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CT texture analysis of pancreatic cancer

  • Gastrointestinal
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

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.

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Abbreviations

CTTA:

CT texture analysis

MPP:

Mean value of positive pixels

NCCN:

National Comprehensive Cancer Network in USA

SSF:

Spatial scaling factor

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Funding

The authors state that this work has not received any funding.

Author information

Authors and Affiliations

  1. Department of Radiology, Indiana University School of Medicine, 550 N. University Blvd., UH 0279, Indianapolis, IN, 46202, USA

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

  2. Department of Medical Imaging, Fuzhou General Hospital, Fuzhou, China

    Yuning Lin

  3. Hope Radiation Cancer, Panama City, FL, USA

    Michael Asare-Sawiri

Authors
  1. Kumar Sandrasegaran
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  2. Yuning Lin
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  3. Michael Asare-Sawiri
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  4. Tai Taiyini
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  5. Mark Tann
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Corresponding author

Correspondence to Kumar Sandrasegaran.

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Guarantor

The scientific guarantor of this publication is Kumaresan Sandrasegaran, M.D.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

A professor of Biostatistics (Dr Yan Tong, PhD) was consulted for specialist advice.

Informed consent

Written informed consent was waived by the institutional review board.

Ethical approval

Institutional review board approval was obtained.

Methodology

• Retrospective

• Case-control study

• Performed at one institution

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Sandrasegaran, K., Lin, Y., Asare-Sawiri, M. et al. CT texture analysis of pancreatic cancer. Eur Radiol 29, 1067–1073 (2019). https://doi.org/10.1007/s00330-018-5662-1

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  • DOI: https://doi.org/10.1007/s00330-018-5662-1

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