Hao Wu1,2, Haipeng Tong1,2, Xuesong Du1,2, Hong Guo1,2, Qiang Ma3, Yulong Zhang1,2, Xiaoyue Zhou4, Heng Liu1,2, Sunan Wang1,2, Jingqin Fang5, Weiguo Zhang6,7. 1. Department of Radiology, Army Medical Center of PLA, Army Medical University, 10# Changjiangzhilu, Chongqing, 400042, People's Republic of China. 2. Chongqing Clinical Research Centre of Imaging and Nuclear Medicine, Chongqing, 400042, China. 3. Department of Pathology, Army Medical Center of PLA, Army Medical University, 10# Changjiangzhilu, Chongqing, 400042, People's Republic of China. 4. MR Collaboration, Siemens Healthineers Ltd., Shanghai, China. 5. Department of Radiology, Army Medical Center of PLA, Army Medical University, 10# Changjiangzhilu, Chongqing, 400042, People's Republic of China. jingqin0405@163.com. 6. Department of Radiology, Army Medical Center of PLA, Army Medical University, 10# Changjiangzhilu, Chongqing, 400042, People's Republic of China. wgzhang01@163.com. 7. Chongqing Clinical Research Centre of Imaging and Nuclear Medicine, Chongqing, 400042, China. wgzhang01@163.com.
Abstract
OBJECTIVE: The current study aimed to evaluate the clinical practice for hemodynamic tissue signature (HTS) method in IDH genotype prediction in three groups derived from high-grade gliomas. METHODS: Preoperative MRI examinations of 44 patients with known grade and IDH genotype were assigned into three study groups: glioblastoma multiforme, grade III, and high-grade gliomas. Perfusion parameters were analyzed and were used to automatically draw the four reproducible habitats (high-angiogenic enhancing tumor habitats, low-angiogenic enhancing tumor habitats, infiltrated peripheral edema habitats, vasogenic peripheral edema habitats) related to vascular heterogeneity. These four habitats were then compared between inter-patient with IDH mutation and their wild-type counterparts at these three groups, respectively. The discriminating potential for HTS in assessing IDH mutation status prediction was assessed by ROC curves. RESULTS: Compared with IDH wild type, IDH mutation had significantly decreased relative cerebral blood volume (rCBV) at the high-angiogenic enhancing tumor habitats and low-angiogenic enhancing tumor habitats. ROC analysis revealed that the rCBVs in habitats had great ability to discriminate IDH mutation from their wild type in all groups. In addition, the Kaplan-Meier survival analysis yielded significant differences for the survival times observed from the populations dichotomized by low (< 4.31) and high (> 4.31) rCBV in the low-angiogenic enhancing tumor habitat. CONCLUSIONS: The HTS method has been proven to have high prediction capabilities for IDH mutation status in high-grade glioma patients, providing a set of quantifiable habitats associated with tumor vascular heterogeneity. KEY POINTS: • The HTS method has a high accuracy for molecular stratification prediction for all subsets of HGG. • The HTS method can give IDH mutation-related hemodynamic information of tumor-infiltrated and vasogenic edema. • IDH-relevant rCBV difference in habitats will be a great prognosis factor in HGG.
OBJECTIVE: The current study aimed to evaluate the clinical practice for hemodynamic tissue signature (HTS) method in IDH genotype prediction in three groups derived from high-grade gliomas. METHODS: Preoperative MRI examinations of 44 patients with known grade and IDH genotype were assigned into three study groups: glioblastoma multiforme, grade III, and high-grade gliomas. Perfusion parameters were analyzed and were used to automatically draw the four reproducible habitats (high-angiogenic enhancing tumor habitats, low-angiogenic enhancing tumor habitats, infiltrated peripheral edema habitats, vasogenic peripheral edema habitats) related to vascular heterogeneity. These four habitats were then compared between inter-patient with IDH mutation and their wild-type counterparts at these three groups, respectively. The discriminating potential for HTS in assessing IDH mutation status prediction was assessed by ROC curves. RESULTS: Compared with IDH wild type, IDH mutation had significantly decreased relative cerebral blood volume (rCBV) at the high-angiogenic enhancing tumor habitats and low-angiogenic enhancing tumor habitats. ROC analysis revealed that the rCBVs in habitats had great ability to discriminate IDH mutation from their wild type in all groups. In addition, the Kaplan-Meier survival analysis yielded significant differences for the survival times observed from the populations dichotomized by low (< 4.31) and high (> 4.31) rCBV in the low-angiogenic enhancing tumor habitat. CONCLUSIONS: The HTS method has been proven to have high prediction capabilities for IDH mutation status in high-grade gliomapatients, providing a set of quantifiable habitats associated with tumor vascular heterogeneity. KEY POINTS: • The HTS method has a high accuracy for molecular stratification prediction for all subsets of HGG. • The HTS method can give IDH mutation-related hemodynamic information of tumor-infiltrated and vasogenic edema. • IDH-relevant rCBV difference in habitats will be a great prognosis factor in HGG.
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