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Trial Title:
Artificial Intelligence-Based Computer-Aided Diagnosis of Prostate Cancer
NCT ID:
NCT05513638
Condition:
the Application of Artificial Intelligence in the Diagnosis of Prostate Cancer
Conditions: Official terms:
Prostatic Neoplasms
Disease
Conditions: Keywords:
artificial intelligence
prostate cancer
magnetic resonance imaging
Study type:
Observational
Overall status:
Recruiting
Study design:
Time perspective:
Prospective
Intervention:
Intervention type:
Diagnostic Test
Intervention name:
the clinical use of artificial intelligence in the diagnosis of prostate cancer
Description:
Each study site will enroll consecutive eligible patients and randomize them to either
(a) a group with human-based interpretation or (b) a group with human-artificial
intelligence interactive interpretation, both of which are utilized as standards of care.
Arm group label:
The First Affiliated Hospital of Nanjing Medical University
Arm group label:
The First Affiliated Hospital of Soochow University
Summary:
One-fifth of all men will develop clinically significant prostate cancers (CsPC) in their
lifetime. An estimated 268,490 new prostate cancer (PCa) cases and 34,500 deaths are
expected in the United States during the year 2022, making PCa the second most common
cause of cancer-related deaths in men. MRI with the Prostate Imaging Reporting and Data
System (PI-RADS) is a current widely used communicative tool for both CsPC detection and
guiding targeted prostate biopsy. The high level of expertise required for accurate
interpretation and persistent inter-reader variability has limited consistency and it has
hindered the widespread adoption of PI-RADS. Artificial intelligence (AI) shows a broad
prospect for medical interpretation and triage in various challenging tasks , including
the PCa detection and staging with MRI. While rapid technical advances are furthering the
application of AI medical imaging, their implementation in clinical practice remains a
major hurdle. Besides, the prospect of data-derived AI tool is to assist human experts
rather than replace them, and whether AI can match or exceed the human experts is still a
matter of debate. Therefore, despite strong potential, there is urgent need for research
to better quantify the accuracy, generalizability and clinical applicability before the
clinical use of an AI in a real-world clinical setting.
Criteria for eligibility:
Study pop:
Patients ≥ 60 years of age who are clinical suspicious of prostate cancer, presenting
with an elevated prostatic specific antigen and/or abnormal digital rectal examination
during the study enrollment period, will be eligible for inclusion. Patients will be
excluded from screening if they are: (1) <60 years of age; (2) a previous surgery,
radiotherapy or drug therapy for prostate cancer (interventions for benign prostatic
hyperplasia or bladder outflow obstruction were deemed acceptable); (3) incomplete mp-MRI
examination or artifacts of the images.
Sampling method:
Probability Sample
Criteria:
Inclusion Criteria:
- Clinical suspicious of prostate cancer, presenting with an elevated prostatic
specific antigen and/or abnormal digital rectal examination
Exclusion Criteria:
- (1) <60 years of age; (2) a previous surgery, radiotherapy or drug therapy for
prostate cancer (interventions for benign prostatic hyperplasia or bladder outflow
obstruction were deemed acceptable); (3) incomplete mp-MRI examination or artifacts
of the images.
Gender:
Male
Minimum age:
60 Years
Maximum age:
90 Years
Healthy volunteers:
No
Locations:
Facility:
Name:
Yu-Dong Zhang
Address:
City:
Nanjing
Zip:
210029
Country:
China
Status:
Recruiting
Contact:
Last name:
Yu-Dong Zhang, MD;PHD
Phone:
15805151704
Email:
njmu_zyd@163.com
Start date:
August 22, 2022
Completion date:
August 22, 2026
Lead sponsor:
Agency:
The First Affiliated Hospital with Nanjing Medical University
Agency class:
Other
Collaborator:
Agency:
The First Affiliated Hospital of Soochow University
Agency class:
Other
Source:
The First Affiliated Hospital with Nanjing Medical University
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT05513638