Histopathologic diagnosis of alopecia: clues and pitfalls in the follicular microcosmos

Stefanato, Catherine M.

doi:10.1016/j.mpdhp.2019.12.003

Cited by 2 publications

(2 citation statements)

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“…Direct immunofluorescence studies (DIF) is of particular value where cutaneous lupus erythematosus and autoimmune blistering conditions are considered in the differential diagnosis. It is important that careful attention is paid to site selection with DIF sampling taking place at the periphery of an active site of inflammation [ 2 ].…”

Section: Sample Processing and Pathology Reportingmentioning

confidence: 99%

“…Scalp skin biopsies can be a useful tool in identifying the underlying pathological process, help guide management, and ultimately establishes realistic treatment goals. Appropriate biopsy site selection along with close communication between the clinician and histopathologist will improve the chance of an accurate diagnosis and is considered advantageous in determining the procedural approach and management plan for these complex patients [ 1 , 2 ].…”

Section: Introductionmentioning

confidence: 99%

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Scarring Alopecias: Pathology and an Update on Digital Developments

2021

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Primary cicatricial alopecias (PCA) represent a challenging group of disorders that result in irreversible hair loss from the destruction and fibrosis of hair follicles. Scalp skin biopsies are considered essential in investigating these conditions. Unfortunately, the recognised complexity of histopathologic interpretation is compounded by inadequate sampling and inappropriate laboratory processing. By sharing our successes in developing the communication pathway between the clinician, laboratory and histopathologist, we hope to mitigate some of the difficulties that can arise in managing these conditions. We provide insight from clinical and pathology practice into how diagnoses are derived and the key histological features observed across the most common PCAs seen in practice. Additionally, we highlight the opportunities that have emerged with advances in digital pathology and how these technologies may be used to develop clinicopathological relationships, improve working practices, enhance remote learning, reduce inefficiencies, optimise diagnostic yield, and harness the potential of artificial intelligence (AI).

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Section: Sample Processing and Pathology Reportingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%