Prostate CA
Conditions
Keywords
MRI, Prostate, Cancer, AI, Artificial Intelligence
Brief summary
Prostate cancer is the most common male cancer in 112 countries and makes up 7% of global cancer cases, and is the second leading cause of cancer-related deaths in men. Normally, men with suspected prostate cancer undergo a prostate MRI, and then a Radiologist would review this scan to identify any suspicious areas for cancer within the prostate. Prostate MRI interpretation, however, is an expert skill with a steep learning curve, and internationally, there is a growing shortage of Radiologists. The PARADIGM trial aims to assess if AI can perform just as well as Radiologists in interpreting prostate MRI scans to identify prostate cancer. Enrolled participants will undergo a prostate MRI, which is the normal method used for investigating suspected prostate cancer. AI and a Radiologist will both interpret the MRI, without knowledge of each other's interpretation. Once both reports have been made, the Radiologist will be asked to produce a third, combined report. If there is a suspicious area in the prostate identified either by AI or the Radiologist, targeted biopsies will be performed. If there are no suspicious areas on the MRI and if you are at low risk of harbouring cancer, which occurs in about 30% of men, then no biopsy will be taken at all.
Detailed description
Aim: To assess whether artificial intelligence is non-inferior to radiologists in the diagnosis of clinically significant prostate cancer on MRI. Objectives Primary 1\. To compare the proportion of men who have clinically significant prostate cancer detected on MRI using AI ± targeted biopsy with radiologists ± targeted biopsy. Secondary 1. To compare the proportion of men who have clinically insignificant prostate cancer detected on MRI using AI ± targeted biopsy with radiologists ± targeted biopsy. 2. To compare the proportion of men with non-suspicious MRIs for AI vs radiologists. 3. To compare the proportion of men with indeterminately scored MRI as reported by AI vs radiologists. 4. To compare the diagnostic test performance of AI vs radiologist. 5. To compare the additive value of AI when used together with a radiologist interpretation (summative of all identified lesions) compared to a radiologist alone. 6. To compare the additive value of AI when used together with a radiologist interpretation (where the radiologist can interact with the AI system by accepting or rejecting AI-identified lesions) compared to a radiologist alone. 7. To determine the frequency of AI failures. 8. To compare treatment eligibility decisions between AI and Radiologist. 9. To compare the cost-effectiveness of unblinded AI interpreted by the radiologist compared to radiologist alone for prostate cancer detection, and AI alone vs. radiologist alone, and a 3-arm analysis considering all three. Design: Prospective, international, within-patient, multi-centre, level-1 evidence trial in participants referred to hospital with a clinical suspicion of prostate cancer.
Interventions
DIAGNOSTIC_TESTAI (Lucida Pi) interpretation
AI algorithm that will interpretate the prostate MRI
DIAGNOSTIC_TESTRadiologist interpretation
Radiologist will interpret the prostate MRI (as per standard of care)
Sponsors
University College, London
Lucida Medical Ltd
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
SINGLE (Caregiver)
Masking description
AI and Radiologist interpreting the MRI for suspicion of prostate cancer are blinded to each other. After both reports are produced, they are unblinded, and a merged report is produced. All bioopsies are conducted as a result of both the AI and Radiologist interpretation, and as a result, lesions will be identified as AI and Radiologist positive, or negative, as appropriate. Diagnostic accuracy will be assessed against histology findings.
Intervention model description
Within-person controlled, paired cohort, diagnostic evaluation study. Participants undergo two index tests and a reference test.
Eligibility
Sex/Gender
MALE
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
1. Men at least 18 years of age referred with clinical suspicion of prostate cancer 2. Serum PSA ≤ 20 ng/mL 3. Fit to undergo all procedures listed in the protocol 4. Able to provide written informed consent
Exclusion criteria
1. Prior prostate biopsy 2. Prior prostate MRI on a previous encounter\* 3. Prior treatment for prostate cancer 4. Contraindication to MRI (e.g. claustrophobia, pacemaker) 5. Metalwork that would give rise to artefact on MRI (e.g. hip prosthesis, pelvic/spinal metalwork) 6. Contraindication to prostate biopsy 7. Unfit to undergo any procedures listed in protocol * An MRI on a previous encounter means a previous prostate MRI which has been seen by a doctor and has been used to inform patient management at the time of the original MRI.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Proportion of men with clinically significant cancer | When biopsy results available, at an expected average of 30 days post-biopsy | Proportion of men with clinically significant cancer detected (any pattern 4 disease on any core (i.e. Gleason Grade ≥ 3+4/Gleason grade group ≥2). |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Agreement between AI and Radiologist in score of suspicion | When MRI results available, at an expected average of 30 days post-MRI | Compare the proportion of MRIs with concordant scores between AI and Radiologist in score of suspicion |
| Diagnostic test performance characteristics (AI versus Radiologist) | When biopsy results available, at an expected average of 30 days post-biopsy | Test performance characteristics for AI and Radiologists, including sensitivity, specificity, area under the receive operating characteristic curve, positive predictive value and negative predictive value. |
| Diagnostic test performance characteristics (AI plus Radiologist) | When biopsy results available, at an expected average of 30 days post-biopsy | Test performance characteristics of AI in combination with Radiologist (summative of all identified lesions) compared to a radiologist alone, including sensitivity, specificity, area under the receive operating characteristic curve, positive predictive value and negative predictive value. |
| Diagnostic test performance characteristics (AI-assisted Radiologist) | When biopsy results available, at an expected average of 30 days post-biopsy | Test performance characteristics of AI in combination with Radiologist (where the radiologist can interact with the AI system by accepting or rejecting AI-identified lesions) compared to a radiologist alone, including sensitivity, specificity, area under the receive operating characteristic curve, positive predictive value and negative predictive value. |
| Significant cancer detected by peri-lesional biopsies | When biopsy results available, at an expected average of 30 days post-biopsy | Proportion of patients with significant cancer detected taking into account peri-lesional biopsies of AI and Radiologist declared lesions. |
| Significant cancer detected by systematic biopsies | When biopsy results available, at an expected average of 30 days post-biopsy | Proportion of patients with significant cancer detected by systematic biopsies |
| Frequency of AI failures | When MRI results available, at an expected average of 30 days post-MRI | Proportion of patients where AI was unable to interpret the MRI scan |
| Treatment eligibility decisions | When biopsy results available, at an expected average of 30 days post-biopsy | Proportion of patients where treatment eligibility changed between AI and Radiologist |
| Cost-efffectiveness | At an expected average of 30 days post-intervention | Cost-effectiveness of unblinded AI interpreted by the radiologist compared to radiologist alone in detecting significant prostate cancer, and AI alone vs. radiologist alone, and a 3-arm analysis considering all three. |
| Proportion of men with clinically insignificant cancer | When biopsy results available, at an expected average of 30 days post-biopsy | Proportion of men with clinically insignificant cancer detected (Gleason grade 3+3/Gleason grade group 1). |
| Proportion of MRIs with indeterminate scores. | When MRI results available, at an expected average of 30 days post-MRI | Proportion of men with indeterminately scored MRI as reported by AI vs radiologists |
| Proportion of men with non-suspicious MRIs | When MRI results available, at an expected average of 30 days post-MRI | Proportion of men with non-suspicious MRIs for AI vs Radiologists |
Contacts
CONTACTNg Alexander, MBBS BSc (Hons)
CONTACTPARADIGM Study Team
STUDY_CHAIRVeeru Kasivisvanathan, MBBS BSc FRCS MSc PGCert PhD
Division of Surgery and Interventional Science, University College London, UK
STUDY_CHAIRDoug Pendse, MB ChB MD (Res) MRCS FRCR
Department of Radiology, Universiy College London Hospitals NHS Foundation Trust, UK
Outcome results
None listed