Journal article

Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI

Alexandra Ljimani, Anna Caroli, Christoffer Laustsen, Susan Francis, Iosif Alexandru Mendichovszky, Octavia Bane, Fabio Nery, Kanishka Sharma, Andreas Pohlmann, Ilona A Dekkers, Jean-Paul Vallee, Katja Derlin, Mike Notohamiprodjo, Ruth P Lim, Stefano Palmucci, Suraj D Serai, Joao Periquito, Zhen Jane Wang, Martijn Froeling, Harriet C Thoeny Show all

Magnetic Resonance Materials in Physics, Biology and Medicine | SPRINGER | Published : 2019

University of Melbourne Researchers

Grants

Awarded by COST (European Cooperation in Science and Technology)


Awarded by Medical Research Council


Awarded by NIH NIDDK individual fellowship


Awarded by Biomarker Enterprise to Attack Diabetic Kidney Disease project- Innovative Medicines Initiative 2 Joint Undertaking


Awarded by Swiss National Science foundation


Awarded by German Ministry for Education and Research (BMBF)


Funding Acknowledgements

The article is based upon work from COST Action Magnetic Resonance Imaging Biomarkers for Chronic Kidney Disease (PARENCHIMA, COST Action CA16103, www.renalmri.org), funded by COST (European Cooperation in Science and Technology), www.cost.eu.For additional information please visit PARENCHIMA project website: www.renalmri.org.MIA funding from the Medical Research Council (Grant No. MR/R02264X/1). BO Grant support (2016-2018) from NIH NIDDK individual fellowship 1F32DK109591. SK was supported by the Biomarker Enterprise to Attack Diabetic Kidney Disease project funded by the Innovative Medicines Initiative 2 Joint Undertaking under Grant agreement 115974. This joint undertaking received support from the European Union's Horizon 2020 Research and Innovation programme and European Federation of Pharmaceutical Industries and Associations. PA receives funding from the German Research Council (DFGY; Collaborative Research Centre SFB 1365 Renoprotection). J-PV and THC are supported by the Swiss National Science foundation Nb: IZCOZ0_177140/1. DK, NM, SEE research collaboration with Siemens. LRP Grant funding from Boehringer-Ingelheim. PJ receives funding from the German Ministry for Education and Research (BMBF; Grant VIP 03P00081). NT is supported by Germany Research Foundation, Collaborative Research Center 1365.