Abstract WP55: Through Thick and Thin: Improved Aspects Grading and Dense Vessel Detection Using Simple Ncct Post-processing

• Published in: Stroke (1970) Vol. 48; no. suppl_1
• Main Authors: Evans, James W, Dey, Sadanand, Eesa, Muneer, Eswaradass, Prasanna, Lun, Ronda, Horn, MacKenzie, Neweduk, Anneliese, Mcdougall, Brooklyn, Pordeli, Pooneh, Jayaraman, Mahesh V, McTaggart, Ryan A, Najm, Mohamed, Goyal, Mayank, Demchuk, Andrew M, Menon, Bijoy K
• Format: Journal Article
• Language: English
• Published: 01.02.2017
• ISSN: 0039-2499; 1524-4628
• DOI: 10.1161/str.48.suppl_1.wp55

Abstract only Introduction: Assessing Alberta Stroke Program Early CT Score (ASPECTS) and identifying hyperdense arteries on non-contrast CT (NCCT) are important components of decision-making in acute stroke. Conventional practice uses 5mm averaged slice thickness NCCT for interpretation of these features. We have systematically evaluated several post processing techniques on NCCT to determine if there is improved reliability in identification of ASPECTS and hyperdense artery. Methodology: We assessed four post-processing techniques on NCCT namely (1) 5mm averaged thickness (2) Minimum Intensity Projection (mIP) - 5mm thickness (3) thin slices (0.625mm) and (4) Maximum Intensity Projection (MIP) - 5mm thickness (Figure 1). Three raters (student, fellow and expert) independently assessed 100 NCCT scans from the PRoveIT database. All scans were read at four different times 10-14 days apart. At each time-point the post processing modality was changed and the patient order randomized. Information on side of suspected infarction was provided. Raters were asked to score ASPECTS and identify presence of hyperdense artery at each reading. Inter-rater reliability was assessed using Intra-cluster correlation (ICC) for ASPECTS and weighted kappa (wKap) for hyperdense artery. Results: The highest inter-rater reliability was found with the MIP technique (ICC 0.42; p<0.001), followed by 5 mm average, mIP and thin slice respectively (ICC 0.33, 0.32, 0.20; all p<0.01). Highest agreement for hyperdense vessel detection was noted with thin slice (wKap 0.30; p<0.001) followed by Average, MIPs and mIPs respectively (wKap 0.25, 0.18, 0.13; all p <0.05). Conclusion: The use of MIP images for ASPECTS grading and thin images for hyperdense vessel detection improves reliability on NCCT. These simple processing steps are easily available on any modern scanner and may help improve patient care.