Early Postoperative Infections After Closed Reduction and Percutaneous Pinning in Type II and Type III Pediatric Supracondylar Humerus Fractures.

BACKGROUND: Supracondylar humerus fractures (SCHF) are the most common elbow fracture type in children, and one of the most common pediatric fracture types overall. Excellent outcomes are generally reported with closed reduction and pinning (CRPP), but the technique involves leaving the pins outside the skin. External pins can act as a nidus for infection. We characterize the infection complications from SCHF treatment at a single-centre tertiary children's hospital over 10 years. This is the largest series on infectious outcomes after CRPP of SCHF reported to date. METHODS: Pediatric patients undergoing CRPP for a type II or type III SCHF from 2011 to 2021 with postsurgical infections within 90 days were identified. Demographic and clinical data were retrieved from medical records. Descriptive statistics were estimated and reported as means or medians with range values or counts with percentages. RESULTS: A total of 18 patients met inclusion criteria, 10 and 8 with type II and III SCHF, respectively. The average age at diagnosis of fracture was 4.7 (2 to 9) years. The average operating time for the index surgery was 29 minutes (12 to 42). The average number of postoperative days until pin removal was 29.8 (18 to 52), and the average number of postoperative days until readmission or visit with symptoms was 38.9 (18 to 77). There was a documented history of a wet cast in 6 patients (33%). Ten (56%) patients presented with fever, and the most common positive culture was methicillin-sensitive Staphylococcus aureus (9, 50%). Thirteen (72%) patients returned to the operating room for incision and drainage. There were no cases with continued complications after the original infection after a median follow-up of 63 days (8 to 559). Infection after CRPP of SCHF is a rare adverse event. In our series, it was most often associated with common pathogens and wet casts. The necessity of return to the operating room will vary with the presentation, but if efficaciously treated afterwards with oral antibiotics, there is a low chance of recurrence or subsequent complications. Patients should be carefully instructed in cast care and demonstrate understanding of risks and complications, and to contact their orthopaedist if their cast demonstrates lack of integrity. LEVEL OF EVIDENCE: Prognostic level IV.

Gain control network conditions in early sensory coding.

Gain control is essential for the proper function of any sensory system. However, the precise mechanisms for achieving effective gain control in the brain are unknown. Based on our understanding of the existence and strength of connections in the insect olfactory system, we analyze the conditions that lead to controlled gain in a randomly connected network of excitatory and inhibitory neurons. We consider two scenarios for the variation of input into the system. In the first case, the intensity of the sensory input controls the input currents to a fixed proportion of neurons of the excitatory and inhibitory populations. In the second case, increasing intensity of the sensory stimulus will both, recruit an increasing number of neurons that receive input and change the input current that they receive. Using a mean field approximation for the network activity we derive relationships between the parameters of the network that ensure that the overall level of activity of the excitatory population remains unchanged for increasing intensity of the external stimulation. We find that, first, the main parameters that regulate network gain are the probabilities of connections from the inhibitory population to the excitatory population and of the connections within the inhibitory population. Second, we show that strict gain control is not achievable in a random network in the second case, when the input recruits an increasing number of neurons. Finally, we confirm that the gain control conditions derived from the mean field approximation are valid in simulations of firing rate models and Hodgkin-Huxley conductance based models.

T7 phage-assisted evolution of riboswitches using error-prone replication and dual selection.

Leveraging riboswitches, non-coding mRNA fragments pivotal to gene regulation, poses a challenge in effectively selecting and enriching these functional genetic sensors, which can toggle between ON and OFF states in response to their cognate inducers. Here, we show our engineered phage T7, enabling the evolution of a theophylline riboswitch. We have replaced T7's DNA polymerase with a transcription factor controlled by a theophylline riboswitch and have created two types of host environments to propagate the engineered phage. Both types host an error-prone T7 DNA polymerase regulated by a T7 promoter along with another critical gene-either cmk or pifA, depending on the host type. The cmk gene is necessary for T7 replication and is used in the first host type for selection in the riboswitch's ON state. Conversely, the second host type incorporates the pifA gene, leading to abortive T7 infections and used for selection in the riboswitch's OFF state. This dual-selection system, termed T7AE, was then applied to a library of 65,536 engineered T7 phages, each carrying randomized riboswitch variants. Through successive passage in both host types with and without theophylline, we observed an enrichment of phages encoding functional riboswitches that conferred a fitness advantage to the phage in both hosts. The T7AE technique thereby opens new pathways for the evolution and advancement of gene switches, including non-coding RNA-based switches, setting the stage for significant strides in synthetic biology.

Estimating the optimal sampling rate using wavelet transform: an application to optical turbulence.

Sampling rate and frequency content determination for optical quantities related to light propagation through turbulence are paramount experimental topics. Some papers about estimating properties of the optical turbulence seem to use ad hoc assumptions to set the sampling frequency used; this chosen sampling rate is assumed good enough to perform a proper measurement. On the other hand, other authors estimate the optimal sampling rate via fast Fourier transform of data series associated to the experiment. When possible, with the help of analytical models, cut-off frequencies, or frequency content, can be determined; yet, these approaches require prior knowledge of the optical turbulence. The aim of this paper is to propose an alternative, practical, experimental method to estimate a proper sampling rate. By means of the discrete wavelet transform, this approach can prevent any loss of information and, at the same time, avoid oversampling. Moreover, it is independent of the statistical model imposed on the turbulence.

Hemodynamic Changes Before and After Endovascular Treatment of Type B Aortic Dissection by 4D Flow MRI.

Objective: The standard treatment for complicated Stanford type B aortic dissection (TBAD) is thoracic endovascular aortic repair (TEVAR). Functional parameters, specifically blood flow, are not measured in the clinical assessment of TEVAR, yet they are of outmost importance in patient outcome. Consequently, we investigated the impact of TEVAR on the flows in the aorta and its branches in TBAD using 4D Phase-Contrast Magnetic Resonance Imaging (4D Flow MRI). Methods: Seven patients with TBAD scheduled for TEVAR underwent pre and post-operative 4D Flow MRI. An experienced reader assessed the presence of helical flow in the false lumen (FL) using streamlines and measured net flow at specific locations. In addition, forward and reverse flows, stasis, helicity, and absolute helicity were computed automatically along the aorta centerline. Average values were then computed in the segmented vessels. Impact of TEVAR on these parameters was assessed with a Wilcoxon signed rank test. Impact of the metallic stent on the velocity quantification was assessed using intra-class correlation coefficient (ICC) between velocities measured intra-stent and in adjacent stent-free regions. Results: FL helical flow was observed proximally in 6 cases and distally in 2 cases pre-operatively. Helical flow disappeared post-TEVAR proximally, but developed distally for 2 patients. Intra-stent measures were similar to stent-free with a median difference of 0.1 L/min and an ICC equal to 0.967 (p < 0.01). Forward flow increased from 59.9 to 81.6% in the TL and significantly decreased in the FL from 15.9 to 3.3%. Similarly, reverse flow increased in the TL from 4.36 to 10.8% and decreased in the FL from 10.3 to 4.6%. No significant changes were observed in net flow for aortic branches (p > 0.05). A significant increase in FL stasis was observed (p = 0.04). Discussion: TEVAR significantly increased forward flow in the TL and significantly decreased both forward and reverse flows in the FL. Interestingly, reverse flow in the TL increased post-TEVAR, which could be due to increased rigidity of the wall, due to the metallic stent. User independent helicity quantification enabled detection of elevated helicity at the level of secondary entry tears which had been missed by streamline visualization.

Improving motion-mask segmentation in thoracic CT with multiplanar U-nets.

PURPOSE: Motion-mask segmentation from thoracic computed tomography (CT) images is the process of extracting the region that encompasses lungs and viscera, where large displacements occur during breathing. It has been shown to help image registration between different respiratory phases. This registration step is, for example, useful for radiotherapy planning or calculating local lung ventilation. Knowing the location of motion discontinuity, that is, sliding motion near the pleura, allows a better control of the registration preventing unrealistic estimates. Nevertheless, existing methods for motion-mask segmentation are not robust enough to be used in clinical routine. This article shows that it is feasible to overcome this lack of robustness by using a lightweight deep-learning approach usable on a standard computer, and this even without data augmentation or advanced model design. METHODS: A convolutional neural-network architecture with three 2D U-nets for the three main orientations (sagittal, coronal, axial) was proposed. Predictions generated by the three U-nets were combined by majority voting to provide a single 3D segmentation of the motion mask. The networks were trained on a database of nonsmall cell lung cancer 4D CT images of 43 patients. Training and evaluation were done with a K-fold cross-validation strategy. Evaluation was based on a visual grading by two experts according to the appropriateness of the segmented motion mask for the registration task, and on a comparison with motion masks obtained by a baseline method using level sets. A second database (76 CT images of patients with early-stage COVID-19), unseen during training, was used to assess the generalizability of the trained neural network. RESULTS: The proposed approach outperformed the baseline method in terms of quality and robustness: the success rate increased from 53 % to 79 % without producing any failure. It also achieved a speed-up factor of 60 with GPU, or 17 with CPU. The memory footprint was low: less than 5 GB GPU RAM for training and less than 1 GB GPU RAM for inference. When evaluated on a dataset with images differing by several characteristics (CT device, pathology, and field of view), the proposed method improved the success rate from 53 % to 83 % . CONCLUSION: With 5-s processing time on a mid-range GPU and success rates around 80 % , the proposed approach seems fast and robust enough to be routinely used in clinical practice. The success rate can be further improved by incorporating more diversity in training data via data augmentation and additional annotated images from different scanners and diseases. The code and trained model are publicly available.

Psychometric properties of the Young Mania Rating Scale for the identification of mania symptoms in Spanish children and adolescents with attention deficit/hyperactivity disorder.

BACKGROUND: Diagnosing mania in children is difficult, due to the high comorbidity and symptom overlap with attention deficit/hyperactivity disorder (ADHD). The detection of manic symptoms in ADHD has important implications for prognosis and choice of treatment. Our objective was to study the utility of the Young Mania Rating Scale (YMRS) for discriminating mania in Spanish children with ADHD. METHOD: One hundred children and adolescents with ADHD between 8 and 17 years of age were evaluated with a structured diagnostic interview (Diagnostic Interview for Children and Adolescents-IV), the YMRS, the Parent-Young Mania Rating Scale (P-YMRS), the Child Mania Rating Scale-Parent Version (CMRS-P) and the Children's Global Assessment Scale. RESULTS: The YMRS showed a 1-dimensional structure with good internal consistency and test-retest reliability. The YMRS was associated with the P-YMRS and the CMRS-P. The scores obtained with the YMRS differentiated between ADHD with and without mania. The receiver operating characteristic curve analysis showed good diagnostic efficiency in differentiating mania in ADHD (area under the curve of 0.90). CONCLUSIONS: The Spanish version of the YMRS is a valid and reliable instrument for detecting and quantifying the symptoms of mania in children and adolescents with ADHD. The results provide further knowledge about the frequent association between ADHD and manic symptoms in children.

Intrinsic and environmental factors modulating autonomous robotic search under high uncertainty.

Autonomous robotic search problems deal with different levels of uncertainty. When uncertainty is low, deterministic strategies employing available knowledge result in most effective searches. However, there are domains where uncertainty is always high since information about robot location, environment boundaries or precise reference points is unattainable, e.g., in cave, deep ocean, planetary exploration, or upon sensor or communications impairment. Furthermore, latency regarding when search targets move, appear or disappear add to uncertainty sources. Here we study intrinsic and environmental factors that affect low-informed robotic search based on diffusive Brownian, naive ballistic, and superdiffusive strategies (Lévy walks), and in particular, the effectiveness of their random exploration. Representative strategies were evaluated considering both intrinsic (motion drift, energy or memory limitations) and extrinsic factors (obstacles and search boundaries). Our results point towards minimum-knowledge based modulation approaches that can adjust distinct spatial and temporal aspects of random exploration to lead to effective autonomous search under uncertainty.

Validation of a novel system to assess end-expiratory lung volume and alveolar recruitment in an ARDS model.

BACKGROUND: Personalizing mechanical ventilation requires the development of reliable bedside monitoring techniques. The multiple-breaths nitrogen washin-washout (MBNW) technique is currently available to measure end-expiratory lung volume (EELVMBNW), but the precision of the technique may be poor, with percentage errors ranging from 28 to 57%. The primary aim of the study was to evaluate the reliability of a novel MBNW bedside system using fast mainstream sensors to assess EELV in an experimental acute respiratory distress syndrome (ARDS) model, using computed tomography (CT) as the gold standard. The secondary aims of the study were: (1) to evaluate trending ability of the novel system to assess EELV; (2) to evaluate the reliability of estimated alveolar recruitment induced by positive end-expiratory pressure (PEEP) changes computed from EELVMBNW, using CT as the gold standard. RESULTS: Seven pigs were studied in 6 experimental conditions: at baseline, after experimental ARDS and during a decremental PEEP trial at PEEP 16, 12, 6 and 2 cmH2O. EELV was computed at each PEEP step by both the MBNW technique (EELVMBNW) and CT (EELVCT). Repeatability was assessed by performing replicate measurements. Alveolar recruitment between two consecutive PEEP levels after lung injury was measured with CT (VrecCT), and computed from EELV measurements (VrecMBNW) as ΔEELV minus the product of ΔPEEP by static compliance. EELVMBNW and EELVCT were significantly correlated (R2 = 0.97). An acceptable non-constant bias between methods was identified, slightly decreasing toward more negative values as EELV increased. The conversion equation between EELVMBNW and EELVCT was: EELVMBNW = 0.92 × EELVCT + 36. The 95% prediction interval of the bias amounted to ± 86 mL and the percentage error between both methods amounted to 13.7%. The median least significant change between repeated measurements amounted to 8% [CI95%: 4-10%]. EELVMBNW adequately tracked EELVCT changes over time (concordance rate amounting to 100% [CI95%: 87%-100%] and angular bias amounting to - 2° ± 10°). VrecMBNW and VrecCT were significantly correlated (R2 = 0.92). A non-constant bias between methods was identified, slightly increasing toward more positive values as Vrec increased. CONCLUSIONS: We report a new bedside MBNW technique that reliably assesses EELV in an experimental ARDS model with high precision and excellent trending ability.

Quantitative-analysis of computed tomography in COVID-19 and non COVID-19 ARDS patients: A case-control study.

PURPOSE: The aim of this study was to assess whether the computed tomography (CT) features of COVID-19 (COVID+) ARDS differ from those of non-COVID-19 (COVID-) ARDS patients. MATERIALS AND METHODS: The study is a single-center prospective observational study performed on adults with ARDS onset ≤72 h and a PaO2/FiO2 ≤ 200 mmHg. CT scans were acquired at PEEP set using a PEEP-FiO2 table with VT adjusted to 6 ml/kg predicted body weight. RESULTS: 22 patients were included, of whom 13 presented with COVID-19 ARDS. Lung weight was significantly higher in COVID- patients, but all COVID+ patients presented supranormal lung weight values. Noninflated lung tissue was significantly higher in COVID- patients (36 ± 14% vs. 26 ± 15% of total lung weight at end-expiration, p < 0.01). Tidal recruitment was significantly higher in COVID- patients (20 ± 12 vs. 9 ± 11% of VT, p < 0.05). Lung density histograms of 5 COVID+ patients with high elastance (type H) were similar to those of COVID- patients, while those of the 8 COVID+ patients with normal elastance (type L) displayed higher aerated lung fraction.

Structured information in small-world neural networks.

The retrieval abilities of spatially uniform attractor networks can be measured by the global overlap between patterns and neural states. However, we found that nonuniform networks, for instance, small-world networks, can retrieve fragments of patterns (blocks) without performing global retrieval. We propose a way to measure the local retrieval using a parameter that is related to the fluctuation of the block overlaps. Simulation of neural dynamics shows a competition between local and global retrieval. The phase diagram shows a transition from local retrieval to global retrieval when the storage ratio increases and the topology becomes more random. A theoretical approach confirms the simulation results and predicts that the stability of blocks can be improved by dilution.

Voxel-wise assessment of lung aeration changes on CT images using image registration: application to acute respiratory distress syndrome (ARDS).

PURPOSE: (1) To improve the accuracy of global and regional alveolar-recruitment quantification in CT scan pairs by accounting for lung-tissue displacements and deformation, (2) To propose a method for local-recruitment calculation. METHODS: Recruitment was calculated by subtracting the quantity of non-aerated lung tissues between expiration and inspiration. To assess global recruitment, lung boundaries were first interactively delineated at inspiration, and then they were warped based on automatic image registration to define the boundaries at expiration. To calculate regional recruitment, the lung mask defined at inspiration was cut into pieces, and these were also warped to encompass the same tissues at expiration. Local-recruitment map was calculated as follows: For each voxel at expiration, the matching location at inspiration was determined by image registration, non-aerated voxels were counted in the neighborhood of the respective locations, and the voxel count difference was normalized by the neighborhood size. The methods were evaluated on 120 image pairs of 12 pigs with experimental acute respiratory distress syndrome. RESULTS: The dispersion of global- and regional-recruitment values decreased when using image registration, compared to the conventional approach neglecting tissue motion. Local-recruitment maps overlaid onto the original images were visually consistent, and the sum of these values over the whole lungs was very close to the global-recruitment estimate, except four outliers. CONCLUSIONS: Image registration can compensate lung-tissue displacements and deformation, thus improving the quantification of alveolar recruitment. Local-recruitment calculation can also benefit from image registration, and its values can be overlaid onto the original image to display a local-recruitment map. They also can be integrated over arbitrarily shaped regions to assess regional or global recruitment.

Development of a Risk Score Based on Aortic Calcification to Predict 1-Year Mortality After Transcatheter Aortic Valve Replacement.

OBJECTIVES: The aim of this study was to develop a new scoring system based on thoracic aortic calcification (TAC) to predict 1-year cardiovascular and all-cause mortality. BACKGROUND: A calcified aorta is often associated with poor prognosis after transcatheter aortic valve replacement (TAVR). A risk score encompassing aortic calcification may be valuable in identifying poor TAVR responders. METHODS: The C4CAPRI (4 Cities for Assessing CAlcification PRognostic Impact) multicenter study included a training cohort (1,425 patients treated using TAVR between 2010 and 2014) and a contemporary test cohort (311 patients treated in 2015). TAC was measured by computed tomography pre-TAVR. CAPRI risk scores were based on the linear predictors of Cox models including TAC in addition to comorbidities and demographic, atherosclerotic disease and cardiac function factors. CAPRI scores were constructed and tested in 2 independent cohorts. RESULTS: Cardiovascular and all-cause mortality at 1 year was 13.0% and 17.9%, respectively, in the training cohort and 8.2% and 11.8% in the test cohort. The inclusion of TAC in the model improved prediction: 1-cm3 increase in TAC was associated with a 6% increase in cardiovascular mortality and a 4% increase in all-cause mortality. The predicted and observed survival probabilities were highly correlated (slopes >0.9 for both cardiovascular and all-cause mortality). The model's predictive power was fair (AUC 68% [95% confidence interval [CI]: 64% to 72%]) for both cardiovascular and all-cause mortality. The model performed similarly in the training and test cohorts. CONCLUSIONS: The CAPRI score, which combines the TAC variable with classical prognostic factors, is predictive of 1-year cardiovascular and all-cause mortality. Its predictive performance was confirmed in an independent contemporary cohort. CAPRI scores are highly relevant to current practice and strengthen the evidence base for decision making in valvular interventions. Its routine use may help prevent futile procedures.

Comorbidity and phenomenology of bipolar disorder in children with ADHD.

OBJECTIVE: To assess the comorbidity of bipolar disorder (BPD) in children with ADHD and to study the psychopathological profile of ADHD children with and without mania. METHOD: A total of 100 children with ADHD were assessed with a semistructured diagnostic interview and questionnaires of mania, ADHD, and general psychopathology. RESULTS: 8% of children met criteria for BPD and 6% for BPD-not specified. ADHD children with bipolar spectrum disorder had greater comorbidity with disruptive behavior disorders and scored higher on the Young Mania Rating Scales and on the Child Behavior Checklist (CBCL) Scales of rule-breaking behavior, externalizing problems, and total problems; however, significance on the CBCL Scales was lost when controlling for disruptive behavior disorders. CONCLUSION: BPD is frequently associated with ADHD; it has important implications for prognosis and choice of treatment. Differences on the CBCL Scales could be explained by the comorbidity with disruptive behavior disorders rather than by a specific manic profile.

Enabling 3D-Liver Perfusion Mapping from MR-DCE Imaging Using Distributed Computing.

An MR acquisition protocol and a processing method using distributed computing on the European Grid Infrastructure (EGI) to allow 3D liver perfusion parametric mapping after Magnetic Resonance Dynamic Contrast Enhanced (MR-DCE) imaging are presented. Seven patients (one healthy control and six with chronic liver diseases) were prospectively enrolled after liver biopsy. MR-dynamic acquisition was continuously performed in free-breathing during two minutes after simultaneous intravascular contrast agent (MS-325 blood pool agent) injection. Hepatic capillary system was modeled by a 3-parameters one-compartment pharmacokinetic model. The processing step was parallelized and executed on the EGI. It was modeled and implemented as a grid workflow using the Gwendia language and the MOTEUR workflow engine. Results showed good reproducibility in repeated processing on the grid. The results obtained from the grid were well correlated with ROI-based reference method ran locally on a personal computer. The speed-up range was 71 to 242 with an average value of 126. In conclusion, distributed computing applied to perfusion mapping brings significant speed-up to quantification step to be used for further clinical studies in a research context. Accuracy would be improved with higher image SNR accessible on the latest 3T MR systems available today.

The use of artificial neural networks in electrostatic force microscopy.

The use of electrostatic force microscopy (EFM) to characterize and manipulate surfaces at the nanoscale usually faces the problem of dealing with systems where several parameters are not known. Artificial neural networks (ANNs) have demonstrated to be a very useful tool to tackle this type of problems. Here, we show that the use of ANNs allows us to quantitatively estimate magnitudes such as the dielectric constant of thin films. To improve thin film dielectric constant estimations in EFM, we first increase the accuracy of numerical simulations by replacing the standard minimization technique by a method based on ANN learning algorithms. Second, we use the improved numerical results to build a complete training set for a new ANN. The results obtained by the ANN suggest that accurate values for the thin film dielectric constant can only be estimated if the thin film thickness and sample dielectric constant are known.PACS: 07.79.Lh; 07.05.Mh; 61.46.Fg.

Characterization of a clinical olfactory test with an artificial nose.

Clinical olfactory tests are used to address hyposmia/anosmia levels in patients with different types of olfactory impairments. Typically, a given test is employed clinically and then replaced by a new one after a certain period of use which can range from days to several months. There is a need to assess control quality of these tests and also for a procedure to quantify their degradation over time. In this paper we propose a protocol to employ low-cost artificial noses for the quantitative characterization of olfactory tests used in clinical studies. In particular, we discuss a preliminary study on the Connecticut Chemosensorial Clinical Research Center Test kit which shows that some odorants, as sensed by an artificial nose, seem to degrade while others are potentiated as the test ages. We also discuss the need to establish a map of correspondence between human and machine olfaction when artificial noses are used to characterize or compare human smell performance in research and clinical studies.

[Rhinocerebral mucormycosis: report on eight cases]. / Mucormicosis rinocerebral: a propósito de ocho casos.

Mucormycosis is a serious condition, usually acute and often fatal, It presents in its most aggressive form in debilitated hosts, usually with diabetic ketoacidosis or immunosuppression. As otolaryngologists, we must diagnose it as early as possible, establish early treatment with amphotericin B and perform a surgical manoeuvre to obtain infection-free margins. It is rare and largely unknown, contributing to delayed diagnosis. It should be borne in mind due to the great increase of population with risk factors. We report eight cases seen in our hospital in recent years (1997-2007). Four were female and four male, aged between 36 and 86 years. The mean age at diagnosis was 57 and all had a predisposing factor. The treatment carried out was that of the underlying disease, systemic antifungal therapy and surgery.

Creatools: una plataforma para el desarrollo de software de procesamiento de imágenes médicas. Aplicación a la segmentación de arterias coronarias y a la detección automática de lesiones en imágenes de angiotac / Creatools: a framework for the development of medical image processing software. Application for the segmentation of coronary arteries and for the automatic detection of lesions in CT images

En este artículo se presenta un software de código abierto, llamado CreaTools, cuyo principal objetivo es el procesar y facilitar la visualización de imágenes médicas. Este software flexible funciona en diferentes sistemas operativos (Linux, Mac OS X, Windows), se desarrolla en el lenguaje de programación C++ para asegurar una fácil integración de módulos C++ y proporciona a los usuarios herramientas computacionales para construir interfaces gráficas de usuario (GUI), incluidos los datos de entrada/salida (manejo de archivos), la visualización, la interacción y el procesamiento de datos. Este artículo muestra también la utilidad de CreaTools mediante un proyecto de investigación que consiste en la detección automática de lesiones arteriales. Los algoritmos desarrollados han sido implementados en una interfaz gráfica amigable con visualización 3D e interacción. Ejemplos de tales algoritmos incluyen la extracción de ejes de arterias y la generación de modelos descriptivos de arterias con lesiones y sin lesiones.

Púrpura fulminans / Purpura fulminans

Se reporta el caso de una mujer de 49 años con lesiones purpúricas diseminadas de aparición súbita y pruebas de coagulación normales. El cuadro se instaló después de intervención quirúrgica porcarcinoma cervico-uterino; hubo resolución con presencia de secuelas