• Abdom Radiol (NY) · Dec 2018

    Precision analysis of a quantitative CT liver surface nodularity score.

    • Andrew Smith, Elliot Varney, Kevin Zand, Tara Lewis, Reza Sirous, James York, Edward Florez, Asser Abou Elkassem, Candace M Howard-Claudio, Manohar Roda, Ellen Parker, Eduardo Scortegagna, David Joyner, David Sandlin, Ashley Newsome, Parker Brewster, Seth T Lirette, and Michael Griswold.
    • Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA. andrewdennissmith@uabmc.edu.
    • Abdom Radiol (NY). 2018 Dec 1; 43 (12): 3307-3316.

    PurposeTo evaluate precision of a software-based liver surface nodularity (LSN) score derived from CT images.MethodsAn anthropomorphic CT phantom was constructed with simulated liver containing smooth and nodular segments at the surface and simulated visceral and subcutaneous fat components. The phantom was scanned multiple times on a single CT scanner with adjustment of image acquisition and reconstruction parameters (N = 34) and on 22 different CT scanners from 4 manufacturers at 12 imaging centers. LSN scores were obtained using a software-based method. Repeatability and reproducibility were evaluated by intraclass correlation (ICC) and coefficient of variation. Using abdominal CT images from 68 patients with various stages of chronic liver disease, inter-observer agreement and test-retest repeatability among 12 readers assessing LSN by software- vs. visual-based scoring methods were evaluated by ICC.ResultsThere was excellent repeatability of LSN scores (ICC:0.79-0.99) using the CT phantom and routine image acquisition and reconstruction parameters (kVp 100-140, mA 200-400, and auto-mA, section thickness 1.25-5.0 mm, field of view 35-50 cm, and smooth or standard kernels). There was excellent reproducibility (smooth ICC: 0.97; 95% CI 0.95, 0.99; CV: 7%; nodular ICC: 0.94; 95% CI 0.89, 0.97; CV: 8%) for LSN scores derived from CT images from 22 different scanners. Inter-observer agreement for the software-based LSN scoring method was excellent (ICC: 0.84; 95% CI 0.79, 0.88; CV: 28%) vs. good for the visual-based method (ICC: 0.61; 95% CI 0.51, 0.69; CV: 43%). Test-retest repeatability for the software-based LSN scoring method was excellent (ICC: 0.82; 95% CI 0.79, 0.84; CV: 12%).ConclusionThe software-based LSN score is a quantitative CT imaging biomarker with excellent repeatability, reproducibility, inter-observer agreement, and test-retest repeatability.

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