Precision analysis of a quantitative CT liver surface nodularity score.
Purpose: To evaluate precision of a software-based liver surface nodularity (LSN) score derived from CT images.Methods: An anthropomorphic CT phantom was constructed with simulated liver containing smooth and nodular segments at the surface and simulated visceral and subcutaneous fat components. The...
| Published in: | Abdominal Radiology Vol. 43; no. 12; pp. 3307 - 3317 |
|---|---|
| Main Authors: | , , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Published: |
Springer Nature
Dec2018
|
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=132730419&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 132730419 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 2366004X JT14 jtl: Abdominal Radiology issn: 2366004X maglogo: N pubinfo: dt: Dec2018 vid: 43 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 132730419 10.1007/s00261-018-1617-x 132730419 ppf: 3307 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Precision analysis of a quantitative CT liver surface nodularity score. aug: au: Varney, Elliot Zand, Kevin Lewis, Tara Sirous, Reza York, James Florez, Edward Howard-Claudio, Candace M. Roda, Manohar Parker, Ellen Scortegagna, Eduardo Joyner, David Sandlin, David Newsome, Ashley Brewster, Parker Abou Elkassem, Asser Smith, Andrew Lirette, Seth T. Griswold, Michael affil: Department of Radiology, University of Mississippi Medical Center, Jackson, MS, USA sug: ab: Purpose: To evaluate precision of a software-based liver surface nodularity (LSN) score derived from CT images.Methods: An 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.Results: There 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%).Conclusion: The software-based LSN score is a quantitative CT imaging biomarker with excellent repeatability, reproducibility, inter-observer agreement, and test-retest repeatability. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|