The application of augmented reality navigation combined with fluorescence laparoscopy in the resection of tumors in the middle lobe of the liver

doi:10.21203/rs.3.rs-4692509/v1

Download PDF

Short Report

The application of augmented reality navigation combined with fluorescence laparoscopy in the resection of tumors in the middle lobe of the liver

https://doi.org/10.21203/rs.3.rs-4692509/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Objective

To investigate the application value of augmented reality (AR) navigation combined with fluorescence laparoscopy in the resection of tumors in the middle lobe of the liver.

Methods

The clinical data of 10 patients who underwent hepatectomy for middle hepatic lobe tumors and AR combined with fluorescence laparoscopy at the Department of Hepatobiliary Surgery, the First Affiliated Hospital of Wannan Medical College, from May 2023 to January 2024 were retrospectively analyzed. The implementation method of AR was as follows: the preoperative 3D model was projected into the created 3D space, and the collected real-time laparoscopic images were fused into the 3D space background to create an interactive environment. For the fluorescence imaging method, according to the results of ICG-15, the appropriate operation time was determined to achieve the best fluorescence imaging effect.

Results

A total of 10 patients were successfully treated without conversion to open surgery. (1) Intraoperative situations: All the tumors were located in the middle lobe of the liver; the intraoperative fluorescence imaging rate was 100%; the average tumor length was 5[4–7] cm; the average operation time was 262.5 ± 24.8 min; and the average amount of intraoperative blood loss was 440.0 ± 58.1 ml. In the technical application of AR, the average registration error was 6.3 ± 0.6 mm; the average intraoperative verification of the number of blood vessels was 5.6 ± 0.6; and the average intraoperative prediction of the number of blood vessels was 4 [2–5]. (2) Postoperative situation: the average postoperative hospital stay was 9.1 ± 1.6 days. The postoperative pathological diagnosis was hepatic cell carcinoma (HCC) in eight cases and metastatic hepatic carcinoma (MHC) in two patients.

Conclusion

In complex hepatectomy, the application of AR combined with fluorescence laparoscopy can help verify and predict important anatomical structures, which has broad clinical application prospects.

Hepatectomy

Fluorescence laparoscopy

Augmented reality

liver tumor

1.1 Clinical data

From May 2023 to January 2024, 10 patients who underwent hepatectomy for middle hepatic lobe tumors with AR combined with fluorescence laparoscopy at our center were included. The perioperative data of 10 patients were retrospectively analyzed, including age, sex, preoperative tumor markers, tumor size, tumor location, ICG-15, operation time, intraoperative blood loss, postoperative hospital stay, postoperative pathology, postoperative complications and postoperative follow-up data. All patients provided written informed consent in accordance with the approval of the hospital ethics committee and in accordance with the Declaration of Medical Ethics of Helsinki.

1.2 Preoperative preparation

For the fluorescence imaging method, all patients underwent preoperative indocyanine green liver function reserve, and the operation time was determined according to the results of the ICG-15. Specific methods: The amount of indocyanine green used was 0.5 mg/kg. Surgery was scheduled 3–5 days later when the ICG-15 concentration was < 10%, and surgery was scheduled 5–7 days later when the ICG-15 concentration was > 10%.

All patients underwent preoperative 3D reconstruction to fully understand the relationship between the tumor and its surrounding vessel and to assess the liver volume after liver resection. Subsequently surgeons performed a simulated hepatectomy (Fig. 1). After sufficient preoperative discussion, all patients were in line with the operation indications, and we performed the operation measures.

1.3 Operation methods

Laparoscopic middle hepatic resection (segment VIII resection + ventral segment V resection + partial MHV resection) is an example. Fluid infusion was limited during hepatectomy, and central venous pressure (CVP) was maintained below 5 mmH2O. A small incision was made 3 cm below the umbilical cord while the patient was in the supine position. Carbon dioxide gas was then inflated to achieve a pneumoperitoneum pressure of 13 mmHg. A Trocar was subsequently inserted for lens entry. A "five-hole" cannula was used during the operation.

After the laparoscope entered the abdominal cavity, the abdominal cavity was explored. When no obvious abnormalities were found, the fluorescence mode was used to explore the liver tumor and determine its location. The round and falciform ligaments of the liver were cut with an ultrasonic scalpel. The second hepatic hilum was dissected, and the MHV and RHV were exposed. The lesser omental sac was dissected with an ultrasonic scalpel in preparation for the Pringle maneuver, and the Pringle maneuver was performed with a hepatic pedicle clamp during the operation [2]. The AR display screen was turned on, and the laparoscopic image was displayed on the same screen as the 3D model established before surgery. The laparoscopic image and 3D model were superimposed to create the AR environment (Fig. 2).

The first image registration was performed based on the general outline of the gallbladder and liver. An ultrasonic knife for retrograde resection and stripping of the gallbladder was used to search for Laennec's membrane. The hepatic portal plate was dissected, and the right and left hepatic tips were revealed. The dissection continued along the right hepatic hilum to reveal the right anterior and right posterior hepatic hilum, and then the liver parenchyma was isolated in the direction of the right anterior hepatic hilum. In the AR display, V5v, the ventral branch of the right anterior hepatic pedicle innervating segment V, is predicted and dissected, and care is taken to protect V5d, which is the dorsal branch innervating segment V. The ultrasonic knife continued to isolate the right anterior hepatic hilum trunk and found a thick portal vein branch innervating segment VIII. The AR display was then turned on, and a second pairing was performed to confirm the location and alignment of this branch as segment VIII of the hepatic hilum. At this time, in fluorescent laparoscopic mode, the liver tumor was shown to compress the hepatic hilum of segment VIII, which was blocked after adequate separation. The left margin of the procedure starts separating the hepatic parenchyma along the labeled MHV liver surface marking line to the venous bifurcation and then turns on the AR display to determine that the branch is located on the left side of the MHV and predicts the MHV position, which, in turn, leads to finding the MHV trunk and continuing separation along the MHV toward the root. The relationship between the MHV trunk and the liver tumor was probed in fluorescence mode to determine the degree of tumor compression of the MHV and subsequent dissociation of the invading MHV (Fig. 2). The detachment continued toward the root of the MHV, and V8i was predicted and dissected under the AR display. Ultrasonic knife detachment to the root of the MHV was followed by cephalad to pedunculate the detachment to expose the RHV. Ultrasonic knife dissection was continued along the main trunk of the RHV, and the location of the RHC branching vessel, V8d, was predicted under actual AR where it was subsequently dissected (Fig. 3). The dissection was continued until complete resection of the liver tumor was achieved.

After carefully examining the liver section and stopping the bleeding, the laparoscopic fluorescence mode was turned on to check for biliary fistulae and tumor remnants. Absorbable hemostatic gauze was used to cover the liver section, and then one hepatic section laparotomy drain was placed. The resected specimen was removed, and the procedure was completed.

1.4 Postoperative management

Hepatoprotective therapy was routinely applied to all patients postoperatively, and the drains were kept open. Upper abdominal CT was performed on all patients on the fifth postoperative day to understand the operative area. All the patients used were followed up routinely after discharge, with follow-up up to date 06/15/2024.

1.5 Statistical methods

SPSS 23.0 software was used for statistical analysis, measures that conformed to a normal distribution were expressed as (n, x̄±s), and those that did not conform to a normal distribution were expressed as medians [ranges].

All patients successfully underwent laparoscopic surgery without intermediate openings. There were eight males and two females among the 10 patients, with an average age of 64.5 ± 2.4 years, a preoperative BMI of 24.8 ± 0.8 kg/m2, a preoperative ICG level of 6.7 ± 0.9%, an average length diameter of the liver tumor of 5[4–7] cm, and cirrhosis in 4 out of the 10 patients. The Child‒Pugh grades were as follows: 8, grade A; 2, grade B (Table 1).

Table 1

Preoperative general data of the 10 patients
Case	Sex	Age	BMI(kg/m2)	Tumor length (cm)	ICG-15(%)	Liver cirrhosis(n)	Child classification	Extent of excision
1	M	71	22.3	7	3.2	No	A	V + VIII
2	M	66	27.2	5	7.9	No	A	IVb + V
3	M	58	23.4	5	4.1	No	A	IVa + VIII
4	F	66	25.6	6	8.5	No	A	IV + V + VIII
5	F	57	25.4	5	3.4	No	A	V + VIII
6	M	75	22.1	5	9.8	Yes	B	VIII
7	M	68	24.2	7	14	Yes	B	IVa + V + VIII
8	M	66	23.1	4	5	No	A	V
9	M	49	30.8	5	4.9	Yes	A	VIII
10	M	69	24.6	5	7.7	Yes	A	V + VIII
Median (range)/mean ± SD ^a		64.5 ± 2.4	24.8 ± 0.8	5[4–7]	6.7 ± 0.9
F female,M male,
ICG-R15, indocyanine green retention rate at 15 min;
^a Normally distributed data are expressed as the mean ± standard deviation (SD); skewed data are expressed as the median (range).

Intraoperative clinical data revealed that the average operative time was 262.5 ± 24.8 min. The average amount of intraoperative bleeding was 440.0 ± 58.1 ml, and the average intraoperative Pringle time was 75.0 ± 8.9 min. In the technical application of AR, the average registration error was 6.3 ± 0.6 mm, the average intraoperative verification of the number of blood vessels was 5.6 ± 0.6, and the average intraoperative prediction of the number of blood vessels was 4 [2–5].

Postoperative clinical data: Ten patients achieved R0 resection after surgery, among whom eight cases were diagnosed with HCC. Two cases were MHC. One patient developed pleural effusion after surgery and was discharged after conservative treatment; the other patient developed lung infection and was discharged after anti-inflammatory and phlegm treatment, which improved the patient's general condition. All patients had no serious complications, such as abdominal hemorrhage, biliary fistula, or liver failure, and the average postoperative hospital stay was 9.1 ± 1.6 days. Ten patients were followed up on 2024.06.15, and all patients were followed up for 4–13 months, with a median of 7 months. None of them had postoperative liver function abnormalities, secondary surgery or postoperative tumor recurrence (Table 2).

Table 2

Intraoperative and postoperative data of 10 patients
Case	Operation time (min)	Blood loss (ml)	Pringle time(min)	registration error(mm)	Verify the number of vessels(n)	Predicting the number of vessels(n)	Pathology	Complications	POHS (days)
1	220	600	60	7.2	7	5	MHC		7
2	330	500	90	4.5	3	3	HCC	pleural effusion	14
3	300	300	15	3.3	4	3	HCC		5
4	350	600	120	5.6	8	5	MHC		11
5	150	400	60	6.7	6	5	HCC		4
6	130	200	60	4.2	4	2	HCC		7
7	360	800	90	7.2	9	5	HCC	lung infection	21
8	270	400	75	6.5	4	3	HCC		8
9	270	300	90	8.9	5	2	HCC		9
10	245	300	90	9.2	8	5	HCC		5
Median (range)/mean ± SD	262.5 ± 24.8	440.0 ± 58.1	75 ± 8.9	6.3 ± 0.6	5.6 ± 0.6	4[2–5]			9.1 ± 1.6
POHS postoperative hospital stay.

Over the past three decades, laparoscopic hepatectomy has gradually gained increasing recognition because of its unique advantages; however, laparoscopic surgery still has many shortcomings, such as a lack of tactile sensation, limited vision, and the inability to see through the complex internal structure of the liver [3]. Alleviating these shortcomings has become one of the most concerning topics for hepatobiliary surgeons. With the rapid development of medical imaging technology, 3D reconstruction, preoperative simulated resection, fluorescence laparoscopy, and AR technology have all been gradually applied in the management of liver tumors in the perioperative period, which has achieved encouraging results.

In the assessment of preoperative liver function, the traditional Child‒Pugh classification still significantly differs among patients with Child A liver function [4], and the MELD score is usually used for patients who need liver transplantation [5]. Preoperative ICG testing can be used to assess liver reserve function safely and accurately, and this method is now widely used [6]. In addition, hepatic resection must take into account the residual liver volume after hepatectomy resection; normal livers can tolerate hepatectomies with residual liver volume/total liver volume ratios greater than 20%-25% [7], whereas hepatectomies with cirrhosis must retain sufficient residual liver volume. Combining the ICG-15 values with preoperative 3D simulated resection techniques to calculate the appropriate simulated postresection residual liver volume from the ICG-15 values may reduce the proportion of postoperative hepatic failure that occurs. Our experience is that through the three-dimensional reconstruction technique, the tumor location and the relationship between the tumor and the liver blood vessels are displayed in three dimensions, the extent of tumor infiltration is judged, and the ratio of the residual liver volume accounted for is calculated after the preresection line of the liver is selected. On the basis of these results, the hepatic resection plane is repeatedly adjusted to develop an optimal surgical plan. The advantage of this scheme is that, on the one hand, it can maximize the preservation of normal liver tissue and reduce the incidence of liver failure, and, on the other hand, it can avoid the main hepatic blood vessels and reduce excessive dissection of blood vessels to reduce intraoperative bleeding.

Since Ishizawa et al. [8] first used ICG molecular fluorescence imaging to navigate hepatic resection in 2009, this technique has been widely used in the diagnostic hand and surgery of hepatobiliary and pancreatic tumors. Laparoscopic fluorescence imaging plays an important role in detecting residual tumors and microscopic lesions at the margins of liver sections, defining tumor boundaries intraoperatively, and improving postoperative tumor-free survival [9, 10]. ICG fluorescence is able to successfully identify superficial lesions as small as 1–2 mm that were previously unidentifiable via preoperative or direct visualization; thus, ICG fluorescence improves the sensitivity of hepatic tumor detection [11]. Uchiyama et al. [12] reported that the sensitivity of ICG fluorescence for tumor detection was 98.1%, whereas that of conventional imaging methods was 88.5%. In addition, ICG fluorescence detection remains highly reliable for tumors within 8–10 mm below the hepatic envelope [13]. We applied fluorescence laparoscopy to laparoscopic hepatic tumor resection and achieved good results. First, this method can rapidly locate the position of the tumor and visualize and expose the boundary of the tumor during the resection process, which is convenient for allowing the operator to timely predict and adjust the resection line and improve the ratio of R0 resection of the tumor. Although fluorescence laparoscopy has been widely used in laparoscopic liver resection, for the resection process of complex livers, the tumor periphery is often adjacent to important blood vessels and the biliary system, which makes smooth implementation of laparoscopic surgery difficult. At the same time, the deep location of some liver tumors cannot be accurately localized laparoscopically, which further increases the difficulty of surgery. Owing to the reliance on fluorescent laparoscopic imaging of the tumor alone, it is impossible to predict and judge the location of important blood vessels in advance, which leads to an increase in intraoperative bleeding and the rate of electrocautery.

In recent years, with the development of AR technology, successful cases of the application of this technology in laparoscopic hepatectomy have been reported [14, 15]. AR technology is an intraoperative application based on a 3D visualization system that projects a preoperative 3D model of the liver into the created 3D space and fuses the captured real-time laparoscopic images into a 3D spatial background to create an interactive environment. The main difficulties of this technology include three aspects: image alignment, continuous image tracking, and selective image fusion. The 3D visualization-based mixed reality navigation system and the 3D visualization-based mixed reality laparoscopic projection navigation system, developed by our center in cooperation with computer engineers, have been granted national patents in China and have been applied for in clinics with good results.

First, in the process of image alignment, the general alignment can be completed according to the contour of the liver and the location of the gallbladder. Second, when verifying or predicting the alignment of tumors, blood vessels and bile ducts are necessary. The secondary image alignment is performed according to the location of the dissected important ducts or tumors. The alignment often requires manual cooperation to address the process, and, in the present study, the alignment error for the 10 patients was 6.3 ± 0.6 mm. The registration error is a measure of accuracy that represents the error in the position of the alignment picture farther away from the alignment target [16]. The registration error is affected by many factors, including respiratory movement, liver position changes, frame shifts and pneumoperitoneum pressure. Within a certain range of registration errors, the surgeon's main concern is whether the technical solution can verify and predict the vessels intraoperatively. In terms of verifying blood vessels, when the operator is unsure of the origin of blood vessels during the processing of ducts in liver sections, previous experience involves roughly determining the origin of the blood vessel from the memory of preoperative film readings, which involves large errors and may result in damage to important blood vessels. In contrast, currently, for complex hepatic resections, the type of pipe encountered can be verified by AR, the need for preservation or resection can be quickly determined intraoperatively, and the average number of vessels verified in this study was 5.6 ± 0.6. In addition, in terms of predicting the vasculature, the ability of the MHV to predict the presence of tumors resected in the middle lobe of the liver cannot be ignored. In previous studies, intraoperative ultrasound was used to localize the MHV on the surface of the liver, and the difficulty lies in the fact that the distal branches of the MHV are encountered during resection from the pedunculated side to the cephalad side. It is often impossible to predict whether the MHV is to the left or to the right of the resection line. AR can predict the location of the MHV according to the branch vessel's shape and position. In addition, AR can predict the ductal structure of important parts in real time and provide early warning. It can be used to predict vessels on average 4 times in 10 patients in this study, which reduces possible intraoperative bleeding.

There are many challenges that need to be solved in augmented reality navigation technology. How to continuously and rapidly track the images of interest and how to quickly and selectively fuse the structures of interest are the focuses of subsequent research. Most of the reported solutions are in the experimental stage [16, 17] and have not been applied in clinical practice. In laparoscopic liver resection, image tracking, rendering and fusion, enhancement of stereoscopic visualization of the anatomical structures in the liver, and real "perspective" effects and early warning require the cooperation of surgeons and computer engineers.

In this study, real-time navigation hepatectomy using AR combined with laparoscopic fluorescence images during complex hepatectomy provides the operator with more information to guide the operation, thus compensating to a certain extent for the lack of tactile sensation and limited field of view in laparoscopic surgery, avoiding damage to important ductal structures and improving the precision and safety of the operation, which has broad development prospects; however, at present, the technology is still in the primary stage, and the current research samples are relatively small, and continuous research is needed.

Permissions

Neither the entire manuscript nor any part of its content has been published or has been accepted elsewhere and this manuscript has not been submitted to any other journal. No portion of the text has been copied from other material in the literature. All of the authors in this manuscript have read and approved the final version submitted, and there are no conflicts involved in this submission.

Competing Interests: The authors declare that they have no competing interests.

Since the first report by Reich et al. [1] in 1991, laparoscopic hepatectomy (LH) has become a routine surgical procedure in liver surgery because of its advantages of minimal trauma and rapid recovery. However, for complex liver tumor resection, owing to the particularity of the nature and location of the tumor, conventional laparoscopy cannot predict and clearly expose the tumor location and surrounding blood vessels in advance. In recent years, with the development of fluorescence laparoscopy, it has provided great advantages in the imaging of liver tumors and has been gradually used in hepatic surgery. However, it is difficult for surgeons to predict the blood vessels around the tumor in advance. With the development of AR technology, surgeons see the prospect of solving this problem. AR combined with the fluorescence laparoscopic technique has been applied for complex liver resection and has a good effect, as described below.

Funding

This study was supported by the 2023 research project of Wannan Medical College (Award Number: WK2023ZQNZ33 Recipient: Zhengchao Shen), and the 2023 Natural Science Research Project of Anhui Province Universities (Award Number: 2023AH040254 Recipient:Xiaoming Wang).

Author Contribution

Study conception and design：Xiaoming Wang, Zhengchao Shen. Acquisition of data: Zhiyuan Chen, Shihang Xi, Xuan Pan. Analysis and interpretation of data: Zhengchao Shen, Zhiyuan Chen. Drafting of manuscript: Zhengchao Shen, Bin Jiang. Critical revision of manuscript: Xiaoming Wang.

Acknowledgements

This thesis would not have been possible without the consistent and valuable reference materials that I received from XW whose insightful guidance and enthusiastic encouragement in the course of my shaping this thesis definitely gain my deepest gratitude.

Reich H, McGlynn F, DeCaprio J Budin R(1991)Laparoscopic excision of benign liver lesions. Obstet Gynecol 78:956–958
Shen Z, Jiang B, Chu H, Wang G, Fang X, Chen Z, Yang Y, Wang J, Wang X(2024)The application of a single-hand-operated hepatic pedicle clamping clamp in laparoscopic hepatectomy. Langenbecks Arch Surg 409:146. https://doi.org/10.1007/s00423-024-03334-8
Kawaguchi Y, Fuks D, Kokudo N, Gayet B(2018)Difficulty of Laparoscopic Liver Resection: Proposal for a New Classification. Ann Surg 267:13–17. https://doi.org/10.1097/SLA.0000000000002176
Forner A, Reig M, Bruix J(2018)Hepatocellular carcinoma. Lancet 391:1301–1314. https://doi.org/10.1016/S0140-6736(18)30010-2
Ruf A, Dirchwolf M, Freeman RB (2022)From Child-Pugh to MELD score and beyond: Taking a walk down memory lane. Ann Hepatol 27:100535. https://doi.org/10.1016/j.aohep.2021.100535
Caimano M, Bianco G, Coppola A, Marrone G, Agnes S, Lai Q, Spoletini G(2024)Indocyanine green clearance tests to assess liver transplantation outcomes: a systematic review. Int J Surg 110:431–440. https://doi.org/10.1097/JS9.0000000000000779
Clavien PA, Petrowsky H, DeOliveira ML, Graf R(2007)Strategies for safer liver surgery and partial liver transplantation. N Engl J Med 356:1545–1559. https://doi.org/10.1056/NEJMra065156
Ishizawa T, Fukushima N, Shibahara J, Masuda K, Tamura S, Aoki T, Hasegawa K, Beck Y, Fukayama M Kokudo N(2009)Real-time identification of liver cancers by using indocyanine green fluorescent imaging. Cancer 115:2491–2504. https://doi.org/10.1002/cncr.24291
Chen H, Wang Y, Xie Z, Zhang L, Ge Y, Yu J, Zhang C, Jia W, Ma J, Liu W(2022)Application Effect of ICG Fluorescence Real-Time Imaging Technology in Laparoscopic Hepatectomy. Front Oncol 12:819960. https://doi.org/10.3389/fonc.2022.819960
Wang X, Teh CSC, Ishizawa T, Aoki T, Cavallucci D, Lee SY et al (2021) Consensus guidelines for the use of fluorescence imaging in hepatobiliary surgery. Ann Surg 274(1):97–106. https://doi.org/10.1097/SLA.0000000000004718
Cassinotti E, Al-Taher M, Antoniou SA, Arezzo A, Baldari L, Boni L, Bonino MA, Bouvy ND, Brodie R, Carus T, Chand M, Diana M, Eussen MMM, Francis N, Guida A, Gontero P, Haney CM, Jansen M, Mintz Y, Morales-Conde S, Muller-Stich BP, Nakajima K, Nickel F, Oderda M, Parise P, Rosati R, Schijven MP, Silecchia G, Soares AS, Urakawa S Vettoretto N(2023)European Association for Endoscopic Surgery (EAES) consensus on Indocyanine Green (ICG) fluorescence-guided surgery. Surg Endosc 37:1629–1648. https://doi.org/10.1007/s00464-023-09928-5
Uchiyama K, Ueno M, Ozawa S, Kiriyama S, Shigekawa Y, Yamaue H (2010) Combined use of contrast-enhanced intraoperative ultrasonography and a fluorescence navigation system for identifying hepatic metastases. World J Surg 34:2953–2959. https://doi.org/10.1007/s00268-010-0764-1
Sposito C, Maspero M, Belotti P, Simonotti N, Altomare M, Ciana P, Mazzaferro V(2022)Indocyanine green fluorescence-guided surgery for gastrointestinal tumors: A systematic review. Ann Surg Open 3:e190. https://doi.org/10.1097/AS9.0000000000000190
Wang Z, Tao H, Wang J, Zhu Y, Lin J, Fang C, Yang J (2023) Laparoscopic right hemi-hepatectomy plus total caudate lobectomy for perihilar cholangiocarcinoma via anterior approach with augmented reality navigation: a feasibility study. Surg Endosc 37:8156–8164. https://doi.org/10.1007/s00464-023-10397-z
Zhang P, Luo H, Zhu W, Yang J, Zeng N, Fan Y, Wen S, Xiang N, Jia F Fang C(2020)Real-time navigation for laparoscopic hepatectomy using image fusion of preoperative 3D surgical plan and intraoperative indocyanine green fluorescence imaging. Surg Endosc 34:3449–3459. https://doi.org/10.1007/s00464-019-07121-1
Teatini A, Pelanis E, Aghayan DL, Kumar RP, Palomar R, Fretland ÅA, Edwin B, Elle OJ(2019)The effect of intraoperative imaging on surgical navigation for laparoscopic liver resection surgery. Sci Rep 9:18687. https://doi.org/10.1038/s41598-019-54915-3
Zhu LY, Hou JC, Yang L, Liu ZR, Tong W, Bai Y, Zhang YM(2022)Application value of mixed reality in hepatectomy for hepatocellular carcinoma. World J Gastrointest Surg 14:36–45. https://doi.org/10.4240/wjgs.v14.i1.36

No competing interests reported.

video.mp4

Download PDF

Version 1

posted

You are reading this latest preprint version

The application of augmented reality navigation combined with fluorescence laparoscopy in the resection of tumors in the middle lobe of the liver

Status:

Version 1

Abstract

Objective

Methods

Results

Conclusion

Figures

1. Materials and methods

1.1 Clinical data

1.2 Preoperative preparation

1.3 Operation methods

1.4 Postoperative management

1.5 Statistical methods

2. Results

3 Discuss

Declarations

Funding

Author Contribution

Acknowledgements

References

Additional Declarations

Supplementary Files

Status:

Version 1