Accelerated 3D whole-brain T1, T2, and proton density mapping: feasibility for clinical glioma MR imaging

Carolin M. Pirkl, Laura Nunez-Gonzalez, Florian Kofler, Sebastian Endt, Lioba Grundl, Mohammad Golbabaee, Pedro Gomez, et al

Research output: Contribution to journalArticlepeer-review

17 Citations (SciVal)


Purpose: Advanced MRI-based biomarkers offer comprehensive and quantitative information for the evaluation and characterization of brain tumors. In this study, we report initial clinical experience in routine glioma imaging with a novel, fully 3D multiparametric quantitative transient-state imaging (QTI) method for tissue characterization based on T1 and T2 values. Methods: To demonstrate the viability of the proposed 3D QTI technique, nine glioma patients (grade II–IV), with a variety of disease states and treatment histories, were included in this study. First, we investigated the feasibility of 3D QTI (6:25 min scan time) for its use in clinical routine imaging, focusing on image reconstruction, parameter estimation, and contrast-weighted image synthesis. Second, for an initial assessment of 3D QTI-based quantitative MR biomarkers, we performed a ROI-based analysis to characterize T1 and T2 components in tumor and peritumoral tissue. Results: The 3D acquisition combined with a compressed sensing reconstruction and neural network-based parameter inference produced parametric maps with high isotropic resolution (1.125 × 1.125 × 1.125 mm 3 voxel size) and whole-brain coverage (22.5 × 22.5 × 22.5 cm 3 FOV), enabling the synthesis of clinically relevant T1-weighted, T2-weighted, and FLAIR contrasts without any extra scan time. Our study revealed increased T1 and T2 values in tumor and peritumoral regions compared to contralateral white matter, good agreement with healthy volunteer data, and high inter-subject consistency. Conclusion: 3D QTI demonstrated comprehensive tissue assessment of tumor substructures captured in T1 and T2 parameters. Aiming for fast acquisition of quantitative MR biomarkers, 3D QTI has potential to improve disease characterization in brain tumor patients under tight clinical time-constraints.

Original languageEnglish
Pages (from-to)1831-1851
Number of pages21
Issue number11
Early online date9 Apr 2021
Publication statusPublished - 17 Nov 2021

Bibliographical note

Funding Information:
Open Access funding enabled and organized by Projekt DEAL. C.M.P., S.E., B.H.M., and M.I.M. are supported by Deutsche Forschungsgemeinschaft (DFG) through Research Training Group GRK 2274 and TUM International Graduate School of Science and Engineering (IGSSE), GSC 81. C.M.P., S.E., M.I.M. receive funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 952172. Patient data were acquired under the GE Healthcare work statement B-GEHC-05.

Publisher Copyright:
© 2021, The Author(s).


  • Glioma imaging
  • Image-based biomarkers
  • MRI
  • Multiparametric imaging
  • Neural networks

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology
  • Cardiology and Cardiovascular Medicine


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