Diffusion of contrast medium after four different techniques for analgesia of the proximal metacarpal region: an in vivo and in vitro study

REASONS FOR PERFORMING STUDY: There is limited information on potential diffusion of local anaesthetic solution after various diagnostic analgesic techniques of the proximal metacarpal region. OBJECTIVE: To document potential distribution of local anaesthetic solution following 4 techniques used for diagnostic analgesia of the proximal metacarpal region. METHODS: Radiodense contrast medium was injected around the lateral palmar or medial and lateral palmar metacarpal nerves in 8 mature horses, using 4 different techniques. Radiographs were obtained 0, 10 and 20 min after injection and were analysed subjectively. A mixture of radiodense contrast medium and methylene blue was injected into 4 cadaver limbs; the location of the contrast medium and dye was determined by radiography and dissection. RESULTS: Following perineural injection of the palmar metacarpal nerves, most of the contrast medium was distributed in an elongated pattern axial to the second and fourth metacarpal bones. The carpometacarpal joint was inadvertently penetrated in 4/8 limbs after injections of the palmar metacarpal nerves from medial and lateral approaches, and in 1/8 limbs when both injections were performed from the lateral approach. Following perineural injection of the lateral palmar nerve using a lateral approach, the contrast medium was diffusely distributed in all but one limb, in which the carpal sheath was inadvertently penetrated. In 5/8 limbs, following perineural injection of the lateral palmar nerve using a medial approach, the contrast medium diffused proximally to the distal third of the antebrachium. CONCLUSIONS AND POTENTIAL RELEVANCE: Inadvertent penetration of the carpometacarpal joint is common after perineural injection of the palmar metacarpal nerves, but less so if both palmar metacarpal nerves are injected using a lateral approach. Following injection of the lateral palmar nerve using a medial approach, the entire palmar aspect of the carpus may be desensitised.

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.