Arvid Lundervold, BSc, MD, PhD
Department of Biomedicine, University of Bergen & Department of Radiology, Haukeland University Hospital, Bergen, Norway - Computational Medicine
ESMRMB 2016 Congress - 33rd Annual Scientific Meeting, Vienna, Austria
Teaching Session: Functional kidney imaging with MRI (adv.)
Thursday 29-SEP-2016, 0800-0830
Github: https://github.com/arvidl/functional-kidney-imaging
Kidney function is related to maintenance of fluids, electrolytes, acid-base balance and clearance of toxins. Normal kidney function is maintained by coordinated regulation at different levels of organization warranting an integrative approach to kidney function in health and disease.
Important parameters describing kidney physiology and function are: renal plasma flow, RPF = (1 – Hct) · RBF, where Hct (hematocrit) is the fraction of blood volume representing the cellular elements of blood, RBF is the volume of blood delivered to the kidneys per unit time [mL/min]; renal perfusion, denoting renal blood flow per unit volume of kidney [mL/min/100 mL]; and glomerular filtration rate, GFR, the volume of fluid filtered from the renal glomerular capillaries into Bowman’s capsule per unit time, equal to the sum of the filtration rates of all functioning nephrons [mL/min]. Typical values in healthy humans: Hct ~0.40, RPF ~600 mL/min, GFR ~125 mL/min (70-kg man, where population studies have shown GFR to be proportional to body surface area, and sex and age dependent).
This teaching session will introduce measurement of renal perfusion and filtration in the framework of imaging-based biomarkers and computational medicine / systems medicine.
(i) The first part will give a brief overview of kidney structure and function and the key physiological parameters relevant to the clinics. In particular, we describe the gross functional anatomy of the kidney, the renal blood supply, and the ultrastructure of the filtration barrier, as well as some major diseases and conditions affecting normal perfusion and filtration. To complete this motivational part, we mention assessment of kidney function in the clinical laboratory based on the measurement of the clearance of various substances (exogenous and endogenous markers) by the kidneys, incorporating the “conservation of mass” principle also underlying imaging-based modeling of renal perfusion and filtration.
(ii) The second part addresses MR acquisition techniques in use for measuring perfusion and filtration, with a focus on DCE-MRI.
(iii) This part presents tracer kinetics and compartment models applied to parenchymal regions down to single voxels, where motion correction can be an issue.
(iv) In the fourth part, model-based estimation of renal perfusion and filtration using different numerical software and programming languages will be demonstrated.
Finally, we will point to relevant literature, software tools, and new initiatives addressing the lack of standardization in acquisition and analysis methods, limited access to data from previous studies, and the challenges of reproducibility and validation.
[1] Eikefjord E, Andersen E, Hodneland E, Zöllner F, Lundervold A, Svarstad E, Rørvik J. Use of 3D DCE-MRI for the estimation of renal perfusion and glomerular filtration rate: an intrasubject comparison of FLASH and KWIC with a comprehensive framework for evaluation. AJR Am J Roentgenol 2015;204:273-281. [PubMed]
[2] Eikefjord E, Andersen E, Hodneland E, Hanson EA, Lundervold A, Sourbron S, Svarstad E, Rørvik J. The repeatability, accuracy, and precision of renal function measurements using 1.5 T dynamic contrast-enhanced MRI and the reference method iohexol-GFR. To appear in Acta Radiologica.
[3] Grenier N, Merville P, Combe. C Radiologic imaging of the renal parenchyma structure and function. Nat Rev Nephrol 2016;12:348–359. [PubMed]
[4] Hodneland E, Hanson EA, Lundervold A, Modersitzki J, Eikefjord E, Munthe-Kaas AZ. Segmentation-driven image registration - application to 4D DCE-MRI recordings of the moving kidneys. IEEE Trans Image Process 2014;23:2392-2404. [PubMed]
[5] Koeppen BM, Stanton BA. Renal Physiology, 5th ed, Mosby, 2013. [Elsevier]
[6] Layton AT, Edwards A. Mathematical Modeling in Renal Physiology, Springer, 2014. [Springer]
[7] Sourbron SP, Michaely HJ, Reiser MF, Schoenberg SO. MRI-measurement of perfusion and glomerular filtration in the human kidney with a separable compartment model. Invest Radiol 2008;43:40-48. [PubMed]
[8] Turner N et al. Oxford Textbook of Clinical Nephrology, 4th ed, OUP, 2016. [Oxford]
Kidney function; Computational medicine; Imaging-based biomarkers; DCE-MRI; Compartment modeling; Software tools