1. Computerized image analysis of the Ki-67 proliferation index in mantle cell lymphoma
- Author
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John Arne Nesheim, Christian H. Geisler, Erlend B. Smeland, Hans Martin Mohn, Håvard E. Danielsen, Harald Holte, John Maddison, Arne Kolstad, Jan Delabie, Yngvild Nuvin Blaker, Knut Liestøl, Tarjei S. Hveem, and Marianne Brodtkorb
- Subjects
Histology ,Proliferation index ,biology ,business.industry ,Cell Count ,Lymphoma, Mantle-Cell ,General Medicine ,Gold standard (test) ,Routine practice ,medicine.disease ,Pathology and Forensic Medicine ,Cohort Studies ,Ki-67 Antigen ,Ki-67 ,Image Processing, Computer-Assisted ,biology.protein ,Humans ,Medicine ,Mantle cell lymphoma ,Continuous parameter ,Image analysis ,business ,Nuclear medicine ,Cell Proliferation ,Automated method - Abstract
Aims Manual counting of the fraction of Ki-67-positive cells (the Ki-67 index) in 1000 tumour cells is considered the ‘gold standard’ to predict prognosis in mantle cell lymphoma (MCL). This time-consuming method is replaced by the faster, but less accurate, semiquantitative estimation in routine practice. The aim of this study was to investigate the use of computerized image analysis software for scoring of Ki-67 in MCL. Methods and results We developed an automated method for determining the Ki-67 index by computerized image analysis and tested it using a cohort of 62 MCL patients. The data were compared to Ki-67 scores obtained by semiquantitative estimation and image-based manual counting. When using the Ki-67 index as a continuous parameter, both image-based manual counting and computerized image analysis were related inversely to survival (P = 0.020 and P = 0.025, respectively). Ki-67 index obtained by semiquantitative estimation was not associated significantly with survival (P = 0.093). The results were validated in a second patient cohort with similar results. Conclusion Computerized image analysis of the Ki-67 index in MCL is an attractive alternative to semiquantitative estimation and can be introduced easily in a routine diagnostic setting for risk stratification in MCL.
- Published
- 2015