Automatic detection of misleading blood flow values in CT perfusion studies of lung cancer. (April 2016) - Bevilacqua, Alessandro; Barone, Domenico; Malavasi, Silvia; Gavelli, Giampaolo
Abstract : Highlights: CT perfusion (CTp) is a promising technique to assess anti-angiogenic therapies. Patient motion and CTp artefacts prevent reliable quantitative measurements. An adaptive thresholding of goodness-of-fit errors histogram is proposed. Voxels with high fitting errors correspond to vessel, bronchi and artefacts. These misleading voxels are removed and the CTp maps increase their reliability. Abstract: In the oncology field, the anti-angiogenetic therapies aim at inhibiting tumour vascularization, that is the development of new capillary blood vessels in tumours, that allows them to grow and spread and, potentially, to metastasi. Computed tomography perfusion (CTp) is a dynamic contrast-enhanced technique that has emerged in the last few years as a promising approach for earlier assessment of such therapies, and of tumour response, in general, since functional changes precede morphological changes, that take more time to become evident. However several issues, such as patient motion and several types of artefacts, jeopardize quantitative measurements, this preventing CTp to be used in standard clinics. This paper presents an original automatic approach, based on the voxel-based analysis of the time–concentration curves (TCCs), that allows emphasizing those physiological structures, such as vessels, bronchi or artefacts, that could affect the final computation of blood flow perfusion values in CTp studies of lung cancer. The automatic exclusion of these misleading values represents a step towards a quantitative CTp, hence its routine use in clinics.