Evaluation of neonatal brain myelination using the T1‐ and T2‐weighted MRI ratio

Soun, Jennifer E.; Liu, Michael Z.; Cauley, Keith A.; Grinband, Jack

doi:10.1002/jmri.25570

Cited by 42 publications

(54 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…All the included participants fulfilled the following inclusion criteria: (1) complete clinical data (including demographic information, origin T1-MPRAGE, T2-FLAIR and PET imaging, and histological diagnosis); and (2) performance of lesionectomy. The following patients were excluded: (1) patients who were less than 3 years old, as the myelination of the neonatal brain does not reach maturity (Soun et al, 2016), which may influence imaging data normalization; (2) patients with low-quality images resulting from head motion, noise or other image artifacts; and (3) patients with FCD III on histopathology, as other principle lesions may affect the performance of the artificial neural network (ANN).…”

Section: Methodsmentioning

confidence: 99%

Clinical Value of Machine Learning in the Automated Detection of Focal Cortical Dysplasia Using Quantitative Multimodal Surface-Based Features

Zhang

et al. 2019

Front. Neurosci.

View full text Add to dashboard Cite

Objective: To automatically detect focal cortical dysplasia (FCD) lesion by combining quantitative multimodal surface-based features with machine learning and to assess its clinical value.Methods: Neuroimaging data and clinical information for 74 participants (40 with histologically proven FCD type II) was retrospectively included. The morphology, intensity and function-based features characterizing FCD lesions were calculated vertex-wise on each cortical surface and fed to an artificial neural network. The classifier performance was quantitatively and qualitatively assessed by performing statistical analysis and conventional visual analysis.Results: The accuracy, sensitivity, specificity of the neural network classifier based on multimodal surface-based features were 70.5%, 70.0%, and 69.9%, respectively, which outperformed the unimodal classifier. There was no significant difference in the detection rate of FCD subtypes (Pearson’s Chi-Square = 0.001, p = 0.970). Cohen’s kappa score between automated detection outcomes and post-surgical resection region was 0.385 (considered as fair).Conclusion: Automated machine learning with multimodal surface features can provide objective and intelligent detection of FCD lesion in pre-surgical evaluation and can assist the surgical strategy. Furthermore, the optimal parameters, appropriate surface features and efficient algorithm are worth exploring.

show abstract

Section: Methodsmentioning

confidence: 99%

Clinical Value of Machine Learning in the Automated Detection of Focal Cortical Dysplasia Using Quantitative Multimodal Surface-Based Features

Zhang

et al. 2019

Front. Neurosci.

View full text Add to dashboard Cite

show abstract

“…Although the T1w/T2w ratio is not a direct index of myelin, it is nevertheless considered a surrogate marker of myelin content [29]. This method was initially developed to evaluate intra-cortical myelin [29][30][31], and myelination of white matter in neonatal brains has also been investigated using this method [32]. The test-retest reliability of the T1w/T2w ratio has been reported to be high [33] and a histological study of patients with MS has shown that the T1w/T2w ratio in the cortex differed significantly between early-stage MS and healthy controls [34].…”

Section: Introductionmentioning

confidence: 99%

Myelin Measurement Using Quantitative Magnetic Resonance Imaging: A Correlation Study Comparing Various Imaging Techniques in Patients with Multiple Sclerosis

Saccenti

Hagiwara

Andica

et al. 2020

Cells

View full text Add to dashboard Cite

Evaluation of myelin by magnetic resonance imaging (MRI) is a difficult challenge, but holds promise in demyelinating diseases, such as multiple sclerosis (MS). Although multiple techniques have been developed, no gold standard has been established. This study aims to evaluate the correlation between synthetic MRI myelin volume fraction (SyMRIMVF) and myelin fraction estimated by other techniques, i.e., magnetization transfer saturation (MTsat), T1-weighted images divided by T2-weighted images (T1w/T2w), and radial diffusivity (RD) in patients with MS. We also compared the sensitivities of these techniques for detecting MS-related myelin damage. SyMRIMVF, MTsat, T1w/T2w, and RD were averaged on plaque, periplaque white matter, and normal-appearing white matter (NAWM). Pairwise correlation was calculated using Spearman’s correlation analysis. For all segmented regions, strong correlations were found between SyMRIMVF and T1w/T2w (Rho = 0.89), MTsat (Rho = 0.82), or RD (Rho = −0.75). For each technique, the average estimated myelin differed significantly among regions, but the percentage change of NAWM from both periplaque white matter and plaque were highest in SyMRIMVF. SyMRIMVF might be suitable for myelin evaluation in MS patients, with relevant results as compared to other well-studied techniques. Moreover, it presented better sensitivity for the detection of the difference between plaque or periplaque white matter and NAWM.

show abstract

“…Although T 1 w/T 2 w ratio is not a direct index of myelin, it is still considered a proxy of myelin content 36 . While intracortical myelin content across different ages has been evaluated using this method 36 , 37 , myelination of white matter (WM) in neonatal brains has also been investigated using this method 38 , 39 . Further, the test-retest reliability of T 1 w/T 2 w ratio has been reported to be high 40 .…”

Section: Introductionmentioning

confidence: 99%

Myelin Measurement: Comparison Between Simultaneous Tissue Relaxometry, Magnetization Transfer Saturation Index, and T1w/T2w Ratio Methods

Hagiwara

Hori

Kamagata

et al. 2018

Sci Rep

112

108

View full text Add to dashboard Cite

Magnetization transfer (MT) imaging has been widely used for estimating myelin content in the brain. Recently, two other approaches, namely simultaneous tissue relaxometry of R1 and R2 relaxation rates and proton density (SyMRI) and the ratio of T1-weighted to T2-weighted images (T1w/T2w ratio), were also proposed as methods for measuring myelin. SyMRI and MT imaging have been reported to correlate well with actual myelin by histology. However, for T1w/T2w ratio, such evidence is limited. In 20 healthy adults, we examined the correlation between these three methods, using MT saturation index (MTsat) for MT imaging. After calibration, white matter (WM) to gray matter (GM) contrast was the highest for SyMRI among these three metrics. Even though SyMRI and MTsat showed strong correlation in the WM (r = 0.72), only weak correlation was found between T1w/T2w and SyMRI (r = 0.45) or MTsat (r = 0.38) (correlation coefficients significantly different from each other, with p values < 0.001). In subcortical and cortical GM, these measurements showed moderate to strong correlations to each other (r = 0.54 to 0.78). In conclusion, the high correlation between SyMRI and MTsat indicates that both methods are similarly suited to measure myelin in the WM, whereas T1w/T2w ratio may be less optimal.

show abstract

Evaluation of neonatal brain myelination using the T1‐ and T2‐weighted MRI ratio

Abstract: 2 Technical Efficacy: Stage2 J. MAGN. RESON. IMAGING 2017;46:690-696.

Cited by 42 publications

References 32 publications

Clinical Value of Machine Learning in the Automated Detection of Focal Cortical Dysplasia Using Quantitative Multimodal Surface-Based Features

Clinical Value of Machine Learning in the Automated Detection of Focal Cortical Dysplasia Using Quantitative Multimodal Surface-Based Features

Myelin Measurement Using Quantitative Magnetic Resonance Imaging: A Correlation Study Comparing Various Imaging Techniques in Patients with Multiple Sclerosis

Myelin Measurement: Comparison Between Simultaneous Tissue Relaxometry, Magnetization Transfer Saturation Index, and T1w/T2w Ratio Methods

Contact Info

Product

Resources

About