Tahamtan Mohammadreza, Afsharzadeh Mahshad, Sarvari Masoumeh, Rahmani Shahryar, Geravandi Mahsa, Amiri Delaram, Kolahi Shahriar
Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Department of Radiology, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran.
Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
Neurooncol Adv. 2025 Jul 19;7(1):vdaf161. doi: 10.1093/noajnl/vdaf161. eCollection 2025 Jan-Dec.
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.
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.
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 (² = 37.3%), with no significant heterogeneity in sensitivity (² = 0%). Publication bias was detected ( <.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.
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.
在神经肿瘤学中，区分肿瘤进展与治疗后变化（如假性进展和放射性坏死）仍然是一项重大挑战。对比剂清除分析（CCA）或治疗反应评估图已成为用于此目的的一种有前景的工具。本系统评价和荟萃分析评估了CCA在区分肿瘤进展与治疗引起的变化方面的诊断准确性，并将其性能与其他先进成像方式进行比较。
按照PRISMA-DTA指南，截至2025年5月在PubMed、Scopus、科学网和Embase上进行了全面检索。使用QUADAS-2工具进行质量评估。使用双变量随机效应荟萃分析模型汇总诊断准确性指标，包括敏感性、特异性和曲线下面积（AUC）。
纳入了9项研究，涉及240例患者和407个脑病变。对比剂清除分析显示汇总敏感性为91%（95%CI，0.84-0.95），特异性为92%（95%CI，0.87-0.95），AUC为88%。在特异性方面观察到中度异质性（I² = 37.3%），在敏感性方面无显著异质性（I² = 0%）。检测到发表偏倚（P <.001），修剪填充法提示可能有5项研究缺失。质量评估显示参考测试领域存在相当大的偏倚风险。
对比剂清除分析在区分肿瘤进展与治疗后变化方面显示出高诊断准确性，优于传统MRI，并且与其他先进成像技术（如磁共振灌注、扩散加权成像和磁共振波谱）表现相当或更优。然而，方法学局限性和参考标准的变异性突出表明未来研究需要标准化方案。
