Diagnostic performance of DSC perfusion MRI to distinguish tumor progression and treatment-related changes: a systematic review and meta-analysis

Background

In patients with high-grade glioma (HGG), true disease progression and treatment-related changes often appear similar on magnetic resonance imaging (MRI), making it challenging to evaluate therapeutic response. Dynamic susceptibility contrast (DSC) MRI has been extensively studied to differentiate between disease progression and treatment-related changes. This systematic review evaluated and synthesized the evidence for using DSC MRI to distinguish true progression from treatment-related changes.

Methods

We searched Ovid MEDLINE and the Ovid MEDLINE in-process file (January 2005-October 2019) and the reference lists. Studies on test performance of DSC MRI using relative cerebral blood volume in HGG patients were included. One investigator abstracted data, and a second investigator confirmed them; two investigators independently assessed study quality. Meta-analyses were conducted to quantitatively synthesize area under the receiver operating curve (AUROC), sensitivity, and specificity.

Results

We screened 1177 citations and included 28 studies with 638 patients with true tumor progression, and 430 patients with treatment-related changes. Nineteen studies reported AUROC and the combined AUROC is 0.85 (95% CI, 0.81-0.90). All studies contributed data for sensitivity and specificity, and the pooled sensitivity and specificity are 0.84 (95% CI, 0.80-0.88), and 0.78 (95% CI, 0.72-0.83). Extensive subgroup analyses based on study, treatment, and imaging characteristics generally showed similar results.

Conclusions

There is moderate strength of evidence that relative cerebral blood volume obtained from DSC imaging demonstrated "excellent" ability to discriminate true tumor progression from treatment-related changes, with robust sensitivity and specificity.

Role of Dynamic Susceptibility Contrast Perfusion MRI in Glioma Progression Evaluation

Accurately and quickly differentiating true progression from pseudoprogression in glioma patients is still a challenge. This study aims to explore if dynamic susceptibility contrast- (DSC-) MRI can improve the evaluation of glioma progression. We enrolled 65 glioma patients with suspected gadolinium-enhancing lesion. Longitudinal MRI follow-up (mean 590 days, range: 210-2670 days) or re-operation (n = 3) was used to confirm true progression (n = 51) and pseudoprogression (n = 14). We assessed the diagnostic performance of each MRI variable and the different combinations. Our results showed that the relative cerebral blood volume (rCBV) in the true progression group (1.094, 95%CI: 1.135-1.636) was significantly higher than that of the pseudoprogression group (0.541 ± 0.154) (p < 0.001). Among the 18 patients who had serial DSC-MRI, the rCBV of the progression group (0.480, 95%CI: 0.173-0.810) differed significantly from pseudoprogression (-0.083, 95%CI: -1.138-0.620) group (p=0.015). With an rCBV threshold of 0.743, the sensitivity and specificity for discriminating true progression from pseudoprogression were 76.5% and 92.9%, respectively. The Cho/Cr and Cho/NAA ratios of the true progression group (2.520, 95%CI: 2.331-2.773; 2.414 ± 0.665, respectively) were higher than those of the pseudoprogression group (1.719 ± 0.664; 1.499 ± 0.500, respectively) ((p=0.001), (p < 0.001), respectively). The areas under ROC curve (AUCs) of enhancement pattern, MRS, and DSC-MRI for the differentiation were 0.782, 0.881, and 0.912, respectively. Interestingly, when combined enhancement pattern, MRS, and DSC-MRI variables, the AUC was 0.965 and achieved sensitivity 90.2% and specificity 100.0%. Our results suggest that DSC-MRI can significantly improve the diagnostic performance for identifying glioma progression. DSC-MRI combined with conventional MRI may promptly distinguish true gliomas progression from pseudoprogression when the suspected gadolinium-enhancing lesion was found, without the need for a long-term follow-up.

Brain Glioma Localization Diagnosis Based on Magnetic Resonance Imaging

BACKGROUND

We used dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) technology and its perfusion parameters to diagnose central glioma high-grade glioma (HGG), primary central nervous system glioma low-grade glioma (LGG), brain metastases, and meningioma and make differential diagnoses.

METHODS

Forty-one cases of brain tumors (8 cases of LGG, 17 cases of HGG, 5 cases of "primary central nervous system lymphoma" [PCNSL], 6 cases of brain metastases, and 5 cases of meningiomas) were subjected to routine and DCE-MRI scans. The DCE-MRI quantitative parameters of the tumor parenchymal area and peripheral enema area of each tumor were measured and recorded as t-Ktrans value, t-Ve value, t-Vp value, t-Kep value and p-Ktrans value, p-Ve value, p-Vp value, and p-Kep value.

RESULTS

Compared with other tumor types, LGG showed lower t-Ktrans value (P < 0.01, sensitivity = 89%, specificity = 99%) and low t-Ve value (P < 0.01, sensitivity = 94%, specificity = 100%); PCNSL showed a high t-Ve value (P < 0.01, sensitivity = 100%, specificity = 88%), but other perfusion parameters overlap more obviously with other tumors. Compared with LGG, the difference between t-Ktrans value, t-Ve value, and t-Kep value is statistically significant. Among them, t-Ktrans value distinguishes the highest sensitivity and specificity (when t-Ktrans value = when 0.154 is the cutoff value, the area under the curve is 1.000, P = 0.000, specificity = 100%, sensitivity = 94.1%); compared with PCNSL, the difference of t-Ve value between HGG and PCNSL is statistically significant, t-Ve of PCNSL. The value is slightly higher, and its specificity and sensitivity are not high.

CONCLUSIONS

DCE-MRI can distinguish HGG and LGG more accurately, of which t-Ktrans value has higher specificity and sensitivity, although the difference of t-Ve value between PCNSL and HGG is statistically significant but the sensitivity and specificity are not high; the p-Ktrans value and p-Kep value of metastatic tumors are lower than HGG and have higher specificity, but meningiomas and HGG and PCNSL, meningiomas and metastases are not accurate identification.