Quantitative magnetic resonance imaging assessments of autosomal recessive polycystic kidney disease progression and response to therapy in an animal model

Erokwu, Bernadette O.; Anderson, Christian E.; Flask, Chris A.; Dell, Katherine MacRae

doi:10.1038/pr.2018.24

Cited by 10 publications

(16 citation statements)

References 38 publications

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“…Autosomal recessive polycystic kidney disease (ARPKD) is a rare but potentially lethal and rapidly progressing genetic disorder that affects approximately 1/20,000 children ( 1 , 2 ). ARPKD is typically characterized by diffuse renal microcysts caused by dilatations of the collecting tubules ( 2 ).…”

Section: Introductionmentioning

confidence: 99%

“…ARPKD kidney disease progression results in declining kidney function at an early age. Of the 70% of patients with ARPKD that survive through the neonatal period ( 3 ), 40% progress to end-stage renal disease (ESRD) by 15 years of age ( 1 , 3 ). Importantly, there are currently no disease-specific therapies for patients with ARPKD beyond kidney transplant and dialysis ( 1 , 2 , 4 ).…”

Section: Introductionmentioning

confidence: 99%

“…Of the 70% of patients with ARPKD that survive through the neonatal period ( 3 ), 40% progress to end-stage renal disease (ESRD) by 15 years of age ( 1 , 3 ). Importantly, there are currently no disease-specific therapies for patients with ARPKD beyond kidney transplant and dialysis ( 1 , 2 , 4 ). As a result, clinical management of chronic kidney disease (CKD) and its complications remains the primary treatment option for patients with ARPKD ( 1 , 2 , 4 ).…”

Section: Introductionmentioning

confidence: 99%

“…Importantly, there are currently no disease-specific therapies for patients with ARPKD beyond kidney transplant and dialysis ( 1 , 2 , 4 ). As a result, clinical management of chronic kidney disease (CKD) and its complications remains the primary treatment option for patients with ARPKD ( 1 , 2 , 4 ).…”

Section: Introductionmentioning

confidence: 99%

“…Several novel therapies have been recently shown to ameliorate kidney disease in animal models of ARPKD and other related ciliopathies ( 1 , 5 – 9 ). However, a major roadblock for implementing clinical trials in patients with ARPKD is the absence of sensitive measures of ARPKD kidney disease progression and / or therapeutic efficacy ( 1 , 4 ). Unfortunately, serum creatinine naturally increases with age in children ( 10 , 11 ).…”

Section: Introductionmentioning

confidence: 99%

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Multi-parametric MRI of kidney disease progression for autosomal recessive polycystic kidney disease: mouse model and initial patient results

et al. 2020

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Background: Autosomal recessive polycystic kidney disease (ARPKD) is a rare but potentially lethal genetic disorder typically characterized by diffuse renal microcysts. Clinical trials for patients with ARPKD are not currently possible due to the absence of sensitive measures of ARPKD kidney disease progression and/or therapeutic efficacy. Methods: In this study, animal and human MRI scanners were used to obtain quantitative kidney T1 and T2 relaxation time maps for both excised kidneys from bpk and wild type (WT) mice as well as for a pediatric patient with ARPKD and a healthy adult volunteer. Results: Mean kidney T1 and T2 relaxation times showed significant increases with age (p<0.05) as well as significant increases in comparison to WT mice (p<2 × 10 −10 ). Significant or nearly significant linear correlations were observed for mean kidney T1 (p=0.030) and T2 (p=0.054) as a function of total kidney volume, respectively. Initial MRF assessments in a patient with ARPKD showed visible increases in both kidney T1 and T2 in comparison to the healthy volunteer. Conclusions: These preclinical and initial clinical MRI studies suggest that renal T1 and T2 relaxometry may provide an additional outcome measure to assess cystic kidney disease progression in patients with ARPKD.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-parametric MRI of kidney disease progression for autosomal recessive polycystic kidney disease: mouse model and initial patient results

et al. 2020

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Renal MRI: From Nephron to NMR Signal

Bane

Seeliger

Cox

et al. 2023

Magnetic Resonance Imaging

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Renal diseases pose a significant socio‐economic burden on healthcare systems. The development of better diagnostics and prognostics is well‐recognized as a key strategy to resolve these challenges. Central to these developments are MRI biomarkers, due to their potential for monitoring of early pathophysiological changes, renal disease progression or treatment effects. The surge in renal MRI involves major cross‐domain initiatives, large clinical studies, and educational programs. In parallel with these translational efforts, the need for greater (patho)physiological specificity remains, to enable engagement with clinical nephrologists and increase the associated health impact. The ISMRM 2022 Member Initiated Symposium (MIS) on renal MRI spotlighted this issue with the goal of inspiring more solutions from the ISMRM community. This work is a summary of the MIS presentations devoted to: 1) educating imaging scientists and clinicians on renal (patho)physiology and demands from clinical nephrologists, 2) elucidating the connection of MRI parameters with renal physiology, 3) presenting the current state of leading MR surrogates in assessing renal structure and functions as well as their next generation of innovation, and 4) describing the potential of these imaging markers for providing clinically meaningful renal characterization to guide or supplement clinical decision making. We hope to continue momentum of recent years and introduce new entrants to the development process, connecting (patho)physiology with (bio)physics, and conceiving new clinical applications. We envision this process to benefit from cross‐disciplinary collaboration and analogous efforts in other body organs, but also to maximally leverage the unique opportunities of renal physiology.Level of Evidence1Technical Efficacy Stage2

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Dynamic parametric MRI and deep learning: Unveiling renal pathophysiology through accurate kidney size quantification

Klein,

Gladytz,

Millward

et al. 2023

NMR in Biomedicine

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Renal pathologies often manifest as alterations in kidney size, providing a valuable avenue for employing dynamic parametric MRI as a means to derive kidney size measurements for the diagnosis, treatment, and monitoring of renal disease. Furthermore, this approach holds significant potential in supporting MRI data‐driven preclinical investigations into the intricate mechanisms underlying renal pathophysiology. The integration of deep learning algorithms is crucial in achieving rapid and precise segmentation of the kidney from temporally resolved parametric MRI, facilitating the use of kidney size as a meaningful (pre)clinical biomarker for renal disease. To explore this potential, we employed dynamic parametric T2 mapping of the kidney in rats in conjunction with a custom‐tailored deep dilated U‐Net (DDU‐Net) architecture. The architecture was trained, validated, and tested on manually segmented ground truth kidney data, with benchmarking against an analytical segmentation model and a self‐configuring no new U‐Net. Subsequently, we applied our approach to in vivo longitudinal MRI data, incorporating interventions that emulate clinically relevant scenarios in rats. Our approach achieved high performance metrics, including a Dice coefficient of 0.98, coefficient of determination of 0.92, and a mean absolute percentage error of 1.1% compared with ground truth. The DDU‐Net enabled automated and accurate quantification of acute changes in kidney size, such as aortic occlusion (−8% ± 1%), venous occlusion (5% ± 1%), furosemide administration (2% ± 1%), hypoxemia (−2% ± 1%), and contrast agent‐induced acute kidney injury (11% ± 1%). This approach can potentially be instrumental for the development of dynamic parametric MRI‐based tools for kidney disorders, offering unparalleled insights into renal pathophysiology.

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Quantitative magnetic resonance imaging assessments of autosomal recessive polycystic kidney disease progression and response to therapy in an animal model

Cited by 10 publications

References 38 publications

Multi-parametric MRI of kidney disease progression for autosomal recessive polycystic kidney disease: mouse model and initial patient results

Multi-parametric MRI of kidney disease progression for autosomal recessive polycystic kidney disease: mouse model and initial patient results

Renal MRI: From Nephron to NMR Signal

Dynamic parametric MRI and deep learning: Unveiling renal pathophysiology through accurate kidney size quantification

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