Iterative Reconstruction Improves Both Objective and Subjective Image Quality in Acute Stroke CTP

Purpose: Computed tomography perfusion (CTP) imaging in acute ischemic stroke (AIS) suffers from measurement errors due to image noise. The purpose of this study was to investigate if iterative reconstruction (IR) algorithms can be used to improve the diagnostic value of standard-dose CTP in AIS. Methods: Twenty-three patients with AIS underwent CTP with standardized protocol and dose. Raw data were reconstructed with filtered back projection (FBP) and IR with intensity levels 3, 4, 5. Image quality was objectively (quantitative perfusion values, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)) and subjectively (overall image quality) assessed. Ischemic core and perfusion mismatch were visually rated. Discriminative power for tissue outcome prediction was determined by the area under the receiver operating characteristic curve (AUC) resulting from the overlap between follow-up infarct lesions and stepwise thresholded CTP maps. Results: With increasing levels of IR, objective image quality (SNR and CNR in white matter and gray matter, elimination of error voxels) and subjective image quality improved. Using IR, mean transit time (MTT) was higher in ischemic lesions, while there was no significant change of cerebral blood volume (CBV) and cerebral blood flow (CBF). Visual assessments of perfusion mismatch changed in 4 patients, while the ischemic core remained constant in all cases. Discriminative power for infarct prediction as represented by AUC was not significantly changed in CBV, but increased in CBF and MTT (mean (95% CI)): 0.72 (0.67–0.76) vs. 0.74 (0.70–0.78) and 0.65 (0.62–0.67) vs 0.67 (0.64–0.70). Conclusion: In acute stroke patients, IR improves objective and subjective image quality when applied to standard-dose CTP. This adds to the overall confidence of CTP in acute stroke triage.