Imaging of the Paranasal Sinuses: Mitigation, Identification, and Workup of Functional Endoscopic Surgery Complications

A Label-Efficient Framework for Automated Sinonasal CT Segmentation in Image-Guided Surgery

OBJECTIVE

Segmentation, the partitioning of patient imaging into multiple, labeled segments, has several potential clinical benefits but when performed manually is tedious and resource intensive. Automated deep learning (DL)-based segmentation methods can streamline the process. The objective of this study was to evaluate a label-efficient DL pipeline that requires only a small number of annotated scans for semantic segmentation of sinonasal structures in CT scans.

STUDY DESIGN

Retrospective cohort study.

SETTING

Academic institution.

METHODS

Forty CT scans were used in this study including 16 scans in which the nasal septum (NS), inferior turbinate (IT), maxillary sinus (MS), and optic nerve (ON) were manually annotated using an open-source software. A label-efficient DL framework was used to train jointly on a few manually labeled scans and the remaining unlabeled scans. Quantitative analysis was then performed to obtain the number of annotated scans needed to achieve submillimeter average surface distances (ASDs).

RESULTS

Our findings reveal that merely four labeled scans are necessary to achieve median submillimeter ASDs for large sinonasal structures-NS (0.96 mm), IT (0.74 mm), and MS (0.43 mm), whereas eight scans are required for smaller structures-ON (0.80 mm).

CONCLUSION

We have evaluated a label-efficient pipeline for segmentation of sinonasal structures. Empirical results demonstrate that automated DL methods can achieve submillimeter accuracy using a small number of labeled CT scans. Our pipeline has the potential to improve pre-operative planning workflows, robotic- and image-guidance navigation systems, computer-assisted diagnosis, and the construction of statistical shape models to quantify population variations.

LEVEL OF EVIDENCE

N/A.

A systematic review of common landmarks in navigated endoscopic sinus surgery (NESS)

BACKGROUND

Navigation brought about a tremendous improvement in functional endoscopic sinus surgery (FESS). When upgraded accordingly, FESS becomes navigated endoscopic sinus surgery (NESS). Indications for intraoperative use of navigation can be broadened to almost any FESS case. NESS in advanced sinus surgery is currently still not used routinely and requires systematic practice guidelines.

PURPOSE

The purpose of this paper is to report on commonly identified landmarks while performing advanced NESS according to evidence-based medicine (EBM) principles.

MATERIAL AND METHODS

This review paper has been assembled following PRISMA guidelines. A PubMed and Scopus (EMBASE) search on anatomical landmarks in functional endoscopic and navigated sinus surgery resulted in 47 results. Of these, only 14 (29.8%) contained original data, constituting the synthesis of best-quality available evidence.

RESULTS

Anatomical landmarks are considered to be the most important points of orientation for optimal use of navigation systems during FESS surgery. The most commonly identified significant landmarks are as follows: (1) Maxillary sinus ostium; (2) Orbital wall; (3) Frontal recess; (4) Skull base; (5) Ground lamella; (6) Fovea posterior; (7) Sphenoid sinus ostium. Conclusions: Establishing common landmarks are essential in performing NESS. This is true for advanced and novice surgeons alike and offers a possibility to use navigation systems systematically, taking advantage of all the benefits of endoscopic navigated surgery.

Navigation and non-navigation CT scan of the sinuses: comparison of the effective doses of radiation in children and adults

BACKGROUND

The advent of 3D navigation imaging has opened new borders to the endoscopic surgical approaches of naso-sinusal inflammatory and neoplastic disease. This technology has gained in popularity among otolaryngologists for endoscopic sinus and skull base surgeries in both adults and children. However, the increased tissue radiation required for data acquisition associated with 3D navigation protocols CT scans is a source of concern because of its potential health hazards. We aimed to compare the effective doses of radiation between 3D navigation protocols and standard protocols for sinus computed tomography (CT) scans for both the adult and pediatric population.

METHODS

We performed a retrospective cohort study through electronic chart review of patients undergoing sinus CT scans (standard and 3D navigation protocols) from May 2019 to December 2019 using a Siemens Drive (VA62A) CT scanner. The effective dose of radiation was calculated in mSv for all exams. Average irradiation doses were compared using a Student's T-Test or a Kruskall-Wallis test when appropriate.

RESULTS

A total of 115 CT scans were selected for analysis, of which 47 were standard protocols and 68 were 3D navigation protocols CT scans. Among these, 31 exams were performed on children and 84 exams on adults. For the total population, mean effective dose in the non-navigation CT scans was 0.37 mSv (SD: 0.16, N = 47) and mean effective dose in the 3D navigation sinus CT group was 2.33 mSv (SD: 0.45, N = 68). The mean difference between the two groups was statistically significant 1.97 mSv (CI 95% - 2.1 to - 1.83; P < 0.0001). There was a sixfold increase in radiation with utilization of 3D navigation protocols. The ratio was identical when the pediatric as well as the adult subset of patients were analyzed.

CONCLUSION

In our center, utilization of 3D navigation sinus CT protocols significantly increases radiation exposure. Otolaryngologists should be aware of this significant increase and should attempt to decrease the radiation exposure of their patients by limiting unnecessary scan orders and by evaluating 3D acquisition protocols locally with radiation physicists.

LEVEL OF EVIDENCE

Level IV.

Computed tomography assessment of anterior ethmoidal canal dehiscence: An interobserver agreement study and review of the literature

PURPOSE

The anterior ethmoidal artery can be injured in functional endoscopic sinus surgery. The ability of computed tomography (CT) to identify dehiscence of the anterior ethmoidal canal (AEC) has not been widely evaluated. The aim of this study was to evaluate the interobserver agreement in the CT assessment of AEC dehiscence.

METHODS

We conducted a retrospective review of consecutive CT scans of the paranasal sinuses (PNS) between January 1, 2012, and December 31, 2012. Two neuroradiologists separately assessed the presence of AEC dehiscence, the presence of PNS opacification, and the best CT plane to evaluate the AEC. Statistical analysis included descriptive analysis and interobserver agreement (kappa coefficient).

RESULTS

The AEC was below the skull base in 199 (22.3%) cases. Dehiscence of the AEC was found in 13.2% for reader 1 and in 7.3% for reader 2. The interobserver agreement for identification of AEC dehiscence was only fair (κ = 0.246). The interobserver agreement for the AEC dehiscence in cases with opacification of ethmoidal air cells was substantial (κ = 0.754).

CONCLUSION

The suboptimal interobserver agreement could potentially limit the usefulness of CT scans for routine assessment of AEC dehiscence. In patients with PNS opacification, CT scans could still add valuable information regarding AEC dehiscence.

Evaluation and Stability Analysis of Video-Based Navigation System for Functional Endoscopic Sinus Surgery on In Vivo Clinical Data

Functional endoscopic sinus surgery (FESS) is one of the most common outpatient surgical procedures performed in the head and neck region. It is used to treat chronic sinusitis, a disease characterized by inflammation in the nose and surrounding paranasal sinuses, affecting about 15% of the adult population. During FESS, the nasal cavity is visualized using an endoscope, and instruments are used to remove tissues that are often within a millimeter of critical anatomical structures, such as the optic nerve, carotid arteries, and nasolacrimal ducts. To maintain orientation and to minimize the risk of damage to these structures, surgeons use surgical navigation systems to visualize the 3-D position of their tools on patients' preoperative Computed Tomographies (CTs). This paper presents an image-based method for enhanced endoscopic navigation. The main contributions are: (1) a system that enables a surgeon to asynchronously register a sequence of endoscopic images to a CT scan with higher accuracy than other reported solutions using no additional hardware; (2) the ability to report the robustness of the registration; and (3) evaluation on in vivo human data. The system also enables the overlay of anatomical structures, visible, or occluded, on top of video images. The methods are validated on four different data sets using multiple evaluation metrics. First, for experiments on synthetic data, we observe a mean absolute position error of 0.21mm and a mean absolute orientation error of 2.8° compared with ground truth. Second, for phantom data, we observe a mean absolute position error of 0.97mm and a mean absolute orientation error of 3.6° compared with the same motion tracked by an electromagnetic tracker. Third, for cadaver data, we use fiducial landmarks and observe an average reprojection distance error of 0.82mm. Finally, for in vivo clinical data, we report an average ICP residual error of 0.88mm in areas that are not composed of erectile tissue and an average ICP residual error of 1.09mm in areas that are composed of erectile tissue.

The Preoperative Sinus CT: Avoiding a "CLOSE" Call with Surgical Complications

Although functional endoscopic sinus surgery is an effective means of treating patients with recurrent and refractory sinusitis, the procedure is not without risk of serious surgical complications. Preoperative computed tomography (CT) affords radiologists the opportunity to prospectively identify anatomic variants that predispose patients to major surgical complications; however, these critical variants are not consistently evaluated or documented on preoperative imaging reports. The purpose of this review is to illustrate important anatomic variants and landmarks on the preoperative sinus CT with a focus on those that predispose patients to surgical complications. These critical variants and landmarks can be quickly recalled and incorporated into the preoperative imaging report through the use of the mnemonic "CLOSE": Cribriform plate, Lamina papyracea, Onodi cell, Sphenoid sinus pneumatization, and (anterior) Ethmoidal artery. This approach will greatly enhance the value of the preoperative imaging report for referring otolaryngologists and help reduce the risk of surgical complications. (©) RSNA, 2016 Online supplemental material is available for this article.

Image-Based Navigation for Functional Endoscopic Sinus Surgery Using Structure From Motion

Functional Endoscopic Sinus Surgery (FESS) is a challenging procedure for otolaryngologists and is the main surgical approach for treating chronic sinusitis, to remove nasal polyps and open up passageways. To reach the source of the problem and to ultimately remove it, the surgeons must often remove several layers of cartilage and tissues. Often, the cartilage occludes or is within a few millimeters of critical anatomical structures such as nerves, arteries and ducts. To make FESS safer, surgeons use navigation systems that register a patient to his/her CT scan and track the position of the tools inside the patient. Current navigation systems, however, suffer from tracking errors greater than 1 mm, which is large when compared to the scale of the sinus cavities, and errors of this magnitude prevent from accurately overlaying virtual structures on the endoscope images. In this paper, we present a method to facilitate this task by 1) registering endoscopic images to CT data and 2) overlaying areas of interests on endoscope images to improve the safety of the procedure. First, our system uses structure from motion (SfM) to generate a small cloud of 3D points from a short video sequence. Then, it uses iterative closest point (ICP) algorithm to register the points to a 3D mesh that represents a section of a patients sinuses. The scale of the point cloud is approximated by measuring the magnitude of the endoscope's motion during the sequence. We have recorded several video sequences from five patients and, given a reasonable initial registration estimate, our results demonstrate an average registration error of 1.21 mm when the endoscope is viewing erectile tissues and an average registration error of 0.91 mm when the endoscope is viewing non-erectile tissues. Our implementation SfM + ICP can execute in less than 7 seconds and can use as few as 15 frames (0.5 second of video). Future work will involve clinical validation of our results and strengthening the robustness to initial guesses and erectile tissues.