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Integrating Quantitative MRI and Artificial Intelligence to Improve Prostate Cancer Classification

About

Brief Summary

This study evaluates how new magnetic resonance imaging (MRI) and artificial intelligence techniques improve the image quality and quantitative information for future prostate MRI exams in patients with suspicious of confirmed prostate cancer. The MRI and artificial intelligence techniques developed in this study may improve the accuracy in diagnosing prostate cancer in the future using less invasive techniques than what is currently used.

Study Type
Observational
Phase
N/A

Eligibility

Gender
Male
Healthy Volunteers
No
Minimum Age
18 Years
Maximum Age
N/A

Inclusion Criteria:

  • Male patients 18 years of age and older
  • Clinical suspicion of prostate cancer or biopsy-confirmed prostate cancer
  • Undergone or undergoing multi-parametric 3 T prostate MRI at the University of California at Los Angeles (UCLA)
  • Ability to provide consent

Exclusion Criteria:

  • Contraindications to MRI (e.g., cardiac devices, prosthetic valves, severe claustrophobia)
  • Contraindications to gadolinium contrast-based agents other than the possibility of an allergic reaction to the gadolinium contrast-based agent
  • Prior radiotherapy

Join this Trial

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Study Stats
Protocol No.
19-002202
Category
Oncology
Radiological Sciences
Principal Investigator
Kyung Hyn Sung
Location
  • UCLA Westwood
For Providers
NCT No.
NCT04765150
For detailed technical eligibility, visit ClinicalTrials.gov.