Background: Perfusion Weighted Imaging (PWI) has been used to differentiate the solitary
metastases from high-grade glioma. However, the CBV value obtained from classical algorithm
can be affected by a number of factors. Tissue Similarity Map (TSM) is a new algorithm depending
solely on the signal intensity time course but does not require the use of Concentration Time Curve
(CTC), which is different from the classical rCBV algorithm.
Objective: The purpose of this study is to investigate the diagnostic utility of TSM based rCBV
values in differentiating between high-grade gliomas and solitary metastases.
Methods: The preoperative MR PWI studies of 30 patients with a solitary cerebral neoplasm were
retrospectively analyzed. All PWI data were calculated for TSM algorithm with MATLAB 7.6
(Math Works, Natick, MA). The TSM based rCBV (rCBVTSM) were measured in the parenchyma of
tumor and peritumoral regions. All specimens were histopathologically categorized as high-grade
gliomas or metastases and were correlated with corresponding rCBVTSM values.
Results: All PWI data could be post-processed by using the TSM post-processing software. The
differences in the rCBVTSM-T between high-grade gliomas and metastases were not statistically
significant (p=0.299). While the rCBVTSM-P of high-grade gliomas was higher than that of metastases
(p=0.040). ROC curve analysis showed significant AUC of rCBVTSM-P for differentiating highgrade
gliomas from metastases (p=0.020). The rCBVTSM-P threshold of 1.725 was found to be a significant
cutoff value for high-grade glioma/metastases prediction with 0.619 sensitivity and 0.889
Conclusion: The rCBVTSM-P derived from MR PWI may be helpful in differentiating high-grade
gliomas from solitary metastases.