Development of an evaluation system for chronic kidney disease using functional MRI (magnetic resonance imaging) and machine learning

Development of an evaluation system for chronic kidney disease using functional MRI (magnetic resonance imaging) and machine learning - Development of an evaluation system for chronic kidney disease using functional MRI (magnetic resonance imaging) and machine learning

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

JPRN

Registry ID

JPRN-UMIN000044746

Enrollment

300

Registered

2021-07-15

Start date

2021-06-07

Completion date

Unknown

Last updated

2026-06-29

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

Conditions

Chronic kidney disease

Interventions

None listed

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: A chronic kidney disease patient who underwent MRI at Saitama Medical University for the diagnosis of chronic kidney disease.

Exclusion criteria

Exclusion criteria: After the introduction of renal replacement therapy, children, acute kidney injury, unilateral kidney disease (such as renovascular hypertension), kidney tumors, nephrotic syndrome, cystic disease, and postrenal renal failure

Design outcomes

Primary

Measure	Time frame
Annual rate of decline in estimated glomerular filtration rate	—

Secondary

Measure	Time frame
Estimated glomerular filtration rate, urinary protein levels and other urine and blood test results	—

Countries

Japan

Contacts

Public ContactHirokazu Okada

Saitama Medical University Department of Nephrology

hirookda@saitama-med.ac.jp0492761611

Outcome results