RM-RENAL

Artículos científicos

• Echeverría-Chasco R, Martin Moreno PL, Garcia-Fernandez N, Vidorreta M, Aramendía-Vidaurreta V, Cano D, Villanueva Larre A, Bastarrika G, Fernandez-Seara MA. Multiparametric renal magnetic resonance imaging: a reproducibility study in renal allografts with stable function. NMR in Biomedicine. 2023; 36:e4832. DOI: 10.1002/nbm.4832
• Mora-Gutiérrez, J.M.; Fernández-Seara, M.A.; Echeverria-Chasco, R.; Garcia-Fernandez, N. Perspectives on the Role of Magnetic Resonance Imaging (MRI) for Noninvasive Evaluation of Diabetic Kidney Disease. J. Clin. Med. 2021, 10, 2461. https://doi.org/10.3390/jcm10112461
• Taso, M, Aramendía-Vidaurreta, V, Englund, EK, et al. Update on state-of-the-art for arterial spin labeling (ASL) human perfusion imaging outside of the brain. Magn Reson Med. 2023; 89: 1754-1776. doi: 10.1002/mrm.29609
  https://onlinelibrary.wiley.com/doi/10.1002/mrm.29609
• Anne Oyarzun-Domeño, Izaskun Cia, Rebeca Echeverria-Chasco, María A. Fernández-Seara, Paloma L. Martin-Moreno, Nuria Garcia-Fernandez, Gorka Bastarrika, Javier Navallas, Arantxa Villanueva, A deep learning image analysis method for renal perfusion estimation in pseudo-continuous arterial spin labelling MRI, Magnetic Resonance Imaging, Volume 104,2023,Pages 39-51,ISSN 0730-725X,https://doi.org/10.1016/j.mri.2023.09.007

Comunicaciones en congresos

• Oyarzun A, Cía I, Echeverria-Chasco R, Fernandez-Seara MA, Martin Moreno PL, Garcia-Fernandez N, Bastarrika G, Navallas J, and Villanueva Larre A. Differential quantification of cortical and medullary perfusion through Gaussian MixtureModel based segmentation on transplanted renal MRI. 2023 ISMRM & ISMRT Annual Meeting & Exhibition. Toronto. Poster.
• Echeverria-Chasco R, Martin Moreno PL, Garcia-Fernandez N, Vidorreta M, García L, Oyarzun A, Villanueva Larre A, Bastarrika G, Fernandez-Seara MA. Potential of multiparametric MRI in the longitudinal assessment of renal allografts after transplantation. 2023 ISMRM & ISMRT Annual Meeting & Exhibition. Toronto. Presentación oral.
• Oyarzun A, Echeverria-Chasco R, Martin Moreno PL, Garcia-Fernandez N, Bastarrika G, Fernandez-Seara MA, and Villanueva Larre A. ROI-Focused Non-Rigid Groupwise. Registration Approach for Motion Correction in ASL Renal Blood Flow Imaging. Annual Meeting ISMRM-ESMRMB. Londres (2022). Poster.
• Oyarzun A, Echeverria-Chasco R, Martin Moreno PL, Garcia-Fernandez N, Bastarrika G, Fernandez-Seara MA, and Villanueva Larre A. Cascaded Weighted UNET-SDM for Kidney Segmentation on Low Resolution ASL-MRI Images. ISMRM Workshop on Perfusion MRI:
  From Head to Toe. Los Angeles (2022). Poster.
• Echeverria-Chasco R, Martin Moreno PL, Garcia-Fernandez N, Vidorreta M, Oyarzun A, Villanueva Larre A, Bastarrika G, Fernandez-Seara MA. Prognostic potential of multiparametric MRI in the assessment of renal allografts early after transplantation. Joint Annual Meeting ISMRM-ESMRMB. Londres (2022). Poster.
• Echeverria-Chasco R, Martin Moreno PL, Garcia-Fernandez N, Vidorreta M, Garcia-Ruiz L, Guriérrez Castañe C, Cano D, Bastarrika G, Fernandez-Seara MA. Prognostic potential of multiparametric MRI in the assessment of renal allografts early after transplantation. ISMRM Perfusion Worshop: From Head to Toe. Los Angeles (2022). Presentación oral.
• Echeverria-Chasco R, Vidorreta M, Aramendia-Vidaurreta V, Cano D, Bastarrika G, Garcia-Fernandez N, Martin Moreno PL, Fernandez-Seara MA. Reproducibility of multiparametric MRI in transplanted kidneys. International Society of Magnetic Resonance in Medicine 29th Annual Meeting. Virtual (2021). Poster

Kidney transplant is the therapy of choice for patients with terminal chronic kidney disease. An average of 40 kidney transplants are performed every year in the Chartered Community of Navarre. In the last 20 years, there has been a dramatic drop in cases of early kidney transplant rejection. Nevertheless, transplant rejection in the medium and long term still affects a significant percentage of patients, with devastating consequences for their quality of life.

RM-RENAL is a project based in work done at the radiology and nephrology departments of the CUN, who have been collaborating since 2014 to use new imaging techniques that can help diagnose kidney disease based on magnetic resonance, a non-invasive technique that does not require the use of ionising radiation. Researchers from the UPNA also participated in RM-RENAL. They provided knowledge and experience with image processing and artificial intelligence methods.

The goal of the project was to optimise the existing tools at both centres and implement new methodologies, when necessary, to develop a method that makes it possible to monitor kidney transplant function after transplant and predict dysfunction of it early. That information is relevant, not just for therapeutic intervention, but also for decision-making about the future follow-up of the transplant.

During the project, the researchers were able to design and implement the method, which includes a magnetic resonance protocol with advanced techniques that make it possible to measure biomarkers related with kidney function and microstructure and a series of image processing algorithms that include automatic learning techniques to quantify the biomarkers using images obtained in the resonance. In the second phase of the project, the method was evaluated in a group of transplant patients with stable kidney function to determine the range of normal values of the biomarkers in the image and determine the reproducibility of the measurements.

Lastly, the diagnostic and prognostic capacity of the method was evaluated in a longitudinal study of recent transplant patients who were monitored over one year after transplant. The longitudinal study will end in 2023. The analysis of the data acquired up to now shows very promising results. The renal biomarkers could be measured with good reproducibility, and they show high correlations with the clinical variables used to measure kidney function. And they show a significant capacity to differentiate between transplants with poor or good functioning (potential diagnostics). Lastly, the images acquired immediately after kidney transplants let us determine which patients will have good kidney function three months after the transplant (prognostic capacity). These results, which have been reported in scientific journals and presented at several international conferences, need to be corroborated in future studies with larger patient groups, a longer monitoring period and the participation of more centres.

This project was made possible by the collaboration of a multidisciplinary research group made up of doctors and engineers from both centres.