Mean displacement map of spine and spinal cord disorders using high b-value q-space imaging-feasibility study

Hori, Masaaki; Motosug, Utaroh; Fatima, Zareen; Ishigame, Keiichi; Araki, Tsutomu

doi:10.1258/ar.2011.110226

Cited by 9 publications

(4 citation statements)

References 28 publications

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“…18,21 However, for q-space analysis, QSI-analyzer was introduced for calculating the FWHM of the PDF and the mean displacement of water molecules. 22,26,30,31 For diŠusional kurtosis analysis, diffusion kurtosis estimator (DKE) 29,32 and the combination of dTV¿FZR (http://www.ut-radiology. umin.jp/people/masutani/dTV.htm) and VOLUME-ONE software (http://www.volume-one.org/) have been introduced in the literature 33,34 (Fig.…”

Section: Software For Calculating Non-gaussian Metricsmentioning

confidence: 99%

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Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

Hori

Fukunaga

Masutani

et al. 2012

MRMS

Self Cite

104

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Recently, non-Gaussian diŠusion-weighted imaging (DWI) techniques, including qspace imaging (QSI) and diŠusional kurtosis imaging (DKI), have emerged as advanced methods to evaluate tissue microstructure in vivo using water diŠusion. QSI and DKI have shown promising results in clinical applications, such as in the evaluation of brain tumors (e.g., grading gliomas), degenerative diseases (e.g., speciˆc diagnosis of Parkinson disease), demyelinating diseases (e.g., assessment of normal-appearing tissue of multiple sclerosis), and cerebrovascular diseases (e.g., assessment of the microstructural environment of fresh infarctions). Representative metrics in clinical use are the full width at half maximum, also known as the mean displacement of the probability density function curve, which is derived from QSI, and diŠusional kurtosis, which is derived from DKI. These new metrics may provide information on tissue structure in addition to that provided by conventional Gaussian DWI investigations that use the apparent diŠusion coe‹cient and fractional anisotropy, recognized indices for evaluating disease and normal development in the brain and spine. In some clinical situations, sensitivity for detecting pathological conditions is higher using QSI and DKI than conventional DWI and diŠusion tensor imaging (DTI) because DWI and DTI calculations are based on the assumption that water molecules follow a Gaussian distribution, whereas hindrance of the distribution of water molecules by complex and restricted structures in actual neural tissues produces distributions that are far from Gaussian. We review the technical aspects and clinical applications of QSI and DKI, focusing on clinical use and in vivo studies and highlighting diŠerences from conventional diŠusional metrics.

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Section: Software For Calculating Non-gaussian Metricsmentioning

confidence: 99%

“…Therefore, they concluded that this technique has the potential to provide additional clinical informa- tion to that obtained with conventional MR imaging. 31 …”

Section: Neoplasms Of the Brain And Spinementioning

confidence: 99%

Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

Hori

Fukunaga

Masutani

et al. 2012

MRMS

Self Cite

104

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“…This technique does not require the assumption of a Gaussian shape and model of water molecules. It has shown promise for evaluating brain and spinal disorders in vivo [8–13] because it can provide additional and different diffusion metrics, namely the root mean square displacement (RMSD) and diffusional kurtosis (DK) [14–20], which give in vivo microstructural information that complements the ADC and FA values. For example, increased ADC can indicate either decreased viscosity of the tissue or spatial dilatation of the water movement space [21].…”

Section: Introductionmentioning

confidence: 99%

New diffusion metrics for spondylotic myelopathy at an early clinical stage

et al. 2012

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ObjectivesTo investigate the use of root mean square displacement (RMSD) and mean diffusional kurtosis (DK) metrics of q-space imaging data to estimate spinal cord compression in patients with early cervical spondylosis.MethodsWe studied 50 consecutive patients at our institution (22 male, 28 female; mean age 58 years; age range 20–86 years) who had clinical signs and symptoms suggestive of early clinical stage cervical myelopathy. After conventional magnetic resonance (MR) imaging, diffusion tensor and q-space image data were acquired using 3-T MR imaging. Fractional anisotropy (FA), apparent diffusion coefficient (ADC), RMSD and mean DK values were calculated and compared between compressed and uncompressed spinal cords.ResultsFA and mean DK values were significantly lower and RMSD was significantly higher (P = 0.0060, 0.0020 and 0.0062, respectively; Mann–Whitney U test with the Bonferroni correction) in compressed spinal cords than in uncompressed cords. ADC was also higher in compressed cords, but this difference was not statistically significant.ConclusionsIn the evaluation of spinal cord damage in early cervical spondylosis, mean DK and RMSD values in the spinal cord may be highly sensitive indicators of microstructural change and damage.Key Points• Absolute surgical indications for cervical spondylosis with myelopathy remain to be established.• Diffusion tensor MRI shows abnormalities in normal-appearing but compressed spinal cord.• Non-Gaussian diffusion analysis is highly sensitive in revealing spinal cord damage.

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“…However, DTI as a single-compartment model allows to reconstruct only a primary diffusion direction and fails to estimate more complex WM fiber configurations like crossing or bending fibers [49]. Higher-order diffusion models such as neurite orientation dispersion and density imaging (NODDI) [50][51][52][53][54][55], Ball-and-Sticks [8,30], diffusion kurtosis imaging (DKI) [56,57], AxCaliber [58,59], composite hindered and restricted model of diffusion (CHARMED) [60], Q-space imaging (QSI) [57,61,62] or q-ball imaging [63], which overcome DTI's limitation by modeling several tissue compartments were recently translated from the brain to SC imaging to provide a more precise depiction of complex SC microstructure.…”

Section: Diffusion Mrimentioning

confidence: 99%

Quantitative MR Markers in Non-Myelopathic Spinal Cord Compression: A Narrative Review

Valošek¹,

Bednařík²,

Keřkovský³

et al. 2022

Preprint

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Degenerative spinal cord (SC) compression is a frequent pathological condition with increasing prevalence throughout aging. Initial non-myelopathic cervical SC compression (NMDC) might progress over time into potentially irreversible degenerative cervical myelopathy (DCM). While quantitative MRI (qMRI) techniques demonstrated the ability to depict intrinsic tissue properties, longitudinal in-vivo biomarkers to identify NMDC patients who will eventually develop DCM are still missing. Thus, we aim to review the ability of qMRI techniques (such as diffusion MRI, diffusion tensor imaging (DTI), magnetization transfer (MT) imaging, magnetic resonance spec-troscopy (1H-MRS)) to serve as prognostic markers in NMDC. While DTI in NMDC patients con-sistently detected lower fractional anisotropy and higher mean diffusivity at compressed levels caused by demyelination and axonal injury, MT and 1H-MRS along with advanced and tract-specific diffusion MRI recently revealed microstructural alterations also rostrally pointing to Wallerian degeneration. Recent studies also disclosed significant relationship between micro-structural damage and functional deficits, assessed by qMRI and electrophysiology, respectively. Thus, tract-specific qMRI in combination with electrophysiology critically extend our under-standing of the underlying pathophysiology of degenerative SC compression and may provide predictive markers of DCM development for accurate patient management. However, the prog-nostic value must be validated in longitudinal studies.

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Mean displacement map of spine and spinal cord disorders using high b-value q-space imaging-feasibility study

Abstract: The heterogeneous MDP values were probably due to differences in tissues and pathologic structures. This technique has potential to provide additional clinical information to that obtained with conventional MR imaging.

Cited by 9 publications

References 28 publications

Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

New diffusion metrics for spondylotic myelopathy at an early clinical stage

Quantitative MR Markers in Non-Myelopathic Spinal Cord Compression: A Narrative Review

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