RecruitingNCT07166445

Deep Learning for Automated Discrimination Between Stage T1-T2 and T3 Renal Cell Carcinoma on Contrast-Enhanced CT

Sponsor

Peking University First Hospital

Enrollment

1,000 participants

Start Date

Sep 1, 2024

Study Type

OBSERVATIONAL

Conditions

Carcinoma, Renal Cell Pathology Deep Learning Diagnostic Imaging

Summary

This study aims to develop and validate a contrast-enhanced CT-based deep-learning model for automatic and accurate preoperative discrimination between T1-T2 and T3 renal cell carcinoma. By quantifying the model's diagnostic performance on an independent test set-using AUC, sensitivity, specificity, positive/negative predictive values, and decision-curve analysis-we will establish a decision-support tool that can be seamlessly integrated into clinical PACS, thereby reducing staging errors, refining surgical planning, and improving patient outcomes.

Eligibility

Min Age: 18 YearsMax Age: 85 Years

Plain Language Summary

Simplified for easier understanding

This is an imaging research study, not a treatment trial. Researchers are training an artificial intelligence (AI) system to automatically identify the stage of kidney cancer from CT scans — specifically to tell apart early-stage (T1–T2) from more advanced (T3) disease. Better AI staging could help doctors plan surgery and treatment more accurately. **You may be eligible if...** - You have had kidney cancer confirmed by surgery and pathology - You had a contrast-enhanced CT scan at the study institution before surgery, with thin image slices (≤1 mm) - Your cancer was staged as T1a–T2b or T3a **You may NOT be eligible if...** - Your tumor is a type other than renal cell carcinoma - Your CT images have severe artifacts or poor image quality Talk to your doctor to see if this trial is right for you.

This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.

Interested in this trial?

Get notified about updates and connect with the research team.

Interventions

OTHERNone intervention

this study is retrospective based on the CT images, which dose include any intervention.

Locations(1)

Peking University First Hospital, Beijing,

Beijing, China

View Full Details on ClinicalTrials.gov

For the most up-to-date information, visit the official listing.

Visit

NCT07166445

Related Trials

Extension Study for Participants in Studies That Include Belzutifan (MK-6482-043/LITESPARK-043)

NCT0740516410 locations

A Clinical Study of Belzutifan (MK-6482) and Zanzalintinib in People With Renal Cell Carcinoma (RCC) (LITESPARK-034/LS-034/MK-6482-034)

NCT074894955 locations

Study of Orellanine in Metastatic Clear-Cell or Papillary Renal Cell Carcinoma

NCT052879455 locations

Prospective User Study and Multicenter Validation of Multimodal Medical Imaging Large Models

NCT075550021 location

Symbiotic-GU-08: A Study to Learn About the Medicine Called PF-08634404 Dosed Alone and in Combination With Other Anticancer Therapies in Adults With Locally Advanced or Metastatic Renal Cell Cancer

NCT0722741549 locations