Dynamic surface reconstruction in robot-assisted minimally invasive surgery based on neural radiance fields

PURPOSE

The purpose of this study was to improve surgical scene perception by addressing the challenge of reconstructing highly dynamic surgical scenes. We proposed a novel depth estimation network and a reconstruction framework that combines neural radiance fields to provide more accurate scene information for surgical task automation and AR navigation.

METHODS

We added a spatial pyramid pooling module and a Swin-Transformer module to enhance the robustness of stereo depth estimation. We also improved depth accuracy by adding unique matching constraints from optimal transport. To avoid deformation distortion in highly dynamic scenes, we used neural radiance fields to implicitly represent scenes in the time dimension and optimized them with depth and color information in a learning-based manner.

RESULTS

Our experiments on the KITTI and SCARED datasets show that the proposed depth estimation network performs close to the state-of-the-art method on natural images and surpasses the SOTA method on medical images with 1.12% in 3 px Error and 0.45 px in EPE. The proposed dynamic reconstruction framework successfully reconstructed the dynamic cardiac surface on a totally endoscopic coronary artery bypass video, achieving SOTA performance with 27.983 dB in PSNR, 0.812 in SSIM, and 0.189 in LPIPS.

CONCLUSION

Our proposed depth estimation network and reconstruction framework provide a significant contribution to the field of surgical scene perception. The framework achieves better results than SOTA methods on medical datasets, reducing mismatches on depth maps and resulting in more accurate depth maps with clearer edges. The proposed ER framework is verified on a series of dynamic cardiac surgical images. Future efforts will focus on improving the training speed and solving the problem of limited field of view.

Effects of robot-assisted minimally invasive surgery on osteoporotic vertebral compression fracture: a systematic review, meta-analysis, and meta-regression of retrospective study

OBJECTIVE

To conduct a systematic review on the effect of robot-assisted minimally invasive surgery (R-MIS) on the clinical outcomes and complications of patients with osteoporotic vertebral compression fractures (OVCFs).

METHODS

The researchers searched the papers published on PubMed, The Cochrane Library, Web of Science, Embase, Scopus, Ovid MEDLINE, Wiley Online Library, China National Knowledge Infrastructure (CNKI), Chinese biomedical literature service system (SinoMed), and China Medical Association Data. The standardized mean difference (SMD) or mean difference (MD), relative risk (RR), and 95% confidence interval (CI) were calculated. Besides, the data was merged through the random-effect model or common-effect model. A meta-regression mixed-effects single-factor model was utilized to analyze the sources of heterogeneity.

RESULTS

Twelve studies were included, involving 1042 OVCFs cases. The prognosis of patients treated with R-MIS was significantly improved, such as Oswestry disability index (ODI) score (MD = -0.65, P = 0.0171), Cobb's angles (MD = -1.03, P = 0.0027), X-ray fluoroscopy frequency (SMD = -2.41, P < 0.0001), Length of hospital stay (MD = -0.33, P = 0.0002), and Cement leakage (RR = 0.37, P < 0.0001). However, no obvious improvement was found in the results of Visual analog scale (VAS) score (MD = -0.16, P = 0.1555), Volume of bone cement (MD = 0.22, P = 0.8339), and Operation time (MD = -3.20, P = 0.3411) after being treated by R-MIS. The meta-regression analysis demonstrated that R-MIS presented no significant impact on the covariates of VAS and Operation time.

CONCLUSION

R-MIS can significantly reduce the patients' ODI, Cobb's angles, X-ray fluoroscopy frequency, and Cement leakage ratio, and shorten the Length of hospital stay. Therefore, R-MIS may be an effective method to promote the patients' functional recovery, correct spinal deformity, reduce the X-ray fluoroscopy frequency, shorten the Length of hospital stay, and reduce the complications of OVCFs bone Cement leakage.

Preoperative planning method based on a MOPSO algorithm for robot-assisted cholecystectomy

PURPOSE

Surgical robots have multiple manipulators with complex mechanisms and need to work in a narrow space in the patient's body. Therefore, for robot-assisted minimally invasive surgery (RMIS), it is very important to develop a reasonable preoperative planning before surgery.

METHODS

A preoperative planning method based on the premise of no collision between surgical instruments and endoscope, an evaluation index with visibility, operability and hand-eye coordination was proposed in this paper. To consider the balance relationship of global optimization index, a multi-objective particle swarm optimization (MOPSO) algorithm was adopted. Because the physical characteristics of each patient are different, the method can determine the selectable area of the incision based on the relevant knowledge of anatomy.

RESULTS

The simulation taking the cholecystectomy as an example was performed on a minimally invasive surgical robotic system. The analysis result showed that the proposed preoperative planning method based on the MOPSO could provide surgeons with a reasonable and effective preoperative planning.

CONCLUSIONS

The proposed preoperative planning method based on the MOPSO is suitable for patients with different physical characteristics, and can provide a guidance for surgeons and effectively reduce the preoperative planning time and improve the safety and efficiency of the operation, especially a novice surgeon who lacks robot-assisted minimally invasive surgery experience.

Tissue discrimination by bioelectrical impedance during PLL resection in anterior decompression surgery for treatment of cervical spondylotic myelopathy

Background

The electrical properties of biological tissues differ depending on their physical properties. This study aimed to explore if bioelectrical impedance (modulus and phase) would discriminate tissues relevant to resection of the posterior longitudinal ligament (PLL) in anterior cervical decompression surgery.

Methods

PLL resection via an anterior approach was performed on the C4/5 segments in six mini-pigs. The bioelectrical impedance measurements were performed for two tissue groups (annulus fibrosus, endplate cartilage, sub-endplate cortical bone, and PLL; PLL, dura mater, spinal cord, and nerve root) using a novel probe and a precision inductance-capacitance-resistance meter. For each group, impedance was analyzed in terms of modulus and phase along a broad spectrum of frequencies (200–3000 kHz) using a nonparametric statistical analysis (Kruskal-Wallis).

Results

The analysis showed a clear difference among the tissues. The modulus and phase show the same changing trend with frequency and present lower values at higher frequencies. Among annulus fibrosus, endplate cartilage, sub-endplate cortical bone, and PLL, it was possible to discriminate each tissue at every frequency point, considering the phase (p < 0.05), while this was not always the case (i.e., annulus fibrosus vs PLL at frequency of 200 kHz, 400 kHz, and 3000 kHz, p > 0.05) for modulus. Among PLL, dura mater, spinal cord, and nerve root, for every comparison, a statistically significant difference was reported in the modulus, phase, or both (p < 0.05).

Conclusions

The results indicated the potential of bioelectrical impedance to provide real-time tissue differentiation and enhance safe PLL resection in anterior cervical decompression surgery, particularly in robot-assisted minimally invasive surgery (RMIS).

New remote centre of motion mechanism for robot-assisted minimally invasive surgery

BACKGROUND

Robot-assisted minimally invasive surgery (RMIS) is promising for improving surgical accuracy and dexterity. As the end effector of the robotic arm, the remote centre of motion mechanism is one of the requisite terms for guaranteeing patient safety. The existing remote centre of motion mechanisms are complex and large in volume, as well as high assembly requirement and unsatisfactory precise. This paper aimed to present a new remote centre of motion mechanism for solving these problems.

METHODS

A new mechanism based on the RMIS requirements is proposed for holding the laparoscope and generating a remote centre of motion for the laparoscope. The mechanism kinematics is then analysed from the perspective of the structural function, and its inverse kinematics is determined with a small number of calculations. Finally, the position deviation of the laparoscope rotational point is chosen as the index to evaluate the mechanism performance. The experiments are performed to test the deviation.

RESULTS

The position deviations of the laparoscope rotational point do not exceed 2 mm, which is lower than that of the existing remote centre of motion mechanism. The 2 mm positioning error of the laparoscope won't affect surgeon observation of the surgical field, and the pressure caused by the positioning error was acceptable for the skin elasticity. The proposed mechanism meets the RMIS requirement.

CONCLUSIONS

The proposed mechanism can achieve the remote centre of motion for the laparoscope. Its simple and compact structure is beneficial to avoid the collision of robotic arms, and it can be applied on other robots for providing the instrument necessary motion in minimally invasive surgery.