Purpose: To compare predicted and final infarct lesion volumes determined by processing apparent diffusion coefficient (ADC) maps derived at admission diffusion-weighted (DW) magnetic resonance (MR) imaging in patients with acute stroke and to verify that predicted areas of infarct growth reflect at-risk penumbral regions based on recanalization status.
Materials and methods: The French legislation waived the requirement for informed patient consent for the described research, which was based on patient medical files. However, patients and/or their relatives were informed that they could decline to participate in the research. Authors tested a semiautomated proprietary image analysis procedure in 98 patients with middle cerebral artery (MCA) stroke by modeling infarct growth on DW imaging-derived ADC maps. Predicted infarct growth (PIG) areas and predicted infarct volumes were correlated with final observed data. In addition, the effect of MCA recanalization on the correlation between predicted and observed infarct growth volumes was qualitatively assessed.
Results: Predicted and final infarct volumes (rho = 0.828; 95% confidence interval [CI]: 0.753, 0.882; P < .0001) and infarct growth volumes (rho = 0.506; 95% CI: 0.342, 0.640; P < .0001) were significantly correlated. Visual comparative examination revealed satisfactory qualitative consistency between predicted and follow-up lesion masks. In patients without MCA recanalization, PIG did not differ significantly from final observed infarct growth (median PIG obtained with 0.93 ADC ratio cutoff [PIG(ratio)] of 27.1 cm(3) vs median infarct growth of 19.8 cm(3), P = .17). MCA recanalization revealed an overestimation of PIG (median PIG(ratio) of 24.8 cm(3) vs median infarct growth of 12 cm(3), P = .005), suggesting that the PIG area was part of ischemic penumbra.
Conclusion: Data show the feasibility of identifying at-risk ischemic tissue in patients with acute MCA stroke by using semiautomated analysis of ADC maps derived at DW imaging, without intravenous contrast material-enhanced perfusion-weighted imaging.
(c) RSNA, 2008.