CT texture analysis: Definitions, applications, biologic correlates, and challenges

Meghan G. Lubner, Andrew D. Smith, Kumar Sandrasegaran, Dushyant V. Sahani, Perry J. Pickhardt

Research output: Contribution to journalReview article

97 Citations (Scopus)

Abstract

This review discusses potential oncologic and nononcologic applications of CT texture analysis (CTTA), an emerging area of “radiomics” that extracts, analyzes, and interprets quantitative imaging features. CTTA allows objective assessment of lesion and organ heterogeneity beyond what is possible with subjective visual interpretation and may reflect information about the tissue microenvironment. CTTA has shown promise in lesion characterization, such as differentiating benign from malignant or more biologically aggressive lesions. Pretreatment CT texture features are associated with histopathologic correlates such as tumor grade, tumor cellular processes such as hypoxia or angiogenesis, and genetic features such as KRAS or epidermal growth factor receptor (EGFR) mutation status. In addition, and likely as a result, these CT texture features have been linked to prognosis and clinical outcomes in some tumor types. CTTA has also been used to assess response to therapy, with decreases in tumor heterogeneity generally associated with pathologic response and improved outcomes. A variety of nononcologic applications of CTTA are emerging, particularly quantifying fibrosis in the liver and lung. Although CTTA seems to be a promising imaging biomarker, there is marked variability in methods, parameters reported, and strength of associations with biologic correlates. Before CTTA can be considered for widespread clinical implementation, standardization of tumor segmentation and measurement techniques, image filtration and postprocessing techniques, and methods for mathematically handling multiple tumors and time points is needed, in addition to identification of key texture parameters among hundreds of potential candidates, continued investigation and external validation of histopathologic correlates, and structured reporting of findings.

Original languageEnglish (US)
Pages (from-to)1483-1503
Number of pages21
JournalRadiographics
Volume37
Issue number5
DOIs
StatePublished - Jan 1 2017

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Neoplasms
Epidermal Growth Factor Receptor
Liver Cirrhosis
Biomarkers
Lung
Mutation
Therapeutics
Hypoxia

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

CT texture analysis : Definitions, applications, biologic correlates, and challenges. / Lubner, Meghan G.; Smith, Andrew D.; Sandrasegaran, Kumar; Sahani, Dushyant V.; Pickhardt, Perry J.

In: Radiographics, Vol. 37, No. 5, 01.01.2017, p. 1483-1503.

Research output: Contribution to journalReview article

Lubner, Meghan G. ; Smith, Andrew D. ; Sandrasegaran, Kumar ; Sahani, Dushyant V. ; Pickhardt, Perry J. / CT texture analysis : Definitions, applications, biologic correlates, and challenges. In: Radiographics. 2017 ; Vol. 37, No. 5. pp. 1483-1503.
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