A simple digital image analysis system for automated Ki67 assessment in primary breast cancer. Issue 2 (5th May 2021)
- Record Type:
- Journal Article
- Title:
- A simple digital image analysis system for automated Ki67 assessment in primary breast cancer. Issue 2 (5th May 2021)
- Main Title:
- A simple digital image analysis system for automated Ki67 assessment in primary breast cancer
- Authors:
- Alataki, Anastasia
Zabaglo, Lila
Tovey, Holly
Dodson, Andrew
Dowsett, Mitch - Abstract:
- Abstract : Aims: Ki67 is a well‐established immunohistochemical marker associated with cell proliferation that has prognostic and predictive value in breast cancer. Quantitative evaluation of Ki67 is traditionally performed by assessing stained tissue slides with light microscopy. Automated image analysis systems have become available and, if validated, could provide greater standardisation and improved precision of Ki67 scoring. Here, we aimed to evaluate the use of the Cognition Master Professional Suite (CogM) image analysis software, which is a simple system for scoring Ki67 in primary breast cancer samples. Methods and results: Sections from 94 core‐cut biopsies, 20 excision specimens and 29 pairs of core‐cut biopsies and excision specimens were stained for Ki67 with MIB1 antibody and the Dako EnVision FLEX Detection System. Stained slides were scanned to convert them to digital data. Computer‐based Ki67 scoring was performed with CogM. Manual Ki67 scoring assessment was conducted on previously stained sections from the same biopsies with a clinically validated system that had been calibrated against the risk of recurrence. A high correlation between manual and digital scores was observed [ r Cores = 0.92, 95% confidence interval (CI) 0.87–0.94, P < 0.0001; r Excisions = 0.95, 95% CI 0.86–0.98, P < 0.0001] and there was no significant bias between them ( P = 0.45). There was also a high correlation of Ki67 scores between paired core‐cut biopsies and excisionAbstract : Aims: Ki67 is a well‐established immunohistochemical marker associated with cell proliferation that has prognostic and predictive value in breast cancer. Quantitative evaluation of Ki67 is traditionally performed by assessing stained tissue slides with light microscopy. Automated image analysis systems have become available and, if validated, could provide greater standardisation and improved precision of Ki67 scoring. Here, we aimed to evaluate the use of the Cognition Master Professional Suite (CogM) image analysis software, which is a simple system for scoring Ki67 in primary breast cancer samples. Methods and results: Sections from 94 core‐cut biopsies, 20 excision specimens and 29 pairs of core‐cut biopsies and excision specimens were stained for Ki67 with MIB1 antibody and the Dako EnVision FLEX Detection System. Stained slides were scanned to convert them to digital data. Computer‐based Ki67 scoring was performed with CogM. Manual Ki67 scoring assessment was conducted on previously stained sections from the same biopsies with a clinically validated system that had been calibrated against the risk of recurrence. A high correlation between manual and digital scores was observed [ r Cores = 0.92, 95% confidence interval (CI) 0.87–0.94, P < 0.0001; r Excisions = 0.95, 95% CI 0.86–0.98, P < 0.0001] and there was no significant bias between them ( P = 0.45). There was also a high correlation of Ki67 scores between paired core‐cut biopsies and excision specimens when CogM was used ( r = 0.78, 95% CI 0.59–0.89, P < 0.0001). Conclusions: CogM image analysis allows for standardised automated Ki67 scoring that accurately replicates previously clinically validated and calibrated manual scores. Abstract : … (more)
- Is Part Of:
- Histopathology. Volume 79:Issue 2(2021)
- Journal:
- Histopathology
- Issue:
- Volume 79:Issue 2(2021)
- Issue Display:
- Volume 79, Issue 2 (2021)
- Year:
- 2021
- Volume:
- 79
- Issue:
- 2
- Issue Sort Value:
- 2021-0079-0002-0000
- Page Start:
- 200
- Page End:
- 209
- Publication Date:
- 2021-05-05
- Subjects:
- automated image analysis -- biopsy -- breast cancer -- immunohistochemistry -- Ki67 scoring
Histology, Pathological -- Periodicals
611.018 - Journal URLs:
- http://www.blackwell-synergy.com/member/institutions/issuelist.asp?journal=his ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-2559 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/his.14355 ↗
- Languages:
- English
- ISSNs:
- 0309-0167
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4316.027000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17554.xml