saved on average per case by automated IHC requesting, by removing duplication of effort. The tool attained 99% accuracy and 0.99 Area Under the Curve (AUC) on the test data. In the validation, the average agreement with pathologists was 0.81, with a mean AUC of 0.80. We demonstrate the proof-of-principle that an AI tool making automated immunohistochemistry requests could create a significantly leaner workflow and result in pathologist time savings.

Diagnostic concordance and discordance in digital pathology: a systematic review and meta-analysis.

BACKGROUND: Digital pathology (DP) has the potential to fundamentally change the way that histopathology is practised, by streamlining the workflow, increasing efficiency, improving diagnostic accuracy and facilitating the platform for implementation of artificial intelligence-based computer-assisted diagnostics. Although the barriers to wider adoption of DP have been multifactorial, limited evidence of reliability has been a significant contributor. A meta-analysis to demonstrate the combined accuracy and reliability of DP is still lacking in the literature. OBJECTIVES: We aimed to review the published literature on the diagnostic use of DP and to synthesise a statistically pooled evidence on safety and reliability of DP for routine diagnosis (primary and secondary) in the context of validation process. METHODS: A comprehensive literature search was conducted through PubMed, Medline, EMBASE, Cochrane Library and Google Scholar for studies published between 2013 and August 2019. The search protocol identified all studies comparing DP with light microscopy (LM) reporting for diagnostic purposes, predominantly including H&E-stained slides. Random-effects meta-analysis was used to pool evidence from the studies. RESULTS: Twenty-five studies were deemed eligible to be included in the review which examined a total of 10 410 histology samples (average sample size 176). For overall concordance (clinical concordance), the agreement percentage was 98.3% (95% CI 97.4 to 98.9) across 24 studies. A total of 546 major discordances were reported across 25 studies. Over half (57%) of these were related to assessment of nuclear atypia, grading of dysplasia and malignancy. These were followed by challenging diagnoses (26%) and identification of small objects (16%). CONCLUSION: The results of this meta-analysis indicate equivalent performance of DP in comparison with LM for routine diagnosis. Furthermore, the results provide valuable information concerning the areas of diagnostic discrepancy which may warrant particular attention in the transition to DP.

Digital pathology and artificial intelligence will be key to supporting clinical and academic cellular pathology through COVID-19 and future crises: the PathLAKE consortium perspective.

The measures to control the COVID-19 outbreak will likely remain a feature of our working lives until a suitable vaccine or treatment is found. The pandemic has had a substantial impact on clinical services, including cancer pathways. Pathologists are working remotely in many circumstances to protect themselves, colleagues, family members and the delivery of clinical services. The effects of COVID-19 on research and clinical trials have also been significant with changes to protocols, suspensions of studies and redeployment of resources to COVID-19. In this article, we explore the specific impact of COVID-19 on clinical and academic pathology and explore how digital pathology and artificial intelligence can play a key role to safeguarding clinical services and pathology-based research in the current climate and in the future.

Interobserver Reliability of Programmed Cell Death Ligand-1 Scoring Using the VENTANA PD-L1 (SP263) Assay in NSCLC.

INTRODUCTION: The VENTANA PD-L1 (SP263) Assay is approved for use with anti-programmed cell death-1/programmed cell death ligand-1 (PD-1/PD-L1) therapies in NSCLC and urothelial carcinoma. Here, we investigate interobserver reliability of the SP263 assay, applied to PD-L1 scoring of tumor cells (TCs) in NSCLC. METHODS: Six practicing European pulmonary pathologists independently scored the proportion of TCs expressing PD-L1 (TC score) from 200 archival, commercially sourced, formalin-fixed paraffin-embedded NSCLC resections stained using the SP263 assay. Agreement in scores was analyzed using the intraclass correlation coefficient and concordance in patient's classification using Fleiss' kappa. RESULTS: Results from 172 samples showed strong pair-wise correlations between pathologists (R2 >0.89) for TC scoring with an intraclass correlation coefficient of 0.96. Overall agreement was greater than 90% for TC of 1% and above, and greater than 94% for TCs of at least 25% and at least 50%. Fleiss' kappa showed substantial agreement for TC of 1% and above, and almost perfect agreement for TCs of at least 25% and at least 50%. CONCLUSIONS: Assessment of TC score in NSCLC was highly reproducible using the SP263 assay, building confidence in the accuracy of this assay in selection of patients for anti-PD-1/PD-L1 therapy.

Altered Decorin Biology in Proliferative Vitreoretinopathy: A Mechanistic and Cohort Study.

Purpose: To determine if vitreous levels of the pro-fibrotic cytokine transforming growth factor beta2 (TGF-ß2) and its opposing regulator decorin predict subsequent proliferative vitreoretinopathy (PVR) development in patients with rhegmatogenous retinal detachment (RRD). Methods: We examined the effect of TGF-ß2 and decorin on epithelial-mesenchymal transition (EMT) and collagen expression in vitro using ARPE-19 cells, and we analyzed extracellular matrix marker expression in PVR membrane and internal limiting membrane patient samples. We performed a prospective noninterventional cohort study, recruiting 125 patients undergoing vitrectomy for RRD and macular hole surgery, measured vitreous levels of TGF-ß2 and decorin by ELISA, and followed them up for 6 months. Patients who did not develop PVR were compared to those who did, in order to determine whether vitreous TGF-ß2 and decorin levels predicted PVR development. Results: In vitro, TGF-ß2 induced EMT and collagen production. Decorin strongly inhibited EMT and collagen production at high levels. PVR membranes expressed high levels of fibrosis-associated proteins, consistent with EMT. Vitreous TGF-ß2 levels were unchanged between patients with macular holes and RRD who did or did not subsequently develop PVR. Average decorin levels were higher in the vitreous of RRD patients who subsequently developed PVR compared to those who did not, but at the measured vitreous concentrations (1-2 µg/mL), decorin did not demonstrate an in vitro inhibitory effect on EMT. Conclusions: In vitro, high concentrations of decorin inhibited EMT and fibrosis. At the levels seen in human vitreous, decorin did not prevent fibrosis or EMT in vitro, and higher initial vitreous decorin levels were associated with the development of postoperative PVR after vitrectomy to treat RRD, but did not reliably predict the outcome.

Gland segmentation in colon histology images: The glas challenge contest.

Colorectal adenocarcinoma originating in intestinal glandular structures is the most common form of colon cancer. In clinical practice, the morphology of intestinal glands, including architectural appearance and glandular formation, is used by pathologists to inform prognosis and plan the treatment of individual patients. However, achieving good inter-observer as well as intra-observer reproducibility of cancer grading is still a major challenge in modern pathology. An automated approach which quantifies the morphology of glands is a solution to the problem. This paper provides an overview to the Gland Segmentation in Colon Histology Images Challenge Contest (GlaS) held at MICCAI'2015. Details of the challenge, including organization, dataset and evaluation criteria, are presented, along with the method descriptions and evaluation results from the top performing methods.

Medical Students' Perceptions of Clinical Teachers as Role Model.

INTRODUCTION: Role models facilitate student learning and assists in the development of professional identity. However, social organization and cultural values influence the choice of role models. Considering that the social organization and cultural values in South East Asia are different from other countries, it is important to know whether this affects the characteristics medical students look for in their role models in these societies. METHODS: A 32 item questionnaire was developed and self-administered to undergraduate medical students. Participants rated the characteristics on a three point scale (0 = not important, 1 = mildly important, 2 = very important). One way ANOVA and student's t-test were used to compare the groups. RESULTS: A total of 349 (65.23%) distributed questionnaires were returned. The highest ranked themes were teaching and facilitating learning, patient care and continuing professional development followed by communication and professionalism. Safe environment and guiding personal and professional development was indicated least important. Differences were also observed between scores obtained by males and females. CONCLUSION: Globally there are attributes which are perceived as essential for role models, while others are considered desirable. An understanding of the attributes which are essential and desirable for role models can help medical educators devise strategies which can reinforce those attributes within their institutions.

Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images.

Detection and classification of cell nuclei in histopathology images of cancerous tissue stained with the standard hematoxylin and eosin stain is a challenging task due to cellular heterogeneity. Deep learning approaches have been shown to produce encouraging results on histopathology images in various studies. In this paper, we propose a Spatially Constrained Convolutional Neural Network (SC-CNN) to perform nucleus detection. SC-CNN regresses the likelihood of a pixel being the center of a nucleus, where high probability values are spatially constrained to locate in the vicinity of the centers of nuclei. For classification of nuclei, we propose a novel Neighboring Ensemble Predictor (NEP) coupled with CNN to more accurately predict the class label of detected cell nuclei. The proposed approaches for detection and classification do not require segmentation of nuclei. We have evaluated them on a large dataset of colorectal adenocarcinoma images, consisting of more than 20,000 annotated nuclei belonging to four different classes. Our results show that the joint detection and classification of the proposed SC-CNN and NEP produces the highest average F1 score as compared to other recently published approaches. Prospectively, the proposed methods could offer benefit to pathology practice in terms of quantitative analysis of tissue constituents in whole-slide images, and potentially lead to a better understanding of cancer.

Validation of digital pathology imaging for primary histopathological diagnosis.

AIMS: Digital pathology (DP) offers advantages over glass slide microscopy (GS), but data demonstrating a statistically valid equivalent (i.e. non-inferior) performance of DP against GS are required to permit its use in diagnosis. The aim of this study is to provide evidence of non-inferiority. METHODS AND RESULTS: Seventeen pathologists re-reported 3017 cases by DP. Of these, 1009 were re-reported by the same pathologist, and 2008 by a different pathologist. Re-examination of 10 138 scanned slides (2.22 terabytes) produced 72 variances between GS and DP reports, including 21 clinically significant variances. Ground truth lay with GS in 12 cases and with DP in nine cases. These results are within the 95% confidence interval for existing intraobserver and interobserver variability, proving that DP is non-inferior to GS. In three cases, the digital platform was deemed to be responsible for the variance, including a gastric biopsy, where Helicobacter pylori only became visible on slides scanned at the ×60 setting, and a bronchial biopsy and penile biopsy, where dysplasia was reported on DP but was not present on GS. CONCLUSIONS: This is one of the largest studies proving that DP is equivalent to GS for the diagnosis of histopathology specimens. Error rates are similar in both platforms, although some problems e.g. detection of bacteria, are predictable.

A Stochastic Polygons Model for Glandular Structures in Colon Histology Images.

In this paper, we present a stochastic model for glandular structures in histology images of tissue slides stained with Hematoxylin and Eosin, choosing colon tissue as an example. The proposed Random Polygons Model (RPM) treats each glandular structure in an image as a polygon made of a random number of vertices, where the vertices represent approximate locations of epithelial nuclei. We formulate the RPM as a Bayesian inference problem by defining a prior for spatial connectivity and arrangement of neighboring epithelial nuclei and a likelihood for the presence of a glandular structure. The inference is made via a Reversible-Jump Markov chain Monte Carlo simulation. To the best of our knowledge, all existing published algorithms for gland segmentation are designed to mainly work on healthy samples, adenomas, and low grade adenocarcinomas. One of them has been demonstrated to work on intermediate grade adenocarcinomas at its best. Our experimental results show that the RPM yields favorable results, both quantitatively and qualitatively, for extraction of glandular structures in histology images of normal human colon tissues as well as benign and cancerous tissues, excluding undifferentiated carcinomas.

Caspase-9 mediates photoreceptor death after blunt ocular trauma.

PURPOSE: Ocular trauma is common in civilian and military populations. Commotio retinae involves acute disruption of photoreceptor outer segments after blunt ocular trauma, with subsequent photoreceptor apoptosis causing permanent visual impairment. The mechanisms of photoreceptor death in commotio retinae have not previously been described, although caspase-dependent death is important in other nontraumatic retinal degenerations. We assessed the role of caspase-9 as a mediator of photoreceptor death in a rat model of ballistic ocular trauma causing commotio retinae. METHODS: Bilateral commotio retinae was induced in rats by ballistic ocular trauma. Caspase-9 activity was assessed by immunohistochemistry, Western blotting, and bVAD-fmk active caspase capture. Caspase-9 was inhibited by unilateral intravitreal injection of highly specific X-linked inhibitor of apoptosis (IAP) baculoviral IAP repeat 3 (XBIR3) domain linked to the cell transduction peptide penetratin 1 (Pen-1) after ballistic injury, and the affected eyes were compared with control eyes treated with Pen-1 injection alone, and retinal function was assessed by electroretinogram a-wave amplitude and photoreceptor survival by outer nuclear layer thickness. RESULTS: Increased levels of cleaved caspase-9 were shown in photoreceptors 5 hours after injury, and catalytically active full-length caspase-9 was isolated from retinas. Photoreceptor death after commotio retinae was reduced by caspase-9 inhibition by using Pen-1-XBIR3, and electroretinographic measurements of photoreceptor function was preserved, providing structural and functional neuroprotection. CONCLUSIONS: The time course of caspase-9 activation and the neuroprotective effects of inhibition suggest that caspase-9 initiates cell death in a proportion of photoreceptors after blunt ocular trauma and that an intravitreally delivered biologic inhibitor may be an effective translational treatment strategy.

Elevated soluble CD163 in gestational diabetes mellitus: secretion from human placenta and adipose tissue.

Recently soluble CD163 (sCD163), a cleaved form of the macrophage receptor CD163, was identified as a macrophage-specific risk-predictor for developing Type 2 Diabetes. Here, we investigate circulating levels of sCD163 in gestational diabetes mellitus (GDM). Furthermore, given the role of the placenta in the pathogenesis of GDM, we assessed placental contribution to sCD163 secretion. Paired maternal (venous) and umbilical vein blood samples from GDM (n = 18) and Body Mass Index (BMI) matched control women (n = 20) delivered by caesarean section at 39-40 week gestation were assessed for circulating levels of sCD163, Tumour necrosis factor alpha (TNF-α) and Interleukin 6 (IL-6). Media from explant culture of maternal subcutaneous fat and corresponding placental tissues were assayed for these same molecules. CD163 positive cell numbers were determined in placental and adipose tissues of GDM and control women. We found significantly elevated circulating sCD163 levels in GDM mothers (688.4±46.9 ng/ml vs. 505.6±38.6 ng/ml) and their offspring (418.2±26.6 ng/ml vs. 336.3±24.4 ng/ml [p<0.05 for both]) as compared to controls, together with elevated circulating TNF-α and IL-6 levels. Moreover, both GDM placentae (268.1±10.8 ng/ml/mg vs. 187.6±20.6 ng/ml/mg) and adipose explants (41.1±2.7 ng/ml/mg vs. 26.6±2.4 ng/ml/mg) released significantly more sCD163 than controls. Lastly, significantly more CD163 positive cells were observed in GDM placentae (25.7±1.1 vs. 22.1±1.2) and adipose tissue (19.1±1.1 vs 12.7±0.9) compared to controls. We describe elevated sCD163 levels in GDM and identify human placenta as a novel source of sCD163 suggesting that placental tissues might contribute to the increased levels of circulating sCD163 in GDM pregnancies.

BAI3, CDX2 and VIL1: a panel of three antibodies to distinguish small cell from large cell neuroendocrine lung carcinomas.

AIMS: Discriminating small-cell lung carcinoma (SCLC) from large-cell neuroendocrine carcinoma (LCNEC) rests on morphological criteria, and reproducibility has been shown to be poor. We aimed to identify immunohistochemical markers to assist this diagnosis. METHODS AND RESULTS: Gene expression profiling on laser captured frozen tumour samples from eight SCLC and eight LCNEC tumours identified a total of 888 differentially expressed genes (DEGs), 23 of which were validated by qRT-PCR. Antibodies to four selected gene products were then evaluated as immunohistochemical markers on a cohort of 173 formalin-fixed paraffin-embedded (FFPE) SCLC/LCNEC tumour samples, including 26 indeterminate tumours without a consensus diagnosis. Three markers, CDX2, VIL1 and BAI3, gave significantly different results in the two tumour types (P < 0.0001): CDX2 and VIL1 in combination (either marker positive) showed sensitivity and specificity of 81% for LCNEC while BAI3 showed 89% sensitivity and 75% specificity for SCLC. Of the 26 indeterminate tumours 15 (58%) showed an immunophenotype suggesting either SCLC or LCNEC, eight (31%) showed staining of both tumour types, and three (11%) were negative for all markers. CONCLUSION: A panel of three markers, BAI3, CDX2 and VIL1, is a useful adjunct in the diagnosis of these tumour types.

Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics.

Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper, we present an extension of the BHC algorithm. Our Gaussian BHC (GBHC) algorithm represents data as a mixture of Gaussian distributions. It uses normal-gamma distribution as a conjugate prior on the mean and precision of each of the Gaussian components. We tested GBHC over 11 cancer and 3 synthetic datasets. The results on cancer datasets show that in sample clustering, GBHC on average produces a clustering partition that is more concordant with the ground truth than those obtained from other commonly used algorithms. Furthermore, GBHC frequently infers the number of clusters that is often close to the ground truth. In gene clustering, GBHC also produces a clustering partition that is more biologically plausible than several other state-of-the-art methods. This suggests GBHC as an alternative tool for studying gene expression data. The implementation of GBHC is available at https://sites.google.com/site/gaussianbhc/

Neuroretinal cell death in a murine model of closed globe injury: pathological and functional characterization.

PURPOSE: Blunt ocular trauma causes severe retinal injury with death of neuroretinal tissue, scarring, and permanent visual loss. The mechanisms of cell death are not known, and there are no therapeutic interventions that improve visual outcome. We aimed to study the extent, distribution, and functional consequences of cell death by developing and characterizing a rat model of retinal injury caused by blunt ocular trauma. METHODS: The eyes of anesthetized adult rats were injured by either weight drop or low-velocity ballistic trauma and assessed by clinical examination, electroretinography, light microscopy, electron microscopy, and TUNEL. Projectile velocity was measured and standardized. RESULTS: Weight drop did not cause reproducible retinal injury, and the energy threshold for retinal injury was similar to that for rupture. Low-velocity ballistic trauma to the inferior sclera created a reproducible retinal injury, with central sclopetaria retinae, retinal necrosis, and surrounding commotio retinae with specific photoreceptor cell death and sparing of cells in the other retinal layers. The extent of photoreceptor cell death declined and necrosis progressed to apoptosis with increasing distance from the impact site. CONCLUSIONS: This is the only murine model of closed globe injury and the only model of retinal trauma with specific photoreceptor cell death. The clinical appearance mirrors that in severe retinal injury after blunt ocular trauma in humans, and the ultrastructural features are consistent with human and animal studies of commotio retinae. After ocular trauma, photoreceptor apoptosis may be prevented and visual outcomes improved by blocking of the cell death pathways.

Differences in amyloid deposition in primary and recurrent corneal lattice dystrophy type 1.

PURPOSE: To report the histopathology of a case of recurrent corneal lattice dystrophy showing altered distribution of the corneal deposits in the recurrent disease compared with the original. METHODS: Clinical details and histopathology of the primary and repeat corneal grafts are reported. RESULTS: A woman originally presented at age 28 years with reduced visual acuity and classic corneal lattice lines in both corneas and underwent bilateral corneal grafts. Recurrent disease was detected 20 years later as anterior haze and various-sized subepithelial opacities but no stromal lattice lines. Histology of the original corneas demonstrated amyloid deposits throughout the corneal stroma, typical of corneal lattice dystrophy. In the repeat grafts, amyloid deposits were confined to the basement membrane region of the anterior cornea and were almost entirely absent from the stroma of the cornea. CONCLUSION: Recurrence of corneal lattice dystrophy is widely recognized to occur, but the pathology of the recurrent disease is not well documented in the literature. This case report highlights that there may be a difference in the distribution of the deposits when the disease recurs. We postulate that the reason for this difference may be that donor keratocytes survive long enough in the transplanted cornea to prevent build-up of abnormal keratoepithelin, the product of the mutated gene in type 1 corneal lattice dystrophy. By contrast, the epithelium, being replaced by host epithelium shortly after grafting, is still producing abnormal protein. The differences in the pattern of deposits may have important clinical implications, particularly regarding treatment modalities in recurrent disease.