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  • 1
    Online Resource
    Online Resource
    Impact Journals, LLC ; 2018
    In:  Oncotarget Vol. 0, No. 0 ( 2018-01-05)
    In: Oncotarget, Impact Journals, LLC, Vol. 0, No. 0 ( 2018-01-05)
    Type of Medium: Online Resource
    ISSN: 1949-2553
    Language: English
    Publisher: Impact Journals, LLC
    Publication Date: 2018
    detail.hit.zdb_id: 2560162-3
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  • 2
    In: Journal of Magnetic Resonance Imaging, Wiley, Vol. 52, No. 4 ( 2020-10), p. 1239-1248
    Abstract: Biopsy Gleason score (GS) is crucial for prostate cancer (PCa) treatment decision‐making. Upgrading in GS from biopsy to radical prostatectomy (RP) puts a proportion of patients at risk of undertreatment. Purpose To develop and validate a radiomics model based on multiparametric magnetic resonance imaging (mp‐MRI) to predict PCa upgrading. Study Type Retrospective, radiomics. Population A total of 166 RP‐confirmed PCa patients (training cohort, n = 116; validation cohort, n = 50) were included. Field Strength/Sequence 3.0T/T 2 ‐weighted (T 2 W), apparent diffusion coefficient (ADC), and dynamic contrast enhancement (DCE) sequences. Assessment PI‐RADSv2 score for each tumor was recorded. Radiomic features were extracted from T 2 W, ADC, and DCE sequences and Mutual Information Maximization criterion was used to identify the optimal features on each sequence. Multivariate logistic regression analysis was used to develop predictive models and a radiomics nomogram and their performance was evaluated. Statistical Tests Student's t or chi‐square were used to assess the differences in clinicopathologic data between the training and validation cohorts. Receiver operating characteristic (ROC) curve analysis was performed and the area under the curve (AUC) was calculated. Results In PI‐RADSv2 assessment, 67 lesions scored 5, 70 lesions scored 4, and 29 lesions scored 3. For each sequence, 4404 features were extracted and the top 20 best features were selected. The radiomics model incorporating signatures from the three sequences achieved better performance than any single sequence (AUC: radiomics model 0.868, T 2 W 0.700, ADC 0.759, DCE 0.726). The combined mode incorporating radiomics signature, clinical stage, and time from biopsy to RP outperformed the clinical model and radiomics model (AUC: combined model 0.910, clinical model 0.646, radiomics model 0.868). The nomogram showed good performance (AUC 0.910) and calibration ( P ‐values: training cohort 0.624, validation cohort 0.294). Data Conclusion Radiomics based on mp‐MRI has potential to predict upgrading of PCa from biopsy to RP. Level of Evidence 3 Technical Efficacy Stage 5 J. Magn. Reson. Imaging 2020;52:1239–1248.
    Type of Medium: Online Resource
    ISSN: 1053-1807 , 1522-2586
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 1497154-9
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  • 3
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2020
    In:  Nephrology Dialysis Transplantation Vol. 35, No. Supplement_3 ( 2020-06-01)
    In: Nephrology Dialysis Transplantation, Oxford University Press (OUP), Vol. 35, No. Supplement_3 ( 2020-06-01)
    Abstract: Renal fibrosis is the strongest prognosis predictor of ESRD in chronic kidney disease (CKD), but non-invasive and repeatable imaging markers are missing. Magnetic resonance imaging (MRI) has wide range of applications in renal parenchymal diseases, and diffusional kurtosis imaging (DKI) is a new promising noninvasive method of MRI which can provide more information about non-Gaussian diffusion using a polynomial model. We had successfully used DKI to assess renal fibrosis in IgA nephropathy in our previous work. This study aimed to evaluate the prognostic value of DKI in CKD. Method We prospectively enrolled forty-two CKD patients in our study in Jan. 2017. On recruitment, the basic clinical data were documented, and DKI was performed on a clinical 3T MR scanner. Region-of-interest (ROI) measurements were performed to determine apparent diffusion coefficient (ADC), kurtosis (K) and diffusivity (D) of the cortex of the kidneys. We had followed up these patients for 3 years, and collected all the clinical data and outcomes. The prognostic value of DKI metrics and clinical parameters were investigated. Results Forty-two patients consisted of 26 males and 16 females with mean age of 41.3±15.4 years. The most common etiology was IgA nephropathy (25/42, 59.5%). At baseline, the mean value of serum creatinine (SCr) was 224.4±156.2μmol/L. Among them, 18 patients had eGFR≥45ml/min and 24 patients had eGFR & lt;45ml/min. According to the etiology and CKD classification, all the patients had received appropriate treatment. Besides supportive treatment and management of CKD complications, 21 patients (50%) had received corticosteroid and/or immunosuppressants treatment. After 36 months follow up, 12 patients had progressed to end stage renal disease (ESRD), and the mean value of SCr of the remaining 30 patients was 153.0±78.8umol/L. The Kaplan-Meyer survival regression showed that the patients with eGFR & lt;45ml/min had worse clinical outcomes (p=0.0006). ROC analysis and Kaplan-Meyer survival regression showed that DKI metrics (K≥0.66 or ADC & lt;1.35) not only predicted severe renal fibrosis, but also had worse clinical outcomes (p=0.01 and p & lt;0.0001) (Figure 1). According to the COX regression analysis, both K (K≥0.66, HR 4.676, 95%CI 1.262-17.325) and ADC (ADC & lt;1.35, HR 13.118, 95%CI 3.499-49.178) values, but not age, gender and eGFR group (cut-off value: 45ml/min), were the independent risk factors for the progression to ESRD. Conclusion Renal ADC and K values obtained from DKI showed significant predictive value for the prognosis of CKD, could be a promising non-invasive technique in patients follow-up.
    Type of Medium: Online Resource
    ISSN: 0931-0509 , 1460-2385
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 1465709-0
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  • 4
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2017
    In:  Abdominal Radiology Vol. 42, No. 9 ( 2017-9), p. 2305-2313
    In: Abdominal Radiology, Springer Science and Business Media LLC, Vol. 42, No. 9 ( 2017-9), p. 2305-2313
    Type of Medium: Online Resource
    ISSN: 2366-004X , 2366-0058
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
    detail.hit.zdb_id: 2845742-0
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  • 5
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2017
    In:  Abdominal Radiology Vol. 42, No. 2 ( 2017-2), p. 561-568
    In: Abdominal Radiology, Springer Science and Business Media LLC, Vol. 42, No. 2 ( 2017-2), p. 561-568
    Type of Medium: Online Resource
    ISSN: 2366-004X , 2366-0058
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
    detail.hit.zdb_id: 2845742-0
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  • 6
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2017
    In:  Abdominal Radiology Vol. 42, No. 8 ( 2017-8), p. 2127-2134
    In: Abdominal Radiology, Springer Science and Business Media LLC, Vol. 42, No. 8 ( 2017-8), p. 2127-2134
    Type of Medium: Online Resource
    ISSN: 2366-004X , 2366-0058
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
    detail.hit.zdb_id: 2845742-0
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  • 7
    Online Resource
    Online Resource
    SAGE Publications ; 2019
    In:  Acta Radiologica Vol. 60, No. 11 ( 2019-11), p. 1553-1561
    In: Acta Radiologica, SAGE Publications, Vol. 60, No. 11 ( 2019-11), p. 1553-1561
    Type of Medium: Online Resource
    ISSN: 0284-1851 , 1600-0455
    RVK:
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2019
    detail.hit.zdb_id: 2024579-8
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  • 8
    In: Nephrology Dialysis Transplantation, Oxford University Press (OUP), Vol. 38, No. Supplement_1 ( 2023-06-14)
    Abstract: Renal function, for decades, has been of interest to clinicians and researchers to describe. For example, serum creatinine (Scr) and estimated glomerulus filtration rate (eGFR) is familiar but also limited in many circumstances. Meanwhile, the physiological volumes of the kidney cortex and medulla are presumed to change with age and have been proven to change with decreasing kidney function. Method We recruited 182 patients with normal Scr levels and contrasted CT images between Oct. 2021 and Feb 2022 in Peking Union Medical College Hospital (PUMCH) with their demographic and clinical data. The automatic segmentation method was modified from U-NET and used for both cortex and medullary separation and their volume calculation, respectively. We combined the kidney volume and clinical data as multimodal features of the machine learning model. All the data were separated into a training dataset (PUMCH training set, 80%) and a test dataset (PUMCH test set, 20%). Besides, we included patients with the same inclusion criteria but with diabetes (PUMCH-DM test set) and diabetic nephropathy (PUMCH-DN test set) for internal comparison to verify the possible clinical value of “KIDNEY AGE” (K-AGE). Data from DongZhiMen Hospital (DZMH test set) was used as separate external validation sets to evaluate model generalizability. Results The PUMCH training set included 146 participants with a mean age of 47.5±7.4 years. 58.9% were female, and the mean Scr is 63.5±12.3 μmol/L. The PUMCH test set included 36 participants with a mean age of 47.1±7.9 years, 52.7% were female, and the mean Scr was 66.9±13.0 μmol/L. For segmented kidneys, volume differences between non-contrast-enhanced CT and non-contrast-enhanced CT in the left and right kidneys were not evident. The multimodal neural network predicted: K-AGE approximately close to the patient's actual physiological age, with 92% prediction within the 95% confidential interval (Figure 1). We also compared the K-AGE prediction in PUMCH, PUMCH-DM, and PUMCH-DN test sets by applying U-NET-nonCon segmentation algorithm in non-contrast CT images. The mean absolute error increases along with the disease process (control group 5.00, diabetes group 6.99, diabetic nephropathy group 9.32) (Figure 2). Conclusion We established a machine learning model for predicting the K-AGE of normal Scr patients.
    Type of Medium: Online Resource
    ISSN: 0931-0509 , 1460-2385
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 1465709-0
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  • 9
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2020
    In:  Nephrology Dialysis Transplantation Vol. 35, No. Supplement_3 ( 2020-06-01)
    In: Nephrology Dialysis Transplantation, Oxford University Press (OUP), Vol. 35, No. Supplement_3 ( 2020-06-01)
    Abstract: Infection is the leading cause of death in elderly patients with anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). Older patients are more frail and have poorer nutritional reserves. The decrease in skeletal muscle mass and the development of sarcopenia is a pervasive problem among the elderly. Computer tomography (CT) scan provides a practical method to measure muscle mass in hospitalized patients which has been shown to predict the mortality in cancer and ICU patients. In the present study, we aim in to investigate the relationship between skeletal muscle area and clinical outcomes in elderly AAV patients with renal involvement. Method Hospitalized AAV patients older than 65 years at the diagnosis in Peking Union Medical Hospital from June, 2014 to June, 2019 were enrolled. Skeletal muscle area was calculated on CT image at the third lumbar vertebra level with previously published method using NIH ImageJ software. Baseline Birmingham Vasculitis Activity Score (BVAS), lab results, intensity of immunosuppressive treatment, follow up time and status of the endpoints (infection or death) were recorded. Characteristics between patients with or without endpoint event were compared. Univariate and multivariate Cox regression model was used to determine the independent predictors of mortality. Results A total of 58 patients were included, with. 48.3% male (n=28) and mean age 71.11(65.13, 78.13) years. Baseline BVAS score was 17±4.36 and eGFR was 18.67 (8.306, 34.59) ml/min×1.73m2. Muscle area was 119.6±24.14 cm2 measured on the first CT scan after admission. The baseline serum albumin was 34 (29, 37) g/L, baseline Hemoglobin was 97.83±21.81g/L and baseline immunoglobulin G level was 14.18±4.83g/L. Treatment include glucocorticoid (100%), cyclophosphamide (87.9%), pulse glucocoritcoid (36.2%) and plasma exchange(25.9%). After a median follow-up of 233.5(56.75, 435.8) days, 30 patients experienced 36 episodes of infections that required either hospitalization or administration of antimicrobial agents, of which 7 episodes were complex infections of more than one site and 10 were infections resulting in ICU admission. Median time to infection was 16 (7.5, 59) days from admission. Pneumonia (n=30) and CMV viremia (n=7) were most common. Seven patients died of infection and 1 died of gastrointestinal bleeding. Median time to death was 44 (25.5,75.3) days from admission. In univariate analysis, only age (HR=1.198, CI 1.046,1.372, p=0.006) and muscle area (HR=0.945, CI 0.907,0.986, p=0.009) significantly predicted death. Other variables including BVAS score, eGFR at the onset of disease, history of diabetes, history of pulmonary disease, disease affecting the respiratory system and whether receiving glucocorticoid pulse therapy and baseline nutritional markers i.e. BMI, serum albumin level, lymphocyte count, hemoglobin level and immunoglobulin G level were not significant predictors of death or infection. In multivariate survival analysis, muscle area were significant predictor of 6 month death even when controlled for baseline BMI and eGFR. Conclusion Muscle area as measured at L3 vertebrae level on non-contrast enhanced CT is an strong predictor of 6 month mortality in elderly AAV patients receiving immunosuppressive therapy
    Type of Medium: Online Resource
    ISSN: 0931-0509 , 1460-2385
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 1465709-0
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  • 10
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2022
    In:  Nephrology Dialysis Transplantation Vol. 37, No. 8 ( 2022-07-26), p. 1451-1460
    In: Nephrology Dialysis Transplantation, Oxford University Press (OUP), Vol. 37, No. 8 ( 2022-07-26), p. 1451-1460
    Abstract: Renal fibrosis is the strongest prognostic predictor of end-stage renal disease (ESRD) in chronic kidney disease (CKD). Diffusion kurtosis imaging (DKI) is a promising method of magnetic resonance imaging successfully used to assess renal fibrosis in immunoglobulin A nephropathy. This study aimed to be the first to evaluate the long-term prognostic value of DKI in CKD patients. Methods Forty-two patients with CKD were prospectively enrolled, and underwent DKI on a clinical 3T MR scanner. We excluded patients with comorbidities that could affect the volume or the components of the kidney. DKI parameters, including mean Kurtosis (K), mean diffusivity and apparent diffusion coefficient (ADC) of kidney cortex were obtained by region-of-interest measurement. We followed up these patients for a median of 43 months and investigated the correlations between each DKI parameter and overall renal prognosis. Results Both K and ADC values were correlated well with the estimated glomerular filtration rate (eGFR) on recruitment and the eGFR of the last visit in follow-up (P ˂ 0.001). K and ADC values were also well associated with the eGFR slopes in CKD patients, both with the first–last time point slope (P = 0.011 and P ˂ 0.001, respectively) and with the regression slope (P = 0.010 and P ˂ 0.001, respectively). Cox proportional hazard regression indicated that lower eGFR and ADC values independently predicted eGFR loss of ˃30% and ESRD. The receiver operating characteristic analysis showed that K and ADC values were predictable for renal prognosis, and ADC displayed better capabilities for both ESRD [area under the curve (AUC) 0.936, sensitivity 92.31%, specificity 82.76%] and the composite endpoint (eGFR loss ˃30% or ESRD) (AUC 0.881, sensitivity 66.67%, specificity 96.3%). Conclusions Renal ADC values obtained from DKI showed significant predictive value for the prognosis of CKD patients, which could be a promising noninvasive technique in follow-up.
    Type of Medium: Online Resource
    ISSN: 0931-0509 , 1460-2385
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 1465709-0
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