Shiteng Suo1, Jiejun Cheng1, Mengqiu Cao1, Qing Lu1, Yan Yin1, Jianrong Xu2, Huawei Wu3. 1. Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No. 160 Pujian Rd, Shanghai 200127, China. 2. Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No. 160 Pujian Rd, Shanghai 200127, China. Electronic address: xujianrong_renji@163.com. 3. Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No. 160 Pujian Rd, Shanghai 200127, China. Electronic address: huaweiwu26@163.com.
Abstract
RATIONALE AND OBJECTIVES: This study aimed to test the hypothesis that the heterogeneity difference between edge and core of lesions by using intensity and entropy features obtained from whole-lesion texture analysis on contrast-enhanced computed tomography (CT) may be useful for differentiation of malignant from inflammatory pulmonary nodules and masses. MATERIALS AND METHODS: In all, 48 single pulmonary nodules and masses were retrospectively evaluated. All lesions were histologically or clinically confirmed (malignancy: inflammation = 24:20). We utilized a newly introduced texture analysis method based on contrast-enhanced CT (first described by Grove et al.) that automatically divided the whole lesion volume into two regions: edge and core. Mean attenuation value (AV) and entropy of each region and also the whole lesion were evaluated separately. Each texture metric (absolute value for each region, and difference value defined as difference between edge and core) of malignant and inflammatory lesions were compared using Mann-Whitney U test. Individual image parameters were combined by using linear discriminant analysis. Receiver operating characteristic curves were generated to assess each texture metric and their combination for discriminating between the two entities. RESULTS: Mean AV difference and entropy difference were significantly higher in malignant lesions than in inflammatory lesions (4.71 HU ± 5.06 vs -1.53 HU ± 5.05, P < .001; 0.45 ± 0.23 vs 0.18 ± 0.30, P = .001). Receiver operating characteristic curves for individual mean AV difference and entropy difference provided relatively high values for the area under the curve (0.836 and 0.795, respectively). The combination of mean AV difference, entropy difference, and lesion volume improved the area under the curve to 0.864. CONCLUSION: Heterogeneity difference between edge and core by using whole-lesion texture analysis on contrast-enhanced CT may be a promising tool for estimating the probability of malignancy in pulmonary nodules and masses.
RATIONALE AND OBJECTIVES: This study aimed to test the hypothesis that the heterogeneity difference between edge and core of lesions by using intensity and entropy features obtained from whole-lesion texture analysis on contrast-enhanced computed tomography (CT) may be useful for differentiation of malignant from inflammatory pulmonary nodules and masses. MATERIALS AND METHODS: In all, 48 single pulmonary nodules and masses were retrospectively evaluated. All lesions were histologically or clinically confirmed (malignancy: inflammation = 24:20). We utilized a newly introduced texture analysis method based on contrast-enhanced CT (first described by Grove et al.) that automatically divided the whole lesion volume into two regions: edge and core. Mean attenuation value (AV) and entropy of each region and also the whole lesion were evaluated separately. Each texture metric (absolute value for each region, and difference value defined as difference between edge and core) of malignant and inflammatory lesions were compared using Mann-Whitney U test. Individual image parameters were combined by using linear discriminant analysis. Receiver operating characteristic curves were generated to assess each texture metric and their combination for discriminating between the two entities. RESULTS: Mean AV difference and entropy difference were significantly higher in malignant lesions than in inflammatory lesions (4.71 HU ± 5.06 vs -1.53 HU ± 5.05, P < .001; 0.45 ± 0.23 vs 0.18 ± 0.30, P = .001). Receiver operating characteristic curves for individual mean AV difference and entropy difference provided relatively high values for the area under the curve (0.836 and 0.795, respectively). The combination of mean AV difference, entropy difference, and lesion volume improved the area under the curve to 0.864. CONCLUSION: Heterogeneity difference between edge and core by using whole-lesion texture analysis on contrast-enhanced CT may be a promising tool for estimating the probability of malignancy in pulmonary nodules and masses.
Authors: Damon Kim; Thomas Elgeti; Tobias Penzkofer; Ingo G Steffen; Laura J Jensen; Stefan Schwartz; Bernd Hamm; Sebastian N Nagel Journal: Eur Radiol Date: 2020-08-21 Impact factor: 5.315
Authors: David Molina; Julián Pérez-Beteta; Alicia Martínez-González; Juan Martino; Carlos Velasquez; Estanislao Arana; Víctor M Pérez-García Journal: PLoS One Date: 2017-06-06 Impact factor: 3.240