The amount of the research-oriented graduates is increasing in affiliated hospitals of medical universities.To create an effective training model can not only help students to succeed but also contribute great to the research level of hospitals.In this study,we summarized our experience,such as individualized teaching,the unity of thinking and performing,words and deeds as well as unity of clinic and research on the formation of research ideas,attitudes and styles.Based on our experiences we hope to provide meaningful methods for the training of medical graduates.

Objective To evaluate the feasibility of contrast material on image quality of coronary CT angiography (CCTA)by using double injection technology and iterative reconstruction.Methods 120 patients with suspected coronary heart disease who underwent CCTA were randomly divided into two groups.Then,60 patients with 30 kg/m2>BMI≥25 kg/m2 were averagely divided into A1 and B1 groups,and other 60 ones with BMI<25 kg/m2 were also averagely divided into A2 and B2 groups.The patients in group A were scanned with 120 kV tube output and iolromide 350 mg I/mL,and the images were reconstructed using filtered back projection (FBP).Meanwhile,the patients in group B were scanned with 80 kV or 100 kV tube output and 245 mg I/mL or 280 mg I/mL of contrast media (BMI≥25 kg/m2 )using double injection technology,and the images were reconstructed using adaptive iterative dose reduction 3D (AIDR 3D).The effective radiation dose (ED)of each patient was also calculated.CT attenuation of the main proximal vessels (ascending or descending aorta,pulmonary artery,RCA,LM,LAD and LCX)and the obj ective image quality (SD,CNR and SNR)were measured,and the subj ective evaluation was also assessed by an experienced radiologist.Results There was significant differences in mean image quality scores,SD,SNR and CNR of ascending aorta between group A1 and B1(P<0.05),but no difference in the SI of values (P>0.05).There was no significant difference in mean image quality scores between group A2 and B2 (P>0.05), however,there were significant differences in the SI,SD of values and SNR,CNR of ascending aorta (P<0.05).The values of BMI were negatively related to the values of CT in ascending aorta between two subgroups (r=-0.66 and -0.441,P<0.05).The values of weight were not related to the values of CT in ascending aorta (P>0.05).There was significant difference in effective dose between subgroups (P<0.05).Conclusion The method with a combination of iterative reconstruction and a contrast material of 245 mg I/mL using double inj ection technology can improve the contrast enhancement without impairing image quality.

OBJECTIVE To surveillance invasive fungal infection rate in SICU,in order to direct intervention to prevent invasive fungal infection.METHODS The samples collected from SICU patients in our hospital between Jan 2003-Nov 2008 were cultured.RESULTS According to the diagnosis standard of nosocomial infections,75 case of 3699 patients were isolated fungi.During 6-years invasive fungal infection rate is 2.027%,(1.05%-2.63%).Totally 86 fungi strains were isolated,the majority of them being Candida albicans,accounting for 46.51%;Candida glabrata 22.09%;Candida tropicalis 13.95%.CONCLUSIONS During 6-years,invasive fungal infection rate and incidence density do not increase.Candida are the major pathogens of fungal infections in SICU.

Objective To explore the clinical feasibility of predicting synchronous liver metastases based on MRI radiomics nomogram based on T2WI in rectal cancer. Methods The imaging and clinical data of 261 patients with primary rectal cancer admitted to Zhejiang People′s Hospital from April 2012 to May 2018 were retrospectively analyzed. 101 patients were accompanied by synchronous liver metastasis All cases were divided into training group (n=182) and verification group (n=79). T2WI image of each patient was selected to extract texture features by AK analysis software of GE company. A radiomics signature was constructed after reduction of dimension in training group by the least absolute shrinkage and selection operator (LASSO). Univariate logistic regression was used to select for independent clinical risk factors and multivariate logistic regression along with imaging omics tags were used to construct predictive models and nomogram. ROC was used to assess the accuracy of the nomogram in the training group and to verify them by the validation group. Finally, the clinical efficacy of each patient′s synchronized liver metastasis risk factor was calculated based on the nomogram. Results A total of 328 texture features were extracted from the T2WI. Seven most valuable features were selected after reducing the dimension by LASSO algorithm, including 3 co-occurrence matrices (GLCM) and 4 run-length matrices(RLM). Tumor staging and radiomic signatures were included in the Multifactor logistic regression to build the prediction model and nomogram. The accuracy of predicting SRLM was 0.862 and 0.844 in the training and the verification group, respectively. To evaluate the accuracy of the nomogram, radiomics signature and the tumor staging in all cases were 0.857, 0.832 and 0.663, respectively. There was no significant difference in the number of SRLM cases between the high risk group and the low risk group based on nomogram (P>0.05). Conclusion The radiomics nomogram based on T2WI can be used as a quantitative tool to predict synchronous liver metastases of rectal cancer.

OBJECTIVETo explore the application value of texture analysis of magnetic resonance images (MRI) in predicting the efficacy of neoadjuvant chemoradiotherapy(nCRT) for rectal cancer.

METHODSA total of 34 rectal cancer patients who were hospitalized at Zhejiang Provincial People's Hospital from February 2015 to April 2017 were prospectively enrolled and received 3.0T MRI examination at pre-nCRT (1 day before nCRT), early stage (at 10-day after nCRT) and middle stage (at 20-day after nCRT).

INCLUSION CRITERIAdistance from tumor lower margin to anal edge was less than 12 cm under rectoscope; rectal cancer was confirmed by preoperative pathology; clinical stage was T3 or above; lymph node metastasis existed but without distant metastasis; functions of liver, kidney and heart present no contraindications of operation.

EXCLUSION CRITERIAunfinished nCRT, surgery and three examinations of MRI; image motion artifacts; lack of postoperative pathological results. All the patients underwent rectal cancer long-term three-dimensional radiotherapy and chemotherapy combined with nCRT (oxaliplatin plus capecitabine). The tumor regression grading (TRG) was divided into TRG 0 to 4 grade after nCRT, and TRG 4 was classified as pathological complete remission (pCR); TRG 2 to 3 was classified as partial remission (PR); the rest was no remission (NR). Extraction and analysis of texture features in T2-weighted MR-defined tumor region were performed using Omni Kinetics texture software. The texture values of each time point were statistically analyzed, and the differences of texture values and change differences between pCR and PR+NR, and NR and pCR+PR were compared respectively. Statistically significant texture values were screened and were used in receiver operating characteristic (ROC) curve to assess the prediction of the efficacy of nCRT.

RESULTSOf 34 patients, 21 were males and 13 were females with median age of 49.3 years. Nineteen (55.9%) patients were low rectal adenocarcinoma and 15 (44.1%) patients were middle rectal adenocarcinoma. Nine (26.5%) cases belonged to pCR, 13 (38.2%) belonged to PR, and 12 (35.3%) belonged to NR. Before nCRT, the entropy of tumor area in pCR patients was significantly higher than that in PR+NR patients (7.164±0.272 vs. 6.823±0.309, t=2.925, P=0.006). At the middle stage of nCRT, as compared with PR+NR patients for the texture features of tumor region, the variance (1566±281 vs. 2883±867, t=-4.435, P=0.000) and entropy(5.436±0.934 vs. 6.803±0.577, t=-4.118,P=0.002) of pCR patients were significantly lower; kurtosis(4.800±1.288 vs. 3.206±1.211, t=3.333, P=0.002) and energy (0.016±0.005 vs. 0.010±0.004, t=3.240, P=0.003) of pCR patients were significantly higher. As compared to pCR+PR patients, the kurtosis(2.461±0.931 vs. 4.264±1.205, t=-4.493, P=0.000) and energy (0.011±0.004 vs. 0.014±0.004, t=-3.453, P=0.000) of the NR patients were significantly lower. As for texture change values between early stage and middle stage, the entropy difference was significant between pCR and PR+NR, NR and pCR+PR (1.344±0.819 vs. 0.489±0.319, t=3.047, P=0.014; 0.446±0.213 vs. 0.917±0.677, t=-3.638, P=0.001, respectively). As for texture change values between pre-nCRT and middle stage, variance and entropy differences between pCR and PR+NR (1759±1226 vs. 977±842, t=2.113, P=0.042; 1.728±0.918 vs. 0.524±0.355, t=3.832, P=0.004), and the change values of entropy between NR and pCR+PR (0.475±0.349 vs. 1.044±0.860, t=-2.722, P=0.011) were statistically significant. The above indicators were included in the ROC curve. The results revealed that at the middle stage, entropy value >5.983 indicated the best efficacy for the diagnosis of pCR, with the area under the ROC curve (AUC) of 0.885, the sensitivity of 100%, and the specificity of 66.7%; the energy <0.010 indicated the best AUC for diagnosis of NR was 0.902, with the sensitivity of 91.7% and specificity of 81.8%.

CONCLUSIONSTexture analysis based on T2 weighted images can predict the efficacy of nCRT for rectal cancer. The middle stage of nCRT is the best time of prediction. The entropy and energy of this period are texture parameters having higher predictive ability.

Chemoradiotherapy ; Female ; Humans ; Magnetic Resonance Spectroscopy ; Male ; Middle Aged ; Neoadjuvant Therapy ; Neoplasm Staging ; Predictive Value of Tests ; Prognosis ; Rectal Neoplasms ; diagnostic imaging ; therapy ; Treatment Outcome

AIM:To investigate the role and molecular mechanisms of SMARCA4(SWI/SNF-related,matrix-associated,actin-dependent regulator of chromatin,subfamily A,member 4)in ferroptosis.METHODS:(1)Human fi-brosarcoma HT1080 cells were treated with dimethyl sulfoxide(DMSO)and different concentrations(31.25,62.5 and 125 nmol/L)of Ras-selective lethal small molecule 3(RSL3;ferroptosis inducer).Each treatment had 3 replicate wells of cells.The protein levels of SMARCA4 were detected by Western blot.(2)Two small interfering RNAs(siSMARCA4-1 and siSMARCA4-2)were constructed according to the SMARCA4 gene sequence.After SMARCA4 knockdown,each treat-ment had 3 replicate wells of cells,and the protein levels of SMARCA4 were determined by Western blot.Effects of DMSO,necrostatin 2 racemate(Nec-1s;necroptosis inhibitor),Z-VAD(OMe)-FMK(Z-VAD,pan-caspase inhibitor/apoptosis inhibitor)and ferrostatin-1(Fer-1,ferroptosis inhibitor)on cell viability were assessed using high-content analy-sis.The levels of ferroptosis indicators,including prostaglandin-endoperoxide synthase 2(PTGS2)transcription,lipid peroxidation,reactive oxygen species(ROS),labile iron pool(LIP)and glutathione,were determined by RT-qPCR and flow cytometry.The mRNA expression levels of pivotal iron metabolism genes,ferroptosis-related ROS regulatory genes,and cholesterol synthesis-related genes were measured using RT-qPCR.Impact of cholesterol on the cell viability were as-sessed using high-content analysis.(3)Common differential gene analysis and gene ontology(GO)enrichment analysis were performed on published online data.RESULTS:(1)Treatment with RSL3 significantly reduced the protein level of SMARCA4(P＜0.05).(2)Knockdown of SMARCA4 resulted in ferroptosis.(3)Knockdown of SMARCA4 did not induce ferroptosis by modulating the LIP and the transcription levels of ROS-related genes.(4)Knockdown of SMARCA4 affected the pathways associated with the cell membrane,lipid raft,and cholesterol synthesis.(5)Addition of cholesterol to cell culture medium rescued the ferroptosis induced by SMARCA4 knockdown(P＜0.01).CONCLUSION:Treatment with RSL3 reduces the protein level of SMARCA4 in human fibrosarcoma HT1080 cells,and inhibition of cholesterol synthesis by SMARCA4 knockdown leads to the ferroptosis of HT1080 cells.

Objective:To investigate the application value of magnetic resonance (MR) diffusion tensor imaging (DTI) automatic fiber quantification (AFQ) in the diagnosis and prediction of Alzheimer's disease (AD).Methods:Clinical and MR data of 21 patients with AD (AD group) and 33 normal controls (NC group) were collected.AFQ software was used to analyze DTI data, track 20 white matter fiber bundles in the brain, and compare the differences of fractional anisotropy (FA) and mean diffusivity (MD) value of each bundle between groups.Each fiber bundle was divided into 100 equal parts along the direction of travel, and the FA or MD value of each part was taken as a characteristic.Screening the characteristics with statistic differences between groups for classification of AD and NC by support vector machine (SVM) with leave one method for cross validation.Classification effectiveness was evaluated using the receiver operating characteristic (ROC) curve.Results:Eleven (left/right anterior thalamic radiation (ATR), left/right corticospinal tract (CST), genu of corpus callosum (CC Genu), right inferior longitudinal fasciculus (ILF), right superior longitudinal fasciculus (SLF), left/right uncinated fasciculus (UF), and left/right arcuate fasciculus (AF)) of the 20 fiber bundles were successfully tracked in all subjects.Compared with NC group, the FA values of 2 fiber bundles (left/right UF) in AD group were significantly decreased( t=-2.532, -2.391, both P<0.05), and the MD values of 7 fiber bundles (left ATR, left/right CST, right ILF, left/right UF, and left AF) were significantly increased ( t=2.569, 2.411, 2.108, 2.357, 3.773, 3.796, 3.492, all P<0.05). Among the 2 200 characteristics of 11 fiber bundles, 412 classification characteristics with inter-group differences were selected.Among which, 78 FA characteristics were distributed in 7 fiber bundles (left ATR, left/right CST, CC Genu, right ILF, left/right UF), and 334 MD characteristics were distributed in 9 fiber tracts (left/right ATR, left/right CST, CC Genu, right ILF, left/right UF, and left AF). The accuracy of SVM classification was 85.19%, sensitivity was 80.95%, specificity was 87.88%, and area under ROC curve was 0.894 7. Conclusion:AFQ analysis based on DTI has a high application value in the diagnosis and prediction of AD.

Objective:To explore the normal ranges of perfusion parameters between cerebral hemisphere, cerebellar hemisphere and brain anatomical subregions (56 pairs) in different gender and age groups with multiple post labeling delay time (Multi-PLD) arterial spin labeling (ASL) imaging.Methods:From November 2020 to December 2020, 42 healthy adult volunteers (Male 25, Female 17) were recruited to perform 7 PLD ASL imaging, including 21 young adults (15 males and 6 females, aged 23—35 years) and 21 seniors (10 males and 11 females, aged 36—74 years). The data was processed offline by Cereflow software to obtain arterial arrival time (ATT) and corrected cerebral blood flow (CBF) and cerebral blood volume (CBV) perfusion parameters. SimpleITK standardization function was used to standardize the calculated perfusion image according to the anatomical automatic labeling (AAL) template. Therefore, CBF, ATT, CBV perfusion values of brain subregions were obtained. Paired samples t test, Wilcoxon rank sum test, independent samples t test and Mann-Whitney U test were used to compare the differences of perfusion parameters in the cerebral hemisphere, the cerebellar hemisphere, brain subregions depending on side, gender and age. Pearson correlation analysis was used to compare the correlations of perfusion parameters with age. Results:CBF in 62.5% (35/56) subregions and CBV in 44.6% (25/56) subregions were higher in right side than those in left side. ATT in most brain anatomical subregions (16/56) were higher in left side. The CBF [(35.30±8.31) vs. (34.34±7.53) ml·100g -1·min -1, P=0.021], CBV [(0.47±0.11) vs. (0.45±0.09) ml/100g, P<0.001], ATT [(1.30±0.10) vs. (1.24±0.11) s, P<0.001] in left cerebellar hemisphere were higher than that of right side. The CBF (28/56) of cerebral hemisphere, cerebellar hemisphere and brain subregions was higher in females than that in males, while ATT in 83.9% (47/56) subregions was lower than that in males (all P<0.05). CBV in female subjects was higher only in 5 brain regions (superior occipital gyrus, middle occipital gyrus, inferior occipital gyrus, superior parietal gyrus and cerebelum_7b) (all P<0.05). In young subjects, CBF in 44.6% (25/56) subregions and CBV in 33.9% (19/56) subregions were higher than those in the senior group (all P<0.05). The ATT in most subregions in young group were lower than those in senior group, but the difference was statistically significant only in rectus gyrus ( P=0.026) and paracentral lobule ( P=0.006). The CBF ( r=-0.430, P=0.005) and CBV ( r=-0.327, P=0.035) of cerebral hemisphere were negatively correlated with age. The CBF (24/25, r range:-0.497 —-0.343, all P<0.05) and CBV (16/19, r range:-0.474 —-0.322, all P<0.05) in most subregions were negatively correlated with age, while ATT was positively correlated (gyrus rectus: r=0.311, P=0.045; paracentral lobule: r=0.392, P=0.010). Conclusions:Multi-PLD ASL imaging could be applied for quantitative analysis of brain perfusion. The perfusion parameters of anatomical subregions are different depending on side, gender, and age.

Objective: To explore the risk factors of predicting white matter hyperintensities progression based on radiomics of MRI of whole-brain white matter. Methods: The imaging and clinical data of 152 patients with white matter hyperintensities admitted to Zhejiang People′s Hospital from March 2014 to October 2018 were retrospectively analyzed. The whole brain white matter on baseline T₁WI images of each patient were segmented by SPM12 software package, and images of white matter were imported into AK software for texture feature extraction and dimensionality reduction. At last, least absolute shrinkage and selection operator(LASSO) was used to calculate the score of radiomics signature of each patient. According to the improved Fazekas scale, patients with WMH progression were divided into three groups: any white matter hyperintensities (AWMH), periventricular white matter hyperintensities (PWMH) and deep white matter hyperintensities (DWMH). Statistical differences of clinical factors and radiomics signature between WMH progression subgroups and non-progression subgroups were compared with independent sample t test or Mann-Whitney U test, and Univariate logistic regression was used to select independent clinical risk factors and multivariate logistic regression along with imaging omics tags were used to construct predictive models, which was evaluated by ROC curve. And the correlation between the clinical indicators of independent risk factors and the texture feature of radiomics signature was analyzed. Results: The efficacy of the model for the detection for AWMH progression, PWMH progression and DWMH progression was 0.818,0.778 and 0.824, respectively. Age is an independent risk factor for AWMH progression and DWMH progression[OR(95%CI), 4.776(2.152-10.601) vs. 3.851(1.101-8.245); P<0.05]. BMI is an independent risk factor for DWMH[OR(95%CI), 3.004(1.204-7.370); P<0.05], and hyperlipidemia is an independent risk factor for AWMH and PWMH[OR(95%CI), 4.062(1.834-8.998) vs. 3.549(1.666-7.563); P<0.05]. In AWMH subgroup, Surface Area was negatively correlated with age and low density lipoprotein(LDL) (r=-0.401, -0.312), and Inverse Difference Moment_ALLDirection_offset 1_SD was negatively correlated with age(r=-0.412). In PWMH subgroup, Compactness 1 was negatively correlated with LDL(r=-0.198), and Inverse Difference Moment_angle 0_offset 7 was positively correlated with LDL(r=0.252). In DWMH subgroup, LongRunEmphasis_ALLDirection_offset 7 was negatively correlated with age(r=-0.322), and GLCMEntropy_angle0_offset 4 was negatively correlated with age(r=-0.278). GLCMEntropy_AllDirection_offset4 was negatively correlated with body mass index(r=-0.514). Conclusion Radiomics based on whole-brain white matter MR imaging can predict WMH progression and identify the risk factors in high-risk populations, thus providing early additional information to conventional magnetic resonance imaging to predict WMH progression.