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1.
Sci Data ; 11(1): 699, 2024 Jun 27.
Article in English | MEDLINE | ID: mdl-38937479

ABSTRACT

Bladder cancer is one of the leading causes of cancer-related mortality in the urinary system. Understanding genomic information is important in the treatment and prognosis of bladder cancer, but the current method used to identify mutations is time-consuming and labor-intensive. There are now many novel and convenient ways to predict cancerous genomics from pathological slides. However, the publicly available datasets are limited, especially for Asian populations. In this study, we developed a dataset consisting of 75 Asian cases of bladder cancers and 112 Whole-Slide Images with one to two images obtained for each patient. This dataset provides information on the most frequently and clinically significant mutated genes derived by whole-exome sequencing in these patients. This dataset will facilitate exploration and development of novel diagnostic and therapeutic technologies for bladder cancer.


Subject(s)
Urinary Bladder Neoplasms , Humans , Asian People/genetics , Exome Sequencing , Genomics , Mutation , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/genetics
2.
BMC Med Imaging ; 24(1): 148, 2024 Jun 17.
Article in English | MEDLINE | ID: mdl-38886638

ABSTRACT

BACKGROUND: Preoperative discrimination between non-muscle-invasive bladder cancer (NMIBC) and the muscle invasive bladder cancer (MIBC) is a determinant of management. The purpose of this research is to employ radiomics to evaluate the diagnostic value in determining muscle invasiveness of compressed sensing (CS) accelerated 3D T2-weighted-SPACE sequence with high resolution and short acquisition time. METHODS: This prospective study involved 108 participants who underwent preoperative 3D-CS-T2-weighted-SPACE, 3D-T2-weighted-SPACE and T2-weighted sequences. The cohort was divided into training and validation cohorts in a 7:3 ratio. In the training cohort, a Rad-score was constructed based on radiomic features selected by intraclass correlation coefficients, pearson correlation coefficient and least absolute shrinkage and selection operator . Multivariate logistic regression was used to develop a nomogram combined radiomics and clinical indices. In the validation cohort, the performances of the models were evaluated by ROC, calibration, and decision curves. RESULTS: In the validation cohort, the area under ROC curve of 3D-CS-T2-weighted-SPACE, 3D-T2-weighted-SPACE and T2-weighted models were 0.87(95% confidence interval (CI):0.73-1.00), 0.79(95%CI:0.63-0.96) and 0.77(95%CI:0.60-0.93), respectively. The differences in signal-to-noise ratio and contrast-to-noise ratio between 3D-CS-T2-weighted-SPACE and 3D-T2-weighted-SPACE sequences were not statistically significant(p > 0.05). While the clinical model composed of three clinical indices was 0.74(95%CI:0.55-0.94) and the radiomics-clinical nomogram model was 0.88(95%CI:0.75-1.00). The calibration curves confirmed high goodness of fit, and the decision curve also showed that the radiomics model and combined nomogram model yielded higher net benefits than the clinical model. CONCLUSION: The radiomics model based on compressed sensing 3D T2WI sequence, which was acquired within a shorter acquisition time, showed superior diagnostic efficacy in muscle invasion of bladder cancer. Additionally, the nomogram model could enhance the diagnostic performance.


Subject(s)
Imaging, Three-Dimensional , Neoplasm Invasiveness , Urinary Bladder Neoplasms , Humans , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/pathology , Male , Female , Middle Aged , Neoplasm Invasiveness/diagnostic imaging , Prospective Studies , Imaging, Three-Dimensional/methods , Aged , Magnetic Resonance Imaging/methods , ROC Curve , Nomograms , Radiomics
3.
BMJ Case Rep ; 17(6)2024 Jun 04.
Article in English | MEDLINE | ID: mdl-38834309

ABSTRACT

Rhabdomyosarcomas are the most common soft-tissue sarcomas, found usually in the younger age group. Histologically, they are subdivided into embryonal, alveolar, pleomorphic and not otherwise specified. They have a heterogenous appearance on imaging with few additional characteristic features based on the subtype. Botryoid variant of embryonal rhabdomyosarcoma commonly involves the genitourinary and the biliary system. They can be multifocal. Most of these lesions have a heterogenous appearance on imaging with areas of necrosis and haemorrhage. On ultrasound, they are polypoidal with cystic areas and are vascular. The lesions are hyperintense on T2 sequences, isointense to the skeletal muscle on T1 sequences and show heterogenous enhancement. Surgery is the mainstay of treatment along with radiotherapy or chemotherapy depending on the site and the stage of the tumour. We report a case of botryoid variant of rhabdomyosarcoma involving the vagina and the urinary bladder.


Subject(s)
Rhabdomyosarcoma, Embryonal , Urinary Bladder Neoplasms , Vaginal Neoplasms , Female , Humans , Magnetic Resonance Imaging , Rhabdomyosarcoma, Embryonal/pathology , Rhabdomyosarcoma, Embryonal/diagnosis , Rhabdomyosarcoma, Embryonal/diagnostic imaging , Rhabdomyosarcoma, Embryonal/surgery , Ultrasonography , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/pathology , Vaginal Neoplasms/pathology , Vaginal Neoplasms/diagnostic imaging , Vaginal Neoplasms/surgery , Vaginal Neoplasms/diagnosis , Child, Preschool
4.
Genet Res (Camb) ; 2024: 4285171, 2024.
Article in English | MEDLINE | ID: mdl-38715622

ABSTRACT

Bladder cancer has recently seen an alarming increase in global diagnoses, ascending as a predominant cause of cancer-related mortalities. Given this pressing scenario, there is a burgeoning need to identify effective biomarkers for both the diagnosis and therapeutic guidance of bladder cancer. This study focuses on evaluating the potential of high-definition computed tomography (CT) imagery coupled with RNA-sequencing analysis to accurately predict bladder tumor stages, utilizing deep residual networks. Data for this study, including CT images and RNA-Seq datasets for 82 high-grade bladder cancer patients, were sourced from the TCIA and TCGA databases. We employed Cox and lasso regression analyses to determine radiomics and gene signatures, leading to the identification of a three-factor radiomics signature and a four-gene signature in our bladder cancer cohort. ROC curve analyses underscored the strong predictive capacities of both these signatures. Furthermore, we formulated a nomogram integrating clinical features, radiomics, and gene signatures. This nomogram's AUC scores stood at 0.870, 0.873, and 0.971 for 1-year, 3-year, and 5-year predictions, respectively. Our model, leveraging radiomics and gene signatures, presents significant promise for enhancing diagnostic precision in bladder cancer prognosis, advocating for its clinical adoption.


Subject(s)
Neoplasm Staging , Neural Networks, Computer , Tomography, X-Ray Computed , Urinary Bladder Neoplasms , Urinary Bladder Neoplasms/genetics , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/pathology , Humans , Tomography, X-Ray Computed/methods , Male , Female , RNA-Seq/methods , Aged , Nomograms , Middle Aged , Biomarkers, Tumor/genetics , ROC Curve , Prognosis , Transcriptome , Radiomics
5.
Scand J Urol ; 59: 90-97, 2024 May 02.
Article in English | MEDLINE | ID: mdl-38698545

ABSTRACT

OBJECTIVE: To evaluate whether artificial intelligence (AI) based automatic image analysis utilising convolutional neural networks (CNNs) can be used to evaluate computed tomography urography (CTU) for the presence of urinary bladder cancer (UBC) in patients with macroscopic hematuria. METHODS: Our study included patients who had undergone evaluation for macroscopic hematuria. A CNN-based AI model was trained and validated on the CTUs included in the study on a dedicated research platform (Recomia.org). Sensitivity and specificity were calculated to assess the performance of the AI model. Cystoscopy findings were used as the reference method. RESULTS: The training cohort comprised a total of 530 patients. Following the optimisation process, we developed the last version of our AI model. Subsequently, we utilised the model in the validation cohort which included an additional 400 patients (including 239 patients with UBC). The AI model had a sensitivity of 0.83 (95% confidence intervals [CI], 0.76-0.89), specificity of 0.76 (95% CI 0.67-0.84), and a negative predictive value (NPV) of 0.97 (95% CI 0.95-0.98). The majority of tumours in the false negative group (n = 24) were solitary (67%) and smaller than 1 cm (50%), with the majority of patients having cTaG1-2 (71%). CONCLUSIONS: We developed and tested an AI model for automatic image analysis of CTUs to detect UBC in patients with macroscopic hematuria. This model showed promising results with a high detection rate and excessive NPV. Further developments could lead to a decreased need for invasive investigations and prioritising patients with serious tumours.


Subject(s)
Artificial Intelligence , Hematuria , Tomography, X-Ray Computed , Urinary Bladder Neoplasms , Urography , Humans , Hematuria/etiology , Hematuria/diagnostic imaging , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/complications , Male , Aged , Female , Tomography, X-Ray Computed/methods , Urography/methods , Middle Aged , Neural Networks, Computer , Sensitivity and Specificity , Aged, 80 and over , Retrospective Studies , Adult
6.
BMC Urol ; 24(1): 109, 2024 May 18.
Article in English | MEDLINE | ID: mdl-38762447

ABSTRACT

INTRODUCTION: Abscess of the bladder wall is a rare urological disorder, with a few cases recorded in the literature. The finding of a bladder wall mass via computed tomography (CT) imaging in a visiting patient is the subject of this report. CASE DISCUSSION: A 37-year-old woman with persistent pain in the suprapubic area and lower urinary tract symptoms was examined as a case study. Through a CT scan revealed an inhomogeneous structure in the anteroinferior part of the right bladder. A cystoscopy procedure followed by transurethral resection was performed to remove the mass, which was found to be an abscess. A Foley catheter with irrigation was administered after surgery, and the patient goes home in three days. CONCLUSION: the patient had no symptoms or discomfort in the lower urinary tract after follow-up. Despite the rarity of bladder wall abscesses, cystoscopy can be used to aid diagnosis. Transurethral resection of bladder wall can reduce the mass and eliminate the possibility of malignancy.


Subject(s)
Abscess , Urinary Bladder Diseases , Urinary Bladder Neoplasms , Humans , Female , Adult , Abscess/diagnostic imaging , Urinary Bladder Neoplasms/surgery , Urinary Bladder Neoplasms/diagnostic imaging , Diagnosis, Differential , Urinary Bladder Diseases/surgery , Urinary Bladder Diseases/diagnostic imaging , Urinary Bladder Diseases/diagnosis , Cystoscopy , Tomography, X-Ray Computed
7.
Med Image Anal ; 95: 103189, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38776840

ABSTRACT

Segmentation of bladder tumors from medical radiographic images is of great significance for early detection, diagnosis and prognosis evaluation of bladder cancer. Deep Convolution Neural Networks (DCNNs) have been successfully used for bladder tumor segmentation, but the segmentation based on DCNN is data-hungry for model training and ignores clinical knowledge. From the clinical view, bladder tumors originate from the mucosal surface of bladder and must rely on the bladder wall to survive and grow. This clinical knowledge of tumor location is helpful to improve the bladder tumor segmentation. To achieve this, we propose a novel bladder tumor segmentation method, which incorporates the clinical logic rules of bladder tumor and bladder wall into DCNNs to harness the tumor segmentation. Clinical logical rules provide a semantic and human-readable knowledge representation and are easy for knowledge acquisition from clinicians. In addition, incorporating logical rules of clinical knowledge helps to reduce the data dependency of the segmentation network, and enables precise segmentation results even with limited number of annotated images. Experiments on bladder MR images collected from the collaborating hospital validate the effectiveness of the proposed bladder tumor segmentation method.


Subject(s)
Neural Networks, Computer , Urinary Bladder Neoplasms , Urinary Bladder Neoplasms/diagnostic imaging , Humans , Magnetic Resonance Imaging/methods , Image Interpretation, Computer-Assisted/methods , Deep Learning
8.
Abdom Radiol (NY) ; 49(6): 1975-1986, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38619611

ABSTRACT

OBJECTIVE: To investigate multiphase computed tomography (CT) radiomics-based combined with clinical factors to predict overall survival (OS) in patients with bladder urothelial carcinoma (BLCA) who underwent transurethral resection of bladder tumor (TURBT). METHODS: Data were retrospectively collected from 114 patients with primary BLCA from February 2016 to February 2018. The regions of interest (ROIs) of the plain, arterial, and venous phase images were manually segmented. The Cox regression algorithm was used to establish 3 basic models for the plain phase (PP), arterial phase (AP), and venous phase (VP) and 2 combination models (AP + VP and PP + AP + VP). The highest-performing radiomics model was selected to calculate the radiomics score (Rad-score), and independent risk factors affecting patients' OS were analyzed using Cox regression. The Rad-score and clinical risk factors were combined to construct a joint model and draw a visualized nomogram. RESULTS: The combined model of PP + AP + VP showed the best performance with the Akaike Information Criterion (AIC) and Consistency Index (C-index) in the test group of 130.48 and 0.779, respectively. A combined model constructed with two independent risk factors (age and Ki-67 expression status) in combination with the Rad-score outperformed the radiomics model alone; AIC and C-index in the test group were 115.74 and 0.840, respectively. The calibration curves showed good agreement between the predicted probabilities of the joint model and the actual (p < 0.05). The decision curve showed that the joint model had good clinical application value within a large range of threshold probabilities. CONCLUSION: This new model can be used to predict the OS of patients with BLCA who underwent TURBT.


Subject(s)
Tomography, X-Ray Computed , Urinary Bladder Neoplasms , Humans , Male , Female , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/pathology , Urinary Bladder Neoplasms/surgery , Retrospective Studies , Middle Aged , Aged , Prognosis , Tomography, X-Ray Computed/methods , Predictive Value of Tests , Aged, 80 and over , Nomograms , Carcinoma, Transitional Cell/diagnostic imaging , Carcinoma, Transitional Cell/pathology , Adult , Contrast Media , Cystectomy/methods , Risk Factors , Radiomics
9.
Abdom Radiol (NY) ; 49(5): 1615-1625, 2024 05.
Article in English | MEDLINE | ID: mdl-38652125

ABSTRACT

PURPOSE: To investigate the influence of deep learning reconstruction (DLR) on bladder MRI, specifically examination time, image quality, and diagnostic performance of vesical imaging reporting and data system (VI-RADS) within a prospective clinical cohort. METHODS: Seventy participants with bladder cancer who underwent MRI between August 2022 and February 2023 with a protocol containing standard T2-weighted imaging (T2WIS), standard diffusion-weighted imaging (DWIS), fast T2WI with DLR (T2WIDL), and fast DWI with DLR (DWIDL) were enrolled in this prospective study. Imaging quality was evaluated by measuring signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and qualitative image quality scoring. Additionally, the apparent diffusion coefficient (ADC) of bladder lesions derived from DWIS and DWIDL was measured and VI-RADS scoring was performed. Paired t-test or paired Wilcoxon signed-rank test were performed to compare image quality score, SNR, CNR, and ADC between standard sequences and fast sequences with DLR. The diagnostic performance for VI-RADS was assessed using the area under the receiver operating characteristic curve (AUC). RESULTS: Compared to T2WIS and DWIS, T2WIDL and DWIDL reduced the acquisition time from 5:57 min to 3:13 min and showed significantly higher SNR, CNR, qualitative image quality score of overall image quality, image sharpness, and lesion conspicuity. There were no significant differences in ADC and AUC of VI-RADS between standard sequences and fast sequences with DLR. CONCLUSIONS: The application of DLR to T2WI and DWI reduced examination time and significantly improved image quality, maintaining ADC and the diagnostic performance of VI-RADS for evaluating muscle invasion in bladder cancer.


Subject(s)
Deep Learning , Magnetic Resonance Imaging , Urinary Bladder Neoplasms , Humans , Prospective Studies , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/pathology , Male , Female , Aged , Middle Aged , Magnetic Resonance Imaging/methods , Neoplasm Invasiveness/diagnostic imaging , Urinary Bladder/diagnostic imaging , Aged, 80 and over , Adult , Image Interpretation, Computer-Assisted/methods , Diffusion Magnetic Resonance Imaging/methods
10.
J Surg Oncol ; 129(7): 1325-1331, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38583145

ABSTRACT

BACKGROUND: The extent of pelvic lymphadenectomy (PLND) as part of radical cystectomy (RC) for bladder cancer (BC) remains unclear. Sentinel-based and lymphangiographic approaches could lead to reduced morbidity without sacrificing oncologic safety. OBJECTIVE: To evaluate the feasibility and diagnostic value of fluorescence-guided template sentinel region dissection (FTD) using a handheld near-infrared fluorescence (NIRF) camera in open radical cystectomy. DESIGN, SETTING, AND PARTICIPANTS: After peritumoral cystoscopic injection of indocyanine green (ICG) 21 patients underwent open RC with FTD due to BC between June 2019 and June 2021. Intraoperatively, the FIS-00 Hamamatsu Photonics® NIRF camera was used to identify and resect fluorescent template sentinel regions (FTRs) followed by extended pelvic lymphadenectomy (ePLND) as oncological back-up. OUTCOME MEASUREMENT AND STATISTICAL ANALYSIS: Descriptive analysis of positive and negative results per template region. RESULTS AND LIMITATIONS: FTRs were identified in all 21 cases. Median time (range) from ICG injection to fluorescence detection was 75 (55-125) minutes. On average (SD), 33.4 (9.6) lymph nodes were dissected per patient. Considering template regions as the basis of analysis, 67 (38.3%) of 175 resected regions were NIRF-positive, with 13 (7.4%) regions harboring lymph node metastases. We found no metastatic lymph nodes in NIRF-negative template regions. Outside the standard template, two NIRF-positive benign nodes were identified. CONCLUSION: The concept of NIRF-guided FTD proved for this group all lymph node metastases to be found in NIRF-positive template regions. Pending validation in a larger collective, resection of approximately 40% of standard regions may be sufficient and may result in less morbidity.


Subject(s)
Cystectomy , Lymph Node Excision , Urinary Bladder Neoplasms , Humans , Urinary Bladder Neoplasms/surgery , Urinary Bladder Neoplasms/pathology , Urinary Bladder Neoplasms/diagnostic imaging , Lymph Node Excision/methods , Lymph Node Excision/instrumentation , Cystectomy/methods , Cystectomy/instrumentation , Female , Male , Aged , Middle Aged , Indocyanine Green , Feasibility Studies , Fluorescence , Prognosis , Follow-Up Studies , Spectroscopy, Near-Infrared/methods , Spectroscopy, Near-Infrared/instrumentation , Lymph Nodes/pathology , Lymph Nodes/surgery , Lymph Nodes/diagnostic imaging , Aged, 80 and over , Coloring Agents
11.
Cancer Imaging ; 24(1): 49, 2024 Apr 08.
Article in English | MEDLINE | ID: mdl-38584289

ABSTRACT

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.


Subject(s)
Urinary Bladder Neoplasms , Urinary Bladder , Male , Humans , Adult , Middle Aged , Aged , Urinary Bladder/diagnostic imaging , Urinary Bladder/pathology , Neoadjuvant Therapy , Retrospective Studies , Magnetic Resonance Imaging/methods , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/drug therapy , Urinary Bladder Neoplasms/pathology
12.
R I Med J (2013) ; 107(5): 26-32, 2024 May 02.
Article in English | MEDLINE | ID: mdl-38687266

ABSTRACT

Bladder cancer is the 6th most common malignancy in the United States, with urothelial carcinomas comprising over 95% of cases of bladder cancer, and commands a significant disease burden in Rhode Island. Imaging studies can provide valuable diagnostic information for urothelial carcinomas at initial presentation and are routinely used for noninvasive staging, treatment response monitoring, and post-treatment surveillance. This review aims to discuss and highlight three imaging modalities: ultrasonography, computed tomography, and magnetic resonance imaging, with particular focus on the notable features and appearance of urothelial carcinoma on each modality and their relative utility throughout the disease course. A general overview of disease epidemiology and treatment practices is also provided.


Subject(s)
Magnetic Resonance Imaging , Tomography, X-Ray Computed , Ultrasonography , Urinary Bladder Neoplasms , Humans , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/epidemiology , Urinary Bladder Neoplasms/diagnosis , Carcinoma, Transitional Cell/diagnostic imaging , Carcinoma, Transitional Cell/epidemiology , Carcinoma, Transitional Cell/diagnosis , Rhode Island/epidemiology
13.
Acta Radiol ; 65(5): 506-512, 2024 May.
Article in English | MEDLINE | ID: mdl-38591942

ABSTRACT

BACKGROUND: Apparent diffusion coefficient (ADC) value is an important part of bladder cancer magnetic resonance imaging (MRI) assessment and can predict the aggressive and invasive potentials. There is growing interest in whole tumor volume measurements. PURPOSE: To investigate if the volumetric ADC measurement method will significantly exceed the diagnostic performance of the selected region of interest (ROI) method in everyday practice. MATERIAL AND METHODS: A prospective evaluation was carried out of 50 patients with bladder cancer by two radiologists. The mean and the minimum ADC values were measured using both methods. The inter-reader agreement was determined by the intraclass correlation coefficient. The ADC values were compared between different grades, states of muscle invasion, and lympho-vascular invasion (LVI); then, validity was evaluated using receiver operating characteristic (ROC) curves. Areas under the curve (AUC) were then compared for the level of statistical significance. RESULTS: The inter-observer agreement was excellent for the ADC values using both methods. The volumetric measurement provides higher mean and lower minimum ADC values with statistically significant differences (P <0.00001). The highest diagnostic accuracy for differentiating tumor grade and predicting muscle invasion was for the minimum ADC by a selected ROI. However, the differences between the achieved AUCs were of no statistical significance. None of the ADC values predicted LVI with statistical significance. CONCLUSION: The selected ROI and volumetric measurement methods of mean and minimum ADC in bladder cancer yield different values, still having comparable diagnostic performance with accurate ROI sampling. The minimum ADC value by ROI is preferred in everyday clinical practice.


Subject(s)
Urinary Bladder Neoplasms , Humans , Urinary Bladder Neoplasms/diagnostic imaging , Female , Male , Aged , Middle Aged , Prospective Studies , Aged, 80 and over , Reproducibility of Results , Adult , Diffusion Magnetic Resonance Imaging/methods , Magnetic Resonance Imaging/methods , Tumor Burden , Observer Variation , Urinary Bladder/diagnostic imaging , Urinary Bladder/pathology , Neoplasm Invasiveness/diagnostic imaging , Image Interpretation, Computer-Assisted/methods
14.
BMC Med Imaging ; 24(1): 98, 2024 Apr 27.
Article in English | MEDLINE | ID: mdl-38678222

ABSTRACT

OBJECTIVES: The aim of the study is to assess the efficacy of the established computed tomography (CT)-based radiomics nomogram combined with radiomics and clinical features for predicting muscle invasion status in bladder cancer (BCa). METHODS: A retrospective analysis was conducted using data from patients who underwent CT urography at our institution between May 2018 and April 2023 with urothelial carcinoma of the bladder confirmed by postoperative histology. There were 196 patients enrolled in all, and each was randomized at random to either the training cohort (n = 137) or the test cohort (n = 59). Eight hundred fifty-one radiomics features in all were retrieved. For feature selection, the significance test and least absolute shrinkage and selection operator (LASSO) approaches were utilized. Subsequently, the radiomics score (Radscore) was obtained by applying linear weighting based on the selected features. The clinical and radiomics model, as well as radiomics-clinical nomogram were all established using logistic regression. Three models were evaluated using analysis of the receiver operating characteristic curve. An area under the curve (AUC) and 95% confidence intervals (CI) as well as specificity, sensitivity, accuracy, negative predictive value, and positive predictive value were included in the analysis. Radiomics-clinical nomogram's performance was assessed based on discrimination, calibration, and clinical utility. RESULTS: After obtaining 851 radiomics features, 12 features were ultimately selected. Histopathological grading and tortuous blood vessels were included in the clinical model. The Radscore and clinical histopathology grading were among the final predictors in the unique nomogram. The three models had an AUC of 0.811 (95% CI, 0.742-0.880), 0.845 (95% CI, 0.781-0.908), and 0.896 (95% CI, 0.846-0.947) in the training cohort and in the test cohort they were 0.808 (95% CI, 0.703-0.913), 0.847 (95% CI, 0.739-0.954), and 0.887 (95% CI, 0.803-0.971). According to the DeLong test, the radiomics-clinical nomogram's AUC in the training cohort substantially differed from that of the clinical model (AUC: 0.896 versus 0.845, p = 0.015) and the radiomics model (AUC: 0.896 versus 0.811, p = 0.002). The Delong test in the test cohort revealed no significant difference among the three models. CONCLUSIONS: CT-based radiomics-clinical nomogram can be a useful tool for quantitatively predicting the status of muscle invasion in BCa.


Subject(s)
Neoplasm Invasiveness , Nomograms , Tomography, X-Ray Computed , Urinary Bladder Neoplasms , Humans , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/pathology , Urinary Bladder Neoplasms/surgery , Male , Retrospective Studies , Female , Tomography, X-Ray Computed/methods , Aged , Middle Aged , Neoplasm Invasiveness/diagnostic imaging , ROC Curve , Predictive Value of Tests , Radiomics
15.
J Pak Med Assoc ; 74(3): 570-572, 2024 Mar.
Article in English | MEDLINE | ID: mdl-38591300

ABSTRACT

It is very un comm on to discover Paraga ngliomas in the uri nar y bladder. Thes e tu mo ur s origina te from the sympathetic nerves which supp ly chromaffin cells in the bladde r wall. They can be classified as functional or nonfunctional. If functional, the most common presentations are with hypertensive crisis or post-micturition syncope. A si lent pa raganglioma of th e bl adder ca n be easily m isdiagnosed w hich can resu lt in severe pe ri- oper ative morbidity. We pre sent a ca se of a male pati ent who was being m a naged fo r hype rt ension for 2-3 ye ars. He presented at The Indus Hospital, Karachi o n 7th August 2022 with gross painless haematuria. An ultrasound scan revealed an echogenic lesion aris ing from base of the urinar y bladder, wh ic h was trea ted via Transurethral Resection o f Bladde r Tumour (TURBT). Histopathological report revealed Paraganglioma of the Bladder. He was later scheduled for Partial Cystectomy (PC) and has been doing well ever since.


Subject(s)
Paraganglioma , Urinary Bladder Neoplasms , Humans , Male , Urinary Bladder/pathology , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/surgery , Paraganglioma/diagnostic imaging , Paraganglioma/surgery , Cystectomy , Pelvis
16.
Abdom Radiol (NY) ; 49(5): 1584-1592, 2024 05.
Article in English | MEDLINE | ID: mdl-38502213

ABSTRACT

PURPOSE: We sought to summarize the value of contrast-enhanced computed tomography (CECT) in the differential diagnosis of bladder paraganglioma (BPG) and bladder cancer. METHODS: The medical records of 19 patients with BPG (13 males, 6 females) and 56 patients with bladder cancer (49 males, 7 females) between November 2007 and June 2023 were retrospectively reviewed. All patients underwent unenhanced and contrast-enhanced CT scanning. RESULTS: Patient age (46.4 ± 11.1 years vs. 58.6 ± 16.0 years), tumor calcification (1/19 vs. 18/56), stalk (0/19 vs. 10/56), internal vessels (15/19 vs. 19/56) and the enlarged adjacent supplying artery (14/19 vs. 10/56) were significantly different between BPG and bladder cancer (P < 0.05). The CT value in the corticomedullary phase (92.4 ± 16.6 HU vs. 64.0 ± 14.5 HU) and the contrast-enhanced value in the corticomedullary phase (54.5 ± 17.4 HU vs. 28.5 ± 12.8 HU) were significantly greater in BPG patients than in bladder cancer patients (P < 0.001), with corresponding area under the curve values of 0.930 and 0.912, respectively. The optimal cutoff values were 83.2 HU and 38.5 HU, respectively. A CT value > 83.2 HU in the corticomedullary phase and a contrast-enhanced CT value > 38.5 HU in the corticomedullary phase were used to indicate BPG with sensitivities of 78.9% and 89.5%, respectively, and specificities of 94.6% and 75.0%, respectively. CONCLUSION: The corticomedullary phase of CECT plays an important role in the preoperative differential diagnosis of BPG and bladder cancer.


Subject(s)
Contrast Media , Paraganglioma , Tomography, X-Ray Computed , Urinary Bladder Neoplasms , Humans , Urinary Bladder Neoplasms/diagnostic imaging , Male , Female , Middle Aged , Diagnosis, Differential , Paraganglioma/diagnostic imaging , Retrospective Studies , Tomography, X-Ray Computed/methods , Adult , Aged , Urinary Bladder/diagnostic imaging
17.
Abdom Radiol (NY) ; 49(5): 1593-1602, 2024 05.
Article in English | MEDLINE | ID: mdl-38502214

ABSTRACT

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.


Subject(s)
Cystectomy , Magnetic Resonance Imaging , Neoplasm Invasiveness , Sensitivity and Specificity , Urinary Bladder Neoplasms , Humans , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/surgery , Urinary Bladder Neoplasms/pathology , Male , Retrospective Studies , Female , Aged , Middle Aged , Magnetic Resonance Imaging/methods , Aged, 80 and over , Adult , Cystectomy/methods , Predictive Value of Tests , Radiology Information Systems
18.
BMC Urol ; 24(1): 63, 2024 Mar 20.
Article in English | MEDLINE | ID: mdl-38509503

ABSTRACT

BACKGROUND: The Vesical Imaging Reporting and Data System (VI-RADS) is widely used for predicting muscle-invasive bladder cancer (MIBC). This study aimed to determine the clinicopathological significance of the VI-RADS ≧4 (VI≧4) group. METHODS: Patients who underwent transurethral resections of bladder tumors during the study period and preoperative magnetic resonance imaging were considered. The patients were pathologically diagnosed with urothelial carcinoma (UC). We first compared the results of patients with VI-RADS scores of 3 and 4 to determine the cut-off score for MIBC; thereafter, the patients were divided into the VI≧4 and VI-RADS ≦3 (VI≦3) groups using VI-RADS. The clinicopathological significance of the VI≧4 group was examined retrospectively by comparing the characteristics of each group. RESULTS: In total, 121 cases were examined, of which 28 were pathologically diagnosed with MIBC. Of the 28 MIBC cases, three (10.7%) had a VI-RADS score of ≦3, and 25 (89.3%) had a VI-RADS score of ≧4. Of the 93 NMIBC cases, 86 (92.5%) had a VI-RADS score of ≦3, and seven (7.5%) had a VI-RADS score of ≧4. The diagnostic performance of the VI-RADS with a cut-off score of 4 was 89.3% for sensitivity, 92.5% for specificity, and an area under the curve (AUC) of 0.91. Contrastingly, for a cut-off score of 3, the sensitivity was 89.3%, specificity was 62.0%, and AUC was 0.72. A VI-RADS score of ≥ 4 could predict MIBC. In the VI≧4 group, 30 of 32 (93.8%) patients had high-grade tumors. The VI≧4 group had significantly more high-grade bladder cancers than the VI≦3 group (p < 0.001 OR = 31.77 95%CI:8.47-1119.07). In addition, the VI≧4 group had more tumor necrosis (VI≧4 vs VI≦3, p < 0.001 OR = 7.46 95%CI:2.61-21.34) and more UC variant cases (VI≧4 vs VI≦3, p = 0.034 OR = 3.28 95%CI:1.05-10.25) than the VI≦3 group. CONCLUSIONS: This study suggests that VI-RADS has a high diagnostic performance in predicting MIBC and that VI-RADS could diagnose high-grade tumors, necrosis, and UC variants.


Subject(s)
Carcinoma, Transitional Cell , Urinary Bladder Neoplasms , Humans , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/pathology , Retrospective Studies , Carcinoma, Transitional Cell/pathology , Urinary Bladder/pathology , Magnetic Resonance Imaging/methods , Necrosis
19.
Urol Oncol ; 42(6): 176.e9-176.e20, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38556403

ABSTRACT

PURPOSE: To compare biparametric magnetic resonance imaging (bp-MRI) radiomics signatures and traditional MRI model for the preoperative prediction of bladder cancer (BCa) grade. MATERIALS AND METHODS: This retrospective study included 255 consecutive patients with pathologically confirmed 113 low-grade and 142 high-grade BCa. The traditional MRI nomogram model was developed using univariate and multivariate logistic regression by the mean apparent diffusion coefficient (ADC), vesical imaging reporting and data system, tumor size, and the number of tumors. Volumes of interest were manually drawn on T2-weighted imaging (T2WI) and ADC maps by 2 radiologists. Using one-way analysis of variance, correlation, and least absolute shrinkage and selection operator methods to select features. Then, a logistic regression classifier was used to develop the radiomics signatures. Receiver operating characteristic (ROC) analysis was used to compare the diagnostic abilities of the radiomics and traditional MRI models by the DeLong test. Finally, decision curve analysis was performed by estimating the clinical usefulness of the 2 models. RESULTS: The area under the ROC curves (AUCs) of the traditional MRI model were 0.841 in the training cohort and 0.806 in the validation cohort. The AUCs of the 3 groups of radiomics model [ADC, T2WI, bp-MRI (ADC and T2WI)] were 0.888, 0.875, and 0.899 in the training cohort and 0.863, 0.805, and 0.867 in the validation cohort, respectively. The combined radiomics model achieved higher AUCs than the traditional MRI model. decision curve analysis indicated that the radiomics model had higher net benefits than the traditional MRI model. CONCLUSION: The bp-MRI radiomics model may help distinguish high-grade and low-grade BCa and outperforming the traditional MRI model. Multicenter validation is needed to acquire high-level evidence for its clinical application.


Subject(s)
Magnetic Resonance Imaging , Neoplasm Grading , Urinary Bladder Neoplasms , Humans , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/pathology , Male , Female , Retrospective Studies , Magnetic Resonance Imaging/methods , Middle Aged , Aged , Nomograms , Adult , Radiomics
20.
Kyobu Geka ; 77(2): 155-159, 2024 Feb.
Article in Japanese | MEDLINE | ID: mdl-38459867

ABSTRACT

A 64-year-old man was admitted because of multiple pulmonary nodules in right upper lobe on chest computed tomography (CT). He had non-muscle invasion bladder cancer resected by transurethral bladder tumor resection seven years ago. Partial resections of the right upper lobe were carried out at the video assisted thracoscopic surgery (VATS) for diagnostic purposes. The postoperative pathological examination revealed featuraes of pulmonary metastasis of bladder cancer. Although chemotherapy after biopsy was performed, a residual tumor in right S3 has grown. Partial resection of residual tumor was carried out thracoscopically and the tumor was diagnosed as metastasis of bladder cancer. He has been without recurrence for 1 year after the operation.


Subject(s)
Lung Neoplasms , Urinary Bladder Neoplasms , Male , Humans , Middle Aged , Neoplasm, Residual , Lung Neoplasms/diagnostic imaging , Lung Neoplasms/surgery , Lung Neoplasms/secondary , Urinary Bladder Neoplasms/diagnostic imaging , Urinary Bladder Neoplasms/surgery , Urinary Bladder Neoplasms/pathology
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