Accepted for/Published in: JMIR Research Protocols
Date Submitted: Apr 30, 2025
Date Accepted: Nov 30, 2025
Deep-learning solution providing molecular marker subtyping of breast cancer whole-slide images: Protocol for a UK clinical service evaluation study
ABSTRACT
Background:
As the histopathology workforce continues to struggle and service demand continues to increase, it has become prudent to consider viable avenues to try and alleviate diagnostic workload burden. One such avenue is computer-based technologies (CBTs). Breast cancer (BC) is the most common malignancy in the UK and requires additional testing for oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER2) status at the time of histological diagnosis. This makes BC diagnostics a promising candidate for the application of an efficient CBT. However, for clinical acceptance, these technologies must prove that they work within a real-life diagnostic environment.
Objective:
We present a study protocol for a prospective clinical service evaluation aimed to validate a UKCA-marked CBT’s ability to provide ER/PR/HER2 results for invasive BCs from scanned haematoxylin and eosin-stained whole slide images (WSIs).
Methods:
This protocol has been designed to utilise and mimic a pre-existing digital pathology workflow within an NHS tertiary referral cancer centre without disrupting normal patient care. Eligible cases are identified prospectively through the laboratory information management system and their WSIs are extracted from the clinical digital workflow. These are then analysed by the CBT in a separate environment providing results for ER, PR and HER2. These results are compared to the ER/PR/HER2 status given on the corresponding pathology report. This comparison will form the basis to determine the CBT’s performance.
Results:
There are no results to present.
Conclusions:
This design assesses a CBT within a clinical environment whilst effectively eliminating any unwanted effects on patient care. This type of service evaluation provides a useful step to establish confidence in a CBT before trialling its effect on patient care. It also offers the opportunity to support interventional randomised controlled trials, health economic evaluations and usability studies. This protocol will hopefully prove useful to others who wish to conduct a similar service evaluation at their own institution.
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