Computed tomography depiction of small pediatric vessels with model-based iterative reconstruction

Computed tomography (CT) is extremely important in characterizing blood vessel anatomy and vascular lesions in children. Recent advances in CT reconstruction technology hold promise for improved image quality and also reductions in radiation dose. This report evaluates potential improvements in image quality for the depiction of small pediatric vessels with model-based iterative reconstruction (Veo trademark), a technique developed to improve image quality and reduce noise. To evaluate Veo trademark as an improved method when compared to adaptive statistical iterative reconstruction (ASIR trademark) for the depiction of small vessels on pediatric CT. Seventeen patients (mean age: 3.4 years, range: 2 days to 10.0 years; 6 girls, 11 boys) underwent contrast-enhanced CT examinations of the chest and abdomen in this HIPAA compliant and institutional review board approved study. Raw data were reconstructed into separate image datasets using Veo trademark and ASIR trademark algorithms (GE Medical Systems, Milwaukee, WI). Four blinded radiologists subjectively evaluated image quality. The pulmonary, hepatic, splenic and renal arteries were evaluated for the length and number of branches depicted. Datasets were compared with parametric and non-parametric statistical tests. Readers stated a preference for Veo trademark over ASIR trademark images when subjectively evaluating image quality criteria for vessel definition, image noise and resolution of small anatomical structures. The mean image noise in the aorta and fat was significantly less for Veo trademark vs. ASIR trademark reconstructed images. Quantitative measurements of mean vessel lengths and number of branches vessels delineated were significantly different for Veo trademark and ASIR trademark images. Veo trademark consistently showed more of the vessel anatomy: longer vessel length and more branching vessels. When compared to the more established adaptive statistical iterative reconstruction algorithm, model-based iterative reconstruction appears to produce superior images for depiction of small pediatric vessels on computed tomography. (orig.)