Imperial Prostate 6 - Cancer Histology Artificial Intelligence Reliability Study.

NCT ID: NCT05228197

Last Updated: 2025-01-22

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

ACTIVE_NOT_RECRUITING

Total Enrollment

750 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-03-11

Study Completion Date

2025-04-30

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

The primary objective is to determine whether the Galen Prostate AI system has sufficient diagnostic accuracy and health economic value to be used for triage of pathology slides within the NHS.

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

In the UK, about 80-100,000 men every year undergo prostate biopsy to diagnose prostate cancer. This equates to approximately 4 million histology slides; this is estimated to increase to 160,000-200,000 men and up to 6 million slides by 2030 due to rising numbers of men being tested for prostate cancer.

Health Education England and the Royal College of Pathology point to a significant pathology work-force shortage with only 3% of departments having adequate staffing levels and a 10% vacancy rate filled by locums costing £26M every year. By 2021, there will be a 3% decrease of the pathology consultant workforce (40 full-time pathologists); a period of time in which other specialties are expected to see a 13% increase. However, to meet the rising numbers of referrals to pathology departments, it is projected that there will need to be a 3-5% annual growth in the number of pathologists.

Inter-observer variability can occur between pathologists in terms of reporting a diagnosis of clinically important and clinically unimportant prostate cancer by as much as 20% although the differences are smaller when highly expert uro-pathologists are compared. This can lead to inappropriate management of cases.

Galen Prostate AI is a CE-marked deep learning AI-algorithm for prostate needle biopsies that can identify cell types, tissue structures and morphological features for cancer diagnosis. The technology is based on multi-layered convolutional neural networks (CNNs) designed for image classification in which whole-slide imaging is analysed for the detection of tissue areas and then benign versus cancer versus other pathology classification. Compared to almost all competitors, Galen Prostate AI has been tested in \~10 times more tissue samples. Further, Galen Prostate AI is the only algorithm that extends beyond cancer detection/grading to other clinically relevant features (e.g., perineural invasion, high-grade prostatic intraepithelial neoplasia \[PIN\], inflammation). This AI-algorithm is believed to be the only one in routine clinical deployment - demonstrating technical feasibility and with proven clinical utility.

The proposed study will perform validation in the NHS, for the first time. It is important to stress that this type of algorithm has never been tested on a UK-based population, and in particular, a population that includes a cohort of MRI targeted biopsies, which is now the new diagnostic strategy as it detects clinically relevant prostate cancer in higher percentages than the routine systematic biopsy.

The study is the first and only to address the performance of the AI-based prostate algorithm that extends beyond cancer detection and Gleason grading, by measuring amount of cancer and detecting clinically meaningful features such as perineural invasion in addition to multiple benign structures (e.g. HGPIN, atrophy, inflammation). Given the clinical relevance for such features in the diagnosis process, a study addressing their validation and performance is not only novel, but critical for implementation in routine clinical use.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Prostatic Neoplasms

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Observational Model Type

COHORT

Study Time Perspective

CROSS_SECTIONAL

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

Calibration Stage

Patients referred to hospital urology departments by their GP due to a clinical suspicion of prostate cancer (elevated serum prostate specific antigen \[PSA\], abnormal feeling prostate on rectal examination). These patients are normally recommended to undergo a prostate MRI as part of standard care.

Patients will need to meet the Inclusion/Exclusion criteria but in addition, purposive identification of cases with a variety and representative sample of different pathology features are needed for this stage (e.g. normal glands, cancer glands, high-grade PIN, inflammation).

Biopsy & Imaging

Intervention Type DIAGNOSTIC_TEST

H\&E stained prostate biopsy slides from standard of care treatment

Validation Stage

Patients referred to hospital urology departments by their GP due to a clinical suspicion of prostate cancer (elevated serum prostate specific antigen \[PSA\], abnormal feeling prostate on rectal examination). These patients are normally recommended to undergo a prostate MRI as part of standard care.

Patients will need to meet the Inclusion/Exclusion.

Biopsy & Imaging

Intervention Type DIAGNOSTIC_TEST

H\&E stained prostate biopsy slides from standard of care treatment

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

Biopsy & Imaging

H\&E stained prostate biopsy slides from standard of care treatment

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

* Patients with a prostate (either cis-male gender or trans-female gender with no prior hormone use at all).
* Age 18 years or above.
* Undergoing prostate biopsy as a result of an elevated serum PSA or abnormal digital rectal exam, who have undergone a pre-biopsy multi-parametric MRI and advised to undergo prostate biopsies.

(Please note: the Calibration stage requires patients who have already undergone a biopsy and the pathology has been processed over the prior 0 to 12 months).

Exclusion Criteria

* Unwilling or unable to give consent.
* Any duration or type or dose of androgen deprivation therapy in the 6 months prior to screening.
* Any prior radiotherapy to the prostate or pelvis (including the prostate) or ablation or chemical treatment of the prostate for treating cancer: these types of treatment affect the anatomy of prostate tissue microstructure for which Galen Prostate AI is not currently validated. NB: any treatment for benign enlargement of the prostate is permitted.
Minimum Eligible Age

18 Years

Eligible Sex

MALE

Accepts Healthy Volunteers

No

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

National Institute for Health Research, United Kingdom

OTHER_GOV

Sponsor Role collaborator

Imperial College London

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Responsibility Role SPONSOR

Principal Investigators

Learn about the lead researchers overseeing the trial and their institutional affiliations.

Hashim U Ahmed

Role: PRINCIPAL_INVESTIGATOR

Imperial College London

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

University Hospitals Coventry and Warwickshire Nhs Trust

Coventry, , United Kingdom

Site Status

Chelsea and Westminster Hospital Nhs Foundation Trust - Chelsea

London, , United Kingdom

Site Status

Chelsea and Westminster Hospital Nhs Foundation Trust - West Middlesex

London, , United Kingdom

Site Status

Imperial College Healthcare Nhs Trust

London, , United Kingdom

Site Status

University College London Hospitals Nhs Foundation Trust

London, , United Kingdom

Site Status

University Hospital Southampton Nhs Foundation Trust

Southampton, , United Kingdom

Site Status

Countries

Review the countries where the study has at least one active or historical site.

United Kingdom

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

21CX6823

Identifier Type: -

Identifier Source: org_study_id

More Related Trials

Additional clinical trials that may be relevant based on similarity analysis.

Artificial Intelligence & Prostate Cancer
NCT06298305 ACTIVE_NOT_RECRUITING