Abstract
One of the most common and aggressive malignant brain tumors is Glioblastoma multiforme. Despite the multimodality treatment such as radiation therapy and chemotherapy (temozolomide: TMZ), the median survival rate of glioblastoma patient is less than 15 months. In this study, we investigated the association between measures of spatial diversity derived from spatial point pattern analysis of multiparametric magnetic resonance imaging (MRI) data with molecular status as well as 12-month survival in glioblastoma. We obtained 27 measures of spatial proximity (diversity) via spatial point pattern analysis of multiparametric T1 post-contrast and T2 fluid-attenuated inversion recovery MRI data. These measures were used to predict 12-month survival status (≤12 or >12 months) in 74 glioblastoma patients. Kaplan-Meier with receiver operating characteristic analyses was used to assess the relationship between derived spatial features and 12-month survival status as well as molecular subtype status in patients with glioblastoma. Kaplan-Meier survival analysis revealed that 14 spatial features were capable of stratifying overall survival in a statistically significant manner. For prediction of 12-month survival status based on these diversity indices, sensitivity and specificity were 0.86 and 0.64, respectively. The area under the receiver operating characteristic curve and the accuracy were 0.76 and 0.75, respectively. For prediction of molecular subtype status, proneural subtype shows highest accuracy of 0.93 among all molecular subtypes based on receiver operating characteristic analysis. We find that measures of spatial diversity from point pattern analysis of intensity habitats from T1 post-contrast and T2 fluid-attenuated inversion recovery images are associated with both tumor subtype status and 12-month survival status and may therefore be useful indicators of patient prognosis, in addition to providing potential guidance for molecularly-targeted therapies in Glioblastoma multiforme.
Highlights
Glioblastoma multiforme (GBM) is one of the most common and malignant brain tumors in humans
We showed that the spatial features obtained using a multitype spatial point pattern representations of T1 post-contrast and T2-Fluid Attenuated Inversion Recovery (FLAIR) magnetic resonance imaging (MRI) data are associated with 12-month survival status and molecular subtypes of GBM
Some studies have shown that the spatial heterogeneity of computed tomography (CT) and MRI intensity values within a tumor is associated with intratumor heterogeneity, tumor malignancy, and patient survival rates [3, 5, 28,29,30]
Summary
Glioblastoma multiforme (GBM) is one of the most common and malignant brain tumors in humans. The median survival rate of GBM patients is between 12 ~ 15 months [1]. Analysis of tumor heterogeneity has the potential to aid treatment of GBM, as different tumor subpopulations may respond differently [2,3,4]. It has been suggested that heterogeneity in gray-level intensity in magnetic resonance imaging (MRI) may be indicative of such distinct tumor habitats [5]. Such heterogeneity is often measured by texture analysis, which provides information about the spatial arrangement of gray-level intensities and quantifies the local characteristic patterns in an image. Texture analyses using modalities such as MRI, positron emission tomography (PET), and computed tomography (CT) have been shown to be promising for cancer prognosis [6,7,8,9]
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