Background: Because of intratumoral heterogeneity, diffusely infiltrating gliomas that lack significant contrast enhancement on magnetic resonance imaging are prone to tissue sampling error. Subsequent histologic undergrading may delay adjuvant treatments. 5-Aminolevulinic acid (5-ALA) leads to accumulation of fluorescent porphyrins in malignant glioma tissue, and is currently used for resection of malignant gliomas. The aim of this study was to clarify whether 5-ALA might serve as marker for visualization of anaplastic foci in diffusely infiltrating gliomas with nonsignificant contrast enhancement for precise intraoperative tissue sampling.
Methods: 5-ALA was administered in 17 patients with diffusely infiltrating gliomas with nonsignificant contrast enhancement. During glioma resection, positive fluorescence was noted by a modified neurosurgical microscope. Intraoperative topographic correlation of focal 5-ALA fluorescence with maximum (11)C-methionine positron emission tomography uptake (PET(max)) was performed. Multiple tissue samples were taken from areas of positive and/or negative 5-ALA fluorescence. Histopathological diagnosis was established according to World Health Organization (WHO) 2007 criteria. Cell proliferation was assessed for multiregional samples by MIB-1 labeling index (LI).
Results: Focal 5-ALA fluorescence was observed in 8 of 9 patients with WHO grade III diffusely infiltrating gliomas. All 8 of 8 WHO grade II diffusely infiltrating gliomas were 5-ALA negative. Focal 5-ALA fluorescence correlated topographically with PET(max) in all patients. MIB-1 LI was significantly higher in 5-ALA-positive than in nonfluorescent areas within a given tumor.
Conclusions: The data indicate that 5-ALA is a promising marker for intraoperative visualization of anaplastic foci in diffusely infiltrating gliomas with nonsignificant contrast enhancement. Unaffected by intraoperative brain shift, 5-ALA may increase the precision of tissue sampling during tumor resection for histopathological grading, and therefore optimize allocation of patients to adjuvant treatments.