Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective To compare the ability of single-phase,dual-phase,and triphasic models in forecasting postoperative pancreatic fistula(POPF)after pancreaticoduodenectomy(PD)using radiomics based on triphasic enhanced CT.Methods A total of 181 patients who underwent multi-phase enhanced CT prior to PD were retrospectively selected,and the collection phase included non-contrast,arterial phase(AP),and equilibrium phase(EP).3D Slicer software was utilized to segment the region of interest(ROI)for the postoperative pancreatic remnant on each phase.Radiomics feature extraction was performed using R software,followed by feature selection through least absolute shrinkage and selection operator(LASSO)regression with five-fold cross-validation to prevent model overfitting.The effective features selected were combined in a weighted linear manner to obtain a Radiomics score(Radscore).The patients were divided into training set and test set in a 7︰3 ratio.Logistic regression was employed to construct seven POPF prediction models(three single-phase,three dual-phase,and one triphasic models)based on different phase combinations.The diagnostic performance of the models was evaluated using the area under the curve(AUC)of receiver operating characteristic(ROC)curve,accuracy(ACC),sensitivity(SEN),and specificity(SPE).The DeLong test was applied to compare the differences in AUC among different models.Results After LASSO regression,24 effective features associated with POPF were selected from different phases.In the test set,the triphasic model exhibited the highest AUC and ACC(AUC=0.76,ACC=0.808).The calibration curve demonstrated the strongest agreement between the estimated probabilities and observed probabilities for the triphasic model.The decision curve analysis(DCA)curve indicated that the triphasic model had the largest threshold range with a higher net benefit.Conclusion Compared with single-phase and dual-phase models,the triphasic model based on enhanced CT provides better prediction of POPF after PD,aiding clinical decision-making and improve prognosis.

Objective To compare the ability of single-phase,dual-phase,and triphasic models in forecasting postoperative pancreatic fistula(POPF)after pancreaticoduodenectomy(PD)using radiomics based on triphasic enhanced CT.Methods A total of 181 patients who underwent multi-phase enhanced CT prior to PD were retrospectively selected,and the collection phase included non-contrast,arterial phase(AP),and equilibrium phase(EP).3D Slicer software was utilized to segment the region of interest(ROI)for the postoperative pancreatic remnant on each phase.Radiomics feature extraction was performed using R software,followed by feature selection through least absolute shrinkage and selection operator(LASSO)regression with five-fold cross-validation to prevent model overfitting.The effective features selected were combined in a weighted linear manner to obtain a Radiomics score(Radscore).The patients were divided into training set and test set in a 7︰3 ratio.Logistic regression was employed to construct seven POPF prediction models(three single-phase,three dual-phase,and one triphasic models)based on different phase combinations.The diagnostic performance of the models was evaluated using the area under the curve(AUC)of receiver operating characteristic(ROC)curve,accuracy(ACC),sensitivity(SEN),and specificity(SPE).The DeLong test was applied to compare the differences in AUC among different models.Results After LASSO regression,24 effective features associated with POPF were selected from different phases.In the test set,the triphasic model exhibited the highest AUC and ACC(AUC=0.76,ACC=0.808).The calibration curve demonstrated the strongest agreement between the estimated probabilities and observed probabilities for the triphasic model.The decision curve analysis(DCA)curve indicated that the triphasic model had the largest threshold range with a higher net benefit.Conclusion Compared with single-phase and dual-phase models,the triphasic model based on enhanced CT provides better prediction of POPF after PD,aiding clinical decision-making and improve prognosis.

Objective:To investigate the hemodynamic characteristics of transverse sinus with sigmoid sinus wall dehiscence (SSWD) of pulsatile tinnitus (PT) based on 4D flow MRI.Methods:Retrospective analysis was performed on all patients admitted to Beijing Friendship Hospital, Capital Medical University from January 2019 to January 2021 for dehiscent sigmoid plate pulsatile tinnitus. A total of 26 patients (sides) who met the criteria and underwent 4D flow MRI were included. A total of 26 subjects (46 sides), matched 1∶1 according to gender and age, were included in the normal healthy control group. Nonparametric rank sum test, Student′s t test, and ANOVA were performed by SPSS 19.0 software. Binary Logistic regression was applied to the data with statistical significance. Results:There were more patients with dominant drainage on the affected side in PT group than in control group (73.1% vs. 42.3%). The incidence of transverse with a focal intraluminal filling defect and tapered stenosis was higher than that in control group (21.7% vs. 69.2%; 17.4% vs. 42.3%). Average through-plane velocity and maximum through-plane velocity in PT group were higher than those in control group [(33.75±13.88) cm/s vs. (15.84±7.21) cm/s; (93.19±33.55) cm/s vs. (40.40±14.40) cm/s]. The middle part and proximal end of Flow avg (ml/s) in PT group were larger than those in control group [4.69 (2.87; 5.62) ml/s vs. 2.76 (1.67; 4.99) ml/s; 3.41 (2.16; 5.47) ml/s vs. 2.67 (1.68; 4.41) ml/s]. In control group, the velocity of transverse sinus changed relatively gently, while in PT group, the velocity of proximal sinus increased significantly. Binary Logistic regression showed that SSWD PT was independently correlated with proximal maximum flow velocity [ OR=1.086(1.029-1.146), P=0.003]. Conclusion:4D flow MRI showed that the dominant drainage and higher velocity at the proximal end of the transverse sinus might be an important hemodynamic characteristics of dehiscent sigmoid plate pulsatile tinnitus.

Abdomen/diagnostic imaging* ; Artificial Intelligence ; Body Composition ; Magnetic Resonance Imaging ; Practice Guidelines as Topic

Humans ; Computed Tomography Angiography ; Deep Learning ; Coronary Angiography ; Coronary Artery Disease ; Tomography, X-Ray Computed ; Coronary Stenosis/diagnosis* ; Retrospective Studies ; Fractional Flow Reserve, Myocardial ; Predictive Value of Tests