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

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

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT06751498

Enrollment

300

Registered

2024-12-30

Start date

2025-01-01

Completion date

2028-01-01

Last updated

2025-04-17

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

Conditions

Renal Cell Cancer

Keywords

Articicial Intelligence, convolutional neural network, renal arterial perfusion model, partial nephrectomy, fractional renal function

Brief summary

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?

Detailed description

This prospective study is conducted to predict postoperative fractional renal function using the perfusion deficit method from a preoperatively established renal arterial perfusion model for people who are proposed to undergo partial nephrectomy. In this study, this prediction method will be compared with the true missing values of renal units on nuclear renal function, eGFR, and CTA. This study aims to evaluate the feasibility of applying the CNN-based model in predicting postoperative renal function after partial nephrectomy and provide high-level clinical evidence for the preoperative integrated diagnostic and treatment process of renal tumors, especially in terms of the functional evaluation.

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to 80 Years

Healthy volunteers

Inclusion criteria

* 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 * Life expectancy greater than 10 years

Exclusion criteria

* 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 * people who convert to radical nephrectomy during surgery * people who receive molecular targeted therapy, immunotherapy or chemotherapy during the postoperative follow-up period * people with serious systemic disease

Design outcomes

Primary

Measure	Time frame
GFR of ipsilateral and contralateral kidneys	3 months after surgery
volume of ipsilateral kidney	3 months after surgery

Secondary

Measure	Time frame
Postoperative total renal function(eGFR)	24 hours, 1 month, 3 months, 6 months, 1 year after surgery

Countries

China

Contacts

Primary ContactShao Pengfei, Professor

spf032@hotmail.com+8613851925825

Backup ContactMiao Haoqi, Postgraduate

mhq@stu.njmu.edu.cn+8613276636957

Outcome results