Comparison Between Manual and Automated Assessment of Ki-67 in Breast Carcinoma: Test of a Simple Method in Daily Practice.

Abstract

BACKGROUND:

In the era of "precision medicine," the availability of high-quality tumor biomarker tests is critical and tumor proliferation evaluated by Ki-67 antibody is one of the most important prognostic factors in breast cancer. But the evaluation of Ki-67 index has been shown to suffer from some interobserver variability. The goal of the study is to develop an easy, automated, and reliable Ki-67 assessment approach for invasive breast carcinoma in routine practice.

PATIENTS AND METHODS:

A total of 151 biopsies of invasive breast carcinoma were analyzed. The Ki-67 index was evaluated by 2 pathologists with MIB-1 antibody as a global tumor index and also in a hotspot. These 2 areas were also analyzed by digital image analysis (DIA).

RESULTS:

For Ki-67 index assessment, in the global and hotspot tumor area, the concordances were very good between DIA and pathologists when DIA focused on the annotations made by pathologist (0.73 and 0.83, respectively). However, this was definitely not the case when DIA was not constrained within the pathologist's annotations and automatically established its global or hotspot area in the whole tissue sample (concordance correlation coefficients between 0.28 and 0.58).

CONCLUSIONS:

The DIA technique demonstrated a meaningful concordance with the indices evaluated by pathologists when the tumor area is previously identified by a pathologist. In contrast, basing Ki-67 assessment on automatic tissue detection was not satisfactory and provided bad concordance results. A representative tumoral zone must therefore be manually selected prior to the measurement made by the DIA.

• Authors: Xavier Catteau, Egor Zindy, Sarah Bouri, Jean-Christophe Noël, Isabelle Salmon, Christine Decaestecker
• Journal: Technology in cancer research & treatment (Technol Cancer Res Treat) 2023 Jan-Dec Vol. 22 Pg. 15330338231169603 ISSN: 1533-0338 [Electronic] United States
• PMID: 37559526 (Publication Type: Journal Article)

Chemical References

• Ki-67 Antigen
• Biomarkers, Tumor

Topics

• Humans
• Female
• Ki-67 Antigen
• Image Processing, Computer-Assisted (methods)
• Breast Neoplasms (diagnosis, pathology)
• Diagnostic Imaging
• Observer Variation
• Biomarkers, Tumor (analysis)