Design, development and performance of a Fe-Mn-Si-Cu alloy for bioabsorbable medical implants.

Bioabsorbable metallic alloys constitute a very challenging and innovative field, mainly aimed to develop the next generation of temporary medical implants. Degradation data, biological and tests are of major importance in particular for complex alloys, in which the individual element additions could enhance material performance and add functionalities. In this study, a novel Fe-Mn-Si-Cu alloy was carefully designed for vascular and blood-contact applications, and its microstructure, mechanical behavior, degradation behavior and biological performances were investigated accordingly.

Biological Characterization of Ti6Al4V Additively Manufactured Surfaces: Comparison Between Ultrashort Laser Texturing and Conventional Post-Processing.

Among Additive Manufacturing (AM) technologies, Laser Powder Bed Fusion (LPBF) has made a great contribution to optimizing the production of customized implant materials. However, the design of the ideal surface topography, capable of exerting the best biological effect without drawbacks, is still a subject of study. The aim of the present study is to topographically and biologically characterize AM-produced Ti6Al4V ELI (Extra Low Interstitial) samples by comparing different surface finishing.

Impact of Surface Finishing on Ti6Al4V Voronoi Additively Manufactured Structures: Morphology, Dimensional Deviation, and Mechanical Behavior.

Additively manufactured medical devices require proper surface finishing before their use to remove partially adhered particles and provide adequate surface roughness. The literature widely investigates regular lattice structures-mainly scaffolds with small pores to enhance osseointegration; however, only a few studies have addressed the impact of surface finishing on the dimensional deviation and the global and local mechanical responses of lattice samples. Therefore, the current research investigates the impact of biomedical surface finishing (i.

Assessing clinical efficacy of polyp detection models using open-access datasets.

Background: Ensuring accurate polyp detection during colonoscopy is essential for preventing colorectal cancer (CRC). Recent advances in deep learning-based computer-aided detection (CADe) systems have shown promise in enhancing endoscopists' performances. Effective CADe systems must achieve high polyp detection rates from the initial seconds of polyp appearance while maintaining low false positive (FP) detection rates throughout the procedure.

Effect of trabecular architectures on the mechanical response in osteoporotic and healthy human bone.

Research at the mesoscale bone trabeculae arrangement yields intriguing results that, due to their clinical resolution, can be applied in clinical field, contributing significantly to the diagnosis of bone-related diseases. While the literature offers quantitative morphometric parameters for a thorough characterization of the mesoscale bone network, there is a gap in understanding relationships among them, particularly in the context of various bone pathologies. This research aims to bridge these gaps by offering a quantitative evaluation of the interplay among morphometric parameters and mechanical response at mesoscale in osteoporotic and non-osteoporotic bones.

PML restrains p53 activity and cellular senescence in clear cell renal cell carcinoma.

Clear-cell renal cell carcinoma (ccRCC), the major subtype of RCC, is frequently diagnosed at late/metastatic stage with 13% 5-year disease-free survival. Functional inactivation of the wild-type p53 protein is implicated in ccRCC therapy resistance, but the detailed mechanisms of p53 malfunction are still poorly characterized. Thus, a better understanding of the mechanisms of disease progression and therapy resistance is required.

In Vitro Assessment of the Neuro-Compatibility of Fe-20Mn as a Potential Bioresorbable Material for Craniofacial Surgery.

Spring-assisted surgery is a popular option for the treatment of non-syndromic craniosynostosis. The main drawback of this procedure is the need for a second surgery for spring removal, which could be avoided if a distractor material could be metabolised over time. Iron-Manganese alloys (FeMn) have a good trade-off between degradation rate and strength; however, their biocompatibility is still debated.

Bactericidal Activity of Silver-Doped Chitosan Coatings via Electrophoretic Deposition on TiAlV Additively Manufactured Substrates.

Prosthetic reconstruction can serve as a feasible alternative, delivering both functional and aesthetic benefits to individuals with hand and finger injuries, frequent causes of emergency room visits. Implant-related infections pose significant challenges in arthroplasty and osteosynthesis procedures, contributing to surgical failures. As a potential solution to this challenge, this study developed a new class of silver (Ag)-doped chitosan (CS) coatings via electrophoretic deposition (EPD) on osseointegrated prostheses for infection therapy.

A biomechanical study of osseointegrated patient-matched additively manufactured implant for treatment of thumb amputees.

Thumb amputations leads to 50 % loss in hand functionality. To date, silicone vacuum prosthesis and autologous transplantation are the most adopted treatment solutions: nevertheless, vacuum prostheses lack in stability and cause skin issue and surgical treatment is not always accepted by patients. Osseointegrated implants were demonstrated to enhance stability, restore osseoperception and increase the time of prosthesis use.

A novel AI device for real-time optical characterization of colorectal polyps.

Accurate in-vivo optical characterization of colorectal polyps is key to select the optimal treatment regimen during colonoscopy. However, reported accuracies vary widely among endoscopists. We developed a novel intelligent medical device able to seamlessly operate in real-time using conventional white light (WL) endoscopy video stream without virtual chromoendoscopy (blue light, BL).

Osseointegrated Metallic Implants for Finger Amputees: A Review of the Literature.

Digital trauma amputations and digital agenesis strongly affect the functionality and aesthetic appearance of the hand. Autologous reconstruction is the gold standard of treatment. Unfortunately, microsurgical options and transplantation procedures are not possible for patients who present contraindications or refuse to undergo transplantation from the toe (e.

Self-Supervised Learning for Few-Shot Medical Image Segmentation.

Fully-supervised deep learning segmentation models are inflexible when encountering new unseen semantic classes and their fine-tuning often requires significant amounts of annotated data. Few-shot semantic segmentation (FSS) aims to solve this inflexibility by learning to segment an arbitrary unseen semantically meaningful class by referring to only a few labeled examples, without involving fine-tuning. State-of-the-art FSS methods are typically designed for segmenting natural images and rely on abundant annotated data of training classes to learn image representations that generalize well to unseen testing classes.

Phenotypic Expression and Outcomes in Individuals With Rare Genetic Variants of Hypertrophic Cardiomyopathy.

Background: Hypertrophic cardiomyopathy (HCM) is caused by rare variants in sarcomere-encoding genes, but little is known about the clinical significance of these variants in the general population.

Objectives: The goal of this study was to compare lifetime outcomes and cardiovascular phenotypes according to the presence of rare variants in sarcomere-encoding genes among middle-aged adults.

Methods: This study analyzed whole exome sequencing and cardiac magnetic resonance imaging in UK Biobank participants stratified according to sarcomere-encoding variant status.

Heat Treatments for Stress Relieving AlSi9Cu3 Alloy Produced by Laser Powder Bed Fusion.

The present work explores the effect of a stress relieving heat treatment on the microstructure, tensile properties and residual stresses of the laser powder bed fused AlSi9Cu3 alloy. In fact, the rapid cooling rates together with subsequent heating/cooling cycles occurred during layer by layer additive manufacturing production make low temperature heat treatments desirable for promoting stress relaxation as well as limited grain growth: this combination can offer the opportunity of obtaining the best compromise between high strength, good elongation to failure and limited residual stresses. The microstructural features were analysed, revealing that the high cooling rate, induced by the process, caused a large supersaturation of the aluminum matrix and the refinement of the eutectic structure.

Explainable Anatomical Shape Analysis Through Deep Hierarchical Generative Models.

Quantification of anatomical shape changes currently relies on scalar global indexes which are largely insensitive to regional or asymmetric modifications. Accurate assessment of pathology-driven anatomical remodeling is a crucial step for the diagnosis and treatment of many conditions. Deep learning approaches have recently achieved wide success in the analysis of medical images, but they lack interpretability in the feature extraction and decision processes.

Effect of Ultrasonic Nanocrystal Surface Modification on the Microstructure and Martensitic Transformation of Selective Laser Melted Nitinol.

Nitinol has significant potential for biomedical and actuating-sensing devices, thanks to its functional properties. The use of selective laser melting (SLM) with Nitinol powder can promote novel applications aimed to produce 3D complex parts with integrated functional performances. As the final step of the production route, finishing processing needs to be investigated both for the optimization of the surface morphology and the limit alteration of the Nitinol functional properties.

Sex and regional differences in myocardial plasticity in aortic stenosis are revealed by 3D model machine learning.

Aims: Left ventricular hypertrophy (LVH) in aortic stenosis (AS) varies widely before and after aortic valve replacement (AVR), and deeper phenotyping beyond traditional global measures may improve risk stratification. We hypothesized that machine learning derived 3D LV models may provide a more sensitive assessment of remodelling and sex-related differences in AS than conventional measurements.

Methods And Results: One hundred and sixteen patients with severe, symptomatic AS (54% male, 70 ± 10 years) underwent cardiovascular magnetic resonance pre-AVR and 1 year post-AVR.

CoCrMo alloys ions release behavior by TiNbN coating: an in vitro study.

The aim of the study was to show in vitro the greater inertness to the corrosion body fluid of TiNbN coating than the CoCrMo alloy substrate. The prosthetic component under study was a femoral component of total knee prosthesis in CoCrMo alloy coated in TiNbN with Physical Vapor Deposition technique immersed in static Hank's balanced salt solution (HBS) (pH = 6) for at least 34 months at a constant temperature of 37 °C. Another uncoated prosthetic component of CoCrMo alloy with the same type and size was left in static immersion in the same solution and for the same period of time.

Deep learning cardiac motion analysis for human survival prediction.

Motion analysis is used in computer vision to understand the behaviour of moving objects in sequences of images. Optimising the interpretation of dynamic biological systems requires accurate and precise motion tracking as well as efficient representations of high-dimensional motion trajectories so that these can be used for prediction tasks. Here we use image sequences of the heart, acquired using cardiac magnetic resonance imaging, to create time-resolved three-dimensional segmentations using a fully convolutional network trained on anatomical shape priors.

Automatic 3D Bi-Ventricular Segmentation of Cardiac Images by a Shape-Refined Multi- Task Deep Learning Approach.

Deep learning approaches have achieved state-of-the-art performance in cardiac magnetic resonance (CMR) image segmentation. However, most approaches have focused on learning image intensity features for segmentation, whereas the incorporation of anatomical shape priors has received less attention. In this paper, we combine a multi-task deep learning approach with atlas propagation to develop a shape-refined bi-ventricular segmentation pipeline for short-axis CMR volumetric images.

Metabolic pathways associated with right ventricular adaptation to pulmonary hypertension: 3D analysis of cardiac magnetic resonance imaging.

Aims: We sought to identify metabolic pathways associated with right ventricular (RV) adaptation to pulmonary hypertension (PH). We evaluated candidate metabolites, previously associated with survival in pulmonary arterial hypertension, and used automated image segmentation and parametric mapping to model their relationship to adverse patterns of remodelling and wall stress.

Methods And Results: In 312 PH subjects (47.

Fetal Skull Reconstruction via Deep Convolutional Autoencoders.

Ultrasound (US) imaging is arguably the most commonly used modality for fetal screening. Recently, 3DUS has been progressively adopted in modern obstetric practice, showing promising diagnosis capabilities, and alleviating many of the inherent limitations of traditional 2DUS, such as subjectivity and operator dependence. However, the involuntary movements of the fetus, and the difficulty for the operator to inspect the entire volume in real-time can hinder the acquisition of the entire region of interest.