Pulmonary embolism (PE) remains a leading cause of cardiovascular mortality and a major diagnostic challenge in emergency settings worldwide. Although computed tomography pulmonary angiography (CTPA) is the reference standard, its interpretation is time-consuming, subject to inter-observer variability, and dependent on subspecialist expertise, potentially delaying life-saving treatment. We developed and validated HUCSR-Net, a fully automated 3D convolutional neural network for PE detection using 128,484 imaging studies from 86 patients at Hospital Universitario Clínica San Rafael (Bogotá, Colombia). A modern R(2 + 1)D-18 architecture, pre-trained on Kinetics-400, was adapted to single-channel input by averaging the RGB weights of the first convolutional layer. The classification head was replaced by a dropout layer (p = 0.6) followed by a single linear unit. The model was trained from scratch with patient-level 5-fold cross-validation, using AdamW optimiser and binary cross-entropy with logits loss. All experiments were conducted on a workstation equipped with an NVIDIA GeForce RTX 5070 Ti GPU (16 GB VRAM) and an AMD Ryzen 9 9950X processor. Performance was evaluated by the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and F1-score. After several experiments, the optimal model was obtained with a validation AUC of 0.7026, sensitivity of 0.8592, specificity of 0.2673, precision of 0.4519, and F1 score of 0.592. The Matthews correlation coefficient was 0.1515, and the area under the precision-recall curve was 0.5907, confirming solid discriminatory performance despite the limited size of the cohort and validation losses of 0.7989, respectively. A deep 3D convolutional network trained from scratch on a modest single-centre cohort can achieve diagnostic performance comparable to published multi-thousand-patient studies relying on large public datasets. These results demonstrate the feasibility of clinically useful automated PE detection in resource-constrained settings and support the integration of such systems as decision-support tools for radiologists.
Real-time 3D reconstruction in minimally invasive surgery improves depth perception and supports intraoperative decision-making and navigation. However, endoscopic imaging presents significant challenges, such as specular reflections, low-texture surfaces, and tissue deformation. We present a novel, deterministic and iterative stereo-matching method based on adaptive support weights that is tailored to these constraints. The algorithm is implemented in CUDA and C++ to enable real-time performance. We evaluated our method on the Stereo Correspondence and Reconstruction of Endoscopic Data (SCARED) dataset and a custom synthetic dataset using the mean absolute error (MAE), root mean square error (RMSE), and frame rate as metrics. On SCARED datasets 8 and 9, our method achieves MAEs of 3.79 mm and 3.61 mm, achieving 24.9 FPS on a system with an AMD Ryzen 9 5950X and NVIDIA RTX 3090. To the best of our knowledge, these results are on par with or surpass existing deterministic stereo-matching approaches. On synthetic data, which eliminates real-world imaging errors, the method achieves an MAE of 140.06 μm and an RMSE of 251.9 μm, highlighting its performance ceiling under noise-free, idealized conditions. Our method focuses on single-shot 3D reconstruction as a basis for stereo frame stitching and full-scene modeling. It provides accurate, deterministic, real-time depth estimation under clinically relevant conditions and has the potential to be integrated into surgical navigation, robotic assistance, and augmented reality workflows.
Biometric authentication has emerged as a convenient method for identity verification, but its widespread adoption raises serious privacy concerns. In this paper, we propose a Torus-based secure Multi-factor biometric Authentication System (ToMAS) that addresses these concerns by securing both the e n r o l l m e n t and a u t h e n t i c a t i o n phases through cryptographic protocols. ToMAS adopts a multi-factor approach using both physiological biometric traits and password-derived secrets, and leverages fully homomorphic encryption (FHE) to perform computations on encrypted data without revealing sensitive information. To reduce overhead and improve efficiency, we introduce a ciphertext packing method and a modified bootstrapping technique for secure Hamming distance evaluation. Our protocol is analyzed against active adversaries. Experiments show that a 9600-bit binary biometric template can be encrypted into an 82KB ciphertext, and the Hamming distance between encrypted templates is computed in under one second on a standard AMD Ryzen Threadripper Pro CPU, with no loss of accuracy. ToMAS offers an efficient and scalable solution suitable for large-scale biometric authentication scenarios.
Objective.Many psychiatric disorders involve excessive avoidant or defensive behavior, such as avoidance in anxiety and trauma disorders or defensive rituals in obsessive-compulsive disorders. Developing algorithms to predict these behaviors from local field potentials (LFPs) could serve as the foundational technology for closed-loop control of such disorders. A significant challenge is identifying the LFP features that encode these defensive behaviors.Approach.We analyzed LFP signals from the infralimbic cortex and basolateral amygdala of rats undergoing tone-shock conditioning and extinction, standard for investigating defensive behaviors. We utilized a comprehensive set of neuro-markers across spectral, temporal, and connectivity domains, employing SHapley Additive exPlanations for feature importance evaluation within Light Gradient-Boosting Machine models. Our goal was to decode three commonly studied avoidance/defensive behaviors: freezing, bar-press suppression, and motion (accelerometry), examining the impact of different features on decoding performance.Main results.Band power and band power ratio between channels emerged as optimal features across sessions. High-gamma (80-150 Hz) power, power ratios, and inter-regional correlations were more informative than other bands that are more classically linked to defensive behaviors. Focusing on highly informative features enhanced performance. Across 4 recording sessions with 16 subjects, we achieved an average coefficient of determination of 0.5357 and 0.3476, and Pearson correlation coefficients of 0.7579 and 0.6092 for accelerometry jerk and bar press rate, respectively. Utilizing only the most informative features revealed differential encoding between accelerometry and bar press rate, with the former primarily through local spectral power and the latter via inter-regional connectivity. Our methodology demonstrated remarkably low training/inference time and memory usage, requiring<310 ms for training,<0.051 ms for inference, and 16.6 kB of memory, using a single core of AMD Ryzen Threadripper PRO 5995WX CPU.Significance.Our results demonstrate the feasibility of accurately decoding defensive behaviors with minimal latency, using LFP features from neural circuits strongly linked to these behaviors. This methodology holds promise for real-time decoding to identify physiological targets in closed-loop psychiatric neuromodulation.
Interest in Intensity Modulated Brachytherapy (IMBT) for High Dose Rate Brachytherapy (HDR) treatments has steadily increased in recent years. However, intensity modulation is not best optimized for currently used HDR sources since they emit high energy photons. To that end, the focus on IMBT has moved to middle energy sources, such as Ytterbium-169; yet even Yb-169 emits some high energy photons at a low yield. We present an alternative isotope, Tungsten-181 (T1/2 = 121 days) that is interesting due to its complete lack of high energy photon emissions. (Eavg = 58.9 keV, Emed = 57.5 keV) making it potentially favorable as high dose rate brachytherapy source from both a medical physics and health physics perspective. The purpose of this study was to determine the feasibility of using W-181 as an HDR brachytherapy source; in this study we focused on W-181's production, dosimetric properties, and intensity modulation capabilities. We determined the isotope production kinetics, its Dose Rate Constant, Radial Dose Function, photon self-absorption, and the shielding intensity modulation capabilities for a W-181 pellet source geometry using the MCNP6.2 Computer Simulations Code. All simulations were performed using a personal computer running an AMD Ryzen 5 3600 6-Core Processor 3.59 GHz. The number of histories run for each study were selected to produce relative simulation convergence errors in the MCNP tally output of less than 2%. Dosimetric calculations were made using the MCNP6.2 computer simulations code and activation analyses were determined mathematically using a Catenary kinetics analysis (also known as a Bateman Analysis) of W-181 and Tantlum-182 production from the neutron activation of a pure Tungsten-180 stable target. Since W-181 emits middle energy photons and has a high density, we also assessed the effects of photon self-absorption within a tungsten pellet. From our analysis, we determined that a 3.5 mm long and 0.6 mm in diameter is feasible for clinical applications. Our activation analyses found that these pellets can achieve W-181 activities up to 7.9Ci and 13Ci using neutron fluence rates of 4E14 cm-2 s-1 and 1E15 cm-2 s-1 respectively, which then would provide a dose rate of 1.84 ± 0.01 cG y/Ci/min at a depth of 1 cm from the source. Using our resulting Monte Carlo simulated Dose Rate Constant of 1.24 ± 0.02 cGy h-1∙U-1, a W-181 source in this geometry would require a source activity upwards of 10Ci for use in HDR treatments. In the intensity modulation analysis, only 0.1 mm of gold shielding was found to reduce a pellet's absorbed dose by over 50% while 0.3 mm of gold shielding, which is thin enough to theoretically fit between an HDR pellet and the inner catheter wall, was found to reduce the pellet's absorbed dose by over 85%. While W-181 has a lower specific activity than Ir-192 and Yb-169, it shows great promise as an isotope for use in Intensity Modulated Brachytherapy due to its easily shielded photons. We therefore expect that W-181 may lend itself best for use as a multi-pellet configuration in IMBT.
Speech is a complex mechanism allowing us to communicate our needs, desires and thoughts. In some cases of neural dysfunctions, this ability is highly affected, which makes everyday life activities that require communication a challenge. This paper studies different parameters of an intelligent imaginary speech recognition system to obtain the best performance according to the developed method that can be applied to a low-cost system with limited resources. In developing the system, we used signals from the Kara One database containing recordings acquired for seven phonemes and four words. We used in the feature extraction stage a method based on covariance in the frequency domain that performed better compared to the other time-domain methods. Further, we observed the system performance when using different window lengths for the input signal (0.25 s, 0.5 s and 1 s) to highlight the importance of the short-term analysis of the signals for imaginary speech. The final goal being the development of a low-cost system, we studied several architectures of convolutional neural networks (CNN) and showed that a more complex architecture does not necessarily lead to better results. Our study was conducted on eight different subjects, and it is meant to be a subject's shared system. The best performance reported in this paper is up to 37% accuracy for all 11 different phonemes and words when using cross-covariance computed over the signal spectrum of a 0.25 s window and a CNN containing two convolutional layers with 64 and 128 filters connected to a dense layer with 64 neurons. The final system qualifies as a low-cost system using limited resources for decision-making and having a running time of 1.8 ms tested on an AMD Ryzen 7 4800HS CPU.
Osteoarthritis of the knee is increasingly prevalent as our population ages, representing an increasing financial burden, and severely impacting quality of life. The invasiveness of in vivo procedures and the high cost of cadaveric studies has left computational tools uniquely suited to study knee biomechanics. Developments in deep learning have great potential for efficiently generating large-scale datasets to enable researchers to perform population-sized investigations, but the time and effort associated with producing robust hexahedral meshes has been a limiting factor in expanding finite element studies to encompass a population. Here we developed a fully automated pipeline capable of taking magnetic resonance knee images and producing a working finite element simulation. We trained an encoder-decoder convolutional neural network to perform semantic image segmentation on the Imorphics dataset provided through the Osteoarthritis Initiative. The Imorphics dataset contained 176 image sequences with varying levels of cartilage degradation. Starting from an open-source swept-extrusion meshing algorithm, we further developed this algorithm until it could produce high quality meshes for every sequence and we applied a template-mapping procedure to automatically place soft-tissue attachment points. The meshing algorithm produced simulation-ready meshes for all 176 sequences, regardless of the use of provided (manually reconstructed) or predicted (automatically generated) segmentation labels. The average time to mesh all bones and cartilage tissues was less than 2 min per knee on an AMD Ryzen 5600X processor, using a parallel pool of three workers for bone meshing, followed by a pool of four workers meshing the four cartilage tissues. Of the 176 sequences with provided segmentation labels, 86% of the resulting meshes completed a simulated flexion-extension activity. We used a reserved testing dataset of 28 sequences unseen during network training to produce simulations derived from predicted labels. We compared tibiofemoral contact mechanics between manual and automated reconstructions for the 24 pairs of successful finite element simulations from this set, resulting in mean root-mean-squared differences under 20% of their respective min-max norms. In combination with further advancements in deep learning, this framework represents a feasible pipeline to produce population sized finite element studies of the natural knee from subject-specific models.
Magnesium deficiency was investigated in critically ill patients, comparing measurements of plasma concentrations with the results obtained by the magnesium tolerance test. 20 critically ill patients (5 females, 15 males) between the ages of 27 and 86 were investigated. Magnesium plasma concentrations were determined before the magnesium tolerance test according to Ryzen was performed. For this purpose, magnesium sulfate (0.1 mmol/kg) was infused intravenously over four hours. Renal magnesium excretion was measured in the 24 h urine beginning at the start of the infusion. Magnesium concentrations in plasma and urine were determined using atomic absorption spectrophotometry. In 12 patients magnesium plasma concentrations were decreased to 0.58-0.79 mmol/l. 6 patients showed values within the normal range of 0.80 to 1.0 mmol/l. In 2 patients the plasma concentration was increased to 1.07 and 1.27 mmol/l. Parenteral magnesium tolerance testing revealed a considerable magnesium deficiency by retention of 65-100% of the loading dose in 14 of the 20 patients. The remaining 6 patients retained 23-48% of the loading dose, thus demonstrating a moderate magnesium deficiency. Determination of magnesium plasma concentration appears suitable as an informative preliminary survey, since low values are reliable indicating a magnesium deficiency. However, this study confirms that normal magnesium plasma concentrations do not exclude a considerable magnesium deficiency, which is more sensitively determined by the magnesium tolerance test.
This paper presents a simple, yet effective demosaicking technique using polarization channel difference prior for polarization images captured by division of focal plane imaging sensors. The polarization channel difference prior embodies that high frequency energy of difference between orthogonal channels tends to be larger than that between non-orthogonal channels. This paper theoretically proves that this prior is physical valid. For each missing polarization channel at a pixel position, three initial predictions are recovered using different channel differences. The missing polarization channel is estimated by the weighted fusion of the three initial predictions, where the weights are determined by the proposed polarization channel difference prior. The prior helps recover polarization information of the edges, fast and effectively. Experiment results on the polarization dataset demonstrate the effectiveness of the polarization channel difference prior for polarization image demosaicking. The proposed polarization demosaicking method consists of only 16 convolution operations, which makes it fast and parallelizable for GPU acceleration. An image of size 1024×1024 can be processed in 0.33 sec on Ryzen 7 3700X CPU and approximately 60 times faster with RTX 2700 SUPER GPU.
97 patients (25 per cent males, ages ranging from 14 to 73 years, median 38 years) with complaints of chronic fatigue (chronic fatigue syndrome, fibromyalgia or/and spasmophilia) have been enrolled in a prospective study to evaluate the Mg status and the dietary intake of Mg. An IV loading test (performed following the Ryzen protocol) showed a Mg deficit in 44 patients. After Mg supplementation in 24 patients, the loading test showed a significant decrease (p = 0.0018) in Mg retention. Mean values of serum Mg, red blood cell Mg and magnesuria showed no significant difference between patients with or without Mg deficiency. No association was found between Mg deficiency, CFS or FM. However serum Mg level was significantly lower in the patients with spasmophilia than in the other patients.
Late-night salivary cortisol (LNSC) is reportedly highly accurate for the diagnosis of Cushing's syndrome (CS). However, diagnostic thresholds for abnormal results are based on healthy, young populations and limited data are available on its use in elderly populations with chronic medical conditions. The purpose of this study was to evaluate LNSC levels in elderly male veterans with and without diabetes. Prospective evaluation of LNSC levels in male veterans. One hundred and fifty-four participants with type 2 diabetes and 52 participants without diabetes. Participants underwent outpatient LNSC (2300 h) testing. Participants with elevated LNSC (> or = 4.3 nmol/l) underwent secondary testing, including 24-h urine free cortisol (24UFC, > 60 microg/day) and dexamethasone suppression testing (DST, serum cortisol > 50 nmol/l). Participants with positive secondary testing had a morning ACTH level analysed and either pituitary or adrenal imaging performed. One hundred and forty-one diabetics and 46 controls (mean age 61 years) returned samples (91% overall). Average LNSC levels (nmol/l) in diabetics were significantly higher than in nondiabetics [median (interquartile range): 2.6 (1.8-4.1) vs. 1.6 (1.0-2.0)] and in those aged > or = 60 compared to < 60 [2.7 (2.0-4.3) vs. 1.9 (1.4-2.9)] (P < 0.001 for both). Thirty-one participants required secondary testing. Seventy-nine per cent of participants who underwent secondary testing had normal 24UFC and DST. No cases of CS have been diagnosed to date. Increasing age [odds ratio (OR) 2.0 per decade], current diabetes mellitus (OR 4.4), and elevated blood pressure (OR 1.3 per 10 mmHg increase in systolic blood pressure) were associated with abnormal LNSC results (P < 0.05 for each). LNSC has been shown to be sensitive and specific in diagnosing CS in certain high-risk populations, primarily the young and middle-aged. The development of age- and comorbidity-adjusted thresholds may be warranted for LNSC testing in elderly subjects and in those with significant comorbidity.
The effect of magnesium deficiency on vitamin D metabolism was assessed in 23 hypocalcemic magnesium-deficient patients by measuring the serum concentrations of 25-hydroxyvitamin D (25OHD) and 1,25-dihydroxyvitamin D [1,25-(OH)2D] before, during, and after 5-13 days of parenteral magnesium therapy. Magnesium therapy raised mean basal serum magnesium [1.0 +/- 0.1 (mean +/- SEM) mg/dl] and calcium levels (7.2 +/- 0.2 mg/dl) into the normal range (2.2 +/- 0.1 and 9.3 +/- 0.1 mg/dl, respectively; P less than 0.001). The mean serum 25OHD concentration was in the low normal range (13.2 +/- 1.5 ng/ml) before magnesium administration and did not significantly change after this therapy (14.8 +/- 1.5 ng/ml). Sixteen of the 23 patients had low serum 1,25-(OH)2D levels (less than 30 pg/ml). After magnesium therapy, only 5 of the patients had a rise in the serum 1,25-(OH)2D concentration into or above the normal range despite elevated levels of serum immunoreactive PTH. An additional normocalcemic hypomagnesemic patient had low 1,25-(OH)2D levels which did not rise after 5 days of magnesium therapy. The serum vitamin D-binding protein concentration, assessed in 11 patients, was low (273 +/- 86 micrograms/ml) before magnesium therapy, but normalized (346 +/- 86 micrograms/ml) after magnesium repletion. No correlation with serum 1,25-(OH)2D levels was found. The functional capacity of vitamin D-binding protein to bind hormone, assessed by the internalization of [3H]1,25-(OH)2D3 by intestinal epithelial cells in the presence of serum was not significantly different from normal (11.42 +/- 1.45 vs. 10.27 +/- 1.27 fmol/2 X 10(6) cells, respectively). These data show that serum 1,25-(OH)2D concentrations are frequently low in patients with magnesium deficiency and may remain low even after 5-13 days of parenteral magnesium administration. The data also suggest that a normal 1,25-(OH)2D level is not required for the PTH-mediated calcemic response to magnesium administration. We conclude that magnesium depletion may impair vitamin D metabolism.
We determined the free fraction of 25-dihydroxyvitamin D (25OHD) in the serum of subjects with clinical evidence of liver disease and correlated these measurements to the levels of vitamin D binding protein and albumin. These subjects when compared to normal individuals had lower total 25OHD levels, higher percent free 25OHD levels, but equivalent free 25OHD levels. These subjects also had reduced vitamin D binding protein and albumin concentrations. The total concentration of 25OHD correlated positively with both vitamin D binding protein and albumin, whereas the percent free 25OHD correlated negatively with vitamin D binding protein and albumin. The free 25OHD levels did not correlate with either vitamin D binding protein or albumin. We conclude that total vitamin D metabolite measurements may be misleading in the evaluation of the vitamin D status of patients with liver disease, and recommend that free 25OHD levels also be determined before making a diagnosis of vitamin D deficiency.
Magnesium (Mg) deficiency is a common finding in critically ill patients. Mg deficiency results primarily from gastrointestinal or urinary Mg losses, but malnutrition and decreased dietary Mg intake may hasten the development of Mg depletion. In our medical intensive-care unit, we have found hypomagnesemia in 65% of patients with normal serum creatinine concentrations. The prevalence of normomagnesemic Mg deficiency in critically ill patients may be even higher and may contribute to the pathogenesis of hypocalcemia, cardiac arrhythmias and other symptoms of Mg deficiency.
In order to determine the effect and mechanism of Mg on vascular tone, a 3-hour infusion of Mg (200 mg/h) was administered to normal subjects. The Mg infusion resulted in a drop in blood pressure (BP), a rise in renal blood flow, and an increase in urinary 6-keto-PGF1 alpha excretion. Cyclooxygenase inhibition with indomethacin and the calcium channel blocker, nifedipine, prevented these vascular effects of Mg. These data suggest that prostacyclin release via changes in Ca2+ flux may be the mechanism of Mg vasodilatory action. Since angiotensin II (AII) acts via the Ca2+ messenger system, we also studied the effects of Mg loading and dietary Mg depletion on AII responses. Mg loading blunted the rise in BP and the aldosterone-stimulating effect of AII, whereas Mg depletion significantly enhanced these AII effects. These results support the hypothesis that Mg may be an antagonist of the pressor and steroidogenic effects of AII.
Hypomagnesemia can cause hypocalcemia. Because less than 1% of the total body magnesium (Mg) is in extracellular fluids, however, patients may be Mg-deficient despite normal serum Mg concentrations. To determine if hypocalcemia can be seen in patients who have normal serum Mg concentrations but low intracellular Mg, we studied the serum and mononuclear cell Mg contents in 82 alcoholic subjects, 30 of whom had hypocalcemia that could not be explained by other known causes of hypocalcemia. The mononuclear cell Mg content in both hypomagnesemic and normomagnesemic patients with and without hypocalcemia was significantly lower than in normal controls. The serum Mg level did not correlate with the mononuclear cell Mg or serum calcium level, but hypocalcemic patients had a significantly lower mononuclear cell content than normocalcemic patients. Six patients underwent parenteral Mg tolerance testing as an additional measure of Mg deficiency and had increased Mg retention. The serum calcium concentration returned to normal in hypocalcemic patients who were given magnesium intravenously.
Hypomagnesemia is a common clinical finding in hospitalized patients and can cause hypocalcemia, cardiac arrhythmias, muscular weakness, and hypokalemia. Hypomagnesemia usually implies cellular magnesium (Mg) depletion, but stress and some clinical conditions which raise serum catecholamine concentrations may lower serum Mg (sMg) concentrations. To help investigate the mechanism and degree of the effect of catecholamines on sMg concentration, we gave intravenous epinephrine (0.1 microgram/kg/min) to 12 normal volunteers for 2 hours. The sMg concentration fell from 1.86 +/- 0.04 mg/dl to 1.63 +/- 0.05 mg/dl (mean +/- SEM, p less than 0.01). Pre-infusion intracellular free Mg (Mg++) in red blood cells (RBC) as measured by nuclear magnetic resonance spectrophotometry (NMR) was 171 +/- 7.6 microM and did not differ significantly from post-infusion RBC Mg++, 186 +/- 12.6 microM. Total blood mononuclear cell Mg content and urine Mg excretion also did not change. These data suggest that epinephrine has a small but significant effect on the lowering of sMg concentrations. Endogenous catecholamine release during stress or acute illness may therefore contribute to the hypomagnesemia seen in acutely ill patients. Our data also suggest that hypomagnesemia seen under conditions of acute stress may not always imply depleted tissue Mg stores. As no absolute change in cellular Mg or in urinary Mg excretion was demonstrated, acute intracellular shifts of Mg into blood cells and/or urinary Mg losses may not account for the hypomagnesemia. The prevalence and clinical consequences of stress hypomagnesemia require further investigation.
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In a prospective, randomized, double-blind, multicenter study, 202 patients with cancer from 19 medical centers were treated for hypercalcemia of malignancy with daily intravenous infusions of etidronate disodium (136 patients) or saline alone (66 patients) for 3 consecutive days. Patients also received up to 3.25 L of saline daily during the treatment period. Of 157 patients for whom data could be evaluated for efficacy, 63% (72/114) of etidronate-treated and 33% (14/43) of saline-treated patients had a normalization of total serum calcium levels. When serum calcium levels were adjusted for albumin (147 assessable patients), 24% of the etidronate- and 7% of the saline-treated patients responded to treatment. No serious side effects or treatment-related deaths occurred. When accompanied by adequate hydration and diuresis, intravenous etidronate was safe and more effective than hydration and diuresis alone in controlling hypercalcemia of malignancy.