Incremental value of automatically segmented perirenal adipose tissue for pathological grading of clear cell renal cell carcinoma: a multicenter cohort study.

OBJECTIVES: Accurate preoperative prediction of the pathological grade of clear cell renal cell carcinoma (ccRCC) is crucial for optimal treatment planning and patient outcomes. This study aims to develop and validate a deep-learning (DL) algorithm to automatically segment renal tumours, kidneys, and perirenal adipose tissue (PRAT) from computed tomography (CT) images and extract radiomics features to predict the pathological grade of ccRCC. METHODS: In this cross-ethnic retrospective study, a total of 614 patients were divided into a training set (383 patients from the local hospital), an internal validation set (88 patients from the local hospital), and an external validation set (143 patients from the public dataset). A two-dimensional TransUNet-based DL model combined with the train-while-annotation method was trained for automatic volumetric segmentation of renal tumours, kidneys, and visceral adipose tissue (VAT) on images from two groups of datasets. PRAT was extracted using a dilation algorithm by calculating voxels of VAT surrounding the kidneys. Radiomics features were subsequently extracted from three regions of interest of CT images, adopting multiple filtering strategies. The least absolute shrinkage and selection operator (LASSO) regression was used for feature selection, and the support vector machine (SVM) for developing the pathological grading model. Ensemble learning was used for imbalanced data classification. Performance evaluation included the Dice coefficient for segmentation and metrics such as accuracy and area under curve (AUC) for classification. The WHO/International Society of Urological Pathology (ISUP) grading models were finally interpreted and visualized using the SHapley Additive exPlanations (SHAP) method. RESULTS: For automatic segmentation, the mean Dice coefficient achieved 0.836 for renal tumours and 0.967 for VAT on the internal validation dataset. For WHO/ISUP grading, a model built with features of PRAT achieved a moderate AUC of 0.711 (95% CI, 0.604-0.802) in the internal validation set, coupled with a sensitivity of 0.400 and a specificity of 0.781. While model built with combination features of the renal tumour, kidney, and PRAT showed an AUC of 0.814 (95% CI, 0.717-0.889) in the internal validation set, with a sensitivity of 0.800 and a specificity of 0.753, significantly higher than the model built with features solely from tumour lesion (0.760; 95% CI, 0.657-0.845), with a sensitivity of 0.533 and a specificity of 0.767. CONCLUSION: Automated segmentation of kidneys and visceral adipose tissue (VAT) through TransUNet combined with a conventional image morphology processing algorithm offers a standardized approach to extract PRAT with high reproducibility. The radiomics features of PRAT and tumour lesions, along with machine learning, accurately predict the pathological grade of ccRCC and reveal the incremental significance of PRAT in this prediction.

Patient-reported outcomes of mesh in minimally invasive (laparoscopic/robot-assisted) immediate subpectoral prosthesis breast reconstruction: a retrospective study.

BACKGROUND: Although there is increasing interest in minimally invasive prosthesis breast reconstruction (PBR), whether meshes application in minimally invasive PBR can improve complications and cosmetic effects remains controversial. The author retrospectively analyzed postoperative complications and evaluated patient-reported quality-of-life outcomes in minimally invasive PBR with and without mesh. METHODS: This study enrolled patients who underwent minimally invasive nipple-sparing mastectomy (NSM) followed by PBR. We used the TiLOOP bra for the mesh-assisted procedure. Patient demographics and postoperative complications data were compared between the procedures. Patient-reported outcomes were evaluated with the Breast-Q. RESULTS: A total of 158 patients underwent 160 minimally invasive NSM-PBR (with mesh, n = 64; without, n = 94). Postoperative complications were comparable in the mesh-assisted (5 [7.7%]) and non-mesh-assisted (5 [5.3%]) groups (p = 0.533). The most common complication in non-mesh-assisted group was infection, with four (4.2%) cases. In mesh-assisted group, implant exposure occurred in two (3.1%) patients. Removal of prosthesis was uncommon, with two (3.1%) and three (3.2%) cases in the mesh-assisted and non-mesh groups, respectively (p = 0.977). The BREAST-Q questionnaire was completed by 52 (81.3%) patients in the mesh-assisted group and 68 (72.3%) in the non-mesh-assisted group. Comparing the non-mesh group, patients in mesh-assisted group had improved scores on the BREAST-Q Satisfaction with breast (66.0) (p < 0.05), Physical Well-being (80.0), and Sexual Well-being (56.0). CONCLUSIONS: Mesh-assisted minimally invasive NSM-PBR has good aesthetic outcomes and high patient satisfaction. There were no significant differences in complication rates between the mesh-assisted and non-mesh-assisted groups.

Engineered poly(A)-surrogates for translational regulation and therapeutic biocomputation in mammalian cells.

Here, we present a gene regulation strategy enabling programmable control over eukaryotic translational initiation. By excising the natural poly-adenylation (poly-A) signal of target genes and replacing it with a synthetic control region harboring RNA-binding protein (RBP)-specific aptamers, cap-dependent translation is rendered exclusively dependent on synthetic translation initiation factors (STIFs) containing different RBPs engineered to conditionally associate with different eIF4F-binding proteins (eIFBPs). This modular design framework facilitates the engineering of various gene switches and intracellular sensors responding to many user-defined trigger signals of interest, demonstrating tightly controlled, rapid and reversible regulation of transgene expression in mammalian cells as well as compatibility with various clinically applicable delivery routes of in vivo gene therapy. Therapeutic efficacy was demonstrated in two animal models. To exemplify disease treatments that require on-demand drug secretion, we show that a custom-designed gene switch triggered by the FDA-approved drug grazoprevir can effectively control insulin expression and restore glucose homeostasis in diabetic mice. For diseases that require instantaneous sense-and-response treatment programs, we create highly specific sensors for various subcellularly (mis)localized protein markers (such as cancer-related fusion proteins) and show that translation-based protein sensors can be used either alone or in combination with other cell-state classification strategies to create therapeutic biocomputers driving self-sufficient elimination of tumor cells in mice. This design strategy demonstrates unprecedented flexibility for translational regulation and could form the basis for a novel class of programmable gene therapies in vivo.

Goal-directed fluid therapy during post-resection phase in low central venous pressure assisted laparoscopic hepatectomy: a randomized controlled superiority trial.

PURPOSE: The purpose of this prospective single blinded randomized controlled trial was to find out whether goal-directed fluid therapy (GDFT) strategy in post-transection period in low central venous pressure (CVP) assisted laparoscopic hepatectomy (LH) has more benefit than traditional fluid strategy. METHODS: Between April 2020 and Dec 2021, patients who were scheduled for laparoscopic liver resection surgery were eligible to participate in the study. Patients were randomly divided into two groups: control group that received traditional fluid strategy in post-transection period in low CVP assisted laparoscopic hepatectomy and GDFT strategy group that received GDFT strategy in post-transection period. The primary outcome parameter is the incidence of postoperative complications. Secondary outcome parameters include perioperative clinical outcomes, postoperative clinical outcomes, length of hospital stay after surgery, postoperative lactic acid, fluids and vasoactive medications during the operation. RESULTS: A total of 159 patients in the control group and 160 patients in the GDFT were included. Two groups had no significant difference in the incidence of postoperative complications including pneumonia (P = 0.34), acute kidney injury (P = 0.72), hepatic insufficiency (P = 0.25), pleural effusion (P = 0.08) and seroperitoneum (P = 1.00), respectively. The amount of perioperative urine output is fewer in GDFT group than in the control group (P = 0.0354), while other perioperative variables and postoperative variables were comparable between two groups. CONCLUSIONS: The results show the implementation of GDFT strategy is not associated with fewer postoperative complications. GDFT strategy did not result in improved outcomes in low CVP-assisted laparoscopic hepatectomy.

Efficacy and safety of Huachansu combined with adjuvant chemotherapy in resected colorectal cancer patients: a prospective, open-label, randomized phase II study.

Although some studies in China have suggested Huachansu (HCS) combined with chemotherapy is effective in the treatment of various cancers, there are few studies on colorectal cancer (CRC), especially in postoperative adjuvant chemotherapy. The aim of this study was to test the hypothesis that HCS combined with adjuvant chemotherapy would improve survival probability in resected CRC patients. This was a prospective, open-label, randomized phase II study. Patients with stage III or high-risk stage II resected CRC were randomly assigned to the chemotherapy and HCS + chemotherapy groups. The Chemotherapy group was treated with the FOLFOX regimen for ≥ 6 cycles or the CAPEOX regimen for ≥ 4 cycles. The HCS + chemotherapy group was treated with HCS on the basis of the chemotherapy group. The primary endpoint was 3-year disease-free survival (DFS), and the secondary endpoints were 3-year overall survival (OS) and toxicity. A total of 250 patients were included in this study (126 chemotherapy, 124 HCS + chemotherapy). There were significant differences in 3-year DFS between the two groups (median 28.7 vs. 31.6 months, respectively; P = 0.027), but no significant differences in 3-year OS between the two groups (median 32.7 vs. 34 months, respectively; P = 0.146). No patients experienced grade four adverse events, and the rates of leukopenia, neutropenia, and diarrhea in the HCS + chemotherapy group were lower than that those in the chemotherapy group. HCS combined with adjuvant chemotherapy after radical resection for patients with stage III or high-risk stage II CRC was demonstrated to be an effective and feasible treatment.

Association of sex-specific abdominal adipose tissue with WHO/ISUP grade in clear cell renal cell carcinoma.

OBJECTIVES: To explore the association between computed tomography (CT)-measured sex-specific abdominal adipose tissue and the pathological grade of clear cell renal cell carcinoma (ccRCC). METHODS: This retrospective study comprised 560 patients (394 males and 166 females) with pathologically proven ccRCC (467 low- and 93 high-grade). Abdominal CT images were used to assess the adipose tissue in the subcutaneous, visceral, and intermuscular regions. Subcutaneous fat index (SFI), visceral fat index (VFI), intermuscular fat index (IFI), total fat index (TFI), and relative visceral adipose tissue (rVAT) were calculated. Univariate and multivariate logistic regression analyses were performed according to sex to identify the associations between fat-related parameters and pathological grade. RESULTS: IFI was significantly higher in high-grade ccRCC patients than in low-grade patients for both men and women. For male patients with high-grade tumors, the SFI, VFI, TFI, and rVAT were significantly lower, but not for female patients. In both univariate and multivariate studies, the IFI continued to be a reliable and independent predictor of high-grade ccRCC, regardless of sex. CONCLUSIONS: Intermuscular fat index proved to be a valuable biomarker for the pathological grade of ccRCC and could be used as a reliable independent predictor of high-grade ccRCC for both males and females. CRITICAL RELEVANCE STATEMENT: Sex-specific fat adipose tissue can be used as a new biomarker to provide a new dimension for renal tumor-related research and may provide new perspectives for personalized tumor management decision-making approaches. KEY POINTS: • There are sex differences in distribution of subcutaneous fat and visceral fat. • The SFI, VFI, TFI, and rVAT were significantly lower in high-grade ccRCC male patients, but not for female patients. • Intermuscular fat index can be used as a reliable independent predictor of high-grade ccRCC for both males and females.

High Expression of F-Box Protein 43 Is Associated With Poor Prognosis and Adjuvant Chemotherapy Resistance in Colorectal Cancer.

Background: The F-box protein 43 (FBXO43), also referred to as endogenous meiotic inhibitor 2 (EMI2), has been linked to the advancement of various types of cancer, such as hepatocellular carcinoma, breast cancer, cholangiocarcinoma, and gastric cancer. Nevertheless, the precise function of FBXO43 in colorectal cancer (CRC) remains unclear. This study employed data from The Cancer Genome Atlas (TCGA) and clinical specimens to analyze the expression, prognostic value, and chemotherapeutic advantages of FBXO43 in CRC. Methods: Level 3 RNA sequencing data pertaining to 631 cases of colon and rectal adenocarcinomas (COAD-READ) were downloaded from TCGA. The data were utilized to analyze the expression, prognosis, and related signal pathways of FBXO43. The expression of FBXO43 in clinical samples was subsequently confirmed through the use of real-time quantitative polymerase chain reaction (qPCR) and immunohistochemistry (IHC). Lastly, a tissue microarray (TMA) consisting of 120 cases of CRC and corresponding normal tissues was established to investigate the relationship between FBXO43 and survival outcomes. Results: Results from both the TCGA analysis and clinical samples indicated that FBXO43 was significantly upregulated in CRC tissues in comparison to normal tissues. Moreover, high level of FBXO43 was found to be relevant to malignant clinical features, such as differentiation, lymph node metastasis, and pathological stage, as well as unfavorable prognosis in CRC patients. Subgroup analysis further demonstrated that FBXO43 could be an effective parameter for stratifying low-risk CRC patients. Notably, survival analysis showed that patients with high level of FBXO43 had worse overall survival (OS) and disease-free survival (DFS) following adjuvant chemotherapy, and FBXO43 was distinctly upregulated in chemotherapy-resistant patients' primary CRC tissues. Conclusions: FBXO43 was upregulated and associated with poor prognosis of CRC; patients with high expression of FBXO43 may not be benefit from adjuvant chemotherapy.

LINC00665 activating Wnt3a/ß-catenin signaling by bond with YBX1 promotes gastric cancer proliferation and metastasis.

Long noncoding RNAs (lncRNAs) play a key role in human cancer development; nevertheless, the effect of lncRNA LINC00665 on the progression of gastric cancer (GC) still unclear. In this study, we found that LINC00665 expression is upregulated in GC than normal gastric mucosa tissues and higher LINC00665 expression is associated with a poor prognosis in GC patients. Downregulated LINC00665 inhibited GC cells proliferation, invasion, and migration in vitro. Pulmonary metastasis animal models showed that downregulated LINC00665 could reduce the lung metastasis of GC in vivo. Tumor organoids were generated from human malignant GC tissues, downregulated LINC00665 could inhibit the growth of the organoids of GC tissues. Mechanistically, downregulated LINC00665 could inhibit GC cells EMT. RNA pulldown, RIP, and RIP-seq studies found that LINC00665 can bind to the transcription factor YBX1 and form a positive feed-forward loop. The luciferase reporter and CHIP results showed that YBX1 could regulate the transcriptional activity of Wnt3a, and downregulation of LINC00665 could block the activation of Wnt/ß-catenin signaling. In conclusion, our results identified a feedback loop between LINC00665 and YBX1 that activates Wnt/ß-catenin signaling, and it may be a potential therapeutic approach to suppress GC progression.

Evaluation of Whole-Tumor Texture Analysis Based on MRI Diffusion Kurtosis and Biparametric VI-RADS Model for Staging and Grading Bladder Cancer.

BACKGROUND: to evaluate the feasibility of texture analysis (TA) based on diffusion kurtosis imaging (DKI) in staging and grading bladder cancer (BC) and to compare it with apparent diffusion coefficient (ADC) and biparametric vesical imaging reporting and data system (VI-RADS). MATERIALS AND METHODS: In this retrospective study, 101 patients with pathologically confirmed BC underwent MRI with multiple-b values ranging from 0 to 2000 s/mm2. ADC- and DKI-derived parameters, including mean kurtosis (MK) and mean diffusivity (MD), were obtained. First-order texture histogram parameters of MK and MD, including the mean; 5th, 25th, 50th, 75th, and 90th percentiles; inhomogeneity; skewness: kurtosis; and entropy; were extracted. The VI-RADS score was evaluated based on the T2WI and DWI. The Mann-Whitney U-test was used to compare the texture parameters and ADC values between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC), as well as between low and high grades. Receiver operating characteristic analysis was used to evaluate the diagnostic performance of each significant parameter and their combinations. RESULTS: The NMIBC and low-grade group had higher MDmean, MD5th, MD25th, MD50th, MD75th, MD90th, and ADC values than those of the MIBC and the high-grade group. The NMIBC and low-grade group yielded lower MKmean, MK25th, MK50th, MK75th, and MK90th than the MIBC and high-grade group. Among all histogram parameters, MD75th and MD90th yielded the highest AUC in differentiating MIBC from NMIBC (both AUCs were 0.87), while the AUC for ADC was 0.86. The MK75th and MK90th had the highest AUC (both 0.79) in differentiating low- from high-grade BC, while ADC had an AUC of 0.68. The AUC (0.92) of the combination of DKI histogram parameters (MD75th, MD90th, and MK90th) with biparametric VI-RADS in staging BC was higher than that of the biparametric VI-RADS (0.89). CONCLUSIONS: Texture-analysis-derived DKI is useful in evaluating both the staging and grading of bladder cancer; in addition, the histogram parameters of the DKI (MD75th, MD90th, and MK90th) can provide additional value to VI-RADS.

Is the radiomics-clinical combined model helpful in distinguishing between pancreatic cancer and mass-forming pancreatitis?

PURPOSE: To develop CT-based radiomics models for distinguishing between resectable PDAC and mass-forming pancreatitis (MFP) and to provide a non-invasive tool for cases of equivocal imaging findings with EUS-FNA needed. METHODS: A total of 201 patients with resectable PDAC and 54 patients with MFP were included. Development cohort: patients without preoperative EUS-FNA (175 PDAC cases, 38 MFP cases); validation cohort: patients with EUS-FNA (26 PDAC cases, 16 MFP cases). Two radiomic signatures (LASSOscore, PCAscore) were developed based on the LASSO model and principal component analysis. LASSOCli and PCACli prediction models were established by combining clinical features with CT radiomic features. ROC analysis and decision curve analysis (DCA) were performed to evaluate the utility of the model versus EUS-FNA in the validation cohort. RESULTS: In the validation cohort, the radiomic signatures (LASSOscore, PCAscore) were both effective in distinguishing between resectable PDAC and MFP (AUCLASSO = 0.743, 95% CI: 0.590-0.896; AUCPCA = 0.788, 95% CI: 0.639-0.938) and improved the diagnostic accuracy of the baseline onlyCli model (AUConlyCli = 0.760, 95% CI: 0.614-0.960) after combination with variables including age, CA19-9, and the double-duct sign (AUCPCACli = 0.880, 95% CI: 0.776-0.983; AUCLASSOCli = 0.825, 95% CI: 0.694-0.955). The PCACli model showed comparable performance to FNA (AUCFNA = 0.810, 95% CI: 0.685-0.935). In DCA, the net benefit of the PCACli model was superior to that of EUS-FNA, avoiding biopsies in 70 per 1000 patients at a risk threshold of 35%. CONCLUSIONS: The PCACli model showed comparable performance with EUS-FNA in discriminating resectable PDAC from MFP.

Artificial intelligence-assisted ultrasound image analysis to discriminate early breast cancer in Chinese population: a retrospective, multicentre, cohort study.

Background: Early diagnosis of breast cancer has always been a difficult clinical challenge. We developed a deep-learning model EDL-BC to discriminate early breast cancer with ultrasound (US) benign findings. This study aimed to investigate how the EDL-BC model could help radiologists improve the detection rate of early breast cancer while reducing misdiagnosis. Methods: In this retrospective, multicentre cohort study, we developed an ensemble deep learning model called EDL-BC based on deep convolutional neural networks. The EDL-BC model was trained and internally validated on B-mode and color Doppler US image of 7955 lesions from 6795 patients between January 1, 2015 and December 31, 2021 in the First Affiliated Hospital of Army Medical University (SW), Chongqing, China. The model was assessed by internal and external validations, and outperformed radiologists. The model performance was validated in two independent external validation cohorts included 448 lesions from 391 patients between January 1 to December 31, 2021 in the Tangshan People's Hospital (TS), Chongqing, China, and 245 lesions from 235 patients between January 1 to December 31, 2021 in the Dazu People's Hospital (DZ), Chongqing, China. All lesions in the training and total validation cohort were US benign findings during screening and biopsy-confirmed malignant, benign, and benign with 3-year follow-up records. Six radiologists performed the clinical diagnostic performance of EDL-BC, and six radiologists independently reviewed the retrospective datasets on a web-based rating platform. Findings: The area under the receiver operating characteristic curve (AUC) of the internal validation cohort and two independent external validation cohorts for EDL-BC was 0.950 (95% confidence interval [CI]: 0.909-0.969), 0.956 (95% [CI]: 0.939-0.971), and 0.907 (95% [CI]: 0.877-0.938), respectively. The sensitivity values were 94.4% (95% [CI]: 72.7%-99.9%), 100% (95% [CI]: 69.2%-100%), and 80% (95% [CI]: 28.4%-99.5%), respectively, at 0.76. The AUC for accurate diagnosis of EDL-BC (0.945 [95% [CI]: 0.933-0.965]) and radiologists with artificial intelligence (AI) assistance (0.899 [95% [CI]: 0.883-0.913]) was significantly higher than that of the radiologists without AI assistance (0.716 [95% [CI]: 0.693-0.738]; p < 0.0001). Furthermore, there were no significant differences between the EDL-BC model and radiologists with AI assistance (p = 0.099). Interpretation: EDL-BC can identify subtle but informative elements on US images of breast lesions and can significantly improve radiologists' diagnostic performance for identifying patients with early breast cancer and benefiting the clinical practice. Funding: The National Key R&D Program of China.

Avoid non-diagnostic EUS-FNA: a DNN model as a possible gatekeeper to distinguish pancreatic lesions prone to inconclusive biopsy.

OBJECTIVE: This work aimed to explore the utility of CT radiomics with machine learning for distinguishing the pancreatic lesions prone to non-diagnostic ultrasound-guided fine-needle aspiration (EUS-FNA). METHODS: 498 patients with pancreatic EUS-FNA were retrospectively reviewed [Development cohort: 147 pancreatic ductal adenocarcinoma (PDAC); Validation cohort: 37 PDAC]. Pancreatic lesions not PDAC were also tested exploratively. Radiomics extracted from contrast-enhanced CT was integrated with deep neural networks (DNN) after dimension reduction. The receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were performed for model evaluation. And, the explainability of the DNN model was analyzed by integrated gradients. RESULTS: The DNN model was effective in distinguishing PDAC lesions prone to non-diagnostic EUS-FNA (Development cohort: AUC = 0.821, 95% CI: 0.742-0.900; Validation cohort: AUC = 0.745, 95% CI: 0.534-0.956). In all cohorts, the DNN model showed better utility than the logistic model based on traditional lesion characteristics with NRI >0 (p < 0.05). And, the DNN model had net benefits of 21.6% at the risk threshold of 0.60 in the validation cohort. As for the model explainability, gray-level co-occurrence matrix (GLCM) features contributed the most averagely and the first-order features were the most important in the sum attribution. CONCLUSION: The CT radiomics-based DNN model can be a useful auxiliary tool for distinguishing the pancreatic lesions prone to nondiagnostic EUS-FNA and provide alerts for endoscopists preoperatively to reduce unnecessary EUS-FNA. ADVANCES IN KNOWLEDGE: This is the first investigation into the utility of CT radiomics-based machine learning in avoiding non-diagnostic EUS-FNA for patients with pancreatic masses and providing potential pre-operative assistance for endoscopists.

Incremental prognostic value of ADC histogram analysis in patients with high-risk prostate cancer receiving adjuvant hormonal therapy after radical prostatectomy.

Purpose: To investigate the incremental prognostic value of preoperative apparent diffusion coefficient (ADC) histogram analysis in patients with high-risk prostate cancer (PCa) who received adjuvant hormonal therapy (AHT) after radical prostatectomy (RP). Methods: Sixty-two PCa patients in line with the criteria were enrolled in this study. The 10th, 50th, and 90th percentiles of ADC (ADC10, ADC50, ADC90), the mean value of ADC (ADCmean), kurtosis, and skewness were obtained from the whole-lesion ADC histogram. The Kaplan-Meier method and Cox regression analysis were used to analyze the relationship between biochemical recurrence-free survival (BCR-fs) and ADC parameters and other clinicopathological factors. Prognostic models were constructed with and without ADC parameters. Results: The median follow-up time was 53.4 months (range, 41.1-79.3 months). BCR was found in 19 (30.6%) patients. Kaplan-Meier curves showed that lower ADCmean, ADC10, ADC50, and ADC90 and higher kurtosis could predict poorer BCR-fs (all p<0.05). After adjusting for clinical parameters, ADC50 and kurtosis remained independent prognostic factors for BCR-fs (HR: 0.172, 95% CI: 0.055-0.541, p=0.003; HR: 7.058, 95% CI: 2.288-21.773, p=0.001, respectively). By adding ADC parameters to the clinical model, the C index and diagnostic accuracy for the 24- and 36-month BCR-fs were improved. Conclusion: ADC histogram analysis has incremental prognostic value in patients with high-risk PCa who received AHT after RP. Combining ADC50, kurtosis and clinical parameters can improve the accuracy of BCR-fs prediction.

[Curative effect analysis of radical endoscopic sinus surgery for eosinophilic chronic rhinosinusitis with nasal polyps].

Objective:To evaluate the efficacy of functional endoscopic sinus surgery（FESS） and radical endoscopic sinus surgery（RESS） in eosinophilic chronic sinusitis with nasal polyps（EosCRSwNP）. Methods:A total of 44 patients diagnosed with EosCRSwNP in the Department of Otorhinolaryngology Head and Neck Surgery, Henan Provincial People's Hospital from July 1st, 2020 to August 1st, 2021 were included, the percentage of eosinophils in leukocytes in all patients included was more than 3.05%. The patients were randomly divided into FESS group and RESS group according to random number table. The visual analogue scale （VAS） score, Lund-Kennedy score and sino-nasal outcome test-22 （SNOT-22） were compared between the two groups before operation, 1 month, 3 months, 6 months and 1 year after operation. Results:At 1 year after operation, the scores of the two groups were significantly improved compared with those before operation, and the differences were statistically significant （P<0.01）. There were significant differences in nasal endoscopic score, VAS score and SNOT-22 score between the two groups（P=0.01, P=0.03, P=0.03）. The recurrence rate of RESS group was 26.09%（6/23） and that of FESS group was 61.90%（13/21）, and the difference was statistically significant（P=0.04）. Conclusion:Both RESS and FESS can improve nasal symptoms and promote olfactory recovery in EosCRSwNP patients, but RESS has more advantages in reducing recurrence and improving the prognosis of patients.

Non-invasive evaluation of the pathological and functional characteristics of chronic kidney disease by diffusion kurtosis imaging and intravoxel incoherent motion imaging: comparison with conventional DWI.

OBJECTIVE: To explore the diagnostic performance of diffusion kurtosis imaging (DKI) and incoherent intravoxel movement (IVIM) in evaluating the clinical and pathological characteristics in chronic kidney disease (CKD) compared to conventional diffusion-weighted imaging (DWI). METHODS: Forty-nine CKD patients and 24 healthy volunteers were included in this retrospective study from September 2020 to September 2021. All participants underwent MRI examinations before percutaneous renal biopsy. Coronal T2WI, axial T1WI and T2WI, and DWI (including IVIM and DKI) sequences obtained in one scan. We measured the apparent diffusion coefficient (ADC), true diffusion coefficient (Dt), pseudo-diffusion coefficient (Dp), perfusion fraction (fp), mean kurtosis (MK), and mean diffusivity (MD) values. One-way analysis of variance, correlation analysis, and receiver operating characteristic curve analysis were used in our study. RESULTS: Cortex and medulla ADC, MK, Dt, fp were significantly different between the healthy volunteers and CKD stages 1-2 (all p < 0.05). All diffusion parameters showed significant differences between CKD stages 1-2 and CKD stages 3-5 (all p < 0.05). Except for the uncorrelation between MDMedulla and vascular lesion score, all other diffusion parameters were low-to-moderately related to clinical and pathological indicators. fpMedulla was the best parameter to differentiate healthy volunteers from CKD stages 1-2. MKCortex was the best parameter to differentiate CKD stages 1-2 from that CKD stages 3-5. CONCLUSION: Renal cortex and medulla fp, Dt, and MK can provide more valuable information than ADC values for the evaluation of clinical and pathological characteristics of CKD patients, and thus can provide auxiliary diagnosis for fibrosis assessment and clinical management of CKD patients. ADVANCES IN KNOWLEDGE: IVIM and DKI can provide more diagnostic valuable information for CKD patients than conventional DWI.

Noninvasive assessment of renal function and fibrosis in CKD patients using histogram analysis based on diffusion kurtosis imaging.

PURPOSE: To investigate the potential of histogram analysis based on diffusion kurtosis imaging (DKI) in evaluating renal function and fibrosis associated with chronic kidney disease (CKD). MATERIALS AND METHODS: Thirty-six CKD patients were enrolled, and DKI was performed in all patients before the renal biopsy. The histogram parameters of diffusivity (D) and kurtosis (K) were obtained using FireVoxel. The histogram parameters between the stable [estimated glomerular filtration rate (eGFR) ≥ 60 ml/min/1.73 m2] and impaired (eGFR < 60 ml/min/1.73 m2) eGFR group were compared. Besides, patients were classified into mild, moderate, and severe fibrosis group using a semi-quantitative standard. The correlations of histogram parameters with eGFR and fibrosis scores were investigated and the diagnostic performances of histogram parameters in assessing renal dysfunction and fibrosis were analyzed. The added value of combination of most significant parameter with 24 h urinary protein (24 h-UPRO) in evaluating fibrosis was also explored. RESULTS: Seven D histogram parameters in cortex (mean, median, 10th, 25th, 75th, 90th percentiles and entropy), two D histogram parameters in medulla (75th, 90th percentiles), seven K histogram parameters in cortex (mean, min, median, 10th, 25th, 75th, 90th percentiles) and three K histogram parameters in medulla (mean, median, 25th percentile) were significantly different between the two groups. The Dmean of cortex was the most relevant parameter to eGFR (r = 0.648, P < 0.001) and had the largest area under the curve (AUC) for differentiating the stable from impaired eGFR group [AUC = 0.889; 95% confidence interval (CI) 0.728-0.970]. The K90th of cortex presented the strongest correlation with fibrosis scores (r = 0.575, P < 0.001) and achieved the largest AUC for distinguishing the mild from moderate to severe fibrosis group (AUC = 0.849, 95% CI 0.706-0.993). Combining the K90th in cortex with 24 h-UPRO gained statistically higher AUC value (AUC = 0.880, 95% CI 0.763-0.996). CONCLUSION: Histogram analysis based on DKI is practicable for the noninvasive assessment of renal function and fibrosis in CKD patients.

WHO/ISUP grade and pathological T stage of clear cell renal cell carcinoma: value of ZOOMit diffusion kurtosis imaging and chemical exchange saturation transfer imaging.

OBJECTIVES: To evaluate the value of ZOOMit diffusion kurtosis imaging (DKI) and chemical exchange saturation transfer (CEST) imaging in predicting WHO/ISUP grade and pathological T stage in clear cell renal cell carcinoma (ccRCC). METHODS: Forty-six patients with ccRCC were included in this retrospective study. All participants underwent MRI including ZOOMit DKI and CEST. The non-Gaussian mean kurtosis (MK), mean diffusivity (MD), magnetization transfer ratio asymmetry (MTRasym (3.5 ppm)), and Ssat (3.5 ppm)/S0 were analyzed based on different WHO/ISUP grades and pT stages. Binary logistic regression was used to identify the best combination of the parameters. Pearson's correlation coefficients were calculated between CEST and diffusion-related parameters. RESULTS: The ADC, MD, and Ssat (3.5 ppm)/S0 values were significantly lower for higher WHO/ISUP grade tumors, whereas the MK and MTRasym (3.5 ppm) were higher in higher WHO/ISUP grade and higher pT stage tumors. MTRasym (3.5 ppm) combined with MD (AUC, 0.930; 95% CI, 0.858-1.000) showed the best diagnostic efficacy in evaluating the WHO/ISUP grade. MTRasym (3.5 ppm) and MK were mildly positively correlated (r = 0.324, p = 0.028). Ssat (3.5 ppm)/S0 was moderately positively correlated with ADC (r = 0.580, p < 0.001), mildly positively correlated with MD (r = 0.412, p = 0.005), and moderately negatively correlated with MK (r = -0.575, p < .001). CONCLUSION: The microstructural and biochemical assessment of ZOOMit DKI and CEST allowed for the characterization of different WHO/ISUP grades and pT stages in ccRCC. MTRasym (3.5 ppm) combined with MD showed the best diagnostic performance for WHO/ISUP grading. KEY POINTS: • Both diffusion kurtosis imaging (DKI) and chemical exchange saturation transfer (CEST) can be used to predict the WHO/ISUP grade and pathological T stage. • MTRasym (3.5 ppm) combined with MD showed the highest AUC (0.930; 95% CI, 0.858-1.000) in WHO/ISUP grading. • MTRasym at 3.5 ppm showed a positive correlation with mean kurtosis.

Effects of Retroperitoneal or Transperitoneal Pneumoperitoneum on Inferior Vena Cava Hemodynamics and Cardiopulmonary Function: A Prospective Real-Time Comparison.

Objective: To evaluate the effects of CO2 pneumoperitoneum on venous hemodynamics and cardiopulmonary function during transperitoneal or retroperitoneal laparoscopic surgery. Materials and Methods: A single-institution prospective study. Forty-three patients with renal-cell carcinoma undergoing retroperitoneal (22) or transperitoneal (21) laparoscopic partial nephrectomy were enrolled. Hemodynamic functions were monitored by minimally invasive FloTrac/Vigileo system. Transesophageal echocardiography was used to measure the diameter and blood flow of the inferior vena cava (IVC). Measured parameters were recorded at baseline, 10, 30, 60 minutes following insufflation to 14 mm Hg and 10 minutes following desufflation. Results: For hemodynamic changes in the transperitoneal laparoscopic surgery (TPL) and retroperitoneal laparoscopic surgery (RPL), transperitoneal CO2 insufflation resulted in a rapid parallel increase in central intravenous pressure (CVP), peak airway pressure (AWP), and IVC blood flow velocity after the first 30 minutes of pneumoperitoneum (p < 0.05). In contrast, CVP, AWP, and IVC blood flow velocity increased progressively in RPL. The variation of those parameters was significantly lower than that of TRL (p < 0.001; p = 0.002; p = 0.004). The mean maximum CVP in the two groups was 20 and 16 mm Hg, respectively. The IVC diameter at the cavoatrial junction was significantly reduced in TPL after 10 minutes of insufflation, but it remained unchanged in RPL throughout the surgery. For cardiopulmonary function changes, heart output decreased after a short period of pneumoperitoneum, but no statistical differences were observed between the two groups. The increments of partial pressure of arterial carbon dioxide and end-tidal carbon dioxide tension were significantly higher in RPL than TPL (p < 0.001; p < 0.001). Conclusions: Compared with retroperitoneal pneumoperitoneum, transperitoneal pneumoperitoneum has significant effects on IVC hemodynamics. Elevated intra-abdominal pressure (IAP) causes higher AWP and venous return resistance, which lead to the significant increase of CVP during transperitoneal approach. Adjusting the balance between IAP and CVP might be an effective way to control intravenous bleeding. Clinical Trial Registry: Registration number: ChiCTR2000038291.

Whole-Lesion CT Texture Analysis as a Quantitative Biomarker for the Identification of Homogeneous Renal Tumors.

Renal tumors are very common in the urinary system, and the preoperative differential diagnosis of homogeneous renal tumors remains a challenge. This study aimed to evaluate the feasibility of the whole-lesion CT texture analysis for the identification of homogeneous renal tumors including clear cell renal cell carcinoma (ccRCC), chromophobe RCC (chRCC), and renal oncocytoma (RO). This retrospective study was approved by our local IRB. Contrast-enhanced CT examination was performed in 128 patients and histopathologically confirmed ccRCC, chRCC, and RO. The one-way ANOVA test with Bonferroni corrections was used to compare the differences, and the receiver operating characteristic (ROC) curve analysis was applied to determine the diagnostic efficiency. The whole-lesion CT histogram analysis was used to demonstrate significant differences between ccRCC and chRCC in both arterial and venous phases, and the entropy demonstrated excellent performance in discriminating these two types of tumors (AUCs = 0.95, 0.91). The inhomogeneity of ccRCC was significantly higher than that of RO both in arterial and venous phases. The entropy of chRCC was significantly lower than that of RO, and the kurtosis and entropy yielded high sensitivity (91%) and moderate specificity (74%) in the arterial phase. The whole-lesion CT histogram analysis could be useful for the differential diagnosis of homogeneous ccRCC, chRCC, and RO.

CARARIME: Interactive web server for comprehensive analysis of renal allograft rejection in immune microenvironment.

Background: Renal transplantation is a very effective treatment for renal failure patients following kidney transplant. However, the clinical benefit is restricted by the high incidence of organ rejection. Therefore, there exists a wealth of literature regarding the mechanism of renal transplant rejection, including a large library of expression data. In recent years, research has shown the immune microenvironment to play an important role in renal transplant rejection. Nephrology web analysis tools currently exist to address chronic nephropathy, renal tumors and children's kidneys, but no such tool exists that analyses the impact of immune microenvironment in renal transplantation rejection. Methods: To fill this gap, we have developed a web page analysis tool called Comprehensive Analysis of Renal Allograft Rerejction in Immune Microenvironment (CARARIME). Results: CARARIME analyzes the gene expression and immune microenvironment of published renal transplant rejection cohorts, including differential analysis (gene expression and immune cells), prognosis analysis (logistics regression, Univariable Cox Regression and Kaplan Meier), correlation analysis, enrichment analysis (GSEA and ssGSEA), and ROC analysis. Conclusions: Using this tool, researchers can easily analyze the immune microenvironment in the context of renal transplant rejection by clicking on the available options, helping to further the development of approaches to renal transplant rejection in the immune microenvironment field. CARARIME can be found in http://www.cararime.com.