ObjectiveTo investigate the diagnostic accuracy and grading capability of ultrasound-derived fat fraction （UDFF）， controlled attenuation parameter （CAP）， and hepatic/renal ratio （HRR） in assessing hepatic steatosis in metabolic associated fatty liver disease （MAFLD） with magnetic resonance imaging-proton density fat fraction （MRI-PDFF） as the gold standard. MethodsA total of 150 patients with MAFLD who attended The First Hospital of Hebei Medical University from January 2023 to December 2024 were enrolled， and 148 healthy volunteers were recruited. All subjects underwent MRI-PDFF， UDFF， CAP， and HRR examinations. Hepatic steatosis was graded based on MRI-PDFF （S0：148 cases； S1：92 cases； S2：21 cases； S3：37 cases）， and the MAFLD patients with different grades of hepatic steatosis were compared in terms of UDFF， CAP， HRR， and clinical features. A one-way analysis of variance was used for comparison of normally distributed continuous data between multiple groups and the Tukey HSD test was used for further comparision between two groups； the Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data between multiple groups， and the Mann-Whitney U test was used for further comparison between two groups； the chi-square test was used for comparison of categorical data between groups. The Spearman correlation analysis was used to investigate the correlation between UDFF， CAP， HRR， and MRI-PDFF in different grades of MAFLD； the receiver operating characteristic （ROC） curve was used to investigate the efficacy of UDFF， CAP， and HRR in the diagnosis of different degrees of hepatic steatosis in MAFLD； the Bland-Altman difference plot was used to analyze the consistency between UDFF and MRI-PDFF in different degrees of hepatic steatosis in MAFLD. ResultsUDFF measurement gradually increased with the increase in the grade of fatty liver （H=201.52，P0.001）. The Spearman correlation analysis showed that there was a strong correlation between any two indicators of UDFF， CAP， HRR， and MRI-PDFF in S1， S2， and S3 MAFLD （all P0.001）， with the strongest correlation between UDFF and MRI-PDFF （r_s1=0.884，r_s2=0.962，r_s3=0.929， all P0.001）. The ROC curve analysis showed that UDFF had a larger area under the ROC curve （AUC） than CAP and HRR in the graded diagnosis of S1 and S3 （all P0.05）， while in the diagnosis of S2 MAFLD， UDFF had a significantly larger AUC than HRR （P0.05） and a similar AUC to CAP （P0.05）. The Bland-Altman difference plot showed good consistency between UDFF and MRI-PDFF in different degrees of hepatic steatosis in MAFLD. ConclusionCompared with CAP and HRR， UDFF can accurately measure liver fat content and has good efficacy in identifying varying degrees of hepatic steatosis in MAFLD.

Objective To observe the value of machine learning(ML)models based on quantitative ultrasound(QUS)and clinical indexes for predicting metabolic associated fatty liver disease(MAFLD).Methods Totally 298 patients underwent abdominal MR and QUS examinations were retrospectively enrolled,including 150 cases with and 148 cases without MAFLD.The patients were divided into training set(including 107 cases of MAFLD and 101 cases of non-MAFLD)and test set(including 43 cases of MAFLD and 47 cases of non-MAFLD)at a ratio of 7∶3.Features were selected using least absolute shrinkage and selection operator(LASSO)regression and logistic regression(LR),based on which predictive models were constructed using 6 ML classifiers,including Gaussian naive Bayes(GNB),LR,random forest(RF),support vector machine(SVM),extreme gradient boosting(XGBoost)and K-nearest neighbor(KNN),respectively.Then the receiver operating characteristic curves were drawn,and the area under the curve(AUC)and the Brier score were calculated to evaluate the predictive efficacy of the models.Results The elevated age,glutamic-pyruvic transaminase(GPT),glutamic-oxaloacetic transaminase(GOT),uric acid(UA),low-density lipoprotein cholesterol(LDL-C),controlled attenuation parameter(CAP),ultrasound-derived fat fraction(UDFF)and shear wave velocity(SWV),as well as blurred liver contour were all independent indicators for higher likelihood of MAFLD(all P＜0.05).The AUC and Brier score of XGBoost model in training set was 0.991 and 0.006,in test set was 0.973 and 0.069,respectively,both higher than those of other models,and decision curve analysis(DCA)indicated that XGBoost model had high net benefit.Conclusion ML models based on QUS and clinical indexes,especially XGBoost model had high efficacy for predicting MAFLD.

Objective To observe the value of machine learning(ML)models based on quantitative ultrasound(QUS)and clinical indexes for predicting metabolic associated fatty liver disease(MAFLD).Methods Totally 298 patients underwent abdominal MR and QUS examinations were retrospectively enrolled,including 150 cases with and 148 cases without MAFLD.The patients were divided into training set(including 107 cases of MAFLD and 101 cases of non-MAFLD)and test set(including 43 cases of MAFLD and 47 cases of non-MAFLD)at a ratio of 7∶3.Features were selected using least absolute shrinkage and selection operator(LASSO)regression and logistic regression(LR),based on which predictive models were constructed using 6 ML classifiers,including Gaussian naive Bayes(GNB),LR,random forest(RF),support vector machine(SVM),extreme gradient boosting(XGBoost)and K-nearest neighbor(KNN),respectively.Then the receiver operating characteristic curves were drawn,and the area under the curve(AUC)and the Brier score were calculated to evaluate the predictive efficacy of the models.Results The elevated age,glutamic-pyruvic transaminase(GPT),glutamic-oxaloacetic transaminase(GOT),uric acid(UA),low-density lipoprotein cholesterol(LDL-C),controlled attenuation parameter(CAP),ultrasound-derived fat fraction(UDFF)and shear wave velocity(SWV),as well as blurred liver contour were all independent indicators for higher likelihood of MAFLD(all P＜0.05).The AUC and Brier score of XGBoost model in training set was 0.991 and 0.006,in test set was 0.973 and 0.069,respectively,both higher than those of other models,and decision curve analysis(DCA)indicated that XGBoost model had high net benefit.Conclusion ML models based on QUS and clinical indexes,especially XGBoost model had high efficacy for predicting MAFLD.

Objective To use helical tomotherapy ( HT ) for determining the difference between actual doses and planning doses to the target volume and organs at risk ( OARs ) in patients with nasopharyngeal carcinoma receiving radiotherapy, and to provide guidance for the clinical treatment. Methods Localization and delineation of the target volume and OARs were performed by computed tomography ( CT) in 21 patients with nasopharyngeal carcinoma receiving radical radiotherapy using HT. All patients underwent megavoltage CT ( MVCT) scan prior to treatment. The obtained MVCT images were used for dose reconstruction in the adaptive module of HT, in which the actual dose was obtained and the non?image?guided dose was simulated. Each single dose distribution and the corresponding CT image were sent to software MIM6. 0 for superimposition, and the overall dose was obtained. The initial plan, image?guided plan, and non?image?guided plan were named Plan?1, 2, and 3, respectively. The dose distribution in the target volume and OARs was compared between the three plans with t ? test or wilcoxon test . Results Compared with those in Plan?1, the D98 values for the planning gross tumor volume ( PGTV) and planning target volume ( PTV) in Plan?2 were significantly reduced by 1. 16% and 2. 3%, respectively ( P=0. 025;P=0. 043);the volumes of the left and right parotids in Plan?2 were significantly reduced by 46. 0% and 46. 5% on average, respectively ( P=0. 000);the distances between the midline and the center?of?mass for left and right parotids were significantly reduced by 6. 9% and 6. 5%, respectively ( P=0. 000);the V26 and Dmean for both parotid glands were significantly elevated by 32. 8% and 25. 2%, respectively ( P=0. 000) . Compared with those in Plan?1, the D98 values for PGTV, PTV?1, and PTV?2 in Plan?3 were significantly reduced by 2. 0%, 1. 9%, and 2. 4%, respectively ( P=0. 001;P=0. 007;P=0. 036);the V26 and Dmean for both parotid glands in Plan?3 were significantly elevated by 33. 6% and 25. 3%, respectively ( P=0. 000);Dmax to the spinal cord was significantly increased by 6. 9%( P=0. 005) . There was no significant difference in D2 to the spinal cord between Plan?2 and Plan?1( P=0. 392) . Conclusions The doses to both parotid glands increase during HT for nasopharyngeal carcinoma, which is closely associated with the shift of the parotid glands toward the midline. Image?guided radiotherapy does not enhance the dose to the target volume, but reduces the dose to the spinal cord.