Objective Using female mice to investigate the reparative effects of human umbilical cord mesenchymal stem cells on radiation-induced ovarian injury. Methods Mice were randomly divided into three groups: a blank control group, a radiation model group, and a cell therapy group. Mice in the radiation model group and the cell therapy group received a single whole-body irradiation of 5 Gy X-rays. Within 2 hours post-irradiation, mice in the cell therapy group underwent ovarian transplantation of UC-MSCs. On days 1, 7, and 14 post-irradiation, body weight was measured, ovarian index was calculated, histopathological changes in ovarian tissue were examined, serum levels of reproductive hormones (follicle-stimulating hormone, anti-Müllerian hormone, and estradiol) were determined, and the colonization of implanted UC-MSCs in the mice was observed. Results On days 1, 7, and 14 post-irradiation, both the cell therapy group and the radiation model group showed decreased body weight compared to the blank control group (P < 0.05). On day 1 post-irradiation compared to day 1 pre-irradiation within the same group, the radiation model group exhibited a greater decrease in body weight than the cell therapy group (P < 0.05). On days 1, 7, and 14 post-irradiation, the ovarian index decreased in both the radiation model group and the cell therapy group compared to the blank control group (P < 0.05). On days 7 and 14 post-irradiation, the ovarian index in the cell therapy group was significantly higher than that in the radiation model group (P < 0.05). Ovarian tissue in the radiation model group exhibited atrophy and a reduction in the number of follicles at all stages. In contrast, follicles in the cell therapy group were large and abundant. On days 1, 7, and 14 post-irradiation, serum follicle-stimulating hormone levels in the cell therapy group were lower than those in the radiation model group, while anti-Müllerian hormone and estradiol levels were higher than those in the radiation model group (P < 0.01). In vivo fluorescence imaging demonstrated that UC-MSCs successfully colonized the ovarian tissue on days 1, 7, and 14 after transplantation. Conclusion UC-MSCs exert a repair effect on radiation-induced ovarian injury in mice.

【Objective】 To compare the efficacy and safety of thulium laser enucleation of the prostate (ThULEP) and holmium laser enucleation of the prostate (HoLEP) in the treatment of benign prostatic hyperplasia (BPH). 【Methods】 Randomized controlled trials (RCTs) and clinical controlled trials (CCTs) were searched in PubMed, Embase, Cochrane Library, CNKI and Wanfang Database from Jan.1,2010 to May 30,2022. Two reviewers independently screened literature, extracted data, and assessed the risk of bias of included studies. All divergences were resolved by a third researcher. RevMan 5.4 software was used for Meta analysis. 【Results】 A total of 7 studies were included, involving 1 726 patients, 750 in the ThULEP group and 976 in the HoLEP group. Meta analysis showed that, compared with HoLEP group, the ThULEP group had shorter catheter indwelling time [MD=-0.10, 95%CI (-0.17--0.03), P=0.004] , shorter hospital stay [MD=-0.43, 95%CI (-0.60--0.25), P<0.000 01] , lower IPSS score 12 months after surgery [MD=-1.13, 95%CI (-1.95- -0.30), P=0.007] , lower QoL score 12 months after surgery [MD=-1.00, 95%CI (-1.19- -0.81), P<0.001] ,lower transfusion rate [OR=0.11, 95%CI (0.03-0.36), P=0.000 3] and lower incidence of urinary incontinence [OR=0.24, 95%CI (0.09-0.66), P=0.006] . 【Conclusion】 ThULEP may have similar efficacy and safety as HoLEP in the treatment of BPH, and has more advantages in some aspects.

Objective:To evaluate the effectiveness of deep learning reconstruction (DLR) compared with hybrid iterative reconstruction (Hybrid IR) in improving the image quality in chest low-dose CT (LDCT).Methods:Seventy-seven patients who underwent LDCT scan for physical examination or regular follow-up in Peking Union Medical College Hospital from October 2020 to March 2021 were retrospectively included. The LDCT images were reconstructed with Hybrid IR at standard level (Hybrid IR Stand) and DLR at standard and strong level (DLR Stand and DLR Strong). Regions of interest were placed on pulmonary lobe, aorta, subscapularis muscle and axillary fat to measure the CT value and image noise. The signal to noise ratio (SNR) and contrast to noise ratio (CNR) were calculated. Subjective image quality was evaluated using Likert 5-score method by two experienced radiologists. The number and features of ground-glass nodule (GGN) were also assessed. If the scores of the two radiologists were inconsistent, the score was determined by the third radiologist. The objective and subjective image evaluation were compared using the Kruskal-Wallis test, and the Bonferroni test was used for multiple comparisons within the group.Results:Among Hybrid IR Stand, DLR Stand and DLR Strong images, the CT value of pulmonary lobe, aorta, subscapularis muscle and axillary fat had no significant differences (all P>0.05), but the image noise and SNR of pulmonary lobe, aorta, subscapularis muscle and axillary fat had significant differences(all P<0.05), and the CNR of images had significant difference( P<0.05), too. The CNR of Hybrid IR Stand images, DLR stand images and DLR strong images were 0.71 (0.49, 0.88), 1.06 (0.78, 1.32) and 1.14 (0.84, 1.48), respectively. Compared with Hybrid IR images, DLR images had lower objective and subjective image noise,higher SNR and CNR (all P<0.05). The scores of DLR images were superior to Hybrid IR images in identifying lung fissures, pulmonary vessels, trachea and bronchi, lymph nodes, pleura, pericardium and GGN (all P<0.05). Conclusions:DLR significantly reduced the image noise, and DLR images were superior to Hybrid IR images in identifying GGN in chest LDCT while maintaining superior image quality at relatively low radiation dose levels. Thus DLR images can improve the safety of lung cancer screening and pulmonary nodule follow-up by CT.

Objective:To explore the effect of deep learning reconstruction (DLR) on radiation dosage reduction and image quality of CTPA compared with hybrid iterative reconstruction (HIR).Methods:A total of 100 patients with suspected pulmonary embolism (APE) or indications for CTPA due to other pulmonary artery diseases in Peking Union Medical College Hospital from December 2020 to April 2021 were prospectively enrolled and divided into HIR group and DLR group according to block randomization, with 50 cases in each group. The patient′s gender, age and body mass index (BMI) were recorded. HIR group and DLR group underwent standard deviation (SD)=8.8 and SD=15 CTPA protocols in combination with HIR and DLR algorithm respectively. Other scanning parameters and contrast medium injection plan were the same. The effective dose (ED) and size-specific dose estimate (SSDE) were calculated. Regions of interest (ROIs) were drawn in the lumen of Grade 1-3 pulmonary arteries and bilateral paravertebral muscles. The corresponding CT and SD values were recorded to acquire signal to noise ratio (SNR) and contrast noise ratio (CNR). Based on a double-blind method, two radiologists evaluated the subjective noise, visualization of pulmonary arteries, and diagnostic confidence of the two groups by 5-point Likert scales. The inconsistent results were judged comprehensively by the third radiologist. Independent samples t-test was used to compare the demographic data, radiation dosage and quantitative image quality of the two groups. Mann-Whitney U test was used to compare the subjective noise, visualization of pulmonary arteries and diagnostic confidence between the two groups. Linear weighted Kappa coefficient was calculated to analyze the consistency of the qualitative scores between the two radiologists. Results:There were no significant differences in gender, age and BMI between the two groups ( P>0.05). The CT values of Grade1-3 pulmonary arteries and paravertebral muscle had no significant differences ( P>0.05). Compared with HIR group, the ED and SSDE in DLR group decreased by about 35% to 1.3 mSv and 4.20 mGy respectively, while the SNR (30±5) and CNR (26±5) of CTPA images were higher in DLR group than those in HIR group (23±5 and 20±5, with t=-6.60 and -5.90, respectively, both P<0.001). The subjective noise score was higher in DLR group than that in HIR group ( Z=-7.34, P<0.001). In addition, two radiologists showed excellent interobserver agreement in DLR group (Kappa=0.847, 95%CI 0.553-1.000). No significant differences were found in visualization of pulmonary arteries and diagnostic confidence between the two groups ( P>0.05). Conclusion:DLR further reduced the radiation dosage and improved the image quality of CTPA, with no detriment to diagnostic confidence. Thus DLR is worthy of clinical promotion.

Objective:To investigate the feasibility of chest ultra-low dose CT (ULDCT) using deep learning reconstruction (DLR) for lung cancer screening, and to compare its image quality and nodule detection rate with ULDCT iterative reconstruction (Hybrid IR) and conventional dose CT (RDCT) Hybrid IR.Methods:The patients who underwent chest CT examination for pulmonary nodules in Peking Union Medical College Hospital from October 2020 to March 2021 were prospectively included and underwent chest RDCT (120 kVp, automatic tube current), followed by ULDCT (100 kVp, 20 mA). The RDCT images were reconstructed with Hybrid IR (adaptive iterative dose reduction 3D,AIDR 3D), and ULDCT was reconstructed with AIDR3D and DLR. Radiation dose parameters and nodule numbers were recorded. Image quality was assessed using objective noise, signal-to-noise ratio (SNR) of the main trachea and left upper lobe, subjective image scores of the lung and nodules. Subjective scores were scored by 2 experienced radiologists on a Likert 5-point scale. The difference of radiation dose was compared with paired t-test between ULDCT and RDCT.The differences of quantitative indexes, objective image noise and subjective scores of the three reconstruction methods were compared with one-way analysis of variance or Friedman test. Results:Forty-five patients were enrolled, including 17 males and 28 females, aged from 32 to 74 (55±11) years. The radiation dose of ULDCT was (0.17±0.01) mSv, which was significantly lower than that of RDCT [(1.35±0.41) mSv, t=15.46, P<0.001]. There were significant differences in the image noise and SNR in the trachea and lung parenchyma and in the CT value of the trachea among ULDCT-AICE, ULDCT-AIDR 3D and RDCT-AIDR 3D images ( P<0.05). Image noise in the trachea and lung parenchyma and CT value in the trachea of ULDCT-AICE were significantly lower than those of ULDCT-AIDR 3D ( P<0.05) and comparable to RDCT-AIDR 3D ( P>0.05). There were significant differences in subjective image scores of the lung and nodules among ULDCT-AICE, ULDCT-AIDR 3D and RDCT-AIDR 3D images (χ2=50.57,117.20, P<0.001). Subjective image scores of the lung and nodules for ULDCT-AICE were significantly higher than those of ULDCT-AIDR 3D ( P<0.05), and non-inferior to RDCT-ADIR 3D ( P>0.05). All 72 clinically significant nodules detected on RDCT-ADIR 3D were also noted on ULDCT-AICE and ULDCT-AIDR 3D images. Conclusions:Chest ULDCT using DLR can significantly reduce the radiation dose, and compared with Hybrid IR, it can effectively reduce the image noise and improve SNR, and display the pulmonary nodules well. The image quality and nodule detection are not inferior to RDCT Hybrid IR routinely used in clinical practice.

Objective:To develop a visualized nomogram with a predictive value to differentiate mass-forming chronic pancreatitis (MFCP) from pancreatic ductal adenocarcinoma (PDAC) patients with chronic pancreatitis (CP) history.Methods:The clinical and radiological data of 5 433 CP patients acoording to the Asia-Pacific Diagnostic Criteria between February 2011 and February 2021 in the First Affiliated Hospital of Naval Medical University were retrospectively analyzed, and 71 PDAC patients with CP history and 67 MFCP who underwent surgery or biopsy and pathologically confirmed were eventually enrolled. The training set included 44 patients with MFCP and 59 patients with PDAC who were diagnosed between February 2011 and April 2018. The validation set consisted of 23 patients with MFCP and 12 patients with PDAC who were diagnosed between May 2018 and February 2021. Univariate and multivariate logistic regression analyses were performed to develop a prediction model for PDAC and MFCP, and the model was visualized as a nomogram. ROC was used to evaluate the predictive efficacy of the nomogram, and the clinical usefulness was judged by decision curve analysis.Results:The univariate analysis showed that a significant association with pancreatic cancer were observed for the duct-to-parenchyma ratio ≥0.34, pancreatic duct cut-off, pancreatic portal hypertension, arterial CT attenuation, portal venous CT attenuation, delayed CT attenuation, and vascular invasion in both the training and validation cohorts, but the duct-penetrating sign in the training cohort only. The multivariable logistic regression analysis showed that statistically significant differences (all P value <0.05) existed in cystic degeneration, a duct-to-parenchyma ratio ≥0.34, the duct-penetrating sign, pancreatic portal hypertension and arterial CT attenuation between the two cohorts. The above parameters were selected for the logistic regression model. The predicted model=3.65-2.59×cystic degeneration+ 1.26×duct-to-parenchyma ratio≥0.34-1.40×duct-penetrating sign+ 1.36×pancreatic portal hypertension-0.05×arterial CT attenuation. Area under the curve, sensitivity, specificity and accuracy of the model-based nomogram were 0.87 (95 CI 0.80-0.94), 89.0%, 75.0% and 83.5% in the training cohort, and 0.94 (95 CI 0.82-0.99), 91.7%, 100% and 97.1% in the validation cohort, respectively. Decision curve analysis showed that when the nomogram differentiated MFCP from PDAC patients with CP history at a rate of 0.05-0.85, the application of the nomogram could benefit the patients. Conclusions:The nomogram based on CT radiological features accurately differentiated MFCP from PDAC patients with CP history and provide reference for guiding the treatment and judging the prognosis.

Objective:To investigate the relationship between the perineural invasion score based on multidetector computed tomography (MDCT) and extrapancreatic perineural invasion (EPNI) in pancreatic ductal adenocarcinoma (PDAC).Methods:The clinical, radiological, and pathological data of 374 patients pathologically diagnosed as pancreatic cancer who underwent radical resection in the First Affiliated Hospital of Naval Medical University from March 2018 to May 2020 were analyzed retrospectively. Patients were divided into EPNI negative group ( n=111) and EPNI positive group (n=263) based on the pathological presence of EPNI. The perineural invasion score was performed for each patient based on radiological images. Univariate and multivariate logistic regression models were used to analyze the association between the perineural invasion score based on MDCT and EPNI in PDAC. Results:There were significant statistical differences between EPNI negative group and positive group on both pathological characteristics (T stage, N stage, invasion of common bile duct, and positive surgical margin) and radiological characteristics (tumor size, vascular invasion, lymph node metastasis, perineural invasion score based on MDCT, pancreatic border, parenchymal atrophy, invasion of duodenum, invasion of spleen and splenic vein and invasion of common bile duct) (all P value <0.05). Univariate analysis revealed that the tumor size, vascular invasion, lymph node metastasis, perineural invasion score based on MDCT, pancreatic border, pancreatic atrophy, invasion of duodenum, invasion of spleen and splenic vein and invasion of common bile duct were independently associated with EPNI. Multivariate analyses revealed that the perineural invasion based on MDCT was an independent risk factor for EPNI in pancreatic cancer (score=1, OR=2.93, 95% CI 1.61-5.32, P<0.001; score=2, OR=5.92, 95% CI 2.68-13.10, P<0.001). Conclusions:The perineural invasion score based on MDCT was an independent risk factor for EPNI in pancreatic cancer and can be used as an evaluation indicator for preoperative prediction of EPNI in PDAC.

Objective:To explore the differential diagnosis of pancreatic acinar cell carcinoma (PACC) and pancreatic ductal adenocarcinoma (PDAC) based on multidetector computed tomography (MDCT) features.Methods:The clinical, pathological and MDCT imaging data of 26 patients with pathologically confirmed PACC and 145 patients with pathologically confirmed PDAC who underwent MDCT from November 2013 to April 2021 were retrospectively studied. The differences of MDCT features including tumor location, tumor size, common pancreatic duct and bile duct dilatation, pancreatitis, lymph node metastasis, cyst, pancreatic parenchyma atrophy, duodenal involvement, bile ductal and vascular involvement between the two groups were compared. Univariate analysis and multivariate analysis by logistic regression models were performed to identify the independent predictive factors for PACC.Results:The tumor size, bile duct dilatation, lymph node metastasis, pancreatic parenchyma atrophy and vascular involvement were significantly different between PACC group and PDAC group (all P value<0.05). Multivariate analysis revealed that the tumor size ( OR=1.07, 95% CI 1.028-1.15, P=0.001), lymph node metastasis ( OR=0.23, 95% CI 0.065-0.800, P=0.02), pancreatic parenchyma atrophy ( OR=0.15, 95% CI 0.048-0.490, P=0.002) were closely associated with PACC. Conclusions:The tumor size, bile duct dilatation, lymph node metastasis, pancreatic parenchyma atrophy and vascular involvement evaluated by MDCT had a certain value in differentiating PACC from PDAC, and the tumor size, lymph node metastasis and pancreatic parenchyma atrophy were independent predictors for the diagnosis of PACC.

Hyperbaric oxygen therapy (HBOT) has been widely used in the treatment ofhypoxia,ischemia,and a series of diseases caused by hypoxia and ischemia.The treatment effect of HBOT on gliomas remains controversial.The presence of local hypoxia in gliomas is the main cause of tumor resistance to radiotherapy and chemotherapy;HBOT can improve the oxygen content in these areas,and thus,treatment should be as effective as other hypoxic diseases;however,most researchers believe that in the process of gliomas,the efficacy of HBOT alone is limited,and HBOT is usually not used alone.More commonly,HBOT is commonly used as adjuvant therapy in other treatments (such as radiotherapy and chemotherapy).Based on the above contents,we summarized as follows and put forward the views on the current debate.

Objective To evaluate the relationship between the degree of brain injury during the perioperative period of liver transplantation and postoperative cognitive dysfunction (POCD).Methods Thirtythree patients,undergoing elective liver transplantation,were enrolled in this study.Before induction of anesthesia (T0),at 5 min before blocking the portal vein (T1),5 min after opening the portal vein (T2),5 min after opening the hepatic artery (T3),and at 24 h after surgery (T4),blood samples were collected from the central vein for determination of the serum concentrations of S1O0β protein and neuron-specific enolase (NSE) by enzyme-linked immunosorbent assay.Patients were divided into POCD group and control group (group C) according to whether POCD happened within 7 days after surgery.Results Compared with the baseline value at T0,the serum concentrations of S100β protein were significantly increased at T2 and T3,and the serum concentrations of NSE was increased at T3 (P＜0.05).There was no significant difference in serum concentrations of S100β and NSE at each time point between group POCD and group C (P＞0.05).Conclusion The degree of brain injury during the perioperative period of liver transplantation is not the dominant factor for the development of POCD in the patients.