A Fast Protocol for Multiparametric Characterisation of Diffusion in the Brain and Brain Tumours

Frontiers in Oncology, vol. 11, pp. 554205

Abstract

Multi-parametric tissue characterisation is demonstrated using a 4-minute protocol based on diffusion trace acquisitions. Three diffusion regimes are covered simultaneously: pseudo-perfusion, Gaussian, and non-Gaussian diffusion. The clinical utility of this method for fast multi-parametric mapping for brain tumours is explored. A cohort of 17 brain tumour patients was measured on a 3T hybrid MR-PET scanner with a standard clinical MRI protocol, to which the proposed multi-parametric diffusion protocol was subsequently added. For comparison purposes, standard perfusion and a full diffusion kurtosis protocol were acquired. Simultaneous amino-acid (18F-FET) PET enabled the identification of active tumour tissue. The metrics derived from the proposed protocol included perfusion fraction, pseudo-diffusivity, apparent diffusivity, and apparent kurtosis. These metrics were compared to the corresponding metrics from the dedicated acquisitions: cerebral blood volume and flow, mean diffusivity and mean kurtosis. Simulations were carried out to assess the influence of fitting methods and noise levels on the estimation of the parameters. The diffusion and kurtosis metrics obtained from the proposed protocol show strong to very strong correlations with those derived from the conventional protocol. However, a bias towards lower values was observed. The pseudo-perfusion parameters showed very weak to weak correlations compared to their perfusion counterparts. In conclusion, we introduce a clinically applicable protocol for measuring multiple parameters and demonstrate its relevance to pathological tissue characterisation.

Authors 5

1. Ricardo Loução Aachen Faculty of Medicine

   Forschungszentrum Jülich · Jülich Aachen Research Alliance · RWTH Aachen University

   Affiliation as printed

   Faculty of Medicine, RWTH Aachen University, Aachen, Germany

   Institute of Neurosciences and Medicine 11, INM-11, JARA, Forschungszentrum Jülich, Jülich, Germany

   Institute of Neurosciences and Medicine 4, INM-4, Forschungszentrum Jülich, Jülich, Germany

2. Ana‐Maria Oros‐Peusquens corresponding

   Forschungszentrum Jülich

   Affiliation as printed

   Institute of Neurosciences and Medicine 4, INM-4, Forschungszentrum Jülich, Jülich, Germany

3. Karl‐Josef Langen

   Forschungszentrum Jülich

   Affiliation as printed

   Institute of Neurosciences and Medicine 4, INM-4, Forschungszentrum Jülich, Jülich, Germany

4. Hugo Alexandre Ferreira

   University of Lisbon

   Affiliation as printed

   Institute of Biophysics and Biomedical Engineering, Faculty of Sciences of the University of Lisbon, Lisbon, Portugal

5. Nadim Jon Shah Aachen Department of Neurology

   Forschungszentrum Jülich · Jülich Aachen Research Alliance · RWTH Aachen University

   Affiliation as printed

   Department of Neurology, RWTH Aachen University, Aachen, Germany

   Institute of Neurosciences and Medicine 11, INM-11, JARA, Forschungszentrum Jülich, Jülich, Germany

   Institute of Neurosciences and Medicine 4, INM-4, Forschungszentrum Jülich, Jülich, Germany

   Jülich Aachen Research Alliance (JARA) - BRAIN - Translational Medicine, Aachen, Germany

   Jülich Aachen Research Alliance (JARA) – BRAIN – Translational Medicine, Aachen, Germany