Methods for medical applications

Objectives: To report the surgical outcomes of treating patellar luxation (PL) in dogs with surgical planning based on three-dimensional (3D) automated measurement of femoral angles. Study design: Multicenter retrospective study. Methods: Forty-one dogs with PL underwent preoperative computed tomography (CT). Three-dimensional femur models were exported as stereolithographic files, and imported into computer-aided design (CAD) software where 3D measurements were performed. The anatomical laterodistal femoral (aLDFA), femoral neck (FNA), and femoral torsion (FTA) angles were recorded. Surgical records, complications, radiographic femoral postoperative alignment, preoperative and postoperative lameness evaluation, and patellar position were reviewed. The success of the surgical outcome was based on the presence of normal patellar tracking at the last clinical recheck. Results: Forty-seven limbs were included; 46% of the cases (22/47) were affected by grade 3 PL. Mean (±SD) 3D aLDFA, FNA, and FTA measurements were 101.4° (±3.6), 132.5° (±2.6), and 17.6° (±4.3) in dogs with medial patellar luxation (MPL) and 89.3° (±7.6), 134.8° (±2.9), 36.9° (±5.3) with lateral patellar luxation (LPL), respectively. Based on the 3D preoperative planning, corrective osteotomies were performed in 34 of 47 cases. The mean radiographic follow-up was 4.7 months. At the final follow-up, PL was successfully treated in 45 of 47 cases. Patella reluxated in five cases. In three of five cases, the 3D automated plan was not followed by the surgeon. Discussion: Surgical treatment of PL based on 3D femoral measurements successfully corrected PL in 45 of 47 cases (96%). This is the first study reporting the use of 3D automated femoral angle measurement in clinical cases affected by PL.

Keywords: 3D computation , dog , femur , limb deformities , patellar luxation

In particle therapy for cancer treatment, the radiation dose to tissues around the tumour can be reduced by employing a rotating gantry—a mechanical structure allowing the delivery of the particle beam to the patient from various angles. Gantries for ion therapy can benefit from the integration of superconducting magnets to minimize the size and weight of the machine. One significant challenge associated with the supporting system of superconducting elements is related to the management of their accuracy during both alignment and operational phases. Concurrently, heat flow from room temperature to cryogenic temperatures through the supporting system must be restricted as the ratio of power needed to operate the cooling system is around 1000 times the power extracted at cryogenic temperature. The design of the supports must consider the variability of the load during operation, i.e. guarantee accuracy of the cold-mass pose (position and rotation) under its own weight during a 360∘ gantry rotation. A literature review had been done highlighting the possible application of a novel exact-constrained solution for the support of superconducting magnets. Within the framework of the European project HITRIplus (heavy Ion Therapy Research Integration), this study proposes the design and optimization of a support system based on a 6 degrees of freedom parallel mechanism (exactly constrained kinematics). A mathematical model is proposed, referred as “error model”, to estimate the accuracy of the pose of the cold-mass due to major unrecoverable errors. The error model estimates the contribution of main error sources: the elasticity of the supports, the elasticity of the vacuum vessel enclosure and the influence of backlash in the joints. An optimization genetic algorithm has been developed and employed to find the optimal configuration of supports that simultaneously increases the accuracy and minimizes heat-loads to the cold-mass. The error model has been validated by finite element analysis, showing its validity for the optimization process. The optimised solution has been compared to solutions that were proposed initially based on common sense, intuition and had been manually refined: the optimized solution shows considerable improvements in the overall accuracy of the system and a substantial reduction of the heat-loads. The optimized solution also implements a pre-load system to eliminate backlash in the joints: this considerably improves the accuracy of the system. The error model presented allows computationally cheaper optimizations and variations of the designed architecture (i.e. variation in cross sections, change in material, change in geometry, implementation of pre-load etc..) with respect to a classic approach based only on finite element analysis. Furthermore, thanks to the kinematics characteristic of the proposed architecture, the 6-legs design clears the way for a more reliable implementation of an automated positioning system with respect to classical over-constrained architectures.

Keywords: Gantry , Particle therapy , Rotating , Superconducting magnets , Supporting system

Background: This paper outlines a comparative study on scenarios of gantries mechanical design for ion-therapy of cancer, which is a crucial step toward the development of the next ion medical machine. Methods: Multiple scenarios were considered based on robustness of the design, size, weight and complexity, deformation and precision performances and costs, as well as environmental impact. Four prospective scenarios were identified, each of them capable of providing beam to at least 220°around the patient. One scenario is capable of providing treatment angles of 360°. This report will describe the unified methodology performed during the study in order to achieve unbiased results in a comprehensive manner. Results: Results show that in statically balanced scenarios, considerable improvements can be reached in terms of safety, deformation, precision performances, complexity and costs of implementation. Conclusions: All scenarios are deemed suitable for further gantry design development.

Keywords: Gantry , Ion Therapy , Mechanical Design , Particle Therapy

Femur fractures are a significant worldwide public health concern that affects patients as well as their families because of their high frequency, morbidity, and mortality. When employing computer-aided diagnostic (CAD) technologies, promising results have been shown in the efficiency and accuracy of fracture classification, particularly with the growing use of Deep Learning (DL) approaches. Nevertheless, the complexity is further increased by the need to collect enough input data to train these algorithms and the challenge of interpreting the findings. By improving on the results of the most recent deep learning-based Arbeitsgemeinschaft für Osteosynthesefragen and Orthopaedic Trauma Association (AO/OTA) system classification of femur fractures, this study intends to support physicians in making correct and timely decisions regarding patient care. A state-of-the-art architecture, YOLOv8, was used and refined while paying close attention to the interpretability of the model. Furthermore, data augmentation techniques were involved during preprocessing, increasing the dataset samples through image processing alterations. The fine-tuned YOLOv8 model achieved remarkable results, with 0.9 accuracy, 0.85 precision, 0.85 recall, and 0.85 F1-score, computed by averaging the values among all the individual classes for each metric. This study shows the proposed architecture\'s effectiveness in enhancing the AO/OTA system\'s classification of femur fractures, assisting physicians in making prompt and accurate diagnoses.

Keywords: Computer assisted diagnosis , Convolutional neural networks , Deep learning , Femur fracture

The aim of this study was to assess the value of the use of software for the preoperative evaluation of cranial bone thickness in syndromic patients undergoing Le Fort III osteotomy. Four patients were evaluated preoperatively to determine whether they were eligible for distraction osteogenesis. Data from the computed tomography scans was evaluated using advanced reverse engineering tools to determine the temporal bone thickness. Three patients showed adequate values for the positioning of a rigid external distractor device (average thickness values >3.5 mm), while one patient showed insufficient bone thickness (average value <2.5 mm) and therefore underwent midface advancement according to the traditional technique. Adequate midface advancement was obtained in the three patients who underwent distraction osteogenesis. No complications related to the rigid external distractor were observed. A shorter skeletal advancement was obtained in the patient who underwent Le Fort III osteotomy according to the traditional technique. A cerebrospinal fluid fistula was observed after the removal of the plates, requiring surgical repair. Software evaluation of the cranial bone thickness is a useful tool in the surgical planning of Le Fort III osteotomy in patients affected by syndromic craniosynostosis.

Keywords: Distraction osteogenesis , Le Fort III osteotomy , Syndromic craniosynostosis

The aim of “Precision Surgery” is to reduce the impact of surgeries on patients' global health. In this context, over the last years, the use of three-dimensional virtual models (3DVMs) of organs has allowed for intraoperative guidance, showing hidden anatomical targets, thus limiting healthy-tissue dissections and subsequent damage during an operation. In order to provide an automatic 3DVM overlapping in the surgical field, we developed and tested a new software, called “ikidney”, based on convolutional neural networks (CNNs). From January 2022 to April 2023, patients affected by organ-confined renal masses amenable to RAPN were enrolled. A bioengineer, a software developer, and a surgeon collaborated to create hyper-accurate 3D models for automatic 3D AR-guided RAPN, using CNNs. For each patient, demographic and clinical data were collected. A total of 13 patients were included in the present study. The average anchoring time was 11 (6–13) s. Unintended 3D-model automatic co-registration temporary failures happened in a static setting in one patient, while this happened in one patient in a dynamic setting. There was one failure; in this single case, an ultrasound drop-in probe was used to detect the neoplasm, and the surgery was performed under ultrasound guidance instead of AR guidance. No major intraoperative nor postoperative complications (i.e., Clavien Dindo > 2) were recorded. The employment of AI has unveiled several new scenarios in clinical practice, thanks to its ability to perform specific tasks autonomously. We employed CNNs for an automatic 3DVM overlapping during RAPN, thus improving the accuracy of the superimposition process.

Keywords: artificial intelligence , kidney cancer , nephron-sparing surgery , partial nephrectomy , renal cell carcinoma , robotic surgery , three-dimensional imaging

Objectives: The research's purpose is to develop a software that automatically integrates and overlay 3D virtual models of kidneys harboring renal masses into the Da Vinci robotic console, assisting surgeon during the intervention. Introduction: Precision medicine, especially in the field of minimally-invasive partial nephrectomy, aims to use 3D virtual models as a guidance for augmented reality robotic procedures. However, the co-registration process of the virtual images over the real operative field is performed manually. Methods: In this prospective study, two strategies for the automatic overlapping of the model over the real kidney were explored: the computer vision technology, leveraging the super-enhancement of the kidney allowed by the intraoperative injection of Indocyanine green for superimposition and the convolutional neural network technology, based on the processing of live images from the endoscope, after a training of the software on frames from prerecorded videos of the same surgery. The work-team, comprising a bioengineer, a software-developer and a surgeon, collaborated to create hyper-accuracy 3D models for automatic 3D-AR-guided RAPN. For each patient, demographic and clinical data were collected. Results: Two groups (group A for the first technology with 12 patients and group B for the second technology with 8 patients) were defined. They showed comparable preoperative and post-operative characteristics. Concerning the first technology the average co-registration time was 7 (3–11) seconds while in the case of the second technology 11 (6–13) seconds. No major intraoperative or postoperative complications were recorded. There were no differences in terms of functional outcomes between the groups at every time-point considered. Conclusion: The first technology allowed a successful anchoring of the 3D model to the kidney, despite minimal manual refinements. The second technology improved kidney automatic detection without relying on indocyanine injection, resulting in better organ boundaries identification during tests. Further studies are needed to confirm this preliminary evidence.

Keywords: artificial intelligence , kidney cancer , nephron-sparing surgery , renal cell carcinoma , robotic surgery , three-dimensional imaging

Robotic surgery, also known as robotic-assisted surgery (RAS), has rapidly evolved during the last decade. RAS systems are developed to assist surgeons to perform complex minimally invasive surgeries, and necessitate augmented interfaces for precise execution of these image-guided procedures. Extended Reality (XR) technologies, augmenting the real-world perception via integrating digital contents, show promise in enhancing RAS efficacy in various studies. Despite multiple reviews on technological and medical aspects, the crucial elements of human-robot interaction (HRI) and user experience (UX) remain underexplored. This review fills this gap by elucidating HRI dynamics within XR-aided RAS systems, emphasizing their impact on UX and overall surgical outcomes. By synthesizing existing literature, this systematic review study identifies challenges and opportunities, paving the way for improved XR-enhanced robotic surgery, ultimately enhancing patient care and surgical performance.

Keywords: extended reality , human-computer interaction , robotic-assisted surgery , surgical robots , user experience

Autologous ear reconstruction is a surgical procedure aimed at total or partial reconstruction of the ear of patients with microtia, which is a malformation or absence of the anatomical element. This procedure involves harvesting cartilage material from the patient at the costal level, cut and sculpt the tissue to create the skeleton of the ear, which is then inserted into a subcutaneous pocket in the malformed region. The sculping procedure takes inspiration from the geometry of the patient's contralateral healthy ear and can be very complex given the particularity of the elements to be reconstructed. Taking advantage of Reverse Engineering and Additive Manufacturing technologies, the authors, in collaboration with hospital staff, proposed patient-specific three-dimensional cutting guides that can facilitate the surgeon in sculpting the ear structure. In this work, a fully automated procedure for creating the printable digital model of such guides is proposed: at first is performed the segmentation of ear elements, which represent the starting data for the automated CAD modelling of the surgical guides. The automatic CAD modelling procedure was tested and validated by medical personnel.

Keywords: CAD Modelling , Ear Reconstruction , Reverse Engineering , Surgical Guide

Background:. Mitral transcatheter edge-to-edge repair (m-TEER) is a minimally invasive procedure for treating mitral regurgitation (MR). m-TEER is a highly technical procedure, and a steep learning curve needs to be overcome for operators to ensure optimal patient outcomes and minimise procedural complications. Training via online simulation and observation of procedures is not sufficient to establish operator confidence; thus, advanced hands-on training modalities need to be explored and developed. Methods:. In this study, a novel anatomical simulator for m-TEER training was evaluated in comparison to a standard model. The proposed simulator resembled the anatomical features of the right and left atrium, left ventricle and mitral valve apparatus. Participants in the questionnaire (n = 18) were recruited across 4 centres in London with (n = 8) and without (n = 10) prior experience in m-TEER. Participants were asked to simulate procedures on both an idealised, routinely used simulator and the newly proposed anatomical model. The questionnaire was designed to assess (i) participants' confidence before and after training and (ii) the realism of the model in the context of the m-TEER procedure. The results of the questionnaires were collected, and statistical analysis (t-test) was performed. Results:. Both models were equally beneficial in increasing operator confidence before and after the simulation of the intervention (P = 0.43). However, increased confidence after training with the anatomical model was recorded (P = 0.02). Participants with prior experience with m-TEER therapy were significantly more confident about the procedure after training with the anatomical model than participants who had no prior experience (P = 0.002). On average, all participants thought that the anatomical model was effective as a training simulator (P = 0.013) and should be integrated into routine training (P = 0.015)). Participants with experience thought that the anatomical model was more effective at reproducing the m-TEER procedure than the idealised model (P = 0.03). Conclusions:. This study showed how a more realistic simulator can be used to improve the effectiveness of m-TEER procedural training. Such pilot results suggest planning future and large investigations to evaluate improvements in clinical practice.

Keywords: 3D printing , Anatomical simulators , MitraClipâ„¢ , Mitral regurgitation (MR) , Mitral transcatheter edge-to-edge repair (m-TEER) , Mitral valve (MV) , Surgical training

The spinal column is the load-bearing structure of the human being along with its components, which together build a strong, resistant, and stable structure, but there are a few different pathologies from which it can suffer, such as herniated discs. The intervertebral disc acts as a shock absorber and ensures the spine's great capacity to support high loads and different states of stress, thanks to its viscoelastic properties. Some studies have attempted to describe the viscoelastic behaviour of the intervertebral disc using classical rheological models, such as the Kelvin-Voigt, or multi-parameter models. Even if these models partially describe the viscoelastic response of disc, all viscoelastic characteristics are not fully captured. This article aims to present the current studies on the biomechanics of intervertebral disc and to introduce a new approach using the powerful mathematical tool of fractional calculus. With fractional rheological models, it could be possible to formulate a fractional law that can fully describe the viscoelastic behaviour of the intervertebral disc. This new approach could lead to a breakthrough in the study of herniated pathologies by understanding how the intervertebral disc is damaged and identifying strategies to deal with these pathological problems.

Keywords: Biomechanics , Fractional calculus , Fractional rheological model , Intervertebral disc , Spinal column , Viscoelastic behaviour

The growing attention of people to aesthetics has led to a greater demand for dental whitening treatments. Several solutions can be utilized to obtain the desired visual whiteness of teeth but, according to literature, at-home supervised treatments are the standard in dental bleaching. They require soft plastic trays to contain a whitening gel, with active chemical agents, and keep it in contact with the patient's teeth. The fitting, comfort, and tightness of trays play a fundamental role in the treatment. Any gel leakage can compromise the effectiveness of the treatment and damage soft tissues. Commonly, the trays are ready-made or based on physical dental impressions and manually modified by the dental technician. These procedures have low repeatability and do not always ensure high accuracy. This work presents an automatic digital algorithm to design customized whitening trays. Starting from a digital scan acquisition of the patient's dental arches, it generates the 3D models of the bespoke trays, in approximately two minutes per arch, ready to be produced by additive manufacturing and thermoforming technologies. The evaluation of the method involved 20 patients. The results emphasize that the custom trays were comfortable and ensured high levels of tightness and fitting.

Keywords: automatic product design , custom teeth trays , dental whitening , digital process

This work aims at the development of a streamlined and robust CAD procedure to design load-bearing implants. The methodology used to reach this result is explained in the paper: 3D digital anatomy reconstruction of defective structures of the patient is performed with the help of a statistical shape model; subsequently, a CAD modelling tool based on implicit modelling (i.e., nTopology) is used to implement a repeatable semi-automatic procedure that can be performed by a competent user with little effort and limited manual operations. Once that the main shape of the implant is defined, lattice geometries are generated to improve mechanical properties of the implant. The procedure requires as inputs the reconstructed anatomy of the patient and a series of clinical indications on the type of implant that needs to be designed. The paper discusses the development of the whole procedure; achieved results, which include the application of the whole framework on multiple case studies, are presented. The procedure allows the design of a whole implant in 20 minutes circa.

Keywords: CAD Design Automation , Custom Implant; Additive Manufacturing , Implicit Modelling , nTopology

Purpose: Among thoracic malformations, pectus deformities have the highest incidence and can result in a wide range of severe and mild clinical manifestations. Recently, the treatment of pectus deformities is shifting from traditional approaches toward customized solutions. This occurs by leveraging innovative rapid prototyping tools that allow for the design and fabrication of patient-specific treatments and medical devices. This paper aims to provide a comprehensive view of the growing literature in this area to analyze the progress made in this direction. Design/methodology/approach: The search was performed on major search engines through keywords inherent to reverse engineering (RE) and additive manufacturing (AM) technologies applied to pectus deformities and related treatments, selecting 54 papers. These were analyzed according to the addressed pathology, the hardware and software tools used and/or implemented and their integration within the clinical pathway. Findings: First, the analysis led to analyze and divide the papers according to how RE and AM technologies are applied for surgical and non-surgical treatments, pathological assessment and preoperative simulation and planning. Second, all papers were considered within the typical rapid prototyping framework consisting of the three phases of three-dimensional (3D) scanning, 3D modelling and 3D printing. Originality/value: To the best of the authors' knowledge, to date, no survey has provided a comprehensive view of innovative and personalized treatment strategies for thoracic malformations; the present work fills this gap, allowing researchers in this field to have access to the most promising findings on the treatment and evaluation of pathology.

Keywords: 3D printing , Additive manufacturing , Pectus carinatum , Pectus excavatum , Reverse engineering

Due to the increasing number of people with severe obesity, the demand for patient-specific modelling in bariatric surgery (BS) is increasing because its potentialities in the improvement of surgical planning, optimization of outcomes and prediction of the mechanical response of the stomach. However, the patient-specific anatomical reconstruction is a pivotal and often time-consuming step due to the lack of efficient and fully automatized tools. Ongoing studies on multi-organ segmentation methods based on neural networks for magnetic resonance images (MRI) are currently available, but they have still several limits, mainly due to both the highly flexible individuals anatomical properties, and convolutional neural networks (CNN) trained only in the detection of physiological stomachs. The aim of this work is to perform a convenient transfer learning from a general-purpose CNN, able to improve the performance in automatically detecting the stomach region of patients with severe obesity. The proposed approach represents the basis for the development of pre- and post-surgical computational models for rapid clinical analysis, especially to boost the mechanical stimulation of gastric receptors. The segmentation masks and the corresponding 3D models were compared with the corresponding manual MRI segmentation as ground truth. Intersection Over Union (IOU) and DICE coefficients (DICE) were used to evaluate 2D masks segmentation, while the Relative Volume Error (RVE), mean surface distance (MSD), standard deviation and the Normalised Hausdorff distance (NHD) were applied to assess the obtained 3D results.

Keywords: Bariatric surgery , Image segmentation , MRI , Stomach

Additive manufacturing allows the creation of highly customized and complex objects that could not be achieved with traditional methods. These characteristics of the production method make the products perfectly suitable for the design of orthotics, where the customization of the device and the speed of production are essential. For example, it may be necessary to create locally more or less rigid orthose depending on the anatomic area or its local function. The 3D printing of objects can be performed with variable properties within their domain by means of the so called Functionally Graded Additive Manufacturing (FGAM). This article presents a new method for the production of reticular orthoses which begins with the acquisition of the area of interest using a 3d scanner, followed by the generation of the reticular structure locally densified according to ergonometric models, and the finalization of the model with truss thickening and application of a closure system. Some models were then reproduced with AM techniques such as SLA and MJF and tested in daily use.

Keywords: Additive manufacturing , Custom manufacturing , Functionally graded materials , Orthotics

Tip steering by induced deformation constitutes one of the most prominent feature to effectively navigate constrained environments with soft growing robots. In this work, we analyze the effects of design parameters on the tip steering capabilities of pneumatically-actuated soft growing robots built from fabric. More specifically, we consider the variability of material, fabric Pneumatic Artificial Muscles (fPAM) diameter, and backbone internal pressure and statistically quantify the effect on the maximum curvature achieved by the robot when a constant fPAM input pressure is applied. In our considered settings, we found a statistically significant main effect (p<0.05 ) of the fPAM diameter and a relevant interaction effect between this and the material factor. These findings provide useful guidelines for the design of fabric-based PAM-actuated soft growing robots with enhanced tip steering capabilities.

Keywords: Design of bioinspired soft robots , Soft actuators , Soft robotics

Over the past years, a wide range of dental implants has been proposed. In general, the dentists may find the best solutions according to the specific needs of the patients. A variety of factors influences the level of osseointegration and, consequently, the anchorage of the implant to the bone. The stress transfer mechanism along the bone-implant interface depends upon the surface area of the bone-implant contact. Great efforts have been devoted to the design of 3D porous lattice structures with tailored architectural features in order to reduce the implant stiffness as well as to favour bone ingrowth, thus stabilizing the device. Accordingly, the aim of the current study was to provide further insight into the design criteria for dental implants. In particular, starting from a screw implant (Implant A), different concepts of dental implants were developed: i) Implants B1–B5, with lattice shell surrounding a solid core, without thread; ii) Implant C, with lattice structure; iii) Implant D as topography optimized implant. Finite element analysis on the several models of bone-implant provided interesting information in terms of stress distributions in cortical and trabecular bone. Some differences among the implants may be ascribed to the different design criteria.

Keywords: Dental implants , Design criteria , Finite element analysis , Lattice structure , Topography optimization , Topology optimization

Preface and Acknowledgements (Editorial)

Keywords: Editorial

Objective and reliable assessment of motor functions, such as dexterity, is a key point for evaluating worker's abilities. In this context, the proposed work presents a tool for objective automatic assessment of the Minnesota Dexterity Test using cameras with depth sensors. Typical performance measurements (i.e., total time and associated percentiles) were estimated using custom algorithms. In addition, the possibility to identify the qualifiers for the code d440 of the International Classification of Functioning, Disability and Health was implemented in the developed algorithms. The proposed tool can also identify the mistakes most frequently committed by the subjects. To prove the capabilities of the proposed method, a series of experimental trials was conducted with 10 healthy young volunteers. Results showed that the developed tool helps clinicians to obtain performance feedback and evaluate patients' dexterity quickly without bias.

Keywords: Automatic assessment , Biomechanics , Depth cameras , Manual dexterity , Motion capture