Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization

Abstract

PurposeTextural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols.Materials and methodsTwenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size.ResultsNo textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases).ConclusionTextural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images.

Hybrid Imaging: Instrumentation and Data Processing

“…Furthermore, the choice and definitions of the textural analysis metrics vary widely and the evaluation techniques differ substantially, thus, rendering a comparison between studies almost impossible [260,297]. The need for standardization efforts in the field of textural analyses has been highlighted previously [260,298,299], and efforts are currently under way to address this challenge [260,[300][301][302].…”

Spatial heterogeneity of oxygenation and haemodynamics in breast cancer resolved in vivo by conical multispectral optoacoustic mesoscopy

“…The possibility of using high-resolution MSOM to analyse tumour heterogeneity may create new opportunities for studying tumour heterogeneity in a more detailed manner. Indeed, MSOM fulfils one set of proposed requirements 49 for analysing three-dimensional variations in tumour properties: high spatial resolution (10-100 μm) and a unique contrast and feature set not available to other imaging modalities. The study suggests the potential of textural measures of spatial heterogeneity such as skewness and kurtosis for image-based analysis of breast cancer.…”

Texture Analysis in Cerebral Gliomas: A Review of the Literature

“…Both Waugh et al 72 and Mayerhoefer et al 13 found spatial resolution to be the most important factor affecting MRTA and that variability in TR/TE, sampling bandwidth, and number of excitations is not significant at higher resolution. However, Molina et al 73 found that several GLCM and GLRLM texture features computed on 3D segmentation of brain gliomas were not robust over different spatial resolution/matrix size and gray-level ranges. They found only entropy to be the most robust feature.…”