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Prostate MRI Analysis by Radiologists and Artificial Intelligence - Disease Identification and Guided Management (PARADIGM)

2026년 6월 9일 업데이트: University College, London

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.

연구 개요

상태

아직 모집하지 않음

정황

개입 / 치료

상세 설명

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 evidnece trial in participants referred to hospital with a clinical suspicion of prostate cancer.

연구 유형

중재적

등록 (추정된)

500

단계

  • 해당 없음

연락처 및 위치

이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.

연구 연락처

연구 연락처 백업

참여기준

연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.

자격 기준

공부할 수 있는 나이

  • 성인
  • 고령자

건강한 자원 봉사자를 받아들입니다

아니

설명

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.

공부 계획

이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.

연구는 어떻게 설계됩니까?

디자인 세부사항

  • 주 목적: 특수 증상
  • 할당: 무작위화되지 않음
  • 중재 모델: 단일 그룹 할당
  • 마스킹: 하나의

무기와 개입

참가자 그룹 / 팔
개입 / 치료
활성 비교기: Radiologist interpretation of MRI +/- prostate biopsy
Radiologist Interpretation
진단 검사: Radiologist interpretation
Radiologist will interpret the prostate MRI (as per standard of care)
실험적: AI interpretation of MRI +/- prostate biopsy
AI Interpretation
진단 검사: AI (Lucida Pi) interpretation
AI algorithm that will interpretate the prostate MRI

연구는 무엇을 측정합니까?

주요 결과 측정

결과 측정
측정값 설명
기간
Proportion of men with clinically significant cancer
기간: 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

2차 결과 측정

결과 측정
측정값 설명
기간
Proportion of men with clinically insignificant cancer
기간: 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
기간: 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.
기간: 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
기간: 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)
기간: 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)
기간: 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)
기간: 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
기간: 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
기간: 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
기간: 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
기간: 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
기간: 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

공동 작업자 및 조사자

여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.

스폰서

University College, London

협력자

Lucida Medical Ltd

수사관

  • 연구 의자: Veeru Kasivisvanathan, MBBS BSc FRCS MSc PGCert PhD, Division of Surgery and Interventional Science, University College London, UK
  • 연구 의자: Doug Pendse, MB ChB MD (Res) MRCS FRCR, Department of Radiology, Universiy College London Hospitals NHS Foundation Trust, UK

연구 기록 날짜

이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.

연구 주요 날짜

연구 시작 (추정된)

2026년 10월 1일

기본 완료 (추정된)

2029년 1월 1일

연구 완료 (추정된)

2029년 1월 1일

연구 등록 날짜

최초 제출

2026년 6월 9일

QC 기준을 충족하는 최초 제출

2026년 6월 9일

처음 게시됨 (실제)

2026년 6월 15일

연구 기록 업데이트

마지막 업데이트 게시됨 (실제)

2026년 6월 15일

QC 기준을 충족하는 마지막 업데이트 제출

2026년 6월 9일

마지막으로 확인됨

2026년 6월 1일

추가 정보

이 연구와 관련된 용어

키워드

추가 관련 MeSH 약관

기타 연구 ID 번호

  • 338739

개별 참가자 데이터(IPD) 계획

개별 참가자 데이터(IPD)를 공유할 계획입니까?

예

IPD 계획 설명

Anonymised data will be available at request for bona fide researchers with important research questions subject to approval by the study steering committee.

IPD 공유 기간

Data will become available 1 year after publication of the main study results.

IPD 공유 액세스 기준

A study steering committee will review all requests for access to the data and will make decisions on whether or not to grant access to bona fide researchers based on the importance of the research question being asked, ensuring analysis is non overlapping with existing analyses and planned analyses.

IPD 공유 지원 정보 유형

  • 연구_프로토콜
  • 수액

약물 및 장치 정보, 연구 문서

미국 FDA 규제 의약품 연구

아니

미국 FDA 규제 기기 제품 연구

아니

이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .

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