NCT06094322

Brief Summary

MR prostate exam is essential for the diagnosis, workup and follow-up of prostate cancer. It allows to detect subclinical prostate cancer following an increase in the level of PSA. The investigators can score the lesion according to the PIRADS classification and obtain an estimate of lesion malignancy. To perform this classification, T2 and DWI sequences are essential. Detection and characterization of malignant lesion is important to address appropriate patient care pathway. The purpose of this project is to evaluate novel deep learning (DL) T2-weighted TSE (T2DL) and Diffusion (DWIDL) sequences for prostate MR exam and investigate its impact on diagnostic, examination time, image quality, and PI-RADS classification compared to standard T2-weighted TSE (T2S) and standard Diffusion (DWIS) sequences.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
34

participants targeted

Target at P25-P50 for not_applicable prostate-cancer

Timeline
Completed

Started Jul 2022

Typical duration for not_applicable prostate-cancer

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Start

First participant enrolled

July 28, 2022

Completed
1.2 years until next milestone

First Submitted

Initial submission to the registry

October 17, 2023

Completed
6 days until next milestone

First Posted

Study publicly available on registry

October 23, 2023

Completed
6 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

April 9, 2024

Completed
1.6 years until next milestone

Study Completion

Last participant's last visit for all outcomes

December 1, 2025

Completed
Last Updated

December 8, 2025

Status Verified

December 1, 2025

Enrollment Period

1.7 years

First QC Date

October 17, 2023

Last Update Submit

December 2, 2025

Conditions

Keywords

T2 FSET2 DLRdiffusion DWIdiffusion DLRDeep Learning Prostate cancerPIRADS

Outcome Measures

Primary Outcomes (1)

  • Change in number of suspicious nodule prostate detection before and after rapid T2-weighted

    1 year

Interventions

Subjects will lie in supine position. The systematic use of a headset will reduce the acoustic noise inherent to the machine. We are going to carry out the standard MR prostate protocol which patients usually benefit from in clinical routine. This protocol consists of morphological sequences (T2 weighting with spin echo readout), Diffusion MR and dynamic contrast-enhanced sequences. We will then perform an additional faster enhanced T2-weighting SE and DWI sequences combined with Deep Learning reconstruction

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Age ≥ 18 ans
  • Healthy subject without history of hepatic disease
  • Patient addressed for an prostate MRI
  • Ability to give consent

You may not qualify if:

  • claustrophobia,
  • major obesity (\>140 kg),
  • Patient under guardianship or curators
  • Age \< 18 years,
  • Women,
  • History of prostatectomy or irradiation of the prostate
  • any contraindication to MRI exam

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Centre Hospitalier Universitaire d'Amiens

Amiens, Picardie, 80000, France

Location

MeSH Terms

Conditions

Prostatic Neoplasms

Condition Hierarchy (Ancestors)

Genital Neoplasms, MaleUrogenital NeoplasmsNeoplasms by SiteNeoplasmsGenital Diseases, MaleGenital DiseasesUrogenital DiseasesProstatic DiseasesMale Urogenital Diseases

Study Design

Study Type
interventional
Phase
not applicable
Allocation
NA
Masking
NONE
Purpose
DIAGNOSTIC
Intervention Model
SINGLE GROUP
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

October 17, 2023

First Posted

October 23, 2023

Study Start

July 28, 2022

Primary Completion

April 9, 2024

Study Completion

December 1, 2025

Last Updated

December 8, 2025

Record last verified: 2025-12

Data Sharing

IPD Sharing
Will not share

Locations