Computed tomography texture analysis (or CTTA) is a method to obtain new useful biomarkers that provide objective and quantitative assessment of tumor heterogeneity by analyzing the differences and patterns within the pixel values of an image. CTs can be worked with as a matrix of numbers, corresponding to Hounsfield units. Algorithms that perform mathematical operations on these matrices can reveal patterns and characteristics. There are over twenty texture analysis parameters which are standardized in radiomics.
Parameters assessed may include
- grey-level frequency distribution: pixel intensity histograms
- mean intensity, threshold (percentage of pixels within a specified range)
- entropy (irregularity)
- standard deviation
- skewness (asymmetry)
- kurtosis (peakedness/flatness of pixel histogram)
- lesion characterization
- pretreatment tumor assessment
- response evaluation for tumors
- 1. Lubner MG, Smith AD, Sandrasegaran K, Sahani DV, Pickhardt PJ. CT Texture Analysis: Definitions, Applications, Biologic Correlates, and Challenges. Radiographics : a review publication of the Radiological Society of North America, Inc. 37 (5): 1483-1503. doi:10.1148/rg.2017170056 - Pubmed
- 2. Zwanenburg, A., Leger, S., Valli`eres, M. & L¨ock, S. Image biomarker standardisation initiative. eprint arXiv:1612.07003 [cs.CV] (2016).