Diagnostic accuracy of MRI techniques for treatment response evaluation in patients with brain metastasis: A systematic review and meta-analysis.

BACKGROUND: Treatment response assessment in patients with brain metastasis uses contrast enhanced T1-weighted MRI. Advanced MRI techniques have been studied, but the diagnostic accuracy is not well known. Therefore, we performed a metaanalysis to assess the diagnostic accuracy of the currently available MRI techniques for treatment response. METHODS: A systematic literature search was done. Study selection and data extraction were done by two authors independently. Meta-analysis was performed using a bivariate random effects model. An independent cohort was used for DSC perfusion external validation of diagnostic accuracy. RESULTS: Anatomical MRI (16 studies, 726 lesions) showed a pooled sensitivity of 79% and a specificity of 76%. DCE perfusion (4 studies, 114 lesions) showed a pooled sensitivity of 74% and a specificity of 92%. DSC perfusion (12 studies, 418 lesions) showed a pooled sensitivity was 83% with a specificity of 78%. Diffusion weighted imaging (7 studies, 288 lesions) showed a pooled sensitivity of 67% and a specificity of 79%. MRS (4 studies, 54 lesions) showed a pooled sensitivity of 80% and a specificity of 78%. Combined techniques (6 studies, 375 lesions) showed a pooled sensitivity of 84% and a specificity of 88%. External validation of DSC showed a lower sensitivity and a higher specificity for the reported cut-off values included in this metaanalysis. CONCLUSION: A combination of techniques shows the highest diagnostic accuracy differentiating tumor progression from treatment induced abnormalities. External validation of imaging results is important to better define the reliability of imaging results with the different techniques.

11C-methyl-L-methionine PET measuring parameters for the diagnosis of tumour progression against radiation-induced changes in brain metastases.

OBJECTIVES: Radiation-induced changes (RIC) secondary to focal radiotherapy can imitate tumour progression in brain metastases and make follow-up clinical decision making unreliable. 11C-methyl-L-methionine-PET (MET-PET) is widely used for the diagnosis of RIC in brain metastases, but minimal literature exists regarding the optimum PET measuring parameter to be used. We analysed the diagnostic performance of different MET-PET measuring parameters in distinguishing between RIC and tumour progression in a retrospective cohort of brain metastasis patients. METHODS: 26 patients with 31 metastatic lesions were included on the basis of having undergone a PET scan due to radiological uncertainty of disease progression. The PET images were analysed and methionine uptake quantified using standardised-uptake-values (SUV) and tumour-to-normal tissue (T/N) ratios, generated as SUVmean, SUVmax, SUVpeak, T/Nmean, T/Nmax-mean and T/Npeak-mean. Metabolic-tumour-volume and total-lesion methionine metabolism were also computed. A definitive diagnosis of either RIC or tumour progression was established by clinicoradiological follow-up of least 4 months subsequent to the investigative PET scan. RESULTS: All MET-PET parameters except metabolic-tumour-volume showed statistically significant differences between tumour progression and lesions with RIC. Receiver-operating-characteristic curve and area-under the-curve analysis demonstrated the highest value of 0.834 for SUVmax with a corresponding optimum threshold of 3.29. This associated with sensitivity, specificity, positive predictive and negative predictive values of 78.57, 70.59%, 74.32 and 75.25% respectively. CONCLUSIONS: MET-PET is a useful modality for the diagnosis of RIC in brain metastases. SUVmax was the PET parameter with the greatest diagnostic performance. ADVANCES IN KNOWLEDGE: More robust comparisons between SUVmax and SUVpeak could enhance follow-up treatment planning.