scholarly journals Selective Inversion Recovery Quantitative Magnetization Transfer Brain MRI at 7T: Clinical and Postmortem Validation in Multiple Sclerosis

2018 ◽  
Vol 28 (4) ◽  
pp. 380-388 ◽  
Author(s):  
Francesca Bagnato ◽  
Simon Hametner ◽  
Giulia Franco ◽  
Siddharama Pawate ◽  
Subramaniam Sriram ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Magnetization Transfer ◽  
Brain Mri ◽  
Inversion Recovery ◽  
Selective Inversion

scholarly journals Selective inversion recovery quantitative magnetization transfer imaging: Toward a 3 T clinical application in multiple sclerosis

2019 ◽  
Vol 26 (4) ◽  
pp. 457-467 ◽  
Author(s):  
Francesca Bagnato ◽  
Giulia Franco ◽  
Fei Ye ◽  
Run Fan ◽  
Patricia Commiskey ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Magnetization Transfer ◽  
Brain Mri ◽  
Inversion Recovery ◽  
Clinical Disease ◽  
Normal Appearing White Matter ◽  
Selective Inversion ◽  
Pool Model ◽  
Magnetic Resonance Imaging Mri

Background:Assessing the degree of myelin injury in patients with multiple sclerosis (MS) is challenging due to the lack of magnetic resonance imaging (MRI) methods specific to myelin quantity. By measuring distinct tissue parameters from a two-pool model of the magnetization transfer (MT) effect, quantitative magnetization transfer (qMT) may yield these indices. However, due to long scan times, qMT has not been translated clinically.Objectives:We aim to assess the clinical feasibility of a recently optimized selective inversion recovery (SIR) qMT and to test the hypothesis that SIR-qMT-derived metrics are informative of radiological and clinical disease-related changes in MS.Methods:A total of 18 MS patients and 9 age- and sex-matched healthy controls (HCs) underwent a 3.0 Tesla (3 T) brain MRI, including clinical scans and an optimized SIR-qMT protocol. Four subjects were re-scanned at a 2-week interval to determine inter-scan variability.Results:SIR-qMT measures differed between lesional and non-lesional tissue ( p < 0.0001) and between normal-appearing white matter (NAWM) of patients with more advanced disability and normal white matter (WM) of HCs ( p < 0.05). SIR-qMT measures were associated with lesion volumes, disease duration, and disability scores ( p ⩽ 0.002).Conclusion:SIR-qMT at 3 T is clinically feasible and predicts both radiological and clinical disease severity in MS.

scholarly journals Rapid whole-brain quantitative magnetization transfer imaging using 3D selective inversion recovery sequences

2020 ◽  
Vol 68 ◽  
pp. 66-74 ◽  
Author(s):  
Matthew J. Cronin ◽  
Junzhong Xu ◽  
Francesca Bagnato ◽  
Daniel F. Gochberg ◽  
John C. Gore ◽  
...  
Keyword(s):  
Magnetization Transfer ◽  
Inversion Recovery ◽  
Magnetization Transfer Imaging ◽  
Whole Brain ◽  
Selective Inversion

scholarly journals Exploratory Radiomic Analysis of Conventional vs. Quantitative Brain MRI: Toward Automatic Diagnosis of Early Multiple Sclerosis

2021 ◽  
Vol 15 ◽  
Author(s):  
Elizaveta Lavrova ◽  
Emilie Lommers ◽  
Henry C. Woodruff ◽  
Avishek Chatterjee ◽  
Pierre Maquet ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Magnetization Transfer ◽  
Medical Image Analysis ◽  
Brain Mri ◽  
External Validation ◽  
Region Of Interest ◽  
Quantitative Mri ◽  
Training Dataset ◽  
Image Type

Conventional magnetic resonance imaging (cMRI) is poorly sensitive to pathological changes related to multiple sclerosis (MS) in normal-appearing white matter (NAWM) and gray matter (GM), with the added difficulty of not being very reproducible. Quantitative MRI (qMRI), on the other hand, attempts to represent the physical properties of tissues, making it an ideal candidate for quantitative medical image analysis or radiomics. We therefore hypothesized that qMRI-based radiomic features have added diagnostic value in MS compared to cMRI. This study investigated the ability of cMRI (T1w) and qMRI features extracted from white matter (WM), NAWM, and GM to distinguish between MS patients (MSP) and healthy control subjects (HCS). We developed exploratory radiomic classification models on a dataset comprising 36 MSP and 36 HCS recruited in CHU Liege, Belgium, acquired with cMRI and qMRI. For each image type and region of interest, qMRI radiomic models for MS diagnosis were developed on a training subset and validated on a testing subset. Radiomic models based on cMRI were developed on the entire training dataset and externally validated on open-source datasets with 167 HCS and 10 MSP. Ranked by region of interest, the best diagnostic performance was achieved in the whole WM. Here the model based on magnetization transfer imaging (a type of qMRI) features yielded a median area under the receiver operating characteristic curve (AUC) of 1.00 in the testing sub-cohort. Ranked by image type, the best performance was achieved by the magnetization transfer models, with median AUCs of 0.79 (0.69–0.90, 90% CI) in NAWM and 0.81 (0.71–0.90) in GM. The external validation of the T1w models yielded an AUC of 0.78 (0.47–1.00) in the whole WM, demonstrating a large 95% CI and a low sensitivity of 0.30 (0.10–0.70). This exploratory study indicates that qMRI radiomics could provide efficient diagnostic information using NAWM and GM analysis in MSP. T1w radiomics could be useful for a fast and automated check of conventional MRI for WM abnormalities once acquisition and reconstruction heterogeneities have been overcome. Further prospective validation is needed, involving more data for better interpretation and generalization of the results.

Brain MRI correlates of magnetization transfer imaging metrics in patients with multiple sclerosis

1999 ◽  
Vol 166 (1) ◽  
pp. 58-63 ◽  
Author(s):  
Marco Rovaris ◽  
Marco Bozzali ◽  
Mariaemma Rodegher ◽  
Carla Tortorella ◽  
Giancarlo Comi ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Magnetization Transfer ◽  
Brain Mri ◽  
Magnetization Transfer Imaging

scholarly journals The Prognostic Value of White-Matter Selective Double Inversion Recovery MRI Sequence in Multiple Sclerosis: An Exploratory Study

Diagnostics ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 686
Author(s):  
Francesco Crescenzo ◽  
Damiano Marastoni ◽  
Anna Isabella Pisani ◽  
Agnese Tamanti ◽  
Caterina Dapor ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Magnetization Transfer ◽  
Inversion Recovery ◽  
Double Inversion Recovery ◽  
Magnetization Transfer Ratio ◽  
Tissue Properties ◽  
Relapsing Remitting ◽  
3.0 T

Using a white-matter selective double inversion recovery sequence (WM-DIR) that suppresses both grey matter (GM) and cerebrospinal fluid (CSF) signals, some white matter (WM) lesions appear surrounded by a dark rim. These dark rim lesions (DRLs) seem to be specific for multiple sclerosis (MS). They could be of great usefulness in clinical practice, proving to increase the MRI diagnostic criteria specificity. The aims of this study are the identification of DRLs on 1.5 T MRI, the exploration of the relationship between DRLs and disease course, the characterization of DRLs with respect to perilesional normal-appearing WM using magnetization transfer imaging, and the investigation of possible differences in the underlying tissue properties by assessing WM-DIR images obtained at 3.0 T MRI. DRLs are frequent in primary progressive MS (PPMS) patients. Amongst relapsing-remitting MS (RRMS) patients, DRLs are associated with a high risk of the disease worsening and secondary progressive MS (SPMS) conversion after 15 years. The mean magnetization transfer ratio (MTR) of DRLs is significantly different from the lesion without the dark rim, suggesting that DRLs correspond to more destructive lesions.

scholarly journals Quantitative magnetization transfer imaging in human brain at 3 T via selective inversion recovery

2011 ◽  
Vol 66 (5) ◽  
pp. 1346-1352 ◽  
Author(s):  
Richard D. Dortch ◽  
Ke Li ◽  
Daniel F. Gochberg ◽  
E. Brian Welch ◽  
Adrienne N. Dula ◽  
...  
Keyword(s):  
Human Brain ◽  
Magnetization Transfer ◽  
Inversion Recovery ◽  
Magnetization Transfer Imaging ◽  
Selective Inversion

scholarly journals Optimization of selective inversion recovery magnetization transfer imaging for macromolecular content mapping in the human brain

2018 ◽  
Vol 80 (5) ◽  
pp. 1824-1835 ◽  
Author(s):  
Richard D. Dortch ◽  
Francesca Bagnato ◽  
Daniel F. Gochberg ◽  
John C. Gore ◽  
Seth A. Smith
Keyword(s):  
Human Brain ◽  
Magnetization Transfer ◽  
Inversion Recovery ◽  
Magnetization Transfer Imaging ◽  
Selective Inversion ◽  
Macromolecular Content

scholarly journals Quantitative magnetization transfer imaging of rodent glioma using selective inversion recovery

2013 ◽  
Vol 27 (3) ◽  
pp. 253-260 ◽  
Author(s):  
Junzhong Xu ◽  
Ke Li ◽  
Zhongliang Zu ◽  
Xia Li ◽  
Daniel F. Gochberg ◽  
...  
Keyword(s):  
Magnetization Transfer ◽  
Inversion Recovery ◽  
Magnetization Transfer Imaging ◽  
Selective Inversion ◽  
Rodent Glioma
Sign in / Sign up

Export Citation Format

Share Document