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Kuhnert S, Halim N, Sommerlad J, Gall H, Yogeswaran A, Roller FC, Krombach G, Reichert M, Askevold I, Hecker A, Koch C, Seeger W, Mayer K, Weinheimer O, Hecker M. Automated CT Image Processing for the Diagnosis, Prediction, and Differentiation of Phenotypes in Chronic Lung Allograft Dysfunction After Lung Transplantation. Clin Transplant 2025; 39:e70137. [PMID: 40136064 DOI: 10.1111/ctr.70137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2025] [Revised: 02/18/2025] [Accepted: 03/11/2025] [Indexed: 03/27/2025]
Abstract
BACKGROUND Chronic lung allograft dysfunction (CLAD) after lung transplantation is a common complication with a poor prognosis. We assessed the utility of quantitative computed tomography (CT) for the diagnosis, prediction, and discrimination of CLAD phenotypes. METHODS We retrospectively analyzed routine inspiratory and expiratory CT scans from 78 patients at different time points after lung transplantation. Mean lung density (MLD), parametric response mapping (PRM), percentage of air trapping, and airway wall morphology parameters were calculated using the image processing software YACTA. Diagnostic and predictive utility was determined by receiver operating characteristic analysis and Pearson correlation. RESULTS Markers of air trapping showed promise for the diagnosis and prediction of bronchiolitis obliterans syndrome (BOS); for example, expiratory MLD showed areas under the curve (AUCs) of 0.905 for diagnosis and 0.729 for 1-year prediction. For diagnosis of CLAD with mixed phenotype, peripheral measurements (e.g., PRM of peripheral functional small airway disease: AUC 0.893) were most suitable. Markers of airway thickening (e.g., expiratory wall thickness at an inner perimeter of 10 mm: AUC 0.767) gave good diagnostic values for the undefined phenotype. CT biomarkers differed significantly among CLAD phenotypes. CONCLUSIONS Different CT biomarkers are suitable for the diagnosis of CLAD phenotypes, prediction of BOS, and differentiation of CLAD phenotypes.
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Affiliation(s)
- Stefan Kuhnert
- Department of Internal Medicine II, University Hospital Giessen and Marburg, Justus-Liebig-University Giessen, Giessen, Germany
- Department of Internal Medicine, Universities of Giessen and Marburg Lung Center (UGMLC), Institute for Lung Health (ILH), Member of the German Center for Lung Research (DZL), Giessen, Germany
| | - Nermin Halim
- Department of Internal Medicine II, University Hospital Giessen and Marburg, Justus-Liebig-University Giessen, Giessen, Germany
| | - Janine Sommerlad
- Department of Internal Medicine II, University Hospital Giessen and Marburg, Justus-Liebig-University Giessen, Giessen, Germany
| | - Henning Gall
- Department of Internal Medicine II, University Hospital Giessen and Marburg, Justus-Liebig-University Giessen, Giessen, Germany
- Department of Internal Medicine, Universities of Giessen and Marburg Lung Center (UGMLC), Institute for Lung Health (ILH), Member of the German Center for Lung Research (DZL), Giessen, Germany
| | - Athiththan Yogeswaran
- Department of Internal Medicine II, University Hospital Giessen and Marburg, Justus-Liebig-University Giessen, Giessen, Germany
- Department of Internal Medicine, Universities of Giessen and Marburg Lung Center (UGMLC), Institute for Lung Health (ILH), Member of the German Center for Lung Research (DZL), Giessen, Germany
| | - Fritz C Roller
- Department of Radiology, Justus-Liebig-University Giessen, Universities of Giessen and Marburg Lung Center (UGMLC), Giessen, Germany
| | - Gabriele Krombach
- Department of Radiology, Justus-Liebig-University Giessen, Universities of Giessen and Marburg Lung Center (UGMLC), Giessen, Germany
| | - Martin Reichert
- Department of General, Visceral, Thoracic and Transplant Surgery, University Hospital Giessen, Justus-Liebig-University Giessen, Giessen, Germany
| | - Ingolf Askevold
- Department of General, Visceral, Thoracic and Transplant Surgery, University Hospital Giessen, Justus-Liebig-University Giessen, Giessen, Germany
| | - Andreas Hecker
- Department of General, Visceral, Thoracic and Transplant Surgery, University Hospital Giessen, Justus-Liebig-University Giessen, Giessen, Germany
| | - Christian Koch
- Department of Anesthesiology, Operative Intensive Care and Pain Medicine, University Hospital Giessen and Marburg, Justus-Liebig-University Giessen, Giessen, Germany
| | - Werner Seeger
- Department of Internal Medicine II, University Hospital Giessen and Marburg, Justus-Liebig-University Giessen, Giessen, Germany
- Department of Internal Medicine, Universities of Giessen and Marburg Lung Center (UGMLC), Institute for Lung Health (ILH), Member of the German Center for Lung Research (DZL), Giessen, Germany
| | - Konstantin Mayer
- Department of Pulmonology and Sleep Medicine, ViDia Clinics, Karlsruhe, Germany
| | - Oliver Weinheimer
- Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany
| | - Matthias Hecker
- Department of Internal Medicine II, University Hospital Giessen and Marburg, Justus-Liebig-University Giessen, Giessen, Germany
- Department of Internal Medicine, Universities of Giessen and Marburg Lung Center (UGMLC), Institute for Lung Health (ILH), Member of the German Center for Lung Research (DZL), Giessen, Germany
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Coelho Sarmento Neto FA, Wada DT, Boas Machado CV, Baddini-Martinez J, Fabro AT, de Nadai TR, Koenigkam-Santos M. Automatic quantitative evaluation of high-resolution computed tomography scans of patients with interstitial lung diseases. Eur J Radiol 2025; 184:111988. [PMID: 39951842 DOI: 10.1016/j.ejrad.2025.111988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2024] [Revised: 02/04/2025] [Accepted: 02/05/2025] [Indexed: 02/16/2025]
Abstract
PURPOSE High-resolution computed tomography (HRCT) is essential in clinical evaluation and management of interstitial lung diseases (ILDs). Quantitative analysis can assist in both accurate diagnosis and longitudinal assessment. The aim was to verify the role of automatic quantitative analysis of HRCT images in the diagnosis and classification of ILD. METHODS Retrospective single-center study evaluating patients undergoing investigation for fibrosing ILD between 2010 and 2019. HRCT images were re-evaluated, ILD patterns were classified according to the 2018 ATS/ERS/JRS/ALAT consensus. Demographic and clinical variables, distribution of fibrosis and honeycombing pattern, and variables obtained from the quantitative analysis performed by YACTA scientific program were compared between ILD groups according to the 2018 ATS/ERS/JRS/ALAT consensus and to the radiological patterns of idiopathic interstitial pneumonia (IIP), using ANOVA, Kruskal-Wallis H test or Pearson's chi-squared test. RESULTS 481 patients (mean age 57.7 ± 14 years, 277 women, 204 men) were evaluated. Patients with radiological pattern of usual interstitial pneumonia (UIP) exhibited lower lung volumes, higher mean lung densities (UIP group, -698.8 ± 66.3; probable UIP group, -743.8 ± 47.9; alternative diagnosis to UIP, -712.7 ± 73.7; p = 0.01), and higher absolute vascular lung volumes. Among tomographic patterns of IIP, bronchiolocentric interstitial pneumonia demonstrated smaller lung volume and higher lung density. Collagen vascular disease was the most prevalent. CONCLUSION This study demonstrated that, in a large dataset of exams, the fully automated quantitative analysis of HRCTs is an objective method, which can help in the diagnostic workup of ILDs.
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Affiliation(s)
| | - Danilo Tadao Wada
- Center for Imaging Sciences and Medical Physics (CCIFM), Ribeirao Preto Medical School, University of Sao Paulo, Av Bandeirantes s/n, Ribeirão Preto, SP, Brazil.
| | - Camila Vilas Boas Machado
- Center for Imaging Sciences and Medical Physics (CCIFM), Ribeirao Preto Medical School, University of Sao Paulo, Av Bandeirantes s/n, Ribeirão Preto, SP, Brazil
| | - José Baddini-Martinez
- Discipline of Pulmonology, Escola Paulista de Medicina/UNIFESP, Rua Pedro de Toledo, 659, Vila Clementino, São Paulo, SP, Brazil.
| | - Alexandre Todorovic Fabro
- Department of Pathology and Forensic Medicine, Ribeirao Preto Medical School, University of São Paulo, Av Bandeirantes s/n, Ribeirão Preto, SP, Brazil.
| | - Tales Rubens de Nadai
- Bauru Medical School, University of São Paulo, Alameda Doutor Octávio Pinheiro Brisolla, 9-75, Bauru, SP 17012-901, Brazil.
| | - Marcel Koenigkam-Santos
- Bauru Medical School, University of São Paulo, Alameda Doutor Octávio Pinheiro Brisolla, 9-75, Bauru, SP 17012-901, Brazil.
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Biomarkers for Chronic Lung Allograft Dysfunction: Ready for Prime Time? Transplantation 2023; 107:341-350. [PMID: 35980878 PMCID: PMC9875844 DOI: 10.1097/tp.0000000000004270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Chronic lung allograft dysfunction (CLAD) remains a major hurdle impairing lung transplant outcome. Parallel to the better clinical identification and characterization of CLAD and CLAD phenotypes, there is an increasing urge to find adequate biomarkers that could assist in the earlier detection and differential diagnosis of CLAD phenotypes, as well as disease prognostication. The current status and state-of-the-art of biomarker research in CLAD will be discussed with a particular focus on radiological biomarkers or biomarkers found in peripheral tissue, bronchoalveolar lavage' and circulating blood' in which significant progress has been made over the last years. Ultimately, although a growing number of biomarkers are currently being embedded in the follow-up of lung transplant patients, it is clear that one size does not fit all. The future of biomarker research probably lies in the rigorous combination of clinical information with findings in tissue, bronchoalveolar lavage' or blood. Only by doing so, the ultimate goal of biomarker research can be achieved, which is the earlier identification of CLAD before its clinical manifestation. This is desperately needed to improve the prognosis of patients with CLAD after lung transplantation.
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Hoang-Thi TN, Chassagnon G, Hua-Huy T, Boussaud V, Dinh-Xuan AT, Revel MP. Chronic Lung Allograft Dysfunction Post Lung Transplantation: A Review of Computed Tomography Quantitative Methods for Detection and Follow-Up. J Clin Med 2021; 10:jcm10081608. [PMID: 33920108 PMCID: PMC8069908 DOI: 10.3390/jcm10081608] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 04/07/2021] [Accepted: 04/08/2021] [Indexed: 12/27/2022] Open
Abstract
Chronic lung allograft dysfunction (CLAD) remains the leading cause of morbidity and mortality after lung transplantation. The term encompasses both obstructive and restrictive phenotypes, as well as mixed and undefined phenotypes. Imaging, in addition to pulmonary function tests, plays a major role in identifying the CLAD phenotype and is essential for follow-up after lung transplantation. Quantitative imaging allows for the performing of reader-independent precise evaluation of CT examinations. In this review article, we will discuss the role of quantitative imaging methods for evaluating the airways and the lung parenchyma on computed tomography (CT) images, for an early identification of CLAD and for prognostic estimation. We will also discuss their limits and the need for novel approaches to predict, understand, and identify CLAD in its early stages.
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Affiliation(s)
- Trieu-Nghi Hoang-Thi
- AP-HP.Centre, Hôpital Cochin, Department of Radiology, Université de Paris, 75014 Paris, France; (T.-N.H.-T.); (G.C.)
- Department of Diagnostic Imaging, Vinmec Central Park Hospital, Ho Chi Minh City 70000, Vietnam
- AP-HP.Centre, Hôpital Cochin, Department of Respiratory Physiology, Université de Paris, 75014 Paris, France; (T.H.-H.); (A.-T.D.-X.)
| | - Guillaume Chassagnon
- AP-HP.Centre, Hôpital Cochin, Department of Radiology, Université de Paris, 75014 Paris, France; (T.-N.H.-T.); (G.C.)
| | - Thong Hua-Huy
- AP-HP.Centre, Hôpital Cochin, Department of Respiratory Physiology, Université de Paris, 75014 Paris, France; (T.H.-H.); (A.-T.D.-X.)
| | - Veronique Boussaud
- AP-HP.Centre, Hôpital Cochin, Department of Pneumology, Université de Paris, 75014 Paris, France;
| | - Anh-Tuan Dinh-Xuan
- AP-HP.Centre, Hôpital Cochin, Department of Respiratory Physiology, Université de Paris, 75014 Paris, France; (T.H.-H.); (A.-T.D.-X.)
| | - Marie-Pierre Revel
- AP-HP.Centre, Hôpital Cochin, Department of Radiology, Université de Paris, 75014 Paris, France; (T.-N.H.-T.); (G.C.)
- Correspondence: ; Tel.: +33-1-5841-2471
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