Egevad Lars, Camilloni Andrea, Delahunt Brett, Samaratunga Hemamali, Eklund Martin, Kartasalo Kimmo
Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Pathol Int. 2025 May;75(5):213-220. doi: 10.1111/pin.70015. Epub 2025 Apr 14.
Artificial intelligence (AI) is an emerging tool in diagnostic pathology, including prostate pathology. This review summarizes the possibilities offered by AI and also discusses the challenges and risks. AI has the potential to assist in the diagnosis and grading of prostate cancer. Diagnostic safety can be enhanced by avoiding the accidental underdiagnosis of small lesions. Another possible benefit is a greater degree of standardization of grading. AI for clinical use needs to be trained on large, high-quality data sets that have been assessed by experienced pathologists. A problem with the use of AI in prostate pathology is the plethora of benign mimics of prostate cancer and morphological variants of cancer that are too unusual to allow sufficient training of AI. AI systems need to be able to account for variations in local routines for cutting, staining, and scanning of slides. We also need to be aware of the risk that users will rely too much on the output of an AI system, leading to diagnostic errors and loss of clinical competence. The reporting pathologist must ultimately be responsible for accepting or rejecting the diagnosis proposed by AI.
人工智能（AI）是诊断病理学领域，包括前列腺病理学领域中一种新兴的工具。本综述总结了人工智能带来的可能性，并讨论了挑战和风险。人工智能有潜力辅助前列腺癌的诊断和分级。通过避免偶然漏诊小病变可提高诊断安全性。另一个可能的益处是分级的标准化程度更高。用于临床的人工智能需要在由经验丰富的病理学家评估过的大型高质量数据集上进行训练。在前列腺病理学中使用人工智能存在的一个问题是前列腺癌的大量良性模仿病变以及过于罕见而无法让人工智能得到充分训练的癌症形态学变异。人工智能系统需要能够考虑到切片切割、染色和扫描的当地常规操作中的差异。我们还需要意识到用户过度依赖人工智能系统输出结果的风险，这可能导致诊断错误和临床能力丧失。最终，报告病理学家必须对接受或拒绝人工智能提出的诊断负责。
