scholarly journals Apparent diffusion coefficient restriction in the white matter: going beyond acute brain territorial ischemia

2011 ◽  
Vol 3 (2) ◽  
pp. 155-164 ◽  
Author(s):  
Valentina Citton ◽  
Alberto Burlina ◽  
Claudio Baracchini ◽  
Massimo Gallucci ◽  
Alessia Catalucci ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
White Matter ◽  
Apparent Diffusion Coefficient ◽  
Apparent Diffusion

The Potential Role of Peritumoral Apparent Diffusion Coefficient Evaluation in Differentiating Glioblastoma and Solitary Metastatic Lesions of the Brain

2021 ◽  
Vol 17 ◽  
Author(s):  
Murat Tepe ◽  
Suzan Saylisoy ◽  
Ugur Toprak ◽  
Ibrahim Inan
Keyword(s):  
Diffusion Coefficient ◽  
White Matter ◽  
Apparent Diffusion Coefficient ◽  
Sensitivity And Specificity ◽  
Brain Mri ◽  
Solitary Metastasis ◽  
Metastatic Lesions ◽  
Institutional Review ◽  
Apparent Diffusion ◽  
Adc Values

Objective: Differentiating glioblastoma (GBM) and solitary metastasis is not always possible using conventional magnetic resonance imaging (MRI) techniques. In conventional brain MRI, GBM and brain metastases are lesions with mostly similar imaging findings. In this study, we investigated whether apparent diffusion coefficient (ADC) ratios, ADC gradients, and minimum ADC values in the peritumoral edema tissue can be used to discriminate between these two tumors. Methods: This retrospective study was approved by the local institutional review board with a waiver of written informed consent. Prior to surgical and medical treatment, conventional brain MRI and diffusion-weighted MRI (b = 0 and b = 1000) images were taken from 43 patients (12 GBM and 31 solitary metastasis cases). Quantitative ADC measurements were performed on the peritumoral tissue from the nearest segment to the tumor (ADC1), the middle segment (ADC2), and the most distant segment (ADC3). The ratios of these three values were determined proportionally to calculate the peritumoral ADC ratios. In addition, these three values were subtracted from each other to obtain the peritumoral ADC gradients. Lastly, the minimum peritumoral and tumoral ADC values, and the quantitative ADC values from the normal appearing ipsilateral white matter, contralateral white matter and ADC values from cerebrospinal fluid (CSF) were recorded. Results: For the differentiation of GBM and solitary metastasis, ADC3 / ADC1 was the most powerful parameter with a sensitivity of 91.7% and specificity of 87.1% at the cut-off value of 1.105 (p < 0.001), followed by ADC3 / ADC2 with a cut-off value of 1.025 (p = 0.001), sensitivity of 91.7%, and specificity of 74.2%. The cut-off, sensitivity and specificity of ADC2 / ADC1 were 1.055 (p = 0.002), 83.3%, and 67.7%, respectively. For ADC3 – ADC1, the cut-off value, sensitivity and specificity were calculated as 150 (p < 0.001), 91.7% and 83.9%, respectively. ADC3 – ADC2 had a cut-off value of 55 (p = 0.001), sensitivity of 91.7%, and specificity of 77.4 whereas ADC2 – ADC1 had a cut-off value of 75 (p = 0.003), sensitivity of 91.7%, and specificity of 61.3%. Among the remaining parameters, only the ADC3 value successfully differentiated between GBM and metastasis (GBM 1802.50 ± 189.74 vs. metastasis 1634.52 ± 212.65, p = 0.022). Conclusion: The integration of the evaluation of peritumoral ADC ratio and ADC gradient into conventional MR imaging may provide valuable information for differentiating GBM from solitary metastatic lesions.

The Apparent Diffusion Coefficient of Water in Gray and White Matter of the Infant Brain

1996 ◽  
Vol 20 (6) ◽  
pp. 1006-1011 ◽  
Author(s):  
Peter B. Toft ◽  
Helle Leth ◽  
Birgit Peitersen ◽  
Hans C. Lou ◽  
Carsten Thomsen
Keyword(s):  
Diffusion Coefficient ◽  
White Matter ◽  
Apparent Diffusion Coefficient ◽  
Apparent Diffusion ◽  
Infant Brain

Quantitative Assessment of Water Diffusion Changes in Brains of Children with Neurofibromatosis Type I Using Apparent Diffusion Coefficient

2008 ◽  
Vol 21 (6) ◽  
pp. 839-843 ◽  
Author(s):  
W. Mizukoshi ◽  
E. Kozawa ◽  
A. Kuramochi ◽  
A. Uchino ◽  
F. Kimura
Keyword(s):  
Diffusion Coefficient ◽  
White Matter ◽  
Apparent Diffusion Coefficient ◽  
Neurofibromatosis Type ◽  
Type I ◽  
Mr Images ◽  
Frontal White Matter ◽  
Apparent Diffusion ◽  
Unpaired Student

We measured diffusion changes in the brains of children with neurofibromatosis type 1 (NF1). Using diffusion-weighted and conventional magnetic resonance (MR) images of 42 children with NF1 (19 girls, 23 boys; 7 months-16 years, mean 6.8 years) and 42 age-matched controls (20 boys, 22 girls; 6 months-17 years, mean, 6.9 years), we calculated the apparent diffusion coefficient (ADC) from the automatically generated ADC maps and placed regions of interest in the pons, middle cerebellar and cerebral peduncles, thalami, globus pallidi and frontal white matter. Evaluating only normal-appearing regions on conventional images, we compared mean ADCs using the unpaired Student t test. Means were not significantly different in frontal white matter but were larger in the other regions in the NF1 (P < 0.01). Although conventional MR showed normal intensity, ADCs of the pons, middle cerebellar and cerebral peduncles, thalami and globus pallidi were significantly larger in the NF1.

scholarly journals Diffusion Tensor Imaging to Predict Long-term Outcome after Cardiac Arrest

2012 ◽  
Vol 117 (6) ◽  
pp. 1311-1321 ◽  
Author(s):  
Charles-Edouard Luyt ◽  
Damien Galanaud ◽  
Vincent Perlbarg ◽  
Audrey Vanhaudenhuyse ◽  
Robert D. Stevens ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Diffusion Coefficient ◽  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Apparent Diffusion Coefficient ◽  
Diffusion Tensor ◽  
Brain Magnetic Resonance Imaging ◽  
Unfavorable Outcome ◽  
Resonance Imaging ◽  
Apparent Diffusion

Background Prognostication in comatose survivors of cardiac arrest is a major clinical challenge. The authors' objective was to determine whether an assessment with diffusion tensor imaging, a brain magnetic resonance imaging sequence, increases the accuracy of 1 yr functional outcome prediction in cardiac arrest survivors. Methods Prospective, observational study in two intensive care units. Fifty-seven comatose survivors of cardiac arrest underwent brain magnetic resonance imaging. Fractional anisotropy (FA), a diffusion tensor imaging value, was measured in predefined white matter regions, and apparent diffusion coefficient was assessed in predefined grey matter regions. Prediction of unfavorable outcome at 1 yr was compared using four prognostic models: FA global, FA selected, apparent diffusion coefficient, and clinical classifiers. Results Of the 57 patients included in the study, 49 had an unfavorable outcome at 12 months. Areas under the receiver operating characteristic curve (95% CI) to predict unfavorable outcome for the FA global, FA selected, clinical, and apparent diffusion coefficient models were 0.92 (0.82-0.98), 0.96 (0.87-0.99), 0.78 (0.65-0.88), and 0.86 (0.74-0.94), respectively. The FA selected model had the best overall accuracy for predicting outcome, with a score above 0.44 having 94% (95% CI, 83-99%) sensitivity and 100% (95% CI, 63-100%) specificity for the prediction of unfavorable outcome. Conclusion Quantitative diffusion tensor imaging indicates that white matter damage is widespread after cardiac arrest. A prognostic model based on FA values in selected white matter tracts seems to predict accurately 1 yr functional outcome. These preliminary results need to be confirmed in a larger population.

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