AI Article Synopsis
- Primary cicatricial alopecias (PCA) are complex disorders that lead to permanent hair loss due to damage to hair follicles, making scalp biopsies crucial for diagnosis.
- Challenges in PCA diagnosis include histopathologic interpretation difficulties, caused by poor sampling and lab techniques, but effective communication among clinicians, labs, and histopathologists can help.
- Advances in digital pathology and AI present opportunities to improve diagnosis, streamline work processes, and enhance education in managing these hair loss conditions.
Article Abstract
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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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8698437 | PMC |
| http://dx.doi.org/10.3390/biomedicines9121755 | DOI Listing |
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