Background: Differentiating tumor progression from posttreatment changes, such as pseudoprogression and radiation necrosis, remains a significant challenge in neuro-oncology. Contrast Clearance Analysis (CCA), or Treatment Response Assessment Maps, has developed as a promising tool for this purpose. This systematic review and meta-analysis evaluate the diagnostic accuracy of CCA in distinguishing tumor progression from treatment-induced changes and compare its performance with other advanced imaging modalities.

Methods: Following PRISMA-DTA guidelines, a comprehensive search was conducted across PubMed, Scopus, Web of Science, and Embase up to May 2025. Quality assessment was performed using the QUADAS-2 tool. Diagnostic accuracy metrics, including sensitivity, specificity, and area under the curve (AUC), were pooled using a bivariate random-effects meta-analysis model.

Results: Nine studies involving 240 patients and 407 brain lesions were included. Contrast Clearance Analysis demonstrated a pooled sensitivity of 91% (95% CI, 0.84-0.95), a specificity of 92% (95% CI, 0.87-0.95), and an AUC of 88%. Moderate heterogeneity was observed in specificity (I² = 37.3%), with no significant heterogeneity in sensitivity (I² = 0%). Publication bias was detected (P <.001), with the trim-and-fill method suggesting 5 potentially missing studies. Quality assessment revealed a considerable risk of bias in the reference test domain.

Conclusion: Contrast Clearance Analysis demonstrates high diagnostic accuracy in differentiating tumor progression from posttreatment changes, outperforming conventional MRI and showing comparable or superior performance to other advanced imaging techniques such as MR perfusion, diffusion-weighted imaging, and MR spectroscopy. However, methodological limitations and variability in reference standards highlight the need for standardized protocols in future research