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Scientific events
RRI IMPACT Scientific Review, December 11th 2025, IECB, Amphitheater
The IMPACT Impulsion Research Network is pleased to invite you to its scientific review on Thursday 11 December 2025 from 9am to 13pm, followed by lunch.
This morning will take place in the amphitheatre of the IECB, Campus Brus.
The 9 projects funded by IMPACT will present their progress and results. The full programme will be announced shortly.
The event is free and open to all, but registration will be required.
Registration Deadline: December 1st 2025 : https://framaforms.org/rri-impact-scientifc-review-1762350147
Conference - Integrating Microscopy Data with Diffusion MRI Tractography, Charles Poirier (LINUM, University of Sherbrooke), December 4, 2025, 11h, IBIO
Distinction
Amel Imene Hadj Bouzid, winner of the "Prize of the President of the Republic for Innovative Researchers"
Charged by the President of the Republic of Algeria, Mr Abdelmadjid Tebboune, and as part of the activities to commemorate National Student Day, celebrated on 19 May each year, the Algerian Prime Minister, Mr Nadir Larbaoui, together with the Minister of Higher Education and Scientific Research, Mr Kamel Baddari, presided over the award ceremony for the Prize of the President of the Republic for the best student.
On Tuesday 20 May, together with the Minister of Higher Education and Scientific Research, Kamel Baddari, Prime Minister Nadir Larbaoui presided over the award ceremony for the first edition of the President of the Republic's Prize for the Innovative Researcher, at the "Abdelhafid Ihaddaden" science and technology centre in Sidi Abdellah (Algiers).
This prestigious award was delivered to Amel Imene Hadj Bouzid, doctoral student at IMPACT working in WP2 "Cardio-thoracic imaging".
Her research centers on the detection of pulmonary lesions using various imaging techniques, including CT scans and MRI, utilizing deep learning methodologies. The goal of her thesis is to ascertain the severity of lung impairments and to explore the potential for applying these methods across different imaging modalities. Her work is especially significant in the context of emerging treatments, aiming to enhance the precision of diagnosing chronic lung diseases.
Call for projects
No call for the moment.
See you soon!
New publications
Publication - 3D Automated Segmentation of Bronchial Abnormalities on Ultrashort Echo Time MRI: A Quantitative MR Outcome in Cystic Fibrosis by A. I. H. Bouzid, I. Benlala, B. D. de Senneville, & al. in Journal of Magnetic Resonance Imaging (2025): 1–11
Abstract
- Background
Cystic fibrosis (CF) monitoring relies on computed tomography (CT), but ultra-short echo time MRI (UTE-MRI) offers a radiation-free alternative. However, its clinical adoption is hindered by the laborious and subjective manual analysis, which prevents standardized quantification of bronchial abnormalities.
- Purpose
To develop a deep learning (DL) system for the segmentation of CF bronchial abnormalities on UTE-MRI and assess clinical relevance in patients undergoing cystic fibrosis transmembrane conductance regulator (CFTR) modulator treatment.
- Study Type
Retrospective.
- Population
One-hundred and sixty-six CF patients were included (age = 23 ± 11, 48% male), comprising a training set (n = 97), a test set (n = 25), and an independent clinical validation cohort (n = 44).
- Field Strength/Sequence
1.5T/UTE-MRI 3D gradient-echo Spiral Volume Interpolated Breath-hold Examination (VIBE) sequence.
- Assessment
The RiSeNet architecture was trained using paired UTE-MRI and CT scans. Its technical performance was evaluated against expert-refined segmentations and compared to state-of-the-art segmentation models using topology-aware metrics: Normalized Surface Dice (NSD) and CenterLine Dice (clDice). Clinical validation was performed by correlating automated measurements at baseline (M0) and 1-year post-CFTR modulator treatment (M12) with Bhalla scores and pulmonary function tests (FEV1%p).
- Statistical Tests
Student's t-test, Mann–Whitney, Wilcoxon, and Chi-square tests were used for group comparisons. The Spearman test was used to assess correlations. A p value < 0.05 was considered statistically significant.
- Results
In the test group, RiSeNet achieved significantly superior performance versus state-of-the-art with NSD scores of 0.84 for bronchiectasis, 0.90 for wall thickening, and 0.75 for mucus; and clDice scores of 0.69, 0.61, and 0.64, respectively. In the clinical validation group, significant correlations with Bhalla (ρ = −0.92/−0.85) and FEV1%p (ρ = −0.68/−0.67) were observed pre/post-CFTR modulator. Post-CFTR modulator, FEV1%p improved (69%–92%) with significant reductions in bronchiectasis (3.88–1.25), wall thickening (30.43–3.05), and mucus (53.30–11.80).
- Data Conclusion
RiSeNet may enable semantic segmentation of CF abnormalities on radiation-free UTE-MRI.
Publication - Quantitative CT of emphysema, wall thickness and mucus plugs in alpha-1-antitrypsin deficiency: relationship to clinical outcomes by Dournes, G., Hadj Bouzid, A.I., Doucet, K. & al. in Eur Radiol (2025)
Abstract
- Objectives
Alpha-1-antitrypsin deficiency (AATD) is a rare genetic disorder leading to chronic obstructive pulmonary disease (COPD). Emphysema is the major structural damage visible on CT scans. However, there is little knowledge on the association between other structural abnormalities, such as bronchiectasis (BE), airway wall thickening (WT) or mucus plugs (MP), and clinical features.
- Materials and methods
Retrospective study between 2008 and 2022 at one University Hospital of Bordeaux on all consecutive AATD patients. Bronchial and parenchymal alterations were evaluated with an (artificial intelligence) AI-driven Normalized Volume of Airway Abnormalities (NOVAA-CT) scoring system, including BE, WT, MP and emphysema quantifications. We evaluated correlations between forced expiratory volume in 1-s (FEV1%), dyspnea severity through the mMRC scale and the occurrence of at least one exacerbation in the year following CT scan.
- Results
Fifty-two AATD patients were included (median FEV1: 47% (40–65)). CT features of BE, WT and MP were present in 100%, 94.2% and 59% of the study population, respectively, with a lower versus upper lung predominance (p < 0.05). WT (p < 0.001) and BE (p = 0.04) correlated with FEV1% but not mMRC (p ≥ 0.09). Conversely, MP did not correlate with FEV1% (p = 0.08) but with mMRC (p = 0.01). Emphysema strongly correlated with both FEV1% and mMRC (p < 0.001). In multivariate analysis, after adjustment for age, genotype and tobacco consumption, the best predictor of exacerbation was WT (OR = 1.12 [1.02–1.22]; p = 0.01).
- Conclusion
This study demonstrates that AI-assisted identification of structural airway abnormalities is frequent in AATD patients and carries distinct clinical significance. Among them, WT was the most robust predictor of exacerbations.
Publication - Quantitative CT Evaluation of Bronchiectasis Improvement in Cystic Fibrosis after CFTR-Modulator Therapy by Amel Imene Hadj Bouzid, Daphné Pasche, Ilyes Benlala,Stéphanie Bui, Julie Macey, Jean Delmas, Fabien Beaufils, Baudouin Denis de Senneville, Patrick Berger and Gaël Dournes in Radiology: Cardiothoracic Imaging, December 2025
Abstract
- Purpose
To assess whether elexacaftor–tezacaftor–ivacaftor (ETI) therapy improves bronchiectasis in cystic fibrosis at CT and to identify associated factors.
- Materials and Methods
- Results
A total of 106 patients were included (median age, 19 years [IQR, 12–29]; 59 male patients; median FEV1%p, 80% [IQR, 55–99]). Of these 106 patients, 101 (95.3%) had mild-to-moderate disease severity, with FEV1%p greater than 40%. Bronchiectasis normalized volumes increased between Y-2 (7.6 [IQR, 2–19]) and Y0 (15.3 [IQR, 5.6–32]) but decreased at Y1 (3.6 [IQR, 0.6–25]; P < .001). Bronchiectasis improved in 74 of 106 patients (69.8%), including 18 of 106 (16.9%) with complete resolution and 56 of 106 (52.9%) with partial reduction, with a median volume reduction of 64% and six resolved segments per patient. Bronchiectasis improvement was associated with younger age (P < .001), cylindric CT pattern (P < .001), fewer CT abnormalities (P < .001), and greater FEV1%p increase (P = .03). Younger age, lower Pseudomonas aeruginosa colonization, and lower CT mucus volume were independent predictors of bronchiectasis improvement (R2 = 0.50; P < .001).
- Conclusion
Bronchiectasis improvement occurred after ETI treatment in a substantial fraction of patients with predominantly mild-to-moderate CF. Improvement was linked to younger age and better disease status at ETI initiation, supporting early intervention.
Publication - Lifespan Tree of Brain Anatomy: Diagnostic Values for Motor and Cognitive Neurodegenerative Diseases by Pierrick Coupé, Boris Mansencal, José V. Manjón, Patrice Péran, Wassilios G. Meissner, Thomas Tourdias, Vincent Planche, Human Brain Mapping