Chest CT quantitative parameters in patients with acute exacerbation of chronic obstructive pulmonary disease:Correlations with blood eosinophil level

Objective To observe the correlations of chest CT quantitative parameters in patients with acute exacerbation of chronic obstructive pulmonary disease(AECOPD)with blood eosinophil(EOS)level.Methods Chest CT data of 162 AECOPD patients with elevated eosinophils were retrospectively analyzed.The patients were divided into low EOS group(n=105)and high EOS group(n=57)according to the absolute counting of blood EOS.The quantitative CT parameters,including the number of whole lung bronchi and the volume of blood vessels,low-attenuation area percentage(LAA%)of whole lung,of left/right lung and each lobe of lung,as well as the luminal diameter(LD),wall thickness(WT),wall area(WA)and WA percentage of total bronchial cross-section(WA%)of grade 3 to 8 bronchi were compared between groups.Spearman correlations were performed to analyze the correlations of quantitative CT parameters with blood EOS level.Results LAA%of the whole lung,of the left/right lung and each lobe of lung,as well as of the upper lobe of right lung LD grade 4,middle lobe of right lung WT grade 5,upper lobe of right lung WA grade 4,middle lobe of right lung WA grade 5 and lower lobe of left lung WA grade 3 in low EOS group were all higher than those in high EOS group(all P<0.05).Except for the upper lobe of right lung LD grade 4,the above quantitative CT indexes being significant different between groups were all weakly and negatively correlated with blood EOS level(r=-0.335 to-0.164,all P<0.05).Conclusion Chest CT quantitative parameters of AECOPD patients were correlated with blood EOS level,among which LAA%,a part of WT and WA were all weakly negatively correlated with blood EOS level.

CR应用于床旁摄影的价值

目的:探讨CR在床旁摄影的价值和贡献。方法:将我院使用CR系统所照的床旁照片与过去普通屏/片系统的床旁照片各1000例,进行对照分析。结果:CR床边片甲级片率提高45%,重照率减少10%,废片率为零。平均曝光量减少30%。结论:CR床边照片较传统床边X线照片相比,在提高影像质量、照片成功率与及降低病人和医护人员的辐射剂量等方面作出了重大贡献。

Research progresses of dual-layer spectral detector CT for preoperative evaluation on colorectal cancer

Dual-layer spectral detector CT is a new spectrum CT imaging technology based on detector being able to obtain both images similar to true plain and spectral images in one time scanning.The reconstructed multi-parameter spectral images can not only improve image quality,enhance tissue contrast,increase the visualization and detection ability of occult lesions,but also provide qualitative and quantitative analysis of the lesions,so as to provide more imaging information and multi-dimensional diagnostic basis.The research progresses of dual-layer spectral detector CT for preoperative evaluation on colorectal cancer were reviewed in this article.

Preoperative CT radiomics models for predicting composition of in vivo urinary calculi

Objective To observe the value of preoperative CT radiomics models for predicting composition of in vivo urinary calculi.Methods Totally 543 urolithiasis patients were retrospectively enrolled and divided into calcium oxalate monohydrate stone group(group A,n=373),anhydrous uric acid stone group(group B,n=86),carbonate apatite group(group C,n=30),ammonium urate stone group(group D,n=28)and ammonium magnesium phosphate hexahydrate stone group(group E,n=26)according to the composition of calculi,also divided into training set and test set at the ratio of 7∶3.Radiomics features were extracted and screened based on plain CT images of urinary system.Five binary task models(model A—E corresponding to group A—E)and a quinary task model were constructed using least absolute shrinkage and selection operator algorithm for predicting the composition of calculi in vivo.Then receiver operating characteristic curves were drawn,and the area under the curves(AUC)were calculated to evaluate the predictive efficacy of binary task models,while the accuracy,precision,recall and F1 score were used to evaluate the predictive efficacy of the quinary task model.Results All binary task models had good efficacy for predicting the composition of urinary calculi in vivo,with AUC of 0.860—0.948 in training set and of 0.856—0.933 in test set.The accuracy,precision,recall and F1 score of the quinary task model for predicting the composition of in vivo urinary calculi was 82.25%,83.79%,46.23%and 0.596 in training set,respectively,while was 80.63%,75.26%,43.48%and 0.551 in test set,respectively.Conclusion Binary task radiomics models based on preoperative plain CT had good efficacy for predicting the composition of in vivo urinary calculi,while the quinary task radiomics model had high accuracy but relatively poor stability.

Artificial intelligence models based on non-contrast chest CT for measuring bone mineral density

Objective To observe the value of artificial intelligence(AI)models based on non-contrast chest CT for measuring bone mineral density(BMD).Methods Totally 380 subjects who underwent both non-contrast chest CT and quantitative CT(QCT)BMD examination were retrospectively enrolled and divided into training set(n=304)and test set(n=76)at a ratio of 8∶2.The mean BMD of L1—L3 vertebrae were measured based on QCT.Spongy bones of T5—T10 vertebrae were segmented as ROI,radiomics(Rad)features were extracted,and machine learning(ML),Rad and deep learning(DL)models were constructed for classification of osteoporosis(OP)and evaluating BMD,respectively.Receiver operating characteristic curves were drawn,and area under the curves(AUC)were calculated to evaluate the efficacy of each model for classification of OP.Bland-Altman analysis and Pearson correlation analysis were performed to explore the consistency and correlation of each model with QCT for measuring BMD.Results Among ML and Rad models,ML Bagging-OP and Rad Bagging-OP had the best performances for classification of OP.In test set,AUC of ML Bagging-OP,Rad Bagging-OP and DL OP for classification of OP was 0.943,0.944 and 0.947,respectively,with no significant difference(all P>0.05).BMD obtained with all the above models had good consistency with those measured with QCT(most of the differences were within the range of Ax-G±1.96 s),which were highly positively correlated(r=0.910—0.974,all P<0.001).Conclusion AI models based on non-contrast chest CT had high efficacy for classification of OP,and good consistency of BMD measurements were found between AI models and QCT.

Self-supervised learning artificial intelligence noise reduction technology based on the nearest adjacent layer in ultra-low dose CT of urinary calculi

Objective To observe the value of self-supervised deep learning artificial intelligence(AI)noise reduction technology based on the nearest adjacent layer applicated in ultra-low dose CT(ULDCT)for urinary calculi.Methods Eighty-eight urinary calculi patients were prospectively enrolled.Low dose CT(LDCT)and ULDCT scanning were performed,and the effective dose(ED)of each scanning protocol were calculated.The patients were then randomly divided into training set(n=75)and test set(n=13),and a self-supervised deep learning AI noise reduction system based on the nearest adjacent layer constructed with ULDCT images in training set was used for reducing noise of ULDCT images in test set.In test set,the quality of ULDCT images before and after AI noise reduction were compared with LDCT images,i.e.Blind/Referenceless Image Spatial Quality Evaluator(BRISQUE)scores,image noise(SD ROI)and signal-to-noise ratio(SNR).Results The tube current,the volume CT dose index and the dose length product of abdominal ULDCT scanning protocol were all lower compared with those of LDCT scanning protocol(all P<0.05),with a decrease of ED for approximately 82.66%.For 13 patients with urinary calculi in test set,BRISQUE score showed that the quality level of ULDCT images before AI noise reduction reached 54.42%level but raised to 95.76%level of LDCT images after AI noise reduction.Both ULDCT images after AI noise reduction and LDCT images had lower SD ROI and higher SNR than ULDCT images before AI noise reduction(all adjusted P<0.05),whereas no significant difference was found between the former two(both adjusted P>0.05).Conclusion Self-supervised learning AI noise reduction technology based on the nearest adjacent layer could effectively reduce noise and improve image quality of urinary calculi ULDCT images,being conducive for clinical application of ULDCT.

Automated body composition analysis system based on chest CT for evaluating content of muscle and adipose

Objective To establish a body composition analysis system based on chest CT,and to observe its value for evaluating content of chest muscle and adipose.Methods T7—T8 layer CT images of 108 pneumonia patients were collected(segmented dataset),and chest CT data of 984 patients were screened from the COVID 19-CT dataset(10 cases were randomly selected as whole test dataset,the remaining 974 cases were selected as layer selection dataset).T7—T8 layer was classified based on convolutional neural network(CNN)derived networks,including ResNet,ResNeXt,MobileNet,ShuffleNet,DenseNet,EfficientNet and ConvNeXt,then the accuracy,precision,recall and specificity were used to evaluate the performance of layer selection dataset.The skeletal muscle(SM),subcutaneous adipose tissue(SAT),intermuscular adipose tissue(IMAT)and visceral adipose tissue(VAT)were segmented using classical fully CNN(FCN)derived network,including FCN,SegNet,UNet,Attention UNet,UNET++,nnUNet,UNeXt and CMUNeXt,then Dice similarity coefficient(DSC),intersection over union(IoU)and 95 Hausdorff distance(HD)were used to evaluate the performance of segmented dataset.The automatic body composition analysis system was constructed based on optimal layer selection network and segmentation network,the mean absolute error(MAE),root mean squared error(RMSE)and standard deviation(SD)of MAE were used to evaluate the performance of automatic system for testing the whole test dataset.Results The accuracy,precision,recall and specificity of DenseNet network for automatically classifying T7—T8 layer from chest CT images was 95.06%,84.83%,92.27%and 95.78%,respectively,which were all higher than those of the other layer selection networks.In segmentation of SM,SAT,IMAT and overall,DSC and IoU of UNet++network were all higher,while 95HD of UNet++network were all lower than those of the other segmentation networks.Using DenseNet as the layer selection network and UNet++as the segmentation network,MAE of the automatic body composition analysis system for predicting SM,SAT,IMAT,VAT and MAE was 27.09,6.95,6.65 and 3.35 cm 2,respectively.Conclusion The body composition analysis system based on chest CT could be used to assess content of chest muscle and adipose.Among them,the UNet++network had better segmentation performance in adipose tissue than SM.

0D-1D coupling model and 3D fluid-structure interaction model based on coronary CT angiography for displaying hemodynamic characteristics of coronary artery stenosis

Objective To observe value of 0D-1D coupling model and 3D fluid-structure interaction(FSI)model based on coronary CT angiography(CCTA)for displaying hemodynamic characteristics of coronary artery stenosis.Methods Based on CCTA data of the stenosed left anterior descending branch(LAD)in a patient with coronary heart disease,an 0D-1D coupling model and 3D FSI model were built,respectively.Then hemodynamic characteristic indexes,including the pressure,flow velocity and wall shear stress(WSS)were obtained in every 0.01 s during 1 s at 5 sampling points(i.e.sampling point 1—5)using these 2 models,respectively,and the consistencies of the results between models were evaluated with Spearman correlation coefficient r s.Results The time consuming for construction of 0D-1D coupling model and 3D FSI model was 0.033 min and 704 min,respectively.Both models showed basically distribution of the pressure,flow velocity and WSS of the stenosed LAD.For more details,the pressure at the stenosed segment of LAD and the proximal segment of stenosis were both higher,which gradually decreased at the distal segment of stenosis,and the flow velocity at the proximal segment of stenosis was in a relatively slow and uniform condition,with significantly increased flow velocity and WSS at the stenosed segment.Compared with 3D FSI model,0D-1D vascular coupling model was relatively unrefined and lack of distal flow lines when displaying blood flow velocity.For sampling point 2 at the stenosed segment of LAD,no significant consistency for pressure between 2 models was found(P=0.118),but strong consistency for the flow velocity and WSS(r s=0.730,0.807,both P<0.05).The consistencies of pressure,flow velocity and WSS between 2 models at the proximal and distal segment of stenosis,i.e.1,3—5 sampling points were week to moderate(r s=0.237—0.669,all P<0.05).Conclusion 0D-1D coupling model exhibited outstanding computational efficiency and might provide relatively reasonable results,while 3D FSI model showed higher accuracy for details and streamline when simulating LAD stenosis.

Highly metabolic thrombus of the portal vein:^(18)F fluorodeoxyglucose positron emission tomography/computer tomography demonstration and clinical significance in hepatocellular carcinoma

AIM： To assess the ability of ^18F-fluorodeoxyglucose positron emission tomography/computer tomography （^18F-FDG PET/CT） to differentiate between benign and malignant portal vein thrombosis in hepatocellular carcinoma （HCC） patients.METHODS： Five consecutive patients who had HBV cirrhosis, biopsy-proven HCC, and thrombosis of the main portal vein and/or left/right portal vein on ultrasound （US）, computer tomography （CT） or magnetic resonance imaging （MRI） were studied with ^18F-FDG PET/CT. The presence or absence of a highly metabolic thrombus on ^18F-FDG PET/CT was considered diagnostic for malignant or benign portal vein thrombosis, respectively. All patients were followed-up monthly with US, CT or MRI. Shrinkage of the thrombus or recanalization of the vessels on US, CT or MRI during follow-up was considered to be definitive evidence of the benign nature of the thrombosis, whereas enlargement of the thrombus, disruption of the vessel wall, and parenchymal infiltration over follow-up were considered to be consistent with malignancy. ^18SF-FDG PET/CT, and US, CT or MRI results were compared.RESULTS： Follow-up （1 to 10 mo） showed signs of malignant thrombosis in 4 of the 5 patients. US, CT or MRI produced a true-positive result for malignancy in 4 of the patients, and a false-positive result in 1. ^18F-FDG PET/CT showed a highly metabolic thrombus in 4 of the 5 patients. ^18F-FDG PET/CT achieved a true-positive result in all 4 of these patients, and a true-negative result in the other patient. No false-positive result was observed using ^18F-FDG PET/CT.CONCLUSION： ^18F-FDG PET/CT may be helpful in discriminating between benign and malignant portal vein thrombi. Patients may benefit from ^18F-FDG PET/CT when portal vein thrombi can not be diagnosed exactly by US, CT or MRI.

THE REAL IN TIME CT MONITORING OF THE MESO-DAMAGE EVOLUTION LAW OF SANDSTONE UNDER TRIAXIAL COMPRESSION

The real in time computerized tomography (CT) testing of the meso damage propagation law of the whole sandstone failure process under triaxial compression has been completed using the newest specified triaxial loading equipment corresponding to the CT machine. Through the CT scanning, the clear CT images which include from the microcracks compressed stage to growth stage, bifurcation stage, development stage, crack fracture stage,the rock sample failure until to unloading stage in the different stress states were obtained. The CT values, CT images and the other data have been analyzed. Based on the results of the CT testing of meso damage evolution law of rock,the stress threshold value of meso damage of rock is given, and the stress strain complete process curve of rock is divided into some sections. The initial rock damage propagation law is given in this paper.

混凝土单轴压缩下细观损伤特性的CT研究

混凝土是一种非均质的材料,在细观层次上将混凝土看作由骨料、砂浆和两者之间的界面组成的三相复合材料。本文利用CT技术对混凝土的细观损伤过程进行实时扫描观测,获得了混凝土试件实时静力压缩CT图像,提取出图像上各点的CT数并根据分区理论定义了一个基于CT数的统计损伤变量。通过对图像和CT数以及损伤变量的分析表明混凝土试件在静力压缩条件下经历了压密阶段、扩容阶段,损伤急剧增大到破坏的细观损伤演化全过程,以此反映了混凝土细观损伤演化的特性。进而通过细观损伤对混凝土材料裂纹的扩展、贯通以及最后失稳破坏的破坏实质进行了有益的探索。

脊柱结核的影像学诊断及临床病理分析

研究脊柱结核的影像学诊断价值,并探讨各型脊柱结核的临床病理特点。对156例经临床及病理证实且影像学资料完整的脊柱结核进行回顾性分析,比较其X线(或CR)、CT及MRI的影像学特点及符合率。结果显示①X线(或CR)、CT及MRI对脊柱结核诊断符合率分别为90.5%、96.2%及99.5%。②X线(或CR)、CT及MRI对椎体骨质破坏、椎间隙狭窄的敏感性分别为74.5%、89.9%及96.87%。③对椎旁软组织肿块和腰大肌脓肿、附件破坏及骨性椎管受累的显示,CT优于X线(和CR)片;对早期病变的显示及脊髓受累情况,MRI优于X线(或CR)及CT,有显著差异性(P<0.01)。④对死骨及钙化的显示CT优于X线(或CR)及MRI。认为X线(或CR)检查为诊断脊柱结核的基本方法,但对早期病变的显示有限度;CT显示早期微小的骨质破坏、死骨、脓肿、钙化及脓肿对椎管脊髓压迫明显优于X线;MRI可清晰显示硬膜外脓肿及脊柱后突畸形对脊髓的压迫和脊髓变性情况,尤其是对早期病变的诊断,有较高的敏感性和特异性,但对死骨及钙化不敏感。

手腕外伤下尺桡关节的CR影像分析

目的分析下尺桡关节脱位的损伤病因、机制、分类及其CR表现。方法对162例腕部外伤病例的临床病史、放射影像资料进行回顾性分析总结。结果下尺桡关节162例,从CR影像上可分为复合性和单纯性脱位;还可分为纵向、掌侧及背侧脱位3型。较大骨折合并下尺桡关节脱位约占67.7%;下尺桡关节单纯性脱位,约占19.8%。结论下尺桡关节脱位表现形式多样,影像复杂。

Computed tomography perfusion in evaluating the therapeutic effect of transarterial chemoembolization for hepatocellular carcinoma

AIM： To prospectively assess the changes in parameters of computed tomography （CT） perfusion pre- and post-transarterial chemoembolization （TACE） of hepatocellular carcinoma （HCC） in different treatment response groups, and to correlate the changes with various responses of HCC to TACE. METHODS： Thirty-nine HCC patients underwent CT perfusion examinations pre-（1 d before TACE） and post-treatment （4 wk after TACE）. The response evaluation criteria for solid tumors （RECIST） were referred to when treatment responses were distributed. Wilcoxon-signed ranks test was used to compare the differences in CT perfusion parameters pre- and post- TACE for different response groups. RESULTS： Only one case had treatment response to CR and the CT perfusion maps of post-treatment lesion displayed complete absence of signals. In the PR treatment response group, hepatic artery perfusion （HAP）, hepatic arterial fracture （HAF） and hepatic blood volume （HBV） of viable tumors post-TACE were reduced compared with pre-TACE （P = 0.001, 0.030 and 0.001, respectively）. In the SD group, all CT perfusion parameters were not significantly different pre- and post-TACE. In the PD group, HAP, HAl=, portal vein perfusion （PVP） and hepatic blood flow （HBF） of viable tumors post-TACE were significantly increased compared with pre-TACE （P = 0.005, 0.012, 0.035 and 0.005, respectively）. CONCLUSION： Changes in CT perfusion parameters of viable tumors are correlated with different responses of HCC to TACE. Therefore, CT perfusion imaging is a feasible technique for monitoring response of HCC to TACE.

A case of multiple intra-abdominal splenosis with computed tomography and magnetic resonance imaging correlative findings

Hepatic splenosis refers to heterotopic auto- transplantation and implantation of splenic tissue resulting from the spillage of cells from the spleen after splenic trauma or splenectomy. The true incidence of splenosis is unknown, because this entity is usually an incidental finding at surgery. Splenic implants are usually multiple, and can be localized anywhere in the peritoneal cavity. Splenic implants in the peritoneal cavity may be confused with renal tumors, abdominal lymphomas and endometriosis. We describe computed tomography (CT) and magnetic resonance imaging (MRI) findings in a rare case of multiple intra-abdominal splenosis located along the hepatic surface and adjacent to the upper pole of the right kidney, mimicking a renal neoplasm.

CR静脉肾盂造影延时摄片在尿路梗阻病例检查中的应用价值

目的探讨CR(计算机X线摄影)静脉肾盂造影延时摄片在诊断尿路梗阻的临床应用价值。方法对东莞石碣医院2009年8月至2010年8月均经B超、CT检查或临床手术证实27例在CR静脉肾盂造影中常规时间里肾盂肾盏、输尿管显影不满意或不显影的患者进行延时摄片,并对所得的结果进行分析。结果 27例患者延时摄片诊断肾结石、输尿管结石22例,肾盂肾盏重复畸形1例,泌尿系结核2例,肾盂输尿管移行部狭窄1例,多发肾囊肿并肾功能丧失1例。结论 CR静脉肾盂造影延时摄片对明确尿路梗阻病例的病因、部位较常规造影有明显提高,并能给临床更清晰、直观的图像资料,延时摄片尤其必要。

Magnetic resonance imaging in distinguishing malignant from benign pleural disease

Objective To explore the role of magnetic resonance imaging (MRI) in distinguishing malignant from benign pleural disease.Methods All 64 patients were examined with both computed tomography (CT) and MRI. The morphologic features of pleural lesions and MR signal intensity on T1-weighted, T2-weighted and contrast-enhanced T1-weighted images were evaluated.Results Mediastinal pleural involvement, circumferential pleural thickening, nodularity, irregularity of pleural contour, and infiltration of the chest wall and/or diaphragm were most suggestive of a malignant cause on CT and MR images. Contrary to what has been reported in the literature, pleural thickness greater than 1?cm either on CT or on MRI did not reveal a significant difference between malignant and benign pleural disease (P>0.05, chi-square test). Using morphologic features in combination with signal intensity features, MRI had a sensitivity of 98% and a specificity of 92% in the detection of pleural malignancy. Conclusions Compared with those on CT, the morphologic features on MRI allowed a mostly equal and in some cases superior detection and evaluation of the spread of pleural disease. In combination with signal intensity and morphologic features, MRI is very useful in distinguishing malignant from benign pleural disease.

Computerized tomography pleurography: a new method for detecting minor pleural lesion

Objectives To evaluate the ability of CT pleurography (CTP) in detecting minor pleural lesions in patients with pleural effusion and to assess its value in distinguishing malignant from benign pleural lesions. Methods A prospective study of 50 patients with pleural effusion was conducted using conventional CT and CTP. CT scan was run after injecting an appropriate amount of contrast medium into the pleural cavity. Results In 24 patients, all lesions detected by conventional CT were demonstrated by CTP. In 13 of 24 patients, CT pleurography detected additional lesions. In 20 of 26 patients with negative findings on conventional CT, CTP was capable of demonstrating the presence of pleural lesions. The sensitivity, specificity and accuracy of detecting pleural lesions were 25%, 100% and 30% for conventional CT, 86%, 100% and 87% for CTP, respectively. Conclusion CTP is superior to conventional CT in detecting and for the differential diagnosis benign and malignant pleural lesions.