Airway wall thickness and airflow limitations in asthma assessed in quantitative computed tomography.
- 作者列表："Patyk M","Obojski A","Sokołowska-Dąbek D","Parkitna-Patyk M","Zaleska-Dorobisz U
BACKGROUND:Asthma is a frequent chronic disease of the airways. In spite of the fact that symptoms of asthma are well known, the pathogenesis has not yet been fully understood. Quantitative computed tomography (qCT) of the lung allows for the measurment of a set of parameters. The aim of this study was to evaluate the usefulness of quantitative computed tomography in the assessment of airway wall thickness in asthma. METHODS:The prospective study was performed on a group of 83 patients with well-defined, long-term asthma between 2016 and 2018. The control group was composed of 30 healthy volunteers. All examined subjects were non-smokers. All computed tomography (CT) studies were performed using a 128 multi-slice CT scanner with no contrast, following a chest scanning protocol in the supine position, at full inspiration and breath-holds. RESULTS:Quantitative bronchial tree measurements were obtained from the third up to the ninth generation of the posterior basal bronchi (B10) of the right lung in a blinded fashion. The value of the wall thickness in patients with asthma was significantly higher in all measured generations of the bronchial tree (third to ninth generation). The lumen area and the inner diameter significantly correlated with the lung function tests and were substantially smaller in the examined group from the seventh to the ninth generation of the bronchi (p < 0.05). Conclusions: We conclude that airway remodelling occurs in most patients with long-term asthma and is associated mainly with the medium and small airways. Imaging techniques, especially qCT can be useful in the diagnosis and management of asthma.
背景: 哮喘是一种常见的气道慢性疾病。尽管哮喘的症状是众所周知的，但发病机制尚未完全清楚。肺定量计算机断层扫描 (qCT) 允许测量一组参数。本研究的目的是评估定量计算机断层扫描在哮喘气道壁厚度评估中的有效性。 方法: 前瞻性研究是在 2018 和 2016年对 83 例明确定义的长期哮喘患者进行的。对照组由 30 名健康志愿者组成。所有受检对象均为不吸烟者。所有计算机断层扫描 (CT) 研究均使用无对比度的 128 多层 CT 扫描仪进行，遵循仰卧位、充分吸气和屏气的胸部扫描方案。 结果: 以盲法获得右肺后基底支气管 (B10) 第三代至第九代的定量支气管树测量。在支气管树的所有测量代 (第三至第九代) 中，哮喘患者的壁厚值显著较高。管腔面积和内径与肺功能检查显著相关，在第七代至第九代支气管的受检者中显著较小 (p <0.05)。 结论: 我们得出结论，气道重塑发生在大多数长期哮喘患者中，主要与中小气道相关。成像技术，尤其是 qCT 可用于哮喘的诊断和治疗。
METHODS:Background Dye localization is a useful method for the resection of unidentifiable small pulmonary lesions. This study compares the transbronchial route with augmented fluoroscopic bronchoscopy (AFB) and conventional transthoracic CT-guided methods for preoperative dye localization in thoracoscopic surgery. Methods Between April 2015 and March 2019, a total of 231 patients with small pulmonary lesions who received preoperative dye localization via AFB or percutaneous CT-guided technique were enrolled in the study. A propensity-matched analysis, incorporating preoperative variables, was used to compare localization and surgical outcomes between the two groups. Results After matching, a total of 90 patients in the AFB group ( N = 30) and CT-guided group ( N = 60) were selected for analysis. No significant difference was noted in the demographic data between both the groups. Dye localization was successfully performed in 29 patients (96.7%) and 57 patients (95%) with AFB and CT-guided method, respectively. The localization duration (24.1 ± 8.3 vs. 21.4 ± 12.5 min, p = 0.297) and equivalent dose of radiation exposure (3.1 ± 1.5 vs. 2.5 ± 2.0 mSv, p = 0.130) were comparable in both the groups. No major procedure-related complications occurred in either group; however, a higher rate of pneumothorax (0 vs. 16.7%, p = 0.029) and focal intrapulmonary hemorrhage (3.3 vs. 26.7%, p = 0.008) was noted in the CT-guided group. Conclusion AFB dye marking is an effective alternative for the preoperative localization of small pulmonary lesions, with a lower risk of procedure-related complications than the conventional CT-guided method.
METHODS:Background The use of artificial intelligence, including machine learning, is increasing in medicine. Use of machine learning is rising in the prediction of patient outcomes. Machine learning may also be able to enhance and augment anesthesia clinical procedures such as airway management. In this study, we sought to develop a machine learning algorithm that could classify vocal cords and tracheal airway anatomy real-time during video laryngoscopy or bronchoscopy as well as compare the performance of three novel convolutional networks for detecting vocal cords and tracheal rings. Methods Following institutional approval, a clinical dataset of 775 video laryngoscopy and bronchoscopy videos was used. The dataset was divided into two categories for use for training and testing. We used three convolutional neural networks (CNNs): ResNet, Inception and MobileNet. Backpropagation and a mean squared error loss function were used to assess accuracy as well as minimize bias and variance. Following training, we assessed transferability using the generalization error of the CNN, sensitivity and specificity, average confidence error, outliers, overall confidence percentage, and frames per second for live video feeds. After the training was complete, 22 models using 0 to 25,000 steps were generated and compared. Results The overall confidence of classification for the vocal cords and tracheal rings for ResNet, Inception and MobileNet CNNs were as follows: 0.84, 0.78, and 0.64 for vocal cords, respectively, and 0.69, 0.72, 0.54 for tracheal rings, respectively. Transfer learning following additional training resulted in improved accuracy of ResNet and Inception for identifying the vocal cords (with a confidence of 0.96 and 0.93 respectively). The two best performing CNNs, ResNet and Inception, achieved a specificity of 0.985 and 0.971, respectively, and a sensitivity of 0.865 and 0.892, respectively. Inception was able to process the live video feeds at 10 FPS while ResNet processed at 5 FPS. Both were able to pass a feasibility test of identifying vocal cords and tracheal rings in a video feed. Conclusions We report the development and evaluation of a CNN that can identify and classify airway anatomy in real time. This neural network demonstrates high performance. The availability of artificial intelligence may improve airway management and bronchoscopy by helping to identify key anatomy real time. Thus, potentially improving performance and outcomes during these procedures. Further, this technology may theoretically be extended to the settings of airway pathology or airway management in the hands of experienced providers. The researchers in this study are exploring the performance of this neural network in clinical trials.
METHODS:BACKGROUND:The optimal mode of delivering topical anesthesia during flexible bronchoscopy remains unknown. This article compares the efficacy and safety of nebulized lignocaine, lignocaine oropharyngeal spray, or their combination. METHODS:Consecutive subjects were randomized 1:1:1 to receive nebulized lignocaine (2.5 mL of 4% solution, group A), oropharyngeal spray (10 actuations of 10% lignocaine, group B), or nebulization (2.5 mL, 4% lignocaine) and two actuations of 10% lignocaine spray (group C). The primary outcome was the subject-rated severity of cough according to a visual analog scale. The secondary outcomes included bronchoscopist-rated severity of cough and overall procedural satisfaction on a visual analog scale, total lignocaine dose, subject's willingness to undergo a repeat procedure, adverse reactions to lignocaine, and others. RESULTS:A total of 1,050 subjects (median age, 51 years; 64.8% men) were included. The median (interquartile range) score for subject-rated cough severity was significantly lower in group B compared to group C or group A (4 [1-10] vs 11 [4-24] vs 13 [5-30], respectively; P < .001). The bronchoscopist-rated severity of cough was also the least (P < .001), and the overall satisfaction was highest in group B (P < .001). The cumulative lignocaine dose administered was the least in group B (P < .001). A significantly higher proportion of subjects (P < .001) were willing to undergo a repeat bronchoscopy in group B (73.7%) than in groups A (49.1%) and C (59.4%). No lignocaine-related adverse events were observed. CONCLUSIONS:Ten actuations of 10% lignocaine oropharyngeal spray were superior to nebulized lignocaine or their combination for topical anesthesia during diagnostic flexible bronchoscopy. TRIAL REGISTRY:ClinicalTrials.gov; No.: NCT03109392; URL: www.clinicaltrials.gov.