Skip to main content
MedPath Trial logoMedPath TrialMedPath Trial Home
Clinical Trials/ChiCTR2400088035
ChiCTR2400088035Not yet recruitingEarly Phase 1

基于 VCUG 图像构建对 VUR 自动诊断和分级的 Deep-VCUG 模型研究

自筹3 sites in 1 countryStarted: January 1, 2024Last updated:
Share to TwitterShare to FacebookShare to LinkedInShare to Reddit

Trial Snapshot

Phase
Early Phase 1
Status
Not yet recruiting
Sponsor
Locations
3
Primary Endpoint
VUR 返流分类结果的曲线下面积
Study OverviewStudy DesignEligibility CriteriaOutcomesInvestigatorsSitesRecords & IdentifiersSimilar Trials

Study Overview

Brief Summary

本研究旨在开发一种深度学习模型，以提高 VUR 对 VCUG 评分的可靠性，并将其性能与临床医生的性能进行比较。

Study Design

Study Type
诊断试验
Primary Purpose
连续入组
Masking
N/a

Eligibility Criteria

Ages
1 to 12 (—)
Sex
All

Inclusion Criteria

  • •在多中心医院就诊并行 VCUG 检查的患儿,年龄 1-13 周岁,影像诊断为膀胱输尿管返流,VCUG 图像清晰，无严重金属伪影。

Exclusion Criteria

  • •无法观察到完整输尿管、图像质量差、畸形过多（如泄殖腔畸形、异位输尿管和尿道下裂）、缺乏斜位片均被排除在外。

Outcomes

Primary Outcomes

VUR 返流分类结果的曲线下面积

VUR 返流分类结果的准确性

VUR 返流分类结果的灵敏度

VUR 返流分类结果的特异度

Secondary Outcomes

No secondary outcomes reported

Investigators

Sponsor
自筹

Study Sites (3)

Loading locations...

Similar Trials

Recruiting
Not Applicable
AI Assisted Screening for VHD Using Routine Chest CT Scans
NCT07449130Second Affiliated Hospital, Zhejiang University, School of Medicine3,000
Unknown
Not Applicable
uCT 868 深度学习重建功能临床试验
ChiCTR2500098537来自上海联影医疗科技股份有限公司的企业资助
Not yet recruiting
Unknown
验证基于深度学习的鼻咽癌 GTV 自动勾画方法准确性的前瞻性、多中心临床研究鼻咽癌
ChiCTR2400081428
Not yet recruiting
Not Applicable
Using Artificial Intelligence to Detect Blockages in Blood Vessels of the heart from CT Scan Images
CTRI/2024/07/070754Manipal Academy of Higher Education Manipal3,000
Not yet recruiting
Phase 3 4
Study on Training BeVigilant™ OraFusion System to Improve Dental AI Accuracy
CTRI/2025/04/084909Vigilant Biosciences Inc100