Objective:To investigate the value of MULTI-parametric MR imaging with flexible design (MTP) combined with microview diffusion weighted imaging (DWI) in predicting pituitary tumor invasion of cavernous sinus.Methods:This was a cross-sectional study. The clinicopathological and imaging data of 59 patients with suspected pituitary tumor who were admitted to the First Affiliated Hospital of Dalian Medical University from December 2021 to August 2024 were prospectively analyzed. According to Knosp classification, patients with pituitary tumor were divided into non-invasive group (28 cases) and invasive group (31 cases). All patients underwent MTP and microview DWI sequence scanning, and the corresponding parameter values [T 1, R 2*, T 2* and apparent diffusion coefficient (ADC)] were measured on the MTP quantitative map and ADC map at the maximum diameter level of the pituitary tumor. Independent sample t test and Mann-Whitney U test were used to compare the clinical data, quantitative parameter values and proliferation index (Ki-67) between the non-invasive group and the invasive group. Quantitative parameter values with statistically significant differences were jointly included in logistic regression to construct the model. Receiver characteristic curve and area under the curve (AUC) were used to analyze single variables and logistic model in predicting the value invasion of pituitary tumor cavernous sinus invasion. Spearman correlation was used to analyze the correlation between the quantitative values and Ki-67 level. Results:There was no significant difference in age and gender between the non-invasive group and the invasive group ( P>0.05). T 1 and T 2* values in invasion group were higher than those in non-invasion group ( Z=4.42, P<0.001; Z=3.43, P<0.001), R 2* values and ADC values in the invasion group were lower than those in the non-invasion group, and the difference was statistically significant (t=4.07, P<0.001; Z=-3.07, P=0.002). The AUC values of T 1, R 2*, T 2*, ADC, logistic model 1(T 1+R 2*+ADC) and logistic model 2(T 1+T 2*+ADC) for predicting pituitary tumor cavernous sinus invasion were 0.835, 0.767, 0.760, 0.733, 0.926 and 0.925, respectively. Correlation analysis showed that the value of pituitary tumor T 1 was positively correlated with Ki-67 ( r=0.431, P=0.002). Conclusion:Quantitative parameters of MTP sequence and microview DWI sequence can quantitatively evaluate pituitary tumor invasion of cavernous sinus, and the combination of the two sequences can significantly improve the prediction efficiency.

Objective To observe the value of pool sign on T2WI for differentiating solitary brain metastasis(SBM)from solitary mass type high grade glioma(HGG).Methods Totally 120 patients with SBM(SBM group)and 184 patients with solitary mass type HGG(HGG group)confirmed by postoperative pathology or clinical follow-up were retrospectively enrolled.The incidence of pool sign were compared between groups,and the efficacy of pool sign for differentiating SBM from solitary mass type HGG was analyzed.Results Pool sign was noticed in 37 cases(37/120,30.83％)in SBM group and 9 cases(9/184,4.89％)in HGG group,the incidence of pool sign in SBM group was higher than that in HGG group(x2=38.063,P＜0.001).The sensitivity,specificity,positive predictive value and negative predictive value of pool sign for differentiating SBM and solitary mass type HGG was 30.83％(37/120),95.11％(175/184),80.43％(37/46)and 67.83％(175/258),respectively.In SBM group,the incidence of pool sign in cases with primary tumor of adenocarcinoma,squamous cell carcinoma and neuroendocrine carcinoma was 40.79％(31/76),16.67％(3/18)and 12.50％(3/24),respectively,with significant difference(x2=8.911,P=0.012),while compared pairwisely showed significant difference between SBM of adenocarcinoma and neuroendocrine carcinoma(x2=6.505,P=0.011).Conclusion The pool sign on T2WI was helpful for differentiating SBM,especially SBM of adenocarcinoma from solitary mass type HGG.

Objective To investigate the value of synthetic MRI(syMRI)for evaluating structural changes of brain nuclei and white matter in patients with Parkinson disease(PD).Methods Forty-five PD patients(PD group)and 35 healthy controls(HC group)were prospectively enrolled.Head scanning with strategically acquired gradient echo sequence was performed,then syMRI was obtained with post-processing.The values of T1,proton density(PrD),R2* and magnetic sensitivity values(MSV)of nuclei and white matter were measured based on syMRI and compared between groups.The correlations of syMRI quantitative parameters of nuclei and white matter being significantly different between groups with neurological function scores of subject were analyzed,and a combined model was established using multivariate logistic regression analysis.Receiver operating characteristic(ROC)curve was drawn,the efficacy of single syMRI quantitative parameter and combined model for diagnosing PD was evaluated.Results Compared with HC group,T1 and PrD values of bilateral caudate nuclei decreased,while MSV of bilateral substatia nigra and right red nucleus increased(all FDR correction P＜0.05),while T1 and PrD values of bilateral splenium of corpus callosum,PrD values of left posterior limbs of the internal capsule(PLIC),R2* values of bilateral PLIC and right genu of the corpus callosum decreased in PD group(all FDR correction P＜0.05).syMRI quantitative parameters of the above brain regions were correlated with scores of Montreal cognitive assessment and Hamilton anxiety scale(r=-0.390-0.416,all P＜0.01).The area under the curve of single syMRI quantitative parameter for diagnosing PD was 0.664-0.788,lower than that of combined model(0.905,Z=2.653-4.096,all P＜0.05).Conclusion SyMRI could be used to quantitatively evaluate structural changes of brain nuclei and white matter in PD patients.

Objective To observe the value of pool sign on T2WI for differentiating solitary brain metastasis(SBM)from solitary mass type high grade glioma(HGG).Methods Totally 120 patients with SBM(SBM group)and 184 patients with solitary mass type HGG(HGG group)confirmed by postoperative pathology or clinical follow-up were retrospectively enrolled.The incidence of pool sign were compared between groups,and the efficacy of pool sign for differentiating SBM from solitary mass type HGG was analyzed.Results Pool sign was noticed in 37 cases(37/120,30.83％)in SBM group and 9 cases(9/184,4.89％)in HGG group,the incidence of pool sign in SBM group was higher than that in HGG group(x2=38.063,P＜0.001).The sensitivity,specificity,positive predictive value and negative predictive value of pool sign for differentiating SBM and solitary mass type HGG was 30.83％(37/120),95.11％(175/184),80.43％(37/46)and 67.83％(175/258),respectively.In SBM group,the incidence of pool sign in cases with primary tumor of adenocarcinoma,squamous cell carcinoma and neuroendocrine carcinoma was 40.79％(31/76),16.67％(3/18)and 12.50％(3/24),respectively,with significant difference(x2=8.911,P=0.012),while compared pairwisely showed significant difference between SBM of adenocarcinoma and neuroendocrine carcinoma(x2=6.505,P=0.011).Conclusion The pool sign on T2WI was helpful for differentiating SBM,especially SBM of adenocarcinoma from solitary mass type HGG.

BACKGROUND:Knee osteoarthritis is a common degenerative disease that significantly impacts patients'quality of life and increases the societal healthcare burden.Early and accurate diagnosis of knee osteoarthritis is crucial for the treatment and prognosis of patients.Traditional diagnostic methods are not only subjective and time-consuming but also do not guarantee consistently high accuracy.OBJECTIVE:To develop an automatic diagnostic method for knee osteoarthritis based on deep learning,utilizing deep learning networks to improve diagnostic accuracy and efficiency.METHODS:A new network model,YOLOV8-ViT,was proposed by replacing the backbone network of YOLOv8n with the Efficient-ViT network and incorporating attention mechanisms for the automatic identification and classification of X-ray images of knee osteoarthritis.The experimental dataset included 5 078 X-ray images of patients with knee osteoarthritis obtained from the Third Affiliated Hospital of Guangzhou University of Chinese Medicine.Three imaging physicians annotated the sites of knee osteoarthritis and classified them according to the Kellgren-Lawrence grading standard using Labelme software,and the results were combined.The evaluation indicators used in this study included Precision,F1 score,mean average precision(mAP),Recall,val/box_loss,val/cls_loss,and val/dfl_loss.RESULTS AND CONCLUSION:The experimental results showed that the YOLOV8-ViT model outperformed the YOLOv5n,YOLOv8n,and YOLOv9n models in terms of precision,mAP50,mAP50-95,F1 score,and Recall,while lowering val/box_loss,val/cls_loss,and val/dfl_loss by 0.496,0.45,and 0.523;1.037,0.305,and 0.728;and 0.267,0.654,and 0.854,respectively.These experimental data validate that this model has high detection accuracy.

Objective To investigate the value of synthetic MRI(syMRI)for evaluating structural changes of brain nuclei and white matter in patients with Parkinson disease(PD).Methods Forty-five PD patients(PD group)and 35 healthy controls(HC group)were prospectively enrolled.Head scanning with strategically acquired gradient echo sequence was performed,then syMRI was obtained with post-processing.The values of T1,proton density(PrD),R2* and magnetic sensitivity values(MSV)of nuclei and white matter were measured based on syMRI and compared between groups.The correlations of syMRI quantitative parameters of nuclei and white matter being significantly different between groups with neurological function scores of subject were analyzed,and a combined model was established using multivariate logistic regression analysis.Receiver operating characteristic(ROC)curve was drawn,the efficacy of single syMRI quantitative parameter and combined model for diagnosing PD was evaluated.Results Compared with HC group,T1 and PrD values of bilateral caudate nuclei decreased,while MSV of bilateral substatia nigra and right red nucleus increased(all FDR correction P＜0.05),while T1 and PrD values of bilateral splenium of corpus callosum,PrD values of left posterior limbs of the internal capsule(PLIC),R2* values of bilateral PLIC and right genu of the corpus callosum decreased in PD group(all FDR correction P＜0.05).syMRI quantitative parameters of the above brain regions were correlated with scores of Montreal cognitive assessment and Hamilton anxiety scale(r=-0.390-0.416,all P＜0.01).The area under the curve of single syMRI quantitative parameter for diagnosing PD was 0.664-0.788,lower than that of combined model(0.905,Z=2.653-4.096,all P＜0.05).Conclusion SyMRI could be used to quantitatively evaluate structural changes of brain nuclei and white matter in PD patients.

BACKGROUND:Knee osteoarthritis is a common degenerative disease that significantly impacts patients'quality of life and increases the societal healthcare burden.Early and accurate diagnosis of knee osteoarthritis is crucial for the treatment and prognosis of patients.Traditional diagnostic methods are not only subjective and time-consuming but also do not guarantee consistently high accuracy.OBJECTIVE:To develop an automatic diagnostic method for knee osteoarthritis based on deep learning,utilizing deep learning networks to improve diagnostic accuracy and efficiency.METHODS:A new network model,YOLOV8-ViT,was proposed by replacing the backbone network of YOLOv8n with the Efficient-ViT network and incorporating attention mechanisms for the automatic identification and classification of X-ray images of knee osteoarthritis.The experimental dataset included 5 078 X-ray images of patients with knee osteoarthritis obtained from the Third Affiliated Hospital of Guangzhou University of Chinese Medicine.Three imaging physicians annotated the sites of knee osteoarthritis and classified them according to the Kellgren-Lawrence grading standard using Labelme software,and the results were combined.The evaluation indicators used in this study included Precision,F1 score,mean average precision(mAP),Recall,val/box_loss,val/cls_loss,and val/dfl_loss.RESULTS AND CONCLUSION:The experimental results showed that the YOLOV8-ViT model outperformed the YOLOv5n,YOLOv8n,and YOLOv9n models in terms of precision,mAP50,mAP50-95,F1 score,and Recall,while lowering val/box_loss,val/cls_loss,and val/dfl_loss by 0.496,0.45,and 0.523;1.037,0.305,and 0.728;and 0.267,0.654,and 0.854,respectively.These experimental data validate that this model has high detection accuracy.

Objective:To investigate the value of MULTI-parametric MR imaging with flexible design (MTP) combined with microview diffusion weighted imaging (DWI) in predicting pituitary tumor invasion of cavernous sinus.Methods:This was a cross-sectional study. The clinicopathological and imaging data of 59 patients with suspected pituitary tumor who were admitted to the First Affiliated Hospital of Dalian Medical University from December 2021 to August 2024 were prospectively analyzed. According to Knosp classification, patients with pituitary tumor were divided into non-invasive group (28 cases) and invasive group (31 cases). All patients underwent MTP and microview DWI sequence scanning, and the corresponding parameter values [T 1, R 2*, T 2* and apparent diffusion coefficient (ADC)] were measured on the MTP quantitative map and ADC map at the maximum diameter level of the pituitary tumor. Independent sample t test and Mann-Whitney U test were used to compare the clinical data, quantitative parameter values and proliferation index (Ki-67) between the non-invasive group and the invasive group. Quantitative parameter values with statistically significant differences were jointly included in logistic regression to construct the model. Receiver characteristic curve and area under the curve (AUC) were used to analyze single variables and logistic model in predicting the value invasion of pituitary tumor cavernous sinus invasion. Spearman correlation was used to analyze the correlation between the quantitative values and Ki-67 level. Results:There was no significant difference in age and gender between the non-invasive group and the invasive group ( P>0.05). T 1 and T 2* values in invasion group were higher than those in non-invasion group ( Z=4.42, P<0.001; Z=3.43, P<0.001), R 2* values and ADC values in the invasion group were lower than those in the non-invasion group, and the difference was statistically significant (t=4.07, P<0.001; Z=-3.07, P=0.002). The AUC values of T 1, R 2*, T 2*, ADC, logistic model 1(T 1+R 2*+ADC) and logistic model 2(T 1+T 2*+ADC) for predicting pituitary tumor cavernous sinus invasion were 0.835, 0.767, 0.760, 0.733, 0.926 and 0.925, respectively. Correlation analysis showed that the value of pituitary tumor T 1 was positively correlated with Ki-67 ( r=0.431, P=0.002). Conclusion:Quantitative parameters of MTP sequence and microview DWI sequence can quantitatively evaluate pituitary tumor invasion of cavernous sinus, and the combination of the two sequences can significantly improve the prediction efficiency.

Objective To observe the influence of different acceleration factors(AF)on compressed sensing susceptibility weighted imaging(CS-SWI)for cerebral medullary veins of healthy people,and to screen the best AF.Methods Forty healthy volunteers were prospectively enrolled.Axial brain SWI images were obtained with CS technique under different AF(AF0,CS2,CS4,CS6,CS8 and CS10),and the phase value(PV)and standard deviation(SD)of bilateral septal vein(SV),internal cerebral vein(ICV),thalamus vein(TV),basal vein(BV)and dentate nucleus vein(DNV)were measured.Taken PV and SD of parietal white matter as controls,the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)of venous images were calculated.Then the original images were reconstructed with minimum intensity projection,and the subjective quality scoring of reconstructed images were performed using a 5-point scale.SNR,CNR,PV and quality score were compared among images under different AF,and the best AF,i.e.with the best performances for displaying and quantitatively analyzing cerebral medullary veins in healthy people was obtained.Results Compared with those acquired with AF0,SNR and CNR of all cerebral medullary veins acquired with CS6,CS8 and CS10 were significantly different(all adjusted P＜0.05).Meanwhile,significant differences of PV in bilateral SV and right TV were found among CS6,CS8 and CS10,also in bilateral ICV,left TV and bilateral BV between CS8 and CS10(all adjusted P＜0.05).Conclusion Excessive AF might decrease image quality of CS-SWI for cerebral medullary veins.CS4 was the best AF for displaying and quantitatively analyzing cerebral medullary veins in healthy people.

Objective To explore the impact of δ-catenin expression level on resting-state brain function in breast cancer patients.Methods Totally 104 female breast cancer patients were prospectively enrolled and divided into δ-catenin high expression group(DH group,n=51)and δ-catenin low expression group(DL group,n=53)according to δ-catenin expression level,while 36 female healthy volunteers were selected as controls(control group).Neuropsychological tests were performed,and resting-state functional MRI(rs-fMRI)were acquired,then parameters of brain function,including amplitude of low frequency fluctuation(ALFF),fractional ALFF(fALFF),regional homogeneity(ReHo)and functional connectivity strength(FCS)of brain regions with differences among groups were obtained.Spearman correlation analysis was used to evaluate the correlations of function parameters of brain regions with general data and neuropsychological test scores.Results Significant differences of fALFF,ReHo and FCS values were found among 3 groups(familywise error rate[FWE]correction,all P＜0.05).fALFF value of left inferior temporal gyrus in DH and DL groups were both higher than that in control group(FWE correction,both P＜0.05),ReHo value of right inferior temporal gyrus in DH group,as well as of right middle temporal gyrus,right inferior temporal gyrus and right fusiform gyrus in DL group were all lower than that in control group(FWE correction,all P＜0.05),FSC value of left lenticular nucleus,left putamen,left fusiform gyrus,left calcarine fissure surrounding cortex and left inferior temporal gyrus in DH group were all higher than that in DL group(FWE correction,all P＜0.05),FSC value of left lenticular nucleus,left putamen,left fusiform gyrus and left calcarine fissure surrounding cortex in DH group were all higher than that in control group(FWE correction,all P＜0.05),while FSC value of left lingual gyrus,left lenticular nucleus and left putamen were both higher than that in control group(FWE correction,both P＜0.05).In brain regions with different fMRI indexes between DH group and DL group,FSC values were lowly positively correlated with CogPCA results(r=0.313,P＜0.05).In brain regions with different fMRI indexes between DH group and control group,fALFF value were lowly positively correlated with trail making test A(TMT A)and trail making test B(TMT B)(r=0.301,0.310,both P＜0.05),ReHo values were lowly negatively correlated with TMT B(r=-0.307,P＜0.05),FCS values were weakly/lowly positively correlated with TMT A and TMT B(r=0.282,0.309,both P＜0.05)and lowly negatively correlated with results of digital symbol substitution test(DSST)(r=-0.363,P＜0.05).In brain regions with different fMRI indexes between DL group and control group,fALFF values were weakly/lowly negatively correlated with results of mini mental state examination(MMSE),Montreal cognitive assessment(MoCA),auditory verbal learning test(AVLT)short-term memory and DSST(r=-0.399,-0.362,-0.344,-0.288,all P＜0.05).Conclusion The expression level of δ-catenin had certain impact on brain function of breast cancer patients,resulted in asymmetry changes of brain network in bilateral hemispheres,as well as memory loss through affecting left inferior temporal gyrus,left lenticular nucleus,left putamen and left fusiform gyrus.