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Differentiating the Invasiveness of Lung Adenocarcinoma Manifesting as Ground Glass Nodules: Combination of Dual-energy CT Parameters and Quantitative-semantic Features.
- Source :
-
Academic radiology [Acad Radiol] 2024 Jul; Vol. 31 (7), pp. 2962-2972. Date of Electronic Publication: 2024 Mar 19. - Publication Year :
- 2024
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Abstract
- Rationale and Objectives: To evaluate the diagnostic performance of dual-energy CT (DECT) parameters and quantitative-semantic features for differentiating the invasiveness of lung adenocarcinoma manifesting as ground glass nodules (GGNs).<br />Materials and Methods: Between June 2022 and September 2023, 69 patients with 74 surgically resected GGNs who underwent DECT examinations were included. CT numbers on virtual monochromatic images were calculated at 40-130 keV generated from DECT. Quantitative morphological measurements and semantic features were evaluated on unenhanced CT images and compared between pathologically confirmed adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA) and invasive lung adenocarcinoma (IAC). Multivariable logistic regression analysis was used to identify independent predictors. The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC) and compared using DeLong's test.<br />Results: Monochromatic CT numbers at 40-130 keV were significantly higher in IAC than in AIS-MIA (all P < 0.05). Multivariate logistic analysis revealed that CT number of 130 keV (odds ratio [OR] = 1.02, P = 0.013), maximum cross-sectional long diameter (OR =1.40, P = 0.014), deep or moderate lobulation sign (OR =19.88, P = 0.005), and abnormal intranodular vessel morphology (OR = 25.57, P = 0.017) were independent predictors of IAC. The combined prediction model showed a favorable differentiation performance with an AUC of 0.966 (95.2% sensitivity, 94.3% specificity, 94.8% accuracy), which was significantly higher than that for each risk factor (AUC = 0.791-0.822, all P < 0.05).<br />Conclusion: A multi-parameter combined prediction model integrating monochromatic CT numbers from DECT and quantitative-semantic features is promising for the preoperative discrimination of IAC and AIS-MIA in GGN-predominant lung adenocarcinoma.<br />Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Chenggong Yan reports financial support was provided by National Natural Science Foundation of China (grant no.82271987). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)
- Subjects :
- Humans
Female
Male
Middle Aged
Aged
Diagnosis, Differential
Retrospective Studies
Adult
Radiography, Dual-Energy Scanned Projection methods
Aged, 80 and over
Sensitivity and Specificity
Tomography, X-Ray Computed methods
Lung Neoplasms diagnostic imaging
Lung Neoplasms pathology
Adenocarcinoma of Lung diagnostic imaging
Adenocarcinoma of Lung pathology
Neoplasm Invasiveness diagnostic imaging
Subjects
Details
- Language :
- English
- ISSN :
- 1878-4046
- Volume :
- 31
- Issue :
- 7
- Database :
- MEDLINE
- Journal :
- Academic radiology
- Publication Type :
- Academic Journal
- Accession number :
- 38508939
- Full Text :
- https://doi.org/10.1016/j.acra.2024.02.011