OBJECT: The authors examined the relationships of brain-tumor interfaces, specific magnetic resonance (MR) imaging features, and angiographic findings in meningiomas to predict tumor cleavage and difficulty of resection. METHODS: Magnetic resonance imaging studies, angiographic data, operative reports, clinical data, and histopathological findings were examined retrospectively in this series, which included 126 patients with intracranial meningiomas who underwent operations in which microsurgical techniques were used. The authors have identified three kinds of brain-tumor interfaces characterized by various difficulties in microsurgical dissection: smooth type, intermediate type, and invasive type. The signal intensity on T1-weighted MR images was very similar regardless of the type of brain-tumor interface (p > 0.1). However, on T2-weighted images the different interfaces seemed to correlate very precisely with the signal intensity and the amount of peritumoral edema (p < 0.01), allowing the prediction of microsurgical effort required during surgery. On angiographic studies, the pial-cortical arterial supply was seen to participate almost equally with the meningeal-dural arterial supply in vascularizing the tumor in 57.9% of patients. Meningiomas demonstrating hypervascularization on angiography, particularly those fed by the pial-cortical arteries, exhibited significantly more severe edema compared with those supplied only from meningeal arteries (p < 0.01). Indeed, a positive correlation was found between the vascular supply from pial-cortical arteries and the type of cleavage (p < 0.05). CONCLUSIONS: In this analysis the authors proved that there is a strong correlation between the amount of peritumoral edema, hyperintensity of the tumor on T2-weighted images, cortical penetration, vascular supply from pial-cortical arteries, and cleavage of the meningioma. Therefore, the consequent difficulty of microsurgical dissection can be predicted preoperatively by analyzing MR imaging and angiographic studies.
OBJECT: The authors examined the relationships of brain-tumor interfaces, specific magnetic resonance (MR) imaging features, and angiographic findings in meningiomas to predict tumor cleavage and difficulty of resection. METHODS: Magnetic resonance imaging studies, angiographic data, operative reports, clinical data, and histopathological findings were examined retrospectively in this series, which included 126 patients with intracranial meningiomas who underwent operations in which microsurgical techniques were used. The authors have identified three kinds of brain-tumor interfaces characterized by various difficulties in microsurgical dissection: smooth type, intermediate type, and invasive type. The signal intensity on T1-weighted MR images was very similar regardless of the type of brain-tumor interface (p > 0.1). However, on T2-weighted images the different interfaces seemed to correlate very precisely with the signal intensity and the amount of peritumoral edema (p < 0.01), allowing the prediction of microsurgical effort required during surgery. On angiographic studies, the pial-cortical arterial supply was seen to participate almost equally with the meningeal-dural arterial supply in vascularizing the tumor in 57.9% of patients. Meningiomas demonstrating hypervascularization on angiography, particularly those fed by the pial-cortical arteries, exhibited significantly more severe edema compared with those supplied only from meningeal arteries (p < 0.01). Indeed, a positive correlation was found between the vascular supply from pial-cortical arteries and the type of cleavage (p < 0.05). CONCLUSIONS: In this analysis the authors proved that there is a strong correlation between the amount of peritumoral edema, hyperintensity of the tumor on T2-weighted images, cortical penetration, vascular supply from pial-cortical arteries, and cleavage of the meningioma. Therefore, the consequent difficulty of microsurgical dissection can be predicted preoperatively by analyzing MR imaging and angiographic studies.
Authors: Pablo A Valdes; Kimon Bekelis; Brent T Harris; Brian C Wilson; Frederic Leblond; Anthony Kim; Nathan E Simmons; Kadir Erkmen; Keith D Paulsen; David W Roberts Journal: Neurosurgery Date: 2014-03 Impact factor: 4.654
Authors: Ziying Yin; Kevin J Glaser; Armando Manduca; Jamie J Van Gompel; Michael J Link; Joshua D Hughes; Anthony Romano; Richard L Ehman; John Huston Journal: Radiology Date: 2015-08-06 Impact factor: 11.105