Diffusion tensor imaging applications in multiple sclerosis patients using 3T magnetic resonance: a preliminary study

Testaverde, Lorenzo; Caporali, Laura; Venditti, Eugenio; Grillea, Giovanni; Colonnese, Claudio

doi:10.1007/s00330-011-2342-9

Cited by 12 publications

(12 citation statements)

References 20 publications

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“…Concerning the spinal cord, the present study agreed with previous DTI studies of the spinal cord in MS patients reported a statistically significant FA difference between the control group and the MS patient group [3,[7][8][9][10][11]. Chen et al [7] stated that the decrease in the FA value of NAWM and the increase in MD value as compared to normal controls indicate the presence of occult damage to the NAWM.…”

Section: Discussionsupporting

confidence: 90%

“…Diffusion tensor imaging (DTI) found to be more sensitive in identifying the occult tissue damage in MS patients than conventional magnetic resonance (MR) by means of accurate data about water diffusion within tissues. The DTI by its quantitative indices fractional anisotropy and mean diffusivity allows evaluation of the more widespread tissue damage occurring outside the lesions seen by conventional MRI [3].…”

Section: Introductionmentioning

confidence: 99%

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Diffusion tensor imaging for assessment of normally appearing white matter of the brain and spinal cord in cases of multiple sclerosis: a multi-parametric correlation in view of patient’s clinical status

ElSayed¹,

Eltoukhy

Asaad

et al. 2019

Egypt J Radiol Nucl Med

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Background: Conventional MRI provides important morphologic information regarding the brain and spinal cord involvement by demyelinating plaques. However, it is of almost no value in assessing the normal-appearing white matter which has been proved by multiple pathologic studies to be directly and indirectly involved in the process of multiple sclerosis. Diffusion-weighted imaging and diffusion tensor imaging MRI have been widely used in multiple researches as a better solution for studying the normal-appearing white matter. The purpose of this study was to evaluate the role of diffusion tensor imaging examination of the normal-appearing white matter of the brain and spinal cord in patients with multiple sclerosis and to determine the relationship between diffusion tensor imaging metrics and patient's clinical status. Results: The significant negative correlation found between expanded disability status scale score of secondary progressive MS patients and global (brain and spinal cord) average fractional anisotropy values in normal-appearing white matter and tracts (P = 0.000). Correlation between average apparent diffusion coefficient of corpus callosum tract and expanded disability status scale score revealed a significant positive correlation in RRMS (P = 0.001). While in secondary progressive MS, a significant negative correlation between fractional anisotropy average of the corpus callosum tract and expanded disability status scale score was noted (P = 0.015). Conclusion: There is a strong relationship between diffusion tensor imaging readings and clinical status of patients can be used to understand unexplained deterioration over disease course and also can be used when conventional MRI findings are equivocal. Corpus callosum affection in MS patients is intimately related to clinical status and its assessment should be done whenever possible.

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Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Diffusion tensor imaging for assessment of normally appearing white matter of the brain and spinal cord in cases of multiple sclerosis: a multi-parametric correlation in view of patient’s clinical status

ElSayed¹,

Eltoukhy

Asaad

et al. 2019

Egypt J Radiol Nucl Med

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“…The mean age range for MS patients in the included studies was between 27.5 and 50 years, with all studies containing cohorts of patients which were predominantly female. Four MRI metrics studied in 27 unique manuscripts had an adequate number of published studies (>4) whose raw data was presented in a manner amenable for meta-analysis: MTR (n=11) 12, 17–20, 27, 28, 30, 31, 36, 39 , ADC (n=7) 23, 25, 29, 32, 33, 35, 44 , FA (n=6) 8, 13, 24, 34, 35, 40 , and MD (n=6) 8, 13, 14, 24, 34, 40 . There were 4 or less studies focused on specific quantitative MRI tissue parameters such as GRE-QSM or T1 or T2 relaxation times.…”

Section: Resultsmentioning

confidence: 99%

The Use of Noncontrast Quantitative MRI to Detect Gadolinium-Enhancing Multiple Sclerosis Brain Lesions: A Systematic Review and Meta-Analysis

Gupta

Al‐Dasuqi²,

Xia

et al. 2017

AJNR Am J Neuroradiol

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Background Concerns have arisen about the long-term health effects of repeated gadolinium injections in multiple sclerosis (MS) patients and the incomplete characterization of MS lesion pathophysiology that results from relying on enhancement characteristics alone. Purpose To perform a systematic review and meta-analysis analyzing whether non-contrast MRI biomarkers can distinguish between enhancing and non-enhancing brain MS lesions. Data Sources Ovid MEDLINE, Ovid Embase, and the Cochrane Database from inception to August 2016. Study Selection We included 37 journal articles on 985 MS patients who had MRI in which T1-weighted post-contrast sequences were compared to non-contrast sequences obtained during the same MRI examination using ROI analysis of individual MS lesions. Data Analysis We performed random-effects meta-analyses comparing the standard mean difference of each MRI metric taken from enhancing versus non-enhancing lesions. Data Synthesis DTI-based FA values are significantly different between enhancing and non-enhancing lesions (P=0.02), with enhancing lesions showing decreased FA compared to non-enhancing lesions. Of the other most frequently studied MRI biomarkers (MD, MTR, or ADC) none were significantly different (P-values of 0.30, 0.47, and 0.19. respectively) between enhancing and non-enhancing lesions. Of the limited studies providing diagnostic accuracy measures, gradient echo-based QSM had the best performance in discriminating between enhancing and non-enhancing MS lesions. Limitations MRI techniques and patient characteristics were variable across studies. Most studies did not provide diagnostic accuracy measures. All imaging metrics were not studied in all 37 studies. Conclusions Non-contrast MRI techniques, such as DTI-based FA, can assess MS lesion acuity without gadolinium.

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“…Investigations of psychiatric disorders, brain development, and epilepsy stand to benefit immensely from noninvasive delineation of connectivity. Basic and clinical neuroscience researchers have widely adopted diffusion tensor imaging (DTI) to delineate anatomic connectivity, in a broad range of settings, including brain development (Cascio et al 2007; Dubois et al 2006; Eluvathingal et al 2007; Hagmann et al 2010; Hüppi and Dubois 2006; Kasprian et al 2008), aging (Makris et al 2007; Ystad et al 2011), epilepsy (Liao et al 2011), multiple sclerosis (Testaverde et al 2012), and psychiatric and behavioral disorders (Ayling et al 2012; Sexton et al 2009; Travers et al 2012; Wang et al 2012; White et al 2008). Recognizing the importance of DTI, functional MR and other modalities in constructing connectivity models of the human brain, the NIH has initiated the Human Connectome Project, the goal of which is to “acquire and share data about the structural and functional connectivity of the human brain” (NIH 2013).…”

Section: Introductionmentioning

confidence: 99%

Edge-Centered DTI Connectivity Analysis: Application to Schizophrenia

et al. 2015

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Diffusion tensor imaging (DTI) provides connectivity information that helps illuminate the processes underlying normal development as well as brain disorders such as autism and schizophrenia. Researchers have widely adopted graph representations to model DTI connectivity among brain structures; however, most measures of connectivity have been centered on nodes, rather than edges, in these graphs. We present an edge-based algorithm for assessing anatomic connectivity; this approach provides information about connections among brain structures, rather than information about structures themselves. This perspective allows us to formulate multivariate graph-based models of altered connectivity that distinguish among experimental groups. We demonstrate the utility of this approach by analyzing data from an ongoing study of schizophrenia.

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Diffusion tensor imaging applications in multiple sclerosis patients using 3T magnetic resonance: a preliminary study

Cited by 12 publications

References 20 publications

Diffusion tensor imaging for assessment of normally appearing white matter of the brain and spinal cord in cases of multiple sclerosis: a multi-parametric correlation in view of patient’s clinical status

Diffusion tensor imaging for assessment of normally appearing white matter of the brain and spinal cord in cases of multiple sclerosis: a multi-parametric correlation in view of patient’s clinical status

The Use of Noncontrast Quantitative MRI to Detect Gadolinium-Enhancing Multiple Sclerosis Brain Lesions: A Systematic Review and Meta-Analysis

Edge-Centered DTI Connectivity Analysis: Application to Schizophrenia

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