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Related Experiment Video

Updated: Mar 17, 2026

Modeling Brain Metastases Through Intracranial Injection and Magnetic Resonance Imaging

Modeling Brain Metastases Through Intracranial Injection and Magnetic Resonance Imaging

Published on: June 7, 2020

Intra-axial brain tumors.

Otto Rapalino¹, Tracy Batchelor², R Gilberto González¹

¹Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.

Handbook of Clinical Neurology

|July 20, 2016

Summary

This overview covers common intra-axial brain tumors and post-treatment changes. Differentiating these from actual tumor progression is crucial for accurate patient diagnosis and follow-up.

Keywords:

astrocytoma cerebral metastases choroid plexus tumor ependymoma glioblastoma gliomas intra-axial brain tumor medulloblastoma oligodendroglioma primitive neuroectodermal tumors

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Last Updated: Mar 17, 2026

Modeling Brain Metastases Through Intracranial Injection and Magnetic Resonance Imaging

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Published on: June 7, 2020

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Published on: May 3, 2019

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Area of Science:

Neurology
Radiology
Oncology

Background:

Intra-axial brain neoplasms encompass diverse primary and secondary tumors.
Imaging features can overlap, complicating differential diagnosis.
Post-treatment changes like pseudoprogression and radiation necrosis mimic tumor progression.

Purpose of the Study:

To provide an overview of common intra-axial brain tumors.
To discuss peculiar post-treatment imaging phenomena.
To aid in the diagnosis and clinical follow-up of patients with brain tumors.

Main Methods:

Review of common intra-axial brain tumors.
Analysis of characteristic and atypical imaging features.
Discussion of post-treatment imaging changes.

Main Results:

Intra-axial tumors present with varied imaging characteristics.
Post-treatment changes can mimic new or progressive lesions.
Accurate interpretation is vital for patient management.

Conclusions:

Understanding common intra-axial tumors and post-treatment changes is essential.
Distinguishing tumor progression from treatment effects improves patient care.
This knowledge supports accurate diagnosis and follow-up strategies.