Dataset Information

Reliability of Histopathology for the Early Recognition of Fibrosis in Traction Alopecia: Correlation with Clinical Severity.

ABSTRACT: Traction alopecia (TA) is hair loss caused by prolonged pulling or repetitive tension on scalp hair; it belongs to the biphasic group of primary alopecia. It is non-scarring, typically with preservation of follicular stem cells and the potential for regrowth of early lesions especially if traction hairstyles are stopped. However, the alopecia may become permanent (scarring) and fail to respond to treatment if the traction is excessive and prolonged. Hence, the ability to detect fibrosis early in these lesions could predict patients who respond to treatment. Histopathological diagnosis based on scalp biopsies has been used as a gold standard to delineate various forms of non-scarring alopecia and to differentiate them from scarring ones. However, due to potential discrepant reporting as a result of the type of biopsy, method of sectioning, and site of biopsy, histopathology often tends to be unreliable for the early recognition of fibrosis in TA. In this study, 45 patients were assessed using the marginal TA severity scoring system, and their biopsies (both longitudinal and transverse sections) were systematically assessed by three dermatopathologists, the aim being to correlate histopathological findings with clinical staging. Intraclass correlation coefficients were used to determine the level of agreement between the assessors. We found poor agreement of the identification and grading of perifollicular and interfollicular fibrosis (0.55 [0.23-0.75] and 0.01 [2.20-0.41], respectively), and no correlation could be drawn with the clinical severity score. Better methods of diagnosis are needed for grading and for recognition of early fibrosis in TA.

SUBMITTER: Ngwanya RM

PROVIDER: S-EPMC6827454 | biostudies-literature | 2019 Apr-Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Reliability of Histopathology for the Early Recognition of Fibrosis in Traction Alopecia: Correlation with Clinical Severity.

Ngwanya Reginald Mzudumile RM Adeola Henry Ademola HA Beach Renée A RA Gantsho Nomphelo N Walker Christopher L CL Pillay Komala K Prokopetz Robert R Gumedze Freedom F Khumalo Nonhlanhla P NP

Dermatopathology (Basel, Switzerland) 20190401 2

Traction alopecia (TA) is hair loss caused by prolonged pulling or repetitive tension on scalp hair; it belongs to the biphasic group of primary alopecia. It is non-scarring, typically with preservation of follicular stem cells and the potential for regrowth of early lesions especially if traction hairstyles are stopped. However, the alopecia may become permanent (scarring) and fail to respond to treatment if the traction is excessive and prolonged. Hence, the ability to detect fibrosis early in ...[more]

PMID: 31700859

Similar Datasets

Project description:Tumors are heterogeneous tissues with different types of cells such as cancer cells, fibroblasts, and lymphocytes. Although the morphological features of tumors are critical for cancer diagnosis and prognosis, the underlying molecular events and genes for tumor morphology are far from being clear. With the advancement in computational pathology and accumulation of large amount of cancer samples with matched molecular and histopathology data, researchers can carry out integrative analysis to investigate this issue. In this study, we systematically examine the relationships between morphological features and various molecular data in breast cancers. Specifically, we identified 73 breast cancer patients from the TCGA and CPTAC projects matched whole slide images, RNA-seq, and proteomic data. By calculating 100 different morphological features and correlating them with the transcriptomic and proteomic data, we inferred four major biological processes associated with various interpretable morphological features. These processes include metabolism, cell cycle, immune response, and extracellular matrix development, which are all hallmarks of cancers and the associated morphological features are related to area, density, and shapes of epithelial cells, fibroblasts, and lymphocytes. In addition, protein specific biological processes were inferred solely from proteomic data, suggesting the importance of proteomic data in obtaining a holistic understanding of the molecular basis for tumor tissue morphology. Furthermore, survival analysis yielded specific morphological features related to patient prognosis, which have a strong association with important molecular events based on our analysis. Overall, our study demonstrated the power for integrating multiple types of biological data for cancer samples in generating new hypothesis as well as identifying potential biomarkers predicting patient outcome. Future work includes causal analysis to identify key regulators for cancer tissue development and validating the findings using more independent data sets.

Dataset Information

Reliability of Histopathology for the Early Recognition of Fibrosis in Traction Alopecia: Correlation with Clinical Severity.

Publications

Reliability of Histopathology for the Early Recognition of Fibrosis in Traction Alopecia: Correlation with Clinical Severity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure