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Updated: May 11, 2026

A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia
Published on: September 16, 2017
Efficacy of dual-layer spectral detector computed tomography for detecting early ischemic changes in patients with
Keiichi Honda1, Seitaro Oda2, Daisuke Kondo1
1Department of Radiological Technology, Kumamoto University, Kumamoto, Japan.
Objectives:
This study evaluated the efficacy of dual-layer spectral detector computed tomography (DLCT) for detecting early ischemic changes (EICs) in patients with acute ischemic stroke (AIS), focusing on electron density (ED) and effective atomic number (effective Z) imaging.
Material And Methods:
This retrospective study included 15 patients (mean age: 76.5 ± 9.8 years) with AIS who underwent non-contrast computed tomography (CT) with DLCT and magnetic resonance imaging (MRI) on the same day. Quantitative analysis was performed to compare conventional CT, ED, and effective Z values between the infarcted and contralateral brain regions. Qualitative assessment was conducted by two radiologists using the modified Alberta Stroke Program Early CT Score methodology. Receiver operating characteristic curve analysis was performed to evaluate diagnostic performance, and kappa statistics were used to assess interobserver agreement.
Results:
Significant differences were observed in the conventional CT and ED values (P < 0.01) but not in effective Z values (P = 0.46) between the infarcted and contralateral regions. ED imaging demonstrated superior diagnostic accuracy (area under curve [AUC] = 0.90) compared with conventional 120-kVp CT (AUC = 0.85) and effective Z imaging (AUC = 0.62). Furthermore, interobserver agreement (kappa = 0.71) was better for ED imaging than for conventional 120-kVp CT (kappa = 0.65). Qualitative analysis revealed that ED images showed better agreement with MRI findings and higher interobserver consistency than conventional 120-kVp images.
Conclusion:
Compared with conventional CT, DLCT with ED imaging significantly enhanced detection of EICs in AIS.
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