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Mireia Sole; Joan Blanco; Debora Gil; Gothami Fonseka; Richard Frodsham; Oliver Valero; Francesca Vidal; Zaida Sarrate |
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Análisis 3d de la territorialidad cromosómica en células espermatogénicas: explorando la infertilidad desde un nuevo prisma |
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2017 |
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Revista Asociación para el Estudio de la Biología de la Reproducción |
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ASEBIR |
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22 |
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2 |
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105 |
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IAM; 600.096; 600.145 |
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Admin @ si @ SBG2017d |
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3042 |
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Debora Gil; Rosa Maria Ortiz; Carles Sanchez; Antoni Rosell |
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Title |
Objective endoscopic measurements of central airway stenosis. A pilot study |
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2018 |
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RES |
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95 |
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63–69 |
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Bronchoscopy; Tracheal stenosis; Airway stenosis; Computer-assisted analysis |
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Endoscopic estimation of the degree of stenosis in central airway obstruction is subjective and highly variable. Objective: To determine the benefits of using SENSA (System for Endoscopic Stenosis Assessment), an image-based computational software, for obtaining objective stenosis index (SI) measurements among a group of expert bronchoscopists and general pulmonologists. Methods: A total of 7 expert bronchoscopists and 7 general pulmonologists were enrolled to validate SENSA usage. The SI obtained by the physicians and by SENSA were compared with a reference SI to set their precision in SI computation. We used SENSA to efficiently obtain this reference SI in 11 selected cases of benign stenosis. A Web platform with three user-friendly microtasks was designed to gather the data. The users had to visually estimate the SI from videos with and without contours of the normal and the obstructed area provided by SENSA. The users were able to modify the SENSA contours to define the reference SI using morphometric bronchoscopy. Results: Visual SI estimation accuracy was associated with neither bronchoscopic experience (p = 0.71) nor the contours of the normal and the obstructed area provided by the system (p = 0.13). The precision of the SI by SENSA was 97.7% (95% CI: 92.4-103.7), which is significantly better than the precision of the SI by visual estimation (p < 0.001), with an improvement by at least 15%. Conclusion: SENSA provides objective SI measurements with a precision of up to 99.5%, which can be calculated from any bronchoscope using an affordable scalable interface. Providing normal and obstructed contours on bronchoscopic videos does not improve physicians' visual estimation of the SI. |
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IAM; 600.075; 600.096; 600.145 |
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Admin @ si @ GOS2018 |
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3043 |
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Rosa Maria Ortiz; Debora Gil; Elisa Minchole; Marta Diez-Ferrer; Noelia Cubero de Frutos |
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Classification of Confolcal Endomicroscopy Patterns for Diagnosis of Lung Cancer |
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2017 |
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18th World Conference on Lung Cancer |
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Confocal Laser Endomicroscopy (CLE) is an emerging imaging technique that allows the in-vivo acquisition of cell patterns of potentially malignant lesions. Such patterns could discriminate between inflammatory and neoplastic lesions and, thus, serve as a first in-vivo biopsy to discard cases that do not actually require a cell biopsy.
The goal of this work is to explore whether CLE images obtained during videobronchoscopy contain enough visual information to discriminate between benign and malign peripheral lesions for lung cancer diagnosis. To do so, we have performed a pilot comparative study with 12 patients (6 adenocarcinoma and 6 benign-inflammatory) using 2 different methods for CLE pattern analysis: visual analysis by 3 experts and a novel methodology that uses graph methods to find patterns in pre-trained feature spaces. Our preliminary results indicate that although visual analysis can only achieve a 60.2% of accuracy, the accuracy of the proposed unsupervised image pattern classification raises to 84.6%.
We conclude that CLE images visual information allow in-vivo detection of neoplastic lesions and graph structural analysis applied to deep-learning feature spaces can achieve competitive results. |
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Yokohama; Japan; October 2017 |
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IASLC WCLC |
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IAM; 600.096; 600.075; 600.145 |
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Admin @ si @ OGM2017 |
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3044 |
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Debora Gil; Aura Hernandez-Sabate; David Castells; Jordi Carrabina |
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CYBERH: Cyber-Physical Systems in Health for Personalized Assistance |
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2017 |
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International Symposium on Symbolic and Numeric Algorithms for Scientific Computing |
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Assistance systems for e-Health applications have some specific requirements that demand of new methods for data gathering, analysis and modeling able to deal with SmallData:
1) systems should dynamically collect data from, both, the environment and the user to issue personalized recommendations; 2) data analysis should be able to tackle a limited number of samples prone to include non-informative data and possibly evolving in time due to changes in patient condition; 3) algorithms should run in real time with possibly limited computational resources and fluctuant internet access.
Electronic medical devices (and CyberPhysical devices in general) can enhance the process of data gathering and analysis in several ways: (i) acquiring simultaneously multiple sensors data instead of single magnitudes (ii) filtering data; (iii) providing real-time implementations condition by isolating tasks in individual processors of multiprocessors Systems-on-chip (MPSoC) platforms and (iv) combining information through sensor fusion
techniques.
Our approach focus on both aspects of the complementary role of CyberPhysical devices and analysis of SmallData in the process of personalized models building for e-Health applications. In particular, we will address the design of Cyber-Physical Systems in Health for Personalized Assistance (CyberHealth) in two specific application cases: 1) A Smart Assisted Driving System (SADs) for dynamical assessment of the driving capabilities of Mild Cognitive Impaired (MCI) people; 2) An Intelligent Operating Room (iOR) for improving the yield of bronchoscopic interventions for in-vivo lung cancer diagnosis. |
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Timisoara; Rumania; September 2017 |
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SYNASC |
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IAM; 600.085; 600.096; 600.075; 600.145 |
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Admin @ si @ GHC2017 |
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3045 |
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Marta Diez-Ferrer; Debora Gil; Elena Carreño; Susana Padrones; Samantha Aso; Vanesa Vicens; Cubero Noelia; Rosa Lopez Lisbona; Carles Sanchez; Agnes Borras; Antoni Rosell |
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Positive Airway Pressure-Enhanced CT to Improve Virtual Bronchoscopic Navigation |
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2016 |
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Chest Journal |
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CHEST |
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150 |
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4 |
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1003A |
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IAM; 600.096; 600.075 |
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Admin @ si @ DGC2016 |
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3099 |
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Esmitt Ramirez; Carles Sanchez; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil |
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BronchoX: bronchoscopy exploration software for biopsy intervention planning |
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2018 |
Publication |
Healthcare Technology Letters |
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HTL |
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5 |
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5 |
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177–182 |
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Virtual bronchoscopy (VB) is a non-invasive exploration tool for intervention planning and navigation of possible pulmonary lesions (PLs). A VB software involves the location of a PL and the calculation of a route, starting from the trachea, to reach it. The selection of a VB software might be a complex process, and there is no consensus in the community of medical software developers in which is the best-suited system to use or framework to choose. The authors present Bronchoscopy Exploration (BronchoX), a VB software to plan biopsy interventions that generate physician-readable instructions to reach the PLs. The authors’ solution is open source, multiplatform, and extensible for future functionalities, designed by their multidisciplinary research and development group. BronchoX is a compound of different algorithms for segmentation, visualisation, and navigation of the respiratory tract. Performed results are a focus on the test the effectiveness of their proposal as an exploration software, also to measure its accuracy as a guiding system to reach PLs. Then, 40 different virtual planning paths were created to guide physicians until distal bronchioles. These results provide a functional software for BronchoX and demonstrate how following simple instructions is possible to reach distal lesions from the trachea. |
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IAM; 600.096; 600.075; 601.323; 601.337; 600.145 |
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Admin @ si @ RSB2018a |
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3132 |
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Debora Gil; Ruth Aris; Agnes Borras; Esmitt Ramirez; Rafael Sebastian; Mariano Vazquez |
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Title |
Influence of fiber connectivity in simulations of cardiac biomechanics |
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2019 |
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International Journal of Computer Assisted Radiology and Surgery |
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IJCAR |
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14 |
Issue |
1 |
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63–72 |
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Cardiac electromechanical simulations; Diffusion tensor imaging; Fiber connectivity |
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PURPOSE:
Personalized computational simulations of the heart could open up new improved approaches to diagnosis and surgery assistance systems. While it is fully recognized that myocardial fiber orientation is central for the construction of realistic computational models of cardiac electromechanics, the role of its overall architecture and connectivity remains unclear. Morphological studies show that the distribution of cardiac muscular fibers at the basal ring connects epicardium and endocardium. However, computational models simplify their distribution and disregard the basal loop. This work explores the influence in computational simulations of fiber distribution at different short-axis cuts.
METHODS:
We have used a highly parallelized computational solver to test different fiber models of ventricular muscular connectivity. We have considered two rule-based mathematical models and an own-designed method preserving basal connectivity as observed in experimental data. Simulated cardiac functional scores (rotation, torsion and longitudinal shortening) were compared to experimental healthy ranges using generalized models (rotation) and Mahalanobis distances (shortening, torsion).
RESULTS:
The probability of rotation was significantly lower for ruled-based models [95% CI (0.13, 0.20)] in comparison with experimental data [95% CI (0.23, 0.31)]. The Mahalanobis distance for experimental data was in the edge of the region enclosing 99% of the healthy population.
CONCLUSIONS:
Cardiac electromechanical simulations of the heart with fibers extracted from experimental data produce functional scores closer to healthy ranges than rule-based models disregarding architecture connectivity. |
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IAM; 600.096; 601.323; |
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Admin @ si @ GAB2019a |
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3133 |
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Marta Diez-Ferrer; Arturo Morales; Rosa Lopez Lisbona; Noelia Cubero; Cristian Tebe; Susana Padrones; Samantha Aso; Jordi Dorca; Debora Gil; Antoni Rosell |
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Ultrathin Bronchoscopy with and without Virtual Bronchoscopic Navigation: Influence of Segmentation on Diagnostic Yield |
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2019 |
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Respiration |
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RES |
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97 |
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3 |
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252-258 |
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Lung cancer; Peripheral lung lesion; Diagnosis; Bronchoscopy; Ultrathin bronchoscopy; Virtual bronchoscopic navigation |
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Background: Bronchoscopy is a safe technique for diagnosing peripheral pulmonary lesions (PPLs), and virtual bronchoscopic navigation (VBN) helps guide the bronchoscope to PPLs. Objectives: We aimed to compare the diagnostic yield of VBN-guided and unguided ultrathin bronchoscopy (UTB) and explore clinical and technical factors associated with better results. We developed a diagnostic algorithm for deciding whether to use VBN to reach PPLs or choose an alternative diagnostic approach. Methods: We compared diagnostic yield between VBN-UTB (prospective cases) and unguided UTB (historical controls) and analyzed the VBN-UTB subgroup to identify clinical and technical variables that could predict the success of VBN-UTB. Results: Fifty-five cases and 110 controls were included. The overall diagnostic yield did not differ between the VBN-guided and unguided arms (47 and 40%, respectively; p = 0.354). Although the yield was slightly higher for PPLs ≤20 mm in the VBN-UTB arm, the difference was not significant (p = 0.069). No other clinical characteristics were associated with a higher yield in a subgroup analysis, but an 85% diagnostic yield was observed when segmentation was optimal and the PPL was endobronchial (vs. 30% when segmentation was suboptimal and 20% when segmentation was optimal but the PPL was extrabronchial). Conclusions: VBN-guided UTB is not superior to unguided UTB. A greater impact of VBN-guided over unguided UTB is highly dependent on both segmentation quality and an endobronchial location of the PPL. Segmentation quality should be considered before starting a procedure, when an alternative technique that may improve yield can be chosen, saving time and resources. |
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IAM; 600.145 |
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Admin @ si @ DML2019 |
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3134 |
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Marta Diez-Ferrer; Debora Gil; Cristian Tebe; Carles Sanchez |
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Positive Airway Pressure to Enhance Computed Tomography Imaging for Airway Segmentation for Virtual Bronchoscopic Navigation |
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Journal Article |
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2018 |
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RES |
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96 |
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6 |
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525-534 |
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Multidetector computed tomography; Bronchoscopy; Continuous positive airway pressure; Image enhancement; Virtual bronchoscopic navigation |
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Abstract
RATIONALE:
Virtual bronchoscopic navigation (VBN) guidance to peripheral pulmonary lesions is often limited by insufficient segmentation of the peripheral airways.
OBJECTIVES:
To test the effect of applying positive airway pressure (PAP) during CT acquisition to improve segmentation, particularly at end-expiration.
METHODS:
CT acquisitions in inspiration and expiration with 4 PAP protocols were recorded prospectively and compared to baseline inspiratory acquisitions in 20 patients. The 4 protocols explored differences between devices (flow vs. turbine), exposures (within seconds vs. 15-min) and pressure levels (10 vs. 14 cmH2O). Segmentation quality was evaluated with the number of airways and number of endpoints reached. A generalized mixed-effects model explored the estimated effect of each protocol.
MEASUREMENTS AND MAIN RESULTS:
Patient characteristics and lung function did not significantly differ between protocols. Compared to baseline inspiratory acquisitions, expiratory acquisitions after 15 min of 14 cmH2O PAP segmented 1.63-fold more airways (95% CI 1.07-2.48; p = 0.018) and reached 1.34-fold more endpoints (95% CI 1.08-1.66; p = 0.004). Inspiratory acquisitions performed immediately under 10 cmH2O PAP reached 1.20-fold (95% CI 1.09-1.33; p < 0.001) more endpoints; after 15 min the increase was 1.14-fold (95% CI 1.05-1.24; p < 0.001).
CONCLUSIONS:
CT acquisitions with PAP segment more airways and reach more endpoints than baseline inspiratory acquisitions. The improvement is particularly evident at end-expiration after 15 min of 14 cmH2O PAP. Further studies must confirm that the improvement increases diagnostic yield when using VBN to evaluate peripheral pulmonary lesions. |
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IAM; 600.145 |
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Admin @ si @ DGT2018 |
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3135 |
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Esmitt Ramirez; Carles Sanchez; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil |
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Title |
Image-Based Bronchial Anatomy Codification for Biopsy Guiding in Video Bronchoscopy |
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2018 |
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OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis |
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11041 |
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Biopsy guiding; Bronchoscopy; Lung biopsy; Intervention guiding; Airway codification |
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Bronchoscopy examinations allow biopsy of pulmonary nodules with minimum risk for the patient. Even for experienced bronchoscopists, it is difficult to guide the bronchoscope to most distal lesions and obtain an accurate diagnosis. This paper presents an image-based codification of the bronchial anatomy for bronchoscopy biopsy guiding. The 3D anatomy of each patient is codified as a binary tree with nodes representing bronchial levels and edges labeled using their position on images projecting the 3D anatomy from a set of branching points. The paths from the root to leaves provide a codification of navigation routes with spatially consistent labels according to the anatomy observes in video bronchoscopy explorations. We evaluate our labeling approach as a guiding system in terms of the number of bronchial levels correctly codified, also in the number of labels-based instructions correctly supplied, using generalized mixed models and computer-generated data. Results obtained for three independent observers prove the consistency and reproducibility of our guiding system. We trust that our codification based on viewer’s projection might be used as a foundation for the navigation process in Virtual Bronchoscopy systems. |
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Granada; September 2018 |
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MICCAIW |
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IAM; 600.096; 600.075; 601.323; 600.145 |
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Admin @ si @ RSB2018b |
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3137 |
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