Neoplasms

Urinary Tract, Sexual Organs, and Pregnancy Conditions

All Conditions

Prostatic Neoplasms

Genital Neoplasms, Male

Urogenital Neoplasms

Genital Diseases

Genital Diseases, Male

Urogenital Diseases

Prostatic Diseases

Male Urogenital Diseases

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).

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.

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

Biopsy & Imaging

Johanna T Sukumar, MSc

Natalia Klimowska-Nassar

David Snead

Bijan Khoubehi

Mattias Winkler

Hashim U Ahmed

Mark Emberton

Tim Dudderidge

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.

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.

Either cis-male gender or trans-female gender with no prior hormone use at all.

Imperial Prostate 6 - Cancer Histology Artificial Intelligence Reliability Study.

A Study to Assess the Clinical and Cost-effectiveness of the Galen Prostate Artificial Intelligence Histology System in Diagnosing Clinically Important Prostate Cancer on Prostate Biopsy Tissue.

Sensitivity, specificity, positive and negative predictive value of Galen Prostate AI on a patient basis for prostate cancer rated Gleason score 7 (ISUP Grade Group \>/=2) or greater by consensus pathology review.

Includes all the relevant cost and consequences for the Ibex-AI and comparator. Costs: medical equipment, mean cost per diagnosis, primary and secondary care appointments, healthcare professionals' costs, cost of the diagnostic tests and of follow-up testing. Consequences: test accuracy, diagnostic yield, and therapeutic yield.

Will be presented in the form of an Incremental Cost-Effectiveness Ratio (ICER), a ratio of 'extra cost per extra unit of health outcome' for the intervention vs the comparator.

Costs: medical equipment, mean cost per diagnosis, primary and secondary care appointments, healthcare professionals' costs, cost of the diagnostic tests and of follow-up testing, implementation costs of adopting the intervention in the NHS, cost of treatment, treatment of adverse effects from the test or treatment, and any monitoring needed before or after the treatment.

Health outcomes: Quality-adjusted life years (QALY). QALYs will be calculated by estimating the years of life remaining for a patient following diagnosis and weighting each year with a quality-of-life score (EQ-5D questionnaire).

Sensitivity, specificity, positive and negative predictive value of Galen Prostate AI on a slide/biopsy grouping basis (weighted by patient) for prostate cancer rated Gleason score \>/=7 (ISUP Grade Group \>/=2) by consensus pathology review.

Sensitivity, specificity, positive and negative predictive value of Galen Prostate AI on a patient basis for all prostate cancer.

Area under the receiver operating characteristic curve (AUC) at the patient and slide/biopsy grouping levels for any cancer and clinically significant prostate cancer defined by any Gleason score \>/=7 (ISUP Grade Group \>/=2).

Agreement of Galen Prostate AI with pathology report for cancer length (mm) on slide/biopsy grouping level and patient level (maximum cancer length).

Agreement of Galen Prostate AI with histology reported percent Gleason Grade pattern 4.

Agreement of Galen Prostate AI with histology reported Gleason score or Grade Group (GG) categories at slide/biopsy grouping level and patient level.

Cancer area (mm2) by slide (Galen Prostate AI only).

Uncalibrated Galen Prostate tool (software) assessed using above primary and secondary metrics.

Volume of local pathology reporting (histology slides) on above primary and secondary metrics compared to independent pathology reporting.

Databank of scanned high-resolution histology slides and MRI DICOM images linked to clinical parameters for future academic and commercial research into development and validation of diagnostic and prognostic tools for prostate diseases.

Number of participants consenting to linkage to national databases for longitudinal healthcare outcomes reporting and correlation to clinical, MR-imaging and histological parameters collected in this study.

Cost-effectiveness of Galen Prostate system within the NHS (QALYs questionnaire).

Spots Global Cancer Trial Database for biopsy & imaging