• Title of article

    Can visual assessment of blood flow patterns by dynamic contrast-enhanced computed tomography distinguish between malignant and benign lung tumors?

  • Author/Authors

    Walbom Harders, Stefan Department of Radiology - The Regional Hospital in Horsens, Denmark , Madsen, Hans Henrik Department of Radiology - Aarhus University Hospital, Denmark , Nellemann, Hanne Marie Department of Radiology - Aarhus University Hospital, Denmark , Rasmussen, Torben Riis Department of Respiratory Medicine and Allergy - Aarhus University Hospital, Denmark , Thygesen, Jesper Department of Medical Engineering - Aarhus University Hospital, Denmark , Hager, Henrik Department of Pathology - Aarhus University Hospital, Denmark , Andersen, Niels Trolle Department of Biostatistics - Institute of Public Health - Aarhus University, Denmark , Rasmussen, Finn Department of Radiology - Aarhus University Hospital, Denmark

  • Pages
    6
  • From page
    1
  • To page
    6
  • Abstract
    Background Dynamic contrast-enhanced computed tomography (DCE-CT) is a tool, which, in theory, can quantify the blood flow and blood volume of tissues. In structured qualitative analysis, parametric color maps yield a visual impression of the blood flow and blood volume within the tissue being studied, allowing for quick identification of the areas with the highest or lowest blood flow and blood volume. Purpose To examine whether DCE-CT could be used to distinguish between malignant and benign lung tumors in patients with suspected lung cancer. Material and Methods Fifty-nine patients with suspected lung cancer and a lung tumor on their chest radiograph were included for DCE-CT. The tumors were categorized using structured qualitative analysis of tumor blood flow patterns. Histopathology was used as reference standard. Results Using structured qualitative analysis of tumor blood flow patterns, it was possible to distinguish between malignant and benign lung tumors (Fisher–Freeman–Halton exact test, P = 0.022). The inter-reader agreement of this method of analysis was slight to moderate (kappa = 0.30; 95% confidence interval [CI] = 0.13–0.46). Conclusion DCE-CT in suspected lung cancer using structured qualitative analysis of tumor blood flow patterns is accurate as well as somewhat reproducible. However, there are significant limitations to DCE-CT.
  • Keywords
    Lung neoplasms , radiography , perfusion imaging , X-ray computed tomography
  • Journal title
    Acta Radiologica Open
  • Serial Year
    2017
  • Record number

    2619906