Article de revue avec comité de lecture (8)
GRENIER Philippe, FETITA Catalin, BRILLET Pierre-Yves
Quantitative computed tomography imaging of airway remodeling in severe asthma. Quantitative imaging in medicine and surgery, february 2016, vol. 6, n° 1, pp. 76-83
URL: http://qims.amegroups.com/article/download/9325/9862
abstract
Asthma is a heterogeneous condition and approximately 5-10% of asthmatic subjects have severe disease associated with structure changes of the airways (airway remodeling) that may develop over time or shortly after onset of disease. Quantitative computed tomography (QCT) imaging of the tracheobronchial tree and lung parenchyma has improved during the last 10 years, and has enabled investigators to study the large airway architecture in detail and assess indirectly the small airway structure. In severe asthmatics, morphologic changes in large airways, quantitatively assessed using 2D-3D airway registration and recent algorithms, are characterized by airway wall thickening, luminal narrowing and bronchial stenoses. Extent of expiratory gas trapping, quantitatively assessed using lung densitometry, may be used to assess indirectly small airway remodeling. Investigators have used these quantitative imaging techniques in order to attempt severity grading of asthma, and to identify clusters of asthmatic patients that differ in morphologic and functional characteristics. Although standardization of image analysis procedures needs to be improved, the identification of remodeling pattern in various phenotypes of severe asthma and the ability to relate airway structures to important clinical outcomes should help target treatment more effectively
BORDAS Rafel, LEFEVRE Christophe, VEECKMANS Bart, PITT-FRANCIS J, FETITA Catalin, BRIGHTLING Christopher, KAY David, SIDDIQUI Salman, BURROWES Kelly
Development and analysis of patient-based complete conducting airways models. PLoS One, december 2015, vol. 10, n° 12, pp. 1-19
URL: http://journals.plos.org/plosone/article/asset?id=10.1371%2Fjournal.pone.0144105.PDF
abstract
The analysis of high-resolution computed tomography (CT) images of the lung is dependent on inter-subject differences in airway geometry. The application of computational models in understanding the significance of these differences has previously been shown to be a useful tool in biomedical research. Studies using image-based geometries alone are limited to the analysis of the central airways, down to generation 6-10, as other airways are not visible on high-resolution CT. However, airways distal to this, often termed the small airways, are known to play a crucial role in common airway diseases such as asthma and chronic obstructive pulmonary disease (COPD). Other studies have incorporated an algorithmic approach to extrapolate CT segmented airways in order to obtain a complete conducting airway tree down to the level of the acinus. These models have typically been used for mechanistic studies, but also have the potential to be used in a patient-specific setting. In the current study, an image analysis and modelling pipeline was developed and applied to a number of healthy (n = 11) and asthmatic (n = 24) CT patient scans to produce complete patient-based airway models to the acinar level (mean terminal generation 15.8 ± 0.47). The resulting models are analysed in terms of morphometric properties and seen to be consistent with previous work. A number of global clinical lung function measures are compared to resistance predictions in the models to assess their suitability for use in a patient-specific setting. We show a significant difference (p < 0.01) in airways resistance at all tested flow rates in complete airway trees built using CT data from severe asthmatics (GINA 3-5) versus healthy subjects. Further, model predictions of airways resistance at all flow rates are shown to correlate with patient forced expiratory volume in one second (FEV1) (Spearman ρ = -0.65, p < 0.001) and, at low flow rates (0.00017 L/s), FEV1 over forced vital capacity (FEV1/FVC) (ρ = -0.58, p < 0.001). We conclude that the pipeline and anatomical models can be used directly in mechanistic modelling studies and can form the basis for future patient-based modelling studies
BRILLET Pierre-Yves, DEBRAY Marie-Pierre, GOLMARD Jl, OULD HMEIDI Y, FETITA Catalin, TAILLÉ Camille, AUBIER Michel, GRENIER Philippe
Computed tomography assessment of airways throughout bronchial tree demonstrates airway narrowing in severe asthma. Academic radiology, june 2015, vol. 22, n° 6, pp. 734-742
abstract
RATIONALE AND OBJECTIVES: To analyze airway dimensions throughout the bronchial tree in severe asthmatic patients using multidetector row computed tomography (MDCT) focusing on airway narrowing. MATERIALS AND METHODS: Thirty-two patients with severe asthma underwent automated (BronCare software) analysis of their right lung bronchi, with counts of airways >3 mm long arising from the main bronchi (airway count) and bronchial dimension quantification at segmental and subsegmental levels (lumen area [LA], wall area [WA], and WA%). Focal bronchial stenosis was defined as >50% narrowing of maximal LA on contiguous cross-sectional slices. Severe asthmatics were compared to 13 nonsevere asthmatic patients and nonasthmatic (pooled) subjects (Wilcoxon rank tests, then stepwise logistic regression). Finally, cluster analysis of severe asthmatic patients and stepwise logistic regression identified specific imaging subgroups. RESULTS: The most significant differences between severe asthmatic patients and the pooled subjects were bronchial stenosis (subsegmental and all bronchi: P < .002) and WA% (P < .0003). Stepwise logistic regression retained WA% as the only explanatory covariable (P = .002). Two identified clusters of severe asthmatic patients differed for parameters characterizing airway narrowing (airway count: P = .0002; focal bronchial stenosis: P = .009). Airway count was as discriminant as forced expiratory volume in 1 second/forced vital capacity (P = .01) to identify patients in each cluster, with both variables being correlated (r = 0.59, P = .005). CONCLUSIONS: Severe asthma-associated morphologic changes were characterized by focal bronchial stenoses and diffuse airway narrowing; the latter was associated with airflow obstruction. WA%, dependent on airway caliber, is the best parameter to identify severe asthmatic patients from pooled subjects
BRILLET Pierre Yves, ATTALI Valérie, NACHBAUR Gaëlle, CAPDEROU André, BECQUEMIN Marie-Hélène, BEIGELMAN-AUBRY Catherine, FETITA Catalin, SIMILOWSKI Thomas, ZELTER Marc, GRENIER Philippe
Multidetector row computed tomography to assess changes in airways linked to asthma control. Respiration, may 2011, vol. 81, n° 6, pp. 461-468
abstract
Background: In asthma, multidetector row computed tomography (MDCT) detects abnormalities that are related to disease severity, including increased bronchial wall thickness. However, whether these abnormalities could be related to asthma control has not been investigated yet. Objective: Our goal was to determine which changes in airways could be linked to disease control. Methods: Twelve patients with poor asthma control were included and received a salmeterol/fluticasone propionate combination daily for 12 weeks. Patients underwent clinical, functional, and MDCT examinations before and after the treatment period. MDCT examinations were performed using a low-dose protocol at a controlled lung volume (65% TLC). Bronchial lumen (LA) and wall areas (WA) were evaluated at a segmental and subsegmental level using BronCare software. Lung density was measured at the base of the lung. Baseline and end-of-treatment data were compared using the Wilcoxon signed-rank test. Results: After the 12-week treatment period, asthma control was achieved. Airflow obstruction and air trapping decreased as assessed by the changes in FEV(1) (p < 0.01) and expiratory reserve volume (p < 0.01). Conversely, LA and WA did not vary significantly. However, a median decrease in LA of >10% was observed in half of the patients with a wide intra- and intersubject response heterogeneity. This was concomitant with a decrease in lung density (p < 0.02 in the anteroinferior areas). Conclusions: MDCT is insensitive for demonstrating any decrease in bronchial wall thickness. This is mainly due to changes in bronchial caliber which may be linked to modifications of the elastic properties of the bronchopulmonary system under treatment.
ORTNER Margarete, FETITA Catalin, BRILLET Pierre Yves, PRETEUX Francoise, GRENIER Philippe
3D vector flow guided segmentation of airway wall in MSCT. Lecture notes in computer science, november 2010, vol. 6454/2010, pp. 302-311
abstract
This paper develops a 3D automated approach for airway wall segmentation and quantification in MSCT based on a patient-specific deformable model. The model is explicitly defined as a triangular surface mesh at the level of the airway lumen segmented from the MSCT data. The model evolves according to simplified Lagrangian dynamics, where the deformation force field is defined by a case-specific generalized gradient vector flow. Such force formulation allows locally adaptive time step integration and prevents model self-intersections. The evaluations performed on simulated and clinical MSCT data have shown a good agreement with the radiologist expertise and underlined a higher potential of the proposed 3D approach for the study of airway remodeling versus 2D cross-section techniques.
BRILLET Pierre Yves, FETITA Catalin, CAPDEROU André, MITREA Mihai, DREUIL Serge, SIMON Jean-Marc, PRETEUX Francoise, GRENIER Philippe
Variability of bronchial measurements obtained by sequential CT using two computer-based methods. European radiology, may 2009, vol. 19, n° 5, pp. 1139-1147
abstract
This study aimed to evaluate the variability of lumen (LA) and wall area (WA) measurements obtained on two successive MDCT acquisitions using energy-driven contour estimation (EDCE) and full width at half maximum (FWHM) approaches. Both methods were applied to a database of segmental and subsegmental bronchi with LA > 4 mm2 containing 42 bronchial segments of 10 successive slices that best matched on each acquisition. For both methods, the 95% confidence interval between repeated MDCT was between 1.59 and 1.5 mm2 for LA, and 3.31 and 2.96 mm2 for WA. The values of the coefficient of measurement variation (CV10, i.e., percentage ratio of the standard deviation obtained from the 10 successive slices to their mean value) were strongly correlated between repeated MDCT data acquisitions (r > 0.72; p < 0.0001). Compared with FWHM, LA values obtained using EDCE were higher for LA < 15 mm2, whereas WA values were lower for bronchi with WA < 13 mm2; no systematic EDCE underestimation or overestimation was observed for thicker-walled bronchi. In conclusion, variability between CT examinations and assessment techniques may impair measurements. Therefore, new parameters such as CV10 need to be investigated to study bronchial remodeling. Finally, EDCE and FWHM are not interchangeable in longitudinal studies.
GRENIER Philippe, FETITA Catalin, BEIGELMAN-AUBRY Catherine, BRILLET Pierre Yves
CT imaging of chronic obstructive pulmonary disease : role in phenotyping and interventions. Expert opinion on medical diagnostics, november 2009, vol. 3, n° 6, pp. 689-703
abstract
Using CT to define phenotypic abnormalities in patients diagnosed as having chronic obstructive pulmonary disease (COPD) may serve to optimize treatment, guide the prognosis and assess response to potential therapeutic interventions. Objective/method: Although the different morphologic abnormalities seen on CT scans of COPD patients often overlap, two separate groups of patients can be identified, those with emphysema predominant disease and those with airway predominant disease due to chronic inflammation with resulting in airway remodelling and narrowing. The former category can be subdivided further based on the type of emphysema present and characterized further by anatomic distribution and severity using visual assessment and volumetric quantitative CT techniques. Patients in the airway predominant category can also be characterized by CT as showing bronchial wall thickening, small airway inflammation, mosaic perfusion and air trapping expressing small airway narrowing, and expiratory bronchial collapse due to cartilage deficiency. Recent advances in automated airway segmentation and quantitative analysis have made measurements of airway dimensions feasible. Conclusion: In longitudinal studies, standardization of procedures and quality control are needed, particularly if quantitative CT outcomes are used as end point in clinical trials and ultimately in the clinical management of individual patients.
BRILLET Pierre Yves, FETITA Catalin, SARAGAGLIA Amaury, BRUN Anne Laure, BEIGELMAN-AUBRY Catherine, PRETEUX Francoise, GRENIER Philippe
Investigation of airways using MDCT for visual and quantitative assessment in COPD patients. International journal of chronic obstructive pulmonary disease, january 2008, vol. 3, n° 1, pp. 97-107
URL: http://www.dovepress.com/getfile.php?fileID=2332
abstract
Multidetector computed tomography (MDCT) acquisition during a single breath hold using thin collimation provides high resolution volumetric data set permitting multiplanar and three dimensional reconstruction of the proximal airways. In chronic obstructive pulmonary disease (COPD) patients, this technique provides an accurate assessment of bronchial wall thickening, tracheobronchial deformation, outpouchings reflecting dilatation of the submucous glands, tracheobronchomalacia, and expiratory air trapping. New software developed to segment adequately the lumen and walls of the airways on MDCT scans allows quantitative assessment of the airway dimensions which has shown to be reliable in clinical practice. This technique can become important in longitudinal studies of the pathogenesis of COPD, and in the assessment of therapeutic interventions.
Communication dans une conférence à comité de lecture (19)
TARANDO Sebastian, FETITA Catalin, KIM Young-Wouk, CHO Hyoun, BRILLET Pierre Yves
Deep learning framework for infiltrative lung disease classification . RFIAP 2018: Reconnaissance des Formes, Image, Apprentissage et Perception, 26-28 june 2018, Marne La Vallée, France, 2018, pp. 1-7
URL: https://rfiap2018.ign.fr/sites/default/files/ARTICLES/RFIAP_2018/RFIAP_2018_Tarando_Deep.pdf
abstract
Infiltrative lung diseases enclose a large group of rreversible lung disorders which require regular follow-up with CT imaging. This paper addresses an automated quantitative assessment of different disorders based on lung texture classification. The proposed approach exploits a cascade of convolutional neural networks and a specific preprocessing of input data based on locally connected filtering. The classification targeting the whole lung parenchyma achieves an average of 84% accuracy (75.8% for normal, 90% for emphysema and fibrosis, 81.5% for ground glass)
Les pathologies pulmonaires diffuses représentent un large groupe de désordres irréversibles qui nécessitent un suivi régulier en imagerie TDM. Pour adresser ce besoin, ce papier propose une analyse quantitative de différentes formes pathologiques en s'appuyant sur une analyse de la texture pulmonaire. Cette analyse exploite une cascade de réseaux neuronaux convolutionnels combinée à un prétraitement spécifique des données par filtrage localement connexe. La classification cible la totalité du champ pulmonaire et atteint une précision moyenne de 84% (75.8% pour le tissu normal, 90% pour l'emphysème et fibrose et 81.5% pour le verre dépoli)
TARANDO Sebastian, FETITA Catalin, KIM Young-Wouk, CHO Hyoun, BRILLET Pierre Yves
Boosting CNN performance for lung texture classification using connected filtering. Medical Imaging 2018: Computer-Aided Diagnosis, Bellingham : SPIE, 12-15 february 2018, Houston, United States, 2018, pp. 1057505, ISBN 9781510616394
abstract
Infiltrative lung diseases describe a large group of irreversible lung disorders requiring regular follow-up with CT imaging. Quantifying the evolution of the patient status imposes the development of automated classification tools for lung texture. This paper presents an original image pre-processing framework based on locally connected filtering applied in multiresolution, which helps improving the learning process and boost the performance of CNN for lung texture classification. By removing the dense vascular network from images used by the CNN for lung classification, locally connected filters provide a better discrimination between different lung patterns and help regularizing the classification output. The approach was tested in a preliminary evaluation on a 10 patient database of various lung pathologies, showing an increase of 10% in true positive rate (on average for all the cases) with respect to the state of the art cascade of CNNs for this task
FETITA Catalin, FORTEMPS DE LONEUX Thierry , KOUVAHE Amélé Eyram, EL HAJJAM Mostafa
Automatic detection and quantification of pulmonary arterio-venous malformations in hereditary hemorrhagic telangiectasia. SPIE Medical Imaging 2017: Computer-Aided Diagnosis, Bellingham : SPIE, 11-16 february 2017, Orlando, United States, 2017, pp. 1013419-1-1013419-9, ISBN 978-1-5106-0713-2
abstract
Hereditary hemorrhagic telangiectasia (HHT) is an autosomic dominant disorder, which is characterized by the development of multiple arterio-venous malformations in the skin, mucous membranes, and/or visceral organs. Pulmonary Arterio-Venous Malformation (PAVM) is an abnormal connection where feeding arteries shunt directly into draining veins with no intervening capillary bed. This condition may lead to paradoxical embolism and hemorrhagic complications. PAVMs patients should systematically be screened as the spontaneous complication rate is high, reaching almost 50%. Chest enhanced contrast CT scanner is the reference screening and follow-up examination. When performed by experienced operators as the prime treatment, percutaneous embolization of PAVMs is a safe, efficient and sustained therapy. The accuracy of PAVM detection and quantification of its progression over time is the key of embolotherapy success. In this paper, we propose an automatic method for PAVM detection and quantification relying on a modeling of vessel deformation, i.e. local caliber increase, based on mathematical morphology. The pulmonary field and vessels are first segmented using geodesic operators. The vessel caliber is estimated by means of a granulometric measure and the local caliber increase is detected by using a geodesic operator, the h-maxdomes. The detection sensitivity can be tuned up according to the choice of the h value which models the irregularity of the vessel caliber along its axis and the PAVM selection is performed according to a clinical criterion of >3 mm diameter of the feeding artery of the PAVM. The developed method was tested on a 20 patient dataset. A sensitivity study allowed choosing the irregularity parameter to maximize the true positive ratio reaching 85.4% in average. A specific false positive reduction procedure targeting the vessel trunks of the arterio-venous tree near mediastinum allows a precision increase from 13% to 67% with an average number of 1.15 false positives per scan
TARANDO Sebastian Roberto, FETITA Catalin, BRILLET Pierre Yves
Cascade of convolutional neural networks for lung texture classification: overcoming ontological overlapping. SPIE Medical Imaging 2017: Computer-Aided Diagnosis, Bellingham : SPIE, 11-16 february 2017, Orlando, United States, 2017, vol. 10134, pp. 1013407-1-1013407-9, ISBN 978-1-5106-0713-2
abstract
The infiltrative lung diseases are a class of irreversible, non-neoplastic lung pathologies requiring regular follow-up with CT imaging. Quantifying the evolution of the patient status imposes the development of automated classification tools for lung texture. Traditionally, such classification relies on a two-dimensional analysis of axial CT images. This paper proposes a cascade of the existing CNN based CAD system, specifically tuned-up. The advantage of using a deep learning approach is a better regularization of the classification output. In a preliminary evaluation, the combined approach was tested on a 13 patient database of various lung pathologies, showing an increase of 10% in True Positive Rate (TPR) with respect to the best suited state of the art CNN for this task
CROSNIER Adeline, FETITA Catalin, THABUT Gabriel, BRILLET Pierre-Yves
Intrapulmonary vascular remodeling : MSCT-based evaluation in COPD and alpha-1 antitrypsin deficient subjects . MEDICAL IMAGING 2016 : Computer-Aided Diagnosis, SPIE Press, 27 february - 03 march 2016, San Diego, United States, 2016, vol. 9785-1, pp. 978516-1-11, ISBN 978-1-5106-0020-1
abstract
Whether COPD is generally known as a small airway disease, recent investigations suggest that vascular remodeling could play a key role in disease progression. This paper develops a specific investigation framework in order to evaluate the remodeling of the intrapulmonary vascular network and its correlation with other image or clinical parameters (emphysema score or FEV1) in patients with smoking- or genetic- (alpha-1 antitrypsin deficiency - AATD) related COPD. The developed approach evaluates the vessel caliber distribution per lung or lung region (upper, lower, 10%- and 20%- periphery) in relation with the severity of the disease and computes a remodeling marker given by the area under the caliber distribution curve for radii less than 1.6mm, AUC16. It exploits a medial axis analysis in relation with local caliber information computed in the segmented vascular network, with values normalized with respect to the lung volume (for which a robust segmentation is developed). The first results obtained on a 34-patient database (13 COPD, 13 AATD and 8 controls) showed significant vascular remodeling for COPD and AATD versus controls, with a negative correlation with the emphysema degree for COPD, but not for AATD. Significant vascular remodeling at 20% lung periphery was found both for the severe COPD and AATD patients, but not for the moderate groups. Also the vascular remodeling in AATD did not correlate with the FEV1, nor with DLCO, which might suggest independent mechanisms for bronchial and vascular remodeling in the lung
FETITA Catalin, TARANDO Sebastian Roberto, BRILLET Pierre-Yves, GRENIER Philippe
Robust lung identification in MSCT via controlled flooding and shape constraints: dealing with anatomical and pathological specificity. MEDICAL IMAGING 2016 : Biomedical Applications in Molecular, Structural, and Functional Imaging, SPIE Press, 27 february - 03 march 2016, San Diego, United States, 2016, pp. 97881A-1-10, ISBN 978-1-5106-0023-2
abstract
Correct segmentation and labeling of lungs in thorax MSCT is a requirement in pulmonary/respiratory disease analysis as a basis for further processing or direct quantitative measures: lung texture classification, respiratory functional simulations, intrapulmonary vascular remodeling evaluation, detection of pleural effusion or subpleural opacities, are only few clinical applications related to this requirement. Whereas lung segmentation appears trivial for normal anatomo-pathological conditions, the presence of disease may complicate this task for fully-automated algorithms. The challenges come either from regional changes of lung texture opacity or from complex anatomic configurations (e.g., thin septum between lungs making difficult proper lung separation). They make difficult or even impossible the use of classic algorithms based on adaptive thresholding, 3-D connected component analysis and shape regularization. The objective of this work is to provide a robust segmentation approach of the pulmonary field, with individualized labeling of the lungs, able to overcome the mentioned limitations. The proposed approach relies on 3-D mathematical morphology and exploits the concept of controlled relief flooding (to identify contrasted lung areas) together with patient-specific shape properties for peripheral dense tissue detection. Tested on a database of 40 MSCT of pathological lungs, the proposed approach showed correct identification of lung areas with high sensitivity and specificity in locating peripheral dense opacities
TARANDO Sebastian Roberto, FETITA Catalin, FACCINETTO Alex, BRILLET Pierre-Yves
Increasing CAD system efficacy for lung texture analysis using a convolutional network . MEDICAL IMAGING 2016 : Computer-Aided Diagnosis, SPIE Press, 27 february - 03 march 2016, San Diego, United States, 2016, pp. 97850Q-1-10, ISBN 978-1-5106-0020-1
abstract
The infiltrative lung diseases are a class of irreversible, non-neoplastic lung pathologies requiring regular follow-up with CT imaging. Quantifying the evolution of the patient status imposes the development of automated classification tools for lung texture. For the large majority of CAD systems, such classification relies on a two-dimensional analysis of axial CT images. In a previously developed CAD system, we proposed a fully-3D approach exploiting a multi-scale morphological analysis which showed good performance in detecting diseased areas, but with a major drawback consisting of sometimes overestimating the pathological areas and mixing different type of lung patterns. This paper proposes a combination of the existing CAD system with the classification outcome provided by a convolutional network, specifically tuned-up, in order to increase the specificity of the classification and the confidence to diagnosis. The advantage of using a deep learning approach is a better regularization of the classification output (because of a deeper insight into a given pathological class over a large series of samples) where the previous system is extra-sensitive due to the multi-scale response on patient-specific, localized patterns. In a preliminary evaluation, the combined approach was tested on a 10 patient database of various lung pathologies, showing a sharp increase of true detections
WALTERS Martin, WELLS Andrew K., JONES Ian, HAMILL Ian, VEEKMANS Bart, VOS Wim, LEFEVRE Christophe, FETITA Catalin
Patient-specific simulation of tidal breathing. MEDICAL IMAGING 2016 : Biomedical Applications in Molecular, Structural, and Functional Imaging, SPIE Press, 27 february - 03 march 2016, San Diego, United States, 2016, pp. 978818-1-13, ISBN 978-1-5106-0023-2
abstract
Patient-specific simulation of air flows in lungs is now straightforward using segmented airways trees from CT scans as the basis for Computational Fluid Dynamics (CFD) simulations. These models generally use static geometries, which do not account for the motion of the lungs and its influence on important clinical indicators, such as airway resistance. This paper is concerned with the simulation of tidal breathing, including the dynamic motion of the lungs, and the required analysis workflow. Geometries are based on CT scans obtained at the extremes of the breathing cycle, Total Lung Capacity (TLC) and Functional Residual Capacity (FRC). It describes how topologically consistent geometries are obtained at TLC and FRC, using a ‘skeleton' of the network of airway branches. From this a 3D computational mesh which morphs between TLC and FRC is generated. CFD results for a number of patient-specific cases, healthy and asthmatic, are presented. Finally their potential use in evaluation of the progress of the disease is discussed, focusing on an important clinical indicator, the airway resistance
FETITA Catalin, BRILLET Pierre-Yves, BRIGHTLING Christopher, GRENIER Philippe
Grading remodeling severity in asthma based on airway wall thickening index and bronchoarterial ratio measured with MSCT. Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling, Bellingham : SPIE, 22-24 february 2015, Orlando, United States, 2015, pp. 1-7, ISBN 978-1628-41505-6
abstract
Defining therapeutic protocols in asthma and monitoring patient response require a more in-depth knowledge on the disease severity and treatment outcome based on quantitative indicators. This paper aims at grading severity in asthma based on objective morphological measurements obtained in automated fashion from 3-D multi-slice computed tomography (MSCT) image datasets. These measures attempt to capture and quantify the airway remodeling process involved in asthma, both at the level of the airway wall thickness and airway lumen. Two morphological changes are thus targeted here, (1) the airway wall thickening measured as a global index characterizing the increase of wall thickness above a normal value of wall-to-lumen-radius ratio, and (2) the bronchoarterial ratio index assessed globally from numerous locations in the lungs. The combination of these indices provides a grading of the severity of the remodeling process in asthma which correlates with the known phenotype of the patients investigated. Preliminary application to assess the patient response in thermoplasty trials is also considered from the point of view of the defined indices
TARANDO Sebastian, LUCIDARME Olivier, GRENIER Philippe, FETITA Catalin
On-line scalable image access for medical remote collaborative meetings. Medical Imaging 2015: PACS and Imaging Informatics: Next Generation and Innovations, Bellingham : SPIE, 22-23 february 2015, Orlando, United States, 2015, pp. 1-10, ISBN 978-1-6284-1508-7
abstract
The increasing need of remote medical investigation services in the framework of collaborative multidisciplinary meetings (e.g. cancer follow-up) raises the challenge of on-line remote access of (large amount of) radiologic data in a limited period of time. This paper proposes a scalable compression framework of DICOM images providing low-latency display through low speed networks. The developed approach relies on useless information removal from images (i.e. not related with the patient body) and the exploitation of the JPEG2000 standard to achieve progressive quality encoding and access of the data. This mechanism also allows the efficient exploitation of any idle times (corresponding to on-line visual image analysis) to download the remaining data at lossless quality in a way transparent to the user, thus minimizing the perceived latency. The experiments performed in comparison with exchanging uncompressed or JPEG-lossless compressed DICOM data, showed the benefit of the proposed approach for collaborative on-line remote diagnosis and follow-up services
FETITA Catalin, FRANCOIS Nicolas, PRETEUX Francoise, DELACROIX Hervé
A unified approach for high throughput analysis of real-time biomolecular interactions in surface plasmon resonance and fluorescence imaging. SPIE Medical Imaging 2011 : Biomedical Applications in Molecular, Structural, and Functional Imaging, Bellingham, WA : SPIE, 13-16 february 2011, Lake Buena Vista, United States, 2011, pp. 1-16, ISBN 978-0-8194-8507-6
[PDF]
abstract
The analysis of real-time biomolecular interactions (observation is performed as the biological interaction occurs) provides information on the formation of target/probe complexes, particularly on their dynamic behaviours. Namely, it allows the determination of the affinity constant, a static value that characterizes the interaction properties, using two dynamic values, the association and dissociation constants. Such dynamic behaviour can be assessed either with surface plasmon resonance (SPR) or uorescence-based biosensors. The challenging issue is the automatic extraction and analysis of the interaction signal for each spotted probe on the biosensor in a highthroughput framework (hundreds of probes). This paper addresses such issue and develops a uniffied approach for analyzing the image data provided by the above-mentioned technologies. A mathematical modelling of the image data allowed building-up a virtual biosensor able to simulate biologic experiences related to various possible parameters (level of signal and noise, presence of artefacts, surface functionalization, spotting heterogeneity). Based on such simulation, a generic and automated approach combining 3D mathematical morphology and spatio-temporal classiffication is proposed for detecting the interacting probes, segmenting the regions of effective signal, and characterizing the associated affinity constants. The developed method has been assessed both qualitatively and quantitatively on simulated and experimental datasets and showed accurate results (maximum error of 7% for the most difficult cases in terms of noise and surface functionalization)
FETITA Catalin, ORTNER Margarete, PRETEUX Francoise, BRILLET Pierre Yves, OULD HMEIDI Y.
Airway shape assessment with visual feed-back in asthma and obstructive diseases. Medical Imaging 2010 : Visualization, Image-Guided Procedures, and Modeling, SPIE, 14-16 february 2010, San Diego, United States, 2010, vol. 7625, pp. 76251E, ISBN 978-0-8194-8026-2
abstract
Airway remodeling in asthma patients has been studied in vivo by means of endobronchial biopsies allowing to assess structural and inflammatory changes. However, this technique remains relatively invasive and difficult to use in longitudinal trials. The development of alternative non-invasive tests, namely exploiting high-resolution imaging modalities such as MSCT, is gaining interest in the medical community. This paper develops a fullyautomated airway shape assessment approach based on the 3D segmentation of the airway lumen from MSCT data. The objective is to easily notify the radiologist on bronchus shape variations (stenoses, bronchiectasis) along the airway tree during a simple visual investigation. The visual feed-back is provided by means of a volumerendered color coding of the airway calibers which are robustly defined and computed, based on a specific 3D discrete distance function able to deal with small size structures. The color volume rendering (CVR) information is further on reinforced by the definition and computation of a shape variation index along the airway medial axis enabling to detect specific configurations of stenoses. Such cases often occur near bifurcations (bronchial spurs) and they are either missed in the CVR or difficult to spot due to occlusions by other segments. Consequently, all detected shape variations (stenoses, dilations and thickened spurs) can be additionally displayed on the medial axis and investigated together with the CVR information. The proposed approach was evaluated on a MSCT database including twelve patients with severe or moderate persistent asthma, or severe COPD, by analyzing segmental and subsegmental bronchi of the right lung. The only CVR information provided for a limited number of views allowed to detect 78% of stenoses and bronchial spurs in these patients, whereas the inclusion of the shape variation index enabled to complement the missing information.
ORTNER Margarete, FETITA Catalin, BRILLET Pierre Yves, PRETEUX Francoise, GRENIER Philippe
Ground truth and CT image model simulation for pathophysiological human airway system. Medical Imaging 2010 : Visualization, Image-Guided Procedures, and Modeling, SPIE, 14-16 february 2010, San Diego, United States, 2010, vol. 7625, pp. 76252K, ISBN 978-0-8194-8026-2
abstract
Recurrent problem in medical image segmentation and analysis, establishing a ground truth for assessment purposes is often difficult. Facing this problem, the scientific community orients its efforts towards the development of objective methods for evaluation, namely by building up or simulating the missing ground truth for analysis. This paper focuses on the case of human pulmonary airways and develops a method 1) to simulate the ground truth for different pathophysiological configurations of the bronchial tree as a mesh model, and 2) to generate synthetic 3D CT images of airways associated with the simulated ground truth. The airway model is here built up based on the information provided by a medial axis (describing bronchus shape, subdivision geometry and local radii), which is computed from real CT data to ensure realism and matching with a patient-specific morphology. The model parameters can be further on adjusted to simulate various pathophysiological conditions of the same patient (longitudinal studies). Based on the airway mesh model, a 3D image model is synthesized by simulating the CT acquisition process. The image realism is achieved by including textural features of the surrounding pulmonary tissue which are obtained by segmentation from the same original CT data providing the airway axis. By varying the scanning simulation parameters, several 3D image models can be generated for the same airway mesh ground truth. Simulation results for physiological and pathological configurations are presented and discussed, illustrating the interest of such a modeling process for designing computer-aided diagnosis systems or for assessing their sensitivity, mainly for follow-up studies in asthma and COPD
CHANG CHIEN Kuang Che, FETITA Catalin, BRILLET Pierre Yves, PRETEUX Francoise, CHANG Ruey-Feng
Detection and classification of interstitial lung diseases and emphysema using a joint morphological-fuzzy approach. SPIE Medical Imaging 2009, SPIE, 10-12 february 2009, Orlando, United States, 2009, vol. 7260, pp. 726030.1-726030.8, ISBN 9780819475114
abstract
Multi-detector computed tomography (MDCT) has high accuracy and specificity on volumetrically capturing serial images of the lung. It increases the capability of computerized classification for lung tissue in medical research. This paper proposes a three-dimensional (3D) automated approach based on mathematical morphology and fuzzy logic for quantifying and classifying interstitial lung diseases (ILDs) and emphysema. The proposed methodology is composed of several stages: (1) an image multi-resolution decomposition scheme based on a 3D morphological filter is used to detect and analyze the different density patterns of the lung texture. Then, (2) for each pattern in the multi-resolution decomposition, six features are computed, for which fuzzy membership functions define a probability of association with a pathology class. Finally, (3) for each pathology class, the probabilities are combined up according to the weight assigned to each membership function and two threshold values are used to decide the final class of the pattern. The proposed approach was tested on 10 MDCT cases and the classification accuracy was: emphysema: 95%, fibrosis/honeycombing: 84% and ground glass: 97%.
FETITA Catalin, ORTNER Margarete, BRILLET Pierre Yves, PRETEUX Francoise, GRENIER Philippe
A morphological-aggregative approach for 3D segmentation of pulmonary airways from generic MSCT acquisitions. EXACT 2009 : 2nd International Workshop on Pulmonary Image Analysis, 20-20 september 2009, Londres, United Kingdom, 2009, pp. 215-226
[PDF]
abstract
Three-dimensional segmentation of airways from multi-slice computed tomography (MSCT) is a key point in the development of computer-aided tools for respiratory investigation. The expected benefits are related to diagnosis improvement of airway pathologies, preoperative planning and follow-up. The segmentation issue becomes even more challenging with regard to the high variability of the MSCT image acquisition in clinical practice due to the different CT scanners used and the various protocols (mainly at low dose). This paper develops a generic and automated 3D airway segmentation approach able to deal with a large spectrum of MSCT protocols by exploiting a combined morphologicalaggregative methodology. The proposed method was independently assessed by an external group of medical experts in the context of a segmentation challenge, on a database consisting of 20 thorax MSCT datasets. This database included acquisitions from several clinical centers equipped with different CT scanners and using various protocols. The evaluation results show a good performance of the developed approach in terms of airway segments detection accuracy, in the context of highly variable MSCT input data
FETITA Catalin, BRILLET Pierre Yves, PRETEUX Francoise
Morpho-geometrical approach for 3D segmentation of pulmonary vascular tree in multi-slice CT. SPIE Medical Imaging '09, SPIE, 10-12 february 2009, Orlando, United States, 2009, vol. 7259, pp. 72594F, ISBN 9780819475107
abstract
The analysis of pulmonary vessels provides better insights into the lung physio-pathology and offers the basis for a functional investigation of the respiratory system. In order to be performed in clinical routine, such analysis has to be compatible with the general protocol for thorax imaging based on multi-slice CT (MSCT), which does not involve the use of contrast agent for vessels enhancement. Despite the fact that a visual assessment of the pulmonary vascular tree is facilitated by the natural contrast existing between vessels and lung parenchyma, a quantitative analysis becomes quickly tedious due to the high spatial density and subdivision complexity of these anatomical structures. In this paper, we develop an automated 3D approach for the segmentation of the pulmonary vessels in MSCT allowing further quantification facilities for the lung function. The proposed approach combines mathematical morphology and discrete geometry operators in order to reach distal small caliber blood vessels and to preserve the border with the wall of the bronchial tree which features identical intensity values. In this respect, the pulmonary field is first roughly segmented using thresholding, and the trachea and the main bronchi removed. The lung shape is then regularized by morphological alternate filtering and the high opacities (vessels, bronchi, and other eventual pathologic features) selected. After the attenuation of the bronchus wall for large and medium airways, the set of vessel candidates are obtained by morphological grayscale reconstruction and binarization. The residual bronchus wall components are then removed by means of a geometrical shape filtering which includes skeletonization and cylindrical shape estimation. The morphology of the reconstructed pulmonary vessels can be visually investigated with volume rendering, by associating a specific color code with the local vessel caliber. The complement set of the vascular tree among the high intensity structures in the lung may also inform on lung pathological conditions (inflammation, interstitial disease, nodular patterns,...). The results obtained on normal and pathological subjects or in inspiration vs. expiration, are presented and discussed.
OULD HMEIDI Y., BEIGELMAN-AUBRY Catherine, ORTNER Margarete, FETITA Catalin, GRENIER Philippe, BRILLET Pierre Yves, AUBIER Michel
Analysis of bronchial bifurcations in severe obstructive lung disease using 2D multiplanar reconstructions and 3D segmentation of bronchial lumina with colour calibre coding (BronCare). 2nd World Congres of Thoracic Imaging and Diagnosis in Chest Disease, 30 may - 02 june 2009, Valencia, Spain, 2009
FRANCOIS Nicolas, FETITA Catalin, DUHIEU Stéphane, MUCCHIELLI Marie-Hélène, PRETEUX Francoise, DELACROIX Hervé
Quantification of macromolecular interactions using SPR detection. MIAAB 2008 : 3rd International workshop on Microscopic Image Analysis with Applications in Biology, 05-06 september 2008, New York City, United States, 2008, pp. 88-93
URL: http://www.miaab.org/miaab-2008-papers.html
abstract
Among different real time imaging techniques of macro molecular interactions, the emerging SPR (Surface Plasmon Resonance) approach is one of the most promising: no molecular labeling is necessary to reveal interactions, and many protein/protein couples can be studied in the same experiment. Such a real time monitoring of various biomolecular interactions raises several challenges in terms of image segmentation, extraction and interpretation of the mean hybridization signal of each spot, and computation of the affinity constants for each protein/protein couples. This paper describes an automated approach for SPR image analysis resolving most of the previous issues. First, a differential signal is computed in order to only conserve the interactions according to the time. Second, a spatio-temporal filtering is used to remove the noise present in the SPR raw data. Then, the data is segmented using the k-means method, in order to identify regions of the spots according to their temporal behavior. Non-uniform hybridization within a spot can thus be detected and the pixels excluded from analysis. In the same manner, the presence of image artifacts (chip scratch, deposit leakage) can be detected and not taken into account for analysis. The mean signal over each spot is then extracted and its temporal behavior provides the kinetic parameters characterizing the biological interaction (association and dissociation constants). The preliminary results obtained on test biomolecular interactions confirmed our expectations concerning our detection capability even at low concentration of analytes. The affinity constants obtained has been compared to those obtained by ELISA. The results are in good agreement, validating therefore the SPR approach for protein/protein interactions studies
SARAGAGLIA Amaury, FETITA Catalin, PRETEUX Francoise, GRENIER Philippe
3D bronchial simulator : automatic generation of volumetric CT images for assessment of bronchial parameter quantification methods. SPIE Medical Imaging 2008 : Visualization, Image-guided Procedures, and Modeling, SPIE, 17-21 february 2008, San Diego, United States, 2008, pp. 69180Y1-69180Y12, ISBN 978-0-8194-7102-4
abstract
The problem of quantifying bronchial parameters from multi-detector computed tomography (MDCT) data has been highly studied in medical research. While the developed methods have been tested and validated on cylindrical computer/physical phantoms or by experimented radiologists on in-vivo/in-vitro CT image data, today there is no established ground truth enabling to compare the different results. This paper proposes an original approach allowing to simulate CT image acquisitions of realistic 3D bronchus-vessel configurations starting from mesh models of perfectly known parameters, with easily modifiable geometry and topology according to different pathology characteristics. The bronchial simulator platform, 3DAirSim, is composed of several modules: 1) 3D model generation of bronchus inner and outer wall surfaces of different calibers, shapes and orientations, 2) texture volume creation corresponding to the lung parenchyma including or not blood vessels, 3) simulation of CT image acquisition mimicking the scanning process. The proposed model generation method relies on the construction of a consistent 2-manifold surface of a branching tubular structure with given medial axis and local radii. First, a coarse triangular mesh is created by connecting polygonal cross-sections along the medial axis. The model is then refined and locally deformed in the surface normal direction under specific force constraints which stabilize its evolution at the level of the input radii. By generating a pathology-specific database, 3DAirSim will contribute to the creation of a test-bed for bronchial parameter quantification. 3DAirSim is currently used to lead various validations of existing approaches with respect to the clinical objective of airway wall remodeling assessment