Using chest computed tomography and unsupervised machine learning for predicting and evaluating response to lumacaftor-ivacaftor in people with cystic fibrosis

Alienor Campredon^{1

2}, Enzo Battistella^{3

4}, Clémence Martin^{2

5

6}, Isabelle Durieu^{6

7

8}, Laurent Mely⁹, Christophe Marguet¹⁰, Chantal Belleguic¹¹, Marlène Murris-Espin¹², Raphaël Chiron¹³, Annlyse Fanton¹⁴, Stéphanie Bui¹⁵, Martine Reynaud-Gaubert¹⁶, Philippe Reix^{17

18}, Trieu-Nghi Hoang-Thi¹, Maria Vakalopoulou^{3

4}, Marie-Pierre Revel^{1

2}, Jennifer Da Silva^{5

19}, Pierre-Régis Burgel^{20

5

6}, Guillaume Chassagnon; Participating investigators in the French CF reference network study group:; Julie Mounard, Claire Poulet, Cinthia Rames Amiens, Christine Person, Françoise Troussier, Thierry Urban Angers, Marie-Laure Dalphin, Jean-Claude Dalphin, Didier Pernet, Bénédicte Richaud-Thiriez Besançon, Stéphanie Bui, Mickael Fayon, Julie Macey-Caro Bordeaux, Karine Campbell, Muriel Laurans Caen, Corinne Borderon, Marie-Christine Heraud, André Labbé, Sylvie Montcouquiol Clermont-Ferrand, Laurence Bassinet, Natascha Remus Créteil, Annlyse Fanton, Anne Houzel-Charavel, Frédéric Huet, Stéphanie Perez-Martin Dijon, Amale Boldron-Ghaddar, Manuela Scalbert Dunkerque, Laurent Mely Giens, Boubou Camara, Catherine Llerena, Isabelle Pin, Sébastien Quétant Grenoble, Aurélie Cottereau, Antoine Deschildre, Alice Gicquello, Thierry Perez, Lidwine Stervinou-Wemeau, Caroline Thumerelle, Benoit Wallaert, Nathalie Wizla Lille, Jane Languepin, Céline Ménétrey, Magalie Dupuy-Grasset Limoges, Lucie Bazus, Clelia Buchs, Virginie Jubin, Marie-Christine Werck-Gallois, Catherine Mainguy, Thomas Perrin, Philippe Reix, Agnès Toutain-Rigolet Lyon Pédiatrie, Isabelle Durieu, Stéphane Durupt, Quitterie Reynaud, Raphaele Nove-Josserand Lyon Adultes, Melisande Baravalle-Einaudi, Bérangère Coltey, Nadine Dufeu, Jean-Christophe Dubus, Nathalie Stremler Marseille, Davide Caimmi, Raphaël Chiron Montpellier, Yves Billon, Jocelyne Derelle, Sébastien Kieffer, Anne-Sophie Pichon, Cyril Schweitzer, Aurélie Tatopoulos Nancy, Sarah Abbes, Tiphaine Bihouée, Isabelle Danner-Boucher, Valérie David, Alain Haloun, Adrien Tissot Nantes, Sylvie Leroy, Carole Bailly-Piccini Nice, Annick Clément, Harriet Corvol, Aline Tamalet ParisTrousseau, Pierre-Régis Burgel, Isabelle Honoré, Dominique Hubert, Reem Kanaan, Clémence Martin Paris Cochin, Cécile Bailly, Frédérique Chédevergne, Jacques De Blic, Brigitte Fauroux, Murielle Le Bourgeois, Isabelle Sermet-Gaudelus Paris Necker, Bertrand Delaisi, Michèle Gérardin, Anne Munck ParisRobert Debré, Michel Abély, Bruno Ravoninjatovo Reims, Chantal Belleguic, Benoit Desrues, Graziella Brinchault Rennes, Michel Dagorne, Eric Deneuville, Sylvaine Lefeuvre Rennes-Saint Brieuc, Anne Dirou, Jean Le Bihan, Sophie Ramel Roscoff, Stéphane Dominique, Christophe Marguet Rouen, Annabelle Payet La Réunion, Romain Kessler, Michele Porzio, Vincent Rosner, Laurence Weiss Strasbourg, Sandra de Miranda, Dominique Grenet, Abdoul Hamid, Clément Picard Suresnes, François Brémont, Alain Didier, Géraldine Labouret, Marie Mittaine, Marlène Murris-Espin, Laurent Têtu Toulouse, Laure Cosson, Charlotte Giraut, Anne-Cécile Henriet, Julie Mankikian, Sophie Marchand Tours, Sandrine Hugé, Véronique Storni Vannes, Emmanuelle Coirier-Duet Versailles; French Cystic Fibrosis Reference Network Study Group

Affiliations

¹ Radiology Dept, Hôpital Cochin, AP-HP Centre Université de Paris, Paris, France.
² Université de Paris, Paris, France.
³ OPIS - OPtimisation Imagerie et Santé, Inria Saclay, Palaiseau, France.
⁴ MICS - Mathématiques et Informatique pour la Complexité et les Systèmes, CentraleSupelec, Gif-sur-Yvette, France.
⁵ Respiratory Medicine and Cystic Fibrosis National Reference Center, Cochin Hospital, AP-HP, Paris, France.
⁶ ERN-Lung CF Network, Frankfurt am Main, Germany.
⁷ Centre de Référence Adulte de la Mucoviscidose, Service de Médecine Interne, Hospices Civils de Lyon, Pierre Bénite, France.
⁸ Research on Healthcare Performance RESHAPE, Inserm U1290, Université Claude Bernard Lyon 1, Lyon, France.
⁹ Hôpital Renée Sabran, Cystic Fibrosis Center, Giens, France.
¹⁰ Pediatric Respiratory Disease and Cystic Fibrosis Center, Hospital UNIROUEN, Inserm EA 2656, Rouen University Hospital, Normandie Université, Rouen, France.
¹¹ Centre de Ressources et de Compétences de la Mucoviscidose Adulte, Centre Hospitalier Universitaire de Rennes, Rennes, France.
¹² Cystic Fibrosis Center, Service de Pneumologie, Pôle des Voies Respiratoires, Hôpital Larrey, CHU de Toulouse, Toulouse, France.
¹³ Cystic Fibrosis Center, Hôpital Arnaud de Villeneuve, Centre Hospitalier Universitaire de Montpellier, Montpellier, France.
¹⁴ Dept of Pulmonary Medicine, Cystic Fibrosis Resource and Competence Centre for Adults, Dijon University Hospital, Dijon, France.
¹⁵ Pediatric Respiratory Disease and Cystic Fibrosis Center and CIC 1401, CHU de Bordeaux, Bordeaux, France.
¹⁶ Dept of Respiratory Medicine and Lung Transplantation, Aix Marseille Universitaire, APHM, Hôpital Nord, Marseille, France.
¹⁷ UMR 5558 CNRS, Equipe EMET, Université Claude Bernard Lyon 1, Lyon, France.
¹⁸ Cystic Fibrosis Center, Hospices Civils de Lyon, Lyon, France.
¹⁹ URC-CIC Paris Descartes Necker Cochin, AP-HP, Hôpital Cochin, Paris, France.
²⁰ Université de Paris, Paris, France pierre-regis.burgel@aphp.fr.

PMID: 34795038
DOI: 10.1183/13993003.01344-2021

Using chest computed tomography and unsupervised machine learning for predicting and evaluating response to lumacaftor-ivacaftor in people with cystic fibrosis

Alienor Campredon et al. Eur Respir J. 2022.

. 2022 Jun 16;59(6):2101344.

doi: 10.1183/13993003.01344-2021. Print 2022 Jun.

Authors

Affiliations

¹ Radiology Dept, Hôpital Cochin, AP-HP Centre Université de Paris, Paris, France.
² Université de Paris, Paris, France.
³ OPIS - OPtimisation Imagerie et Santé, Inria Saclay, Palaiseau, France.
⁴ MICS - Mathématiques et Informatique pour la Complexité et les Systèmes, CentraleSupelec, Gif-sur-Yvette, France.
⁵ Respiratory Medicine and Cystic Fibrosis National Reference Center, Cochin Hospital, AP-HP, Paris, France.
⁶ ERN-Lung CF Network, Frankfurt am Main, Germany.
⁷ Centre de Référence Adulte de la Mucoviscidose, Service de Médecine Interne, Hospices Civils de Lyon, Pierre Bénite, France.
⁸ Research on Healthcare Performance RESHAPE, Inserm U1290, Université Claude Bernard Lyon 1, Lyon, France.
⁹ Hôpital Renée Sabran, Cystic Fibrosis Center, Giens, France.
¹⁰ Pediatric Respiratory Disease and Cystic Fibrosis Center, Hospital UNIROUEN, Inserm EA 2656, Rouen University Hospital, Normandie Université, Rouen, France.
¹¹ Centre de Ressources et de Compétences de la Mucoviscidose Adulte, Centre Hospitalier Universitaire de Rennes, Rennes, France.
¹² Cystic Fibrosis Center, Service de Pneumologie, Pôle des Voies Respiratoires, Hôpital Larrey, CHU de Toulouse, Toulouse, France.
¹³ Cystic Fibrosis Center, Hôpital Arnaud de Villeneuve, Centre Hospitalier Universitaire de Montpellier, Montpellier, France.
¹⁴ Dept of Pulmonary Medicine, Cystic Fibrosis Resource and Competence Centre for Adults, Dijon University Hospital, Dijon, France.
¹⁵ Pediatric Respiratory Disease and Cystic Fibrosis Center and CIC 1401, CHU de Bordeaux, Bordeaux, France.
¹⁶ Dept of Respiratory Medicine and Lung Transplantation, Aix Marseille Universitaire, APHM, Hôpital Nord, Marseille, France.
¹⁷ UMR 5558 CNRS, Equipe EMET, Université Claude Bernard Lyon 1, Lyon, France.
¹⁸ Cystic Fibrosis Center, Hospices Civils de Lyon, Lyon, France.
¹⁹ URC-CIC Paris Descartes Necker Cochin, AP-HP, Hôpital Cochin, Paris, France.
²⁰ Université de Paris, Paris, France pierre-regis.burgel@aphp.fr.

PMID: 34795038
DOI: 10.1183/13993003.01344-2021

Erratum in

"Using chest computed tomography and unsupervised machine learning for predicting and evaluating response to lumacaftor-ivacaftor in people with cystic fibrosis." A. Campredon, E. Battistella, C. Martin, et al. Eur Respir J 2022; 59: 2101344.
[No authors listed] [No authors listed] Eur Respir J. 2023 Mar 30;61(3):2151344. doi: 10.1183/13993003.51344-2021. Print 2023 Mar. Eur Respir J. 2023. PMID: 36997234 No abstract available.

Abstract

Objectives: Lumacaftor-ivacaftor is a cystic fibrosis transmembrane conductance regulator (CFTR) modulator known to improve clinical status in people with cystic fibrosis (CF). The aim of this study was to assess lung structural changes after 1 year of lumacaftor-ivacaftor treatment and to use unsupervised machine learning to identify morphological phenotypes of lung disease that are associated with response to lumacaftor-ivacaftor.

Methods: Adolescents and adults with CF from a French multicentre real-world prospective observational study evaluating the first year of treatment with lumacaftor-ivacaftor were included if they had pre-therapeutic and follow-up chest computed tomography (CT) scans available. CT scans were visually scored using a modified Bhalla score. A k-means clustering method was performed based on 120 radiomics features extracted from unenhanced pre-therapeutic chest CT scans.

Results: In total, 283 patients were included. The Bhalla score significantly decreased after 1 year of lumacaftor-ivacaftor (-1.40±1.53 points compared with pre-therapeutic CT, p<0.001). This finding was related to a significant decrease in mucus plugging (-0.58±0.88 points, p<0.001), bronchial wall thickening (-0.35±0.62 points, p<0.001) and parenchymal consolidations (-0.24±0.52 points, p<0.001). Cluster analysis identified three morphological clusters. Patients from cluster C were more likely to experience an increase in per cent predicted forced expiratory volume in 1 s (FEV₁ % pred) ≥5% under lumacaftor-ivacaftor than those in the other clusters (54% of responders versus 32% and 33%; p=0.02).

Conclusion: 1-year treatment with lumacaftor-ivacaftor was associated with a significant visual improvement of bronchial disease on chest CT. Radiomics features on pre-therapeutic CT scans may help to predict lung function response under lumacaftor-ivacaftor.

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Conflict of interest statement

Conflict of interest: A. Campredon has nothing to disclose. Conflict of interest: E. Battistella has nothing to disclose. Conflict of interest: C. Martin reports lecture payments or honoraria from Chiesi and Zambon, outside the submitted work. Conflict of interest: I. Durieu has nothing to disclose. Conflict of interest: L. Mely has nothing to disclose. Conflict of interest: C. Marguet reports consulting fees from Gleamer; lecture payments or honoraria from Vertex, Viatis and Zambon; support for attending meetings and/or travel from Zambon; and participation on a Data Safety Monitoring Board or Advisory Board for Zambon and Viatis; outside the submitted work. Conflict of interest: C. Belleguic has nothing to disclose. Conflict of interest: M. Murris-Espin has nothing to disclose. Conflict of interest: R. Chiron has nothing to disclose. Conflict of interest: A. Fanton has nothing to disclose. Conflict of interest: S. Bui reports payment for expert testimony for inhaled antibiotics for Zambon, outside the submitted work. Conflict of interest: M. Reynaud-Gaubert has nothing to disclose. Conflict of interest: P. Reix has nothing to disclose. Conflict of interest: T-N. Hoang-Thi has nothing to disclose. Conflict of interest: M. Vakalopoulou has nothing to disclose. Conflict of interest: M-P. Revel has nothing to disclose. Conflict of interest: J. Da Silva has nothing to disclose. Conflict of interest: P-R. Burgel reports grants or contracts from Vertex and GSK; consulting fees from AstraZeneca, Chiesi, GSK, Insmed, Vertex and Zambon; and lecture payments or honoraria from Pfizer and Novartis; outside the submitted work. Conflict of interest: G. Chassagnon reports lecture payments or honoraria from Chiesi, outside the submitted work.

Comment in

Radiomics-derived morphological features predict pulmonary function response during lumacaftor/ivacaftor therapy in patients with cystic fibrosis.
Zhang B, Zhang S. Zhang B, et al. Eur Respir J. 2022 Jul 7;60(1):2103077. doi: 10.1183/13993003.03077-2021. Print 2022 Jul. Eur Respir J. 2022. PMID: 35086826 No abstract available.
Diversity of approaches in artificial intelligence: an opportunity for discoveries in thoracic imaging.
Chassagnon G, Campredon A, Vakalopoulou M, Burgel PR. Chassagnon G, et al. Eur Respir J. 2022 Jul 7;60(1):2200022. doi: 10.1183/13993003.00022-2022. Print 2022 Jul. Eur Respir J. 2022. PMID: 35086838 No abstract available.

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Using chest computed tomography and unsupervised machine learning for predicting and evaluating response to lumacaftor-ivacaftor in people with cystic fibrosis

Affiliations

Using chest computed tomography and unsupervised machine learning for predicting and evaluating response to lumacaftor-ivacaftor in people with cystic fibrosis

Authors

Affiliations

Erratum in

Abstract

Conflict of interest statement

Comment in