Search

Purpose: Tumor grading is very important both in treatment decision and evaluation of prognosis. While tissue samples are obtained as part of most therapeutic approaches, factors that may result in inaccurate grading due to sampling error (namely, heterogeneity in tissue sampling, as well as tumor-grade heterogeneity within the same tumor specimen), have led to a desire to use imaging better to ascertain tumor grade. The purpose in our study was to evaluate the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under the curve (AUC), and accuracy of diffusion-weighted MR imaging (DWI), proton MR spectroscopic imaging (MRSI) or both in grading primary cerebral gliomas., Materials and Methods: We performed conventional MR imaging (MR), DWI, and MRSI in 74 patients with newly diagnosed brain gliomas: 59 patients had histologically verified high-grade gliomas: 37 glioblastomas multiform (GBM) and 22 anaplastic astrocytomas (AA), and 15 patients had low-grade gliomas. Apparent diffusion coefficient (ADC) values of tumor and peritumoral edema, and ADC ratios (ADC in tumor or peritumoral edema to ADC of contralateral white matter, as well as ADC in tumor to ADC in peritumoral edema) were determined from three regions of interest. The average of the mean, maximum, and minimum for ADC variables was calculated for each patient. The metabolite ratios of Cho/Cr and Cho/NAA at intermediate TE were assessed from spectral maps in the solid portion of tumor, peritumoral edema and contralateral normal-appearing white matter. Tumor grade determined with the two methods was then compared with that from histopathologic grading. Logistic regression and receiver operating characteristic (ROC) curve analysis were performed to determine optimum thresholds for tumor grading. Measures of diagnostic examination performance, such as sensitivity, specificity, PPV, NPV, AUC, and accuracy for identifying high-grade gliomas were also calculated., Results: Statistical analysis demonstrated a threshold minimum ADC tumor value of 1.07 to provide sensitivity, specificity, PPV, and NPV of 79.7%, 60.0%, 88.7%, and 42.9% respectively, in determining high-grade gliomas. Threshold values of 1.35 and 1.78 for peritumoral Cho/Cr and Cho/NAA metabolite ratios resulted in sensitivity, specificity, PPV, and NPV of 83.3%, 85.1%, 41.7%, 97.6%, and 100%, 57.4%, 23.1% and 100% respectively for determining high-grade gliomas. Significant differences were noted in the ADC tumor values and ratios, peritumoral Cho/Cr and Cho/NAA metabolite ratios, and tumoral Cho/NAA ratio between low- and high-grade gliomas. The combination of mean ADC tumor value, maximum ADC tumor ratio, peritumoral Cho/Cr and Cho/NAA metabolite ratios resulted in sensitivity, specificity, PPV, and NPV of 91.5%, 100%, 100% and 60% respectively., Conclusion: Combining DWI and MRSI increases the accuracy of preoperative imaging in the determination of glioma grade. MRSI had superior diagnostic performance in predicting glioma grade compared with DWI alone. The predictive values are helpful in the clinical decision-making process to evaluate the histologic grade of tumors, and provide a means of guiding treatment., (Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.)

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. [ABSTRACT FROM AUTHOR]