Three-dimensional–printed marker–based augmented reality neuronavigation: a new neuronavigation technique

Abstract

OBJECTIVE The aim of this study was to assess the precision and feasibility of 3D-printed marker–based augmented reality (AR) neurosurgical navigation and its use intraoperatively compared with optical tracking neuronavigation systems (OTNSs). METHODS Three-dimensional–printed markers for CT and MRI and intraoperative use were applied with mobile devices using an AR light detection and ranging (LIDAR) camera. The 3D segmentations of intracranial tumors were created with CT and MR images, and preoperative registration of the marker and pathology was performed. A patient-specific, surgeon-facilitated mobile application was developed, and a mobile device camera was used for neuronavigation with high accuracy, ease, and cost-effectiveness. After accuracy values were preliminarily assessed, this technique was used intraoperatively in 8 patients. RESULTS The mobile device LIDAR camera was found to successfully overlay images of virtual tumor segmentations according to the position of a 3D-printed marker. The targeting error that was measured ranged from 0.5 to 3.5 mm (mean 1.70 ± 1.02 mm, median 1.58 mm). The mean preoperative preparation time was 35.7 ± 5.56 minutes, which is longer than that for routine OTNSs, but the amount of time required for preoperative registration and the placement of the intraoperative marker was very brief compared with other neurosurgical navigation systems (mean 1.02 ± 0.3 minutes). CONCLUSIONS The 3D-printed marker–based AR neuronavigation system was a clinically feasible, highly precise, low-cost, and easy-to-use navigation technique. Three-dimensional segmentation of intracranial tumors was targeted on the brain and was clearly visualized from the skin incision to the end of surgery.

Evaluation Metrics for Augmented Reality in Neurosurgical Preoperative Planning, Surgical Navigation, and Surgical Treatment Guidance: A Systematic Review

“…In 30 studies (38%), the use of a head-mounted device for neurosurgery was evaluated ( Supplemental Digital Content 2, Table 1 , http://links.lww.com/ONS/B48). 10-86 In most of these studies, the HoloLens (Microsoft) was used for AR visualization. In 26 studies (32%), an image overlay, for either the microscopic or endoscopic field of view, was used.…”

“…Most of the studies reported on multiple evaluation metrics ( Supplemental Digital Content 3, Table 2 , http://links.lww.com/ONS/B49). 10-83,85-90 Based on the results of this review, the following evaluation categories have been defined: (1) registration accuracy, (2) clinical outcome, (3) time measurements, (4) task performance, (5) technical reliability, and (6) user perception (Table).…”

The usefulness of an Augmented Reality-based Interactive 3D Furniture Catalog as a Tool to Aid Furniture Store Sales Operations

“…Augmented Reality that necessitates the use of markers (Marker Based Tracking) This method necessitates the use of a marker image, which is typically a black-andwhite square illustration with bold black borders and white background. The computer will then recognize the position and orientation of the marker object and generate a 3D display with the coordinates (0, 0, 0) and an axis made up of X, Y, and Z [7]. The camera is pointed at the marker image and recognizes the marker image and then displays a 3D object based on the recognized marker image.…”

A systematic comparison of the accuracy of monocular RGB tracking and LiDAR for neuronavigation

“…Here, we build on a more nascent approach to register and track anatomy and tools; one that leverages light detection and ranging (LiDAR) technology, a tracking technique that uses principles of radar, but with laser light instead of electromagnetic radiation. Existing literature has only studied the use of LiDAR in registration [ 41 ], not tracking of anatomy and tools. Further, no systematic comparison between visual and LiDAR‐based tracking accuracy has been performed.…”