Iohexol tracing of hyaluronic acid distribution in the knee joint cavity of rabbits / 南方医科大学学报

<p><b>OBJECTIVE</b>To investigate the distribution of hyaluronic acid (HA) with iohexol tracing in the knee joint cavity of rabbits using CT plain scan, three-dimensional reconstruction and Χ-ray and observe how different injection sites affect HA distribution.</p><p><b>METHODS</b>Mixtures of HA and iohexol (tracer) were prepared that contained final iohexol concentrations of 2.5%, 5%, 10%, 20%, or 40%. The HA-iohexol mixtures (0.5 ml) were injected into rabbit knee joints, and the optimal iohexol concentration that allowed clear differentiation of the injected agents from the surrounding tissues was determined using dual-source CT plain scan and three-dimensional reconstruction technique. The HA-iohexol mixture (0.5 ml) containing the optimal concentration of iohexol was then injected into the knees of the rabbits either through the patella medial approach or the medial joint line approach, and HA distribution in the knee joint cavity was observed using CT scan and Χ-ray.</p><p><b>RESULTS</b>The CT value of HA-iohexol mixture increased progressively with the tracer concentration. After injection of the mixture containing 2.5%, 5%, 10%, 20%, and 40% iohexol, the CT value ratios of the soft tissue, HA-iohexol mixture and bone cortex were 2:7:46, 2:14:44, 2:28:44, 2:60:46, and 2:98:45, respectively, and a iohexol concentration of 5% was determined as optimal for differntiating the injected agents from the surrounding tissues. The HA-iohexol mixutre containing 5% iohexol injected through the medial-patellar approach was distributed mainly over the patello-femoral joint, and that injected through the joint line approach was found mainly over the tibio-femoral joint.</p><p><b>CONCLUSION</b>HA-iohexol mixture containing 5% iohexol allows clear differentiation of bone cortex and soft tissues in rabit knee joint from the injected agents on CT scan and Χ-ray, and the injection approach can influence HA distribution in the knee joint cavity.</p>

Structural analysis based on adaptive window for pulmonary nodule detection / 南方医科大学学报

Radiographic detection of pulmonary nodules based on three-dimensional Hessian matrix is highly sensitive but frequently produces false positive results in areas where blood vessels intersect. We propose a novel approach to pulmonary nodule detection using Hessian matrix-based adaptive window structure analysis, in which the structure coefficients is used to differentiate a voxel that belongs to a nodule or vascular structures, followed by construction of the 3D adaptive window to analyze the local structure characteristics; the nodules were then detected using the discrimination function. The experimental results on pulmonary CT images from 17 patients showed a 100% detection sensitivity for nodules of varying sizes and types, with also significantly reduced false positive results generated by the vessel junctions. This approach provides valuable assistance to follow-up positioning and segmentation of the pulmonary nodules.