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

Not Applicable
Completed
Conditions
Prostate Cancer
Registration Number
NCT06094322
Lead Sponsor
Centre Hospitalier Universitaire, Amiens
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.

Detailed Description

Not available

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
3
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

Study & Design

Study Type
INTERVENTIONAL
Study Design
SINGLE_GROUP
Primary Outcome Measures
NameTimeMethod
Change in number of suspicious nodule prostate detection before and after rapid T2-weighted1 year
Secondary Outcome Measures
NameTimeMethod

Trial Locations

Locations (1)

Centre Hospitalier Universitaire d'Amiens

🇫🇷

Amiens, Picardie, France

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