- ICH GCP
- Registro degli studi clinici negli Stati Uniti
- Sperimentazione clinica 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.
Panoramica dello studio
Stato
Condizioni
Intervento / Trattamento
Descrizione dettagliata
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.
Tipo di studio
Iscrizione (Stimato)
Fase
- Non applicabile
Contatti e Sedi
Contatto studio
- Nome: Ng Alexander, MBBS BSc (Hons)
- Numero di telefono: +44 0207 679 5057
- Email: alexander.ng@ucl.ac.uk
Backup dei contatti dello studio
- Nome: PARADIGM Study Team
- Email: med.paradigm@ucl.ac.uk
Criteri di partecipazione
Criteri di ammissibilità
Età idonea allo studio
- Adulto
- Adulto più anziano
Accetta volontari sani
Descrizione
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.
Piano di studio
Come è strutturato lo studio?
Dettagli di progettazione
- Scopo principale: Diagnostico
- Assegnazione: Non randomizzato
- Modello interventistico: Assegnazione di gruppo singolo
- Mascheramento: Separare
Armi e interventi
Gruppo di partecipanti / Arm |
Intervento / Trattamento |
|---|---|
|
Comparatore attivo: Radiologist interpretation of MRI +/- prostate biopsy
Radiologist Interpretation
|
Radiologist will interpret the prostate MRI (as per standard of care)
|
|
Sperimentale: AI interpretation of MRI +/- prostate biopsy
AI Interpretation
|
AI algorithm that will interpretate the prostate MRI
|
Cosa sta misurando lo studio?
Misure di risultato primarie
Misura del risultato |
Misura Descrizione |
Lasso di tempo |
|---|---|---|
|
Proportion of men with clinically significant cancer
Lasso di tempo: 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
|
Misure di risultato secondarie
Misura del risultato |
Misura Descrizione |
Lasso di tempo |
|---|---|---|
|
Proportion of men with clinically insignificant cancer
Lasso di tempo: 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
Lasso di tempo: 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.
Lasso di tempo: 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
Lasso di tempo: 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)
Lasso di tempo: 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)
Lasso di tempo: 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)
Lasso di tempo: 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
Lasso di tempo: 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
Lasso di tempo: 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
Lasso di tempo: 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
Lasso di tempo: 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
Lasso di tempo: 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
|
Collaboratori e investigatori
Sponsor
Collaboratori
Investigatori
- Cattedra di studio: Veeru Kasivisvanathan, MBBS BSc FRCS MSc PGCert PhD, Division of Surgery and Interventional Science, University College London, UK
- Cattedra di studio: Doug Pendse, MB ChB MD (Res) MRCS FRCR, Department of Radiology, Universiy College London Hospitals NHS Foundation Trust, UK
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Primo Inserito (Effettivo)
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Termini relativi a questo studio
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Termini MeSH pertinenti aggiuntivi
Altri numeri di identificazione dello studio
- 338739
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