|
| Study (year) (ref) | Tumor type () | Average age (year) | Imaging modality (method or model; parameter analysis) | Indexes | Results | Limitations |
|
| Law et al. (2002) [116] | HGG (24)
MET (12) | 52 | DSC-MRI (leakage effect uncorrected; ROI-based analysis) | rCBV | rCBV in peritumoral region was significantly different between HGG and MET | The peritumoral region was not defined clearly; the threshold value was not provided |
|
| Cha et al. (2007) [117] | GBM (27)
MET (16) | 52 | DSC-MRI (alteration of and flip angle for leakage correction; ROI-based analysis) | PSR
PH | Significant difference of all parameters between GBM and MET; PSR was the most powerful with 100% specificity | Small sample size; some cases were not confirmed by histopathology |
|
| Mangla et al. (2011) [118] | GBM (22)
MET (22)
PCNSL (22) | 54 | DSC-MRI (preload for leakage correction; ROI-based analysis) | rCBV
PSR | PSR was better than rCBV for differentiation | Small sample size; impact of steroid treatment on parameter evaluation |
|
| Toh et al. (2013) [119] | GBM (20)
PCNSL (15) | 60 | DSC-MRI (algorithm for leakage correction; ROI-based analysis) | rCBV
| Uncorrected rCBV is much better for differentiating | Lack of direct correlation between parameters and histopathologic features |
|
| Xing et al. (2014) [120] | HGG (26)
PCNSL (12) | 51 | DSC-MRI (leakage effect uncorrected; ROI-based analysis) | rCBV
PSR | The combination of rCBV with PSR might help in more accurate differentiation | Impact of leakage effect on parameter measurements |
|
| Kickingereder et al. (2014) [121] | GBM (60)
PCNSL (11) | N/A | DCE-MRI (TK model; ROI-based analysis) |
| and could identify the two tumors. was the optimum parameter | Relative small sample size of PCNSL |
|
| Kickingereder et al. (2014) [122] | GBM (28)
PCNSL (19) | 66 | DSC-MRI (preload for leakage correction; ROI-based analysis), DWI, SWI | rCBV
ADC
ITSS | Multiparametric MRI allowed differentiation of GBM from PCNSL | Small sample size |
|
| Zhao et al. (2015) [52] | LGG (9)
HGG (15)
MET (5) | 46 | DCE-MRI (TK model; ROI-based analysis) |
IAUC | All parameters were significantly different between LGG, HGG, and MET. IAUC had the most diagnostic power | Small sample size; subjectivity of ROI selection |
|
| Jung et al. (2016) [123] | GBM (26)
MET (32) | N/A | DCE-MRI (ETK model, ROI-based analysis) |
AUC
Washout log slope | Semiquantitative parameters could differentiate between GBM and hypovascular metastasis | Subjectivity of ROI selection |
|
