Y Y Wang1, T Zhang2, S W Li3, T Y Qian4, X Fan2, X X Peng5, J Ma3, L Wang6, T Jiang7. 1. From the Beijing Neurosurgical Institute (Y.Y.W., T.J.) Departments of Neurosurgery (Y.Y.W., T.Z., X.F., L.W., T.J.). 2. Departments of Neurosurgery (Y.Y.W., T.Z., X.F., L.W., T.J.). 3. Neuroradiology (S.W.L., J.M.), Beijing Tiantan Hospital, Capital Medical University, Beijing, China. 4. Siemens Healthcare (T.Y.Q.), MR Collaboration NE Asia, Beijing, China. 5. Department of Epidemiology and Biostatistics (X.X.P.), School of Public Health and Family Medicine, Capital Medical University, Beijing, China. 6. Departments of Neurosurgery (Y.Y.W., T.Z., X.F., L.W., T.J.) China National Clinical Research Center for Neurological Diseases (L.W.), Beijing, China taojiang1964@163.com wangleitiantan@126.com. 7. From the Beijing Neurosurgical Institute (Y.Y.W., T.J.) Departments of Neurosurgery (Y.Y.W., T.Z., X.F., L.W., T.J.) Beijing Institute for Brain Disorders (T.J.), Beijing, China. taojiang1964@163.com wangleitiantan@126.com.
Abstract
BACKGROUND AND PURPOSE: Brain tumor location has proved to be a prognostic factor that may be associated with features of neoplastic origin. Mutation of p53 is an atypical genetic change that occurs during tumorigenesis. Thus, a potential correlation may exist between tumor location and p53 status. The purpose of the current study was to identify anatomic characteristics of mutant p53 expression by using quantitative neuroimaging analyses. MATERIALS AND METHODS: Preoperative MR images from 182 patients with histologically confirmed low-grade gliomas were retrospectively analyzed. All tumors were manually marked and registered to the standard space. Using a voxel-based lesion-symptom mapping analysis, we located brain regions associated with a high occurrence of p53 mutation and corrected them by using a permutation test. The acquired clusters were further included as a factor in survival analyses. RESULTS: Statistical analysis demonstrated that the left medial temporal lobe and right anterior temporal lobe were specifically associated with high expression of mutant p53. Kaplan-Meier curves showed that tumors located in these regions were associated with significantly worse progression-free survival compared with tumors occurring elsewhere. CONCLUSIONS: Our voxel-level imaging analysis provides new evidence that genetic changes during cancer may have anatomic specificity. Additionally, the current study suggests that tumor location identified on structural MR images could potentially be used for customized presurgical outcome prediction.
BACKGROUND AND PURPOSE:Brain tumor location has proved to be a prognostic factor that may be associated with features of neoplastic origin. Mutation of p53 is an atypical genetic change that occurs during tumorigenesis. Thus, a potential correlation may exist between tumor location and p53 status. The purpose of the current study was to identify anatomic characteristics of mutant p53 expression by using quantitative neuroimaging analyses. MATERIALS AND METHODS: Preoperative MR images from 182 patients with histologically confirmed low-grade gliomas were retrospectively analyzed. All tumors were manually marked and registered to the standard space. Using a voxel-based lesion-symptom mapping analysis, we located brain regions associated with a high occurrence of p53 mutation and corrected them by using a permutation test. The acquired clusters were further included as a factor in survival analyses. RESULTS: Statistical analysis demonstrated that the left medial temporal lobe and right anterior temporal lobe were specifically associated with high expression of mutant p53. Kaplan-Meier curves showed that tumors located in these regions were associated with significantly worse progression-free survival compared with tumors occurring elsewhere. CONCLUSIONS: Our voxel-level imaging analysis provides new evidence that genetic changes during cancer may have anatomic specificity. Additionally, the current study suggests that tumor location identified on structural MR images could potentially be used for customized presurgical outcome prediction.
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