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Article Abstract

Objectives: To investigate the prognostic utility of DTI and DSC-PWI perfusion-derived parameters in brain metastases patients.

Methods: Retrospective analyses of DTI-derived parameters (MD, FA, CL, CP, and CS) and DSC-perfusion PWI-derived rCBV from 101 patients diagnosed with brain metastases prior to treatment were performed. Using semi-automated segmentation, DTI metrics and rCBV were quantified from enhancing areas of the dominant metastatic lesion. For each metric, patients were classified as short- and long-term survivors based on analysis of the best coefficient for each parameter and percentile to separate the groups. Kaplan-Meier analysis was used to compare mOS between these groups. Multivariate survival analysis was subsequently conducted. A correlative histopathologic analysis was performed in a subcohort ( = 10) with DTI metrics and rCBV on opposite ends of the spectrum.

Results: Significant differences in mOS were observed for MD ( < 0.05), FA ( < 0.01), CL ( < 0.05), and CP ( < 0.01) and trend toward significance for rCBV ( = 0.07) between the two risk groups, in the univariate analysis. On multivariate analysis, the best predictive survival model was comprised of MD ( = 0.05), rCBV ( < 0.05), RPA ( < 0.0001), and number of lesions ( = 0.07). On histopathology, metastatic tumors showed significant differences in the amount of stroma depending on the combination of DTI metrics and rCBVmax values. Patients with high stromal content demonstrated poorer mOS.

Conclusion: Pretreatment DTI-derived parameters, notably MD and rCBVmax, are promising imaging markers for prognostication of OS in patients with brain metastases. Stromal cellularity may be a contributing factor to these differences.

Advances In Knowledge: The correlation of DTI-derived metrics and perfusion MRI with patient outcomes has not been investigated in patients with treatment naïve brain metastasis. DTI and DSC-PWI can aid in therapeutic decision-making by providing additional clinical guidance.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733614PMC
http://dx.doi.org/10.1259/bjr.20220516DOI Listing

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