Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Nervous Tissue: Neuron Types01:19

Nervous Tissue: Neuron Types

6.2K
Neurons, the fundamental units of the nervous system, can be classified based on both their structural and functional characteristics.
Structurally, neurons are categorized into three main types: multipolar, bipolar, and unipolar (or pseudounipolar). Multipolar neurons, which are the most common type in the brain and spinal cord, as well as all motor neurons, possess multiple dendrites and a single axon.
Bipolar neurons, on the other hand, have one primary dendrite and one axon. They are...
6.2K
Connective Tissue Cell Types01:22

Connective Tissue Cell Types

4.2K
Connective tissue develops from the mesoderm of a developing embryo and consists of cells, fibers, and ground substance: a gel-like material containing large complexes of carbohydrates and proteins. Connective tissue was first identified as a separate tissue family in the 18th century, and Johannes Peter Muller coined the term connective tissue.
Fat cells (adipocytes), smooth muscle cells (myoblasts), and bone cells (osteoblasts) are some connective tissue cell types. Some immune system cells...
4.2K
Microtubule Associated Proteins (MAPs)01:42

Microtubule Associated Proteins (MAPs)

5.9K
Microtubule function and architecture are regulated by an array of specialized proteins called microtubule-associated proteins or MAPs. These proteins are widespread across different organisms and have conserved protein motifs, like the multi-TOG domain for tubulin binding found in the CLASP family of MAPs. Some MAPs are lineage-specific based on their conserved domains. Their functions depend upon the cytoskeletal architecture and cell type they are located within. In-plant cells, a specific...
5.9K
Plotting of Topographic Maps01:29

Plotting of Topographic Maps

519
Topographic maps represent the Earth's surface features using contour lines, which connect points of equal elevation to create a two-dimensional representation of three-dimensional terrain. Creating a topographic map requires a systematic approach.Begin by plotting a scaled grid and marking intersections corresponding to the survey's elevation data points. Assign elevation values at these intersections to build the base map. Next, determine contour levels using a consistent contour interval,...
519
Coordinates and Map Projections01:29

Coordinates and Map Projections

612
Coordinates and map projections are essential tools in accurately representing the Earth's surface for various applications, ranging from navigation to spatial analysis. The latitude and longitude coordinate system is a universally recognized framework for defining locations. Latitude specifies the distance of a point north or south of the equator, measured in degrees from 0° at the equator to 90° at the poles. Longitude indicates a location's position east or west of the prime meridian,...
612
Types of RNA01:23

Types of RNA

72.8K
Overview
Three main types of RNA are involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). These RNAs perform diverse functions and can be broadly classified as protein-coding or non-coding RNA. Non-coding RNAs play important roles in the regulation of gene expression in response to developmental and environmental changes. Non-coding RNAs in prokaryotes can be manipulated to develop more effective antibacterial drugs for human or animal use.
RNA...
72.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Magnetic resonance spectroscopy in hospitalised older people shows age and delirium-specific metabolic changes.

Age and ageing·2026
Same author

Quasi-Diffusion Imaging: Application to Ultra-High b-Value and Time-Dependent Diffusion Images of Brain Tissue.

NMR in biomedicine·2025
Same author

Diffusion decrease in normal-appearing white matter structures following photon or proton irradiation indicates differences in regional radiosensitivity.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology·2024
Same author

Magnetic resonance lymphangiography: Establishing normal.

Journal of vascular surgery. Venous and lymphatic disorders·2024
Same author

Characterisation of paediatric brain tumours by their MRS metabolite profiles.

NMR in biomedicine·2024
Same author

Radiofrequency thalamotomy for tremor produces focused and predictable lesions shown on magnetic resonance images.

Brain communications·2023

Related Experiment Video

Updated: Jan 30, 2026

Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures
06:32

Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures

Published on: January 9, 2019

8.3K

Tissue-type mapping of gliomas.

Felix Raschke1, Thomas R Barrick2, Timothy L Jones3

  • 1Institute of Radiooncology - OncoRay, Helmholtz-Zentrum Dresden-Rossendorf, Rossendorf, Germany.

Neuroimage. Clinical
|January 12, 2019
PubMed
Summary

This study developed a multimodal MRI (mMRI) method to map glial brain tumour tissue heterogeneity. The technique accurately identifies tumour grade and infiltration, aiding in patient management.

Keywords:
GliomaMagnetic resonance spectroscopy (MRS)Multimodal MRINosologic imagingPattern recognition

More Related Videos

A Protocol for Explant Cultures of IDH1-mutant Diffuse Low-grade Gliomas
06:27

A Protocol for Explant Cultures of IDH1-mutant Diffuse Low-grade Gliomas

Published on: May 9, 2025

1.2K
Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
09:17

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

2.7K

Related Experiment Videos

Last Updated: Jan 30, 2026

Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures
06:32

Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures

Published on: January 9, 2019

8.3K
A Protocol for Explant Cultures of IDH1-mutant Diffuse Low-grade Gliomas
06:27

A Protocol for Explant Cultures of IDH1-mutant Diffuse Low-grade Gliomas

Published on: May 9, 2025

1.2K
Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
09:17

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

2.7K

Area of Science:

  • Neuroimaging
  • Medical Physics
  • Oncology

Background:

  • Glial brain tumours exhibit significant tissue heterogeneity, complicating accurate grading and margin delineation.
  • Multimodal MRI (mMRI) offers rich information but requires advanced methods for integrated analysis.
  • Current methods may not fully capture the complex tissue composition of gliomas.

Purpose of the Study:

  • To develop a statistical method for combining mMRI data in adult glial brain tumours.
  • To generate tissue heterogeneity maps indicative of tumour grade and infiltration margins.
  • To improve diagnostic accuracy and treatment planning for glioma patients.

Main Methods:

  • Retrospective analysis of mMRI data from 25 glioma patients.
  • Utilized 1H Magnetic Resonance Spectroscopic Imaging (MRSI) for tissue-specific labeling.
  • Employed Bayesian inference and superpixel segmentation on diffusion-weighted, T2-weighted, and proton density images.

Main Results:

  • Tissue-type maps generated from mMRI showed strong correlation with manual delineations (r=0.87).
  • High-grade tumour volumes were accurately identified across different glioma grades.
  • Tumour high-grade volume significantly correlated with patient survival outcomes.

Conclusions:

  • 1H MRSI effectively labels tumour tissue types for mMRI analysis.
  • The developed mMRI tissue-type mapping algorithm shows potential for aiding glial tumour patient management.
  • This approach may enhance the non-invasive assessment of tumour grade and extent.