(1) Background: Digital pathology (DP) is transforming the landscape of clinical practice, offering a revolutionary approach to traditional pathology analysis and diagnosis. (2) Methods: This innovative technology involves the digitization of traditional glass slides which enables pathologists to access, analyze, and share high-resolution whole-slide images (WSI) of tissue specimens in a digital format. By integrating cutting-edge imaging technology with advanced software, DP promises to enhance clinical practice in numerous ways. DP not only improves quality assurance and standardization but also allows remote collaboration among experts for a more accurate diagnosis. Artificial intelligence (AI) in pathology significantly improves cancer diagnosis, classification, and prognosis by automating various tasks. It also enhances the spatial analysis of tumor microenvironment (TME) and enables the discovery of new biomarkers, advancing their translation for therapeutic applications. (3) Results: The AI-driven immune assays, Immunoscore (IS) and Immunoscore-Immune Checkpoint (IS-IC), have emerged as powerful tools for improving cancer diagnosis, prognosis, and treatment selection by assessing the tumor immune contexture in cancer patients. Digital IS quantitative assessment performed on hematoxylin–eosin (H&E) and CD3+/CD8+ stained slides from colon cancer patients has proven to be more reproducible, concordant, and reliable than expert pathologists’ evaluation of immune response. Outperforming traditional staging systems, IS demonstrated robust potential to enhance treatment efficiency in clinical practice, ultimately advancing cancer patient care. Certainly, addressing the challenges DP has encountered is essential to ensure its successful integration into clinical guidelines and its implementation into clinical use. (4) Conclusion: The ongoing progress in DP holds the potential to revolutionize pathology practices, emphasizing the need to incorporate powerful AI technologies, including IS, into clinical settings to enhance personalized cancer therapy.
（1）背景：数字病理学正在重塑临床实践的格局，为传统病理学分析与诊断带来革命性突破。（2）方法：这项创新技术通过将传统玻璃切片数字化，使病理学家能够以数字形式访问、分析和共享组织标本的高分辨率全切片图像。通过将尖端成像技术与先进软件相结合，数字病理学有望从多个维度提升临床实践水平。它不仅能够强化质量保证与标准化流程，还支持专家远程协作以实现更精准的诊断。病理学中的人工智能技术通过自动化多项任务，显著提升了癌症诊断、分类及预后评估水平。该技术同时增强了肿瘤微环境的空间分析能力，推动新型生物标志物的发现及其在治疗应用中的转化。（3）结果：基于人工智能的免疫检测技术——免疫评分和免疫评分-免疫检查点，通过评估癌症患者的肿瘤免疫微环境，已成为改善癌症诊断、预后判断和治疗方案选择的重要工具。对结肠癌患者苏木精-伊红染色及CD3+/CD8+染色切片进行的数字化免疫评分定量评估，相较于病理专家对免疫反应的主观评估，展现出更优的可重复性、一致性和可靠性。免疫评分技术超越了传统分期系统的局限，在临床实践中显示出提升治疗效率的强大潜力，最终推动癌症患者诊疗水平的进步。当然，解决数字病理学面临的技术挑战，对于确保其成功融入临床指南并实现临床应用至关重要。（4）结论：数字病理学的持续发展有望彻底变革病理学实践模式，这凸显了将包括免疫评分在内的先进人工智能技术整合到临床环境中，以提升个性化癌症治疗水平的迫切需求。
肿瘤(癌症)患者之家