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Objectives: We sought to identify in which clinical scenarios 3D printed models are used to plan for fetal surgeries as well as the main purpose and the imaging method utilized for the models. In addition, we describe benefits and shortcomings of the models, as well as potential future improvements. Methods: In this scoping review, data were collected retrospectively from scientific databases (PubMed, Embase, Cochrane CENTRAL, CINAHL, Scopus, and the Web of Science platform) and screened by title, abstract, and full text against strict criteria. The inclusion criteria required the study be performed on a live fetus and involve 3D models used for fetal surgery. The models must have been designed from diagnostic imaging modalities such as CT, MRI, or ultrasound. The articles considered include clinical trials, review articles, cohort studies, case series, case reports, and conference abstracts. Results: Of the initial 742 articles collected, six met the inclusion criteria. Spina bifida and EXIT procedures were the most frequent use cases that inspired surgeons to print models for surgical planning. The ability to view patient-specific anatomy in a 3D handheld model was often touted as providing a great benefit to the surgical team's ability to anticipate intraoperative challenges. Conclusions: Three-dimensional printing models have been applied to plan for fetal surgeries, more specifically, for EXIT procedures and fetoscopic surgical repair of spina bifida. The potential benefits of 3D printing in fetal surgery are enormous.

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BACKGROUND: Over the last decade, simulation models have been increasingly applied as an adjunct for surgical training in neurosurgery. We aim through a practical course at a national neurosurgical conference to evaluate 3D non-cadaveric simulation models along with augmented reality for learning and practicing the pterional craniotomy approach among a wide variety of participants including medical students, neurosurgery residents, and attending neurosurgeons. METHODS: Our course was conducted during an international neurosurgery meeting with 93 participants but the course surveys (pre- and post-course) were completed by 42 participants. RESULTS: Most participants were medical students (31; 73.8%). Participants with no experience (the majority) in cadaver lab dissections, craniotomy as first operator, and as second operator represented 12 (27.9%), 29 (69%), and 22 (52.4%), respectively. Participants with moderate experience in cadaver lab dissections were 23 (53.5%). Post-course survey respondents noted positive feedback in most items queried including enhancement of familiarity and acquiring skills, confidence with neurosurgery instruments, confidence with microscope, part of standard training, traditional training, and lifelong training. CONCLUSIONS: Simulation model combining augmented reality with physical simulation for hybrid experience can be a promising and valuable tool especially for medical students or early career neurosurgical residents.

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Aortic valve (AV) disease is a common valvular lesion in the United States, present in about 5% of the population at age 65 with increasing prevalence with advancing age. While current replacement heart valves have extended life for many, their long-term use remains hampered by limited durability. Non-surgical treatments for AV disease do not yet exist, in large part because our understanding of AV disease etiology remains incomplete. The direct study of human AV disease remains hampered by the fact that clinical data is only available at the time of treatment, where the disease is at or near end stage and any time progression information has been lost. Large animal models, long used to assess replacement AV devices, cannot yet reproduce AV disease processes. As an important alternative mouse animal models are attractive for their ability to perform genetic studies of the AV disease processes and test potential pharmaceutical treatments. While mouse models have been used for cellular and genetic studies of AV disease, their small size and fast heart rates have hindered their use for tissue- and organ-level studies. We have recently developed a novel ex vivo micro-CT-based methodology to 3D reconstruct murine heart valves and estimate the leaflet mechanical behaviors (Feng et al. in Sci Rep 13(1):12852, 2023). In the present study, we extended our approach to 3D reconstruction of the in vivo functional murine AV (mAV) geometry using high-frequency four-dimensional ultrasound (4DUS). From the resulting 4DUS images we digitized the mAV mid-surface coordinates in the fully closed and fully opened states. We then utilized matched high-resolution µCT images of ex vivo mouse mAV to develop mAV NURBS-based geometric model. We then fitted the mAV geometric model to the in vivo data to reconstruct the 3D in vivo mAV geometry in the closed and open states in n = 3 mAV. Results demonstrated high fidelity geometric results. To our knowledge, this is the first time such reconstruction was ever achieved. This robust assessment of in vivo mAV leaflet kinematics in 3D opens up the possibility for longitudinal characterization of murine models that develop aortic valve disease.

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We describe the use of three-dimensional printing to create precise airway models for a patient with Treacher Collins syndrome who presented for bimaxillary temporomandibular joint prostheses, and for whom airway management was predicted to be difficult. The model was based on pre-operative cone beam computed tomography images and printed in the 3D Lab of Hospital Universitario La Paz. Transparent models allowed clear visualisation for simulation and iterative refinement of airway management techniques and aided in risk assessment and instrument sizing. This case report emphasises the utility of this approach in complex airway scenarios.

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BACKGROUND: The responsible use of 3D-printing in medicine includes a context-based quality assurance. Considerable literature has been published in this field, yet the quality of assessment varies widely. The limited discriminatory power of some assessment methods challenges the comparison of results. The total error for patient specific anatomical models comprises relevant partial errors of the production process: segmentation error (SegE), digital editing error (DEE), printing error (PrE). The present review provides an overview to improve the general understanding of the process specific errors, quantitative analysis, and standardized terminology. METHODS: This review focuses on literature on quality assurance of patient-specific anatomical models in terms of geometric accuracy published before December 4th, 2022 (n = 139). In an attempt to organize the literature, the publications are assigned to comparable categories and the absolute values of the maximum mean deviation (AMMD) per publication are determined therein. RESULTS: The three major examined types of original structures are teeth or jaw (n = 52), skull bones without jaw (n = 17) and heart with coronary arteries (n = 16). VPP (vat photopolymerization) is the most frequently employed basic 3D-printing technology (n = 112 experiments). The median values of AMMD (AMMD: The metric AMMD is defined as the largest linear deviation, based on an average value from at least two individual measurements.) are 0.8 mm for the SegE, 0.26 mm for the PrE and 0.825 mm for the total error. No average values are found for the DEE. CONCLUSION: The total error is not significantly higher than the partial errors which may compensate each other. Consequently SegE, DEE and PrE should be analyzed individually to describe the result quality as their sum according to rules of error propagation. Current methods for quality assurance of the segmentation are often either realistic and accurate or resource efficient. Future research should focus on implementing models for cost effective evaluations with high accuracy and realism. Our system of categorization may be enhancing the understanding of the overall process and a valuable contribution to the structural design and reporting of future experiments. It can be used to educate specialists for risk assessment and process validation within the additive manufacturing industry.

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Traditional teaching methods struggle to convey three-dimensional concepts effectively. While 3D virtual models and virtual reality platforms offer a promising approach to teaching anatomy, their cost and specialized equipment pose limitations, especially in disadvantaged areas. A simpler alternative is to use virtual 3D models displayed on regular screens, but they lack immersion, realism, and stereoscopic vision. To address these challenges, we developed an affordable method utilizing smartphone-based 360° photogrammetry, virtual camera recording, and stereoscopic display (anaglyph or side-by-side technique). In this study, we assessed the feasibility of this method by subjecting it to various specimen types: osteological, soft organ, neuroanatomical, regional dissection, and a dedicated 3D-printed testing phantom. The results demonstrate that the 3D models obtained feature a complete mesh with a high level of detail and a realistic texture. Mesh and texture resolutions were estimated to be approximately 1 and 0.2 mm, respectively. Additionally, stereoscopic animations were both feasible and effective in enhancing depth perception. The simplicity and affordability of this method position it as a technique of choice for creating easily photorealistic anatomical models combined with stereoscopic depth visualization.

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PURPOSE: To identify the clinical impact and potential benefits of in-house 3D-printed objects through a questionnaire, focusing on three principal areas: patient education; interdisciplinary cooperation; preoperative planning and perioperative execution. MATERIALS AND METHODS: Questionnaires were sent from January 2021 to August 2022. Participants were directed to rate on a scale from 1 to 10. RESULTS: The response rate was 43%. The results of the rated questions are averages. 84% reported using 3D-printed objects in informing the patient about their condition/procedure. Clinician-reported improvement in patient understanding of their procedure/disease was 8.1. The importance of in-house placement was rated 9.2. 96% reported using the 3D model to confer with colleagues. Delay in treatment due to 3D printing lead-time was 1.8. The degree with which preoperative planning was altered was 6.9. The improvement in clinician perceived preoperative confidence was 8.3. The degree with which the scope of the procedure was affected, in regard to invasiveness, was 5.6, wherein a score of 5 is taken to mean unchanged. Reduction in surgical duration was rated 5.7. CONCLUSION: Clinicians report the utilization of 3D printing in surgical specialties improves procedures pre- and intraoperatively, has a potential for increasing patient engagement and insight, and in-house location of a 3D printing center results in improved interdisciplinary cooperation and allows broader access with only minimal delay in treatment due to lead-time.

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OBJECTIVES: Among types of 3D printing, fused deposition modeling (FDM) and digital light processing (DLP) are the most accessible, making them attractive, low-cost options for simulating surgical procedures. This study characterized and compared inexpensive, synthetic temporal bone models printed using Resin, PETG, and Simubone™. MATERIALS AND METHODS: This study compared models made of polyethylene terephthalate glycol (PETG), Simubone™ produced from a FDM printer, and photopolymer resin from a DLP printer. These temporal bone models were processed by: (1) DICOM files from a patient's CT scan were segmented to define critical parts expected in a temporal bone surgery. (2) The model was appended with a base that articulates with a 3D-printed temporal bone holder. (3) The refined, patient-specific model was manufactured using FDM and DLP printing technologies. (4) The models were sent to evaluators, who assessed the models based on anatomic accuracy, dissection experience, and its applicability as a surgical simulation tool for temporal bone dissection. RESULTS: The photopolymer resin outperformed PETG and Simubone™ in terms of anatomical accuracy and dissection experience. Additionally, resin and PETG were evaluated to be appropriate for simple mastoidectomy and canal wall down mastoidectomy while Simubone™ was only suitable for simple mastoidectomy. All models were unsuitable for posterior tympanotomy and labyrinthectomy. CONCLUSIONS: Photopolymer resin and PETG have shown to be suitable materials for dissection models with 3D-printed resin models showing more accuracy in replicating anatomical structures and dissection experience. Hence, the use of 3D-printed temporal bones may be a suitable low-cost alternative to cadaveric dissection.

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In recent decades, a number of simulation models for microsurgical training have been published. The human placenta has received extensive validation in microneurosurgery and is a useful instrument to facilitate learning in microvascular repair techniques as an alternative to using live animals. This study uses a straightforward, step-by-step procedure for instructing the creation of simulators with dynamic flow to characterize the placental vascular tree and assess its relevance for plastic surgery departments. Measurements of the placental vasculature and morphological characterization of 18 placentas were made. After the model was used in a basic microsurgery training laboratory session, a survey was given to nine plastic surgery residents, two microsurgeons, and one hand surgeon. In all divisions, venous diameters were larger than arterial diameters, with minimum diameters of 0.8 and 0.6 mm, respectively. The majority of the participants considered that the model faithfully reproduces a real microsurgical scenario; the consistency of the vessels and their dissection are similar in in vivo tissue. Furthermore, all the participants considered that this model could improve their surgical technique and would propose it for microsurgical training. As some of the model's disadvantages, an abundantly thick adventitia, a thin tunica media, and higher adherence to the underlying tissue were identified. The color-perfused placenta is an excellent tool for microsurgical training in plastic surgery. It can faithfully reproduce a microsurgical scenario, offering an abundance of vasculature with varying sizes similar to tissue in vivo, enhancing technical proficiency, and lowering patient error.

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Advances in modeling and imaging have resulted in realistic tools that can be applied to education and training, and even direct patient care. These include point-of-care ultrasound (POCUS), 3-dimensional and digital anatomic modeling, and extended reality. These technologies have been used for the preparation of complex patient care through simulation-based clinical rehearsals, direct patient care such as the creation of patient devices and implants, and for simulation-based education and training for health professionals, patients and families. In this section, we discuss these emerging technologies and describe how they can be utilized to improve patient care.

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PURPOSE: This article aims to discuss the use of three-dimensional (3D) printed models of vascular variation cases as an educational tool for undergraduate and postgraduate anatomy students. METHODS: This advanced study involved ten anatomy assistants who were provided with five distinct cases of congenital cardiovascular variations, each accompanied by a computed tomography angiography (CT-A) and 1:1 solid model format. The residents were asked to generate perceptions for both formats and then compare these perceptions based on identifying the variation, defining the structural features, and evaluating relevant educational perspectives. RESULTS: The vascular origin measurement values compared to the statistically evaluated real values of the related cases showed that models were 1:1 identical copies. Qualitative assessment feedback from five stations supported the usefulness of 3D models as educational tools for organ anatomy, simulation of variational structures, and overall medical education and anatomy training. Models showcasing different anatomical variations such as aortic arch with Type 2 pattern, a right-sided aortic arch with Type 2 pattern, an aberrant right subclavian artery, arteria lusoria in thorax, and a left coronary artery originating from pulmonary trunk in an Alcapa type pattern allow for better analysis due to their complex anatomies, thus optimizing the study of variation-specific anatomy. The perception level in the 3D model contained higher points in all of the nine parameters, namely identification of cardiovascular variations, defining the vessel with anomaly, aortic arch branch count and appearance order, feasibility of using it in peers and student education. 3D models received a score 9.1 points, while CT-A images were rated at 4.8 out of 10. CONCLUSION: 3D printed anatomical models of variational cardiovascular anatomy serve as essential components of anatomy training and postgraduate clinical perception by granting demonstrative feedback and a superior comprehension of the visuospatial relationship between the anatomical structures.

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Temperature-based time of death estimation using simulation methods such as the finite element method promise higher accuracy and broader applicability in nonstandard cooling scenarios than established phenomenological methods. Their accuracy depends crucially on the simulation model to capture the actual situation, which in turn hinges on the representation of the corpse's anatomy in form of computational meshes as well as on the thermodynamic parameters. While inaccuracies in anatomy representation due to coarse mesh resolution are known to have a minor impact on the estimated time of death, the sensitivity with respect to larger differences in the anatomy has so far not been studied. We assess this sensitivity by comparing four independently generated and vastly different anatomical models in terms of the estimated time of death in an identical cooling scenario. In order to isolate the impact of shape variation, the models are scaled to a reference size, and the possible impact of measurement location variation is excluded explicitly by finding measurement locations leading to minimum deviations. The thus obtained lower bound on the impact of anatomy on the estimated time of death shows, that anatomy variations lead to deviations of at least 5-10%.

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Medical 3D printing is a complex, highly interdisciplinary, and revolutionary technology that is positively transforming the care of patients. The technology is being increasingly adopted at the Point of Care (PoC) as a consequence of the strong value offered to medical practitioners. One of the key technologies within the medical 3D printing portfolio enabling this transition is desktop inverted Vat Photopolymerization (VP) owing to its accessibility, high quality, and versatility of materials. Several reports in the peer-reviewed literature have detailed the medical impact of 3D printing technologies as a whole. This review focuses on the multitude of clinical applications of desktop inverted VP 3D printing which have grown substantially in the last decade. The principles, advantages, and challenges of this technology are reviewed from a medical standpoint. This review serves as a primer for the continually growing exciting applications of desktop-inverted VP 3D printing in healthcare.

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OBJECTIVE: 3D printing is increasingly used to fabricate three-dimensional neurosurgical simulation models, making training more accessible and economical. 3D printing includes various technologies with different capabilities for reproducing human anatomy. This study evaluated different materials across a broad range of 3D printing technologies to identify the combination that most precisely represents the parietal region of the skull for burr hole simulation. METHODS: Eight different materials (polyethylene terephthalate glycol, Tough PLA, FibreTuff, White Resin, BoneSTN, SkullSTN, polymide [PA12], glass-filled polyamide [PA12-GF]) across 4 different 3D printing processes (fused filament fabrication, stereolithography, material jetting, selective laser sintering) were produced as skull samples that fit into a larger head model derived from computed tomography imaging. Five neurosurgeons conducted burr holes on each sample while blinded to the details of manufacturing method and cost. Qualities of mechanical drilling, visual appearance, skull exterior, and skull interior (i.e., diploë) and overall opinion were documented, and a final ranking activity was performed along with a semistructured interview. RESULTS: The study found that 3D printed polyethylene terephthalate glycol (using fused filament fabrication) and White Resin (using stereolithography) were the best models to replicate the skull, surpassing advanced multimaterial samples from a Stratasys J750 Digital Anatomy Printer. The interior (e.g., infill) and exterior structures strongly influenced the overall ranking of samples. All neurosurgeons agreed that practical simulation with 3D printed models can play a vital role in neurosurgical training. CONCLUSIONS: The study findings reveal that widely accessible desktop 3D printers and materials can play a valuable role in neurosurgical training.

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Understanding the three-dimensional (3D) structure of the human skull is imperative for medical courses. However, medical students are overwhelmed by the spatial complexity of the skull. Separated polyvinyl chloride (PVC) bone models have advantages as learning tools, but they are fragile and expensive. This study aimed to reconstruct 3D-printed skull bone models (3D-PSBs) using polylactic acid (PLA) with anatomical characteristics for spatial recognition of the skull. Student responses to 3D-PSB application were investigated through a questionnaire and tests to understand the requirement of these models as a learning tool. The students were randomly divided into 3D-PSB (n = 63) and skull (n = 67) groups to analyze pre- and post-test scores. Their knowledge was improved, with the gain scores of the 3D-PSB group (50.0 ± 3.0) higher than that of the skull group (37.3 ± 5.2). Most students agreed that using 3D-PSBs with quick response codes could improve immediate feedback on teaching (88%; 4.41 ± 0.75), while 85.9% of the students agreed that individual 3D-PSBs clarified the structures hidden within the skull (4.41 ± 0.75). The ball drop test revealed that the mechanical strength of the cement/PLA model was significantly greater than that of the cement or PLA model. The prices of the PVC, cement, and cement/PLA models were 234, 1.9, and 10 times higher than that of the 3D-PSB model, respectively. These findings imply that low-cost 3D-PSB models could revolutionize skull anatomical education by incorporating digital technologies like the QR system into the anatomical teaching repertoire.

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BACKGROUND: Otolaryngology-head and neck surgical (OHNS) trainees' operating exposure is supplemented by a combination of didactic teaching, textbook reading, and cadaveric dissections. Conventional teaching, however, may not adequately equip trainees with an understanding of complex visuospatial relationships of the middle ear. Both face and content validation were assessed of a novel three-dimensional (3D) photorealistic virtual ear simulation tool underwent face and content validation as an educational tool for OHNS trainees. METHODS: A three-dimensional mesh reconstruction of open access imaging was generated using geometric modeling, which underwent global illumination, subsurface scattering, and texturing to create photorealistic virtual reality (VR) ear models were created from open access imaging and comiled into a educational platform. This was compiled into an educational VR platform which was explored to validate the face and content validity questionnaires in a prospective manner. OHNS post-graduate trainees were recruited from University of Toronto and University of Calgary OHNS programs. Participation was on a voluntary basis. RESULTS: Total of 23 OHNS post-graduate trainees from the two universities were included in this study. The mean comfort level of otologic anatomy was rated 4.8 (± 2.2) out of 10. Senior residents possessed more otologic surgical experience (P < 0.001) and higher average comfort when compared to junior residents [6.7 (± 0.7) vs. 3.6 (± 1.9); P = 0.001]. Face and content validities were achieved in all respective domains with no significant difference between the two groups. Overall, respondents believed OtoVIS was a useful tool to learn otologic anatomy with a median score of 10.0 (8.3-10.0) and strongly agreed that OtoVIS should be added to OHNS training with a score of 10.0 (9.3-10.0). CONCLUSIONS: OtoVIS achieved both face and content validity as a photorealistic VR otologic simulator for teaching otologic anatomy in the postgraduate setting. As an immersive learning tool, it may supplement trainees' understanding and residents endorsed its use.

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INTRODUCTION: Mock circulatory loops (MCLs) are mechanical representations of the cardiovascular system largely used to test the hemodynamic performance of cardiovascular medical devices (MD). Thanks to 3 dimensional (3D) printing technologies, MCLs can nowadays also incorporate anatomical models so to offer enhanced testing capabilities. The aim of this review is to provide an overview on MCLs and to discuss the recent developments of 3D anatomical models for cardiovascular MD testing. METHODS: The review first analyses the different techniques to develop 3D anatomical models, in both rigid and compliant materials. In the second section, the state of the art of MCLs with 3D models is discussed, along with the testing of different MDs: implantable blood pumps, heart valves, and imaging techniques. For each class of MD, the MCL is analyzed in terms of: the cardiovascular model embedded, the 3D model implemented (the anatomy represented, the material used, and the activation method), and the testing applications. DISCUSSIONS AND CONCLUSIONS: MCLs serve the purpose of testing cardiovascular MDs in different (patho-)physiological scenarios. The addition of 3D anatomical models enables more realistic connections of the MD with the implantation site and enhances the testing capabilities of the MCL. Current attempts focus on the development of personalized MCLs to test MDs in patient-specific hemodynamic and anatomical scenarios. The main limitation of MCLs is the impossibility to assess the impact of a MD in the long-term and at a biological level, for which animal experiments are still needed.

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OBJECTIVE: To present and validate a new simulation model for endoscopic phonomicrosurgery training as an improved teaching method. METHODS: A low-cost artificial model was assembled using 3D printing, silicone, and gelatin. The study was designed to test the model's ability to carry out training and teaching of endoscopic phonomicrosurgery. The synthetic model was built to simulate normal and pathological vocal folds such as polyps, intracordal cysts and keratoses, made of silicone and gelatin and embedded in a larynx framework made by 3D printing. Simulations of endoscopic surgical procedures were performed and documented through photographs and videos and the images were submitted to the evaluation of a group of 17 otorhinolaryngologists who used a Likert scale questionnaire. The responses were submitted to an agreement analysis using the sum of the scores obtained for the responses as an appropriate level of validation. Cronbach's alpha index was calculated to measure the degree of the questionnaire internal consistency. RESULT: The evaluations indicated maximum approval for the model adequacy for use in practical classes and for the teaching of the procedures, as well as in the overall satisfaction with the model in the use of surgical training. CONCLUSION: The present proposal for training laryngeal endoscopic surgery in a 3D synthetic model is a viable option according to the validation methodology used in the present study.

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Three-dimensional (3D) scanning and printing technology has allowed for the production of anatomical replicas at virtually any size. But what size optimizes the educational potential of 3D printing models? This study systematically investigates the effect of model size on nominal anatomy learning. The study population of 380 undergraduate students, without prior anatomical knowledge, were randomized to learn from two of four bone models (either vertebra and pelvic bone [os coxae], or scapula and sphenoid bone), each model 3D printed at 50%, 100%, 200%, and either 300% or 400% of normal size. Participants were then tested on nominal anatomy recall on the respective bone specimens. Mental rotation ability and working memory were also assessed, and opinions regarding learning with the various models were solicited. The diameter of the rotational bounding sphere for the object ("longest diameter") had a small, but significant effect on test score (F(2,707) = 17.15, p < 0.05, R2  = 0.046). Participants who studied from models with a longest diameter greater than 10 cm scored significantly better than those who used models less than 10 cm, with the exception of the scapula model, on which performance was equivalent across all sizes. These results suggest that models with a longest diameter beyond 10 cm are unlikely to incur a greater size-related benefit in learning nominal anatomy. Qualitative feedback suggests that there also appear to be inherent features of bones besides longest diameter that facilitate learning.

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Patients with myocardial infarction are at elevated risk of sudden cardiac death, and scar tissue arising from infarction is known to play a role. The accurate identification of scars therefore is crucial for risk assessment, quantification and guiding interventions. Typically, core scars and grey peripheral zones are identified by radiologists and clinicians based on cardiac late gadolinium enhancement magnetic resonance images (LGE-MRI). Scar regions from LGE-MRI vary in size, shape, heterogeneity, artifacts, and image resolution. Thus, manual segmentation is time consuming, and influenced by the observer's experience (bias effect). We propose a fully automatic framework that develops 3D anatomical models of the left ventricle with border zone and core scar regions that are free from bias effect. Our myocardium (SOCRATIS), border scar and core scar (BZ-SOCRATIS) segmentation pipelines were evaluated using internal and external validation datasets. The automatic myocardium segmentation framework performed a Dice score of 81.9% and 70.0% in the internal and external validation dataset. The automatic scar segmentation pipeline achieved a Dice score of 60.9% for the core scar segmentation and 43.7% for the border zone scar segmentation in the internal dataset and in the external dataset a Dice score of 44.2% for the core scar segmentation and 54.8% for the border scar segmentation respectively. To the best of our knowledge, this is the first study outlining a fully automatic framework to develop 3D anatomical models of the left ventricle with border zone and core scar regions. Our method exhibits high performance without the need for training or tuning in an unseen cohort (unsupervised).

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