Multi-parametric MRI in Patients of Bladder Cancer
Knowledge-guided Causal Diagnostic Network for the Detection of Muscle-invasive Bladder Cancer With Single T2-weighted Imaging
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Locations
-
-
-
Nanjing, China, 210029
- Recruiting
- Yu-Dong Zhang
-
Contact:
- Yu-Dong Zhang, MD;PHD
- Phone Number: 15805151704
- Email: njmu_zyd@163.com
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Urothelial carcinoma of the bladder confirmed by final histopathology ②Received a standard contrast-enhanced 3.0T mpMRI before surgery ③All tumors within patients included were resected and received pathologic examination separately
Exclusion Criteria:
①Absence of surgical interventions
②With inadequate image quality or with inadequate pathology for analysis
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
muscle-invasive bladder cancer
The postoperative pathology was muscle-invasive bladder cancer
|
Patients of bladder cancer underwent multiparameter magnetic resonance imaging before surgery
|
|
non-muscle-invasive bladder cancer
The postoperative pathology was non-muscle-invasive bladder cancer
|
Patients of bladder cancer underwent multiparameter magnetic resonance imaging before surgery
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Muscle-invasive bladder cancer
Time Frame: one month
|
The artificial intelligence diagnosis results, based on preoperative MRI, indicated muscle-invasive bladder cancer.
Subsequently, this preoperative diagnosis was compared with the postoperative pathological diagnosis to evaluate the diagnostic performance of the artificial intelligence.
|
one month
|
|
Non-muscle-invasive bladder cancer
Time Frame: one month
|
The artificial intelligence diagnosis results, based on preoperative MRI, indicated non-muscle-invasive bladder cancer.
Subsequently, this preoperative diagnosis was compared with the postoperative pathological diagnosis to evaluate the diagnostic performance of the artificial intelligence.
|
one month
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 2022-SR-471
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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