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Background: Partial nephrectomy is the preferred surgical approach for renal neoplasms smaller than 7 cm, without compromising disease-free or cancer-specific survival. It is increasingly being performed in patients with complex renal tumors. Three-dimensional models of preoperative computed tomography (CT) or magnetic resonance imaging (MRI) scans are the future for accurately identifying the tumor's location and planning the surgical strategy. Objectives: This study aims to develop an application for use by medical professionals, designed to view three-dimensional (3D) renal images with radius, extension, nearness, anterior/posterior, and lines scores from preoperative CT or MRI exams. Methods: This descriptive study focuses on developing a mobile application, which was entirely created by a urologist on a no-code platform without using programming languages. The renal 3D images were generated from the patient's specific CT or MRI scans. A dedicated database was also utilized for the application. Results: The development of the NeoRenal application resulted in ten complexly designed screens created within a no-code platform, each serving a specific purpose in a coherent sequence to ensure an optimal user experience. The uniform flow and design of these screens aim to provide intuitive and comprehensive user acceptance, facilitating registration, data entry, visualization, and editing functionalities. Conclusions: The application was successfully developed and is ready to be published on various operating systems.
Background: Partial nephrectomy is the preferred surgical approach for renal neoplasms smaller than 7 cm, without compromising disease-free or cancer-specific survival. It is increasingly being performed in patients with complex renal tumors. Three-dimensional models of preoperative computed tomography (CT) or magnetic resonance imaging (MRI) scans are the future for accurately identifying the tumor's location and planning the surgical strategy. Objectives: This study aims to develop an application for use by medical professionals, designed to view three-dimensional (3D) renal images with radius, extension, nearness, anterior/posterior, and lines scores from preoperative CT or MRI exams. Methods: This descriptive study focuses on developing a mobile application, which was entirely created by a urologist on a no-code platform without using programming languages. The renal 3D images were generated from the patient's specific CT or MRI scans. A dedicated database was also utilized for the application. Results: The development of the NeoRenal application resulted in ten complexly designed screens created within a no-code platform, each serving a specific purpose in a coherent sequence to ensure an optimal user experience. The uniform flow and design of these screens aim to provide intuitive and comprehensive user acceptance, facilitating registration, data entry, visualization, and editing functionalities. Conclusions: The application was successfully developed and is ready to be published on various operating systems.
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