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K. Hata
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MINI 36 - Imaging and Diagnostic Workup (ID 163)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Screening and Early Detection
- Presentations: 1
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MINI36.01 - Three-Dimensional Quantitative Computed Tomography Evaluation of Pulmonary Adenocarcinoma Using Image-Analysis Software (ID 772)
18:30 - 18:35 | Author(s): K. Hata
- Abstract
Background:
Several 2-dimensional computed tomography (CT)-based evaluation methods of small-sized lung adenocarcinomas have been reported as predictors of the disease invasiveness. They include the ratio of the maximum diameter of consolidation to the maximum entire tumor diameter (C/T ratio), tumor shadow disappearance rate on mediastinal window images (TDR), and visual estimation of the ratio of ground-glass opacity area (GGO-R). However, these measurements can be poorly reproducible due to possible inter-observer discrepancy, and can be unrepresentative because measuring is done only on one section of a lesion. We have developed a 3-dimensional quantitative entire-nodule evaluation method using novel image-analysis software. The aim of this study is to compare the new method to these 2-dimensional evaluation methods as a predictor of small-sized invasive lung adenocarcinomas.
Methods:
There were 101 consecutive patients with clinical stage IA adenocarcinoma of the lung who underwent complete resection between 2002 and 2005 at our institution, excluding patients undergoing preoperative treatment and those with multiple lung nodules or with a past history of other cancers. Of them, 75 had a nodule separated from the chest wall and mediastinum depicted on preoperative thin section CT scan without contrast enhancement, and they were the subject of this study. The reconstruction interval of the CT scans was 0.2mm and the reconstructed slice thickness was 0.5mm. The image analysis software recognizes a nodule as a collection of cubic voxels. Ground glass opacity (GGO) was defined as the area of increased attenuation in the lung with preservation of the bronchial and vascular margins. As the average CT value of pulmonary arteries on non-contrast-enhanced CT was 50 Hounsfield Unit (HU), we measured the percentage of the voxels over 50 HU in a nodule to identify voxels representing solid component, and the percentage was defined as R-50. Invasive cancer was defined as a nodule with pathological lymphatic permeation, vascular invasion or node involvement. The correlation between invasive lung cancer and clinicopathological factors, including the image findings (C/T ratio, TDR, GGO-R and R-50) was evaluated using multivariate analysis. The areas under the curve (AUC) of receiver operating characteristics curves were compared among the image evaluation methods.
Results:
There were 17 invasive cancers. C/T Ratio, TDR, GGO-R and R-50 were independent predictors of invasive lung cancers (p<0.01). R-50 was equivalent in AUC to the other evaluation methods (AUC: R-50, 0.807; C/T Ratio, 0.800; TDR, 0.809; GGO-R, 0.792, respectively).
Conclusion:
Our new 3-dimensional quantitative evaluation method using image-analysis software had invasive cancer predictability similar to the other 2-dimensional evaluation methods. As this method enables entire-tumor evaluation quantitatively and objectively, it should be more reproducible and reliable than the conventional methods.
