Video-based Soft Tissue Deformation Tracking for Laparoscopic Augmented Reality-based Navigation in Kidney Surgery.

Minimally invasive surgery (MIS) remains technically demanding due to the difficulty of tracking hidden critical structures within the moving anatomy of the patient. In this study, we propose a soft tissue deformation tracking augmented reality (AR) navigation pipeline for laparoscopic surgery of the kidneys. The proposed navigation pipeline addresses two main sub-problems: the initial registration and deformation tracking. Our method utilizes preoperative MR or CT data and binocular laparoscopes without any additional interventional hardware. The initial registration is resolved through a probabilistic rigid registration algorithm and elastic compensation based on dense point cloud reconstruction. For deformation tracking, the sparse feature point displacement vector field continuously provides temporal boundary conditions for the biomechanical model. To enhance the accuracy of the displacement vector field, a novel feature points selection strategy based on deep learning is proposed. Moreover, an ex-vivo experimental method for internal structures error assessment is presented. The ex-vivo experiments indicate an external surface reprojection error of 4.07 ± 2.17mm and a maximum mean absolutely error for internal structures of 2.98mm. In-vivo experiments indicate mean absolutely error of 3.28 ± 0.40mm and 1.90±0.24mm, respectively. The combined qualitative and quantitative findings indicated the potential of our AR-assisted navigation system in improving the clinical application of laparoscopic kidney surgery.

Non-rigid scene reconstruction of deformable soft tissue with monocular endoscopy in minimally invasive surgery.

PURPOSE: The utilization of image-guided surgery has demonstrated its ability to improve the precision and safety of minimally invasive surgery (MIS). Non-rigid scene reconstruction is a challenge in image-guided system duo to uniform texture, smoke, and instrument occlusion, etc. METHODS: In this paper, we introduced an algorithm for 3D reconstruction aimed at non-rigid surgery scenes. The proposed method comprises two main components: firstly, the front-end process involves the initial reconstruction of 3D information for deformable soft tissues using embedded deformation graph (EDG) on the basis of dual quaternions, enabling the reconstruction without the need for prior knowledge of the target. Secondly, the EDG is integrated with isometric nonrigid structure from motion (Iso-NRSFM) to facilitate centralized optimization of the observed map points and camera motion across different time instances in deformable scenes. RESULTS: For the quantitative evaluation of the proposed method, we conducted comparative experiments with both synthetic datasets and publicly available datasets against the state-of-the-art 3D reconstruction method, DefSLAM. The test results show that our proposed method achieved a maximum reduction of 1.6 mm in average reconstruction error compared to method DefSLAM across all datasets. Additionally, qualitative experiments were performed on video scene datasets involving surgical instrument occlusions. CONCLUSION: Our method proved to outperform DefSLAM on both synthetic datasets and public datasets through experiments, demonstrating its robustness and accuracy in the reconstruction of soft tissues in dynamic surgical scenes. This success highlights the potential clinical application of our method in delivering surgeons with critical shape and depth information for MIS.

Operation Procedure and Precautions of Thread-Embedding Acupuncture Therapy in Alzheimer.

Thread-embedding therapy (TEAT) is a treatment that prevents and manages diseases by inserting a biodegradable suture into an acupoint, providing long-lasting stimulation. TEAT is a simple approach that avoids the discomfort of regular acupuncture and provides sustained therapeutic effects. This article discusses the potential impact of TEAT on the learning and memory abilities of rats with Alzheimer's disease-like symptoms. Since chemically induced neuronal degeneration and cognitive impairments in rats does not entirely reflect the true pathological changes observed in Alzheimer's disease. Consequently, our research group has designated these manifestations as Alzheimer's disease-like symptoms. A protocol has been established to outline the selection of acupoints, the operation process, and necessary precautions for the head and lower back. The experiment was conducted on three groups: a control group, a model group, and a TEAT group, each containing 6 rats. To induce Alzheimer's disease-like symptoms, rats were intraperitoneally injected with D-galactose for 7 weeks (49 days). The rats in the TEAT group received acupoint catgut embedding treatment. Following the intervention period, a Morris Water Maze (MWM) was conducted to evaluate the rats' learning and memory. Subsequently, the rats were sacrificed, and their brain tissue was examined. A histological examination was performed to understand the effects of TEAT on the pathology of rats exhibiting symptoms of Alzheimer's disease. This study suggests that TEAT may improve learning and memory in rats with Alzheimer's disease-like symptoms, indicating a potentially promising new treatment approach for this neurodegenerative condition.

Operation Procedure and Precautions of Lingnan Fire-Needle Therapy in Osteoporosis Model Rats.

Compared to filiform needle therapy, fire-needle therapy has both the stimulation of needles and the warming effect of heat, making it have unexpected effects on some chronic diseases and incurable diseases. Osteoporosis (OP) has a high incidence in postmenopausal women and middle-aged and elderly men, and the treatment cycle is long. According to Traditional Chinese Medicine (TCM), Lingnan fire-needle therapy has shown potential in treating osteoporosis. However, there is still a long way to go before it can be widely used. This article focuses on the application of Lingnan fire-needle therapy in the intervention of OP in rats. It covers the selection of needle tools, acupuncture point selection, positioning of rats' bodies, and fixation methods. We also outline the steps and precautions to be taken during and after needling with fire needles. The experiment was done with three groups: a normal group, a model group, and a fire-needle group, each containing 10 rats. The rats in the fire-needle group were treated with fire-needle intervention for six sessions. After the intervention period, we collected femoral specimens and performed micro-CT scans. The results suggest that fire needling can enhance bone morphology and mineral density in OP rats. This information can serve as a methodological basis for conducting basic research on fire-needle therapy.

Computer-assisted preoperative planning system with an automated registration method in prosthesis-driven oral implantology.

PURPOSE: Dentition defect including edentulism is a problem that deserves attention, which requires precise preoperative planning. The trajectories of the implants can be determined using a pre-made radiographic template, which is adopted for prosthesis-driven oral implantology. However, existing solutions for the registration between the radiographic template and the patient's CBCT still require manual operation and cause inadequate accuracy. In this study, a pre-operative planning system for prosthesis-driven oral implantology is developed with a novel automated registration method. METHODS: Based on threshold segmentation and morphological feature filtering, the potential feature points on two sets of CBCTs are, respectively, recognized. The distance features of the point sets are used to predict the optimal solution for point pair matching, after which the automated registration is implemented. The prosthesis-driven planning can be completed according to the results of registration and multi-planar reconstruction. Then, the surgical templates can be designed and fabricated using 3D printing technology based on the planning results and finally used for intra-operative guidance during implant placement. RESULTS: Verification of the proposed method was conducted on three clinical cases. The mean Fiducial Registration Error of 0.13 ± 0.01mm was achieved with great efficiency. The average time was 0.15 s for the automatic registration algorithm, and 15.64 s for the whole procedure. CONCLUSIONS: The proposed method proved to be accurate and robust. The results indicate that it can achieve higher efficiency while maintaining a low error level, which will have great potential clinical applications in the future.