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.

Automatic skull defect restoration and cranial implant generation for cranioplasty.

A fast and fully automatic design of 3D printed patient-specific cranial implants is highly desired in cranioplasty - the process to restore a defect on the skull. We formulate skull defect restoration as a 3D volumetric shape completion task, where a partial skull volume is completed automatically. The difference between the completed skull and the partial skull is the restored defect; in other words, the implant that can be used in cranioplasty. To fulfill the task of volumetric shape completion, a fully data-driven approach is proposed. Supervised skull shape learning is performed on a database containing 167 high-resolution healthy skulls. In these skulls, synthetic defects are injected to create training and evaluation data pairs. We propose a patch-based training scheme tailored for dealing with high-resolution and spatially sparse data, which overcomes the disadvantages of conventional patch-based training methods in high-resolution volumetric shape completion tasks. In particular, the conventional patch-based training is applied to images of high resolution and proves to be effective in tasks such as segmentation. However, we demonstrate the limitations of conventional patch-based training for shape completion tasks, where the overall shape distribution of the target has to be learnt, since it cannot be captured efficiently by a sub-volume cropped from the target. Additionally, the standard dense implementation of a convolutional neural network tends to perform poorly on sparse data, such as the skull, which has a low voxel occupancy rate. Our proposed training scheme encourages a convolutional neural network to learn from the high-resolution and spatially sparse data. In our study, we show that our deep learning models, trained on healthy skulls with synthetic defects, can be transferred directly to craniotomy skulls with real defects of greater irregularity, and the results show promise for clinical use. Project page: https://github.com/Jianningli/MIA.

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.

Cell Morphology on Poly(methyl methacrylate) Microstructures as Function of Surface Energy.

Whilst the significance of substrate topography as a regulator of cell function is well established, a systematic analysis of the principles underlying this is still unavailable. Here we evaluate the hypothesis that surface energy plays a decisive role in substrate-mediated modulation of cell phenotype by evaluation of cell behaviour on synthetic microstructures exhibiting pronounced differences in surface energy. These microstructures, specifically cubes and walls, were fabricated from a biocompatible base polymer, poly(methyl methacrylate), by variotherm injection molding. The dimensions of the cubes were 1 µm x 1 µm x 1 µm (height x width x length) with a periodicity of 1:1 and 1:5 and the dimensions of the walls 1 µm x 1 µm x 15 mm (height x width x length) with a periodicity of 1:1 and 1:5. Mold inserts were made by lithography and electroplating. The surface energy of the resultant microstructures was determined by static contact angle measurements. Light scanning microscopy of the morphology of NT2/D1 and MC3T3-E1 preosteoblast cells cultured on structured PMMA samples in both cases revealed a profound surface energy dependence. "Walls" appeared to promote significant cell elongation, whilst a lack of cell adhesion was observed on "cubes" with the lowest periodicity. Contact angle measurements on walls revealed enhanced surface energy anisotropy (55 mN/m max., 10 mN/m min.) causing a lengthwise spreading of the test liquid droplet, similar to cell elongation. Surface energy measurements for cubes revealed increased isotropic hydrophobicity (87° max., H2O). A critical water contact angle of ≤ 80° appears to be necessary for adequate cell adhesion. A "switch" for cell adhesion and subsequently cell growth could therefore be applied by, for example, adjusting the periodicity of hydrophobic structures. In summary cell elongation on walls and a critical surface energy level for cell adhesion could be produced for NT2/D1 and MC3T3-E1 cells by symmetrical and asymmetrical energy barrier levels. We, furthermore, propose a water-drop model providing a common physicochemical cause regarding similar cell/droplet geometries and cell adhesion on the investigated microstructures.

A 300 µm Organotypic Bone Slice Culture Model for Temporal Investigation of Endochondral Osteogenesis.

Translational studies to elucidate the response of immature bone to biologic and physical stimuli have been held back by the lack of a viable long-term functional bone explant model. This study attempts to bridge this gap between cell culture and animal model studies. In this study, we describe a methodology to derive a 300 µm organotypic femur slice comprising physiological zones (epiphysis and meta-diaphysis) essential for endochondral bone development. The unique capability of slice culture model incorporating enhanced nutrient access to distinct bone tissue components associated with linear bone growth facilitates the investigation of the orchestrated cellular transition of chondrogenic and osteogenic cells involved in endochondral bone development in an ex vivo setup. Bone slices of 300 µm were prepared from 4-day-old postnatal rats and were viable in culture up to 21 days. On days 7 and 15, an increase in chondrogenic and osteogenic modulations was confirmed in epiphysis, metaphysis, and diaphysis. An increase in osteocytes, osteoblasts, and hypertrophic cells were found at these time points, as well as a noticeable increased expression of chondrogenic and osteogenic markers (collagen II, Runx2, and osteocalcin) confirmed endochondral progression. Osteoclast-mediated bone resorption was demonstrated on day 15 by tartrate-resistant acid phosphatase staining. Attenuated total reflection infrared spectroscopic analyses, furthermore, confirmed a time-dependent increase in phosphate levels, bone minerals, and hydroxyapatite for 15 days. Our establishment of a bone slice culture model closely mimicking the in vivo cellular transitions and endochondral microenvironment of a mineralizing bone provides a vital new tool for the elucidation of cellular and endochondral mechanisms of bone development, maturation, and growth plate modulations. The presented model has the potential to be utilized in implementation of preclinical, toxicological, and therapeutic investigations.

MicroRNA-451a overexpression induces accelerated neuronal differentiation of Ntera2/D1 cells and ablation affects neurogenesis in microRNA-451a-/- mice.

MiR-451a is best known for its role in erythropoiesis and for its tumour suppressor features. Here we show a role for miR-451a in neuronal differentiation through analysis of endogenous and ectopically expressed or silenced miR-451a in Ntera2/D1 cells during neuronal differentiation. Furthermore, we compared neuronal differentiation in the dentate gyrus of hippocampus of miR-451a-/- and wild type mice. MiR-451a overexpression in lentiviral transduced Ntera2/D1 cells was associated with a significant shifting of mRNA expression of the developmental markers Nestin, ßIII Tubulin, NF200, DCX and MAP2 to earlier developmental time points, compared to control vector transduced cells. In line with this, accelerated neuronal network formation in AB.G.miR-451a transduced cells, as well as an increase in neurite outgrowth both in number and length was observed. MiR-451a targets genes MIF, AKT1, CAB39, YWHAZ, RAB14, TSC1, OSR1, POU3F2, TNS4, PSMB8, CXCL16, CDKN2D and IL6R were, moreover, either constantly downregulated or exhibited shifted expression profiles in AB.G.miR-451a transduced cells. Lentiviral knockdown of endogenous miR-451a expression in Ntera2/D1 cells resulted in decelerated differentiation. Endogenous miR-451a expression was upregulated during development in the hippocampus of wildtype mice. In situ hybridization revealed intensively stained single cells in the subgranular zone and the hilus of the dentate gyrus of wild type mice, while genetic ablation of miR-451a was observed to promote an imbalance between proliferation and neuronal differentiation in neurogenic brain regions, suggested by Ki67 and DCX staining. Taken together, these results provide strong support for a role of miR-451a in neuronal maturation processes in vitro and in vivo.

Interactive reconstructions of cranial 3D implants under MeVisLab as an alternative to commercial planning software.

In this publication, the interactive planning and reconstruction of cranial 3D Implants under the medical prototyping platform MeVisLab as alternative to commercial planning software is introduced. In doing so, a MeVisLab prototype consisting of a customized data-flow network and an own C++ module was set up. As a result, the Computer-Aided Design (CAD) software prototype guides a user through the whole workflow to generate an implant. Therefore, the workflow begins with loading and mirroring the patients head for an initial curvature of the implant. Then, the user can perform an additional Laplacian smoothing, followed by a Delaunay triangulation. The result is an aesthetic looking and well-fitting 3D implant, which can be stored in a CAD file format, e.g. STereoLithography (STL), for 3D printing. The 3D printed implant can finally be used for an in-depth pre-surgical evaluation or even as a real implant for the patient. In a nutshell, our research and development shows that a customized MeVisLab software prototype can be used as an alternative to complex commercial planning software, which may also not be available in every clinic. Finally, not to conform ourselves directly to available commercial software and look for other options that might improve the workflow.