Quantitative apparent diffusion coefficients in the characterization of brain tumors and associated peritumoral edema

Abstract

Background: Conventional magnetic resonance (MR) imaging has a number of limitations in the diagnosis of the most common intracranial brain tumors, including tumor specification and the detection of tumoral infiltration in regions of peritumoral edema. Purpose: To prospectively assess if diffusion-weighted MR imaging (DWI) could be used to differentiate between different types of brain tumors and to distinguish between peritumoral infiltration in high-grade gliomas, lymphomas, and pure vasogenic edema in metastases and meningiomas. Material and Methods: MR imaging and DWI was performed on 93 patients with newly diagnosed brain tumors: 59 patients had histologically verified high-grade gliomas (37 glioblastomas multiforme, 22 anaplastic astrocytomas), 23 patients had metastatic brain tumors, five patients had primary cerebral lymphomas, and six patients had meningiomas. Apparent diffusion coefficient (ADC) values of tumor (enhancing regions or the solid portion of tumor) and peritumoral edema, and ADC ratios (ADC of tumor or peritumoral edema to ADC of contralateral white matter, ADC of tumor to ADC of peritumoral edema) were compared with the histologic diagnosis. ADC values and ratios of high-grade gliomas, primary cerebral lymphomas, metastases, and meningiomas were compared by using ANOVA and multiple comparisons. Optimal thresholds of ADC values and ADC ratios for distinguishing high-grade gliomas from metastases were determined by receiver operating characteristic (ROC) curve analysis. Results: Statistically significant differences were found for minimum and mean of ADC tumor and ADC tumor ratio values between metastases and high-grade gliomas when including only one factor at a time. Including a combination of in total four parameters (mean ADC tumor, and minimum, maximum and mean ADC tumor ratio) resulted in sensitivity, specificity, positive (PPV), and negative predictive values (NPV) of 72.9, 82.6, 91.5, and 54.3% respectively. In the ROC curve analysis, the area under the curve of the combined four parameters was the largest (0.84), indicating a good test. Conclusion: Our results suggest that ADC values and ADC ratios (minimum and mean of ADC tumor and ADC tumor ratio) may be helpful in the differentiation of metastases from high-grade gliomas. It cannot distinguish high-grade gliomas from lymphomas, and lymphomas from metastases. ADC values and ADC ratios in peritumoral edema cannot be used to differentiate edema with infiltration of tumor cells from vasogenic edema when measurements for high-grade gliomas, lymphomas, metastases, and meningiomas were compared.

Original article Abnormalities in the normal appearing white matter of the cerebral hemisphere contralateral to a malignant brain tumor detected by diffusion tensor imaging

“…Abnormal FA or ADC values are not a proof of malignant transformation as they cannot differen tiate between tumor and edema [31]. Apparent diffusion coefficient may be influenced by several parameters such as cellular density, existence and distribution of vasogenic edema, and tissue hypoxia [11].…”

Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

“…Although some papers have focused on diŠerentiating high-grade gliomas and lymphoma, whose cellularities are diŠerent, 53,[56][57][58][59][60] ADC values overlap between gliomas and lymphoma. 61 Murakami's team reported that use of the ADC can improve accuracy in grading astrocytic tumors, using a combination of minimum ADCs and ADC diŠerence values (2-parameter method). 62 However, the clinical usefulness of this technique remains limited because of overlap in the regional Fig.…”

Morphometric model for discrimination between glioblastoma multiforme and solitary metastasis using three‐dimensional shape analysis

“…Moreover, lower classification rates (60-F o r P e e r R e v i e w 6 80%) or <0.8 average AUC were reported to distinguish GBM and MET in other previous studies (13,14,16,17,(22)(23)(24)(25).…”