Artificial intelligence for detection of microsatellite instability in colorectal cancer—a multicentric analysis of a pre-screening tool for clinical application
Open accessAbstract
BACKGROUND: Microsatellite instability (MSI)/mismatch repair deficiency (dMMR) is a key genetic feature which should be tested in every patient with colorectal cancer (CRC) according to medical guidelines. Artificial intelligence (AI) methods can detect MSI/dMMR directly in routine pathology slides, but the test performance has not been systematically investigated with predefined test thresholds. METHOD: We trained and validated AI-based MSI/dMMR detectors and evaluated predefined performance metrics using nine patient cohorts of 8343 patients across different countries and ethnicities. RESULTS: Classifiers achieved clinical-grade performance, yielding an area under the receiver operating curve (AUROC) of up to 0.96 without using any manual annotations. Subsequently, we show that the AI system can be applied as a rule-out test: by using cohort-specific thresholds, on average 52.73% of tumors in each surgical cohort [total number of MSI/dMMR = 1020, microsatellite stable (MSS)/ proficient mismatch repair (pMMR) = 7323 patients] could be identified as MSS/pMMR with a fixed sensitivity at 95%. In an additional cohort of N = 1530 (MSI/dMMR = 211, MSS/pMMR = 1319) endoscopy biopsy samples, the system achieved an AUROC of 0.89, and the cohort-specific threshold ruled out 44.12% of tumors with a fixed sensitivity at 95%. As a more robust alternative to cohort-specific thresholds, we showed that with a fixed threshold of 0.25 for all the cohorts, we can rule-out 25.51% in surgical specimens and 6.10% in biopsies. INTERPRETATION: When applied in a clinical setting, this means that the AI system can rule out MSI/dMMR in a quarter (with global thresholds) or half of all CRC patients (with local fine-tuning), thereby reducing cost and turnaround time for molecular profiling.
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A line of work has focused on developing and validating AI for predicting microsatellite instability, a feature associated with clinical outcomes and a biomarker for immunotherapy.
“a line of work (97-99) has focused on developing and validating AI for predicting microsatellite instability (MSI), a feature associated with clinical outcomes and a biomarker for immunotherapy (100).”
From Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions (2024) · cites this paper as [97]
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- Authors
- Echle, A., Ghaffari Laleh, N., Quirke, P., Grabsch, H. I., Muti, H. S., Saldanha, O. L., Brockmoeller, S. F., van den Brandt, P. A., Hutchins, G. G. A., Richman, S. D., Horisberger, K., Galata, C., Ebert, M. P., Eckardt, M., Boutros, M., Horst, D., Reissfelder, C., Alwers, E., Brinker, T. J., Langer, R., Jenniskens, J. C. A., Offermans, K., Mueller, W., Gray, R., Gruber, S. B., Greenson, J. K., Rennert, G., Bonner, J. D., Schmolze, D., Chang-Claude, J., Brenner, H., Trautwein, C., Boor, P., Jaeger, D., Gaisa, N. T., Hoffmeister, M., West, N. P., & Kather, J. N.
- Affiliations
- Universitätsklinikum Aachen (DE)
- University of Leeds (GB)
- University Hospital Zurich (CH)
- Johannes Gutenberg University Mainz (DE)
- Heidelberg University (DE)
- German Cancer Research Center (DE)
- Charité – Universitätsmedizin Berlin (DE)
- University of Bern (CH)
- Maastricht University Medical Centre (NL)
- University of Oxford (GB)
- City Of Hope National Medical Center (US)
- Technion – Israel Institute of Technology (IL)
- Universität Hamburg (DE)
- University Hospital Heidelberg (DE)
- Corresponding author
- Kather, J.N.
- ORCID
- Echle, A.
- Quirke, P.
- Grabsch, H.I.
- Muti, H.S.
- Saldanha, O.L.
- Brockmoeller, S.F.
- Hutchins, G.G.A.
- Richman, S.D.
- Horisberger, K.
- Galata, C.
- Ebert, M.P.
- Boutros, M.
- Horst, D.
- Reissfelder, C.
- Alwers, E.
- Brinker, T.J.
- Langer, R.
- Jenniskens, J.C.A.
- Offermans, K.
- Gray, R.
- Gruber, S.B.
- Greenson, J.K.
- Rennert, G.
- Bonner, J.D.
- Schmolze, D.
- Chang-Claude, J.
- Brenner, H.
- Trautwein, C.
- Boor, P.
- Gaisa, N.T.
- Hoffmeister, M.
- West, N.P.
- Kather, J.N.
- Venue
- ESMO Open
- Publisher
- Elsevier BV
- Published
- 2022-04
- Volume
- 7
- Issue
- 2
- Pages
- 100400
- ISSN
- 2059-7029 (ISSN-L)
- PMC
- PMC9058894
- OpenAlex
- W4214909253
- Cited by
- 111
- References
- 37
- Citations by year
- 2026: 12 · 2025: 25 · 2024: 30 · 2023: 28 · 2022: 16
- FWCI
- 8.14
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- ESMO Open (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, cc-by)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- BORIS (University Library Bern) (submittedVersion, cc-by)
- RWTH Publications (RWTH Aachen) (submittedVersion, other-oa)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- RWTH Publications (RWTH Aachen)
- Open Access CRIS of the University of Bern
- Funders
- Bundesministerium für Bildung und Forschung (STOP-FSGS01GM1901A)
- Bundesministerium für Gesundheit (ZMVI1-2520DAT111)
- Bundesministerium für Bildung Wissenschaft Forschung und Technologie Dienststelle Berlin
- National Institute for Health and Care Research
- Deutsche Forschungsgemeinschaft (SFB-CRC1382)
- National Institutes of Health (R01 CA197350)
- Yorkshire Cancer Research (L386)
- Bundesministerium für Wirtschaft und Energie (R01 CA81488)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Health Sciences › Medicine › Pathology and Forensic Medicine › Genetic factors in colorectal cancer
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- microsatellite instability, mismatch repair deficiency, colorectal cancer, artificial intelligence, computer-aided diagnosis, histopathology image analysis, rule-out test, prescreening, surgical specimens, molecular profiling, fine-tuning
- MeSH terms
- Artificial Intelligence, Humans, Colorectal Neoplasms, Microsatellite Instability, DNA Mismatch Repair, Early Detection of Cancer
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