Assessment of Heterogeneity Difference Between Edge and Core by Using Texture Analysis: Differentiation of Malignant From Inflammatory Pulmonary Nodules and Masses.
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.



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.



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.



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.
Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No. 160 Pujian Rd, Shanghai 200127, China.
Shiteng
S
Suo
Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No. 160 Pujian Rd, Shanghai 200127, China.
Jiejun
J
Cheng
Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No. 160 Pujian Rd, Shanghai 200127, China.
Mengqiu
M
Cao
Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No. 160 Pujian Rd, Shanghai 200127, China.
Qing
Q
Lu
Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No. 160 Pujian Rd, Shanghai 200127, China.
Yan
Y
Yin
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.
Jianrong
J
Xu
Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, No. 160 Pujian Rd, Shanghai 200127, China. Electronic address: huaweiwu26@163.com.
Huawei
H
Wu
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003287:Contrast Media; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D011856:Radiographic Image Enhancement / Q000379:methods*; D012189:Retrospective Studies; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods*
D003287:Contrast Media
Heterogeneity; contrast-enhanced CT; inflammation; lung cancer; texture analysis