Clinical Trial Details
— Status: Recruiting
Administrative data
| NCT number |
NCT06418490 |
| Other study ID # |
2024-KY-042 |
| Secondary ID |
|
| Status |
Recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
July 1, 2024 |
| Est. completion date |
February 28, 2025 |
Study information
| Verified date |
April 2024 |
| Source |
Zhujiang Hospital |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational [Patient Registry]
|
Clinical Trial Summary
This research discusses the clinical application value of augmented reality navigation
technology combined with three-dimensional visualization technology in improving surgical
safety and promoting the development of precision surgery. This technology can reduce
intraoperative vascular and bile duct injuries, effectively avoid serious postoperative
complications, and reduce residual cysts.
Description:
Choledochal cysts (CC) have traditionally been considered as cystic dilatations of the
extrahepatic bile duct. Choledochal cysts are now referred to as choledochal dilatation,
which also includes intrahepatic and extrahepatic cysts. Choledochal cysts are defined as
cystic dilatations involving the bile duct tree of single or multiple segments of the
intrahepatic and extrahepatic bile ducts. In 1959, Alonso-Lej et al. first divided CC into 3
types based on the location of bile duct dilatation. It was not until 1977 that Todani et al.
revised the classification, adding 2 more types of CCs, which is the most commonly used
classification by clinicians today; however, some experts dispute this, claiming that each
type of CC has its own natural history, complications, and treatments. It is suggested to
focus more on the pathogenesis rather than a simple anatomical classification of the bile
duct tree. Choledochal cysts are a rare anomaly and are sometimes considered as a
precancerous condition, which often leads to diagnostic challenges. The typical presentation
of this condition is nonspecific. Medical teams must have a high clinical suspicion of
choledochal cysts when investigating patients with jaundice, abdominal pain, and palpable
abdominal masses. Due to the ambiguity of these symptoms and physical examination findings,
appropriate imaging studies are crucial for diagnosis. Resection of choledochal dilatation
has shown excellent results, with a complication-free rate of 89% and an overall 5-year
survival rate exceeding 90%. Therefore, early diagnosis and appropriate management are
essential to achieve optimal outcomes and a good prognosis.
Clinical practice has confirmed that the modern digital imaging technology, such as
three-dimensional visualization and augmented reality navigation technology, built for
hepatobiliary surgery diagnosis and treatment platform plays a crucial guiding role in
precise preoperative assessment, lesion localization, formulation of optimal surgical plans,
and intraoperative navigation to avoid collateral damage. Professor Fang Chihua's team has
conducted long-term research and breakthroughs in this field. A significant portion of the
literature in the field of digital intelligent diagnosis and treatment technology retrieved
from SinoMed - China Biomedical Literature Service System comes from Professor Fang Chihua's
team. The team has published consecutive expert consensus in the Chinese Journal of Practical
Surgery in the field of digital intelligence in hepatobiliary surgery, including the
publication of "Expert Consensus on Precise Diagnosis and Treatment of Three-Dimensional
Visualization of Hepatobiliary Stones (2019 Edition)," which affirms the significant impact
of three-dimensional visualization technology in guiding the precise diagnosis and treatment
of hepatobiliary stones. The "Consensus recommendations of three-dimensional visualization
for diagnosis and management of liver disease" published in an international journal
demonstrates that China's research level in this field is at the forefront globally. Sioh
Huang Lim et al. utilized ICG intraoperative navigation technology to visualize the
extrahepatic bile ducts without radiation, enabling quicker identification of bile ducts
compared to cholangiography. Liu Yangsui et al. applied fluorescence imaging technology for
real-time navigation of the extrahepatic bile ducts, achieving superior outcomes in terms of
surgical time, intraoperative blood loss, and postoperative hospital stay compared to the
traditional surgery group. In laparoscopic re-exploration of the bile duct, Tian Guangjin et
al. used ICG fluorescence navigation technology as surgical assistance, with a conversion to
open surgery rate of approximately 3.3% in the navigation group compared to 22.9% in the
conventional surgery group, achieving higher rates of minimally invasive abdominal surgery in
the navigation group. Takeshi Aoki et al. indicated in their literature the successful
staining of subsegments or liver segments in 33 out of 35 cases (94.3%) using fluorescence
imaging technology for liver resection navigation. Kunshan He et al. demonstrated that
near-infrared (NIR) imaging method resulted in less blood loss and shorter hospital stay
compared to traditional methods. ICG fluorescence imaging technology has shown promising
prospects in partial liver resection surgery. In conclusion, three-dimensional visualization
technology can achieve precise preoperative differentiation of vascular variations, formulate
individualized surgical plans based on reconstructed three-dimensional models, and provide
real-time navigation during surgery to ensure the success of the operation. Intraoperative
real-time augmented reality technology navigation helps prevent intraoperative bile duct
injuries, effectively reduce severe postoperative complications, and decrease residual cysts
and associated complications. Therefore, the combined application of both technologies in the
treatment of choledochal cysts surgery provides better medical technological support,
enhances surgical safety and precision, promotes the development of minimally invasive
surgery, and holds significant clinical value.
