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Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
Temporal Changes of Texture Features Extracted From Pulmonary Nodules on Dynamic Contrast-Enhanced Chest Computed
Hyungjin Kim1, Chang Min Park, Sang Joon Park
1From the *Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul; †Aerospace Medical Group, Air Force Education and Training Command, Jinju; ‡Cancer Research Institute, Seoul National University, Seoul; and §Armed Forces Seoul Hospital, Seoul, Korea.
Objectives:
The aim of this study was to describe the temporal changes of various texture features extracted from pulmonary nodules on dynamic contrast-enhanced computed tomography (DCE-CT) and to compare the feature values among multiple scanning time points. We also aimed to analyze the variability of texture features across multiple scan delay times.
Materials And Methods:
This retrospective study was approved by the institutional review board of Seoul National University Hospital with waiver of patients' informed consent. Twenty patients (M:F, 6:14; mean age, 60.25 ± 11.97 years) with 20 lung nodules (mean size, 24.1 ± 12.3 mm) underwent DCE-CT with multiple scan delays (30, 60, 90, 120, 150, 180, 210, 240, 300, and 480 seconds) after precontrast scans. Lung nodule segmentation and texture feature extraction were performed at each time point using in-house software. Texture feature values were compared among the multiple time points using the Friedman test with post hoc pairwise Wilcoxon signed rank test. In addition, the dynamic range (DR) reflecting the variability between 2 time points to the interpatient range was calculated. Thereafter, we determined the stable time range that met both "DR greater than 0.90" and "no statistically significant difference" between all time point pairs for each feature. The degree of variability across all scan delay times was obtained using coefficients of variation.
Results:
Standard deviation, variance, entropy, sphericity, discrete compactness, gray-level cooccurrence matrix (GLCM) inverse difference moment (IDM), GLCM contrast, and GLCM entropy did not show significant differences between scan delays of 30 and 180 seconds with DR greater than 0.90 between all time point pairs. When the range was narrowed down to 60 to 150 seconds, an additional 2 values (mean and homogeneity) showed stability. Among the 13 texture features, entropy, sphericity, discrete compactness, and GLCM entropy exhibited the lowest variability (coefficient of variation ≤5%).
Conclusions:
Most texture features exhibited stability with low variation between 60 and 150 seconds on DCE-CT. Thus, texture features extracted from contrast-enhanced CT with a scan delay range of 60 to 150 seconds can be used for tumor characterization despite the heterogeneity in delay time.
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