The evolution of a photochemically induced cerebral thrombotic infarction was followed in rats during the first week after the insult by means of NMR imaging and histology. Heavily T2-weighted images provided an excellent lesion detection and a high specificity for the discrimination of different histological abnormalities. The T2-weighted images showed a brain lesion evolving during the first 24 h from a homogeneous hyperintense area, histologically corresponding to diffuse vasogenic and cytotoxic oedema with concomitant neuronal necrosis, to an iso-intense area with a hyperintense seam, which microscopically correlated with increased vascular permeability at the periphery of the lesion. The hyperintense seam was observed up to day 7, but at that time coincided with gliomesodermal repair reaction which could be verified histochemically and ultrastructurally. It may be concluded that NMR-micro-imaging at a moderately high field, enables early detection and adequate follow-up of small cerebral infarctions in rats.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/BF01405538 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
3D MRI with CT-like bone contrast (3D-BONE): a pictorial review of clinical applications.
Acta Radiol
January 2025
Department of Radiology, Changi General Hospital, Singapore, Republic of Singapore.
Background: Computed tomography (CT) is the gold standard imaging modality for the assessment of 3D bony morphology but incurs the cost of ionizing radiation exposure. High-resolution 3D magnetic resonance imaging (MRI) with CT-like bone contrast (CLBC) may provide an alternative to CT in allowing complete evaluation of both bony and soft tissue structures with a single MRI examination.
Purpose: To review the technical aspects of an optimized stack-of-stars 3D gradient recalled echo pulse sequence method (3D-Bone) in generating 3D MR images with CLBC, and to present a pictorial review of the utility of 3D-Bone in the clinical assessment of common musculoskeletal conditions.
Correlation of zero echo time functional MRI with neuronal activity in rats.
J Cereb Blood Flow Metab
January 2025
A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland.
Zero echo time (zero-TE) pulse sequences provide a quiet and artifact-free alternative to conventional functional magnetic resonance imaging (fMRI) pulse sequences. The fast readouts (<1 ms) utilized in zero-TE fMRI produce an image contrast with negligible contributions from blood oxygenation level-dependent (BOLD) mechanisms, yet the zero-TE contrast is highly sensitive to brain function. However, the precise relationship between the zero-TE contrast and neuronal activity has not been determined.
View Article and Find Full Text PDFAdvanced electrocardiography heart age: a prognostic, explainable machine learning approach applicable to sinus and non-sinus rhythms.
Eur Heart J Digit Health
January 2025
Kolling Institute, Royal North Shore Hospital, University of Sydney, St Leonards, Sydney, NSW 2065, Australia.
Aims: An explainable advanced electrocardiography (A-ECG) Heart Age gap is the difference between A-ECG Heart Age and chronological age. This gap is an estimate of accelerated cardiovascular aging expressed in years of healthy human aging, and can intuitively communicate cardiovascular risk to the general population. However, existing A-ECG Heart Age requires sinus rhythm.
View Article and Find Full Text PDFA 3D decoupling Alzheimer's disease prediction network based on structural MRI.
Health Inf Sci Syst
December 2025
School of Mathematics and Computing, University of Southern Queensland, 487-535 West Street, Toowoomba, QLD 4350 Australia.
Purpose: This paper aims to develop a three-dimensional (3D) Alzheimer's disease (AD) prediction method, thereby bettering current predictive methods, which struggle to fully harness the potential of structural magnetic resonance imaging (sMRI) data.
Methods: Traditional convolutional neural networks encounter pressing difficulties in accurately focusing on the AD lesion structure. To address this issue, a 3D decoupling, self-attention network for AD prediction is proposed.
Machine learning applications in placenta accreta spectrum disorders.
Eur J Obstet Gynecol Reprod Biol X
March 2025
Mother and Newborn Health Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
This review examines the emerging applications of machine learning (ML) and radiomics in the diagnosis and prediction of placenta accreta spectrum (PAS) disorders, addressing a significant challenge in obstetric care. It highlights recent advancements in ML algorithms and radiomic techniques that utilize medical imaging modalities like magnetic resonance imaging (MRI) and ultrasound for effective classification and risk stratification of PAS. The review discusses the efficacy of various deep learning models, such as nnU-Net and DenseNet-PAS, which have demonstrated superior performance over traditional diagnostic methods through high AUC scores.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!