Texture Analysis in Quantitative MR Imaging

Abstract

The diagnostic potential of texture analysis in quantitative tissue characterisation by MR imaging at 1.5 T was evaluated in the brain of 6 healthy volunteers and in 88 patients with intracranial tumours. Texture images were computed from calculated T1 and T2 parameter images by applying groups of common first-order and second-order grey level statistics. Tissue differentiation in the images was estimated by the presence or absence of significant differences between tissue types. A fine discrimination was obtained between white matter, cortical grey matter, and cerebrospinal fluid in the normal brain, and white matter was readily separated from the tumour lesions. Moreover, separation of solid tumour tissue and peritumoural oedema was suggested for some tumour types. Mutual comparison of all tumour types revealed extensive differences, and even specific tumour differentiation turned out to be successful in some cases of clinical importance. However, no discrimination between benign and malignant tumour growth was possible. Much texture information seems to be contained in MR images, which may prove useful for classification and image segmentation.