The implementation of augmented reality (AR) in image-guided surgery (IGS) can improve surgical interventions by presenting the image data directly on the patient at the correct position and in the actual orientation. This approach can resolve the switching focus problem, which occurs in conventional IGS systems when the surgeon has to look away from the operation field to consult the image data on a 2-dimensional screen. The Microsoft HoloLens, a headmounted AR display, was combined with an optical navigation system to create an AR-based IGS system. Experiments were performed on a phantom model to determine the accuracy of the complete system and to evaluate the effect of adding AR. The results demonstrated a mean Euclidean distance of 2.3 mm with a maximum error of 3.5 mm for the complete system. Adding AR visualization to a conventional system increased the mean error by 1.6 mm. The introduction of AR in IGS was promising. The presented system provided a solution for the switching focus problem and created a more intuitive guidance system. With a further reduction in the error and more research to optimize the visualization, many surgical applications could benefit from the advantages of AR guidance.

Purpose The purpose of this study was to evaluate the clinical accuracy of the fusion of intra-oral scans in cone-beam computed tomography (CBCT) scans using two commercially available software packages. Materials and methods Ten dry human skulls were subjected to structured light scanning, CBCT scanning, and intra-oral scanning. Two commercially available software packages were used to perform fusion of the intra-oral scans in the CBCT scan to create an accurate virtual head model: IPS CaseDesigner® and OrthoAnalyzer™. The structured light scanner was used as a gold standard and was superimposed on the virtual head models, created by IPS CaseDesigner® and OrthoAnalyzer™, using an Iterative Closest Point algorithm. Differences between the positions of the intra-oral scans obtained with the software packages were recorded and expressed in six degrees of freedom as well as the inter- and intra-observer intra-class correlation coefficient. Results The tested software packages, IPS CaseDesigner® and OrthoAnalyzer™, showed a high level of accuracy compared to the gold standard. The accuracy was calculated for all six degrees of freedom. It was noticeable that the accuracy in the cranial/caudal direction was the lowest for IPS CaseDesigner® and OrthoAnalyzer™ in both the maxilla and mandible. The inter- and intra-observer intra-class correlation coefficient showed a high level of agreement between the observers. Clinical relevance IPS CaseDesigner® and OrthoAnalyzer™ are reliable software packages providing an accurate fusion of the intra-oral scan in the CBCT. Both software packages can be used as an accurate fusion tool of the intra-oral scan in the CBCT which provides an accurate basis for 3D virtual planning.

Background In patients with acetabular fractures, the reconstructed three-dimensional (3D) model of the contralateral acetabulum could be used as a mirrored template for the anatomical configuration of the affected joint. This has not been validated. Objective To investigate whether the right and left acetabula, as reconstructed 3D models, are valid mirrored duplicates that can be used as a reference model for the contralateral side. Methods CT scans of twenty patients with unaffected acetabula were used. The symmetry of the generated 3D models was evaluated through: (1) mirroring of the acetabulum; (2) initial rough matching; (3) automatic optimisation of the matching via surface-based matching; (4) calculation of distances between surfaces by evaluating the Euclidean (straight-line) error distance between the closest points between left and right. The percentages of surface points of the left and right acetabulum with a distance smaller than 0.5, 1.0, 1.5 and 2.0 mm were calculated and evaluated, in relation to Matta's criteria, for acetabular fracture reductions. Results The mean distance deviation was less than 0.75 mm in all 40 comparisons. The calculated distances in 90.7% of the surface points of the left and right acetabulum were below the tolerance threshold of 1.0 mm, based on Matta's anatomical reduction criteria, and 98.7% of the surface points scored below Matta's imperfect tolerance threshold of 2.0 mm. Conclusion This study demonstrates 3D reconstructed models of healthy left and right acetabula are highly similar and could potentially be used as mirrored duplicates. The next step will be to investigate these results in patients with reduced acetabular fractures.

Background Passive paramagnetic markers on magnetic resonance imaging (MRI)-compatible endovascular devices induce susceptibility artifacts, enabling MRI-visibility and real-time MRI-guidance. Optimised visibility is crucial for automatic detection and device tracking but depends on MRI technical parameters and marker characteristics. We assessed marker visibility and automatic detection robustness for varying MRI parameters and marker characteristics in a pulsatile flow phantom. Methods Guidewires with varying iron(II,III) oxide nanoparticle (IONP) concentration markers were imaged using gradient-echo (GRE) and balanced steady-state free precession (bSSFP) sequences at 3 T. Furthermore, echo time (TE), slice thickness (ST) and phase encoding direction (PED) were varied. Artifact width was measured and contrast-to-noise ratios were calculated. Marker visibility and image quality were scored by two MRI interventional radiologists. Additionally, a deep learning model for automatic marker detection was trained and the effects of the parameters on detection performance were evaluated. Two-tailed Wilcoxon signed-rank tests were used (significance level, p < 0.05). Results Medan artifact width (IQR) was larger in bSSFP compared to GRE images (12.7 mm (11.0–15.2) versus 8.4 mm (6.5–11.0)) (p < 0.001) and showed a positive relation with TE and IONP concentration. Switching PED and doubling ST had limited effect on artifact width. Image quality assessment scores were higher for GRE compared to bSSFP images. The deep learning model automatically detected the markers. However, the model performance was reduced after adjusting PED, TE, and IONP concentration. Conclusion Marker visibility was sufficient and a large range of artifact sizes was generated by adjusting TE and IONP concentration. Deep learning-based marker detection was feasible but performance decreased for altered MR parameters. These factors should be considered to optimise device visibility and ensure reliable automatic marker detectability in MRI-guided endovascular interventions.

The aim of this study was to evaluate a novel soft tissue-based method to register an intraoral scan (IOS) with a cone beam computed tomography (CBCT) scan. IOS and CBCT data were obtained from eight dentate patients (mean age 21 AE 2 years; three male, five female) and 14 fully edentulous patients (mean age 56 AE 9 years; eight male, six female). An algorithm was developed to create a soft tissue model of the CBCT scan, which allowed a soft tissue-based registration to be performed with the IOS. First, validation was performed on dentate jaws with registration of the palatal mucosal surface and accuracy evaluation at the level of the teeth. Second, fully edentulous jaws were registered using both the palatal and alveolar crest mucosal surfaces. Distance maps were created to measure the method accuracy. The mean registration error was 0.49 AE 0.26 mm for the dentate jaws. Registration of the fully edentulous jaws had a mean error of 0.16 AE 0.08 mm at the palate and 0.16 AE 0.05 mm at the alveolar crest. In conclusion, the high accuracy of this registration method may allow the digital workflow to be optimized when no teeth are available to perform a regular registration procedure.