Non-invasive assessment of heterogeneity of gliomas using diffusion and perfusion MRI: correlation with spatially co-registered PET

医学 胶质瘤 分级(工程) 磁共振成像 核医学 灌注 有效扩散系数 磁共振弥散成像 正电子发射断层摄影术 接收机工作特性 灌注扫描 曲线下面积 恶性肿瘤 标准摄取值 放射科 病理 内科学 土木工程 工程类 癌症研究
作者
Ying Zhang,Yu Lin,Zhen Xing,Shaobo Yao,Dairong Cao,Weibing Miao
出处
期刊:Acta Radiologica [SAGE]
卷期号:63 (5): 664-671 被引量:3
标识
DOI:10.1177/02841851211006913
摘要

Heterogeneity of gliomas challenges the neuronavigated biopsy and oncological therapy. Diffusion and perfusion magnetic resonance imaging (MRI) can reveal the cellular and hemodynamic heterogeneity of tumors. Integrated positron emission tomography (PET)/MRI is expected to be a non-invasive imaging approach to characterizing glioma.To evaluate the value of apparent diffusion coefficient (ADC), cerebral blood volume (CBV), and spatially co-registered maximal standard uptake value (SUVmax) for tissue characterization and glioma grading.Thirty-seven consecutive patients with pathologically confirmed gliomas were retrospectively investigated. The relative minimum ADC (rADCmin), relative maximal ADC (rADCmax), relative maximal rCBV (rCBVmax), the relative minimum rCBV (rCBVmin), and the corresponding relative SUVmax (rSUVmax) were measured. The paired t-test was used to compare the quantitative parameters between different regions to clarify tumor heterogeneity. Imaging parameters between WHO grade IV and grade II/III gliomas were compared by t-test. The diagnostic efficiency of multiparametric PET/MRI was analyzed by receiver operating characteristic (ROC) curve.The values of rSUVmax were significantly different between maximal diffusion/perfusion area and minimum diffusion/perfusion area (P < 0.001/P < 0.001) within tumor. The values of rADCmin (P < 0.001), rCBVmax (P = 0.002), and corresponding rSUVmax (P = 0.001/P < 0.001) could be used for grading gliomas. The areas under the ROC curves of rSUVmax defined by rADCmin and rCBVmax were 0.89 and 0.91, respectively.Diffusion and perfusion MRI can detect glioma heterogeneity with excellent molecular imaging correlations. Regions with rCBVmax suggest tissues with the highest metabolism and malignancy for guiding glioma grading and tissue sampling.

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