Automated brain computed tomographic densitometry of early ischemic changes in acute stroke

Berend C. Stoel*, Henk A. Marquering, Marius Staring, Ludo F. Beenen, Cornelis H. Slump, Yvo B. Roos, Charles B. Majoie

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    17 Citations (Scopus)
    29 Downloads (Pure)

    Abstract

    The Alberta Stroke Program Early CT score (ASPECTS) scoring method is frequently used for quantifying early ischemic changes (EICs) in patients with acute ischemic stroke in clinical studies. Varying interobserver agreement has been reported, however, with limited agreement. Therefore, our goal was to develop and evaluate an automated brain densitometric method. It divides CT scans of the brain into ASPECTS regions using atlas-based segmentation. EICs are quantified by comparing the brain density between contralateral sides. This method was optimized and validated using CT data from 10 and 63 patients, respectively. The automated method was validated against manual ASPECTS, stroke severity at baseline and clinical outcome after 7 to 10 days (NIH Stroke Scale, NIHSS) and 3 months (modified Rankin Scale). Manual and automated ASPECTS showed similar and statistically significant correlations with baseline NIHSS (R=-0.399 and-0.277, respectively) and with follow-up mRS (R=-0.256 and-0.272), except for the follow-up NIHSS. Agreement between automated and consensus ASPECTS reading was similar to the interobserver agreement of manual ASPECTS (differences <1 point in 73% of cases). The automated ASPECTS method could, therefore, be used as a supplementary tool to assist manual scoring.

    Original languageEnglish
    Article number014004
    Number of pages11
    JournalJournal of medical imaging
    Volume2
    Issue number1
    DOIs
    Publication statusPublished - 1 Jan 2015

    Keywords

    • ASPECTS scoring
    • Computed tomography
    • Densitometry
    • Image processing
    • Stroke

    Fingerprint Dive into the research topics of 'Automated brain computed tomographic densitometry of early ischemic changes in acute stroke'. Together they form a unique fingerprint.

    Cite this