Fast Method Research Articles

A six-year comprehensive review of eye cytology cases received at a tertiary level hospital.

Ocular cytology is an effective method of diagnosing infective, benign, and malignant ocular disease processes due to easy accessibility and rapid turnaround time. However, these specimens pose significant diagnostic challenges due to rarity of the specimen type, sparse diagnostic material available for ancillary workup, and unfamiliarity of the diagnostic entities by the cytopathologist. This study conducted a 6-year comprehensive review of 65 eye cytology cases received at a tertiary level hospital. Cytopathologic diagnoses of "negative for malignancy" and "atypical" were categorized as negative findings (70.8%, n = 46) and diagnoses of "suspicious for malignancy" and "positive for malignancy" were categorized as positive findings (23.1%, n = 15). A 44.6% (n = 29) of cases had subsequent histopathology and/or flow cytometry diagnoses. Premalignant and malignant lesions detected on histopathology were considered as significant findings. Statistical analysis was performed to evaluate the concordance of ocular cytology with associated histopathology and/or flow cytometry diagnoses. The accuracy of final cytology-histopathology and/or cytology-flow cytometry diagnoses in this cohort of cases is 86.2%. The sensitivity and specificity of ocular diagnosis by cytology are 66.6% and 100%, respectively. The positive and negative predictive values of ocular diagnosis by cytology are 100% and 80.9%, respectively. Ocular cytology is a fast, effective, and sensitive method for diagnosing ocular pathology specimens. Familiarity with these specimen types by cytopathologists can help in diagnosing ocular diseases effectively on small, challenging cytologic preparations.

Reassociation of Skeletal Remains Using Laser-Induced Breakdown Spectroscopy.

A major challenge in forensic anthropology and bioarcheology is the development of fast and effective methods for sorting commingled remains. This study assesses how portable laser-induced breakdown spectroscopy (LIBS) can be used to group skeletal remains based on their elemental profiles. LIBS spectra were acquired from the remains of 45 modern skeletons, with a total data set of 8388 profiles from 1284 bones. Spectral feature selection was conducted to reduce the spectral profiles to the peaks exhibiting the highest variation among individuals. Emission lines corresponding to 9 elements (Ca, P, C, K, Mg, Na, Al, Ba, and Sr) were found important for classification. Linear discriminant analysis (LDA) was concurrently used to classify each spectral profile. From the 45 individuals, each LIBS spectrum was successfully sorted to its corresponding skeleton with an average accuracy of 87%. These findings indicate that variation exists among the LIBS profiles of individuals' skeletal remains, highlighting the potential for portable LIBS technology to aid in the sorting of commingled remains.

Short- and long term preservation of cardiac tissue-engineered constructs

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): This research was financially supported by the Gravitation Program ‘‘Materials Driven Regeneration,’’ funded by the Netherlands Organization for Scientific Research (024.003.013) and the EU-funded project BRAV∃ (H2020, ID:874827). Background Cardiac tissue engineering (cTE) has already advanced towards the first clinical trials, investigating safety and feasibility of cTE construct transplantation in failing hearts. However, the lack of well-established preservation methods poses a hindrance to further scalability, commercialization, and transportation, thereby reducing their clinical implementation. Purpose In this study, hypothermic (short-term) preservation (4°C), and slow and fast freezing methods for cryopreservation, at -196°C and -150°C respectively, were investigated as potential solutions to extend the cTE construct implantation window and increase their clinical applicability. Material and Methods The cTE model used consisted of induced-pluripotent stem cell-derived cardiomyocytes and human cardiac fibroblasts embedded in a natural-derived hydrogel and supported by a polymeric melt electrowritten hexagonal scaffold. Constructs, composed of cardiomyocytes of different maturity, were preserved for three days, using several commercially available preservation protocols and solutions. Their viability, function (BPM and calcium handling), and metabolic activity were investigated after rewarming. Results Our observations suggest that cardiomyocyte maturation did not influence post-rewarming viability, however, aging positively influenced construct function pre- and post-storage. Hypothermic preservation in Hypothermosol ensured retained construct viability and function. Furthermore, fast-freezing outperformed slow-freezing, but both viability and function were severely reduced after rewarming. Conclusion In conclusion, whereas long-term preservation remains a challenge, hypothermic preservation in Hypothermosol represents a promising solution for cTE construct short-term preservation and potential transportation, aiding in off-the-shelf availability, ultimately increasing their clinical applicability.Graphical abstract

A fast point cloud registration method based on spatial relations and features

Abstract Point cloud registration plays a crucial role in mobile robot localization, map building and 3D model reconstruction. However, it remains challenged by issues such as compromised accuracy and sluggish efficiency, posing significant obstacles in achieving precise and timely alignments. Therefore, we propose a lightweight and fast point cloud registration method. Firstly, we mesh the 3D point cloud, compared with the traditional gridded point cloud method, it achieves initial point cloud registration by preserving the curvature characteristics of the internal point cloud, and utilizing the spatial relationship between grid cells and the quantitative relationship between the internal point cloud. Moreover, we adopt an iterative nearest point (ICP) based on KD-Tree to realize the fine registration. So, our method does not necessitate intricate feature analysis and data training, and is resilient to similar transformations, non-uniform densities and noise. Finally, we conduct point cloud registration experiments using multiple publicly available point cloud datasets and compare them with several point cloud registration methods. The results demonstrate it is able to accomplish the point cloud registration quickly and exhibit high accuracy. More importantly, it maintains its efficacy and robustness even in the presence of noisy and defective point clouds.

A Hybrid Finite Element Method – Kirchhoff Approximation Method for Modeling Acoustic Scattering from an Underwater Vehicle Model with Alberich Coatings with Periodic Internal Cavities

Anechoic tiles can significantly reduce the echo intensity of underwater vehicles, thereby increasing the difficulty of detecting such vehicles. However, the computational efficiency of conventional methods such as the finite element method (FEM) and the boundary element method (BEM) has its limitations. A fast hybrid method for modeling acoustic scattering from underwater vehicles with anechoic tiles with periodic internal cavities, is developed by combining the Kirchhoff approximation (KA) and FEM. The accuracy and rapidity of the KA method were validated by FEM. According to the actual situation, the reflection coefficients of rubber materials with two different structures under rigid backing are simulated by FEM. Using the KA method, the acoustic scattering characteristics of the underwater vehicle with anechoic tiles are obtained by inputting the reflection coefficients and the target’s geometric grid. Experiments on the monostatic target strength (TS) in the frequency range of 1 to 20 kHz and time domain echo characteristics of acoustic scattering on a benchmark scale model with anechoic tiles are conducted. The research results indicate that the TS values and echo characteristic curves of the KA solutions closely approximate the experimental results, which verifies the accuracy of the KA method in calculating the TS and echo characteristics of underwater vehicles with anechoic tiles.

Cotton seed cultivar identification based on the fusion of spectral and textural features.

The mixing of cotton seeds of different cultivars and qualities can lead to differences in growth conditions and make field management difficult. In particular, except for yield loss, it can also lead to inconsistent cotton quality and poor textile product quality, causing huge economic losses to farmers and the cotton processing industry. However, traditional cultivar identification methods for cotton seeds are time-consuming, labor-intensive, and cumbersome, which cannot meet the needs of modern agriculture and modern cotton processing industry. Therefore, there is an urgent need for a fast, accurate, and non-destructive method for identifying cotton seed cultivars. In this study, hyperspectral images (397.32 nm-1003.58 nm) of five cotton cultivars, namely Jinke 20, Jinke 21, Xinluzao 64, Xinluzao 74, and Zhongmiansuo 5, were captured using a Specim IQ camera, and then the average spectral information of seeds of each cultivar was used for spectral analysis, aiming to estab-lish a cotton seed cultivar identification model. Due to the presence of many obvious noises in the < 400 nm and > 1000 nm regions of the collected spectral data, spectra from 400 nm to 1000 nm were selected as the representative spectra of the seed samples. Then, various denoising techniques, including Savitzky-Golay (SG), Standard Normal Variate (SNV), and First Derivative (FD), were applied individually and in combination to improve the quality of the spectra. Additionally, a successive projections algorithm (SPA) was employed for spectral feature selection. Based on the full-band spectra, a Partial Least Squares-Discriminant Analysis (PLS-DA) model was established. Furthermore, spectral features and textural features were fused to create Random Forest (RF), Convolutional Neural Network (CNN), and Extreme Learning Machine (ELM) identification models. The results showed that: (1) The SNV-FD preprocessing method showed the optimal denoising performance. (2) SPA highlighted the near-infrared region (800-1000 nm), red region (620-700 nm), and blue-green region (420-570 nm) for identifying cotton cultivar. (3) The fusion of spectral features and textural features did not consistently improve the accuracy of all modeling strategies, suggesting the need for further research on appropriate modeling strategies. (4) The ELM model had the highest cotton cultivar identification accuracy, with an accuracy of 100% for the training set and 98.89% for the test set. In conclusion, this study successfully developed a highly accurate cotton seed cultivar identification model (ELM model). This study provides a new method for the rapid and non-destructive identification of cotton seed cultivars, which will help ensure the cultivar consistency of seeds used in cotton planting, and improve the overall quality and yield of cotton.

Fast image-free autofocus method for passive FSPI microscopy

Autofocus is crucial for capturing sharp images with imaging devices for information acquisition. Traditional autofocus strategies based on post-processing become less efficient for passive FSPI microscopy of yet low temporal resolution. In this Letter, a fast and image-free autofocus system is proposed for passive FSPI microscopy. Based on the complementary design of an optical path, the system can measure the focus degree at 5000 fps while maintaining a high light efficiency for imaging. The proposed system can be easily combined with existing trinocular microscopes, which provides a welcomed boost to the practicability of passive FSPI microscopy.

An adversarial example attack method based on predicted bounding box adaptive deformation in optical remote sensing images

Existing global adversarial attacks are not applicable to real-time optical remote sensing object detectors based on the YOLO series of deep neural networks, which makes it difficult to improve the adversarial robustness of single-stage detectors. The existing methods do not work well enough in optical remote sensing images, which may be due to the mechanism of adversarial perturbations is not suitable. Therefore, an adaptive deformation method (ADM) was proposed to fool the detector into generating wrong predicted bounding boxes. Building upon this, we introduce the Adaptive Deformation Method Iterative Fast Gradient Sign Method (ADM-I-FGSM) and Adaptive Deformation Mechanism Projected Gradient Descent (ADM-PGD) against YOLOv4 and YOLOv5. ADM method can obtain the deformation trend values based on the length-to-width ratio of the prediction box, and the adversarial perturbation trend generated based on these trend values has better adversarial effect. Through experiments, we validate that our approach exhibits a higher adversarial success rate compared to the state-of-the-art methods. We anticipate that our unveiled attack scheme will aid in the evaluation of adversarial resilience of these models.

Fast and accurate prediction of interference spectra of non-adiabatic tapered microfiber Mach-Zehnder interferometer in liquid

Microfiber Mach-Zehnder interferometer (MMZI) is a widely used optical device. To solve the problems of large difference between the theoretical and experimental spectrum, low calculation efficiency, poor universality in spectrum calculation of MMZI, a fast and accurate calculation method for predicting the interference spectrum of MMZI used in liquid is proposed. In calculations, phase accumulated in transition region of the taper is considered to reach a good agreement between theoretical and experimental spectrum. To further improve the computational efficiency, dependence of the phase accumulation on wavelength is developed by linear fitting, and a non-linear fitting of difference of effective refractive index (∆neff) on fiber diameter, wavelength, temperature and salinity of the surrounding is obtained by the data from commercial software. In addition, a visual interface for displaying the predicted spectrum is established, by which one accurate spectral calculation can be realized within only two or three seconds. Finally, effects of LP03 mode and shape of transition region on transmission spectrum are discussed and the accuracy of this method is also verified by sensitivity. The calculation method demonstrated here provides an accurate and fast spectral prediction method for MMZI, and will afford important reference for sensor design and optimization.

Impact of different numerical approaches on the magnetocaloric effect modeling

As an ecological alternative to the conventional refrigeration technology, magnetocaloric refrigeration is still facing scientific and technological challenges hindering their application. Magnetocaloric devices rely on the magnetocaloric effect, where temperature variations result from magnetic field changes. The correct implementation of the magnetocaloric effect in numerical models is crucial before prototyping the related solutions. Here, we present a comparison between the three most used numerical methods to simulate the magnetocaloric effect: continuous temperature change, discrete temperature change step and heat source obtained from adiabatic temperature. By varying the time and space steps, it was observed that the continuous temperature change method is the most appropriate for small time steps, but has the largest computational cost. The discrete method can only be applied to small time steps, but is the fastest method. Finally, the adiabatic temperature change power source method can be applied in the entire range and is the one that presents the best results for larger time steps.

New methodological approach for deep penetrating geochemistry and environmental studies, Part 1: on-site soil extraction of trace and rare earth elements

The use of on-site soil extractions for direct quantification provides a fast and efficient method for environmental monitoring and mineral prospecting. In this study, an on-site extraction protocol was developed and tested on northern boreal soils using partial extractants: 0.01 M calcium chloride (CaCl 2 ) and 0.43 M nitric acid (HNO 3 ). CaCl 2 is commonly used as an extractant for mobile and directly available elements, while 0.43 M HNO 3 is used to extract also the reactive pool with the weakly bound elements from soil particle surfaces. These two extractants were chosen because (i) they have no specific constraints for electrochemical or spectrometric analysis for element quantification and (ii) they are more environmentally friendly than the ones often used for mineral exploration, e.g. the aqua regia (AR) or mobile metal ions such as Ionic Leach™ (IL, ALS). Extractions with HNO 3 offered the same patterns as those obtained with AR but with better contrast for anomalies, while the CaCl 2 results were very similar to those obtained with IL. Nevertheless, neither HNO 3 nor CaCl 2 was effective in mobilizing Au, W or Sn due to their low concentrations. Our study demonstrated that on-site soil extractions with HNO 3 and CaCl 2 were potentially good candidates for the detection of REEs, such as Ce and La, and some trace elements, especially Cd, for both extractions, Co, Pb and U with HNO 3 , and Mn and Ni with CaCl 2 . This work highlights the potential of on-site extraction using partial extractants. This is a key step prior to the quantification of elements by on-site voltametric techniques.

Sp2-rich dendrite-like carbon nanowalls as effective electrode for environmental monitoring of explosive nitroaromatic

Nitroaromatic compounds are commonly used explosive materials that pose a risk to human health and ecosystems due to their acute toxicity and carcinogenicity. Nitroaromatics have numerous pathways into the environment via discarded munitions (e.g. into the Baltic Sea after World War II), after use in mining operations, and in industrial run-off from factories producing these compounds (which are produced across the world to date). The current detection method relies on chromatography and mass spectrometry methods, which are time-consuming, expensive, and require specialist equipment and training. Carbon-based electrochemical sensors offer a low-cost, fast, and easy on-site method for the detection of a variety of compounds. This study demonstrates an efficient approach for rapid electrochemical sensing of Tetryl (N-methyl-N-2,4,6-tetranitroaniline) through the use of boron-doped sp2-rich carbon structures. These structures, known as dendrite-like carbon nanowalls (D:CNW), were fabricated in one-step deposition and extensively characterized to understand the structure and surface chemistry. Electrodes were used to detect a range of nitroaromatic compounds, most notably tetryl in both laboratory and real environmental samples, with an excellent sensitivity of 153.0 µA cm−2 ppm−1 and a detection limit of 17 ppb. The analytical and electrochemical capabilities of D:CNW electrodes indicate their suitability for extensive environmental monitoring.

CLUSTERING ANALYSIS FOR GROUPING SUB-DISTRICTS IN BOJONEGORO DISTRICT WITH THE K-MEANS METHOD WITH A VARIETY OF APPROACHES

Population data is an important piece of information that is useful for regional planning and development. Insight into the state of an area is more straightforward to observe if there are grouped sub-districts. In this case, data mining techniques can identify patterns and relationships in population data. The K-Means algorithm is a clustering technique that divides data into groups or clusters based on similar characteristics. This research aims to apply the K-Means method with various approaches to clustering sub-districts in the Bojonegoro district according to population data. The research method used is a quantitative method with an exploratory study in the application of the K-Means method with a variety of approaches, namely the use of the Kernel K-Means method by utilizing the mapping function to map data to a higher dimension before the clustering process. In addition, the Fast K-Means method is used, which reduces the model training time to improve the cluster-centered recalibration problem as the amount of data increases. The data source used in this research is secondary population data in the form of birth, death, migrant, and moving variables obtained from the Satu Data Bojonegoro website developed by the Bojonegoro Regency Government. It is found that the best K-Means approach is the Kernel K-Means method with a number of clusters of 5. The performance of the cluster method is evaluated by measuring the average distance within the cluster. The data coordinate pattern in the Kernel K-means method clustering shows a smooth initial trend when the value of the number of clusters is 5 so that the clusters formed are obtained clearly. The conclusion from this study's results is that the K-Means method's best approach in grouping sub-districts in Bojonegoro district is the Kernel K-Means approach.

Simultaneous quantification of terpenes and cannabinoids by reversed-phase LC-APCI-MS/MS in Cannabis sativa L. samples combined with a subsequent chemometric analysis.

Cannabis sativa L. has been the most discussed medicinal plant in recent years. In particular, the dynamic shift from a formerly illicit and tightly controlled substance to a plant recognized for both medicinal and recreational purposes has brought C. sativa into the global spotlight. Due to the ongoing international legalization processes, fast and convenient analytical methods for the quality control of C. sativa flowers for medicinal and recreational purposes are of tremendous interest. In this study, we report the development and validation of a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based method applying atmospheric pressure chemical ionization (APCI) to fully quantify 16 terpenes and 7 cannabinoids including their acidic forms by a single chromatographic method. The method presented here is unique and simple, as it eliminates the need for derivatization reactions and includes the unconventional analysis of volatile compounds by liquid chromatography. Samples were prepared by a simple and fast ethanolic extraction. Separation was accomplished within 25min on a reversed-phase C18 column. Method validation was conducted according to international guidelines regarding selectivity, accuracy, precision, robustness, and linearity. Detection was done in multiple reaction monitoring, which allowed the simultaneous quantification of co-eluting analytes applying two selective mass transitions. In addition, due to reproducible in-source decarboxylation, the acidic forms of cannabinoids were reliably quantified using mass transitions of the neutral forms. The accuracy given as the bias was below 15% for all analytes. Matrix effects for cannabinoids were studied by spiking Humulus lupulus extracts with the analytes at varying concentrations. APCI did not show susceptibility toward ion suppression or enhancement. In addition, the recovery effect after spiking was between 80 and 120% for terpenes. Further, 55 authentic C. sativa extracts were fully quantified, and the obtained results for the terpene profiles were compared to state-of-the-art gas chromatography coupled to flame ionization detection. Comparable results were achieved, emphasizing the method's applicability for cannabinoids and terpenes. Further, acquired metabolite patterns for C. sativa samples were studied, identifying a relationship between cannabinoid and terpene patterns, as well as the abundance of myrcene in CBD-dominant C. sativa strains.

A fast calculation method for internal blast shock wave in confined structures

Internal explosions are more complicated and destructive than external explosions. It is hard to give accurate predictions of the internal blast load by existing simplified models. In the present work, a fast calculation method for the shock wave of internal blast within a confined space was developed. Firstly, the theoretical bases of this method, the reflection addition rules and the image burst theory, were introduced and validated. Then, the concept of the influence region of image burst for internal blast calculation was proposed, and the detailed calculation method for internal blast load was presented. In addition, the internal blast loads inside a typical cubic structure and a tunnel model were calculated using this developed method, respectively. Moreover, comparison studies between the calculated results and experimental data as well as numerical simulation results were conducted. It was found that the results of the fast calculation model are in good agreement with those of the blast experiment and fine numerical simulation, but the fast calculation takes only less than 2 min. Finally, the advantages and defects of the present method were discussed and further study advices were suggested to improve the accuracy.

Development and Validation of a Sonication-Assisted Dispersive Liquid-Liquid Microextraction Procedure and an HPLC-PDA Method for Quantitative Determination of Zolpidem in Human Plasma and Its Application to Forensic Samples.

The use of z-drugs has increased worldwide since its introduction. Although the prescribing patterns of hypnotics differ among countries, zolpidem is the most widely used z-drug in the world. Zolpidem may be involved in poisoning and deaths. A simple and fast HPLC-PDA method was developed and validated. Zolpidem and the internal standard chloramphenicol were extracted from plasma using a sonication-assisted dispersive liquid-liquid microextraction procedure. The method was validated including selectivity, linearity, precision, accuracy, and recovery. The calibration range (0.15-0.6 µg/mL) covers therapeutic and toxic levels of zolpidem in plasma. The limit of quantification was set at 0.15 µg/mL. Intra- and interday accuracy and precision values were lower than 15% at the concentration levels studied. Excellent recovery results were obtained for all concentrations. The proposed method was successfully applied to ten real postmortem plasma samples. In our series, multiple substances (alcohol and/or other drugs) were detected in most cases of death involving zolpidem. Our analytical method is suitable for routine toxicological analysis.

3D Refraction Travel Time Accuracy Study in High Contrasted Media

Among all the existing methods to solve the eikonal equation, three methods are chosen to verify accuracy, symmetry, reciprocity and error propagation along large offsets of refracted waves in seismic near surface exploration context. Performance is extremely highlighted nowadays and accuracy is being neglected, then an eikonal solver poorly explored in geoscience is used. A classical solver, the Fast Iterative and the modified Fast Sweeping Method are applied in three modeling schemes: a simple two layers model, a large four layers and a complex benchmark model. The three methods compute the first arrival of refracted waves in high contrast media and the results are compared to the analytical solution. A circular geometry is considered in all experiments to explore the method applicability using full azimuth angles. On the first scheme, the errors in travel time are computed among the three methods using different model sample spacing and we discuss accuracy, symmetry and reciprocity of first arrivals. On the second scheme, three circular receivers are placed in different offsets to check errors along refracted wave propagation. Finally, the third scheme, four shots are strategically positioned over the SEG/EAGE Overthrust model in order to compare the full acoustic wavefield with the eikonal solvers and then check the similarities. Although the focus is on methods accuracy, the algorithm run time is also considered and the comparison shows that the modified Fast Sweeping Method is the most accurate. The most computational efficient eikonal solver is the Fast Iterative Method, but its geoscience applicability needs to be cautious, because of its inaccurate results.

Expected performance of the Pyramid wavefront sensor with a laser guide star for 40 m class telescopes

Context. The use of artificial laser guide stars (LGS) is planned for the new generation of giant segmented mirror telescopes in order to extend the sky coverage of their adaptive optics systems. The LGS, being a 3D object at a finite distance, will have a large elongation that will affect its use with the Shack–Hartmann (SH) wavefront sensor. Aims. In this paper, we compute the expected performance for a Pyramid WaveFront Sensor (PWFS) using an LGS for a 40 m telescope affected by photon noise, and also extend the analysis to a flat 2D object as reference. Methods. We developed a new way to discretize the LGS, and a new, faster method of propagating the light for any Fourier filtering wavefront sensors (FFWFS) when using extended objects. We present the use of a sensitivity model to predict the performance of a closed-loop adaptive optic system. We optimized a point-source-calibrated interaction matrix to accommodate the signal of an extended object by computing optical gains using a convolutional model. Results. We find that the sensitivity drop, given the size of the extended laser source, is large enough to make the system operate in a low-performance regime given the expected return flux of the LGS. The width of the laser beam is identified as the limiting factor, rather than the thickness of the sodium layer. Even an ideal, flat LGS will have a drop in performance due to the flux of the LGS, and small variations in the return flux will result in large variations in performance. Conclusions. We conclude that knife-edge-like wavefront sensors, such as the PWFS, are not recommended for use with LGS for a 40 m telescope, as they will operate in a low-performance regime, given the size of the extended object.

Comparative Analysis of Transpedal and Transfemoral Access During Genicular Artery Embolization for Knee Osteoarthritis.

This retrospective study aimed to compare the efficacy and safety of transpedal access (TPA) with transfemoral access (TFA) in Genicular Artery Embolization (GAE). 60 patients who underwent GAE between January and June 2023, were recruited and outcomes were compared between the TFA (n = 37) and TPA (n = 23) groups. Technical and clinical success rates, complications, and patient-reported outcomes were assessed. All patients attained a 100% technical success rate, which was defined as the successful selective catheterization and embolization of at least one feeding artery to the knee joint, without encountering any major complications. Minor complications, observed in 12/60 patients (20%), were predominantly manifested as a transient skin discoloration. The TPA group had a comparatively higher (p = 0.008) rate of minor complication than the TFA group. Notably, TPA was associated with a longer duration of the procedure (p = 0.013), duration of fluoroscopy (p = 0.004), increased total air kerma (p = 0.037), dose-area product values (p = 0.021), and a greater incidence of vasospasm (p = 0.018) than TFA. However, TPA patients reported shorter recovery times and less post-procedural discomfort, especially reduced back pain due to postinterventional bedrest (p < 0.001). At the 3-month follow-up, the clinical success rate was similar between the two groups (p = 0.905). TFA is the safer and faster method for GAE, offering fewer complications and reduced radiation exposure. For patients with challenging groin anatomies, however, TPA may provide a valuable alternative.

The Novel Impact of Augmented Reality and 3D Printing in the Diagnosis of Complex Acetabular Fractures: A Comparative Randomized Study in Orthopedic Residents.

Augmented reality (AR) and 3D printing (3DP) are novel technologies in the orthopedic field. Over the past decade, enthusiasm for these new digital applications has driven new perspectives in improving diagnostic accuracy and sensitivity in the field of traumatology. Currently, however, it is still difficult to quantify their value and impact in the medical-scientific field, especially in the improvement of diagnostics in complex fractures. Acetabular fractures have always been a challenge in orthopedics, due to their volumetric complexity and low diagnostic reliability. Background/Objectives: The goal of this study was to determine whether these methods could improve the learning aspect and diagnostic accuracy of complex acetabular fractures compared to gold-standard CT (computed tomography). Methods: Orthopedic residents of our department were selected and divided into Junior (JUN) and Senior (SEN) groups. Associated fractures of acetabulum were included in the study, and details of these were provided as CT scans, 3DP models, and AR models displayed on a tablet screen. In a double-blind questionnaire, each resident classified every fracture. Diagnostic accuracy (DA), response time (RT), agreement (R), and confidence (C) were measured. Results: Twenty residents (JUN = 10, SEN = 10) classified five fractures. Overall DA was 26% (CT), 18% (3DP), and 29% (AR). AR-DA was superior to 3DP-DA (p = 0.048). DA means (JUN vs. SEN, respectively): CT-DA was 20% vs. 32% (p < 0.05), 3DP-DA was 12% vs. 24% (p = 0.08), and AR-DA was 28% vs. 30% (p = 0.80). Overall RT was 61.2 s (±24.6) for CT, 35.8 s (±20.1) for 3DP, and 46.7 s (±20.8) for AR. R was fairly poor between methods and groups. Overall, 3DPs had superior C (65%). Conclusions: AR had the same overall DA as CT, independent of experience, 3DP had minor differences in DA and R, but it was the fastest method and the one in which there was the most confidence. Intra- and inter-observer R between methods remained very poor in residents.