Zine-Eddine Khene1, Claire Richard1, Juliette Hascoet2, Anis Gasmi1, Anna Goujon1, Charlène Brochard3, Magali Jezequel4, Quentin Alimi5, Laurent Siproudhis3, Guillaume Bouguen6, Jacques Kerdraon7, Andrea Manunta5, Xavier Gamé8, Romain Mathieu1, Benoit Peyronnet9. 1. Service d'urologie, CHU Rennes, 35000 Rennes, France. 2. Service d'urologie, CHU Rennes, 35000 Rennes, France; Centre de référence spina bifida, CHU Rennes, 35000 Rennes, France; Equipe thématique INPHY CIC 1414 et INSERM UMR 991, CHU Rennes, 35000 Rennes, France. 3. Centre de référence spina bifida, CHU Rennes, 35000 Rennes, France; Equipe thématique INPHY CIC 1414 et INSERM UMR 991, CHU Rennes, 35000 Rennes, France; Service de Gastro-Entérologie, CHU Rennes, 35000 Rennes, France. 4. Centre de référence spina bifida, CHU Rennes, 35000 Rennes, France. 5. Service d'urologie, CHU Rennes, 35000 Rennes, France; Centre de référence spina bifida, CHU Rennes, 35000 Rennes, France. 6. Equipe thématique INPHY CIC 1414 et INSERM UMR 991, CHU Rennes, 35000 Rennes, France; Service de Gastro-Entérologie, CHU Rennes, 35000 Rennes, France. 7. Centre de référence spina bifida, CHU Rennes, 35000 Rennes, France; Centre de rééducation de Kerpape, 56270 Ploemeur, France. 8. Département d'Urologie, Transplantation Rénale et Andrologie, CHU Rangueil, 33000 Toulouse, France. 9. Service d'urologie, CHU Rennes, 35000 Rennes, France; Centre de référence spina bifida, CHU Rennes, 35000 Rennes, France; Equipe thématique INPHY CIC 1414 et INSERM UMR 991, CHU Rennes, 35000 Rennes, France. Electronic address: peyronnetbenoit@hotmail.fr.
Abstract
OBJECTIVE: To investigate computed tomography (CT) texture analysis of the bladder wall as a predictor of urodynamics findings in adult patient with spina bifida. METHODS: A single-center prospective trial was conducted from March 2015 to March 2017 including all consecutive adult spina bifida patients seen for urodynamic testing. A contrast-enhanced abdominal CT was systematically performed in all patients during the same visit. Texture features of the bladder wall related to the gray-level histogram and gray-level co-occurrence were evaluated on CT images. Multivariate analysis was performed to identify independent predictors of poor bladder compliance and detrusor overactivity among clinical and texture parameters. RESULTS: Fourty patients were included. The Lasso penalized logistic regression analysis identified 2 texture parameters as potential predictors of poor bladder compliance: Skewness (coefficient weight, -1.81) and S.1.1.SumVarnc (coefficient weight, -3.52). Multivariate logistic regression analysis confirmed skewness (odds ratio [confidence interval 95%] = 0.40 [0.14, 0.97], P = .04) as an independent predictor of poor bladder compliance. The Lasso penalized logistic regression analysis identified one texture parameters as potential predictor of detrusor overactivity: Kurtosis (coefficient weight, -3.52), which was confirmed in multivariate logistic regression analysis (odds ratio [confidence interval 95%] = 1.12 [1.01, 1.55], P = .02). CONCLUSION: Our findings demonstrate that CT texture analysis of the bladder wall might be an interesting tool to identify spina bifida patients with high risk urodynamic features.
OBJECTIVE: To investigate computed tomography (CT) texture analysis of the bladder wall as a predictor of urodynamics findings in adult patient with spina bifida. METHODS: A single-center prospective trial was conducted from March 2015 to March 2017 including all consecutive adult spina bifidapatients seen for urodynamic testing. A contrast-enhanced abdominal CT was systematically performed in all patients during the same visit. Texture features of the bladder wall related to the gray-level histogram and gray-level co-occurrence were evaluated on CT images. Multivariate analysis was performed to identify independent predictors of poor bladder compliance and detrusor overactivity among clinical and texture parameters. RESULTS: Fourty patients were included. The Lasso penalized logistic regression analysis identified 2 texture parameters as potential predictors of poor bladder compliance: Skewness (coefficient weight, -1.81) and S.1.1.SumVarnc (coefficient weight, -3.52). Multivariate logistic regression analysis confirmed skewness (odds ratio [confidence interval 95%] = 0.40 [0.14, 0.97], P = .04) as an independent predictor of poor bladder compliance. The Lasso penalized logistic regression analysis identified one texture parameters as potential predictor of detrusor overactivity: Kurtosis (coefficient weight, -3.52), which was confirmed in multivariate logistic regression analysis (odds ratio [confidence interval 95%] = 1.12 [1.01, 1.55], P = .02). CONCLUSION: Our findings demonstrate that CT texture analysis of the bladder wall might be an interesting tool to identify spina bifidapatients with high risk urodynamic features.