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

Abstract

BackgroundTumor spatial heterogeneity is an important prognostic factor, which may be reflected in medical imagesMethodsImage texture analysis is an approach of quantifying heterogeneity that may not be appreciated by the naked eye. Different methods can be applied including statistical-, model-, and transform-based methods.ResultsEarly 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.ConclusionThis review provides an overview of the application of texture analysis with different imaging modalities, CT, MRI, and PET, to date and describes the technical challenges that have limited its widespread clinical implementation so far. With further efforts to refine its application, image texture analysis has the potential to develop into a valuable clinical tool for oncologic imaging.Teaching Points• Tumor spatial heterogeneity is an important prognostic factor.• Image texture analysis is an approach of quantifying heterogeneity.• Different methods can be applied, including statistical-, model-, and transform-based methods.• Texture analysis could improve the diagnosis, tumor staging, and therapy response assessment.

Autoclustering of Non-small Cell Lung Carcinoma Subtypes on 18F-FDG PET Using Texture Analysis: A Preliminary Result

“…Histopathological characteristics of tumor may compose the gross texture of the tumor not only on the tissue, but also on the images. Previous researches have investigated the potential of texture analysis in anatomical imaging such as US, CT and MRI, and presented the data supporting the hypothesis that texture features on images can discriminate the tissue types [14][15][16]. Regardless of these successes of texture analysis in anatomical imaging, developments in PET image analysis have been delayed because of its relatively poorer spatial resolution than that of anatomical images.…”

“…Regardless of these successes of texture analysis in anatomical imaging, developments in PET image analysis have been delayed because of its relatively poorer spatial resolution than that of anatomical images. To date, there have been only a few studies investigating the PET texture analysis, and these studies have been localized to prediction of prognosis and evaluation for radiotherapy planning [15]. However, these studies have some ambiguous points about the relationship between textural features and histopathologic characteristics of tumors [17].…”

The precision of textural analysis in 18F-FDG-PET scans of oesophageal cancer

“…There are early reports that textural analysis, an additional tool quantifying intratumoural heterogeneity of 18 FDG-PET tracer uptake, may improve prediction of response and prognosis and it is hypothesised that image heterogeneity may be related to underlying biology and reflect the behaviour of malignant tumours [3][4][5][6][7].…”

Mapping spatial heterogeneity in the tumor microenvironment: a new era for digital pathology

“…We note that other methodologies such as those employing non-invasive imaging are particularly useful for offering measurements of temporal sampling, 3D vasculature and heterogeneity of metastatic tumors. 11,12 Whilst the sensitivity and specificity of imaging techniques have advanced dramatically in recent years, pathology still offers the ability to map genetic and phenotypic aberrations at cellular resolution. Therefore, the focus of this paper is on approaches that offer objective identification and consider the spatial context of individual microenvironmental components in pathological samples.…”