scholarly journals A New Scoring System Combining A Four-Section Honeycomb Lung Percentage on HRCT and Other Comprehensive Multiparameter for Evaluating Pulmonary Fibrosis Severity

2020 ◽  
Author(s):  
Chengsheng Yin ◽  
Yuan Zhang ◽  
Yiliang Su ◽  
Feng Zhang ◽  
Jingyun Shi ◽  
...  
Keyword(s):  
Pulmonary Fibrosis ◽  
Pulmonary Function ◽  
Correlation Coefficient ◽  
Predictive Accuracy ◽  
New Method ◽  
Fibrosis Stage ◽  
Physiological Parameter ◽  
Death Risk ◽  
Severity Grade ◽  
Fibrosis Staging

Abstract Background: How to accurately assess IPF severity and predict prognosis remains a problem. This study aimed to develop a new method, which can be easily used to assess pulmonary fibrosis severity.Method:1. Development of a HRCT combined pulmonary function & physiological parameter (CTPF) assessment method: The method included two parts. 1) CT-based fibrosis staging: Four representative lung CT sections were selected and evenly divided into 100 small areas. The percentage of honeycomb lesion area in the four sections was determined fibrosis stage,2) PF-based severity grade: FVC%pred,DLco%pred,SpO2% age and gender were used to assess PF severity grade. 2. Validation of the new method: The method was used to assess 192 patients with IPF. Two radiologists used the CT-based fibrosis staging method to determine the fibrosis stage. Pulmonologist determined the PF severity grade. 3. Statistical analyses: By Intra-group correlation coefficient and Spearman correlation coefficient to estimate the consistency between the CT scores from the two radiologists and the correlation between CT scores and lung function parameters. Using the competitive risk Fine–Gray model to analyze the relationship between CT-based stage/PF-based grade and prognosis. CT-based stage, PF-based grade, and GAP stage were used as predictor models to predicted the death risk. Results: 1. The intra-group correlation coefficient of the CT scores of the two radiologists was 0.95, P<0.05. 2. The CT scores negatively correlated with pulmonary function. 3. The CTPF comprehensive model, showed higher predictive accuracy.Conclusion: Combined CT-based staging and PF-based grading methods CTPF can be adopted easily in clinical practice, and can assess IPF severity and predict death risk more accurately.

scholarly journals Development and Validation of a Comprehensive Multiparameter-based Scoring System to Assess Pulmonary Fibrosis Severity

2020 ◽  
Author(s):  
Chengsheng Yin ◽  
Yuan Zhang ◽  
Yiliang Su ◽  
Feng Zhang ◽  
Jingyun Shi ◽  
...  
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Pulmonary Function ◽  
Correlation Coefficient ◽  
Assessment Method ◽  
New Method ◽  
Fibrosis Stage ◽  
Death Risk ◽  
Severity Grade ◽  
Fibrosis Staging

Abstract Background Survival time varies greatly in patients with idiopathic pulmonary fibrosis (IPF). An assessment method that can accurately assess the severity and prognosis of idiopathic pulmonary fibrosis is currently lacking. This study aimed to develop a new method, which can be easily used to assess pulmonary fibrosis severity. Method 1. Development of a HRCT combined pulmonary function & physiological parameter (CTPF) assessment method: The method included two parts. 1) CT-based fibrosis staging: Four representative lung CT sections were selected and evenly divided into 100 small areas. The percentage of honeycomb lesion area in the four sections was determined fibrosis stage,2) PF-based severity grade: FVC%pred,DLco%pred,SpO2% age and gender were used to assess PF severity grade. 2. Validation of the new method: The method was used to assess 192 patients with IPF. Two radiologists used the CT-based fibrosis staging method to determine the fibrosis stage. Pulmonologist determined the PF severity grade. 3. Statistical analyses: Intra-group correlation coefficient to estimate the consistency between the CT scores from the two radiologists. Spearman correlation coefficient to evaluate the correlation between CT scores and lung function parameters. The competitive risk Fine–Gray model was used to analyze the relationship between CT-based stage/PF-based grade and prognosis. CT-based stage, PF-based grade, and GAP stage were used as predictors to predicted the death risk. Results 1. The intra-group correlation coefficient of the CT scores of the two radiologists was 0.95, P<0.05. 2. The CT scores negatively correlated with pulmonary function. 3. The CTPF comprehensive model, showed higher predictive accuracy. Conclusion Combined CT-based staging and PF-based grading methods CTPF can be adopted easily in clinical practice, and can assess IPF severity and predict death risk more accurately.

scholarly journals Liver fibrosis staging by deep learning: a visual-based explanation of diagnostic decisions of the model

2021 ◽  
Author(s):  
Yunchao Yin ◽  
Derya Yakar ◽  
Rudi A. J. O. Dierckx ◽  
Kim B. Mouridsen ◽  
Thomas C. Kwee ◽  
...  
Keyword(s):  
Deep Learning ◽  
Liver Fibrosis ◽  
Liver Parenchyma ◽  
Ct Images ◽  
Fibrosis Stage ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Liver Surface ◽  
Fibrosis Staging

Abstract Objectives Deep learning has been proven to be able to stage liver fibrosis based on contrast-enhanced CT images. However, until now, the algorithm is used as a black box and lacks transparency. This study aimed to provide a visual-based explanation of the diagnostic decisions made by deep learning. Methods The liver fibrosis staging network (LFS network) was developed at contrast-enhanced CT images in the portal venous phase in 252 patients with histologically proven liver fibrosis stage. To give a visual explanation of the diagnostic decisions made by the LFS network, Gradient-weighted Class Activation Mapping (Grad-cam) was used to produce location maps indicating where the LFS network focuses on when predicting liver fibrosis stage. Results The LFS network had areas under the receiver operating characteristic curve of 0.92, 0.89, and 0.88 for staging significant fibrosis (F2–F4), advanced fibrosis (F3–F4), and cirrhosis (F4), respectively, on the test set. The location maps indicated that the LFS network had more focus on the liver surface in patients without liver fibrosis (F0), while it focused more on the parenchyma of the liver and spleen in case of cirrhosis (F4). Conclusions Deep learning methods are able to exploit CT-based information from the liver surface, liver parenchyma, and extrahepatic information to predict liver fibrosis stage. Therefore, we suggest using the entire upper abdomen on CT images when developing deep learning–based liver fibrosis staging algorithms. Key Points • Deep learning algorithms can stage liver fibrosis using contrast-enhanced CT images, but the algorithm is still used as a black box and lacks transparency. • Location maps produced by Gradient-weighted Class Activation Mapping can indicate the focus of the liver fibrosis staging network. • Deep learning methods use CT-based information from the liver surface, liver parenchyma, and extrahepatic information to predict liver fibrosis stage.

scholarly journals Breathing Well Across the Lifespan: Pulmonary Aging and Geroscience-Targeted Therapies

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 749-749
Author(s):  
Jason Sanders
Keyword(s):  
Pulmonary Fibrosis ◽  
Pulmonary Function ◽  
Pulmonary Diseases ◽  
Human Populations ◽  
Aging Research ◽  
Novel Treatments ◽  
Organ Specific ◽  
Nutrient Signaling ◽  
Telomere Biology ◽  
Increased Susceptibility

Abstract Excellent pulmonary function is one of the strongest predictors of longevity across animal models and human populations. Unfortunately, none of the major age-associated pulmonary diseases – obstructive lung disease, pulmonary fibrosis, and increased susceptibility to pneumonia – have strongly effective disease modifying therapies. There is growing evidence that normal age-associated decline in pulmonary function and major age-associated pulmonary diseases are linked to the hallmarks of aging including senescence, nutrient signaling dysregulation, mitochondrial dysfunction, and telomere disorders. This presents opportunities for collaboration between gerontologists and pulmonologists to unravel age-associated developmental mechanisms and design novel treatments. In this symposium, leaders in pulmonary aging research will present novel data on links between aging and pulmonary health and geroscience-based interventions under study. Dr. Sanders will provide an overview of the scientific and clinical space and present epidemiologic associations between aging biomarkers, early pulmonary fibrosis, and mortality. Dr. Le Saux will discuss senescence and specifically how eicosanoid biology may explain organ-specific patterns of senescence-associated fibrosis. Dr. Thannickal will discuss age-associated perturbations in metabolism and mitochondrial function and targeting these pathways to improve lung function and treat pulmonary diseases. Dr. Newton will discuss mechanisms and clinical applications of telomere biology to pulmonary aging. Symposium attendees will (1) be poised to generate collaborations between gerontologists and pulmonologists to address existing knowledge gaps in mechanisms of pulmonary aging, and (2) develop a better understanding of translational opportunities to design geroscience-based diagnostics and therapeutics to improve pulmonary health with aging.

scholarly journals Hybrid Krill Herd-ANN Model for Prediction Strength and Stiffness of Bolted Connections

Buildings ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 229
Author(s):  
Iman Faridmehr ◽  
Mehdi Nikoo ◽  
Mohammad Hajmohammadian Baghban ◽  
Raffaele Pucinotti
Keyword(s):  
Correlation Coefficient ◽  
Predictive Accuracy ◽  
Supply And Demand ◽  
Steel Structures ◽  
Ann Model ◽  
Krill Herd Algorithm ◽  
Seat Angle ◽  
Taylor Diagram ◽  
Krill Herd ◽  
Strength And Stiffness

The behavior of beam-to-column connections significantly influences the stability, strength, and stiffness of steel structures. This is particularly important in extreme non-elastic responses, i.e., earthquakes, and sudden column removal, as the fluctuation in strength and stiffness affects both supply and demand. Accordingly, it is essential to accurately estimate the strength and stiffness of connections in the analysis of and design procedures for steel structures. Beginning with the state-of-the-art, the capacity of three available component-based mechanical models to estimate the complex mechanical properties of top- and seat-angle connections with double-web angles (TSACWs), with variable parameters, were investigated. Subsequently, a novel hybrid krill herd algorithm-artificial neural network (KHA-ANN) model was proposed to acquire an informational model from the available experimental dataset. Using several statistical metrics, including the corresponding coefficient of variation (CoV), correlation coefficient (R), and the correlation coefficient provided by the Taylor diagram, this study revealed that the krill herd-ANN model achieved the most reliable predictive accuracy for the strength and stiffness of top- and seat-angle connections with double web angles.

scholarly journals Preliminary Analysis of the Therapeutic Mechanism of Feiluoning in Convalescent Patients With COVID-19

2020 ◽  
Vol 15 (12) ◽  
pp. 1934578X2097762
Author(s):  
Zongchao Hong ◽  
Maolin Hong ◽  
Bo Liu ◽  
Ying Zhang ◽  
Yanfang Yang ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Pulmonary Fibrosis ◽  
Pulmonary Function ◽  
Target Genes ◽  
Interaction Analysis ◽  
Binding Capacity ◽  
Chemical Constituents ◽  
The Core ◽  
Target Network ◽  
Compound Target

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), is often accompanied by injury to pulmonary function and pulmonary fibrosis. Feiluoning (FLN) is a new Chinese medicine prescription which is available for the treatment of severe and critical convalescence of COVID-19 patients. FLN also has a positive effect on pulmonary function injury and pulmonary fibrosis. We explored the potential mechanism of FLN’s effect on the convalescent treatment of COVID-19. According to the pharmacodynamic activity parameters, we screened the active chemical constituents of FLN by comparing the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The Uniprot database was used to querying the corresponding target genes, and Cytoscape 3.6.1 was used to construct a herb-compound-target network. Protein interaction analysis, target gene function enrichment analysis, and signal pathway analysis were performed using the STRING, DAVID, and Kyoto Encyclopedia of Genes and Genomes pathway databases. Molecular docking was used to predict the binding capacity of the core compound with COVID-19 hydrolase 3 Cl and angiotensin-converting enzyme 2 (ACE2). The herb-compound-target network was successfully constructed and key targets identified, including prostaglandin G/H synthase 2, estrogen receptor 1, heat shock protein HSP 90, and androgen receptor. The major affected metabolic pathways were pathways in cancer, pancreatic cancer, nonsmall cell lung cancer, and toll-like receptor signaling. The core compounds of FLN, including quercetin, luteolin, kaempferol, and stigmasterol, could strongly bind to COVID-19 3 Cl hydrolase, and other compounds, including 7-O-methylisomucronulatol and medicocarpin, could strongly bind to ACE2. Thus, it is predicted that FLN has the characteristics of a multicomponent, multitarget, and multichannel overall control compound. FLN’s mechanism of action in the treatment of COVID-19 may be associated with the regulation of inflammation and immune-related signaling pathways, and the influence of COVID-19 3 Cl hydrolase binding ability.

scholarly journals Annual changes in pulmonary function in combined pulmonary fibrosis and emphysema: Over a 5-year follow-up

2013 ◽  
Vol 107 (12) ◽  
pp. 1986-1992 ◽  
Author(s):  
Yoshiaki Kitaguchi ◽  
Keisaku Fujimoto ◽  
Ryoichi Hayashi ◽  
Masayuki Hanaoka ◽  
Takayuki Honda ◽  
...  
Keyword(s):  
Pulmonary Fibrosis ◽  
Pulmonary Function ◽  
Annual Changes

Pulmonary Function Tests and Idiopathic Pulmonary Fibrosis

CHEST Journal ◽  
1997 ◽  
Vol 111 (1) ◽  
pp. 7-8 ◽  
Author(s):  
Steven H. Kirtland ◽  
Richard H. Winterbauer
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Pulmonary Function ◽  
Pulmonary Function Tests ◽  
Function Tests

Vague Correlation Coefficient of Interval Vague Sets and its Applications to Topsis in MADM Problems

2014 ◽  
pp. 140-173
Author(s):  
John Robinson P. ◽  
Henry Amirtharaj E. C.
Keyword(s):  
Fuzzy Sets ◽  
Correlation Coefficient ◽  
Intuitionistic Fuzzy Sets ◽  
New Method ◽  
Numerical Illustration ◽  
Vague Sets ◽  
Intuitionistic Fuzzy ◽  
Statistical Confidence ◽  
Order Preference ◽  
Novel Method

Various attempts are made by researchers on the study of vagueness of data through Intuitionistic Fuzzy sets and Vague sets, and also it is shown that Vague sets are Intuitionistic Fuzzy sets. However, there are algebraic and graphical differences between Vague sets and Intuitionistic Fuzzy sets. In this chapter, an attempt is made to define the correlation coefficient of Interval Vague sets lying in the interval [0,1], and a new method for computing the correlation coefficient of interval Vague sets lying in the interval [-1,1] using a-cuts over the vague degrees through statistical confidence intervals is also presented by an example. The new method proposed in this work produces a correlation coefficient in the form of an interval. The proposed method produces a correlation coefficient in the form of an interval from a trapezoidal shaped fuzzy number derived from the vague degrees. This chapter also aims to develop a new method based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to solve MADM problems for Interval Vague Sets (IVSs). A TOPSIS algorithm is constructed on the basis of the concepts of the relative-closeness coefficient computed from the correlation coefficient of IVSs. This novel method also identifies the positive and negative ideal solutions using the correlation coefficient of IVSs. A numerical illustration explains the proposed algorithms and comparisons are made with some existing methods.

Sign in / Sign up

Export Citation Format

Share Document