- ICH GCP
- Yhdysvaltain kliinisten tutkimusten rekisteri
- Kliininen tutkimus NCT07647445
Prostate MRI Analysis by Radiologists and Artificial Intelligence - Disease Identification and Guided Management (PARADIGM)
A Study Assessing Whether Artificial Intelligence is Non-inferior to Radiologists in the Diagnosis of Clinically Significant Prostate Cancer.
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 interpretating 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. f 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.
Tutkimuksen yleiskatsaus
Tila
Ehdot
Yksityiskohtainen kuvaus
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
- To compare the proportion of men who have clinically insignificant prostate cancer detected on MRI using AI ± targeted biopsy with radiologists ± targeted biopsy.
- To compare the proportion of men with non-suspicious MRIs for AI vs radiologists.
- To compare the proportion of men with indeterminately scored MRI as reported by AI vs radiologists.
- To compare the diagnostic test performance of AI vs radiologist.
- To compare the additive value of AI when used together with a radiologist interpretation (summative of all identified lesions) compared to a radiologist alone.
- 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.
- To determine the frequency of AI failures.
- To compare treatment eligibility decisions between AI and Radiologist.
- 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 evidnece trial in participants referred to hospital with a clinical suspicion of prostate cancer.
Opintotyyppi
Ilmoittautuminen (Arvioitu)
Vaihe
- Ei sovellettavissa
Yhteystiedot ja paikat
Opiskeluyhteys
- Nimi: Ng Alexander, MBBS BSc (Hons)
- Puhelinnumero: +44 0207 679 5057
- Sähköposti: alexander.ng@ucl.ac.uk
Tutki yhteystietojen varmuuskopiointi
- Nimi: PARADIGM Study Team
- Sähköposti: med.paradigm@ucl.ac.uk
Osallistumiskriteerit
Kelpoisuusvaatimukset
Opintokelpoiset iät
- Aikuinen
- Vanhempi Aikuinen
Hyväksyy terveitä vapaaehtoisia
Kuvaus
Inclusion Criteria:
- Men at least 18 years of age referred with clinical suspicion of prostate cancer
- Serum PSA ≤ 20 ng/mL
- Fit to undergo all procedures listed in the protocol
- Able to provide written informed consent
Exclusion Criteria:
- Prior prostate biopsy
- Prior prostate MRI on a previous encounter*
- Prior treatment for prostate cancer
- Contraindication to MRI (e.g. claustrophobia, pacemaker)
- Metalwork that would give rise to artefact on MRI (e.g. hip prosthesis, pelvic/spinal metalwork)
- Contraindication to prostate biopsy
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.
Opintosuunnitelma
Miten tutkimus on suunniteltu?
Suunnittelun yksityiskohdat
- Ensisijainen käyttötarkoitus: Diagnostiikka
- Jako: Ei satunnaistettu
- Inventiomalli: Yksittäinen ryhmätehtävä
- Naamiointi: Yksittäinen
Aseet ja interventiot
Osallistujaryhmä / Arm |
Interventio / Hoito |
|---|---|
|
Active Comparator: Radiologist interpretation of MRI +/- prostate biopsy
Radiologist Interpretation
|
Radiologist will interpret the prostate MRI (as per standard of care)
|
|
Kokeellinen: AI interpretation of MRI +/- prostate biopsy
AI Interpretation
|
AI algorithm that will interpretate the prostate MRI
|
Mitä tutkimuksessa mitataan?
Ensisijaiset tulostoimenpiteet
Tulosmittaus |
Toimenpiteen kuvaus |
Aikaikkuna |
|---|---|---|
|
Proportion of men with clinically significant cancer
Aikaikkuna: 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).
|
When biopsy results available, at an expected average of 30 days post-biopsy
|
Toissijaiset tulostoimenpiteet
Tulosmittaus |
Toimenpiteen kuvaus |
Aikaikkuna |
|---|---|---|
|
Proportion of men with clinically insignificant cancer
Aikaikkuna: 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).
|
When biopsy results available, at an expected average of 30 days post-biopsy
|
|
Proportion of men with non-suspicious MRIs
Aikaikkuna: When MRI results available, at an expected average of 30 days post-MRI
|
Proportion of men with non-suspicious MRIs for AI vs Radiologists
|
When MRI results available, at an expected average of 30 days post-MRI
|
|
Proportion of MRIs with indeterminate scores.
Aikaikkuna: 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
|
When MRI results available, at an expected average of 30 days post-MRI
|
|
Agreement between AI and Radiologist in score of suspicion
Aikaikkuna: 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
|
When MRI results available, at an expected average of 30 days post-MRI
|
|
Diagnostic test performance characteristics (AI versus Radiologist)
Aikaikkuna: 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.
|
When biopsy results available, at an expected average of 30 days post-biopsy
|
|
Diagnostic test performance characteristics (AI plus Radiologist)
Aikaikkuna: 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.
|
When biopsy results available, at an expected average of 30 days post-biopsy
|
|
Diagnostic test performance characteristics (AI-assisted Radiologist)
Aikaikkuna: 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.
|
When biopsy results available, at an expected average of 30 days post-biopsy
|
|
Significant cancer detected by peri-lesional biopsies
Aikaikkuna: 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.
|
When biopsy results available, at an expected average of 30 days post-biopsy
|
|
Significant cancer detected by systematic biopsies
Aikaikkuna: When biopsy results available, at an expected average of 30 days post-biopsy
|
Proportion of patients with significant cancer detected by systematic biopsies
|
When biopsy results available, at an expected average of 30 days post-biopsy
|
|
Frequency of AI failures
Aikaikkuna: 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
|
When MRI results available, at an expected average of 30 days post-MRI
|
|
Treatment eligibility decisions
Aikaikkuna: When biopsy results available, at an expected average of 30 days post-biopsy
|
Proportion of patients where treatment eligibility changed between AI and Radiologist
|
When biopsy results available, at an expected average of 30 days post-biopsy
|
|
Cost-efffectiveness
Aikaikkuna: 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.
|
At an expected average of 30 days post-intervention
|
Yhteistyökumppanit ja tutkijat
Sponsori
Yhteistyökumppanit
Tutkijat
- Opintojen puheenjohtaja: Veeru Kasivisvanathan, MBBS BSc FRCS MSc PGCert PhD, Division of Surgery and Interventional Science, University College London, UK
- Opintojen puheenjohtaja: Doug Pendse, MB ChB MD (Res) MRCS FRCR, Department of Radiology, Universiy College London Hospitals NHS Foundation Trust, UK
Opintojen ennätyspäivät
Opi tärkeimmät päivämäärät
Opiskelun aloitus (Arvioitu)
Ensisijainen valmistuminen (Arvioitu)
Opintojen valmistuminen (Arvioitu)
Opintoihin ilmoittautumispäivät
Ensimmäinen lähetetty
Ensimmäinen toimitettu, joka täytti QC-kriteerit
Ensimmäinen Lähetetty (Todellinen)
Tutkimustietojen päivitykset
Viimeisin päivitys julkaistu (Todellinen)
Viimeisin lähetetty päivitys, joka täytti QC-kriteerit
Viimeksi vahvistettu
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Avainsanat
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