Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

OBJECTIVE: To investigate the role of α7-nicotinic acetylcholine receptor (α7-nAChR) in the regulation of neuronal activity and expression of synapse-related proteins in the thalamic reticular nucleus (TRN) of insomnia rats treated by acupuncture. METHODS: A total of 36 male Sprague-Dawley (SD) rats of clean grade were randomly divided into a control group, a model group, an acupuncture group, and an acupuncture+antagonist group, with 9 rats in each group. The model group, the acupuncture group, and the acupuncture+antagonist group were treated with intraperitoneal injection of p-chlorophenylalanine (PCPA) to establish insomnia model. After successful modeling, the acupuncture group and the acupuncture+antagonist group received acupuncture at bilateral Neiguan (PC6) and Zusanli (ST36) once daily for 5 consecutive days. Thirty min before each acupuncture session, the acupuncture+antagonist group was intraperitoneally injected with methyllycaconitine citrate (MLA), an α7-nAChR antagonist, at a dosage of 5 mg/kg while the acupuncture group received the same volume of 0.9% sodium chloride solution. The rats' daytime spontaneous activity was observed. Neuronal discharge in the TRN was detected using neuroelectrophysiological methods. Immunofluorescence staining was used to detect parvalbumin-positive (PV⁺) neurons and co-expression of PV⁺ and postsynaptic density protein-95 (PSD-95) in the TRN. RESULTS: Compared with the control group, the model group showed increased daytime spontaneous activity (P<0.01); decreased average fluorescence intensity and positive number of PV⁺ neurons in the TRN (P<0.01); decreased neuronal discharge frequency (P<0.01), prolonged inter-discharge intervals (P<0.01) in the TRN; reduced number of PV⁺/PSD-95 double-positive cells in the TRN (P<0.01). Compared with the model group, the acupuncture group showed decreased daytime spontaneous activity (P<0.01); increased average fluorescence intensity and positive number of PV⁺ neurons in the TRN (P<0.01); increased neuronal discharge frequency (P<0.01), shortened inter-discharge intervals (P<0.01) in the TRN; increased number of PV⁺/PSD-95 double-positive cells in the TRN (P<0.05). Compared with the acupuncture group, the acupuncture+antagonist group exhibited increased daytime spontaneous activity (P<0.01); reduced average fluorescence intensity and positive number of PV⁺ neurons in the TRN (P<0.01); decreased neuronal discharge frequency (P<0.05), prolonged inter-discharge intervals (P<0.05) in the TRN; reduced number of PV⁺/PSD-95 double-positive cells in the TRN (P<0.01). CONCLUSION α7-nAChR are involved in mediating the regulatory effect of acupuncture on circadian rhythm disturbances in PCPA-induced insomnia rats. Blocking α7-nAChR attenuates the activating effect of acupuncture on TRN neurons, and reduces the expression of PSD-95 protein on GABAergic neurons.
Animals ; Male ; Acupuncture Therapy ; alpha7 Nicotinic Acetylcholine Receptor/genetics* ; Rats, Sprague-Dawley ; Rats ; Sleep Initiation and Maintenance Disorders/physiopathology* ; Neurons/metabolism* ; Humans ; Thalamic Nuclei/physiopathology* ; Acupuncture Points ; Disks Large Homolog 4 Protein

Objective To compare the clinical efficacy and safety of transarterial chemoembolization(TACE)plus apatinib(Apa)and camrelizumab(Cam)and TACE plus Apa in treating CNLC stage Ⅲ hepatocellular carcinoma(HCC).Methods A total of 54 patients in Affiliated Yancheng No.1 People's Hospital,School of Medicine,Nanjing University with CNLC stage Ⅲ HCC were enrolled in this study.The patients were divided into triple treatment group(n=25,receiving TACE plus Apa and Cam)and dual treatment group(n=29,receiving TACE plus Apa).The overall survival(OS)and progression-free survival(PFS)were compared between the two groups.Univariate analysis and multivariate analysis were used to determine the independent influencing factors for OS and PFS.The target immunotherapy-related adverse reactions(TRAE)were analyzed.Results The median OS and PFS in the triple treatment group were 23.2 months and 10.9 months respectively,which were higher than 15.2 months and 5.8 months respectively in the dual treatment group(both P＜0.001).Multivariate analysis indicated that the therapeutic regimen and the type of portal vein tumor thrombosis(PVTT)were the independent factors affecting OS,while only the therapeutic regimen was the independent factor affecting PFS.The incidence of≥grade Ⅲ TRAE in the triple treatment group and the dual treatment group was 20％(5/25)and 17.2％(5/29)respectively,the difference between the two groups was not statistically significant(P＞0.05).Conclusion For the treatment of patients with CNLC stage Ⅲ HCC,TACE plus Apa and Cam is superior to TACE plus Apa in OS and PFS,and the type of PVTT and the therapeutic regimen are the independent prognostic factors associated with patient's survival.

Objective:To construct a machine-learning model for predicting the progression of pancreatic cystic lesions (PCLs) based on clinical and CT features, and to evaluate its predictive performance in internal/external testing cohorts.Methods:Baseline clinical and radiological data of 200 PCLs in 177 patients undergoing abdominal thin slice enhanced CT examination at Peking Union Medical College Hospital from July 2014 to December 2022 were retrospectively collected. PCLs were divided into progressive and non-progressive groups according to whether the signs indicated for surgery by the guidelines of the European study group on PCLs were present during three-year follow-up. 200 PCLs were randomly divided into training (150 PCLs) and internal testing cohorts (50 PCLs) at the ratio of 1∶3. 15 PCLs in 14 patients at Jinling Affiliated Hospital of Medical School of Nanjing University from October 2011 to May 2020 were enrolled as external testing cohort. The clinical and CT radiological features were recorded. Multiple feature selection methods and machine-learning models were implemented and combined to identify the optimal machine-learning model based on the 10-fold cross-validation method. Receiver operating characteristics (ROC) curve was drawn and area under curve (AUC) was calculated. The model with the highest AUC was determined as the optimal model. The optimal model's predictive performance was evaluated on testing cohort by calculating AUC, sensitivity, specificity and accuracy. Permutation importance was used to assess the importance of optimal model features. Calibration curves of the optimal model were established to evaluate the model's clinical applicability by Hosmer-Lemeshow test.Results:In training and internal testing cohorts, the progressive and non-progressive groups were significantly different on history of pancreatitis, lesions size, main pancreatic duct diameter and dilation, thick cyst wall, presence of septation and thick septation (all P value <0.05) In internal testing cohort, the two groups were significantly different on gender, lesion calcification and pancreatic atrophy (all P value <0.05). In external testing cohort, the two groups were significantly different on lesions size and pancreatic duct dilation (both P<0.05). The support vector machine (SVM) model based on five features selected by F test (lesion size, thick cyst wall, history of pancreatitis, main pancreatic duct diameter and dilation) achieved the highest AUC of 0.899 during cross-validation. SVM model for predicting the progression of PCLs demonstrated an AUC of 0.909, sensitivity of 82.4%, specificity of 72.7%, and accuracy of 76.0% in the internal testing cohort, and 0.944, 100%, 77.8%, and 86.7% in the external testing cohort. Calibration curved showed that the predicted probability by the model was comparable to the real progression of PCLs. Hosmer-Lemeshow goodness-of-fit test affirmed the model's consistency with actual PCLs progression in testing cohorts. Conclusions:The SVM model based on clinical and CT features can help doctors predict the PCLs progression within three-year follow-up, thus achieving efficient patient management and rational allocation of medical resource.

Objective To investigate the efficacy and safety of hybrid surgery for the recanalization of carotid artery occlusion after stenting.Methods Clinical data and results of 17 patients with occlusion after carotid artery stenting and treated with hybrid surgery from June 2016 to April 2023 at the Department of Neurosurgery Cerebral Blood Flow Reconstruction Center of Xuanwu Hospital,Capital Medical University were retrospectively analyzed.According to whether the recanalization was successful,17 patients were divided into the the successful recanalization group and the failed recanalization group.Successful recanalization was defined as achieving modified thrombolysis in cerebral infarction(mTICI)grade ≥2b and residual stenosis＜50％.Baseline data(age,sex,body mass index,smoking history,alcohol consumption history,hypertension history,diabetes history,hyperlipidemia history,coronary heart disease history),clinical data(National Institutes of Health Stroke Scale[NIHSS]score at admission,fasting blood glucose,low density lipoprotein,high density lipoprotein,total cholesterol,triglyceride,occlusion side and segment,combination with severe stenosis or occlusion of the contralateral carotid artery,opening of the anterior communicating artery,opening of the posterior communicating artery,compensation of the external and internal carotid artery,compensation of the pia artery,stump morphology,and time from imaging diagnosis of occlusion to recanalization)were documented and compared between groups.The recanalization of occlusive vessels and perioperative complications were recorded.Imaging and clinical follow-up were performed 3,6 months and≥1 year after surgery.Results Among the 17 patients,the ratio of successful recanalization was 13/17.One patient had re-occlusion after operation,which was re-opened after thrombolysis,but neck hematoma with dyspnea occurred,and recovered after emergency operation.There was no postoperative stroke or death.The incidence of perioperative complications was 1/17.Compared with the successful recanalization group,the levels of high density lipoprotein and total cholesterol in the failed recanalization group were higher,and the differences between the groups were statistically significant(high density lipoprotein[1.3±0.3]mmol/L vs.[0.9±0.3]mmol/L,t=-2.139;total cholesterol:[4.2±0.8]mmol/L vs.[3.1±0.7]mmol/L,t=-2.649;both P＜0.05);There were no significant differences in other baseline data and clinical data(all P＞0.05).Imaging follow-up was completed in 9 of the 13 patients in the successful recanalization group,and the follow-up time was 3.8-36.9 months,with a median follow-up time of 22.8(12.8,34.7)months.Among them,1 patient(1/9)developed restenosis of recanalization vessels at 33.0 months after surgery and underwent stent implantation again.Conclusions The preliminary analysis showed that the occlusion after carotid artery stenting had better recanalization success and lower perioperative complications.In patients with chronic occlusion after carotid stenting,the application of a hybrid surgery for opening may be attempted under multimodal imaging assessment.

Objective: To evaluate the image quality of novel dark-blood computed tomography angiography (CTA) imaging combined with deep learning reconstruction (DLR) compared to delayed-phase CTA images with hybrid iterative reconstruction (HIR), to visualize the cervical artery wall in patients with Takayasu arteritis (TAK). Materials and Methods: This prospective study continuously recruited 53 patients with TAK (mean age: 33.8 ± 10.2 years; 49 females) between January and July 2022 who underwent head-neck CTA scans. The arterial- and delayed-phase images were reconstructed using HIR and DLR. Subtracted images of the arterial-phase from the delayed-phase were then added to the original delayed-phase using a denoising filter to generate the final-dark-blood images. Qualitative image quality scores and quantitative parameters were obtained and compared among the three groups of images: Delayed-HIR, Dark-blood-HIR, and Dark-blood-DLR. Results: Compared to Delayed-HIR, Dark-blood-HIR images demonstrated higher qualitative scores in terms of vascular wall visualization and diagnostic confidence index (all P < 0.001). These qualitative scores further improved after applying DLR (Dark-blood-DLR compared to Dark-blood-HIR, all P < 0.001). Dark-blood DLR also showed higher scores for overall image noise than Dark-blood-HIR (P < 0.001). In the quantitative analysis, the contrast-to-noise ratio (CNR) values between the vessel wall and lumen for the bilateral common carotid arteries and brachiocephalic trunk were significantly higher on Darkblood-HIR images than on Delayed-HIR images (all P < 0.05). The CNR values were significantly higher for Dark-blood-DLR than for Dark-blood-HIR in all cervical arteries (all P < 0.001). Conclusion Compared with Delayed-HIR CTA, the dark-blood method combined with DLR improved CTA image quality and enhanced visualization of the cervical artery wall in patients with TAK.