scholarly journals Renal Diffusion-Weighted Imaging (DWI) for Apparent Diffusion Coefficient (ADC), Intravoxel Incoherent Motion (IVIM), and Diffusion Tensor Imaging (DTI): Basic Concepts

2021 ◽  
pp. 187-204
Author(s):  
Neil Peter Jerome ◽  
Anna Caroli ◽  
Alexandra Ljimani
Keyword(s):  
Diffusion Weighted Imaging ◽  
Diffusion Tensor ◽  
Renal Tissue ◽  
The European Union ◽  
Tissue Microstructure ◽  
Diffusion Weighted ◽  
Apparent Diffusion ◽  
Basic Concepts ◽  
Renal Diffusion ◽  
Renal Mri

AbstractThe specialized function of the kidney is reflected in its unique structure, characterized by juxtaposition of disorganized and ordered elements, including renal glomerula, capillaries, and tubules. The key role of the kidney in blood filtration, and changes in filtration rate and blood flow associated with pathological conditions, make it possible to investigate kidney function using the motion of water molecules in renal tissue. Diffusion-weighted imaging (DWI) is a versatile modality that sensitizes observable signal to water motion, and can inform on the complexity of the tissue microstructure. Several DWI acquisition strategies are available, as are different analysis strategies, and models that attempt to capture not only simple diffusion effects, but also perfusion, compartmentalization, and anisotropy. This chapter introduces the basic concepts of DWI alongside common acquisition schemes and models, and gives an overview of specific DWI applications for animal models of renal disease.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.

scholarly journals Analysis of Renal Diffusion-Weighted Imaging (DWI) Using Apparent Diffusion Coefficient (ADC) and Intravoxel Incoherent Motion (IVIM) Models

2021 ◽  
pp. 611-635
Author(s):  
Neil Peter Jerome ◽  
João S. Periquito
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Diffusion Weighted Imaging ◽  
Careful Consideration ◽  
Intravoxel Incoherent Motion ◽  
Tissue Properties ◽  
Diffusion Weighted ◽  
Apparent Diffusion ◽  
Renal Diffusion ◽  
Renal Mri

AbstractAnalysis of renal diffusion-weighted imaging (DWI) data to derive markers of tissue properties requires careful consideration of the type, extent, and limitations of the acquired data. Alongside data quality and general suitability for quantitative analysis, choice of diffusion model, fitting algorithm, and processing steps can have consequences for the precision, accuracy, and reliability of derived diffusion parameters. Here we introduce and discuss important steps for diffusion-weighted image processing, and in particular give example analysis protocols and pseudo-code for analysis using the apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) models. Following an overview of general principles, we provide details of optional steps, and steps for validation of results. Illustrative examples are provided, together with extensive notes discussing wider context of individual steps, and notes on potential pitfalls.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concepts and experimental procedure.

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.

scholarly journals Does the Acute Diffusion-Weighted Imaging Lesion Represent Penumbra as Well as Core? A Combined Quantitative PET/MRI Voxel-Based Study

2004 ◽  
Vol 24 (11) ◽  
pp. 1249-1254 ◽  
Author(s):  
Joseph V. Guadagno ◽  
Elizabeth A. Warburton ◽  
Franklin I. Aigbirhio ◽  
Piotr Smielewski ◽  
Tim D. Fryer ◽  
...  
Keyword(s):  
Diffusion Weighted Imaging ◽  
Diffusion Tensor ◽  
Oxygen Extraction Fraction ◽  
Irreversible Damage ◽  
The Core ◽  
Quantitative Pet ◽  
Diffusion Weighted ◽  
Positron Emission ◽  
Misery Perfusion ◽  
Apparent Diffusion

In acute ischemic stroke, the diffusion-weighted imaging (DWI) lesion is widely held to represent the core of irreversible damage and is therefore crucial in selecting patients for thrombolysis. However, recent research suggests it may also represent penumbra. An illustrative patient was imaged 7 hours after stroke onset with back-to-back 3T diffusion tensor imaging and quantitative positron emission tomography, which showed a DWI lesion and misery perfusion, respectively. Using previously validated voxel-based probabilistic CBF, CMRO2, and Oxygen Extraction Fraction (OEF) thresholds, the authors show that the DWI lesion contained not only core but also substantial proportions of penumbra. Also, severe apparent diffusion coefficient reductions were present within the potentially salvageable penumbra as well as in the core. These findings have potential implications regarding treatment decisions.

scholarly journals Diffusion tensor imaging on 3-T MRI breast: diagnostic performance in comparison to diffusion-weighted imaging

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Dalia Abdelhady ◽  
Amany Abdelbary ◽  
Ahmed H. Afifi ◽  
Alaa-eldin Abdelhamid ◽  
Hebatallah H. M. Hassan
Keyword(s):  
Breast Cancer ◽  
Diffusion Tensor Imaging ◽  
Sensitivity And Specificity ◽  
Diffusion Weighted Imaging ◽  
Diffusion Tensor ◽  
Breast Mri ◽  
Breast Lesions ◽  
Dce Mri ◽  
Additional Tool ◽  
Diffusion Weighted

Abstract Background Breast cancer is the most prevalent cancer among females. Dynamic contrast-enhanced MRI (DCE-MRI) breast is highly sensitive (90%) in the detection of breast cancer. Despite its high sensitivity in detecting breast cancer, its specificity (72%) is moderate. Owing to 3-T breast MRI which has the advantage of a higher signal to noise ratio and shorter scanning time rather than the 1.5-T MRI, the adding of new techniques as diffusion tensor imaging (DTI) to breast MRI became more feasible. Diffusion-weighted imaging (DWI) which tracks the diffusion of the tissue water molecule as well as providing data about the integrity of the cell membrane has been used as a valuable additional tool of DCE-MRI to increase its specificity. Based on DWI, more details about the microstructure could be detected using diffusion tensor imaging. The DTI applies diffusion in many directions so apparent diffusion coefficient (ADC) will vary according to the measured direction raising its sensitivity to microstructure elements and cellular density. This study aimed to investigate the diagnostic accuracy of DTI in the assessment of breast lesions in comparison to DWI. Results By analyzing the data of the 50 cases (31 malignant cases and 19 benign cases), the sensitivity and specificity of DWI in differentiation between benign and malignant lesions were about 90% and 63% respectively with PPV 90% and NPV 62%, while the DTI showed lower sensitivity and specificity about 81% and 51.7%, respectively, with PPV 78.9% and NPV 54.8% (P-value ≤ 0.05). Conclusion While the DWI is still the most established diffusion parameter, DTI may be helpful in the further characterization of tumor microstructure and differentiation between benign and malignant breast lesions.

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.

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