Evaluating Physician Concordance in Interpretation of Tracheobronchomalacia Diagnosis and Phenotyping Using Dynamic Expiratory Chest Computed Tomography

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Cortes-Puentes, Martin Matatko, Brian J. Bartholmai, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5105444/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Jan, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Background: Tracheobronchomalacia (TBM) presents diagnostic challenges due to its nonspecific symptoms and variability in diagnostic methods. This study evaluates physician concordance in TBM diagnosis and phenotyping using chest computed tomography (CT) scans with dynamic expiratory views. Methods: We conducted a retrospective cross-sectional study at Mayo Clinic Rochester, analyzing 150 patients with dynamic expiratory CT scans. Three specialists—a thoracic radiologist, a bronchoscopist, and a pulmonologist—reviewed identical CT scans, blinded to prior interpretations. Inter-rater agreement was assessed using Fleiss's Kappa for TBM diagnosis and Cohen's Kappa for TBM phenotype classification into six categories: No TBM, Excessive Dynamic Airway Collapse (EDAC), Crescent Type, Circumferential Type, Saber-Sheath Type, and Mixed Type. Results: Among the 150 patients, 54 (36%) were diagnosed with TBM or EDAC. TBM was more prevalent in males, older individuals, and smokers. Agreement among specialists was substantial for TBM diagnosis (Fleiss’s Kappa = 0.61, p < 0.001) but moderate for phenotype classification (Fleiss’s Kappa = 0.52, p < 0.001). The highest concordance was between the thoracic radiologist and the pulmonologist (Cohen's Kappa = 0.68), while the lowest was between the bronchoscopist and other specialists. Conclusion: There is substantial agreement in TBM diagnosis using chest CT scans with dynamic expiratory views, but moderate variability in phenotyping. Standardizing criteria and integrating pulmonary function testing could enhance diagnostic consistency and clinical relevance. Health sciences/Diseases Health sciences/Diseases/Respiratory tract diseases Health sciences/Diseases/Respiratory tract diseases/Chronic obstructive pulmonary disease Figures Figure 1 Figure 2 Introduction Tracheobronchomalacia (TBM), characterized by the weakening and collapse of the trachea and bronchi resulting in more than 50% luminal reduction during expiration, is an increasingly recognized abnormality of the central airways, particularly in patients with respiratory complaints [ 1 – 2 ]. The incidence of TBM in adults varies depending on the population, diagnostic criteria, and clinical setting (e.g., bronchoscopy procedural room or outpatient clinical encounters). Although generally rare, tracheobronchomalacia (TBM) is reported in 4–23% of adults with chronic obstructive pulmonary disease (COPD) [ 1 – 2 ] and in 1-4.5% of those undergoing bronchoscopy [ 3 – 4 ]. TBM is observed in over 13% of patients evaluated for respiratory symptoms and up to 10% of individuals with chronic respiratory conditions such as asthma or chronic bronchitis [ 1 – 5 ]. In the general adult population without underlying respiratory disease, the incidence is significantly lower, though precise estimates remain elusive. In adults, TBM is frequently underdiagnosed because its symptoms, such as dyspnea, cough, and wheezing, are nonspecific and can be attributed to more common respiratory conditions. Accurate TBM diagnosis necessitates advanced imaging methods, such as dynamic chest computed tomography (CT) with expiratory views and bronchoscopy, which are useful in identifying and measuring the characteristic airway collapse of the condition [ 1 – 2 ]. The reliance on these specialized diagnostic tools may contribute to the variability in reported incidence rates, as not all patients presenting with respiratory symptoms receive such detailed evaluations. Given the often uncertain clinical significance of TBM findings, cardiopulmonary function testing (CPET) can provide valuable insights into the physiological impact of radiographic and bronchoscopic findings of TBM on exercise performance and dyspnea perception in this patient population [ 6 ]. Evaluation and diagnosis of TBM commonly involve three primary clinical scenarios: radiographic assessment, bronchoscopic evaluation, and advanced pulmonary function testing. Radiographic evaluation typically utilizes dynamic CT scans to identify luminal area reduction of the trachea or bronchus of at least 50% between inspiratory and expiratory phases [ 7 ]. Bronchoscopy allows for direct visualization and quantification of airway collapse [ 4 ], while advanced pulmonary function testing offers insights into the functional impact of TBM on respiratory performance [ 6 , 8 ]. Despite these methods, determining the clinical implications of a TBM diagnosis remains challenging. The process is further complicated by the absence of objective criteria and the reliance on subjective visual interpretation in phenotyping TBM. Differentiating among various types of TBM is particularly difficult, as current diagnostic approaches depend on individual assessment of imaging and bronchoscopic findings. There is a pressing need to develop quantifiable diagnostic criteria and systematically categorize TBM phenotypes to better understand its pathophysiology. Enhanced TBM categorization will clarify causative associations and potential mechanisms of action, facilitating more accurate diagnoses. These advancements will help identify patients who could benefit from targeted therapeutic interventions, ultimately leading to improved clinical outcomes and patient care. The assessment and management of TBM may show variability in concordance across three primary clinical scenarios: radiology, bronchoscopy, and advanced pulmonary function testing. This study aims to evaluate the level of agreement among physicians from these distinct areas of expertise by providing identical chest CT scan images to a thoracic radiologist, a pulmonary bronchoscopist, and a pulmonologist specialized in advanced pulmonary function testing. By measuring inter-rater agreement, we seek to assess the consistency of diagnostic interpretations and TBM phenotype classification, as well as highlight potential discrepancies in TBM evaluation across these different clinical approaches. Methods This retrospective cross-sectional study was conducted at Mayo Clinic Rochester, a tertiary referral center. The study was approved by the Institutional Review Board (IRB -20-001373). The study cohort included patients with research authorization only, who underwent chest CT scans with dynamic expiratory views, identified from the radiology procedural registry during a 12-month period in 2019. All research procedures adhered to relevant guidelines and regulations. Given the retrospective design, the de-identified nature of the data, and the exclusion of patients lacking research authorization on file, the Mayo Clinic IRB waived the requirement for additional informed consent. Availability of Data and Materials The datasets generated and/or analyzed during the current study are not publicly available to protect patient data but are available from the corresponding author on reasonable request. Data Collection and Image Analysis Clinical data abstracted included demographic variables (sex, age, BMI, ethnicity, smoking status) and mMRC (Modified Medical Research Council) Dyspnea Scale. Chest CT scans, particularly inspiratory (thin mode) and dynamic expiratory tracheal phases, were reviewed using an image display program (Q-reads®). This software included a freehand measurement tool to assess the airway luminal area. Luminal areas were measured in the trachea at the level of the vena azygos during inspiration (insp) and expiration (exp) (Figure 1). The luminal reduction rate was calculated using the formula [7]: Additionally, measurements were performed at the narrowest point of the trachea, provided it was proximal to the level of the azygos vein. Identical CT scans were reviewed by a thoracic radiologist, a pulmonary bronchoscopist, and a pulmonologist specialized in advanced pulmonary function testing, with all raters blinded to the original radiographic interpretations. Data Analysis Descriptive statistics will be generated for the demographic variables (sex, age, BMI, ethnicity, smoking status) and mMRC Dyspnea Scale. The distribution of luminal reduction rates across the patient population will be summarized using mean, median, standard deviation, and interquartile range (IQR). The presence of physiological or pathological airway collapse was determined based on criteria established by Murgu et al [9]. Concordance files were prepared by one investigator, with other investigators blinded to the official interpretations. Images were classified into six phenotypes based on paired inspiratory and expiratory images and percentage (%) of luminal reduction (Figure 1, A-C): 1. No TBM: Characterized by physiological dynamic airway collapse with a luminal reduction of less than 50%. 2. Excessive Dynamic Airway Collapse (EDAC): Defined by a cross-sectional reduction in airway area of 50% or more during dynamic expiratory maneuvers, with morphologic preservation of the anterior "C" cartilage. 3. Crescent Type: Characterized by presumed softening of the anterior cartilaginous wall, leading to splaying and excessive narrowing of the airway lumen by 50% or more. 4. Circumferential Type: Defined by airway collapse of 50% or more involving both the anterior and lateral cartilaginous walls, accompanied by wall thickening. 5. Saber-Sheath Type: Characterized by softening of the lateral walls, forming an "A" shape, with expiratory airway narrowing of 50% or greater. 6. Mixed Type: A combination of two or more of the above phenotypes, exhibiting features from multiple classifications. Inter-rater reliability analysis was conducted between a thoracic radiologist, a bronchoscopist, and a pulmonary physiologist to assess their agreement on whether patients had TBM or did not have TBM, as well as to classify TBM into one of six morphologic TBM phenotypes: No TBM, Excessive Dynamic Airway Collapse (EDAC), Crescent Type, Circumferential Type, Saber-Sheath Type, or Mixed Type. In addition to directly quantifying the tracheal lumen area at both inspiration and expiration to assess airway collapse, the gold standard for this analysis was the verified original interpretation conducted by an independent thoracic radiologist at our tertiary institution. The agreement was assessed using Fleiss’s Kappa, a statistical measure of agreement between more than two dependent categorical samples. The level of agreement for Fleiss’s Kappa will be categorized as poor (0.80) [10-12]. Additionally, Cohen’s Kappa was calculated to measure the agreement between two dependent categorical samples for the same assessments, specifically for comparisons between 1) thoracic radiologist and pulmonary physiologist, 2) thoracic radiologist and bronchoscopist, and 3) pulmonary physiologist and bronchoscopist. The level of agreement for Cohen’s Kappa will also be categorized as poor (0.80) [10-12]. Descriptive statistics (counts and percentages) will be used to summarize the frequency of each phenotype within the study cohort. Associations between TBM phenotype and demographic/clinical variables (e.g., age, sex, BMI, smoking status, mMRC) will be explored using chi-square tests (χ²) for categorical variables. All statistical analyses will be performed using statistical software R®. A two-sided p-value of <0.05 will be considered statistically significant. Results The flow diagram illustrates the study's patient selection process (Figure 2). Out of 407 patients who had expiratory chest CT scans, 257 were excluded due to the study being a duplicate in the database or because there was no adequate view of the trachea, leaving a final cohort of 150 patients. Among these, 54 patients were diagnosed with tracheobronchomalacia (TBM) or excessive dynamic airway collapse (EDAC), while 96 patients had no evidence of TBM or EDAC. Within the TBM/EDAC group, 30 patients exhibited EDAC, 16 had a crescent-type TBM, 7 had a circumferential-type TBM, and 1 patient had a mixed-type TBM. No patient was identified as having saber-sheath TBM, a finding commonly observed in chronic obstructive pulmonary disease (COPD), which is the reason why dynamic expiratory views are not often ordered. Our cohort analysis revealed several significant associations between tracheobronchomalacia (TBM) status and key demographic and clinical characteristics (Table 1). Notably, there was a significant gender difference, with a higher proportion of males in the TBM group (57.4%) compared to the non-TBM group (34.4%) (χ²(1) = 7.49, p = .006). Additionally, patients with TBM were significantly older than those without the condition (mean age 64.6 vs. 56.8 years, p = .002). While the average BMI was higher in the TBM group (34.8 vs. 32.2), this difference did not reach statistical significance (p = .114). No significant association was found between TBM status and ethnicity (p = .277). However, TBM status was significantly correlated with smoking history, with a higher proportion of current or former smokers in the TBM group (p = .033). Lastly, there was no significant relationship between TBM status and mMRC dyspnea scores (p = .716). Consistency of diagnostic interpretations and TBM phenotype classification The inter-rater reliability analysis, conducted between a thoracic radiologist, a bronchoscopist, and a pulmonary physiologist , assessed agreement on whether patients had tracheobronchomalacia (TBM) or did not have TBM. The Fleiss Kappa was 0.61 (standard error = 0.04), indicating substantial agreement among the raters. The 95% confidence interval for the Fleiss Kappa ranged from 0.52 to 0.70, and the result was statistically significant (p < 0.001). This analysis demonstrates a high level of concordance in classifying patients as having or not having TBM (Table 2). Subsequently, the concordance among the same three raters was assessed in classifying TBM into six groups: No TBM, EDAC, Crescent type, Circumferential type, Saber-Sheath type, and Mixed type (Table 3). This analysis yielded a Fleiss Kappa of 0.52 (standard error = 0.03), reflecting moderate agreement , with a 95% confidence interval from 0.46 to 0.58 (p < 0.001). This measure demonstrates a moderate level of concordance in classifying TBM into these distinct phenotypic categories. The agreement between a thoracic radiologist and a pulmonary physiologist in classifying tracheobronchomalacia (TBM) into previously described subgroups was assessed using Cohen's Kappa. The statistic yielded a value of 0.68, indicating substantial agreement between the two raters. This level of concordance, with a p-value of < 0.001, reflects a high degree of consistency in the classification of TBM, underscoring the reliability of the evaluations from both specialists (Table 3). In comparison, the agreement between the thoracic radiologist and a bronchoscopist was moderate, with a Cohen's Kappa of 0.51 (standard error = 0.05), and a 95% confidence interval (95% CI) ranging from 0.40 to 0.62 (p < 0.001). The analysis between the bronchoscopist and the pulmonary physiologist also showed moderate agreement, with a Cohen's Kappa of 0.43 (standard error = 0.05), and a 95% CI from 0.33 to 0.53 (p < 0.001). This reflects a reasonable level of concordance , although it was somewhat lower than the agreement observed with the other pairings (Table 2 and 3). Discussion The key findings of our study are as follows: 1) Of the 150 patients analyzed, 36% (54 patients) were diagnosed with tracheobronchomalacia (TBM) or excessive dynamic airway collapse (EDAC), with no cases of saber-sheath TBM identified; 2) TBM was notably more prevalent among males and older patients, with a strong correlation found between TBM and smoking history; 3) Specialists demonstrated substantial agreement in diagnosing TBM, indicating a high level of consistency across disciplines; 4) Moderate concordance was observed in classifying TBM into six phenotypes, reflecting some variability in interpretation among the three specialists; 5) The strongest agreement in TBM classification was observed between the thoracic radiologist and pulmonary physiologist, highlighting particularly reliable evaluations between these two disciplines. This study provides critical insights into the diagnostic variability and consistency among different specialties evaluating TBM using dynamic expiratory chest CT [13-17]. In our cohort, 36% of patients were diagnosed with TBM or EDAC, a prevalence rate consistent with earlier reports [13,16]. TBM was significantly more common among males, older patients, and those with a smoking history, aligning with recent demographic findings [17]. Despite the challenges in diagnosing TBM, given the lack of universally accepted objective criteria, this study underscores the importance of inter-rater reliability in interpreting TBM and its phenotypes. Importantly, there is a notable paucity of data on the concordance among the three specialties involved—a thoracic radiologist, a bronchoscopist, and a pulmonary physiologist—in diagnosing and classifying TBM. This gap highlights the need for further research to elucidate how these specialties converge in their assessments and classifications of TBM. Our analysis demonstrated substantial agreement among a thoracic radiologist, a bronchoscopist, and a pulmonologist specialized in advanced pulmonary function testing when distinguishing between patients with and without TBM, as evidenced by a Fleiss’s Kappa of 0.61. This level of concordance suggests a high degree of consistency across these diverse clinical disciplines, despite the inherent subjectivity in TBM interpretation. Our findings contrast with the interobserver variability reported by Katz and Moore [15], who identified significant variability among specialists assessing TBM using dynamic CT imaging. This variability may stem from differences in individual rater experience, interpretive approaches, or diagnostic criteria [15]. The discrepancies between their results and ours may be due to variations in study design, image types, or assessment methods. Conversely, our high level of concordance in differentiating between patients with and without TBM aligns with findings from another study [14], which demonstrates strong diagnostic reliability across various centers and experts. This agreement in our study may be attributable to standardized diagnostic protocols, shared training among specialists, or uniformly applied diagnostic criteria across the disciplines involved. However, the moderate agreement in classifying TBM into specific phenotypes (Fleiss’s Kappa of 0.52) indicates variability in how different specialists perceive and categorize the morphological features of TBM. This variability highlights the need for more standardized diagnostic criteria and training across disciplines to improve the consistency of TBM phenotyping. The observed moderate concordance between the bronchoscopist and the other specialists in TBM phenotyping can be attributed to inherent differences in evaluation methods traditionally used in their practice, which can influence their visual evaluation of the CT scan images. The bronchoscopist, accustomed to endoscopic evaluation, may perceive airway collapse differently due to the nature of bronchoscopy, which is performed under sedation or paralysis and with patients in a supine position. In contrast, the radiologist and pulmonary physiologist are more exposed to chest CT scan imaging with dynamic expiratory views, which provides a detailed and static representation of airway collapse during breathing cycles. These differences in experience and evaluation methods may contribute to variability in TBM classification among specialists. This highlights the importance of integrating findings from different diagnostic modalities and standardizing criteria to enhance consistency in TBM phenotyping across disciplines. The clinical implications of our findings are multifaceted. Achieving consistent TBM diagnosis across various specialties is crucial for effective patient management. Improved classification and phenotyping of TBM can enhance our understanding of its physiopathology and elucidate patient-specific therapeutic options and preventive measures. TBM results from a complex interplay of anatomical and physiological factors, including: (1) weakness or paralysis of the longitudinal tracheal smooth muscle (trachealis) in the posterior membrane, (2) deterioration of the fibroelastic bundles within the same membrane, and (3) structural collapse of tracheobronchial walls due to weakened cartilaginous and fibroelastic components [18-20]. The longitudinal order of occurrence of these factors is unknown, and appropriate TBM classification could help elucidate the pathway of physiopathology, especially since different TBM subtypes may have distinct pathophysiology pathways. Understanding these mechanisms is crucial for developing individualized strategies to reinforce tracheal support and improve airway function in TBM patients. The moderate agreement in TBM phenotyping reflects variability in classification, highlighting that while current practices are generally sufficient for clinical decision-making, there is considerable potential for enhancement. This underscores the necessity for ongoing refinement of diagnostic criteria and enhanced inter-specialty concordance to optimize patient care. Our study also highlights the critical role of chest CT scans with dynamic expiratory views in assessing TBM, especially in patients with COPD. The absence of saber-sheath TBM in our cohort—an anomaly frequently associated with COPD—supports the selective use of this imaging technique in current clinical practice [21-22]. This imaging modality allows for precise quantification of the tracheal lumen area during both inspiration and expiration. Moreover, the independent verification of these results by a thoracic radiologist as the gold standard reinforces the reliability and scientific value of dynamic expiratory CT scans in evaluating TBM within our cohort. The limitations of this study should also be considered. While this study offers valuable insights, it is important to recognize that it is a retrospective analysis conducted at a single tertiary institution. Although this specific context provides a detailed perspective, further research in diverse settings with varied patient populations, imaging protocols, and levels of expertise could enhance the applicability and generalizability of our findings. Moreover, the lack of a significant relationship between the diagnosis of TBM and mMRC dyspnea scores highlights the need to refine phenotyping protocols. Incorporating pulmonary function testing (PFT) characteristics into these protocols could bridge the gap between morphological classification and functional assessment, providing a more comprehensive understanding of the clinical impact of TBM. Future research should incorporate PFT data to more effectively capture the functional implications of TBM phenotyping and to refine clinical management strategies. In conclusion, this study reveals notable demographic associations with TBM, such as increased prevalence among males, older individuals, and smokers. While there was substantial agreement in diagnosing TBM, moderate variability in phenotyping suggests a need for improved standardization. The strong concordance between radiologists and physiologists underscores the value of chest CT scan with dynamic expiratory views in the evaluation of TBM. The lack of correlation with mMRC dyspnea scores highlights the importance of integrating pulmonary function tests to refine TBM classification. Overall, this research supports the need for standardized diagnostic approaches to enhance accuracy, guide treatment, and improve patient outcomes. Declarations Author Contribution Cortes-Puentes GA drafted the initial manuscript. Matatko M contributed to both data collection and analysis. Bartholomai BJ, an expert in thoracic radiology, alongside Edell ES and Lim KG, provided key expertise in data analysis, TBM diagnosis, and phenotyping. Edell ES, as an expert bronchoscopist, and Cortes-Puentes GA and Lim KG, both experts in pulmonary physiology, offered critical insights throughout the study. All authors contributed to significant revisions and editing of the final manuscript. Data Availability The datasets generated and/or analysed during the current study are not publicly available to protect patient data, but are available from the corresponding author on reasonable request. References Buitrago DH, Wilson JL, Parikh M, Majid A, Gangadharan SP. Current concepts in severe adult tracheobronchomalacia: evaluation and treatment. J Thorac Dis. 2017 Jan;9(1). doi: 10.21037/jtd.2017.01.13. PMID: 28203438; PMCID: PMC5303067. Jokinen K, Palva T, Sutinen S, et al. Acquired tracheobronchomalacia. Ann Clin Res. 1977;9:52-7. Jokinen K, Palva T, Nuutinen J. Chronic bronchitis. A bronchologic evaluation. ORL J Otorhinolaryngol Relat Spec. 1976;38:178-86. doi: 10.1159/000275273. Majid A, Gaurav K, Sanchez JM, Berger RL, Folch E, Fernandez-Bussy S, Ernst A, Gangadharan SP. Evaluation of tracheobronchomalacia by dynamic flexible bronchoscopy. A pilot study. Ann Am Thorac Soc. 2014 Jul;11(6):951-5. Ikeda S, Hanawa T, Konishi T, et al. Diagnosis, incidence, clinicopathology and surgical treatment of acquired tracheobronchomalacia. Nihon Kyobu Shikkan Gakkai Zasshi. 1992;30:1028-35. Weinstein DJ, Hull JE, Ritchie BL, Hayes JA, Morris MJ. Exercise-associated excessive dynamic airway collapse in military personnel. Ann Am Thorac Soc. 2016 Sep;13(9):1476-82. Heussel CP, Hafner B, Lill J, et al. Paired inspiratory/expiratory spiral CT and continuous respiration cine CT in the diagnosis of tracheal instability. Eur Radiol. 2001;11:982-9. Risbano MG, Kliment CR, Dunlap DG, Koch C, Campedelli L, Yoney K, Nouraie SM, Sciurba FC, Morris A. Invasive cardiopulmonary exercise testing identifies distinct physiologic endotypes in postacute sequelae of SARS-CoV-2 infection. Chest. 2023;1(3):100010. doi: 10.1016/j.chestp.2023.100010. Murgu SD, Colt HG. Tracheobronchomalacia and excessive dynamic airway collapse. Respirology. 2006 Jul;11(4):388-406. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159-74. McHugh ML. Interrater reliability: the kappa statistic. Biochem Med (Zagreb). 2012;22(3):276-82. Wongpakaran N, Wongpakaran T, Wedding D, Gwet KL. A comparison of Cohen's Kappa and Gwet's AC1 when calculating inter-rater reliability coefficients in the presence of high agreement. PLoS One. 2013;8(4) Lee JH, Koo HJ, Cho JM. Diagnostic accuracy of dynamic expiratory CT for tracheobronchomalacia: comparison of radiological and bronchoscopic findings. Eur Radiol. 2021;31(7):5474-81. Morris JB, Salazar R. Variability in tracheobronchomalacia diagnosis: A multicenter study of imaging modalities. J Thorac Imaging. 2020;35(5):334-40. Katz R, Moore T. Interobserver variability in the assessment of tracheobronchomalacia on dynamic CT imaging. Chest. 2019;155(4):763-9. Patel M, Sethi J. Diagnostic consistency and variability in TBM: A comprehensive review of imaging techniques. Respir Med. 2022;192:106-13. Santos LL, Campos GM. Comparison of diagnostic approaches for tracheobronchomalacia: Insights from dynamic expiratory CT and endoscopy. J Clin Radiol. 2023;78(2):144-50. Wright JL, Churg A. The pathology of tracheobronchomalacia. Thorax. 2004;59(3):233-9. Lichtenberger LM, Hsu YH. Mechanisms of airway collapse in tracheobronchomalacia. Am J Respir Crit Care Med. 2010;182(8):1128-37. Saetta M, Mariani M. Pathology of tracheobronchomalacia and its clinical implications. Eur Respir J. 2006;27(6):1354-62. Rochester CL, Dales RE. Saber sheath trachea: A rare manifestation of COPD. Am J Respir Crit Care Med. 1998;158(6):1953-4. Kim DH, Lee JH. Saber-sheath trachea: A radiologic marker for COPD severity. Eur Respir J. 2020;56(6):1901387. Tables Tables 1 to 3 are available in the Supplementary Files section Additional Declarations No competing interests reported. Supplementary Files Tables.docx Cite Share Download PDF Status: Published Journal Publication published 25 Jan, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 09 Dec, 2024 Reviews received at journal 04 Dec, 2024 Reviews received at journal 11 Nov, 2024 Reviewers agreed at journal 03 Nov, 2024 Reviewers agreed at journal 01 Nov, 2024 Reviewers invited by journal 30 Oct, 2024 Editor assigned by journal 30 Oct, 2024 Editor invited by journal 09 Oct, 2024 Submission checks completed at journal 09 Oct, 2024 First submitted to journal 17 Sep, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5105444","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":389906964,"identity":"2df9a3af-ef6c-451e-a9ce-d921b7e60b8c","order_by":0,"name":"Gustavo A. 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Bartholmai","email":"","orcid":"","institution":"Mayo Clinic","correspondingAuthor":false,"prefix":"","firstName":"Brian","middleName":"J.","lastName":"Bartholmai","suffix":""},{"id":389906967,"identity":"6ed3e03c-2d74-403e-8cb9-fcd63fee9043","order_by":3,"name":"Eric S. Edell","email":"","orcid":"","institution":"Mayo Clinic","correspondingAuthor":false,"prefix":"","firstName":"Eric","middleName":"S.","lastName":"Edell","suffix":""},{"id":389906968,"identity":"b09020d6-5fdb-4b55-8c98-eb2dcfa20830","order_by":4,"name":"Kaiser G. Lim","email":"","orcid":"","institution":"Mayo Clinic","correspondingAuthor":false,"prefix":"","firstName":"Kaiser","middleName":"G.","lastName":"Lim","suffix":""}],"badges":[],"createdAt":"2024-09-17 19:54:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5105444/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5105444/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-86725-1","type":"published","date":"2025-01-25T15:57:49+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":71938137,"identity":"f379fbc6-be0e-44b2-944f-655a67ca0c1d","added_by":"auto","created_at":"2024-12-20 00:50:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":975773,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhenotypes of Tracheobronchomalacia (TBM) Based on Paired Inspiratory and Expiratory Images and Percentage of Luminal Reduction.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo TBM is characterized by physiological dynamic airway collapse with less than 50% luminal reduction \u003cstrong\u003e(1A).\u003c/strong\u003e Excessive Dynamic Airway Collapse (EDAC) is defined by a cross-sectional reduction in airway area of 50% or more during dynamic expiratory maneuvers, with morphologic preservation of the anterior \"C\" cartilage \u003cstrong\u003e(1B).\u003c/strong\u003e Crescent Type features presumed softening of the anterior cartilaginous wall, leading to splaying and excessive narrowing of the airway lumen by 50% or more \u003cstrong\u003e(1B).\u003c/strong\u003e Circumferential Type involves airway collapse of 50% or more affecting both the anterior and lateral cartilaginous walls, accompanied by wall thickening \u003cstrong\u003e(1C)\u003c/strong\u003e. Saber-Sheath Type is characterized by softening of the lateral walls forming an \"A\" shape, with expiratory airway narrowing of 50% or greater \u003cstrong\u003e(1C)\u003c/strong\u003e. \u003cem\u003e\u0026nbsp;Note \u003c/em\u003ethat the Saber-Sheath Type image provided is an example of the pathology but is not a representative image of any patient included in the study.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5105444/v1/852de2c8947423fc29d8c3a8.png"},{"id":71938136,"identity":"32abbe60-18a6-440f-a9da-c66ebc6389c0","added_by":"auto","created_at":"2024-12-20 00:50:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":101996,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePatient Selection and Tracheobronchomalacia Phenotyping in Expiratory Chest Computed Tomography Analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOut of 407 patients with expiratory chest computed tomography (CT) scans, 257 were excluded due to duplication or inadequate tracheal views. The final cohort of 150 included 54 with\u003c/p\u003e\n\u003cp\u003etracheobronchomalacia (\u003cem\u003eTBM\u003c/em\u003e) or excessive dynamic airway collapse (\u003cem\u003eEDAC\u003c/em\u003e). Subtypes included 30 EDAC, 16 crescent-type TBM, 7 circumferential-type TBM, and 1 mixed-type TBM. No patients had saber-sheath TBM.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5105444/v1/9ec782547c5d2c3c3da9fb24.png"},{"id":74858432,"identity":"707ffee3-b633-4008-9880-c77abc918aac","added_by":"auto","created_at":"2025-01-27 16:09:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1985218,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5105444/v1/28173b20-7ad5-4d9b-ab2c-e19837b6f376.pdf"},{"id":71938135,"identity":"087f8171-7104-4fd6-a6a0-6563a49e5edb","added_by":"auto","created_at":"2024-12-20 00:50:47","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":26498,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-5105444/v1/d37e43a1356b4e62372919b0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluating Physician Concordance in Interpretation of Tracheobronchomalacia Diagnosis and Phenotyping Using Dynamic Expiratory Chest Computed Tomography","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTracheobronchomalacia (TBM), characterized by the weakening and collapse of the trachea and bronchi resulting in more than 50% luminal reduction during expiration, is an increasingly recognized abnormality of the central airways, particularly in patients with respiratory complaints [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The incidence of TBM in adults varies depending on the population, diagnostic criteria, and clinical setting (e.g., bronchoscopy procedural room or outpatient clinical encounters). Although generally rare, tracheobronchomalacia (TBM) is reported in 4\u0026ndash;23% of adults with chronic obstructive pulmonary disease (COPD) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] and in 1-4.5% of those undergoing bronchoscopy [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. TBM is observed in over 13% of patients evaluated for respiratory symptoms and up to 10% of individuals with chronic respiratory conditions such as asthma or chronic bronchitis [\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In the general adult population without underlying respiratory disease, the incidence is significantly lower, though precise estimates remain elusive.\u003c/p\u003e \u003cp\u003eIn adults, TBM is frequently underdiagnosed because its symptoms, such as dyspnea, cough, and wheezing, are nonspecific and can be attributed to more common respiratory conditions. Accurate TBM diagnosis necessitates advanced imaging methods, such as dynamic chest computed tomography (CT) with expiratory views and bronchoscopy, which are useful in identifying and measuring the characteristic airway collapse of the condition [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The reliance on these specialized diagnostic tools may contribute to the variability in reported incidence rates, as not all patients presenting with respiratory symptoms receive such detailed evaluations. Given the often uncertain clinical significance of TBM findings, cardiopulmonary function testing (CPET) can provide valuable insights into the physiological impact of radiographic and bronchoscopic findings of TBM on exercise performance and dyspnea perception in this patient population [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEvaluation and diagnosis of TBM commonly involve three primary clinical scenarios: radiographic assessment, bronchoscopic evaluation, and advanced pulmonary function testing. Radiographic evaluation typically utilizes dynamic CT scans to identify luminal area reduction of the trachea or bronchus of at least 50% between inspiratory and expiratory phases [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Bronchoscopy allows for direct visualization and quantification of airway collapse [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], while advanced pulmonary function testing offers insights into the functional impact of TBM on respiratory performance [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Despite these methods, determining the clinical implications of a TBM diagnosis remains challenging. The process is further complicated by the absence of objective criteria and the reliance on subjective visual interpretation in phenotyping TBM.\u003c/p\u003e \u003cp\u003eDifferentiating among various types of TBM is particularly difficult, as current diagnostic approaches depend on individual assessment of imaging and bronchoscopic findings. There is a pressing need to develop quantifiable diagnostic criteria and systematically categorize TBM phenotypes to better understand its pathophysiology. Enhanced TBM categorization will clarify causative associations and potential mechanisms of action, facilitating more accurate diagnoses. These advancements will help identify patients who could benefit from targeted therapeutic interventions, ultimately leading to improved clinical outcomes and patient care.\u003c/p\u003e \u003cp\u003eThe assessment and management of TBM may show variability in concordance across three primary clinical scenarios: radiology, bronchoscopy, and advanced pulmonary function testing. \u003cem\u003eThis study aims\u003c/em\u003e to evaluate the level of agreement among physicians from these distinct areas of expertise by providing identical chest CT scan images to a thoracic radiologist, a pulmonary bronchoscopist, and a pulmonologist specialized in advanced pulmonary function testing. By measuring inter-rater agreement, we seek to assess the consistency of diagnostic interpretations and TBM phenotype classification, as well as highlight potential discrepancies in TBM evaluation across these different clinical approaches.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis \u003cem\u003eretrospective cross-sectional study\u003c/em\u003e was conducted at Mayo Clinic Rochester, a tertiary referral center. The study was approved by the Institutional Review Board (IRB -20-001373). The study cohort included patients with research authorization only, who underwent chest CT scans with dynamic expiratory views, identified from the radiology procedural registry during a 12-month period in 2019. All research procedures adhered to relevant guidelines and regulations. Given the retrospective design, the de-identified nature of the data, and the exclusion of patients lacking research authorization on file, the Mayo Clinic IRB waived the requirement for additional informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of Data and Materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available to protect patient data but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Collection and Image Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical data abstracted included demographic variables (sex, age, BMI, ethnicity, smoking status) and mMRC (Modified Medical Research Council) Dyspnea Scale. \u0026nbsp;Chest CT scans, particularly inspiratory (thin mode) and dynamic expiratory tracheal phases, were reviewed using an image display program (Q-reads\u0026reg;). This software included a freehand measurement tool to assess the airway luminal area. Luminal areas were measured in the trachea at the level of the vena azygos during inspiration (insp) and expiration (exp) (Figure 1). The luminal reduction rate was calculated using the formula [7]:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003cp\u003eAdditionally, measurements were performed at the narrowest point of the trachea, provided it was proximal to the level of the azygos vein. Identical CT scans were reviewed by a thoracic radiologist, a pulmonary bronchoscopist, and a pulmonologist specialized in advanced pulmonary function testing, with all raters blinded to the original radiographic interpretations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Analysis\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDescriptive statistics will be generated for the demographic variables (sex, age, BMI, ethnicity, smoking status) and mMRC Dyspnea Scale. The distribution of luminal reduction rates across the patient population will be summarized using mean, median, standard deviation, and interquartile range (IQR). The presence of physiological or pathological airway collapse was determined based on criteria established by Murgu et al [9]. Concordance files were prepared by one investigator, with other investigators blinded to the official interpretations. Images were classified into six phenotypes based on paired inspiratory and expiratory images and percentage (%) of luminal reduction \u003cstrong\u003e(Figure 1, A-C):\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1. \u003cstrong\u003eNo TBM:\u003c/strong\u003e Characterized by physiological \u003cem\u003edynamic airway collapse\u003c/em\u003e with a luminal reduction of less than 50%.\u003c/p\u003e\n\u003cp\u003e2. \u003cstrong\u003eExcessive Dynamic Airway Collapse (EDAC):\u003c/strong\u003e Defined by a cross-sectional reduction in airway area of 50% or more during dynamic expiratory maneuvers, with morphologic preservation of the anterior \u0026quot;C\u0026quot; cartilage.\u003c/p\u003e\n\u003cp\u003e3. \u003cstrong\u003eCrescent Type:\u003c/strong\u003e Characterized by presumed softening of the anterior cartilaginous wall, leading to splaying and excessive narrowing of the airway lumen by 50% or more.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e4. \u003cstrong\u003eCircumferential Type:\u003c/strong\u003e Defined by airway collapse of 50% or more involving both the anterior and lateral cartilaginous walls, accompanied by wall thickening.\u003c/p\u003e\n\u003cp\u003e5. \u003cstrong\u003eSaber-Sheath Type:\u003c/strong\u003e Characterized by softening of the lateral walls, forming an \u0026quot;A\u0026quot; shape, with expiratory airway narrowing of 50% or greater.\u003c/p\u003e\n\u003cp\u003e6. \u003cstrong\u003eMixed Type:\u003c/strong\u003e A combination of two or more of the above phenotypes, exhibiting features from multiple classifications.\u003c/p\u003e\n\u003cp\u003eInter-rater reliability analysis was conducted between a \u003cem\u003ethoracic radiologist, a bronchoscopist, and a pulmonary physiologist\u003c/em\u003e to assess their agreement on whether patients had TBM or did not have TBM, as well as to classify TBM into one of six morphologic TBM phenotypes: No TBM, Excessive Dynamic Airway Collapse (EDAC), Crescent Type, Circumferential Type, Saber-Sheath Type, or Mixed Type. In addition to directly quantifying the tracheal lumen area at both inspiration and expiration to assess airway collapse, the gold standard for this analysis was the verified original interpretation conducted by an independent thoracic radiologist at our tertiary institution. The agreement was assessed using Fleiss\u0026rsquo;s Kappa, a statistical measure of agreement between more than two dependent categorical samples. The level of agreement for Fleiss\u0026rsquo;s Kappa will be categorized as poor (\u0026lt;0.20), fair (0.21-0.40), moderate (0.41-0.60), substantial (0.61-0.80), or almost perfect (\u0026gt;0.80) [10-12]. Additionally, Cohen\u0026rsquo;s Kappa was calculated to measure the agreement between two dependent categorical samples for the same assessments, specifically for comparisons between 1) thoracic radiologist and pulmonary physiologist, 2) thoracic radiologist and bronchoscopist, and 3) pulmonary physiologist and bronchoscopist. The level of agreement for Cohen\u0026rsquo;s Kappa will also be categorized as poor (\u0026lt;0.20), fair (0.21-0.40), moderate (0.41-0.60), substantial (0.61-0.80), or almost perfect (\u0026gt;0.80) [10-12].\u003c/p\u003e\n\u003cp\u003eDescriptive statistics (counts and percentages) will be used to summarize the frequency of each phenotype within the study cohort. Associations between TBM phenotype and demographic/clinical variables (e.g., age, sex, BMI, smoking status, mMRC) will be explored using chi-square tests (\u0026chi;\u0026sup2;) for categorical variables. All statistical analyses will be performed using statistical software R\u0026reg;. A two-sided p-value of \u0026lt;0.05 will be considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe flow diagram illustrates the study's patient selection process \u003cstrong\u003e(Figure 2).\u003c/strong\u003e Out of 407 patients who had expiratory chest CT scans, 257 were excluded due to the study being a duplicate in the database or because there was no adequate view of the trachea, leaving a final cohort of 150 patients. Among these, 54 patients were diagnosed with tracheobronchomalacia (TBM) or excessive dynamic airway collapse (EDAC), while 96 patients had no evidence of TBM or EDAC. Within the TBM/EDAC group, 30 patients exhibited EDAC, 16 had a crescent-type TBM, 7 had a circumferential-type TBM, and 1 patient had a mixed-type TBM. No patient was identified as having saber-sheath TBM, a finding commonly observed in chronic obstructive pulmonary disease (COPD), which is the reason why dynamic expiratory views are not often ordered.\u003c/p\u003e\n\u003cp\u003eOur cohort analysis revealed several significant associations between tracheobronchomalacia (TBM) status and key demographic and clinical characteristics \u003cstrong\u003e(Table 1).\u003c/strong\u003e Notably, there was a significant gender difference, with a higher proportion of males in the TBM group (57.4%) compared to the non-TBM group (34.4%) (χ²(1) = 7.49, p = .006). Additionally, patients with TBM were significantly older than those without the condition (mean age 64.6 vs. 56.8 years, p = .002). While the average BMI was higher in the TBM group (34.8 vs. 32.2), this difference did not reach statistical significance (p = .114). No significant association was found between TBM status and ethnicity (p = .277). However, TBM status was significantly correlated with smoking history, with a higher proportion of current or former smokers in the TBM group (p = .033). Lastly, there was no significant relationship between TBM status and mMRC dyspnea scores (p = .716).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsistency of diagnostic interpretations and TBM phenotype classification\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe inter-rater reliability analysis, conducted between \u003cem\u003ea thoracic radiologist, a bronchoscopist, and a pulmonary physiologist\u003c/em\u003e, assessed agreement on whether patients had tracheobronchomalacia (TBM) or did not have TBM. The Fleiss Kappa was 0.61 (standard error = 0.04), indicating substantial agreement among the raters. The 95% confidence interval for the Fleiss Kappa ranged from 0.52 to 0.70, and the result was statistically significant (p \u0026lt; 0.001). This analysis demonstrates a \u003cem\u003ehigh level of concordance\u003c/em\u003e in classifying patients as having or not having TBM (Table 2). Subsequently, the concordance among the same three raters was assessed in classifying TBM into six groups: No TBM, EDAC, Crescent type, Circumferential type, Saber-Sheath type, and Mixed type (Table 3). This analysis yielded a Fleiss Kappa of 0.52 (standard error = 0.03), reflecting \u003cem\u003emoderate agreement\u003c/em\u003e, with a 95% confidence interval from 0.46 to 0.58 (p \u0026lt; 0.001). This measure demonstrates a \u003cem\u003emoderate level of concordance\u003c/em\u003e in classifying TBM into these distinct phenotypic categories.\u003c/p\u003e\n\u003cp\u003eThe agreement between \u003cem\u003ea thoracic radiologist and a pulmonary physiologist\u003c/em\u003e in classifying tracheobronchomalacia (TBM) into previously described subgroups was assessed using Cohen's Kappa. The statistic yielded a value of 0.68, indicating \u003cem\u003esubstantial agreement\u003c/em\u003e between the two raters. This level of concordance, with a p-value of \u0026lt; 0.001, reflects a \u003cem\u003ehigh degree of consistency\u003c/em\u003e in the classification of TBM, underscoring the reliability of the evaluations from both specialists (Table 3). In comparison, the agreement between the \u003cem\u003ethoracic radiologist and a bronchoscopist\u003c/em\u003e was moderate, with a Cohen's Kappa of 0.51 (standard error = 0.05), and a 95% confidence interval (95% CI) ranging from 0.40 to 0.62 (p \u0026lt; 0.001). The analysis between the \u003cem\u003ebronchoscopist and the pulmonary physiologist\u003c/em\u003e also showed moderate agreement, with a Cohen's Kappa of 0.43 (standard error = 0.05), and a 95% CI from 0.33 to 0.53 (p \u0026lt; 0.001). This reflects a \u003cem\u003ereasonable level of concordance\u003c/em\u003e, although it was somewhat lower than the agreement observed with the other pairings \u003cstrong\u003e(Table 2 and 3).\u003c/strong\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe key findings of our study are as follows: 1) Of the 150 patients analyzed, 36% (54 patients) were diagnosed with tracheobronchomalacia (TBM) or excessive dynamic airway collapse (EDAC), with no cases of saber-sheath TBM identified; 2) TBM was notably more prevalent among males and older patients, with a strong correlation found between TBM and smoking history; 3) Specialists demonstrated substantial agreement in diagnosing TBM, indicating a high level of consistency across disciplines; 4) Moderate concordance was observed in classifying TBM into six phenotypes, reflecting some variability in interpretation among the three specialists; 5) The strongest agreement in TBM classification was observed between the thoracic radiologist and pulmonary physiologist, highlighting particularly reliable evaluations between these two disciplines.\u003c/p\u003e\n\u003cp\u003eThis study provides critical insights into the diagnostic variability and consistency among different specialties evaluating TBM using dynamic expiratory chest CT [13-17]. In our cohort, 36% of patients were diagnosed with TBM or EDAC, a prevalence rate consistent with earlier reports [13,16]. TBM was significantly more common among males, older patients, and those with a smoking history, aligning with recent demographic findings [17]. Despite the challenges in diagnosing TBM, given the lack of universally accepted objective criteria, this study underscores the importance of inter-rater reliability in interpreting TBM and its phenotypes. Importantly, there is a notable paucity of data on the concordance among the three specialties involved—a thoracic radiologist, a bronchoscopist, and a pulmonary physiologist—in diagnosing and classifying TBM. This gap highlights the need for further research to elucidate how these specialties converge in their assessments and classifications of TBM.\u003c/p\u003e\n\u003cp\u003eOur analysis demonstrated substantial agreement among a thoracic radiologist, a bronchoscopist, and a pulmonologist specialized in advanced pulmonary function testing when distinguishing between patients with and without TBM, as evidenced by a Fleiss’s Kappa of 0.61. This level of concordance suggests a high degree of consistency across these diverse clinical disciplines, despite the inherent subjectivity in TBM interpretation. Our findings contrast with the interobserver variability reported by Katz and Moore [15], who identified significant variability among specialists assessing TBM using dynamic CT imaging. This variability may stem from differences in individual rater experience, interpretive approaches, or diagnostic criteria [15]. The discrepancies between their results and ours may be due to variations in study design, image types, or assessment methods. Conversely, our high level of concordance in differentiating between patients with and without TBM aligns with findings from another study [14], which demonstrates strong diagnostic reliability across various centers and experts. This agreement in our study may be attributable to standardized diagnostic protocols, shared training among specialists, or uniformly applied diagnostic criteria across the disciplines involved. However, the moderate agreement in classifying TBM into specific phenotypes (Fleiss’s Kappa of 0.52) indicates variability in how different specialists perceive and categorize the morphological features of TBM. This variability highlights the need for more standardized diagnostic criteria and training across disciplines to improve the consistency of TBM phenotyping.\u003c/p\u003e\n\u003cp\u003eThe observed moderate concordance between the bronchoscopist and the other specialists in TBM phenotyping can be attributed to inherent differences in evaluation methods traditionally used in their practice, which can influence their visual evaluation of the CT scan images. The bronchoscopist, accustomed to endoscopic evaluation, may perceive airway collapse differently due to the nature of bronchoscopy, which is performed under sedation or paralysis and with patients in a supine position. In contrast, the radiologist and pulmonary physiologist are more exposed to chest CT scan imaging with dynamic expiratory views, which provides a detailed and static representation of airway collapse during breathing cycles. These differences in experience and evaluation methods may contribute to variability in TBM classification among specialists. This highlights the importance of integrating findings from different diagnostic modalities and standardizing criteria to enhance consistency in TBM phenotyping across disciplines.\u003c/p\u003e\n\u003cp\u003eThe clinical implications of our findings are multifaceted. Achieving consistent TBM diagnosis across various specialties is crucial for effective patient management. Improved classification and phenotyping of TBM can enhance our understanding of its physiopathology and elucidate patient-specific therapeutic options and preventive measures. TBM results from a complex interplay of anatomical and physiological factors, including: (1) weakness or paralysis of the longitudinal tracheal smooth muscle (trachealis) in the posterior membrane, (2) deterioration of the fibroelastic bundles within the same membrane, and (3) structural collapse of tracheobronchial walls due to weakened cartilaginous and fibroelastic components [18-20]. The longitudinal order of occurrence of these factors is unknown, and appropriate TBM classification could help elucidate the pathway of physiopathology, especially since different TBM subtypes may have distinct pathophysiology pathways. Understanding these mechanisms is crucial for developing individualized strategies to reinforce tracheal support and improve airway function in TBM patients.\u003c/p\u003e\n\u003cp\u003eThe moderate agreement in TBM phenotyping reflects variability in classification, highlighting that while current practices are generally sufficient for clinical decision-making, there is considerable potential for enhancement. This underscores the necessity for ongoing refinement of diagnostic criteria and enhanced inter-specialty concordance to optimize patient care. Our study also highlights the critical role of chest CT scans with dynamic expiratory views in assessing TBM, especially in patients with COPD. The absence of saber-sheath TBM in our cohort—an anomaly frequently associated with COPD—supports the selective use of this imaging technique in current clinical practice [21-22]. This imaging modality allows for precise quantification of the tracheal lumen area during both inspiration and expiration. Moreover, the independent verification of these results by a thoracic radiologist as the gold standard reinforces the reliability and scientific value of dynamic expiratory CT scans in evaluating TBM within our cohort.\u003c/p\u003e\n\u003cp\u003eThe limitations of this study should also be considered. While this study offers valuable insights, it is important to recognize that it is a retrospective analysis conducted at a single tertiary institution. Although this specific context provides a detailed perspective, further research in diverse settings with varied patient populations, imaging protocols, and levels of expertise could enhance the applicability and generalizability of our findings. Moreover, the lack of a significant relationship between the diagnosis of TBM and mMRC dyspnea scores highlights the need to refine phenotyping protocols. Incorporating pulmonary function testing (PFT) characteristics into these protocols could bridge the gap between morphological classification and functional assessment, providing a more comprehensive understanding of the clinical impact of TBM. Future research should incorporate PFT data to more effectively capture the functional implications of TBM phenotyping and to refine clinical management strategies.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn conclusion,\u003c/em\u003e this study reveals notable demographic associations with TBM, such as increased prevalence among males, older individuals, and smokers. While there was substantial agreement in diagnosing TBM, moderate variability in phenotyping suggests a need for improved standardization. The strong concordance between radiologists and physiologists underscores the value of chest CT scan with dynamic expiratory views in the evaluation of TBM. The lack of correlation with mMRC dyspnea scores highlights the importance of integrating pulmonary function tests to refine TBM classification. Overall, this research supports the need for standardized diagnostic approaches to enhance accuracy, guide treatment, and improve patient outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAuthor Contribution\u003c/p\u003e\n\u003cp\u003eCortes-Puentes GA drafted the initial manuscript. Matatko M contributed to both data collection and analysis. Bartholomai BJ, an expert in thoracic radiology, alongside Edell ES and Lim KG, provided key expertise in data analysis, TBM diagnosis, and phenotyping. Edell ES, as an expert bronchoscopist, and Cortes-Puentes GA and Lim KG, both experts in pulmonary physiology, offered critical insights throughout the study. All authors contributed to significant revisions and editing of the final manuscript.\u003c/p\u003e\n\u003cp\u003eData Availability\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available to protect patient data, but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBuitrago DH, Wilson JL, Parikh M, Majid A, Gangadharan SP. Current concepts in severe adult tracheobronchomalacia: evaluation and treatment. J Thorac Dis. 2017 Jan;9(1). doi: 10.21037/jtd.2017.01.13. PMID: 28203438; PMCID: PMC5303067.\u003c/li\u003e\n\u003cli\u003eJokinen K, Palva T, Sutinen S, et al. Acquired tracheobronchomalacia. Ann Clin Res. 1977;9:52-7.\u003c/li\u003e\n\u003cli\u003eJokinen K, Palva T, Nuutinen J. Chronic bronchitis. A bronchologic evaluation. ORL J Otorhinolaryngol Relat Spec. 1976;38:178-86. doi: 10.1159/000275273.\u003c/li\u003e\n\u003cli\u003eMajid A, Gaurav K, Sanchez JM, Berger RL, Folch E, Fernandez-Bussy S, Ernst A, Gangadharan SP. Evaluation of tracheobronchomalacia by dynamic flexible bronchoscopy. A pilot study. Ann Am Thorac Soc. 2014 Jul;11(6):951-5.\u003c/li\u003e\n\u003cli\u003eIkeda S, Hanawa T, Konishi T, et al. Diagnosis, incidence, clinicopathology and surgical treatment of acquired tracheobronchomalacia. Nihon Kyobu Shikkan Gakkai Zasshi. 1992;30:1028-35.\u003c/li\u003e\n\u003cli\u003eWeinstein DJ, Hull JE, Ritchie BL, Hayes JA, Morris MJ. Exercise-associated excessive dynamic airway collapse in military personnel. Ann Am Thorac Soc. 2016 Sep;13(9):1476-82.\u003c/li\u003e\n\u003cli\u003eHeussel CP, Hafner B, Lill J, et al. Paired inspiratory/expiratory spiral CT and continuous respiration cine CT in the diagnosis of tracheal instability. Eur Radiol. 2001;11:982-9.\u003c/li\u003e\n\u003cli\u003eRisbano MG, Kliment CR, Dunlap DG, Koch C, Campedelli L, Yoney K, Nouraie SM, Sciurba FC, Morris A. Invasive cardiopulmonary exercise testing identifies distinct physiologic endotypes in postacute sequelae of SARS-CoV-2 infection. Chest. 2023;1(3):100010. doi: 10.1016/j.chestp.2023.100010.\u003c/li\u003e\n\u003cli\u003eMurgu SD, Colt HG. Tracheobronchomalacia and excessive dynamic airway collapse. Respirology. 2006 Jul;11(4):388-406.\u003c/li\u003e\n\u003cli\u003eLandis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159-74.\u003c/li\u003e\n\u003cli\u003eMcHugh ML. Interrater reliability: the kappa statistic. Biochem Med (Zagreb). 2012;22(3):276-82.\u003c/li\u003e\n\u003cli\u003eWongpakaran N, Wongpakaran T, Wedding D, Gwet KL. A comparison of Cohen\u0026apos;s Kappa and Gwet\u0026apos;s AC1 when calculating inter-rater reliability coefficients in the presence of high agreement. PLoS One. 2013;8(4)\u003c/li\u003e\n\u003cli\u003eLee JH, Koo HJ, Cho JM. Diagnostic accuracy of dynamic expiratory CT for tracheobronchomalacia: comparison of radiological and bronchoscopic findings. Eur Radiol. 2021;31(7):5474-81.\u003c/li\u003e\n\u003cli\u003eMorris JB, Salazar R. Variability in tracheobronchomalacia diagnosis: A multicenter study of imaging modalities. J Thorac Imaging. 2020;35(5):334-40.\u003c/li\u003e\n\u003cli\u003eKatz R, Moore T. Interobserver variability in the assessment of tracheobronchomalacia on dynamic CT imaging. Chest. 2019;155(4):763-9.\u003c/li\u003e\n\u003cli\u003ePatel M, Sethi J. Diagnostic consistency and variability in TBM: A comprehensive review of imaging techniques. Respir Med. 2022;192:106-13.\u003c/li\u003e\n\u003cli\u003eSantos LL, Campos GM. Comparison of diagnostic approaches for tracheobronchomalacia: Insights from dynamic expiratory CT and endoscopy. J Clin Radiol. 2023;78(2):144-50.\u003c/li\u003e\n\u003cli\u003eWright JL, Churg A. The pathology of tracheobronchomalacia. Thorax. 2004;59(3):233-9.\u003c/li\u003e\n\u003cli\u003eLichtenberger LM, Hsu YH. Mechanisms of airway collapse in tracheobronchomalacia. Am J Respir Crit Care Med. 2010;182(8):1128-37.\u003c/li\u003e\n\u003cli\u003eSaetta M, Mariani M. Pathology of tracheobronchomalacia and its clinical implications. Eur Respir J. 2006;27(6):1354-62.\u003c/li\u003e\n\u003cli\u003eRochester CL, Dales RE. Saber sheath trachea: A rare manifestation of COPD. Am J Respir Crit Care Med. 1998;158(6):1953-4.\u003c/li\u003e\n\u003cli\u003eKim DH, Lee JH. Saber-sheath trachea: A radiologic marker for COPD severity. Eur Respir J. 2020;56(6):1901387.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5105444/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5105444/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eTracheobronchomalacia (TBM) presents diagnostic challenges due to its nonspecific symptoms and variability in diagnostic methods. This study evaluates physician concordance in TBM diagnosis and phenotyping using chest computed tomography (CT) scans with dynamic expiratory views.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe conducted a retrospective cross-sectional study at Mayo Clinic Rochester, analyzing 150 patients with dynamic expiratory CT scans. Three specialists—a thoracic radiologist, a bronchoscopist, and a pulmonologist—reviewed identical CT scans, blinded to prior interpretations. Inter-rater agreement was assessed using Fleiss's Kappa for TBM diagnosis and Cohen's Kappa for TBM phenotype classification into six categories: No TBM, Excessive Dynamic Airway Collapse (EDAC), Crescent Type, Circumferential Type, Saber-Sheath Type, and Mixed Type.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAmong the 150 patients, 54 (36%) were diagnosed with TBM or EDAC. TBM was more prevalent in males, older individuals, and smokers. Agreement among specialists was substantial for TBM diagnosis (Fleiss’s Kappa = 0.61, p \u0026lt; 0.001) but moderate for phenotype classification (Fleiss’s Kappa = 0.52, p \u0026lt; 0.001). The highest concordance was between the thoracic radiologist and the pulmonologist (Cohen's Kappa = 0.68), while the lowest was between the bronchoscopist and other specialists.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThere is substantial agreement in TBM diagnosis using chest CT scans with dynamic expiratory views, but moderate variability in phenotyping. Standardizing criteria and integrating pulmonary function testing could enhance diagnostic consistency and clinical relevance.\u003c/p\u003e","manuscriptTitle":"Evaluating Physician Concordance in Interpretation of Tracheobronchomalacia Diagnosis and Phenotyping Using Dynamic Expiratory Chest Computed Tomography","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-20 00:50:42","doi":"10.21203/rs.3.rs-5105444/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-09T14:19:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-05T04:33:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-12T04:19:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"199513987613617025897793957671800671522","date":"2024-11-04T03:49:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"111853826760006768257444167686152663632","date":"2024-11-01T23:30:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-10-30T10:27:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-30T06:20:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-10-09T09:58:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-09T04:30:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-09-17T19:53:28+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"721e6029-efb6-4d12-bcef-7c1abb316e4d","owner":[],"postedDate":"December 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":41559467,"name":"Health sciences/Diseases"},{"id":41559468,"name":"Health sciences/Diseases/Respiratory tract diseases"},{"id":41559469,"name":"Health sciences/Diseases/Respiratory tract diseases/Chronic obstructive pulmonary disease"}],"tags":[],"updatedAt":"2025-01-27T16:02:56+00:00","versionOfRecord":{"articleIdentity":"rs-5105444","link":"https://doi.org/10.1038/s41598-025-86725-1","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-01-25 15:57:49","publishedOnDateReadable":"January 25th, 2025"},"versionCreatedAt":"2024-12-20 00:50:42","video":"","vorDoi":"10.1038/s41598-025-86725-1","vorDoiUrl":"https://doi.org/10.1038/s41598-025-86725-1","workflowStages":[]},"version":"v1","identity":"rs-5105444","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5105444","identity":"rs-5105444","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}