Poster viewing and lunch

48P - An AI System for accurate Ki-67 IHC Assessment in Breast Cancer following the IKWG Whole Section Global Scoring Protocol (ID 268)

Lecture Time
12:15 - 12:15
Session Name
Poster viewing and lunch
Room
Exhibition area
Date
Fri, 12.05.2023
Time
12:15 - 13:00
Speakers
  • Ramona Erber (Erlangen, Germany)
Authors
  • Ramona Erber (Erlangen, Germany)
  • Patrick Frey (Hamburg, Germany)
  • Felix Keil (Regensburg, Germany)
  • Malte Gronewold (Hannover, Germany)
  • Niklas Abele (Erlangen, Germany)
  • Witold Rezner (Kielce, Poland)
  • Thomas Beister (Hamburg, Germany)
  • Khalid Daifalla (Hamburg, Germany)
  • Marc P├Ąpper (Hamburg, Germany)
  • Sebastian Springenberg (Hamburg, Germany)
  • Arndt Hartmann (Erlangen, Germany)
  • Tobias Lang (Hamburg, Germany)

Abstract

Background

Assessment of immunohistochemical (IHC) Ki-67 expression plays a crucial role in breast cancer diagnostics for many therapy decisions. The International Ki-67 in Breast Cancer Working Group (IKWG) has recently proposed a new global scoring method on whole tissue sections to improve accuracy, involving assessment of up to four representative tumor areas with negligible, low, medium and strong proliferation levels. As precise manual assessment is time-consuming, artificial intelligence (AI) support is necessary to make this method practicable for clinical routine.

Methods

We developed an AI software for automated Ki-67 scoring according to the IKWG protocol. Seven pathologists assessed Ki-67 IHC status in 2 x 214 readings of whole-slide images (WSI) derived from 72 breast cancer specimens, four scanning hardware types and two clones. Pathologists selected representative areas manually, scored them with assistance of a CE-cleared AI software for region-of-interest (ROI) analysis and concluded global scores (weighted/unweighted). After a 2-week washout period, the same pathologists were presented with the same slides together with results by a fully automatic AI (AI-only): 1) selection of regions, 2) score and weight per region, and 3) two global scores (weighted/unweighted). Being able to adjust the AI-suggested results, pathologists concluded the two global scores (AI+path).

Results

For weighted global scoring, interrater-agreements between a) pathologist and AI+path, b) pathologist and AI-only, and c) AI-only and AI+path were 93.9%, 92.5%, and 96.7%, respectively (for unweighted scores, 91.1%/92.1%/96.3%). With AI-assistance, pathologists scored significantly faster compared to manual scoring (median time per WSI: 229 vs. 306 sec).

Conclusions

Used as a diagnostics assistance tool, the presented AI system showed high agreement with pathologist scores, while reducing assessment time. Likewise, also fully automatic AI use showed high agreement with human scoring. Overall, this demonstrates that the investigated AI system is suitable to enable safe implementation of the global scoring protocol in clinical routine, ultimately leading to higher accuracy and reproducibility in Ki-67 IHC scoring.

Legal entity responsible for the study

Mindpeak GmbH.

Funding

Mindpeak GmbH.

Disclosure

R. Erber: Financial Interests, Personal, Invited Speaker: AstraZeneca, Novartis, Daiichi Sankyo , Roche, Pfizer, Eisai; Financial Interests, Personal, Expert Testimony: Mindpeak GmbH; Financial Interests, Personal, Other: Mindpeak GmbH, Diaceutics, Veracyte; Financial Interests, Personal, Research Grant: Gilead; Financial Interests, Institutional, Funding: Cepheid, Roche, Biocartis; Financial Interests, Personal and Institutional, Funding: NanoString Technologies; Financial Interests, Personal and Institutional, Other: BioNTech. P. Frey, K. Daifalla, S. Springenberg: Financial Interests, Personal, Full or part-time Employment: Mindpeak GmbH. N. Abele: Financial Interests, Personal, Other: Mindpeak GmbH; Financial Interests, Personal, Advisory Board: Mindpeak GmbH. M. Päpper, T. Lang: Financial Interests, Personal, Full or part-time Employment: Mindpeak GmbH; Financial Interests, Personal, Stocks/Shares: Mindpeak GmbH. A. Hartmann: Financial Interests, Institutional, Funding: AstraZeneca, Roche, Janssen-Cilag, NanoString Technologies, Biocartis, ZytoVision, Novartis, Cepheid, Mindpeak, Gilead, palleos healthcare, BioNTech; Financial Interests, Personal, Advisory Board: BMS, MSD, Roche, Cepheid; Financial Interests, Personal, Invited Speaker: Qiagen, Agilent, Diaceutics, Lilly, AstraZeneca, Boehringer Ingelheim, AbbVie, Janssen-Cilag, Pfizer, Ipsen. All other authors have declared no conflicts of interest.

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