BACKGROUND/AIMS: To establish an objective and precise vascular naming method to explore the segmental anatomy of the liver with major anomalies using three dimensional (3D) simulations. METHODOLOGY: Two algorithms, "Alternative vascular visualization method" (Algorithm A) and "Cholecystic axis based definition" (Algorithm B), were devised. Twenty livers with typical anatomy and four anomalous cases were screened by six masked physicians using a blinded protocol. RESULTS: After confirming the feasibility in subjects with a typical anatomy, the accuracies of the algorithms were tested in anomalous cases. Using conventional 3D screening, the accuracies of the portal and hepatic venous definitions were 40.6% and 61.1%, respectively. However, after the introduction of the presently reported algorithms, these results improved to 83.4% and 83.4%, respectively, for Algorithm A, and 88.5% and 83.3%, respectively, for Algorithm B. In particular, the accuracy was further improved to nearly 100% when the naming process was started from the larger side of the liver in Algorithm A. CONCLUSIONS: The present study confirmed that Algorithm A enables the precise vascular definitions when the process is started from the larger side of the liver. This method may be a useful tool for anatomic exploration of liver with major anomalies.
BACKGROUND/AIMS: To establish an objective and precise vascular naming method to explore the segmental anatomy of the liver with major anomalies using three dimensional (3D) simulations. METHODOLOGY: Two algorithms, "Alternative vascular visualization method" (Algorithm A) and "Cholecystic axis based definition" (Algorithm B), were devised. Twenty livers with typical anatomy and four anomalous cases were screened by six masked physicians using a blinded protocol. RESULTS: After confirming the feasibility in subjects with a typical anatomy, the accuracies of the algorithms were tested in anomalous cases. Using conventional 3D screening, the accuracies of the portal and hepatic venous definitions were 40.6% and 61.1%, respectively. However, after the introduction of the presently reported algorithms, these results improved to 83.4% and 83.4%, respectively, for Algorithm A, and 88.5% and 83.3%, respectively, for Algorithm B. In particular, the accuracy was further improved to nearly 100% when the naming process was started from the larger side of the liver in Algorithm A. CONCLUSIONS: The present study confirmed that Algorithm A enables the precise vascular definitions when the process is started from the larger side of the liver. This method may be a useful tool for anatomic exploration of liver with major anomalies.