Cristian Tejos

Pontifical Catholic University of Chile, CiudadSantiago, Santiago Metropolitan, Chile

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Publications (62)124.15 Total impact


  • No preview · Article · Feb 2016 · Journal of Magnetic Resonance Imaging
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    ABSTRACT: Wall shear stress (WSS) and oscillatory shear index (OSI) are important parameters for the assessment of the loss of vascular function and the integrity of the vessel tissue. Several methods have been proposed to estimate WSS and OSI from PCMRI, where the in-plane gradients of velocity on 2D planes are approximated through finite differences or differentiation of other interpolation schemes. However, such methods neglect the longitudinal velocity gradients that typically arise in cardiovascular flow, particularly on vessel geometries whose cross section and centerline orientation strongly vary in the axial direction. Thus, the contribution of longitudinal velocity gradients to the estimation of WSS and OSI remains understudied. In this work, we propose a 3D finite-element method for the quantification of WSS and OSI from 3D CINE PC-MRI that accounts for both in-plane and longitudinal velocity gradients. We demonstrate the convergence and robustness of the method on cylindrical geometries using a synthetic phantom based on the Poiseuille flow equation. We also show that, in the presence of noise, the method is both stable and accurate for voxel sizes that are in the range of those found in routine medical imaging procedures. Using computational fluid dynamics simulations on curved geometries with rigid walls as a benchmark, we show that the proposed 3D method results in more accurate WSS estimates than those obtained from a 2D analysis not considering out-of-plane velocity gradients, particularly in regions of moderate to high vessel curvature. Further, we conclude that for irregular geometries the accurate prediction of WSS requires the consideration of longitudinal gradients in the velocity field. To demonstrate the medical applicability of the method, we compute 3D maps of WSS and OSI for 3D CINE PC-MRI data sets from an aortic phantom and sixteen healthy volunteers and two patients. The OSI values show a greater dispersion than WSS, which is strongly dependent on the PC-MRI resolution. We envision that the proposed 3D method will improve the estimation of WSS and OSI from 3D PC-MRI images, allowing for more accurate estimates in vessels with pathologies that induce high longitudinal velocity gradients, such as coarctations and aneurisms.
    No preview · Article · Jan 2016 · IEEE Transactions on Medical Imaging
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    ABSTRACT: Purpose: MRI can produce quantitative liver fat fraction (FF) maps noninvasively, which can help to improve diagnoses of fatty liver diseases. However, most sequences acquire several two-dimensional (2D) slices during one or more breath-holds, which may be difficult for patients with limited breath-holding capacity. A whole-liver 3D FF map could also be obtained in a single acquisition by applying a reliable breathing-motion correction method. Several correction techniques are available for 3D imaging, but they use external devices, interrupt acquisition, or jeopardize the spatial resolution. To overcome these issues, a proof-of-concept study introducing a self-navigated 3D three-point Dixon sequence is presented here. Methods: A respiratory self-gating strategy acquiring a center k-space profile was integrated into a three-point Dixon sequence. We obtained 3D FF maps from a water-fat emulsions phantom and fifteen volunteers. This sequence was compared with multi-2D breath-hold and 3D free-breathing approaches. Results and conclusion: Our 3D three-point Dixon self-navigated sequence could correct for respiratory-motion artifacts and provided more precise FF measurements than breath-hold multi-2D and 3D free-breathing techniques.
    No preview · Article · Nov 2015 · Magnetic Resonance in Medicine
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    ABSTRACT: While earlier Brain-Computer Interface (BCI) studies have mostly focused on modulating specific brain regions or signals, new developments in pattern classification of brain states are enabling real-time decoding and modulation of an entire functional network. The present study proposes a new method for real-time pattern classification and neurofeedback of brain states from electroencephalographic (EEG) signals. It involves the creation of a fused classification model based on the method of Common Spatial Patterns (CSPs) from data of several healthy individuals. The subject-independent model is then used to classify EEG data in real-time and provide feedback to new individuals. In a series of offline experiments involving training and testing of the classifier with individual data from 27 healthy subjects, a mean classification accuracy of 75.30% was achieved, demonstrating that the classification system at hand can reliably decode two types of imagery used in our experiments, i.e., happy emotional imagery and motor imagery. In a subsequent experiment it is shown that the classifier can be used to provide neurofeedback to new subjects, and that these subjects learn to " match " their brain pattern to that of the fused classification model in a few days of neurofeedback training. This finding can have important implications for future studies on neurofeedback and its clinical applications on neuropsychiatric disorders.
    Full-text · Article · Oct 2015 · Frontiers in Behavioral Neuroscience
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    ABSTRACT: Autism spectrum disorder (ASD) is a developmental disability characterized by early-onset difficulties in social communication and restricted repetitive behavior. One the most important impairments in ASD is the abnormal processes of human faces [1]. This deficit could be associated with an abnormal activity of fusiform face area (FFA) [2]. Therefore, the modulation of this area could lead to positive behavioral modifications. Brain-Computer Interfaces (BCI) based on real-time functional Magnetic Resonance Imaging (rtfMRI-BCI) is a novel technique that have allowed healthy individuals and patients to achieve self-regulation of circumscribed brain regions, leading to behavioral changes [3,4]. Despite a growing number of studies using rtfMRI-BCI [5, 6], this methodology has not yet been reported in ASD. The objective of our work is to determine if young patients with ASD can achieve self-regulation of the activity of FFA with rtfMRI-BCI. A healthy subject (male, age = 25) and one ASD patient (male, age = 17) participated in a 4-day experiment; 13 rtfMRI training runs in total (3 up-regulation, 4 baseline blocks/run). During up-regulation runs, subjects received real-time contingent visual feedback of the BOLD signal coming from bilateral FFA. Results indicated that the healthy individual could self- regulate FFA from day 1. The ASD patient was able to self-regulate FFA after 3 days of training. Importantly, the ASD subject showed a positive learning curve through the days of training, for both left and right FFA (R2 left-FFA: .464 (p=0.10); R2 right-FFA: 0.431 (p=0.15)). Albeit preliminary, our results indicate that self-regulation of FFA with rtfMRI-BCI is possible in patients with ASD. This results open important possibilities for the correction of abnormally activated brain areas. New subjects are being currently tested, along with behavioral analyses to explore the effect of FFA self-regulation as a potential tool for symptom alleviation in this severe and chronic brain disorder. References: [1] Dawson et al. Developmental Neuropsychology, 27(3), 2005; [2] Nickl-Jockschat T et al. Brain Struct Funct. 2014 May 29; [3] Sitaram et al. Computational Intelligence and Neuroscience, 2007; [4] Birbaumer et al. Trends in Cognitive Sciences, 17(6), 2013. [5] Sulzer et al. NeuroImage, 76, 2013; [6] Ruiz et al. Biological Psychology, 95, 2014; Acknowledgments: This work was supported by Comisión Nacional de Investigación Científica y Tecnológica de Chile (Conicyt) through Fondo Nacional de Desarrollo Científico y Tecnológico, Fondecyt (project nº 11121153) and through CONICYT-PCHA/Doctorado Nacional/2014-21140705 and Vicerrectoría de Investigación de la Pontificia Universidad Católica de Chile (Proyecto de Investigación Interdisciplina Nº15 /2013).
    No preview · Conference Paper · Sep 2015
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    DESCRIPTION: In recent years, rapid prototyping (RP) models have emerged as a useful tool in implant design and surgery planning for oral and maxillofacial applications. For these applications, the accuracy of the RP model is fundamental. There has been some attempts to quantify the error in the construction of RP models, but these methods are ambiguous and do not provide information about the error distribution throughout the model, nor global metrics to compare different models. In this work, we applied a new methodology to assess the geometric accuracy of RP models of in-vivo human jaws. We built RP models from CT images of 8 patients with different pathologies. Then, we scanned the models to compare them with the images of the patients using our methodology. We computed global and local accuracy measurements and found that the RP models consistently overestimate the size of the jaw. We also found that larger errors tend to be localized at regions with high curvature. The RP models overestimate areas with indentations, such as interdental and interradicular spaces, and underestimate sharp structures, such as the lingula of the mandible. Our findings suggest that surgeons should keep in mind these geometric errors that occur in manufacturing biomodels with RP technologies, especially when faced with surgical planning in tight spaces or when extreme precision is required.
    Full-text · Research · Aug 2015
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    ABSTRACT: Level set-based algorithms have been extensively used for medical image segmentation. Despite their relative success, standard level set segmentations tend to fail when images are severely corrupted or in poorly defined regions. This problem has been tackled incorporating shape prior knowledge, i.e. restricting the evolving curve to a distribution of shapes pre-defined during a training process. Such shape restriction needs to incorporate invariance to translation, rotations and scaling. The common approach for this is to solve a registration problem during the curve evolution, i.e. finding optimal registration parameters. This procedure is slow and produces variable results depending on the order in which the registration parameters were optimized. To overcome this issue Cremers et al. (2006) proposed an intrinsic alignment formulation, which is a normalized coordinate system for each shape, thus avoiding the optimization step to account for the registration. Nevertheless, their proposed solution considered only scaling and translation, but not rotations which are critical for medical imaging applications. We added rotations to this intrinsic alignment, using eigenvalues and eigenvector matrices of the covariance matrix of each shape, and we incorporated them into the evolution equation, allowing us to use shape priors in complex segmentation problems. We tested our algorithm combined with a Chan-Vese functional in synthetic images and in 2D right ventricle MRI.
    No preview · Article · Jul 2015
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    ABSTRACT: To investigate the feasibility of estimating the portal vein blood volume that flows into the intrahepatic volume (IHPVBV) in each cardiac cycle using non-contrast MR venography technique as a surrogate marker of portal hypertension (PH). Ten patients with chronic liver disease and clinical symptoms of PH (40% males, median age:54.0, range:44-73y.o.) and ten healthy volunteers (80% males, median age:54.0, range:44-66y.o.) were included in this study. A non-contrast Triple-Inversion-Recovery Arterial-Spin-Labeling (TIR-ASL) technique was used to quantify the IHPVBV in one and two cardiac cycles. Liver (LV) and spleen volume (SV) were measured by manual segmentation from anatomical MR images as morphological markers of PH. All images were acquired in a 1.5T Philips Achieva MR scanner. PH patients had larger SV (P=0.02) and lower liver-to-spleen ratio (P=0.02) compared with healthy volunteers. The median IHPVBV in healthy volunteers was 13.5cm(3) and 26.5cm(3) for one and two cardiac cycles respectively, whereas in PH patients a median volume of 3.1cm(3) and 9.0cm(3) was observed. When correcting by LV, the IHPVBV was significantly higher in healthy volunteers than PH patients for one and two cardiac cycles. The combination of morphological information (liver-to-spleen ratio) and functional information (IHPVBV/LV) can accurately identify the PH patients with a sensitivity of 90% and specificity of 100%. Results show that the portal vein blood volume that flows into the intrahepatic volume in one and two cardiac cycles is significantly lower in PH patients than in healthy volunteers and can be quantified with non-contrast MRI techniques. Copyright © 2015. Published by Elsevier Inc.
    Full-text · Article · Jun 2015 · Magnetic Resonance Imaging
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    Full-text · Dataset · Jun 2015
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    Full-text · Dataset · Jun 2015
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    Full-text · Conference Paper · Jun 2015
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    Full-text · Conference Paper · Jun 2015
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    ABSTRACT: We present a computational method for calculating the distribution of wall shear stress (WSS) in the aorta based on a velocity field obtained from two-dimensional (2D) phase-contrast magnetic resonance imaging (PC-MRI) data and a finite-element method. The WSS vector was obtained from a global least-squares stress-projection method. The method was benchmarked against the Womersley model, and the robustness was assessed by changing resolution, noise, and positioning of the vessel wall. To showcase the applicability of the method, we report the axial, circumferential and magnitude of the WSS using in-vivo data from five volunteers. Our results showed that WSS values obtained with our method were in good agreement with those obtained from the Womersley model. The results for the WSS contour means showed a systematic but decreasing bias when the pixel size was reduced. The proposed method proved to be robust to changes in noise level, and an incorrect position of the vessel wall showed large errors when the pixel size was decreased. In volunteers, the results obtained were in good agreement with those found in the literature. In summary, we have proposed a novel image-based computational method for the estimation of WSS on vessel sections with arbitrary cross-section geometry that is robust in the presence of noise and boundary misplacements. Copyright © 2015 Elsevier Ltd. All rights reserved.
    No preview · Article · Apr 2015 · Journal of Biomechanics
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    ABSTRACT: Portal hypertension (PH) is a frequent syndrome in patients with chronic liver diseases and it is characterized by an increased liver resistance to blood flow. The increased resistance induces a rise in the portal pressure gradient (PPG), leading to hepatic hemodynamic changes: decreasing the relative contribution of portal vein and increasing the relative contribution of hepatic artery to liver perfusion. The relevance of portal hypertension derives from the frequency and severity of its complications, which represent the first cause of hospital admission, death and liver transplantation in patients with cirrhosis. It has been suggested that the measure of the severity of PH should be evaluated in all patients with chronic liver diseases as a surrogate marker of the liver chronic damage and the response to treatments. The currently favored method for determining portal venous pressure involves catheterization of the hepatic vein and measurement of the hepatic venous pressure gradient (HVPG). However this method is invasive, expensive, and probably not suitable to screen asymptomatic high-risk patients. In this work we propose to indirectly measure the severity of PH by estimating the portal vein blood volume that flows into the intrahepatic circulation (IHPVBV) in a certain number of heart cycles. The rationality of this idea comes from the concept that PPG (like the gradient pressure in any vascular system) is determined by the product of portal vein flow (Q) and the liver vascular resistance (R). Therefore, the measurement of the intrahepatic blood volume that flows in a certain number of heart cycles would be a good estimation of the P/R ratio and indirectly of the severity of PH. In order to quantify the IHPVBV in one and two cardiac cycles we use the technique called TIR-ASL, which is a flow dependent non-contrast technique, that does not require a subtraction step as classic arterial spin labelling (ASL) methods, and could be easily adapted to evaluate the IHPVBV in one or two heart cycles.
    Full-text · Conference Paper · Mar 2015
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    Full-text · Conference Paper · Feb 2015
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    Full-text · Conference Paper · Feb 2015
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    ABSTRACT: Additive manufacturing (AM) models are used in medical applications for surgical planning, prosthesis design and teaching. For these applications, the accuracy of the AM models is essential. Unfortunately, this accuracy is compromised due to errors introduced by each of the building steps: image acquisition, segmentation, triangulation, printing and infiltration. However, the contribution of each step to the final error remains unclear.We performed a sensitivity analysis comparing errors obtained from a reference with those obtained modifying parameters of each building step. Our analysis considered global indexes to evaluate the overall error, and local indexes to show how this error is distributed along the surface of the AM models.Our results show that the standard building process tends to overestimate the AM models, i.e. models are larger than the original structures. They also show that the triangulation resolution and the segmentation threshold are critical factors, and that the errors are concentrated at regions with high curvatures.Errors could be reduced choosing better triangulation and printing resolutions, but there is an important need for modifying some of the standard building processes, particularly the segmentation algorithms.
    Full-text · Article · Jan 2015 · Medical Engineering & Physics

  • No preview · Conference Paper · Nov 2014
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    ABSTRACT: Background: Approximately 5–10% of adults with Congenital Heart Disease (CHD) develop Pulmonary Arterial Hypertension (PAH), mainly due to systemic to pulmonary shunting. Chronically raised pulmonary blood flow causes abnormal endothelial shear stress and a progressive pulmonary vasculopathy (1). Quantification of Wall Shear Stress (WSS) in the pulmonary circulation might be helpful to identify patients with CHD at risk for developing PAH. Using 4D flow MRI, the quantification of WSS has been recently reported in the aorta (2). However, there are few reports that have studied this parameter in the Pulmonary Artery (PA). The objective of this work was to develop a reproducible method to calculate WSS using a Strain Rate Tensor based on cylindrical coordinates obtained from 4D flow data. The method was applied to calculate WSS values in the main, right and left PA (MPA, RPA and LPA) of healthy volunteers and patients with CHD. Method: 4D flow data of the Whole Heart (reconstructed spatial resolution = 2.5 mm 3 , temporal resolution = 38 ms) was acquired on 17 volunteers and 5 patients with Congenital Heart Diseases (CHD) (repaired Transposition of the great arteries, two after one and a half ventricle repair, and two with partial anomalous pulmonary venous return, one of them with Atrial Septal Defect). Using a homemade software, three slices were reformatted perpendicular to the MPA, RPA and LPA. Subsequently, we segmented the blood pool, and calculated Magnitude (WSS-M), Axial (WSS-A), and Circumferential (WSS-C) WSS using a Strain Rate Tensor based on cylindrical coordinates. For each slice, we generated three contiguous slices to include variations of the velocity along the direction of the vessel. Two independent observers processed the data to study the reproducibility of the proposed method with our software.
    Full-text · Conference Paper · May 2014
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    Full-text · Conference Paper · May 2014

Publication Stats

148 Citations
124.15 Total Impact Points

Institutions

  • 2008-2015
    • Pontifical Catholic University of Chile
      • División Medicina
      CiudadSantiago, Santiago Metropolitan, Chile
  • 2014
    • University of Santiago, Chile
      CiudadSantiago, Santiago Metropolitan, Chile
  • 2004
    • University of Cambridge
      • School of Clinical Medicine
      Cambridge, England, United Kingdom