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Abstract: PO1229

Magnetic Resonance Fingerprinting (MRF) Identifies Potential Imaging Biomarkers for Autosomal Recessive Polycystic Kidney Disease (ARPKD)

Session Information

Category: Genetic Diseases of the Kidneys

  • 1001 Genetic Diseases of the Kidneys: Cystic

Authors

  • Keshock, Elise, Case Western Reserve University, Cleveland, Ohio, United States
  • Perino, Jacob R., Case Western Reserve University, Cleveland, Ohio, United States
  • Macaskill, Christina J., Case Western Reserve University, Cleveland, Ohio, United States
  • Parsons, Ashlee, Cleveland Clinic Children's Hospital, Cleveland, Ohio, United States
  • Hach, Jenna M., Cleveland Clinic Children's Hospital, Cleveland, Ohio, United States
  • Farr, Susan, Case Western Reserve University, Cleveland, Ohio, United States
  • Flask, Chris, Case Western Reserve University, Cleveland, Ohio, United States
  • Dell, Katherine MacRae, Case Western Reserve University, Cleveland, Ohio, United States
Background

Autosomal Recessive Polycystic Kidney Disease (ARPKD) is an important cause of morbidity and mortality in children with chronic kidney disease (CKD). Novel therapies have shown efficacy in ARPKD animal models, but clinical trials in ARPKD patients have not been possible due to the lack of sensitive measures of kidney disease progression. Non-invasive Magnetic Resonance Imaging (MRI) techniques, including novel MR Fingerprinting (MRF), show promise in addressing this unmet need. We previously identified MRF-based T1 and T2 mapping as potential biomarkers of ARPKD kidney disease in animal models and initial human studies. In the current study, we evaluated the relationship between these imaging parameters and renal function in ARPKD subjects with mild CKD.

Methods

ARPKD subjects (age 6-25 yrs) with estimated glomerular filtration rate (eGFR) >60ml/min/1.73m2 (bedside Schwartz <18 yo; CKD-EPI >18 yo) were scanned on a Siemens 3T MRI scanner utilizing novel MRF technology to simultaneously generate mean kidney T1 and T2 maps in 15 secs/imaging slice with no sedation or injectable contrast agent. The relationship between eGFR (U25 eGFR formula) and imaging parameters was assessed by Pearson correlations with significance set at <0.05.

Results

7 subjects (2M/5F, age=12±5 years) were imaged. eGFR was 87±21, range=52-109 ml/min/1.73m2; 5 had hypertension. Mean kidney T2 (94±10 msec) showed a significant negative correlation with eGFR (R=-0.86, p=0.013). Mean kidney T1 (2162±376 msec) also showed a strong negative correlation (R=-0.69) but did not yet reach significance (p=0.086). Mean T1 and T2 values for the right and left kidneys also demonstrated a significant correlation (T1: R=0.99, T2: R=0.79).

Conclusion

This is the first study to establish a relationship between MRI-derived imaging biomarkers (T1 and T2) and kidney function (eGFR) in ARPKD subjects. Despite the small cohort, data clearly demonstrate that mean T1 and T2 both increase with declining eGFR. These important findings suggest that MRF-based T1 and T2 mapping may provide a safe, non-invasive, quantitative, and reproducible measure of kidney disease severity to support future clinical trials to identify subjects at high risk for disease progression and monitor response to treatment.

Funding

  • NIDDK Support –