Purpose To explore the relationship between semi-quantitative parameters maximum standard uptake value(SUVmax)and target-background ratio(TBR)of 18F-FDG PET/CT imaging and the activity of Takayasu arteritis.Materials and Methods A total of 110 patients with Takayasu arteritis from February 2016 to December 2022 in the First Affiliated Hospital of Zhengzhou University who underwent 18F-FDG PET/CT images were retrospectively reviewed.All Takayasu arteritis patients were divided into active(92 cases)and inactive groups(18 cases)according to Kerr score.The region of interest technique was used to measure the SUVmax of the arterial wall,and compares the SUVmax with the average SUV in the center of the inferior vena cava and the maximum SUV measured in the right lobe of the liver to obtain TBRblood pool and TBRliver.The diagnostic efficacy of SUVmax,TBRblood pool and TBRliver in Takayasu arteritis activity was compared using the receiver operating characteristic curve.The relationship between PET/CT parameters and Kerr score,erythrocyte sedimentation rate and C-reactive protein was evaluated.Results SUVmax,TBRblood pool and TBRliver in the active group were higher than those in the inactive group[3.70(3.03,5.18)vs.1.45(1.38,1.53),2.50(1.93,3.88)vs.0.91(0.79,1.16)and 1.37(1.00,1.96)vs.0.44(0.39,0.63);Z=5.510-5.900,all P<0.001],respectively.A SUVmax level of 2.65 was shown to be the best predictive cut-off value for Takayasu arteritis disease activity(sensitivity 83.7%,specificity 100%and area under the curve 0.91).A TBRblood pool level of 1.63 was shown to be the best predictive cut-off value for Takayasu arteritis disease activity(sensitivity 83.7%,specificity 94.4%and area under the curve 0.93).A TBRliver level of 0.81 was shown to be the best predictive cut-off value for Takayasu arteritis disease activity(sensitivity 87.0%,specificity 100%and area under the curve 0.94).SUVmax,TBRblood pool,TBRliver were all positively correlated with the Kerr score(r=0.88,0.89.0.90,all P<0.001),among which the correlation coefficient between TBRliver and the Kerr score was the highest.Conclusion SUVmax,TBRblood pool and TBRliver can evaluate disease activity in Takayasu arteritis patients,with TBRliver being the best.

Reduced or interrupted blood flow is an important pathological and physiological process in femoral head necrosis,so understanding the blood flow of the femoral head can help better understand the progression of femoral head necrosis.With the continuous development and improvement of imaging technology,the technical methods for detecting the blood flow of the femoral head are gradually being widely applied,allowing clinical physicians to better understand the blood flow situation of patients with femoral head necrosis.However,at present,the prognosis prediction of femoral head necrosis still mainly revolves around factors such as the area and angle of femoral head necrosis.Therefore,this article explores imaging techniques covering studies such as femoral head vascular imaging or blood flow perfusion parameters,summarizes their application research progress in femoral head necrosis blood flow assessment,and aims to provide more objective basis for exploring the prevention and prognosis of femoral head necrosis from the perspective of femoral head blood flow.

Objective To observe the value of three-dimensional ultrasound combined with microvascular flow imaging for prenatal diagnosis of fetal intracranial anomalies.Methods Totally 118 fetuses with intracranial anomalies diagnosed through cranial MRI/induced labor specimen dissection who underwent prenatal ultrasound examination were retrospectively enrolled.Two-dimensional,three-dimensional ultrasound and microvascular flow imaging manifestations of fetal intracranial anomalies were observed,and the accuracy of three-dimensional ultrasound combined with microvascular flow imaging for prenatal diagnosis of fetal intracranial anomalies was analyzed.Results The accuracy of three-dimensional ultrasound combined with microvascular flow imaging for prenatal diagnosis of fetal intracranial anomalies was 93.22％(110/118),of isolated and non-isolated intracranial anomalies was 97.47％(77/79)and 84.62％(33/39),respectively.Six fetuses were missed diagnosis of malformations of cortical development(1 fetus of tuberous sclerosis,4 of abnormal morphology of the sulci gyrus and 1 of schizencephaly)and 1 fetus of intracranial softening lesion,while posterior fossa arachnoid cyst in 1 fetus was misdiagnosed as mega cisterna magna.Conclusion The accuracy of three-dimensional ultrasound combined with microvascular flow imaging for prenatal diagnosis of fetal intracranial anomalies was relatively high.

Objective To observe the value of prenatal ultrasound for diagnosing fetal intracranial arachnoid cyst(IAC)and predicting outcomes.Methods A total of 240 fetuses with IAC confirmed by fetal brain MR examination or clinical follow-up were retrospectively enrolled,and the prenatal ultrasonic manifestations were observed.The outcomes of pregnancy were recorded,and the neurological development and treatment after birth were regularly followed up,then the fetuses were classified into good outcome or poor outcome groups.Univariate and binary logistic regression were used to analyze clinical data and prenatal ultrasonic findings,and the impact factors of outcomes of fetal IAC were screened.Results Among 240 fetuses,IAC located in the supratentorial area in 192(192/240,80.00％)and in the infratentorial area in 48(48/240,20.00％)fetuses.The size of IAC was 0.3-6.2 cm,with an average of(1.4±0.9)cm.Single lesion was found in 230 fetuses(230/240,95.83％),while multiple lesions were detected in 10 fetuses(10/240,4.17％).IAC presented as thin-walled cystic echoes with clear intracranial boundaries and good intracapsular sound transmission in all 240 fetuses,including 150(150/240,62.50％)with simple IAC and 90(90/240,37.50％)complicated with intracranial or other system malformations.Totally 189 fetuses were delivered successfully,while 51 underwent induction of labor.The newborns were followed up to 6-84 months.Among 240 fetuses with IAC,171(171/240,71.25％)had good outcome and 69(69/240,28.75％)had poor outcome.The size,number of lesion and whether combined with malformations or not on prenatal ultrasound and gender were all independent impact factors of outcomes of fetal IAC(OR=1.558,6.323,0.911,2.662,all P＜0.05).Conclusion Prenatal ultrasound could accurately diagnose and predict the outcomes of fetal IAC.

Fetal malformation of cortical development(MCD)is a group of structural neurological disorders caused by abnormalities in development of cortical layer during embryogenesis,characterized by significant heterogeneity and diversity,which may lead to adverse clinical outcomes such as epilepsy and intellectual disabilities.The progresses in prenatal evaluation on fetal MCD were reviewed in this article.

Objective To observe the correlations of metabolite levels in medial prefrontal cortex(mPFC)and cancer-related depression(CRD)in patients with non-small cell lung cancer(NSCLC).Methods Totally 38 NSCLC patients were prospectively enrolled and divided into CRD group(n=23)and non CRD group(n=15)based on Hamilton depression scale(HAMD-17).Meanwhile,22 healthy individuals were taken as control group.1 H-MR spectroscopy was performed using Meshcher-Garwood point resolved spectroscopy sequence,then metabolite levels of mPFC were measured,and their correlations with HAMD-17 score were analyzed.Results Significant differences of gamma-aminobutyric acid(GABA)+/Water and glutamate/glutamine complex(Glx)/Water in mPFC were found among 3 groups.GABA+/Water in mPFC of CRD group was significantly lower than that of the other 2 groups(both P＜0.05),and Glx/Water in mPFC of CRD group was significantly lower than that of control group(P=0.034).In NSCLC patients,GABA+/Water in mPFC was negatively correlated with HAMD-17 score(r=-0.491,P=0.002).Conclusion GABA+/Water in mPFC was negatively correlated with HAMD-17 score in NSCLC patients.

Objective To explore the correlations of spatial distribution frequency map of posterior reversible encephalopathy syndrome(PRES)and cerebral microvascular density map,cerebral blood flow(CBF)map,standard template of cerebral metabolic imaging and the spatial gene transcription map of human brain based on normative analysis strategy,and to analyze the pathophysiological mechanisms of PRES.Methods Cerebral MRI data of 184 patients with PRES were retrospectively analyzed.ROI of the lesions were delineated on T1WI,then registered to Montreal Neurological Institute(MNI)standard space.The spatial distribution frequency map of PRES lesions were obtained with superposition.Spatial correlation analysis were performed to observe correlations of spatial distribution frequency map of PRES and the cerebral microvascular density map,CBF map and standard template of cerebral metabolic imaging based on large sample.The potential related gene expressions were decoded based on gene expression data of Allen human brain atlas,and the correlations of spatial parts of PRES and those expressions were observed.Results No significant correlation was found between spatial distribution frequency map of PRES and cerebral microvascular density,CBF nor distribution of neurotransmitters(all P＞0.05).PLS1 weighted genes,VEGF-A gene,AQP-4 gene and RGS2 gene were all correlated with spatial distribution of PRES(r=-0.363-0.653,all P＜0.05),among which KCNAB3 gene had the highest weight(Z=17.288).Conclusion The spatial patterns of PRES risk or protective genes in brain regions were correlated with regional distribution of PRES lesions,which was consistent with arginine vasopressin(AVP)theory of the occurrence and development of PRES.

Objective To compare the efficacy of Qwen2.5(model A)and GPT-4o model(model B)for converting free-text reports of thyroid ultrasound into structured reports.Methods Preoperative thyroid ultrasound data of 100 patients who then underwent thyroidectomy(236 thyroid nodules)were retrospectively collected.Free-text reports were written by an attending ultrasound physician in accordance with guidelines of American College of Radiology thyroid imaging reporting and data system(ACR TI-RADS)and input into both model A and B for 3 times to generate structured thyroid ultrasound reports.The quality of these structured reports output by 2 models were compared,including structured writing,ACR TI-RADS categories and management recommendations,while the consistency of 3 times structured reports output by the models were analyzed.Results Among 300 structured reports output by models,the total satisfaction rate of structured writing was 94.00％(282/300)for model A and 94.67％(284/300)for model B,and no significant difference was found(x2=0.045,P=0.832).Among 236 thyroid nodules,there were 36,47,33,39 and 81 in ACR TI-RADS categories 1,2,3,4 and 5,respectively.The total accuracy model A and B for 3 times categories of thyroid nodules was 88.28％(625/708)and 89.27％(632/708),respectively,with no significant difference(x2=0.582,P=0.505).Moderate consistencies of results of 3 times structured writing(ICC=0.531,0.673)and nodules categories(ICC=0.714,0.747)were noticed between 2 models.The coincidence rate of model A and B for providing management recommendations for thyroid nodules was 74.86％(530/708)and 67.51％(478/708),respectively,the former was higher than the latter(x2=4.567,P=0.033),and the consistencies of 3 times management recommendations provided by 2 models were both good(ICC=0.836,0.769).Conclusion The efficacy of structured writing and ACR TI-RADS categories of Qwen2.5 and GPT-4o models for converting thyroid ultrasound free-text reports into structured reports was comparable,while the former was more effective for providing management recommendations.

Objective To observe the value of ultrasound radiomics based on convolutional neural network(CNN)for predicting effect of neoadjuvant chemotherapy(NAC)for breast cancer.Methods Totally 164 women with breast cancer were retrospectively enrolled and divided into effective group(n=68)and ineffective group(n=96)according to the treatment response,also randomly divided into training set(n=131)and validation set(n=33)at the ratio of 8∶2.Based on ultrasound before NAC,radiomics features of breast cancer were extracted and screened with CNN,radiomics models were constructed with logistic regression(LR),support vector machine(SVM),K-nearest neighbor(KNN),random forest(RF)and multilayer perceptron(MLP),respectively.The best radiomics model was selected,deep learning score(DL-Score)was calculated,and the nomogram was drawn combined with clinical features.Results Among 5 radiomics models,MLP model had the best comprehensive efficacy for predicting effect of NAC for breast cancer,and its sensitivity,specificity and area under the curve(AUC)in training set was 77.78％,92.21％and 0.929,respectively,which in validation set was 78.57％,84.21％and 0.921,respectively.The estrogen or progesterone receptor,human epidermal growth factor receptor 2 and DL-Score were all independent predictors of NAC effect for breast cancer(all P＜0.05).The sensitivity,specificity and AUC of nomogram drawn based on the above independent predictors was 83.30％,92.21％and 0.953 in training set,85.71％,94.74％and 0.955 in validation set,respectively.AUC of the nomogram was slightly higher than that of MLP model,but no significant difference was found(both P＞0.05).The integrated discrimination improvement index showed that adding clinical features(i.e.the above-mentioned immunohistochemically indicators)could improve the predictive performance of radiomics models(P＜0.001).Conclusion Ultrasound radiomics based on CNN could be used to predict effect of NAC for breast cancer.Combining with immunohistochemically indicators might improve their efficacy.

Objective To observe the value of digital breast tomosynthesis(DBT)-based radiomics nomogram for predicting Ki-67 expression levels in breast invasive ductal carcinoma(BIDC).Methods Data of 374 cases of BIDC were retrospectively analyzed and divided into high-expression group(n=224)and low-expression group(n=150)according to expression of Ki-67 as well as training set(n=271,162 cases in high-expression group and 109 cases in low-expression group)and test set(n=103,62 cases in high-expression group and 41 cases in low-expression group)at the ratio of 7∶3.Clinical characteristics and lesion's image manifestations were compared between groups,and radiomic features were extracted and filtered.Then imaging radiomics models were constructed with 8 classifiers,respectively,and the optimal classifier was selected.A nomogram model was subsequently developed through integrating image features and radiomics scores.Receiver operating characteristic curves were drawn,and the area under the curves(AUC)were calculated to evaluate the performance of the above models.Results Significant differences of the maximum diameter and spiculated margin of the lesions were found between groups(both P＜0.05),and AUC of multi-layer perceptron(MLP)image model constructed based on these indexes for predicting BIDC expression level of Ki-67 was 0.654 in training set and 0.715 in test set,of MLP radiomics model constructed based on 8 radiomics features was 0.802 in training set and 0.806 in test set,while of the nomogram model constructed based on image features and radiomics scores was 0.802 in training set and 0.806 in test set,respectively.Conclusion DBT-based radiomics nomogram could be used to effectively predict Ki-67 expression levels in BIDC.