Maria Ciolina1, Balaji Ganeshan2, Andrea Laghi1
1 Department of Radiological Sciences, Oncology and Pathology, Sapienza – University of Rome, Polo Pontino, Latina, Italy
2 Institute of Nuclear Medicine, University College London, United Kingdom
Texture analysis is an image-processing algorithm that can be used to quantify tissue heterogeneity based on the distribution of pixel gray-level intensity, coarseness and regularity within an image. Texture analysis was first introduced to medical imaging in 1973, when it was applied to radiographs and, subsequently, to ultrasound (reviewed in ). Only recently has it found new applications in oncologic imaging (e.g. CT, PET, MRI, mammography) where texture is emerging as a possible imaging biomarker, to assess the heterogeneity within a tumor. This essay provides a brief overview of the methodological aspects and clinical utility of texture analysis in oncology.