Ji Ye Son1, Ho Yun Lee2, Jae-Hun Kim1, Joungho Han3, Ji Yun Jeong3,4, Kyung Soo Lee1, O Jung Kwon5, Young Mog Shim6. 1. Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-gu, Seoul, 135-710, Korea. 2. Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-gu, Seoul, 135-710, Korea. hoyunlee96@gmail.com. 3. Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 135-710, Korea. 4. Department of Pathology, Kyungpook National University Medical Center, Kyungpook National University School of Medicine, Daegu, 702-210, Korea. 5. Division of Respiratory and Critical Medicine of the Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 135-710, Korea. 6. Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-gu, Seoul, 135-710, Korea. youngmog.shim@samsung.com.
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.
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.
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