A Complete Digital Workflow for Planning, Simulation, and Evaluation in Orthognathic Surgery.

The purpose of this study was to develop a complete digital workflow for planning, simulation, and evaluation for orthognathic surgery based on 3D digital natural head position reproduction, a cloud-based collaboration platform, and 3D landmark-based evaluation. We included 24 patients who underwent bimaxillary orthognathic surgery. Surgeons and engineers could share the massive image data immediately and conveniently and collaborate closely in surgical planning and simulation using a cloud-based platform. The digital surgical splint could be optimized for a specific patient before or after the physical fabrication of 3D printing splints through close collaboration. The surgical accuracy was evaluated comprehensively via the translational (linear) and rotational (angular) discrepancies between identical 3D landmarks on the simulation and postoperative computed tomography (CT) models. The means of the absolute linear discrepancy at eight tooth landmarks were 0.61 ± 0.55, 0.86 ± 0.68, and 1.00 ± 0.79 mm in left-right, advance-setback, and impaction-elongation directions, respectively, and 1.67 mm in the root mean square direction. The linear discrepancy in the left-right direction was significantly different from the other two directions as shown by analysis of variance (ANOVA, p < 0.05). The means of the absolute angular discrepancies were 1.43 ± 1.06°, 0.50 ± 0.31°, and 0.58 ± 0.41° in the pitch, roll, and yaw orientations, respectively. The angular discrepancy in the pitch orientation was significantly different from the other two orientations (ANOVA, p < 0.05). The complete digital workflow that we developed for orthognathic patients provides efficient and streamlined procedures for orthognathic surgery and shows high surgical accuracy with efficient image data sharing and close collaboration.

Robot-Assisted Maxillary Positioning in Orthognathic Surgery: A Feasibility and Accuracy Evaluation.

Several methods enabling independent repositioning of the maxilla have been introduced to reduce intraoperative errors inherent in the intermediate splint. However, the accuracy is still to be improved and a different approach without time-consuming laboratory process is needed, which can allow perioperative modification of unoptimized maxillary position. The purpose of this study is to assess the feasibility and accuracy of a robot arm combined with intraoperative image-guided navigation in orthognathic surgery. The experiments were performed on 12 full skull phantom models. After Le Fort I osteotomy, the maxillary segment was repositioned to a different target position using a robot arm and image-guided navigation and stabilized. Using the navigation and the postoperative computed tomography (CT) images, the achieved maxillary position was compared with the planned position. Although the maxilla showed mild displacement during the fixation, the mean absolute deviations from the target position were 0.16 mm, 0.18 mm, and 0.20 mm in medio-lateral, antero-posterior, and supero-inferior directions, respectively, in the intraoperative navigation. Compared with the target position using postoperative CT, the achieved maxillary position had a mean absolute deviation of less than 0.5 mm for all dimensions and the mean root mean square deviation was 0.79 mm. The results of this study suggest that the robot arm combined with the intraoperative image-guided navigation may have great potential for surgical plan transfer with the accurate repositioning of the maxilla in the orthognathic surgery.

Real-time augmented model guidance for mandibular proximal segment repositioning in orthognathic surgery, using electromagnetic tracking.

It is essential to reposition the mandibular proximal segment (MPS) as close to its original position as possible during orthognathic surgery. Conventional methods cannot pinpoint the exact position of the condyle in the fossa in real time during repositioning. In this study, based on an improved registration method and a separable electromagnetic tracking tool, we developed a real-time, augmented, model-guided method for MPS surgery to reposition the condyle into its original position more accurately. After virtual surgery planning, using a complex maxillomandibular model, the final position of the virtual MPS model was simulated via 3D rotations. The displacements resulting from the MPS simulation were applied to the MPS landmarks to indicate their final postoperative positions. We designed a new registration body with 24 fiducial points for registration, and determined the optimal point group on the registration body through a phantom study. The registration between the patient's CT image and physical spaces was performed preoperatively using the optimal points. We also developed a separable frame for installing the electromagnetic tracking tool on the patient's MPS. During MPS surgery, the electromagnetic tracking tool was repeatedly attached to, and separated from, the MPS using the separable frame. The MPS movement resulting from the surgeon's manipulation was tracked by the electromagnetic tracking system. The augmented condyle model and its landmarks were visualized continuously in real time with respect to the simulated model and landmarks. Our method also provides augmented 3D coronal and sagittal views of the fossa and condyle, to allow the surgeon to examine the 3D condyle-fossa positional relationship more accurately. The root mean square differences between the simulated and intraoperative MPS models, and between the simulated and postoperative CT models, were 1.71 ± 0.63 mm and 1.89 ± 0.22 mm respectively at three condylar landmarks. Thus, the surgeons could perform MPS repositioning conveniently and accurately based on real-time augmented model guidance on the 3D condyle positional relationship with respect to the glenoid fossa, using augmented and simulated models and landmarks.

Autonomous bone reposition around anatomical landmark for robot-assisted orthognathic surgery.

The purpose of this study was to develop a new method for enabling a robot to assist a surgeon in repositioning a bone segment to accurately transfer a preoperative virtual plan into the intraoperative phase in orthognathic surgery. We developed a robot system consisting of an arm with six degrees of freedom, a robot motion-controller, and a PC. An end-effector at the end of the robot arm transferred the movements of the robot arm to the patient's jawbone. The registration between the robot and CT image spaces was performed completely preoperatively, and the intraoperative registration could be finished using only position changes of the tracking tools at the robot end-effector and the patient's splint. The phantom's maxillomandibular complex (MMC) connected to the robot's end-effector was repositioned autonomously by the robot movements around an anatomical landmark of interest based on the tool center point (TCP) principle. The robot repositioned the MMC around the TCP of the incisor of the maxilla and the pogonion of the mandible following plans for real orthognathic patients. The accuracy of the robot's repositioning increased when an anatomical landmark for the TCP was close to the registration fiducials. In spite of this influence, we could increase the repositioning accuracy at the landmark by using the landmark itself as the TCP. With its ability to incorporate virtual planning using a CT image and autonomously execute the plan around an anatomical landmark of interest, the robot could help surgeons reposition bones more accurately and dexterously.

Virtual skeletal complex model- and landmark-guided orthognathic surgery system.

In this study, correction of the maxillofacial deformities was performed by repositioning bone segments to an appropriate location according to the preoperative planning in orthognathic surgery. The surgery was planned using the patient's virtual skeletal models fused with optically scanned three-dimensional dentition. The virtual maxillomandibular complex (MMC) model of the patient's final occlusal relationship was generated by fusion of the maxillary and mandibular models with scanned occlusion. The final position of the MMC was simulated preoperatively by planning and was used as a goal model for guidance. During surgery, the intraoperative registration was finished immediately using only software processing. For accurate repositioning, the intraoperative MMC model was visualized on the monitor with respect to the simulated MMC model, and the intraoperative positions of multiple landmarks were also visualized on the MMC surface model. The deviation errors between the intraoperative and the final positions of each landmark were visualized quantitatively. As a result, the surgeon could easily recognize the three-dimensional deviation of the intraoperative MMC state from the final goal model without manually applying a pointing tool, and could also quickly determine the amount and direction of further MMC movements needed to reach the goal position. The surgeon could also perform various osteotomies and remove bone interference conveniently, as the maxillary tracking tool could be separated from the MMC. The root mean square (RMS) difference between the preoperative planning and the intraoperative guidance was 1.16 ± 0.34 mm immediately after repositioning. After surgery, the RMS differences between the planning and the postoperative computed tomographic model were 1.31 ± 0.28 mm and 1.74 ± 0.73 mm for the maxillary and mandibular landmarks, respectively. Our method provides accurate and flexible guidance for bimaxillary orthognathic surgery based on intraoperative visualization and quantification of deviations for simulated postoperative MMC and landmarks. The guidance using simulated skeletal models and landmarks can complement and improve conventional navigational surgery for bone repositioning in the craniomaxillofacial area.

An integrated orthognathic surgery system for virtual planning and image-guided transfer without intermediate splint.

Accurate surgical planning and transfer of the planning in orthognathic surgery are very important in achieving a successful surgical outcome with appropriate improvement. Conventionally, the paper surgery is performed based on a 2D cephalometric radiograph, and the results are expressed using cast models and an articulator. We developed an integrated orthognathic surgery system with 3D virtual planning and image-guided transfer. The maxillary surgery of orthognathic patients was planned virtually, and the planning results were transferred to the cast model by image guidance. During virtual planning, the displacement of the reference points was confirmed by the displacement from conventional paper surgery at each procedure. The results of virtual surgery were transferred to the physical cast models directly through image guidance. The root mean square (RMS) difference between virtual surgery and conventional model surgery was 0.75 ± 0.51 mm for 12 patients. The RMS difference between virtual surgery and image-guidance results was 0.78 ± 0.52 mm, which showed no significant difference from the difference of conventional model surgery. The image-guided orthognathic surgery system integrated with virtual planning will replace physical model surgical planning and enable transfer of the virtual planning directly without the need for an intermediate splint.

Material classification of multi-energy CT images using multiple discriminant analysis.

Energy resolved photon-counting detectors could achieve more than one spectral measurement. The goal of this study is to investigate, with experiment, the ability to decompose five materials using energy discriminating detectors and multiple discriminant analysis (MDA). A small field-of-view multi-energy CT system was built. Linear attenuation coefficient was considered as features of multiple energy CT. MDA was used to decompose five materials with six measurements of the energy dependent linear attenuation coefficients. The results of the experimental study showed that a CT system based on CdTe detectors with MDA can be used to decompose five materials.

Radiation dose reduction in CBCT imaging using K-edge filtering and energy weighting.

This paper presents K-edge filtering and energy weighting methods which enhance the contrast with less radiation does. Usually, energy weighting methods are used with photon-counting detector based CT for each energy bin data obtained to enhance the quality of image. However, we used these methods combine with K-edge filtering in energy-integrating detector. Using K-edge filtering, different energy bin data for energy weighting methods were obtained, and then energy weighting factors were calculated to enhance the contrast of image. We report an evaluation of the contrast-to-noise ratio (CNR) of reconstructed image with and without these two methods. This evaluation was proceeded with two phantoms; one is the phantom created personally, and the other is Sendentexct IQ dental CBCT (SENDENTEXCT, EU). As for the phantom created personally, the CNR of images reconstructed with these methods were increased than CNR of standard images. It was seen that 31% to 81% in each energy weighting method for optimizing each material (cortical bone, inner bone, soft tissue, iodine (18.5 g/l), iodine (37 g/l)). In conclusion, we can enhance the contrast of CT images with less radiation dose using K-edge filtering and energy weighting method.