title: Application of texture analysis based on apparent diffusion coefficient maps in discriminating different stages of rectal cancer.
abstract: To explore the potential of texture analysis based on apparent diffusion coefficient (ADC) maps, as a predictor of local invasion depth (stage pT1-2 versus pT3-4) and nodal status (pN0 versus pN1-2) of rectal cancer.
  
  
  
  Sixty-eight patients with rectal cancer underwent preoperative magnetic resonance (MR) imaging including diffusion weighted imaging (DWI) at a 3.0 Tesla system. Routine ADC variables (ADCmean, ADCmin, ADCmax), histogram features (skewness, kurtosis) and gray level co-occurrence matrix features (entropy, contrast, correlation) were compared between pT1-2 and pT3-4 stages, between pN0 and pN1-2 stages.
  
  
  
  Skewness, entropy, and contrast were significantly lower in patients with pT1-2 as compared to those with pT3-4 tumors (0.166 versus 0.476, P = 0.015; 3.212 versus 3.441 P = 0.004; 10.773 versus 13.596, P = 0.017). Furthermore, skewness and entropy were identified as independent predictors for extramural invasion of tumors (stage pT3-4). Significant differences were observed between pN0 and pN1-2 tumors with respect to ADCmean(1.152 versus 1.044, P = 0.029), ADCmax(1.692 versus 1.460, P = 0.006) and entropy (3.299 versus 3.486, P = 0.015). ADCmax.and entropy were independent predictors of positive nodal status.
  
  
  
  Texture analysis on ADC maps could provide valuable information in identifying locally advanced rectal cancer.
  
  
  
  3 J. MAGN. RESON. IMAGING 2017;45:1798-1808.
authors.affiliation: Department of Radiology, Shandong Cancer Hospital affiliated to Shandong University, Shandong Academy of Medical Sciences, Jinan, China.|Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
authors.forename: Liheng
authors.initials: L
authors.lastname: Liu
authors.affiliation: Department of Radiology, Shandong Cancer Hospital affiliated to Shandong University, Shandong Academy of Medical Sciences, Jinan, China.
authors.forename: Yuhui
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Department of Radiology, Shandong Cancer Hospital affiliated to Shandong University, Shandong Academy of Medical Sciences, Jinan, China.
authors.forename: Liang
authors.initials: L
authors.lastname: Xu
authors.affiliation: Southeast University, Laboratory of Image Science and Technology, Nanjing, China.
authors.forename: Zhenjiang
authors.initials: Z
authors.lastname: Li
authors.affiliation: Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
authors.forename: Han
authors.initials: H
authors.lastname: Lv
authors.affiliation: Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
authors.forename: Ningning
authors.initials: N
authors.lastname: Dong
authors.affiliation: Department of Radiology, Shandong Cancer Hospital affiliated to Shandong University, Shandong Academy of Medical Sciences, Jinan, China.
authors.forename: Wenwu
authors.initials: W
authors.lastname: Li
authors.affiliation: Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
authors.forename: Zhenghan
authors.initials: Z
authors.lastname: Yang
authors.affiliation: Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
authors.forename: Zhenchang
authors.initials: Z
authors.lastname: Wang
authors.affiliation: Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
authors.forename: Erhu
authors.initials: E
authors.lastname: Jin
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D018450:Disease Progression; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D000069550:Machine Learning; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D010363:Pattern Recognition, Automated / Q000379:methods*; D012004:Rectal Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted
keywords: apparent diffusion coefficient; diffusion-weighted imaging; magnetic resonance imaging; rectal carcinoma; texture analysis