Radiomics Analysis Based on Ultrasound Images to Distinguish the Tumor Stage and Pathological Grade of Bladder Cancer

Gao, Ruizhi; Wen, Rong; Wen, Dong‐Yue; Huang, Jing; Qin, Hui; Li, Xin; Wang, Xinrong; He, Yun; Yang, Hong

doi:10.1002/jum.15659

Cited by 9 publications

(9 citation statements)

References 46 publications

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“…In MIBC, to determine whether a lesion still exists after neoadjuvant therapy in MIBC, it is necessary to examine the T2, DWI, and DCE sequences on MRI. Then it is evaluated if there is a response to the therapy, which can be partial, complete, or absent [26].…”

Section: Multiparametric-mri After Neoadjuvant Therapymentioning

confidence: 99%

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Role of Multiparametric-MRI in Bladder Cancer

Eusebi¹,

Masino

Gifuni

et al. 2023

Curr Radiol Rep

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Purpose of Review This narrative review article aims to show the actual role of imaging, in particular MRI, and the role of VI-RADS Score, in recognition and follow-up of the tumor. Recent Findings A team of professionals created VI-RADS with the goal of standardizing the acquisition and interpretation of multiparametric-MRI in bladder cancer. Summary Bladder cancer is the most common cancer involving the urinary system. It is the fourth most common urological cancer in men and the second most frequent cancer affecting the urinary tract. Main risks factors are advanced age, male sex, and cigarette smoking. Bladder cancer ranges from unaggressive and usually non-invasive tumors that recur and commit patients to long-term invasive surveillance, to aggressive and invasive tumors with high disease-specific mortality. At the time of diagnosis, 70% of patients are experiencing non-muscle-invasive bladder cancer. Vesical imaging-reporting and data system score (VI-RADS) is a scoring system useful to standardize the approach to multiparametric-MRI interpretation, and reporting for bladder cancer.

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Section: Multiparametric-mri After Neoadjuvant Therapymentioning

confidence: 99%

“…The use of the VI-RADS score is also proposed in the evaluation of the bladder cancer response to systemic therapy [26].…”

Section: Multiparametric-mri After Neoadjuvant Therapymentioning

confidence: 99%

Role of Multiparametric-MRI in Bladder Cancer

Eusebi¹,

Masino

Gifuni

et al. 2023

Curr Radiol Rep

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“…In another study (Xie et al 2021), PET/CT-based nomogram incorporating SUV max and CT radiomics for preoperative nodal staging in non-small cell lung cancer was developed. Gao et al (2021) applied ultrasound radiomics analysis for preoperative prediction of tumor stage and pathological grade of bladder cancer. Recently, it was clearly shown that 68 Ga-radiolabeled prostate-specific membrane antigen PET (PSMA-PET) radiomics could predict Gleason score in prostate cancer (Solari et al 2022).…”

Section: Dl-based Featuresmentioning

confidence: 99%

Radiomics-guided radiation therapy: opportunities and challenges

Abdollahi

Chin²,

Clark

et al. 2022

Phys. Med. Biol.

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Radiomics is an advanced image-processing framework, which extracts image features and considers them as biomarkers towards personalized medicine. Applications include disease detection, diagnosis, prognosis, and therapy response assessment/prediction. As radiation therapy aims for further individualized treatments, radiomics could play a critical role in various steps before, during and after treatment. Elucidation of the concept of radiomics-guided radiation therapy (RGRT) is the aim of this review, attempting to highlight opportunities and challenges underlying the use of radiomics to guide clinicians and physicists towards more effective radiation treatments. This work identifies the value of RGRT in various steps of radiotherapy from patient selection to follow-up, and subsequently provides recommendations to improve future radiotherapy using quantitative imaging features.

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“…( 23 ). Ultrasound-based radiomics models may accurately predict preoperative tumor stage and pathological grading in BLCA ( 24 ). Magnetic resonance imaging radiomics might predict Ki67 expression status and be linked to survival outcomes of patients with BCa ( 25 ).…”

Section: Introductionmentioning

confidence: 99%

Construction and prognostic value of enhanced CT image omics model for noninvasive prediction of HRG in bladder cancer based on logistic regression and support vector machine algorithm

Luo²,

Liu³

et al. 2023

Front. Oncol.

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BackgroundUrothelial Carcinoma of the bladder (BLCA) is the most prevalent cancer of the urinary system. In cancer patients, HRG fusion is linked to a poor prognosis. The prediction of HRG expression by imaging omics in BLCA has not yet been fully investigated.MethodsHRG expression in BLCA and healthy adjoining tissues was primarily identified utilizing data sourced from The Cancer Genome Atlas (TCGA). Using Kaplan–Meier survival curves and Landmark analysis, the relationship between HRG expression, clinicopathological parameters, and overall survival (OS) was investigated. Additionally, gene set variation analysis (GSVA) was conducted and CIBERSORTx was used to investigate the relationship between HRG expression and immune cell infiltration. The Cancer Imaging Archive (TCIA) provided CT images that were used for prognostic analysis, radiomic feature extraction, and construction of the model, respectively. The HRG expression levels were predicted using the constructed and evaluated LR and SMV models.ResultsHRG expression was shown to be substantially lower in BLCA tumors as opposed to that observed in normal tissues (p < 0.05). HRG expression had a close positive relationship with Eosinophils and a close negative relationship with B cells naive. The findings of the Landmark analysis illustrated that higher HRG was associated with improved patient survival at an early stage (P=0.048). The predictive performance of the two models, based on logistic regression analysis and support vector machine, was outstanding in the training and validation sets, yielding AUCs of 0.722 and 0.708, respectively, in the SVM model, and 0.727 and 0.662, respectively, in the LR.The models have good predictive efficiency.ConclusionHRG expression levels can have a significant impact on BLCA patients’ prognoses. The radiomic characteristics can successfully predict the pre-surgical HRG expression levels, based on CT- Image omics.

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Radiomics Analysis Based on Ultrasound Images to Distinguish the Tumor Stage and Pathological Grade of Bladder Cancer

Cited by 9 publications

References 46 publications

Role of Multiparametric-MRI in Bladder Cancer

Role of Multiparametric-MRI in Bladder Cancer

Radiomics-guided radiation therapy: opportunities and challenges

Construction and prognostic value of enhanced CT image omics model for noninvasive prediction of HRG in bladder cancer based on logistic regression and support vector machine algorithm

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