Ultrafast cone-beam computed tomography imaging and postprocessing data during image-guided therapeutic practice

Our objective was to evaluate ultrafast cone-beam computed tomography (u-CBCT) image data using cross-sectional images, perfusion blood volume (PBV), and image fusion during tumour detection at the course of transarterial chemoembolization.

One hundred and fifty patients (63 ± 20 years; 33-82) were examined from February to October 2013 with u-CBCT. Tumour delineation and conspicuity were determined using u-CBCT cross-sectional PBV and u-CBCT-magnetic resonance imaging (MRI) fused data sets for hyperenhanced (HYET), heterogeneously enhanced (HEET), and unenhanced (UET) tumour categories. Catheter localisation and tumour feeding vessels were assessed using all data sets. Quantitative and qualitative analyses were performed using appropriate statistical tests.

Qualitative and quantitative tumour delineation showed significant difference (all P < 0.05) among tumour categories. Mean tumour-liver-contrast was higher in HYET than in HEET, and UET; moreover, differences between tumour categories were statistically significant (all P < 0.0001). Fused data showed higher value with statistical significance (P < 0.05) compared with other data sets during catheter localisation and feeding-vessel identification.

Tumour delineation was clearly possible using u-CBCT cross sections with contrast material. PBV uses color-coded images to increase detection and produces good tumour differentiation. Image fusion helps accurately identify tumour and feeding vessels and locate contrast material injection sites and catheter tips without additional data acquisition.

• Ultrafast CBCT cross-sectional data provide good tumour delineation with contrast material • Postprocessed PBV using u-CBCT increased detectability and tumour differentiation • u-CBCT cross-sectional PBV and u-CBCT-MRI data helps image guidance during chemoembolization • u-CBCT-MRI can identify tumours and feeding vessels and locate catheter tip accurately.