3D printing in medicine最新文献

Background: Despite advancements in imaging technologies, including CT scans and MRI, these modalities may still fail to capture intricate details of congenital heart defects accurately. Virtual 3D models have revolutionized the field of pediatric interventional cardiology by providing clinicians with tangible representations of complex anatomical structures. We examined the feasibility and accuracy of utilizing an automated, Artificial Intelligence (AI) driven, cloud-based platform for virtual 3D visualization of complex congenital heart disease obtained from 3D rotational angiography DICOM images.

Methods: Five patients selected at random with 3DRA performed in the pediatric cardiac catheterization suite were selected. 3DRA's were performed following published institutional protocols and segmentations performed by primary operators. The 3DRA DICOM images were anonymized as per protocol and exported. Images when then processed by Axial3D Artificial Intelligence (AI) driven cloud-based platform for virtual segmentation. Two separate expert operators were selected to subjectively analyze the segmentations and compare them to the operator reconstructions for anatomic accuracy.

Results: Comparing results with local reconstructions by expert operators, five different patient anatomies were analyzed, showcasing Axial3D's ability to produce highly detailed reconstructions with improved visual appeal, including color-coded segments for implanted materials like stents. The reconstructions exhibited superior segmentation of different intrathoracic structures when compared to local models, offering valuable insights for medical professionals and patients.

Conclusions: The use of the AI driven, cloud-based platform for 3D visualization of complex congenital heart lesions presents a promising advancement in pediatric interventional cardiology, facilitating enhanced patient care, procedural planning, and educational opportunities for trainees and patients alike.

Background: There exists a need for validated lumbar spine models in spine biomechanics research. Although cadaveric testing is the current gold standard for spinal implant development, it poses significant issues related to reliability and repeatability due to the wide variability in cadaveric physiologies. Moreover, there are increasing ethical concerns with human dissection practices. Analogue models can act as cost saving alternatives to human tissue with better repeatability. The current study proposes a new methodology of spinal biomechanics testing using 3D printable surrogates and characterized its multi-dimensional stiffness in displacement-controlled loading scenarios.

Methods: The model consisted of L1 to S1 vertebrae, intervertebral discs (IVD), intertransverse, interspinous, anterior and posterior longitudinal ligaments. The vertebrae and the IVDs were derived from an open-source 3D MRI anatomography database, while the ligaments were modeled based on literature incorporating mounting points on the spinous and transverse processes. Stereolithography 3D printing along with a combination of stiff and soft photopolymer resins were used to manufacture the vertebrae and the soft tissues in the model. Thereafter, displacement-controlled pure moments were applied in the range of ± 15° at 0.5°/sec in all bending modes using a torsion testing machine and a custom pure bending jig. Model rotation and resisting moment under loading were recorded to quantify the rotational stiffness and hysteresis in the model.

Results: The model reached a maximum of 5.66Nm and 3.53Nm at 15° flexion-extension, 3.84Nm and 3.93Nm at 15° right and left lateral bending, and 2.45Nm and 2.59Nm at 15° right and left axial rotation respectively. Model RMS error against ex vivo human response was estimated to be 1.57°, 1.64°, 0.82° in flexion-extension, lateral bending and axial rotation respectively. Bilateral symmetry in model stiffness was observed in lateral bending and axial rotation directions.

Conclusions: This study presents a reproducible 3D printable L1-S1 lumbar spine and validated it in all three orthogonal bending modes in the range of ± 15° against ex vivo and in silico data. The 3D printed analogue spine model described herein shows promising results, suggesting this model, with further validation, could have potential as a human cadaveric tissue substitute within the explored contexts of use.

Background: The emergence of 3D printing has revolutionized medical training and preoperative planning. However, existing models have limitations, prompting the development of newly designed flexible 3D-printed bone fracture models.

Methods: The designed flexible 3D-printed bone fracture models were evaluated by 133 trauma surgeons with different levels of experience for perceived value as educational tool or as preoperative planning tool.

Results: The models allowed drilling and showed resistance to manipulation and sterilization. Surgeons found the flexible model helpful for teaching and planning the reduction of fractures, planning and simulating osteosynthesis, understanding fractures, visualizing fractures, and planning surgical approaches.

Conclusions: Flexible 3D-printed bone fracture models offer a dynamic and realistic approach to understanding complex fractures, potentially improving surgical training and preoperative planning.

Background: Penile implant surgery is the standard surgical treatment for end-stage erectile dysfunction. However, the growing complexity of modern high-tech penile prostheses has increased the demand for more practical training opportunities. The most advanced contemporary training methods involve simulation training using cadavers, with costs exceeding $5,000 per cadaver, inclusive of biohazard fees. This study introduces an innovative and cost-efficient male urogenital simulator designed to enhance penile implant surgery training.

Methods: Utilizing image segmentation of patient pre-operative computed tomography (CT) scans, combined with three-dimensional (3D) printing and silicone molding techniques, we developed a high-fidelity simulator replicating the anatomical structures of the male urogenital system. The simulator incorporates an innovative double-layer structural design encompassing the corpus spongiosum and glans, corpora cavernosa, testes, epididymides, and pelvic bones. Additionally, it utilizes a two-stage skin manufacturing process tailored for different skin regions. The simulator was produced at a low material cost of £10, with an average production time of 3 h. To evaluate its training efficacy, we conducted a penile implant surgery training session involving 15 urology trainees and surgeons ranging from specialty training levels ST3 to ST6. The session began with a demonstration of penile implant surgery and error detection. Trainees, averaging three per simulator, practiced corporotomy, dilation, measurement, penile prosthesis, and scrotal pump placement under expert guidance. Participants' feedback was collected using a Likert scale questionnaire, assessing learning, satisfaction, and anatomical accuracy.

Results: Quantitative analysis of the questionnaire responses indicated highly positive feedback from the participants. Satisfaction rates surpassed 96% in learning effectiveness, over 89% in overall satisfaction, and 86% in anatomical accuracy demonstration. The simulator was favourably reviewed by both urology trainees and experienced surgeons, highlighting its utility as a practical training tool. Its low production cost and high precision make it a viable alternative to current training models.

Conclusions: The development of this cost-efficient, anatomically accurate urogenital simulator through advanced imaging and additive manufacturing techniques represents a significant advancement in penile implant surgical training. This state-of-the-art simulator not only provides a realistic and practical training experience but also underscores the potential for 3D printing technologies to revolutionize medical education and training.

Background: 3D technologies [Virtual and Augmented 3D planning, 3D printing (3DP), Additive Manufacturing (AM)] are rapidly being adopted in the healthcare sector, demonstrating their relevance in personalized medicine and the rapid development of medical devices. The study's purpose was to understand the state and evolution of 3DP/AM technologies at the Point-of-Care (PoC), its adoption, organization and process in Spanish hospitals and to understand and compare the evolution of the models, clinical applications, and challenges in utilizing the technology during the COVID-19 pandemic and beyond.

Methods: This was a questionnaire-based qualitative and longitudinal study. Data on 3DP and AM activities in Spain were collected from 73 hospitals/institutions falling under the ITEMAS (Platform for Innovation in Medical and Health Technologies) and the Plataforma ISCIII Biomodelos y Biobancos from January 2019 to May 2020 for the first study, and at the end of 2022 and 2023 for the second study.

Results: A total of 23 (31.5%) hospitals during the first study, while 30 (41.09%) during the second study reported having at least one 3DP/AM initiative. Post-covid, the majority of hospitals had onsite 3DP/AM services with a well-defined, structured, and centralized system. Traumatology and maxillofacial surgery services were found to be the most involved in 3DP projects for the production of custom-made surgical guides, prostheses and orthoses. Bioprinting initiatives were also noted to be expanding. Human resources, cost, and regulatory compliance were the key hurdles in introducing 3D/AM in hospitals.

Conclusions: In-house 3DP/AM units, with Mixed-Model is the most common model in Spain; The COVID-19 pandemic influenced the 3D planning activity and adoption. Further research and clinical trials, and improvements in resources, reimbursement and regulatory compliance are critical for the Point-of-care hospital growth of this breakthrough technology.

The most common surgical procedure to manage the malunion of the bones is corrective osteotomy. The current gold standard for securing the bone segments after osteotomy is the use of titanium plates and allografts which have disadvantages such as possible allergic reaction, additional operations such as extraction of the graft from other sites and removal operation. The utilization of resorbable materials presents an opportunity to mitigate these drawbacks but has not yet been thoroughly researched in the literature. This study assesses the viability of using biodegradable, 3D-printed patient-specific implants made of Poly(-L-lactide-co-D, L-lactide) (PLDLLA) and β-Tricalcium Phosphate (β-TCP) as an alternative material in an in-vitro biomechanical study involving ex vivo biomechanical compression testing, biodegradation testing, and calorimetric measurements. These implants possess a unique shape, resembling a wedge and are fixated as a connection between the osteotomised bone using resorbable screws. Following point-of-care virtual planning, bio-mechanical compressive tests with (n = 5) ex vivo radii equipped with PLDLLA/ β-TCP implants were performed to prove sufficient stability of the connection. All PLDLLA/ β-TCP implants withstood a compressive force of at least 1'211 N which exceeds the maximum force reported in literature in case of a fall from the height of one meter. Furthermore, the results showed a consistent surface chemistry and slow degradation rate. The outcomes are encouraging, establishing the groundwork for an innovative distal radius corrective osteotomy surgical method. However, further research is necessary to thoroughly evaluate the long-term biodegradability and mechanical efficacy of the implants.

Breast cancer screening is implemented as part of governmental healthcare policy in many countries. While breast imaging tests contribute to reducing mortality, some breast cancers may emerge between these screenings. Consequently, it is crucial for women to be vigilant about any changes in their breasts to facilitate the early detection of breast cancer. Recently, the application of 3-dimensional printing technology in the medical field has expanded, including uses in medical imaging and surgical training. In this study, we developed 3D-printed palpation models for breast tumor detection and surveyed seven surgeons specializing in breast care to evaluate the usability of the models. As a result of the survey, we created a model that obtained a maximum mean rating of 7.1(maximum rating 10, minimum rating 3) on the item 'How accurately does the model simulate the feel of a real tumor?' on a scale from 1 to 10. Although there is some variation in the average value, through this study, we found that it is possible to create a model that is quite close to the actual tumor depending on the materials and shape of the models. Our findings demonstrated the potential use of personalized models both in medical trainee and patient education.

Background: The development of phantoms to reduce animal testing or to validate new instruments or operation techniques is of increasing importance. For this reason, a blood circulation phantom was developed to test a newly designed retractor system with an integrated oxygen sensor. This phantom was used to evaluate the impact of the 3D printed blood vessel on the measurement of the oxygen saturation.

Methods: A solution of nickel sulfate and copper sulfate was prepared as a substitute for real blood. The absorption spectra of these solutions were recorded and compared with those of blood. Subsequently, the oxygen sensor used was calibrated to the blood substitute. Additionally, blood vessels with a simplified geometry were designed and manufactured using inverted vat polymerization and an elastic material (Formlabs Elastic 50 A). To determine the orientation during the printing process, various vessels were printed. Measurements to assess the effects of disturbance (rotation of the vessels during measurements) on the sensor readouts were prepared.

Results: The impact of disturbances was verified through the rotation of the 3D printed vessels. It was demonstrated that a direct measurement on the disturbances led to outliers and higher values. An optimal orientation was determined to be a lateral placement (90° or 270°) of the sensor. Regarding the orientation of the vessels within the printing space, an orientation of 45° yielded the best results, as the individual layers had the least impact on the light emitted and received by the oxygen sensor.

Conclusion: The achieved results demonstrate the influence of the orientation of the vessel during 3D printing as well as the influence of the position of the vessel during the measurement using a conventional oxygen sensor.

Aim: This study compares the precision, accuracy, and user experience of 3D body surface scanning of human subjects using the Artec Leo hand-held scanner and the iPad Pro as 3D scanning devices for capturing cervical and craniofacial data. The investigation includes assessing methods for correcting 'dropped head syndrome' during scanning, to demonstrate the ability of the scanner to be used to reconstruct body surface of patients.

Methods: Eighteen volunteers with no prior history of neck weakness were scanned three times in three different positions, using the two different devices. Surface area, scanning time, and participant comfort scores were evaluated for both devices. Precision and accuracy were assessed using Mean Absolute Deviation (MAD), Mean Absolute Percentage Error (MAPE), and Intra-Class Correlation Coefficients (ICC).

Results: Surface area comparisons revealed no significant differences between devices and positions. Scanning times showed no significant difference between devices or positions. Comfort scores varied across positions. MAD analysis identified chin to chest measurements as having the highest variance, especially in scanning position 3. However, no statistical differences were found. MAPE results confirmed accuracy below 5% error for both devices. ICC scores indicated good reliability for both measurement methods, particularly for chin to chest measurements in positions 1 and 3.

Conclusion: The iPad Pro using the Qlone app demonstrates a viable alternative to the Artec Leo, particularly for capturing head and neck surface area within a clinical setting. The scanning resolution, with an error margin within ±5%, is consistent with clinically accepted standards for orthosis design, where padding and final fit adjustments allow for bespoke devices that accommodate patient comfort. This study highlights the comparative performance of the iPad, as well as suggests two methods which can be used within clinics to correct head drop for scanning.

Background: The use of 3D-printing in medicine requires a context-specific quality assurance program to ensure patient safety. The process of medical 3D-printing involves several steps, each of which might be prone to its own set of errors. The segmentation error (SegE), the digital editing error (DEE) and the printing error (PrE) are the most important partial errors. Approaches to evaluate these have not yet been implemented in a joint concept. Consequently, information on the stability of the overall process is often lacking and possible process optimizations are difficult to implement. In this study, SegE, DEE, and PrE are evaluated individually, and error propagation is used to examine the cumulative effect of the partial errors.

Methods: The partial errors were analyzed employing surface deviation analyses. The effects of slice thickness, kernel, threshold, software and printers were investigated. The total error was calculated as the sum of SegE, DEE and PrE.

Results: The higher the threshold value was chosen, the smaller were the segmentation results. The deviation values varied more when the CT slices were thicker and when the threshold was more distant from a value of around -400 HU. Bone kernel-based segmentations were prone to artifact formation. The relative reduction in STL file size [as a proy for model complexity] was greater for higher levels of smoothing and thinner slice thickness of the DICOM datasets. The slice thickness had a minor effect on the surface deviation caused by smoothing, but it was affected by the level of smoothing. The PrE was mainly influenced by the adhesion of the printed part to the build plate. Based on the experiments, the total error was calculated for an optimal and a worst-case parameter configuration. Deviations of 0.0093 mm ± 0.2265 mm and 0.3494 mm ± 0.8001 mm were calculated for the total error.

Conclusions: Various parameters affecting geometric deviations in medical 3D-printing were analyzed. Especially, soft reconstruction kernels seem to be advantageous for segmentation. The concept of error propagation can contribute to a better understanding of the process specific errors and enable future analytical approaches to calculate the total error based on process parameters.