|
| Study (year) (ref) | Group () | Average age (year) | Imaging modality (method or model; parameter analysis) | Indexes | Threshold (Sp%, Sn%) | Limitations |
|
| Barajas et al. (2009) [182] | RN (17)
rGB (40) | 54 | DSC-MRI (alteration of and flip angle for leakage correction, ROI-based analysis) | rCBV
rPH
rPSR | rPH = 1.38 (81.38%, 89.32%)
rPSR = 87.3% (76.19%, 78.26%)
rCBV = 1.75 (71.58%, 78.92%) | Impact of partial volume averaging effect on parameter evaluation |
|
| Hu et al. (2009) [183] | rHGG (24)
RN (16) | 47 | DSC-MRI (baseline subtraction method for leakage correction; ROI-based analysis) | rCBV | rCBV = 0.71 (100%, 91.7%) | Various tumor types; inconsistent radiation dose and different therapies |
|
| Bisdas et al. (2011) [184] | rHGG (12)
RN (6) | N/A | DCE-MRI (TK model; ROI-based analysis) |
IAUC | = 0.19 (83%, 100%)
IAUC = 15.35 (71%, 71%)
No significant difference of and between RN and rHGG | Small sample size; lack of histopathologic confirmation in some cases |
|
| Shin et al. (2014) [158] | Recurrent glioma (19)
RN (4) | 55 | DCE-MRI (TK model; ROI-based analysis), DSC-MRI (preload for leakage corrected; ROI-based analysis) | r
rIAUC
rCBV | rCBV = 2.33 (70%, 72.2%)
r = 2.1 (80%, 61.1%)
rIAUC = 2.29 (70%, 66.6%) | Relative small sample size; ROI-based method was not comprehensive |
|
| Larsen et al. (2013) [185] | Recurrent glioma (11)
RN (3) | 56 | DCE-MRI (deconvolution technique) | CBV | CBV = 2.0 ml/100 g (100%, 100%) | Small sample size; sample bias in histological analysis; various tumor types |
|
| Masch et al. (2016) [186] | Recurrent glioma (16)
RN (8) | 51 | DSC-MRI (preload for leakage correction; ROI-based analysis) | rCBV | Not provided; elevated rCBV in recurrent lesion compared with RN | Various tumor types; lack of histological confirmation in some cases |
|
