Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice?

This review provides an overview of the application of texture analysis with different imaging modalities, computed tomography, magnetic resonance imaging, and positron emission tomography, to date and describes the technical challenges that have limited its widespread clinical implementation so far

Fergus Davnall

2012

Scholarcy highlights

  • Tumor heterogeneityImaging is used widely in oncologic practice for lesion characterization, confirmation of diagnosis, staging, treatment planning, targeting therapy, assessing treatment response, and surveillance
  • Early evidence suggests that texture analysis has the potential to augment diagnosis and characterization as well as improve tumor staging and therapy response assessment in oncological practice
  • This review provides an overview of the application of texture analysis with different imaging modalities, computed tomography, magnetic resonance imaging, and positron emission tomography, to date and describes the technical challenges that have limited its widespread clinical implementation so far
  • This study found that texture analysis was a better predictor of response than current response assessment methods based on size and/or enhancement change
  • This study found that the addition of second-order statistics such as run-length non-uniformity, gray-level non-uniformity, angular second moment, and entropy to the findings from dynamic contrast-enhanced-MRI had 100 % negative predictive value, 79 % positive predictive value, 100 % sensitivity, and 62 % specificity in differentiating malignant glioneuronal tumors from glioblastoma multiforme
  • With further efforts to refine its applications and direct standardization, this technique has the potential to develop into a valuable clinical tool in oncologic imaging in the future

Need more features? Save interactive summary cards to your Scholarcy Library.