Cornerstones of CT urography: a shared document by the Italian board of urogenital radiology

Ascenti, Giorgio; Cicero, Giuseppe; Cardone, Gianpiero; Bertelli, Elena; Papa, Maurizio; Ciccone, Vincenzo; Manetta, Rosa; Gentili, Francesco; Francioso, Antonio Pio; Mazzei, Maria Antonietta; Floridi, Chiara; Cesare, E. Di; Gandolfo, Nicoletta; Filippo, Massimo De; Miele, Vittorio; Giovagnoni, Andrea

doi:10.1007/s11547-023-01623-8

Cited by 3 publications

(2 citation statements)

References 50 publications

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“…The European Society of Urogenital Radiology recommends a split-bolus CTU protocol for patients at low to intermediate risk of UC, and a single-bolus CTU protocol for patients at high risk of UC [6] . While these recommendations are primarily based on expert opinion, it is essential to recognize that both the nephrographic and excretory phases are complementary for detection of UTUC [7] , [8] .…”

mentioning

confidence: 99%

Re: Kristina F. Galtung, Peter M. Lauritzen, Gunnar Sandbæk, et al. Is a Single Nephrographic Phase Computed Tomography Sufficient for Detecting Urothelial Carcinoma in Patients with Visible Haematuria? A Prospective Paired Noninferiority Comparison. Eur Urol Open Sci 2023;55:1–10

Zattoni,

Dal Moro,

Bednarova

et al. 2024

European Urology Open Science

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mentioning

confidence: 99%

Re: Kristina F. Galtung, Peter M. Lauritzen, Gunnar Sandbæk, et al. Is a Single Nephrographic Phase Computed Tomography Sufficient for Detecting Urothelial Carcinoma in Patients with Visible Haematuria? A Prospective Paired Noninferiority Comparison. Eur Urol Open Sci 2023;55:1–10

Zattoni,

Dal Moro,

Bednarova

et al. 2024

European Urology Open Science

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“…Zattoni et al back their skepticism regarding single nephrographic-phase computed tomography (SNPCT) by elaborating on the utility of multiphase CT. To support their position, they refer to European Association of Urology guidelines, expert opinions, and a review by Janisch et al reporting superior accuracy of CT urography (CTU) in diagnosing UTUC [3] , [4] , [5] , [6] . The evidence summarized in this review forms most of the basis for the guidelines and the expert opinions.…”

mentioning

confidence: 99%

Reply to Fabio Zattoni, Fabrizio Dal Moro, Iliana Bednarova, and Giacomo Novara’s Letter to the Editor re: Kristina F. Galtung, Peter M. Lauritzen, Gunnar Sandbæk, et al. Is a Single Nephrographic Phase Computed Tomography Sufficient for Detecting Urothelial Carcinoma in Patients with Visible Haematuria? A Prospective Paired Noninferiority Comparison. Eur Urol Open Sci 2023;55:1–10

Galtung,

Lauritzen,

Rud

2024

European Urology Open Science

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Construction of a CT Radiomics Model for Predicting Her2 Expression in Bladder Cancer Based on Random Forest Algorithm

Zhang,

Chen,

Xia

et al. 2024

Preprint

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Objective This study aimed to develop and evaluate a predictive model for Human Epidermal Growth Factor Receptor 2 (HER2) expression levels in bladder cancer patients using clinical data and computed tomography (CT) radiomic features across various imaging phases. Methods The investigation involved: (1) compiling clinical data from bladder cancer patients; (2) performing HER2 immunohistochemistry (IHC) assessments post-surgery using the Hercep Test scoring system; (3) delineating tumor regions on CT images to extract radiomic features; (4) utilizing T-tests and Least Absolute Shrinkage and Selection Operator (LASSO) regression to identify the most predictive radiomic features of HER2 status. Decision trees and random forest algorithms were then employed to construct radiomic models. Each model's predictive accuracy, sensitivity, specificity, and area under the curve (AUC) were evaluated through cross-validation, identifying the model with the highest AUC as the optimal radiomic predictor. Results The study included 84 bladder cancer patients, with 53 classified as HER2-negative and 31 as HER2-positive via IHC. Radiomic features that correlated with HER2 status were identified, with three, eight, and two features selected from non-contrast, arterial, and venous phase CTs, respectively. Models based solely on arterial phase features exhibited modest predictive capacity (AUC = 0.44), which improved slightly with the inclusion of clinical data (AUC = 0.48). However, a model integrating features from all three CT phases (totaling 13 features) significantly enhanced performance, achieving an AUC of 0.78, which further improved to 0.83 when combined with clinical variables. Conclusion CT-based radiomics is a viable method for predicting HER2 expression in bladder cancer. The comprehensive model, incorporating features from non-contrast, arterial, and venous CT phases alongside clinical data, demonstrated superior predictive efficacy.

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Cornerstones of CT urography: a shared document by the Italian board of urogenital radiology

Cited by 3 publications

References 50 publications

Re: Kristina F. Galtung, Peter M. Lauritzen, Gunnar Sandbæk, et al. Is a Single Nephrographic Phase Computed Tomography Sufficient for Detecting Urothelial Carcinoma in Patients with Visible Haematuria? A Prospective Paired Noninferiority Comparison. Eur Urol Open Sci 2023;55:1–10

Re: Kristina F. Galtung, Peter M. Lauritzen, Gunnar Sandbæk, et al. Is a Single Nephrographic Phase Computed Tomography Sufficient for Detecting Urothelial Carcinoma in Patients with Visible Haematuria? A Prospective Paired Noninferiority Comparison. Eur Urol Open Sci 2023;55:1–10

Construction of a CT Radiomics Model for Predicting Her2 Expression in Bladder Cancer Based on Random Forest Algorithm

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