The Clinical Significance of CT-based Biomarkers in the Classification and Prognosis of Bronchiectasis

Bronchiectasis is a common lung disease with a high incidence and low attention rate, and the imaging of bronchiectasis is characterized by diverse sites of involvement, morphological features and airway obstruction, as well as different clinical symptoms, severity and prognosis, and response to treatment. Therefore, how to establish a personalized prognostic evaluation system has also become a current research hotspot.

It has been demonstrated that chronic sputum aggregation or destruction of the airway wall leads to the appearance of emphysema, mucus plugs, and pulmonary solid changes in the lung parenchyma adjacent to the diseased bronchus. Emphysema and bronchiectasis share the same pathogenesis, such as chronic inflammation and alpha-1 trypsin deficiency, etc., and to some extent a vicious circle of mutual exacerbation. Thus subjects with coexisting emphysema tend to have a higher likelihood of infection compared to subjects with bronchiectasis without manifestations of emphysema. Emphysema is also recognized as an independent risk factor for 5-year mortality in patients with bronchiectasis. Meanwhile, high mucus secretion, another major manifestation in patients with bronchiectasis, which may be visualized on imaging as the formation of mucus plugs or dendritic signs, is a contributing factor to chronic obstruction in bronchiectasis and also appears to be the best predictor of mortality in patients with bronchiectasis. It can be concluded that different imaging manifestations in patients with bronchiectasis are closely related to clinical manifestations and prognosis. In this study, we attempted to establish a new assessment system of imaging severity by analyzing the imaging manifestations of patients with bronchiectasis and conducting a 3-year follow-up of the patients with bronchiectasis to further understand the clinical significance of imaging in the staging of bronchiectasis and the prognosis of the disease.

According to the inclusion and exclusion criteria, patients with confirmed diagnosis of bronchiectasis attending Union Hospital of Tongji Medical College, Huazhong University of Science and Technology between March 31, 2024 and March 31, 2027 were included in this study. At the time of enrollment, the researchers collected the subjects' demographic information, such as gender, age, height (m), weight (kg), clinical symptoms, such as cough, sputum, hemoptysis, dyspnea, blood test results, such as red blood cell count (10^12/L), hemoglobin (g/L), white blood cells (10^9/L), CRP (mg/L), sputum culture, and lung function test results, such as FVC (L), FVC (L), FVC (L), FVC (L), FVC (L), CRP (M), FVC (L), and sputum culture. , such as FVC (L), FEV1 (L), FEV1/FVC (%), and lung imaging (CT, etc.), such as type of bronchiectasis; degree of bronchiectasis, number of lung segments involved, grade of lung segments involved, and thickness of tubular wall; site of emphysema, its severity, number of segments involved, and its typology; site of mucus plugs, number of lung segments involved; lung abscesses; lung solids; and lung macroglossia.

Through the collection of the above data, the investigators will score the imaging and clinical manifestations of the patients, such as Bhalla score, Reiff score, BSI, FACED, emphysema grading, mucus plug score, etc. The subjects were also followed up every six months for three years after enrollment to obtain the number of acute exacerbations, number of hospitalizations, and patient survival per year in order to derive the relationship between imaging manifestations and prognosis and staging of bronchiectasis.

METHODS: In this study, blood, sputum, lung function and lung CT results were collected from the subjects during their normal visit to the clinic without any intervention and without any additional tests performed by the subjects. Where lung CT scores were scored according to Bhalla scoring criteria, Reiff scoring criteria respectively and scored by two medical imaging physicians.

Emphysema：The distribution of emphysema can be determined by a radiologist's qualitative, visual assessment of the scanned image or quantitatively by CT imaging.The Fleischner Society has standardized the description of visually determined emphysema patterns. Specific software is available that automatically identifies the lungs, traces their contours, and determines a histogram of lung attenuation values that can be used to distinguish between non-emphysematous and emphysematous lung tissue. In healthy lungs, attenuation values are most often distributed between -750 and -850 HU, with an average attenuation of -789 HU. Negative values for emphysema on CT are usually expressed as a percentage of low attenuation areas below a given threshold, with larger values indicating more emphysema. Below -910 HU, -950 HU, and -960 HU are usually considered to be associated with pathologic emphysema. The first value is the most accepted to define mild emphysema, while the last two can be used to define severe emphysema. Large non-AATD COPD clinical studies such as COPDGene (COPD Genetic Epidemiology), SPIROMICS (Subgroups and Intermediate Outcome Indicators in COPD Studies), and ECLIPSE (Longitudinal Evaluation of COPD to Determine Predictive Surrogate Endpoints) have mostly used -950 HU as their threshold for defining emphysema. Therefore, 950 HU was used as the threshold for emphysema in this study.

Mucus plug score：The score is based on counting the number of lung segments with mucus plugs completely blocking middle-to-large-sized airways (i.e., -2-10 mm-lumen diameter) on computed tomography scans. Readers recorded the number of lung segments with mucus plugs in each lobe, with the lingula as a separate lobe. The score ranges from O (no mucus plugs seen in any lung segments) to 18 (all lung segments with mucus plugs). The employed bronchial nomenclature consists of 18 lung segments (right lung: 3, 2, and 5 lung segments in the upper, middle, and lower lobes, respectively; left lung: 2, 2, and 4 lung segments in the upper lobe,lingula, and lower lobe, respectively).

Statistical analysis and statistical methods: The data obtained during the study period were pre-organized. For continuous data, normality test was first executed. If all groups conformed to the normality values, the Student's t-test was used for comparison between groups. Otherwise, nonparametric Wilcoxon rank sum test was considered. For categorical variables, the χ2 test was used. Multifactor logistic regression analysis was performed for statistically significant data. The effect of different nutritional status on the prognosis of subjects with bronchiectasis was analyzed using the subject work characteristics (ROC) and Delong's method, and the difference was statistically significant at P<0.05.

Statistical analysis of all data was performed by SPSS (IBM SPSS Statistics 26.0, SPSS Inc., Chicago, IL) and R language (version 4.1.3, www.R-project.org/). All statistical tests were two-sided and statistical significance was set at 0.05.