Multi-site blinded validation of a deep learning approach for clinical-grade MSI/dMMR detection in colorectal cancer from H&E-stained pathology images.

C Cher Bass (Panakeia Technologies, Cambridge, United Kingdom) S Steffen Wolf (Physikalisches Institut, Albert-Ludwigs-Universität Freiburg 1 , D-79104 Freiburg,) F Foivos Ntelemis (Panakeia Technologies, Cambridge, United Kingdom) A Andre Geraldes (Panakeia Technologies Limited, Cambridge, United Kingdom) J Julian Schmidt (Department of Chemistry) D Debapriya Mehrotra (Panakeia Technologies, Cambridge, United Kingdom) S Shikha Singhal (Panakeia Technologies Limited, Cambridge, United Kingdom) N Nicholas Bennett (University of Leeds, Leeds, United Kingdom) M Mitchell Hyde (University of Leeds, Leeds, United Kingdom) B Bejal Mistry G Grace Rogerson (University of Leeds, Leeds, United Kingdom) M Michele Cummings C Clare Freer E Elizabeth Walsh (University of Leeds, Leeds, United Kingdom) N Naren Kumar (Panakeia Technologies, Cambridge, United Kingdom) P Pahini Pandya N Nicolas M. Orsi S Salim Arslan (Panakeia Technologies, Cambridge, United Kingdom)

Abstract

44 Background: Testing for microsatellite instability (MSI) or mismatch repair deficiency (dMMR) is part of the diagnosis and clinical management of patients with colorectal cancer (CRC). Healthcare services recommend MSI or dMMR testing for all CRC patients to guide therapeutic choices and assist in identifying Lynch Syndrome. However, in clinical practice, high costs and the demand for timely test results, combined with the rising prevalence of CRC and a shrinking pathology workforce, present a barrier to universal adoption. This highlights the need for rapid and affordable alternatives. PANProfiler CRC (PPC) is a deep learning-based solution for detecting MSI/dMMR in CRC tumors that only requires whole slide images (WSIs) of haematoxylin and eosin (H&E)-stained tissue to provide test results. Using only WSIs, PPC offers an efficient alternative to standard testing. This study evaluates PPC's performance in a multi-site blinded setting. Methods: Blinded validation was performed using 3246 WSIs of H&E-stained CRC specimens. PPC provided outputs as "Stable", "Unstable", or "Indeterminate", with "Unstable" indicating dMMR or MSI-High, and "Stable" indicating proficient mismatch repair or non-MSI-High. "Indeterminate" was returned when PPC did not have a definitive result. PPC was evaluated by comparison to standard MSI/dMMR tests. Validation data spanned three cohorts from two sites (Table). St James’s University Hospital (SJUH), Leeds, UK, supplied Cohorts 1 and 2; Cohort 3 was sourced from Wales Cancer Biobank (WCB), UK. Blinded analysis was performed at SJUH. Results: Results are given (Table). PPC demonstrated an overall percent agreement of 93.91%, a positive percent agreement of 92.17%, and a negative percent agreement of 94.15%, returning a definitive result for 88.05% of WSIs. Conclusions: This real-world, multi-site, blinded validation study demonstrates PPC’s remarkable performance, comparable to standard tests for detecting MSI/dMMR in CRC, with high test replacement rates. In the clinical setting, PPC could significantly accelerate testing and enable timely delivery of stratified treatment plans. This accurate and cost-effective diagnostic solution promises to revolutionize MSI/dMMR testing in CRC. Blinded validation results of PPC with confidence intervals (CI) at 95%. Site Cohort Sample Size (Unstable; Stable) Overall Percent Agreement % (CI) Positive Percent Agreement % (CI) Negative Percent Agreement %(CI) Test Replacement Rate % SJUH 1 488 (78; 410) 92.79 (89.86-95.08) 90.16 (79.81-96.30) 93.24(90.11-95.62) 85.25 SJUH 2 2704 (318; 2386) 94.31(93.31-95.21) 92.31(88.48-95.18) 94.57(93.52-95.50) 88.42 WCB 3 54 (11; 43) 84.31 (71.41-92.98) 100.00(71.51-100.00) 80.00(64.35-90.95) 94.44 All 3246 (407; 2839) 93.91 (92.97-94.76) 92.17(88.82-94.78) 94.15(93.16-95.04) 88.05

Article Details

Volume / Issue Vol. 43, Issue 4_suppl
Published February 01, 2025
Pages 44-44
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (18)

C

Cher Bass

Panakeia Technologies, Cambridge, United Kingdom

S

Steffen Wolf

Physikalisches Institut, Albert-Ludwigs-Universität Freiburg 1 , D-79104 Freiburg,

F

Foivos Ntelemis

Panakeia Technologies, Cambridge, United Kingdom

A

Andre Geraldes

Panakeia Technologies Limited, Cambridge, United Kingdom

J

Julian Schmidt

Department of Chemistry

D

Debapriya Mehrotra

Panakeia Technologies, Cambridge, United Kingdom

S

Shikha Singhal

Panakeia Technologies Limited, Cambridge, United Kingdom

N

Nicholas Bennett

University of Leeds, Leeds, United Kingdom

M

Mitchell Hyde

University of Leeds, Leeds, United Kingdom

B

Bejal Mistry

G

Grace Rogerson

University of Leeds, Leeds, United Kingdom

M

Michele Cummings

C

Clare Freer

E

Elizabeth Walsh

University of Leeds, Leeds, United Kingdom

N

Naren Kumar

Panakeia Technologies, Cambridge, United Kingdom

P

Pahini Pandya

N

Nicolas M. Orsi

S

Salim Arslan

Panakeia Technologies, Cambridge, United Kingdom