The role of relative cerebral blood volume obtained from Perfusion Weighted Imaging-MRI in glioma tumor grading before surgery

Document Type : Conference Proceedings


1 MSc of Medical Physics, Department of Medial physics, Kermanshah University of Medical Sciences, Kermanshah, Iran.

2 Assistant Professor, Department of Radiology, Imam Reza Hospital, Kermanshah University of Medical Science, Kermanshah, Iran.

3 Associate Professor, Medical Physics Department, Medicine School, Kermanshah University of Medical Sciences, Kermanshah, Iran.

4 MSc Student of Medical Physics, Department of Medial physics, Kermanshah University of Medical Sciences, Kermanshah, Iran.


Introduction: Glioma is the most common type of brain malignancy among adults. Treatment for this type of tumor involves surgery, radiotherapy, and in higher grades, including chemotherapy. The precise grading of the tumor is critical for treatment planning and prognosis determining. Considering the possibility of problems such as errors in tissue sampling during surgery, as well as errors in histopathological grading of the lesions or the impossibility of surgery and sampling in some patients, the importance of advanced neuroimaging techniques as a non-invasive technique is more pronounced. Perfusion Weighted Imaging (PWI) is one of the advanced MR imaging techniques that can be helpful in tumor grading by evaluating tissue physiology alongside conventional MR images. Relative cerebral blood volume (rCBV) is one of the parameters that is obtained from the analysis of perfusion images. Our purpose in this study is to examine this parameter in tumor grading.
Materials and Methods: 15 primary glioma patients who had confirmed histopathology
entered the study. All patients were initially subjected to conventional MRI and PWI. The
images were reviewed in collaboration with an experienced radiologist and then examined
for determining the threshold values for tumor grading. Results were compared with
histopathologic grade. Statistical analysis was performed using SPSS software.
Results: According to the results of images and statistical analysis, the rCBV threshold value, sensitivity and specificity in the high grade glioma determination were 2.91, 94.6 and 93.7, respectively. There was also a significant difference between high and low grade glioma in rCBV value (P< 0.001).
Conclusion: The advanced PWI-MRI imaging technique increases the accuracy of the glioma tumor marker and also the rCBV value can be recognized as a biomarker for tumor grading.