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Numerical optimization of alignment reproducibility for customizable surgical guides.

Kroes T, Valstar E, Eisemann E - Int J Comput Assist Radiol Surg (2015)

Bottom Line: The proposed optimization technique has been compared to manual optimization by experts, as well as participants with domain experience.Manually optimizing CSG parameters turns out to be a counterintuitive task.Even after training, subjects with and without anatomical background fail in choosing appropriate CSG configurations.

View Article: PubMed Central - PubMed

Affiliation: Computer Graphics and Visualization Group, Department of Intelligent Systems, Delft University of Technology, Mekelweg 4, 2628 CD, Delft, The Netherlands. t.kroes@tudelft.nl.

ABSTRACT

Purpose: Computer-assisted orthopedic surgery aims at minimizing invasiveness, postoperative pain, and morbidity with computer-assisted preoperative planning and intra-operative guidance techniques, of which camera-based navigation and patient-specific templates (PST) are the most common. PSTs are one-time templates that guide the surgeon initially in cutting slits or drilling holes. This method can be extended to reusable and customizable surgical guides (CSG), which can be adapted to the patients' bone. Determining the right set of CSG input parameters by hand is a challenging task, given the vast amount of input parameter combinations and the complex physical interaction between the PST/CSG and the bone.

Methods: This paper introduces a novel algorithm to solve the problem of choosing the right set of input parameters. Our approach predicts how well a CSG instance is able to reproduce the planned alignment based on a physical simulation and uses a genetic optimization algorithm to determine optimal configurations. We validate our technique with a prototype of a pin-based CSG and nine rapid prototyped distal femora.

Results: The proposed optimization technique has been compared to manual optimization by experts, as well as participants with domain experience. Using the optimization technique, the alignment errors remained within practical boundaries of 1.2 mm translation and [Formula: see text] rotation error. In all cases, the proposed method outperformed manual optimization.

Conclusions: Manually optimizing CSG parameters turns out to be a counterintuitive task. Even after training, subjects with and without anatomical background fail in choosing appropriate CSG configurations. Our optimization algorithm ensures that the CSG is configured correctly, and we could demonstrate that the intended alignment of the CSG is accurately reproduced on all tested bone geometries.

No MeSH data available.


Related in: MedlinePlus

Interface for manually creating a pin-based CSG configuration.  user interface for choosing a pin configuration, in this case, the user can only pick a limited amount of pins because the exposure is limited.  Visualization of the pins on the surface of the cartilage/bone in the planned alignment
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Fig14: Interface for manually creating a pin-based CSG configuration. user interface for choosing a pin configuration, in this case, the user can only pick a limited amount of pins because the exposure is limited. Visualization of the pins on the surface of the cartilage/bone in the planned alignment

Mentions: The manually configured CSGs from Table 3 were generated by nine participants (age 24–62). Participants were divided into three groups: (a) three untrained participants without special a priori knowledge of human anatomy, (b) four medical visualization students with prior anatomical knowledge, but no surgical experience (although one even has a background as a radiology assistant), and (c) two expert orthopedic surgeons (approximately 15 and 30 years of surgical experience). The concept of the pin-based CSG was explained to the participants, stressing the importance of alignment reproducibility and stability of the CSG when docked onto the bone. They were asked to create two pin configurations (based on full and limited exposure) that would optimize the placement of the CSG in its equilibrium state (the smallest translational and rotational error with respect to the planned alignment). To facilitate this task, participants were given the option to use our computer program to set active pins using a mouse and to see the corresponding CSG device in the intended equilibrium state with all active pins in contact with the bone (see Fig. 14). The experiments were performed under no time pressure; each participant could use as much time as wanted and had as many attempts as needed to setup a configuration. Up to ten pins were allowed to be placed on the device, despite the possibility to use less, all participants used all pins. The experiments started with a quick demonstration of an ad hoc configuration and a short explanation of the simple computer program to set and investigate the pin combination. Participants took between one and three minutes to create a pin configuration.


Numerical optimization of alignment reproducibility for customizable surgical guides.

Kroes T, Valstar E, Eisemann E - Int J Comput Assist Radiol Surg (2015)

Interface for manually creating a pin-based CSG configuration.  user interface for choosing a pin configuration, in this case, the user can only pick a limited amount of pins because the exposure is limited.  Visualization of the pins on the surface of the cartilage/bone in the planned alignment
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4591200&req=5

Fig14: Interface for manually creating a pin-based CSG configuration. user interface for choosing a pin configuration, in this case, the user can only pick a limited amount of pins because the exposure is limited. Visualization of the pins on the surface of the cartilage/bone in the planned alignment
Mentions: The manually configured CSGs from Table 3 were generated by nine participants (age 24–62). Participants were divided into three groups: (a) three untrained participants without special a priori knowledge of human anatomy, (b) four medical visualization students with prior anatomical knowledge, but no surgical experience (although one even has a background as a radiology assistant), and (c) two expert orthopedic surgeons (approximately 15 and 30 years of surgical experience). The concept of the pin-based CSG was explained to the participants, stressing the importance of alignment reproducibility and stability of the CSG when docked onto the bone. They were asked to create two pin configurations (based on full and limited exposure) that would optimize the placement of the CSG in its equilibrium state (the smallest translational and rotational error with respect to the planned alignment). To facilitate this task, participants were given the option to use our computer program to set active pins using a mouse and to see the corresponding CSG device in the intended equilibrium state with all active pins in contact with the bone (see Fig. 14). The experiments were performed under no time pressure; each participant could use as much time as wanted and had as many attempts as needed to setup a configuration. Up to ten pins were allowed to be placed on the device, despite the possibility to use less, all participants used all pins. The experiments started with a quick demonstration of an ad hoc configuration and a short explanation of the simple computer program to set and investigate the pin combination. Participants took between one and three minutes to create a pin configuration.

Bottom Line: The proposed optimization technique has been compared to manual optimization by experts, as well as participants with domain experience.Manually optimizing CSG parameters turns out to be a counterintuitive task.Even after training, subjects with and without anatomical background fail in choosing appropriate CSG configurations.

View Article: PubMed Central - PubMed

Affiliation: Computer Graphics and Visualization Group, Department of Intelligent Systems, Delft University of Technology, Mekelweg 4, 2628 CD, Delft, The Netherlands. t.kroes@tudelft.nl.

ABSTRACT

Purpose: Computer-assisted orthopedic surgery aims at minimizing invasiveness, postoperative pain, and morbidity with computer-assisted preoperative planning and intra-operative guidance techniques, of which camera-based navigation and patient-specific templates (PST) are the most common. PSTs are one-time templates that guide the surgeon initially in cutting slits or drilling holes. This method can be extended to reusable and customizable surgical guides (CSG), which can be adapted to the patients' bone. Determining the right set of CSG input parameters by hand is a challenging task, given the vast amount of input parameter combinations and the complex physical interaction between the PST/CSG and the bone.

Methods: This paper introduces a novel algorithm to solve the problem of choosing the right set of input parameters. Our approach predicts how well a CSG instance is able to reproduce the planned alignment based on a physical simulation and uses a genetic optimization algorithm to determine optimal configurations. We validate our technique with a prototype of a pin-based CSG and nine rapid prototyped distal femora.

Results: The proposed optimization technique has been compared to manual optimization by experts, as well as participants with domain experience. Using the optimization technique, the alignment errors remained within practical boundaries of 1.2 mm translation and [Formula: see text] rotation error. In all cases, the proposed method outperformed manual optimization.

Conclusions: Manually optimizing CSG parameters turns out to be a counterintuitive task. Even after training, subjects with and without anatomical background fail in choosing appropriate CSG configurations. Our optimization algorithm ensures that the CSG is configured correctly, and we could demonstrate that the intended alignment of the CSG is accurately reproduced on all tested bone geometries.

No MeSH data available.


Related in: MedlinePlus