Search Results (208)

For the first time, twenty spun polychrome glass figurines (considered as tangible cultural heritage objects) stylistically assigned to workshops of the city of Nevers from the 17th to 19th centuries have been analyzed at the Musée de la Faïence et des Beaux-Arts of Nevers using non-invasive XRF and Raman spectroscopy. The results are compared with those previously obtained for figurines assigned to the Perrot’s Orléans workshop. A wide variety of glass compositions is observed, ranging from lead-free to lead-rich compositions, which are attributed to the preparation technique that involves mixing glass stems of different origins during the creation of the figurine. White opacification is achieved with Ca₂Sb₂O₇. The cobalt source is consistently arsenic-rich, but its composition becomes more complex during the 18th century, indicating the use of different cobalt sources. A variety of lead-tin and Naples yellow pigments are identified. Metal nanoparticles are used for pink, ruby, and carnation colors. The detection of associated arsenic and/or tin supports the identification of the use of gold nanoparticles. Cassiterite and arsenates of lead/calcium/potassium are also detected in a few figurines, probably from a different workshop. This latter opacifier, being more frequent in previously studied artifacts assigned to Orléans, suggests that the assignment to Nevers could be questioned. Aventurine glass is present in two objects. Full article

Background: Tissue expanders with metallic ports are commonly used in post-mastectomy breast reconstruction but can produce significant computed tomography (CT) artifacts, which impair accurate delineation of target volumes during radiotherapy planning. The Motiva Flora^® expander incorporates an integrated radiofrequency identification (RFID) valve, designed to be magnet-free and magnetic resonance imaging (MRI)-conditional, potentially minimizing image distortion and improving the precision of treatment planning. This pilot study aims to quantitatively compare the extent of CT image distortion observed in radiotherapy simulation scans between conventional metallic-valve expanders and RFID-valve expanders, evaluating their impact on radiotherapy planning quality. Methods: Between January 2024 and September 2025, fourteen consecutive patients who underwent post-mastectomy two-stage breast reconstruction followed by adjuvant RT at Hospital Santa Maria della Misericordia (Udine, Italy) were included. Seven patients received Motiva Flora^® tissue expanders with a non-metallic RFID port, and seven received Mentor CPX4^® expanders with a conventional metallic port. The volume of areas with a significant level of artifacts (artifact volume) was quantitatively evaluated by delineating the CT image area of distortion caused by the valve. Moreover, a comparison of the ratio between artifact volume and clinical target volume (artifact volume/CTV volume) between expander types to assess potential imaging-related distortions has been made. Group comparisons of volume ratio were performed using Welch’s t-test. Results: Patients reconstructed with Motiva Flora^® showed a mean artifact volume of 24.5 ± 10.3 cc, whereas those with Mentor CPX4^® expanders presented a mean artifact volume of 64.2 ± 38.1 cc. The ratio between artifact volume and clinical target volume (CTV) was lower in patients reconstructed with Motiva expanders compared to those reconstructed with Mentor expanders and this difference was significant with Welch’s t-test (p = 0.046). Conclusions: The reduced CT distortion observed with the RFID valve-equipped Motiva Flora suggests a superior radiological compatibility compared to conventional metallic-port expanders, with potential to enhance the accuracy of radiotherapy planning. Full article

Objectives: Cone-beam computed tomography (CBCT) is central to three-dimensional assessment in oral surgery and implant dentistry; however, CBCT-derived gray values expressed as HU-like units are not equivalent to true CT-derived Hounsfield Units (HU). This brief methodological secondary analysis evaluated the reliability and practical limitations of such values in assessing radiographic changes after peri-implantitis surgery. Methods: The analysis used the imaging protocol and group-level radiological data from a previously published prospective clinical cohort, conducted under the same protocol and ethical approval of the Institutional Ethics Committee of the Medical University of Lublin (KE-0254/248/11/2023; 23 November 2023). The source cohort included 57 patients treated after implant removal for severe peri-implantitis with small-particle dentin (n = 22), Bio-Oss (n = 15), or spontaneous healing without grafting (n = 20). CBCT scans were analyzed in OnDemand3D (version 1.0.11.1007) using manually selected square regions of interest (ROI; 30 × 30 pixels). No external phantom calibration, cross-device normalization, or formal intra-/inter-observer reproducibility assessment was available in the secondary dataset. Results: The previously reported mean study-site values were 779.62 ± 325.92 gray-value units for small-particle dentin, 910.51 ± 155.03 gray-value units for Bio-Oss, and 206.04 ± 174.21 gray-value units for controls. These findings are presented as protocol-dependent attenuation patterns, not as direct material rankings, bone-density thresholds, or proof of regeneration. Variability remained substantial, with study-site coefficients of variation of 41.8%, 17.0%, and 84.6%, respectively, and high adjacent-site variability. Interpretation was constrained by manual ROI placement, lack of calibration, absence of observer-agreement metrics, unequal follow-up timing, and CBCT sensitivity to scatter, beam hardening, field of view, reconstruction settings, and metal-related artifacts. Conclusions: CBCT-derived gray values may be useful as relative indicators of local radiographic attenuation change within a standardized protocol, but they should not be interpreted as absolute measures of bone density. Future regenerative oral surgery studies should combine standardized acquisition, explicit ROI methodology, repeated measurements, observer-agreement analysis, and complementary clinical, radiographic, or histological outcomes. Full article

Interbody cages are employed in spinal surgery to enhance segmental stability and facilitate decompression of the spinal cord and nerve roots. As these devices are commonly made of titanium, they produce metal-induced artifacts during postsurgical magnetic resonance (MR) imaging. This study aims to provide a descriptive comparison of five titanium interbody cage prototypes regarding the spatial extent of signal loss artifacts produced during MR imaging under phantom conditions. Five cage prototypes, 3D-printed from a titanium alloy, were imaged using a 3.0 T MR system in accordance with the F2119-07 standard of the American Society for Testing and Materials (ASTM), with advanced metal artifact reduction applied. The cages had identical external geometries but differed in metal volume, contact surface, layout, porosity, and, when applicable, hole geometry. The extent of the studied artifacts demonstrated high to very high repeatability and good to excellent reliability across all MR imaging settings. The quantified extent of signal loss artifacts was lowest for the cage prototype with a solid frame and an interior net structure. Under specific phantom MR imaging conditions, the porous cage with a frame-net layout, but without a centrally positioned hole, produces signal loss artifacts with the smallest spatial extent, which may be advantageous. However, the potential clinical translation of these findings is limited and requires future investigation. Full article

Metal additive manufacturing (AM) has progressed from prototyping toward industrial deployment, yet adoption remains uneven because many initiatives are still driven by isolated process demonstrations rather than system-level manufacturing strategy. This framework review proposes a gated decision workflow for integrating metal AM into industrial systems by coupling process-family selection and route definition, Design for Additive Manufacturing (DfAM) and sustainability considerations. The paper consolidates a comparative matrix of six metal AM process families for early down-selection, introduces a minimal evidence checklist linking each decision gate to required artifacts, and contextualizes the workflow through representative part archetypes. The framework is further supported by practical guidance on process-specific DfAM constraints, including support strategy, residual stress, and surface integrity in powder bed fusion; shrinkage-driven design in sinter-based routes; and machining allowances in repair and hybrid manufacturing. Rather than positioning metal AM as a universal substitute for conventional manufacturing, this work defines it as a complementary, strategy-dependent enabler whose sustainability benefits depend on system-level integration and application context. Full article

Background/Objectives: Dental metallic implants cause severe streaking artifacts in kilovoltage CT (kVCT), compromising dose calculation in radiotherapy (RT) treatment planning. The purpose of this study is to assess the dosimetric agreement of synthetic MVCT (sMVCT) images generated from artifact-affected kVCT using a deep learning network with respect to true MVCT (tMVCT) acquired at the treatment machine. Methods: Nineteen head and neck cancer patients with dental metallic implants treated with RT were included. Planning kVCT images were converted to sMVCT using Metal Artifact Reduction through Domain Transformation Network (MAR-DTN), a UNet-inspired deep learning network. The sMVCT images were rigidly registered to true MVCT (tMVCT) acquired on the Hi-Art II Tomotherapy system. Mean Hounsfield Unit (HU) values were compared across seven structures (thyroid, bilateral parotids, brainstem, spinal cord, GTV, PTV70) using pairwise Wilcoxon tests and Two One-Sided Tests (TOST) for statistical equivalence within a pre-specified margin of ±20 HU (corresponding to a 2% deviation in physical density). Dose distributions were recalculated on sMVCT using the AAA algorithm and compared to reference tMVCT-based plans via dose–volume histogram (DVH) metrics, evaluated for equivalence by TOST within a margin of ±2% of the prescribed dose (±142 cGy of 70.95 Gy), and via 3D gamma index, evaluated by one-sided non-inferiority test against the clinically accepted thresholds of 90% (2 mm/2%) and 95% (3 mm/3%). A pre-specified sensitivity analysis was performed by repeating all comparisons on the strictly independent sub-cohort (n = 16) excluding three patients drawn from the MAR-DTN training set. Results: All seven anatomical structures showed statistical equivalence between sMVCT and tMVCT under the ±20 HU margin (TOST p < 0.05; mean HU differences in the range −1.1 to +8.4 HU; all Wilcoxon p > 0.05). All nine DVH metrics achieved formal dosimetric equivalence within ±2% of the prescribed dose (TOST p < 0.05). Mean 3D gamma pass rates were 94.3% (95% CI: 89.3–97.1) for the 2 mm/2% criterion and 97.6% (95% CI: 94.8–99.0) for the 3 mm/3% criterion, both formally non-inferior to the respective clinical thresholds (p < 0.0001). Residual gamma failures were concentrated at the patient surface, consistent with inter-session repositioning uncertainty rather than errors in synthetic image generation. Sensitivity analysis on the n = 16 sub-cohort confirmed all conclusions, with mean HU and DVH differences smaller than in the full cohort for the structures showing the largest mean differences, and comparable for the remaining structures, with all TOST equivalence and gamma non-inferiority tests confirmed in both cohorts. Conclusions: sMVCT images generated via MAR-DTN show dosimetric agreement with physically acquired tMVCT in head and neck patients with dental implants, formally demonstrated by TOST equivalence within ±2% of prescribed dose for all DVH metrics. The combined HU and gamma index framework presented here represents a promising quality assurance approach for AI-based synthetic imaging tools in radiotherapy, pending validation in larger prospective multicentre cohorts. Full article

Elemental sulfur frequently coexists with organic polysulfides in environmental samples and laboratory sulfurization experiments, complicating the accurate analysis of sulfur speciation. Reliable methods for selective sulfur removal are therefore required to avoid analytical artifacts. In this study, we systematically evaluated commonly used chemical sulfur removal approaches, including treatment with metallic copper and silver and reaction with tetrabutylammonium sulfite, and compared them with a chromatographic separation method based on C18 reversed-phase silica gel column chromatography. Model organic polysulfides, dimethyl polysulfides, diallyl polysulfides, dibenzyl disulfide, and cyclic polysulfide lenthionine were used to assess method performance under controlled conditions. The results demonstrate that chemical treatments are non-selective and lead to substantial decomposition of organic polysulfides, particularly for longer-chain compounds. In contrast, C18 reversed-phase silica gel column chromatography enables efficient and selective removal of elemental sulfur while preserving the original composition of organic polysulfides, with recoveries in the range of ~90–107%. These findings indicate that commonly applied sulfur removal procedures may introduce significant biases in sulfur speciation analyses. The chromatographic approach presented here provides a reproducible and non-destructive alternative for sample preparation, improving the reliability of studying sulfur speciation and transformation in natural and laboratory systems. Full article

Micro- and nano-container-based self-healing coatings have emerged as a promising strategy for the long-term conservation of cultural heritage artifacts, including metals, stone, organic matter, and construction materials. These coatings incorporate microcapsules or nanocapsules with tailored shell and core materials, enabling autonomous release of healing agents or corrosion inhibitors in response to damage. For metallic artifacts, benzotriazole@mesoporous silica nanoparticles (BTA@MSN) microcapsules achieve selective pH-responsive release, reaching 77% at pH 9.0 and 42% at pH 5.0, effectively mitigating localized corrosion. Temperature-adaptive poly(methyl methacrylate-co-methacrylic acid) (PMMA-MA)/MgO microcapsules exhibit controlled rupture rates, with a 75% reduction at elevated temperatures, enhancing crack repair efficiency by approximately 5%. Organic artifacts, such as wooden or paper manuscripts, benefit from clove oil nanocapsules, which increase tensile strength by 43.5% and fracture toughness by 101.9%, with only 2.91% weight loss over 7 days compared to 33.1% for unencapsulated oil. Advanced fabrication methods—including microfluidics, Pickering emulsions, and multi-core systems—enable high encapsulation efficiency (up to 73.5%), uniform particle size, and repeatable healing. Multi-stimuli responsiveness (pH, temperature, light, magnetic fields) and biobased, environmentally friendly materials further enhance adaptability and sustainability. In this review, “self-healing” is defined broadly to include both physical crack repair and autonomous restoration of protective functions. Overall, self-healing micro/nanocapsule coatings provide a highly controllable, efficient, and durable solution for active heritage protection, representing a shift from passive to intelligent conservation strategies. Furthermore, a systematic comparison of different capsule systems is provided to clarify their respective advantages and limitations. Overall, hybrid systems exhibit the most balanced performance, while inorganic nanocontainers offer superior stability and controlled release, and polymeric capsules enable rapid healing but limited reusability. Full article

Metallic cultural heritage artifacts are highly susceptible to multi-factor electrochemical degradation, driven by chloride ions, humidity, acidic deposition, and heterogeneous material interfaces. Traditional conservation materials, including organic and inorganic coatings and corrosion inhibitors, often exhibit limited interfacial compatibility, poor long-term stability, and insufficient multifunctionality. Recent advances in protective materials—including nano-enhanced coatings, self-healing systems, smart-responsive polymers, green biodegradable formulations, and metal–organic framework (MOF)-based composites—offer multifunctional, long-lasting, and minimally invasive solutions. These materials enhance corrosion inhibition, barrier performance, structural reinforcement, and environmental responsiveness, while enabling in situ sensing, reversible application, and ethical deployment. Laboratory evaluation, accelerated aging tests, and field verification demonstrate their efficacy in preserving artifact integrity and aesthetics. This review systematically discusses degradation mechanisms, limitations of traditional materials, and the mechanisms, applications, and future perspectives of novel functional coatings, providing a roadmap for scientifically optimized and ethically responsible conservation of metallic heritage. Full article

Non-Line-Of-Sight (NLOS) Terahertz (THz) radar 3D imaging leverages electromagnetic wave propagation characteristics such as reflection, diffraction, scattering, and penetration to detect, locate, and image hidden targets in occluded environments. It holds significant potential for applications in autonomous driving, disaster rescue, and urban warfare. However, uncertainties introduced by reflecting surfaces and occluding objects in practical NLOS scenarios, such as phase errors, aperture shadowing, and multipath effects, lead to issues like blurred imaging and increased artifacts in radar imaging. To address these challenges, this study proposes a 3D learning imaging method for NLOS THz radar based on a holographic imaging operator, leveraging the adaptive optimization properties of deep unfolding networks and prior environmental perception. First, a 3D imaging model for NLOS THz radar in the Looking Around Corner (LAC) scenario is established. A holographic imaging operator is introduced to enhance imaging efficiency and reduce computational complexity. Second, a high-precision NLOS 3D imaging network is constructed based on the Fast Iterative Shrinkage/Thresholding Algorithm (FISTA) framework. Utilizing features specific to NLOS scenes and designing algorithm parameters as functions of network weights, the method achieves high-precision and high-efficiency in the 3D reconstruction of NLOS targets. Finally, a near-field NLOS radar imaging platform operating at 121 GHz (within the sub-THz regime) is developed. Experimental validations in the LAC scenario are performed on targets, including metal letters “E”, a metal resolution chart, and a pair of scissors. The results demonstrate that the proposed method significantly improves 3D imaging precision, achieving a two-orders-of-magnitude increase in computational speed over traditional imaging algorithms. Full article

Metal artifacts generated by dental implants significantly degrade cone-beam computed tomography (CBCT) volumes, obscuring critical anatomical structures and compromising diagnostic precision. To address this, an unsupervised deep learning framework has been proposed for Metal Artifact Reduction (MAR) utilizing a Cycle-Consistent Adversarial Network (CycleGAN) optimized for high-fidelity restoration. Unlike supervised methods that rely on unattainable voxel-aligned paired datasets, the proposed approach leverages an unpaired dataset of approximately 4000 images, curated from the public ToothFairy dataset. The architecture integrates U-Net-based generators and PatchGAN discriminators, specifically tuned to mitigate generative hallucinations and preserve morphological integrity. Quantitative benchmarking on a held-out test set demonstrates a 34.6% improvement in the Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) score, a substantial reduction in Fréchet Inception Distance (FID) from 207.03 to 157.04, and a superior Structural Similarity Index Measure (SSIM) of 0.9105. The framework achieves real-time efficiency with a 3.03 ms inference time per slice, effectively suppressing artifacts while preserving anatomical detail. Expert validation confirms high fidelity; however, to ensure reliability in extreme cases, the architecture is recommended as a clinical decision-support tool under human-in-the-loop oversight. By enhancing diagnostic clarity via a scalable software pipeline, this study provides a robust solution for high-fidelity dental implant imaging. Full article

Metal artifact reduction (MAR) remains a long-standing challenge in computed tomography (CT) reconstruction. Metallic implants introduce inconsistencies between the acquired projection data and the ideal Radon transform, resulting in severe streaking artifacts in images reconstructed using the conventional filtered back projection (FBP) algorithm. In this work, we propose a nonlinear weighted anisotropic total variation (NWATV) regularization method to mitigate metal artifacts and improve CT image quality. The effectiveness of the NWATV method is evaluated through three experiments, and the results demonstrate that it achieves superior reconstruction performance compared to the conventional linear interpolation method, the normalized metal artifact reduction method and the anisotropic total variation (TV) regularization method. Full article

Artificial intelligence (AI) is increasingly transforming spine surgery, with expanding applications in diagnostics, intraoperative imaging, and surgical navigation. As the field advances toward greater precision and safety, machine learning (ML) and deep learning technologies are being integrated to augment surgeon expertise and optimize operative workflows. In particular, AI-driven innovations in image acquisition and navigation are reshaping intraoperative decision-making and technical execution. This narrative review provides an overview of AI applications relevant to intraoperative imaging and navigation in spine surgery. We begin by defining key concepts in AI, ML, and deep learning and briefly outline the historical evolution of AI within spine practice. We then examine current capabilities in image recognition and automated pathology detection, emphasizing their clinical relevance. Given the central role of imaging accuracy in modern navigation-assisted procedures, we review conventional acquisition platforms, including intraoperative computed tomography (CT) systems (e.g., O-arm, GE, Airo), surface-based registration to preoperative CT (Stryker, Medtronic), and optical surface mapping technologies (e.g., 7D Surgical). Emerging AI-optimized advancements are subsequently discussed, including low-dose intraoperative CT protocols, expanded scan windows, metal artifact reduction algorithms, integration of 2D fluoroscopy with preoperative CT datasets, and 3D reconstruction derived from 2D imaging. These developments aim to improve image quality, reduce radiation exposure, and enhance navigational accuracy. By synthesizing current evidence and technological progress, this review highlights how AI-enhanced imaging systems are redefining intraoperative spine surgery and shaping the future of precision-based care. The primary purpose of this review is to outline the applications of AI and its potential for perioperative and intraoperative optimization, including radiation exposure reduction, workflow streamlining, preoperative planning, robot-assisted surgery, and navigation. The secondary purpose is to define AI, machine learning, and deep learning within the medical context, describe image and pathology recognition, and provide a historical overview of AI in orthopedic spine surgery. Full article

Cold-mercury gilding uses mercury as an adhesive to bond gold foil onto the surface of copper and silver artifacts. This technique and mercury gilding (fire gilding) both belong to the Au-Hg system and are closely related in technology. Clarifying the technical differences between them is of great significance for revealing the developmental sequence of ancient gilding technologies. On the basis of reconstructing traditional fire gilding, simulated cold-mercury-gilded samples were successfully prepared using experimental archeological methods, and multi-scale characterization was performed using SEM-EDS, XRD, and XPS. The results show that the surface of cold-mercury-gilded samples displays a micromorphology of folded and overlapped gold foil accompanied by locally dense particle aggregation. The cross-section of the gold layer exhibits a multilayer stacked structure, in which mercury is enriched at the gold layer/substrate interface and forms an AuHgCu/Ag diffusion layer. Room-temperature-stable Au-Hg and Ag-Hg phases such as Au₂Hg and AgHg are present in the gold layer, reflecting complex phase transformation behavior of the Au-Hg/Ag-Hg system at room temperature. During cold-mercury gilding, liquid mercury first adheres to the gold foil, and then interdiffusion and phase reactions occur between mercury, gold, and copper/silver atoms at room temperature. Intermetallic compounds and diffusion layers formed at the interface achieve firm bonding between the gold layer and the substrate. Both cold-mercury gilding and mercury gilding achieve metallurgical bonding through atomic interdiffusion. However, affected by differences in the initial state of mercury and operating temperature, the phase transformation and atomic diffusion behaviors of the system differ significantly, which are ultimately reflected in the cross-sectional structure of the gold layer, the composition of the interfacial diffusion layer, and the types of phases. Therefore, mercury-gilded artifacts show superior gold layer durability and bonding strength with the substrate compared with cold-mercury-gilded artifacts. Both techniques pioneered the application of mercury in metallic gilding and represent important innovations in ancient surface decoration technology. Full article

Archaeological bone artifacts frequently exhibit diminished mechanical integrity as a result of organic matrix degradation. Under adverse environmental conditions, such artifacts are particularly susceptible to surface cracking and disintegration into powder. It is urgently necessary to develop protective materials that possess high permeability, strong reinforcing power and good compatibility. This study evaluated the protective performance of a novel Acrylate Metal Complex (AMC) and two conventional commercial consolidants (acrylic resin Paraloid B72 and ethyl silicate-based material Remmers 300) on fragile bone artifacts. Using simulated samples resembling bone artefacts, a systematic evaluation was conducted to assess the penetration, mechanical reinforcement efficacy, microstructural modifications, chromatic impact, and aging resistance of three consolidants. The results indicate that AMC demonstrates optimal permeation capability and can significantly enhance the surface hardness of bone specimens, achieving an increase of 7.7%. The colorimetric changes observed in all three reinforced materials following treatment remained within acceptable limits (ΔE* < 1.5). Accelerated aging tests—including 300 h of UV irradiation and 30 cycles of alternating dry-wet conditions—demonstrated that bone-mimetic composites reinforced with AMC exhibited significantly superior aging resistance relative to those treated with B72 and Remmers 300. In the actual application verification of the archaeological bone relics, the surface hardness of the reinforced AMC increased by 10%, the wave velocity increased by 14.8%, and there was no glare or crust on the surface. Comprehensive comparison shows that AMC outperforms traditional commercial materials in key performance indicators, demonstrating great potential as a next-generation bone relic conservation material. Full article