Eduardo Flores-Alvarez1, Coral Durand-Muñoz2, Filiberto Cortes-Hernandez3, Onofre Muñoz-Hernandez4, Sergio Moreno-Jimenez5, Ernesto Roldan-Valadez6. 1. Department of Neurosurgery, Hospital General de Mexico Eduardo Liceaga (HGMEL), Mexico City, Mexico. 2. Department of Internal Medicine, Medica Sur Clinic and Foundation, Mexico City, Mexico. 3. Department of Medical Physics, Autonomous University of State of Mexico, Toluca City, Mexico. 4. Direction of Research, Hospital Infantil de Mexico Federico Gomez (HIMFG), National Health Institute, Mexico City, Mexico. 5. Radioneurosurgery Unit, National Institute of Neurology and Neurosurgery, Mexico City, Mexico. 6. Directorate of Research, Hospital General de Mexico "Dr. Eduardo Liceaga", Mexico City, Mexico; I.M. Sechenov First Moscow State Medical University (Sechenov University), Department of Radiology, Moscow, Russia.
Abstract
INTRODUCTION: Fractional anisotropy (FA), a diffusion tensor image (DTI) derived biomarker is related to invasion, infiltration, and extension of glioblastoma (GB). We aimed to evaluate FA values and their association with intervals of overall survival (OS). MATERIALS AND METHODS: Retrospective study conducted in 36 patients with GB included 23 (63.9%) males, 46 ± 14 y; and 13 (36.1%) females, 53 ± 13; followed up for 36 months. We measured FA at edema, enhancing rim, and necrosis. We created two categorical variables using levels of FA and intervals of OS to evaluate their relationships. Kaplan-Meier method and correspondence analysis evaluated the association between OS (grouped in 7 six-month intervals) and FA measurements. RESULTS: Median FA values were higher in healthy brain regions (0.351), followed by peritumoral edema (0.190), enhancing ring (0.116), and necrosis (0.071). Pair-wise comparisons among tumor regions showed a significant difference, P < 0.001. The median OS for all patients was 19.3 months; variations in the OS curves among subgroups was significant χ2 (3) = 8.48, P = 0.037. Correspondence analysis showed a significant association between FA values in the edema region and the survival intervals χ2 (18) = 30.996, P = 0.029. CONCLUSIONS: Alternative multivariate assessment using correspondence analysis might supplement the traditional survival analysis in patients with GB. A close follow-up of the variability of FA in the peritumoral edema region is predictive of the OS within specific six-month interval subgroup. Further studies should focus on predictive models combining surgical and DTI biomarkers.
INTRODUCTION: Fractional anisotropy (FA), a diffusion tensor image (DTI) derived biomarker is related to invasion, infiltration, and extension of glioblastoma (GB). We aimed to evaluate FA values and their association with intervals of overall survival (OS). MATERIALS AND METHODS: Retrospective study conducted in 36 patients with GB included 23 (63.9%) males, 46 ± 14 y; and 13 (36.1%) females, 53 ± 13; followed up for 36 months. We measured FA at edema, enhancing rim, and necrosis. We created two categorical variables using levels of FA and intervals of OS to evaluate their relationships. Kaplan-Meier method and correspondence analysis evaluated the association between OS (grouped in 7 six-month intervals) and FA measurements. RESULTS: Median FA values were higher in healthy brain regions (0.351), followed by peritumoral edema (0.190), enhancing ring (0.116), and necrosis (0.071). Pair-wise comparisons among tumor regions showed a significant difference, P < 0.001. The median OS for all patients was 19.3 months; variations in the OS curves among subgroups was significant χ2 (3) = 8.48, P = 0.037. Correspondence analysis showed a significant association between FA values in the edema region and the survival intervals χ2 (18) = 30.996, P = 0.029. CONCLUSIONS: Alternative multivariate assessment using correspondence analysis might supplement the traditional survival analysis in patients with GB. A close follow-up of the variability of FA in the peritumoral edema region is predictive of the OS within specific six-month interval subgroup. Further studies should focus on predictive models combining surgical and DTI biomarkers.