X-ray phase-contrast CT of a pancreatic ductal adenocarcinoma mouse model

PLoS One. 2013;8(3):e58439. doi: 10.1371/journal.pone.0058439. Epub 2013 Mar 11.

Abstract

To explore the potential of grating-based x-ray phase-contrast computed tomography (CT) for preclinical research, a genetically engineered mouse model of pancreatic ductal adenocarcinoma (PDAC) was investigated. One ex-vivo mouse specimen was scanned with different grating-based phase-contrast CT imaging setups covering two different settings: i) high-resolution synchrotron radiation (SR) imaging and ii) dose-reduced imaging using either synchrotron radiation or a conventional x-ray tube source. These experimental settings were chosen to assess the potential of phase-contrast imaging for two different types of application: i) high-performance imaging for virtual microscopy applications and ii) biomedical imaging with increased soft-tissue contrast for in-vivo applications. For validation and as a reference, histological slicing and magnetic resonance imaging (MRI) were performed on the same mouse specimen. For each x-ray imaging setup, attenuation and phase-contrast images were compared visually with regard to contrast in general, and specifically concerning the recognizability of lesions and cancerous tissue. To quantitatively assess contrast, the contrast-to-noise ratios (CNR) of selected regions of interest (ROI) in the attenuation images and the phase images were analyzed and compared. It was found that both for virtual microscopy and for in-vivo applications, there is great potential for phase-contrast imaging: in the SR-based benchmarking data, fine details about tissue composition are accessible in the phase images and the visibility of solid tumor tissue under dose-reduced conditions is markedly superior in the phase images. The present study hence demonstrates improved diagnostic value with phase-contrast CT in a mouse model of a complex endogenous cancer, promoting the use and further development of grating-based phase-contrast CT for biomedical imaging applications.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Carcinoma, Pancreatic Ductal / diagnosis
  • Carcinoma, Pancreatic Ductal / diagnostic imaging*
  • Disease Models, Animal
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging
  • Mice
  • Pancreatic Neoplasms / diagnosis
  • Pancreatic Neoplasms / diagnostic imaging*
  • Radiation Dosage
  • Synchrotrons
  • Tomography, X-Ray Computed / methods*

Grants and funding

This study was supported by the DFG Cluster of Excellence Munich-Centre for Advanced Photonics (MAP), the DFG Gottfried Wilhelm Leibniz program, the European Research Council (ERC, FP7, StG 240142), the French research networks (RTRA) "Digiteo" and "Triangle de la Physique" (grants 2009-034T and 2009-79D), the DFG within the SFB-Initiative 824 "Imaging for Selection, Monitoring and Individualization of Cancer Therapies" (SFB824, project C6, C4, TPZ02). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.