Prospective Assessment of Vesical Imaging Reporting and Data System (VI-RADS) and Its Clinical Impact on the Management of High-risk Non–muscle-invasive Bladder Cancer Patients Candidate for Repeated Transurethral Resection

Cancer risk and male Infertility: Unravelling predictive biomarkers and prognostic indicators

In recent years, there has been a global increase in cases of male infertility. There are about 30 million cases of male infertility worldwide and male reproductive health is showing rapid decline in last few decades. It is now recognized as a potential risk factor for developing certain types of cancer, particularly genitourinary malignancies like testicular and prostate cancer. Male infertility is considered a potential indicator of overall health and an early biomarker for cancer. Cases of unexplained male factor infertility have high levels of oxidative stress and oxidative DNA damage and this induces both denovo germ line mutations and epimutations due to build up of 8-hydroxy 2 deoxygunaosine abase which is highly mutagenic and also induces hypomethylation and genomic instability. Consequently, there is growing evidence to explore the various factors contributing to an increased cancer risk. Currently, the available prognostic and predictive biomarkers associated with semen characteristics and cancer risk are limited but gaining significant attention in clinical research for the diagnosis and treatment of elevated cancer risk in the individual and in offspring. The male germ cell being transcriptionally and translationally inert has a highly truncated repair mechanism and has minimal antioxidants and thus most vulnerable to oxidative injury due to environmental factors and unhealthy lifestyle and social habits. Therefore, advancing our understanding requires a thorough evaluation of the pathophysiologic mechanisms at the DNA, RNA, protein, and metabolite levels to identify key biomarkers that may underlie the pathogenesis of male infertility and associated cancer. Advanced methodologies such as genomics, epigenetics, proteomics, transcriptomics, and metabolomics stand at the forefront of cutting-edge approaches for discovering novel biomarkers, spanning from infertility to associated cancer types. Henceforth, in this review, we aim to assess the role and potential of recently identified predictive and prognostic biomarkers, offering insights into the success of assisted reproductive technologies, causes of azoospermia and idiopathic infertility, the impact of integrated holistic approach and lifestyle modifications, and the monitoring of cancer susceptibility, initiation and progression. Comprehending these biomarkers is crucial for providing comprehensive counselling to infertile men and cancer patients, along with their families.

Vesical Imaging-Reporting and Data System (VI-RADS) as a grouping imaging biomarker combined with a decision-tree mode to preoperatively predict the pathological grade of bladder cancer

AIM

To investigate whether the Vesical Imaging-Reporting and Data System (VI-RADS) could be used to develop a new non-invasive preoperative grade-prediction system to partially predict high-grade bladder cancer (HG-BC).

MATERIALS AND METHODS

The present study enrolled 89 primary BC patients prospectively from March 2022 to June 2023. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of VI-RADS for predicting HG-BC and muscle-invasive bladder cancer (MIBC) in the entire group. In the low VI-RADS (≤2) group, the decision tree-based method was used to obtain significant predictors and construct the decision-tree model (DT model). The performance of the DT model and low VI-RADS scores for predicting HG-BC was determined using ROC, calibration, and decision curve analyses.

RESULTS

At a cut-off of ≥3, the specificity and positive predictive value of VI-RADS for predicting HG-BC in the entire group was 100%, and the area under the ROC curve (AUC) was 0.697. Among 65 patients with low VI-RADS scores, the DT model showed an AUC of 0.884 in predicting HG-BC compared to 0.506 for low VI-RADS scores. Calibration and decision curve analyses showed that the DT model performed better than the low VI-RADS scores.

CONCLUSION

Most VI-RADS scores ≥3 correspond to HG-BCs. VI-RADS could be used as a grouping imaging biomarker for a pathological grade-prediction procedure, which in combination with the DT model for low VI-RADS (≤2) populations, would provide a potential preoperative non-invasive method of predicting HG-BC.

Multiparametric MRI for characterization of the tumour microenvironment

Our understanding of tumour biology has evolved over the past decades and cancer is now viewed as a complex ecosystem with interactions between various cellular and non-cellular components within the tumour microenvironment (TME) at multiple scales. However, morphological imaging remains the mainstay of tumour staging and assessment of response to therapy, and the characterization of the TME with non-invasive imaging has not yet entered routine clinical practice. By combining multiple MRI sequences, each providing different but complementary information about the TME, multiparametric MRI (mpMRI) enables non-invasive assessment of molecular and cellular features within the TME, including their spatial and temporal heterogeneity. With an increasing number of advanced MRI techniques bridging the gap between preclinical and clinical applications, mpMRI could ultimately guide the selection of treatment approaches, precisely tailored to each individual patient, tumour and therapeutic modality. In this Review, we describe the evolving role of mpMRI in the non-invasive characterization of the TME, outline its applications for cancer detection, staging and assessment of response to therapy, and discuss considerations and challenges for its use in future medical applications, including personalized integrated diagnostics.

MRI evaluation of vesical imaging reporting and data system for bladder cancer after neoadjuvant chemotherapy

BACKGROUND

The Vesical Imaging-Reporting and Data System (VI-RADS) has demonstrated effectiveness in predicting muscle invasion in bladder cancer before treatment. The urgent need currently is to evaluate the muscle invasion status after neoadjuvant chemotherapy (NAC) for bladder cancer. This study aims to ascertain the accuracy of VI-RADS in detecting muscle invasion post-NAC treatment and assess its diagnostic performance across readers with varying experience levels.

METHODS

In this retrospective study, patients with muscle-invasive bladder cancer who underwent magnetic resonance imaging (MRI) after NAC from September 2015 to September 2018 were included. VI-RADS scores were independently assessed by five radiologists, consisting of three experienced in bladder MRI and two inexperienced radiologists. Comparison of VI-RADS scores was made with postoperative histopathological diagnosis. Receiver operating characteristic curve analysis (ROC) was used for evaluating diagnostic performance, calculating sensitivity, specificity, and area under ROC (AUC)). Interobserver agreement was assessed using the weighted kappa statistic.

RESULTS

The final analysis included 46 patients (mean age: 61 years ± 9 [standard deviation]; age range: 39-70 years; 42 men). The pooled AUC for predicting muscle invasion was 0.945 (95% confidence interval (CI): 0.893-0.977) for experienced readers, and 0.910 (95% CI: 0.831-0.959) for inexperienced readers, and 0.932 (95% CI: 0.892-0.961) for all readers. At an optimal cut-off value ≥ 4, pooled sensitivity and specificity were 74.1% (range: 66.0-80.9%) and 94.1% (range: 88.6-97.7%) for experienced readers, and 63.9% (range: 59.6-68.1%) and 86.4% (range: 84.1-88.6%) for inexperienced readers. Interobserver agreement ranged from substantial to excellent between all readers (k = 0.79-0.92).

CONCLUSIONS

VI-RADS accurately assesses muscle invasion in bladder cancer patients after NAC and exhibits good diagnostic performance across readers with different experience levels.

Clinical application of bladder MRI and the Vesical Imaging-Reporting and Data System

Diagnostic work-up and risk stratification in patients with bladder cancer before and after treatment must be refined to optimize management and improve outcomes. MRI has been suggested as a non-invasive technique for bladder cancer staging and assessment of response to systemic therapy. The Vesical Imaging-Reporting And Data System (VI-RADS) was developed to standardize bladder MRI image acquisition, interpretation and reporting and enables accurate prediction of muscle-wall invasion of bladder cancer. MRI is available in many centres but is not yet recommended as a first-line test for bladder cancer owing to a lack of high-quality evidence. Consensus-based evidence on the use of MRI-VI-RADS for bladder cancer care is needed to serve as a benchmark for formulating guidelines and research agendas until further evidence from randomized trials becomes available.

A Nomogram of MRI Features to Assess Muscle Invasion in VI-RADS 2 Tumors With Stalk

BACKGROUND

Vesical Imaging-Reporting and Data System (VI-RADS) is widely used to assess the muscle-invasive status of bladder cancer. However, the current classification efficacy of VI-RASD 2 tumors of stalk is unsatisfactory.

PURPOSE

To develop a nomogram to assess muscle-invasive bladder cancer (MIBC) in VI-RADS 2 tumors with stalk.

STUDY TYPE

Retrospective.

POPULATION

A total of 186 patients (age: 67.8 ± 12.7 years) with 15.1% females, divided randomly into a training cohort (N = 130) and validation cohort (N = 56).

FIELD STRENGTH/SEQUENCE

3-T, T2-weighted imaging (turbo spin-echo), diffusion-weighted imaging (breathing-free spin-echo), and dynamic contrast-enhanced imaging (gradient-echo).

ASSESSMENT

Twenty-one MRI features of tumors and stalks were developed from training cohort. The mean apparent diffusion coefficient (ADC) values of the tumor, stalk, and psoas muscles were calculated from the three circular regions of interest. The normalized T value = mean ADC tumor mean ADC muscle . The normalized ST value = mean ADC stalk mean ADC tumor . Three readers assessed the morphology of tumors and stalks.

STATISTICAL TESTS

The final features of nomogram were selected by univariable logistic and the least absolute shrinkage and selection operator (LASSO) regression. The performance of the nomogram was assessed by the receiver operating characteristic (ROC) curve, calibration, and decision curve analysis.

RESULTS

In VI-RADS 2 tumors with stalk, tumor size over 3 cm, increased stalk width, stalk morphology, decreased normalized T value, and increased normalized ST value were selected as the risk factors for MIBC. The AUC, accuracy, sensitivity, and specificity of the nomogram to assess MIBC were 0.969 (95% CI: 0.941-0.997), 92.3%, 94.1%, and 92.0% in training cohort and 0.940 (95% CI: 0.859-1.000), 89.3%, 75.0%, and 91.7% in validation cohort.

DATA CONCLUSION

This study constructed a nomogram for preoperative assessment of MIBC and modifying the current VI-RADS.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Enhancing recurrence risk prediction for bladder cancer using multi-sequence MRI radiomics

OBJECTIVE

We aimed to develop a radiomics-clinical nomogram using multi-sequence MRI to predict recurrence-free survival (RFS) in bladder cancer (BCa) patients and assess its superiority over clinical models.

METHODS

A retrospective cohort of 229 BCa patients with preoperative multi-sequence MRI was divided into a training set (n = 160) and a validation set (n = 69). Radiomics features were extracted from T2-weighted images, diffusion-weighted imaging, apparent diffusion coefficient, and dynamic contrast-enhanced images. Effective features were identified using the least absolute shrinkage and selection operator (LASSO) method. Clinical risk factors were determined via univariate and multivariate Cox analysis, leading to the creation of a radiomics-clinical nomogram. Kaplan-Meier analysis and log-rank tests assessed the relationship between radiomics features and RFS. We calculated the net reclassification improvement (NRI) to evaluate the added value of the radiomics signature and used decision curve analysis (DCA) to assess the nomogram's clinical validity.

RESULTS

Radiomics features significantly correlated with RFS (log-rank p < 0.001) and were independent of clinical factors (p < 0.001). The combined model, incorporating radiomics features and clinical data, demonstrated the best prognostic value, with C-index values of 0.853 in the training set and 0.832 in the validation set. Compared to the clinical model, the radiomics-clinical nomogram exhibited superior calibration and classification (NRI: 0.6768, 95% CI: 0.5549-0.7987, p < 0.001).

CONCLUSION

The radiomics-clinical nomogram, based on multi-sequence MRI, effectively assesses the BCa recurrence risk. It outperforms both the radiomics model and the clinical model in predicting BCa recurrence risk.

CRITICAL RELEVANCE STATEMENT

The radiomics-clinical nomogram, utilizing multi-sequence MRI, holds promise for predicting bladder cancer recurrence, enhancing individualized clinical treatment, and performing tumor surveillance.

KEY POINTS

• Radiomics plays a vital role in predicting bladder cancer recurrence. • Precise prediction of tumor recurrence risk is crucial for clinical management. • MRI-based radiomics models excel in predicting bladder cancer recurrence.

Performance of VI-RADS in predicting muscle-invasive bladder cancer after transurethral resection: a single center retrospective analysis

PURPOSE

To assess VIRADS performance and inter-reader agreement for detecting muscle-invasive bladder cancer (MIBC) following transurethral resection of bladder tumor (TURBT).

METHODS

An IRB-approved, HIPAA-compliant, retrospective study from 2016 to 2020 included patients with bladder urothelial carcinoma who underwent MRI after TURBT, and cystectomy within 3 months without post-MRI treatments. Three radiologists blinded to pathology results independently reviewed MR images and assigned a VI-RADS score. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of VI-RADS were assessed for diagnosing MIBC using VI-RADS scores ≥ 3 and ≥ 4. Inter-reader agreement was assessed using Gwet's agreement coefficient (AC) and percent agreement.

RESULTS

The cohort consisted of 70 patients (mean age, 68 years ± 11 [SD]; range 39-85; 58 men) and included 32/70 (46%) with MIBC at cystectomy. ROC analysis revealed an AUC ranging from 0.67 to 0.77 and no pairwise statistical difference between readers (p-values, 0.06, 0.08, 0.97). Percent sensitivity, specificity, PPV, NPV and accuracy for diagnosing MIBC for the three readers ranged from 81.3-93.8, 36.8-55.3, 55.6-60.5, 77.3-87.5, and 62.9-67.1 respectively for VI-RADS score ≥ 3, and 78.1-81.3, 47.4-68.4, 55.6-67.6, 72.0-78.8 and 61.4-72.9 respectively for VI-RADS score ≥ 4. Gwet's AC was 0.63 [95% confidence interval (CI): 0.49,0.78] for VI-RADS score ≥ 3 with 79% agreement [95% CI 72,87] and 0.54 [95%CI 0.38,0.70] for VI-RADS score ≥ 4 with 76% agreement [95% CI 69,84]. VIRADS performance was not statistically different among 31/70 (44%) patients who received treatments prior to MRI (p ≥ 0.16).

CONCLUSION

VI-RADS had moderate sensitivity and accuracy but low specificity for detection of MIBC following TURBT, with moderate inter-reader agreement.

Practical Guide to VI-RADS: MRI Protocols, Lesion Characterization, and Pitfalls

Urothelial carcinoma is the most common type of bladder cancer (BC), accounting for approximately 90% of all cases. Evaluating the depth of tumor invasion in the bladder wall (tumor staging) is essential for determining the treatment and prognosis in patients with BC. Neoadjuvant therapy followed by radical cystectomy is the most common treatment of localized muscle-invasive BC (MIBC). Therefore, it is vital to differentiate non-MIBC from MIBC. Transurethral resection of bladder tumor (TURBT) is the reference standard to determine the extent of tumor invasion into the bladder wall through tissue sampling. However, this diagnostic and therapeutic method may not adequately sample the muscularis propria, leading to a higher risk of residual disease, early recurrence, and tumor understaging in approximately 50% of patients during the initial TURBT. Multiparametric MRI can overcome some of the limitations of TURBT when evaluating BC, particularly regarding tumor staging. In this context, the Vesical Imaging Reporting and Data System (VI-RADS) classification was developed to establish standards for bladder multiparametric MRI and interpretation. It uses a 5-point scale to assess the likelihood of detrusor muscle invasion. T2-weighted MR images are particularly useful as an initial guide, especially for categories 1-3, while the presence of muscular invasion is determined with diffusion-weighted and dynamic contrast-enhanced sequences. Diffusion-weighted imaging takes precedence as the dominant method when optimal image quality is achieved. The presence of a stalk or a thickened inner layer and no evidence of interruption of the signal intensity of the muscular layer are central for predicting a low likelihood of muscle invasion. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Hoegger in this issue.

A novel predict method for muscular invasion of bladder cancer based on 3D mp-MRI feature fusion

Objective. To assist urologist and radiologist in the preoperative diagnosis of non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC), we proposed a combination models strategy (CMS) utilizing multiparametric magnetic resonance imaging.Approach. The CMS includes three components: image registration, image segmentation, and multisequence feature fusion. To ensure spatial structure consistency of T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced imaging (DCE), a registration network based on patch sampling normalized mutual information was proposed to register DWI and DCE to T2WI. Moreover, to remove redundant information around the bladder, we employed a segmentation network to obtain the bladder and tumor regions from T2WI. Using the coordinate mapping from T2WI, we extracted these regions from DWI and DCE and integrated them into a three-branch dual-channel input. Finally, to fully fuse low-level and high-level features of T2WI, DWI, and DCE, we proposed a distributed multilayer fusion model for preoperative MIBC prediction with five-fold cross-validation.Main results. The study included 436 patients, of which 404 were for the internal cohort and 32 for external cohort. The MIBC was confirmed by pathological examination. In the internal cohort, the area under the curve, accuracy, sensitivity, and specificity achieved by our method were 0.928, 0.869, 0.753, and 0.929, respectively. For the urologist and radiologist, Vesical Imaging-Reporting and Data System score >3 was employed to determine MIBC. The urologist demonstrated an accuracy, sensitivity, and specificity of 0.842, 0.737, and 0.895, respectively, while the radiologist achieved 0.871, 0.803, and 0.906, respectively. In the external cohort, the accuracy of our method was 0.831, which was higher than that of the urologist (0.781) and the radiologist (0.813).Significance. Our proposed method achieved better diagnostic performance than urologist and was comparable to senior radiologist. These results indicate that CMS can effectively assist junior urologists and radiologists in diagnosing preoperative MIBC.

Progress of Multiparameter Magnetic Resonance Imaging in Bladder Cancer: A Comprehensive Literature Review

Magnetic resonance imaging (MRI) has been proven to be an indispensable imaging method in bladder cancer, and it can accurately identify muscular invasion of bladder cancer. Multiparameter MRI is a promising tool widely used for preoperative staging evaluation of bladder cancer. Vesical Imaging-Reporting and Data System (VI-RADS) scoring has proven to be a reliable tool for local staging of bladder cancer with high accuracy in preoperative staging, but VI-RADS still faces challenges and needs further improvement. Artificial intelligence (AI) holds great promise in improving the accuracy of diagnosis and predicting the prognosis of bladder cancer. Automated machine learning techniques based on radiomics features derived from MRI have been utilized in bladder cancer diagnosis and have demonstrated promising potential for practical implementation. Future work should focus on conducting more prospective, multicenter studies to validate the additional value of quantitative studies and optimize prediction models by combining other biomarkers, such as urine and serum biomarkers. This review assesses the value of multiparameter MRI in the accurate evaluation of muscular invasion of bladder cancer, as well as the current status and progress of its application in the evaluation of efficacy and prognosis.

Vesical Imaging-Reporting and Data System use predicting the outcome of neoadjuvant pembrolizumab in muscle-invasive bladder cancer

OBJECTIVE

To evaluate the predictive capability of the pre- and post-pembrolizumab Vesical Imaging-Reporting and Data System (VI-RADS) to identify ypT0N0 or ypT≤1N0 response in muscle-invasive bladder cancer (MIBC) within the PURE-01 trial (ClinicalTrials.gov identifier: NCT02736266).

PATIENTS AND METHODS

Patients were staged with bladder multiparametric magnetic resonance imaging (mpMRI) before and after treatment (three cycles of pembrolizumab) prior to radical cystectomy (RC). Logistic regression models were used to analyse the pre- and post- pembrolizumab VI-RADS against ypT≤1N0 and ypT0N0 response. The VI-RADS scores were dichotomised between 0 and 3 (0 = no evidence of disease) and 4-5. Event-free survival (EFS) and overall survival (OS) analyses were performed. Comprehensive genomic profiling and transcriptome-wide expression profiling data were matched with the VI-RADS scores.

RESULTS

In total, 110 patients underwent centrally reviewed scans (N = 220 mpMRI), treated between February 2017 and July 2020. Both pre- and post-pembrolizumab VI-RADS 0-3 scores were the only significant covariates that predicted the ypT≤1N0 endpoint in multivariable analyses, and the strongest effect was seen with post-pembrolizumab VI-RADS 0-3 predicting the ypT≤1N0 response (P < 0.001). The area under the curve for this model was 0.90. Post-pembrolizumab VI-RADS 0-3 also predicted a longer EFS (P < 0.001) and OS (P = 0.044). The scores of several gene signatures from baseline tumours differed between the pre-pembrolizumab VI-RADS 0-3 and 4-5 categories.

CONCLUSION

Post-pembrolizumab VI-RADS scores are strongly associated with pathological downstaging and survival. VI-RADS scores were also characterised by distinct biomarker features. These results indicate that the VI-RADS is emerging as an important tool for designing next-generation trials for MIBC.

Biparametric versus Multiparametric Magnetic Resonance Imaging for Assessing Muscle Invasion in Bladder Urothelial Carcinoma with Variant Histology Using the Vesical Imaging-Reporting and Data System

BACKGROUND

The diagnostic performance of contrast medium-free biparametric magnetic resonance imaging (bpMRI; combining T2-weighted imaging [T2WI] and diffusion-weighted imaging [DWI]) for evaluating variant-histology urothelial carcinoma (VUC) remains unknown.

OBJECTIVE

To compare the diagnostic performance of bpMRI and multiparametric MRI (mpMRI; combining T2WI, DWI, and dynamic contrast-enhanced MRI]) for assessing muscle invasion of VUC.

DESIGN, SETTING, AND PARTICIPANTS

This multi-institution retrospective analysis included 118 patients with pathologically verified VUC who underwent bladder mpMRI before transurethral bladder tumor resection between 2010 and 2019.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Three board-certified radiologists separately evaluated two sets of images, set 1 (bpMRI) and set 2 (mpMRI), in accordance with the Vesical Imaging Reporting and Data System (VI-RADS). The histopathology results were utilized as a reference standard. Receiver operating characteristic curve analysis, Z test, and Wald test were used to assess diagnostic abilities.

RESULTS AND LIMITATIONS

Sixty-six (55.9%) and 52 (44.1%) of the 118 patients with VUC included in the analysis (mean age, 71 ± 10 yr; 88 men) had muscle-invasive bladder cancer (MIBC) and non-MIBC, respectively. For the diagnosis of MIBC, the areas under the curve for bpMRI were significantly smaller than those for mpMRI (0.870-0.884 vs 0.902-0.923, p < 0.05). The sensitivity of bpMRI was significantly lower than that of mpMRI for all readers with a VI-RADS cutoff score of 4 (65.2-66.7% vs 77.3-80.3%, p < 0.05). The specificity of bpMRI and mpMRI did not differ significantly for all readers (88.5-90.4 vs 88.5-92.3, p > 0.05). A limitation of the study is the limited sample size because of the rarity of VUC.

CONCLUSIONS

In patients with VUC, on applying VI-RADS, the diagnostic results of bpMRI were inferior to those of mpMRI for evaluating muscle invasion. Therefore, mpMRI-based methods are recommended for evaluating muscle invasiveness of VUC.

PATIENT SUMMARY

Contrast medium-free biparametric magnetic resonance imaging (bpMRI)-based Vesical Imaging Reporting and Data System (VI-RADS) can accurately diagnose pure urothelial carcinomas, similar to conventional multiparametric magnetic resonance imaging-based VI-RADS. However, bpMRI-based VI-RADS may misdiagnose muscle invasiveness of urothelial carcinoma with variant histology, particularly when its cutoff score is 4.

Vesical imaging reporting and data system (VI-RADS) could predict the survival of bladder-cancer patients who received radical cystectomy

Vesical Imaging Reporting and Data System (VI-RADS) shows good potential in determining muscle-invasive bladder cancer (MIBC) patients. However, whether VI-RADS could predict the prognosis of radical cystectomy (RC) patients has not been reported. Our purpose is to determine whether VI-RADS contributed to predict oncologic outcomes. In this retrospective study, we analysed the information of bladder cancer patients who admitted to our centre from June 2012 to June 2022. All patients who underwent multiparametric magnetic resonance imaging (mpMRI) and underwent RC were included. VI-RADS scoring was performed by two radiologists blinded to the clinical data. Patients' clinical features, pathology data, and imaging information were recorded. Kaplan-Meier method was used to estimate patients' overall survival (OS) and progression-free survival (PFS). Log-rank test was used to assess statistical differences. COX regression analysis was used to estimate risk factors. Ultimately, we included 219 patients, with 188 males and 31 females. The median age was 66 (IQR = 61-74.5) years. The VI-RADS scores were as follows: VI-RADS 1, 4 (1.8%); VI-RADS 2, 68 (31.1%); VI-RADS 3, 40 (18.3%); VI-RADS 4, 69 (31.5%); and VI-RADS 5, 38 (17.4%). Patients with VI-RADS ≥ 3 had poorer OS and PFS than those with VI-RADS < 3. The AUC of VI-RADS predicting 3-year OS was 0.804, with sensitivity of 0.824 and negative predictive value of 0.942. Multivariate COX analysis showed that VI-RADS ≥ 3 was risk factors for OS (HR = 3.517, P = 0.003) and PFS (HR = 4.175, P < 0.001). In the MIBC subgroup, patients with VI-RADS ≥ 4 had poorer OS and PFS. In the non-muscle invasive bladder cancer (NMIBC) subgroup, the prognosis of patients with VI-RADS ≥ 3 remained poorer. VI-RADS scores could effectively predict the survival of patients after RC.

Can magnetic resonance imaging differentiate muscle invasion (T2) and lamina propria invasion (T1) urothelial carcinoma of the bladder? A systematic review and meta-analysis of Vesical Imaging-Reporting and Data System accuracy

Background

Vesical Imaging-Reporting and Data System (VI-RADS) was developed as a structured reporting tool to anticipate the possibility of muscle invasion. This study is aimed to investigate the diagnostic accuracy of VI-RADS for discriminating T2 from T1 bladder cancer.

Materials and methods

Scopus, Web of Science, PubMed, and Embase were searched on October 4, 2021, for studies with the following characteristics: (1) bladder cancer patient population, (2) VI-RADS as an index test, (3) retransurethral resection of bladder tumor/cystectomy as a reference, and (4) adequate VI-RADS score data for T1 and T2 lesions. The analyses were performed using the binary regression model of MIDAS in Stata.

Results

Six studies with 624 magnetic resonance imaging reports were included. The receiver operating characteristics curve for differentiation of T2 from T1 bladder cancer showed an area under the curve of 0.93 (95% confidence interval [CI], 0.91-0.95) for a VI-RADS ≥3 and 0.75 (95% CI, 0.71-0.79) for a VI-RADS ≥4. A VI-RADS ≥3 showed high sensitivity of 93% (95% CI, 85%-97%), specificity of 61% (95% CI, 30%-86%), positive likelihood ratio of 2.4 (95% CI, 1.1-5.3), and negative likelihood ratio of 0.11 (95% CI, 0.05-0.24). A total of 10.4% of T2 lesions were scored as VI-RADS 2, while 10% of T1 lesions were scored as VI-RADS 4 or 5.

Conclusions

The VI-RADS ≥3 has high accuracy and sensitivity for detecting muscle invasion in borderline populations of T1 or T2 bladder cancer. Thus, the VI-RADS could be a good non-invasive screening test for the detection of T2 urothelial lesions.

Targeted therapies in bladder cancer: signaling pathways, applications, and challenges

Bladder cancer (BC) is one of the most prevalent malignancies in men. Understanding molecular characteristics via studying signaling pathways has made tremendous breakthroughs in BC therapies. Thus, targeted therapies including immune checkpoint inhibitors (ICIs), antibody-drug conjugates (ADCs), and tyrosine kinase inhibitor (TKI) have markedly improved advanced BC outcomes over the last few years. However, the considerable patients still progress after a period of treatment with current therapeutic regimens. Therefore, it is crucial to guide future drug development to improve BC survival, based on the molecular characteristics of BC and clinical outcomes of existing drugs. In this perspective, we summarize the applications and benefits of these targeted drugs and highlight our understanding of mechanisms of low response rates and immune escape of ICIs, ADCs toxicity, and TKI resistance. We also discuss potential solutions to these problems. In addition, we underscore the future drug development of targeting metabolic reprogramming and cancer stem cells (CSCs) with a deep understanding of their signaling pathways features. We expect that finding biomarkers, developing novo drugs and designing clinical trials with precisely selected patients and rationalized drugs will dramatically improve the quality of life and survival of patients with advanced BC.

A machine learning model based on MRI for the preoperative prediction of bladder cancer invasion depth

OBJECTIVES

To construct and validate a prediction model based on full-sequence MRI for preoperatively evaluating the invasion depth of bladder cancer.

METHODS

A total of 445 patients with bladder cancer were divided into a seven-to-three training set and test set for each group. The radiomic features of lesions were extracted automatically from the preoperative MRI images. Two feature selection methods were performed and compared, the key of which are the Least Absolute Shrinkage and Selection Operator (LASSO) and the Max Relevance Min Redundancy (mRMR). The classifier of the prediction model was selected from six advanced machine-learning techniques. The receiver operating characteristic (ROC) curves and the area under the curve (AUC) were applied to assess the efficiency of the models.

RESULTS

The models with the best performance for pathological invasion prediction and muscular invasion prediction consisted of LASSO as the feature selection method and random forest as the classifier. In the training set, the AUC of the pathological invasion model and muscular invasion model were 0.808 and 0.828. Furthermore, with the mRMR as the feature selection method, the external invasion model based on random forest achieved excellent discrimination (AUC, 0.857).

CONCLUSIONS

The full-sequence models demonstrated excellent accuracy for preoperatively predicting the bladder cancer invasion status.

CLINICAL RELEVANCE STATEMENT

This study introduces a full-sequence MRI model for preoperative prediction of the depth of bladder cancer infiltration, which could help clinicians to recognise pathological features associated with tumour infiltration prior to invasive procedures.

KEY POINTS

• Full-sequence MRI prediction model performed better than Vesicle Imaging-Reporting and Data System (VI-RADS) for preoperatively evaluating the invasion status of bladder cancer. • Machine learning methods can extract information from T1-weighted image (T1WI) sequences and benefit bladder cancer invasion prediction.

Tumor contact length with bladder wall provides effective risk stratification for lesions with a VIRADS score of 2-3

OBJECTIVES

To evaluate the diagnostic performance of the tumor contact length (TCL) in the prediction of MIBC (muscle-invasive bladder cancer) in lesions corresponding to the vesical imaging-reporting and data system (VIRADS) score 2-3.

METHODS

This is a single institution, retrospective study targeting 191 consecutive patients assigned of VIRADS score 2-3, who had pre-transurethral resection MRI from July 2019 to September 2021. Logistic regression analyses were performed to determine meaningful predictors of MIBC for this score group, and a nomogram was plotted with those variables. The diagnostic performance of each predictor was compared at predefined thresholds (VIRADS score 3 and TCL 3 cm) using the generalized linear model and ROC analysis.

RESULTS

Both VIRADS score and TCL remained independent predictors of MIBC for this score group (odds ratio 7.3 for VIRADS score, and 1.3 for TCL, p < 0.01 for both). The contribution of TCL to the probability of MIBC in the nomogram was greater than that of the VIRADS score. VIRADS score had a sensitivity of 0.54 (14/26), specificity of 0.92 (203/221), and diagnostic accuracy of 0.88 (217/247), and TCL showed a sensitivity of 0.89 (23/26), specificity of 0.95 (209/221), and diagnostic accuracy of 0.94 (232/247). The difference in sensitivity (p = 0.03) and accuracy (p = 0.04) was statistically significant. The AUC was also significantly wider for TCL than for VIRADS (0.97 vs. 0.73, p < 0.01).

CONCLUSION

A simple index, TCL, may be helpful in further risk stratification for MIBC in patients with a score of VIRADS 2-3.

CLINICAL RELEVANCE STATEMENT

For bladder cancer patients with insufficient qualitative evidence of muscle layer invasion using VIRADS categorization, TCL, a simple quantitative indicator defined as the curvilinear contact length between the bladder wall and the tumor, may be helpful in risk stratification.

KEY POINTS

• Even when only lesions with score 2-3 were targeted, VIRADS was still a meaningful indicator of MIBC. • With a predefined threshold of 3 cm applied, TCL outperformed VIRADS in the score 2-3 group, in predicting MIBC. • A longer TCL for a lesion with a VIRADS score 2 may warrant an additional warning for MIBC, whereas a shorter TCL for a lesion with a score 3 may indicate a lower risk of MIBC.

Development and Validation of an MRI-Based Nomogram for Preoperative Detection of Muscle Invasion in VI-RADS 3

BACKGROUND

The relationship between tumor and muscle layer in the vesical imaging-reporting and data system (VI-RADS) 3 is ambiguous, and there is a lack of preoperative and non-invasive procedures to detect muscle invasion in VI-RADS 3.

PURPOSE

To develop a nomogram based on MRI features for detecting muscle invasion in VI-RADS 3.

STUDY TYPE

Retrospective.

POPULATION

235 cases (Age: 67.5 ± 11.5 years) with 11.9% females were randomly divided into a training cohort (n = 164) and a validation cohort (n = 71).

FIELD STRENGTH/SEQUENCE

3T, T2-weighted imaging (turbo spin-echo), diffusion-weighted imaging (breathing-free spin echo), and dynamic contrast-enhanced imaging (gradient echo).

ASSESSMENT

3 features were selected from the training cohort, including tumor contact length greater than maximum tumor diameter (TCL > Dmax), flat tumor morphology, and lower standard deviation of apparent diffusion coefficient (ADCSD ). Three readers assessed VI-RADS scores and the tumor morphology.

STATISTICAL TESTS

Interobserver agreement was assessed by Kappa analysis. Features for final analysis were selected by logistic regression. The performance of the nomogram was evaluated by the receiver operating characteristic curve, decision curve analysis, and calibration curve.

RESULTS

TCL > Dmax, flat morphology, and lower ADCSD were the independent risk factors for muscle invasive in VI-RADS 3. The AUCs, accuracy, sensitivity, and specificity of the nomogram 1 composed of three features for detecting muscle invasion were 0.852 (95% CI: 0.793-0.912), 0.756, 0.917, and 0.663 in the training cohort, and 0.885 (95% CI: 0.801-0.969), 0.817, 0.900, and 0.784 in the validation cohort. The nomogram 2 without ADCSD has nearly the same performance as the nomogram 1.

DATA CONCLUSION

Nomogram can be an efficient tool for preoperative detection of muscle invasion in VI-RADS 3.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Application of nanotechnology in bladder cancer diagnosis and therapeutic drug delivery

Bladder cancer (BC) is one of the most common malignant tumors in the urinary system, and its high recurrence rate is a great economic burden to patients. Traditional diagnosis and treatment methods have the disadvantages of insufficient targeting, obvious side effects and low sensitivity, which seriously limit the accurate diagnosis and efficient treatment of BC. Due to their small size, easy surface modification, optical properties such as plasmon resonance, and surface enhanced Raman scattering, good electrical conductivity and photothermal conversion properties, nanomaterials have great potential application value in the realization of specific diagnosis and targeted therapy of BC. At present, the application of nanomaterials in the diagnosis and treatment of BC is attracting great attention and achieving rich research results. Therefore, this paper summarizes the recent research on nanomaterials in the diagnosis and treatment of BC, clarifies the existing advantages and disadvantages, and provides theoretical guidance for promoting the accurate diagnosis and efficient treatment of BC.

Novel utility of Vesical Imaging-Reporting and Data System in multimodal treatment for muscle-invasive bladder cancer

OBJECTIVES

To examine the clinical significance of the Vesical Imaging-Reporting and Data System (VI-RADS) in predicting outcome of multimodal treatment (MMT) in muscle-invasive bladder cancer (MIBC) patients.

METHODS

We reviewed 78 pathologically proven MIBC patients who underwent MMT including transurethral resection and chemoradiotherapy, followed by partial or radical cystectomy. Treatment response was assessed through histologic evaluation of cystectomy specimens. Two radiologists categorized the index lesions of pretherapeutic MRI according to the 5-point VI-RADS score. The associations of VI-RADS score with the therapeutic effect of MMT were analyzed. The diagnostic performance of VI-RADS scores with a cut-off VI-RADS scores  ≤ 2 or ≤ 3 for predicting pathologic complete response to MMT (MMT-CR) was evaluated.

RESULTS

MMT-CR was achieved in 2 (100%) of VI-RADS score 1 (n = 2), 16 (84%) of score 2 (n = 19), 12 (86%) of score 3 (n = 14), 7 (64%) of score 4 (n = 11), and 14 (44%) of score 5 (n = 32). VI-RADS score was inversely associated with the incidence of MMT-CR (p = 0.00049). The cut-off VI-RADS score  ≤ 2 and  ≤ 3 could predict the favorable therapeutic outcome of MMT with high specificity (0.89 with 95% confidence interval [CI]: 0.71-0.98 and 0.82 with 95% CI: 0.62-0.94, respectively) and high positive predictive value (0.86 with 95% CI: 0.64-0.97 and 0.86 with 95% CI: 0.70-0.95, respectively).

CONCLUSION

VI-RADS score may serve as an imaging marker in MIBC patients for predicting the therapeutic outcome of MMT.

CLINICAL RELEVANCE STATEMENT

Muscle-invasive bladder cancer patients with a lower Vesical Imaging-Reporting and Data System score can be a good candidate for bladder-sparing treatment incorporating multimodal treatment.

KEY POINTS

• Vesical Imaging-Reporting and Data System (VI-RADS) score was potentially valuable for classifying pathologic tumor response in patients with muscle-invasive bladder cancer. • The likelihood of achieving complete response of multimodal treatment (MMT) decreased with increasing VI-RADS score. • VI-RADS score could serve as an imaging marker that optimizes patient selection for MMT.

A Brief Review of Artificial Intelligence in Genitourinary Oncological Imaging

Genitourinary (GU) system is among the most commonly involved malignancy sites in the human body. Imaging plays a crucial role not only in diagnosis of cancer but also in disease management and its prognosis. However, interpretation of conventional imaging methods such as CT or MR imaging (MRI) usually demonstrates variability across different readers and institutions. Artificial intelligence (AI) has emerged as a promising technology that could improve the patient care by providing helpful input to human readers through lesion detection algorithms and lesion classification systems. Moreover, the robustness of these models may be valuable in automating time-consuming tasks such as organ and lesion segmentations. Herein, we review the current state of imaging and existing challenges in GU malignancies, particularly for cancers of prostate, kidney and bladder; and briefly summarize the recent AI-based solutions to these challenges.

Pathologic collision of urinary bladder urothelial carcinoma with small cell carcinoma: a case report

BACKGROUND

Urothelial carcinoma is a major subtype of bladder cancer and small cell carcinoma (SCC) is a rare type of cancer in clinical practice. Pathologic collision of urinary bladder urothelial carcinoma with SCC is not common in clinical settings.

CASE PRESENTATION

Here, we report a patient with high-grade papillary carcinoma which changed to collision tumor with SCC. The patient underwent radical cystectomy; however, neck and mediastinum lymph nodes metastases were detected 11 months after the operation. The lymph nodes were diagnosed pathologically as SCC. Chemoradiotherapy was subsequently prescribed. Unfortunately, this patient died of COVID-19 in early 2023.

DISCUSSION

We hypothesized the mechanism underlying this pathological transformation. For patients with urothelial bladder cancer, pathological analysis should be conducted to allow standardized and persistent treatment. Moreover, drugs should be selected depending on the type of pathology, especially for patients who develop relapse, since collision tumor or other pathological tumors may be present.

CONCLUSIONS

We recommend that radical cystectomy be performed early enough for patients with non-muscle invasive bladder cancer, who are at a high risk of tumor recurrence. However, this conclusion needs to be validated in a larger number of patients.

A proof-of-concept study on endoscopic ultrasound-guided biopsy of detrusor muscle in porcine bladders

Introduction

Conventionally, we rely on transurethral resection of bladder tumour (TURBT) for local staging of muscle-invasive bladder cancer (MIBC). However, the procedure is limited by its staging inaccuracy which may delay the definitive treatment of MIBC.

Methods

We conducted a proof-of concept study on endoscopic ultrasound (EUS)-guided biopsy of detrusor muscle in porcine bladders. Five porcine bladders were used in this experiment. Upon EUS, four layers of tissue including the mucosa (hypoechoic), submucosa (hyperechoic), detrusor muscle (hypoechoic) and serosa (hyperechoic) could be identified.

Results

A total of 37 EUS-guided biopsies were taken from 15 sites (three sites per bladder), and the mean number of biopsies taken from each site was 2.47±0.64. Among the 37 biopsies, 30 of them (81.1%) obtained detrusor muscle in the biopsy specimen. For the per biopsy site analysis, detrusor muscle was obtained in 73.3% if only one biopsy was taken, and 100% if two or more biopsies were taken from the same biopsy site. Overall, detrusor muscle was successfully obtained from all 15 biopsy sites (100%). No bladder perforation was observed throughout all biopsy processes.

Conclusion

EUS-guided biopsy of the detrusor muscle could be performed during the initial cystoscopy session, thus expediting the histological diagnosis and subsequent treatment of MIBC.

Is high accuracy of Vesical Imaging-Reporting and Data System (VI-RADS) sufficient for its implementation in the urological practice?

AIMS

Currently, the only method used to differentiate between MIBC and NMIBC is transurethral resection of the bladder tumour (TURBT). Magnetic resonance and Vesical Imaging-Reporting and Data System (VI-RADS) would allow for discrimination between NMIBC and MIBC. We evaluate the sensitivity and specificity of VI-RADS in the diagnosis of muscle-invasive bladder cancer and discuss its value in everyday urological practice.

METHODS

64 patients with bladder cancer (BC) were enrolled into this prospective study. Multiparametric magnetic resonance imaging (mpMRI) was performed before transurethral resection of the bladder tumour (TURBT) and evaluated using the VI-RADS score. Score were compared to histopathology results. We evaluated the sensitivity, specificity, positive and negative predictive value of this system using both cut-off VI-RADS ≥ 3 and ≥ 4.

RESULTS

Sensitivity of 92.3% (95%CI: 64.0; 99.8), specificity of 81.4% (95%CI: 69.1; 90.3), positive predictive value of 52.2% (95%CI: 30.6; 73.2) and negative predictive value of 98.0% (95%CI: 89.1; 99.9) was determined using cut off VI-RADS ≥ 3, while sensitivity of 76.9% (95%CI: 46.2; 95.0), specificity of 91.5% (95%CI: 81.3; 97.2), positive predictive value of 66.7% (95%CI: 38.4; 88.2), and negative predictive value of 94.7% (95%CI: 85.4; 98.9) was determined using cut-off VI-RADS ≥ 4. Based on our results, we consider the optimal cut-off point to be VI-RADS ≥ 3 with the overall prediction accuracy of 83.3% (95%CI: 72.7; 91.1).

CONCLUSIONS

We acknowledge that mpMRI provides valuable information with regard to BC staging, however, despite its high overall accuracy, we do not consider the VI-RADS could replace TURBT in discrimination between non-muscle invasive and MIBC.

To determine correlation between VIRADS scoring and pathological staging in bladder cancer: A prospective study and review of literature

The development of standardized reporting systems is of paramount importance in medical-imaging. Based on the "RADS" methodology, PIRADS and BI-RADS have been successfully used. The management of bladder cancer (BC) depends on the stage at the time of identification. Accurate assessment of the muscle-invasive stage can alter therapies that are radically different. MRI can accurately diagnose this in a standardized manner (Vesical Imaging-Reporting and Data System: VIRADS) and spare additional procedures. The aim of the study is to determine diagnostic accuracy of VIRADS scoring in evaluation of muscle invasiveness in patients with BC. This study was conducted in a single center over a period of 2 years from April 2020. A total of 76 patients with bladder SOL/diagnosed BC were included. Final VIRADS scoring was calculated and compared with histopathological report.76 patients were evaluated which included 64 males and 12 females. Most of the cases came under the VIRADS-II category (23, 30.26%) followed by VIRADS-V (17, 22.36%). VIRADS-I was reported in 14 cases (18.42%). A total of 8 cases (10.52 %) were reported as VIRADS III and 14 cases (18.42%) as VIRADS IV. VIRADS-III was taken as cut off and found to have a sensitivity of 94.44%, a specificity of 87.50%, a positive predictive value of 87.17% and a negative predictive value of 94.59%. Though number of cases are still less to accurately predict test characteristics of VIRADS, our results are consistent with previously done retrospective studies and VIRADS has got good correlation with pathological staging.

Identification and validation of RB1 as an immune-related prognostic signature based on tumor mutation burdens in bladder cancer

Bladder cancer (BCa) is one of the most common malignant tumors in the urinary system. Developing effective prognostic gene and exploring the immune cells that affect the prognosis of tumor are required. Full transcriptome data ( n = 433), clinical information ( n = 581) and mutation sequencing ( n = 412) were obtained from The Cancer Genome Atlas and independent mutation sequencing data of 101 samples were acquired from International Cancer Genome Consortium. Statistical processing was conducted using R packages. Gene biologically functional research was performed with gene set enrichment analysis based on Kyoto Encyclopedia of Genes and Genomes database. Twenty-two types of immune cell infiltration were assessed and calculated in 398 samples of BCa. Furthermore, the expression of immune-related prognostic signature was verified. The relationship between prognostic gene and immune cells was explored preliminarily. Tumor mutation burdens of mutant-type groups were higher than wild-type groups of 19 genes, except for FGFR3 and CREBBP. Kaplan-Meier analysis showed that high frequency of retinoblastomal 1 (RB1) mutation led to poor prognosis of BCa patients and was an independent prognostic factor ( P = 0.004; HR = 1.776). Proportions and correlation of 22 types of immune cells in 433 samples were determined. We found that RB1 expression decreased in BCa validated through quantitative PCR and immunohistochemistry. In addition, regulatory T cells (Tregs) were detected as a negatively correlated type of immune cell to mutation of RB1, whereas fluorescence costaining showed that Foxp3 expression of Tregs infiltration was negatively related to the expression of RB1. Mutation of RB1 can be identified as an independent prognostic predictor of BCa, and it may suppress the infiltration of Tregs in BCa tissues, increasing the incidence of tumor immune escape.

Performance of Node-RADS Scoring System for a Standardized Assessment of Regional Lymph Nodes in Bladder Cancer Patients

BACKGROUND

Current cross-sectional imaging modalities exhibit heterogenous diagnostic performances for the detection of a lymph node invasion (LNI) in bladder cancer (BCa) patients. Recently, the Node-RADS score was introduced to provide a standardized comprehensive evaluation of LNI, based on a five-item Likert scale accounting for both size and configuration criteria. In the current study, we hypothesized that the Node-RADS score accurately predicts the LNI and tested its diagnostic performance.

METHODS

We retrospectively reviewed BCa patients treated with radical cystectomy (RC) and bilateral extended pelvic lymph node dissection, from January 2019 to June 2022. Patients receiving preoperative systemic chemotherapy were excluded. A logistic regression analysis tested the correlation between the Node-RADS score and LNI both at patient and lymph-node level. The ROC curves and the AUC depicted the overall diagnostic performance. In addition, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for different cut-off values (>1, >2, >3, >4).

RESULTS

Overall, data from 49 patients were collected. Node-RADS assigned on CT scans images, was found to independently predict the LNI after an adjusted multivariable regression analysis, both at the patient (OR 3.36, 95%CI 1.68-9.40, p = 0.004) and lymph node (OR 5.18, 95%CI 3.39-8.64, p < 0.001) levels. Node-RADS exhibited an AUC of 0.87 and 0.91 at the patient and lymph node levels, respectively. With increasing Node-RADS cut-off values, the specificity and PPV increased from 57.1 to 97.1% and from 48.3 to 83.3%, respectively. Conversely, the sensitivity and NPV decreased from 100 to 35.7% and from 100 to 79.1%, respectively. Similar trends were recorded at the lymph node level. Potentially, Node-RADS > 2 could be considered as the best cut-off value due to balanced values at both the patient (77.1 and 78.6%, respectively) and lymph node levels (82.4 and 93.4%, respectively).

CONCLUSIONS

The current study lays the foundation for the introduction of Node-RADS for the regional lymph-node evaluation in BCa patients. Interestingly, the Node-RADS score exhibited a moderate-to-high overall accuracy for the identification of LNI, with the possibility of setting different cut-off values according to specific clinical scenarios. However, these results need to be validated on larger cohorts before drawing definitive conclusions.

The Additional Value of Tri-parametric MRI in Identifying Muscle-invasive Status in Bladder Cancer

RATIONALE AND OBJECTIVES

Identification of muscle-invasive status (MIS) of bladder cancer (BCa) is critical for treatment decisions. The Vesical Imaging-Reporting and Data System (VI-RADS) has been widely used in preoperatively predicting MIS using tri-parametric MR imaging including T2-weighted (T2W), diffusion-weighted (DW), and dynamic contrast-enhanced (DCE) sequences. While the diagnostic values of radiomics features from bi-parametric MRI such as T2W + DW to identification of MIS have been reported, whether the tri-parametric MRI could provide additional diagnostic value to the radiomics prediction task, and how to integrate DCE features into the radiomics model, which is the objectives of this study, remain unknown.

MATERIALS AND METHODS

Patients with postoperatively confirmed BCa lesions (150 in non-muscle-invasive BCa and 56 in muscle-invasive BCa groups) were retrospectively included. Their T2W, DW with apparent diffusion coefficient (ADC) maps, and DCE sequences were acquired using a 3.0T MR system. Regions of interest were manually depicted and VI-RADS scores were assessed by three radiologists. Three predictive models were developed by the radiomics features extracted from sequence combinations of T2W + DW (Model one), T2W + DCE (Model two), and T2W + DW + DCE (Model three), respectively, using the least absolute shrinkage and selection operator. The performance of each model was quantitatively assessed on both the training (n = 165) and testing (n = 41) cohorts. Then a 10 times five-fold cross validation was conducted to assess the overall performance.

RESULTS

Three models achieved area under the curve of 0.888, 0.869, and 0.901 in the cross validation, respectively. The tri-parametric model performed significantly superior than the two bi-parametric models and VI-RADS. The analysis of feature coefficients derived from least absolute shrinkage and selection operator algorithm showed features from the tri-parametric MRI are effective in MIS discrimination.

CONCLUSION

The tri-parametric MRI provides additional value to the radiomics-based identification of MIS.

Value of multiparametric magnetic resonance imaging for local staging of invasive urinary bladder tumours

BACKGROUND

Initial tumour staging in bladder cancer mainly relies on the histo-pathological outcome of the transurethral bladder tumour resection (TURBT) and imaging by means of a CT-scan (CT-intravenous urography; CT-IVU). The reported risk of understaging varies from 24-50%. To further improve the the evaluation of depth of invasion of the bladder tumour the application of magnetic resonance imaging (MRI) may be useful. To substantiate the additional value of this imaging modality the present observational study was designed.

STUDY DESIGN

This is a prospective observational study to analyse bladder tumour staging with multiparametric magnetic resonance imaging (mpMRI) in patients with a known bladder tumour, who are planned for radical cystectomy.

STUDY POPULATION

Patients with an invasive bladder cancer who are planned for radical cystectomy.

INTERVENTION

Patients were accrued during their visit to the outpatient department of urology. They underwent routine cystoscopy, laboratory tests (including serum Creatinin) and CT-IVU investigations and subsequently a mpMRI.

MAIN STUDY PARAMETERS/ENDPOINTS

To demonstrate the value of mpMRI in the initial staging of bladder tumours using radiological bladder tumour stage (T-stage) based on mpMRI and pathological bladder tumour stage based on 'whole-mount' histo-pathology after radical cystectomy.

RESULTS

Thirty-seven participants with known bladder tumours underwent mpMRI and subsequent cystectomy. After mpMRI 10 participants were diagnosed with non-muscle-invasive bladder cancer (NMIBC) and 27 participants with muscle-invasive bladder cancer (MIBC). In the 'whole-mount' pathology results 12 participants had NMIBC and 25 participants had MIBC. We found a sensitivity and specificity of 0.88 en 0.58 respectively, for the evaluation of MIBC. The positive and negative predictive value were 81% and 70% respectively. The diagnostic accuracy of mpMRI to differentiate between NMIBC and MIBC was 78%.

CONCLUSIONS

We found a sensitivity of 88% and a specificity of 58% for mpMRI to discriminate NMIBC from MIBC.

Inter-reader reliability of the vesical imaging-reporting and data system (VI-RADS) for muscle-invasive bladder cancer: a systematic review and meta-analysis

To evaluate the diagnostic agreement between readers in VI-RADS interpretation to detect muscle-invasive bladder cancer (MIBC) preoperatively, we conducted a systematic review and meta-analysis of the available data. Scopus, PubMed, Web of Science, and Embase databases were systematically searched up to November 13, 2021. Case reports, review articles, editorials, and studies with insufficient data were eliminated. The Quality Appraisal of the Diagnostic Reliability Checklist was used to assess the risk of bias. The degree of agreement was determined by Cohen's kappa coefficient (κ) for comparison of data. The heterogeneity of these studies was explored using subgroup analysis and meta-regression analysis. The level of confidence was set at 0.05. All analyses were conducted in STATA 16.0. Overall, 19 eligible studies, consisting of 2439 participants, were included in this meta-analysis. The inter-reader agreement for VI-RADS in MIBC detection ranged from κ of 0.45 to 0.96 among included studies. The pooled inter-reader reliability was calculated as 0.76 [95% CI 0.73-0.80; I² = 92.13%, Q(50) = 635.08, p < 0.01]. Sources of heterogeneity included magnetic strength, T2WI slice thickness, number of readers, sample size, study design, number of centers, year of publication, proportion of male patients, and mean age. There is substantial reliability in VI-RADS interpretation for MIBC among radiologists with various levels of expertise. The high degree of inter-reader agreement for MIBC detection supports the implementation of VI-RADS in routine clinical practice for the staging paradigm of bladder cancer.

Multi-task deep learning based on T2-Weighted Images for predicting Muscular-Invasive Bladder Cancer

BACKGROUND

An accurate preoperative assessment of Non-Muscle-Invasive Bladder Cancer (NMIBC) and Muscle-Invasive Bladder Cancer (MIBC) in Bladder Cancer (BCa) can help the urologist make diagnostic decisions. Considering the absence of multiparametric MRI for contrast medium allergy and economic reasons, this study aims to develop a deep learning method based on T2-Weighted (T2WI) images alone for predicting NMIBC and MIBC.

METHOD

We propose a Multi-task BCa Muscular Invasion Prediction (MBMIP) model to discriminate MIBC from NMIBC. The three-channel-input including the original T2WI image, segmented bladder, and the region of interest can help the MBMIP model locate the bladder and pay more attention to the surrounding information of the tumor. Inception V3 is used as the feature extraction module, which uses multiple branches to extract high-level features with different degrees of abstraction. In addition, based on the idea of multi-task learning, a reconstruction block for T2WI images is also introduced to assist the backbone classification network to improve the classification performance.

RESULTS

The entire data consist of retrospective data (390 cases), prospective data (39 cases), and multi-center data (39 cases). In the retrospective test, the accuracy, sensitivity, and specificity of the MBMIP model are 0.911, 0.889, and 0.920 respectively, while those of the prospective test are 0.923, 1.000, and 0.885. And in the muti-center test, the MBMIP model yields accuracy, sensitivity, and specificity of 0.846, 0.667, and 0.879.

CONCLUSION

The MBMIP model could achieve a satisfactory prediction result in discriminating between NMIBC and MIBC, which may aid urologists in preoperative decision-making for BCa patients.

Comparison between biparametric and multiparametric MRI in predicting muscle invasion by bladder cancer based on the VI-RADS

This study aimed to compare the diagnostic validity of biparametric magnetic resonance imaging (bpMRI) with that of multiparametric MRI (mpMRI) based on the Vesicle Imaging-Reporting and Data System (VI-RADS) in predicting muscle invasion by bladder cancer (BCa). We retrospectively examined 357 patients with an initial diagnosis of BCa who underwent preoperative MRI; 257 and 100 patients underwent mpMRI and bpMRI, respectively. Two urogenital radiologists evaluated all bpMRI and mpMRI scans using VI-RADS, and the diagnostic validity of VI-RADS for predicting muscle invasion by BCa was analyzed based on histopathology of the first and/or second transurethral resection of bladder tumors and radical cystectomy. Receiver operating characteristic (ROC) curves were plotted with the calculation of area under the curves (AUCs), and the level of significance was P < 0.05. Both groups showed optimal performance with a VI-RADS score ≥ 3. BpMRI showed comparable diagnostic performance to mpMRI (reader 1: AUC, 0.903 [0.827-0.954] vs. 0.935 [0.884-0.968], p = 0.510; and reader 2: AUC, 0.901 [0.814-0.945] vs. 0.915 [0.874-0.946]; p = 0.655). The inter-reader agreement between both readers was excellent (Cohen's kappa value = 0.942 and 0.905 for bpMRI and mpMRI, respectively). This comparative study suggests that bpMRI has comparable diagnostic performance to mpMRI and may be an alternative option to predict muscle invasion by BCa.

Clinical utility of vesical imaging-reporting and data system (VI-RADS) in non-muscle invasive bladder cancer (NMIBC) patients candidate for en-bloc transurethral resection: A prospective study

OBJECTIVES

To assess accuracy of vesical imaging-reporting and data system (VI-RADS) 5-point score in detection of muscle invasive bladder cancer and avoiding second look transurethral resection of the tumors (TURBT). Additionally, to assess safety and efficacy of bipolar en-block transurethral urethral resection of bladder tumor.

METHODS

Patients with bladder mass up to 5 cm were included in the study. VI-RADS 5-point score was done preoperative for all cases and postoperatively before second look TURBT. Patients were followed up for 12 months.

RESULTS

In all, 80 cases were eligible for the study. Preoperative VI-RADS score at cutoff of 3 had sensitivity of 89.3 %, specificity 83.3 %, postive predective value (PPV) 92.6 %, negative predictive value (NPV) 76.9 %, accuracy of 87.5 %, while at cutoff 2 sensitivity was 82.1%, specificity 91.7%, PPV 95.8%, NPV 68.8%, accuracy of 85.0%. Operative time 28.8 ± 9.4 minutes, hemoglobin drop 0.3 ± 0.05 g/dl, catheterization time 2.8 ± 0.8 days, hospital stay 1.4 ± 0.4 days. No complications occurred. Recurrence in field of resection 3.75%. Detrusor muscle was available in 76 cases (95%). Postoperative VI-RADS score at cutoff of 3 had sensitivity of 78.6%, specificity 77.8%, PPV 84.6%, NPV 70.0%, accuracy of 78.3%. At cutoff 2 VI-RADS score sensitivity was 71.4%, specificity 77.8%, PPV 83.3%, NPV 63.6%, accuracy of 73.9%.

CONCLUSION

VI-RADS 5-point score showed high sensitivity and specificity in preoperative discrimination of non-muscle invasive bladder cancer (NMIBC) from muscle invasive bladder cancer cases and in avoiding unnecessary second look TURBT. Bipolar en-block TURBT technique is both safe and efficacious in resecting NMIBC cases with low recurrence rate.

The probability of residual tumor detection in the second transurethral resection of pT1 urothelial bladder cancer according to the risk factors

OBJECTIVE

To analyze the predictive factors for residual tumors in the second resection after the initial transurethral resection of bladder tumor (TUR-BT) in patients with pT1 tumors and to develop a simple method to predict the probability of residual tumor detection.

MATERIAL AND METHODS

Patients with pT1 bladder cancer who underwent a second resection within two to six weeks after the initial TUR-BT were included in our retrospective study. The patients' demographics and the tumor characteristics of the initial and second resections were recorded.

RESULTS

A total of 144 patients were included in our analysis with a 53-month follow-up. In the univariate logistic regression analysis, tumor grade, concomitant carcinoma in situ (CIS), macroscopic appearance of the tumor (solid vs papillary), and presence of a variant histology, were significant risk factors for residual tumor. In the multivariate analysis, tumor grade was the only independent predictor of residual tumor at second TUR (OR: 5.62, 95% CI: 1.228-25.708, p = 0.026). According to our findings, the patients with the highest risk have a 90.9% residual tumor detection probability at the second resection, and the patients with the lowest risk have 25.4%.

CONCLUSIONS

Tumor grade, macroscopic appearance of the tumor (solid vs papillary), and concomitant CIS, were important predictors of residual tumors at second resection of primary pT1 NMIBC patients. We were able to calculate the probability of residual tumor which helped us determine risk adapted strategies according to these probabilities.

The role of radiomics with machine learning in the prediction of muscle-invasive bladder cancer: A mini review

Bladder cancer is a common malignant tumor in the urinary system. Depending on whether bladder cancer invades muscle tissue, it is classified into non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC). It is crucial to accurately diagnose the muscle invasion of bladder cancer for its clinical management. Although imaging modalities such as CT and multiparametric MRI play an important role in this regard, radiomics has shown great potential with the development and innovation of precision medicine. It features outstanding advantages such as non-invasive and high efficiency, and takes on important significance in tumor assessment and laor liberation. In this article, we provide an overview of radiomics in the prediction of muscle-invasive bladder cancer and reflect on its future trends and challenges.

A novel pathway to detect muscle-invasive bladder cancer based on integrated clinical features and VI-RADS score on MRI: results of a prospective multicenter study

Purpose

To determine the clinical, pathological, and radiological features, including the Vesical Imaging-Reporting and Data System (VI-RADS) score, independently correlating with muscle-invasive bladder cancer (BCa), in a multicentric national setting.

Method and Materials

Patients with BCa suspicion were offered magnetic resonance imaging (MRI) before trans-urethral resection of bladder tumor (TURBT). According to VI-RADS, a cutoff of ≥ 3 or ≥ 4 was assumed to define muscle-invasive bladder cancer (MIBC). Trans-urethral resection of the tumor (TURBT) and/or cystectomy reports were compared with preoperative VI-RADS scores to assess accuracy of MRI for discriminating between non-muscle-invasive versus MIBC. Performance was assessed by ROC curve analysis. Two univariable and multivariable logistic regression models were implemented including clinical, pathological, radiological data, and VI-RADS categories to determine the variables with an independent effect on MIBC.

Results

A final cohort of 139 patients was enrolled (median age 70 [IQR: 64, 76.5]). MRI showed sensitivity, specificity, PPV, NPV, and accuracy for MIBC diagnosis ranging from 83–93%, 80–92%, 67–81%, 93–96%, and 84–89% for the more experienced readers. The area under the curve (AUC) was 0.95 (0.91–0.99). In the multivariable logistic regression model, the VI-RADS score, using both a cutoff of 3 and 4 (P < .0001), hematuria (P = .007), tumor size (P = .013), and concomitant hydronephrosis (P = .027) were the variables correlating with a bladder cancer staged as ≥ T2. The inter-reader agreement was substantial (k = 0.814).

Conclusions

VI-RADS assessment scoring proved to be an independent predictor of muscle-invasiveness, which might implicate a shift toward a more aggressive selection approach of patients’ at high risk of MIBC, according to a novel proposed predictive pathway.

Comparison of reduced field-of-view DWI and full field-of view DWI for the differentiation between non-muscle invasive bladder cancer and muscle invasive bladder cancer using VI-RADS

Purpose

To evaluate whether reduced field-of-view (rFOV) DWI sequence improves the differentiation between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) using VI-RADS.

Material and methods

Eighty-nine patients underwent bladder MRI with full field-of-view (fFOV) DWI and rFOV DWI sequence. Images were independently evaluated by 2 radiologists. The sensitivities, specificities, accuracies, and areas under the curve (AUCs) for the differentiation between NMIBC and MIBC with fFOV DWI and with rFOV DWI sequence were calculated using VI-RADS. Apparent diffusion coefficients (ADC) values were measured for each patient and averaged.

Results

The sensitivity, specificity, accuracy, and AUC by reader 1 were 92%, 78%, 82% and 0.905 with fFOV DWI, and 92%, 86%, 88% and 0.916 with rFOV DWI sequence, respectively. The sensitivity, specificity, accuracy and AUC by reader 2 were 96%, 76%, 82% and 0.900 with conventional DWI, and 96%, 81%, 85% and 0.907 with rFOV DWI sequence, respectively. The specificity and accuracy of reader 1 were significantly better with rFOV DWI sequence than with fFOV DWI, in contrast there was no significant difference for the others. The average of ADC values of fFOV DWI and rFOV DWI sequence were 1.004×10⁻⁶ mm²/s and 1.003×10⁻⁶ mm²/s, respectively.

Conclusion

The diagnostic ability of rFOV DWI sequence may be better than that of fFOV DWI using VI-RADS for the differentiation between NMIBC and MIBC regardless of image-reading experience, it is controversial.

The application value of multi-parameter cystoscope in improving the accuracy of preoperative bladder cancer grading

Purpose

To develop and validate a preoperative cystoscopic-based predictive model for predicting postoperative high-grade bladder cancer (BCa), which could be used to guide the surgical selection and postoperative treatment strategies.

Materials and methods

We retrospectively recruited 366 patients with cystoscopy biopsy for pathology and morphology evaluation between October 2010 and January 2021. A binary logistic regression model was used to assess the risk factors for postoperative high-grade BCa. Diagnostic performance was analyzed by plotting receiver operating characteristic curve and calculating area under the curve (AUC), sensitivity, specificity. From January 2021 to July 2021, we collected 105 BCa prospectively to validate the model's accuracy.

Results

A total of 366 individuals who underwent transurethral resection of bladder tumor (TURBT) or radical cystectomy following cystoscopy biopsy were included for analysis. 261 (71.3%) had a biopsy pathology grade that was consistent with postoperative pathology grade. We discovered five cystoscopic parameters, including tumor diameter, site, non-pedicled, high-grade biopsy pathology, morphology, were associated with high-grade BCa. The established multi-parameter logistic regression model (“JSPH” model) revealed AUC was 0.917 (P < 0.001). Sensitivity and specificity were 86.2% and 84.0%, respectively. And the consistency of pre- and post-operative high-grade pathology was improved from biopsy-based 70.5% to JSPH model-based 85.2%. In a 105-patients prospective validation cohort, the consistency of pre- and post-operative high-grade pathology was increased from 63.1 to 84.2% after incorporation into JSPH model for prediction.

Conclusion

The cystoscopic parameters based “JSPH model” is accurate at predicting postoperative pathological high-grade tumors prior to operations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12894-022-01054-z.

VI-RADS score system - A primer for urologists

Bladder cancer (BCa) is one of the most common cancers worldwide and is also considered to be one of the most relapsing and aggressive neoplasms. About 30% of patients will present with muscle invasive disease, which is associated with a higher risk for metastatic disease. The aim of this article is to review the state of art imaging in Radiology, while providing a complete guide to urologists, with case examples, for the rationale of the development of the Vesical Imaging Reporting and Data System (VI-RADS), a scoring system emphasizing a standardized approach to multiparametric Magnetic Resonance Imaging (mpMRI) acquisition, interpretation, and reporting for BCa. Also, we examine relevant external validation studies and the consolidated literature of mpMRI for bladder cancer. In addition, this article discusses some of the potential clinical implications of this scoring system for disease management and follow-up.

Radiologic Diagnosis and Staging of Bladder Cancer: An Update

Although cystoscopic biopsy is the standard of care for initial diagnosis and local staging of bladder cancer, radiologic imaging plays a major role in identifying local invasion, nodal status, distant metastasis, and posttreatment surveillance. Recent development of the Vesical Imaging-Reporting and Data System for interpretation of multiparametric magnetic resonance imaging of the bladder has expanded the role diagnostic imaging in the management of bladder cancer. This article reviews multimodality imaging appearances, staging, and differential diagnosis of bladder cancer.

Multiparametric MRI Evaluation of VI-RADS for Bladder Tumors Located at the Ureteral Orifice

Background The Vesical Imaging Reporting and Data System (VI-RADS) based on multiparametric MRI scans standardizes preoperative bladder cancer staging. However, limitations have been reported for VI-RADS, particularly for ureteral orifice tumors. Purpose To investigate the diagnostic performance and interobserver agreement of VI-RADS in evaluating muscle invasion for bladder tumors located at the ureteral orifice. Materials and Methods In this retrospective study, patients with histopathologically confirmed bladder cancer occurring at the ureteral orifice from January 2012 to November 2021 were analyzed. Two blinded radiologists independently scored multiparametric MRI scans according to VI-RADS. Interobserver agreement of the VI-RADS scores was evaluated with weighted κ analysis. Receiver operating characteristic curve analysis was used to evaluate the diagnostic performance of the VI-RADS scores in the prediction of muscle invasion. Results A total of 78 patients (mean age, 67 years ± 7 [SD]; age range, 46-90 years; 67 men) were included in the final analysis: 25 with non-muscle-invasive bladder cancer and 53 with muscle-invasive bladder cancer (MIBCa). At consensus reading, one (1%) case was scored as VI-RADS 1, 27 cases (35%) were scored as VI-RADS 2, six (8%) were scored as VI-RADS 3, 10 (13%) were scored as VI-RADS 4, and 34 (44%) were scored as VI-RADS 5. On comparison of the VI-RADS score with histopathologic findings, it was confirmed that the presence of muscle invasion was 0% (zero of one) for VI-RADS 1, 15% (four of 27) for VI-RADS 2, 83% (five of six) for VI-RADS 3, 100% (10 of 10) for VI-RADS 4, and 100% (34 of 34) for VI-RADS 5. The area under the receiver operating characteristic curve of VI-RADS in the detection of MIBCa was 0.96 (95% CI: 0.92, 1.00). Conclusion The Vesical Imaging Reporting and Data System could be used to accurately predict muscle invasion for bladder tumors occurring at the ureteral orifice. © RSNA, 2022 Online supplemental material is available for this article.

What is the impact of dynamic contrast-enhancement sequence in the Vesical Imaging, Reporting and Data System (VI-RADS)? A subgroup analysis

Background

A scoring system focusing on the risk of muscle layer invasion by Bladder cancer (BCa) has been released, Vesical Imaging - Radiological and Data System (VI-RADS), with a growing interest in evaluating its diagnostic accuracy.

Our goal was to assess the accuracy and reproducibility of the VI-RADS score for assessment of the vesical muscular layer with (multiparametric-mp) and without (biparametric-bp) a dynamic-contrast enhancement (DCE) sequence.

Methods

Retrospective study conducted from July 2018 to July 2020. All patients had suspicions of BCa and underwent Magnetic Resonance Imaging (MRI) before any intervention. MRI was interpreted by two radiologists with different levels of experience, and a VI-RADS score assigned in two different sessions (3 months apart) without and with DCE. After exclusions, 44 patients with 50 lesions were enrolled. The standard of reference was transurethral resection in 18 patients (40.9%) and cystectomy in 26 patients (59.1%).

Results

Twenty-five lesions (50%) were muscle-invasive. There was no significant difference between the two groups for gender and presence of a stalk, but mean age of NMIBCa group was significantly higher (p = 0.01). The sizes of lesions were significantly different between groups for both readers at 2.42+/− 1.58 vs. 5.70+/− 2.67 cm for reader 1 (p < 0.0001) and 2.37+/− 1.50 vs. 5.44 +/− 2.90 cm for reader 2 (p = 0.001). The area under the curve (AUC) for muscle invasion with mpVI-RADS, considering all lesions, was 0.885 +/− 0.04 (95% CI-0.79-0.98) for reader 1 and 0.924 +/− 0.04 (0.84–0.99) for reader 2, and for bpVI-RADS was 0.879+/− 0.05 and 0.916 +/− 0.04 (0.85–0.99), respectively, both differences not statistically significant (p = 0.24 and 0.07, respectively). When considering only small lesions (< 3.0 cm), the accuracy for mpVI-RADS was 0.795 +/− 0.11 (0.57–1.0) for reader1, and 0.80 +/− 0.11(0.57–1.0) for reader 2, a non-significant difference (p = 0.56) and for bpVI-RADS was 0.747 +/− 0.12 (0.50–0.99) for reader 1 and 0.80 +/− 0.11(0.57–1.0) for reader 2, a significant difference (p = 0.04). The intraclass correlation coefficient for the final score was 0.81 (0.60–1.0) for mpVI-RADS and 0.85 (0.63–1.0) for bpVI-RADS.

Conclusion

The VI-RADS system was accurate in demonstrating muscle-invasive BCa, for both experienced and less experienced reader, regardless of the use of a DCE sequence. However, when only small lesions were assessed the difference between the two readers was significant only for the biparametric analysis. The reproducibility was similar between multiparametric and biparametric approach.

Increased NUSAP1 expression is associated with lymph node metastasis and survival prognosis in bladder urothelial carcinoma

The main route of metastasis of bladder urothelial carcinoma is through lymph nodes; however, its exact mechanism remains unclear. In this study, we found an association of nucleolar and spindle associated protein 1 (NUSAP1) expression with BUC tissues along with lymph node metastasis and the survival prognosis. A total of 178 pathological specimens following radical bladder cancer resection were obtained. NUSAP1 expression was analyzed by immunohistochemistry. We evaluated the correlation between clinicopathological characteristics and NUSAP1 expression. Logistic regression was used to determine the independent variables that influenced lymph node metastasis. Uni- and multi-factorial Cox regression methods were used to determine the prognostic value of NUSAP1 expression in urothelial carcinoma of the bladder. High expression of NUSAP1 in BUC was not significantly related to the patient’s gender, age, or tumor number (p > 0.05), however was significantly associated with pathological grade, tumor diameter, pathological stage, and lymph node metastasis (p < 0.05). Lymph node metastasis was significantly correlated with pathological stage, pathological grade, tumor number, tumor diameter, and NUSAP1 expression (p < 0.05); only NUSAP1 expression was an independent predictor of lymph node metastasis in BUC (OR:1.786, 95% CI 1.229–2.596, p = 0.002). In addition, high NUSAP1 expression was an independent prognostic predictor for BUC. In BUC, NUSAP1 showed high expression and was significantly associated with lymph node metastasis, pathological stage, pathological grade, and tumor diameter. NUSAP1 was an independent predictor of lymph node metastasis and prognosis in BUC; higher expression indicated poorer prognosis of BUC patients.