Clinical Feasibility of Synthetic MRI in Multiple Sclerosis: A Diagnostic and Volumetric Validation Study

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SyMRI is a quantitative synthetic MR imaging method where a single saturation recovery TSE sequence is used to estimate the proton density, longitudinal relaxation rate, and transverse relaxation rate and allows for a free range of synthetic weightings. Twenty patients with MS and 20 healthy controls were enrolled and synthetic MR imaging was implemented on a Siemens 3T scanner. Diagnostic accuracy, lesion detection, and artifacts were assessed by blinded neuroradiologic evaluation, and CNR by manual tracing. Synthetic PD-, T1-, and T2-weighted images were of sufficient or good quality and were acquired in 7% less time than with conventional MRI. Synthetic FLAIR images suffered from artifacts. Also, synthetic MRI provided segmentations with the shortest processing time (16 seconds) and the lowest repeatability error for brain volume. Synthetic MRI can be an alternative to conventional MRI for generating diagnostic PD-, T1-, and T2-weighted images in patients with MS with fast and robust volumetric measurements.

Abstract

Conventional (top row) and synthetic (middle row) axial noncontrast MR imaging in a 49-year-old male patient with MS, from left to right: T1-, PD-, and T2-weighted, and FLAIR images. The bottom row shows brain tissue segmentations of the WM (cyan), GM (green), CSF (magenta), and other remaining brain tissues (yellow) from SyMRI.
Conventional (top row) and synthetic (middle row) axial noncontrast MR imaging in a 49-year-old male patient with MS, from left to right: T1-, PD-, and T2-weighted, and FLAIR images. The bottom row shows brain tissue segmentations of the WM (cyan), GM (green), CSF (magenta), and other remaining brain tissues (yellow) from SyMRI.

BACKGROUND AND PURPOSE

Quantitative MR imaging techniques are gaining interest as methods of reducing acquisition times while additionally providing robust measurements. This study aimed to implement a synthetic MR imaging method on a new scanner type and to compare its diagnostic accuracy and volumetry with conventional MR imaging in patients with MS and controls.

MATERIALS AND METHODS

Twenty patients with MS and 20 healthy controls were enrolled after ethics approval and written informed consent. Synthetic MR imaging was implemented on a Siemens 3T scanner. Comparable conventional and synthetic proton-density–, T1-, and T2-weighted, and FLAIR images were acquired. Diagnostic accuracy, lesion detection, and artifacts were assessed by blinded neuroradiologic evaluation, and contrast-to-noise ratios, by manual tracing. Volumetry was performed with synthetic MR imaging, FreeSurfer, FMRIB Software Library, and Statistical Parametric Mapping. Repeatability was quantified by using the coefficient of variance.

RESULTS

Synthetic proton-density–, T1-, and T2-weighted images were of sufficient or good quality and were acquired in 7% less time than with conventional MR imaging. Synthetic FLAIR images were degraded by artifacts. Lesion counts and volumes were higher in synthetic MR imaging due to differences in the contrast of dirty-appearing WM but did not affect the radiologic diagnostic classification or lesion topography (P = .50–.77). Synthetic MR imaging provided segmentations with the shortest processing time (16 seconds) and the lowest repeatability error for brain volume (0.14%), intracranial volume (0.12%), brain parenchymal fraction (0.14%), and GM fraction (0.56%).

CONCLUSIONS

Synthetic MR imaging can be an alternative to conventional MR imaging for generating diagnostic proton-density–, T1-, and T2-weighted images in patients with MS and controls while additionally delivering fast and robust volumetric measurements suitable for MS studies.

 

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Clinical Feasibility of Synthetic MRI in Multiple Sclerosis: A Diagnostic and Volumetric Validation Study
jross
Jeffrey Ross • Mayo Clinic, Phoenix

Dr. Jeffrey S. Ross is a Professor of Radiology at the Mayo Clinic College of Medicine, and practices neuroradiology at the Mayo Clinic in Phoenix, Arizona. His publications include over 100 peer-reviewed articles, nearly 60 non-refereed articles, 33 book chapters, and 10 books. He was an AJNR Senior Editor from 2006-2015, is a member of the editorial board for 3 other journals, and a manuscript reviewer for 10 journals. He became Editor-in-Chief of the AJNR in July 2015. He received the Gold Medal Award from the ASSR in 2013.

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