Diagnosis and grading of adrenal cortical carcinoma.

IF 3.1 3区 医学 Q1 PATHOLOGY
Giulia Vocino Trucco, Eleonora Duregon, Mauro Papotti, Marco Volante
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引用次数: 0

Abstract

The 5th edition of the WHO classification of endocrine and neuroendocrine tumors represents a significant advancement in the diagnostic approach to adrenocortical carcinoma (ACC), integrating novel molecular insights with established histopathological criteria to enhance diagnostic accuracy and to refine prognostic assessment. This review outlines key histopathological features and diagnostic strategies for ACC, offering a practical framework for evaluation and grading in daily practice. The updated WHO classification reaffirms the central role of histopathology, employing multiparametric scoring systems that assess invasion, architectural and cytological features, mitotic activity, and necrosis. However, these parameters often pose interpretive challenges, and no single algorithm ensures complete sensitivity, specificity, or reproducibility. Therefore, combining diagnostic approaches is advisable, particularly in morphologically ambiguous cases. For tumor grading, the WHO employs a two-tiered system based on a mitotic count cut of 20 per 10 mm2, aiming to improve interinstitutional consistency. Immunohistochemistry remains essential for diagnostic confirmation and prognostic evaluation. Among available markers, SF1 is the most specific for adrenocortical origin, while Ki-67, mismatch repair proteins, p53, and β-catenin are useful for predicting patient outcomes or screening for hereditary predisposition. In this complex diagnostic setting, artificial intelligence holds potential to support ACC diagnostics. However, its application is limited by the rarity of the disease, histological variability, and the scarcity of large, well-annotated datasets necessary for algorithm development.

肾上腺皮质癌的诊断与分级。
世卫组织内分泌和神经内分泌肿瘤分类第5版代表了肾上腺皮质癌(ACC)诊断方法的重大进步,将新的分子见解与已建立的组织病理学标准相结合,以提高诊断准确性并完善预后评估。本综述概述了ACC的主要组织病理学特征和诊断策略,为日常实践中的评估和分级提供了一个实用的框架。更新后的世卫组织分类重申了组织病理学的核心作用,采用多参数评分系统评估侵袭、建筑和细胞学特征、有丝分裂活性和坏死。然而,这些参数通常会带来解释上的挑战,而且没有一种算法能保证完全的灵敏度、特异性或可重复性。因此,结合诊断方法是可取的,特别是在形态学模糊的情况下。对于肿瘤分级,世界卫生组织采用了一种基于每10平方毫米有丝分裂计数减少20的双层系统,旨在提高机构间的一致性。免疫组织化学对于诊断确认和预后评估仍然是必不可少的。在现有的标记物中,SF1对肾上腺皮质起源的特异性最强,而Ki-67、错配修复蛋白、p53和β-catenin则可用于预测患者预后或筛查遗传易感性。在这种复杂的诊断环境中,人工智能具有支持ACC诊断的潜力。然而,它的应用受到疾病的稀缺性、组织学变异性以及算法开发所需的大型、注释良好的数据集的稀缺性的限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Virchows Archiv
Virchows Archiv 医学-病理学
CiteScore
7.40
自引率
2.90%
发文量
204
审稿时长
4-8 weeks
期刊介绍: Manuscripts of original studies reinforcing the evidence base of modern diagnostic pathology, using immunocytochemical, molecular and ultrastructural techniques, will be welcomed. In addition, papers on critical evaluation of diagnostic criteria but also broadsheets and guidelines with a solid evidence base will be considered. Consideration will also be given to reports of work in other fields relevant to the understanding of human pathology as well as manuscripts on the application of new methods and techniques in pathology. Submission of purely experimental articles is discouraged but manuscripts on experimental work applicable to diagnostic pathology are welcomed. Biomarker studies are welcomed but need to abide by strict rules (e.g. REMARK) of adequate sample size and relevant marker choice. Single marker studies on limited patient series without validated application will as a rule not be considered. Case reports will only be considered when they provide substantial new information with an impact on understanding disease or diagnostic practice.
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