Aimed at the issues of high feature dimensionality,excessive data redundancy,and low recognition accuracy of using single classifiers on ground-glass lung nodule recognition,a recognition method was proposed based on ...Aimed at the issues of high feature dimensionality,excessive data redundancy,and low recognition accuracy of using single classifiers on ground-glass lung nodule recognition,a recognition method was proposed based on CatBoost feature selection and Stacking ensemble learning.First,the method uses a feature selection algorithm to filter important features and remove features with less impact,achieving the effect of data dimensionality reduction.Second,random forests classifier,decision trees,K-nearest neighbor classifier,and light gradient boosting machine were used as base classifiers,and support vector machine was used as meta classifier to fuse and construct the ensemble learning model.This measure increases the accuracy of the classification model while maintaining the diversity of the base classifiers.The experimental results show that the recognition accuracy of the proposed method reaches 94.375%.Compared to the random forest algorithm with the best performance among single classifiers,the accuracy of the proposed method is increased by 1.875%.Compared to the recent deep learning methods(ResNet+GBM+Attention and MVCSNet)on ground-glass pulmonary nodule recognition,the proposed method’s performance is also better or comparative.Experiments show that the proposed model can effectively select features and make recognition on ground-glass pulmonary nodules.展开更多
BACKGROUND In recent years,the detection rate of ground-glass nodules(GGNs)has been improved dramatically due to the popularization of low-dose computed tomography(CT)screening with high-resolution CT technique.This p...BACKGROUND In recent years,the detection rate of ground-glass nodules(GGNs)has been improved dramatically due to the popularization of low-dose computed tomography(CT)screening with high-resolution CT technique.This presents challenges for the characterization and management of the GGNs,which depends on a thorough investigation and sufficient diagnostic knowledge of the GGNs.In most diagnostic studies of the GGNs,morphological manifestations are used to differentiate benignancy and malignancy.In contrast,few studies are dedicated to the assessment of the hemodynamics,i.e.,perfusion parameters of the GGNs.AIM To assess the dual vascular supply patterns of GGNs on different histopathology and opacities.METHODS Forty-seven GGNs from 47 patients were prospectively included and underwent the dynamic volume CT.Histopathologic diagnoses were obtained within two weeks after the CT examination.Blood flow from the bronchial artery[bronchial flow(BF)]and pulmonary artery[pulmonary flow(PF)]as well as the perfusion index(PI)=[PF/(PF+BF)]were obtained using first-pass dual-input CT perfusion analysis and compared respectively between different histopathology and lesion types(pure or mixed GGNs)and correlated with the attenuation values of the lesions using one-way ANOVA,student’s t test and Pearson correlation analysis.RESULTS Of the 47 GGNs(mean diameter,8.17 mm;range,5.3-12.7 mm),30(64%)were carcinoma,6(13%)were atypical adenomatous hyperplasia and 11(23%)were organizing pneumonia.All perfusion parameters(BF,PF and PI)demonstrated no significant difference among the three conditions(all P>0.05).The PFs were higher than the BFs in all the three conditions(all P<0.001).Of the 30 GGN carcinomas,14 showed mixed GGNs and 16 pure GGNs with a higher PI in the latter(P<0.01).Of the 17 benign GGNs,4 showed mixed GGNs and 13 pure GGNs with no significant difference of the PI between the GGN types(P=0.21).A negative correlation(r=-0.76,P<0.001)was demonstrated between the CT attenuation values and the PIs in the 30 GGN carcinomas.CONCLUSION The GGNs are perfused dominantly by the PF regardless of its histopathology while the weight of the BF in the GGN carcinomas increases gradually during the progress of its opacification.展开更多
AIM:To obtain the diagnostic performance of percu-taneous transthoracic needle biopsy(PTNB)under Computed tomography(CT)fuoroscopy guidance for lung ground-glass opacity(GGO).METHODS:We searched for English-and Chines...AIM:To obtain the diagnostic performance of percu-taneous transthoracic needle biopsy(PTNB)under Computed tomography(CT)fuoroscopy guidance for lung ground-glass opacity(GGO).METHODS:We searched for English-and Chinese-language studies in PubMed,EMBASE,EBSCO,OVID,and CNKI(China National Knowledge Infrastructure)database.Data were calculated with Meta-Disc version 1.4 and Rev Man version 5.2 software.From the pooled data,we calculated sensitivity(Sen),specificity(Spe),positive likelihood ratio(+LR),negative likelihood ratio(-LR),and diagnostic odds ratio(DOR).Summary receiver operating characteristic(SROC)curves were constructed and incidence of complications was recorded.RESULTS:Four documents included in this present meta-analysis met the criteria for analysis.The pooled Sen,Spe,+LR,-LR and DOR with 95%CI were 0.91(0.86-0.95),1.0(0.91-1.0),18.64(4.83-71.93),0.11(0.05-0.26)and 153.17(30.78-762.33),respectively.The area under the SROC curve was 0.98.The incidence of pneumothorax and hemoptysis was 17.86%-51.80%and 10.50%-19.40%,respectively.CONCLUSION:CT fuoroscopy-guided PTNB,which has an acceptable incidence of complications,can be used as a primary examination method for lung GGO,with moderate sensitivity and specifcity.展开更多
This study examined the value of volume rendering （VR） interpretation in assessing the growth of pulmonary nodular ground-glass opacity （nGGO）. A total of 47 nGGOs （average size, 9.5 mm; range, 5.7-20.6 mm） were...This study examined the value of volume rendering （VR） interpretation in assessing the growth of pulmonary nodular ground-glass opacity （nGGO）. A total of 47 nGGOs （average size, 9.5 mm; range, 5.7-20.6 mm） were observed by CT scanning at different time under identical parameter settings. The growth of nGGO was analyzed by three radiologists by comparing the thin slice （TS） CT images of initial and repeat scans with side-by-side cine mode. One week later synchronized VR images of the two scans were compared by side-by-side cine mode to evaluate the nGGO growth. The nodule growth was rated on a 5-degree scale： notable growth, slight growth, dubious growth, stagnant growth, shrinkage. Growth standard was defined as： Density increase 〉 30 HU and （or） diameter increase （by 20% in nodules 〉_10 mm, 30% in nodules of 5-9 mm）. Receiver operating characteristic （ROC） was performed. The results showed that 32 nGGOs met the growth criteria （29 nGGOs showed an increase in density; 1 nGGO showed an increase in diameter; 2 nGGOs showed an increase in both diameter and density）. Area under ROC curve revealed that the performance with VR interpretation was better than that with TS interpretation （P〈0.01, P〈0.05 and P〈0.05 for observers A, B and C respectively）. Consistency between different observers was excellent with both VR interpretation （κ=0.89 for observers A＆C A＆B, B＆C） and TS interpretation （κ=0.71 for A＆B, κ=0.68 for A＆C, κ=0.74 for B＆C）, but time spending was less with VR interpretation than with TS interpretation （P〈0.0001, P〈0.0001 and P〈0.05 for observers A, B and C, respectively）. It was concluded that VR is a useful technique for evaluating the growth of nGGO.展开更多
INTRODUCTION Pulmonary ground-glass shadow is a common clinical imaging manifestation shared by many pulmonary diseases such as interstitial pneumonia, pulmonary fungal infection, parasitic infection, viral pneumonia,...INTRODUCTION Pulmonary ground-glass shadow is a common clinical imaging manifestation shared by many pulmonary diseases such as interstitial pneumonia, pulmonary fungal infection, parasitic infection, viral pneumonia, and heart failure. Some of the lung cancers, especially lung adenocarcinoma,展开更多
基金the National Natural Science Foundation of China(No.62271466)the Natural Science Foundation of Beijing(No.4202025)+1 种基金the Tianjin IoT Technology Enterprise Key Laboratory Research Project(No.VTJ-OT20230209-2)the Guizhou Provincial Sci-Tech Project(No.ZK[2022]-012)。
文摘Aimed at the issues of high feature dimensionality,excessive data redundancy,and low recognition accuracy of using single classifiers on ground-glass lung nodule recognition,a recognition method was proposed based on CatBoost feature selection and Stacking ensemble learning.First,the method uses a feature selection algorithm to filter important features and remove features with less impact,achieving the effect of data dimensionality reduction.Second,random forests classifier,decision trees,K-nearest neighbor classifier,and light gradient boosting machine were used as base classifiers,and support vector machine was used as meta classifier to fuse and construct the ensemble learning model.This measure increases the accuracy of the classification model while maintaining the diversity of the base classifiers.The experimental results show that the recognition accuracy of the proposed method reaches 94.375%.Compared to the random forest algorithm with the best performance among single classifiers,the accuracy of the proposed method is increased by 1.875%.Compared to the recent deep learning methods(ResNet+GBM+Attention and MVCSNet)on ground-glass pulmonary nodule recognition,the proposed method’s performance is also better or comparative.Experiments show that the proposed model can effectively select features and make recognition on ground-glass pulmonary nodules.
基金Supported by the National Natural Science Foundation of China,No.81671680.
文摘BACKGROUND In recent years,the detection rate of ground-glass nodules(GGNs)has been improved dramatically due to the popularization of low-dose computed tomography(CT)screening with high-resolution CT technique.This presents challenges for the characterization and management of the GGNs,which depends on a thorough investigation and sufficient diagnostic knowledge of the GGNs.In most diagnostic studies of the GGNs,morphological manifestations are used to differentiate benignancy and malignancy.In contrast,few studies are dedicated to the assessment of the hemodynamics,i.e.,perfusion parameters of the GGNs.AIM To assess the dual vascular supply patterns of GGNs on different histopathology and opacities.METHODS Forty-seven GGNs from 47 patients were prospectively included and underwent the dynamic volume CT.Histopathologic diagnoses were obtained within two weeks after the CT examination.Blood flow from the bronchial artery[bronchial flow(BF)]and pulmonary artery[pulmonary flow(PF)]as well as the perfusion index(PI)=[PF/(PF+BF)]were obtained using first-pass dual-input CT perfusion analysis and compared respectively between different histopathology and lesion types(pure or mixed GGNs)and correlated with the attenuation values of the lesions using one-way ANOVA,student’s t test and Pearson correlation analysis.RESULTS Of the 47 GGNs(mean diameter,8.17 mm;range,5.3-12.7 mm),30(64%)were carcinoma,6(13%)were atypical adenomatous hyperplasia and 11(23%)were organizing pneumonia.All perfusion parameters(BF,PF and PI)demonstrated no significant difference among the three conditions(all P>0.05).The PFs were higher than the BFs in all the three conditions(all P<0.001).Of the 30 GGN carcinomas,14 showed mixed GGNs and 16 pure GGNs with a higher PI in the latter(P<0.01).Of the 17 benign GGNs,4 showed mixed GGNs and 13 pure GGNs with no significant difference of the PI between the GGN types(P=0.21).A negative correlation(r=-0.76,P<0.001)was demonstrated between the CT attenuation values and the PIs in the 30 GGN carcinomas.CONCLUSION The GGNs are perfused dominantly by the PF regardless of its histopathology while the weight of the BF in the GGN carcinomas increases gradually during the progress of its opacification.
文摘AIM:To obtain the diagnostic performance of percu-taneous transthoracic needle biopsy(PTNB)under Computed tomography(CT)fuoroscopy guidance for lung ground-glass opacity(GGO).METHODS:We searched for English-and Chinese-language studies in PubMed,EMBASE,EBSCO,OVID,and CNKI(China National Knowledge Infrastructure)database.Data were calculated with Meta-Disc version 1.4 and Rev Man version 5.2 software.From the pooled data,we calculated sensitivity(Sen),specificity(Spe),positive likelihood ratio(+LR),negative likelihood ratio(-LR),and diagnostic odds ratio(DOR).Summary receiver operating characteristic(SROC)curves were constructed and incidence of complications was recorded.RESULTS:Four documents included in this present meta-analysis met the criteria for analysis.The pooled Sen,Spe,+LR,-LR and DOR with 95%CI were 0.91(0.86-0.95),1.0(0.91-1.0),18.64(4.83-71.93),0.11(0.05-0.26)and 153.17(30.78-762.33),respectively.The area under the SROC curve was 0.98.The incidence of pneumothorax and hemoptysis was 17.86%-51.80%and 10.50%-19.40%,respectively.CONCLUSION:CT fuoroscopy-guided PTNB,which has an acceptable incidence of complications,can be used as a primary examination method for lung GGO,with moderate sensitivity and specifcity.
基金supported by a grant from the Science and Technology Program of Guangdong Province of China(No.2009B030801120)
文摘This study examined the value of volume rendering （VR） interpretation in assessing the growth of pulmonary nodular ground-glass opacity （nGGO）. A total of 47 nGGOs （average size, 9.5 mm; range, 5.7-20.6 mm） were observed by CT scanning at different time under identical parameter settings. The growth of nGGO was analyzed by three radiologists by comparing the thin slice （TS） CT images of initial and repeat scans with side-by-side cine mode. One week later synchronized VR images of the two scans were compared by side-by-side cine mode to evaluate the nGGO growth. The nodule growth was rated on a 5-degree scale： notable growth, slight growth, dubious growth, stagnant growth, shrinkage. Growth standard was defined as： Density increase 〉 30 HU and （or） diameter increase （by 20% in nodules 〉_10 mm, 30% in nodules of 5-9 mm）. Receiver operating characteristic （ROC） was performed. The results showed that 32 nGGOs met the growth criteria （29 nGGOs showed an increase in density; 1 nGGO showed an increase in diameter; 2 nGGOs showed an increase in both diameter and density）. Area under ROC curve revealed that the performance with VR interpretation was better than that with TS interpretation （P〈0.01, P〈0.05 and P〈0.05 for observers A, B and C respectively）. Consistency between different observers was excellent with both VR interpretation （κ=0.89 for observers A＆C A＆B, B＆C） and TS interpretation （κ=0.71 for A＆B, κ=0.68 for A＆C, κ=0.74 for B＆C）, but time spending was less with VR interpretation than with TS interpretation （P〈0.0001, P〈0.0001 and P〈0.05 for observers A, B and C, respectively）. It was concluded that VR is a useful technique for evaluating the growth of nGGO.
文摘INTRODUCTION Pulmonary ground-glass shadow is a common clinical imaging manifestation shared by many pulmonary diseases such as interstitial pneumonia, pulmonary fungal infection, parasitic infection, viral pneumonia, and heart failure. Some of the lung cancers, especially lung adenocarcinoma,
