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Updated: Jul 10, 2025

Laser Capture Microdissection of Glioma Subregions for Spatial and Molecular Characterization of Intratumoral Heterogeneity, Oncostreams, and Invasion

Laser Capture Microdissection of Glioma Subregions for Spatial and Molecular Characterization of Intratumoral Heterogeneity, Oncostreams, and Invasion

Published on: April 12, 2020

MR Perfusion Imaging for Gliomas.

Jina Lee¹, Melissa M Chen¹, Ho-Ling Liu²

¹Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA.

Magnetic Resonance Imaging Clinics of North America

|November 25, 2023

Summary

This summary is machine-generated.

Multiparametric MR perfusion imaging offers crucial insights for diagnosing and monitoring gliomas. This technique aids in classifying tumors and differentiating treatment effects from recurrence, improving clinical decision-making.

Keywords:

Arterial spin labeling Brain tumor Dynamic contrast-enhanced Dynamic susceptibility contrast Glioma Perfusion

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Last Updated: Jul 10, 2025

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PET and MRI Guided Irradiation of a Glioblastoma Rat Model Using a Micro-irradiator

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Published on: December 28, 2017

Area of Science:

Neuroimaging
Oncology
Radiology

Background:

Accurate glioma diagnosis and treatment evaluation are critical for clinical decisions.
Conventional MRI has limitations in distinguishing tumor recurrence from treatment effects.
Multiparametric MR perfusion imaging provides valuable physiologic information.

Purpose of the Study:

To review the role of MR perfusion imaging in glioma diagnosis and treatment monitoring.
To highlight its utility in classifying gliomas and differentiating post-treatment changes.
To provide an update on its application in various treatment regimens.

Main Methods:

Review of current literature on multiparametric MR perfusion imaging in gliomas.
Analysis of its application in differentiating neoplastic and nonneoplastic entities.
Evaluation of its role in distinguishing tumor recurrence from radiation necrosis, pseudoprogression, and pseudoresponse.

Main Results:

Multiparametric MR perfusion imaging reveals glioma-specific physiologic features.
It aids in classifying gliomas based on histologic and molecular characteristics.
It is effective in differentiating tumor recurrence from treatment-induced changes like radiation necrosis and pseudoprogression.

Conclusions:

Multiparametric MR perfusion imaging is essential for accurate glioma diagnosis and treatment evaluation.
It enhances the ability to monitor treatment response and differentiate recurrence from other conditions.
This advanced imaging technique supports personalized treatment strategies for glioma patients.