Histological studies and morphometry quantitative analysis have been performed on trial rabbit’s dilated common bile duct(CBD),which does not dilate simultaneously.The results shows:①Epithelia of rabbit’s CBD have a ber reparable function,which is fairly significant to the prevention of bile duct’s further injure under the pathogenic situation.②The smooth muscle cell(SMC)of the CBD is the histological basis of contraction,some SMC can be seen in contracting state under light microscope.This indicates that the SMC in rabbit’s CBD possess contracting function.③The collagenous and elastic fibers have the normal histological morphometric characteristics and quantity in it’s dilatation process,and no breekdown and degeneration of the fibers can be detected.Because of the morphological structure of these sections is quite similiar with normal ones,theoretically,we suspect that when pathological change of bile duct’s distal portion is relieved and the bile pressure is normal again.It is possible for this dilating bile duct to return to its formal shape and size.
Immuno-fluorescence technique can qualitatively determine certain nuclear translocation, of which NF-κB/p65 implicates the activation of NF-κB signal pathways. Immuno-fluorescence analysis software with independent property rights is able to quantitatively analyze dynamic location of NF-κB/p65 by computing relative fluorescence units in nuclei and cytoplasm. We verified the quantitative analysis by Western Blot. When we applied the software to analysis of nuclear translocation in lipopolysaccharide (LPS) induced (0.5 h, 1 h, 2 h, 4 h) primary human umbilical vein endothelial cells (HUVECs), we found that nuclear translocation peak showed up at 2h as with calculated Western blot verification results, indicating that the inventive immuno-fluorescence analysis software can be applied to the quantitative analysis of immuno-fluorescence.
Takayasu arteritis (TA) is a chronic nonspecific inflammation that commonly occurs in the aorta and its main branches. Most patients with TA are lack of clinical manifestations, leading to misdiagnosis. When the TA is correctly diagnosed, the patients may already have stenosis or occlusion in the involved arteries, resulting in arterial ischemia and hypoxia symptoms, and in severe cases it will be life-threatening. Contrast-enhanced ultrasonography (CEUS) is an emerging method for assessing TA, but the assessment relies heavily on experiences of radiologists performing manual and qualitative analyses, so the diagnostic results are often not accurate. To overcome this limitation, this paper presents a computer-assisted quantitative analysis of TA carotid artery lesions based on CEUS. First, the TA lesion was outlined on the carotid wall, and one homogeneous rectangle and one polygon were selected as two reference regions in the carotid lumen. The temporal and spatial features of the lesion region and the reference regions were then calculated. Furthermore, the difference and ratio of the features between the lesion and the reference regions were computed as new features (to eliminate interference factors). Finally, the correlation was analyzed between the CEUS features and inflammation biomarkers consisting of erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP). The data in this paper were collected from 34 TA patients in Zhongshan Hospital undergoing CEUS examination with a total of thirty-seven carotid lesions, where two patients were with two lesions before and after treatment and one patient was with left and right bilateral lesions. Among these patients, 13 were untreated primary patients with a total of 14 lesions, where one patient was with bilateral lesions. The results showed that for all patients, the neovascularization area ratio in the 1/3 inner region of a lesion (ARi1/3) achieved a correlation coefficient (r) of 0.56 (P=0.001) with CRP, and for the primary patients, the neovascularization area ratio in the 1/2 inner region of a lesion (ARi1/2) had an r-value of 0.76 (P=0.001) with CRP. This study indicates that the proposed computer-assisted method can objectively and semi-automatically extract quantitative features from CEUS images, so as to reduce the effect on diagnosis due to subjective experiences of the radiologists, and thus it is expected to be used for clinical diagnosis and severity evaluation of TA carotid lesions.
ObjectiveTo investigate the value of proton magnetic resonance spectroscopy (1H-MRS), gradient dual-echo, and triple-echo sequences in the quantitative evaluation of treatment effect of fatty liver at 3.0T MR.MethodsThirty patients with fatty liver diagnosed by CT or ultrasound who admitted in Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital between August 2017 and May 2018, were enrolled and undergone gradient dual-echo, triple-echo, and 1H-MRS examination before and 3 months after treatment. The fat index (FI) and relative lipid content (RLC) were measured. Fatty liver index (FLI) was calculated from blood biochemical indicators, waist circumference, and BMI at the same time. With the reference standard of FLI, the results before and after treatment measured from MRI were analyzed.ResultsThere were significantly differences of FLI, FIdual, FItriple, and RLC before and after treatment (t=5.281, P<0.001; Z=–3.651, P<0.001; Z=–3.630, P<0.001; Z=–4.762, P<0.001), all indexes decreased after treatment. FIdual and FItriple were positively correlated with FLI before (rs=0.413, P=0.023; rs=0.396, P=0.030) and after treatment (rs=0.395, P=0.031; rs=0.519, P=0.003), the highest correlation factor was FItriple to FLI after treatment. There were no significant correlation between RLC and FLI before and after treatment (P>0.05).ConclusionsIt is feasible to quantitatively evaluate the treatment effect of fatty liver by using 1H-MRS, gradient dual-echo, and triple-echo sequences. Gradient triple-echo sequences has better accuracy, which is technically easy to implement and more suitable for clinical development.
In order to quantitatively analyze the morphology and period of pulse signals, a time-space analytical modeling and quantitative analysis method for pulse signals were proposed. Firstly, according to the production mechanism of the pulse signal, the pulse space-time analytical model was built after integrating the period and baseline of pulse signal into the analytical model, and the model mathematical expression and its 12 parameters were obtained for pulse wave quantification. Then, the model parameters estimation process based on the actual pulse signal was presented, and the optimization method, constraints and boundary conditions in parameter estimation were given. The spatial-temporal analytical modeling method was applied to the pulse waves of healthy subjects from the international standard physiological signal sub-database Fantasia of the PhysioNet in open-source, and we derived some changes in heartbeat rhythm and hemodynamic generated by aging and gender difference from the analytical models. The model parameters were employed as the input of some machine learning methods, e.g. random forest and probabilistic neural network, to classify the pulse waves by age and gender, and the results showed that random forest has the best classification performance with Kappa coefficients over 98%. Therefore, the space-time analytical modeling method proposed in this study can effectively quantify and analyze the pulse signal, which provides a theoretical basis and technical framework for some related applications based on pulse signals.
ObjectiveTo investigate the value of chest high-resolution computed tomography (HRCT) score in evaluating the severity of hip fracture-induced early acute lung injury (ALI) in the elderly patients.MethodsThe clinical data of 289 elderly hip fracture patients in Chongqing Traditional Chinese Medicine Hospital from July 2014 to April 2020 were retrospectively analyzed. All patients were divided into two groups, including an ALI group (n=114, 36 males and 78 females at age of 82.94±6.85 years) and a non-ALI group (n=175, 51 males and 124 females at age of 84.42±6.31 years). General information, chest HRCT scores and PaO2/FiO2 were compared between the two groups. Correlation analysis was used to compare the relationship between chest HRCT scores and PaO2/FiO2. Multiple linear stepwise regression analysis was applied to evaluate the effective extent of the diffuse ground glass opacity (DGGO), intense parenchymal opacification (IPO), and reticulation HRCT scores to the overall HRCT scores.ResultsThe DGGO scores, IPO scores, reticulation scores, overall HRCT scores and PaO2/FiO2 were higher in the ALI group than those in the non-ALI group (P<0.001). In the ALI group, correlation analysis showed that DGGO, overall HRCT scores were in significantly negative correlation with PaO2/FiO2 (P<0.001). In addition, the correlation among PaO2/FiO2 and overall HRCT scores was more significant than that of DGGO scores. Multiple stepwise regression analysis indicated that DGGO, IPO, and reticulation scores were independent influencing factors for overall HRCT scores. Among the influencing factors, DGGO scores had the greatest impact, then IPO scores and reticulation scores. The HRCT signs of DGGO, IPO, and reticulation appeared simultaneously had the greatest effects on the overall HRCT scores.ConclusionThe chest HRCT score, which is associated with PaO2/FiO2, also can be used in the severity assessment of elderly patients with early ALI caused by hip fracture.
Objective To explore the clinical value of artificial intelligence (AI) quantitative parameters of pulmonary ground-glass nodules (GGN) in predicting the degree of infiltration. Methods A retrospective analysis of 168 consecutive patients with 178 GGNs in our hospital from October 2019 to May 2021 was performed, including 43 males and 125 females, aged 21-78 (55.76±10.88) years. Different lesions of the same patient were analyzed as independent samples. Totally, 178 GGNs were divided into two groups, a non-invasive group (24 adenocarcinoma in situ and 77 minimally invasive adenocarcinoma), and an invasive group (77 invasive adenocarcinoma). We compared the difference of AI quantitative parameters between the two groups, and evaluated predictive valve by receiver operating characteristic curve and binary logistic regression model. Results (1) Except for the gender (P=0.115), the other parameters, such as maximal diameter [15.10 (11.50, 21.60) mm vs. 8.90 (7.65, 11.15) mm], minimum diameter [10.80 (8.85, 15.20) mm vs. 7.40 (6.10, 8.95) mm], proportion of consolidation/tumor ratio [13.58% (1.61%, 63.76%) vs. 0.00% (0.00%, 0.67%)], mean CT value [–347.00 (–492.00, –101.50) Hu vs. –598.00 (–657.50, –510.00) Hu], CT maximum value [40.00 (–40.00, 94.50) Hu vs. –218.00 (–347.00, –66.50) Hu], CT minimum value [–584.00 (–690.50, –350.00) Hu vs. –753.00 (–786.00, –700.00) Hu], danger rating (proportion of high-risk nodules, 92.2% vs. 66.3%), malignant probability [91.66% (85.62%, 94.92%) vs. 81.81% (59.98%, 90.29%)] and age (59.93±8.53 years vs. 52.04±12.10 years) were statistically significant between the invasive group and the non-invasive group (all P<0.001). (2) The highest predictive value of a single quantitative parameter was the maximal diameter (area under the curve=0.843), the lowest one was the risk classification (area under the curve=0.627), the combination of two among the three parameters (maximal diameter, mean CT value, and consolidation/tumor ratio) improved the predictive value entirely. (3) Logistic regression analysis showed that maximal diameter and mean CT value both were the independent risk factor for predicting invasive adenocarcinoma. (4) When the threshold of v was 1.775%, the diagnostic sensitivity of invasive adenocarcinoma was 0.753 and the specificity was 0.851. Conclusion AI quantitative parameters can effectively predict the degree of infiltration of GGNs and provide a reliable reference basis for clinicians.
Quantitative analysis of ultrasound molecular imaging is of great significance for clinical diagnosis and research. Based on Visual Studio development platform and C# language, this paper designs a set of ultrasound molecular imaging region of interest quantitative analysis software, which can complete the ultrasound image scaling processing, rectangular and arbitrary shape of the region of interest capture, mark saving and loading, gray value quantitative analysis and so on. In this paper, the function of the software is described in detail and the software is tested and verified. It is proved that the software can quantitatively analyze the conventional ultrasound images and ultrasound contrast images, which can provide a basis for the relevant research on the quantitative analysis of the gray value of ultrasound molecular imaging.