Neoplasms

Digestive System Diseases

Diseases and Abnormalities at or Before Birth

All Conditions

Symptoms and General Pathology

Rare Diseases

Choledochal Cyst

Dilatation, Pathologic

Cysts

Pathological Conditions, Anatomical

Bile Duct Diseases

Biliary Tract Diseases

Gastrointestinal Diseases

Congenital Abnormalities

Digestive System Abnormalities

Bile Duct Cysts

Central Nervous System Depressants

All Drugs and Chemicals

Hematinics

Gastrointestinal Agents

Anesthetics

Liver Extracts

Pancrelipase

Pancreatin

After adequate general anesthesia, the non-3D group underwent conventional choledochal cyst excision surgery, while the 3D group underwent choledochal cyst excision surgery guided by three-dimensional visualization technology or enhanced reality navigation.

Three-dimensional reconstruction technology is a software that can collect CT and MRI data, perform image segmentation and three-dimensional reconstruction of the liver, gallbladder, dilated bile ducts, pancreas, venous, and arterial systems step by step. The software is called Abdominal Medical Image 3D Visualization Software (MI-3DVS, software copyright registration number: 2008SR18798).The AR-ANS (Software Copyright No.: 2018SR840555) is an intraoperative navigation system that integrates three-dimensional visualization technology.This modification provides visual guidance for surgeons when ligating or protecting critical vascular tissues during surgery.

Three-dimensional visualization technology

zeng ning, Doctor

cai peilin, master

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.

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.

The Application of Digital Intelligent Diagnostic and Therapeutic Technology in Biliary Dilation Diagnosis

Navigating the Biliary Maze：a Retrospective Cohort Study of Augmented Reality Improving Outcomes in Choledochal Dilation Resection

Comprehensive Complication Index:integrating all recorded complications weighted by severity in a single formula.

Zhujiang Hospital

Patients with congenital biliary dilatation diagnosed according to the Japanese Study Group on Congenital Biliary Dilatation (JSCBD) guideline.

Patients with secondary biliary dilatation attributed to choledocholithiasis or malignancies (hilar cholangiocarcinoma, pancreatic carcinoma, and distal cholangiocarcinoma).

Diagnosis models are established using quantitative morphological characteristics extracted from the 3D reconstructed bile duct from contrast-enhanced computed tomography (CECT) images.

Contrast-enhanced computed tomography (CECT) and 3D morphological analysis

Huijun Chen, Ph.D.

Jiahong Dong, M.D.

Congenital biliary dilatation necessitates timely intervention owing to potential complications. This study endeavors to enhance diagnostic precision using quantitative three-dimensional morphological characteristics. Objectives involve developing models to differentiate congenital from secondary biliary dilatation and identify intrahepatic involvement. Employing machine learning, robust diagnostic models aim to elevate clinical detection rates and improve accuracy.

Congenital biliary dilatation is a primary anomaly affecting the biliary tract. It can involve the extrahepatic bile ducts, intrahepatic bile ducts, or the entire biliary system, including the common bile duct. Patients with congenital biliary dilatation exhibit abnormal expansion of the bile duct system, which can lead to complications such as bile duct stones, pancreatic inflammation, and even bile duct cancer. Timely and accurate diagnosis, followed by surgical intervention to remove the dilated bile duct lesion, is crucial for the treatment of choledochal dilation. However, the differentiation of congenital biliary dilatation in clinical practice poses challenges, primarily due to the limitations of subjective physician experience and macroscopic imaging features, making it difficult to achieve high sensitivity in discerning congenital biliary dilatation. Particularly, in distinguishing between congenital biliary dilatation and secondary biliary dilatation, the similarities of the bile ducts limit the precision of clinical decisions. Therefore, this study aims to address the current challenges in the differential diagnosis of congenital biliary dilatation and secondary biliary dilatation by quantitatively describing the morphology of dilated bile ducts. Moreover, this study plans to build a predictive model of intrahepatic bile duct dilatation to provide more comprehensive clinical support. Specifically, the research objectives are outlined as follows:

1. Establish a diagnostic model for congenital biliary dilatation utilizing three-dimensional morphological characteristics, especially quantitative shape- and diameter-based characteristics, to enhance the accurate discrimination between congenital biliary dilatation and secondary biliary dilatation.
2. Develop a model for identifying intrahepatic involvement of congenital biliary dilatation, aiming to provide more precise information for surgical planning and supportive treatment.
3. Construct robust diagnostic models using machine learning with quantitative three-dimensional morphological characteristics, aiming to increase clinical detection rates and accuracy, thereby achieving risk stratification for patients with biliary dilatation.

Congenital Biliary Dilatation Diagnosis Based on 3D Morphological Characteristics

The area under the ROC curve is calculated by integrating the ROC curve, which plots Sensitivity against 1 - Specificity.

The area under the precision-recall curve is determined by integrating the Precision-Recall curve, which plots Precision against Recall.

Sensitivity is calculated as the ratio of true positives to the sum of true positives and false negatives.

Specificity is calculated as the ratio of true negatives to the sum of true negatives and false positives.

Accuracy is calculated as the ratio of the sum of true positives and true negatives to the total number of cases.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
The Application of Digital Intelligent Diagnostic and Therapeutic Technology in Biliary Dilation Diagnosis	NCT06418490	Congenital Bili... Choledochal Cys...	Three-dimension...	16 Years - 75 Years	Zhujiang Hospital
Congenital Biliary Dilatation Diagnosis Based on 3D Morphological Characteristics	NCT06162520	Congenital Bili...	Contrast-enhanc...	-	Tsinghua University
The Application of Digital Intelligent Diagnostic and Therapeutic Technology in Biliary Dilation Diagnosis	NCT06418490	Congenital Bili... Choledochal Cys...	Three-dimension...	16 Years - 75 Years	Zhujiang Hospital

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