Immunohistochemical analysis of T-cell subsets in the inflammatory infiltrates of alopecia areata and its comparison with androgenetic alopecia

نویسندگان

  • Afshin Moradi Pathology Department, Shohada- Tajrish Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Azadeh Rakhshan Pathology Department, Shohada- Tajrish Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Hedieh Peiroolia Pathology Department, Shohada- Tajrish Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
چکیده مقاله:

Background: Androgenic hair loss (AGA) and alopecia areata (AA) are common conditions which sometimes are histologically difficult to differentiate. This study was conducted to detect differentiating features of these two disorders with IHC analysis of T-cell subsets in the inflammatory infiltrates of alopecia areata and androgenetic alopecia. Methods: This cross-sectional study was conducted at Shohadae-Tajrish Hospital in 2018. Twenty-eight cases of alopecia areata and 32 androgenic hair loss cases were evaluated. H&E; and IHC staining for CD3, CD4, and CD8+ T-lymphocytes were performed. Lymphocytic densities were graded in a quintet grading system. The inflammation density in various areas of skin tissue was evaluated. Statistical analysis was performed using SPSS version 21. Results: Peribulbar lymphocytic infiltration was seen in 88.5% of AA patients and 12.5% of AGA patients (P = 0.000). Presence of melanin, pigmented casts, and lymphocytes in follicular stelawere in favor of AA diagnosis. CD3, CD4, and CD8+ T-cells in follicular stela, peri-bulbar, and subcutaneous regions were higher and denser in AA patients, while CD3 and CD4+ T-cells aroundsebaceous ducts were in favor of AGA diagnosis. Conclusion: Peribulbar lymphocytic infiltration is among the most important differentiating features of AA and AGA. Infiltration of T-cells in various regions of skin tissue has high diagnosticvalue. Histologic and immunohistochemical evaluation of skin tissues according to these factors can differentiate these two entities with high precision.

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عنوان ژورنال

دوره 23  شماره 1

صفحات  21- 27

تاریخ انتشار 2020-04-01

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