Ignite Creation Date:
2024-05-06 @ 3:49 PM
Last Modification Date:
2024-10-26 @ 1:57 PM
Study NCT ID:
NCT04765150
Status:
RECRUITING
Last Update Posted:
2024-04-16
First Post:
2021-02-18
Brief Title:
Integrating Quantitative MRI and Artificial Intelligence to Improve Prostate Cancer Classification
Sponsor:
Jonsson Comprehensive Cancer Center
Organization:
Jonsson Comprehensive Cancer Center
Study Overview
Official Title:
Integrating Quantitative MRI and Artificial Intelligence to Improve Prostate Cancer Classification
Status:
RECRUITING
Status Verified Date:
2024-04
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
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
Detailed Description:
PRIMARY OBJECTIVES
I To develop and evaluate quantitative dynamic contrast-enhanced DCE-MRI analysis techniques that minimize patient- and scanner-specific variabilities in the calculation of quantitative parameters
II To develop and evaluate diffusion weighted imaging DWI methods that reduce prostate geometric distortion due to patient- and scanner-specific susceptibility and eddy current effects
III To develop and evaluate multi-class deep learning models that systematically integrate quantitative multi-parametric mp-MRI features for accurate detection and classification of clinically significant prostate cancer csPCa
OUTLINE
RETROSPECTIVE Patients medical records are reviewed
PROSPECTIVE Patients undergo additional 3 Tesla T MRI imaging over 30 minutes before during or after their standard of care 3T MRI for a total of 15 hours
I To develop and evaluate quantitative dynamic contrast-enhanced DCE-MRI analysis techniques that minimize patient- and scanner-specific variabilities in the calculation of quantitative parameters
II To develop and evaluate diffusion weighted imaging DWI methods that reduce prostate geometric distortion due to patient- and scanner-specific susceptibility and eddy current effects
III To develop and evaluate multi-class deep learning models that systematically integrate quantitative multi-parametric mp-MRI features for accurate detection and classification of clinically significant prostate cancer csPCa
OUTLINE
RETROSPECTIVE Patients medical records are reviewed
PROSPECTIVE Patients undergo additional 3 Tesla T MRI imaging over 30 minutes before during or after their standard of care 3T MRI for a total of 15 hours
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
False
Is an FDA AA801 Violation?:
None
Secondary IDs
| Secondary ID | Type | Domain | Link |
|---|---|---|---|
| 441480-KS-29447 | OTHER_GRANT | NCI | httpsreporternihgovquickSearchR01CA248506 |
| NCI-2021-00373 | REGISTRY | None | None |
| 19-002202 | OTHER | None | None |
| R01CA248506 | NIH | None | None |