Righi Luisella, Gatti Gaia, Volante Marco, Papotti Mauro
Department of Oncology, San Luigi Hospital, Orbassano, Italy.
Department of Oncology, City of Health and Science, University of Turin, Torino, Italy.
J Thorac Dis. 2017 Nov;9(Suppl 15):S1442-S1447. doi: 10.21037/jtd.2017.01.59.
Lung neuroendocrine tumors (NETs) are a heterogeneous family of neoplasms comprising four histologic types, namely typical and atypical carcinoid (TC and AC), large-cell neuroendocrine and small cell carcinoma (SCC). Classification criteria include the number of mitoses per 2 mm, the occurrence and extent of necrosis, cytological and histological features and immunohistochemistry for neuroendocrine markers. The classification system and the diagnostic workflow of lung NETs are apparently easy to apply and well established. However, several unresolved issues still exist in classification and pathological characterization of these tumors, probably because inter-observer diagnostic reproducibility remains disappointing, likely due to inconsistency in recognizing necrosis, mitoses and cytological details, especially in small biopsy or cytological materials. Furthermore, the lack of strong prognostic and grading criteria leads to the incomplete interpretation of some rare intermediate entities that stand in between AC and large cell neuroendocrine carcinoma (LCNEC) categories.
肺神经内分泌肿瘤(NETs)是一组异质性肿瘤,包括四种组织学类型,即典型类癌和非典型类癌(TC和AC)、大细胞神经内分泌癌和小细胞癌(SCC)。分类标准包括每2毫米的有丝分裂数、坏死的发生及范围、细胞学和组织学特征以及神经内分泌标志物的免疫组化。肺NETs的分类系统和诊断流程显然易于应用且已确立。然而,这些肿瘤的分类和病理特征仍存在一些未解决的问题,这可能是因为观察者间诊断的可重复性仍然令人失望,可能是由于在识别坏死、有丝分裂和细胞学细节方面存在不一致,尤其是在小活检或细胞学材料中。此外,缺乏强有力的预后和分级标准导致对一些介于AC和大细胞神经内分泌癌(LCNEC)类别之间的罕见中间实体的解读不完整。