title: Non-small cell lung cancer: histopathologic correlates for texture parameters at CT.
abstract: OBJECTIVE
  To correlate computed tomographic (CT) texture in non-small cell lung cancer (NSCLC) with histopathologic markers for angiogenesis and hypoxia.
  
  
  METHODS
  The study was institutional review board approved, and informed consent was obtained. Fourteen patients with NSCLC underwent CT prior to intravenous administration of pimonidazole (0.5 g/m(2)), a marker of hypoxia, 24 hours before surgery. Texture was assessed for unenhanced and contrast material-enhanced CT images by using a software algorithm that selectively filters and extracts texture at different anatomic scales (1.0 [fine detail] to 2.5 [coarse features]), with quantification of the standard deviation (SD) of all pixel values and the mean value of positive pixels (MPP) and uniformity of distribution of positive gray-level pixel values (UPP). After surgery, matched tumor sections were stained for angiogenesis (CD34 expression) and for markers of hypoxia (glucose transporter protein 1 [Glut-1] and pimonidazole). The percentage and average intensity of the tumor stained were assessed. A linear mixed-effects model was used to assess the correlations between CT texture and staining intensity.
  
  
  RESULTS
  SD and MPP quantified from medium to coarse texture on contrast-enhanced CT images showed significant associations with the average intensity of tumor staining with pimonidazole (for SD: filter value, 2.5; slope = 0.003; P = .0003). UPP (medium to coarse texture) on unenhanced CT images showed a significant inverse association with tumor Glut-1 expression (filter value, 2.5; slope = -115.13; P = .0008). MPP quantified from medium to coarse texture on both unenhanced and contrast-enhanced CT images showed significant inverse associations with tumor CD34 expression (unenhanced CT: filter value, 1.8; slope = -0.0008; P = .003; contrast-enhanced CT: filter value, 1.8; slope = -0.0006; P = .004).
  
  
  CONCLUSIONS
  Texture parameters derived from CT images of NSCLC have the potential to act as imaging correlates for tumor hypoxia and angiogenesis.
  
  
  BACKGROUND
  http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12112428/-/DC1.
authors.affiliation: Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, University of Sussex, Brighton, England.
authors.forename: Balaji
authors.initials: B
authors.lastname: Ganeshan
authors.forename: Vicky
authors.initials: V
authors.lastname: Goh
authors.forename: Henry C
authors.initials: HC
authors.lastname: Mandeville
authors.forename: Quan Sing
authors.initials: QS
authors.lastname: Ng
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Hoskin
authors.forename: Kenneth A
authors.initials: KA
authors.lastname: Miles
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001706:Biopsy; D002289:Carcinoma, Non-Small-Cell Lung / Q000175:diagnosis*; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000175:diagnosis*; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013223:Statistics as Topic; D014057:Tomography, X-Ray Computed / Q000379:methods*