Three-dimensional (3D) visualization involves feature extraction and 3D reconstruction of CT images using a computer processing technology. It is a tool for displaying, describing, and interpreting 3D anatomy and morphological features of organs, thus providing intuitive, stereoscopic, and accurate methods for clinical decision-making. It has played an increasingly significant role in the diagnosis and management of liver diseases. Over the last decade, it has been proven safe and effective to use 3D simulation software for pre-hepatectomy assessment, virtual hepatectomy, and measurement of liver volumes in blood flow areas of the portal vein; meanwhile, the use of 3D models in combination with hydrodynamic analysis has become a novel non-invasive method for diagnosis and detection of portal hypertension. We herein describe the progress of research on 3D visualization, its workflow, current situation, challenges, opportunities, and its capacity to improve clinical decision-making, emphasizing its utility for patients with liver diseases. Current advances in modern imaging technologies have promised a further increase in diagnostic efficacy of liver diseases. For example, complex internal anatomy of the liver and detailed morphological features of liver lesions can be reflected from CT-based 3D models. A meta-analysis reported that the application of 3D visualization technology in the diagnosis and management of primary hepatocellular carcinoma has significant or extremely significant differences over the control group in terms of intraoperative blood loss, postoperative complications, recovery of postoperative liver function, operation time, hospitalization time, and tumor recurrence on short-term follow-up. However, the acquisition of high-quality CT images and the use of these images for 3D visualization processing lack a unified standard, quality control system, and homogeneity, which might hinder the evaluation of application efficacy in different clinical centers, causing enormous inconvenience to clinical practice and scientific research. Therefore, rigorous operating guidelines and quality control systems need to be established for 3D visualization of liver to develop it to become a mature technology. Herein, we provide recommendations for the research on diagnosis and management of 3D visualization in liver diseases to meet this urgent need in this research field.

Consensus recommendations of three-dimensional visualization for diagnosis and management of liver diseases / Fang C.; An J.; Bruno A.; Cai X.; Fan J.; Fujimoto J.; Golfieri R.; Hao X.; Jiang H.; Jiao L.R.; Kulkarni A.V.; Lang H.; Lesmana C.R.A.; Li Q.; Liu L.; Liu Y.; Lau W.; Lu Q.; Man K.; Maruyama H.; Mosconi C.; Ormeci N.; Pavlides M.; Rezende G.; Sohn J.H.; Treeprasertsuk S.; Vilgrain V.; Wen H.; Wen S.; Quan X.; Ximenes R.; Yang Y.; Zhang B.; Zhang W.; Zhang P.; Zhang S.; Qi X.. - In: HEPATOLOGY INTERNATIONAL. - ISSN 1936-0533. - ELETTRONICO. - 14:4(2020), pp. 437-453. [10.1007/s12072-020-10052-y]

Consensus recommendations of three-dimensional visualization for diagnosis and management of liver diseases

Bruno A.;Golfieri R.;Mosconi C.;
2020

Abstract

Three-dimensional (3D) visualization involves feature extraction and 3D reconstruction of CT images using a computer processing technology. It is a tool for displaying, describing, and interpreting 3D anatomy and morphological features of organs, thus providing intuitive, stereoscopic, and accurate methods for clinical decision-making. It has played an increasingly significant role in the diagnosis and management of liver diseases. Over the last decade, it has been proven safe and effective to use 3D simulation software for pre-hepatectomy assessment, virtual hepatectomy, and measurement of liver volumes in blood flow areas of the portal vein; meanwhile, the use of 3D models in combination with hydrodynamic analysis has become a novel non-invasive method for diagnosis and detection of portal hypertension. We herein describe the progress of research on 3D visualization, its workflow, current situation, challenges, opportunities, and its capacity to improve clinical decision-making, emphasizing its utility for patients with liver diseases. Current advances in modern imaging technologies have promised a further increase in diagnostic efficacy of liver diseases. For example, complex internal anatomy of the liver and detailed morphological features of liver lesions can be reflected from CT-based 3D models. A meta-analysis reported that the application of 3D visualization technology in the diagnosis and management of primary hepatocellular carcinoma has significant or extremely significant differences over the control group in terms of intraoperative blood loss, postoperative complications, recovery of postoperative liver function, operation time, hospitalization time, and tumor recurrence on short-term follow-up. However, the acquisition of high-quality CT images and the use of these images for 3D visualization processing lack a unified standard, quality control system, and homogeneity, which might hinder the evaluation of application efficacy in different clinical centers, causing enormous inconvenience to clinical practice and scientific research. Therefore, rigorous operating guidelines and quality control systems need to be established for 3D visualization of liver to develop it to become a mature technology. Herein, we provide recommendations for the research on diagnosis and management of 3D visualization in liver diseases to meet this urgent need in this research field.
2020
Consensus recommendations of three-dimensional visualization for diagnosis and management of liver diseases / Fang C.; An J.; Bruno A.; Cai X.; Fan J.; Fujimoto J.; Golfieri R.; Hao X.; Jiang H.; Jiao L.R.; Kulkarni A.V.; Lang H.; Lesmana C.R.A.; Li Q.; Liu L.; Liu Y.; Lau W.; Lu Q.; Man K.; Maruyama H.; Mosconi C.; Ormeci N.; Pavlides M.; Rezende G.; Sohn J.H.; Treeprasertsuk S.; Vilgrain V.; Wen H.; Wen S.; Quan X.; Ximenes R.; Yang Y.; Zhang B.; Zhang W.; Zhang P.; Zhang S.; Qi X.. - In: HEPATOLOGY INTERNATIONAL. - ISSN 1936-0533. - ELETTRONICO. - 14:4(2020), pp. 437-453. [10.1007/s12072-020-10052-y]
Fang C.; An J.; Bruno A.; Cai X.; Fan J.; Fujimoto J.; Golfieri R.; Hao X.; Jiang H.; Jiao L.R.; Kulkarni A.V.; Lang H.; Lesmana C.R.A.; Li Q.; Liu L.; Liu Y.; Lau W.; Lu Q.; Man K.; Maruyama H.; Mosconi C.; Ormeci N.; Pavlides M.; Rezende G.; Sohn J.H.; Treeprasertsuk S.; Vilgrain V.; Wen H.; Wen S.; Quan X.; Ximenes R.; Yang Y.; Zhang B.; Zhang W.; Zhang P.; Zhang S.; Qi X.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/795286
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