Background/Objectives: Intramedullary tumors are uncommon spinal cord lesions that account for a small proportion of central nervous system neoplasms but are associated with a high risk of neurological morbidity. Accurate preoperative characterization is essential because therapeutic strategies, surgical planning, and functional prognosis depend strongly on tumor biology and growth behavior within the confined spinal cord environment. This study aims to characterize the radiological phenotype of intramedullary tumors and to identify imaging patterns that may assist in lesion characterization and diagnostic stratification. Methods: A retrospective analysis of preoperative MRI findings in patients with histopathologically confirmed intramedullary tumors was performed. Preoperative MRI examinations were systematically analyzed to describe imaging features according to tumor histology using conventional sequences (T1-weighted, T2-weighted, and contrast-enhanced imaging). Results: Distinct radiological phenotypes were observed across a wide spectrum of lesions. Glial tumors, including subependymoma, ependymoma, pilocytic astrocytoma, diffuse midline glioma H3K27M, glioblastoma, high-grade astrocytoma with piloid features, ganglioglioma, and diffuse leptomeningeal glioneural tumors, demonstrated variable combinations of cord expansion, margin definition, enhancement patterns, and tract involvement, reflecting differences between expansile and infiltrative growth. Secondary tumors such as metastases frequently exhibited aggressive imaging features, including extensive edema and intense or heterogeneous enhancement. Vascular lesions, including hemangioblastoma and cavernoma, showed characteristic vascular signatures, such as nodular enhancement with flow voids or susceptibility-related signal changes. Developmental lesions, such as epidermoid cysts, neurenteric cysts, and lipoma, displayed distinctive signal characteristics, especially on diffusion and T1, that aided differentiation from neoplastic processes. Conclusions: In conclusion, the structured radiological interpretation functions proposed herein are not only useful for diagnostic purposes, but could also be useful for risk stratification and therapeutic guidance.
Dauleac et al. (2026) studied this question.