Factors correlating the expression of PD-L1.

OBJECTIVE: PD-L1 was an important biomarker in lung adenocarcinoma. The study was to confirm the most important factor affecting the expression of PD-L1 remains undetermined. METHODS: The clinical records of 1045 lung adenocarcinoma patients were retrospectively reviewed. The High-Resolution Computed Tomography (HRCT) scanning images of all the participants were analyzed, and based on the CT characteristics, the adenocarcinomas were categorized according to CT textures. Furthermore, PD-L1 expression and Ki67 index were detected by immunohistochemistry. All patients underwent EGFR mutation detection. RESULTS: Multivariate logistic regression analysis revealed that smoking (OR: 1.73, 95% CI: 1.04-2.89, p = 0.004), EGFR wild (OR: 1.52, 95% CI: 1.11-2.07, p = 0.009), micropapillary subtypes (OR: 2.05, 95% CI: 1.46-2.89, p < 0.0001), and high expression of Ki67 (OR: 2.02, 95% CI: 1.44-2.82, p < 0.0001) were independent factors which influence PD-L1 expression. In univariate analysis, tumor size > 3 cm and CT textures of pSD showed a correlation with high expression of PD-L1. Further analysis revealed that smoking, micropapillary subtype, and EGFR wild type were also associated with high Ki67 expression. Moreover, high Ki67 expression was observed more frequently in tumors of size > 3 cm than in tumors with ≤ 3 cm size as well as in CT texture of pSD than lesions with GGO components. In addition, multivariate logistic regression analysis revealed that only lesions with micropapillary components correlated with pSD (OR: 3.96, 95% CI: 2.52-5.37, p < 0.0001). CONCLUSION: This study revealed that in lung adenocarcinoma high Ki67 expression significantly influenced PD-L1 expression, an important biomarker for immune checkpoint treatment.

Continuum topological derivative - a novel application tool for denoising CT and MRI medical images.

BACKGROUND: CT and MRI modalities are important diagnostics tools for exploring the anatomical and tissue properties, respectively of the human beings. Several advancements like HRCT, FLAIR and Propeller have advantages in diagnosing the diseases very accurately, but still have enough space for improvements due to the presence of inherent and instrument noises. In the case of CT and MRI, the quantum mottle and the Gaussian and Rayleigh noises, respectively are still present in their advanced modalities of imaging. This paper addresses the denoising problem with continuum topological derivative technique and proved its trustworthiness based on the comparative study with other traditional filtration methods such as spatial, adaptive, frequency and transformation techniques using measures like visual inspection and performance metrics. METHODS: This research study focuses on identifying a novel method for denoising by testing different filters on HRCT (High-Resolution Computed Tomography) and MR (Magnetic Resonance) images. The images were acquired from the Image Art Radiological Scan Centre using the SOMATOM CT and SIGNA Explorer (operating at 1.5 Tesla) machines. To compare the performance of the proposed CTD (Continuum Topological Derivative) method, various filters were tested on both HRCT and MR images. The filters tested for comparison were Gaussian (2D convolution operator), Wiener (deconvolution operator), Laplacian and Laplacian diagonal (2nd order partial differential operator), Average, Minimum, and Median (ordinary spatial operators), PMAD (Anisotropic diffusion operator), Kuan (statistical operator), Frost (exponential convolution operator), and HAAR Wavelet (time-frequency operator). The purpose of the study was to evaluate the effectiveness of the CTD method in removing noise compared to the other filters. The performance metrics were analyzed to assess the diligence of noise removal achieved by the CTD method. The primary outcome of the study was the removal of quantum mottle noise in HRCT images, while the secondary outcome focused on removing Gaussian (foreground) and Rayleigh (background) noise in MR images. The study aimed to observe the dynamics of noise removal by examining the values of the performance metrics. In summary, this study aimed to assess the denoising ability of various filters in HRCT and MR images, with the CTD method being the proposed approach. The study evaluated the performance of each filter using specific metrics and compared the results to determine the effectiveness of the CTD method in removing noise from the images. RESULTS: Based on the calculated performance metric values, it has been observed that the CTD method successfully removed quantum mottle noise in HRCT images and Gaussian as well as Rayleigh noise in MRI. This can be evidenced by the PSNR (Peak Signal-to-Noise Ratio) metric, which consistently exhibited values ranging from 50 to 65 for all the tested images. Additionally, the CTD method demonstrated remarkably low residual values, typically on the order of e-09, which is a distinctive characteristic across all the images. Furthermore, the performance metrics of the CTD method consistently outperformed those of the other tested methods. Consequently, the results of this study have significant implications for the quality, structural similarity, and contrast of HRCT and MR images, enabling clinicians to obtain finer details for diagnostic purposes. CONCLUSION: Continuum topological derivative algorithm is found to be constructive in removing prominent noises in both CT and MRI images and can serve as a potential tool for recognition of anatomical details in case of diseased and normal ones. The results obtained from this research work are highly inspiring and offer great promise in obtaining accurate diagnostic information for critical cases such as Thoracic Cavity Carina, Brain SPI Globe Lens 4th Ventricle, Brain-Middle Cerebral Artery, Brain-Middle Cerebral Artery and neoplastic lesions. These findings lay the foundation for implementing the proposed CTD technique in routine clinical diagnosis.

Residual Lung Abnormalities after COVID-19 Hospitalization: Interim Analysis of the UKILD Post-COVID-19 Study.

Rationale: Shared symptoms and genetic architecture between coronavirus disease (COVID-19) and lung fibrosis suggest severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may lead to progressive lung damage. Objectives: The UK Interstitial Lung Disease Consortium (UKILD) post-COVID-19 study interim analysis was planned to estimate the prevalence of residual lung abnormalities in people hospitalized with COVID-19 on the basis of risk strata. Methods: The PHOSP-COVID-19 (Post-Hospitalization COVID-19) study was used to capture routine and research follow-up within 240 days from discharge. Thoracic computed tomography linked by PHOSP-COVID-19 identifiers was scored for the percentage of residual lung abnormalities (ground-glass opacities and reticulations). Risk factors in linked computed tomography were estimated with Bayesian binomial regression, and risk strata were generated. Numbers within strata were used to estimate posthospitalization prevalence using Bayesian binomial distributions. Sensitivity analysis was restricted to participants with protocol-driven research follow-up. Measurements and Main Results: The interim cohort comprised 3,700 people. Of 209 subjects with linked computed tomography (median, 119 d; interquartile range, 83-155), 166 people (79.4%) had more than 10% involvement of residual lung abnormalities. Risk factors included abnormal chest X-ray (risk ratio [RR], 1.21; 95% credible interval [CrI], 1.05-1.40), percent predicted DlCO less than 80% (RR, 1.25; 95% CrI, 1.00-1.56), and severe admission requiring ventilation support (RR, 1.27; 95% CrI, 1.07-1.55). In the remaining 3,491 people, moderate to very high risk of residual lung abnormalities was classified at 7.8%, and posthospitalization prevalence was estimated at 8.5% (95% CrI, 7.6-9.5), rising to 11.7% (95% CrI, 10.3-13.1) in the sensitivity analysis. Conclusions: Residual lung abnormalities were estimated in up to 11% of people discharged after COVID-19-related hospitalization. Health services should monitor at-risk individuals to elucidate long-term functional implications.

Use of serum KL-6 and chest radiographic severity grade to predict 28-day mortality in COVID-19 patients with pneumonia: a retrospective cohort study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has had a global social and economic impact. An easy assessment procedure to handily identify the mortality risk of inpatients is urgently needed in clinical practice. Therefore, the aim of this study was to develop a simple nomogram model to categorize patients who might have a poor short-term outcome. METHODS: A retrospective cohort study of 189 COVID-19 patients was performed at Shanghai Ren Ji Hospital from December 12, 2022 to February 28, 2023. Chest radiography and biomarkers, including KL-6 were assessed. Risk factors of 28-day mortality were selected by a Cox regression model. A nomogram was developed based on selected variables by SMOTE strategy. The predictive performance of the derived nomogram was evaluated by calibration curve. RESULTS: In total, 173 patients were enrolled in this study. The 28-day mortality event occurred in 41 inpatients (23.7%). Serum KL-6 and radiological severity grade (RSG) were selected as the final risk factors. A nomogram model was developed based on KL-6 and RSG. The calibration curve suggested that the nomogram model might have potential clinical value. The AUCs for serum KL-6, RSG, and the combined score in the development group and validation group were 0.885 (95% CI: 0.804-0.952), 0.818 (95% CI: 0.711-0.899), 0.868 (95% CI: 0.776-0.942) and 0.932 (95% CI: 0.862-0.997), respectively. CONCLUSIONS: Our results suggested that the nomogram based on KL-6 and RSG might be a potential method for evaluating 28-day mortality in COVID-19 patients. A high combined score might indicate a poor outcome in COVID-19 patients with pneumonia.

Clustering analysis of HRCT parameters measured using a texture-based automated system: relationship with clinical outcomes of IPF.

PURPOSE: The extent of honeycombing and reticulation predict the clinical prognosis of IPF. Emphysema, consolidation, and ground glass opacity are visible in HRCT scans. To date, there have been few comprehensive studies that have used these parameters. We conducted automated quantitative analysis to identify predictive parameters for clinical outcomes and then grouped the subjects accordingly. METHODS: CT images were obtained while patients held their breath at full inspiration. Parameters were analyzed using an automated lung texture quantification system. Cluster analysis was conducted on 159 IPF patients and clinical profiles were compared between clusters in terms of survival. RESULTS: Kaplan-Meier analysis revealed that survival rates declined as fibrosis, reticulation, honeycombing, consolidation, and emphysema scores increased. Cox regression analysis revealed that reticulation had the most significant impact on survival rate, followed by honeycombing, consolidation, and emphysema scores. Hierarchical and K-means cluster analyses revealed 3 clusters. Cluster 1 (n = 126) with the lowest values for all parameters had the longest survival duration, and relatively-well preserved FVC and DLCO. Cluster 2 (n = 15) with high reticulation and consolidation scores had the lowest FVC and DLCO values with a predominance of female, while cluster 3 (n = 18) with high honeycombing and emphysema scores predominantly consisted of male smokers. Kaplan-Meier analysis revealed that cluster 2 had the lowest survival rate, followed by cluster 3 and cluster 1. CONCLUSION: Automated quantitative CT analysis provides valuable information for predicting clinical outcomes, and clustering based on these parameters may help identify the high-risk group for management.

Applicability of ChOLE staging to preoperative HRCT temporal bone in chronic otitis media with cholesteatoma.

PURPOSE: Chronic otitis media with cholesteatoma is a frequent disease entity in otology, requiring surgery in overwhelming majority of cases. Despite the huge burden there is no established grading system available to assess the severity and extent of disease preoperatively until date. Aim of our study is to assess the applicability of ChOLE staging to preoperative HRCT temporal bone in Chronic otitis media with cholesteatoma. METHODOLOGY: Patients clinically diagnosed as COM with cholesteatoma, who underwent preoperative HRCT temporal bone imaging and mastoid exploration at our tertiary care centre were included. Preoperative radiology was assessed and a radiological ChOLE (r-ChOLE) was given by radiologist. This was then compared with the postop ChOLE. RESULTS: 21 patients were included in the study. Data was linear and normally distributed (Shapiro wilk test). Pearson's product-moment correlation used to see relationship between radiological and postop Total score showed strong statistically significant positive correlation with correlation coefficient (r) of 0.977. Paired t test showed p value was 0.329 (p > 0.05) suggesting no significant difference between radiological and postop Total scores. Cohen kappa test of agreement was applied. It revealed an overall strong agreement (p < 0.001). CONCLUSION: ChOLE staging may be extended to preoperative HRCT of temporal bone in COM with cholesteatoma (rCHOLE). A preoperative radiological staging will help in better prioritizing, planning and execution of tympanomastoid surgeries.

Lung ultrasound and high-resolution computed tomography quantitative variations during nintedanib treatment for systemic sclerosis-associated interstitial lung disease.

OBJECTIVES: Lung ultrasound (LUS) and high-resolution computed tomography (HRCT) are commonly used for the evaluation of interstitial lung disease (ILD). Nintedanib (NIN) is an antifibrotic therapy approved for systemic sclerosis-associated ILD (SSc-ILD). We assessed LUS and quantitative HRCT changes in SSc-ILD patients treated with NIN during a one-year follow-up, evaluating relationships between imaging variations and functional or quality-of-life outcomes. METHODS: SSc-ILD patients who started NIN were enrolled and followed for twelve months. Pulmonary function tests and patient-reported outcome measures (PROMs) were assessed half-yearly and quarterly, respectively. LUS was performed quarterly evaluating the presence of B-lines (BL) and pleural line irregularities (PLI). HRCT was repeated after one year and quantitatively analysed with CALIPER software. RESULTS: Ten patients (70% female, mean age 62 years) were enrolled. The mean total number of both BL and PLI was constantly decreased during NIN treatment, being significantly reduced after twelve months (from 175.1 ± 66.7-120.8 ± 70.3 for BL, p= 0.005 and from 50.6 ± 32.5-37.2 ± 22.4 for PLI, p= 0.05). Male gender, smoking habit and baseline forced vital capacity <70% predicted were associated with worse LUS outcomes. A greater reduction of both BL and PLI was observed in those who improved in PROMs, especially modified Medical Research Council dyspnoea scale (p= 0.016 and p= 0.04, respectively) and Saint George's Respiratory Questionnaire (p= 0.006 and p= 0.026, respectively). No significant changes in the CALIPER percentages of normal parenchyma or ILD elements were observed after twelve months of NIN, thus paralleling the stabilization obtained at pulmonary function tests. CONCLUSIONS: We present preliminary results on NIN effects on SSc-ILD as assessed by LUS, a useful method for frequently repeated monitoring, and CALIPER, a valid implementation whenever a HRCT is performed.

HRCT1, negatively regulated by miR-124-3p, promotes tumor metastasis and the growth of gastric cancer by activating the ERBB2-MAPK pathway.

BACKGROUND: Gastric cancer is the fourth leading cause of cancer-related deaths worldwide. And patient outcomes are poor due to tumor relapse and metastasis. To develop new therapeutic strategies, it is of great importance to explore the mechanism underlying the progression of gastric cancer. METHODS: Primary gastric cancer samples with lymph node metastases (LNM) and without LNM were subjected to mRNA microarray assay. The differentially expressed genes were confirmed by RT-qPCR. HRCT1 protein expression was further detected using an immunohistochemistry (IHC) assay. In vitro and in vivo assays were performed to investigate the role of HRCT1 in tumor invasion, metastasis, and proliferation. The expressions of the downstream target genes of HRCT1 were detected by microarray, RT-qPCR and Western blot assays. Dual-luciferase reporter and Western blot assays were carried out to identify miRNAs target to HRCT1. RESULTS: HRCT1 was upregulated in gastric cancer, and high expression of HRCT1 was associated with poor overall survival (OS) and disease-free survival (DFS). Moreover, HRCT1protein expression was an independent predictor for poor OS and DFS. HRCT1 could promote gastric cancer cells' migration, invasion, and proliferation in vitro as well as tumor metastasis and growth in vivo. Notably, our data showed that HRCT1 promoted gastric cancer progression by activating the ERBB2-MAPK signaling pathway. At least partially, the expression of HRCT1 could be negatively regulated by miR-124-3p. CONCLUSIONS: The upregulated expression of HRCT1 predicts poor survival for patients with gastric cancer. HRCT1 promotes tumor progression by activating the ERBB2-MAPK pathway. HRCT1, negatively regulated by miR-124-3p, may be a potential therapeutic target for patients with gastric cancer.

The value of lung ultrasound in COVID-19 pneumonia, verified by high resolution computed tomography assessed by artificial intelligence.

BACKGROUND: Lung ultrasound (LUS) is an increasingly popular imaging method in clinical practice. It became particularly important during the COVID-19 pandemic due to its mobility and ease of use compared to high-resolution computed tomography (HRCT). The objective of this study was to assess the value of LUS in quantifying the degree of lung involvement and in discrimination of lesion types in the course of COVID-19 pneumonia as compared to HRCT analyzed by the artificial intelligence (AI). METHODS: This was a prospective observational study including adult patients hospitalized due to COVID-19 in whom initial HRCT and LUS were performed with an interval < 72 h. HRCT assessment was performed automatically by AI. We evaluated the correlations between the inflammation volume assessed both in LUS and HRCT, between LUS results and the HRCT structure of inflammation, and between LUS and the laboratory markers of inflammation. Additionally we compared the LUS results in subgroups depending on the respiratory failure throughout the hospitalization. RESULTS: Study group comprised 65 patients, median 63 years old. For both lungs, the median LUS score was 19 (IQR-interquartile range 11-24) and the median CT score was 22 (IQR 16-26). Strong correlations were found between LUS and CT scores (for both lungs r = 0.75), and between LUS score and percentage inflammation volume (PIV) (r = 0.69). The correlations remained significant, if weakened, for individual lung lobes. The correlations between LUS score and the value of the percentage consolidation volume (PCV) divided by percentage ground glass volume (PGV), were weak or not significant. We found significant correlation between LUS score and C-reactive protein (r = 0.55), and between LUS score and interleukin 6 (r = 0.39). LUS score was significantly higher in subgroups with more severe respiratory failure. CONCLUSIONS: LUS can be regarded as an accurate method to evaluate the extent of COVID-19 pneumonia and as a promising tool to estimate its clinical severity. Evaluation of LUS in the assessment of the structure of inflammation, requires further studies in the course of the disease. TRIAL REGISTRATION: The study has been preregistered 13 Aug 2020 on clinicaltrials.gov with the number NCT04513210.

Artificial intelligence guided HRCT assessment predicts the severity of COVID-19 pneumonia based on clinical parameters.

BACKGROUND: The purpose of the study was to compare the results of AI (artificial intelligence) analysis of the extent of pulmonary lesions on HRCT (high resolution computed tomography) images in COVID-19 pneumonia, with clinical data including laboratory markers of inflammation, to verify whether AI HRCT assessment can predict the clinical severity of COVID-19 pneumonia. METHODS: The analyzed group consisted of 388 patients with COVID-19 pneumonia, with automatically analyzed HRCT parameters of volume: AIV (absolute inflammation), AGV (absolute ground glass), ACV (absolute consolidation), PIV (percentage inflammation), PGV (percentage ground glass), PCV (percentage consolidation). Clinical data included: age, sex, admission parameters: respiratory rate, oxygen saturation, CRP (C-reactive protein), IL6 (interleukin 6), IG - immature granulocytes, WBC (white blood count), neutrophil count, lymphocyte count, serum ferritin, LDH (lactate dehydrogenase), NIH (National Institute of Health) severity score; parameters of clinical course: in-hospital death, transfer to the ICU (intensive care unit), length of hospital stay. RESULTS: The highest correlation coefficients were found for PGV, PIV, with LDH (respectively 0.65, 0.64); PIV, PGV, with oxygen saturation (respectively - 0.53, -0.52); AIV, AGV, with CRP (respectively 0.48, 0.46); AGV, AIV, with ferritin (respectively 0.46, 0.45). Patients with critical pneumonia had significantly lower oxygen saturation, and higher levels of immune-inflammatory biomarkers on admission. The radiological parameters of lung involvement proved to be strong predictors of transfer to the ICU (in particular, PGV ≥ cut-off point 29% with Odds Ratio (OR): 7.53) and in-hospital death (in particular: AIV ≥ cut-off point 831 cm3 with OR: 4.31). CONCLUSIONS: Automatic analysis of HRCT images by AI may be a valuable method for predicting the severity of COVID-19 pneumonia. The radiological parameters of lung involvement correlate with laboratory markers of inflammation, and are strong predictors of transfer to the ICU and in-hospital death from COVID-19. TRIAL REGISTRATION: National Center for Research and Development CRACoV-HHS project, contract number SZPITALE-JEDNOIMIENNE/18/2020.

MUC5B rs35705950 minor allele associates with older age and better survival in idiopathic pulmonary fibrosis.

BACKGROUND AND OBJECTIVE: The minor T-allele of the MUC5B promoter polymorphism rs35705950 is strongly associated with idiopathic pulmonary fibrosis (IPF). However, conflicting results have been reported on the relationship between the MUC5B minor allele and survival and it is unknown whether a specific subgroup of IPF patients might benefit from MUC5B minor allele carriage. We investigated the association between MUC5B rs35705950, survival and patient characteristics in a real-world population of European IPF patients. METHODS: In this retrospective study, 1751 patients with IPF from 8 European centres were included. MUC5B rs35705950 genotype, demographics, clinical characteristics at diagnosis and survival data were analysed. RESULTS: In a multi-variate Cox proportional hazard model the MUC5B minor allele was a significant independent predictor of survival when adjusted for age, sex, high resolution computed tomography pattern, smoking behaviour and pulmonary function tests in IPF. MUC5B minor allele carriers were significantly older at diagnosis (p = 0.001). The percentage of MUC5B minor allele carriers increased significantly with age from 44% in patients aged <56 year, to 63% in patients aged >75. In IPF patients aged <56, the MUC5B minor allele was not associated with survival. In IPF patients aged ≥56, survival was significantly better for MUC5B minor allele carriers (45 months [CI: 42-49]) compared to non-carriers (29 months [CI: 26-33]; p = 4 × 10-12 ). CONCLUSION: MUC5B minor allele carriage associates with a better median transplant-free survival of 16 months in the European IPF population aged over 56 years. MUC5B genotype status might aid disease prognostication in clinical management of IPF patients.

Predictors of pulmonary hypertension in patients with hypersensitivity pneumonitis.

BACKGROUND: Hypersensitivity pneumonitis (HP) is an immunologically induced inflammation of the lung parenchyma that occurs in susceptible individuals in response to a variety of antigens. Repeated exposures to the causative antigens lead to chronic HP. The condition could be complicated with pulmonary hypertension (PH). METHODOLOGY: 60 patients with established diagnosis of HP were included, clinical examination, high resolution computed tomography (HRCT) of chest, arterial blood gases, six minute walking test (6MWT), desaturation index, spirometry, echocardiography were performed to all patients and right heart catheter was done for patients with high echo probability of PH. RESULTS: The mean age of patients was 41.67 ± 13.4 years with female predominance 83.3% of patients had history of raising birds. 71.7% of cases suffered from resting hypoxia with oxygen saturation 89 ± 11% with desaturation index 9% ± 8%, Echo probability of PH ranged from low to high 71.67, 21.67 and 6.67% respectively, mean pulmonary artery systolic pressure was 63.65 (18.48) mmHg. PH was diagnosed in 17 (28.33%) patients. HP with PH patients were significantly more symptomatic with predominant fibrotic pattern in HRCT chest P < 0.001, 82% of them had hypoxia P < 0.001 with significant desaturation after 6MWT P = 0.001. Predictors of PH in study group were fibrotic pattern in HRCT chest and hypoxia OR = 62.22, P < 0.001; 49.2, P < 0.001 respectively. CONCLUSION: PH was prevalent in 28.33% of patients with HP, predictors of development of PH were fibrotic pattern in HRCT chest and hypoxia. TRIAL REGISTRATION: Retrospectively registered, registration number is NCT05458635, date of registration 07/12/2022.

Assessment of cardiopulmonary manifestations and its correlation with semi-quantitative scoring of high-resolution computed tomography in patients with autoimmune rheumatic diseases.

PURPOSE: Autoimmune rheumatic diseases (ARD) are groups of diseases that are commonly associated with cardiac and pulmonary manifestations and may affect the morbidity and mortality of the patients. The study aimed to the assessment of cardiopulmonary manifestations and their correlation with the semi-quantitative scoring of high-resolution computed tomography (HRCT) in ARD patients. METHODS AND PATIENTS: 30 patients with ARD were included in the study (mean age 42.2 ± 9.76 years) [10 patients were scleroderma (SSc), 10 patients were rheumatoid arthritis (RA), and 10 patients were systemic lupus erythematosus (SLE)]. They all met the diagnostic criteria of the American College of Rheumatology and underwent spirometry, echocardiography, and chest HRCT. The HRCT was assessed by a semi-quantitative score for parenchymal abnormalities. Correlation between HRCT lung scores and: inflammatory markers, lung volumes in spirometry, and echocardiographic indices has been performed. RESULTS: The total lung score (TLS) by HRCT was 14.8 ± 8.78 (mean ± SD), ground glass opacity score (GGO) was 7.20 ± 5.79 (mean ± SD) and fibrosis lung score (F) was 7.63 ± 6.05 (mean ± SD). TLS correlated significantly with ESR (r 0.528, p 0.003), CRP (r 0.439, p 0.015), PaO2 (r -0.395, P 0.031) FVC% (r -0.687, p 0.001), and echocardiographic Tricuspid E (r -0.370, p 0.044), Tricuspid E/è (r -0.397,p 0.03), ESPAP (r 0.459,p 0.011), TAPSE (r -0.405, p 0.027), MPI-TDI (r -0.428, p 0.018) and RV Global strain(r -0.567, p 0.001). GGO score correlated significantly with ESR (r 0.597, p 0.001), CRP (r 0.473, p 0.008), FVC% (r -0.558, p 0.001), and RV Global strain(r -0.496, p 0.005). F score correlated significantly with FVC% (r -0.397, p 0.030), Tricuspid E/è (r -0.445, p 0.014), ESPAP (r 0.402, p 0.028), and MPI-TDI (r -0.448, p 0.013). CONCLUSION: The total lung score and GGO score in ARD were found to be consistently significantly correlated with FVC% predicted, PaO2, inflammatory markers, and RV functions. Fibrotic score correlated with ESPAP. Therefore, in a clinical setting, most clinicians who monitor patients suffering from ARD should concern with the applicability of semiquantitative HRCT scoring in clinical practice.

Tetrandrine slows the radiographic progression of progressive massive fibrosis in pneumoconiosis: a retrospective cohort study.

OBJECTIVE: This study aims to explore the clinical effect of Tetrandrine (Tet) on progressive massive fibrosis (PMF) of pneumoconiosis. METHODS: This retrospective study collected 344 pneumoconiosis patients with PMF, and 127 were eligible for the final analysis, including 57 patients in the Tet group and 70 patients in the control group. The progress of imaging and lung function were compared between the two groups. RESULTS: After 13 months (median) of treatment, the size of PMF was smaller in the Tet group than that in the control group (1526 vs. 2306, p=0.001), and the size was stable in the Tet group (1568 vs. 1526, p= 0.381), while progressed significantly in the control group (2055 vs. 2306, p=0.000). The small nodule profusion and emphysema were also milder than that in the control group (6.0 vs. 7.5, p=0.046 and 8.0 vs. 12, p=0.016 respectively). Pulmonary ventilation function parameters FVC and FEV1 improved in the Tet group (3222 vs. 3301, p=0.021; 2202 vs. 2259, p=0.025 respectively) and decreased in the control group (3272 vs. 3185, p= 0.00; 2094 vs. 1981, p=0.00 respectively). FEV1/FVC was also significantly higher in the Tet group than that in the control group (68.45vs. 60.74, p=0.001). However, similar result was failed to observed for DLco%, which showed a significant decrease in both groups. CONCLUSION: Tet has shown great potential in the treatment of PMF by slowing the progression of pulmonary fibrosis and the decline of lung function.

Correlation of the High-Resolution Computed Tomography Patterns of Intrathoracic Sarcoidosis with Serum Levels of SAA, CA 15.3, SP-D, and Other Biomarkers of Interstitial Lung Disease.

Studies on the serum biomarkers of granulomatous inflammation and pulmonary interstitial disease in intrathoracic sarcoidosis have shown conflicting results. We postulated that differences in the concentrations of serum biomarkers can be explained by the heterogenous patterns of sarcoidosis seen on thoracic HRCT. Serum biomarker levels in 79 consecutive patients, newly diagnosed with intrathoracic sarcoidosis, were compared to our control group of 56 healthy blood donors. An analysis was performed with respect to HRCT characteristics (the presence of lymph node enlargement, perilymphatic or peribronchovascular infiltrates, ground-glass lesions, or fibrosis), CXR, and disease extent. Serum levels of CXCL9, CXCL10, CTO, and CCL18 were statistically significantly increased in all patients compared to controls. Serum levels of CA15.3 were statistically significantly increased in all patients with parenchymal involvement. SAA was increased in patients with ground-glass lesions while SP-D levels were statistically significantly increased in patients with lung fibrosis. Only SP-D and CA15.3 showed a significant correlation to interstitial disease extent. In conclusion, we found that sarcoidosis patients with different HRCT patterns of intrathoracic sarcoidosis have underlying biochemical differences in their serum biomarkers transcending Scadding stages. The stratification of patients based on both radiologic and biochemical characteristics could enable more homogenous patient selection for further prognostic studies.

Patients with Diabetes Experienced More Serious and Protracted Sickness from the COVID-19 Infection: A Prospective Study.

Background and Objectives: In December 2019, a flu-like illness began in the Chinese city of Wuhan. This sickness mainly affected the lungs, ranging from a minor respiratory tract infection to a severe lung involvement that mimicked the symptoms of Severe Acute Respiratory Syndrome (SARS). The World Health Organization (WHO) labelled this sickness as a pandemic in March 2020, after it quickly spread throughout the world population. It became clear, as the illness progressed, that people with concomitant illnesses, particularly diabetes mellitus (DM) and other immunocompromised states, were outmatched by this illness. This study was aimed to evaluate the correlation between Computed Tomographic Severity Score (CTSS) and underlying diabetes mellitus in coronavirus disease (COVID)-19 patients. Materials and Methods: This was a hospital-based prospective study in which a total of 152 patients with reverse transcriptase polymerase chain reaction (RT-PCR) positive COVID status who underwent high-resolution computed tomography (HRCT) of the chest were evaluated and categorized into mild, moderate and severe cases based on the extent of lung parenchymal involvement. A total score from 0-25 was given, based on the magnitude of lung involvement. Statistical analysis was used to derive a correlation between DM and CTSS, if any. Results: From our study, it was proven that patients with underlying diabetic status had more severe involvement of the lung as compared to non-diabetics, and it was found to be statistically significant (p = 0.024). Conclusions: On analysis of what we found based on the study, it can be concluded that patients with underlying diabetic status had a more prolonged and severe illness in comparison to non-diabetics, with higher CTSS in diabetics than in non-diabetics.

One-year pulmonary impairment after severe COVID-19: a prospective, multicenter follow-up study.

BACKGROUND: Long-term pulmonary sequelae following hospitalization for SARS-CoV-2 pneumonia is largely unclear. The aim of this study was to identify and characterise pulmonary sequelae caused by SARS-CoV-2 pneumonia at 12-month from discharge. METHODS: In this multicentre, prospective, observational study, patients hospitalised for SARS-CoV-2 pneumonia and without prior diagnosis of structural lung diseases were stratified by maximum ventilatory support ("oxygen only", "continuous positive airway pressure (CPAP)" and "invasive mechanical ventilation (IMV)") and followed up at 12 months from discharge. Pulmonary function tests and diffusion capacity for carbon monoxide (DLCO), 6 min walking test, high resolution CT (HRCT) scan, and modified Medical Research Council (mMRC) dyspnea scale were collected. RESULTS: Out of 287 patients hospitalized with SARS-CoV-2 pneumonia and followed up at 1 year, DLCO impairment, mainly of mild entity and improved with respect to the 6-month follow-up, was observed more frequently in the "oxygen only" and "IMV" group (53% and 49% of patients, respectively), compared to 29% in the "CPAP" group. Abnormalities at chest HRCT were found in 46%, 65% and 80% of cases in the "oxygen only", "CPAP" and "IMV" group, respectively. Non-fibrotic interstitial lung abnormalities, in particular reticulations and ground-glass attenuation, were the main finding, while honeycombing was found only in 1% of cases. Older patients and those requiring IMV were at higher risk of developing radiological pulmonary sequelae. Dyspnea evaluated through mMRC scale was reported by 35% of patients with no differences between groups, compared to 29% at 6-month follow-up. CONCLUSION: DLCO alteration and non-fibrotic interstitial lung abnormalities are common after 1 year from hospitalization due to SARS-CoV-2 pneumonia, particularly in older patients requiring higher ventilatory support. Studies with longer follow-ups are needed.

Investigation of the relationship of CO-RADS and CT patterns with laboratory parameters in COVID-19 patients and a new perspective on the total CT scoring system.

BACKGROUND: It is important to determine the correlation of the CO-RADS classification and computed tomography (CT) patterns of the lung with laboratory data. To investigate the relationship of CO-RADS categories and CT patterns with laboratory data in patients with a positive RT-PCR test. We also developed a structured total CT scoring system and investigated its correlation with the total CT scoring system. METHOD: The CT examinations of the patients were evaluated in terms of the CO-RADS classification, pattern groups and total CT score. Structured total CT score values were obtained by including the total CT score values and pattern values in a regression analysis. The CT data were compared according to the laboratory data. RESULTS: A total of 198 patients were evaluated. There were significant differences between the CO-RADS groups in terms of age, ICU transfer, oxygen saturation, creatinine, LDH, D-dimer, high-sensitivity cardiac troponin-T (hs-TnT), CRP, structured total CT score values, and total CT score values. A significant difference was also observed between the CT pattern groups and oxygen saturation, creatinine and CRP values. When the structured total CT score values and total CT score values were compared they were observed to be correlated. CONCLUSIONS: Creatinine can be considered as an important marker for the CO-RADS and pattern classifications in lung involvement. LDH can be considered as an important marker of parenchymal involvement, especially bilateral and diffuse involvement. The structured total CT scoring system is a new system that can be used as an alternative.

Quantitative imaging analysis detects subtle airway abnormalities in symptomatic military deployers.

BACKGROUND: Exposure to inhalational hazards during post-9/11 deployment to Southwest Asia and Afghanistan puts military personnel at risk for respiratory symptoms and disease. Pulmonary function and qualitative chest high resolution computed tomography (HRCT) are often normal in "deployers" with persistent respiratory symptoms. We explored the utility of quantitative HRCT imaging markers of large and small airways abnormalities, including airway wall thickness, emphysema, and air trapping, in symptomatic deployers with clinically-confirmed lung disease compared to controls. METHODS: Chest HRCT images from 45 healthy controls and 82 symptomatic deployers with asthma, distal lung disease or both were analyzed using Thirona Lung quantification software to calculate airway wall thickness (by Pi10), emphysema (by percentage of lung volume with attenuation < -950 Hounsfield units [LAA%-950]), and three parameters of air trapping (expiratory/inspiratory total lung volume and mean lung density ratios, and LAA%-856). SAS v.9.4 was used to compare demographic and clinical characteristics between deployers and controls using Chi-Square, Fisher Exact or t-tests. Linear regression was used to assess relationships between pulmonary function and quantitative imaging findings. RESULTS: Gender and smoking status were not statistically significantly different between groups, but deployers were significantly younger than controls (42 vs 58 years, p < 0.0001), had higher body mass index (31 vs 28 kg/m2, p = 0.01), and had fewer total smoking pack-years (8 vs. 26, p = 0.007). Spirometric measures were not statistically significantly different between groups. Pi10 and LAA%-950 were significantly elevated in deployers compared to controls in unadjusted analyses, with the emphysema measure remaining significantly higher in deployers after adjustment for age, sex, smoking, BMI, and expiratory total lung volume. Air trapping parameters were more common in control images, likely due to differences in age and smoking between groups. Among deployers, LAA%-950 and Pi10 were significantly correlated with spirometric markers of obstruction based on ratio of forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) and/or percent predicted FEV1. CONCLUSIONS: Quantitative chest HRCT imaging analysis identifies emphysema in deployers with asthma and distal lung disease, and may be useful in detecting and monitoring deployment-related lung disease in a population where spirometry is typically normal.

The new useful high-resolution computed tomography finding for diagnosing fibrotic hypersensitivity pneumonitis: "hexagonal pattern": a single-center retrospective study.

BACKGROUND: Centrilobular nodules, ground-glass opacity (GGO), mosaic attenuation, air trapping, and three-density pattern were reported as high-resolution computed tomography (HRCT) findings characteristic of fibrotic hypersensitivity pneumonitis (HP). However, it is often difficult to differentiate fibrotic HP from idiopathic pulmonary fibrosis (IPF). In fibrotic HP, the HRCT sometimes shows tortoiseshell-like interlobular septal thickening that extends from the subpleural lesion to the inner layers. This finding is called "hexagonal pattern," and this study is focused on the possibility that such finding is useful for differentiating fibrotic HP from IPF. METHODS: This study included patients with multidisciplinary discussion (MDD) diagnosis of fibrotic HP or IPF undergoing surgical lung biopsy between January 2015 and December 2017 in Kanagawa Cardiovascular and Respiratory Center. Two radiologists have evaluated the HRCT findings without clinical and pathological information. RESULTS: A total of 23 patients were diagnosed with fibrotic HP by MDD and 48 with IPF. Extensive GGO, centrilobular nodules, and hexagonal pattern were more frequent findings in fibrotic HP than in IPF. No significant difference was observed between the two groups in the presence or absence of mosaic attenuation, air trapping, or three-density pattern. In the multivariate logistic regression, the presence of extensive GGO and hexagonal pattern was associated with increased odds ratio of fibrotic HP. The sensitivity and specificity of the diagnosis of fibrotic HP in the presence of the hexagonal pattern were 69.6% and 87.5%, respectively. CONCLUSION: Hexagonal pattern is a useful finding for differentiating fibrotic HP from IPF.