Navigation Surgery Research Articles

Sentinel Node Navigation Surgery for Early Gastric Cancer: A Narrative Review.

Early gastric cancer (EGC) refers to malignant tumor lesions that are limited to the mucosa and submucosa layers, regardless of the presence of lymph node metastasis. Typically, EGC has a low rate of perigastric lymph node metastasis, and long-term survival outcomes are good after radical surgical treatment. The primary objective of surgical treatment for EGC is to achieve functional preservation while ensuring a radical cure. Sentinel node navigation surgery (SNNS) is a surgical technique used in the treatment of EGC. This approach achieves functional preservation by limiting lymph node dissection and performing restrictive gastrectomy guided by intraoperative negative sentinel node (SN) biopsy. Despite the apparent improvement in the detection rate of SN with the emergence of various tracing dyes and laparoscopic fluorescence systems, the oncological safety of SNNS remains a controversial research topic. SNNS, as a true form of stomach preservation surgery that enhances the quality of life, has become a topic of interest in the EGC field. In recent years, scholars from Japan and South Korea have conducted extensive research on the feasibility and safety of SNNS in the treatment of EGC. This article aims to provide reference choices for surgeons treating EGC by reviewing relevant research on SNNS for EGC in recent years.

A Novel Intraoperative CT Navigation System for Spinal Fusion Surgery in Lumbar Degenerative Disease: Accuracy and Safety of Pedicle Screw Placement.

Background: In recent years, intraoperative computed tomography (CT) navigation has become widely used for the insertion of pedicle screws in spinal fusion surgery. However, conventional intraoperative CT navigation may be impaired by infrared interference between the infrared camera and surgical instruments, which can lead to the misplacement of pedicle screws. Recently, a novel intraoperative CT navigation system, NextAR, has been developed. It uses a small infrared camera mounted on surgical instruments within the surgical field. NextAR navigation can minimize the problem of infrared interference and be expected to improve the accuracy of pedicle screw placement. Methods: This study investigated the accuracy of pedicle screw insertion under NextAR navigation in spinal fusion surgery for lumbar degenerative diseases. The accuracy of pedicle screw placement was evaluated in 15 consecutive patients using a CT grading scale. Results: Screw perforation occurred in only 1 of the total 70 screws (1.4%). Specifically, there was one grade 1 perforation within 2 mm, but no perforations larger than 2 mm. There were no reoperations or neurological complications due to screw misplacement. Conclusions: NextAR navigation can provide high accuracy for pedicle screw insertion and help ensure safe spinal fusion surgery for lumbar degenerative diseases.

A System for Mixed-Reality Holographic Overlays of Real-Time Rendered 3D-Reconstructed Imaging Using a Video Pass-through Head-Mounted Display-A Pathway to Future Navigation in Chest Wall Surgery.

Background: Three-dimensional reconstructions of state-of-the-art high-resolution imaging are progressively being used more for preprocedural assessment in thoracic surgery. It is a promising tool that aims to improve patient-specific treatment planning, for example, for minimally invasive or robotic-assisted lung resections. Increasingly available mixed-reality hardware based on video pass-through technology enables the projection of image data as a hologram onto the patient. We describe the novel method of real-time 3D surgical planning in a mixed-reality setting by presenting three representative cases utilizing volume rendering. Materials: A mixed-reality system was set up using a high-performance workstation running a video pass-through-based head-mounted display. Image data from computer tomography were imported and volume-rendered in real-time to be customized through live editing. The image-based hologram was projected onto the patient, highlighting the regions of interest. Results: Three oncological cases were selected to explore the potentials of the mixed-reality system. Two of them presented large tumor masses in the thoracic cavity, while a third case presented an unclear lesion of the chest wall. We aligned real-time rendered 3D holographic image data onto the patient allowing us to investigate the relationship between anatomical structures and their respective body position. Conclusions: The exploration of holographic overlay has proven to be promising in improving preprocedural surgical planning, particularly for complex oncological tasks in the thoracic surgical field. Further studies on outcome-related surgical planning and navigation should therefore be conducted. Ongoing technological progress of extended reality hardware and intelligent software features will most likely enhance applicability and the range of use in surgical fields within the near future.

Image-Guided Navigation in Spine Surgery: From Historical Developments to Future Perspectives.

Intraoperative navigation is critical during spine surgery to ensure accurate instrumentation placement. From the early era of fluoroscopy to the current advancement in robotics, spinal navigation has continued to evolve. By understanding the variations in system protocols and their respective usage in the operating room, the surgeon can use and maximize the potential of various image guidance options more effectively. At the same time, maintaining navigation accuracy throughout the procedure is of the utmost importance, which can be confirmed intraoperatively by using an internal fiducial marker, as demonstrated herein. This technology can reduce the need for revision surgeries, minimize postoperative complications, and enhance the overall efficiency of operating rooms.

Surgical Navigation in the Anterior Skull Base Using 3-Dimensional Endoscopy and Surface Reconstruction

Image guidance is an important adjunct for endoscopic sinus and skull base surgery. However, current systems require bulky external tracking equipment, and their use can interrupt efficient surgical workflow. To evaluate a trackerless surgical navigation system using 3-dimensional (3D) endoscopy and simultaneous localization and mapping (SLAM) algorithms in the anterior skull base. This interventional deceased donor cohort study and retrospective clinical case study was conducted at a tertiary academic medical center with human deceased donor specimens and a patient with anterior skull base pathology. Participants underwent endoscopic endonasal transsphenoidal dissection and surface model reconstruction from stereoscopic video with registration to volumetric models segmented from computed tomography (CT) and magnetic resonance imaging. To assess the fidelity of surface model reconstruction and accuracy of surgical navigation and surface-CT model coregistration, 3 metrics were calculated: reconstruction error, registration error, and localization error. In deceased donor models (n = 9), high-fidelity surface models of the posterior wall of the sphenoid sinus were reconstructed from stereoscopic video and coregistered to corresponding volumetric CT models. The mean (SD; range) reconstruction, registration, and localization errors were 0.60 (0.24; 0.36-0.93), 1.11 (0.49; 0.71-1.56) and 1.01 (0.17; 0.78-1.25) mm, respectively. In a clinical case study of a patient who underwent a 3D endoscopic endonasal transsphenoidal resection of a tubercular meningioma, a high-fidelity surface model of the posterior wall of the sphenoid was reconstructed from intraoperative stereoscopic video and coregistered to a volumetric preoperative fused CT magnetic resonance imaging model with a root-mean-square error of 1.38 mm. The results of this study suggest that SLAM algorithm-based endoscopic endonasal surgery navigation is a novel, accurate, and trackerless approach to surgical navigation that uses 3D endoscopy and SLAM-based algorithms in lieu of conventional optical or electromagnetic tracking. While multiple challenges remain before clinical readiness, a SLAM algorithm-based endoscopic endonasal surgery navigation system has the potential to improve surgical efficiency, economy of motion, and safety.

Deformable registration of preoperative MR and intraoperative long-length tomosynthesis images for guidance of spine surgery via image synthesis

PurposeImproved integration and use of preoperative imaging during surgery hold significant potential for enhancing treatment planning and instrument guidance through surgical navigation. Despite its prevalent use in diagnostic settings, MR imaging is rarely used for navigation in spine surgery. This study aims to leverage MR imaging for intraoperative visualization of spine anatomy, particularly in cases where CT imaging is unavailable or when minimizing radiation exposure is essential, such as in pediatric surgery. MethodsThis work presents a method for deformable 3D-2D registration of preoperative MR images with a novel intraoperative long-length tomosynthesis imaging modality (viz., Long-Film [LF]). A conditional generative adversarial network is used to translate MR images to an intermediate bone image suitable for registration, followed by a model-based 3D-2D registration algorithm to deformably map the synthesized images to LF images. The algorithm’s performance was evaluated on cadaveric specimens with implanted markers and controlled deformation, and in clinical images of patients undergoing spine surgery as part of a large-scale clinical study on LF imaging. ResultsThe proposed method yielded a median 2D projection distance error of 2.0 mm (interquartile range [IQR]: 1.1–3.3 mm) and a 3D target registration error of 1.5 mm (IQR: 0.8–2.1 mm) in cadaver studies. Notably, the multi-scale approach exhibited significantly higher accuracy compared to rigid solutions and effectively managed the challenges posed by piecewise rigid spine deformation. The robustness and consistency of the method were evaluated on clinical images, yielding no outliers on vertebrae without surgical instrumentation and 3% outliers on vertebrae with instrumentation. ConclusionsThis work constitutes the first reported approach for deformable MR to LF registration based on deep image synthesis. The proposed framework provides access to the preoperative annotations and planning information during surgery and enables surgical navigation within the context of MR images and/or dual-plane LF images.

Top 25 Most-Cited Articles on Robotic-Assisted Lumbar Spine Surgery.

Robot-guided lumbar spine surgery has evolved rapidly with evidence to support its utility and feasibility compared with conventional freehand and fluoroscopy-based techniques. The objective of this study was to assess trends among the top 25 most-cited articles pertaining to robotic-guided lumbar spine surgery. An "advanced document search" using Boolean search operator terms was performed on 16 November 2022 through the Web of Science and SCOPUS citation databases to determine the top 25 most-referenced articles on robotic lumbar spine surgery. The articles were compiled into a directory and hierarchically organized based on the total number of citations. Cumulatively, the "Top 25" list for robot-assisted navigation in lumbar spine surgery received 2240 citations, averaging 97.39 citations annually. The number of citations ranged from 221 to 40 for the 25 most-cited articles. The most-cited study, by Kantelhardt et al, received 221 citations, averaging 18 citations per year. As utilization of robot-guided modalities in lumbar spine surgery increases, this review highlights the most impactful studies to support its efficacy and implementation. Practical considerations such as cost-effectiveness, however, need to be better defined through further longitudinal studies that evaluate patient-reported outcomes and cost-utility. Through an overview of the top 25 most-cited articles, the present review highlights the rising prominence and technical efficacy of robotic-guided systems within lumbar spine surgery, with consideration to pragmatic limitations and need for additional data to facilitate cost-effective applications.

Stereotactic Navigation-Assisted Laparoscopic Resection of Challenging Low Pelvic Tumors: A Case Series.

(1) Introduction: The laparoscopic approach to low pelvic tumors is challenging and hindered by suboptimal tumor visualization and dissection, with possible oncological failure. Stereotactic navigation provides real-time image guidance that may optimize safety, accuracy, and precision when dissecting challenging low pelvic tumors. (2) Methods: Preoperative CT images were acquired with eight skin-fixed fiducials and loaded into a navigation system. A patient tracker was mounted on the bed side. Patient-to-image paired point registration was performed, and an instrument tracker was mounted on a laparoscopic instrument and calibrated for instrument tracking. Surgical operations were performed with real-time stereotactic navigation assistance. (3) Results: Three patients underwent stereotactic navigation surgery. Fiducial registration errors were good to optimal (±1.9, ±3.4, and ±3.4 mm). Lesions were easily identified and targeted with real-time navigation. Surgeries were uneventful. Histopathology examinations identified one retro-rectal schwannoma, one lateral pelvic recurrence from rectal adenocarcinoma, and one advanced anal canal carcinoma. No navigation-related complications, readmissions, or postoperative mortalities were observed. (4) Conclusions: The application of laparoscopic stereotactic navigation surgery to complex low pelvic tumors is feasible and could impact oncological surgical quality by enabling tumor targeting and ensuring resection margins. Further wider series are needed to confirm stereotactic navigation's impact on challenging low pelvic tumors.

Unfolded Protein-Based Sandwich AIE Probe Imparts High Fluorescent Contrast for Pan-Cancer Surgical Navigation.

Fluorescence imaging-guided navigation for cancer surgery has a promising clinical application. However, pan-cancer encompasses a wide variety of cancer types with significant heterogeneity, resulting in the lack of universal and highly contrasted fluorescent probes for surgical navigation. Here, we developed an aggregation-induced emission (AIE) probe (MI-AIE-TsG, MAT) with dual activation for pan-cancer surgical navigation. MAT weakly activates fluorescence by targeting the SUR1 protein on the endoplasmic reticulum (ER) through the TsG group. Subsequently, the sulfhydryl groups on the unfolded proteins, which are highly enriched in cancer ER, react with the maleimide (MI) of MAT through the thiol-ene click reaction, further enhancing the fluorescence. The formation of a SUR1-MAT-unfolded protein sandwich complex reinforces the restriction of intramolecular motion and eliminates photoinduced electron transfer of MAT, leading to high signal-to-noise (9.2) fluorescence imaging and use for surgical navigation of pan-cancer. The generally high content of unfolded proteins in cancer cells makes MAT imaging generalizable, and it currently has proven feasibility in ovarian, cervical, and breast cancers. Meanwhile, MAT promotes cellular autophagy by hindering protein folding, thereby inhibiting cancer cell proliferation. This generalizable, high-contrast AIE fluorescent probe spans the heterogeneity of pancreatic cancer, enabling precise pancreatic cancer surgery navigation and treatment.

Robotically Assisted Implantology - A Systematic Review from a Young Dental Professional’s Perspective: I Have No Fear, My Dental Robot Is Near!

Objective: There are multiple opportunities to enhance the quality of dental care through robotics. Robotics-assisted dentistry continues to evolve from traditional navigational surgery to more complex systems that prove to be essential in implantology and the overall maintenance of oral health. The purpose of this study is to provide a brief literature review of robotics in dentistry and dental education, identify reasons for their limited penetration and highlight the enormous potential of robots to enhance the future of professionals, newly entering implantology. Methods: A systematic review of articles was performed, focusing on robotics in dentistry, a specificality in implantology within the last decade, limiting the search to English language publications. The search was conducted across two major electronic databases, PubMed and EMBASE and Google as a generic source of information. With articles up to July 2022. Employing a combination of relevant key terms and synonyms, including “robotics” Yomi”, “dental robots”, “robotic implantology” and aliases, over 31 articles were screened. In total, the systematic search identified 17 articles which were included in the review. The perspective of someone newly entering the profession was also included as an opinion. Results: The introduction of robotics in implantology dates back only a few years. The perception of robotics as cost-prohibitive or threatening to the dental profession are partly to blame. Among other reasons for the limited penetration are the lack of technology expertise and patient acceptance. Robotic implant systems have the potential to alter quality of care through improved and more precise treatment. Robotically guided implant placement allows for dynamic surgical tracking in real-time. It can be used to augment dental implant procedures for the placement of reliable, repeatable, dental implant outcomes. Dentists newly entering the profession can benefit from the accuracy, speed and agility of assistive robotics. Conclusion: Robotics in dentistry is delayed compared to medicine due to perception of cost, fear for displacement of the dental profession and limited technological readiness. New professionals entering the field of dentistry should not see robots displacing their role as dentists but rather enhancing it and transforming the holistic approach to dental care from planning to flawless execution. For new dentists, the foundational knowledge and compassionate ear will remain indispensable. I have no fear as I know my dental robot is near!

The application of extended reality technology-assisted intraoperative navigation in orthopedic surgery.

Extended reality (XR) technology refers to any situation where real-world objects are enhanced with computer technology, including virtual reality, augmented reality, and mixed reality. Augmented reality and mixed reality technologies have been widely applied in orthopedic clinical practice, including in teaching, preoperative planning, intraoperative navigation, and surgical outcome evaluation. The primary goal of this narrative review is to summarize the effectiveness and superiority of XR-technology-assisted intraoperative navigation in the fields of trauma, joint, spine, and bone tumor surgery, as well as to discuss the current shortcomings in intraoperative navigation applications. We reviewed titles of more than 200 studies obtained from PubMed with the following search terms: extended reality, mixed reality, augmented reality, virtual reality, intraoperative navigation, and orthopedic surgery; of those 200 studies, 69 related papers were selected for abstract review. Finally, the full text of 55 studies was analyzed and reviewed. They were classified into four groups-trauma, joint, spine, and bone tumor surgery-according to their content. Most of studies that we reviewed showed that XR-technology-assisted intraoperative navigation can effectively improve the accuracy of implant placement, such as that of screws and prostheses, reduce postoperative complications caused by inaccurate implantation, facilitate the achievement of tumor-free surgical margins, shorten the surgical duration, reduce radiation exposure for patients and surgeons, minimize further damage caused by the need for visual exposure during surgery, and provide richer and more efficient intraoperative communication, thereby facilitating academic exchange, medical assistance, and the implementation of remote healthcare.

Pedicle screw placement accuracy in robot-assisted versus image-guided freehand surgery of thoraco-lumbar spine (ROBARTHRODESE): study protocol for a single-centre randomized controlled trial

BackgroundRobotic spinal surgery may result in better pedicle screw placement accuracy, and reduction in radiation exposure and length of stay, compared to freehand surgery. The purpose of this randomized controlled trial (RCT) is to compare screw placement accuracy of robot-assisted surgery with integrated 3D computer-assisted navigation versus freehand surgery with 2D fluoroscopy for arthrodesis of the thoraco-lumbar spine.MethodsThis is a single-centre evaluator-blinded RCT with a 1:1 allocation ratio. Participants (n = 300) will be randomized into two groups, robot-assisted (Mazor X Stealth Edition) versus freehand, after stratification based on the planned number of pedicle screws needed for surgery. The primary outcome is the proportion of pedicle screws placed with grade A accuracy (Gertzbein-Robbins classification) on postoperative computed tomography images. The secondary outcomes are intervention time, operation room occupancy time, length of stay, estimated blood loss, surgeon’s radiation exposure, screw fracture/loosening, superior-level facet joint violation, complication rate, reoperation rate on the same level or one level above, functional and clinical outcomes (Oswestry Disability Index, pain, Hospital Anxiety and Depression Scale, sensory and motor status) and cost-utility analysis.DiscussionThis RCT will provide insight into whether robot-assisted surgery with the newest generation spinal robot yields better pedicle screw placement accuracy than freehand surgery. Potential benefits of robot-assisted surgery include lower complication and revision rates, shorter length of stay, lower radiation exposure and reduction of economic cost of the overall care.Trial registrationClinicalTrials.gov NCT05553028. Registered on September 23, 2022

Clinical Efficacy of Laparoscopic Sentinel Node Navigation Surgery for Stomach Preservation in Patients With Early Gastric Cancer: 5-year Results of the SENORITA Trial.

This study aimed to compare laparoscopic standard gastrectomy (LSG) and laparoscopic sentinel node navigation surgery (LSNNS) for EGC in terms of 5-year long-term oncologic outcomes. The oncological safety of LSNNS for early gastric cancer (EGC) has not been confirmed. Three-year disease-free survival (DFS), which is the primary endpoint of the phase III multicenter randomized controlled clinical trial (SEntinel Node ORIented Tailored Approach [SENORITA] trial), did not show the non-inferiority of LSNNS relative to LSG. The SENORITA trial, a multicenter randomized clinical trial, was designed to show that LSNNS is non-inferior to LSG in terms of 3-year DFS. In the present study, we collected 5-year follow-up data from 527 patients recruited in the SENORITA trial as the full analysis set (FAS). Disease-free survival (DFS), overall survival (OS), disease-specific survival (DSS), and recurrence patterns were evaluated using the FAS of both LSG (n=269) and LSNNS (n=258). The 5-year DFS was not significantly different between the LSG and LSNNS groups (P=0.0561). During the 5-year follow-up, gastric cancer-related events, such as metachronous cancer, were more frequent in the LSNNS group than in the LSG group. However, ten recurrent cancers in the remnant stomach of both groups were curatively resected by additional gastrectomy and one by additional endoscopic resection. Two of the 198 patients who underwent local resection for stomach preservation based on the LSNNS results developed distant metastasis. However, there was no statistically significant difference in the 5-year OS and DSS (P=0.7403 and P=0.9586, respectively) between the two groups. The 5-year DFS, DSS and OS did not differ significantly between the two groups. Considering the benefits of LSNNS on postoperative quality of life, LSNNS could be recommended as an alternative treatment option for EGC.

Clinical evaluation of augmented reality-based 3D navigation system for brachial plexus tumor surgery

BackgroundAugmented reality (AR), a form of 3D imaging technology, has been preliminarily applied in tumor surgery of the head and spine, both are rigid bodies. However, there is a lack of research evaluating the clinical value of AR in tumor surgery of the brachial plexus, a non-rigid body, where the anatomical position varies with patient posture.MethodsPrior to surgery in 8 patients diagnosed with brachial plexus tumors, conventional MRI scans were performed to obtain conventional 2D MRI images. The MRI data were then differentiated automatically and converted into AR-based 3D models. After point-to-point relocation and registration, the 3D models were projected onto the patient’s body using a head-mounted display for navigation. To evaluate the clinical value of AR-based 3D models compared to the conventional 2D MRI images, 2 senior hand surgeons completed questionnaires on the evaluation of anatomical structures (tumor, arteries, veins, nerves, bones, and muscles), ranging from 1 (strongly disagree) to 5 (strongly agree).ResultsSurgeons rated AR-based 3D models as superior to conventional MRI images for all anatomical structures, including tumors. Furthermore, AR-based 3D models were preferred for preoperative planning and intraoperative navigation, demonstrating their added value. The mean positional error between the 3D models and intraoperative findings was approximately 1 cm.ConclusionsThis study evaluated, for the first time, the clinical value of an AR-based 3D navigation system in preoperative planning and intraoperative navigation for brachial plexus tumor surgery. By providing more direct spatial visualization, compared with conventional 2D MRI images, this 3D navigation system significantly improved the clinical accuracy and safety of tumor surgery in non-rigid bodies.

Workflow and Recommendations for Lateral Position Spinal Surgery With Robotics and Navigation

Recent decades have seen numerous significant advancements in the field of spinal and lumbar fusion surgeries, including the augmentation of surgical precision with robotic navigation. Use of robotic navigation in single-position lumbar fusion surgery (SPLS), which utilizes a lateral approach and requires no mid-procedure repositioning of the patient, has been shown to improve outcome measures and overall operative efficiency in addition to reducing patient time under anesthesia. Despite indications that robotically-assisted SPLS is superior to more traditional approaches in terms of cost and outcomes, relatively few surgeons currently utilize this innovative combination. This is largely attributed to the well-documented learning curve associated with robotically assisted surgery. In an attempt to mitigate this and reduce the barrier to entry for robotically-assisted spinal surgery, this report will give a detailed description of the workflow for SPLS procedures using robotic navigation. The authors will also give best-practice recommendations applicable for spine surgeons and surgical residents unfamiliar with surgical robotics systems.

Clinical outcomes of sentinel node navigation surgery in patients with preoperatively estimated stage IA endometrial cancer and evaluation of validity for continuing sentinel node navigation surgery based on dispersion of recurrence probability.

To evaluate the feasibility of the use and continuation of sentinel lymph node navigation surgery (SNNS) as an alternative to pelvic lymph node dissection (PLND) for patients with preoperatively estimated stage IA endometrial cancer. This retrospective study selected the electronic medical records of all patients who had received CT scans and MRI imaging before surgery from April 1, 2009 to March 31, 2021. Sentinel lymph nodes (SLNs) were detected by administrating 99mTc-phytate and/or indocyanine green into the cervix, and the clinical outcomes of the patients who underwent SNNS or PLND were evaluated. Furthermore, in case of nodal recurrence, a new procedure to determine whether the facility should continue with SNNS or not was developed that compares the maximum likelihood hypothesis and an alternative one based on recurrence rates. Among 137 patients, SLN biopsies with ultrastaging were performed on 91 patients. The SLN detection rate was 95.6%. Over a 59-month median observation period, no statistically significant differences were shown in overall survival, disease-specific survival and disease-free survival between the SNNS and PLND groups when introducing the propensity score method (p-values: 0.06, 0.153, and 0.625, respectively). Our procedure demonstrated that, in our department without recurrence up to the 65th attempt, it was possible to continue SNNS if a recurrence occurs at the 66th attempt. This study suggests the validity of SNNS as an alternative to PLND. Even in the absence of evidence from randomized controlled trials, we can confirm the validity of continuing SNNS using our procedure.

EVALUATION OF CLINICAL OUTCOMES AND ACCURACY IN TRANSPEDICULAR SCREW FIXATION USING INTRAOPERATIVE CT-GUIDED NAVIGATION FOR LUMBAR SPONDYLOLISTHESIS

The use of intraoperative navigation and robotic surgery for minimally invasive lumbar fusion has been increasing over the past decade. The aim of this study is to evaluate postoperative clinical outcomes, intraoperative parameters, and accuracy of pedicle screw insertion guided by intraoperative navigation in patients undergoing lumbar interbody fusion for spondylolisthesis. Patients who underwent posterior lumbar fusion interbody using intraoperative 3D navigation since December 2021 were included. Visual Analogue Scale (VAS), Oswestry Disability Index (ODI), and Short Form Health Survey-36 (SF-36) were assessed preoperatively and postoperatively at 1, 3, and 6 months. Screw placement accuracy, measured by Gertzbein and Robbins classification, and facet joint infringement, measured by Yson classification, were assessed by intraoperative Cone Beam CT scans performed at the end of instrumentation. Finally, operation time, intraoperative blood loss, hospital stay, and screw insertion time were evaluated. This study involved 50 patients with a mean age of 63.7 years. VAS decreased from 65.8±23 to 20±22 (p<.01). ODI decreased from 35.4%±15 to 11.8%±14 (p<.01). An increase of SF-36 from 51.5±14 to 76±13 (p<.01) was demonstrated. The accuracy of “perfect” and “clinically acceptable” pedicle screw fixation was 89.5% and 98.4%, respectively. Regarding facet violation, 96.8% of the screws were at grade 0. Finally, the average screw insertion time was 4.3±2 min, hospital stay was 4.2±0.8 days, operation time was 205±53 min, and blood loss was 169±107 ml. Finally, a statistically significant correlation of operation time with hospital stay, blood loss and placement time per screw was found. We demonstrated excellent results for accuracy of pedicle screw fixation and violation of facet joints. VAS, ODI and SF-36 showed statistically significant improvements from the control at one month after surgery.Navigation with intraoperative 3D images represents an effective system to improve operative performance in the surgical treatment of spondylolisthesis.

Artificial intelligence- and computer-assisted navigation for shoulder surgery.

Background: Over the last few decades, shoulder surgery has undergone rapid advancements, with ongoing exploration and the development of innovative technological approaches. In the coming years, technologies such as robot-assisted surgeries, virtual reality, artificial intelligence, patient-specific instrumentation, and different innovative perioperative and preoperative planning tools will continue to fuel a revolution in the medical field, thereby pushing it toward new frontiers and unprecedented advancements. In relation to this, shoulder surgery will experience significant breakthroughs. Main body: Recent advancements and technological innovations in the field were comprehensively analyzed. We aimed to provide a detailed overview of the current landscape, emphasizing the roles of technologies. Computer-assisted surgery utilizing robotic- or image-guided technologies is widely adopted in various orthopedic specialties. The most advanced components of computer-assisted surgery are navigation and robotic systems, with functions and applications that are continuously expanding. Surgical navigation requires a visual system that presents real-time positional data on surgical instruments or implants in relation to the target bone, displayed on a computer monitor. There are three primary categories of surgical planning that utilize navigation systems. The initial category involves volumetric images, such as ultrasound echogram, computed tomography, and magnetic resonance images. The second type is based on intraoperative fluoroscopic images, and the third type incorporates kinetic information about joints or morphometric data about the target bones acquired intraoperatively. Conclusion: The rapid integration of artificial intelligence and deep learning into the medical domain has a significant and transformative influence. Numerous studies utilizing deep learning-based diagnostics in orthopedics have remarkable achievements and performance.

Towards an optimization of catheter guidance in vascular surgery: A comparative analysis of the contribution of reinforcement learning

BackgroundPrecision in catheter guidance is essential for the success of vascular surgeries, yet current methods often need more accuracy due to the complex anatomy and dynamics of blood vessels. MethodsThis study evaluates the efficacy of advanced reinforcement learning (RL) techniques to enhance catheter navigation. We compare different RL approaches within simulated vascular environments, focusing on their success rates, operational efficiency, and adaptability to varied clinical scenarios. ResultsAdvanced reinforcement learning techniques display exceptional performance, yielding high success rates and improved precision in catheter guidance. Integrating specific enhancements has notably increased learning speeds and strengthened operational robustness. ConclusionThe study indicates that reinforcement learning could significantly improve the precision and safety of catheter navigation in vascular surgery. By adopting these techniques, medical practices could see more accurate and less invasive procedures, enhancing patient outcomes. Future research should aim to refine these algorithms for wider clinical use and integration.

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.