Fast Whole-Brain Three-dimensional Macromolecular Proton Fraction Mapping in Multiple Sclerosis

Abstract Background: MR fingerprinting (MRF) is a novel imaging method proposed for the diagnosis of Multiple Sclerosis (MS). This study aims to determine if MR Fingerprinting (MRF) relaxometry can differentiate frontal normal appearing white matter (F-NAWM) and splenium in patients diagnosed with MS as compared to controls and to characterize the relaxometry of demyelinating plaques relative to the time of diagnosis.Methods: Three-dimensional (3D) MRF data were acquired on a 3.0T MRI system resulting in isotropic voxels (1x1x1mm3) and a total acquisition time of 4min 38s. Data were collected on 18 subjects paired with 18 controls. Regions of interested were drawn over MRF-derived T1 relaxometry maps encompassing selected MS lesions, F-NAWM and splenium. T1 and T2 relaxometry features from those segmented areas were used to classify MS lesions from F-NAWM and splenium with T-distributed stochastic neighbor embedding algorithms (T-SNE). Partial least squares discriminant analysis (PLS-DA) was performed to discriminate NAWM and Splenium in MS compared with controls. Results: Mean out-of-fold machine learning prediction accuracy for discriminant results between MS patients and controls for F-NAWM was 65% and approached 90% for the splenium. There was significant positive correlation between time since diagnosis and MS lesions mean T2 (p=0.015), minimum T1 (p=0.03) and negative correlation with splenium uniformity (p=0.04). Perfect discrimination (AUC=1) was achieved between selected features from MS lesions and F-NAWM.Conclusions: 3D-MRF has the ability to differentiate between MS and controls based on relaxometry properties from the F-NAWM and splenium. Whole brain coverage allows the assessment of quantitative properties within lesions that provide chronological assessment of the time from MS diagnosis.

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Whole brain 3D MR fingerprinting in multiple sclerosis: a pilot study

BMC Medical Imaging ◽

10.1186/s12880-021-00620-5 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Thomaz R. Mostardeiro ◽

Ananya Panda ◽

Norbert G. Campeau ◽

Robert J. Witte ◽

Nicholas B. Larson ◽

...

Keyword(s):

Multiple Sclerosis ◽

Prediction Accuracy ◽

Three Dimensional ◽

Acquisition Time ◽

Imaging Method ◽

Whole Brain ◽

Normal Appearing White Matter ◽

Quantitative Properties ◽

Perfect Discrimination ◽

3.0T Mri

Abstract Background MR fingerprinting (MRF) is a novel imaging method proposed for the diagnosis of Multiple Sclerosis (MS). This study aims to determine if MR Fingerprinting (MRF) relaxometry can differentiate frontal normal appearing white matter (F-NAWM) and splenium in patients diagnosed with MS as compared to controls and to characterize the relaxometry of demyelinating plaques relative to the time of diagnosis. Methods Three-dimensional (3D) MRF data were acquired on a 3.0T MRI system resulting in isotropic voxels (1 × 1 × 1 mm3) and a total acquisition time of 4 min 38 s. Data were collected on 18 subjects paired with 18 controls. Regions of interest were drawn over MRF-derived T1 relaxometry maps encompassing selected MS lesions, F-NAWM and splenium. T1 and T2 relaxometry features from those segmented areas were used to classify MS lesions from F-NAWM and splenium with T-distributed stochastic neighbor embedding algorithms. Partial least squares discriminant analysis was performed to discriminate NAWM and Splenium in MS compared with controls. Results Mean out-of-fold machine learning prediction accuracy for discriminant results between MS patients and controls for F-NAWM was 65 % (p = 0.21) and approached 90 % (p < 0.01) for the splenium. There was significant positive correlation between time since diagnosis and MS lesions mean T2 (p = 0.015), minimum T1 (p = 0.03) and negative correlation with splenium uniformity (p = 0.04). Perfect discrimination (AUC = 1) was achieved between selected features from MS lesions and F-NAWM. Conclusions 3D-MRF has the ability to differentiate between MS and controls based on relaxometry properties from the F-NAWM and splenium. Whole brain coverage allows the assessment of quantitative properties within lesions that provide chronological assessment of the time from MS diagnosis.

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Rapid, high-resolution, whole-brain, susceptibility-based MRI of multiple sclerosis

Multiple Sclerosis Journal ◽

10.1177/1352458514525868 ◽

2014 ◽

Vol 20 (11) ◽

pp. 1464-1470 ◽

Cited By ~ 52

Author(s):

P Sati ◽

DM Thomasson ◽

N Li ◽

DL Pham ◽

NM Biassou ◽

...

Keyword(s):

Multiple Sclerosis ◽

High Resolution ◽

Phase Contrast ◽

Neurological Diseases ◽

Three Dimensional ◽

Planar Imaging ◽

Whole Brain ◽

Imaging Sequence ◽

Tissue Iron ◽

Echo Planar

Background: Susceptibility-based MRI offers a unique opportunity to study neurological diseases such as multiple sclerosis (MS). In this work, we assessed a three-dimensional segmented echo-planar-imaging (3D-EPI) sequence to rapidly acquire high-resolution T2*-weighted and phase contrast images of the whole brain. We also assessed if these images could depict important features of MS at clinical field strength, and we tested the effect of a gadolinium-based contrast agent (GBCA) on these images. Materials and methods: The 3D-EPI acquisition was performed on four healthy volunteers and 15 MS cases on a 3T scanner. The 3D sagittal images of the whole brain were acquired with a voxel size of 0.55 × 0.55 × 0.55 mm3 in less than 4 minutes. For the MS cases, the 3D-EPI acquisition was performed before, during, and after intravenous GBCA injection. Results: Both T2*-weighted and phase-contrast images from the 3D-EPI acquisition were sensitive to the presence of lesions, parenchymal veins, and tissue iron. Conspicuity of the veins was enhanced when images were obtained during injection of GBCA. Conclusions: We propose this rapid imaging sequence for investigating, in a clinical setting, the spatiotemporal relationship between small parenchymal veins, iron deposition, and lesions in MS patient brains.

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