Patient specific pointer tool for corrective osteotomy: Quality of symmetry based planning and case study of ulnar reconstruction surgery

Clinical Applications of Three-Dimensional Printing in Upper Extremity Surgery: A Systematic Review

Three-dimensional printing for medical applications in surgery of the upper extremity has gained in popularity as reflected by the increasing number of publications. This systematic review aims to provide an overview of the clinical use of 3D printing in upper extremity surgery.

METHODS

We searched the databases PubMed and Web of Science for clinical studies that described clinical application of 3D printing for upper extremity surgery including trauma and malformations. We evaluated study characteristics, clinical entity, type of clinical application, concerned anatomical structures, reported outcomes, and evidence level.

RESULTS

We finally included 51 publications with a total of 355 patients, of which 12 were clinical studies (evidence level II/III) and 39 case series (evidence level IV/V). The types of clinical applications were for intraoperative templates (33% of a total of 51 studies), body implants (29%), preoperative planning (27%), prostheses (15%), and orthoses (1%). Over two third of studies were linked to trauma-related injuries (67%).

CONCLUSION

The clinical application of 3D printing in upper extremity surgery offers great potential for personalized approaches to aid in individualized perioperative management, improvement of function, and ultimately help to benefit certain aspects in the quality of life.

Evaluation of CT-MR image registration methodologies for 3D preoperative planning of forearm surgeries

Computerized surgical planning for forearm procedures that considers both soft and bony tissue, requires alignment of preoperatively acquired computed tomography (CT) and magnetic resonance (MR) images by image registration. Normalized mutual information (NMI) registration techniques have been researched to improve efficiency and to eliminate the user dependency associated with manual alignment. While successfully applied in various medical fields, the application of NMI registration to images of the forearm, for which the relative pose of the radius and ulna likely differs between CT and MR acquisitions, is yet to be described. To enable the alignment of CT and MR forearm data, we propose an NMI-based registration pipeline, which allows manual steering of the registration algorithm to the desired image subregion and is, thus, applicable to the forearm. Successive automated registration is proposed to enable planning incorporating multiple target anatomical structures such as the radius and ulna. With respect to gold-standard manual registration, the proposed registration methodology achieved mean accuracies of 0.08 ± 0.09 mm (0.01-0.41 mm range) in comparison with 0.28 ± 0.23 mm (0.03-0.99 mm range) associated with a landmark-based registration when tested on 40 patient data sets. Application of the proposed registration pipeline required less than 10 minutes on average compared with 20 minutes required by the landmark-based registration. The clinical feasibility and relevance of the method were tested on two different clinical applications, a forearm tumor resection and radioulnar joint instability analysis, obtaining accurate and robust CT-MR image alignment for both cases.