Objective To investigate the value of multimodal MRI radiomics in predicting muscle-invasive bladder cancer.Methods A total of 178 patients with pathology diagnosis of bladder cancer were retrospectively collected,including 31 cases of muscle invasive bladder cancer(MIBC)and 147 cases of non-muscle invasive bladder cancer(NMIBC).Patients were randomly divided into training group and testing group at a ratio of 7︰3.The range of bladder tumors in T2WI,diffusion weighted imaging(DWI)and apparent diffusion coefficient(ADC)images were segmented as volume of interest(VOI)by using ITK-SNAP software.Radiomics features were extracted through A.K software.The optimal radiomics features were obtained through radiomics algorithm and least absolute shrinkage and selection operator(LASSO)method.Finally,the logistic regression analysis method and random forest model method were used to construct prediction models.The performance of prediction models was evaluated by the receiver operating characteristic(ROC)curve.Results This study constructed four groups of models containing T2WI prediction model,DWI prediction model,ADC prediction model,and T2WI+DWI+ADC prediction model.The area under the curve(AUC)of T2WI,DWI,and ADC prediction models for identifying MIBC and NMIBC were separately 0.920,0.914,and 0.954 in the training group while those were respectively 0.881,0.773,and 0.871 in the testing group.There was no statistical significance between T2WI,DWI,and ADC prediction models.In training and testing groups,the AUC of T2WI+DWI+ADC prediction model were respectively 0.959 and 0.909,which were higher than the single sequence prediction model.The sensitivity and specificity of the training group were 0.905 and 0.853 and the sensitivity and specificity of the testing group were 0.778 and 0.795.Conclusion MRI radiomics prediction model can effectively differentiate MIBC and NMIBC.The T2WI+DWI+ADC prediction model shows better prediction efficiency.

Objective To compare the effects of three kinds of artificial hydronephrosis in percutaneous nephrolithotomy.Methods A total of 120 patients who underwent single-tract percutaneous nephrolithotomy in the Eighth Hospital of Wuhan from May 2020 to April 2022 were selected and divided equally into three groups according to different methods of artificial hydronephrosis.Patients in group A were received preoperative indwelling ureteral catheter and injection of normal saline through ureteral catheter to dilate renal pelvis and form artificial hydronephrosis.Patients in Group B were placed with double J catheters before surgery,and the bladder was filled with physiological saline through the catheter.The renal pelvis was dilated through the double J catheters,resulting in artificial hydronephrosis.Patients in Group C were received intravenous injection of furosemide and stimulated diuretic method to actively dilate renal pelvis to form hydronephrosis.The one-time puncture success rate,channel establishment time,overall operation time,stone clearance rate and incidence of surgical complications of percutaneous nephrolithotomy after hydronephrosis were compared among the three groups.Results The operation was successfully completed in the three groups.There was no significant difference in the one-time puncture success rate and channel establishment time between group A and group B(P>0.05),which were all higher than group C(P<0.05).The overall operation time of group B was shorter than that of group A and group C(P<0.05).There were no significant differences in stone clearance rate and surgical complications among the three groups(P>0.05).Conclusion Preoperative indwelling of double J tubes to create artificial kidney hydronephrosis has advantages such as high success rate of one-time puncture,short channel establishment time,and surgical time.

Objective To explore the performance of a new multimodal feature fusion classification model based on distance matching and discriminative representation learning for differentiating high-grade glioma(HGG)from solitary brain metastasis(SBM).Methods We collected multi-parametric magnetic resonance imaging(MRI)data from 61 patients with HGG and 60 with SBM,and delineated regions of interest(ROI)on T1WI,T2WI,T2-weighted fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)images.The radiomics features were extracted from each sequence using Pyradiomics and fused using a multimodal feature fusion classification model based on distance matching and discriminative representation learning to obtain a classification model.The discriminative performance of the classification model for differentiating HGG from SBM was evaluated using five-fold cross-validation with metrics of specificity,sensitivity,accuracy,and the area under the ROC curve(AUC)and quantitatively compared with other feature fusion models.Visual experiments were conducted to examine the fused features obtained by the proposed model to validate its feasibility and effectiveness.Results The five-fold cross-validation results showed that the proposed multimodal feature fusion classification model had a specificity of 0.871,a sensitivity of 0.817,an accuracy of 0.843,and an AUC of 0.930 for distinguishing HGG from SBM.This feature fusion method exhibited excellent discriminative performance in the visual experiments.Conclusion The proposed multimodal feature fusion classification model has an excellent ability for differentiating HGG from SBM with significant advantages over other feature fusion classification models in discrimination and classification tasks between HGG and SBM.

Objective To explore the comparative study of constructing prediction models for muscle invasive of bladder cancer based on different machine learning algorithms combined with MRI radiomic.Methods A total of 187 bladder cancer patients who underwent MRI examination and were confirmed by pathology were retrospectively selected.Patients were randomly divided into a training set and a test set in a 7∶3 ratio.The patients were divided into muscle invasive bladder cancer(MIBC)group and non-muscle invasive bladder cancer(NMIBC)group according to the surgical pathology results.Tumor volume of interest(VOI)was outlined on the images of T2 WI,diffusion weighted imaging(DWI),and apparent diffusion coefficient(ADC),and the radiomic features were extracted by A.K software,and dimensionality reduction was performed using the maximum relevance minimum redundancy(mRMR)algorithm combined with least absolute shrinkage and selection operator(LASSO).Six machine learning algorithms,including K-nearest neighbor(KNN),decision tree(DT),support vector machine(SVM),logistic regression(LR),random forest(RF),and explainable boosting machine(EBM)were used to construct the radiomic model and calculate the corresponding area under the curve(AUC),accuracy,sensitivity,and specificity,respectively.Results Six machine learning algorithms,including KNN,DT,SVM,LR,RF,and EBM were used to construct the radiomic model,and the AUC values for predicting MIBC in the training set were 0.863,0.838,0.853,0.866,0.977,0.997,and in the test set were 0.748,0.833,0.860,0.868,0.870,0.900.Among them,the MRI radiomic model constructed based on EBM had the highest predictive efficacy for MIBC,with AUC values,accuracy,sensitivity and specificity of 0.997,0.977,0.957 and 0.981 in the training set,and 0.900,0.877,0.800,and 0.894 in the test set,respectively.Conclusion Multiple machine learning algorithms combined with MRI radiomic to construct models have good predictive efficacy for MIBC,and the model constructed based on EBM shows the highest predictive value.

Objective To explore the performance of a new multimodal feature fusion classification model based on distance matching and discriminative representation learning for differentiating high-grade glioma(HGG)from solitary brain metastasis(SBM).Methods We collected multi-parametric magnetic resonance imaging(MRI)data from 61 patients with HGG and 60 with SBM,and delineated regions of interest(ROI)on T1WI,T2WI,T2-weighted fluid attenuated inversion recovery(T2_FLAIR)and post-contrast enhancement T1WI(CE_T1WI)images.The radiomics features were extracted from each sequence using Pyradiomics and fused using a multimodal feature fusion classification model based on distance matching and discriminative representation learning to obtain a classification model.The discriminative performance of the classification model for differentiating HGG from SBM was evaluated using five-fold cross-validation with metrics of specificity,sensitivity,accuracy,and the area under the ROC curve(AUC)and quantitatively compared with other feature fusion models.Visual experiments were conducted to examine the fused features obtained by the proposed model to validate its feasibility and effectiveness.Results The five-fold cross-validation results showed that the proposed multimodal feature fusion classification model had a specificity of 0.871,a sensitivity of 0.817,an accuracy of 0.843,and an AUC of 0.930 for distinguishing HGG from SBM.This feature fusion method exhibited excellent discriminative performance in the visual experiments.Conclusion The proposed multimodal feature fusion classification model has an excellent ability for differentiating HGG from SBM with significant advantages over other feature fusion classification models in discrimination and classification tasks between HGG and SBM.

OBJECTIVE To estimate the quality markers of antioxidant activity for standard decoction of Schisandrae Chinensis Fructus.METHODS 15 batches of Schisandrae Chinensis Fructus standard decoctions were subjected to quality evaluation by ultra high-performance liquid chromatography(UPLC)based on single-marker(QAMS)method,before being summarized by chemometrics analysis.The antioxidant abilities of 15 batches of samples were determined by DPPH and ABTS methods,while gray correlation analy-sis(GRA)and the partial least squares regression(PLSR)methods were subsequently applied to investigating the relationship between the contents of 8 components and the antioxidant activity.Ultimately,molecule docking was utilized to explore the binding properties between candidate quality markers and the core targets of anti-oxidation,with the experimental verification being executed on the indi-vidual compound by in vitro anti-oxidation.RESULTS There was no remarkable difference between the results of QAMS and external standard method(ESM),with P valued greater than 0.05.And it was speculated that protocatechuic acid,gomisin A,schizantherin B and schisandrin B were the constituents of quality difference.Moreover,the 4 quality variation components were reckoned to be the al-ternative markers on antioxidant according to the results of GRA and PLSR.The molecule docking result also showed that 4 candidate quality markers presented good binding affinity with the antioxidant core targets.The antioxidant capacity was presumably originated from the collaborated effects by multi-components in the standard decoction of Schisandrae Chinensis Fructus.In the interim,protocate-chuic acid exhibited noteworthy antioxidant efficacy with dosage-depended manner in the results of single-compound verification,which was best conformed to the characteristics of quality markers and supposed to be the antioxidant quality marker for Schisandrae Chinensis Fructus standard decoction.CONCLUSION This research predicts the potential antioxidant substances on the basis of content deter-mination by UPLC and in vitro antioxidant assay,but also provides rational foundation for quality assessment on other preparations of Schisandrae Chinensis Fructus.

OBJECTIVE: To investigate the feasibility of MRI three-dimensional (3D) reconstruction model in quantifying glenoid bone defect by comparing with CT 3D reconstruction model measurement. METHODS: Forty patients with shoulder anterior dislocation who met the selection criteria between December 2021 and December 2022 were admitted as study participants. There were 34 males and 6 females with an average age of 24.8 years (range, 19-32 years). The injury caused by sports injury in 29 cases and collision injury in 6 cases, and 5 cases had no obvious inducement. The time from injury to admission ranged from 4 to 72 months (mean, 28.5 months). CT and MRI were performed on the patients' shoulder joints, and a semi-automatic segmentation of the images was done with 3D slicer software to construct a glenoid model. The length of the glenoid bone defect was measured on the models by 2 physicians. The intra-group correlation coefficient ( ICC) was used to evaluate the consistency between the 2 physicians, and Bland-Altman plots were constructed to evaluate the consistency between the 2 methods. RESULTS: The length of the glenoid bone defects measured on MRI 3D reconstruction model was (3.83±1.36) mm/4.00 (0.58, 6.13) mm for physician 1 and (3.91±1.20) mm/3.86 (1.39, 5.96) mm for physician 2. The length of the glenoid bone defects measured on CT 3D reconstruction model was (3.81±1.38) mm/3.80 (0.60, 6.02) mm for physician 1 and (3.99±1.19) mm/4.00 (1.68, 6.38) mm for physician 2. ICC and Bland-Altman plot analysis showed good consistency. The ICC between the 2 physicians based on MRI and CT 3D reconstruction model measurements were 0.73 [95% CI (0.54, 0.85)] and 0.80 [95% CI (0.65, 0.89)], respectively. The 95% CI of the difference between the two measurements of physicians 1 and 2 were (-0.46, 0.49) and (-0.68, 0.53), respectively. CONCLUSION The measurement of glenoid bone defect based on MRI 3D reconstruction model is consistent with that based on CT 3D reconstruction model. MRI can be used instead of CT to measure glenoid bone defects in clinic, and the soft tissue of shoulder joint can be observed comprehensively while reducing radiation.
Male ; Female ; Humans ; Young Adult ; Adult ; Imaging, Three-Dimensional/methods* ; Tomography, X-Ray Computed/methods* ; Joint Instability ; Shoulder Joint/diagnostic imaging* ; Shoulder Dislocation ; Magnetic Resonance Imaging/methods*

Objective:To compare the clinical efficacy between robot-assisted and free-hand percutaneous cannulated screwing (PCS) in the treatment of femoral neck fractures in the middle-aged and young patients.Methods:A retrospective study was conducted to analyze the clinical data of 53 patients with femoral neck fracture who had been treated with PCS from May 2020 to May 2022 at Department of Traumatic Surgery, Maoming Hospital Affiliated to Southern Medical University. In the robot group of 25 patients subjected to robot-assisted PCS, there were 11 males and 14 females with an age of (48.2 ± 11.9) years; in the free-hand group of 28 patients subjected to free-hand PCS, there were 13 males and 15 females with an age of (48.5 ± 9.8) years. The 2 groups were compared in terms of operation time, intraoperative bleeding, intraoperative guide drills, intraoperative fluoroscopy frequency, fracture union time, Harris hip score at the last follow-up and postoperative complications. Postoperative imaging examination was performed to evaluate distribution accuracy of the cannulated screws in the femoral neck (deviation between the screws and the femoral neck axis, parallelism between the screws and distance between the screws and the neck cortex).Results:There was no statistically significant difference between the robot and free-hand groups in the general clinical data before operation, showing comparability ( P>0.05). The robot group showed significantly shorter operation time [(32.7 ± 4.8) min], significantly less intraoperative bleeding [(14.6 ± 4.8) mL], significantly less intraoperative guide drillings [(3.5 ± 0.7) times] and significantly less intraoperative fluoroscopy frequency [(7.9 ± 1.4) times] than the free-hand group [(56.9 ± 11.3) min, (27.0 ± 7.3) mL, (9.1 ± 1.8) times and (16.3 ± 6.0) times)] (all P<0.05). Postoperative imaging showed that the deviation between the screws and the femoral neck axis was 4.4° ± 1.1° on the anteroposterior X-ray film and 3.2° ± 0.8° on the lateral X-ray film, the parallelism between the screws 4.9° ± 0.8° on the anteroposterior X-ray film and 3.0° ± 0.7° on the lateral X-ray film, and the distance between the screws and the femoral neck cortex (10.4 ± 2.7) mm in the robot group, all significantly smaller than those in the free-hand group [10.5° ± 2.8°, 4.9° ± 1.1°, 12.1° ± 4.0°, 5.1° ± 1.3°, and (15.4 ± 3.2) mm] (all P<0.05). All the 53 patients were followed up for (22.2 ± 8.5) months. All fractures got united. The fracture union time in the robot group [(20.6 ± 4.6) weeks] was insignificantly shorter than that in the free-hand group [(23.7 ± 7.7) weeks] ( P>0.05). At the last follow-up, the Harris hip score in the robot group [(88.6 ± 5.6) points] was significantly higher than that in the free-hand group [(84.8 ± 6.3) points] ( P<0.05). Follow-ups revealed 2 cases of internal fixation loosening, 1 case of screw head cutting and 1 case of femoral head necrosis in the free-hand group but none of such complications in the robot group. Conclusion:In the treatment of femoral neck fractures in the middle-aged and young patients, compared with free-hand PCS, robot-assisted PCS shows advantages of shorter intraoperative time, less bleeding, less fluoroscopic radiation, higher accuracy of screw placement, a lower incidence of postoperative complications and better functional recovery of the hip joint.

OBJECTIVE To study the correlation between processing time, chroma value and UPLC fingerprint map of Dipsaci Radix. METHODS Established the UPLC fingerprint of Dipsaci Radix. Monitored the changes of chemical components in the processing process of wine and salt processed Dipsaci Radix, spectrophotometer was used to objectively quantify the chroma value of different processed products. SPSS 20.0 and SIMCA 14.0 statistical software was used to analyze the correlation between processing time and chroma value and fingerprint. RESULTS In the process of processing, the decoction pieces color of the powder deepened and L*, b* and E* values decreased. The correlation analysis showed that the processing time was significantly correlated with the chroma value and fingerprint of decoction pieces. CONCLUSION The method of UPLC fingerprint is stabled and reliabled, combines with the objective discriminant analysis of the chroma value of the Dipsaci Radix processed products, which lay the foundation for standardizing the processing technology of wine and salt processed products and evaluating the quality of Dipsaci Radix.

Atherosclerotic cardiovascular disease is a common disease with high incidence rate and mortality worldwide. Atherosclerosis is an important pathological basis for the formation of ischemic cardiovascular diseases such as cardiovascular disease， which is related to inflammation， oxidative stress， apoptosis， vascular endothelial damage， foam cell formation， platelet activation， and so on， involving mitogen-activated protein kinase （MAPK）， phosphoinositide 3-kinase/protein kinase B （PI3K/Akt）， cyclic adenosine monophosphate/protein kinase A （cAMP/PKA）， Ras homolog gene family member A （RhoA）/Rho-associated coiled-coil containing protein kinase （ROCK）， nuclear factor-kappa B （NF-κB）， and other signaling pathways. In the past few decades， high-intensity statins were mainly used to treat atherosclerosis by reducing blood lipid levels， which usually caused obvious side effects. Therefore， the development of safer and more effective drugs and treatment modes is the focus of research at this stage. In recent years， Chinese medicine has been playing an increasingly important role in the prevention and treatment of cardiovascular diseases in China. There are many studies on the mechanism of Chinese medicine in the prevention and treatment of atherosclerosis， and it is found that a variety of single Chinese medicine regulate the formation process of atherosclerosis by regulating targeted signal molecules. This paper reviewed the research results of related signaling pathways involved in the pathological formation of atherosclerosis and the mechanism of Chinese medicine in the prevention and treatment of cardiovascular diseases， thereby providing references for the clinical treatment of cardiovascular diseases.