Diffusion weighted imaging for the differentiation of breast tumors: From apparent diffusion coefficient to high order diffusion tensor imaging

2015 ◽  
Vol 43 (5) ◽  
pp. 1111-1121 ◽  
Author(s):  
Jose R. Teruel ◽  
Pål E. Goa ◽  
Torill E. Sjøbakk ◽  
Agnes Østlie ◽  
Hans E. Fjøsne ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Diffusion Tensor Imaging ◽  
Apparent Diffusion Coefficient ◽  
Diffusion Weighted Imaging ◽  
Diffusion Tensor ◽  
Breast Tumors ◽  
High Order ◽  
Diffusion Weighted ◽  
Apparent Diffusion

scholarly journals ANALYSIS OF FRACTIONAL ANISOTROPY (FA) VALUES AND APPARENT DIFFUSION COEFFICIENT (ADC) VALUES IN ISCHEMIC STROKE DISEASES OF MRI GE 3 TESLA

2019 ◽  
Vol 2 (3) ◽  
pp. 107
Author(s):  
Ali Mustofa ◽  
Anggraini Dwi Sensusiati ◽  
Muhaimin Muhaimin ◽  
Sri Andreani Utomo ◽  
Risalatul Latifah
Keyword(s):  
Diffusion Coefficient ◽  
Ischemic Stroke ◽  
Diffusion Tensor Imaging ◽  
Apparent Diffusion Coefficient ◽  
Fractional Anisotropy ◽  
Diffusion Weighted Imaging ◽  
Diffusion Tensor ◽  
Diffusion Weighted ◽  
Apparent Diffusion Coefficient Values ◽  
Apparent Diffusion

Background: Diffusion Weighted Imaging and Diffusion Tensor Imaging is an advanced technique in MRI that shows the diffusion in brain of ischemic stroke disease. Diffusion Weighted Imaging (DWI) shows the lesions without gadolinium contrast agent and produce Apparent Diffusion Coefficient values. Whereas, Diffusion Tensor Imaging (DTI) shows connectivity’s of central nervous system that cannot be seen by using conventional MRI. Diffusion Tensor Imaging produces Fractional Anisotropy values. Purpose:This study has aim to analyze the Apparent Diffusion Coefficient values and Fractional Anisotropy values in Stroke Ischemic disease. Methods: Total samples used are 14 samples, consist of 7 (50%) man and 7 (50%) woman with ischemic stroke disease. Each sample deals by Diffusion Weighted Imaging and Diffusion Tensor Imaging sequences. The Region of Interest (ROI) is placed in ischemic stroke lesions and contra lateral side of lesions. Results: The result shows that 9 samples of brain tissue lesions located in the right side and 5 samples in the left side. Right lesions have the average ADC stroke: 0.001748; normal ADC: 0.000954; FA stroke: 0.144522; and normal FA: 0.426111. While, left lesions have the average ADC strokes 0.000979; normal ADC: 0.000835; FA stroke: 0.2556; and normal FA 0.4324. Conclusion: So, the conclusion of this study is Apparent Diffusion Coefficient (ADC) values in case of ischemic stroke can decreases or increases depend on the age of stroke. While, the Fractional Anisotropy (FA) values will decrease without being affected by age of stroke.

Diffusion tensor imaging reveals microstructural differences between subtypes of trigeminal neuralgia

2020 ◽  
Vol 133 (2) ◽  
pp. 573-579 ◽  
Author(s):  
Matthew S. Willsey ◽  
Kelly L. Collins ◽  
Erin C. Conrad ◽  
Heather A. Chubb ◽  
Parag G. Patil
Keyword(s):  
Diffusion Coefficient ◽  
Diffusion Tensor Imaging ◽  
Trigeminal Neuralgia ◽  
Apparent Diffusion Coefficient ◽  
Diffusion Tensor ◽  
Statistical Significance ◽  
Region Of Interest ◽  
Pain Syndrome ◽  
Radial Diffusivity ◽  
Apparent Diffusion

OBJECTIVETrigeminal neuralgia (TN) is an uncommon idiopathic facial pain syndrome. To assist in diagnosis, treatment, and research, TN is often classified as type 1 (TN1) when pain is primarily paroxysmal and episodic or type 2 (TN2) when pain is primarily constant in character. Recently, diffusion tensor imaging (DTI) has revealed microstructural changes in the symptomatic trigeminal root and root entry zone of patients with unilateral TN. In this study, the authors explored the differences in DTI parameters between subcategories of TN, specifically TN1 and TN2, in the pontine segment of the trigeminal tract.METHODSThe authors enrolled 8 patients with unilateral TN1, 7 patients with unilateral TN2, and 23 asymptomatic controls. Patients underwent DTI with parameter measurements in a region of interest within the pontine segment of the trigeminal tract. DTI parameters were compared between groups.RESULTSIn the pontine segment, the radial diffusivity (p = 0.0049) and apparent diffusion coefficient (p = 0.023) values in TN1 patients were increased compared to the values in TN2 patients and controls. The DTI measures in TN2 were not statistically significant from those in controls. When comparing the symptomatic to asymptomatic sides in TN1 patients, radial diffusivity was increased (p = 0.025) and fractional anisotropy was decreased (p = 0.044) in the symptomatic sides. The apparent diffusion coefficient was increased, with a trend toward statistical significance (p = 0.066).CONCLUSIONSNoninvasive DTI analysis of patients with TN may lead to improved diagnosis of TN subtypes (e.g., TN1 and TN2) and improve patient selection for surgical intervention. DTI measurements may also provide insights into prognosis after intervention, as TN1 patients are known to have better surgical outcomes than TN2 patients.

scholarly journals Classification of paediatric brain tumours by diffusion weighted imaging and machine learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jan Novak ◽  
Niloufar Zarinabad ◽  
Heather Rose ◽  
Theodoros Arvanitis ◽  
Lesley MacPherson ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Posterior Fossa ◽  
Brain Tumours ◽  
Diffusion Weighted Imaging ◽  
Regions Of Interest ◽  
Apparent Diffusion Coefficients ◽  
Diffusion Weighted ◽  
Apparent Diffusion ◽  
Paediatric Brain Tumours

AbstractTo determine if apparent diffusion coefficients (ADC) can discriminate between posterior fossa brain tumours on a multicentre basis. A total of 124 paediatric patients with posterior fossa tumours (including 55 Medulloblastomas, 36 Pilocytic Astrocytomas and 26 Ependymomas) were scanned using diffusion weighted imaging across 12 different hospitals using a total of 18 different scanners. Apparent diffusion coefficient maps were produced and histogram data was extracted from tumour regions of interest. Total histograms and histogram metrics (mean, variance, skew, kurtosis and 10th, 20th and 50th quantiles) were used as data input for classifiers with accuracy determined by tenfold cross validation. Mean ADC values from the tumour regions of interest differed between tumour types, (ANOVA P < 0.001). A cut off value for mean ADC between Ependymomas and Medulloblastomas was found to be of 0.984 × 10−3 mm2 s−1 with sensitivity 80.8% and specificity 80.0%. Overall classification for the ADC histogram metrics were 85% using Naïve Bayes and 84% for Random Forest classifiers. The most commonly occurring posterior fossa paediatric brain tumours can be classified using Apparent Diffusion Coefficient histogram values to a high accuracy on a multicentre basis.

Sign in / Sign up

Export Citation Format

Share Document