Evaluation of Rapid T2-weighted and DWI MR Sequences Reconstructed by Deep Learning for Prostate Imaging

NCT ID: NCT06094322

Last Updated: 2025-12-08

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

34 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-07-28

Study Completion Date

2025-12-01

Brief Summary

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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.

Detailed Description

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Conditions

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Prostate Cancer

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Interventions

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MR prostate exam

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

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

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

Exclusion Criteria

* 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
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Centre Hospitalier Universitaire, Amiens

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Centre Hospitalier Universitaire d'Amiens

Amiens, Picardie, France

Site Status

Countries

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France

Other Identifiers

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PI2022_843_0108

Identifier Type: -

Identifier Source: org_study_id

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