Patient-specific Anatomical Models Research Articles

Quality assurance of 3D-printed patient specific anatomical models: a systematic review

BackgroundThe 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.MethodsThis 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.ResultsThe 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.ConclusionThe 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.Graphical Context of the figures in this review. Center: Fig. 5+ 7; top (blue): Fig. 8; right (green): Fig. 9; bottom (yellow): Fig. 10; left (red): Fig. 11. A version in high resolution can be found online in the supplementary material.

Application of three-dimensional printed biomodels in endoscopic spinal surgery.

Three-dimensional printing (3DP) is increasingly used to individualise surgery and may be an effective tool for representing patient anatomy. Current literature on patient-specific anatomical models (biomodels) for minimally invasive spinal surgery is a limited number of case series and cohort studies. However, studies investigating 3DP in other specialties have reported multiple benefits. This prospective study considered a series of patients (n=33) undergoing elective endoscopic spinal surgery, including combinations of microdiscectomy (n=27), foraminotomy (n=7), and laminectomy (n=3). These surgeries were conducted at vertebral levels ranging from L2/3 to L5/S1. The surgeon then recorded the impact on preoperational planning, intraoperative decision-making and accelerating the learning curve with a qualitative questionnaire. There were benefits to planning in 54.5% of cases (n=18), improved intraoperative decision-making in 60.6% of cases (n=20). These benefits were reported more frequently earlier in the cases, with improvements to learning reported in 60% of the first five cases and not in subsequent cases. The surgeon commented that the biomodels were more useful on. The rates of preoperative and intraoperative benefits are consistent with existing studies, and the early benefit to the learning curve may be suitable for applications to surgical training. Additional research is required to determine the practicality of biomodels and their impact on patient outcomes for endoscopic spinal surgery.

Use of three-dimensional printing technology for supporting the hip reconstruction surgery in paediatric patients

The use of three-dimensional (3D) printed patient-specific anatomical models is nowadays a viable strategy for improving surgical outcome in medicine. In adult surgery, 3D printing technology is commonly studied, but its use in paediatric surgery is still under development. This work presents the implementation of 3D printing technology in Orthopaedic department of the paediatric hospital “Santobono-Pausilipon” in Naples by fabricating 3D printed anatomical models of paediatric patients. The 3D printed models fabricated were used for the training of the surgical team during the preoperative planning and for carrying out a surgical simulation. The anatomical models are designed in compliance with the current European Medical Devices regulation and following the already existing guidelines in literature. The impact of the 3D printed anatomical models used, a total of seven printed anatomical models based on four patients, is then evaluated throughout a questionnaire proposed to the surgical team, composed by eight paediatric orthopaedic surgeons. Surgeons answered to a total of ten questions, six scale-based questions and four free-text questions. Results obtained from the questionnaires highlighted how 3D printed anatomical models can lead to a better understating of the treated pathologies, carrying relevant improvements in both the surgical team training and the surgical outcome.

Assessing views and attitudes toward the use of extended reality and its implications in neurosurgical education: a survey of neurosurgical trainees.

Extended reality (XR) systems, including augmented reality (AR), virtual reality (VR), and mixed reality, have rapidly emerged as new technologies capable of changing the way neurosurgeons prepare for cases. Thus, the authors sought to evaluate the perspectives of neurosurgical trainees on the integration of these technologies into neurosurgical education. A 20-question cross-sectional survey was administered to neurosurgical residents and fellows to evaluate perceptions of the use of XR in neurosurgical training. Respondents evaluated each statement using a modified Likert scale (1-5). One hundred sixteen responses were recorded, with 59.5% of participants completing more than 90% of the questions. Approximately 59% of participants reported having institutional access to XR technologies. The majority of XR users (72%) believed it was effective for simulating surgical situations, compared with only 41% for those who did not have access to XR. Most respondents (61%) agreed that XR could become a standard in neurosurgical education and a cost-effective training tool (60%). Creating patient-specific anatomical XR models was considered relatively easy by 56% of respondents. Those with XR access reported finding it easier to create intraoperative models (58%) than those without access. A significant percentage (79%) agreed on the need for technical skill training outside the operating room (OR), especially among those without XR access (82%). There was general agreement (60%) regarding the specific need for XR. XR was perceived as effectively simulating stress in the OR. Regarding clinical outcomes, 61% believed XR improved efficiency and safety and 48% agreed it enhanced resection margins. Major barriers to XR integration included lack of ample training hours and/or time to use XR amid daily clinical obligations (63%). The data presented in this study indicate that there is broad agreement among neurosurgical trainees that XR holds potential as a training modality in neurosurgical education. Moreover, trainees who have access to XR technologies tend to hold more positive perceptions regarding the benefits of XR in their training. This finding suggests that the availability of XR resources can positively influence trainees' attitudes and beliefs regarding the utility of these technologies in their education and training.

Role of Three-Dimensional Printing in Treatment Planning for Orthognathic Surgery: A Systematic Review.

Three-dimensional (3D) printing refers to a wide range of additive manufacturing processes that enable the construction of structures and models. It has been rapidly adopted for a variety of surgical applications, including the printing of patient-specific anatomical models, implants and prostheses, external fixators and splints, as well as surgical instrumentation and cutting guides. In comparison to traditional methods, 3D-printed models and surgical guides offer a deeper understanding of intricate maxillofacial structures and spatial relationships. This review article examines the utilization of 3D printing in orthognathic surgery, particularly in the context of treatment planning. It discusses how 3D printing has revolutionized this sector by providing enhanced visualization, precise surgical planning, reduction in operating time, and improved patient communication. Various databases, including PubMed, Google Scholar, ScienceDirect, and Medline, were searched with relevant keywords. A total of 410 articles were retrieved, of which 71 were included in this study. This article concludes that the utilization of 3D printing in the treatment planning of orthognathic surgery offers a wide range of advantages, such as increased patient satisfaction and improved functional and aesthetic outcomes.

The Inaugural "Century" of Mixed Reality in Cranial Surgery: Virtual Reality Rehearsal/Augmented Reality Guidance and Its Learning Curve in the First 100-Case, Single-Surgeon Series.

Virtual reality (VR) refers to a computer-generated three-dimensional space in which a surgeon can interact with patient-specific anatomic models for surgical planning. Augmented reality (AR) is the technology that places computer-generated objects, including those made in VR, into the surgeon's visual space. Together, VR and AR are called mixed reality (MxR), and it is gaining importance in neurosurgery. MxR is helpful for selecting and creating templates for an optimal surgical approach and identifying key anatomic landmarks intraoperatively. By reporting our experience with the first 100 consecutive cases planned with VR and executed with AR, our objective is to detail the learning curve and encountered obstacles while adopting the new technology. This series includes the first 100 consecutive complex cranial cases of a single surgeon for which MxR was intended for use. Effectiveness of the VR rehearsal and AR guidance was analyzed for four specific contributions: (1) opening size, (2) precise craniotomy placement, (3) guidance toward anatomic landmarks or target, and (4) antitarget avoidance. Seventeen cases in the study cohort were matched with historical non-MxR cases for comparison of outcome parameters. The cases in which MxR failed were plotted over time to determine the nature of the "learning curve." AR guidance was abandoned in eight operations because of technical problems, but problem-free application of MxR increased between the 44th and 63rd cases. This provides some evidence of proficiency acquisition in between. Comparing the 17 pairs of matched MxR and non-MxR cases, no statistically significant differences exist in the groups regarding blood loss, length of stay nor duration of surgery. Cases where MxR had above-expectation performances are highlighted. MxR is a powerful tool that can help tailor operations to patient-specific anatomy and provide efficient intraoperative guidance without additional time for surgery or hospitalization.

Trends and Challenges in the Development of 3D-Printed Heart Valves and Other Cardiac Implants: A Review of Current Advances.

This article provides a comprehensive review of the current trends and challenges in the development of 3D-printed heart valves and other cardiac implants. By providing personalized solutions and pushing the limits of regenerative medicine, 3D printing technology has revolutionized the field of cardiac healthcare. The use of several organic and synthetic polymers in 3D printing heart valves is explored in this article, with emphasis on both their benefits and drawbacks. In cardiac tissue engineering, stem cells are essential, and their potential to lessen immunological rejection and thrombogenic consequences is highlighted. In the clinical applications section, the article emphasizes the importance of 3D printing in preoperative planning. Surgery results are enhanced when surgeons can visualize and assess the size and placement of implants using patient-specific anatomical models. Customized implants that are designed to match the anatomy of a particular patient reduce the likelihood of complications and enhance postoperative results. The development of physiologically active cardiac implants, made possible by 3D bioprinting, shows promise by eliminating the need for artificial valves. In conclusion, this paper highlights cutting-edge research and the promise of 3D-printed cardiac implants to improve patient outcomes and revolutionize cardiac treatment.

The Role of 3D Printing in Treatment Planning of Spine and Sacral Tumors.

Three-dimensional (3D) printing technology has proven to have many advantages in spine and sacrum surgery. 3D printing allows the manufacturing of life-size patient-specific anatomic and pathologic models to improve preoperative understanding of patient anatomy and pathology. Additionally, virtual surgical planning using medical computer-aided design software has enabled surgeons to create patient-specific surgical plans and simulate procedures in a virtual environment. This has resulted in reduced operative times, decreased complications, and improved patient outcomes. Combined with new surgical techniques, 3D-printed custom medical devices and instruments using titanium and biocompatible resins and polyamides have allowed innovative reconstructions.

Recent Advancements in 3-D Printing in Medical Applications

The field of three-dimensional (3D) printing has witnessed significant advancements in recent years, and its potential for revolutionizing medical applications is rapidly emerging. This review aims to provide an overview of the current state and scope of 3D printing in the medical field. The review begins by highlighting the various 3D printing technologies currently employed in healthcare settings, including stereolithography, selective laser sintering, fused deposition modeling, and inkjet printing. Each technology's advantages and limitations are discussed, shedding light on their suitability for different medical applications. Next, the review delves into the diverse range of medical applications where 3D printing has shown promise. These applications include the fabrication of patient-specific anatomical models for preoperative planning, surgical guides and tools, customized implants and prosthetics, tissue engineering scaffolds, and drug delivery systems. The potential benefits of using 3D printing in these areas, such as enhanced surgical accuracy, improved patient outcomes, reduced surgery time, and personalized medicine, are explored. Furthermore, the review addresses the challenges and limitations associated with implementing 3D printing in medical settings. These challenges include regulatory concerns, standardization of processes, material biocompatibility, cost-effectiveness, and scalability. The ongoing efforts to overcome these barriers and the future directions of 3D printing in medicine are also discussed. In conclusion, 3D printing holds immense potential for transforming various aspects of medical practice. While considerable progress has been made, there are still challenges to be addressed before widespread adoption can be achieved. With continued research and development, coupled with regulatory support and collaboration between academia, industry, and healthcare professionals, 3D printing is poised to International Journal of Scientific Research in Engineering and Management (IJSREM) Volume: 07 Issue: 07 | July - 2023 SJIF Rating: 8.176 ISSN: 2582-3930 © 2023, IJSREM | www.ijsrem.com DOI: 10.55041/IJSREM24845 | Page 2 make a substantial impact in the field of medicine, improving patient care and treatment outcomes. Key words: Additive manufacturing (AM); Bio-medical; Fused Deposition Modelling (FDM); Selective Laser Sintering (SLS); Stereolithography (SLA); Digital Light Processing (DLP); Binder Jetting; Material Jetting; Direct Energy Deposition (DED).

Optimization of laser dosimetry based on patient-specific anatomical models for the ablation of pancreatic ductal adenocarcinoma tumor

Laser-induced thermotherapy has shown promising potential for the treatment of unresectable primary pancreatic ductal adenocarcinoma tumors. Nevertheless, heterogeneous tumor environment and complex thermal interaction phenomena that are established under hyperthermic conditions can lead to under/over estimation of laser thermotherapy efficacy. Using numerical modeling, this paper presents an optimized laser setting for Nd:YAG laser delivered by a bare optical fiber (300 µm in diameter) at 1064 nm working in continuous mode within a power range of 2–10 W. For the thermal analysis, patient-specific 3D models were used, consisting of tumors in different portions of the pancreas. The optimized laser power and time for ablating the tumor completely and producing thermal toxic effects on the possible residual tumor cells beyond the tumor margins were found to be 5 W for 550 s, 7 W for 550 s, and 8 W for 550 s for the pancreatic tail, body, and head tumors, respectively. Based on the results, during the laser irradiation at the optimized doses, thermal injury was not evident either in the 15 mm lateral distances from the optical fiber or in the nearby healthy organs. The present computational-based predictions are also in line with the previous ex vivo and in vivo studies, hence, they can assist in the estimation of the therapeutic outcome of laser ablation for pancreatic neoplasms prior to clinical trials.

Cell to whole organ global sensitivity analysis on a four-chamber heart electromechanics model using Gaussian processes emulators.

Cardiac pump function arises from a series of highly orchestrated events across multiple scales. Computational electromechanics can encode these events in physics-constrained models. However, the large number of parameters in these models has made the systematic study of the link between cellular, tissue, and organ scale parameters to whole heart physiology challenging. A patient-specific anatomical heart model, or digital twin, was created. Cellular ionic dynamics and contraction were simulated with the Courtemanche-Land and the ToR-ORd-Land models for the atria and the ventricles, respectively. Whole heart contraction was coupled with the circulatory system, simulated with CircAdapt, while accounting for the effect of the pericardium on cardiac motion. The four-chamber electromechanics framework resulted in 117 parameters of interest. The model was broken into five hierarchical sub-models: tissue electrophysiology, ToR-ORd-Land model, Courtemanche-Land model, passive mechanics and CircAdapt. For each sub-model, we trained Gaussian processes emulators (GPEs) that were then used to perform a global sensitivity analysis (GSA) to retain parameters explaining 90% of the total sensitivity for subsequent analysis. We identified 45 out of 117 parameters that were important for whole heart function. We performed a GSA over these 45 parameters and identified the systemic and pulmonary peripheral resistance as being critical parameters for a wide range of volumetric and hemodynamic cardiac indexes across all four chambers. We have shown that GPEs provide a robust method for mapping between cellular properties and clinical measurements. This could be applied to identify parameters that can be calibrated in patient-specific models or digital twins, and to link cellular function to clinical indexes.

Higher Computed Tomography (CT) Scan Resolution Improves Accuracy of Patient-specific Mandibular Models When Compared to Cadaveric Gold Standard

3D-printed patient-specific anatomical models are becoming an increasingly popular tool for planning reconstructive surgeries to treat oral cancer. Currently there is a lack of information regarding model accuracy, and how the resolution of the computed tomography (CT) scan affects the accuracy of the final model. The primary objective of this study was to determine the CT z-axis resolution necessary in creating a patient specific mandibular model with clinically acceptable accuracy for global bony reconstruction. This study also sought to evaluate the effect of the digital sculpting and 3D printing process on model accuracy. This was a cross-sectional study using cadaveric heads obtained from the Ohio State University Body Donation Program. The first independent variable is CT scan slice thickness of either 0.675, 1.25, 3.00, or 5.00mm. The second independent variable is the three produced models for analysis (unsculpted, digitally sculpted, 3D printed). The degree of accuracy of a model as defined by the root mean square (RMS) value, a measure of a model's discrepancy from its respective cadaveric anatomy. All models were digitally compared to their cadaveric bony anatomy using a metrology surface scan of the dissected mandible. The RMS value of each comparison evaluates the level of discrepancy. One-way ANOVA tests (P<.05) were used to determine statistically significant differences between CT scan resolutions. Two-way ANOVA tests (P<.05) were used to determine statistically significant differences between groups. CT scans acquired for 8 formalin-fixed cadaver heads were processed and analyzed. The RMS for digitally sculpted models decreased as slice thickness decreased, confirming that higher resolution CT scans resulted in statistically more accurate model production when compared to the cadaveric gold standard. Furthermore, digitally sculpted models were significantly more accurate than unsculpted models (P<.05) at each slice thickness. Our study demonstrated that CT scans with slice thicknesses of 3.00mm or smaller created statistically significantly more accurate models than models created from slice thicknesses of 5.00mm. The digital sculpting process statistically significantly increased the accuracy of models and no loss of accuracy through the 3D printing process was observed.

A state-of-the-art guide about the effects of sterilization processes on 3D-printed materials for surgical planning and medical applications: A comparative study.

Surgeons use different medical devices in the surgery, such as patient-specific anatomical models, cutting and positioning guides, or implants. These devices must be sterilized before being used in the operation room. There are many sterilization processes available, with autoclave, hydrogen peroxide, and ethylene oxide being the most common in hospital settings. Each method has both advantages and disadvantages in terms of mechanics, chemical interaction, and post-treatment accuracy. The aim of the present study is to evaluate the dimensional and mechanical effect of the most commonly used sterilization techniques available in clinical settings, i.e., Autoclave 121, Autoclave 134, and hydrogen peroxide (HPO), on 11 of the most used 3D-printed materials fabricated using additive manufacturing technologies. The results showed that the temperature (depending on the sterilization method) and the exposure time to that temperature influence not only the mechanical behavior but also the original dimensioning planned on the 3D model. Therefore, HPO is a better overall option for most of the materials evaluated. Finally, based on the results of the study, a recommendation guide on sterilization methods per material, technology, and clinical application is presented.

PO-02-229 AUTOMATED LOCALIZATION OF ATRIAL ECTOPIC BEATS USING 12-LEAD ECG MEAN SPATIO-TEMPORAL VECTOR POSITION: IMPORTANCE OF INCORPORATING PATIENT-SPECIFIC ANATOMIC MODELS

Localizing the origin of atrial ectopic activity from the 12-lead ECG can be challenging, particularly in patients with atrial pathology. To identify the origin of paced atrial ectopic beats (simulating atrial ectopy) using software that quantifies the mean spatio-temporal vector position of cardiac depolarization projected onto generic and patient-specific atrial models. 12-lead ECG data were collected during sinus rhythm (SR) and during regular pacing from the high and low right atrium (HRA/LRA), proximal and distal coronary sinus (CS), pulmonary veins (LSPV, LIPV, RSPV, RIPV), and left atrial appendage (LAA). The origin and trajectory of the atrial signals were calculated with software that analyzes P-waves from the 12-lead ECG and automatically constructs a net vector of electrical activity projected onto a standard generic model of human atria (CineECG; Nieuwerbrug, The Netherlands). The model atria were split into 9 segments, and the software accuracy was scored based on localization of the paced atrial signal origin to the correct segment. To see if patient-specific anatomy improved localization, we also incorporated atrial anatomy from cardiac MRIs acquired from a subset of 12 patients and compared localization to the generic model. We enrolled 19 patients (mean age 70±9, 4 female) with paroxysmal (63%) or persistent (37%) AF and left atrial (LA) enlargement (mean LA volume 58 cc/m2) undergoing pulmonary vein isolation for treating AF. Using the generic atrial model, the software correctly localized 105/142 (74%) beats to the correct atrial segment (Figure). Accuracy was better for RA compared to LA signals (90% vs. 62%, p < 0.05). Localization worked best in the coronary sinus (19/19, 100%) and worst in the LPVs (14/33, 42%). Patient-specific models improved localization of PV signals, particularly left-sided ones (generic vs. patient-specific: RPVs 70% vs 85%, p = 0.36, LPVs 42% vs 76%, p = 0.03). Accuracy improved and was similar for RA vs. LA localization when using patient-specific models (90% vs. 82%, p = 0.48). The novel software algorithm can automatically localize paced signals in both the left and right atria despite significant atrial pathology. Patient-specific anatomic models improve localization. This software holds promise for automatically localizing and classifying atrial arrhythmias and guiding therapy, including catheter ablation, based on standard 12-lead ECG data.

Automated localization of atrial ectopic beats using 12-lead ECG mean spatio-temporal vector position: Importance of incorporating patient-specific anatomic models

Las complicaciones en los pacientes hospitalizados en sala convencional suelen ser frecuentes y estar asociadas a mayor mortalidad, aumento de la estancia hospitalaria e incremento del coste sanitario. Las constantes fisiológicas monitorizadas habitualmente en los pacientes pueden predecir el riesgo de presentar estas complicaciones. Los sistemas de respuesta rápida son dispositivos de atención a pacientes en riesgo de descompensación en sala de hospitalización que se han creado con el objetivo de detectar estos episodios de forma temprana e instaurar un tratamiento precoz. Para identificar estas situaciones de riesgo están disponibles diferentes escalas de valoración basadas en los parámetros fisiológicos monitorizados. Funcionan mediante un sumatorio de puntos donde a mayor puntuación el paciente presenta un riesgo más alto de descompensación, facilitando la decisión de en qué momento activar el sistema de respuesta. La monitorización remota en sala juega un papel fundamental a modo de nexo entre la detección de estos pacientes y la activación de los sistemas. Actualmente los aparatos y sistemas de monitorización, tales como dispositivos portátiles, sensores inteligentes o dispositivos contactless están disponibles, permitiendo medir estas variables de forma simple, fiable y fácilmente exportable, disminuyendo así el error de transcripción y la carga de trabajo. Además, muchos de estos sistemas de monitorización permiten calcular de manera automática estas diferentes escalas e incluso activar directamente a los sistemas de respuesta rápida, permitiéndoles dar una respuesta proporcional al grado de alteración. En vista de los beneficios descritos sobre la implantación de estos sistemas, el presente artículo realiza una revision de sus componentes y de las herramientas actuales con las que cuenta para optimizar su utilidad.Patients admitted in hospital wards often present complications which are associated with an increase in mortality, length of stay and healthcare costs. The rapid response systems are basically organizations of care to inward patients who potentially can present these events with the objective of an early detection. In order to provide complementary monitoring, proper treatment or intensive care unit transfer if needed. The risk of developing adverse events could be predicted through the vital signs routinely monitored in hospitalized patients. Remote monitoring of the physiological parameters in the ward plays a fundamental role as a link between the detection of these patients and the activation of the rapid response system. Based on the information obtained there are available different assessment scales to identify risk situations. They work through a punctuation system, understanding that a higher score means higher risk of deteriorating; this information will support the decision process which finally activates the response system. Currently, monitoring devices and systems such as portable devices, smart sensors, contactless devices are widely available, allowing these variables to be measured in a simple, reliable and easily exportable way, reducing transcription error and workload. In addition, many of these monitoring systems allow these different scales to be calculated automatically and even directly activating the rapid response systems, allowing them to give a response proportional to the degree of alteration. In view of the benefits described with the implementation of these systems, this article reviews their components and the current tools that we have in order to optimize their usefulness.

Quality assurance in 3D-printing: A dimensional accuracy study of patient-specific 3D-printed vascular anatomical models.

3D printing enables the rapid manufacture of patient-specific anatomical models that substantially improve patient consultation and offer unprecedented opportunities for surgical planning and training. However, the multistep preparation process may inadvertently lead to inaccurate anatomical representations which may impact clinical decision making detrimentally. Here, we investigated the dimensional accuracy of patient-specific vascular anatomical models manufactured via digital anatomical segmentation and Fused-Deposition Modelling (FDM), Stereolithography (SLA), Selective Laser Sintering (SLS), and PolyJet 3D printing, respectively. All printing modalities reliably produced hand-held patient-specific models of high quality. Quantitative assessment revealed an overall dimensional error of 0.20 ± 3.23%, 0.53 ± 3.16%, -0.11 ± 2.81% and -0.72 ± 2.72% for FDM, SLA, PolyJet and SLS printed models, respectively, compared to unmodified Computed Tomography Angiograms (CTAs) data. Comparison of digital 3D models to CTA data revealed an average relative dimensional error of -0.83 ± 2.13% resulting from digital anatomical segmentation and processing. Therefore, dimensional error resulting from the print modality alone were 0.76 ± 2.88%, + 0.90 ± 2.26%, + 1.62 ± 2.20% and +0.88 ± 1.97%, for FDM, SLA, PolyJet and SLS printed models, respectively. Impact on absolute measurements of feature size were minimal and assessment of relative error showed a propensity for models to be marginally underestimated. This study revealed a high level of dimensional accuracy of 3D-printed patient-specific vascular anatomical models, suggesting they meet the requirements to be used as medical devices for clinical applications.

Patient-specific Composite Anatomic Models: Improving the Foundation for Craniosynostosis Repair.

Preoperative surgical planning incorporating computer-aided design and manufacturing is increasingly being utilized today within the fields of craniomaxillofacial, orthopedic, and neurosurgery. Application of these techniques for craniosynostosis reconstruction can include patient-specific anatomic reference models, "normal" reference models or patient-specific cutting/marking guides based on the presurgical plan. The major challenge remains the lack of tangible means to transfer the preoperative plan to the operating table. We propose a simple solution to utilize a digitally designed, 3D-printed "composite model" as a structural template for cranial vault reconstruction. The composite model is generated by merging the abnormal patient cranial anatomy with the "dural surface topography" of an age-matched, sex-matched, and ethnicity-matched normative skull model. We illustrate the applicability of this approach in 2 divergent cases: 22-month-old African American male with sagittal synostosis and 5-month-old White male with metopic synostosis. The aim of this technical report is to describe our application of this computer-aided design and modeling workflow for the creation of practical 3D-printed skulls that can serve as intraoperative frameworks for the correction of craniosynostosis. With success in our first 2 cases, we believe this approach of a composite model is another step in reducing our reliance on subjective guesswork, and the fundamental aspect of the workflow has a wider application within the field of craniofacial surgery for both clinical patient care and education.

Updates in the Use of 3D Bioprinting in Biomedical Engineering for Clinical Application: A Review

Three-dimensional (3D) printing is one of the most well-liked new innovative and promising manufacturing techniques, which has demonstrated tremendous potential for the creation of biostructures in tissue engineering, particularly for bones, orthopaedic tissues, and related organs.  3D printing for the medical industry was considered a lofty pipe dream. Time and money, though, made it a reality. Today's 3D printing technology has a significant possibility to assist pharmaceutical and medical corporations in developing more specialised pharmaceuticals, enabling the quick creation of medical implants, and transforming how doctors and surgeons approach surgical planning. In today's practise of precision medicine and for individualised therapies, patient-specific anatomical models that are 3D printed are becoming increasingly helpful tools. In contrast to the conventional use of 3D printing to create cell-free scaffolds, 3D bioprinting requires various technical methods, such as biomimicry, autonomous self-assembly, and mini-tissue building blocks, to create 3D structures with mechanical and biological properties suitable for the deposition of living cells and the restoration of tissue and organ function. Cells, bioinks, and bioprinters are all necessary components of the bioprinting process, and each one of them has biological, technological, ethical, and cost- and clinically-effectiveness-related issues. As a result, there are several difficulties in integrating 3D bioprinting into widespread clinical practise. Currently, there are multiple applications for 3D bioprinting such as in surgery, cardiovascular system, musculoskeletal and even in drug screening. All of which will be discussed in this review.

An Introductory Module in Medical Image Segmentation for BME Students

To support recent trends toward the use of patient-specific anatomical models from medical imaging data, we present a learning module for use in the undergraduate BME curriculum that introduces image segmentation, the process of partitioning digital images to isolate specific anatomical features. Five commercially available software packages were evaluated based on their perceived learning curve, ease of use, tools for segmentation and rendering, special tools, and cost: ITK-SNAP, 3D Slicer, OsiriX, Mimics, and Amira. After selecting the package best suited for a stand-alone course module on medical image segmentation, instructional materials were developed that included a general introduction to imaging, a tutorial guiding students through a step-by-step process to extract a skull from a provided stack of CT images, and a culminating assignment where students extract a different body part from clinical imaging data. This module was implemented in three different engineering courses, impacting more than 150 students, and student achievement of learning goals was assessed. ITK-SNAP was identified as the best software package for this application because it is free, easiest to learn, and includes a powerful, semi-automated segmentation tool. After completing the developed module based on ITK-SNAP, all students attained sufficient mastery of the image segmentation process to independently apply the technique to extract a new body part from clinical imaging data. This stand-alone module provides a low-cost, flexible way to bring the clinical and industry trends combining medical image segmentation, CAD, and 3D printing into the undergraduate BME curriculum.

The Effect of Segmentation Variability in Forward ECG Simulation.

Segmentation of patient-specific anatomical models is one of the first steps in Electrocardiographic imaging (ECGI). However, the effect of segmentation variability on ECGI remains unexplored. In this study, we assess the effect of heart segmentation variability on ECG simulation. We generated a statistical shape model from segmentations of the same patient and generated 262 cardiac geometries to run in an ECG forward computation of body surface potentials (BSPs) using an equivalent dipole layer cardiac source model and 5 ventricular stimulation protocols. Variability between simulated BSPs for all models and protocols was assessed using Pearson's correlation coefficient (CC). Compared to the BSPs of the mean cardiac shape model, the lowest variability (average CC = 0.98 ± 0.03) was found for apical pacing whereas the highest variability (average CC = 0.90 ± 0.23) was found for right ventricular free wall pacing. Furthermore, low amplitude BSPs show a larger variation in QRS morphology compared to high amplitude signals. The results indicate that the uncertainty in cardiac shape has a significant impact on ECGI.