Publications Old

Ouvrages édités à titre de seul éditeur ou en collaboration

2011

XXIIIrd congress of the International Society of Biomechanics - ISB2011 Conference book - Programme & Abstracts

ISB 2011 Conference book

2005

3D Reconstruction of the Necropolis in Itanos, Crete

Communications publiées lors de congrès ou colloques nationaux et internationaux

A paraître

Robust Structured Light Pattern for Use with a Hologram in 3D Endoscopy

This paper introduces a novel structured light pattern designed to be compatible with the hologram projection. Here is proposed to use a De Bruijn-based sequence and a combination of continuous and dashed lines for the pattern. Dashed lines are coded by a combination of their period and of their duty cycles. It provides 16 different lines which limits to two the required number of lines for identification. The segmentation has been made easier by inserting continuous lines between two dashed lines. As required by the use of holograms, the sequence has been adapted by making it symmetric. It has been improved by guaranteeing a hamming distance equal to two for contiguous lines. The implementation on a virtual model has shown that a subpixel accuracy has been achieved. The aim of this pattern is to be used in 3D endoscopy

AI Guided Panoramic Image Reconstruction

2024

Training Data Selection to Improve Multi-class Instance Segmentation in Digital Pathology

Finding the best channel for tissue segmentation in whole-slide images

In digital pathology, segmentation between tissue and glass slide is a very common pre-processing step in image processing pipelines. It is often presented as relatively trivial, and solved using ad-hoc heuristics that are not always precisely defined nor justified. Most tissue segmentation pipelines start by reducing the color image to a single-channel representation, grayscale being the most common. We show in this study that representations that focus on the colorfulness or entropy offer better separability between tissue and background, and lead to better results in simple thresholding pipelines.

Assessing Local Descriptors for Feature-Based Registration of Whole-Slide Images

Feature-based registration has become increasingly popular in digital pathology for achieving initial global alignment between image pairs. However, the selection of algorithms used in this approach is often not well-justified. Specifically, the choice of local feature descriptor is rarely, if ever, discussed in the context of digital pathology. The majority of feature-based whole-slide image registration methods rely on the SIFT descriptor. In this study, we demonstrate that the choice of descriptor significantly influences the quality of registration results and that the BRIEF descriptor captures more optimal information for histological image registration.

2023

Automatic detection of windows reflection or transparency pollution in TLS acquisitions

Fibroblast Activation Protein Inhibitor, a Promising Radiotracer inFibrogenesis

Rationale: Idiopathic pulmonary fibrosis (IPF) is a chronic and irreversible interstitial lung diseasefor which biomarker of the fibrotic activity of the disease are lacking. Fibroblast activation protein-α(FAP) is a marker of activated fibroblasts. The development of quinoline-based PET tracers that actas FAP inhibitors (FAPIs) demonstrated promising results in oncology with a high and selectivetumor uptake. In the present study, we evaluated the potential role of FAPI as a biomarker of lungfibrogenesis. Methods: The lung uptake of FAPI and its kinetic was assessed in a mouse model ofpulmonary fibrosis. Thus, intratracheal instillation of bleomycin (0.02U/mouse) was performed onC56BL/6 mice. Control mice received an intratracheal instillation of NaCl 0.9%. FAPI was providedby SOFIE (Totowa, USA) and the radiotracer 18F-FAPI was produced in the department of NuclearMedicine of Erasme Hospital. PET/CT imaging were determined at different timepoints (days 3, 10,16 and 28) after the instillation of bleomycin. A time course of uptake of the radiotracer wasevaluated. The results are presented as the mean standardized uptake value (SUV mean) in thelungs and the calculation of a lung-to-muscle ratio (LMR). To correlate with the PET scan results, theextent of fibrosis was assessed by measuring lung content of hydroxyproline and by evaluating theAshcroft modified scale. Results: The optimal imaging window was determined between 40 and 90minutes after radiotracer injection. Bleomycin-treated mice presented a significantly higher uptakeof 18F-FAPI (both SUV mean and LMR) at days 10 and 16 after instillation as compared to controlmice (p < 0.01). No significant statistical difference was observed at day 3 and day 28 afterinstillation. At day 10 and day 16, a strong correlation between 18F-FAPI uptake and hydroxyprolinelung content was observed, as well as a moderate correlation with the Ashcroft modified score.Conclusions: Our results suggest that FAPI constitutes a promising marker of fibrogenesis whoseexpression can be assessed by PET/CT imaging in a mouse model of lung fibrosis. Interestingly, nosignificant increase of lung FAPI uptake was observed during the initial inflammatory phase afterbleomycin instillation as well as at the later stage when fibrotic changes are established and nolonger grow. 18F-FAPi PET/CT could be a useful tool for preclinical evaluation of antifibrotic drugsand further studies should assess its value in patients with IPF.

A Quantitative Evaluation of Trademark Search Engines' Performances through Large-Scale Statistical Analysis

Intellectual Property Offices now offer their users trademark search engines to help them identify earlier trademarks in their register. Such tools have proven to be extremely useful given the growing number of trademarks registered but have never been subjected to thorough evaluation, despite the necessity for openness and accountability in justice systems. Additionally, their performance is unknown, in particular the reliability of their results pertaining to applicable legal rules. In fact, their "black box nature" makes automatic and at-scale evaluation hard to perform directly, which is why we propose a novel method for evaluating their performance using settled case-law for ground truth, and at-scale analysis. Based on this methodology, we evidence the performance for two such systems, the Benelux Office of Intellectual Property (BOIP) and European Union Intellectual Property Office (EUIPO), using 8 126 opposition division decisions from the EUIPO. We show important disparities between the two systems, along with surprisingly good results for EUIPO's system.

2022

Extracting Microseismic Ground Motion From Legacy Seismograms

Before digital recordings became available in the 1970s, the ground motion was recorded using ink on white paper, scratching black-smoked paper, or light on photographic paper. While those analog seismic records offer unique continuous observations from the last century, most of them are now stacked and archived in boxes and potentially exposed to physical decay and permanent loss. To preserve those records and ultimately subject them to modern methods of analysis, it is time-sensitive to scan and digitize them. Here, we worked on a method for automatic digitization of paper seismograms using image processing and machine learning to extract microseismic ground-motion periods and amplitudes. We implemented the method on legacy data recorded at the Royal Observatory of Belgium to extract power spectral densities for major storms during the last century, which are compared with modeled microseisms levels computed using a numerical ocean wave model. This further shows how digitizing analog seismograms does not only preserve the scientific legacy but also makes new research possible by bringing analog data to the digital age.

2021

Processing multi-expert annotations in digital pathology: A study of the Gleason2019 challenge

3D scanner colorization taking into account lighting problems (shadows, overexposures, lighting changes, and lack of light)

2020

Thermal Image Super-Resolution Challenge - PBVS 2020

This paper summarizes the top contributions to the first challenge on thermal image super-resolution (TISR), which was organized as part of the Perception Beyond the Visible Spectrum (PBVS) 2020 workshop. In this challenge, a novel thermal image dataset is considered together with state- of-the-art approaches evaluated under a common framework. The dataset used in the challenge consists of 1021 thermal images, obtained from three distinct thermal cameras at different resolutions (low-resolution, mid-resolution, and high-resolution), resulting in a total of 3063 thermal images. From each resolution, 951 images are used for training and 50 for testing while the 20 remaining images are used for two proposed evaluations. The first evaluation consists of downsampling the low-resolution, mid-resolution, and high-resolution thermal images by ×2, ×3 and ×4 respectively, and comparing their super-resolution results with the corresponding ground truth images. The second evaluation is comprised of obtaining the ×2 super-resolution from a given mid-resolution thermal image and comparing it with the corresponding semi-registered high- resolution thermal image. Out of 51 registered participants, 6 teams reached the final validation phase.

3D digitization of the Brussels City Hall and the medieval archangel Michael wind vane: architectural and archaeological exploitation

In order to make the architectural and archaeological study, the roofs, the courtyard and the facades of the Brussels City Hall were digitized with a 3D scanner, coupled with photographic acquisitions. Various elements, such as the main portal tympanum and the archangel Michael, - an exceptionally preserved 5-metre-high medieval metal wind vane that adorned the top of the 96-metre-high tower -, were also digitized in high definition. Numerical surveys shows different colorimetric (variation of colorimetry related to the changes in natural lighting) and geometric defects (erroneous points related to the passages of persons and vehicles, flying points or noises inherent to the acquisition device). A specific and automatic processing pipeline has therefore been developed and applied to correct all this problems. Given the amount of data and operations for creating plans, a software has been developed to present the data as an enriched 2D representation. This is similar to orthophotos complemented by the possibility to navigate in the depth and to vary the rendering mode (color, intensity, orientation ...), to highlight elements (surfaces, edges ...) hardly visible in simple color mode of rendering. Its functionalities allowed the drawing of very precise elevations and to generate projection images in high definition of all buildings parts and also of the archangel statue. Indeed, this survey allowed to draw the entire statue to the real scale and in a completely proportioned way. Archeologists have been able to distinguish the main work components, and they better understand the articulations between its constitutive parts and the various transformations made to the metal statue over the centuries.

2019

Data augmentation for training deep regression for in vitro cell detection

SNOW: Semi-Supervised, NOisy and/or Weak Data for Deep Learning in Digital Pathology

Digital pathology produces a lot of images. For machine learning applications, these images need to be annotated, which can be complex and time consuming. Therefore, outside of a few benchmark datasets, real-world applications often rely on data with scarce or unreliable annotations. Inthis paper, we quantitatively analyze how different types of perturbations influence the results of a typical deep learning algorithm by artificially weakening the annotations of a benchmark biomedical dataset. We use classical machine learning paradigms (semi-supervised, noisy and weak learning) adapted to deep learning to try to counteract those effects, and analyze the effectiveness of these methods in addressing different types of weakness.

2018

Artifact Identification in Digital Pathology from Weak and Noisy Supervision with Deep Residual Networks

RGB Guided Thermal Super-Resolution Enhancement

In visual surveillance and security problems, objects can occur in different conditions of illumination and occlusion, therefore thermal images have become a major tool in a large variety of applications. By the reason of their high cost compared to their visual (RGB) counterpart, thermal sensors are used in low-resolution and in low contrast which introduces the necessity to obtain a higher resolution version. In this work, we propose a deep learning model by which to enhance the thermal image resolution guided by RGB images using GAN based model. The results indicate an improvement in resolution enhancement using RGB guided thermal super-resolution models compared to the classical single thermal super-resolution approach.

Multimodal Sensor Fusion In Single Thermal image Super-Resolution

With the fast growth in the visual surveillance and security sectors, thermal infrared images have become increasingly necessary ina large variety of industrial applications. This is true even though IR sensors are still more expensive than their RGB counterpart having the same resolution. In this paper, we propose a deep learning solution to enhance the thermal image resolution. The following results are given:(I) Introduction of a multimodal, visual-thermal fusion model that ad-dresses thermal image super-resolution, via integrating high-frequency information from the visual image.(II) Investigation of different net-work architecture schemes in the literature, their up-sampling methods, learning procedures, and their optimization functions by showing their beneficial contribution to the super-resolution problem.(III) A bench-mark ULB17-VT dataset that contains thermal images and their visual images counterpart is presented.(IV) Presentation of a qualitative evaluation of a large test set with 58 samples and 22 raters which shows that our proposed model performs better against state-of-the-arts.

Numérisation 3D de l'Hôtel de Ville de Bruxelles et de la statue du saint Michel : exploitation architecturale et archéologique

2017

A Graph Based Algorithm for Star Recognition

Analysis of abdominal movement with Phase Optical Flow: Application to Diffusion imaging.

2016

Image normalization for quantitative immunohistochemistry in digital pathology

We propose to adapt to immunohistochemistry (IHC) some methods proposed to normalize images from histological slices stained with hematoxylin-eosin (H&E). Our final aim is to provide a coherent quantitative characterization of IHC biomarkers across different IHC batches with possible staining variations. In contrast to H&E, IHC staining strongly varies with the tissue analyzed and the protein targeted, making image normalization challenging. To solve this problem, we added in each IHC batch a slice from a reference tissue microarray (TMA) and then digitalized it to establish an inter-batch normalization transform. A comparison of two methods adapted to the specificity of IHC-stained slides evidences some normalization requirements to make valid IHC biomarker quantification across different staining batches.

2015

Amplified spontaneous emission injection into an optical fiber with the aid of a nematicon

Amplified Spontaneous Emission (ASE) has become popular for applications like spectroscopy, fiber sensors and imaging that require incoherent light. In our setup ASE is generated in a dye-doped nematic liquid crystal cell and it is then collected into an optical fiber to integrate into the device. We demonstrate that, generating a nematicon from the same fiber, the ASE collection efficiency is increased of almost one order of magnitude thanks to the wave-guiding action of the nematicon that induces the injection into the fiber. Moreover the collected emission is highly linearly polarized parallel to the direction of the liquid crystal director

Comparison of Normalized Transfer Functions for Fast Blending-based Color Correction of Scans Acquired under Natural Conditions

High-Throughput Analysis of Tissue-Based Biomarkers in Digital Pathology

Real-time Fullscale Model Colorization and Global Color Quality Evaluation for Rapid Scanning in Uncontrolled Environment

Automated Tissue Microarray Image Processing in Digital Pathology.

2014

Multi-sensor data fusion for hand tracking using Kinect and leap motion

2013

Human Motion Tracking for Rehabilitation using Depth Images and Particle Filter Optimization

Fast Color Correction for Rapid Scanning in Uncontrolled Environment

Human motion tracking for rehabilitation using depth images and particle filter optimization

The algorithm presented here allows the motion tracking of a human subject performing rehabilitation exercises during physiotherapy. The motion is tracked by fitting a model into the observed data, which are depth images coming from one or multiple Kinect sensors. The model consists of a surface mesh morphologically close to the patient's body and an articulated skeleton. The mesh is deformed by linear blend skinning according to the pose of the skeleton. The optimization is performed by particle filtering. Thanks to the graphics pipeline and the computing capabilities of the GPU, our algorithm reaches execution speeds close to real time. When working offline with a model very close to the patient's morphology, the joints locations and rotations are estimated with an average accuracy respectively smaller than a few millimeters and a few degrees.

Hybrid method to extract striation features from ship noise spectrogram

2012

Plans Extraction From Complex Buildings 3D Acquisitions

Robust structured light pattern for use with a hologram in 3D endoscopy

3D augmented reality applied to the treatment of neuropathic pain.

Unsupervised vehicle detection in traffic scene using distributed one class classifiers

3D augmented reality applied to the treatment of neuropathic pain

2011

Tridimensional laser scanning to retrieve engineering site drawings. The experience of the Brussels Park Bunker rehabilitation project.

Geometrical 3D reconstruction using real-time RGB-D cameras

Programme and Abstracts

2010

Detecting man-made structure changes to assist geographic data producers in planning their update strategy, ISPRS

Computerised geometric analysis of a spire coming from a Gothic tabernacle

Ki-67 hot-spots detection on glioblastoma tissue sections

The use of ORFEO toolbox in the context of map updating

2009

Reconstruction and Digitalization of an archaeological site, Itanos, Crete

A multi-features stereo vision system for road traffic analysis

This paper presents a method for counting and classifying vehicles on motorway. The system is based on a multi-camera system fixed over the road. Different features (maximum phase congruency and edges) are detected on the two images and matched together with local matching algorithm. The resulting 3D points cloud is processed by maximum spanning tree clustering algorithm to group the points into vehicle objects. Bounding boxes are defined for each detected object, giving an approximation of the vehicles 3D sizes. A complementary 2D quadrilateral detector has been developed to enhance the probability of matching features on vehicle exhibiting little texture such as long vehicles. The algorithm presented here was validated manually and gives 90% of good detection accuracy.

Weakened watershed assembly for remote sensing image segmentation and change detection

A camera auto-calibration algorithm for realtime road traffic analysis

This paper presents a new mono-camera system for traffic surveillance. It uses an original algorithm to obtain automatically a calibration pattern from road lane markings. Movement detection is done with a Σ - Δ background estimation which is a non linear method of background substraction based on comparison and elementary increment/decrement. Foreground and calibration data obtained allow to determine vehicles speed in an efficient manner. Finally, a new method to estimate the height of vehicles is presented.

3D Reconstruction and Digitalization of an
archaeological site, Itanos, Crete

Numérisation 3D de la grotte d'El Castillo (Puente Viesgo)

Influence d'images évocatrices et distractrices sur une tâche de jugement en acoustique des salles

Biomedical Engineer and Phlebologist

Comparaison et évaluation de méthodes de segmentation avec contrainte en vue d'une classification du bâti et des routes

2008

Cells Tracking by Snakes

In this paper, a cells detection method based on active contours is presented. Active contours or snakes are widely use in image segmentation and tracking problems. Traditionally, active contours initialization is performance manually, this method provides an automatic initialization based on cross correlation. Cell tracking based on active contours provide a faster method to performance this task to multitarget problem. External and internal forces on the image are computed to determinate the action area of the active contours, this task is performance by the Vector Field Convolution (VFC) algorithm.

Cell tracking by normalized cross-correlation with image processing

Here, cell tracking task involves normalized cross correlation of the cell target and microscope images. The sensibility of this method was improved applying image processing algorithms prior to the cross correlation task. © 2008 IEEE.

Cell recognition and tracking using nonlinear cross-correlation

Phase contrast image segmentation by weak watershed transform assembly

Design of an articulated mini-fixation device for proximal interphalangeal joint finger fractures

Digital Integrated Operating Room

Registration and segmentation of head and neck volumes in IMRT applications

Using a Pocket PC as an interaction peripheral for Virtual Realty

Un projet d'ingénierie biomédicale à double objectif pédagogique

2007

Image Processing for in Vitro Cell Tracking

In this paper, we propose an image processing method able to detect cells trough in vitro phase-contrast video microscopy. Bodies of the cells and image background are very similar; it does not allow having a good performance of tracking process. The proposed method normalizes original image to obtain better object-background contrast, image is equalized to highlight the object to be tracked, and image is threshold in order to obtain a better object-background contrast. Gray Level Morphological Gradient is applied to obtain more defined contours in the areas surrounded by Halos. Dilatation and Erosion were combined to achieve this goal. A subtraction process was applied after dilation of image to obtain borders. © Springer-Verlag Berlin Heidelberg 2007.

Documentation of the El Castillo (Puente Viesgo) cave using 3D scanning

3D and Virtual Reality

Graph Nodes Clustering based on the Commute-Time Kernel

Cell tracking by border-optical hybrid model

We propose an hybrid (image processing-correlation) method to obtain cells detection and cells migration tracking in order to analyze cells behaviors under different conditions. © 2007 OSA.

2006

Computer assisted needle positioning for liver tumor radiofrequency ablation (RFA)

Detection of Biological Cells in Phase-Contrast Microscopy Images

Interactive web-based application for potteries capacity computing

Imaging technologies for avoiding back pain at work

Interactive airway wall thickness measurement from computed tomography data

Apple Stem and Calyx Recognition by Decision Trees

2005

Automatic fluoroscopic Image Calibration for Traumatology Intervention Guidance

Hierarchical Modeling

Real Time L-System Generated Trees Based on Modern Graphics Hardware

Distal locking of intra-medullary nail using non-constrained fluoroscopic images

Modélisation hiérarchique

Hierarchical modeling

Computers and 3D Image Synthesis as Tools for Archaeology

Mitotic Tree Construction by Computer In Vitro Cell Tracking : a Tool for Proliferation and Motility Features Extraction

2004

Comparison of very high spatial resolution satellite image segmentations

Since 1999, very high spatial resolution data represent the surface of the earth with more details. However, information extraction by computer-assisted classification techniques proves to be very complex owing to the internal variability increase in land-cover units and to the weakness of spectral resolution1, 2, 3. The increase in variability decreases the statistical separability of land-cover classes in the spectral space 4. Per pixel multispectral classification techniques are then insufficient for an extraction of complex categories and spectrally heterogeneous land-cover, like urban areas5. Per region classification was proposed as an alternative approach6, 7. The first step of this approach is the segmentation. A large variety of segmentation algorithms were developed these last 20 years8 and a comparison of their implementation on very high spatial resolution images is necessary. For this study, four algorithms from the two main groups of segmentation algorithms (boundary-based and region-based algorithms) were selected. In order to compare the algorithms, an evaluation of each algorithm was carried out with empirical discrepancy evaluation methods. This evaluation is carried out with a visual segmentation of IKONOS panchromatic images.

Towards a Virtual 3D Reconstruction of a Rood-Screen from its Archaeological Fragments

An environment for the analysis and reconstruction of archaeological objects

3D orientation of archaeological fragments coming from a Gothic spire

Traumatology surgical intervention guided by virtual reality

2002

Conception of a navigation system controlling the reduction of long bone fractures treated by external fixation

Wood Analyst©: A new image analysis software adapted for douglas-fir thin cross sections

2001

Real-time simulation of virtual objects impact with shattering

Limiting the Number of Trees in Random Forests

Adjusting the outputs of a classifier to new a priori probabilities may significantly improve classification accuracy: Evidence from a multi-class problem in remote sensing

Characterization of acting filaments in cancer cells by the Hough transform

Amélioration de l'interprétation numérique de l'occupation du sol

Remote Sensing Classification of Spectral, Spatial and Contextual Data Using Multiple Classifier Systems

2000

Mixing Bagging and Multiple Feature Subsets to Improve Classification Accuracy of Decision Tree Combination

Different Ways of Weakening Decision Trees and Their Impact on Classification Accuracy of DT Combination

Virtual reality based on Conventional X-Rays

1999

Building virtual 3D bone fragments models to control diaphyseal fracture reduction

1998

Automatic objects selection in computer-assisted microscopy

1996

Two and three-dimensional processing of medical images on a personal computer

1995

Comparisons of different RBF networks for pattern classification

Multiple-Knowledge Representation in Concept Learning

Towards Neuro-Fuzzy Defuzzification in Benelearn '95

Comparing RBF and fuzzy inference systems on theoretical and practical basis

1994

Cognitive and Semantic interpretation of a NN classifier using prototypes

How to "secure" the decisions of a NN classifier

1993

Using prototypes to solve problems in neural net classifiers

NNP: a neural net classifier using prototypes

We present a three-layer neural net classifier for multiclass object recognition problems requiring piecewise nonlinear discriminant surfaces. The hidden layer is composed of prototypes of each class. The weights from the input to the hidden layer are the vector descriptions of prototypes (in the input feature space). The output layer neurons represent the classes, the hidden-to-output weights being binary and fixed. They map each prototype neuron to one of the class output neurons. Only the input-to-hidden weights are adapted by an algorithm using deterministic annealing and gradient descent techniques. This algorithm permits the distribution of prototypes in classes while minimising the classification error rate.

1991

Description Contrasting in Incremental Concept Formation

Statistical Strategies in Incremental Conceptual Classification

Incremental Classification, a Multidisciplinary Viewpoint

1990

Image processing and Application of CAD to the manufacture of prostheses

Formation de concepts en intelligence artificielle

Des des travaux précédents ([Decaes89 a,b][Decaes90]), l'auteure a étudié des mécanismes incrémentaux de "Formation de Concepts", et a développé ADECLU, un système incrémental de "Conceptual Clustering". Dans cet article, l'auteure présente les différentes version de ADECLU et les compare, du point de vue conceptuel et des performances, aux méthodes développées en Analyse Relationnelle (Agrégation et Bloc Sériation) [Marc81, 87][Mich87]

1989

Incremental Concept Formation with Attribute Selection

Application of CAD / CAM in Prosthetics and Orthotics

Formation incrémentale de concepts par un critère d'adéquation

Application de la CAO. La conception et la fabrication de prothèses et d'orthèses

Application of the " CAD - CAM " in

Incremental concept formation via a suitability criterion

1988

Philosophy and Application of CAD-CAM for Ortheses and Prostheses

Participations à des congrès et colloques internationaux

2023

Adaptive Changes in Heart Rate Variability and Cardiac Function during Long-term Spaceflight: Insights from Wearable Devices

Adaptive Changes in Heart Rate Variability and Cardiac Function during Long-term Spaceflight

2021

Un outil en ligne pour l'étude 3D de la sculpture ?

Panorama, une plateforme de recherche à l'ULB, et le projet USINE, webplaterforme3D pour l'étude collaborative de la sculpture

2014

ADAM-17/FHL2 Colocalisation Suggests Interaction and Role of These Proteins in Colorectal Cancer

2010

Indoleamine 2,3-dioxygenase expression is an independent prognostic factor in pT1-4N1Mx staged colorectal cancer

2009

In vivo assessment of temozolomide delivery systems for inhalation therapy of lung cancer

In Vivo Assessment of Temozolomide Local Delivery for Lung Cancer Inhalation Therapy Nathalie Wauthoz, Philippe Deleuze, Julien Hecq, Isabelle Roland, Sven Saussez, Ivan Adanja, Olivier Debeir, Christine Decaestecker, Véronique Mathieu, Karim Amighi Laboratoire de Pharmacie Galénique et de Biopharmacie Director : Karim Amighi Abstract The aim of this study was to compare the efficacy of local drug delivery by inhalation to intravenous delivery in a B16F10 melanoma metastatic lung model. Temozolomide was formulated as a suspension, which was elaborated and evaluated in terms of particle size, shape and agglomeration. An endotracheal administration device was used to aerosolize the suspension. This mode of delivery was evaluated at different temozolomide concentrations and was optimized for the uniformity of delivered dose, the droplet size distribution and the distribution of droplets in vivo. Of the particles in the stabilized suspension, 79% were compatible with the human respirable size range, and this formulation retained 100% in vitro anticancer activity as compared to temozolomide alone in three distinct cancer cell lines. The pulmonary delivery device provided good reproducibility in terms of both the dose delivered and the droplet size distribution. Most of the lung tissues that were exposed to aerosol droplets contained the particles, as revealed by fluorescent microscopy techniques. The global in vivo antitumor activity of the inhaled temozolomide provided a median survival period similar to that for intravenous temozolomide delivery, and three out of twenty-seven mice (11%) survived with almost complete eradication of the lung tumours. The present study thus shows that inhalation of a simple liquid formulation is well tolerated and active against a very biologically aggressive mouse melanoma pulmonary pseudo-metastatic model. This inhalation delivery could be used to deliver other types of anticancer drugs.

2008

Aristolochic acid induces proximal tubule apoptosis, EMT and interstitial cell infiltration

Aristolochic acid induces proximal tubule apoptosis, epithelial to mesenchymal transformation and immuncompetents cells infiltration

2007

Early intratubular epithelial to mesenchymal transition (EMT) after aristolochic acid intoxication

From aristolochic acid intoxication to renal fibrosis

1990

Blocs Sériation de Matrices Binaires par Algorithme Génétique

Le but de cet article est de montrer que l'Algorithme Génétique ("Genetic Algorithms in Search, Optimization and Machine Learning", H. Goldberg, Addison Wesley, 1989.