Prognostication of overall survival in patients with brain metastases using diffusion tensor imaging and dynamic susceptibility contrast-enhanced MRI.

de Godoy, Laiz Laura, Chen, Yin Jie, Chawla, Sanjeev, Viaene, Angela N, Wang, Sumei, Loevner, Laurie A, Alonso-Basanta, Michelle, Poptani, Harish ORCID: 0000-0002-0593-3235 and Mohan, Suyash
(2022) Prognostication of overall survival in patients with brain metastases using diffusion tensor imaging and dynamic susceptibility contrast-enhanced MRI. The British journal of radiology, 95 (1140). p. 20220516.

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<h4>Objectives</h4>To investigate the prognostic utility of DTI and DSC-PWI perfusion-derived parameters in brain metastases patients.<h4>Methods</h4>Retrospective analyses of DTI-derived parameters (MD, FA, CL, CP, and CS) and DSC-perfusion PWI-derived rCBV<sub>max</sub> from 101 patients diagnosed with brain metastases prior to treatment were performed. Using semi-automated segmentation, DTI metrics and rCBV<sub>max</sub> 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 (<i>n</i> = 10) with DTI metrics and rCBV<sub>max</sub> on opposite ends of the spectrum.<h4>Results</h4>Significant differences in mOS were observed for MD<sub>min</sub> (<i>p</i> < 0.05), FA (<i>p</i> < 0.01), CL (<i>p</i> < 0.05), and CP (<i>p</i> < 0.01) and trend toward significance for rCBV<sub>max</sub> (<i>p</i> = 0.07) between the two risk groups, in the univariate analysis. On multivariate analysis, the best predictive survival model was comprised of MD<sub>min</sub> (<i>p</i> = 0.05), rCBV<sub>max</sub> (<i>p</i> < 0.05), RPA (<i>p</i> < 0.0001), and number of lesions (<i>p</i> = 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.<h4>Conclusion</h4>Pretreatment DTI-derived parameters, notably MD<sub>min</sub> 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.<h4>Advances in knowledge</h4>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.

Item Type: Article
Uncontrolled Keywords: Humans, Brain Neoplasms, Magnetic Resonance Imaging, Magnetic Resonance Angiography, Retrospective Studies, Diffusion Tensor Imaging
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology
Depositing User: Symplectic Admin
Date Deposited: 28 Nov 2022 10:07
Last Modified: 08 Jan 2024 03:48
DOI: 10.1259/bjr.20220516
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