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Impact of Preanalytical Factors During Histology Processing on Section Suitability for Digital Image Analysis.
Chlipala, Elizabeth A; Butters, Mark; Brous, Miles; Fortin, Jessica S; Archuletta, Roni; Copeland, Karen; Bolon, Brad.
Afiliación
  • Chlipala EA; Premier Laboratory, LLC, Longmont, CO, USA.
  • Butters M; Premier Laboratory, LLC, Longmont, CO, USA.
  • Brous M; Premier Laboratory, LLC, Longmont, CO, USA.
  • Fortin JS; Department of Pathobiology and Diagnostic Investigation, College of Veterinary Medicine, 3078Michigan State University, East Lansing, MI, USA.
  • Archuletta R; Premier Laboratory, LLC, Longmont, CO, USA.
  • Copeland K; Boulder Statistics, LLC, Steamboat Springs, CO, USA.
  • Bolon B; GEMpath, Inc, Longmont, CO, USA.
Toxicol Pathol ; 49(4): 755-772, 2021 06.
Article en En | MEDLINE | ID: mdl-33251977
ABSTRACT
Digital image analysis (DIA) is impacted by the quality of tissue staining. This study examined the influence of preanalytical variables-staining protocol design, reagent quality, section attributes, and instrumentation-on the performance of automated DIA software. Our hypotheses were that (1) staining intensity is impacted by subtle differences in protocol design, reagent quality, and section composition and that (2) identically programmed and loaded stainers will produce equivalent immunohistochemical (IHC) staining. We tested these propositions by using 1 hematoxylin and eosin stainer to process 13 formalin-fixed, paraffin-embedded (FFPE) mouse tissues and by using 3 identically programmed and loaded immunostainers to process 5 FFPE mouse tissues for 4 cell biomarkers. Digital images of stained sections acquired with a commercial whole slide scanner were analyzed by customizable algorithms incorporated into commercially available DIA software. Staining intensity as viewed qualitatively by an observer and/or quantitatively by DIA was affected by staining conditions and tissue attributes. Intrarun and inter-run IHC staining intensities were equivalent for each tissue when processed on a given stainer but varied measurably across stainers. Our data indicate that staining quality must be monitored for each method and stainer to ensure that preanalytical factors do not impact digital pathology data quality.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Biomarcadores de Tumor Límite: Animals Idioma: En Revista: Toxicol Pathol Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Biomarcadores de Tumor Límite: Animals Idioma: En Revista: Toxicol Pathol Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos