Abstract
Objectives: To determine whether quantitative analysis of iodine-enhanced images generated from dual-energy CT (DECT) have added value in distinguishing invasive adenocarcinoma from non-invasive or minimally invasive adenocarcinoma (MIA) showing ground-glass nodule (GGN). Methods: Thirty-four patients with 39 GGNs were enrolled in this prospective study and underwent DECT followed by complete tumour resection. Various quantitative imaging parameters were assessed, including virtual non-contrast (VNC) imaging and iodine-enhanced imaging. Results: Of all 39 GGNs, four were adenocarcinoma in situ (AIS) (10 %), nine were MIA (23 %), and 26 were invasive adenocarcinoma (67 %). When assessing only VNC imaging, multivariate analysis revealed that mass, uniformity, and size-zone variability were independent predictors of invasive adenocarcinoma (odds ratio [OR] = 19.92, P = 0.02; OR = 0.70, P = 0.01; OR = 16.16, P = 0.04, respectively). After assessing iodine-enhanced imaging with VNC imaging, both mass on the VNC imaging and uniformity on the iodine-enhanced imaging were independent predictors of invasive adenocarcinoma (OR = 5.51, P = 0.04 and OR = 0.67, P < 0.01). The power of diagnosing invasive adenocarcinoma was improved after adding the iodine-enhanced imaging parameters versus VNC imaging alone, from 0.888 to 0.959, respectively (P = 0.029). Conclusion: Quantitative analysis using iodine-enhanced imaging metrics versus VNC imaging metrics alone generated from DECT have added value in distinguishing invasive adenocarcinoma from AIS or MIA. Key Points: • Quantitative analysis using DECT was used to distinguish invasive adenocarcinoma. • Tumour mass and uniformity were independent predictors of invasive adenocarcinoma. • Diagnostic performance was improved after adding iodine parameters to VNC parameters.
| Original language | English |
|---|---|
| Pages (from-to) | 43-54 |
| Number of pages | 12 |
| Journal | European Radiology |
| Volume | 26 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Jan 2016 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Dual-energy CT
- Histogram analysis
- Iodine quantification
- Lung adenocarcinoma
- Pure ground glass opacity
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