CT texture analysis of pancreatic cancer

Kumar Sandrasegaran, Yuning Lin, Michael Asare-Sawiri, Tai Taiyini, Mark Tann

Research output: Contribution to journalArticle

27 Scopus citations


Objectives: We investigated the value of CT texture analysis (CTTA) in predicting prognosis of unresectable pancreatic cancer. Methods: Sixty patients with unresectable pancreatic cancers at presentation were enrolled for post-processing with CTTA using commercially available software (TexRAD Ltd, Cambridge, UK). The largest cross-section of the tumour on axial CT was chosen to draw a region-of-interest. CTTA parameters (mean value of positive pixels (MPP), kurtosis, entropy, skewness), arterial and venous invasion, metastatic disease and tumour size were correlated with overall and progression-free survivals. Results: The median overall and progression-free survivals of cohort were 13.3 and 7.8 months, respectively. On multivariate Cox proportional hazard regression analysis, presence of metastatic disease at presentation had the highest association with overall survival (p = 0.003–0.05) and progression-free survival (p < 0.001 to p = 0.004). MPP at medium spatial filter was significantly associated with poor overall survival (p = 0.04). On Kaplan–Meier survival analysis of CTTA parameters at medium spatial filter, MPP of more than 31.625 and kurtosis of more than 0.565 had significantly worse overall survival (p = 0.036 and 0.028, respectively). Conclusions: CTTA features were significantly associated with overall survival in pancreas cancer, particularly in patients with non-metastatic, locally advanced disease. Key Points: • CT texture analysis is easy to perform on contrast-enhanced CT. • CT texture analysis can determine prognosis in patients with unresectable pancreas cancer. • The best predictors of poor prognosis were high kurtosis and MPP.

Original languageEnglish (US)
JournalEuropean Radiology
StateAccepted/In press - Jan 1 2018


  • Neoplasm invasion
  • Neoplasm metastases
  • Pancreas cancer
  • Survival analysis
  • Tomography, X-Ray Computed

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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    Sandrasegaran, K., Lin, Y., Asare-Sawiri, M., Taiyini, T., & Tann, M. (Accepted/In press). CT texture analysis of pancreatic cancer. European Radiology. https://doi.org/10.1007/s00330-018-5662-1