Diffusion-weighted imaging (DWI) is a technique that assesses the cellularity, tortuosity of the extracellular/extravascular space, and cell membrane density based on differences in water proton mobility in tissues. The strength of the diffusion weighting is reflected by the b value. DWI using several b values enables the quantification of the apparent diffusion coefficient. DWI is increasingly used in liver imaging for multiple reasons: it can add useful qualitative and quantitative information to conventional imaging sequences; it is acquired relatively quickly; it is easily incorporated into existing clinical protocols; and it is a noncontrast technique.
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http://dx.doi.org/10.1016/j.mric.2014.04.009 | DOI Listing |
Sci Data
January 2025
Brain and Language Lab, Department of Psychology, Faculty of Psychology and Education Science, University of Geneva, Geneva, Switzerland.
This paper introduces the "NEBULA101 - Neuro-behavioural Understanding of Language Aptitude" dataset, which comprises behavioural and brain imaging data from 101 healthy adults to examine individual differences in language and cognition. Human language, a multifaceted behaviour, varies significantly among individuals, at different processing levels. Recent advances in cognitive science have embraced an integrated approach, combining behavioural and brain studies to explore these differences comprehensively.
View Article and Find Full Text PDFJ Comput Assist Tomogr
November 2024
From the Diagnostic Radiology Department, Faculty of Medicine, Mansoura University-Egypt, Mansoura, Egypt.
Objective: The aim of the study is to assess the diagnostic performance of quantitative analysis of diffusion-weighted imaging in assessing treatment response in cervical cancer patients.
Methods: A retrospective analysis was done for 50 patients with locally advanced cervical cancer who received concurrent chemoradiotherapy and underwent magnetic resonance imaging and diffusion-weighted imaging. Treatment response was classified into 4 categories according to RECIST criteria 6 months after therapy completion.
PLoS One
January 2025
Department of Radiology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Objective: This study aimed to assess the feasibility of the deep learning in generating T2 weighted (T2W) images from diffusion-weighted imaging b0 images.
Materials And Methods: This retrospective study included 53 patients who underwent head magnetic resonance imaging between September 1 and September 4, 2023. Each b0 image was matched with a corresponding T2-weighted image.
Front Oncol
December 2024
Istituto Oncologico del Mediterraneo, Viagrande, Italy.
Front Oncol
December 2024
Department of Radiology, School of Medicine, University of Washington, Seattle, WA, United States.
Introduction: Diffusion weighted MRI (DWI) has emerged as a promising adjunct to reduce unnecessary biopsies prompted by breast MRI through use of apparent diffusion coefficient (ADC) measures. The purpose of this study was to investigate the effects of different lesion ADC measurement approaches and ADC cutoffs on the diagnostic performance of breast DWI in a high-risk MRI screening cohort to identify the optimal approach for clinical incorporation.
Methods: Consecutive screening breast MRI examinations (August 2014-Dec 2018) that prompted a biopsy for a suspicious breast lesion (BI-RADS 4 or 5) were retrospectively evaluated.
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