The Value of a Convolutional Neural Network-Based Renal Artery Perfusion Model in Predicting Renal Function After Partial Nephrectomy: A Prospective Study

Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18-80
SponsorShao Pengfei

About this trial

The goal of this observational study is to develop a CNN-based machine module to predict postoperative fractional renal function in people who are proposed to undergo partial nephrectomy. The main question it aims to answer is:

• Does this machine learning model accurately predict renal function after partial nephrectomy?

Eligibility criteria

Qualifiers

people with stage cT1 renal tumors confirmed by preoperative CT or MR

people who are proposed to undergoing partial nephrectomy

localized renal tumors without lymph node and distant metastases as defined by NCCN guidelines

ECOG score of 0 or 1

Disqualifiers

people with surgically unresectable lesions

people with Abnormal preoperative renal function, eGFR(estimated by CKD-EPI)<90ml/min/1.73m2

people who receive preoperative molecular targeted therapy, immunotherapy, chemotherapy

people with any contraindications to surgery

Trial design

Treatments tested in this trial

  • Not listed

Trial groups

No trial groups listed

Sponsors and collaborators

Shao Pengfei

Lead sponsor

The First Affiliated Hospital with Nanjing Medical University

Sponsor institution