Three-dimensional echocardiographic virtual endoscopy for the diagnosis of congenital heart disease in children

Virtual endoscopy (VE) is a new post-processing method that uses volumetric data sets to simulate the tracks of a “conventional” flexible endoscope. However, almost all studies of this method have involved virtual visualizations of the cardiovascular structures applied to computed tomography (CT) and magnetic resonance (MR) datasets. This paper introduces a novel visualization method called the “three-dimensional echocardiographic intracardiac endoscopic simulation system (3DE IESS)”, which uses 3D echocardiographic images in a virtual reality (VR) environment to diagnose congenital heart disease. The aim of this study was to analyze the feasibility of VE in the evaluation of congenital heart disease in children and its accuracy compared with 2DE. Three experienced pediatric cardiologists blinded to the patients’ diagnoses separately reviewed 40 two-dimensional echocardiographic (2DE) datasets and 40 corresponding VE datasets and judged whether abnormal intracardiac anatomy was present in terms of a five-point scale (1 = definitely absent; 2 = probably absent; 3 = cannot be determined; 4 = probably present; and 5 = definitely present). Compared with clinical diagnosis, the diagnostic accuracy of VE was 98.7% for ASD, 92.4% for VSD, 92.6% for TOF, and 94% for DORV, respectively. Diagnostic accuracy of VE was significantly higher than that of 2DE for TOF and DORV except for ASD and VSD. The receiver operating characteristic (ROC) curve for VE was closer to the optimal performance point than was the ROC curve for 2DE. The area under the ROC curve was 0.96 for VE and 0.93 for 2DE. Kappa values (range, 0.73–0.79) for VE and 2DE indicated substantial agreement. 3D echocardiographic VE can enhance our understanding of intracardiac structures and facilitate the evaluation of congenital heart disease

Design and Implementation of Quantity Calculation Method Based on BIM Data

Manual quantity takeoff using two-dimensional (2D) drawings and personal knowledge is error-prone and time-consuming. Theoretically, quantity can be automatically calculated from building information model more quickly and reliably by extracting geometric data and semantic attributes of building elements. Specific construction classification systems embedded in mainstream modeling software for building information modeling (BIM) make it difficult for countries adopting different systems to calculate quantity directly. This paper proposes a BIM-based quantity takeoff code mapping (BQTCM) method to solve the above issue, and develops a quantity takeoff code mapping plug-in (QTCMP) on a BIM modeling software based on the proposed BQTCM method to obtain an accurate bill of quantities directly and efficiently. Moreover, by conducting a statistical analysis and examining a case study, this paper verifies the accuracy and efficiency of quantity takeoff attained from the proposed BQTCM method and QTCMP