Methods for medical applications

Evaluations of injuries and the assessment of residual dexterity is carried out by clinicians by means of standardized tests. Several dexterity tests have been developed and all of them require the test administrator to sit in front of the subject and visually assess the motions performed. Automatic tools can reduce the time needed for the evaluation and can provide additional useful information. For many of the available dexterity tests, automated evaluation methods have been developed. However, for the Minnesota dexterity test, despite being widely used, just one automated solution based on multiple depth sensor cameras was developed. This study aims to provide a wearable and flexible method to automatically evaluate the outcomes of Minnesota dexterity tests. The proposed methodology consists of a parametric model that is capable of processing acceleration data collected with an IMU attached to the centre of mass of the subject's dominant hand. The developed model was successfully validated against a subject study with ten participants.

Keywords: Automatic assessment , Biomechanics , Manual dexterity , Parametric model , Wearable devices

Statistical Shape Model (SSM) for infant cranial analysis is challenging due to open sutures, which complicate the process of establishing anatomical correspondences between models. This study proposes a Wrap4D-based methodology for accurate preparation of newborn's cranial samples used in SSM. The approach integrates skin and skull segmentation with a guided wrapping technique that supports suture filling through anatomically-guided surface adaptation, while ensuring high fidelity in shape alignment. SSM algorithm uses the prepared dataset of 75 normal infant skulls from Meyer Children's Hospital IRCCS for the creation of a template, which serves as the reference model for defining a standard newborn's cranial shape. The methodology offers a rapid, reproducible and anatomically accurate solution for modelling suture closure. Preliminary results led to a Generalization of 1.245 mm, a Specificity of 2.659 mm and a Compactness of 98% with 20 modes of variation. Finally, quantitative comparison with traditional wrapping techniques reveals Wrap4D superior anatomical preservation in the region of suture.

Keywords: Newborn Skull , Statistical Shape Model , Suture closure , Wrapping

Objective: Pediatric airway management presents unique challenges, particularly in patients with congenital conditions that increase the risk of difficult intubation. Simulation offers a safe environment for clinicians to practice, yet current pediatric mannequins often lack pathological realism. This study aims to develop and validate a high-fidelity, patient-specific pediatric airway mannequin simulating difficult intubation associated with Crouzon syndrome. Technology or Method: A modular training mannequin was developed through CT-based modeling and additive manufacturing at the T3Ddy Laboratory, a collaboration between AOU Meyer Children's Hospital-IRCCS and the University of Florence. Anatomical structures were segmented from CT and MRI scans of a 19-month-old patient with Crouzon syndrome. These 3-D models guided the design of a realistic airway, including nasal and oral access, a flexible tongue, and a movable jaw. Rigid parts were 3-D-printed; soft tissues were cast in silicones of varying hardness. Design choices were validated through iterative testing and refinement. Results: The simulator was evaluated during a pediatric bronchoscopy training course. Physicians assessed realism, tactile feedback, and usability via a Likert-scale questionnaire. Results indicated strong agreement on the mannequin's effectiveness in replicating challenging intubation scenarios, particularly those requiring fiberoptic-guided techniques. Conclusion: This modular, patient-specific pediatric airway simulator provides a realistic, high-fidelity platform for training clinicians in difficult intubation techniques. Its anatomically accurate design enhances procedural confidence and skill acquisition, particularly for managing complex cases like those associated with Crouzon syndrome.

Keywords: 3-D printing , additive manufacturing , Crouzon syndrome simulator , pathological airway , pediatric simulation

Purpose: Reverse Shoulder Arthroplasty (RSA) is widely used to treat shoulder joint pathologies. However, this procedure may result in reduced range of motion (ROM), scapular notching, and prosthetic instability. These complications vary among patients, highlighting the need for individualized preoperative planning. This study introduces a novel parametric methodology to determine optimal glenoid component positioning by evaluating ROM, instability ratio, and the percentage of bone resected. Method: The proposed approach was applied to four patient models treated with two prosthetic designs. The methodology consists of four steps within a patient-specific parametric tool: 3D anatomical reconstruction, virtual surgical planning, biomechanical and geometric evaluation, and identification of optimal configurations. Fifteen glenoid component orientations were generated by varying tilt angles. The best configurations were identified based on ROM and instability assessments, while bone resection volume was calculated as an additional parameter. Results: Maximum values of abduction–adduction, internal rotation, and external rotation were 87.23°, 90°, and 70.59°, respectively, although not achieved in a single configuration. Instability ratios ranged from 0.23 to 0.62. Bone resection varied between 0.4% and 5.5%, depending on the configuration. Conclusions: This methodology provides a patient-specific framework to support preoperative planning in RSA.

Keywords: CAD-based planning , Glenoid positioning , Joint stability , Patient-specific modeling , Range of motion , Reverse shoulder arthroplasty

Ankle injuries are common due to the joint's role in weight-bearing and dynamic motion. Finite element method (FEM) has become a valuable tool for understanding joint biomechanics and planning clinical interventions. However, many existing models are limited by static simulations, simplified geometry, or generalised approaches that do not focus specifically on the talus-tibial joint. This study presents a subject-specific FEM framework of the ankle, integrating magnetic resonance imaging (MRI) and gait data from a healthy 49-year-old male. The tibia and talus were reconstructed from MRI and cartilages were modeled using a custom method to compensate for limitations in image resolution. Kinematic data was collected using the Xsens motion capture system and applied to a dynamic FEM developed in Abaqus. The model yielded contact pressures between 1.2 and 21.8 MPa and maximum von Mises stresses up to 5.7 MPa. The stress distribution was predominantly lateral, consistent with known biomechanical patterns. This framework allows realistic simulation of ankle mechanics and provides a basis for assessment of pathological conditions and surgical planning.

Keywords: 3D Modeling , Ankle , Finite Element Analysis , Gait Analysis

This study aims to develop an intraoperative navigation system for in-vivo procedures leveraging optical flow techniques. Traditional methods for organ tracking often fail in intraoperative scenarios due to domain complexity and, in the case of machine learning methods, by lack of annotated data. To address this challenge, we present a novel organ tracking system based on optical flow and evaluate the performance of four state-of-the-art neural networks for optical flow to determine the most suitable one to use in our system. The proposed system combines semantic segmentation and optical flow estimation. Segmentation networks identify the organ, surgical tools, and background in each frame. Then, deep learning-based optical flow networks estimate its motion across frames. The resulting motion is used to compute the organ's rotation and translation and update the 3D virtual model accordingly. The performances of the four neural networks for optical flow are tested on two video sequences of a robot-assisted partial nephrectomy, where the tracked organ of interest is the kidney. Among the tested networks, and for the concerns of this specific domain of use, RAFT and GMFlow achieved the most promising results in terms of IoU accuracy.

Keywords: 3D Organ Tracking , Deep Learning for Surgery , Partial Nephrectomy , Real-Time Surgical Assistance , Semantic Segmentation

This study presents a fully automated pipeline for the morphometric analysis of the dens, based on an enhanced Statistical Shape Model of the C2 vertebra. Developed in MATLAB, the pipeline integrates semantic segmentation directly into the shape model, enabling precise and reproducible identification of anatomical regions without manual intervention. Unlike deep learning approaches, the proposed framework is well-suited to applications involving limited or heterogeneous data. The model was trained on 25 C2 vertebrae from the VerSe dataset and tested on three independent specimens. Evaluation of model compactness, generalization, and specificity confirmed the robustness of the Statistical Model. Morphometric parameters are extracted in reference to a local coordinate system derived from the mean C2 shape, ensuring anatomical consistency across specimens. The morphometric results for the dens fell within the anatomical ranges reported in the literature, supporting the method's validity. While not intended for clinical use due to dataset limitations, this work lays the foundation for scalable, reproducible, and anatomically informed morphometric analysis of the dens.

Keywords: Automatic Feature Recognition , Biomedical Image Analysis , Statistical Shape Modeling

Accurate identification of spinal landmarks is critical in postural assessment, spinal deformity monitoring, and biomechanical modeling. Conventional techniques, such as radiographic imaging and manual palpation, suffer from significant limitations, including radiation exposure and operator dependence. This study presents a novel, fully automated method for localizing spinal apophyses using high-resolution 3D surface scans and shape index analysis. The proposed approach extracts the dorsal symmetry line and analyzes perturbations in the shape index, a differential geometric descriptor computed from local principal curvatures, to infer spinous process locations. Experimental validation was conducted on 21 healthy subjects using a structured-light 3D optical scanner, with palpation-based identification serving as a clinical reference. The method demonstrated high sensitivity, with a false negative rate of only 1.58% relative to operator-identified landmarks. The approach also identified additional plausible landmarks not detected by the operator, suggesting potential for improved diagnostic accuracy. These results support the method's suitability for objective, repeatable spinal landmark detection, with implications for both clinical assessment and computational modeling. Future work will focus on validation against radiographic ground-truth and applicability in pathological cases.

Keywords: 3D Surface Topography , Automated Landmark Detection , Shape Index Analysis , Spinous Process Detection

(1) Background: HTPLA FDM-printed cutting guides enable the low-cost, in-hospital production of patient-specific instruments. However, annealing, which is required for steam sterilization, may alter the dimensions of fit-critical fixation pin holes. (2) Methods: HTPLA cylindrical specimens (height 5 mm) were printed with fixed process parameters and vertical orientation. Inner diameter (1.6–5.0 mm) and wall thickness (2–6 mm) were varied using a two-factor Central Composite Design (n = 13). Following a two-stage annealing treatment (80 °C, 10 min; 100 °C, 50 min), post-annealing dimensions were measured and modeled using Response Surface Methodology. An illustrative verification was performed on additional specimens. (3) Results: Annealing induced a systematic decrease in inner diameter (−0.4 to −0.9 mm) and an increase in wall thickness (+0.1 to +0.4 mm). A reduced quadratic model accurately captured these trends within the investigated range, with small residuals observed during verification (≤0.1 mm). (4) Conclusions: The proposed local, geometry-driven model supports compensation in fixation pin-hole dimensions in annealed HTPLA cutting guides, improving dimensional predictability within a defined design and process window.

Keywords: 3D printing , annealing , cutting guides , deformation , fused deposition modelling , high-temperature polylactic acid , orthopedics , PLA , polylactic acid , thermal treatment

Tissue-mimicking materials are essential for developing realistic ultrasound phantoms in medical training and device calibration. This study systematically evaluates the acoustic and physical properties of 15 materials, including gelatin-based formulations, synthetic gels, and rubbers, to assess their suitability for simulating human soft tissues. The investigation focused on ultrasound propagation speed, attenuation coefficients, and temporal stability, with measurements conducted under controlled conditions to ensure consistency. Results revealed that organic gelatins exhibited propagation speeds (1508–1626 m/s) and attenuation coefficients (0.21–1.10 dB/cm) closely aligned with soft tissue benchmarks (1540 m/s and 0.54 dB/cm MHz, respectively), with minimal variations (<5%) over 15 days. However, their susceptibility to dehydration and mold growth necessitates protective measures. Synthetic gels, such as ballistic gel and PVC-Plastisol, demonstrated superior long-term stability but required more complex fabrication processes. Rubbers, while durable, exhibited acoustic properties that deviated significantly from tissue standards, limiting their utility. The study quantitatively highlights trade-offs between material categories: gelatins offer cost-effectiveness and acoustic fidelity for short-term use, whereas synthetic gels provide durability for repeated applications. These findings provide a comprehensive framework for selecting materials tailored to specific phantom requirements, balancing acoustic accuracy, stability, and manufacturability. The work advances the development of high-fidelity, cost-effective phantoms, with implications for improving ultrasound training and diagnostic tool validation. Future research should explore hybrid materials and extended stability assessments to further optimize phantom performance.

Keywords: Acoustics , Biomimetic Materials , Gelatin , Gels , Humans , Materials Testing , Phantoms, Imaging , Rubber , Ultrasonics , Ultrasonography

Burn scars represent a significant clinical challenge, owing to their morphological complexity and their functional and aesthetic impact on the patient. Traditionally, the assessment of such scars relies on subjective scales, which are prone to inter-observer variability. This study proposes an innovative approach that integrates colorimetric analysis with artificial intelligence models to provide an objective and reproducible assessment of burn scars. To this end, two novel colorimetric indices—the Erythema Index (EI) and the Vascularity Index (VI)—were introduced. These indices, when combined with machine learning algorithms, enable the automation of scar analysis, yielding promising results in terms of accuracy and reliability.

Keywords: Burn scars , Colorimetric analysis , Colorimetric indices , Machine learning , Objective assessment

Preoperative anxiety is a common condition that can negatively impact patient compliance, pain tolerance, and anesthesia management. Traditional pharmacological treatments include sedatives and anxiolytics, but these can cause adverse effects, such as respiratory issues. Non-pharmacological approaches like cognitive-behavioral therapy (CBT), aromatherapy, and music therapy have also been explored but they require pathways of variable duration that may delay surgery. Virtual reality (VR) is emerging as a promising alternative, allowing patients to engage in immersive experiences that distract them from anxiety-inducing stimuli. A prospective randomized controlled trial was conducted to assess the impact of VR on preoperative anxiety and postoperative pain in patients undergoing elective surgery. A total of 355 patients were randomized into two groups: Group A received entertainment videos via VR headset during the preoperative phase, while Group B received standard care. The primary outcome was the change in STAI (State-Trait Anxiety Inventory) scores at baseline, preoperatively, and postoperatively. Secondary outcomes included pain assessment using the Visual Analog Scale (VAS). Results showed no significant difference in baseline anxiety scores between the two groups. However, both preoperative and postoperative STAI scores were significantly lower in the VR group (p = 0.001 and 0.005, respectively). Additionally, 12 h post-surgery, patients in the VR group reported significantly lower pain scores (3.6 ± 1.3 vs. 5.6 ± 1.6, p = 0.001). No significant differences in pain scores were observed at 24 and 48 h post-surgery. VR could represent a useful aid in the management of preoperative anxiety.

Keywords: Anxiety , Postoperative pain , Preoperative management , Virtual reality

The stability and mechanical performance of collagen scaffolds are critical for bone tissue engineering. This study evaluated two neutralization methods and two physical crosslinking strategies in Viscolma®, a medical-grade collagen. Dropwise or non-dropwise neutralization during synthesis promoted fiber formation, followed by scaffold fabrication via freeze-drying. Crosslinking was achieved by ultraviolet irradiation (UV) (30 min) or dehydrothermal (DHT) treatment at 75 °C or 100 °C for 24–48 h. UV irradiation impaired the physical properties of the scaffold, whereas DHT preserved collagen fiber integrity and produced favourable morphological, physicochemical, and mechanical characteristics. Human bone marrow mesenchymal stem cells grown on DHT-treated scaffolds exhibited high viability, enhanced alkaline phosphatase activity, and increased RUNX2, osteopontin, and osteocalcin expression. These findings highlight DHT crosslinking as a simple, chemical-free approach to produce mechanically robust, biologically active collagen scaffolds with strong potential for trabecular bone regeneration.

Keywords: Bone tissue engineering , Collagen scaffolds , Dehydrothermal treatment , Design methods , Measurements , Sterilization , Ultraviolet irradiation treatment

Recent advancements in additive manufacturing have enabled the design of tailored lattice structures, suitable for a range of applications, including biomedical implants. The design of lattice structures for biomedical applications requires accurate prediction of both stiffness and strength. This study presents a numerical framework to estimate the effective elastic properties and limit stresses of periodic lattice structures using a strain energy-based homogenization method combined with an efficient method to assess limit stresses along the different directions of the lattice structures. Four cell topologies (ACC, BCC, SC-BCC, F2CC) with varying strut diameters were analysed. The effective elastic constants were computed by applying periodic boundary conditions to the representative volume element of the lattice structure. To estimate the effective limit stresses, a method based on the volume-averaged stress over a subset of the most stressed elements (Ω) was proposed. Three selection strategies for Ω were developed and evaluated through sensitivity analyses. Results show that the estimated limit stresses strongly depends on the definition of Ω. The proposed method enables early-stage design of lattice-based implants with tailored mechanical behaviour and controlled failure limits, enhancing safety and biological integration, contributing to the development of computational tools for patient-specific implant design.

Keywords: Additive manufacturing , Finite Element Analysis , Homogenization , Lattice structure , Osseointegration

Central vision loss (CVL) is an increasingly prevalent condition that significantly affects essential daily activities such as reading and visual search. This study simulates a central scotoma in a controlled experimental setting using the Microsoft HoloLens 2 augmented reality (AR) headset, enabling the investigation of compensatory mechanisms when the foveal region is compromised. Thirty-three participants performed a reading task (Task 1) and a visual search task (Task 2) under both normal vision and AR-simulated defect conditions, while eye-tracking data were recorded to analyze differences in visual behaviour and compensatory strategies. Key performance metrics included error rates, task completion times, and eye movement metrics such as the number and duration of fixations and saccades. Results showed that simulated central vision loss induced a more effortful visual exploration strategy, with an increased number of fixations and saccades, as well as longer total fixation duration, while saccadic timing remained stable. Specifically, the mean number and total duration of fixations during the reading task were approximately 14 and 8 s under normal vision, and 18 and 11 s under CVL condition, respectively. These findings demonstrate the potential of AR-based methods to replicate visual impairments in research settings. Future work could expand on the use of extended reality technologies for assistive and rehabilitative applications in individuals with central vision deficits.

Keywords: AR , Augmented Reality , Central vision loss , Eye-tracking , HoloLens 2 , Scotoma , Visual impairment

Objective: Joint replacement surgery, also known as arthroplasty, is a common procedure that restores mobility and relieves pain in patients with severe joint pathologies. Despite being considered routine, arthroplasties are complex interventions with potential complications and variable clinical outcomes. Accurate evaluation of replaced joint mobility to ensure implant stability within the patient's functional range of motion (ROM) is a major challenge in postoperative care. However, the reliability of current assessment methods is limited due to their lack of standardized and quantitative tools. This study presents a patient-specific Mixed Reality (MR) framework designed to enhance postoperative evaluation in joint replacement with a focus on total hip arthroplasty (THA). Methods: The proposed system enables objective quantification and MR visualization of prosthesis biomechanics by integrating ROM simulation and 3D modeling, promoting explainability and interpretability of surgery outcomes. A retrospective analysis of 67 THAs was performed to compare simulated ROM results with clinical assessments and literature benchmarks. Additionally, surgeons evaluated the system's clinical relevance and usability through a preliminary study, including completion of the System Usability Scale (SUS). Results: Simulated ROM measurements showed good agreement with both clinical assessments and established literature reference values across ten movements commonly examined in orthopedic practice. The MR tool demonstrated high accuracy, repeatability, and potential to support postoperative decision-making, with usability testing yielding a favorable median SUS score of 82.5, indicating strong acceptance among clinicians. Conclusion: The patient-specific MR framework provides a reliable, quantitative, and interpretable method for assessing prosthetic joint performance after replacement, supporting its integration into postoperative workflows for improved surgical outcome assessment.

Keywords: Computer-aided surgery , Human-computer interaction , Joint replacement , Mixed reality , Orthopedic surgery , Total Hip arthroplasty

Cutting guides are widely used in cranio-maxillofacial surgery by providing mechanical references for precise bone resections and reducing intraoperative variability. Nevertheless, their rigid and patient-specific design requires dedicated CAD modeling and fabrication, making them time-consuming to produce and difficult to adapt when anatomical conditions or bone surfaces change. This work presents a hybrid surgical cutting guide that combines a physically adjustable device with Augmented Reality (AR) feedback to support intraoperative alignment in maxillofacial osteotomies. The concept merges the tactile reliability of conventional guides with the adaptability of digital visualization, enabling surgeons to fine-tune the cutting plane directly through AR tracking. Registration was performed using cephalometric landmarks and an inside-out tracking approach with HoloLens 2, allowing precise superimposition of virtual cutting planes onto 3D-printed mandibular models. The system was evaluated by both expert and novice operators under three feedback conditions: no AR, holographic overlay, and real-time distance guidance. Results showed that AR feedback was associated with improved positional accuracy, with mean linear deviations of 1.27±0.71mm and angular errors of 4.46±3.27°. Operator experience influenced overall performance, yet enhanced feedback compensated part of this variability. Combining physical and digital guidance can yield more adaptable, precise, and reusable osteotomy tools, paving the way for flexible surgical assistance in clinical settings.

Keywords: Adjustable surgical guide , Augmented Reality , Cranio-maxillofacial surgery , Hololens 2 , Hybrid surgical guide , Pose estimation

Early and reliable identification of vertebral metastases on computed tomography remains a major challenge in oncologic imaging due to the morphological complexity of metastatic lesions and the high inter-patient variability of spinal anatomy. In this study, an end-to-end interpretable radiomic-based framework was developed to automatically distinguish healthy from metastatic vertebrae using segmented DICOM data, coupled with an interactive virtual reality (VR) visualization module implemented in Unity 3D. The proposed framework integrates radiomic feature extraction and selection, informed undersampling to address class imbalance, and automatic machine learning-based classification. To facilitate interpretation, patient-specific 3D models with overlapped classifier outputs were integrated into a VR desktop application, enabling advanced exploration of patient-specific spinal models, with color-coded visualization of algorithmic predictions and expert-defined suspicious lesions. The final classification model, trained using a Random Forest algorithm and optimized via stratified 5-fold cross-validation, achieved an overall accuracy of 0.86, an Area Under the Receiver Operating Characteristic Curve of 0.91, and an F1-score of 0.81 for the metastatic class on the independent test set, achieving competitive diagnostic performance while preserving transparency and clinical interpretability. This study represents a foundational step toward intelligent, interactive, and clinically interpretable tools for the diagnosis and follow-up of spinal metastatic disease.

Keywords: automatic lesion classification , bone lesions , machine learning , medical 3D visualization , spinal metastases , virtual reality

The lack of a standardized methodology complicates accuracy assessment in computer-assisted mandibular reconstruction. Existing landmark-based methods are susceptible to operator variability, while surface-based comparisons can mask local deviations. This study validates a novel, automated protocol, the Global Positioning Layout (GPL), to quantify the 3D discrepancy between the virtual surgical plan and the postoperative outcome, by comparing its performance and reliability against Methods A and B. A retrospective cohort of 17 patients was analysed, with three operators performing all measurements on two occasions. The GPL method demonstrated complete reproducibility, with no inter- or intra-operator variability, providing a detailed, spatially-oriented assessment of deviations. In contrast, the landmark-based method showed poor reproducibility and systematic bias and was often inapplicable due to the absence of landmarks after resection. The surface-based method, while objective for its mean error metric, was operator-dependent for initial alignment and its non-directional output masked significant localized deviations. This study validates GPL as a robust and fully reproducible tool that overcomes the critical limitations of established techniques. The GPL method provides a strong foundation for a standardized protocol, essential for the reliable comparison of surgical outcomes, refinement of surgical techniques, and improvement of long-term patient outcomes.

Keywords: Accuracy assessment, Validation , Computer-Aided Manufacturing , Mandibular reconstruction, Computer-Aided Design , Prosthesis

Objectives: This study aimed to investigate the effect of erythritol air-polishing on implant surface topography and bacterial colonization, and to determine the antimicrobial activity of erythritol powder. Materials and Methods: Titanium implants, with machined/acid-etched hybrid design, were divided into three groups: erythritol air-polishing for 1 min (E1), 5 min (E5), and untreated control. Surface analysis was performed using a stylus profilometer and scanning electron microscope (SEM). To test the ability to prevent biofilm formation, four bacteria strains (Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus mutans, Streptococcus sanguinis) were separately cultured on five implants per group and colony counting was performed. The intrinsic erythritol antibacterial activity was investigated by means of minimum inhibitory concentration against the same strains. Results: At SEM analysis implant surfaces appeared unaltered by air-polishing and presented increasing amount of residues depending on the treatment duration. Machined surfaces exhibited no significant differences in roughness parameters between the groups. On acid-etched surfaces, E5 presented significantly lower Ra (vs. E1 and control) and Rz (vs. control). The count of colonies was significantly lower for all bacterial strains on treated implants as compared to control, with E1 and E5 being equally capable to reduce by 1.5 log bacteria growth. Erythritol antimicrobial activity against all tested bacterial strains was confirmed. Conclusions: The proposed erythritol air-polishing protocols did not alter implant surfaces and the antimicrobial properties of erythritol are conserved by the titanium implant surfaces. Clinical Relevance: Erythritol air-polishing could be repeatedly used in supportive peri-implant care programmes.

Keywords: antimicrobial , bacterial adhesion , dental implant , erythritol , powder