CT-derived 3D-diaphragm motion in emphysema and IPF compared to normal subjects

Application of 3D computed tomography in emphysematous parenchyma patients scheduled for bronchoscopic lung volume reduction

Bronchoscopic lung volume reduction (BLVR) is a feasible, safe, effective and minimally invasive technique to significantly improve the quality of life of advanced severe chronic obstructive pulmonary disease (COPD). In this study, three-dimensional computed tomography (3D-CT) automatic analysis software combined with pulmonary function test (PFT) was used to retrospectively evaluate the postoperative efficacy of BLVR patients. The purpose is to evaluate the improvement of lung function of local lung tissue after operation, maximize the benefits of patients, and facilitate BLVR in the treatment of patients with advanced COPD. All the reported cases of advanced COPD patients treated with BLVR with one-way valve were collected and analysed from 2017 to 2020. Three-dimensional-CT image analysis software system was used to analyse the distribution of low-density areas <950 Hounsfield units in both lungs pre- and post- BLVR. Meanwhile, all patients performed standard PFT pre- and post-operation for retrospective analysis. We reported six patients that underwent unilateral BLVR with 1 to 3 valves according to the range of emphysema. All patients showed a median increase in forced expiratory volume in 1 second (FEV1) of 34%, compared with baseline values. Hyperinflation was reduced by 16.6% (range, 4.9%-47.2%). The volumetric measurements showed a significant reduction in the treated lobe volume among these patients. Meanwhile, the targeted lobe volume changes were inversely correlated with change in FEV1/FEV1% in patients with heterogeneous emphysematous. We confirm that 3D-CT analysis can quantify the changes of lung volume, ventilation and perfusion, to accurately evaluate the distribution and improvement of emphysema and rely less on the observer.

Selective dysfunction of the crural diaphragm in patients with chronic restrictive and obstructive lung disease

BACKGROUND

Gastroesophageal reflux (GER) is known to be associated with chronic lung diseases. The driving force of GER is the transdiaphragmatic pressure (Pdi) generated mainly by costal and crural diaphragm contraction. The latter also enhances the esophagogastric junction (EGJ) pressure to guard against GER.

METHODS

The relationship between Pdi and EGJ pressure was determined using high resolution esophageal manometry in patients with interstitial lung disease (ILD, n = 26), obstructive lung disease (OLD, n- = 24), and healthy subjects (n = 20).

KEY RESULTS

The patient groups did not differ with respect to age, gender, BMI, and pulmonary rehabilitation history. Patients with ILD had significantly higher Pdi but lower EGJ pressures as compared to controls and OLD patients (p < 0.001). In control subjects, the increase in EGJ pressure at all-time points during inspiration was greater than Pdi. In contrast, the EGJ pressure during inspiration was less than Pdi in 14 patients with ILD and 7 patients with OLD. The drop in EGJ pressure was usually seen after the peak Pdi in ILD group (p < 0.0001) and before the peak Pdi in OLD group, (p = 0.08). Nine patients in the ILD group had sliding hiatus hernia, compared to none in control subjects (p = 0.003) and two patients in the OLD, (p = 0.04).

CONCLUSIONS AND INFERENCES

A higher Pdi and low EGJ pressure, and dissociation between Pdi and EGJ pressure temporal relationship suggests selective dysfunction of the crural diaphragm in patients with chronic lung diseases and may explain the higher prevalence of GERD in ILD as seen in previous studies.

A Survey on Artificial Intelligence in Pulmonary Imaging

Over the last decade, deep learning (DL) has contributed a paradigm shift in computer vision and image recognition creating widespread opportunities of using artificial intelligence in research as well as industrial applications. DL has been extensively studied in medical imaging applications, including those related to pulmonary diseases. Chronic obstructive pulmonary disease, asthma, lung cancer, pneumonia, and, more recently, COVID-19 are common lung diseases affecting nearly 7.4% of world population. Pulmonary imaging has been widely investigated toward improving our understanding of disease etiologies and early diagnosis and assessment of disease progression and clinical outcomes. DL has been broadly applied to solve various pulmonary image processing challenges including classification, recognition, registration, and segmentation. This paper presents a survey of pulmonary diseases, roles of imaging in translational and clinical pulmonary research, and applications of different DL architectures and methods in pulmonary imaging with emphasis on DL-based segmentation of major pulmonary anatomies such as lung volumes, lung lobes, pulmonary vessels, and airways as well as thoracic musculoskeletal anatomies related to pulmonary diseases.

Comparison of optimization parametrizations for regional lung compliance estimation using personalized pulmonary poromechanical modeling

Interstitial lung diseases, such as idiopathic pulmonary fibrosis (IPF) or post-COVID-19 pulmonary fibrosis, are progressive and severe diseases characterized by an irreversible scarring of interstitial tissues that affects lung function. Despite many efforts, these diseases remain poorly understood and poorly treated. In this paper, we propose an automated method for the estimation of personalized regional lung compliances based on a poromechanical model of the lung. The model is personalized by integrating routine clinical imaging data - namely computed tomography images taken at two breathing levels in order to reproduce the breathing kinematic-notably through an inverse problem with fully personalized boundary conditions that is solved to estimate patient-specific regional lung compliances. A new parametrization of the inverse problem is introduced in this paper, based on the combined estimation of a personalized breathing pressure in addition to material parameters, improving the robustness and consistency of estimation results. The method is applied to three IPF patients and one post-COVID-19 patient. This personalized model could help better understand the role of mechanics in pulmonary remodeling due to fibrosis; moreover, patient-specific regional lung compliances could be used as an objective and quantitative biomarker for improved diagnosis and treatment follow up for various interstitial lung diseases.

Characteristics of Diaphragmatic and Chest Wall Motion in People with Normal Pulmonary Function: A Study with Free-Breathing Dynamic MRI

Objective: We aimed to quantitatively study the characteristic of diaphragm and chest wall motion using free-breathing dynamic magnetic resonance imaging (D-MRI) in Chinese people with normal lung function. Methods: 74 male subjects (mean age, 37 ± 11 years old) were prospectively enrolled, and they underwent high-resolution CT(HRCT), pulmonary functional tests (PFTs), and D-MRI in the same day. D-MRI was acquired with a gradient-echo sequence during the quiet and deep breathing. The motion of the diaphragm and chest wall were respectively assessed by measuring thoracic anteroposterior diameter (AP), left−right diameter (LR), cranial−caudal diameter (CC), and thoracic area ratios between end-inspiration and end-expiration. The effect of age, body mass index (BMI), and smoking on respiratory muscle function was also analyzed. Results: The mean ratio of right and left AP was greater than that of LR on three transversal planes during both quiet and deep breathing. The mean ratio at the anterior diaphragm (AND, Quiet: 1.04 ± 0.03; Deep: 1.15 ± 0.09) was weaker than that of the apex (vs. APD, Quiet: 1.08 ± 0.05, p < 0.001; Deep: 1.29 ± 0.12, p < 0.001) and posterior diaphragm (vs. POD, Quiet: 1.09 ± 0.04, p < 0.001; Deep: 1.30 ± 0.12, p < 0.001) both in quiet and deep breathing. Compared with non-smokers, the left AP and thoracic area ratios in smokers were significantly decreased (p < 0.05). However, the ratios of AP, LR, CC, and thoracic area on each plane were similar among groups in different age and BMI. Conclusions: During both quiet and deep breathing, the chest wall motion is prominent in the anteroposterior direction. The motions of diaphragm apex and posterior diaphragm were more prominent than that of the anterior diaphragm. Smoking may affect the respiratory muscle mobility. Dynamic MRI can quantitatively evaluate the motion of respiratory muscles.

CT-based lung motion differences in patients with usual interstitial pneumonia and nonspecific interstitial pneumonia

We applied quantitative CT image matching to assess the degree of motion in the idiopathic ILD such as usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP). Twenty-one normal subjects and 42 idiopathic ILD (31 UIP and 11 NSIP) patients were retrospectively included. Inspiratory and expiratory CT images, reviewed by two experienced radiologists, were used to compute displacement vectors at local lung regions matched by image registration. Normalized three-dimensional and two-dimensional (dorsal-basal) displacements were computed at a sub-acinar scale. Displacements, volume changes, and tissue fractions in the whole lung and the lobes were compared between normal, UIP, and NSIP subjects. The dorsal-basal displacement in lower lobes was smaller in UIP patients than in NSIP or normal subjects (p = 0.03, p = 0.04). UIP and NSIP were not differentiated by volume changes in the whole lung or upper and lower lobes (p = 0.53, p = 0.12, p = 0.97), whereas the lower lobe air volume change was smaller in both UIP and NSIP than normal subjects (p = 0.02, p = 0.001). Regional expiratory tissue fractions and displacements showed positive correlations in normal and UIP subjects but not in NSIP subjects. In summary, lung motionography quantified by image registration-based lower lobe dorsal-basal displacement may be used to assess the degree of motion, reflecting limited motion due to fibrosis in the ILD such as UIP and NSIP.