Inter- and Intra-Observer Variability in Diagnosis of Oral Dysplasia

Biological biomarkers of oral cancer

The oral squamous cell carcinoma (OSCC) 5 year survival rate of 41% has marginally improved in the last few years, with less than a 1% improvement per year from 2005 to 2017, with higher survival rates when detected at early stages. Based on histopathological grading of oral dysplasia, it is estimated that severe dysplasia has a malignant transformation rate of 7%-50%. Despite these numbers, oral dysplasia grading does not reliably predict its clinical behavior. Thus, more accurate markers predicting oral dysplasia progression to cancer would enable better targeting of these lesions for closer follow-up, especially in the early stages of the disease. In this context, molecular biomarkers derived from genetics, proteins, and metabolites play key roles in clinical oncology. These molecular signatures can help predict the likelihood of OSCC development and/or progression and have the potential to detect the disease at an early stage and, support treatment decision-making and predict treatment responsiveness. Also, identifying reliable biomarkers for OSCC detection that can be obtained non-invasively would enhance management of OSCC. This review will discuss biomarkers for OSCC that have emerged from different biological areas, including genomics, transcriptomics, proteomics, metabolomics, immunomics, and microbiomics.

Ki-67 Expression as a Prognostic Marker: A Comparative Immunohistochemical Analysis of Oral Epithelial Dysplasia and Oral Squamous Cell Carcinoma

Introduction Oral dysplasia is a frequent precancerous condition that may lead to oral cancer. The histopathologic abnormalities exhibited in a chronic, progressive, and premalignant condition of the oral mucosa are referred to as oral epithelial dysplasia (OED). It might show up as erythroplakia, leukoplakia, or leukoerythroplakia. OED is a premalignancy histologic marker that predicts a higher likelihood of squamous cell carcinoma development. Aims and objectives The aim of this study is to identify an association between Ki-67 protein expression and histological grading of OED and oral squamous cell carcinoma (OSCC) and to compare the expression of Ki-67 in different grades of OED and OSCC with the prognosis. Materials and methods The current retrospective research is focused on evaluating epithelial dysplasia and analyzing the function of Ki-67 as a prognostic marker after receiving institutional ethical approval. Group I - normal oral mucosa (NOM), Group II - OED, and Group III - OSCC were included in the study. For statistical analysis, SPSS Statistics version 21.0 (IBM Corp. Released 2021. IBM SPSS Statistics for Windows, Version 28.0. Armonk, NY: IBM Corp) was utilized. The Cox regression model was employed to look at interactions between various prognostic variables. At p<0.05, differences were deemed statistically significant. Results Ki-67 expression was confined to the basal layers in the normal oral epithelium and in the basal, suprabasal, and spinous layers in OED. Ki-67 positive cells were mostly found on the perimeter of well, moderate, and poorly differentiated OSCC tumor nests with Ki-67 positive cells scattered throughout OSCC. According to statistical analysis, there is a substantial difference in expression between OED and NOM, OSCC and NOM, and OED and OSCC. Conclusion Our study showed that there is a progressive increase in Ki-67 expression across various grades of OED, and the highest expression was noted in OSCC. Early identification and prompt treatment will help in improving the quality of life of such patients.

Oral Epithelial Dysplasia Grading Systems: A Systematic Review & Meta-Analysis

This systematic review and meta-analysis aims to provide a robust qualitative and quantitative analysis of the different systems used to assess the grade of oral epithelial dysplasia (OED). This study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-analyzes (PRISMA) statement. Six electronic databases were searched for primary research published over the past four decades. Overall quality and level of evidence were based on the Johns Hopkins Research Evidence Appraisal Tool, while evidence of heterogeneity was determined by the Q-statistic and I^{^2} statistic. Evidence of publication bias was determined using Egger's regression and the Rank correlation tests. A total of 170 records were identified. Only 9 primary research articles were included in the qualitative systematic review. Four studies (4/9) were included in the final quantitative meta-analysis. The grading systems analyzed included the WHO, binary, Ljubljana, Smith and Pindborg, Brothwell, and the oral intraepithelial neoplasia. The results demonstrate the binary system to be superior to the WHO system in grading OED, by providing better inter-observer agreement, however, the substantial error among the inter-observer κ values analyzed indicates the significance of this finding to be of minimal impact. Lack of reliable reproducibility of the grading systems and lack of common effect size (heterogeneity analysis) were noted.

Deep learning system for lymph node quantification and metastatic cancer identification from whole-slide pathology images

BACKGROUND

Traditional diagnosis methods for lymph node metastases are labor-intensive and time-consuming. As a result, diagnostic systems based on deep learning (DL) algorithms have become a hot topic. However, current research lacks testing with sufficient data to verify performance. The aim of this study was to develop and test a deep learning system capable of identifying lymph node metastases.

METHODS

921 whole-slide images of lymph nodes were divided into two cohorts: training and testing. For lymph node quantification, we combined Faster RCNN and DeepLab as a cascade DL algorithm to detect regions of interest. For metastatic cancer identification, we fused Xception and DenseNet-121 models and extracted features. Prospective testing to verify the performance of the diagnostic system was performed using 327 unlabeled images. We further validated the proposed system using Positive Predictive Value (PPV) and Negative Predictive Value (NPV) criteria.

RESULTS

We developed a DL-based system capable of automated quantification and identification of metastatic lymph nodes. The accuracy of lymph node quantification was shown to be 97.13%. The PPV of the combined Xception and DenseNet-121 model was 93.53%, and the NPV was 97.99%. Our experimental results show that the differentiation level of metastatic cancer affects the recognition performance.

CONCLUSIONS

The diagnostic system we established reached a high level of efficiency and accuracy of lymph node diagnosis. This system could potentially be implemented into clinical workflow to assist pathologists in making a preliminary screening for lymph node metastases in gastric cancer patients.

Grading of Oral Leukoplakia: Can It be Improvised Using Immunohistochemical Markers p63 and CD31

Introduction

Oral squamous cell carcinoma is usually preceded by potentially malignant disorders (PMDs), the most common being oral leukoplakia. A conservative management protocol is followed for milder dysplastic cases, while severe dysplastic lesions are surgically excised. Several classification systems have been developed based mainly on histopathological features with a lot of inter-observer variations. The present study was done to assess the use of immunohistochemical (IHC) markers in grading leukoplakic lesions in addition to histopathological grading.

Aims and Objectives

To grade leukoplakia using different grading systems and assess if IHC markers can aid in categorizing leukoplakia.

Materials and Methods

Thirty-five cases of leukoplakia were graded using Ljubljana, 2005 World Health Organization (WHO), and Binary System followed by IHC staining with p63 and CD31.

Results and Statistics

Variation was noted in 12 cases while using WHO, 11 using Ljubljana, and 7 using Binary System and was significant on Cohen-Kappa statistics, with the least significant variation noted on Binary System. p63 staining assisted to group doubtful cases and even identify variation in cases graded positively on histopathology. In total, 17 cases stained one-third (mild/low), while 15 cases stained one-half or more (higher grade) epithelial thickness. A weak correlation was observed between all grading systems and p63 on Kendall's Tau-b analysis and the weak correlation was significant for the WHO and binary grading systems. Analyzing p63 and CD31 using Kruskal-Wallis test, an increase in mean vessel density (MVD) was noted for mild/moderate cases but decreased for severe cases.

Conclusion

Addressing histological categorization of PMDs assisted by IHC markers to understand the biological behavior of the tissues is currently essential with studies on more markers to assist in the management protocol.

Proliferative Verrucous Leukoplakia: An Expert Consensus Guideline for Standardized Assessment and Reporting

The many diverse terms used to describe the wide spectrum of changes seen in proliferative verrucous leukoplakia (PVL) have resulted in disparate clinical management. The objective of this study was to produce an expert consensus guideline for standardized assessment and reporting by pathologists diagnosing PVL related lesions. 299 biopsies from 84 PVL patients from six institutions were selected from patients who had multifocal oral leukoplakic lesions identified over several years (a minimum follow-up period of 36 months). The lesions demonstrated the spectrum of histologic features described in PVL, and in some cases, patients developed oral cavity squamous cell carcinoma (SCC). An expert working group of oral and maxillofacial and head and neck pathologists reviewed microscopic features in a rigorous fashion, in combination with review of clinical photographs when available. The working group then selected 43 single slide biopsy cases for whole slide digital imaging (WSI) review by members of the consensus conference. The digital images were then reviewed in two surveys separated by a washout period of at least 90 days. Five non-PVL histologic mimics were included as controls. Cases were re-evaluated during a consensus conference with 19 members reporting on the cases. The best inter-observer diagnostic agreement relative to PVL lesions were classified as "corrugated ortho(para)hyperkeratotic lesion, not reactive" and "SCC" (chi-square p = 0.015). There was less than moderate agreement (kappa < 0.60) for lesions in the "Bulky hyperkeratotic epithelial proliferation, not reactive" category. There was ≥ moderate agreement (> 0.41 kappa) for 35 of 48 cases. This expert consensus guideline has been developed with support and endorsement from the leadership of the American Academy of Oral and Maxillofacial Pathology and the North American Society of Head and Neck Pathologists to recommend the use of standardized histopathologic criteria and descriptive terminology to indicate three categories of lesions within PVL: (1) "corrugated ortho(para)hyperkeratotic lesion, not reactive;" (2) "bulky hyperkeratotic epithelial proliferation, not reactive;" and (3) "suspicious for," or "squamous cell carcinoma." Classification of PVL lesions based on a combination of clinical findings and these histologic descriptive categories is encouraged in order to standardize reporting, aid in future research and potentially guide clinical management.

Inter-observer Variability in the Diagnosis of Proliferative Verrucous Leukoplakia: Clinical Implications for Oral and Maxillofacial Surgeon Understanding: A Collaborative Pilot Study

The use of diverse terminology may lead to inconsistent diagnosis and subsequent mistreatment of lesions within the proliferative verrucous leukoplakia (PVL) spectrum. The objectives of this study were: (a) to measure inter-observer variability between a variety of pathologists diagnosing PVL lesions; and (b) to evaluate the impact of diverse terminologies on understanding, interpretation, and subsequent treatment planning by oral and maxillofacial surgeons (OMFS). Six oral pathologists (OP) and six head and neck pathologists (HNP) reviewed 40 digitally scanned slides of PVL-type lesions. Inter-observer agreement on diagnoses was evaluated by Fleiss' kappa analysis. The most commonly used diagnostic terminologies were sent to ten OMFS to evaluate their resulting interpretations and potential follow-up treatment approaches. The overall means of the surgeons' responses were compared by Student t test. There was poor inter-observer agreement between pathologists on the diagnosis of PVL lesions (κ = 0.270), although there was good agreement (κ = 0.650) when diagnosing frankly malignant lesions. The lowest agreement was in diagnosing verrucous hyperplasia (VH) with/without dysplasia, atypical epithelial proliferation (AEP), and verrucous carcinoma (VC). The OMFS showed the lowest agreement on identical categories of non-malignant diagnoses, specifically VH and AEP. This study demonstrates a lack of standardized terminology and diagnostic criteria for the spectrum of PVL lesions. We recommend adopting standardized criteria and terminology, proposed and established by an expert panel white paper, to assist pathologists and clinicians in uniformly diagnosing and managing PVL spectrum lesions.