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ID07333495

Study of Non-invasive MRI to Monitor Kidney Transplant Function Using Personalized and Standalone Approaches

Led by Tongji Hospital · Updated on 2026-01-12

1000

Participants Needed

3

Research Sites

52 weeks

Total Duration

AI-Summary

What this Trial Is About

Researchers are investigating a new, non-invasive method to monitor kidney function after transplantation using advanced non-contrast Magnetic Resonance Imaging MRI. This study aims to create individualized baselines for transplanted kidneys by scanning donors before donation, allowing earlier detection of kidney problems compared to current blood tests or biopsies. It includes both donor-recipient pairs and recipients without donor data, primarily from deceased donors, to evaluate MRIs ability to track kidney health over time. Participants are divided into two main groups one where donors undergo pre-transplant MRI to establish a personalized baseline for their kidney before transplant, and recipients are followed post-transplant to compare function against this baseline the other group includes recipients without donor MRI data to validate MRIs standalone monitoring ability. The study also assesses body composition and metabolic health to better understand their impact on transplant kidney function. During the study, participants will undergo scheduled non-contrast MRI scans alongside clinical, laboratory, and body composition assessments. Data such as serum creatinine, eGFR, and biopsy results when available will be collected to correlate with MRI findings. The main outcome is the diagnostic accuracy of MRI for detecting transplant kidney rejection and dysfunction over up to five years. Approximately 1000 participants will be enrolled to provide robust data for developing a precise, individualized monitoring tool for kidney transplant patients.

CONDITIONS

Brief Title

A Mixed Cohort, Multicentre Exploratory Study of Non-invasive Quantitative Assessment of Renal Graft Function With Non-contrast Functional Magnetic Resonance Imaging

Research Team

Z

Zhen Professor Li, PHD,MD

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