Digital and Computational Pathology Applications in Bladder Cancer: Novel Tools Addressing Clinically Pressing Needs.

IF 7.1 1区 医学 Q1 PATHOLOGY Modern Pathology Pub Date : 2024-10-12 DOI:10.1016/j.modpat.2024.100631
João Lobo, Bassel Zein-Sabatto, Priti Lal, George J Netto
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Abstract

Bladder cancer (BC) remains a major disease burden in terms of incidence, morbidity, mortality, and economic cost. Deciphering the intrinsic molecular subtypes and identification of key drivers of BC has yielded successful novel therapeutic strategies. Advances in computational and digital pathology are reshaping the field of anatomical pathology. This review offers an update on the most relevant computational algorithms in digital pathology that have been proposed to enhance BC management. These tools promise to enhance diagnostics, staging, and grading accuracy and streamline efficiency while advancing practice consistency. Computational applications that enable intrinsic molecular classification, predict response to neoadjuvant therapy, and identify targets of therapy are also reviewed.

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数字和计算病理学在膀胱癌中的应用:解决临床迫切需求的新工具。
就发病率、发病率、死亡率和经济成本而言,膀胱癌(BC)仍然是一种主要的疾病负担。破译膀胱癌的内在分子亚型和识别膀胱癌的关键驱动因素已成功地产生了新的治疗策略。计算和数字病理学的进步正在重塑解剖病理学领域。本综述介绍了数字病理学中最相关的计算算法的最新进展,这些算法已被提出用于加强膀胱癌的管理。这些工具有望提高诊断、分期和分级的准确性,并在提高实践一致性的同时简化效率。此外,还对能够进行内在分子分类、预测对新辅助治疗的反应以及确定治疗靶点的计算应用进行了综述。
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来源期刊
Modern Pathology
Modern Pathology 医学-病理学
CiteScore
14.30
自引率
2.70%
发文量
174
审稿时长
18 days
期刊介绍: Modern Pathology, an international journal under the ownership of The United States & Canadian Academy of Pathology (USCAP), serves as an authoritative platform for publishing top-tier clinical and translational research studies in pathology. Original manuscripts are the primary focus of Modern Pathology, complemented by impactful editorials, reviews, and practice guidelines covering all facets of precision diagnostics in human pathology. The journal's scope includes advancements in molecular diagnostics and genomic classifications of diseases, breakthroughs in immune-oncology, computational science, applied bioinformatics, and digital pathology.
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