2891
Kidney MR Fingerprinting and Arterial Spin Labeling (ASL) Assessments of Autosomal Recessive Polycystic Kidney Disease (ARPKD)
Christina J. MacAskill1, Madison E. Kretzler2, Ashlee Parsons3, Victoria Gange3, Jenna Hach3, Stephanie Larson3, Yuran Zhu1, Jacob Perino2, Susan Farr2, Michael Markley2, Nicole Pritts2, Mireia Perera-Gonzalez4, Heather Clark5, Bernd Kuehn6, Ke Cheng Liu6, Xin Yu1,2,7, Dan Ma1,2, Yong Chen1,2, Katherine M. Dell3,8, and Chris A. Flask1,2,8
1Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, 2Radiology, University Hospitals- Cleveland Medical Center, Cleveland, OH, United States, 3Center for Pediatric Nephrology, Cleveland Clinic Children’s, Cleveland, OH, United States, 4Bioengineering, Northeastern University, Boston, MA, United States, 5School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, United States, 6Siemens Healthineers, Erlangen, Germany, 7Physiology and Biophysics, Case Western Reserve University, Cleveland, OH, United States, 8Pediatrics, Case Western Reserve University, Cleveland, OH, United States
1Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, 2Radiology, University Hospitals- Cleveland Medical Center, Cleveland, OH, United States, 3Center for Pediatric Nephrology, Cleveland Clinic Children’s, Cleveland, OH, United States, 4Bioengineering, Northeastern University, Boston, MA, United States, 5School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, United States, 6Siemens Healthineers, Erlangen, Germany, 7Physiology and Biophysics, Case Western Reserve University, Cleveland, OH, United States, 8Pediatrics, Case Western Reserve University, Cleveland, OH, United States
Synopsis
Keywords: Kidney, Genetic Diseases, ARPKD, Pediatric Genetic Disease
Motivation: There are no clinically available therapies for ARPKD.
Goal(s): We evaluated the ability of T1 and T2 from MR Fingerprinting (MRF) to assess kidney cystic burden and Arterial Spin Labeling (ASL) to assess kidney perfusion to detect and stage ARPKD kidney disease.
Approach: 12 ARPKD patients and 10 healthy adult volunteers were scanned on a Siemens 3T with kidney MRF and ASL MRI methods to generate kidney cortical perfusion maps.
Results: Significant increases in kidney T1 and T2, and reduced perfusion were observed between ARPKD patients and healthy volunteers (p<0.001) and between ARPKD patients with early and mild-to-moderate CKD based on eGFR (p<0.03).
Impact: The multi-modal MRI biomarkers in combination evaluated were able to distinctly stratify all three cohorts, including the two ARPKD patient cohorts, demonstrating the utility of a multi-modal MRI approach during future clinical trials aimed at limiting ARPKD kidney disease progression.
Introduction: Autosomal Recessive Polycystic Kidney Disease (ARPKD) is a potentially lethal genetic disorder that affects approximately 1/20,000 children. ARPKD kidney disease is characterized by diffuse fusiform dilatations of the collecting tubules ("microcysts").1–3 Importantly, there are currently no disease-specific, clinically-available therapies for ARPKD and treatment is limited to management of hypertension and chronic kidney disease (CKD) complications.4 Several novel therapies have shown promise in ARPKD animal models.5–8 Unfortunately, there are currently no effective measures for ARPKD kidney disease progression, creating a roadblock for implementing clinical trials in ARPKD patients. The goal of this study was to assess the combined ability of three quantitative MRI biomarkers to sensitively detect and stage ARPKD kidney disease: T1 and T2 relaxation times from MRF to assess cystic burden, and Arterial Spin Labeling (ASL) to assess kidney perfusion.
Methods: We obtained kidney MRI scans for 12 ARPKD patients (6-22 years of age) and 10 healthy adult volunteers (18-59 years of age). Each subject was scanned in a Siemens Vida 3T MRI scanner with three sequential protocols: (a) localizer scans for slice positioning; (b) a novel kidney Magnetic Resonance Fingerprinting (MRF) method to generate inherently co-registered coronal kidney T1 and T2 maps in 15 seconds / imaging slice9; and (c) a non-contrast Arterial Spin Labeling (ASL) MRI method to generate kidney cortical perfusion maps10. Serum creatinine and cystatin C were obtained for assessment of estimated GFR using the CKID U25 formula for the ARPKD patients11. A subset of ARPKD patients (n=10) underwent a second MRI scan the following day to determine the repeatability of the quantitative kidney MRF and ASL methods. A region-of-interest analysis was used to calculate mean kidney T1, T2, and perfusion values for each subject. Two-tailed Student’s t-tests were used to compare the kidney MRI and eGFR data between the subjects with ARPKD and the healthy volunteers. A probability of 0.05 (α) was used to test for significance.
Results: Significant differences between the MRF T1 and T2 and perfusion measurements were observed between ARPKD patients stratified into subgroups with early and mild-moderate CKD based on eGFR (above and below 90 ml/min/1.73m2, n=6/group, Figure 1, p<0.03). There were significant increases in both kidney T1 and T2, along with reduced perfusion detected between ARPKD patients (n=12) and healthy volunteers (n=10, p<0.001) (Figure 2). Kidney MRF showed a significant increase in both kidney T1 and T2 in the ARPKD patients in comparison to the healthy volunteers (T1: 2212 vs. 1597 ms; T2: 97 vs. 68 ms, p<0.002). These increased kidney MRF T1 and T2 values are consistent with our preclinical findings in bpk mice12 and are reflective of the increased cystic burden for ARPKD patients, as cysts are known to have higher T1 and T2 values in comparison to normal renal parenchyma. Scans on consecutive days for a subset of ARPKD patients (n=10) revealed mean variation of 2.1% for T1, 2.8% for T2, and 16.3% for perfusion. Figure 3 depicts a visual 3D comparison for cystic burden (T1,T2) and perfusion for the ARPKD patient cohorts and healthy volunteers. Importantly, the multi-modal MRI biomarkers in combination were able to distinctly stratify all three cohorts, including the two ARPKD patient cohorts, demonstrating the utility of a multi-modal MRI approach.
Conclusions: This initial cross-sectional study in children and young adults with ARPKD showed that these quantitative MRI biomarkers can: (1) sensitively detect early-stage ARPKD kidney disease (eGFR≥90, n=6) in comparison to healthy asymptomatic adult volunteers (n=10); and (2) differentiate subjects with early-stage CKD from subjects with mild-moderate CKD (eGFR<90, n=6). The multi-modal MRI methods shown in this study are repeatable in subjects with ARPKD as young as 6 years of age and can be completed within <15 minutes of total scan time with no injectable MRI contrast agent or sedation. As such, despite the small cohort size, these preliminary findings suggest that kidney MRF T1 and T2 and perfusion can be used as sensitive outcome measures in combination with clinical measures of kidney function (eGFR) during future clinical trials aimed at limiting ARPKD kidney disease progression.
Methods: We obtained kidney MRI scans for 12 ARPKD patients (6-22 years of age) and 10 healthy adult volunteers (18-59 years of age). Each subject was scanned in a Siemens Vida 3T MRI scanner with three sequential protocols: (a) localizer scans for slice positioning; (b) a novel kidney Magnetic Resonance Fingerprinting (MRF) method to generate inherently co-registered coronal kidney T1 and T2 maps in 15 seconds / imaging slice9; and (c) a non-contrast Arterial Spin Labeling (ASL) MRI method to generate kidney cortical perfusion maps10. Serum creatinine and cystatin C were obtained for assessment of estimated GFR using the CKID U25 formula for the ARPKD patients11. A subset of ARPKD patients (n=10) underwent a second MRI scan the following day to determine the repeatability of the quantitative kidney MRF and ASL methods. A region-of-interest analysis was used to calculate mean kidney T1, T2, and perfusion values for each subject. Two-tailed Student’s t-tests were used to compare the kidney MRI and eGFR data between the subjects with ARPKD and the healthy volunteers. A probability of 0.05 (α) was used to test for significance.
Results: Significant differences between the MRF T1 and T2 and perfusion measurements were observed between ARPKD patients stratified into subgroups with early and mild-moderate CKD based on eGFR (above and below 90 ml/min/1.73m2, n=6/group, Figure 1, p<0.03). There were significant increases in both kidney T1 and T2, along with reduced perfusion detected between ARPKD patients (n=12) and healthy volunteers (n=10, p<0.001) (Figure 2). Kidney MRF showed a significant increase in both kidney T1 and T2 in the ARPKD patients in comparison to the healthy volunteers (T1: 2212 vs. 1597 ms; T2: 97 vs. 68 ms, p<0.002). These increased kidney MRF T1 and T2 values are consistent with our preclinical findings in bpk mice12 and are reflective of the increased cystic burden for ARPKD patients, as cysts are known to have higher T1 and T2 values in comparison to normal renal parenchyma. Scans on consecutive days for a subset of ARPKD patients (n=10) revealed mean variation of 2.1% for T1, 2.8% for T2, and 16.3% for perfusion. Figure 3 depicts a visual 3D comparison for cystic burden (T1,T2) and perfusion for the ARPKD patient cohorts and healthy volunteers. Importantly, the multi-modal MRI biomarkers in combination were able to distinctly stratify all three cohorts, including the two ARPKD patient cohorts, demonstrating the utility of a multi-modal MRI approach.
Conclusions: This initial cross-sectional study in children and young adults with ARPKD showed that these quantitative MRI biomarkers can: (1) sensitively detect early-stage ARPKD kidney disease (eGFR≥90, n=6) in comparison to healthy asymptomatic adult volunteers (n=10); and (2) differentiate subjects with early-stage CKD from subjects with mild-moderate CKD (eGFR<90, n=6). The multi-modal MRI methods shown in this study are repeatable in subjects with ARPKD as young as 6 years of age and can be completed within <15 minutes of total scan time with no injectable MRI contrast agent or sedation. As such, despite the small cohort size, these preliminary findings suggest that kidney MRF T1 and T2 and perfusion can be used as sensitive outcome measures in combination with clinical measures of kidney function (eGFR) during future clinical trials aimed at limiting ARPKD kidney disease progression.
Acknowledgements
Siemens Healthineers, NIHReferences
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- Hartung, E. A. et al. Neurocognition in Children with Autosomal Recessive Polycystic Kidney Disease in the CKiD Cohort Study. Pediatr Nephrol 29, 1957–1965 (2014).
- Bergmann, C. ARPKD and early manifestations of ADPKD: the original polycystic kidney disease and phenocopies. Pediatr Nephrol 30, 15–30 (2015).
- Guay-Woodford, L. M. et al. Consensus Expert Recommendations for the Diagnosis and Management of Autosomal Recessive Polycystic Kidney Disease: Report of an International Conference. The Journal of Pediatrics 165, 611–617 (2014).
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- Shillingford, J. M. et al. The mTOR pathway is regulated by polycystin-1, and its inhibition reverses renal cystogenesis in polycystic kidney disease. Proc Natl Acad Sci U S A 103, 5466–5471 (2006).
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- MacAskill, C. J. et al. Rapid B1 -Insensitive MR Fingerprinting for Quantitative Kidney Imaging. Radiology 300, 380–387 (2021).
- Dekkers, I. A. et al. Consensus-based technical recommendations for clinical translation of renal T1 and T2 mapping MRI. Magma (New York, N.y.) 33, 163 (2020).
- Pierce, C. B. et al. Age- and sex-dependent clinical equations to estimate glomerular filtration rates in children and young adults with chronic kidney disease. Kidney Int 99, 948–956 (2021).
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Figures
Figure 1: Representative kidney T1 (A-C), T2 (D-F), and perfusion maps (G-I) from a healthy volunteer and two pediatric ARPKD patients representing the cohort with early CKD (eGFR ≥90 ml/min/1.73m2) and mild-moderate CKD (eGFR <90 ml/min/1.73m2) cohorts.
Figure 2: Comparison of mean kidney T1, T2 (from MRF), and perfusion (from ASL). All three MRI assessments detected significant differences between the two ARPKD cohorts with early CKD (eGFR ≥90 ml/min/1.73m2) and mild-moderate CKD (eGFR <90 ml/min/1.73m2) (p≤0.03) and between the ARPKD patients and the healthy volunteers (p≤0.03) (A-C).
Figure 3: A 3D visualization showing distinct stratification among all three cohorts (ARPKD patients with early CKD (blue, eGFR ≥90 ml/min/1.73m2), ARPKD patients with mild-to-moderate CKD (red, eGFR <90 ml/min/1.73m2), and healthy adult volunteers (green)).
DOI: https://doi.org/10.58530/2024/2891