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Pathology ; 51(7): 681-687, 2019 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-31630876

RESUMEN

Invasive lobular carcinoma (ILC) is almost always classified as Nottingham histological grade 2. Despite this, prognosis is markedly varied, with some ILCs behaving more akin to grade 3 invasive ductal carcinoma (IDC). Methods to separate these aggressive ILCs are needed. Digital image analysis (DIA) of the Ki-67 biomarker has potential in this regard; thus, we sought to determine the feasibility of its use for automated evaluation of ILC. An initial pilot study demonstrated no ILC specific changes were required to our Ki-67 DIA algorithm for reproducible results. Subsequently, 42 consecutive cases of ILC were evaluated by visual mitosis counting in H&E stained sections and by DIA on Ki-67 stained sections. Ki-67 proliferative index (PI) DIA showed significant correlation with visual mitosis counting on H&E stained sections (rs=0.63; p<0.05), significant strong correlation (rs=0.78; p<0.05) and substantial agreement (κ=0.62) with manual/visual Ki-67 assessment and significant positive associations with grade, nodal status and 'pleomorphic' ILC subtype, and a wide stratification of values in classical/grade 2 ILC. In conclusion, DIA of Ki-67 PI in ILC is feasible, correlates with mitotic index, manual/visual Ki-67 PI and clinico-pathological variables. The broad stratification of Ki-67 PI in classical/grade 2 ILC supports its practicability as a biomarker with prognostic and predictive potential, although large studies with outcome data are required for validation.


Asunto(s)
Biomarcadores de Tumor/análisis , Neoplasias de la Mama/diagnóstico por imagen , Carcinoma Lobular/diagnóstico por imagen , Antígeno Ki-67/análisis , Adulto , Anciano , Algoritmos , Mama/diagnóstico por imagen , Mama/patología , Neoplasias de la Mama/clasificación , Neoplasias de la Mama/patología , Carcinoma Lobular/clasificación , Carcinoma Lobular/patología , Proliferación Celular , Estudios de Cohortes , Femenino , Humanos , Procesamiento de Imagen Asistido por Computador , Inmunohistoquímica , Persona de Mediana Edad , Clasificación del Tumor , Proyectos Piloto , Pronóstico
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