A novel multimodal prediction model based on DNA methylation biomarkers and low-dose computed tomography images for identifying early-stage lung cancer.

Objective: DNA methylation alterations are early events in carcinogenesis and immune signalling in lung cancer. This study aimed to develop a model based on short stature homeobox 2 gene (SHOX2)/prostaglandin E receptor 4 gene (PTGER4) DNA methylation in plasma, appearance subtype of pulmonary nodules (PNs) and low-dose computed tomography (LDCT) images to distinguish early-stage lung cancers. Methods: We developed a multimodal prediction model with a training set of 257 individuals. The performance of the multimodal prediction model was further validated in an independent validation set of 42 subjects. In addition, we explored the association between SHOX2/PTGER4 DNA methylation and driver gene mutations in lung cancer based on data from The Cancer Genome Atlas (TCGA) portal. Results: There were significant differences between the early-stage lung cancers and benign groups in the methylation levels. The area under a receiver operator characteristic curve (AUC) of SHOX2 in patients with solid nodules, mixed ground-glass opacity nodules and pure ground-glass opacity nodules were 0.693, 0.497 and 0.864, respectively, while the AUCs of PTGER4 were 0.559, 0.739 and 0.619, respectively. With the highest AUC of 0.894, the novel multimodal prediction model outperformed the Mayo Clinic model (0.519) and LDCT-based deep learning model (0.842) in the independent validation set. Database analysis demonstrated that patients with SHOX2/PTGER4 DNA hypermethylation were enriched in TP53 mutations. Conclusions: The present multimodal prediction model could more efficiently distinguish early-stage lung cancer from benign PNs. A prognostic index based on DNA methylation and lung cancer driver gene alterations may separate the patients into groups with good or poor prognosis.

Development and external validation of the multichannel deep learning model based on unenhanced CT for differentiating fat-poor angiomyolipoma from renal cell carcinoma: a two-center retrospective study.

PURPOSE: There are undetectable levels of fat in fat-poor angiomyolipoma. Thus, it is often misdiagnosed as renal cell carcinoma. We aimed to develop and evaluate a multichannel deep learning model for differentiating fat-poor angiomyolipoma (fp-AML) from renal cell carcinoma (RCC). METHODS: This two-center retrospective study included 320 patients from the First Affiliated Hospital of Sun Yat-Sen University (FAHSYSU) and 132 patients from the Sun Yat-Sen University Cancer Center (SYSUCC). Data from patients at FAHSYSU were divided into a development dataset (n = 267) and a hold-out dataset (n = 53). The development dataset was used to obtain the optimal combination of CT modality and input channel. The hold-out dataset and SYSUCC dataset were used for independent internal and external validation, respectively. RESULTS: In the development phase, models trained on unenhanced CT images performed significantly better than those trained on enhanced CT images based on the fivefold cross-validation. The best patient-level performance, with an average area under the receiver operating characteristic curve (AUC) of 0.951 ± 0.026 (mean ± SD), was achieved using the "unenhanced CT and 7-channel" model, which was finally selected as the optimal model. In the independent internal and external validation, AUCs of 0.966 (95% CI 0.919-1.000) and 0.898 (95% CI 0.824-0.972), respectively, were obtained using the optimal model. In addition, the performance of this model was better on large tumors (≥ 40 mm) in both internal and external validation. CONCLUSION: The promising results suggest that our multichannel deep learning classifier based on unenhanced whole-tumor CT images is a highly useful tool for differentiating fp-AML from RCC.

Robot-assisted partial nephrectomy for large complex renal cancer: step-by-step segmental artery unclamping

ABSTRACT Introduction Main renal artery clamping and selective arterial clamping are two conventional devascularization methods for robot-assisted partial nephrectomy (RAPN) (1, 2). Decreasing warm ischemic (WI) time (3, 4) and improving clear surgical visualization (5) are the main surgically modifiable factors for RAPN, especially in large complex renal cancer (6). In this study, we described our surgical technique, focusing on gradual segmental artery unclamping on patients with large renal tumors. Material and methods Two patients (R.E.N.A.L score 10 and 11) underwent RAPN with gradual segmental artery unclamping (Figures 1 and 2). The unclamping included five key steps. First, all renal segmental arteries were identified as tumor feeding vessel(s) and the vessels for normal kidney parenchyma under the guidance of CT angiography (CTA) 3-division (3D) reconstruction. Second, all segmental arteries were isolated, and the feeding one(s) should be blocked before other arteries were blocked. Third, the tumor was resected outside the pseudocapsule, and the deep resection bed was sutured for initial hemostasis. Fourth, the segmental arteries were reopened except for the tumor feeding one(s), and normal kidney parenchyma restored blood supply. And fifth, the resection bed was completely sutured, and the feeding vessel supplying the tumor was opened after the suture. Warm ischemia time (WIT) was defined as the time measured between clamping and unclamping of the renal artery. WIT1 was the time for normal kidney parenchyma and WIT2 was the time for resection area. Patient demographics, perioperative variables, and warm ischemic time were included in our study. And we presented the details of gradual segmental artery unclamping in the video. Results In both cases, the total operation times were 215 and 130 mins for patient 1 and patient 2, respectively. WIT1 and WIT2 for patient 1 were 15 min and 33 min., and WIT1 and WIT2 for patient 2 were 21 min and 32 min, respectivelly. The maximum diameters of the masses resected were 10.8 and 7.3 cm, and surgical margins were negative. No patient had complications after operation. Preoperative and postoperative eGFR did not change significantly. Pre- and postoperative eGFR were 111 and 108 mL/min for patient 1, 91 and 83 mL/min for patient 2, respectively. Key hints for outcomes optimization during RAPN on patients with large complex renal tumors: 1) Each segmental renal artery is precised clamped before we excise the tumor, and an excellent surgical vision is essential for precising excision and shortening clamping time, 2) Other segmental renal arteries are unclamped except tumor feeding branch after suturing deep layer of parenchyma, and most normal parenchyma restores blood supply, 3) Preoperative high-resolution computed tomography angiography (CTA) and 3D reconstructive renal structure serve as a guide to clear the approach to find the tumor and segmental arteries (7, 8). Conclusions Gradual segmental artery unclamping is feasible and efficient to excise large complex renal cancer. Compared with main renal artery clamping, it can shorten the warm ischemic time of normal parenchyma; On the other hand, compared with selective segmental arterial clamping, the technique can reduce bleeding from the deep resection bed, keep a clear surgical vision, and decrease the incidence of positive margin.

Development and validation of a novel defined mutation classifier based on Lasso logistic regression for predicting the overall survival of immune checkpoint inhibitor therapy in renal cell carcinoma.

Background: Currently, immune checkpoint inhibitor (ICI)-based therapy has become the first-line treatment for advanced renal cell carcinoma (RCC). However, few biomarkers have been identified to predict the response to ICI therapy in RCC patients. Herein, our research aimed to build a gene mutation prognostic indicator for ICI therapy. Methods: This multi-cohort study explored the mutation patterns in 2 publicly available advanced RCC ICI therapy cohorts, the Memorial Sloan Kettering Cancer Center (MSKCC) advanced RCC ICI therapy cohort and the CheckMate ICI therapy cohort. A total of 261 patients in the CheckMate ICI therapy cohort were randomly assigned to either the training or validation set. Least absolute shrinkage and selection operator (Lasso) logistic regression analysis was subsequently used to develop a mutation classifier utilizing the training set. The classifier was then validated internally in the validation set and externally in 2 ICI therapy cohorts and 2 non-ICI therapy cohorts. Survival analysis, receiver operator characteristic curves and Harrell's concordance index were performed to assess the prognostic value of the classifier. Function and immune microenvironment analysis in each subgroup defined by the classifier were performed. Results: A 10-gene mutation classifier was constructed based on the CheckMate ICI therapy cohort to separate patients into 2 risk groups, with patients in the high-risk group showing significantly lower overall survival probability than those in the low-risk group [the training set (HR: 1.791; 95% CI: 1.207-2.657; P=0.003), the validation set (HR: 1.842; 95% CI: 1.133-2.996; P=0.012) and combination set (HR: 1.819; 95% CI: 1.339-2.470; P<0.001)]. Further validation confirmed that the mutation classifier only showed predictive value for patients receiving ICI therapy instead of non-ICI therapy. Combined with the clinical characteristics, the risk score was proven to be an independent prognostic factor for overall survival in ICI therapy by multivariate Cox regression analysis. Functional and immune infiltration analysis demonstrated that lower risk scores tended to associate with immunologically "hot" status in RCC. Conclusions: Our 10-gene mutation classifier was found to be a biomarker for predicting the overall survival of patients with advanced RCC to ICI therapy.

Robot-assisted partial nephrectomy for large complex renal cancer: step-by-step segmental artery unclamping.

INTRODUCTION: Main renal artery clamping and selective arterial clamping are two conventional devascularization methods for robot-assisted partial nephrectomy (RAPN) (1, 2). Decreasing warm ischemic (WI) time (3, 4) and improving clear surgical visualization (5) are the main surgically modifiable factors for RAPN, especially in large complex renal cancer (6). In this study, we described our surgical technique, focusing on gradual segmental artery unclamping on patients with large renal tumors. MATERIAL AND METHODS: Two patients (R.E.N.A.L score 10 and 11) underwent RAPN with gradual segmental artery unclamping (Figures 1 and 2). The unclamping included five key steps. First, all renal segmental arteries were identified as tumor feeding vessel(s) and the vessels for normal kidney parenchyma under the guidance of CT angiography (CTA) 3-division (3D) reconstruction. Second, all segmental arteries were isolated, and the feeding one(s) should be blocked before other arteries were blocked. Third, the tumor was resected outside the pseudocapsule, and the deep resection bed was sutured for initial hemostasis. Fourth, the segmental arteries were reopened except for the tumor feeding one(s), and normal kidney parenchyma restored blood supply. And fifth, the resection bed was completely sutured, and the feeding vessel supplying the tumor was opened after the suture. Warm ischemia time (WIT) was defined as the time measured between clamping and unclamping of the renal artery. WIT1 was the time for normal kidney parenchyma and WIT2 was the time for resection area. Patient demographics, perioperative variables, and warm ischemic time were included in our study. And we presented the details of gradual segmental artery unclamping in the video. RESULTS: In both cases, the total operation times were 215 and 130 mins for patient 1 and patient 2, respectively. WIT1 and WIT2 for patient 1 were 15 min and 33 min., and WIT1 and WIT2 for patient 2 were 21 min and 32 min, respectivelly. The maximum diameters of the masses resected were 10.8 and 7.3 cm, and surgical margins were negative. No patient had complications after operation. Preoperative and postoperative eGFR did not change significantly. Pre- and postoperative eGFR were 111 and 108 mL/min for patient 1, 91 and 83 mL/min for patient 2, respectively. Key hints for outcomes optimization during RAPN on patients with large complex renal tumors: 1) Each segmental renal artery is precised clamped before we excise the tumor, and an excellent surgical vision is essential for precising excision and shortening clamping time, 2) Other segmental renal arteries are unclamped except tumor feeding branch after suturing deep layer of parenchyma, and most normal parenchyma restores blood supply, 3) Preoperative high-resolution computed tomography angiography (CTA) and 3D reconstructive renal structure serve as a guide to clear the approach to find the tumor and segmental arteries (7, 8). CONCLUSIONS: Gradual segmental artery unclamping is feasible and efficient to excise large complex renal cancer. Compared with main renal artery clamping, it can shorten the warm ischemic time of normal parenchyma; On the other hand, compared with selective segmental arterial clamping, the technique can reduce bleeding from the deep resection bed, keep a clear surgical vision, and decrease the incidence of positive margin.

m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer.

BACKGROUND: N6-methyladenosine (m6A) related long noncoding RNAs (lncRNAs) may have prognostic value in bladder cancer for their key role in tumorigenesis and innate immunity. METHODS: Bladder cancer transcriptome data and the corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) database. The m6A-immune-related lncRNAs were identified using univariate Cox regression analysis and Pearson correlation analysis. A risk model was established using least absolute shrinkage and selection operator (LASSO) Cox regression analyses, and analyzed using nomogram, time-dependent receiver operating characteristics (ROC) and Kaplan-Meier survival analysis. The differences in infiltration scores, clinical features, and sensitivity to Talazoparib of various immune cells between low- and high-risk groups were investigated. RESULTS: Totally 618 m6A-immune-related lncRNAs and 490 immune-related lncRNAs were identified from TCGA, and 47 lncRNAs of their intersection demonstrated prognostic values. A risk model with 11 lncRNAs was established by Lasso Cox regression, and can predict the prognosis of bladder cancer patients as demonstrated by time-dependent ROC and Kaplan-Meier analysis. Significant correlations were determined between risk score and tumor malignancy or immune cell infiltration. Meanwhile, significant differences were observed in tumor mutation burden and stemness-score between the low-risk group and high-risk group. Moreover, high-risk group patients were more responsive to Talazoparib. CONCLUSIONS: An m6A-immune-related lncRNA risk model was established in this study, which can be applied to predict prognosis, immune landscape and chemotherapeutic response in bladder cancer.

An Aging and Senescence-Related Gene Signature for Prognosis Prediction in Clear Cell Renal Cell Carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) is the most common solid lesion in the kidney. This study aims to establish an aging and senescence-related mRNA model for risk assessment and prognosis prediction in ccRCC patients. Methods: ccRCC data were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. By applying univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression, a new prognostic model based on aging and senescence-related genes (ASRGs) was established. Depending on the prognostic model, high- and low-risk groups were identified for further study. The reliability of the prediction was evaluated in the validation cohort. Pan-cancer analysis was conducted to explore the role of GNRH1 in tumors. Results: A novel prognostic model was established based on eight ASRGs. This model was an independent risk factor and significantly correlated with the prognosis and clinicopathological features of ccRCC patients. The high- and low-risk groups exhibited distinct modes in the principal component analysis and different patterns in immune infiltration. Moreover, the nomogram combining risk score and other clinical factors showed excellent predictive ability, with AUC values for predicting 1-, 3-, and 5-year overall survival in the TCGA cohort equal to 0.88, 0.82, and 0.81, respectively. Conclusion: The model and nomogram based on the eight ASRGs had a significant value for survival prediction and risk assessment for ccRCC patients, providing new insights into the roles of aging and senescence in ccRCC.

circCHST15 is a novel prognostic biomarker that promotes clear cell renal cell carcinoma cell proliferation and metastasis through the miR-125a-5p/EIF4EBP1 axis.

BACKGROUND: Circular RNAs (circRNAs) have been indicated as potentially critical mediators in various types of tumor progression, generally acting as microRNA (miRNA) sponges to regulate downstream gene expression. However, the aberrant expression profile and dysfunction of circRNAs in human clear cell renal cell carcinoma (ccRCC) need to be further investigated. This study mined key prognostic circRNAs and elucidates the potential role and molecular mechanism of circRNAs in regulating the proliferation and metastasis of ccRCC. METHODS: circCHST15 (hsa_circ_0020303) was identified by mining two circRNA microarrays from the Gene Expression Omnibus database and comparing matched tumor versus adjacent normal epithelial tissue pairs or matched primary versus metastatic tumor tissue pairs. These results were validated by quantitative real-time polymerase chain reaction and agarose gel electrophoresis. We demonstrated the biological effect of circCHST15 in ccRCC both in vitro and in vivo. To test the interaction between circCHST15 and miRNAs, we conducted a number of experiments, including RNA pull down assay, dual-luciferase reporter assay and fluorescence in situ hybridization. RESULTS: The expression of circCHST15 was higher in ccRCC tissues compared to healthy adjacent kidney tissue and higher in RCC cell lines compared to normal kidney cell lines. The level of circCHST15 was positively correlated with aggressive clinicopathological characteristics, and circCHST15 served as an independent prognostic indicator for overall survival and progression-free survival in patients with ccRCC after surgical resection. Our in vivo and in vitro data indicate that circCHST15 promotes the proliferation, migration, and invasion of ccRCC cells. Mechanistically, we found that circCHST15 directly interacts with miR-125a-5p and acts as a microRNA sponge to regulate EIF4EBP1 expression. CONCLUSIONS: We found that sponging of miR-125a-5p to promote EIF4EBP1 expression is the underlying mechanism of hsa_circ_0020303-induced ccRCC progression. This prompts further investigation of circCHST15 as a potential prognostic biomarker and therapeutic target for ccRCC.

Circular RNA circSNX6 promotes sunitinib resistance in renal cell carcinoma through the miR-1184/GPCPD1/ lysophosphatidic acid axis.

Sunitinib resistance is a major challenge in systemic therapy for renal cell carcinoma (RCC). The role of circular RNAs (circRNAs) in regulating sunitinib resistance of RCC is largely unknown. We established sunitinib-resistant RCC cell lines in vivo. Through RNA-sequencing, we identified circSNX6, whose expression is upregulated in sunitinib-resistant cells compared with their parental cells. High circSNX6 expression was correlated with sunitinib resistance and worse oncologic outcomes in a cohort of 81 RCC patients. In vitro and in vivo experiments confirmed that circSNX6 could promote sunitinib resistance in RCC. circSNX6 acts as a molecular "sponge" to relieve the suppressive effect of microRNA (miR)-1184 on its target gene, glycerophosphocholine phosphodiesterase 1 (GPCPD1), which increases intracellular lysophosphatidic acid (LPA) levels and, ultimately, promotes sunitinib resistance in RCC cells. Our findings demonstrated that the circSNX6/miR-1184/GPCPD1 axis had a critical role in regulation of intracellular LPA levels and sunitinib resistance in RCC; they also provide a novel prognostic indicator and promising therapeutic targets.

Positive feedback regulation of lncRNA PVT1 and HIF2α contributes to clear cell renal cell carcinoma tumorigenesis and metastasis.

Long noncoding RNAs (lncRNAs) have been reported to exert important roles in tumors, including clear cell renal cell carcinoma (ccRCC). PVT1 is an important oncogenic lncRNA which has critical effects on onset and development of various cancers, however, the underlying mechanism of PVT1 functioning in ccRCC remains largely unknown. VHL deficiency-induced HIF2α accumulation is one of the major factors for ccRCC. Here, we identified the potential molecular mechanism of PVT1 in promoting ccRCC development by stabilizing HIF2α. PVT1 was significantly upregulated in ccRCC tissues and high PVT1 expression was associated with poor prognosis of ccRCC patients. Both gain-of-function and loss-of function experiments revealed that PVT1 enhanced ccRCC cells proliferation, migration, and invasion and induced tumor angiogenesis in vitro and in vivo. Mechanistically, PVT1 interacted with HIF2α protein and enhanced its stability by protecting it from ubiquitination-dependent degradation, thereby exerting its biological significance. Meanwhile, HIF2α bound to the enhancer of PVT1 to transactivate its expression. Furthermore, HIF2α specific inhibitor could repress PVT1 expression and its oncogenic functions. Therefore, our study demonstrates that the PVT1/ HIF2α positive feedback loop involves in tumorigenesis and progression of ccRCC, which may be exploited for anticancer therapy.

Development and validation of the prognostic value of the immune-related genes in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is a highly heterogeneous tumor, resulting a challenge of developing target therapeutics. Not long ago, immune checkpoint blockade regimens combine with tyrosin kinase inhibitors have evolved frontline options in metastatic RCC, which implies arrival of the era of tumor immunotherapy. Studies have demonstrated immune-related genes (IRGs) could characterize tumor milieu and related to patient survival. Nevertheless, the clinical significance of classifier depending on IRGs in ccRCC has not been well established. METHODS: The R package limma, univariate and LASSO cox regression analysis were used to screen the prognostic related IRGs from TCGA database. Multivariate cox regression was utilized to establish a risk prediction model for candidate genes. Quantitative real-time PCR was used to confirm the expression of candidates in clinical samples from our institution. CIBERSORT algorithm and correlation analysis were applied to explore tumor-infiltrating immune cells signature between different risk groups. A clinical nomogram was also developed to predict OS by using the rms R package based on the risk prediction model and other independent risk factors. The ICGC data was used for external validation of either gene risk model or nomogram. RESULTS: We identified 382 differentially expressed immune related genes. Four unique prognostic IRGs (CRABP2, LTB4R, PTGER1 and TEK) were finally affirmed to associate with tumor survival independently and utilized to establish the risk score model. All candidates' expression was successfully laboratory confirmed by q-PCR. CIBERSORT analysis implied patients in unfavorable-risk group with high CD8 T cell, regulatory T cell and NK cell infiltration, as well as high expression of PD-1, CTLA4, TNFRSF9, TIGIT and LAG3. A nomogram combined IRGs risk score with age, gender, TNM stage, Fuhrman grade, necrosis was further generated to predict of 3- and 5-year OS, which exhibited superior discriminative power (AUCs were 0.811 and 0.795). CONCLUSIONS: Our study established and validated a survival prognostic model system based on 4 unique immune related genes in ccRCC, which expands knowledge in tumor immune status and provide a potent prediction tool in future.

A panel of eight autophagy-related long non-coding RNAs is a good predictive parameter for clear cell renal cell carcinoma.

Clear-cell renal cell carcinoma (ccRCC) carries a variable prognosis. Prognostic biomarkers can stratify patients according to risk, and can provide crucial information for clinical decision-making. We screened for an autophagy-related long non-coding lncRNA (lncRNA) signature to improve postoperative risk stratification in The Cancer Genome Atlas (TCGA) database. We confirmed this model in ICGC and SYSU cohorts as a significant and independent prognostic signature. Western blotting, autophagic-flux assay and transmission electron microscopy were used to verify that regulation of expression of 8 lncRNAs related to autophagy affected changes in autophagic flow in vitro. Our data suggest that 8-lncRNA signature related to autophagy is a promising prognostic tool in predicting the survival of patients with ccRCC. Combination of this signature with clinical and pathologic parameters could aid accurate risk assessment to guide clinical management, and this 8-lncRNAs signature related to autophagy may serve as a therapeutic target.

Contrast-enhanced transrectal ultrasound can reduce collection of unnecessary biopsies when diagnosing prostate cancer and is predictive of biochemical recurrence following a radical prostatectomy in patients with localized prostate cancer.

BACKGROUND: To investigate the value of using contrast-enhanced transrectal ultrasound (CETRUS) to reduce unnecessary collection of biopsies during prostate cancer diagnosis and its utility in predicting biochemical recurrence in patients with localized prostate cancer. METHODS: This was a prospective study of suspected prostate cancer patients who were evaluated with CETRUS followed by a prostate biopsy. Prostate blood flow via CETRUS was graded using a 5-point scale. The relationship between CETRUS score and biopsy outcome was then analyzed for all patients; univariate and multi-variate analyses were used to determine the probable prognostic factors for biochemical recurrence in patients with localized prostate cancer that underwent a radical prostatectomy. RESULTS: A total of 347 patients were enrolled in the study. Prostate cancer was found in 164 patients. A significant positive correlation (r = 0.69, p < 0.001) was found between CETRUS scores and prostate cancer incidence. Using CETRUS scores ≥2 as the threshold for when to biopsy could have safely reduced the number of biopsies taken overall by 12.1% (42/347) and spared 23.0% (42/183) of patients from undergoing an unnecessary biopsy. 77 patients with localized prostate cancer underwent a radical prostatectomy. The median follow-up time was 30 months (range: 8-56 months) and 17 of these 77 patients exhibited biochemical recurrence during the follow-up period. 3-year biochemical recurrence-free survival rates were 86% for patients with low CETRUS scores (≤ 3) and 59% for patients with high scores (> 3; p = 0.015). Multivariate Cox regression analysis indicated that CETRUS score was an independent predictor of biochemical recurrence (HR: 7.02; 95% CI: 2.00-24.69; p = 0.002). CONCLUSIONS: CETRUS scores may be a useful tool for reducing the collection unnecessary biopsy samples during prostate cancer diagnosis and are predictive of biochemical recurrence in patients with localized prostate cancer following a radical prostatectomy.

Multiparametric MRI for Bladder Cancer: Validation of VI-RADS for the Detection of Detrusor Muscle Invasion.

Background The Vesical Imaging-Reporting and Data System (VI-RADS) scoring system was created in 2018 to standardize imaging and reporting of bladder cancer staging with multiparametric MRI. The system provides a five-point VI-RADS score, which suggests the likelihood of detrusor muscle invasion. Muscle-invasive disease carries a worse prognosis and requires radical surgery. Purpose To determine the performance of the VI-RADS score in detecting muscle-invasive bladder cancer in a cohort of patients undergoing multiparametric MRI before surgery. Materials and Methods In this retrospective study, a total of 340 patients with bladder cancer were identified from a database of consecutive patients undergoing multiparametric MRI from November 2011 to August 2018. The tumor with the largest burden was selected in those patients with multifocal tumors. Bladder tumors were retrospectively categorized according to the VI-RADS five-point scoring system by two readers, independently and in consensus, who were blinded to histologic findings. The VI-RADS score was compared with postoperative pathology for each tumor, and the performance of VI-RADS for determining detrusor muscle invasion was analyzed by using the Cochran-Armitage test. Results Among the 340 patients, there were 296 men and 44 women; the median age was 64.0 years (interquartile range [IQR], 57.0-87.0 years). Of 340 tumors, 255 (75.0%) were verified as non-muscle-invasive and 85 (25.0%) as muscle-invasive bladder cancer. Both the VI-RADS score and its components were associated with muscle-invasive condition (P < .001). The area under the receiver operating characteristic curve for VI-RADS for muscle invasion was 0.94 (95% confidence interval [CI]: 0.90, 0.98). The sensitivity and specificity of a VI-RADS score of 3 or greater were 87.1% (95% CI: 78%, 93%) and 96.5% (95% CI: 93%, 98%), respectively. Conclusion The Vesical Imaging-Reporting and Data System score effectively defines the likelihood of detrusor muscle invasion in bladder cancer and should be considered for evaluation of tumors prior to surgery. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Margolis and Hu in this issue.

Radiomics analysis of multiparametric MRI for the preoperative evaluation of pathological grade in bladder cancer tumors.

OBJECTIVES: To develop and validate an MRI-based radiomics strategy for the preoperative estimation of pathological grade in bladder cancer (BCa) tumors. METHODS: A primary cohort of 70 patients (31 high-grade BCa and 39 low-grade BCa) with BCa were retrospectively enrolled. Three sets of radiomics features were separately extracted from tumor volumes on T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) maps. Two sets of multimodal features were separately generated by the maxout and concatenation of the above mentioned single-modality features. Each feature set was subjected to a two-sample t test and the least absolute shrinkage and selection operator (LASSO) algorithm for feature selection. Multivariable logistic regression (LR) analysis was used to obtain five corresponding radiomics models. The diagnostic abilities of the radiomics models were evaluated using receiver operating characteristic (ROC) curve analysis and compared using the DeLong test. Validation was performed on a time-independent cohort containing 30 consecutive patients. RESULTS: The areas under the ROC curves (AUCs) of single-modality T2WI, DWI, and ADC models in the training cohort were 0.7933 (95% confidence interval [CI] 0.7471-0.8396), 0.8083 (95% CI 0.7565-0.8601), and 0.8350 (95% CI 0.7924-0.8776), respectively. Both multimodality models achieved higher AUCs (maxout 0.9233, 95% CI 0.9001-0.9466; concatenation 0.9233, 95% CI 0.9001-0.9466) than single-modality models. The AUCs of the maxout and concatenation models in the validation cohort were 0.9186 and 0.9276, respectively. CONCLUSIONS: The MRI-based multiparametric radiomics approach has the potential to be used as a noninvasive imaging tool for preoperative grading of BCa tumors. Multicenter validation is needed to acquire high-level evidence for its clinical application. KEY POINTS: • Multiparametric MRI may help in the preoperative grading of BCa tumors. • The Joint_Model established from T2WI, DWI, and ADC feature subsets demonstrated a high diagnostic accuracy for preoperative prediction of pathological grade in BCa tumors. • The radiomics approach has the potential to preoperatively assess tumor grades in BCa and avoid subjectivity.

Predictive value of single-nucleotide polymorphism signature for recurrence in localised renal cell carcinoma: a retrospective analysis and multicentre validation study.

BACKGROUND: Identification of high-risk localised renal cell carcinoma is key for the selection of patients for adjuvant treatment who are at truly higher risk of reccurrence. We developed a classifier based on single-nucleotide polymorphisms (SNPs) to improve the predictive accuracy for renal cell carcinoma recurrence and investigated whether intratumour heterogeneity affected the precision of the classifier. METHODS: In this retrospective analysis and multicentre validation study, we used paraffin-embedded specimens from the training set of 227 patients from Sun Yat-sen University (Guangzhou, Guangdong, China) with localised clear cell renal cell carcinoma to examine 44 potential recurrence-associated SNPs, which were identified by exploratory bioinformatics analyses of a genome-wide association study from The Cancer Genome Atlas (TCGA) Kidney Renal Clear Cell Carcinoma (KIRC) dataset (n=114, 906 600 SNPs). We developed a six-SNP-based classifier by use of LASSO Cox regression, based on the association between SNP status and patients' recurrence-free survival. Intratumour heterogeneity was investigated from two other regions within the same tumours in the training set. The six-SNP-based classifier was validated in the internal testing set (n=226), the independent validation set (Chinese multicentre study; 428 patients treated between Jan 1, 2004 and Dec 31, 2012, at three hospitals in China), and TCGA set (441 retrospectively identified patients who underwent resection between 1998 and 2010 for localised clear cell renal cell carcinoma in the USA). The main outcome was recurrence-free survival; the secondary outcome was overall survival. FINDINGS: Although intratumour heterogeneity was found in 48 (23%) of 206 cases in the internal testing set with complete SNP information, the predictive accuracy of the six-SNP-based classifier was similar in the three different regions of the training set (areas under the curve [AUC] at 5 years: 0·749 [95% CI 0·660-0·826] in region 1, 0·734 [0·651-0·814] in region 2, and 0·736 [0·649-0·824] in region 3). The six-SNP-based classifier precisely predicted recurrence-free survival of patients in three validation sets (hazard ratio [HR] 5·32 [95% CI 2·81-10·07] in the internal testing set, 5·39 [3·38-8·59] in the independent validation set, and 4·62 [2·48-8·61] in the TCGA set; all p<0·0001), independently of patient age or sex and tumour stage, grade, or necrosis. The classifier and the clinicopathological risk factors (tumour stage, grade, and necrosis) were combined to construct a nomogram, which had a predictive accuracy significantly higher than that of each variable alone (AUC at 5 years 0·811 [95% CI 0·756-0·861]). INTERPRETATION: Our six-SNP-based classifier could be a practical and reliable predictor that can complement the existing staging system for prediction of localised renal cell carcinoma recurrence after surgery, which might enable physicians to make more informed treatment decisions about adjuvant therapy. Intratumour heterogeneity does not seem to hamper the accuracy of the six-SNP-based classifier as a reliable predictor of recurrence. The classifier has the potential to guide treatment decisions for patients at differing risks of recurrence. FUNDING: National Key Research and Development Program of China, National Natural Science Foundation of China, Guangdong Provincial Science and Technology Foundation of China, and Guangzhou Science and Technology Foundation of China.

Global longitudinal strain is an independent predictor of cardiovascular events in patients with maintenance hemodialysis: a prospective study using three-dimensional speckle tracking echocardiography.

The aim of this study was to investigate subclinical LV changes in patients with maintenance hemodialysis (MHD) using three-dimensional speckle-tracking echocardiography (3DSTE) and to explore its prognostic value. A total of 88 individuals were consecutively enrolled, including 66 subjects with MHD and 22 age- and sex-matched controls. Conventional and Real-time three-dimensional echocardiography was performed and analyzed. Left ventricular volume, strain and time parameters were calculated and compared. The MHD cohort was then followed to record cardiovascular events (CVE). Univariate and multivariate logistic regression analysis was used to identify independent predictors of CVE. Compared with the controls, MHD patients had significantly lower global longitudinal and radial strain (GLS and GRS), and LVEF (GLS: -17.0 ± 2.3 vs -18.8 ± 2.3 %; GRS: 37.0 ± 3.5 vs 39.4 ± 3.4 %; LVEF: 57.3 ± 4.2 vs 59.5 ± 3.5 %, p < 0.05 for all), as well as enlarged LV volume (EDV: 51.3 ± 14.2 vs 40.4 ± 7.3 ml/m(2); ESV: 22.0 ± 6.9 vs 16.3 ± 3.2 ml/m(2); SV: 29.2 ± 8.0 vs 24.0 ± 4.7 ml/m(2), p < 0.01 for all) and LV mass index (LVMi) (107.7 ± 28.6 vs 83.7 ± 20.6 g/m(2)). Time to minimum end-systolic volume and to peak longitudinal strain (T-msv and T-ls) were delayed in the MHD group (T-msv: 38.1 ± 5.2 vs 41.4 ± 6.4 %; T-ls: 38.1 ± 4.6 vs 42.1 ± 6.8 %, p < 0.05). Systolic dyssynchrony index (SDI) of the MHD group was significant larger than that of the controls (6.4 ± 1.5 vs 4.9 ± 1.8 %, p < 0.01). CVE occurred in 23 patients within a follow-up of 2 years. GLS and LVMi remained significant predictors of CVE [OR = 3.94, 95 % CI (1.33-11.66) for GLS and OR = 1.04, 95 % CI (1.01-1.07) for LVMi, p = 0.013 and 0.009, respectively]. Subclinical LV deformation and dysfunction exist in MHD patients with preserved LVEF. GLS and LVMi are two important predictors of CVE in MHD patients. Strain assessment in MHD patients may contribute to better vascular risk stratification.

Three-Dimensional Echocardiography in the Evaluation of Right Ventricular Global and Regional Systolic Function in Patients with Atrial Septal Defect before and after Percutaneous Closure.

OBJECTIVE: To evaluate right ventricular (RV) global and regional systolic function in patients with atrial septal defect (ASD) before and after percutaneous closure using real time three-dimensional echocardiography (RT3DE). METHODS: RT3DE was performed in 81 patients with ASD within 24 hours before and after percutaneous closure to obtain RV global and regional ejection fraction (EF) in three compartments (inflow, body, and outflow). RV fractional area change (FAC), tricuspid annular plane systolic excursion (TAPSE), peak tricuspid systolic velocity (S), and pulmonary vascular resistance (PVR) were recorded. Forty matched normal adults were included as controls. RESULTS: When compared with controls, RV global and regional EF were decreased in preclosure patients (P < 0.001). FAC was lower while TAPSE and S were higher in preclosure patients than in controls (P < 0.05). After closure, RV systolic function parameters were all reduced (P < 0.001). Regional EF in the body compartment was the lowest among the three compartments in ASD patients (P < 0.05). Procedural percentage changes of RV global EF and regional EF in the inflow compartment were lower than those of two-dimensional systolic function parameters (P < 0.05). RV global and regional EF in the inflow compartment were negatively correlated with PVR in patients after closure (r = -0.601, -0.543, P < 0.001). CONCLUSIONS: RV global and regional systolic functions are impaired in open and closed ASD. RT3DE-derived systolic function parameters are negatively correlated with RV after load. RT3DE has potential value in the evaluation of RV systolic function in patients with ASD.

Sparganosis presenting as pericardial effusion and lung lesions.

We herein report a rare form of sparganosis in a 29-year-old man presenting with pericardial effusion and lung lesions. The diagnosis was confirmed by the patient's history of eating inadequately cooked snake, significant elevated eosinophils in the peripheral blood and pericardial effusion, and marked positive reactions against Sparganum mansoni antigen in the serum. After two consecutive doses of praziquantel treatment, the patient's symptoms and laboratory and imaging findings were improved. Both specific antibody detection and follow-up of the patient's eosinophils, serum antibody, and imaging changes are important for sparganosis diagnosis, particularly in cases without a subcutaneous lump or mass.

The myocardial ischemia evaluated by real-time contrast echocardiography may predict the response to cardiac resynchronization therapy: a large animal study.

Evidence-based criteria for applying cardiac resynchronization therapy (CRT) in patients with ischemic cardiomyopathy are still scarce. The aim of the present study was to evaluate the predictive value of real-time myocardial contrast echocardiography (RT-MCE) in a preclinical canine model of ischemic cardiomyopathy who received CRT. Ischemic cardiomyopathy was produced by ligating the first diagonal branch in 20 beagles. Dogs were subsequently divided into two groups that were either treated with bi-ventricular pacing (CRT group) or left untreated (control group). RT-MCE was performed at baseline, before CRT, and 4 weeks after CRT. Two-dimensional speckle tracking imaging was used to evaluate the standard deviation of circumferential (Cir12SD), radial (R12SD), and longitudinal (L12SD) strains of left ventricular segments at basal as well as middle levels. Four weeks later, the Cir12SD, R12SD, and myocardial blood flow (MBF) of the treated group were significantly improved compared to their non-CRT counterparts. Furthermore, MBF values measured before CRT were significantly higher in responders than in non-responders to bi-ventricular pacing. Meanwhile, no significant differences were observed between the responder and non-responder groups in terms of Cir12SD, R12SD, and L12SD. A high degree of correlation was found between MBF values before CRT and LVEF after CRT. When MBF value>24.9 dB/s was defined as a cut-off point before CRT, the sensitivity and specificity of RT-MCE in predicting the response to CRT were 83.3% and 100%, respectively. Besides, MBF values increased significantly in the CRT group compared with the control group after 4 weeks of pacing (49.8±15.5 dB/s vs. 28.5±4.6 dB/s, p<0.05). Therefore, we considered that myocardial perfusion may be superior to standard metrics of LV synchrony in selecting appropriate candidates for CRT. In addition, CRT can improve myocardial perfusion in addition to cardiac synchrony, especially in the setting of ischemic cardiomyopathy.