Automated Ki-67 labeling index assessment in prostate cancer using artificial intelligence and multiplex fluorescence immunohistochemistry.

Journal: The Journal of pathology
Published Date:

Abstract

The Ki-67 labeling index (Ki-67 LI) is a strong prognostic marker in prostate cancer, although its analysis requires cumbersome manual quantification of Ki-67 immunostaining in 200-500 tumor cells. To enable automated Ki-67 LI assessment in routine clinical practice, a framework for automated Ki-67 LI quantification, which comprises three different artificial intelligence analysis steps and an algorithm for cell-distance analysis of multiplex fluorescence immunohistochemistry (mfIHC) staining, was developed and validated in a cohort of 12,475 prostate cancers. The prognostic impact of the Ki-67 LI was tested on a tissue microarray (TMA) containing one 0.6 mm sample per patient. A 'heterogeneity TMA' containing three to six samples from different tumor areas in each patient was used to model Ki-67 analysis of multiple different biopsies, and 30 prostate biopsies were analyzed to compare a 'classical' bright field-based Ki-67 analysis with the mfIHC-based framework. The Ki-67 LI provided strong and independent prognostic information in 11,845 analyzed prostate cancers (p < 0.001 each), and excellent agreement was found between the framework for automated Ki-67 LI assessment and the manual quantification in prostate biopsies from routine clinical practice (intraclass correlation coefficient: 0.94 [95% confidence interval: 0.87-0.97]). The analysis of the heterogeneity TMA revealed that the Ki-67 LI of the sample with the highest Gleason score (area under the curve [AUC]: 0.68) was as prognostic as the mean Ki-67 LI of all six foci (AUC: 0.71 [p = 0.24]). The combined analysis of the Ki-67 LI and Gleason score obtained on identical tissue spots showed that the Ki-67 LI added significant additional prognostic information in case of classical International Society of Urological Pathology grades (AUC: 0.82 [p = 0.002]) and quantitative Gleason score (AUC: 0.83 [p = 0.018]). The Ki-67 LI is a powerful prognostic parameter in prostate cancer that is now applicable in routine clinical practice. In the case of multiple cancer-positive biopsies, the sole automated analysis of the worst biopsy was sufficient. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Authors

  • Niclas C Blessin
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Cheng Yang
    State Key Laboratory of Medicinal Chemical Biology and College of Pharmacy, Nankai University, Tianjin 300071, China.
  • Tim Mandelkow
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Jonas B Raedler
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Wenchao Li
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Elena Bady
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Ronald Simon
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Eik Vettorazzi
    Department of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Maximilian Lennartz
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Christian Bernreuther
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Christoph Fraune
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Frank Jacobsen
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Till Krech
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Institute of Pathology, Clinical Center Osnabrueck, Osnabrueck, Germany.
  • Andreas Marx
    Institute of Pathology, Klinikum Fürth, Fürth, Germany.
  • Patrick Lebok
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Sarah Minner
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Eike Burandt
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Till S Clauditz
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Waldemar Wilczak
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Guido Sauter
    Sami-Ramzi Leyh-Bannurah, Dirk Pehrke, Hartwig Huland, Markus Graefen, and Lars Budäus, Prostate Cancer Center Hamburg-Eppendorf; Sami-Ramzi Leyh-Bannurah, Margit Fisch, and Guido Sauter, University Medical Center Hamburg-Eppendorf, Hamburg; Ulrich Wolffgang, University of Muenster, Muenster, Germany; and Zhe Tian and Pierre I. Karakiewicz, University of Montreal Health Center, Montreal, Canada.
  • Hans Heinzer
    Martini-Clinic Prostate Cancer Center, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Alexander Haese
    Martini-Clinic, Prostate Cancer Center, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Thorsten Schlomm
    Department of Urology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
  • Markus Graefen
    Martini-Klinik Prostate Cancer Center, Hamburg, Germany.
  • Stefan Steurer
    Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.