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Research on the Application of Deep Learning and Rendering Technologies for Preoperative Planning of Laparoscopic Retroperitoneal Tumor Resection

Research on the Application of Deep Learning and Rendering Technologies for Preoperative Planning of Laparoscopic Retroperitoneal Tumor Resection

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600120546
Enrollment
Unknown
Registered
2026-03-16
Start date
2026-04-01
Completion date
Unknown
Last updated
2026-03-23

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

retroperitoneal tumor

Interventions

3D Surgical Navigation Model Constructed by AIIR-HRR:None
Conventional volume reconstruction:None

Sponsors

Yongchuan Hospital of Chongqing Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1.18–80 years old; 2.Clinically suspected retroperitoneal tumor requiring preoperative CT.

Exclusion criteria

Exclusion criteria: 1.Pregnancy; 2.Contrast allergy,radiation contraindications. 3.Renal dysfunction;

Design outcomes

Primary

MeasureTime frame
intraoperative blood loss;vascular injury rate;sensitivity of =1 mm vessel depiction;tumor-anatomy misclassification rate;—

Countries

China

Contacts

Public ContactYongxia Zhou

Yongchuan Hospital of Chongqing Medical University

120988395@qq.com+86 23 8538 1329

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Apr 3, 2026