Explore New Magnetic Resonance Technology in Assessment of Renal Dysfunction

Recruiting now

Conditions studied: Renal Insufficiency, Chronic

In brief

Currently, renal biopsy is the gold standard for evaluating renal pathology and renal fibrosis, but it is invasive and carries the risk of serious complications; and the sampled tissue is only a small part of the kidney, which is prone to sampling bias. The lack of reliable, comprehensive test results has hindered the research of new anti-fibrotic drugs and delayed the clinical application of effective new drugs. Therefore, the development of a non-invasive dynamic detection method for renal insufficiency and renal fibrosis in vivo is an urgent clinical problem to be solved. With the continuous development and update of technology, imaging provides a new way to non-invasively evaluate renal fibrosis. Due to the high resolution of soft tissue and the ability to perform multi-parameter analysis, magnetic resonance has developed the diagnosis of renal insufficiency and renal fibrosis from macroscopic simple biomorphological changes to microscopically complex pathophysiological changes. Many imaging techniques measure renal dysfunction and renal fibrosis by assessing the impact of fibrosis on the functional status, physical properties, and molecular properties of the kidney. In recent years, in the context of precision medicine, artificial intelligence technologies such as radiomics and machine learning are rapidly becoming very promising auxiliary tools in the imaging assessment of renal fibrosis. It can extract and learn features in images with high throughput, make greater use of information in medical images that cannot be recognized by the human eye, and achieve disease diagnosis, prognosis assessment, and efficacy prediction by building models. However, most of the current research is in the preliminary stage, and there are still few studies on the assessment of renal insufficiency and renal fibrosis. I believe that with the continuous improvement of algorithms and the optimization of models, the progress of radiomics and machine learning will be great. To a certain extent, it promotes the development of personalized medicine and precision medicine for patients with renal insufficiency and renal fibrosis.

Key facts

Study ID

NCT06366529

Run by

Zhen Li

People needed

500

Starts

2023-09-01

Expected to finish

2030-09-01

Last updated by the study team

2024-04-17

Who can join

Age: any. Sex: any. Healthy volunteers: accepted.

You may qualify if…

• Patients with clinically suspected or confirmed renal insufficiency and prescribed MR examination;
• Age/gender: no limit;
• Patients who voluntarily participate in clinical trials and sign written informed consent forms

You may not qualify if…

• Patients with pacemakers of unknown material, metal implants in the body, neurostimulators, and claustrophobia, etc.
• Patients who cannot tolerate sufficient breath-holding for adequate MR examination

Where it is running

• Tongji hospital, NO.1095 jiefang avenue — Wuhan, Hubei, China (enrolling)

Full record on ClinicalTrials.gov

Trial information comes from ClinicalTrials.gov and is refreshed daily. TrialsForMe does not provide medical care and does not run the studies it lists.