4 research outputs found
Interobserver agreement in dysplasia grading: toward an enhanced gold standard for clinical pathology trials
Objective: Interobserver agreement in the context of oral epithelial dysplasia (OED) grading has been notoriously unreliable and can impose barriers for developing new molecular markers and diagnostic technologies. This paper aimed to report the details of a 3-stage histopathology review and adjudication process with the goal of achieving a consensus histopathologic diagnosis of each biopsy. Study Design: Two adjacent serial histologic sections of oral lesions from 846 patients were independently scored by 2 different pathologists from a pool of 4. In instances where the original 2 pathologists disagreed, a third, independent adjudicating pathologist conducted a review of both sections. If a majority agreement was not achieved, the third stage involved a face-to-face consensus review. Results: Individual pathologist pair κ values ranged from 0.251 to 0.706 (fair-good) before the 3-stage review process. During the initial review phase, the 2 pathologists agreed on a diagnosis for 69.9% of the cases. After the adjudication review by a third pathologist, an additional 22.8% of cases were given a consensus diagnosis (agreement of 2 out of 3 pathologists). After the face-to-face review, the remaining 7.3% of cases had a consensus diagnosis. Conclusions: The use of the defined protocol resulted in a substantial increase (30%) in diagnostic agreement and has the potential to improve the level of agreement for establishing gold standards for studies based on histopathologic diagnosis
‘Cytology-on-a-chip’ based sensors for monitoring of potentially malignant oral lesions
Despite significant advances in surgical procedures and treatment, long-term prognosis for patients with oral cancer remains poor, with survival rates among the lowest of major cancers. Better methods are desperately needed to identify potential malignancies early when treatments are more effective. Objective To develop robust classification models from cytology-on-a-chip measurements that mirror diagnostic performance of gold standard approach involving tissue biopsy. Materials and methods Measurements were recorded from 714 prospectively recruited patients with suspicious lesions across 6 diagnostic categories (each confirmed by tissue biopsy -histopathology) using a powerful new ‘cytology-on-a-chip’ approach capable of executing high content analysis at a single cell level. Over 200 cellular features related to biomarker expression, nuclear parameters and cellular morphology were recorded per cell. By cataloging an average of 2000 cells per patient, these efforts resulted in nearly 13 million indexed objects. Results Binary “low-risk”/“high-risk” models yielded AUC values of 0.88 and 0.84 for training and validation models, respectively, with an accompanying difference in sensitivity + specificity of 6.2%. In terms of accuracy, this model accurately predicted the correct diagnosis approximately 70% of the time, compared to the 69% initial agreement rate of the pool of expert pathologists. Key parameters identified in these models included cell circularity, Ki67 and EGFR expression, nuclear-cytoplasmic ratio, nuclear area, and cell area. Conclusions This chip-based approach yields objective data that can be leveraged for diagnosis and management of patients with PMOL as well as uncovering new molecular-level insights behind cytological differences across the OED spectrum
Nuclear F-actin cytology in oral dysplasia and oral squamous cell carcinoma
Oral cavity cancer has a low 5-y survival rate, but outcomes improve when the disease is detected early. Cytology is a less invasive method to assess oral potentially malignant disorders relative to the gold-standard scalpel biopsy and histopathology. In this report, we aimed to determine the utility of cytological signatures, including nuclear F-actin cell phenotypes, for classifying the entire spectrum of oral epithelial dysplasia and oral squamous cell carcinoma. We enrolled subjects with oral potentially malignant disorders, subjects with previously diagnosed malignant lesions, and healthy volunteers without lesions and obtained brush cytology specimens and matched scalpel biopsies from 486 subjects. Histopathological assessment of the scalpel biopsy specimens classified lesions into 6 categories. Brush cytology specimens were analyzed by machine learning classifiers trained to identify relevant cytological features. Multimodal diagnostic models were developed using cytology results, lesion characteristics, and risk factors. Squamous cells with nuclear F-actin staining were associated with early disease (i.e., lower proportions in benign lesions than in more severe lesions), whereas small round parabasal-like cells and leukocytes were associated with late disease (i.e., higher proportions in severe dysplasia and carcinoma than in less severe lesions). Lesions with the impression of oral lichen planus were unlikely to be either dysplastic or malignant. Cytological features substantially improved upon lesion appearance and risk factors in predicting squamous cell carcinoma. Diagnostic models accurately discriminated early and late disease with AUCs (95% CI) of 0.82 (0.77 to 0.87) and 0.93 (0.88 to 0.97), respectively. The cytological features identified here have the potential to improve screening and surveillance of the entire spectrum of oral potentially malignant disorders in multiple care settings