Anatomical Models Research Articles

3D printed anatomical models for preoperative planning of complex orthopaedic surgical operations of the lower limb

Complex multifragmentary fractures of the pelvis and lower limb are a major challenge for operative orthopaedic surgery. The successful metallic osteosynthesis of the fractures requires an extensive planning process, which can be dramatically improved with the 3D printed anatomical models – replicas of the bones with high fidelity generated from CT and MRI imaging studies. The models represent the spatial properties of the skeleton with a dimensional error of approximately 8 μm/mm. They can be manufactured easily and with high reproducibility with commercial or open-access software and FDM 3D printing. Orthopaedic surgeons use the preoperative models as a highly accurate physical model of complex fractures and allow them to choose and prepare the optimal operation window, surgical tools, metallic implants, and as a template for recontouring (pre-bending) of fixation plates, which will be used during the surgery. The approach provides a new level of personalisation in operative orthopaedic surgery and significantly reduces the duration of the operation, the amount of blood loss and the intraoperative X-rays. The proper anatomical repositioning of the fracture is achieved at a higher rate in the surgeries, which are planned with 3D-printed anatomical models. The planning of surgical operations with 3D-printed models increases the overall effectiveness of the surgery, reduces the rate of post-surgical complications, and allows for a patient-specific approach.The paper will describe the methods for manufacturing accurate 3D-printed anatomical models representing complex fractures and their application for preoperative planning of orthopaedic operation.The anatomical 3D models were generated from CT datasets with open-access medical informatics software (3D Slicer) and 3D printed on an FDM 3D printer with minimal thermal deformation (Polylactate, PLA). The finished models were used for preoperative planning of complex orthopaedic operations, including high-energy multifragmentary hip, knee and ankle fractures. The preoperative planning included selecting surgical access, preparing tools and implants, and contouring (pre-bending) metal plates for metallic osteosynthesis. Several parameters, such as operation time, blood loss, intraoperative X-rays, and the achievement of anatomical reduction of the fractures, were observed in order to measure the quality of the operations.Accurate anthropomorphic 3D models representing the spatial properties of the bones can be generated from tomographic imaging studies easily and accurately, even with open-source software. They can be utilised as a tool for preoperatively planning complex orthopaedical operations of the lower limb. Using 3D-printed models allows a patient-specific approach, which leads to good anatomical reduction and favourable functional results in complex surgeries regarding the pelvis, acetabulum, tibial plateau, and calcaneus.The methods described in the paper are routinely used for the preoperative planning of complex orthopaedical operations regarding the lower limb. In the future, they will be combined with the implementation of 3D-printed personalised titanium implants to achieve good anatomical reduction even for the most challenging multigragmental fractures.In the paper, we described the technical aspects and clinical considerations for the preoperative planning of complex orthopaedical operations, which can assist engineers and clinicians alike in implementing the useful method in clinical practice.

A novel CNN-based image segmentation pipeline for individualized feline spinal cord stimulation modeling

Objective. Spinal cord stimulation (SCS) is a well-established treatment for managing certain chronic pain conditions. More recently, it has also garnered attention as a means of modulating neural activity to restore lost autonomic or sensory-motor function. Personalized modeling and treatment planning are critical aspects of safe and effective SCS (Rowald and Amft 2022 Front. Neurorobotics 16 983072, Wagner et al 2018 Nature 563 65–71). However, the generation of spine models at the required level of detail and accuracy requires time and labor intensive manual image segmentation by human experts. This study aims to develop a maximally automated segmentation routine capable of producing high-quality anatomical models, even with limited data, to facilitate safe and effective personalized SCS treatment planning. Approach. We developed an automated image segmentation and model generation pipeline based on a novel convolutional neural network (CNN) architecture trained on feline spinal cord magnetic resonance imaging data. The pipeline includes steps for image preprocessing, data augmentation, transfer learning, and cleanup. To assess the relative importance of each step in the pipeline and our choice of CNN architecture, we systematically dropped steps or substituted architectures, quantifying the downstream effects in terms of tissue segmentation quality (Jaccard index and Hausdorff distance) and predicted nerve recruitment (estimated axonal depolarization). Main results. The leave-one-out analysis demonstrated that each pipeline step contributed a small but measurable increment to mean segmentation quality. Surprisingly, minor differences in segmentation accuracy translated to significant deviations (ranging between 4% and 13% for each pipeline step) in predicted nerve recruitment, highlighting the importance of careful workflow design. Additionally, transfer learning techniques enhanced segmentation metric consistency and allowed generalization to a completely different spine region with minimal additional training data. Significance. To our knowledge, this work is the first to assess the downstream impacts of segmentation quality differences on neurostimulation predictions. It highlights the role of each step in the pipeline and paves the way towards fully automated, personalized SCS treatment planning in clinical settings.

Bridging theory and practice: enhancing medical education through simulation-based training methods

ntroduction. With the complexities of contemporary healthcare systems and the paramount importance of high-quality patient care, Simulation-Based Medical Education (SBME) has emerged as a pivotal innovation in the process of training healthcare professionals. This study explores the integration of SBME in undergraduate medical education to bridge the gap between theoretical knowledge and clinical practice, thereby preparing students with the necessary competencies for effective healthcare delivery. Material and methods. Employing a narrative review approach, this study meticulously examined relevant literature from multiple databases, including Google Scholar, PubMed, and MedEdPublish. Following objectives, we chose the sources that were best suited to explore our research questions, focusing on keywords such as „simulation”, „undergraduate medical education”, „simulation-based medical education”, „theoretical frameworks”, „procedural framework” „curriculum design”, „training efficacy”, and „training evaluation” with no restriction for the date of publications. Results. The review identified foundational educational theories underpinning SBME, such as Experiential Learning Theory and Adult Learning Theory, and traced the evolution of simulation methods from simple anatomical models to sophisticated high-fidelity simulators and virtual reality technologies. Various simulation techniques, including task trainers, manikins, and standardized patients, were analyzed for their educational value. Significant benefits of SBME, such as enhanced safety, repeatability, and adaptability, were highlighted alongside challenges like high costs and limited access. Comparative analysis revealed SBME’s advantages over traditional clinical education, particularly in learning efficiency and scalability. Conclusions. SBME represents a transformative approach in undergraduate medical education, offering a dynamic and interactive learning environment that significantly enhances clinical skills, critical thinking, and confidence. Despite its challenges, the integration of simulation-based methodologies into medical curricula is essential for addressing the evolving needs of medical training and improving patient care outcomes. Future research should focus on longitudinal studies to assess the long-term impact of SBME on clinical practice and explore the integration of emerging technologies to enhance the efficacy and accessibility of simulation-based training.

Current trends and outlook of 3D printing in vascular surgery

BackgroundThree-dimensional (3D) printing is an additive manufacturing technique capable of the rapid prototyping of objects not feasible by other manufacturing methods. Vascular surgery has welcomed this technology and found it useful in many areas. MethodsThe integration of 3D-printed models in surgical training offers to bridge existing training gaps and increase exposure to complex pathology, while maintaining patient safety, during this time where the surgical education paradigm is shifting. Sterilizable 3D-printed models are being used to aid in the development of physician-modified endografts with excellent results. Rehearsing with patient-specific anatomic models before surgery has demonstrated evidence in improving operator confidence and decreased operative and fluoroscopy times. Research trends have demonstrated that technology such as printed custom implantable devices with tunable chemical and physical properties may be on the horizon. ResultsDespite all of this, the current use of 3D printing in vascular surgery is limited by factors such as materials, time constraints, and initial technical challenges to developing a printing protocol. All of these are areas actively being researched to improve applicability and adaptation of 3D printing. As its use continues to grow, 3D printing may find utility in meeting the global need for safe, timely, and affordable vascular surgical care. ConclusionsThe analysis delves into current uses, challenges, and future visions for this technology, emphasizing its transformative influence in the field of vascular surgery.

Artificial Intelligence-Based Thermal Imaging for Breast Tumor Location and Size Estimation Using Thermal Impedance

Abstract Tumors can be detected from a temperature gradient due to high vascularization and increased metabolic activity of cancer cells. Thermal infrared images have been recognized as potential alternatives to detect these tumors. However, even the use of artificial intelligence directly on these images has failed to accurately locate and detect the tumor size due to the low sensitivity of temperatures and position within the breast. Thus, we aimed to develop techniques based on applying the thermal impedance method and artificial intelligence to determine the origin of the heat source (abnormal cancer metabolism) and its size. The low sensitivity to tiny and deep tumors is circumvented by utilizing the concept of thermal impedance and artificial intelligence techniques such as deep learning. We describe the development of a thermal model and the creation of a database based on its solution. We also outline the choice of detectable parameters in the thermal image, the use of deep learning libraries, and network training using convolutional neural networks (CNNs). Lastly, we present tumor location and size estimates based on thermographic images obtained from simulated thermal models of a breast, using Cartesian geometry and a scanned geometric shape of an anatomical phantom model.

Structured light for touchless 3D registration in video-based surgical navigation

PurposeArthroscopic surgery, with its inherent difficulties on visibility and maneuverability inside the joint, poses significant challenges to surgeons. Video-based surgical navigation (VBSN) has proven to have clinical benefits in arthroscopy but relies on a time-consuming and challenging surface digitization using a touch probe to accomplish registration of intraoperative data with preoperative anatomical models. This paper presents an off-the-shelf laser scanner for noninvasive registration that enables an increased area of reachable region.MethodsOur solution uses a standard arthroscope and a light projector with visual markers for real-time extrinsic calibration. Nevertheless, the shift from a touch probe to a laser scanner introduces a new challenge—the presence of a significant amount of outliers resulting from the reconstruction of nonrigid structures. To address this issue, we propose to identify the structures of interest prior to reconstruction using a deep learning-based semantic segmentation technique.ResultsExperimental validation using knee and hip phantoms, as well as ex-vivo data, assesses the laser scanner’s effectiveness. The integration of the segmentation model improves results in ex-vivo experiments by mitigating outliers. Specifically, the laser scanner with the segmentation model achieves registration errors below 2.2 mm, with the intercondylar region exhibiting errors below 1 mm. In experiments with phantoms, the errors are always below 1 mm.ConclusionThe results show the viability of integrating the laser scanner with VBSN as a noninvasive and potential alternative to traditional methods by overcoming surface digitization challenges and expanding the reachable region. Future efforts aim to improve hardware to further optimize performance and applicability in complex procedures.

Frank Cockett and the story of the ancient anatomical wax model of the left iliac vein compression

In 1988, Professor Donini organized an international phlebo-lymphology meeting at the University of Ferrara in Italy. At that time, I was a young surgical resident with the task of picking up Professor Frank Cockett at the railway station. I recognized him immediately, introduced myself and, together, we crossed the station square to my car. I asked him where he wanted to be taken, and he asked me to go to the anatomical museum of the University. We arrived just before the closure time, and Mister Cockett was intrigued and enthusiastic about an anatomical wax specimen.

Use of a 3D Printer in the Prototyping of an Anatomical Model of the Human Heart with Morphophysiological Alterations

Use of a 3D Printer in the Prototyping of an Anatomical Model of the Human Heart with Morphophysiological Alterations

Validation of a 3D-printed model of cryptoglandular perianal fistulas.

Visualising the course of a complex perianal fistula on imaging can be difficult. It has been postulated that three-dimensional (3D) models of perianal fistulas improve understanding of the perianal pathology, contribute to surgical decision-making and might even improve future outcomes of surgical treatment. The aim of the current study is to investigate the accuracy of 3D-printed models of perianal fistulas compared with magnetic resonance imaging (MRI). MRI scans of 15 patients with transsphincteric and intersphincteric fistulas were selected and then assessed by an experienced abdominal and colorectal radiologist. A standardised method of creating a 3D-printed anatomical model of cryptoglandular perianal fistula was developed by a technical medical physicist and a surgeon in training with special interest in 3D printing. Manual segmentation of the fistula and external sphincter was performed by a trained technical medical physicist. The anatomical models were 3D printed in a 1:1 ratio and assessed by two colorectal surgeons. The 3D-printed models were then scanned with a 3D scanner. Volume of the 3D-printed model was compared with manual segmentation. Inter-rater reliability statistics were calculated for consistency between the radiologist who assessed the MRI scans and the surgeons who assessed the 3D-printed models. The assessment of the MRI was considered the 'gold standard'. Agreement between the two surgeons who assessed the 3D printed models was also determined. Consistency between the radiologist and the surgeons was almost perfect for classification (κ = 0.87, κ = 0.87), substantial for complexity (κ = 0.73, κ = 0.74) and location of the internal orifice (κ = 0.73, κ = 0.73) and moderate for the percentage of involved external anal sphincter in transsphincteric fistulas (ICC 0.63, ICC 0.52). Agreement between the two surgeons was substantial for classification (κ = 0.73), complexity (κ = 0.74), location of the internal orifice (κ = 0.75) and percentage of involved external anal sphincter in transsphincteric fistulas (ICC 0.77). Our 3D-printed anatomical models of perianal fistulas are an accurate reflection of the MRI. Further research is needed to determine the added value of 3D-printed anatomical models in preoperative planning and education.

Perspectives on Optimized Transcranial Electrical Stimulation Based on Spatial Electric Field Modeling in Humans.

Background: Transcranial electrical stimulation (tES) generates an electric field (or current density) in the brain through surface electrodes attached to the scalp. Clinical significance has been demonstrated, although with moderate and heterogeneous results partly due to a lack of control of the delivered electric currents. In the last decade, computational electric field analysis has allowed the estimation and optimization of the electric field using accurate anatomical head models. This review examines recent tES computational studies, providing a comprehensive background on the technical aspects of adopting computational electric field analysis as a standardized procedure in medical applications. Methods: Specific search strategies were designed to retrieve papers from the Web of Science database. The papers were initially screened based on the soundness of the title and abstract and then on their full contents, resulting in a total of 57 studies. Results: Recent trends were identified in individual- and population-level analysis of the electric field, including head models from non-neurotypical individuals. Advanced optimization techniques that allow a high degree of control with the required focality and direction of the electric field were also summarized. There is also growing evidence of a correlation between the computationally estimated electric field and the observed responses in real experiments. Conclusions: Computational pipelines and optimization algorithms have reached a degree of maturity that provides a rationale to improve tES experimental design and a posteriori analysis of the responses for supporting clinical studies.

Impact of magnetic data collection prior to electroanatomic model creation on acute outcomes in de novo AF procedures

Abstract Background As ablation and electroanatomical mapping technology evolve, workflows change to maximize the impact on procedural efficacy, safety, and efficiency. In a magnetic-primary navigation mode, optimization of the magnetic-impedance field links (VoXels) must be considered to provide accurate environments for anatomic modeling, mapping, and lesion placement. To achieve this accuracy and optimize speed of data collection, many operators have adopted the strategy of collecting VoXels using an ablation catheter prior to introduction of a multipolar mapping catheter. However, the impact of this workflow on procedural metrics has not yet been quantified in a multicenter, international cohort. Objective Assess the impact of optimizing the magnetic navigation field using an ablation catheter prior to collecting left atrial (LA) data using a high-density diagnostic tool on acute outcomes in de novo atrial fibrillation (AF) ablation procedures. Methods Acute observational data from 199 de novo pulmonary vein isolation (PVI) cases was prospectively collected from 56 operators at 42 centers in Europe, the US, and Australia. Procedural metrics, modeling workflow, ablation technology used, and acute outcomes were collected. Results Of 199 de novo AF (62.3% PAF) ablation procedures, VoXels were collected with an ablation catheter prior to LA map collection with a multipolar catheter in 65/199 (32.7%) cases; the remainder collected with multipolar catheter first. An irrigated, contact force sensing RF ablation catheter was used in all procedures. Mean procedure duration was similar in procedures in which VoXels were collected prior to map collection (VC) compared to those that did not (nVC) (107.0±46.8 min and 115.4±59.2 min, respectively (p=0.28)). Mean fluoroscopy time was significantly reduced in VC cases compared to nVC cases (3.0±4.5 min and 5.3±5.6 min, respectively (p=0.002)). Total RF duration was significantly reduced in VC cases compared to nVC cases (904±444s and 1063±632s, respectively (p=0.04)). There was also a significant reduction in fluid delivered through the ablation catheter in VC cases, 369±159mL, compared to nVC cases, 520±243mL (p<0.001). Acute success rates were similar between groups: 98.5% for VC cases and 99.2% for nVC cases (p=0.64). Conclusion In this international cohort, cases where VoXels were collected prior to map and model collection had significantly reduced fluoroscopy times, RF durations, and fluid volumes delivered through the ablation catheter, potentially as a result of improved model quality. Despite the introduction of an additional step to the workflow, there was a trend toward shorter procedures when VoXels were collected prior to map and model collection, although it did not achieve statistical significance. Better quantification of the impact of this workflow on model quality, along with analysis of long-term patient outcomes, is warranted.Procedure Duration Comparison_VC vs. nVCFluoroscopy Comparison_VC vs. nVC

Imageless electrocardiographic imaging for atrial electrophysiological characterization: a validation study

Abstract Background The mechanisms responsible for atrial fibrillation (AF) are not yet fully understood and treatment strategies remain suboptimal. Electrocardiographic imaging (ECGi) could provide new insights into the arrhythmogenic substrate’s characterization. Objective To validate a novel imageless ECGi technique against electroanatomical mapping (EAM) systems to evaluate its use in guiding therapeutic decisions. Methods Periprocedural ECGi was implemented on 12 patients submitted for pulmonary vein isolation with EAM arriving in sinus rhythm. As opposed to current methods requiring patient-specific torso-heart geometries from CT/MRI scans, the employed ECGi system computes a cardiac anatomical model from a 3D-camera torso reconstruction. Both ECGi signals and intracavitary recordings were acquired simultaneously during catheter stimulation from a single atrial site at two different pacing cycles and local activation time (LAT) maps were derived. As a result, an ECGi and an EAM map were obtained for both 300 and 600 ms distal coronary sinus pacing for each patient. These were then compared by splitting the left atrial geometries from both mapping methodologies into 7 predefined, clinically relevant regions and identifying the earliest and latest activation sites in each. Results For all 24 LAT maps under consideration, the pacing sites identified by non-invasive ECGi maps were consistent with those determined through EAM as 100% accuracy was obtained in terms of detecting the first activated region. As well as the correct stimulation area, according to the corresponding EAM instance, the earliest ECGi activations were also found in one of its immediate neighbours in 38% of the maps, indicating a broader region of interest. Regarding the latest activation sites, ECGi achieved an accurate localisation in 92% of the activation sequences and, similarly, other neighbouring regions showed the maximum LAT in one third of the studied maps. Conclusions Considering the spatial resolution constraints inherent to its non-invasive nature, imageless ECGi activation patterns are congruent with the gold-standard technique for substrate mapping without the need for prior medical imaging.

Effects of different types of fibrotic remodelling in areas of low voltage on atrial fibrillation dynamics: an in-silico study

Abstract Background Personalized computational models include the effects of personalised anatomy and atrial fibrillation (AF) remodelling in a framework that can be used to investigate patient-specific AF mechanisms and test treatment response, but modelling fibrosis remains an unresolved matter. The interpretation of regions exhibiting low voltage in electroanatomic mapping data at different pacing rates also remain unclear. However, these occurrences are correlated with fibrotic remodelling. We aimed to use patient-specific simulations to investigate the effects of fibrosis type on AF properties by modelling conduction velocity slowing, changes in ionic channels, and replacement fibrosis, incorporated in regions of low voltage identified through omnipolar mapping at different pacing rates. Methods Local activation times (LATs) voltage and geometry data were obtained from patients undergoing ablation for persistent AF. LATs were collected in sinus rhythm with coronary sinus pacing at pacing interval (PIs) of 250ms and 600ms. For a total of 10 cases, personalised anatomical models were constructed for electrophysiology simulations, and analysed using an automated pipeline in python. For conductivity models, areas with peak omnipolar voltage (OV) below 0.5mV were assigned low conduction velocity. To incorporate ionic changes, the ionic properties were altered in fibrotic regions (peak OV < 0.5mV). In the simulations where replacement fibrosis was included through a probabilistic percolation method, percolation was modelled by using random number generator to probabilistically remove elements of low voltage. Pulmonary vein isolation was simulated in each model after 5s of AF, and wavefront propagation patterns were analysed to quantify the number of rotational areas or areas of wavefront break-up in 7 anatomical segments. Results The models with conductivity fibrotic remodelling demonstrated rotational drivers in more than two LA anatomical segments for both CS250ms pacing rate and CS600ms pacing rate across all 10 cases. The anterior wall exhibited the largest degree of rotational activity in 7 out of 10 cases for CS250ms pacing rate and in 9 out of 10 cases for CS600ms pacing rate (Figure A). The combination of percolation and conductivity remodelling also exhibited rotational activity on the anterior wall in 9 out of 10 cases at CS250ms pacing rate, and 7 out of 10 cases for CS600ms pacing rate. For the simulations where replacement fibrosis was included (percolation), both the roof and anterior wall exhibited the largest degree of rotational activity in 5 out of 10 cases at CS250ms pacing rate; while at CS600ms pacing rate, the posterior walled exhibited the majority of rotational activity in 7 cases (Figure B). All fibrosis models containing ionic changes terminated in more than half of the 10 cases for both pacing rates (CS250ms and 600). Conclusion The impact of low voltage on fibrotic remodelling causes complex effects on AF dynamics.

Impact of phase-correction of late-gadolinium enhancement images on quantification of scar metrics and in-silico VT-modelling in patients with an ischemic cardiomyopathy

Abstract Background Late gadolinium enhancement (LGE) is used to perform tissue characterization and has become the cornerstone to guide treatment of ventricular tachyarrhythmia (VT). Traditionally, LGE acquisition is reconstructed in two distinct forms: non-phase corrected magnitude (MIR) and phase-corrected inversion recovery (PSIR) images. However, the influence of MIR vs. PSIR on the quantification of scar metrics and the repercussion on estimating myocardial arrhythmogenicity have not been comprehensively explored. Aim This study investigated the influence of PSIR and MIR LGE on the quantification of scar metrics in a randomly selected cohort of patients with ischemic cardiomyopathy who had undergone imaging prior to ICD implantation and had received device therapy during follow-up. In addition, this study assessed how these image variations affect functional estimation of arrhythmogenicity using computational modelling. Methods ADAS 3D LV was used to generate scar maps from 2D PSIR and MIR LGE images in 10 patients. The extent of variation in scar-characteristics was evaluated by quantifying the borderzone (BZ), scar core, and conduction corridors. Electrical simulations were performed on the patient-specific anatomical models using the Virtual Induction and Treatment of Arrhythmias (VITA) framework. VITA was used to assess the electrical vulnerability of potential reentrant channels and provided the number of inducible VTs and their corresponding round-trip-time (RTT), an equivalent of VT cycle-length. Results Scar quantification using PSIR LGE resulted in a significantly larger BZ (22.1±23.7g vs. 6.2±2.7g, p <.001) and scar core (43.5±21.5g vs. 10.5±4g, p =.047). Furthermore, both the absolute number (6.8±4 vs. 3.4±1.5, p = .031) and weight (13±13.1g vs. 1.4±0.8g, p =.018) of conduction corridors were also higher using PSIR. VTs were inducible in 8 PSIR-models and 7 MIR-models. Despite large differences in scar characteristics, VITA metrics were not significantly different between PSIR and MIR derived models. Although, the absolute number of inducible VTs were larger for PSIR (6.2±5.4 vs. 3.4±3.1), non-parametric testing using Wilcoxon signed-rank test did not demonstrate a significant difference (Z = -1.334, p =.139). A comparable, non-significant difference was observed for mean- (117±78 vs. 79±60, p =.257) and max-RTT (181±141 vs. 120±103, p =.294) between PSIR and MIR derived models. Conclusion PSIR resulted in significantly larger BZ, scar core area, and conduction corridors. While the absolute, VITA-derived estimation of myocardial arrhythmogenicity, including inducible VTs and RTT, were higher in the PSIR-based quantification, these differences did not reach statistical significance. These results highlight important differences between two clinically applied image reconstruction techniques for the assessment of arrhythmogenic substrate, emphasizing the need for additional investigation and refinement of scar quantification techniques.

Coronary CTA-based vascular radiomics predicts atherosclerosis development proximal to LAD myocardial bridging.

Cardiac cycle morphological changes can accelerate plaque growth proximal to myocardial bridging (MB) in the left anterior descending artery (LAD). To assess coronary computed tomography angiography (CCTA)-based vascular radiomics for predicting proximal plaque development in LAD MB. Patients with repeated CCTA scans showing LAD MB without proximal plaque in index CCTA were included from Jinling Hospital as a development set. They were divided into training and internal testing in an 8:2 ratio. Patients from four other tertiary hospitals were set as external validation set. The endpoint was proximal plaque development of LAD MB in follow-up CCTA. Four vascular radiomics models were built: MB centreline (MB CL), proximal MB CL (pMB CL), MB cross-section (MB CS), and proximal MB CS (pMB CS), whose performances were evaluated using area under the receiver operating characteristic curve (AUC), integrated discrimination improvement (IDI), and net reclassification improvement (NRI). In total, 295 patients were included in the development (n = 192; median age, 54 ± 11 years; 137 men) and external validation sets (n = 103; median age, 57 ± 9 years; 57 men). The pMB CS vascular radiomics model exhibited higher AUCs in training, internal test, and external sets (AUC = 0.78, 0.75, 0.75) than the clinical and anatomical model (all P < 0.05). Integration of the pMB CS vascular radiomics model significantly raised the AUC of the clinical and anatomical model from 0.56 to 0.75 (P = 0.002), along with enhanced NRI [0.76 (0.37-1.14), P < 0.001] and IDI [0.17 (0.07-0.26), P < 0.001] in the external validation set. The CCTA-based pMB CS vascular radiomics model can predict plaque development in LAD MB.

#1967 Towards the design optimisation of catheters for paediatric dialysis using a bioengineering approach

Abstract Background and Aims Central venous lines (CVLs) used for haemodialysis (HD) in children are associated with a high complication rate, leading to inadequate dialysis and need for a line replacement in nearly 45% of children on HD. This high complication rate may be due to poor CVL configurations, designed without considering specific anatomical differences between children and adults. Using a bioengineering approach, we aim to provide a fluid dynamics characterization of different CVL models commonly used in children to establish an association between CVL design and clinical complications, and to improve CVL performance by optimising their design. Method Computational fluid dynamics (CFD) using modelling and simulations is a powerful engineering tool that use computers to study complex systems, applying mathematics, physics and computer science. Four models of CVLs of varying designs and sizes (6.5Fr, 8Fr, 10Fr and 14Fr) were scanned by microCT to reconstruct computational models. CFD analyses were set up to simulate blood flow within the CVLs under both ideal and realistic models of superior vena cava. A variety of flow rates, routinely used in clinical practice, were applied to study the whole range of working conditions. Haemodynamic features that cannot be measured in vivo such as high shear stresses and large areas of stagnation, were analysed. CFD findings were compared to clinical outcomes (n = 26 patients with 57 lines) and to the blood clots distribution of CVLs removed from patients (n = 8). Fluid dynamics characteristics of the CVLs studied were used to set up a preliminary design optimisation process of a 6.5F CVL model. Using sampling methods, a variety of CVL designs were created starting from the original model and results were compared. Results In all the simulated CVLs, the arterial lumens showed the highest stagnation and recirculation areas. The role of arterial tip configuration was negligible for the blood flows and the proximal side holes played a major role for blood aspiration being also subject to the highest levels of shear stress, regardless of the design. In all the anatomical models, blood velocity increased after catheter insertion (Fig. 1a) together with wall shear stresses. CFD results were in accordance with the clinical data which showed a higher recurrence rate of thrombosis for the 8Fr and 10Fr CVLs. Also, microCT of the CVLs removed due to complications confirmed presence of thrombosis at the catheter tips. Results suggest that shear stress is the parameter most strongly related to clinical complications. The preliminary design optimisation study was used to find the parameters which have the highest influence on the CVL performance. Preliminarily optimised designs of the 6.5F model showed a better haemodynamic performance, reducing stagnation areas (Fig. 1b). Conclusion Characterisation of the fluid dynamics of commercially available CVLs explains some of the clinical outcomes experienced by patients. Identification of potential design-related complications in CVLs has allowed to set up the optimisation process which will lead to new CVL designs with improved blood flow distribution and minimal damage to blood cells. Funding Kidney Research UK, PhD fellowship and MedTech grants.

The effect of 3D modeling on family quality of life, surgical success, and patient outcomes in congenital heart diseases: objectives and design of a randomized controlled trial.

Understanding the severity of the disease from the parents' perspective can lead to better patient outcomes, improving both the child's health-related quality of life and the family's quality of life. The implementation of 3-dimensional (3D) modeling technology in care is critical from a translational science perspective. The purpose of this study is to determine the effect of 3D modeling on family quality of life, surgical success, and patient outcomes in congenital heart diseases. Additionally, we aim to identify challenges and potential solutions related to this innovative technology. The study is a two-group pretest-posttest randomized controlled trial protocol. The sample size is 15 in the experimental group and 15 in the control group. The experimental group's heart models will be made from their own computed tomography (CT) images and printed using a 3D printer. The experimental group will receive surgical simulation and preoperative parent education with their 3D heart model. The control group will receive the same parent education using the standard anatomical model. Both groups will complete the Sociodemographic Information Form, the Surgical Simulation Evaluation Form - Part I-II, and the Pediatric Quality of Life Inventory (PedsQL) Family Impacts Module. The primary outcome of the research is the average PedsQL Family Impacts Module score. Secondary outcome measurement includes surgical success and patient outcomes. Separate analyses will be conducted for each outcome and compared between the intervention and control groups. Anomalies that can be clearly understood by parents according to the actual size and dimensions of the child's heart will affect the preoperative preparation of the surgical procedure and the recovery rate in the postoperative period.

Normscan: open-source Python software to create average models from CT scans.

Age-matched average 3D models facilitate both surgical planning and intraoperative guidance of cranial birth defects such as craniosynostosis. We aimed to develop an algorithm that accepts any number of CT scans as input and generates highly accurate, average models with minimal user input that are ready for 3D printing and clinical use. Using a compiled database of 'normal' pediatric computed tomography (CT) scans, we report Normscan, an open-source platform built in Python that allows users to generate normative models of CT scans through user-defined landmarks. We use the basion, nasion, and left and right porions as anatomical landmarks for initial correspondence and then register the models using the iterative closest points algorithm before downstream averaging. Normscan is fast and easy to use via our user interface and also creates highly accurate average models of any number of input models. Additionally, it is highly repeatable, with coefficients of variance for the surface area and volume of the average model being less than 3% across ten independent trials. Average models can then be 3D printed and/or visualized in augmented reality. Normscan provides an end-to-end pipeline for the creation of average models of skulls. These models can be used for the generation of databases of specific demographic anatomical models as well as for intraoperative guidance and surgical planning. While Normscan was designed for craniosynostosis repair, due to the modular nature of the algorithm, Normscan has many applications in other areas of surgical planning and research.

An endoscopic chisel: intraoperative imaging carves 3D anatomical models.

Preoperative imaging plays a pivotal role in sinus surgery where CTs offer patient-specific insights of complex anatomy, enabling real-time intraoperative navigation to complement endoscopy imaging. However, surgery elicits anatomical changes not represented in the preoperative model, generating an inaccurate basis for navigation during surgery progression. We propose a first vision-based approach to update the preoperative 3D anatomical model leveraging intraoperative endoscopic video for navigated sinus surgery where relative camera poses are known. We rely on comparisons of intraoperative monocular depth estimates and preoperative depth renders to identify modified regions. The new depths are integrated in these regions through volumetric fusion in a truncated signed distance function representation to generate an intraoperative 3D model that reflects tissue manipulation RESULTS: We quantitatively evaluate our approach by sequentially updating models for a five-step surgical progression in an ex vivo specimen. We compute the error between correspondences from the updated model and ground-truth intraoperative CT in the region of anatomical modification. The resulting models show a decrease in error during surgical progression as opposed to increasing when no update is employed. Our findings suggest that preoperative 3D anatomical models can be updated using intraoperative endoscopy video in navigated sinus surgery. Future work will investigate improvements to monocular depth estimation as well as removing the need for external navigation systems. The resulting ability to continuously update the patient model may provide surgeons with a more precise understanding of the current anatomical state and paves the way toward a digital twin paradigm for sinus surgery.

Advanced Imaging Guidance for Ductus Venosus Stenting in Obstructed Total Anomalous Pulmonary Venous Return.

Obstructed infracardiac total anomalous pulmonary venous return is nearly always a surgical emergency in which infants present in severe cardiopulmonary distress. Ductal venosus stenting can provide a temporizing option for premature, low birth weight infants with high risk for surgical complications. In challenging anatomic cases, virtual reality, 3D-printed models, and fusion image guidance can aid in procedural planning and provide support for successful intervention.