Grading of neuroendocrine tumors with Ki-67 requires high-quality assessment practices.
Gastrointestinal and pancreatic neuroendocrine tumors (NETs) arise from disseminated neuroendocrine cells, expressing general and specific neuroendocrine markers. The World Health Organization 2010 classification of NETs is based on grading them according to the proliferation index (PI), which is determined by immunohistochemical staining of the nuclear antigen Ki-67. The classification introduces Ki-67 as the most important criterion for tumor grading, influencing patients' prognoses and the choice of treatment. The aim of this study was to evaluate the assessment of PI value in NETs and its influence on tumor grading. The tumor material consisted of 51 NETs from the pancreas (n=31) and ileum (n=20). The slides were stained with the Ki-67 antibody and visualized using a polymer kit. PI was assessed visually by microscope oculars and using a public domain image analysis software, ImmunoRatio. The PI was measured from the most proliferative areas of the tumor. The PI values and tumor grade by ImmunoRatio were highly reproducible as compared with conventional assessment, which suffered from variation especially if ascertained by different observers. Computer-aided assessments had almost perfect correlation (r=0.985, r=0.987, and r=0.995) (P=0.000) and reproducibility (κ=0.886, κ=0.886, and κ=1.000) (P=0.000) in PI values and tumor grades, respectively. The PI values and tumor grade between conventional and ImmunoRatio assessments by a qualified observer were in good agreement. ImmunoRatio is a qualified diagnostic aid to more objectively analyze Ki-67 PI-based tumor grade in NETs.
Department of Pathology, Haartman Institute University of Helsinki and HUSLAB, Haartmaninkatu, Helsinki, Finland. satu.remes@hus.fi
Satu Maria
SM
Remes
Vilppu J
VJ
Tuominen
Heikki
H
Helin
Jorma
J
Isola
Johanna
J
Arola
D014408:Biomarkers, Tumor / Q000378:metabolism*; D049109:Cell Proliferation; D006801:Humans; D007078:Ileal Neoplasms / Q000145:classification / Q000378:metabolism / Q000473:pathology*; D007091:Image Processing, Computer-Assisted; D019394:Ki-67 Antigen / Q000378:metabolism*; D060787:Neoplasm Grading; D018358:Neuroendocrine Tumors / Q000145:classification / Q000378:metabolism / Q000473:pathology*; D010190:Pancreatic Neoplasms / Q000145:classification / Q000378:metabolism / Q000473:pathology*; D015203:Reproducibility of Results
D014408:Biomarkers, Tumor; D019394:Ki-67 Antigen