Clinical Applications of Synthetic MR
Masaaki Hori1

1Radiology, Juntendo University, Tokyo, Japan

Synopsis

Synthetic MR imaging is a technique of combination of 5-7 minutes MR scanning for source images and subsequent quantification of relaxation rates (T1, T2) and proton density for calculation of the signal intensity of a pixel by virtually setting any combination of echo time, repetition time to create MR images in clinical use, such as T1-weighted, T2-weighted and PD-weighted images. Moreover, some MR images based on single or double inversion time also can be computed. Purpose of this lecture is to understand the clinical usefulness of synthetic MR imaging towards neurologic disease, such as multiple sclerosis.

Target audience

Physicists and clinicians interested in clinical applications of synthetic MR imaging in the brain.

Objectives

Understand the clinical usefulness of synthetic MR imaging towards neurologic disease.

Methods

Synthetic MR imaging is a technique combining 5-7 minutes MR scan for source images and subsequent quantification of relaxation rates and proton density for calculation of the signal intensity of a pixel by virtually setting any combination of echo time (TE), repetition time (TR) and inversion time (TI) to create contrast-weighted MR images in clinical use, such as T1-weighted, T2-weighted, PD-weighted or fluid attenuated inversion recovery (FLAIR) images (1, 2). For ‘Go faster’ MR imaging in clinical use, Synthetic MR imaging has been used as below.

Rapid computed conventional imaging

From 5-7 minutes MR scan data, T1WI, T2WI, PDWI and FLAIR images can be obtained with any combination of TE, TR and TI settings using Synthetic MR imaging. In other words, it is not necessary to fix these parameters before actual patients study. This leads to faster MR scan with reduced failure rate. For example, the immature and developing normal brain has higher water content than the adult brain and is associated with a markedly higher T1 and T2 values (3). Moreover, myelination disorder shows abnormal T1 and T2 values in the brain parenchyma. Therefore, determining appropriate TE for T2WI in such conditions is often difficult before scanning to acquire high-contrast and high signal-to-noise ratio images. Using Synthetic MR, optimal T2WI can be feasible in every scanning by post-processing.

Rapid inversion recovery (IR) imaging

Images using IR technique, such as double inversion recovery (DIR, suppressing WM and CSF) or phase-sensitive inversion recovery (PSIR, relative values, instead of absolute values, are displayed based on T1IR images broaden the dynamic range), are reported as more useful tools for detecting pathologic lesions (e.g. multiple sclerosis (MS) plaques), compared with T2WI and FLAIR images (4). However, DIR and PSIR are time-consuming and often difficult to be used for every patient in clinical practice. Using Synthetic MR imaging, DIR and PSIR images can be computed from the same data, which are used for computing T1WI, T2WI and FLAIR, without extra scanning time. This leads to higher detectability for MS lesions in vivo in the same scanning time, compared with conventional MR imaging (5). Moreover, any preferable TI can be used for computing MR images using IR techniques. It has a potential for the new contrast MR images, which highlight the specific disease condition in vivo (6).

Rapid T1, T1 values and Proton density estimation for clinical diagnosis

Quantitative MR relaxometry in vivo has been applied to clinical investigation but not widely used in clinical daily practice, mainly because it needs relatively long scanning time. Synthetic MR imaging can provide T1, T2 and PD values in the whole brain voxels in clinical feasible scanning time. These quantitative MR relaxometry values may provide different and useful information to clinical diagnosis, in addition to conventional MR images (7). Moreover, the rapid quantitative MR relaxometry has a potential for rapid myelin estimation in vivo for neurological disorders such as MS, based on a theory utilizing the relaxometry values (8-10).

Acknowledgements

Akifumi Hagiwara, Christina Andica, Marcel Warntjes and Shigeki Aoki.

References

  1. Warntjes JB, Leinhard OD, West J, Lundberg P. Rapid magnetic resonance quantification on the brain: Optimization for clinical usage. Magn Reson Med 2008;60(2):320-329.
  2. Hagiwara A, Warntjes M, Hori M, et al. SyMRI of the Brain: Rapid Quantification of Relaxation Rates and Proton Density, With Synthetic MRI, Automatic Brain Segmentation, and Myelin Measurement. Invest Radiol 2017;52(10):647-657.
  3. http://www.mrineonatalbrain.com/ch02-03.php
  4. Nelson F, Poonawalla AH, Hou P, Huang F, Wolinsky JS, Narayana PA. Improved identification of intracortical lesions in multiple sclerosis with phase-sensitive inversion recovery in combination with fast double inversion recovery MR imaging. AJNR Am J Neuroradiol 2007;28(9):1645-1649.
  5. Hagiwara A, Hori M, Yokoyama K, et al. Synthetic MRI in the Detection of Multiple Sclerosis Plaques. AJNR Am J Neuroradiol 2017;38(2):257-263.
  6. Hagiwara A, Nakazawa M, Andica C, et al. Dural Enhancement in a Patient with Sturge-Weber Syndrome Revealed by Double Inversion Recovery Contrast Using Synthetic MRI. Magn Reson Med Sci 2016;15(2):151-152.
  7. Blystad I, Hakansson I, Tisell A, et al. Quantitative MRI for Analysis of Active Multiple Sclerosis Lesions without Gadolinium-Based Contrast Agent. AJNR Am J Neuroradiol 2016;37(1):94-100.
  8. Warntjes M, Engstrom M, Tisell A, Lundberg P. Modeling the Presence of Myelin and Edema in the Brain Based on Multi-Parametric Quantitative MRI. Front Neurol 2016;7:16.
  9. Warntjes JBM, Persson A, Berge J, Zech W. Myelin Detection Using Rapid Quantitative MR Imaging Correlated to Macroscopically Registered Luxol Fast Blue-Stained Brain Specimens. AJNR Am J Neuroradiol 2017;38(6):1096-1102.
  10. Hagiwara A, Hori M, Yokoyama K, et al. Analysis of White Matter Damage in Patients with Multiple Sclerosis via a Novel In Vivo MR Method for Measuring Myelin, Axons, and G-Ratio. AJNR Am J Neuroradiol 2017;38(10):1934-1940.
Proc. Intl. Soc. Mag. Reson. Med. 26 (2018)