Thyroid cancer is caused by multiple factors, including genetics, environment, metabolism, and the immune microenvironment, among which ionizing radiation exposure is an important risk factor for thyroid cancer. As one of the most sensitive target organs of ionizing radiation, the thyroid gland may have different risks of thyroid cancer caused by different types of ionizing radiation exposures, such as medical exposure, occupational exposure, and emergency exposure. The sensitivity of children and adolescents are higher than that of adults. The dose-response relationship still needs to be further explored. The molecular mechanism between ionizing radiation and the increased risk of thyroid cancer is complex, which may involve DNA damage and repair abnormalities, gene mutations, non-coding RNA regulation, DNA methylation, cell cycle regulation imbalance, and immune microenvironment changes. This article reviews the risk and molecular mechanisms associated with different types of ionizing radiation exposure in thyroid cancer, based on literature retrieved from CNKI and PubMed databases. It aims to provide a theoretical basis for the early monitoring, prevention, and intervention of thyroid cancer related to ionizing radiation exposure.

[This corrects the article DOI: 10.1016/j.jpha.2023.08.006.].

ObjectiveTo observe the therapeutic effect of Qiwei Baizhusan（QWBZS） on diabetic encephalopathy（DE） rat model， and to explore the possible mechanism of QWBZS in the treatment of DE based on phosphatidylinositol 3-kinase（PI3K）/protein kinase B（Akt）/glycogen synthase kinase-3β（GSK-3β） signaling pathway. MethodForty-eight SPF male Wistar rats were randomly divided into blank group（8 rats） and high-fat diet group（40 rats）. After 12 weeks of feeding， rats in the high-fat diet group were intraperitoneally injected with 35 mg·kg^-1 of 1% streptozotocin（STZ） for 2 consecutive days to construct a DE model， and rats in the blank group were injected with the same amount of sodium citrate buffer. After successful modeling， according to blood glucose and body weight， model rats were randomly divided into model group， low， medium and high dose groups of QWBZS（3.15， 6.3， 12.6 g·kg^-1）， combined western medicine group（metformin+rosiglitazone， 0.21 g·kg^-1）， with 6 rats in each group. The administration group was given the corresponding dose of drug by gavage， and the blank group and the model group were given an equal volume of 0.9% sodium chloride solution by gavage， 1 time/day for 6 weeks. Morris water maze was used to detect the spatial memory ability of DE rats. Fasting insulin （FINS） level was detected by enzyme-linked immunosorbent assay（ELISA） and insulin resistance index（HOMA-IR） was calculated. Hematoxylin-eosin（HE） staining was used to observe the morphological changes of hippocampus in rats， ELISA was used to detect the indexes of oxidative stress in hippocampal tissues， real-time fluorescence quantitative polymerase chain reaction（Real-time PCR） was used to detect mRNA expression levels of PI3K， Akt， nuclear transcription factor-κB（NF-κB）， tumor necrosis factor-α（TNF-α） and interleukin-1β（IL-1β） in hippocampus， and Western blot was used to detect the protein expression of PI3K， Akt， phosphorylated（p）-Akt， GSK-3β and p-GSK-3β in hippocampus of rats. ResultCompared with the blank group， FINS and HOMA-IR values of the model group were significantly increased（P<0.01）， the path of finding the original position of the platform was significantly increased， and the escape latency was significantly prolonged（P<0.01）， the morphology of neuronal cells in hippocampal tissues was disrupted， the levels of reactive oxygen species（ROS） and malondialdehyde（MDA） in hippocampus of rats were increased， and the activity of superoxide dismutase（SOD） was decreased（P<0.05， P<0.01）， mRNA expression levels of PI3K and Akt were decreased（P<0.01）， mRNA expression levels of NF-κB， TNF-α and IL-1β were increased（P<0.05， P<0.01）， the protein expression levels of PI3K， p-Akt and p-GSK-3β were significantly decreased， and the protein expression of GSK-3β was significantly increased（P<0.01）. Compared with the model group， the FINS and HOMA-IR values of the medium dose group of QWBZS and the combined western medicine group were significantly decreased（P<0.01）， the path of finding the original position of the platform and the escape latency were significantly shortened（P<0.01）， the hippocampal tissue structure of rats was gradually recovered， and the morphological damage of nerve cells was significantly improved， the contents of ROS and MDA in hippocampus of rats decreased and the level of SOD increased（P<0.01）， the mRNA expression levels of PI3K and Akt were increased（P<0.01）， and the mRNA expression levels of NF-κB， TNF-α and IL-1β were decreased （P<0.05， P<0.01）， the protein expression levels of PI3K， p-Akt and p-GSK-3β were significantly increased（P<0.01）， and the expression of GSK-3β was significantly decreased（P<0.01）. ConclusionQWBZS can alleviate insulin resistance in DE rats， it may repair hippocampal neuronal damage and improve learning and cognitive ability of DE rats by activating PI3K/Akt/GSK-3β signaling pathway.

Objective To observe the value of clinical and CT radiomics features for predicting microsatellite instability-high(MSI-H)status of gastric cancer.Methods Totally 150 gastric cancer patients including 30 cases of MSI-H positive and 120 cases of MSI-H negative were enrolled and divided into training set(n=105)or validation set(n=45)at the ratio of 7∶3.Based on abdominal vein phase enhanced CT images,lesions radiomics features were extracted and screened,and radiomics scores(Radscore)was calculated.Clinical data and Radscores were compared between MSI-H positive and negative patients in training set and validation set.Based on clinical factors and Radscores being significant different between MSI-H positive and negative ones,clinical model,CT radiomics model and clinical-CT radiomics combination model were constructed,and their predictive value for MSI-H status of gastric cancer were observed.Results Significant differences of tumor location and Radscore were found between MSI-H positive and negative patients in both training and validation sets(all P＜0.05).The area under the curve(AUC)of clinical model,CT radiomics model and combination model for evaluating MSI-H status of gastric cancer in training set was 0.760,0.799 and 0.864,respectively,of that in validation set was 0.735,0.812 and 0.849,respectively.AUC of clinical-CT radiomics combination model was greater than that of the other 2 single models(all P＜0.05).Conclusion Clinical-CT radiomics combination model based on tumor location and Radscore could effectively predict MSI-H status of gastric cancer.

Imaging omics can predict disease evolution, progression, and treatment response by extracting high-dimensional quantitative features from medical imaging. Positron emission tomography (PET) related imaging omics has been a research hotspot in recent years, and its application in urogenital system tumors is rapidly increasing. This article provides a review of the research progress on the application of PET related imaging omics in urogenital system tumors, and discusses the existing challenges and future prospects, in order to provide reference for further clinical application research.

Objective To observe the reproducibility of radiomics feature(RF)extracted from virtual monoenergetic image(VMI)of rabbit VX2 hepatoma models obtained with 3 different dual-energy CT(DECT)systems,and to explore relationship of reproducibility and diagnostic performance of RF.Methods Fifteen rabbits with VX2 hepatoma were randomly divided into 3 groups(each n=5).Contrast-enhanced abdominal CT scanning under volume CT dose index(CTDIvol)levels of 6,9 and 12 mGy were performed with dual-source DECT(dsDECT),rapid kV switching DECT(rsDECT)and dual-layer detector DECT(dlDECT),respectively.VMI were reconstructed at 10 keV increments from 40 to 140 keV.RF were extracted from VMI,the reproducibility was assessed using intra-class correlation coefficient(ICC),and those with ICC≥0.8 were considered as reproducible RF.The percentage of reproducible features(denoted by R)were compared among different scanner pairings and different CTDIvol levels.Within each CTDIvol group,the reconstruction energy levels yielding the maximum number(denoted by N)of common RF across different scanner pairings were identified.The receiver operating characteristic(ROC)curve was drawn,the area under the curve(AUC)was calculated,and the diagnostic efficacies of reproducible RF and other RF were compared under optimal reproducible conditions.Spearman correlation coefficient between ICC and the corresponding AUC of RF were calculated.Results RrsDECT-dsDECT(6.45％,95％CI[2.36％,8.87％])was higher than RdlDECT-dsDECT(0.72％,95％CI[0.15％,1.79％])and RrsDECT-dlDECT(1.43％,95％CI[0.60％,4.06％])(all adjusted P＜0.05),R9mGy(3.70％,95％CI[1.31％,5.73％])and R12mGy(2.63％,95％CI[0.60％,6.69％])were higher than R6mGy(1.31％,95％CI[0.12％,1.55％])(all adjusted P＜0.05).The optimal reproducible reconstruction energy levels of RF under CTDIvol of 6,9 and 12 mGy concentrated at 50-70 keV.AUC of reproducible RFs were higher than of other RF(all adjusted P＜0.05)and had certain correlation with the reproducibility(rs=0.102-0.516,P＜0.05).Conclusion The reproducibility of RF extracted from contrast-enhanced VMI CT images of rabbit VX2 hepatoma models associated with DECT scanner,CTDIvol level and reconstruction energy level.RF with higher reproducibility might have better diagnostic performance.

Objective To investigate the value of CT radiomics combined with CT and preoperative pathological features for predicting postoperative early recurrence(ER)of local advanced esophageal squamous cell carcinoma(LAESCC).Methods Data of 334 patients with LAESCC were retrospectively analyzed.The patients were divided into training set(n=234)and verification set(n=100)at the ratio of 7:3 and were followed up to observe ER(recurrence within 12 months after surgery)or not.Univariate and multivariate logistic regression were used to analyze clinical,CT and preoperative pathological features of LAESCC in patients with or without ER in training set.The independent risk factors of ER were screened,and a CT-preoperative pathology model was constructed.Based on venous phase CT in training set,the radiomics features of lesions were extracted and screened to establish radiomics model,and finally a combined model was established based on radiomics model and the independent risk factors.Receiver operating characteristic(ROC)curves were drawn,and the area under the curve(AUC)was calculated to evaluate the diagnostic efficacy of each model.Results Among 334 cases,168 were found with but 166 without ER.In training set,117 cases were found with while the rest 117 without ER,while in verification set,51 were found with but 49 without ER.The length of lesions,cT stage and cN stage shown on CT and tumor differentiation degree displayed with preoperative pathology were all independent risk factors for ER of LAESCC(all P＜0.05).The AUC of CT-preoperative pathology model in training set and validation set was 0.759 and 0.783,respectively.Ten best radiomics features of LAESCC were selected,and AUC of the established radiomics model in training set and validation set was 0.770 and 0.730,respectively.The AUC of combined model in training and validation set was 0.838 and 0.826,respectively.The AUC of CT radiomics combined with CT and preoperative pathological features in training set was higher than that of CT-preoperative pathologymodel and radiomics model(both P＜0.01).Conclusion CT radiomics combined with CT and preoperative pathological features could effectively predict postoperative ER of LAESCC.

Objective To observe the value of clinical data combined with CT radiomics features for evaluating programmed cell death-ligand 1(PD-L1)status in gastric cancer.Methods Totally 277 gastric cancer patients were retrospectively enrolled and randomly divided into training set(n=195)and validation set(n=82)at the ratio of 7:3.There were 88 cases in PD-L1 positive subgroup and 107 cases in negative subgroup of training set,while 37 and 45 cases of validation set,respectively.The clinical and conventional CT features were compared between subgroups in both sets,the independent influencing factors of PD-L1 status in gastric cancer were analyzed,and radiomic features were screened based on CT data.Then clinical model,radiomics model and clinical-radiomics model were established,and the efficacy of each model for evaluating PD-L1 status in gastric cancer was observed.Results In training set,Borrmann type,cN stage,cM stage,clinical stage,maximum diameter and thickness were significant difference between subgroups(all P＜0.05).Borrmann type,clinical stage and the thickness were all independent influencing factors of PD-L1 positivity(all P＜0.05).The area under the curve(AUC)of clinical model,radiomic model and clinical-radiomics model for evaluating PD-L1 status in gastric cancer in training set was 0.748,0.832 and 0.841,respectively,and was 0.657,0.801 and 0.789 in validation set,respectively.AUC of clinical model was lower than the other models(all P＜0.05).Conclusion Clinical data combined with CT radiomics features was helpful for evaluating PD-L1 status in gastric cancer.

Objective To observe the value of dual-energy CT(DECT)radiomics combined with clinical and CT features for predicting differentiation degree of gastric adenocarcinoma(GAC).Methods Totally 254 patients with GAC were prospectively analyzed and divided into high-grade group(low differentiation GAC,n=88)and low-grade group(middle-high differentiation GAC,n=166)according to pathological results.The patients were also divided into training set(n=203,including 70 high-grade and 133 low-grade GAC)and verification set(n=51,including 18 high-grade and 33 low-grade GAC)at the ratio of 8∶2.Radiomics features were extracted and screened based on venous phase single-level(40,70,100 and 140 keV)DECT,and a multi-energy radiomics model was constructed to predict GAC classification.Univariate analysis and multivariate logistic regression were used to analyze clinical and CT features as well as DECT parameters in training set to construct a clinic-CT model.Then a combined model was constructed through combining clinic-CT model with radiomics model.The predictive efficacy of the models were evaluated,and the calibration degree of the combined model was assessed.Results The area under the curve(AUC)of clinic-CT model,multi-energy radiomics model and combined model was 0.74,0.75 and 0.78 in training set,and 0.73,0.77 and 0.78 in verification set,respectively.Except for AUC of combined model was higher than that of clinic-CT model in training set(P＜0.05),no significant difference of AUC was found among models in training set nor verification set(all P＞0.05).The calibration degree of combined model was good in both training set and verification set(both P＞0.05).Conclusion DECT radiomics combined with clinical and CT features could effectively predict differentiation degree of GAC.

Objective To observe the value of spectral CT parameters for evaluating T staging of advanced gastric cancer(AGC).Methods Totally 155 AGC patients were collected and divided into T2 stage(n=40)and T3/4a stage(n=115)according to postoperative pathology.CT values,water concentration(WC)and iodine concentration(IC)of AGC lesions on 40-140 keV arteriovenous phase single energy level images were measured,and the standardized IC(nIC)and spectral curve slopes k1 and k2 were calculated.Clinical variables and spectral quantitative parameters were compared between groups,and receiver operating characteristic curve was plotted,the area under the curve(AUC)was calculated to evaluate the value of each parameter and model for identifying T2 and T3/4a stage AGC.Results Tumor thickness,proportion of low differentiation degree,CT100kev,CT140kev,and WC values in T3/4a group were all significantly higher than those in T2 group(all P＜0.05).CT140keV of AGC lesions on venous phase images presented the highest discrimination efficacy among single parameters,with AUC of 0.782.AUC of clinical-arterial phase-venous phase model was 0.848,higher than that of clinical model and arterial phase model alone(both P＜0.05)but not significantly different compared with AUC of venous phase model(P＞0.05).Conclusion Spectral CT quantitative parameters,especially venous phase parameters could be used to effectively identify T stage of AGC.Multi-parameter combined models had higher diagnostic value.