Preoperative Imaging for Staging Bladder Cancer

A clinically practical model for the preoperative prediction of lymph node metastasis in bladder cancer: a multicohort study

BACKGROUND

The aim of this study was to construct a clinically practical model to precisely predict lymph node (LN) metastasis in bladder cancer patients.

METHODS

Four independent cohorts were included. The least absolute shrinkage and selection operator regression with multivariate logistic regression were applied. The diagnostic efficacy of LN score and CT/MRI was compared by accuracy, sensitivity, specificity, and area under curve (AUC).

RESULTS

A total of 606 patients were included to develop a basic prediction model. After multistep gene selection, the LN metastasis prediction model was constructed with 5 genes. The model can accurately predict LN metastasis with an AUC of 0.781. For clinically practical use, we transformed the model into a Fast LN Scoring System using the SYSMH cohort (n = 105). High LN score patients exhibited a 72.2% LN metastasis rate, while low LN score patients showed a 3.4% LN metastasis rate. The LN score achieved a superior accuracy than CT/MRI (0.882 vs. 0.727). Application of LN score can correct the diagnosis of 88% (22/25) patients who were misdiagnosed by CT/MRI.

DISCUSSION

The clinically practical LN score can precisely, rapidly, and conveniently predict LN status, which will assist preoperative diagnosis for LN metastasis and guide precise therapy.

[Bladder preservation treatments for bladder cancer: Trimodality therapy, an overview of clinical practices in 2023]

Bladder cancer is the most frequent tumor of the urinary tract. Patients diagnosed at a stage when the tumor has spread into or through the muscle layer of the bladder wall are usually treated with cystectomy. The evolution of cancer treatments, related to the development of alternative treatment options to the historical surgical standard and to the implication of the patient as an actor in decision-making, trends towards organ and function preservation without sacrificing efficacy. Trimodality therapy, which is a maximal transurethral resection of the tumor followed by concurrent chemoradiation, is an interesting therapeutic alternative for patients unfit for surgery and for those wishing to benefit from organ preservation. Radiotherapy offers excellent treatment possibilities for muscle-invasive bladder cancer. In selected T2-stage patients fit for trimodality therapy, it has an equivalent oncological outcome compared to cystectomy while having less severe complications and offering organ preservation. It remains feasible in inoperable patients while offering significant perspectives of relapse-free survival. Finally, it also is an efficient palliative treatment in patients where mid-term local control and hemostasis are sought after.

Predicting Lymph Node Metastasis Status from Primary Muscle-Invasive Bladder Cancer Histology Slides Using Deep Learning: A Retrospective Multicenter Study

BACKGROUND

Accurate prediction of lymph node metastasis (LNM) status in patients with muscle-invasive bladder cancer (MIBC) before radical cystectomy can guide the use of neoadjuvant chemotherapy and the extent of pelvic lymph node dissection. We aimed to develop and validate a weakly-supervised deep learning model to predict LNM status from digitized histopathological slides in MIBC.

METHODS

We trained a multiple instance learning model with an attention mechanism (namely SBLNP) from a cohort of 323 patients in the TCGA cohort. In parallel, we collected corresponding clinical information to construct a logistic regression model. Subsequently, the score predicted by the SBLNP was incorporated into the logistic regression model. In total, 417 WSIs from 139 patients in the RHWU cohort and 230 WSIs from 78 patients in the PHHC cohort were used as independent external validation sets.

RESULTS

In the TCGA cohort, the SBLNP achieved an AUROC of 0.811 (95% confidence interval [CI], 0.771-0.855), the clinical classifier achieved an AUROC of 0.697 (95% CI, 0.661-0.728) and the combined classifier yielded an improvement to 0.864 (95% CI, 0.827-0.906). Encouragingly, the SBLNP still maintained high performance in the RHWU cohort and PHHC cohort, with an AUROC of 0.762 (95% CI, 0.725-0.801) and 0.746 (95% CI, 0.687-0.799), respectively. Moreover, the interpretability of SBLNP identified stroma with lymphocytic inflammation as a key feature of predicting LNM presence.

CONCLUSIONS

Our proposed weakly-supervised deep learning model can predict the LNM status of MIBC patients from routine WSIs, demonstrating decent generalization performance and holding promise for clinical implementation.

A tumor microenvironment preoperative nomogram for prediction of lymph node metastasis in bladder cancer

Background

Growing evidence suggests that tumor metastasis necessitates multi-step microenvironmental regulation. Lymph node metastasis (LNM) influences both pre- and post-operative bladder cancer (BLCA) treatment strategies. Given that current LNM diagnosis methods are still insufficient, we intend to investigate the microenvironmental changes in BLCA with and without LNM and develop a prediction model to confirm LNM status.

Method

"Estimation of Stromal and Immune cells in Malignant Tumors using Expression data" (ESTIMATE) algorithm was used to characterize the tumor microenvironment pattern of TCGA-BLCA cohort, and dimension reduction, feature selection, and StrLNM signature construction were accomplished using least absolute shrinkage and selection operator (LASSO) regression. StrLNM signature was combined with the genomic mutation to establish an LNM nomogram by using multivariable logistic regression. The performance of the nomogram was evaluated in terms of calibration, discrimination, and clinical utility. The testing set from the TCGA-BLCA cohort was used for internal validation. Moreover, three independent cohorts were used for external validation, and BLCA patients from our cohort were also used for further validation.

Results

The StrLNM signature, consisting of 22 selected features, could accurately predict LNM status in the TCGA-BLCA cohort and several independent cohorts. The nomogram performed well in discriminating LNM status, with the area under curve (AUC) of 75.1% and 65.4% in training and testing datasets from the TCGA-BLCA cohort. Furthermore, the StrLNM nomogram demonstrated good calibration with p >0.05 in the Hosmer-Lemeshow goodness of fit test. Decision curve analysis (DCA) revealed that the StrLNM nomogram had a high potential for clinical utility. Additionally, 14 of 22 stably expressed genes were identified by survival analysis and confirmed by qPCR in BLCA patient samples in our cohort.

Conclusion

In summary, we developed a nomogram that included an StrLNM signature and facilitated the preoperative prediction of LNM status in BLCA patients.

State-of-the-Art Advances of Nanomedicine for Diagnosis and Treatment of Bladder Cancer

Bladder cancer is a common malignant tumor of the urinary system. Cystoscopy, urine cytology, and CT are the routine diagnostic methods. However, there are some problems such as low sensitivity and difficulty in staging, which must be urgently supplemented by novel diagnostic methods. Surgery, intravesical instillation, systemic chemotherapy, and radiotherapy are the main clinical treatments for bladder cancer. It is difficult for conventional treatment to deal with tumor recurrence, progression and drug resistance. In addition, the treatment agents usually have the defects of poor specific distribution ability to target tumor tissues and side effects. The rapid development of nanomedicine has brought hope for the treatment of bladder cancer in reducing side effects, enhancing tumor inhibition effects, and anti-drug resistance. Overall, we review the new progression of nano-platforms in the diagnosis and treatment of bladder cancer.

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.

Optimization of Preoperative Lymph Node Staging in Patients with Muscle-Invasive Bladder Cancer Using Radiomics on Computed Tomography

Approximately 25% of the patients with muscle-invasive bladder cancer (MIBC) who are clinically node negative have occult lymph node metastases at radical cystectomy (RC) and pelvic lymph node dissection. The aim of this study was to evaluate preoperative CT-based radiomics to differentiate between pN+ and pN0 disease in patients with clinical stage cT2-T4aN0-N1M0 MIBC. Patients with cT2-T4aN0-N1M0 MIBC, of whom preoperative CT scans and pathology reports were available, were included from the prospective, multicenter CirGuidance trial. After manual segmentation of the lymph nodes, 564 radiomics features were extracted. A combination of different machine-learning methods was used to develop various decision models to differentiate between patients with pN+ and pN0 disease. A total of 209 patients (159 pN0; 50 pN+) were included, with a total of 3153 segmented lymph nodes. None of the individual radiomics features showed significant differences between pN+ and pN0 disease, and none of the radiomics models performed substantially better than random guessing. Hence, CT-based radiomics does not contribute to differentiation between pN+ and pN0 disease in patients with cT2-T4aN0-N1M0 MIBC.

Conspicuity and muscle-invasiveness assessment for bladder cancer using VI-RADS: a multi-reader, contrast-free MRI study to determine optimal b-values for diffusion-weighted imaging

OBJECTIVE

To (1) compare bladder cancer (BC) muscle invasiveness among three b-values using a contrast-free approach based on Vesical Imaging-Reporting and Data System (VI-RADS), to (2) determine if muscle-invasiveness assessment is affected by the reader experience, and to (3) compare BC conspicuity among three b-values, qualitatively and quantitatively.

METHODS

Thirty-eight patients who underwent a bladder MRI on a 3.0-T scanner were enrolled. The gold standard was histopathology report following transurethral resection of BC. Three sets of images, including T2w and different b-values for DWI, set 1 (b = 1000 s/mm²), set 2 (b = 1500 s/mm²), and set 3 (b = 2000 s/mm²), were reviewed by three differently experienced readers. Descriptive statistics and Intraclass Correlation Coefficient (ICC) were calculated. Comparisons among readers and DWI sets were performed with the Wilcoxon test. Receiver operating characteristic (ROC) analysis was performed. Areas under the curves (AUCs) and pairwise comparison were calculated.

RESULTS

AUCs of muscle-invasiveness assessment ranged from 0.896 to 0.984 (reader 1), 0.952-0.968 (reader 2), and 0.952-0.984 (reader 3) without significant differences among different sets and readers (p > 0.05). The mean conspicuity qualitative scores were higher in Set 1 (2.21-2.33), followed by Set 2 (2-2.16) and Set 3 (1.82-2.14). The quantitative conspicuity assessment showed that mean normalized intensity of tumor was significantly higher in Set 2 (4.217-4.737) than in Set 1 (3.923-4.492) and Set 3 (3.833-3.992) (p < 0.05).

CONCLUSION

Muscle invasiveness can be assessed with high accuracy using a contrast-free protocol with T2W and DWI, regardless of reader's experience. b = 1500 s/mm² showed the best tumor delineation, while b = 1000 s/mm² allowed for better tumor-wall interface assessment.

Prediction of Metastatic Patterns in Bladder Cancer: Spatiotemporal Progression and Development of a Novel, Web-based Platform for Clinical Utility

Background

Bladder cancer (BCa), the sixth commonest cancer in the USA, is highly lethal when metastatic. Spatial and temporal patterns of patient-specific metastatic spread are deemed random and unpredictable. Whether BCa metastatic patterns can be quantified and predicted more accurately is unknown.

Objective

To develop a web-based calculator for forecasting metastatic progression in individual BCa patients.

Design setting and participants

We used a prospectively collected longitudinal dataset of 3503 BCa patients who underwent a radical cystectomy following diagnosis and were enrolled continuously. We subdivided patients by their pathologic subgroup stages of organ confined (OC), extravesical (EV), and node positive (N+). We illustrated metastatic pathway progression using color-coded, circular, tree ring diagrams. We created a dynamical, data-visualization, web-based platform that displays temporal, spatial, and Markov modeling figures with predictive capability.

Outcome measurements and statistical analysis

Patients underwent history and physical examination, serum studies, and liver function tests. Surveillance follow-up included computed tomography scans, chest x-rays, and radiographic evaluation of the reservoir and upper tracts, with bone scans performed only if clinically indicated. Outcomes were measured by time to clinical recurrence and overall or progression-free survival.

Results and limitations

Metastases developed in 29% of patients (n = 812; median follow-up 15.3 yr), with 5-yr overall survival of 20.2%, compared with 78.6% in those without metastases (n = 1983; median follow-up 10.9 yr). The three commonest sites of spread at the time of first progression were bone (n = 214; 26.4%), pelvis (n = 194; 23.9%), and lung (n = 194; 23.9%). The order and frequency of these sites vary when divided by pathologic subgroup stages of OC (lung [n = 65; 25.1%], urethra [n = 45; 17.4%], and bone [n = 29; 11.2%]), EV (pelvis [n = 63; 33.0%], bone [n = 45; 23.6%], and lung [n = 29; 15.2%]), and N+ (bone [n = 111; 30.7%], retroperitoneum [n = 70; 19.3%], and pelvis [n = 60; 16.6%]). Markov chain modeling indicated a higher probability of spread from bladder to bone (15.5%), pelvis (14.7%), and lung (14.2%).

Conclusions

Our web-based calculator allows real-time analyses in the clinic based on individual patient-specific demographic and cancer data elements. For contrasting subgroups, the models indicated differences in Markov transition probabilities. Spatiotemporal patterns of BCa metastasis and sites of spread indicated underlying organotropic mechanisms in the prediction of response. This recognition opens the possibility of organ site-specific therapeutic targeting in the oligometastatic BCa setting. In the precision medicine era, visualization of complex, time-resolved clinical data will enhance management of postoperative metastatic BCa patients.

Patient summary

We developed a web-based calculator to forecast metastatic progression for individual bladder cancer (BCa) patients, based on the clinical and demographic information obtained at diagnosis. This can help in predicting disease status and survival, and improving management in postoperative metastatic BCa patients.

Take  Home Message

Future pathways of metastatic progression for individual bladder cancer patients can be determined based on currently available clinical and demographic information obtained at diagnosis. In focused subgroups of patients, these metastatic spread patterns can also portend disease status and survival.

Computed-tomography based scoring system predicts outcome for clinical lymph node-positive patients undergoing radical cystectomy

Purpose:

Contrast-enhanced CT scan is the standard staging modality for patients with bladder cancer undergoing radical cystectomy (RC). Involvement of lymph nodes (LN) determines prognosis of patients with bladder cancer. The detection of LN metastasis by CT scan is still insufficient. Therefore, we investigated various CT scan characteristics to predict lymph node ratio (LNR) and its impact on survival. Also, pre-operative CT scan characteristics might hold potential to risk stratify cN+ patients.

Materials and Methods:

We analyzed preoperative CT scans of patients undergoing RC in a tertiary high volume center. Retrospectively, local tumor stage and LN characteristics such as size, morphology (MLN) and number of loco-regional LN (NLN) were investigated and correlation to LNR and survival was analyzed. CT scan characteristics were used to develop a risk stratification using Kaplan-Maier and multivariate analysis.

Results:

764 cN0 and 166 cN+ patients with complete follow-up and imaging data were included in the study. Accuracy to detect LN metastasis and locally advanced tumor stage in CT scan was 72% and 62%. LN larger than 15mm in diameter were significantly associated with higher LNR (p=0.002). Increased NLN correlated with decreased CSS and OS (p=0.001: p=0.002). Furthermore, CT scan based scoring system precisely differentiates low-risk and high-risk profiles to predict oncological outcome (p <0.001).

Conclusion:

In our study, solely LN size >15mm significantly correlated with higher LNR. Identification of increased loco-regional LN was associated with worse survival. For the first time, precise risk stratification based on computed-tomography findings was developed to predict oncological outcome for clinical lymph node-positive patients undergoing RC.

Application of deep learning as a noninvasive tool to differentiate muscle-invasive bladder cancer and non-muscle-invasive bladder cancer with CT

OBJECTIVE

To construct a deep-learning convolution neural network (DL-CNN) system for the differentiation of muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC) on contrast-enhanced computed tomography (CT) images in patients with bladder cancer.

MATERIALS AND METHODS

A total of 1200 cross-sectional CT images were obtained from 369 patients with bladder cancer receiving radical cystectomy from January 2015 to June 2018, including 249 non-muscle-invasive bladder cancer (NMIBC) series and 120 muscle-invasive bladder cancer (MIBC) series. All eligible images were distributed randomly into the training, validation, and testing cohorts with ratios of 70 %, 15 %, and 15 %, respectively. We developed one small DL-CNN containing four convolutional and max pooling layers and eight DL-CNNs with pretrained bases from the ImageNet dataset to differentiate NMIBC from MIBC. The intermediate activations were applied on the test dataset to visualize how successive DL-CNN layers transform their input.

RESULTS

The area under the receiver operating characteristic curve (AUROC) of the validation and testing datasets for the small DL-CNN was 0.946 and 0.998, respectively. The AUROCs of eight deep learning algorithms with pretrained bases ranged from 0.762 to 0.997 in the testing dataset. The VGG16 model had the largest AUROC of 0.997 among the eight algorithms with a sensitivity and specificity of 0.889 and 0.989. The independent features encoded by the small DL-CNN filters were displayed as assemblies of individual channels.

CONCLUSION

Based on contrast-enhanced CT images, our DL-CNN system could successfully classify NMIBC and MIBC with favorable AUROC in patients with bladder cancer. The application of our system in early stage might assist the pathological examination for the improvement of diagnostic accuracy.

Lymphatic metastasis of bladder cancer: Molecular mechanisms, diagnosis and targeted therapy

Bladder cancer is the most common and lethal cancer of the urinary system. Lymphatic metastasis is the primary and main metastatic type of bladder cancer, leading to an extremely poor prognosis in patients. Therefore, a better understanding of molecular mechanisms may provide potential targets for the diagnosis and treatment of lymphatic metastasis in bladder cancer. Herein, we summarize the current knowledge of molecular mechanisms of the lymphatic metastasis in bladder cancer, including lymphangiogenesis and its regulators, noncoding RNAs, and microenvironment-associated molecules. Novel radiomics and genomics approaches have substantially improved the preoperative diagnostic accuracy of lymph node metastasis in patients with bladder cancer. Newly discovered targets may lead to promising therapeutic strategies for clinical intervention in lymphatic metastasis of bladder cancer. More basic and translational studies need to be conducted to further clarify the molecular mechanisms, and identify predictive markers and therapeutic targets of lymphatic metastasis for bladder cancer patients.

Estadificación clínica como factor pronóstico en cáncer de vejiga músculo-invasor

El cáncer de vejiga músculo invasor (CV-MI), requiere de una adecuada estadificación clínica y patológica, ya que eso determina las estrategias terapéuticas y el pronóstico de la enfermedad, caracterizada por una alta morbimortalidad. Este articulo tiene como objetivo realizar una revisión de la literatura sobre la exactitud diagnóstica de las técnicas de imagen disponibles para la estadificación clínica de los pacientes con CV-MI y cómo se debería realizar el seguimiento radiológico en los pacientes llevados a cirugía. Para eso se realizó una búsqueda en la base de datos Pubmed de artículos en inglés y en español, se incluyeron artículos de revisión, metanálisis, guías clínicas, estudios retrospectivos y prospectivos de pronóstico y diagnóstico desde el año 1988 hasta el año 2020.

Role of magnetic resonance imaging in tumor staging and follow-up for bladder cancer

Urothelial carcinoma of the bladder is a common urologic malignancy. Complex factors, such as local stage, tumor grade, biologic potential, and various conditions, can affect the treatment strategy for bladder cancer. However, the local stage-in particular, the presence or absence of muscle invasion-significantly influences decisions regarding treatment strategy. The role of cystoscopy for screening, diagnosis, and transurethral resection cannot be overlooked. The importance of local staging with magnetic resonance imaging is increasing; magnetic resonance imaging of the bladder is considered a useful staging modality. Moreover, a radiologic reporting system for evaluating and scoring muscle invasion of bladder cancer was recently released. This system is based on multiparametric magnetic resonance imaging and is also expected to be feasible for post-treatment follow-up of bladder cancer. In this review, we discuss the role of magnetic resonance imaging in the local staging of urothelial carcinoma of the urinary bladder and post-treatment imaging. In addition, several technical aspects for obtaining appropriate quality magnetic resonance images of the bladder will be discussed.

Utilization of imaging for staging in bladder cancer: is there a role for MRI or PET-computed tomography?

PURPOSE OF REVIEW

Accurate staging of bladder cancer is essential to guide appropriate management. In this review, we discuss the principles, applications and performance of multiparametric MRI (mpMRI) and PET-computer tomography (PET-CT) for local and distant staging of bladder cancer.

RECENT FINDINGS

Bladder mpMRI has a high diagnostic performance in local staging of bladder cancer, superior to other imaging modalities. It can accurately differentiate muscle invasive bladder cancer (MIBC) from non-MIBC (NMIBC), as well as ≤T2 from ≥T3 stages. mpMRI can be used to assess pelvic lymph nodes, although its sensitivity is relatively low. For the assessment of the upper urinary tract, CT urography is the imaging modality of choice. magnetic resonance urography is a viable alternative to CT in selected cases. Although PET-CT is accurate for nodal and distant staging of bladder cancer, there is no clear evidence on its superior diagnostic performance compared with contrast-enhanced CT.

SUMMARY

mpMRI is the most accurate imaging modality for local staging of bladder cancer, capable to accurately distinguish MIBC from NMIBC. Nodal and distant staging relies primarily on contrast-enhanced CT.

Endoscopic Molecular Imaging plus Photoimmunotherapy: A New Strategy for Monitoring and Treatment of Bladder Cancer

Due to the high recurrence and progression rate of non-muscle invasive bladder cancer after transurethral resection of bladder tumor, some new optical imaging technologies have arisen as auxiliary imaging modes for white light cystoscopy to improve the detection rate of small or occult tumor lesions, such as photodynamic diagnosis, narrow-band imaging, and molecular imaging. White light cystoscopy is inadequate and imperfect for bladder cancer detection, and thus residual tumors or coexisting flat malignant lesions, especially carcinoma in situ, would be ignored during conventional resection. The bladder, a hollow organ with high compliance, provides an ideal closed operation darkroom for endoscopic molecular imaging free from interference of external light sources. Also, intravesical instillation of a molecular fluorescent tracer is simple and convenient before surgery through the urethra. Molecular fluorescent tracer has high sensitivity and specificity to tumor cells, and its mediated molecular imaging allows small or occult tumor lesion detection while minimizing false-positive results. Meanwhile, endoscopic molecular imaging provides a real-time and dynamic image during surgery, which helps urologists to perform high-quality and complete tumor resection through accurate judgment of tumor boundaries and depth of invasion. Photoimmunotherapy is a novel molecular targeted therapeutic pattern of photodynamic therapy that kills malignant cells selectively and minimizes the cytotoxicity to normal tissues. The combination of endoscopic molecular imaging and photoimmunotherapy used in initial treatment may avoid the need of repeat transurethral resection in strictly selected patients and improve oncological outcomes such as recurrence-free survival and overall survival after operation.

Association of chromosome 7 aneuploidy measured by fluorescence in situ hybridization assay with muscular invasion in bladder cancer

Background

The preoperative prediction of muscular invasion status is important for adequately treating bladder cancer (BC) but nevertheless, there are some existing dilemmas in the current preoperative diagnostic accuracy of BC with muscular invasion. Here, we investigated the potential association between the fluorescence in situ hybridization (FISH) assay and muscular invasion among patients with BC. A cytogenetic‐clinical nomogram for the individualized preoperative differentiation of muscle‐invasive BC (MIBC) from non‐muscle‐invasive BC (NMIBC) is also proposed.

Methods

All eligible BC patients were preoperatively tested using a FISH assay, which included 4 sites (chromosome‐specific centromeric probe [CSP] 3, 7, and 17, and gene locus‐specific probe [GLP]‐p16 locus). The correlation between the FISH assay and BC muscular invasion was evaluated using the Chi‐square tests. In the training set, univariate and multivariate logistic regression analyses were used to develop a cytogenetic‐clinical nomogram for preoperative muscular invasion prediction. Then, we assessed the performance of the nomogram in the training set with respect to its discriminatory accuracy and calibration for predicting muscular invasion, and clinical usefulness, which were then validated in the validation set. Moreover, model comparison was set to evaluate the discrimination and clinical usefulness between the nomogram and the individual variables incorporated in the nomogram.

Results

Muscular invasion was more prevalent in BC patients with positive CSP3, CSP7 and CSP17 status (OR [95% CI], 2.724 [1.555 to 4.774], P < 0.001; 3.406 [1.912 to 6.068], P < 0.001 and 2.483 [1.436 to 4.292], P = 0.001, respectively). Radiology‐determined tumor size, radiology‐determined clinical tumor stage and CSP7 status were identified as independent risk factors of BC muscular invasion by the multivariate regression analysis in the training set. Then, a cytogenetic‐clinical nomogram incorporating these three independent risk factors was constructed and was observed to have satisfactory discrimination in the training (AUC 0.784; 95% CI: 0.715 to 0.853) and validation (AUC 0.743; 95% CI: 0.635 to 0.850) set. The decision curve analysis (DCA) indicated the clinical usefulness of our nomogram. In models comparison, using the receiver operator characteristic (ROC) analyses, the nomogram showed higher discriminatory accuracy than any variables incorporated in the nomogram alone and the DCAs also identified the nomogram as possessing the highest net benefits at wide range of threshold probabilities.

Conclusion

CSP7 status was identified as an independent factor for predicting muscular invasion in BC patients and was successfully incorporated in a clinical nomogram combining the results of the FISH assay with clinical risk factors.

Development of a noninvasive tool to preoperatively evaluate the muscular invasiveness of bladder cancer using a radiomics approach

BACKGROUND

Bladder cancer (BCa) can be divided into muscle-invasive BCa (MIBC) and non-muscle-invasive BCa (NMIBC). Whether the tumor infiltrates the detrusor muscle is a critical determinant of disease management in patients with BCa. However, the current preoperative diagnostic accuracy of muscular invasiveness is less than satisfactory. The authors report a radiomic-clinical nomogram for the individualized preoperative differentiation of MIBC from NMIBC.

METHODS

In total, 2602 radiomics features were extracted from whole bladder tumors and the basal part of the lesions on T2-weighted magnetic resonance imaging. Then, a radiomics signature was constructed using the least absolute shrinkage and selection operator algorithm in the training set (n = 130). Furthermore, a radiomic-clinical nomogram was developed incorporating the radiomics signature and selected clinical predictors based on a multivariable logistic regression analysis. The performance of the nomogram (discrimination, calibration, and clinical usefulness) was assessed and validated in an independent validation set (n = 69).

RESULTS

The radiomics signature, consisting of 23 selected features, showed good discrimination in the training and validation sets (area under the curve [AUC], 0.913 and 0.874, respectively). Incorporating the radiomics signature and magnetic resonance imaging-determined tumor size, the radiomic-clinical nomogram showed favorable calibration and discrimination in the training set with an AUC of 0.922, which was confirmed in the validation set (AUC, 0.876). Decision curve analysis and net reclassification improvement and integrated discrimination improvement indices (net reclassification improvement, 0.338, integrated discrimination improvement, 0.385) demonstrated the clinical usefulness of the nomogram.

CONCLUSIONS

The proposed noninvasive radiomic-clinical nomogram can increase the accuracy of preoperatively discriminating MIBC from NMIBC, which may aid in clinical decision making and improve patient prognosis.

How rapid advances in imaging are defining the future of precision radiation oncology

Imaging has an essential role in the planning and delivery of radiotherapy. Recent advances in imaging have led to the development of advanced radiotherapy techniques—including image-guided radiotherapy, intensity-modulated radiotherapy, stereotactic body radiotherapy and proton beam therapy. The optimal use of imaging might enable higher doses of radiation to be delivered to the tumour, while sparing normal surrounding tissues. In this article, we review how the integration of existing and novel forms of computed tomography, magnetic resonance imaging and positron emission tomography have transformed tumour delineation in the radiotherapy planning process, and how these advances have the potential to allow a more individualised approach to the cancer therapy. Recent data suggest that imaging biomarkers that assess underlying tumour heterogeneity can identify areas within a tumour that are at higher risk of radio-resistance, and therefore potentially allow for biologically focussed dose escalation. The rapidly evolving concept of adaptive radiotherapy, including artificial intelligence, requires imaging during treatment to be used to modify radiotherapy on a daily basis. These advances have the potential to improve clinical outcomes and reduce radiation-related long-term toxicities. We outline how recent technological advances in both imaging and radiotherapy delivery can be combined to shape the future of precision radiation oncology.

A glance at imaging bladder cancer

Purpose

Early and accurate diagnosis of Bladder cancer (BCa) will contribute extensively to the management of the disease. The purpose of this review was to briefly describe the conventional imaging methods and other novel imaging modalities used for early detection of BCa and outline their pros and cons.

Methods

Literature search was performed on Pubmed, PMC, and Google scholar for the period of January 2014 to February 2018 and using such words as "bladder cancer, bladder tumor, bladder cancer detection, diagnosis and imaging".

Results

A total of 81 published papers were retrieved and are included in the review. For patients with hematuria and suspected of BCa, cystoscopy and CT are most commonly recommended. Ultrasonography, MRI, PET/CT using ¹⁸F-FDG or ¹¹C-choline and recently PET/MRI using ¹⁸F-FDG also play a prominent role in detection of BCa.

Conclusion

For initial diagnosis of BCa, cystoscopy is generally performed. However, cystoscopy can not accurately detect carcinoma insitu (CIS) and can not distinguish benign masses from malignant lesions. CT is used in two modes, CT and computed tomographic urography (CTU), both for dignosis and staging of BCa. However, they cannot differentiate T1 and T2 BCa. MRI is performed to diagnose invasive BCa and can differentiate muscle invasive bladder carcinoma (MIBC) from non-muscle invasive bladder carcinoma (NMIBC). However, CT and MRI have low sensitivity for nodal staging. For nodal staging PET/CT is preferred. PET/MRI provides better differentiation of normal and pathologic structures as compared with PET/CT. Nonetheless none of the approaches can address all issues related for the management of BCa. Novel imaging methods that target specific biomarkers, image BCa early and accurately, and stage the disease are warranted.

A Genomic-clinicopathologic Nomogram for the Preoperative Prediction of Lymph Node Metastasis in Bladder Cancer

Preoperative lymph node (LN) status is important for the treatment of bladder cancer (BCa). Here, we report a genomic-clinicopathologic nomogram for preoperatively predicting LN metastasis in BCa. In the discovery stage, 325 BCa patients from TCGA were involved and LN-status-related mRNAs were selected. In the training stage, multivariate logistic regression analysis was used to developed a genomic-clinicopathologic nomogram for preoperative LN metastasis prediction in the training set (SYSMH set, n=178). In the validation stage, we validated the nomogram using two independent sample sets (SYSUCC set, n=142; RJH set, n=104) with respect to its discrimination, calibration and clinical usefulness. As results, we identified five LN-status-related mRNAs, including ADRA1D, COL10A1, DKK2, HIST2H3D and MMP11. Then, a genomic classifier was developed to classify patients into high- and low-risk groups in the training set. Furthermore, a nomogram incorporating the five-mRNA-based classifier, image-based LN status, transurethral resection (TUR) T stage, and TUR lymphovascular invasion (LVI) was constructed in the training set, which performed well in the training and validation sets. Decision curve analysis demonstrated the clinical value of our nomogram. Thus, our genomic-clinicopathologic nomogram shows favorable discriminatory ability and may aid in clinical decision-making, especially for cN-patients.

A Radiomics Nomogram for the Preoperative Prediction of Lymph Node Metastasis in Bladder Cancer

Purpose: To develop and validate a radiomics nomogram for the preoperative prediction of lymph node (LN) metastasis in bladder cancer.Experimental Design: A total of 118 eligible bladder cancer patients were divided into a training set (n = 80) and a validation set (n = 38). Radiomics features were extracted from arterial-phase CT images of each patient. A radiomics signature was then constructed with the least absolute shrinkage and selection operator algorithm in the training set. Combined with independent risk factors, a radiomics nomogram was built with a multivariate logistic regression model. Nomogram performance was assessed in the training set and validated in the validation set. Finally, decision curve analysis was performed with the combined training and validation set to estimate the clinical usefulness of the nomogram.Results: The radiomics signature, consisting of nine LN status-related features, achieved favorable prediction efficacy. The radiomics nomogram, which incorporated the radiomics signature and CT-reported LN status, also showed good calibration and discrimination in the training set [AUC, 0.9262; 95% confidence interval (CI), 0.8657-0.9868] and the validation set (AUC, 0.8986; 95% CI, 0.7613-0.9901). The decision curve indicated the clinical usefulness of our nomogram. Encouragingly, the nomogram also showed favorable discriminatory ability in the CT-reported LN-negative (cN0) subgroup (AUC, 0.8810; 95% CI, 0.8021-0.9598).Conclusions: The presented radiomics nomogram, a noninvasive preoperative prediction tool that incorporates the radiomics signature and CT-reported LN status, shows favorable predictive accuracy for LN metastasis in patients with bladder cancer. Multicenter validation is needed to acquire high-level evidence for its clinical application. Clin Cancer Res; 23(22); 6904-11. ©2017 AACR.

Preoperative Imaging for Clinical Staging Prior to Radical Cystectomy

The importance of patient selection for quality outcomes following radical cystectomy is critical. Clinical staging is one of the key elements necessary for patient selection, and staging relies on accurate preoperative imaging. Many imaging modalities are available and have been utilized for preoperative staging with published operating characteristics. In this update, we review recently published literature for advances in preoperative imaging prior to radical cystectomy.

Application of dual-energy spectral CT imaging in differential diagnosis of bladder cancer and benign prostate hyperplasia

The aim of this study was to explore the clinical value of dual-energy spectral CT imaging in the differential diagnosis between bladder cancer and benign prostate hyperplasia (BPH).We retrospectively analyzed images of 118 patients who received pelvic dual-energy spectral CT imaging. These patients were later confirmed to have bladder cancer in 61 patients and BPH in 57 patients. CT values of the 2 lesion types from 40 to 140 keV were measured from the monochromatic spectral CT image to generate spectral HU curves. The slope of the spectral curve and the lesion effective atomic number were calculated. The measured parameters were analyzed with independent-sample Mann-Whitney U test.There was a statistically significant difference in CT value between the 2 groups from 40 to 90 keV, with the biggest difference at 40 keV (median and interquartile range: 83.3 HU and 22.9 HU vs 60.6 HU and 16.7 HU, Z = 5.932, P < 0.001). The slope of the spectral HU curve for bladder cancer was markedly higher than that of BPH (median and interquartile range: 0.48 and 0.23 vs 0.26 and 0.22, Z = 5.162, P < 0.001); the difference in effective atomic number (median and interquartile range: 7.99 and 0.21 vs 7.80 and 0.20, Z = 5.233, P < 0.001) was also statistically significant.Dual-energy spectral CT imaging provides high sensitivity and specificity for differentiating bladder cancer from benign prostate hyperplasia.

Pelvic Lymph Node Staging by Combined 18F-FDG-PET/CT Imaging in Bladder Cancer Prior to Radical Cystectomy

BACKGROUND

Accurate lymph node (LN) staging in bladder cancer before radical cystectomy is essential as LN metastases have an independent prognostic value. Most studies used a cutoff of > 10 mm in detecting pelvic LN spread. The aim of this study was to evaluate the diagnostic accuracy of contrast-enhanced computed tomography (CT) and ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET) alone, or combined for preoperative pelvic LN staging.

PATIENTS AND METHODS

We retrospectively analyzed the data of 70 bladder cancer patients that were staged with ¹⁸F-FDG-PET/CT before radical cystectomy between 2012 and 2015. ¹⁸F-FDG-PET images were analyzed visually and semi-quantitatively by calculating the maximum standardized uptake value. CT scans were reviewed using different cutoffs of pelvic LNs, with the best cutoff at 8 mm (area under the curve = 0.684).

RESULTS

Metastatic LNs were confirmed in 53 (2.8%) of 1906 resected LNs in 11 (15.7%) patients. Sensitivity, specificity, and accuracy were 54.5%, 89.8%, and 84.3% for ¹⁸F-FDG-PET alone; 45.5%, 91.5%, and 84.3% for CT (LNs > 8 mm) alone; and 27.3%, 96.6%, and 85.7% for CT (LNs > 10 mm) alone, respectively. Combined ¹⁸F-FDG-PET/CT resulted in a nonsignificant increase of diagnostic accuracy using a cutoff > 8 mm for LN evaluation (63.6%, 86.4%, and 82.9%, respectively). A significant improvement of sensitivity to 63.6% was achieved only when LNs > 10 mm were considered suspicious (P = .046), but this reduced specificity to 88.1% (P = .025).

CONCLUSIONS

Combined ¹⁸F-FDG-PET/CT does not seem to be justified in preoperative staging if the threshold of pelvic LNs is set > 8 mm.

Assessment of colon and bladder crosstalk in an experimental colitis model using contrast-enhanced magnetic resonance imaging

BACKGROUND

Inflammatory bowel disease (IBD) consists of two chronic remitting-relapsing inflammatory disorders in the colon referred to as ulcerative colitis and Crohn's disease (CD). Inflammatory bowel disease affects about 1.4 million Americans. 2,4,6-trinitrobenzene sulfonic acid (TNBS)-induced colitis is a widely used model of experimental intestinal inflammation with characteristic transmural and segmental lesions that are similar to CD.

METHODS

Here, we report on the use of contrast-enhanced magnetic resonance imaging (CE-MRI) to monitor in vivo bladder permeability changes resulting from bladder crosstalk following colon TNBS exposure, and TNBS-induced colitis. Changes in MRI signal intensities and histology were evaluated for both colon and bladder regions.

KEY RESULTS

Uptake of contrast agent in the colon demonstrated a significant increase in signal intensity (SI) for TNBS-exposed rats (p < 0.01) compared to controls. In addition, a significant increase in bladder SI for colon TNBS-exposed rats (p < 0.001) was observed compared to saline controls. Histological damage within the colon was observed, however, bladder histology indicated a normal urothelium in rats with TNBS-induced colitis, despite increased permeability seen by CE-MRI.

CONCLUSIONS & INFERENCES

Contrast-enhanced MRI was able to quantitatively measure inflammation associated with TNBS-induced colitis, and assess bladder crosstalk measured as an increase in urothelial permeability. Although CE-MRI is routinely used to assess inflammation with IBD, currently there is no diagnostic test to assess bladder crosstalk with this disease, and our developed method may be useful in providing crosstalk information between organ and tissue systems in IBD patients, in addition to colitis.

Optimal management of muscle-invasive bladder cancer - a review

Muscle-invasive bladder cancer is a complex disease requiring aggressive management. Patients are often older with comorbid conditions that impact treatment options. This review describes the available therapies for invasive urothelial carcinoma, including chemotherapy, radical extirpative surgery, and bladder-preserving strategies.

Functional Radiotherapy Targeting using Focused Dose Escalation

Various quantitative and semi-quantitative imaging biomarkers have been identified that may serve as valid surrogates for the risk of recurrence after radiotherapy. Tumour characteristics, such as hypoxia, vascularity, cellular proliferation and clonogen density, can be geographically mapped using biological imaging techniques. The potential gains in therapeutic ratio from the precision targeting of areas of intrinsic resistance makes focused dose escalation an exciting field of study. This overview will explore the issues surrounding biologically optimised radiotherapy, including its requirements, feasibility, technical considerations and potential applicability.