Objective:To evaluate the diagnostic value of native T1 mapping in differentiating Oxford classification (MEST-C) scores in patients with IgA nephropathy.Methods:In this prospective study, patients who underwent both T1 mapping and renal biopsy at the First Medical Center of the Chinese PLA General Hospital between April 2023 and October 2024 were consecutively enrolled. Two radiologists, blinded to clinical and pathological information, measured renal T1 mapping parameters, including cortical T1 (cT1), medullary T1 (mT1), the corticomedullary difference (ΔT1), and the corticomedullary ratio (T1 ratio). Clinical and renal biopsy data based on the Oxford classification from patients with IgA nephropathy were collected. The Oxford classification includes five indicators: Mesangial hypercellularity (M), Endocapillary hypercellularity (E), Segmental glomerulosclerosis or adhesion (S), Tubular atrophy/interstitial fibrosis (T), and Cellular or fibrocellular crescents (C). Spearman correlation analysis was applied to evaluate the associations between MEST-C scores and T1 parameters. The diagnostic performance of T1 parameters for discriminating among scores of the Oxford classification was analyzed using the receiver operating characteristic (ROC) curve.Results:A total of 124 patients with IgA nephropathy were included in this study [66 males, 58 females; age 19-70 years, 39 (30, 51) years]. Except for the E indicator, M, S, T, and C were significantly correlated with renal T1 values ( ρ=0.177-0.414, all P<0.05). cT1 showed the best diagnostic efficacy for the S score, with an area under the curve (AUC) of 0.798, a sensitivity of 68.7%, and a specificity of 88.0%. The best T1 parameter for differentiating the T score was the T1 ratio, with an AUC of 0.687, a sensitivity of 57.9%, and a specificity of 79.1%. Conclusion:Native T1 mapping can be used for the non-invasive assessment of the S and T scores in the Oxford classification of patients with IgA nephropathy.

Objective:To evaluate the efficacy of preoperative prediction of regional lymph node (RLN) metastasis in renal cell carcinoma (RCC) using a machine learning model based on habitat imaging radiomics from renal MRI.Methods:This cross-sectional study retrospectively analyzed 220 patients with RCC who underwent nephrectomy and RLN dissection at four medical centers of Chinese PLA General Hospital from January 2010 to August 2023. The cohort included 65 patients with RLN metastasis and 155 without. A stratified random sampling method was used to divide 175 patients from the first medical center into a training set ( n=140) and an internal test set ( n=35) in an 8∶2 ratio, while 45 patients from the third, fourth, and fifth medical centers constituted the external test set. The primary RCC lesions were categorized into 15 habitat subregions based on corticomedullary-phase enhancement and T 2WI signal intensity on MRI, and the volume fractions of different subregions were analyzed. In the training cohort, radiomics features derived from the habitat subregions were used to construct a radiomics model employing various machine learning algorithms, including extremely random trees (ET), gradient boosting decision trees (GBDT), random forest (RF), and support vector machine (SVM). The optimal model was selected and combined with RLN short-axis diameter to develop a combined model. The efficacy of each model in predicting RLN metastasis was evaluated using the receiver operating characteristic (ROC) curve. Results:The volume fraction of hyper-enhanced hyper-intense regions in the non-metastatic group was significantly higher than that in the metastatic group (0.05±0.09 vs. 0.02±0.03; t=3.00, P=0.003). Among the machine learning models constructed using 15 optimal habitat radiomics features, the SVM model demonstrated the best performance, with area under the ROC curve (AUC) values of 0.85 (95% CI 0.72-0.98) in the internal test set and 0.82 (95% CI 0.67-0.98) in the external test set, surpassing those of the ET, GBDT, and RF models. The combined model, integrating the SVM model with RLN short-axis diameter, achieved AUC values of 0.94 (95% CI 0.85-1.00) in the internal test set and 0.89 (95% CI 0.78-1.00) in the external test set, with RLN short-axis diameter contributing AUC values of 0.81 (95% CI 0.66-0.96) and 0.81 (95% CI 0.68-0.94), respectively. The diagnostic sensitivity of the combined model was 91.7% in the internal test set and 85.7% in the external test set, with specificities of 78.3% and 67.7%, respectively. Conclusion:The combined model based on MRI habitat imaging radiomics and RLN short-axis diameter demonstrates excellent preoperative assessment capability for RLN metastasis in RCC.

Objective:To evaluate the diagnostic value of native T1 mapping in differentiating Oxford classification (MEST-C) scores in patients with IgA nephropathy.Methods:In this prospective study, patients who underwent both T1 mapping and renal biopsy at the First Medical Center of the Chinese PLA General Hospital between April 2023 and October 2024 were consecutively enrolled. Two radiologists, blinded to clinical and pathological information, measured renal T1 mapping parameters, including cortical T1 (cT1), medullary T1 (mT1), the corticomedullary difference (ΔT1), and the corticomedullary ratio (T1 ratio). Clinical and renal biopsy data based on the Oxford classification from patients with IgA nephropathy were collected. The Oxford classification includes five indicators: Mesangial hypercellularity (M), Endocapillary hypercellularity (E), Segmental glomerulosclerosis or adhesion (S), Tubular atrophy/interstitial fibrosis (T), and Cellular or fibrocellular crescents (C). Spearman correlation analysis was applied to evaluate the associations between MEST-C scores and T1 parameters. The diagnostic performance of T1 parameters for discriminating among scores of the Oxford classification was analyzed using the receiver operating characteristic (ROC) curve.Results:A total of 124 patients with IgA nephropathy were included in this study [66 males, 58 females; age 19-70 years, 39 (30, 51) years]. Except for the E indicator, M, S, T, and C were significantly correlated with renal T1 values ( ρ=0.177-0.414, all P<0.05). cT1 showed the best diagnostic efficacy for the S score, with an area under the curve (AUC) of 0.798, a sensitivity of 68.7%, and a specificity of 88.0%. The best T1 parameter for differentiating the T score was the T1 ratio, with an AUC of 0.687, a sensitivity of 57.9%, and a specificity of 79.1%. Conclusion:Native T1 mapping can be used for the non-invasive assessment of the S and T scores in the Oxford classification of patients with IgA nephropathy.

Objective:To evaluate the efficacy of preoperative prediction of regional lymph node (RLN) metastasis in renal cell carcinoma (RCC) using a machine learning model based on habitat imaging radiomics from renal MRI.Methods:This cross-sectional study retrospectively analyzed 220 patients with RCC who underwent nephrectomy and RLN dissection at four medical centers of Chinese PLA General Hospital from January 2010 to August 2023. The cohort included 65 patients with RLN metastasis and 155 without. A stratified random sampling method was used to divide 175 patients from the first medical center into a training set ( n=140) and an internal test set ( n=35) in an 8∶2 ratio, while 45 patients from the third, fourth, and fifth medical centers constituted the external test set. The primary RCC lesions were categorized into 15 habitat subregions based on corticomedullary-phase enhancement and T 2WI signal intensity on MRI, and the volume fractions of different subregions were analyzed. In the training cohort, radiomics features derived from the habitat subregions were used to construct a radiomics model employing various machine learning algorithms, including extremely random trees (ET), gradient boosting decision trees (GBDT), random forest (RF), and support vector machine (SVM). The optimal model was selected and combined with RLN short-axis diameter to develop a combined model. The efficacy of each model in predicting RLN metastasis was evaluated using the receiver operating characteristic (ROC) curve. Results:The volume fraction of hyper-enhanced hyper-intense regions in the non-metastatic group was significantly higher than that in the metastatic group (0.05±0.09 vs. 0.02±0.03; t=3.00, P=0.003). Among the machine learning models constructed using 15 optimal habitat radiomics features, the SVM model demonstrated the best performance, with area under the ROC curve (AUC) values of 0.85 (95% CI 0.72-0.98) in the internal test set and 0.82 (95% CI 0.67-0.98) in the external test set, surpassing those of the ET, GBDT, and RF models. The combined model, integrating the SVM model with RLN short-axis diameter, achieved AUC values of 0.94 (95% CI 0.85-1.00) in the internal test set and 0.89 (95% CI 0.78-1.00) in the external test set, with RLN short-axis diameter contributing AUC values of 0.81 (95% CI 0.66-0.96) and 0.81 (95% CI 0.68-0.94), respectively. The diagnostic sensitivity of the combined model was 91.7% in the internal test set and 85.7% in the external test set, with specificities of 78.3% and 67.7%, respectively. Conclusion:The combined model based on MRI habitat imaging radiomics and RLN short-axis diameter demonstrates excellent preoperative assessment capability for RLN metastasis in RCC.

Objective:To investigate the impact of the interval period between biopsy and MR examination on tumor detection and extraprostatic extension (EPE) assessment for prostate cancer (PCa) using multi-parametric MRI (mpMRI).Methods:The study was cross-sectional and retrospectively included 130 patients with PCa who underwent RP and preoperative systematic biopsies followed by mpMRI between January 2021 and December 2022 in the First Medical Center of Chinese PLA General Hospital. Patients were divided into 3 groups according to interval following biopsy (group A,<3 weeks, 31 cases; group B, 3-6 weeks, 67 cases; group C,>6 weeks, 32 cases). The percentages of hemorrhage volume in the total prostate were drawn on T 1WI and calculated. The junior, senior and expert radiologists independently localized the index lesions and calculated the accuracy for tumor detection, in addition to assessing the probabilities of EPE according to EPE grade. The correlation between the hemorrhage extent and interval was analyzed using the Spearman correlation coefficient. The accuracy for tumor detection was compared using χ2 test among groups. The diagnostic performance of the radiologists for EPE prediction was assessed using the receiver operating characteristic curve, and the differences between the corresponding area under the curve (AUC) were compared using the DeLong test. Results:The percentage of hemorrhage was correlated with the interval between biopsy and MR examination ( r=-0.325, P<0.001). The detection accuracy of junior radiologist was 83.9% (26/31), 76.1% (51/67), and 78.1% (25/32) in group A, B and C, respectively; no differences were observed in the detection accuracy among three groups ( χ2=0.76, P=0.685). The detection accuracy of senior radiologist was 83.9% (26/31), 80.6% (54/67), and 71.9% (23/32) in 3 groups with no differences ( χ2=1.53, P=0.464). The detection accuracy of expert radiologist was 80.6% (25/31), 77.6% (52/67), and 93.8% (30/32) with no differences ( χ2=3.95, P=0.139). The AUC (95% CI) for predicting EPE were 0.830 (0.652-0.940), 0.704 (0.580-0.809), 0.800 (0.621-0.920) in the group A, B and C for junior radiologist; 0.876 (0.708-0.966), 0.768 (0.659-0.863), 0.896 (0.736-0.975) for senior radiologist; and 0.866 (0.695-0.961), 0.813 (0.699-0.895), 0.852 (0.682-0.952) for expert radiologist, respectively. No differences were observed among the subgroups in each radiologist ( P>0.05). Conclusion:The interval period does not significantly affect the detection accuracy and EPE assessment of PCa using mpMRI. There is probably no necessity for prolonged intervals following systematic biopsy to preserve the clarity of MRI interpretation for PCa.

Objective:To explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters in different regions of the kidney in distinguishing IgA nephropathy (IgAN) patients from healthy volunteers.Methods:This study was a cross-sectional study. Eighty-four patients diagnosed with IgAN (IgAN group) who underwent renal biopsy (lower pole of the left kidney) and were pathologically confirmed at the First Medical Center of PLA General Hospital from February 2022 to September 2023 and thirty-four healthy volunteers (control group) were included prospectively. The regions of interest were outlined in the right renal cortex, medulla, and parenchyma for all subjects, and the apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D *), and perfusion fraction (f) were measured in the corresponding regions. The differences in IVIM-DWI parameters between the IgAN group and the control group were compared using the student′s t-test or the Mann-Whitney U test. Receiver operating characteristic curve analysis was performed on the parameters with statistically significant differences, and the area under the curve (AUC) was calculated. Results:There were statistically significant differences in renal cortical ADC, renal parenchymal ADC, renal cortical D, renal parenchymal D, and renal medullary f values between the IgAN group and the control group ( Z=-3.03, -2.21, -2.62, -2.03, -2.03; P=0.002, 0.027, 0.009, 0.043, 0.042). The AUCs (95% CI) for diagnosing IgAN using renal cortical ADC, renal parenchymal ADC, renal cortical D, renal parenchymal D, and renal medullary f values were 0.679 (0.586-0.762), 0.630 (0.537-0.717), 0.654 (0.535-0.774), 0.619 (0.497-0.742), and 0.620 (0.495-0.745), respectively. There were no statistically significant differences in renal medullary ADC, D, renal cortex, medulla and parenchyma D *, renal cortical and renal parenchymal f values between the two groups ( P>0.05). Conclusion:The quantitative parameters of renal IVIM-DWI are influenced by different measurement regions, among which the ADC, D of renal cortex and parenchyma, and f of renal medulla can be used for the initial diagnosis of IgAN.

Objective To examine the compliance of and factors affecting target attainment of serum trough concentration of norvancomycin in ICU patients,and the effects of different trough concentrations on clinical efficacy and renal impairment.Methods Adult patients admitted to the Department of Critical Care Medicine of Huangshan People's Hospital and receiving intravenous infusion of norvancomycin from January 2020 to December 2022 were included.The dosing regimens and steady-state trough concentrations of norvancomycin were analyzed.The clinical efficacy and renal impairment were compared between different trough concentration levels.The compliance of trough concentration in critically ill patients with different renal functions was examined.Logistic regression analysis was performed to profile the factors possibly affecting the trough concentration of norvancomycin.Results A total of 97 patients were included.The target serum trough concentration(10-20 mg/L)was reached in only 33.0％(32/97)of the critically ill patients.The serum trough concentration was below the target in 51.5％(50/97)of the patients,above the target in 15.5％of the patients.The clinical cure rate and incidence of renal impairment were significantly different among the three groups of patients with different trough concentrations(P＜0.05).The compliance with target serum trough concentration varied with different renal function tests(P＜0.05).Augmented renal clearance and normal renal function were associated with trough concentrations lower than the target.As renal dysfunction got worse,serum trough concentration was more probably higher than the target(P＜0.05).Univariate analysis showed that daily dose,age,gender,height,weight,body mass index(BMI),APACHE Ⅱ score,sequential organ failure assessment(SOFA)score,blood creatinine,urea nitrogen,procalcitonin,concomitant septic shock,and use of norepinephrine were significantly correlated with trough concentrations of norvancomycin(P＜0.05).Multivariate logistic regression analysis indicated that age,SOFA score,blood urea nitrogen,gender,and norepinephrine use were independent factors affecting the serum trough concentration of norvancomycin(P＜0.05).Conclusions The serum trough concentration of norvancomycin varied with renal function states in ICU patients.It is difficult to achieve the steady-state target trough concentration(10-20 mg/L).The clinical cure rate is lower when the trough concentration is lower than the target.As the trough concentration increases,the incidence of renal impairment increases.Age,SOFA score,urea nitrogen,gender,and norepinephrine use are independent factors affecting the serum trough concentrations of norvancomycin.

ObjectiveTo clone coumarate-3-hydroxylase gene （C3H） from Angelica sinensis， and analyze the correlation between its bioinformatics， expression patterns and content of ferulic acid， and to explore the functions of ASC3H. MethodReal-time polymerase chain reaction （Real-time PCR） was used to clone the full-length cDNA of ASC3H based on the transcriptome dataset of A. sinensis， and the bioinformatics analysis of the gene sequence was carried out. Real-time PCR and high performance liquid chromatography （HPLC） were used to determine relative expression of ASC3H and content of ferulic acid in different root tissues of A. sinensis （periderm， cortex and stele）. ResultThe open reading frame （ORF） of ASC3H （GenBank accession number： MN2550298） was 1 530 bp， encoding 509 amino acids， with a theoretical molecular weight of 57.86 kDa and an isoelectric point of 8.36. It was a hydrophilic protein that was located in the chloroplast with multiple phosphorylation sites and a transmembrane region， and contained a conserved domain CGYDWPKGYGPIINVW_P450 （383-399 aa） in cytochrome P450. Multiple amino acid sequence alignment analysis showed that ASC3H had high similarity with C3H from other plants， especially Ammi majus in Umbelliferae. The Real-time PCR revealed that ASC3H had different expressions in periderm， cortex and stele tissues of A. sinensis roots. It was found from HPLC that the cortex tissues had the highest content of ferulic acid， and the stele tissues had the lowest. ConclusionASC3H was successfully cloned from A. sinensis， and its sequence characteristics were understood more clearly， suggesting that ASC3H might be involved in the ferulic acid biosynthesis pathway of A. sinensis. This paper provided a basis for further studying the functions of the gene and exploring the biosynthesis and regulation mechanism of ferulic acid in A. sinensis， while laying the foundation for the genetic improvement of A. sinensis．

Objective:To investigate the intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) in the differential diagnosis of diabetic nephropathy (DN) and non-diabetic renal disease (NDRD) among patients with type 2 diabetes mellitus (T2DM).Methods:A diagnostic test. In this prospective study, patients with T2DM who underwent both IVIM-DWI and renal biopsy at the First Medical Center of Chinese PLA General Hospital between October 2017 and September 2021 were consecutively enrolled. IVIM-DWI parameters including perfusion fraction (f), pure diffusion coefficient (D), and pseudo-diffusion coefficient (D*) were measured in the renal cortex, medulla, and parenchyma. Patients were divided into the DN group and NDRD group based on the renal biopsy results. IVIM-DWI parameters, clinical information, and diabetes-related biochemical indicators between the two groups were compared using Student′s t-test or Mann-Whitney U test. The correlation of IVIM-DWI parameters with diabetic nephropathy histological scores were analyzed using Spearman′s correlation analyzes. The diagnostic efficiency of IVIM-DWI parameters for distinguishing between DN and NDRD were assessed using the receiver operating characteristic (ROC) curves. Results:A total of 27 DN patients and 23 NDRD patients were included in this study. The DN group comprised 19 male and 8 female patients, with an average age of 52±9 years. The NDRD group comprised 16 male and 7 female patients, with an average age of 49±10 years. The DN group had a higher D* value in the renal cortex and a lower f value in the renal medulla than the NDRD group (9.84×10 -3 mm 2/s vs. 7.35×10 -3 mm 2/s, Z=-3.65; 41.01% vs. 46.74%, Z=-2.29; all P<0.05). The renal medulla D* value was negatively correlated with DN grades, interstitial lesion score, and interstitial fibrosis and tubular atrophy (IFTA) score ( r=-0.571, -0.409, -0.409; all P<0.05) while the renal cortex f value was positively correlated with vascular sclerosis score ( r=0.413, P=0.032). The renal cortex D* value had the highest area under the curve (AUC) for discriminating between the DN and NDRD groups (AUC=0.802, sensitivity 91.3%, specificity 55.6%). Conclusion:IVIM-derived renal cortex D* value can be used non-invasively to differentiate DN from NDRD in patients with T2DM that can potentially facilitate individualized treatment planning for diabetic patients.

Objective:To explore the value of quantitative parameters of enhanced MRI in predicting the establishment of inferior vena cava collateral circulation in patients with renal cell carcinoma and inferior vena cava tumor thrombus.Methods:Sixty-seven patients with renal cell carcinoma and inferior vena cava tumor thrombus who underwent radical resection and inferior vena cava venography in First Medical Center, PLA General Hospital from May 2006 to January 2021 were included retrospectively. According to the results of inferior vena cava venography, the patients were divided into two groups: the well-established collateral circulation group ( n=41) and the poor-established collateral circulation group ( n=26). Quantitative parameters were measured on preoperative enhanced MRI images, including tumor size, the maximum diameter of bilateral lumbar veins, the length of tumor thrombus, and the long and short diameters of tumor thrombus. Student′s t test or Mann-Whitney U test was used for comparison between the two groups. The independent risk factors related to the establishment of collateral circulation were obtained by binary logistic regression analysis and the model was established. The receiver operating characteristic curve was employed to evaluate MRI quantitative parameters and the logistic model, and the area under the curve (AUC) was compared by the DeLong test. Results:Between the well-established collateral circulation group and the poor-established collateral circulation group, the maximum diameter of the right lumbar vein, the maximum diameter of the left lumbar vein, the length of the tumor thrombus, the long diameter of the tumor thrombus, and the short diameter of the tumor thrombus were different significantly ( P<0.05). There was no significant difference in the tumor size between the two groups ( t=0.30, P=0.766). The AUC of the maximum diameters of the right lumbar veins and left lumbar veins, length of tumor thrombus, long and short diameters of tumor thrombus in predicting the collateral circulation were 0.917 (95%CI 0.824-0.971), 0.869 (95%CI 0.764-0.939), 0.756 (95%CI 0.636-0.853), 0.886 (95%CI 0.785-0.951), and 0.906 (95%CI 0.809-0.963). The AUC of the maximum diameter of the right lumbar vein and the short diameter of the tumor thrombus were larger than those of the length of the tumor thrombus, and the differences were statistically significant ( Z=2.25, 2.04, P=0.025, 0.041), but the AUC between other parameters had no significant difference ( P>0.05). The maximum diameter of the right lumbar vein (OR 24.210, 95%CI 2.845-205.998), the maximum diameter of the left lumbar vein (OR 20.973, 95%CI 2.359-186.490), and the length of the tumor thrombus (OR 23.006, 95%CI 2.952-179.309) were independent risk factors for predicting the establishment of inferior vena cava collateral circulation. The AUC of logistic model was 0.969 (95%CI 0.931-1.000). Conclusion:Quantitative parameters of tumor thrombus and lumbar vein based on enhanced MRI have a good ability in predicting the establishment of inferior vena cava collateral circulation in patients with renal cell carcinoma and inferior vena cava tumor thrombus. The maximum diameter of bilateral lumbar veins and the length of the tumor thrombus were independent risk factors for inferior vena cava collateral circulation.