Abstract
Histological examination of biopsy material is imperative to diagnosis. It consists of three stages before the histological slide can be interpreted: tissue fixation, tissue processing and staining. Following this, the stained slide is analysed by a histopathologist, who makes a diagnosis depending on factors including morphological features, as well as the use of further stains such as immuno-histochemistry. There are many new developments within uropathology, including the use of molecular techniques in newly defined renal neoplasms, new immunohistochemical stains and, with respect to prostate cancer, the potential future use of Artificial Intelligence.
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Further Reading
Suvarna SK, Layton C, Bancroft JD. Bancroft’s theory and practice of histological techniques. 8th ed. Elsevier Health Sciences; 2018.
Nagpal K, Foote D, Liu Y, Chen PHC, Wulczyn E, Tan F, et al. Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer. Npj Digit Med. 2019;2(48) https://doi.org/10.1038/s41746-019-0112-2.
Bulten W, Kartasalo K, Chen PHC, Ström P, Pinckaers H, Nagpal K, et al. Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge. Nat Med. 2022;(13):154–63.
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Miller, T. (2023). Histopathological Processing, Staining and Immuno-Histochemistry. In: Tolofari, S., Moon, D., Starmer, B., Payne, S. (eds) Imaging and Technology in Urology . Springer, Cham. https://doi.org/10.1007/978-3-031-26058-2_33
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DOI: https://doi.org/10.1007/978-3-031-26058-2_33
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