[Magnetic resonance in brain tumors: a classification based on signal behavior in multiple echo sequences]

Area of Science:

• Neuroradiology
• Oncology
• Medical Imaging

Background:

• Magnetic Resonance (MR) imaging offers high sensitivity but limited specificity in detecting brain lesions compared to Computed Tomography (CT).
• Improving the specificity of MR imaging is crucial for accurate brain tumor diagnosis.

Purpose of the Study:

• To evaluate the utility of multiple echo sequences in improving MR imaging specificity for intracranial tumors.
• To develop a classification system for brain tumors based on signal intensity patterns in T2-weighted images (T2 WI).

Main Methods:

• Reviewed 343 histologically verified intracranial tumors using MR with multiple echo sequences.
• Classified tumors into 5 distinct groups based on signal intensity patterns observed in T2 WI.
• Analyzed signal characteristics including progressive increase/decrease, uniform intensity, and mixed patterns.

Main Results:

• Established 5 distinct signal pattern classes for brain tumors in T2 WI.
• Demonstrated varying signal patterns for different tumor types, such as craniopharyngiomas, astrocytomas, medulloblastomas, meningiomas, glioblastomas, and oligodendrogliomas.
• Found signal patterns to be characteristic but not pathognomonic, aiding in narrowing differential diagnoses.

Conclusions:

• Multiple echo sequences significantly improve MR imaging specificity for brain tumor diagnosis.
• The proposed 5-class system based on T2 WI signal patterns is a useful criterion for restricting differential diagnoses of intracranial tumors.
• Analysis of T1 and T2 values appeared less beneficial for tumor classification compared to signal patterns.