Computer-aided implant design for the restoration of cranial defects

Neural shape completion for personalized Maxillofacial surgery

In this paper, we investigate the effectiveness of shape completion neural networks as clinical aids in maxillofacial surgery planning. We present a pipeline to apply shape completion networks to automatically reconstruct complete eumorphic 3D meshes starting from a partial input mesh, easily obtained from CT data routinely acquired for surgery planning. Most of the existing works introduced solutions to aid the design of implants for cranioplasty, i.e. all the defects are located in the neurocranium. In this work, we focus on reconstructing defects localized on both neurocranium and splanchnocranium. To this end, we introduce a new dataset, specifically designed for this task, derived from publicly available CT scans and subjected to a comprehensive pre-processing procedure. All the scans in the dataset have been manually cleaned and aligned to a common reference system. In addition, we devised a pre-processing stage to automatically extract point clouds from the scans and enrich them with virtual defects. We experimentally compare several state-of-the-art point cloud completion networks and identify the two most promising models. Finally, expert surgeons evaluated the best-performing network on a clinical case. Our results show how casting the creation of personalized implants as a problem of shape completion is a promising approach for automatizing this complex task.

Creating high-resolution 3D cranial implant geometry using deep learning techniques

Creating a personalized implant for cranioplasty can be costly and aesthetically challenging, particularly for comminuted fractures that affect a wide area. Despite significant advances in deep learning techniques for 2D image completion, generating a 3D shape inpainting remains challenging due to the higher dimensionality and computational demands for 3D skull models. Here, we present a practical deep-learning approach to generate implant geometry from defective 3D skull models created from CT scans. Our proposed 3D reconstruction system comprises two neural networks that produce high-quality implant models suitable for clinical use while reducing training time. The first network repairs low-resolution defective models, while the second network enhances the volumetric resolution of the repaired model. We have tested our method in simulations and real-life surgical practices, producing implants that fit naturally and precisely match defect boundaries, particularly for skull defects above the Frankfort horizontal plane.

Accuracy of Orbital Shape Reconstruction-Comparative Analysis of Errors in Implant Shape Versus Implant Positioning: A Cadaveric Study

INTRODUCTION

Orbital blowout fractures are commonly reconstructed with implants shaped to repair orbital cavity defects, restore ocular position and projection, and correct diplopia. Orbital implant shaping has traditionally been performed manually by surgeons, with more recent use of computer-assisted design (CAD). Accuracy of implant placement is also key to reconstruction. This study compares the placement accuracy of orbital implants, testing the hypothesis that CAD-shaped implants indexed to patient anatomy will better restore orbit geometry compared with manually shaped implants and manually placed implants.

METHODS

The placement accuracy of orbital implants was assessed within a cadaveric blowout fracture model (3 skulls, 6 orbits) via 3-dimensional CT analysis. Defects were repaired with 4 different techniques: manually placed-manually shaped composite (titanium-reinforced porous polyethylene), manually placed CAD composite, indexed placed CAD composite, and indexed placed CAD titanium mesh.

RESULTS

Implant placement accuracy differed significantly with the implant preparation method ( P =0.01). Indexing significantly improved the placement accuracy ( P =0.002). Indexed placed titanium mesh CAD implants (1.42±0.33 mm) were positioned significantly closer to the intact surface versus manually placed-manually shaped composite implants (2.12±0.39 mm).

DISCUSSION

Computer-assisted design implants indexed to patient geometry yielded average errors below the acceptable threshold (2 mm) for enophthalmos and diplopia. This study highlights the importance of adequately indexing CAD-designed implants to patient geometry to ensure accurate orbital reconstructions.

The simplified tailor-made workflows for a 3D slicer-based craniofacial implant design

A specific design of craniofacial implant model is vital and urgent for patients with traumatic head injury. The mirror technique is commonly used for modeling these implants, but it requires the presence of a healthy skull region opposite to the defect. To address this limitation, we propose three processing workflows for modeling craniofacial implants: the mirror method, the baffle planner, and the baffle-based mirror guideline. These workflows are based on extension modules on the 3D Slicer platform and were developed to simplify the modeling process for a variety of craniofacial scenarios. To evaluate the effectiveness of these proposed workflows, we investigated craniofacial CT datasets collected from four accidental cases. The designed implant models were created using the three proposed workflows and compared to reference models created by an experienced neurosurgeon. The spatial properties of the models were evaluated using performance metrics. Our results show that the mirror method is suitable for cases where a healthy skull region can be completely reflected to the defect region. The baffle planner module offers a flexible prototype model that can be fit independently to any defect location, but it requires customized refinement of contour and thickness to fill the missing region seamlessly and relies on the user's experience and expertise. The proposed baffle-based mirror guideline method strengthens the baffle planner method by tracing the mirrored surface. Overall, our study suggests that the three proposed workflows for craniofacial implant modeling simplify the process and can be practically applied to a variety of craniofacial scenarios. These findings have the potential to improve the care of patients with traumatic head injuries and could be used by neurosurgeons and other medical professionals.

CranGAN: Adversarial Point Cloud Reconstruction for patient-specific Cranial Implant Design

Automatizing cranial implant design has become an increasingly important avenue in biomedical research. Benefits in terms of financial resources, time and patient safety necessitate the formulation of an efficient and accurate procedure for the same. This paper attempts to provide a new research direction to this problem, through an adversarial deep learning solution. Specifically, in this work, we present CranGAN - a 3D Conditional Generative Adversarial Network designed to reconstruct a 3D representation of a complete skull given its defective counterpart. A novel solution of employing point cloud representations instead of conventional 3D meshes and voxel grids is proposed. We provide both qualitative and quantitative analysis of our experiments with three separate GAN objectives, and compare the utility of two 3D reconstruction loss functions viz. Hausdorff Distance and Chamfer Distance. We hope that our work inspires further research in this direction. Clinical relevance- This paper establishes a new research direction to assist in automated implant design for cranioplasty.

Adaptive Mechanism for Designing a Personalized Cranial Implant and Its 3D Printing Using PEEK

The rehabilitation of the skull's bones is a difficult process that poses a challenge to the surgical team. Due to the range of design methods and the availability of materials, the main concerns are the implant design and material selection. Mirror-image reconstruction is one of the widely used implant reconstruction techniques, but it is not a feasible option in asymmetrical regions. The ideal design approach and material should result in an implant outcome that is compact, easy to fit, resilient, and provides the perfect aesthetic and functional outcomes irrespective of the location. The design technique for the making of the personalized implant must be easy to use and independent of the defect's position on the skull. As a result, this article proposes a hybrid system that incorporates computer tomography acquisition, an adaptive design (or modeling) scheme, computational analysis, and accuracy assessment. The newly developed hybrid approach aims to obtain ideal cranial implants that are unique to each patient and defect. Polyetheretherketone (PEEK) is chosen to fabricate the implant because it is a viable alternative to titanium implants for personalized implants, and because it is simpler to use, lighter, and sturdy enough to shield the brain. The aesthetic result or the fitting accuracy is adequate, with a maximum deviation of 0.59 mm in the outside direction. The results of the biomechanical analysis demonstrate that the maximum Von Mises stress (8.15 MPa), Von Mises strain (0.002), and deformation (0.18 mm) are all extremely low, and the factor of safety is reasonably high, highlighting the implant's load resistance potential and safety under high loading. Moreover, the time it takes to develop an implant model for any cranial defect using the proposed modeling scheme is very fast, at around one hour. This study illustrates that the utilized 3D reconstruction method and PEEK material would minimize time-consuming alterations while also improving the implant's fit, stability, and strength.

Three-dimensional deep learning to automatically generate cranial implant geometry

We present a 3D deep learning framework that can generate a complete cranial model using a defective one. The Boolean subtraction between these two models generates the geometry of the implant required for surgical reconstruction. There is little or no need for post-processing to eliminate noise in the implant model generated by the proposed approach. The framework can be used to meet the repair needs of cranial imperfections caused by trauma, congenital defects, plastic surgery, or tumor resection. Traditional implant design methods for skull reconstruction rely on the mirror operation. However, these approaches have great limitations when the defect crosses the plane of symmetry or the patient's skull is asymmetrical. The proposed deep learning framework is based on an enhanced three-dimensional autoencoder. Each training sample for the framework is a pair consisting of a cranial model converted from CT images and a corresponding model with simulated defects on it. Our approach can learn the spatial distribution of the upper part of normal cranial bones and use flawed cranial data to predict its complete geometry. Empirical research on simulated defects and actual clinical applications shows that our framework can meet most of the requirements of cranioplasty.

AutoImplant 2020-First MICCAI Challenge on Automatic Cranial Implant Design

The aim of this paper is to provide a comprehensive overview of the MICCAI 2020 AutoImplant Challenge. The approaches and publications submitted and accepted within the challenge will be summarized and reported, highlighting common algorithmic trends and algorithmic diversity. Furthermore, the evaluation results will be presented, compared and discussed in regard to the challenge aim: seeking for low cost, fast and fully automated solutions for cranial implant design. Based on feedback from collaborating neurosurgeons, this paper concludes by stating open issues and post-challenge requirements for intra-operative use. The codes can be found at https://github.com/Jianningli/tmi.

Idealization through interactive modeling and experimental assessment of 3D-printed gyroid for trabecular bone scaffold

Porous scaffolds assisted bone tissue engineering is a viable alternative for reconstruction of large segmental bone defects caused by bone pathologies or trauma. In the current study, we intend to develop trabecular bone scaffolds using gyroid architecture. An interactive modeling framework is developed for the design of three-dimensional gyroid scaffolds using advanced generative tools including K3DSurf, MeshLab, and Netfabb. The suggested modeling approach resulted in uniform and interconnected pores. Subsequently, fused deposition modeling 3D-printing is employed to fabricate the scaffolds using poly lactic acid material. The pores interconnectivity, porosity, and surface finish of the fabricated scaffolds are characterized using micro-computer tomography and scanning electron microscopy. Additionally, to assess the performance of scaffolds as a bone substitute, compression, and in-vitro biocompatibility tests on sterilized scaffolds are conducted. Compression tests reveal mechanical strength in the range of native bone while human adipose-derived mesenchymal stem cells show high proliferation after 72 h of incubation. Based on these results, the fabricated gyroid scaffolds can be said to possess favorable properties for trabecular bone scaffold.

Synthetic skull bone defects for automatic patient-specific craniofacial implant design

Patient-specific craniofacial implants are used to repair skull bone defects after trauma or surgery. Currently, cranial implants are designed and produced by third-party suppliers, which is usually time-consuming and expensive. Recent advances in additive manufacturing made the in-hospital or in-operation-room fabrication of personalized implants feasible. However, the implants are still manufactured by external companies. To facilitate an optimized workflow, fast and automatic implant manufacturing is highly desirable. Data-driven approaches, such as deep learning, show currently great potential towards automatic implant design. However, a considerable amount of data is needed to train such algorithms, which is, especially in the medical domain, often a bottleneck. Therefore, we present CT-imaging data of the craniofacial complex from 24 patients, in which we injected various artificial cranial defects, resulting in 240 data pairs and 240 corresponding implants. Based on this work, automatic implant design and manufacturing processes can be trained. Additionally, the data of this work build a solid base for researchers to work on automatic cranial implant designs.

Measurement(s)	Image Acquisition Matrix Size • Image Slice Thickness • craniofacial region
Technology Type(s)	imaging technique • computed tomography
Sample Characteristic - Organism	Homo sapiens

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13265225

Comparison of complications in cranioplasty with various materials: a systematic review and meta-analysis

Objective: Meta-analysis to evaluate complications in the use of autogenous bone and bone substitutes and to compare bone substitutes, specifically HA, polyetheretherketone (PEEK) and titanium materials.Methods: Search of PubMed, Cochrane, Embase and Google scholar to identify all citations from 2010 to 2019 reporting complications regarding materials used in cranioplasty.Results: 20 of 2266 articles met the inclusion criteria, including a total of 2913 patients. The odds of overall complication were significantly higher in the autogenous bone group (n = 214/644 procedures, 33.2%) than the bone substitute groups (n = 116/436 procedures, 26.7%, CI 1.29-2.35, p < 0.05). In bone substitutes groups, there was no significant difference in overall complication rate between HA and Ti (OR, 1.2; 95% CI, 0.47-3.14, p = 0.69). PEEK has lower overall complication rates (OR, 0.51; 95% CI, 0.30-0.87, p = 0.01) and lower implant exposure rates (OR, 0.17; 95% CI, 0.06-0.53, p = 0.002) than Ti, but there was no significant difference in infection rates and postoperative hematoma rates.Conclusions: Cranioplasty is associated with high overall complication rates with the use of autologous bone grafts compared with bone substitutes. PEEK has a relatively low overall complication rates in substitutes groups, but still high infection rates and postoperative hematoma rates. Thus, autologous bone grafts should only be used selectively, and prospective long-term studies are needed to further refine a better material in cranioplasty.

A review on computer-aided design and manufacturing of patient-specific maxillofacial implants

Introduction: Various prefabricated maxillofacial implants are used in the clinical routine for the surgical treatment of patients. In addition to these prefabricated implants, customized CAD/CAM implants become increasingly important for a more precise replacement of damaged anatomical structures. This paper reviews the design and manufacturing of patient-specific implants for the maxillofacial area.Areas covered: The contribution of this publication is to give a state-of-the-art overview in the usage of customized facial implants. Moreover, it provides future perspectives, including 3D printing technologies, for the manufacturing of patient-individual facial implants that are based on patient's data acquisitions, like Computed Tomography (CT) or Magnetic Resonance Imaging (MRI).Expert opinion: The main target of this review is to present various designing software and 3D manufacturing technologies that have been applied to fabricate facial implants. In doing so, different CAD designing software's are discussed, which are based on various methods and have been implemented and evaluated by researchers. Finally, recent 3D printing technologies that have been applied to manufacture patient-individual implants will be introduced and discussed.

Nanoscale 3D Bioprinting for Osseous Tissue Manufacturing

3D printing, as a driving force of innovation over many areas, brings numerous manufacturing methods together from the macro to nano scales. New revolutionary materials (such as polymeric materials and natural biomaterials) can be produced into unique 3D printed nanostructures. The morphology and functionality of various 3D printing methods as well in vitro and in vivo results of their use towards regenerating bone are discussed in this review. This review further focuses nano scale 3D bioprinting technology for bone tissue engineering, mainly including recent progress in research on technical materials and methods, typical applications, and crucial achievements; explaining the scientific and technical challenges for bone tissue fabrication; and describing micro-nano scale 3D printing application prospects, development directions, and trends for the future for this field to realize its full potential.

Fabrication and Analysis of a Ti6Al4V Implant for Cranial Restoration

A custom made implant is critical in cranioplasty to cushion and restore intracranial anatomy, as well as to recover the appearance and attain cognitive stability in the patient. The utilization of customized titanium alloy implants using three-dimensional (3D) reconstruction technique and fabricated using Electron Beam Melting (EBM) has gained significant recognition in recent years, owing to their convenience and effectiveness. Besides, the conventional technique or the extant practice of transforming the standard plates is unreliable, arduous and tedious. As a result, this work aims to produce a customized cranial implant using 3D reconstruction that is reliable in terms of fitting accuracy, appearance, mechanical strength, and consistent material composition. A well-defined methodology initiating from EBM fabrication to final validation has been outlined in this work. The custom design of the implant was carried out by mirror reconstruction of the skull’s defective region, acquired through computer tomography. The design of the customized implant was then analyzed for mechanical stresses by applying finite element analysis. Consequently, the 3D model of the implant was fabricated from Ti6Al4V ELI powder with a thickness of ≃1.76–2 mm. Different tests were employed to evaluate the bio-mechanical stability and strength of the fabricated customized implant design. A 3D comparison study was performed to ensure there was anatomical accuracy, as well as to maintain gratifying aesthetics. The bio-mechanical analysis results revealed that the maximum Von Mises stress (2.5 MPa), strain distribution (1.49 × 10−4) and deformation (3.26 × 10−6 mm) were significantly low in magnitude, thus proving the implant load resistance ability. The average yield and tensile strengths for the fabricated Ti6Al4V ELI EBM specimen were found to be 825 MPa and 880 MPa, respectively, which were well over the prescribed strength for Ti6Al4V ELI implant material. The hardness study also resulted in an acceptable outcome within the acceptable range of 30–35 HRC. Certainly, the chemical composition of the fabricated EBM specimen was intact as established in EDX analysis. The weight of the cranial implant (128 grams) was also in agreement with substituted defected bone portion, ruling out any stress shielding effect. With the proposed approach, the anatomy of the cranium deformities can be retrieved effectively and efficiently. The implementation of 3D reconstruction techniques can conveniently reduce tedious alterations in the implant design and subsequent errors. It can be a valuable and reliable approach to enhance implant fitting, stability, and strength.

Implementation of a semiautomatic method to design patient-specific instruments for corrective osteotomy of the radius

PURPOSE

3D-printed patient-specific instruments (PSIs), such as surgical guides and implants, show great promise for accurate navigation in surgical correction of post-traumatic deformities of the distal radius. However, existing costs of computer-aided design and manufacturing process prevent everyday surgical use. In this paper, we propose an innovative semiautomatic methodology to streamline the PSIs design.

METHODS

The new method was implemented as an extension of our existing 3D planning software. It facilitates the design of a regular and smooth implant and a companion guide starting from a user-selected surface on the affected bone. We evaluated the software by designing PSIs starting from preoperative virtual 3D plans of five patients previously treated at our institute for corrective osteotomy. We repeated the design for the same cases also with commercially available software, with and without dedicated customization. We measured design time and tracked user activity during the design process of implants, guides and subsequent modifications.

RESULTS

All the designed shapes were considered valid. Median design times ([Formula: see text]) were reduced for implants (([Formula: see text]) = 2.2 min) and guides (([Formula: see text]) = 1.0 min) compared to the standard (([Formula: see text]) = 13 min and ([Formula: see text]) = 8 min) and the partially customized (([Formula: see text]) = 6.5 min and ([Formula: see text]) = 6.0 min) commercially available alternatives. Mouse and keyboard activities were reduced (median count of strokes and clicks during implant design (([Formula: see text]) = 53, and guide design (([Formula: see text]) = 27) compared to using standard software (([Formula: see text]) = 559 and ([Formula: see text]) = 380) and customized commercial software (([Formula: see text]) = 217 and ([Formula: see text]) = 180).

CONCLUSION

Our software solution efficiently streamlines the design of PSIs for distal radius malunion. It represents a first step in making 3D-printed PSIs technology more accessible.

Surgery of complex craniofacial defects: A single-step AM-based methodology

BACKGROUND AND OBJECTIVE

The purpose of the present paper is to pave the road to the systematic optimization of complex craniofacial surgical intervention and to validate a design methodology for the virtual surgery and the fabrication of cranium vault custom plates. Recent advances in the field of medical imaging, image processing and additive manufacturing (AM) have led to new insights in several medical applications. The engineered combination of medical actions and 3D processing steps, foster the optimization of the intervention in terms of operative time and number of sessions needed. Complex craniofacial surgical intervention, such as for instance severe hypertelorism accompanied by skull holes, traditionally requires a first surgery to correctly "resize" the patient cranium and a second surgical session to implant a customized 3D printed prosthesis. Between the two surgical interventions, medical imaging needs to be carried out to aid the design the skull plate. Instead, this paper proposes a CAD/AM-based one-in-all design methodology allowing the surgeons to perform, in a single surgical intervention, both skull correction and implantation.

METHODS

A strategy envisaging a virtual/mock surgery on a CAD/AM model of the patient cranium so as to plan the surgery and to design the final shape of the cranium plaque is proposed. The procedure relies on patient imaging, 3D geometry reconstruction of the defective skull, virtual planning and mock surgery to determine the hypothetical anatomic 3D model and, finally, to skull plate design and 3D printing.

RESULTS

The methodology has been tested on a complex case study. Results demonstrate the feasibility of the proposed approach and a consistent reduction of time and overall cost of the surgery, not to mention the huge benefits on the patient that is subjected to a single surgical operation.

CONCLUSIONS

Despite a number of AM-based methodologies have been proposed for designing cranial implants or to correct orbital hypertelorism, to the best of the authors' knowledge, the present work is the first to simultaneously treat osteotomy and titanium cranium plaque.