4.4 Article

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

期刊

NEURORADIOLOGY
卷 63, 期 11, 页码 1831-1851

出版社

SPRINGER
DOI: 10.1007/s00234-021-02703-0

关键词

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

资金

  1. Deutsche Forschungsgemeinschaft (DFG) [GRK 2274]
  2. TUM International Graduate School of Science and Engineering (IGSSE) [GSC 81]
  3. European Union [952172]
  4. Projekt DEAL

向作者/读者索取更多资源

The study introduced a novel 3D multiparametric quantitative transient-state imaging (QTI) method for routine glioma imaging, demonstrating its feasibility in clinical practice and showing increased T1 and T2 values in tumor and peritumoral regions compared to healthy tissue. The 3D QTI technique, with high isotropic resolution and whole-brain coverage, has the potential to provide rapid and comprehensive tissue assessment for brain tumor patients, improving disease characterization under clinical time-constraints.
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 x 1.125 x 1.125 mm(3) voxel size) and whole-brain coverage (22.5 x 22.5 x 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.

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