Efficient EndoNeRF reconstruction and its application for data-driven surgical simulation.

PURPOSE: The healthcare industry has a growing need for realistic modeling and efficient simulation of surgical scenes. With effective models of deformable surgical scenes, clinicians are able to conduct surgical planning and surgery training on scenarios close to real-world cases. However, a significant challenge in achieving such a goal is the scarcity of high-quality soft tissue models with accurate shapes and textures. To address this gap, we present a data-driven framework that leverages emerging neural radiance field technology to enable high-quality surgical reconstruction and explore its application for surgical simulations. METHOD: We first focus on developing a fast NeRF-based surgical scene 3D reconstruction approach that achieves state-of-the-art performance. This method can significantly outperform traditional 3D reconstruction methods, which have failed to capture large deformations and produce fine-grained shapes and textures. We then propose an automated creation pipeline of interactive surgical simulation environments through a closed mesh extraction algorithm. RESULTS: Our experiments have validated the superior performance and efficiency of our proposed approach in surgical scene 3D reconstruction. We further utilize our reconstructed soft tissues to conduct FEM and MPM simulations, showcasing the practical application of our method in data-driven surgical simulations. CONCLUSION: We have proposed a novel NeRF-based reconstruction framework with an emphasis on simulation purposes. Our reconstruction framework facilitates the efficient creation of high-quality surgical soft tissue 3D models. With multiple soft tissue simulations demonstrated, we show that our work has the potential to benefit downstream clinical tasks, such as surgical education.

Evaluation of different doses of Femoston therapy for incomplete abortion: A prospective observational trial.

This study aimed to compare the efficacy of different doses of femoston with expectant management in patients with incomplete abortions. Patients diagnosed with incomplete abortion were included if they chose to continue medical treatment after relevant contraindications were excluded. Participants were divided into 3 groups: the femoston (1/10) and femoston (2/10) groups received different doses of femoston, and patients in the control group received expectant treatment. The success rate of complete abortion and the rate of menstrual recovery among the 3 groups were compared to evaluate the efficacy of different doses of femoston in patients with incomplete abortions. A total of 197 patients were analyzed: 73 in the femoston (1/10) group, 73 in the femoston (2/10) group, and 51 patients were followed up without treatment in the control group. The femoston group was significantly more effective than the control group P < .0001). The adjusted odds ratio (OR) and 95% confidence interval (CI) were 3.103 and 1.153 to 8.350 (P = .025). The success rate of complete abortion in the femoston (2/10) group was significantly higher than that in the femoston (1/10) group (adjusted OR: 0.403, 95% CI: 0.145-1.118, P = .081). In addition, the rate of menstrual recovery in the femoston group was significantly higher than that in the control group (P = .007), and the rate in the femoston (2/10) group was also higher than the femoston (1/10) group with statistically significant (P = .001). Femoston is effective in treating incomplete abortion, with femostons containing 2 mg estrogen being more effective. Patients with incomplete abortion are treated with femoston, and menstrual recovery time may be shortened. Femostons may be a new option for pharmacological treatment of incomplete abortions.