Condition: Renal Insufficiency, Chronic · Sponsor: Zhen Li
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 u…
This description comes directly from the study's public registry record.
Zhen Li, Doctor · 02783663543 · zhenli@hust.edu.cn
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Source record: clinicaltrials.gov/study/NCT06366529