Multiparametric MRI analysis for the evaluation of renal function in patients with hyperuricemia: a preliminary study.

BACKGROUND: To investigate the renal dysfunction in patients with hyperuricemia by employing a multiparametric MRI protocol, consisting of quantitative water molecule diffusion, microstructure, microscopic perfusion, and oxygenation measurements in kidneys. MATERIALS AND METHODS: A total of 48 patients with hyperuricemia (HU) and 22 age-matched healthy control subjects (HC) were enrolled in the study. For each participant, three different functional magnetic resonance imaging (fMRI) sequences were acquired and analyzed, including intravoxel incoherent motion imaging (IVIM), diffusion tensor imaging (DTI), and blood-oxygen-level-dependent MRI (BOLD). Thereafter, an independent two-sample t-test was applied to discover the significant differences of MRI indices between the hyperuricemia (HU) and HC groups, and the specific potential biomarkers between two subgroups of HU group (asymptomatic hyperuricemia group (AH) and gouty arthritis group (GA)). Further, multivariate logistic regression analyses were performed to classify the AH from the GA group using the MRI indices with significant between-group differences. The receiver operating characteristic (ROC) curve was plotted, and the area under the ROC curve (AUC) was calculated to assess the performance of each MR index for differentiation between the AH and GA groups. RESULTS: Ten parametric values of the HU group were significantly lower than those of the HC group among the 14 fMRI parameters (P < 0.05). The cortical D, D*, and f values and medullary D and R2*values had significant differences between the AH and GA groups (P < 0.05). Combining the cortical D and f values and medullary R2* value gave the best diagnostic efficacy, yielding an AUC, sensitivity, and specificity of 0.967 ± 0.022, 91.67%, and 95.83%, respectively. CONCLUSIONS: A multiparametric MR analysis plays an important role in the evaluation of renal dysfunction in hyperuricemia from multiple perspectives. It could be a promising method for noninvasive detection and identification of the early-stage renal damage induced by hyperuricemia.

Non-invasive investigation of early kidney damage in streptozotocin-induced diabetic rats by intravoxel incoherent motion diffusion-weighted (IVIM) MRI.

BACKGROUND: The current study investigated the performance of intravoxel incoherent motion diffusion (IVIM) technology in monitoring early renal injury in streptozotocin rats. METHODS: Forty-eight Sprague-Dawley (SD) rats were divided into a control group and a diabetic mellitus (DM) group. Six rats in each group were randomly selected for MR scans at four different time points (0, 4, 8, and 12 weeks). The IVIM-derived parameters (D, D*, f and ADC values) of the renal cortex (CO), outer and inner stripe of the outer medulla (OS, IS), and internal medulla (IM) were acquired. Changes in each IVIM-derived parameter over time were analyzed, and differences between the two groups at each point were assessed. The associations between the IVIM parameters and IV collagen expression, urine volume (UV), blood urea nitrogen (BUN), and serum creatinine (Scr) were investigated. RESULTS: The D and D* values of CO and the ADC values of CO, OS, IS and IM displayed significantly different trends between the two groups over time (P<0.05). In addition, significant correlations were discovered between the D* value of CO and UV and BUN (r=0.527, P=0.033; r=0.617, P=0.005), between the ADC value of IM and BUN (r=0.557, P=0.019) and between the f value of IM and BUN (r=0.527, P=0.033). No correlation was found between IVIM parameters and IV collagen expression and Scr. CONCLUSIONS: IVIM is a potential sensitive and noninvasive technology for the simultaneous assessment of early renal cortical and medullary injuries induced by diabetes.

Development and Validation of a Machine Learning Approach for Automated Severity Assessment of COVID-19 Based on Clinical and Imaging Data: Retrospective Study.

BACKGROUND: COVID-19 has overwhelmed health systems worldwide. It is important to identify severe cases as early as possible, such that resources can be mobilized and treatment can be escalated. OBJECTIVE: This study aims to develop a machine learning approach for automated severity assessment of COVID-19 based on clinical and imaging data. METHODS: Clinical data-including demographics, signs, symptoms, comorbidities, and blood test results-and chest computed tomography scans of 346 patients from 2 hospitals in the Hubei Province, China, were used to develop machine learning models for automated severity assessment in diagnosed COVID-19 cases. We compared the predictive power of the clinical and imaging data from multiple machine learning models and further explored the use of four oversampling methods to address the imbalanced classification issue. Features with the highest predictive power were identified using the Shapley Additive Explanations framework. RESULTS: Imaging features had the strongest impact on the model output, while a combination of clinical and imaging features yielded the best performance overall. The identified predictive features were consistent with those reported previously. Although oversampling yielded mixed results, it achieved the best model performance in our study. Logistic regression models differentiating between mild and severe cases achieved the best performance for clinical features (area under the curve [AUC] 0.848; sensitivity 0.455; specificity 0.906), imaging features (AUC 0.926; sensitivity 0.818; specificity 0.901), and a combination of clinical and imaging features (AUC 0.950; sensitivity 0.764; specificity 0.919). The synthetic minority oversampling method further improved the performance of the model using combined features (AUC 0.960; sensitivity 0.845; specificity 0.929). CONCLUSIONS: Clinical and imaging features can be used for automated severity assessment of COVID-19 and can potentially help triage patients with COVID-19 and prioritize care delivery to those at a higher risk of severe disease.

Extramedullary plasmacytoma involving rectum: A case report and literature review.

Extramedullary plasmacytoma (EMP) of the gastrointestinal tract is an extreme rarity. Clinical manifestations of EMPs are varied, depending on the position and progress of tumor. Here we report a case of an EMP involving rectum in an 80-year-old, male patient with a change of bowel habit. Computed tomography scanning confirmed a circumscribed, iso-attenuating mass with the obvious heterogeneous enhancement. Patient received the surgical resection by laparoscope and the plasmacytoma was finally confirmed by the pathology. Furthermore, we made a literature review about the EMP of gastrointestinal tract to get the further study. Finally, we found out there is no specificity in imaging examination. Diagnosis of EMP still depends on the histopathology.

Combined application of DTI and BOLD-MRI in the assessment of renal injury with hyperuricemia.

OBJECTIVE: To explore the value of combined diffusion tensor imaging (DTI) and blood oxygenation level-dependent magnetic resonance imaging (BOLD-MRI) in detecting early renal alterations in patients with hyperuricemia. MATERIALS AND METHODS: Seventy-one individuals were enrolled in this study and divided into three groups according to their serum uric acid (SUA) level and clinical symptoms: healthy controls (HC, n = 23), asymptomatic hyperuricemia (AH, n = 22) and gouty arthritis (GA, n = 26). All patients underwent both DTI and BOLD-MRI examination. Renal cortical and medullary ADC, FA and R2* values were calculated, respectively, and compared among the three groups. Correlations between ADC, FA and R2* with estimated glomerular filtration rate (eGFR) and SUA in hyperuricemia were evaluated, respectively. RESULT: In the renal cortex, the ADC, FA and R2* values of the AH and GA groups were significantly lower than those of the HC groups (p < 0.05). In the renal medulla, the ADC and FA values in AH and GA patients were significantly lower than those in healthy controls (p < 0.05). The R2* value of the GA group significantly decreased, compared to that of the AH and HC groups (p < 0.05). SUA was negatively correlated with cortical ADC, FA and R2* values (p < 0.05) as well as with medullary ADC and FA values. No significant correlation was discovered between the eGFR and ADC, FA and R2* values. CONCLUSION: The combined evaluation of DTI and BOLD might provide a sensitive and non-invasive approach for detection of renal microstructural alterations and oxygen metabolism abnormality in hyperuricemia.

Epithelioid hemangioendothelioma of spine: A case report with review of literatures.

Primary epithelioid hemangioendothelioma of the spine is the extremely rare malignant vascular neoplasm with an unpredictable outcome. A case of epithelioid hemangioendothelioma with multiple lytic lesions of thoracolumbar spine and other bones in a 29-year-old male patient is reported. A review of the published data regarding this rare neoplasm is also presented. The features of epithelioid hemangioendothelioma include the occurrence in the young male patient, multiple osteolytic lesions with thin sclerotic rim and hypermetabolic activities. However, its imaging features are not specific. Positron emission tomography/computed tomography is essential for identification of the lesions and subsequent follow-up for treatment.

Intravoxel incoherent motion imaging of the kidney: The application in patients with hyperuricemia.

BACKGROUND: Hyperuricemia is an independent risk factor for onset and progression of kidney disease. However, there remains a lack of a reliable and noninvasive biomarker to identify and monitor the changes of renal function in patients with hyperuricemia. PURPOSE: To assess the utility of intravoxel incoherent motion (IVIM) parameters in identifying the early changes of renal function in patients with hyperuricemia. STUDY TYPE: Retrospective case-control study. POPULATION: Eighty-four male participants, including asymptomatic hyperuricemia (AH, 27 cases), gouty arthritis (GA, 31 cases), and 26 age-matched healthy controls. FIELD STRENGTH/SEQUENCE: 3.0T; intravoxel incoherent motion (IVIM). ASSESSMENT: Differences in the IVIM parameters among the three groups were assessed. Pure molecular diffusion (D value); perfusion-related diffusion (D* value); pseudodiffusion fraction (f value); apparent diffusion coefficient (ADC value); estimated glomerular filtration rate (eGFR). Also, they were correlated with eGFR. STATISTICAL TESTS: Bonferroni test, Tamhane's T2 method, and Pearson correlation analysis. RESULTS: The D values in renal cortex and medulla significantly decreased from the control, AH to GA groups (P < 0.05). The GA patients had a significantly lower cortical f value than the controls and AH patients (P < 0.05). The medullary f values in the AH and GA patients were significantly lower than that in the controls (P < 0.05). Also, the cortical and medullary ADC values had similar results across the three groups (P < 0.05), except for the comparison between the AH and GA groups (P = 0.668, P = 0.111, respectively). No significant correlation was found between any IVIM parameters with eGFR. DATA CONCLUSION: IVIM imaging may be helpful for detecting the early changes of renal function induced by hyperuricemia. The D value could be the most sensitive IVIM-derived parameter in the assessment of renal function in patients with hyperuricemia in this study. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2020;51:833-840.