583 research outputs found

    Additively manufactured versus conventionally pressed cranioplasty implants: An accuracy comparison

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    This article compared the accuracy of producing patient-specific cranioplasty implants using four different approaches. Benchmark geometry was designed to represent a cranium and a defect added simulating a craniectomy. An ‘ideal’ contour reconstruction was calculated and compared against reconstructions resulting from the four approaches –‘conventional’, ‘semi-digital’, ‘digital – non-automated’ and ‘digital – semi-automated’. The ‘conventional’ approach relied on hand carving a reconstruction, turning this into a press tool, and pressing titanium sheet. This approach is common in the UK National Health Service. The ‘semi-digital’ approach removed the hand-carving element. Both of the ‘digital’ approaches utilised additive manufacturing to produce the end-use implant. The geometries were designed using a non-specialised computer-aided design software and a semi-automated cranioplasty implant-specific computer-aided design software. It was found that all plates were clinically acceptable and that the digitally designed and additive manufacturing plates were as accurate as the conventional implants. There were no significant differences between the additive manufacturing plates designed using non-specialised computer-aided design software and those designed using the semi-automated tool. The semi-automated software and additive manufacturing production process were capable of producing cranioplasty implants of similar accuracy to multi-purpose software and additive manufacturing, and both were more accurate than handmade implants. The difference was not of clinical significance, demonstrating that the accuracy of additive manufacturing cranioplasty implants meets current best practice

    3D shape reconstruction of the femur from planar X-ray images using statistical shape and appearance models

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    Major trauma is a condition that can result in severe bone damage. Customised orthopaedic reconstruction allows for limb salvage surgery and helps to restore joint alignment. For the best possible outcome three dimensional (3D) medical imaging is necessary, but its availability and access, especially in developing countries, can be challenging. In this study, 3D bone shapes of the femur reconstructed from planar radiographs representing bone defects were evaluated for use in orthopaedic surgery. Statistical shape and appearance models generated from 40 cadaveric X-ray computed tomography (CT) images were used to reconstruct 3D bone shapes. The reconstruction simulated bone defects of between 0% and 50% of the whole bone, and the prediction accuracy using anterior–posterior (AP) and anterior–posterior/medial–lateral (AP/ML) X-rays were compared. As error metrics for the comparison, measures evaluating the distance between contour lines of the projections as well as a measure comparing similarities in image intensities were used. The results were evaluated using the root-mean-square distance for surface error as well as differences in commonly used anatomical measures, including bow, femoral neck, diaphyseal–condylar and version angles between reconstructed surfaces from the shape model and the intact shape reconstructed from the CT image. The reconstructions had average surface errors between 1.59 and 3.59 mm with reconstructions using the contour error metric from the AP/ML directions being the most accurate. Predictions of bow and femoral neck angles were well below the clinical threshold accuracy of 3°, diaphyseal–condylar angles were around the threshold of 3° and only version angle predictions of between 5.3° and 9.3° were above the clinical threshold, but below the range reported in clinical practice using computer navigation (i.e., 17° internal to 15° external rotation). This study shows that the reconstructions from partly available planar images using statistical shape and appearance models had an accuracy which would support their potential use in orthopaedic reconstruction

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

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    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. Image Acquisition Matrix Size center dot Image Slice Thickness center dot craniofacial regionimaging technique center dot computed tomography Sample Characteristic - Organism Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13265225This investigation was approved by the internal review board (IRB) of the Medical University of Graz, Austria (IRB: EK-30-340 ex 17/18). This work was supported by CAMed (COMET K-Project 871132), which is funded by the Austrian Federal Ministry of Transport, Innovation and Technology (BMVIT) and the Austrian Federal Ministry for Digital and Economic Affairs (BMDW) and the Styrian Business Promotion Agency (SFG). Furthermore, the Austrian Science Fund (FWF) KLI 678-B31: "enFaced: Virtual and Augmented Reality Training and Navigation Module for 3D-Printed Facial Defect Reconstructions" and the TU Graz LEAD Project "Mechanics, Modeling and Simulation of Aortic Dissection". Privatdozent Dr. Dr. Jan Egger was supported as Visiting Professor by the Overseas Visiting Scholars Program from the Shanghai Jiao Tong University (SJTU) in China. Finally, we thank Professor Hannes Deutschmann, MD, from the Department of Radiology - Division of Neuroradiology, Vascular and Interventional Neuroradiology of the Medical University of Graz, for having kindly provided us with the source CT datasets used in this work

    Robotic Implant Modification for Neuroplastic Surgery

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    Neuroplastic surgery, which combines neurosurgery with plastic surgery, is a novel field that has not been rigorously studied. It has crucial clinical potentials in implanting instrumented devices for brain imaging, targeted drug delivery, deep brain stimulation, shunt placement, and so on. A specific application of neuroplastic surgery is single-stage cranioplasty. Current practice involves resizing a prefabricated oversized customized cranial implant (CCI). This method provides intraoperative flexibility for skull resection. However, surgeons need to manually resize the CCI to fit the craniofacial bone defect based on their judgment and estimation. This manual modification can be time-consuming and imprecise, resulting in large bone gaps between the skull and the resized implant. This work investigates the possibility of applying robotic and computer-integrated techniques to improve the procedure. This dissertation describes the development and examination of several systems to address the challenges that emerged from the CCI resizing process: (i) To assist the manual modification, a portable projection mapping device (PPMD) provides precise real-time visual guidance for surgeons to outline the defect boundary on the oversized CCI. (ii) Even with the assistance of a projection system, the subsequent manual resizing may still be imprecise and prone to failure. This work introduces an automated workflow for intraoperative CCI modification using a robotic system. (iii) A 2-scan method accomplishes the patient-to-CT registration using a handheld 3D scanner and addresses the challenges posed by the soft tissues and the surgical draping requirement using reattachable fiducial markers. (iv) A toolpath algorithm generates a cutting toolpath for the robot to resize the implant based on the defect geometry. (v) Due to certain limitations associated with mechanical cutting, this work presents a 5-axis CO\textsubscript{2} laser cutting system that achieves fast and precise implant modification, ideal for fabricating instrumented implants. The evaluation of the automated workflow shows a significant improvement in CCI resizing accuracy. This indicates lower risk of implant failure causing post-surgical complications. Furthermore, the functions provided by these systems can be expanded to other neuroplastic applications

    A review of image processing methods for fetal head and brain analysis in ultrasound images

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    Background and objective: Examination of head shape and brain during the fetal period is paramount to evaluate head growth, predict neurodevelopment, and to diagnose fetal abnormalities. Prenatal ultrasound is the most used imaging modality to perform this evaluation. However, manual interpretation of these images is challenging and thus, image processing methods to aid this task have been proposed in the literature. This article aims to present a review of these state-of-the-art methods. Methods: In this work, it is intended to analyze and categorize the different image processing methods to evaluate fetal head and brain in ultrasound imaging. For that, a total of 109 articles published since 2010 were analyzed. Different applications are covered in this review, namely analysis of head shape and inner structures of the brain, standard clinical planes identification, fetal development analysis, and methods for image processing enhancement. Results: For each application, the reviewed techniques are categorized according to their theoretical approach, and the more suitable image processing methods to accurately analyze the head and brain are identified. Furthermore, future research needs are discussed. Finally, topics whose research is lacking in the literature are outlined, along with new fields of applications. Conclusions: A multitude of image processing methods has been proposed for fetal head and brain analysis. Summarily, techniques from different categories showed their potential to improve clinical practice. Nevertheless, further research must be conducted to potentiate the current methods, especially for 3D imaging analysis and acquisition and for abnormality detection. (c) 2022 Elsevier B.V. All rights reserved.FCT - Fundação para a Ciência e a Tecnologia(UIDB/00319/2020)This work was funded by projects “NORTE-01–0145-FEDER- 0 0 0 059 , NORTE-01-0145-FEDER-024300 and “NORTE-01–0145- FEDER-0 0 0 045 , supported by Northern Portugal Regional Opera- tional Programme (Norte2020), under the Portugal 2020 Partner- ship Agreement, through the European Regional Development Fund (FEDER). It was also funded by national funds, through the FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020 and by FCT and FCT/MCTES in the scope of the projects UIDB/05549/2020 and UIDP/05549/2020 . The authors also acknowledge support from FCT and the Euro- pean Social Found, through Programa Operacional Capital Humano (POCH), in the scope of the PhD grant SFRH/BD/136670/2018 and SFRH/BD/136721/2018

    External surface anatomy of the postfolding human embryo: Computer-aided, three-dimensional reconstruction of printable digital specimens

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    Opportunities for clinicians, researchers, and medical students to become acquainted with the three-dimensional (3D) anatomy of the human embryo have historically been limited. This work was aimed at creating a collection of digital, printable 3D surface models demonstrating major morphogenetic changes in the embryo's external anatomy, including typical features used for external staging. Twelve models were digitally reconstructed based on optical projection tomography, high-resolution episcopic microscopy and magnetic resonance imaging datasets of formalin-fixed specimens of embryos of developmental stages 12 through 23, that is, stages following longitudinal and transverse embryo folding. The reconstructed replica reproduced the external anatomy of the actual specimens in great detail, and the progress of development over stages was recognizable in a variety of external anatomical features and bodily structures, including the general layout and curvature of the body, the pharyngeal arches and cervical sinus, the physiological gut herniation, and external genitalia. In addition, surface anatomy features commonly used for embryo staging, such as distinct steps in the morphogenesis of facial primordia and limb buds, were also apparent. These digital replica, which are all provided for 3D visualization and printing, can serve as a novel resource for teaching and learning embryology and may contribute to a better appreciation of the human embryonic development

    Integrated Methodologies and Technologies for the Design of Advanced Biomedical Devices

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    Biomedical devices with tailored properties were designed using advanced methodologies and technologies. In particular, design for additive manufacturing, reverse engineering, material selection, experimental and theoretical analyses were properly integrated. The focus was on the design of: i) 3D additively manufactured hybrid structures for cranioplasty; ii) technical solutions and customized prosthetic devices with tailored properties for skull base reconstruction after endoscopic endonasal surgery; iii) solid-lattice hybrid structures with optimized properties for biomedical applications. The feasibility of the proposed technical solutions was also assessed through virtual and physical models

    Radiological Society of North America (RSNA) 3D printing Special Interest Group (SIG): Guidelines for medical 3D printing and appropriateness for clinical scenarios

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    Este número da revista Cadernos de Estudos Sociais estava em organização quando fomos colhidos pela morte do sociólogo Ernesto Laclau. Seu falecimento em 13 de abril de 2014 surpreendeu a todos, e particularmente ao editor Joanildo Burity, que foi seu orientando de doutorado na University of Essex, Inglaterra, e que recentemente o trouxe à Fundação Joaquim Nabuco para uma palestra, permitindo que muitos pudessem dialogar com um dos grandes intelectuais latinoamericanos contemporâneos. Assim, buscamos fazer uma homenagem ao sociólogo argentino publicando uma entrevista inédita concedida durante a sua passagem pelo Recife, em 2013, encerrando essa revista com uma sessão especial sobre a sua trajetória
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