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

Introduction The three-dimensional (3D) endoscope is considered a new surgical tool used in different approaches in intranasal and anterior skull base surgical procedures. There are many advantages of 3D over two-dimensional (2D) endoscopy that have been demonstrated in clinical applications, surgical training, and different experimental studies. Objective To show the difference between using the 3D and 2D endoscopes during endonasal and anterior skull base surgery and its importance. Methods Our study is divided into two phases (clinical and cadaveric phases). In the clinical study we, have performed 52 endonasal and anterior skull base surgical procedures (26 study cases and 26 control cases). We recorded accuracy, duration, and intraoperative complication for each case. The cadaveric study was performed on three cadavers. Differences in accuracy and dissection time were recorded using 3D and 2D endoscopy for each side chosen by randomization. Results In the clinical study, the cases done by 3D endoscope were significantly faster and more accurate with less intraoperative complications compared with cases done using 2D endoscope. In cadaveric dissection, while using 3D endoscope, there was better depth of perception regarding the anatomical landmarks compared with 2D endoscope. Conclusion Three-dimensional endoscopy is an advanced instrument that allows better training for the coming generation of ear, nose, and throat surgeons. Both clinical and cadaveric studies offer a promising outcome in both endonasal and anterior skull base surgery.

Importance Skull base surgery requires precise preoperative assessment and intraoperative management of the patient. Surgical navigation is routinely used for complex skull base cases; however, the image guidance is commonly based on preoperative scans alone. Objective The primary objective of this study was to assess the image quality of intraoperative cone-beam computed tomography (CBCT) within anatomical landmarks used in sinus and skull base surgery. The secondary objective was to assess the registration error of a surgical navigation system based on intraoperative CBCT. Design Present study is a retrospective case series of image quality after intraoperative cone beam CT. Setting The study was conducted at Toronto General Hospital and Princess Margaret Cancer Centre, University Health Network, Toronto. Participants A total of 46 intraoperative scans (34 patients, 21 skull base, 13 head and neck) were studied. Main Outcome and Measures Thirty anatomical landmarks (vascular, soft tissue, and bony) within the sinuses and anterior skull base were evaluated for general image quality characteristics: (1) bony detail visualization; (2) soft-tissue visualization; (3) vascular visualization; and (4) freedom from artifacts (e.g., metal). Levels of intravenous (IV) contrast enhancement were quantified in Hounsfield's units (HU). Standard paired-point registration between imaging and tracker coordinates was performed using 6 to 8 skin fiducial markers and the corresponding fiducial registration error (FRE) was measured. Results Median score for bony detail on CBCT was 5, remaining at 5 after administration of IV contrast. Median soft-tissue score was 2 for both pre- and postcontrast. Median vascular score was 1 precontrast and 3 postcontrast. Median score for artifacts on CBCT were 2 for both pre-and postcontrast, and metal objects were noted to be the most significant source of artifact. Intraoperative CBCT allowed preresection images and immediate postresection images to be available to the skull base surgeon. There was a significant improvement in mean (standard deviation [SD]) CT intensity in the left carotid artery postcontrast 334 HU (67 HU) ( p < 10 -10 ). The mean FRE was 1.8 mm (0.45 mm). Conclusion Intraoperative CBCT in complex skull base procedures provides high-resolution bony detail allowing immediate assessment of complex resections. The use of IV contrast with CBCT improves the visualization of vasculature. Image-guidance based on CBCT yields registration errors consistent with standard techniques.

The application of robotic surgery to anterior skull base disease has yet to be defined despite the potential for improved tumour resection with less morbidity in this region. Complex anatomy and restricted access have limited the development of robotic anterior skull base surgery. A limited number of transoral robotic surgical anterior skull base procedures have been undertaken; however, there are significant limitations to the utilization of this technology in the anterior skull base. In this article, the advantages, disadvantages and limitations of robotic anterior skull base surgery are discussed. Currently, the major limitation is the size of the robotic endoscope and of the available instrumentation. Technological advancements that provide promise for the future development of robotic anterior skull base surgery are in development, such as single-port robots, flexible instrument systems and miniaturization and growth of minimally invasive platforms. Although transnasal access to the skull base is not possible with the currently available robotic systems, promising technology does exist and is in development. Robotic anterior skull base surgery promises to provide greater access to skull base disease, improve oncologic results, reduce morbidity and to reduce the ergonomic burden on the surgeon.

Simultaneous localization and mapping (SLAM) is the key technology to realize self-localization of autonomous vehicles. However, the lidar SLAM with traditional loop closure detection cannot obtain reliable accuracy and real-time under large scale scene due to the accumulated error of point cloud registration. In this paper, a hybrid loop closure detection (HLCD) method based on spatial location and appearance similarity is proposed and introduced into lidar SLAM technology. An experimental test is implemented on the platform of autonomous vehicle to verify the correctness and feasibility of theoretical design. Experimental results show that the proposed method can effectively reduce the cumulative deviation and time consuming.

[This corrects the article DOI: 10.1371/journal.pone.0227312.].

S203 – The STAMP Registration for Image‐guided Otologic Surgery

Surgical navigation assists in endoscopic surgeries by enabling surgeons to see concealed lesions and surrounding organs. Successful surgical navigation depends on accurate registration between a medical image and a patient. For accurate point-based registration, it is important to determine the matching order and positions of the markers correctly. It is particularly difficult to determine the order and positions when part of the markers cannot be located on the patient's body or when they cannot be identified in the images. By using the automatic marker-matching option of the proposed tool, an optimum registration result can be obtained even with the partial loss of markers. In addition, this tool provides an intuitive marker selection interface that displays the registration error of each marker pair in different colors. The efficiency of the described tool in terms of the registration accuracy and time has been confirmed in more than 70 clinical applications. The fiducial registration errors were 1.28 + or - 1.09 mm in ear, nose, and throat surgery and 3.55 + or - 1.30 mm in liver tumor ablation therapy. The proposed automatic matching scheme with marker selection interface was particularly effective where the markers were partly lost or incorrectly identified.

Despite the increasing utility of the endoscopic endonasal approach (EEA) for management of anterior skull base (ASB) pathologies, the optimal treatment strategy for olfactory groove meningiomas (OGM) remains unclear. This project sought to systematically compare outcomes of EEA management with conventional transcranial approach (TCA) for the treatment of OGMs. A systematic review was performed to identify studies that compared outcomes following EEA and TCA for OGMs. Data extracted from each study included gross total resection (GTR), incidence of cerebrospinal fluid (CSF) leaks, and post-operative complications including anosmia. The results of the search yielded 5 studies which met the criteria for inclusion and analysis. All studies compared TCA (n = 922) with EEA (n = 141) outcomes for OGMs. Overall, the rate of gross total resection (GTR) was lower among the endoscopic group (70.9%) relative to the transcranial group (91.5%). The rate of post-operative CSF leak was 6.3% vs. 25.5% for the transcranial and endoscopic groups, respectively. Post-operative anosmia was higher for patients undergoing EEA (95.9%) compared with patients in the transcranial group (37.4%). In this analysis, EEA was associated with a lower rate of GTR and higher incidences of CSF leaks and post-operative anosmia. However, with increasing surgeon familiarity of the endoscopic anatomy and technique for managing ASB pathologies, a nuanced approach may be used to minimize patient morbidity and widen the spectrum of skull base surgery.

Introduction: The objective of this pilot study was to evaluate the utility of novel 3-dimensional (3D) endoscopy during endoscopic sinonasal and skull base surgery.

Anterior skull base surgery without prophylactic airway diversion procedures

Super-resolution reconstruction of image sequences is highly dependent on the quality of the motion estimation between successive frames. This work presents a statistical analysis of the least mean square (LMS) algorithm applied to super-resolution reconstruction of an image sequence. Deterministic recursions are derived for the mean and mean square behaviors of the reconstruction error as functions of the registration errors. The new model describes the behavior of the algorithm in realistic situations, and significantly improves the accuracy of a simple model available in the literature. Monte Carlo simulations show good agreement between actual and predicted behaviors

Laparoscopic surgery is a widely used minimally invasive technique to treat a variety of pathologies within the abdominopelvic region. Compared to conventional open surgery, laparoscopic surgery reduces iatrogenic trauma and hospital stay length. Nevertheless, surgeons have a limited field of view during operation because surgical instruments are inserted through the patient's body via small incisions. To improve surgeon's perception, surgical navigation techniques are implemented to improve visualization. A number of surgical navigation systems being developed are integrated with computer algorithms to enhance their efficiency. In this work, we generate novel views, depths, and camera poses of corresponding laparoscopic images to augment our dataset, which can then be used to train and evaluate learning-based computer vision algorithms such as simultaneous localization and mapping (SLAM) and visual odometry. Our existing dataset was generated from porcine tissue images using a laparoscope and an optical tracking system to capture camera poses. We performed tissue surface reconstruction of the dataset via the NeRF-SLAM algorithm. Camera poses were transformed to acquire novel views of RGB laparoscopic images and their corresponding depth images. The results show that the simulated RGB images have an average peak signal-to-noise ratios (PSNR) between 29.17 - 29.79 dB, structural similarity index measure (SSIM) value between 0.6061 - 0.6174, and learned perceptual image patch similarity (LPIPS) value between 0.568 - 0.592 compared to the corresponding input images. This work provides a foundation for the generation of synthetic datasets, which could be useful for learning-based autonomous surgical navigation systems.

Objective: Three-dimensional (3D) endoscopy is a new procedure in endonasal and anterior skull base surgery which improve the depth of perception and intraoperative orientation over two-dimensional (2D) endoscopy. Its importance has been demonstrated in surgical training, clinical applications and experimental studies. This study aimed to clarify the difference between uses 2D and 3D endoscopes by novice users and importance of 3D endoscope in cadaveric dissections and surgical techniques in endonasal and anterior skull base surgery.

Surgical navigation technology combines patient imaging studies with intraoperative real-time data to improve surgical precision and patient outcomes. The navigation workflow can also include preoperative planning, which can reliably simulate the intended resection and reconstruction. The advantage of this approach in skull-base surgery is that it guides access into a complex three-dimensional area and orients tumors intraoperatively with regard to critical structures, such as the orbit, carotid artery and brain. This enhances a surgeon's capabilities to preserve normal anatomy while resecting tumors with adequate margins. The aim of this narrative review is to outline the state of the art and the future directions of surgical navigation in the skull base, focusing on the advantages and pitfalls of this technique. We will also present our group experience in this field, within the frame of the current research trends.

The aim of this article is to investigate the feasibility of using a statistical shape model (SSM)-based reconstruction technique to derive a scaled, patient-specific surface model of the pelvis from a single standard anteroposterior (AP) x-ray radiograph and the feasibility of estimating the scale of the reconstructed surface model by performing a surface-based 3D/3D matching. Data sets of 14 pelvises (one plastic bone, 12 cadavers, and one patient) were used to validate the single-image based reconstruction technique. This reconstruction technique is based on a hybrid 2D/3D deformable registration process combining a landmark-to-ray registration with a SSM-based 2D/3D reconstruction. The landmark-to-ray registration was used to find an initial scale and an initial rigid transformation between the x-ray image and the SSM. The estimated scale and rigid transformation were used to initialize the SSM-based 2D/3D reconstruction. The optimal reconstruction was then achieved in three stages by iteratively matching the projections of the apparent contours extracted from a 3D model derived from the SSM to the image contours extracted from the x-ray radiograph: Iterative affine registration, statistical instantiation, and iterative regularized shape deformation. The image contours are first detected by using a semiautomatic segmentation tool based on the Livewire algorithm and then approximated by a set of sparse dominant points that are adaptively sampled from the detected contours. The unknown scales of the reconstructed models were estimated by performing a surface-based 3D/3D matching between the reconstructed models and the associated ground truth models that were derived from a CT-based reconstruction method. Such a matching also allowed for computing the errors between the reconstructed models and the associated ground truth models. The technique could reconstruct the surface models of all 14 pelvises directly from the landmark-based initialization. Depending on the surface-based matching techniques, the reconstruction errors were slightly different. When a surface-based iterative affine registration was used, an average reconstruction error of 1.6 mm was observed. This error was increased to 1.9 mm, when a surface-based iterative scaled rigid registration was used. It is feasible to reconstruct a scaled, patient-specific surface model of the pelvis from single standard AP x-ray radiograph using the present approach. The unknown scale of the reconstructed model can be estimated by performing a surface-based 3D/3D matching.