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

Sex classification of 3D skull images using deep neural networks

Determining the fundamental characteristics that define a face as "feminine" or "masculine" has long fascinated anatomists and plastic surgeons, particularly those involved in aesthetic and gender-affirming surgery. Previous studies in this area have relied on manual measurements, comparative anatomy, and heuristic landmark-based feature extraction. In this study, we collected retrospectively at Cedars Sinai Medical Center (CSMC) a dataset of 98 skull samples, which is the first dataset of this kind of 3D medical imaging. We then evaluated the accuracy of multiple deep learning neural network architectures on sex classification with this dataset. Specifically, we evaluated methods representing three different 3D data modeling approaches: Resnet3D, PointNet++, and MeshNet. Despite the limited number of imaging samples, our testing results show that all three approaches achieve AUC scores above 0.9 after convergence. PointNet++ exhibits the highest accuracy, while MeshNet has the lowest. Our findings suggest that accuracy is not solely dependent on the sparsity of data representation but also on the architecture design, with MeshNet's lower accuracy likely due to the lack of a hierarchical structure for progressive data abstraction. Furthermore, we studied a problem related to sex determination, which is the analysis of the various morphological features that affect sex classification. We proposed and developed a new method based on morphological gradients to visualize features that influence model decision making. The method based on morphological gradients is an alternative to the standard saliency map, and the new method provides better visualization of feature importance. Our study is the first to develop and evaluate deep learning models for analyzing 3D facial skull images to identify imaging feature differences between individuals assigned male or female at birth. These findings may be useful for planning and evaluating craniofacial surgery, particularly gender-affirming procedures, such as facial feminization surgery.

Back to the Roots: Reconstructing Large and Complex Cranial Defects using an Image-based Statistical Shape Model

Designing implants for large and complex cranial defects is a challenging task, even for professional designers. Current efforts on automating the design process focused mainly on convolutional neural networks (CNN), which have produced state-of-the-art results on reconstructing synthetic defects. However, existing CNN-based methods have been difficult to translate to clinical practice in cranioplasty, as their performance on large and complex cranial defects remains unsatisfactory. In this paper, we present a statistical shape model (SSM) built directly on the segmentation masks of the skulls represented as binary voxel occupancy grids and evaluate it on several cranial implant design datasets. Results show that, while CNN-based approaches outperform the SSM on synthetic defects, they are inferior to SSM when it comes to large, complex and real-world defects. Experienced neurosurgeons evaluate the implants generated by the SSM to be feasible for clinical use after minor manual corrections. Datasets and the SSM model are publicly available at https://github.com/Jianningli/ssm .

Application of 3D Printing in Cleft Lip and Palate Repair

This manuscript reviews the transformative impact of 3-dimensional (3D) printing technologies in the treatment and management of cleft lip and palate (CLP), highlighting its application across presurgical planning, surgical training, implantable scaffolds, and postoperative care. By integrating patient-specific data through computer-aided design and manufacturing, 3D printing offers tailored solutions that improve surgical outcomes, reduce operation times, and enhance patient care. The review synthesizes current research findings, technical advancements, and clinical applications, illustrating the potential of 3D printing to revolutionize CLP treatment. Further, it discusses the future directions of combining 3D printing with other innovative technologies like artificial intelligence, 4D printing, and in situ bioprinting for more comprehensive care strategies. This paper underscores the necessity for multidisciplinary collaboration and further research to overcome existing challenges and fully utilize the capabilities of 3D printing in CLP repair.

Interest of a 3D custom-made implant in the reconstruction of bone defects of the cranial vault

The authors report a case of a patient managed for severe cranial vault depression following combined neurosurgery and radiotherapy. This situation caused major aesthetic discomfort and was potentially dangerous due to the mechanical weakness of the bone flap. The authors had a CAD (computer aided design) silicone elastomer custom-made implant made to fill perfectly the depression. Beforehand, an expansion was performed to cover the implant after removal of the radiated skin. The surgery and post-operative course raised no concerns. After one year of follow-up, the result is very good and the patient very satisfied, proving that this technique certainly has its place in the therapeutic arsenal when faced with a tissue defect of the cranial vault.

Combining Patient-specific Implant With Malar Reduction to Repair Mid-facial Asymmetry Caused by Craniofacial Fractures in Asians

Mid-facial asymmetry caused by bone defect or deformation resulted from craniofacial fracture was a common secondary complication needed to repair. Patient-specific implant (PSI) designed with the unaffected side as a template is a good choice to repair this kind of facial asymmetry. However, in Asians, the broad and prominent zygomatic bone in unaffected side is not an optimal template, because the oval facial shape was considered as a more attractive appearance in Asian esthetic concept. To repair the mid-facial asymmetry and to improve the facial contour, the authors combined PSI implantation with malar reduction in one-stage surgery. The authors referred the facial proportion index (the optimal ratio of mid and lower face was 1.27) as a basis for preoperative precise design to determine the ideal facial shape of unaffected side, and used mirror image overlay technique with the ideal shape of unaffected side as a template to design the PSI. With this surgical strategy, patients not only can repair facial asymmetry but also can get a more attractive appearance.

3D Printing Applications for Craniomaxillofacial Reconstruction: A Sweeping Review

The field of craniomaxillofacial (CMF) surgery is rich in pathological diversity and broad in the ages that it treats. Moreover, the CMF skeleton is a complex confluence of sensory organs and hard and soft tissue with load-bearing demands that can change within millimeters. Computer-aided design (CAD) and additive manufacturing (AM) create extraordinary opportunities to repair the infinite array of craniomaxillofacial defects that exist because of the aforementioned circumstances. 3D printed scaffolds have the potential to serve as a comparable if not superior alternative to the "gold standard" autologous graft. In vitro and in vivo studies continue to investigate the optimal 3D printed scaffold design and composition to foster bone regeneration that is suited to the unique biological and mechanical environment of each CMF defect. Furthermore, 3D printed fixation devices serve as a patient-specific alternative to those that are available off-the-shelf with an opportunity to reduce operative time and optimize fit. Similar benefits have been found to apply to 3D printed anatomical models and surgical guides for preoperative or intraoperative use. Creation and implementation of these devices requires extensive preclinical and clinical research, novel manufacturing capabilities, and strict regulatory oversight. Researchers, manufacturers, CMF surgeons, and the United States Food and Drug Administration (FDA) are working in tandem to further the development of such technology within their respective domains, all with a mutual goal to deliver safe, effective, cost-efficient, and patient-specific CMF care. This manuscript reviews FDA regulatory status, 3D printing techniques, biomaterials, and sterilization procedures suitable for 3D printed devices of the craniomaxillofacial skeleton. It also seeks to discuss recent clinical applications, economic feasibility, and future directions of this novel technology. By reviewing the current state of 3D printing in CMF surgery, we hope to gain a better understanding of its impact and in turn identify opportunities to further the development of patient-specific surgical care.

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.

Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the AutoImplant 2021 cranial implant design challenge

Cranial implants are commonly used for surgical repair of craniectomy-induced skull defects. These implants are usually generated offline and may require days to weeks to be available. An automated implant design process combined with onsite manufacturing facilities can guarantee immediate implant availability and avoid secondary intervention. To address this need, the AutoImplant II challenge was organized in conjunction with MICCAI 2021, catering for the unmet clinical and computational requirements of automatic cranial implant design. The first edition of AutoImplant (AutoImplant I, 2020) demonstrated the general capabilities and effectiveness of data-driven approaches, including deep learning, for a skull shape completion task on synthetic defects. The second AutoImplant challenge (i.e., AutoImplant II, 2021) built upon the first by adding real clinical craniectomy cases as well as additional synthetic imaging data. The AutoImplant II challenge consisted of three tracks. Tracks 1 and 3 used skull images with synthetic defects to evaluate the ability of submitted approaches to generate implants that recreate the original skull shape. Track 3 consisted of the data from the first challenge (i.e., 100 cases for training, and 110 for evaluation), and Track 1 provided 570 training and 100 validation cases aimed at evaluating skull shape completion algorithms at diverse defect patterns. Track 2 also made progress over the first challenge by providing 11 clinically defective skulls and evaluating the submitted implant designs on these clinical cases. The submitted designs were evaluated quantitatively against imaging data from post-craniectomy as well as by an experienced neurosurgeon. Submissions to these challenge tasks made substantial progress in addressing issues such as generalizability, computational efficiency, data augmentation, and implant refinement. This paper serves as a comprehensive summary and comparison of the submissions to the AutoImplant II challenge. Codes and models are available at https://github.com/Jianningli/Autoimplant_II.

Bespoke Implants for Cranial Reconstructions: Preoperative to Postoperative Surgery Management System

Traumatic brain injury is a leading cause of death and disability worldwide, with nearly 90% of the deaths coming from low- and middle-income countries. Severe cases of brain injury often require a craniectomy, succeeded by cranioplasty surgery to restore the integrity of the skull for both cerebral protection and cosmetic purposes. The current paper proposes a study on developing and implementing an integrative surgery management system for cranial reconstructions using bespoke implants as an accessible and cost-effective solution. Bespoke cranial implants were designed for three patients and subsequent cranioplasties were performed. Overall dimensional accuracy was evaluated on all three axes and surface roughness was measured with a minimum value of 2.209 μm for Ra on the convex and concave surfaces of the 3D-printed prototype implants. Improvements in patient compliance and quality of life were reported in postoperative evaluations of all patients involved in the study. No complications were registered from both short-term and long-term monitoring. Material and processing costs were lower compared to a metal 3D-printed implants through the usage of readily available tools and materials, such as standardized and regulated bone cement materials, for the manufacturing of the final bespoke cranial implants. Intraoperative times were reduced through the pre-planning management stages, leading to a better implant fit and overall patient satisfaction.

A novel methodology for exact targeting of human and non-human primate brain structures and skull implants using atlas-based 3D reconstruction

BACKGROUND

Accurate targeting of brain areas for stimulation and/or electrophysiological recording is key in many therapeutic applications and basic neuroscience research. Nevertheless, there are currently no end-to-end packages that accommodate all steps required for exact localization, visualization and targeting regions of interest (ROIs) using standard atlases and for designing skull implants.

NEW METHOD

We have implemented a new processing pipeline that addresses this issue in macaques and humans including various preprocessing, registration, warping procedures and 3D reconstructions and provide a noncommercial open-source graphical software which we refer to as the MATLAB-based reconstruction for recording and stimulation (MATres).

RESULTS

The results of skull stripping were shown to work seamlessly in humans and monkeys. Linear and nonlinear warping of the standard atlas to the native space outperformed state-of-the-art using AFNI with improvements being more prominent in humans which had a more complex gyration geometry. The skull surface extracted by MATres using MRI images had more than 90% match with CT ground truth and could be used to design skull implants that conformed well to the skull's local curvature.

COMPARISON WITH EXISTING METHOD(S)

The accuracy of the various steps including skull stripping, standard atlas registration and skull reconstruction in MATres was compared with and shown to outperform the AFNI. The localization accuracy of the recording chambers designed with MATres and implanted in two macaque monkeys was further confirmed using MRI imaging.

CONCLUSIONS

Precise localization of ROIs offered by MATres can be used for planning electrode penetrations for recording and for shallow or deep brain stimulation (DBS).

An optimization approach for studying the effect of lattice unit cell's design-based factors on additively manufactured poly methyl methacrylate cranio-implant

In craniomaxillofacial surgery the inclusion of lattice structure on the Cranio-implants for the surgical procedure of cranial defects is difficult. Additive manufacturing open ups a huge space for the development of intricate profiles for complex surgical practices. Designing lattice structures with various design topologies has gained more interest in the medical community for reducing the weight of the implants in the cranial region. This research proposes the mimicking of cranial defective portion concerning bone-like porous structure by means of Poly methyl methacrylate (PMMA) material via 3D printing technology. The experiments were optimized by incorporating square-type porous lattice structure in the development of cranial implants. The design-based factors of the unit cell were enhanced with the aid of the Design of experiments (DOE) technique. L₉ orthogonal array is developed by incorporating various design-based factors of the lattice unit cell like unit cell size (mm), skewing angle (°), wall thickness (mm), and unit cell orientation (°). The experiments are optimized with respect to obtaining better compressive strength and compressive strength/density of the prepared lattice structure incorporated polymeric samples. The result shows that for obtaining the maximum compressive strength in the porous square lattice-structured PMMA compression samples will be a lower cell size of 2 mm, a higher skewing angle of 30°, a higher wall thickness of 1 mm, and a unit cell orientation of 90°. The experimental optimized condition results of the design-based factors achieve the maximum compressive strength and compressive strength/density of 83.37 MPa and 189.73 MPa/g mm^-3. The lattice structure orientated with 90° has a significant contribution towards reducing the development of structural deviations of incorporating square lattice structure on the PMMA polymeric material. Therefore, the topologically modified square lattice structure incorporated 3D printed PMMA material has a potential scope for the replacement of conventional maxillofacial cranial implants.

Synergy between artificial intelligence and precision medicine for computer-assisted oral and maxillofacial surgical planning

OBJECTIVES

The aim of this review was to investigate the application of artificial intelligence (AI) in maxillofacial computer-assisted surgical planning (CASP) workflows with the discussion of limitations and possible future directions.

MATERIALS AND METHODS

An in-depth search of the literature was undertaken to review articles concerned with the application of AI for segmentation, multimodal image registration, virtual surgical planning (VSP), and three-dimensional (3D) printing steps of the maxillofacial CASP workflows.

RESULTS

The existing AI models were trained to address individual steps of CASP, and no single intelligent workflow was found encompassing all steps of the planning process. Segmentation of dentomaxillofacial tissue from computed tomography (CT)/cone-beam CT imaging was the most commonly explored area which could be applicable in a clinical setting. Nevertheless, a lack of generalizability was the main issue, as the majority of models were trained with the data derived from a single device and imaging protocol which might not offer similar performance when considering other devices. In relation to registration, VSP and 3D printing, the presence of inadequate heterogeneous data limits the automatization of these tasks.

CONCLUSION

The synergy between AI and CASP workflows has the potential to improve the planning precision and efficacy. However, there is a need for future studies with big data before the emergent technology finds application in a real clinical setting.

CLINICAL RELEVANCE

The implementation of AI models in maxillofacial CASP workflows could minimize a surgeon's workload and increase efficiency and consistency of the planning process, meanwhile enhancing the patient-specific predictability.

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.

Three-dimensional technologies in presurgical planning of bone surgeries: current evidence and future perspectives

BACKGROUND

The recent development of three-dimensional (3D) technologies introduces a novel set of opportunities to the medical field in general, and specifically to surgery. The preoperative phase has proven to be a critical factor in surgical success. Utilization of 3D technologies has the potential to improve preoperative planning and overall surgical outcomes. In this narrative review article, the authors describe existing clinical data pertaining to the current use of 3D printing, virtual reality, and augmented reality in the preoperative phase of bone surgery.

METHODS

The methodology included keyword-based literature search in PubMed and Google Scholar for original articles published between 2014 and 2022. After excluding studies performed in nonbone surgery disciplines, data from 61 studies of five different surgical disciplines were processed to be included in this narrative review.

RESULTS

Among the mentioned technologies, 3D printing is currently the most advanced in terms of clinical use, predominantly creating anatomical models and patient-specific instruments that provide high-quality operative preparation. Virtual reality allows to set a surgical plan and to further simulate the procedure via a 2D screen or head mounted display. Augmented reality is found to be useful for surgical simulation upon 3D printed anatomical models or virtual phantoms.

CONCLUSIONS

Overall, 3D technologies are gradually becoming an integral part of a surgeon's preoperative toolbox, allowing for increased surgical accuracy and reduction of operation time, mainly in complex and unique surgical cases. This may eventually lead to improved surgical outcomes, thereby optimizing the personalized surgical approach.

Functional Hydrogels and Their Applications in Craniomaxillofacial Bone Regeneration

Craniomaxillofacial bone defects are characterized by an irregular shape, bacterial and inflammatory environment, aesthetic requirements, and the need for the functional recovery of oral-maxillofacial areas. Conventional clinical treatments are currently unable to achieve high-quality craniomaxillofacial bone regeneration. Hydrogels are a class of multifunctional platforms made of polymers cross-linked with high water content, good biocompatibility, and adjustable physicochemical properties for the intelligent delivery of goods. These characteristics make hydrogel systems a bright prospect for clinical applications in craniomaxillofacial bone. In this review, we briefly demonstrate the properties of hydrogel systems that can come into effect in the field of bone regeneration. In addition, we summarize the hydrogel systems that have been developed for craniomaxillofacial bone regeneration in recent years. Finally, we also discuss the prospects in the field of craniomaxillofacial bone tissue engineering; these discussions can serve as an inspiration for future hydrogel design.

Next-generation personalized cranioplasty treatment

Decompressive craniectomy (DC) is a surgical procedure, that is followed by cranioplasty surgery. DC is usually performed to treat patients with traumatic brain injury, intracranial hemorrhage, cerebral infarction, brain edema, skull fractures, etc. In many published clinical case studies and systematic reviews, cranioplasty surgery is reported to restore cranial symmetry with good cosmetic outcomes and neurophysiologically relevant functional outcomes in hundreds of patients. In this review article, we present a number of key issues related to the manufacturing of patient-specific implants, clinical complications, cosmetic outcomes, and newer alternative therapies. While discussing alternative therapeutic treatments for cranioplasty, biomolecules and cellular-based approaches have been emphasized. The current clinical practices in the restoration of cranial defects involve 3D printing to produce patient-specific prefabricated cranial implants, that provide better cosmetic outcomes. Regardless of the advancements in image processing and 3D printing, the complete clinical procedure is time-consuming and requires significant costs. To reduce manual intervention and to address unmet clinical demands, it has been highlighted that automated implant fabrication by data-driven methods can accelerate the design and manufacturing of patient-specific cranial implants. The data-driven approaches, encompassing artificial intelligence (machine learning/deep learning) and E-platforms, such as publicly accessible clinical databases will lead to the development of the next generation of patient-specific cranial implants, which can provide predictable clinical outcomes. STATEMENT OF SIGNIFICANCE: Cranioplasty is performed to reconstruct cranial defects of patients who have undergone decompressive craniectomy. Cranioplasty surgery improves the aesthetic and functional outcomes of those patients. To meet the clinical demands of cranioplasty surgery, accelerated designing and manufacturing of 3D cranial implants are required. This review provides an overview of biomaterial implants and bone flap manufacturing methods for cranioplasty surgery. In addition, tissue engineering and regenerative medicine-based approaches to reduce clinical complications are also highlighted. The potential use of data-driven computer applications and data-driven artificial intelligence-based approaches are emphasized to accelerate the clinical protocols of cranioplasty treatment with less manual intervention and shorter intraoperative time.

Clinical Applications of Artificial Intelligence-An Updated Overview

Artificial intelligence has the potential to revolutionize modern society in all its aspects. Encouraged by the variety and vast amount of data that can be gathered from patients (e.g., medical images, text, and electronic health records), researchers have recently increased their interest in developing AI solutions for clinical care. Moreover, a diverse repertoire of methods can be chosen towards creating performant models for use in medical applications, ranging from disease prediction, diagnosis, and prognosis to opting for the most appropriate treatment for an individual patient. In this respect, the present paper aims to review the advancements reported at the convergence of AI and clinical care. Thus, this work presents AI clinical applications in a comprehensive manner, discussing the recent literature studies classified according to medical specialties. In addition, the challenges and limitations hindering AI integration in the clinical setting are further pointed out.

Tissue Engineered Neurovascularization Strategies for Craniofacial Tissue Regeneration

Craniofacial tissue injuries, diseases, and defects, including those within bone, dental, and periodontal tissues and salivary glands, impact an estimated 1 billion patients globally. Craniofacial tissue dysfunction significantly reduces quality of life, and successful repair of damaged tissues remains a significant challenge. Blood vessels and nerves are colocalized within craniofacial tissues and act synergistically during tissue regeneration. Therefore, the success of craniofacial regenerative approaches is predicated on successful recruitment, regeneration, or integration of both vascularization and innervation. Tissue engineering strategies have been widely used to encourage vascularization and, more recently, to improve innervation through host tissue recruitment or prevascularization/innervation of engineered tissues. However, current scaffold designs and cell or growth factor delivery approaches often fail to synergistically coordinate both vascularization and innervation to orchestrate successful tissue regeneration. Additionally, tissue engineering approaches are typically investigated separately for vascularization and innervation. Since both tissues act in concert to improve craniofacial tissue regeneration outcomes, a revised approach for development of engineered materials is required. This review aims to provide an overview of neurovascularization in craniofacial tissues and strategies to target either process thus far. Finally, key design principles are described for engineering approaches that will support both vascularization and innervation for successful craniofacial tissue regeneration.

The 3D skull 0-4 years: A validated, generative, statistical shape model

Background

This study aims to capture the 3D shape of the human skull in a healthy paediatric population (0-4 years old) and construct a generative statistical shape model.

Methods

The skull bones of 178 healthy children (55% male, 20.8 ± 12.9 months) were reconstructed from computed tomography (CT) images. 29 anatomical landmarks were placed on the 3D skull reconstructions. Rotation, translation and size were removed, and all skull meshes were placed in dense correspondence using a dimensionless skull mesh template and a non-rigid iterative closest point algorithm. A 3D morphable model (3DMM) was created using principal component analysis, and intrinsically and geometrically validated with anthropometric measurements. Synthetic skull instances were generated exploiting the 3DMM and validated by comparison of the anthropometric measurements with the selected input population.

Results

The 3DMM of the paediatric skull 0-4 years was successfully constructed. The model was reasonably compact - 90% of the model shape variance was captured within the first 10 principal components. The generalisation error, quantifying the ability of the 3DMM to represent shape instances not encountered during training, was 0.47 mm when all model components were used. The specificity value was <0.7 mm demonstrating that novel skull instances generated by the model are realistic. The 3DMM mean shape was representative of the selected population (differences <2%). Overall, good agreement was observed in the anthropometric measures extracted from the selected population, and compared to normative literature data (max difference in the intertemporal distance) and to the synthetic generated cases.

Conclusion

This study presents a reliable statistical shape model of the paediatric skull 0-4 years that adheres to known skull morphometric measures, can accurately represent unseen skull samples not used during model construction and can generate novel realistic skull instances, thus presenting a solution to limited availability of normative data in this field.

MUG500+: Database of 500 high-resolution healthy human skulls and 29 craniotomy skulls and implants

In this article, we present a skull database containing 500 healthy skulls segmented from high-resolution head computed-tomography (CT) scans and 29 defective skulls segmented from craniotomy head CTs. Each healthy skull contains the complete anatomical structures of human skulls, including the cranial bones, facial bones and other subtle structures. For each craniotomy skull, a part of the cranial bone is missing, leaving a defect on the skull. The defects have various sizes, shapes and positions, depending on the specific pathological conditions of each patient. Along with each craniotomy skull, a cranial implant, which is designed manually by an expert and can fit with the defect, is provided. Considering the large volume of the healthy skull collection, the dataset can be used to study the geometry/shape variabilities of human skulls and create a robust statistical model of the shape of human skulls, which can be used for various tasks such as cranial implant design. The craniotomy collection can serve as an evaluation set for automatic cranial implant design algorithms.