Section 9 of 10
ONGOING TRIALS
Mustafa Guldan, Ibrahim Gulmaliyev, Rama AlShiab, Ermeena Shah, Lasin Ozbek, Mahmut Altindal, Bengi Gurses, Magdalena Madero, Alberto Ortiz, Adrian Covic, and Mehmet Kanbay · about 4 minutes
A variety of current clinical trials (Table 3) are investigating new renal imaging biomarkers in diverse populations affected by CKD, DKD, and kidney transplants. Multiple trials seek to establish a correlation between multiparametric MRI parameters (such as T1/T2 mapping, ASL, and ADC) and histopathological markers, including fibrosis, inflammation, and age-related decline. Some researchers utilize hyperpolarized^13C MRI to detect metabolic changes, including glycolysis and lactate accumulation, thereby providing insights into early disease phenotypes. A segment of research investigates repeatability through comparisons of scans acquired at brief intervals, while other studies evaluate imaging performance relative to gold-standard benchmarks, such as biopsy or renal perfusion assessed via CEUS. Using MRI and positron emission tomography (PET), a multicenter research study tracks DKD imaging indication. This implies that the prediction of imaging outcomes is being evaluated. There is a growing interest in the application of advanced imaging to predict the progression of a disease, ensure that the appropriate medication is administered to the appropriate individual, and enhance the accuracy of non-invasive kidney tests.
Clinical trial number | Study title | Status | Study type | Patient population | Imaging modality & exposure | Primary imaging or clinical outcome | Secondary outcomes/biomarkers
NCT06202235 | Multifrequency Renal MR Elastography in Evaluation of CKDs: Can Shear Stiffness Evaluate Renal Fibrosis in GFR-normal Patients? | Recruiting (28/04/2023) | Observational | Target sample size: 100Adults aged 18–65 years with CKD stages 1–5, undergoing renal MRI and biopsy | Multifrequency magnetic resonance elastography (MRE) | MRE accuracy in identifying renal fibrosis in CKD [Time Frame: 12 months] |
NCT06210555 | Multiparametric MRI in a Prospective Cohort of Living Kidney Donors, Recipients, and Healthy Controls: Correlations with Markers of Renal Function, Fibrosis, and Ageing | Recruiting (29/10/2024) | Observational | Target sample size: 96Living kidney donors, transplant recipients, and healthy controls ages 18–80 | Multiparametric MRI: T1/T2 mapping, ADC, ASL | Correlation between MRI parameters and fibrosis from renal biopsy [Time frame: up to 24 months] | GFR, biomarkers, aging-related decline, predictive modeling of allograft fibrosis
CTIS2024-512491-35–00 | CKD—imaging the metabolic derangements with ultra-sensitive MRI | Recruiting (01/04/2024) | Interventional (Therapeutic exploratory, Phase II) | Target sample size: 30Adults aged 18–85 years old; 8 healthy, 12 CKD (eGFR > 60), 10 ADPKD patients. | Multiparametric MRI using hyperpolarized [1–13C] pyruvate | MRI metabolic signature of the kidney: glycolysis shift, lactate/alanine production, fibrosis/inflammation correlation | Kidney function (blood/urine), expired CO₂ measures
NCT03716401 | Prognostic Imaging Biomarkers for DKD | Recruiting (01/09/2018) | Observational | Target sample size: 500Adults aged 18–80 years old with Type 2 diabetes and eGFR ≥30 ml/min/1.73 m2 | MRI, US, PET, microvascular assessment, and renal biopsy | Cross-sectional imaging biomarkers and renal biopsy correlation [Time Frame: 2 years] | Longitudinal imaging/biopsy marker assessment [Time Frame: 4 years]
NCT06159439 | Validation of Contrast Enhanced Ultrasound (CEUS) for the Assessment of Renal Perfusion Using Renal MRI in CKD | Not yet recruiting (02/01/2024) | Interventional, Single Group Assignment | Target sample size: 10Adults with CKD stages 3b or 4 (non-ADPKD), eligible for MRI and CEUS | CEUS and ASL-MRI scans | Correlation between ASL-MRI measures of cortical perfusion and CEUS measures of renal microvascular blood flow. | CEUS vs MRA perfusion metrics, PC-MRI flow, CEUS repeatability
NCT03578523 | Using MRI ASL Techniques for Quantitative Measurement of Renal Hemodynamics and Structural Parameters in Acute Kidney Injury and CKD | Unknown status (October 2015) | Observational | Target sample size: 50Adults aged >18 and <95 years old with CKD stages 3–4 | 3 Tesla multiparametric MRI (diffusion weighted imaging, T1, volume), iohexol clearance, renal biopsy | Differences in DWI, volume, and T1 MRI parameters between healthy, CKD, and AKI patients [Time frame: 3 years] | Correlation with eGFR, creatinine, renal biopsy, blood/urine sampling
| | | | (eGFR 20–60) and AKI stage 2–3. Excludes transplant patients. | | |
NCT03705091 | Non-Contrast MRI to Measure Renal Transplant Perfusion and Fibrosis—Association with Function and Prognosis | Unknown status (11/07/2017) | Observational | Target sample size: 20Adults aged 18–80 years old with recent or pending kidney transplantation | Magnetic resonance imaging | Change in arterial spin labeling (ASL) [Time Frame: Measured at 2, 6, and 12 months post-transplant] | Change in ADC [Time Frame: Measured at 2, 6, and 12 months post-transplant]
NCT04508049 | Quantitative Magnetization Transfer MRI for Evaluation of Renal Fibrosis | Active, not recruiting (01/10/2020) | Interventional, Single Group Assignment | Target sample size: 24Adults aged 40–80 years old with renovascular hypertension, eGFR >30; no transplant | Quantitative Magnetization Transfer MRI (qMT-MRI) | Fibrosis in stenotic and contralateral kidneys using qMT-MRI [Time Frame: Baseline] | Comparison of fibrosis to kidney function and injury markers
NCT05229263 | Exploratory Multicenter Clinical Study to Assess Repeatibility, Reproducibility, Acceptability, and Clinical Validity of Multiparametric Renal Magnetic Resonance Imaging | Active, not recruiting (25/11/2022) | Interventional, Non-Randomized, Parallel Assignment | Target sample size: 140Healthy adults and CKD stage 2–3 patients, ages 18+ | Non- contrast Enhanced Multiparametric Renal Magnetic Resonance (T1, T2, R2*, ADC, perfusion, ASL) | Repeatability and reproducibility of multiple MRI biomarkers across time points (1–2 weeks) | Variation by age/gender, correlation with eGFR, acceptability, full dataset completeness