Objective: We aimed to investigate the diagnostic value of apparent diffusion coefficient (ADC) maps in magnetic resonance imaging (MRI) in the volume of acute cerebral infarction (ACI).
Methods: A total of 207 ACI patients were selected in our study. The cerebral infarction (CI) volume in the initial diffusion-weighted imaging examination, minimum ADC value, relative apparent diffusion coefficient (rADC) value, and mean ADC value were measured. The correlations between age, smoking, drinking, hypertension, diabetes, coronary heart disease, clinical stage, the lowest ADC value, the mean ADC value, and the mean rADC value with CI volume were analyzed by logistic regression analysis. A receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of the ADC value in the ACI volume.
Results: There was a significant difference in the distribution of the CI volume in ACI patients (P <.05). A significant difference was found in the signal intensity and percentage distribution of ADC map in patients of different CI groups with different CI volumes (P <.05). The signal of the ADC map was positively correlated with the CI volume. The mean ADC and rADC values had significant differences between different CI volumes (all P <.05). Logistic regression analysis revealed that the mean ADC value was significantly correlated with the CI volume (P <.05). Analysis of the ROC curve showed that the quantitative value of ADC has a diagnostic value for the ACI volume.
Conclusion: This study has shown that the signal intensity change on the ADC map in MRI and quantitative analysis of the ADC value can be used as a reference for predicting the ACI volume.
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http://dx.doi.org/10.1016/j.jstrokecerebrovasdis.2016.07.041 | DOI Listing |
Radiology
January 2025
From the Department of Radiology, Shenzhen Nanshan People's Hospital, Shenzhen University, Taoyuan Rd No. 89, Nanshan District, Shenzhen 518000, Guangdong, China (H.H., Z.D., Y.Q.); Medical AI Laboratory and Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China (J.M., R.L., B.H.); Department of Medical Imaging, People's Hospital of Longhua, Shenzhen, Guangdong, China (X.P., Y.Z.); and Department of Radiology, Shenzhen People's Hospital, Shenzhen, Guangdong, China (D.Z., G.H.).
Background Multiparametric MRI, including contrast-enhanced sequences, is recommended for evaluating suspected prostate cancer, but concerns have been raised regarding potential contrast agent accumulation and toxicity. Purpose To evaluate the feasibility of generating simulated contrast-enhanced MRI from noncontrast MRI sequences using deep learning and to explore their potential value for assessing clinically significant prostate cancer using Prostate Imaging Reporting and Data System (PI-RADS) version 2.1.
View Article and Find Full Text PDFCureus
December 2024
Department of Radiology, University of Medicine and Pharmacy of Craiova, Craiova, ROU.
Background: Cervical cancer is considered one of the most common gynecological malignancies with an increased incidence in developing countries. Magnetic resonance imaging (MRI) plays a valuable role in staging cervical cancer and providing valuable information necessary for selecting the appropriate treatment plan, while closely correlating with the prognosis of the patient.
Objective: The aim of this study is to assess the diagnostic value of diffusion-weighted imaging (DWI) in the preoperative loco-regional staging of cervical carcinoma.
Curr Med Imaging
January 2025
Department of Radiology and Medical Imaging, King Saud University Medical City, King Saud University, Riyadh, KSA.
Background: Multiple sclerosis (MS) is one of the most common disabling central nervous system diseases affecting young adults. Magnetic resonance imaging (MRI) is an essential tool for diagnosing and following up multiple sclerosis. Over the years, many MRI techniques have been developed to improve the sensitivity of MS disease detection.
View Article and Find Full Text PDFInvest Radiol
January 2025
From the Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany (N.M., A.I., A.L., L.B., T.D., D. Kravchenko, D. Kuetting, C.C.P., J.A.L.); Quantitative Imaging Lab Bonn (QILaB), Bonn, Germany (N.M., A.I., L.B., D. Kravchenko, D. Kuetting, J.A.L.); Philips Healthcare, Hamburg, Germany (C.K.); Philips Medical Systems, Eindhoven, the Netherlands (A.H.-M.); and Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany (C.Y.).
Objectives: Impaired image quality and long scan times frequently occur in respiratory-triggered sequences in liver magnetic resonance imaging (MRI). We evaluated the impact of an in-bore active breathing guidance (BG) application on image quality and scan time of respiratory-triggered T2-weighted (T2) and diffusion-weighted imaging (DWI) by comparing sequences with standard triggering (T2S and DWIS) and with BG (T2BG and DWIBG).
Materials And Methods: In this prospective study, random patients with clinical indications for liver MRI underwent 3 T MRI with standard and BG acquisitions.
J Chem Inf Model
January 2025
Institute of Biophysics of the Czech Academy of Sciences, Kralovopolska 135, 612 00 Brno, Czech Republic.
RNA recognition motifs (RRMs) are a key class of proteins that primarily bind single-stranded RNAs. In this study, we applied standard atomistic molecular dynamics simulations to obtain insights into the intricate binding dynamics between uridine-rich RNAs and TbRGG2 RRM using the recently developed OL3-Stafix AMBER force field, which improves the description of single-stranded RNA molecules. Complementing structural experiments that unveil a primary binding mode with a single uridine bound, our simulations uncover two supplementary binding modes in which adjacent nucleotides encroach upon the binding pocket.
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