Tensor‐valued diffusion MRI differentiates cortex and white matter in malformations of cortical development associated with epilepsy

Lampinen, Björn; Zampeli, Ariadne; Björkman–Burtscher, Isabella M.; Szczepankiewicz, Filip; Källén, Kristina; Strandberg, Maria Compagno; Nilsson, Markus

doi:10.1111/epi.16605

Cited by 30 publications

(22 citation statements)

References 47 publications

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“…This method adds the possibility of disentangling bundle-specific metrics within a WM voxel with multiple fiber orientations. As diffusion-relaxation correlation [52], oscillating gradients [105,106], and tensorvalued encoding [107] with spin echo-prepared EPI read-out are all increasingly used for in vivo human studies on high-end conventional clinical scanners, our massively multidimensional acquisition and analysis approach has potential for translation to clinical research studies using only moderately longer scanning times than each of the individual lowerdimensional methods. Further studies are needed where all the quantitative information from the obtained distributions and maps is integrated with phantoms validation [108], as well as with advanced histological validation [109] of healthy and pathological tissues.…”

Section: Discussionmentioning

confidence: 99%

Massively Multidimensional Diffusion-Relaxation Correlation MRI

et al. 2022

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Diverse approaches such as oscillating gradients, tensor-valued encoding, and diffusion-relaxation correlation have been used to study microstructure and heterogeneity in healthy and pathological biological tissues. Recently, acquisition schemes with free gradient waveforms exploring both the frequency-dependent and tensorial aspects of the encoding spectrum b(ω) have enabled estimation of nonparametric distributions of frequency-dependent diffusion tensors. These “D(ω)-distributions” allow investigation of restricted diffusion for each distinct component resolved in the diffusion tensor trace, anisotropy, and orientation dimensions. Likewise, multidimensional methods combining longitudinal and transverse relaxation rates, R1 and R2, with (ω-independent) D-distributions capitalize on the component resolution offered by the diffusion dimensions to investigate subtle differences in relaxation properties of sub-voxel water populations in the living human brain, for instance nerve fiber bundles with different orientations. By measurements on an ex vivo rat brain, we here demonstrate a “massively multidimensional” diffusion-relaxation correlation protocol joining all the approaches mentioned above. Images acquired as a function of the magnitude, normalized anisotropy, orientation, and frequency content of b(ω), as well as the repetition time and echo time, yield nonparametric D(ω)-R1-R2-distributions via a Monte Carlo data inversion algorithm. The obtained per-voxel distributions are converted to parameter maps commonly associated with conventional lower-dimensional methods as well as unique statistical descriptors reporting on the correlations between restriction, anisotropy, and relaxation.

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Section: Discussionmentioning

confidence: 99%

Massively Multidimensional Diffusion-Relaxation Correlation MRI

et al. 2022

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“…T1 and T2 imaging distinguish the cortex and white matter and depend on differences in the myelin sheath. However, it cannot detect abnormal changes in phosphatides in myelin caused by MCD (Lampinen B, et al, 2020). The development of morphometric analysis programs (MAPs), an automated technique derived from T1-maps has helped lesion diagnosis with normal MRI, such as in patients with MCD (González-Ortiz S, et al, 2021).…”

Section: Imaging Technology In Patients With Structural Lesionsmentioning

confidence: 99%

Application value of molecular imaging technology in epilepsy

Rong

Zhang

Wang

et al. 2021

Ibrain

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Epilepsy is a common neurological disease with various seizure types, complicated etiologies, and unclear mechanisms. Its diagnosis mainly relies on clinical history, but an electroencephalogram is also a crucial auxiliary examination. Recently, brain imaging technology has gained increasing attention in the diagnosis of epilepsy, and conventional magnetic resonance imaging can detect epileptic foci in some patients with epilepsy. However, the results of brain magnetic resonance imaging are normal in some patients. New molecular imaging has gradually developed in recent years and has been applied in the diagnosis of epilepsy, leading to enhanced lesion detection rates. However, the application of these technologies in epilepsy patients with negative brain magnetic resonance must be clarified. Thus, we reviewed the relevant literature and summarized the information to improve the understanding of the molecular imaging application value of epilepsy.

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“…Quantitative assessment for potential imaging biomarkers was available for 10 studies (10/25, 40%) including 4 studies with hippocampal volumetry (19,30,35,36), 3 studies with diffusion tensor parameters (37) or fiber tracking (38,43) on DTI, 2 studies with metabolites from MR spectroscopy (35, 39), 1 study with vessel density (40), 1 study with perivascular space (41), and 1 study with functional MRI (42).…”

Section: Systematic Review Of Quantitative Assessment and Potential Imentioning

confidence: 99%

Utility of 7 Tesla Magnetic Resonance Imaging in Patients With Epilepsy: A Systematic Review and Meta-Analysis

et al. 2021

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Objective: 7 Tesla magnetic resonance imaging (MRI) enables high resolution imaging and potentially improves the detection of morphologic abnormalities in patients with epilepsy. However, its added value compared with conventional 1.5T and 3.0T MRI is unclear. We reviewed the evidence for the use of 7 Tesla MRI in patients with epilepsy and compared the detection rate of focal lesions with clinical MRI.Methods: Clinical retrospective case studies were identified using the indexed text terms “epilepsy” AND “magnetic resonance imaging” OR “MR imaging” AND “7T” OR “7 Tesla” OR “7T” in Medline (2002-September 1, 2020) and Embase (1999-September 1, 2020). The study setting, MRI protocols, qualitative, and quantitative assessment were systematically reviewed. The detection rate of morphologic abnormalities on MRI was reported in each study in which surgery was used as the reference standard. Meta-analyses were performed using a univariate random-effects model in diagnostic performance studies with patients that underwent both 7T MRI and conventional MRI.Results: Twenty-five articles were included (467 patients and 167 healthy controls) consisting of 10 case studies, 10 case-control studies, 4 case series, and 1 cohort study. All studies included focal epilepsy; 12 studies (12/25, 48%) specified the disease etiology and 4 studies reported focal but non-lesional (MRI-negative on 1.5/3.0T) epilepsy. 7T MRI showed superior detection and delineation of morphologic abnormalities in all studies. In nine comparative studies, 7T MRI had a superior detection rate of 65% compared with the 22% detection rate of 1.5T or 3.0T.Significance: 7T MRI is useful for delineating morphologic abnormalities with a higher detection rate compared with conventional clinical MRI. Most studies were conducted using a case series or case study; therefore, a cohort study design with clinical outcomes is necessary.Classification of Evidence: Class IV Criteria for Rating Diagnostic Accuracy Studies.

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Tensor‐valued diffusion MRI differentiates cortex and white matter in malformations of cortical development associated with epilepsy

Abstract: This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Cited by 30 publications

References 47 publications

Massively Multidimensional Diffusion-Relaxation Correlation MRI

Massively Multidimensional Diffusion-Relaxation Correlation MRI

Application value of molecular imaging technology in epilepsy

Utility of 7 Tesla Magnetic Resonance Imaging in Patients With Epilepsy: A Systematic Review and Meta-Analysis

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