Three-dimensional simulation of the pancreatic parenchyma, pancreatic duct and vascular arrangement in pancreatic surgery using a deep learning algorithm

Ryoichi Miyamoto; Amane Takahashi; Aya Ogasawara; Toshiro Ogura; Kei Kitamura; Hiroyuki Ishida; Shinichi Matsudaira; Satoshi Nozu; Yoshiyuki Kawashima

doi:10.1371/journal.pone.0276600

Three-dimensional simulation of the pancreatic parenchyma, pancreatic duct and vascular arrangement in pancreatic surgery using a deep learning algorithm

PLoS One. 2022 Oct 28;17(10):e0276600. doi: 10.1371/journal.pone.0276600. eCollection 2022.

Authors

Ryoichi Miyamoto¹, Amane Takahashi¹, Aya Ogasawara², Toshiro Ogura¹, Kei Kitamura¹, Hiroyuki Ishida¹, Shinichi Matsudaira¹, Satoshi Nozu³, Yoshiyuki Kawashima¹

Affiliations

¹ Department of Gastroenterological Surgery, Saitama Cancer Center, Kita-Adachi-gun, Saitama, Japan.
² Imaging Technology Center, Fujifilm Corporation, Minato-ku, Tokyo, Japan.
³ Department of Radiology, Saitama Cancer Center, Kita-Adachi-gun, Saitama, Japan.

Abstract

Three-dimensional surgical simulation, already in use for hepatic surgery, can be used in pancreatic surgery. However, some problems still need to be overcome to achieve more precise pancreatic surgical simulation. The present study evaluates the performance of SYNAPSE VINCENT® (version 6.6, Fujifilm Medical Co., Ltd., Tokyo, Japan) in the semiautomated surgical simulation of the pancreatic parenchyma, pancreatic ducts, and peripancreatic vessels using an artificial intelligence (AI) engine designed with deep learning algorithms. One-hundred pancreatic cancer patients and a control group of 100 nonpancreatic cancer patients were enrolled. The evaluation methods for visualizing the extraction were compared using the Dice coefficient (DC). In the pancreatic cancer patients, tumor size, position, and stagewise correlations with the pancreatic parenchymal DC were analyzed. The relationship between the pancreatic duct diameter and the DC, and between the manually and AI-measured diameters of the pancreatic duct were analyzed. In the pancreatic cancer/control groups, the pancreatic parenchymal DC and pancreatic duct extraction were 0.83/0.86 and 0.84/0.77. The DC of the arteries (portal veins/veins) and associated sensitivity and specificity were 0.89/0.88 (0.89/0.88), 0.85/0.83 (0.85/0.82), and 0.82/0.81 (0.84/0.81), respectively. No correlations were observed between pancreatic parenchymal DC and tumor size, position, or stage. No correlation was observed between the pancreatic duct diameter and the DC. A positive correlation (r = 0.61, p<0.001) was observed between the manually and AI-measured diameters of the pancreatic duct. Extraction of the pancreatic parenchyma, pancreatic duct, and surrounding vessels with the SYNAPSE VINCENT® AI engine assumed to be useful as surgical simulation.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Artificial Intelligence
Deep Learning*
Humans
Pancreatic Ducts / pathology
Pancreatic Ducts / surgery
Pancreatic Neoplasms* / pathology
Pancreatic Neoplasms* / surgery

Grants and funding

This research is a cooperative study with Fujifilm Medical Co., Ltd., Tokyo, Japan. MR received a specific grant from Fujifilm Medical Co., Ltd., Tokyo, Japan. The funders and MR analyzed the collected data together. The funder had no role in study design, data collection, decision to publish, or preparation of the manuscript.