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ObjectivesEvaluation and follow-up of idiopathic pulmonary fibrosis (IPF) mainly rely on high-resolution computed tomography (HRCT) and pulmonary function tests (PFTs). The elastic registration technique can quantitatively assess lung shrinkage. We aimed to investigate the correlation between lung shrinkage and morphological and functional deterioration in IPF.MethodsPatients with IPF who underwent at least two HRCT scans and PFTs were retrospectively included. Elastic registration was performed on the baseline and follow-up HRCTs to obtain deformation maps of the whole lung. Jacobian determinants were calculated from the deformation fields and after logarithm transformation, log_jac values were represented on color maps to describe morphological deterioration, and to assess the correlation between log_jac values and PFTs.ResultsA total of 69 patients with IPF (male 66) were included. Jacobian maps demonstrated constriction of the lung parenchyma marked at the lung base in patients who were deteriorated on visual and PFT assessment. The log_jac values were significantly reduced in the deteriorated patients compared to the stable patients. Mean log_jac values showed positive correlation with baseline percentage of predicted vital capacity (VC%) (r = 0.394, p < 0.05) and percentage of predicted forced vital capacity (FVC%) (r = 0.395, p < 0.05). Additionally, the mean log_jac values were positively correlated with pulmonary vascular volume (r = 0.438, p < 0.01) and the number of pulmonary vascular branches (r = 0.326, p < 0.01).ConclusionsElastic registration between baseline and follow-up HRCT was helpful to quantitatively assess the morphological deterioration of lung shrinkage in IPF, and the quantitative indicator log_jac values were significantly correlated with PFTs.Key points• The elastic registration on HRCT was helpful to quantitatively assess the deterioration of IPF. • Jacobian logarithm was significantly reduced in deteriorated patients and mean log_jac values were correlated with PFTs. • The mean log_jac values were related to the changes of pulmonary vascular volume and the number of vascular branches.

Accurate detection of fibrotic interstitial lung disease (f-ILD) is conducive to early intervention. Our aim was to develop a lung graph-based machine learning model to identify f-ILD. A total of 417 HRCTs from 279 patients with confirmed ILD (156 f-ILD and 123 non-f-ILD) were included in this study. A lung graph-based machine learning model based on HRCT was developed for aiding clinician to diagnose f-ILD. In this approach, local radiomics features were extracted from an automatically generated geometric atlas of the lung and used to build a series of specific lung graph models. Encoding these lung graphs, a lung descriptor was gained and became as a characterization of global radiomics feature distribution to diagnose f-ILD. The Weighted Ensemble model showed the best predictive performance in cross-validation. The classification accuracy of the model was significantly higher than that of the three radiologists at both the CT sequence level and the patient level. At the patient level, the diagnostic accuracy of the model versus radiologists A, B, and C was 0.986 (95% CI 0.959 to 1.000), 0.918 (95% CI 0.849 to 0.973), 0.822 (95% CI 0.726 to 0.904), and 0.904 (95% CI 0.836 to 0.973), respectively. There was a statistically significant difference in AUC values between the model and 3 physicians (p < 0.05). The lung graph-based machine learning model could identify f-ILD, and the diagnostic performance exceeded radiologists which could aid clinicians to assess ILD objectively. Given a sequence of HRCT slices from a patient, the lung field is first automatically extracted. Next, this lung region is divided into 36 sub-regions using geometric rules, obtaining a lung atlas. And then, the lung graph is built based on 3D radiomics features of each sub-region of the lung atlas. Finally, the model's predictions were compared to the physicians' assessment results. [ABSTRACT FROM AUTHOR]

Background: Studies on the incidence of venous thromboembolism (VTE) events in patients with interstitial lung disease (ILD) are limited and the results are inconsistent. The aim of this research was to investigate the incidence and risk factors of VTE in ILD during hospitalization. Materials and methods: In this retrospective, cross-sectional, observational study, a total of 5009 patients diagnosed with ILD from January 2016 to March 2022 in our hospital were retrospectively included. In ILD patients, VTE including pulmonary thromboembolism (PTE) and deep vein thrombosis (DVT) were screened from the electronic medical record system. Diagnosis of PTE and DVT were performed by CT pulmonary angiography (CTPA), CTV or ultrasound. And then the incidence and risk factors of VTE in different types of ILD were assessed. Results: Among 5009 patients with ILD, VTE was detected in 129 (2.6%) patients, including 15(0.3%) patients with both PTE and DVT, 34 (0.7%) patients with PTE and 80 (1.6%) patients with DVT. 85.1% of patients with APE were in the intermediate-low risk group. The incidence of VTE in Anti-Neutrophil Cytoplasmic Antibodies -associated vasculitis related ILD (ANCA-AV-ILD), hypersensitivity pneumonitis and idiopathic pulmonary fibrosis (IPF) respectively was 7.9% and 3.6% and 3.5%. In patients with connective tissue disease-associated ILD (CTD-ILD), the incidence of VTE, DVT, PTE, combined PTE and DVT respectively was 3.0%, 2.3%, 0.4% and 0.3%. Among the various risk factors, different ILD categories, age ≥ 80 years (OR 4.178, 95% CI 2.097–8.321, P < 0.001), respiratory failure (OR 2.382, 95% CI 1.533–3.702, P < 0.001) and varicose veins (OR 3.718, 95% CI 1.066–12.964, P = 0.039) were independent risk factors of VTE. The incidence of VTE in patients with ILD increased with the length of time in hospital from 2.2% (< 7 days) to 6.4% (> 21 days). Conclusion: The incidence of VTE during hospitalization in ILD patients was 2.6%, with a 1.6% incidence of DVT, higher than the 0.7% incidence of PTE. Advanced age, ILD categories, respiratory failure and varicose veins as independent risk factors for the development of VTE should be closely monitored. [ABSTRACT FROM AUTHOR]