BACKGROUND AND PURPOSE: Head and neck squamous cell carcinoma associated with human papillomavirus infection represents a distinct tumor entity. We hypothesized that diffusion phenotypes based on the histogram analysis of ADC values reflect distinct degrees of tumor heterogeneity in human papillomavirus–positive and human papillomavirus–negative head and neck squamous cell carcinomas.
The condition of prematurity, however, is dissimilar to intrauterine life. We sought to establish normal values of fetal brain apparent diffusion coefficient (ADC) to highlight its abnormal changes in pathologic conditions and to obtain information about normal brain development. Apparent Diffusion Coefficient (ADC) of the vitreous humor and Susceptibility Weighted Imaging (SWI) of the retina in abused children with retinal hemorrhages Misun Hwang, Samuel S. Shin, Matthew A. Thimm, Anish Ghodadra, Christin L. Sylvester, Ken Nischal, Ashok Panigrahy, Giulio Zuccoli
Apparent diffusion coefficient (ADC) is a measure of the magnitude of diffusion (of water molecules) within tissue, and is commonly clinically calculated using MRI with diffusion weighted imaging (DWI) 1 . Diffusion-weighted imaging (DWI) is widely appreciated as an indispensable tool in the examination of the CNS. The purpose of our study was to evaluate the ability of apparent diffusion coefficient (ADC) values and conventional MRI features to differentiate TDLs from PCNSLs and high-grade gliomas. MATERIALS AND METHODS. May 17, 2019 · Apparent diffusion coefficient (ADC) is obtained from diffusion weighted magnetic resonance imaging (MRI-DWI) after processing, and it is a functional parameter that mainly reflects the Brownian motion of water molecules. Calculating the ADC value of the tumor can quantitatively reflect its intrinsic biological features . Background and Purpose—Early and accurate diagnosis of brain edema in stroke patients is essential for the selection of appropriate treatment.We examined the correlations between the changes in the apparent diffusion coefficient (ADC), regional water content, and tissue ultrastructure during early focal cerebral ischemia. Diffusion-weighted magnetic resonance imaging (DWI) and the calculated apparent diffusion coefficient (ADC) are widely used to distinguish necrotic or cystic brain tumors from abscesses [10–11]. BACKGROUND AND PURPOSE: Accurate imaging characterization of a solitary thyroid nodule has been clearly problematic. The purpose of this study was to evaluate the role of the apparent diffusion coefficient (ADC) values in the differentiation between malignant and benign solitary thyroid nodules.
Objective To clarify diffusion and perfusion abnormalities and evaluate correlation between apparent diffusion coefficient (ADC), MR perfusion and histopathologic parameters of pancreatic cancer (PC). Methods Eighteen patients with PC underwent diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). On the relationship between the apparent diffusion coefficient and extravascular extracellular volume fraction in human breast cancer Lori R. Arlinghaus, Xia Li, A. Ridwan Rahman, E. Brian Welch, Lei Xu, John C. Gore, Thomas Yankeelov May 10, 2014 · With a short acquisition time and high contrast resolution between tumor and normal prostatic tissue , DWI and apparent diffusion coefficient (ADC) mapping demonstrate an inverse and significant correlation with the Gleason score [7, 14]. Apparent diffusion coefficient (ADC) measured by diffusion-weighted MRI and first-order histogram (FOH) extracted features, as markers of tumor heterogeneity, have been implicated in differentiating grade of the intracranial tumors. Scatterplots of concordance correlation coefficients between reader 1 and reader 2 at the Time 1 and at Time 2 regarding darkest part of the tumor (DpTu) apparent diffusion coefficient (ADC) maximum (A,B), DpTu ADC mean (C,D), and DpTu ADC minimum (E,F). The role of whole-lesion apparent diffusion coefficient analysis for predicting outcomes of prostate cancer patients on active surveillance Tsutomu Tamada, Hasan Dani, Samir S. Taneja, Andrew B. Rosenkrantz