Differentiate Xp11.2 Translocation Renal Cell Carcinoma from Computed Tomography Images and Clinical Data with ResNet-18 CNN and XGBoost

This study aims to apply ResNet-18 convolutional neural network(CNN)and XGBoost to preoperative computed tomography(CT)images and clinical data for distinguishing Xp11.2 translocation renal cell carcinoma(Xp11.2 tRCC)from common subtypes of renal cell carcinoma(RCC)in order to provide patients with individualized treatment plans.Data from45 patients with Xp11.2 tRCC fromJanuary 2007 to December 2021 are collected.Clear cell RCC(ccRCC),papillary RCC(pRCC),or chromophobe RCC(chRCC)can be detected from each patient.CT images are acquired in the following three phases:unenhanced,corticomedullary,and nephrographic.A unified framework is proposed for the classification of renal masses.In this framework,ResNet-18 CNN is employed to classify renal cancers with CT images,while XGBoost is adopted with clinical data.Experiments demonstrate that,if applying ResNet-18 CNN or XGBoost singly,the latter outperforms the former,while the framework integrating both technologies performs similarly or better than urologists.Especially,the possibility of misclassifying Xp11.2 tRCC,pRCC,and chRCC as ccRCC by the proposed framework is much lower than urologists.

Medical imaging for the diagnosis,recurrence and metastasis evaluation of clear cell sarcoma

Clear cell sarcoma(CCS)of soft tissue is extremely rare,accounting for approximately 1%of all soft tissue tumours.It is very difficult to diagnose CCS based on clinical manifestations.Magnetic resonance imaging(MRI)provides highresolution images of soft tissues and pathological features such as mucus,necrosis,bleeding,and fat through high and low signals on T1 weighted image(T1WI)and T2 weighted image(T2WI).On the other hand,the paramagnetism of melanin in CCS shortens the relaxation time of T1 and T2,and high signal intensity on T1WI and low signal intensity on T2WI can be found.This is different from most other soft tissue sarcomas.At present,the treatment method for CCS is surgical resection.MRI can effectively display the tumour edge,extent of surrounding oedema,and extent of fat involvement,which is highly important for guiding surgical resection and predicting postoperative recurrence.As an invasive sarcoma,CCS has a high risk of metastasis.Regardless of the pathological condition of the resected tumour,MRI or computed tomography(CT)should be performed every 1-2 years to assess recurrence at the primary site and to screen for metastasis in the lungs,liver,and bones.If necessary,PET-CT can be performed to evaluate the overall condition of the patient.

Multimodal imaging in the diagnosis of bone giant cell tumors:A retrospective study

BACKGROUND Giant cell tumor of bone is a locally aggressive and rarely metastasizing tumor,and also a potential malignant tumor that may develop into a primary malignant giant cell tumor.AIM To evaluate the role of multimodal imaging in the diagnosis of giant cell tumors of bone.METHODS The data of 32 patients with giant cell tumor of bone confirmed by core-needle biopsy or surgical pathology at our hospital between March 2018 and March 2023 were retrospectively selected.All the patients with giant cell tumors of the bone were examined by X-ray,computed tomography(CT)and magnetic resonance imaging(MRI),and 7 of them were examined by positron emission tomography(PET)-CT.RESULTS X-ray imaging can provide overall information on giant cell tumor lesions.CT and MRI can reveal the characteristics of the internal structure of the tumor as well as the adjacent relationships of the tumor,and these methods have unique advantages for diagnosing tumors and determining the scope of surgery.PET-CT can detect small lesions and is highly valuable for identifying benign and malignant tumors to aid in the early diagnosis of metastasis.CONCLUSION Multimodal imaging plays an important role in the diagnosis of giant cell tumor of bone and can provide a reference for the treatment of giant cell tumors.

Advances of multidetector computed tomography in the characterization and staging of renal cell carcinoma

Renal cell carcinoma(RCC) accounts for approximately 90%-95% of kidney tumors. With the widespread use of cross-sectional imaging modalities, more than half of RCCs are detected incidentally, often diagnosed at an early stage. This may allow the planning of more conservative treatment strategies. Computed tomography(CT) is considered the examination of choice for thedetection and staging of RCC. Multidetector CT(MDCT) with the improvement of spatial resolution and the ability to obtain multiphase imaging, multiplanar and threedimensional reconstructions in any desired plane brought about further improvement in the evaluation of RCC. Differentiation of RCC from benign renal tumors based on MDCT features is improved. Tumor enhancement characteristics on MDCT have been found closely to correlate with the histologic subtype of RCC, the nuclear grade and the cytogenetic characteristics of clear cell RCC. Important information, including tumor size, localization, and organ involvement, presence and extent of venous thrombus, possible invasion of adjacent organs or lymph nodes, and presence of distant metastases are provided by MDCT examination. The preoperative evaluation of patients with RCC was improved by depicting the presence or absence of renal pseudocapsule and by assessing the possible neoplastic infiltration of the perirenal fat tissue and/or renal sinus fat compartment.

Perfusion computed tomography in renal cell carcinoma

Various imaging modalities are available for the diagnosis, staging and response evaluation of patients with renal cell carcinoma(RCC). While contrast enhanced computed tomography(CT) is used as the standard of imaging for size, morphological evaluation and response assessment in RCC, a new functional imaging technique like perfusion CT(p CT), goes down to the molecular level and provides new perspectives in imaging of RCC. p CT depicts regional tumor perfusion and vascular permeability which are indirect parameters of tumor angiogenesis and thereby provides vital information regarding tumor microenvironment. Also response evaluation using p CT may predate the size criteria used in Response Evaluation Criteria in Solid Tumors, as changes in the perfusion occurs earlier following tissue kinase inhibitors before any actual change in size. This may potentially help in predicting prognosis, better selection of therapy and more accurate and better response evaluation in patients with RCC. This article describes the techniques and role of p CT in staging and response assessment in patients with RCCs.

Comparison of pancreatic acinar cell carcinoma and adenocarcinoma using multidetector-row computed tomography

AIM:To distinguish acinar cell carcinoma(ACC)from pancreatic adenocarcinoma(AC)by comparing their computed tomography findings.METHODS:Patients with ACC and AC were identified on the basis of results obtained using surgically resected pancreatectomy specimens.The preoperative computer tomographic images of 6 acinar cell carcinoma patients and 67 pancreatic adenocarcinoma patients in 4 phases(non-contrast,arterial,portal venous,and delayed phase)were compared.The scan delay times were 40,70,and 120 s for each contrast-enhanced phase.The visual pattern,tomographic attenuation value,and time attenuation curve were assessed and compared between AC and ACC cases using the 2test,Wilcoxon signed-rank test,and Mann Whitney U test.RESULTS:The adenocarcinomas tended to be hypodense in all 4 phases.The acinar cell carcinomas also tended to be hypodense in the 3 contrast-enhancedphases,although their computed tomographic attenuation values were higher.Further,5 of the 6 acinar cell carcinomas(83%)were isodense in the non-contrast phase.The time attenuation curve of the adenocarcinomas showed a gradual increase through the 4 phases,and all adenocarcinomas showed peak enhancement during the delayed phase.The time attenuation curve of the acinar cell carcinomas showed peak enhancement during the portal venous phase in 4 cases and during the arterial phase in 2 cases.None of the 6 acinar cell carcinomas showed peak enhancement during the delayed phase.CONCLUSION:The tumor density in the non-contrast phase and time attenuation curve pattern clearly differ between acinar cell carcinomas and adenocarcinomas,and multidetector-row computed tomography can thus distinguish these tumors.

Clinical and computed tomography features of adult abdominopelvic desmoplastic small round cell tumor

To investigate the clinical and computed tomography(CT)features of desmoplastic small round cell tumor(DSRCT),we retrospectively analyzed the clinical presentations,treatment and outcome,as well as CT manifestations of four cases of DSRCT confirmed by surgery and pathology.The CT manifestations of DSRCT were as follows:(1)multiple soft-tissue masses or diffuse peritoneal thickening in the abdomen and pelvis,with the dominant mass usually located in the pelvic cavity;(2)masses without an apparent organbased primary site;(3)mild to moderate homogeneous or heterogeneous enhancement in solid area on enhanced CT;and(4)secondary manifestations,such as ascites,hepatic metastases,lymphadenopathy,hydronephrosis and hydroureter.The prognosis and overall survival rates were generally poor.Commonly used treatment strategies including aggressive tumor resection,polychemotherapy,and radiotherapy,showed various therapeutic effects.CT of DSRCT shows characteristic features that are helpful in diagnosis.Early discovery and complete resection,coupled with postoperative adjuvant chemotherapy,are important for prognosis of DSRCT.Whole abdominopelvic rather than locoregional radiotherapy is more effective for unresectable DSRCT.

Application of computed tomography-based radiomics in differential diagnosis of adenocarcinoma and squamous cell carcinoma at the esophagogastric junction

BACKGROUND The biological behavior of carcinoma of the esophagogastric junction(CEGJ)is different from that of gastric or esophageal cancer.Differentiating squamous cell carcinoma of the esophagogastric junction(SCCEG)from adenocarcinoma of the esophagogastric junction(AEG)can indicate Siewert stage and whether the surgical route for patients with CEGJ is transthoracic or transabdominal,as well as aid in determining the extent of lymph node dissection.With the development of neoadjuvant therapy,preoperative determination of pathological type can help in the selection of neoadjuvant radiotherapy and chemotherapy regimens.AIM To establish and evaluate computed tomography(CT)-based multiscale and multiphase radiomics models to distinguish SCCEG and AEG preoperatively.METHODS We retrospectively analyzed the preoperative contrasted-enhanced CT imaging data of single-center patients with pathologically confirmed SCCEG(n=130)and AEG(n=130).The data were divided into either a training(n=182)or a test group(n=78)at a ratio of 7:3.A total of 1409 radiomics features were separately extracted from two dimensional(2D)or three dimensional(3D)regions of interest in arterial and venous phases.Intra-/inter-observer consistency analysis,correlation analysis,univariate analysis,least absolute shrinkage and selection operator regression,and backward stepwise logical regression were applied for feature selection.Totally,six logistic regression models were established based on 2D and 3D multi-phase features.The receiver operating characteristic curve analysis,the continuous net reclassification improvement(NRI),and the integrated discrimination improvement(IDI)were used for assessing model discrimination performance.Calibration and decision curves were used to assess the calibration and clinical usefulness of the model,respectively.RESULTS The 2D-venous model(5 features,AUC:0.849)performed better than 2D-arterial(5 features,AUC:0.808).The 2D-arterial-venous combined model could further enhance the performance(AUC:0.869).The 3D-venous model(7 features,AUC:0.877)performed better than 3D-arterial(10 features,AUC:0.876).And the 3D-arterial-venous combined model(AUC:0.904)outperformed other single-phase-based models.The venous model showed a positive improvement compared with the arterial model(NRI>0,IDI>0),and the 3D-venous and combined models showed a significant positive improvement compared with the 2D-venous and combined models(P<0.05).Decision curve analysis showed that combined 3D-arterial-venous model and 3D-venous model had a higher net clinical benefit within the same threshold probability range in the test group.CONCLUSION The combined arterial-venous CT radiomics model based on 3D segmentation can improve the performance in differentiating EGJ squamous cell carcinoma from adenocarcinoma.

Computational fluid dynamics simulation of gas-liquid two phases flow in 320 m^3 air-blowing mechanical flotation cell using different turbulence models

According to the recently developed single-trough floating machine with the world's largest volume(inflatable mechanical agitation flotation machine with volume of 320 m3) in China, the gas-fluid two-phase flow in flotation cell was simulated using computational fluid dynamics method. It is shown that hexahedral mesh scheme is more suitable for the complex structure of the flotation cell than tetrahedral mesh scheme, and a mesh quality ranging from 0.7 to 1.0 is obtained. Comparative studies of the standard k-ε, k-ω and realizable k-ε turbulence models were carried out. It is indicated that the standard k-ε turbulence model could give a result relatively close to the practice and the liquid phase flow field is well characterized. In addition, two obvious recirculation zones are formed in the mixing zones, and the pressure on the rotor and stator is well characterized. Furthermore, the simulation results using improved standard k-ε turbulence model show that surface tension coefficient of 0.072, drag model of Grace and coefficient of 4, and lift coefficient of 0.001 can be achieved. The research results suggest that gas-fluid two-phase flow in large flotation cell can be well simulated using computational fluid dynamics method.

SPECTRUM OF FUNCTIONING ISLET CELL TUMOR ON MULTISLICE COMPUTED TOMOGRAPHY:EXPERIENCE ON 70 PATIENTS

Objective To review experience in preoperative detection of islet cell tumors using multislice computed tomography （MSCT） and summarize various imaging features of functioning islet cell tumors on enhanced MSCT. Methods Seventy patients with clinical or pathological diagnosis of functioning pancreatic islet cell tumor between October 2003 and February 2007 were included in this retrospective study. Seventy-four enhanced MSCT scans in these patients were identified. All MSCT scans were interpreted by two experienced radiologists by consensus interpretation. Surgery and pathology reports were used to confirm the diagnosis, localization, and size of tumors. Results Totally, 73 functioning islet cell tumors including 65 benign insulinomas, 2 benign glucagonomas, 3 malignant insulinomas, and 3 malignant glucagonomas were pathologically diagnosed. Tumors in only two cases were not found by MSCT. In 67 benign lesions, 32 showed typical enhancement style, 21 showed prolonged enhancement in portal venous phase, 4 showed delayed enhancement, 4 had iso-dense enhancement with normal pancreatic parenchyma, 2 had no enhancement at all in arterial phase and portal venous phase, and 4 had inhomogeneous enhancement with necrosis or cyst-formation. Patchy or spotty calcifications were found in 3 of the 67 tumors. In 6 malignant islet cell tumors, vessel invasion （2/6） and bowel invasion （1/6） were seen. Different enhancement patterns were shown. All hepatic metastases showed hyper-enhancement during their arterial phase. Conelttsions Pancreatic islet cell tumor may display a wide spectrum of presentations in MSCT. Tumors with unusual appearances often present as diagnostic challenges. Non-contrast and post-contrast multiphase scans are recommended for the localization of functioning islet cell tumors.

Optimization study of a PEM fuel cell performance using 3D multi-phase computational fluid dynamics model

An optimization study using a comprehensive 3D, multi-phase, non-isothermal model of a PEM （proton exchange membrane） fuel cell that incorporates significant physical processes and key parameters affecting fuel cell performance is presented and discussed in detail. The model accounts for both gas and liquid phase in the same computational domain, and thus allows for the implementation of phase change inside the gas diffusion layers. The model includes the transport of gaseous species, liquid water, protons, energy, and water dissolved in the ion-conducting polymer. Water is assumed to be exchanged among three phases： liquid, vapottr, and dissolved, with equilibrium among these phases being assumed. This model also takes into account convection and diffusion of different species in the channels as well as in the porous gas diffusion layer, heat transfer in the solids as well as in the gases, and electrochemical reactions. The results showed that the present multi-phase model is capable of identifying important parameters for the wetting behaviour of the gas diffusion layers and can be used to identify conditions that might lead to the onset of pore plugging, which has a detrimental effect on the fuel cell performance. This model is used to study the effects of several operating, design, and material parameters on fuel cell performance. Detailed analyses of the fuel cell performance under various operating conditions have been conducted and examined.

Coupled computation method of physics fields in aluminum reduction cells

Considering importance of study on physics fields and computer simulation for aluminum reduction cells so as to optimize design on aluminum reduction cells and develop new type of cells, based on analyzing coupled relation of physics fields in aluminum reduction cells, the mathematics and physics models were established and a coupled computation method on distribution of electric current and magnetic field, temperature profile and metal velocity in cells was developed. The computational results in 82 kA prebaked cells agree well with the measured results, and the errors of maxium value calculated for three main physics property fields are less than 10%, which proves that the model and arithmetic are available. So the software developed can be not only applied to optimization design on traditional aluminum reduction cells, but also to establishing better technology basis to develop new drained aluminum reduction cells.

NUMERICAL MODELING OF DUCTILE CRACK EXTENSION USING COMPUTATIONAL CELL ELEMENTS FOR WELDED JOINTS

A 3-D computationalframework was suggested to model stable growth of a macroscopic crack under model I condition. The Gurson-Tverpaaof dilatant plasticity model for voided materials describes the damage process. Fixed-sized, computational cell elements (containing voids) defined over a thin layer at the cmck plane simulate the ductile crack extension. Outside of this layer, the material remains undamaged by the void growth. The micro-mechanics parumeters controlling cmck growth are the thickness Of computational cell layen D, and the initial void porosity, fo. These parameters are calculated through analyses of ductile tearing to match R-curve obtained from testing of deep notch bend specimens for welded joints. The R-curve for the double edge notched tension specimens is eNctively predicted using these pammeters.The predicted R-curve gives a good agreement with the expemment results.

How can we kill cancer cells:Insights from the computational models of apoptosis

Cancer cells are widely known to be protected from apoptosis,a phenomenon that is a major hurdle to successful anticancer therapy.Over-expression of several anti-apoptotic proteins,or mutations in proapoptotic factors,has been recognized to confer such resistance.Development of new experimental strategies,such as in silico modeling of biological pathways,can increase our understanding of how abnormal regulation of apoptotic pathway in cancer cells can lead to tumour chemoresistance.Monte Carlo simulations are in particular well suited to study inherent variability,such as spatial heterogeneity and cell-to-cell variations in signaling reactions.Using this approach,often in combination with experimental validation of the computational model,we observed that large cell-to-cell variability could explain the kinetics of apoptosis,which depends on the type of pathway and the strength of stress stimuli.Most importantly,Monte Carlo simulations of apoptotic signaling provides unexpected insights into the mechanisms of fractional cell killing induced by apoptosis-inducing agents,showing that not only variation in protein levels,but also inherent stochastic variability in signaling reactions,can lead to survival of a fraction of treated cancer cells.

Numerical simulation of a direct internal reforming solid oxide fuel cell using computational fluid dynamics method

A detailed mathematical model of a direct internal reforming solid oxide fuel cell(DIR-SOFC) incorporating with simulation of chemical and physical processes in the fuel cell is presented. The model is developed based on the reforming and electrochemical reaction mechanisms,mass and energy conservation,and heat transfer. A computational fluid dynamics(CFD) method is used for solving the complicated multiple partial differential equations(PDEs) to obtain the numerical approximations. The resulting distributions of chemical species concentrations,temperature and current density in a cross-flow DIR-SOFC are given and analyzed in detail. Further,the influence between distributions of chemical species concentrations,temperature and current density during the simulation is illustrated and discussed. The heat and mass transfer,and the kinetics of reforming and electrochemical reactions have significant effects on the parameter distributions within the cell. The results show the particular characteristics of the DIR-SOFC among fuel cells,and can aid in stack design and control.

Automated Artificial Intelligence Empowered White Blood Cells Classification Model

White blood cells (WBC) or leukocytes are a vital component ofthe blood which forms the immune system, which is accountable to fightforeign elements. The WBC images can be exposed to different data analysisapproaches which categorize different kinds of WBC. Conventionally, laboratorytests are carried out to determine the kind of WBC which is erroneousand time consuming. Recently, deep learning (DL) models can be employedfor automated investigation of WBC images in short duration. Therefore,this paper introduces an Aquila Optimizer with Transfer Learning basedAutomated White Blood Cells Classification (AOTL-WBCC) technique. Thepresented AOTL-WBCC model executes data normalization and data augmentationprocess (rotation and zooming) at the initial stage. In addition,the residual network (ResNet) approach was used for feature extraction inwhich the initial hyperparameter values of the ResNet model are tuned by theuse of AO algorithm. Finally, Bayesian neural network (BNN) classificationtechnique has been implied for the identification of WBC images into distinctclasses. The experimental validation of the AOTL-WBCC methodology isperformed with the help of Kaggle dataset. The experimental results foundthat the AOTL-WBCC model has outperformed other techniques which arebased on image processing and manual feature engineering approaches underdifferent dimensions.

Design and implementation of instruction-driven and data-driven self-reconfigurable cell array

The reconfigurable chip,which integrates the advantages of high performance,high flexibility,high parallelism,low power consumption,and low cost,has achieved rapid development and wide application.Generally,the control part and the computing part of algorithm is accelerated based on different reconfigurable architectures,but it is difficult to obtain overall performance improvement.For improving efficiency of reconfigurable structure both for the control part and the computing part,a hybrid of instruction-driven and data-driven self-reconfigurable cell array is proposed.On instruction-driven mode,processing element(PE)works like a reduced instruction set computer(RSIC)machine,which is mainly for the control part of algorithm.On data-driven mode,data is calculated by flowing between the preconfigured PEs,which is mainly for the computing of algorithm.For verifying the efficiency of architecture,some high-efficiency video coding(HEVC)video compression algorithms are implemented on the proposed architecture.The proposed architecture has been implemented on Xilinx FPGA Virtex UltraScale VU440 develop board.The same circuitry is able to run at75 MHz.Compared with the architecture that only supports instruction-driven,the proposed architecture has better calculation efficiency.

Qualitative visual trichotomous assessment improves the value of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography in predicting the prognosis of diffuse large B-cell lymphoma

Introduction:Fluorine-18 fluorodeoxyglucose(18F-FDG)positron emission tomography/computed tomography(PET/CT)is a powerful tool for monitoring the response of diffuse large B-cell lymphoma(DLBCL)to therapy,but the criteria to interpret PET/CT results remain under debate.We investigated the value of post-treatment PET/CT in predicting the prognosis of DLBCL patients when interpreted according to qualitative visual trichotomous assessment(QVTA)criteria compared with the Deauvil e criteria.Methods:In this retrospective study,final PET/CT scans of DLBCL patients treated with rituximab-based regimens between October 2005 and November 2010 were interpreted using the Deauvil e and QVTA criteria.Survival curves were estimated using Kaplan-Meier analysis and compared using the log-rank test.Results:A total of 253 patients were enrol ed.The interpretation according to the Deauvil e criteria revealed that 181patients had negative PET/CT scan results and 72 had positive results.The 3 year overal survival(OS)rate was significantly higher in patients with negative scan results than in those with positive results(91.6%vs.57.5%,P<0.001).The72 patients with positive scan results according to the Deauville criteria were divided into two groups by the interpretation according to the QVTA criteria:29 had indeterminate results,and 43 had positive results.The 3 year OS rate was significantly higher in patients with indeterminate scan results than in those with positive results(91.2%vs.33.5%,P<0.001)but was similar between patients with negative and indeterminate scan results(91.6%vs.91.2%,P=0.921).Conclusions:Compared with the Deauvil e criteria,using the QVTA criteria for interpreting post-treatment PET/CT scans of DLBCL patients is likely to reduce the number of false positive results.The QVTA criteria are feasible for therapeutic outcome evaluation and can be used to guide risk-adapted therapy.

Rare finding of primary aortoduodenal fistula on single-photon emission computed tomography/computed tomography of gastrointestinal bleeding: A case report

BACKGROUND Primary aortoduodenal fistula is a rare cause of gastrointestinal(GI)bleeding consisting of abnormal channels between the aorta and GI tract without previous vascular intervention that results in massive intraluminal hemorrhage.CASE SUMMARY A 67-year-old man was hospitalized for coffee ground vomiting,tarry stools,and colic abdominal pain.He was repeatedly admitted for active GI bleeding and hypovolemic shock.Intermittent and spontaneously stopped bleeders were undetectable on multiple GI endoscopy,angiography,computed tomography angiography(CTA),capsule endoscopy,and ^(99)mTc-labeled red blood cell(RBC)scans.The patient received supportive treatment and was discharged without signs of rebleeding.Thereafter,he was re-admitted for bleeder identification.Repeated CTA after a bleed revealed a small aortic aneurysm at the renal level contacting the fourth portion of the duodenum.A ^(99)mTc-labeled RBC singlephoton emission CT(SPECT)/CT scan performed during bleeding symptoms revealed active bleeding at the duodenal level.According to his clinical symptoms(intermittent massive GI bleeding with hypovolemic shock,dizziness,dark red stool,and bloody vomitus)and the abdominal CTA and ^(99)mTc-labeled RBC SPECT/CT results,we suspected a small aneurysm and an aortoduodenal fistula.Subsequent duodenal excision and duodenojejunal anastomosis were performed.A 7-mm saccular aneurysm arising from the anterior wall of the abdominal aorta near the left renal artery was identified.Percutaneous intravascular stenting of the abdominal aorta was performed and his symptoms improved.CONCLUSION Our findings suggest that ^(99)mTc-labeled RBC SPECT/CT scanning can aid the diagnosis of a rare cause of active GI bleeding.

Establishment of a prognostic model related to tregs and natural killer cells infiltration in bladder cancer

BACKGROUND Regulatory T cells(Tregs)and natural killer(NK)cells play an essential role in the development of bladder urothelial carcinoma(BUC).AIM To construct a prognosis-related model to judge the prognosis of patients with bladder cancer,meanwhile,predict the sensitivity of patients to chemotherapy and immunotherapy.METHODS Bladder cancer information data was obtained from The Cancer Genome Atlas and GSE32894.The CIBERSORT was used to calculate the immune score of each sample.Weighted gene co-expression network analysis was used to find genes that will have the same or similar expression patterns.Subsequently,multivariate cox regression and lasso regression was used to further screen prognosis-related genes.The prrophetic package was used to predict phenotype from gene expression data,drug sensitivity of external cell line and predict clinical data.RESULTS The stage and risk scores are independent prognostic factors in patients with BUC.Mutations in FGFR3 lead to an increase in Tregs percolation and affect the prognosis of the tumor,and additionally,EMP1,TCHH and CNTNAP3B in the model are mainly positively correlated with the expression of immune checkpoints,while CMTM8,SORT1 and IQSEC1 are negatively correlated with immune checkpoints and the high-risk group had higher sensitivity to chemotherapy drugs.CONCLUSION Prognosis-related models of bladder tumor patients,based on Treg and NK cell percolation in tumor tissue.In addition to judging the prognosis of patients with bladder cancer,it can also predict the sensitivity of patients to chemotherapy and immunotherapy.At the same time,patients were divided into high and low risk groups based on this model,and differences in genetic mutations were found between the high and low risk groups.