Intraoperative fiducial-less patient registration using volumetric 3D ultrasound: a prospective series of 32 neurosurgical cases

Charting the success of neuronavigation in brain tumor surgery: from inception to adoption and evolution

PURPOSE

Neuronavigation, explored as an intra-operative adjunct for brain tumor surgery three decades ago, has become globally utilized with a promising upward trajectory. This study aims to chart its success from idea to adoption and evolution within the US and globally.

METHODS

A three-pronged methodology included a systematic literature search, impact analysis using NIH relative citation ratio (RCR) and Altmetric scores, and assessment of patent holdings. Data was dichotomized for US and international contexts.

RESULTS

The first neuronavigation publication stemmed from Finland in 1993, marking its inception. Over three decades, the cumulative number of 323 studies, along with the significantly increasing publication trend (r = 0.74, p < 0.05) and distribution across 34 countries, underscored its progressive and global adoption. Neuronavigation, mostly optical systems (58%), was utilized in over 19,000 cases, predominantly for brain tumor surgery (84%). Literature impact showed a robust cumulative median RCR score surpassing that for NIH-funded studies (1.37 vs. 1.0), with US studies having a significantly higher median RCR than international (1.71 vs. 1.21, p < 0.05). Technological evolution was characterized by adjuncts, including micro/exo/endoscope (21%), MRI (17%), ultrasound (10%), and CT (7%). Patent analysis demonstrated academic and industrial representation with an interdisciplinary convergence of medical and computational sciences.

CONCLUSION

Since its inception thirty years ago, neuronavigation has been adopted worldwide, and it has evolved with adjunct technology integration to enhance its meaningful use. The current neuronavigation innovation pipeline is progressing, with academic and industry partnering to advance its further application in treating brain tumor patients.

Surgical Navigation System for Hypertensive Intracerebral Hemorrhage Based on Mixed Reality

Hypertensive intracerebral hemorrhage (HICH) is an intracerebral bleeding disease that affects 2.5 per 10,000 people worldwide each year. An effective way to cure this disease is puncture through the dura with a brain puncture drill and tube; the accuracy of the insertion determines the quality of the surgery. In recent decades, surgical navigation systems have been widely used to improve the accuracy of surgery and minimize risks. Augmented reality- and mixed reality-based surgical navigation is a promising new technology for surgical navigation in the clinic, aiming to improve the safety and accuracy of the operation. In this study, we present a novel multimodel mixed reality navigation system for HICH surgery in which medical images and virtual anatomical structures can be aligned intraoperatively with the actual structures of the patient in a head-mounted device and adjusted when the patient moves in real time while under local anesthesia; this approach can help the surgeon intuitively perform intraoperative navigation. A novel registration method is used to register the holographic space and serves as an intraoperative optical tracker, and a method for calibrating the HICH surgical tools is used to track the tools in real time. The results of phantom experiments revealed a mean registration error of 1.03 mm and an average time consumption of 12.9 min. In clinical usage, the registration error was 1.94 mm, and the time consumption was 14.2 min, showing that this system is sufficiently accurate and effective for clinical application.

Intraoperative Computed Tomography and Finite Element Modelling for Multimodal Image Fusion in Brain Surgery

BACKGROUND

intraoperative computer tomography (iCT) and advanced image fusion algorithms could improve the management of brainshift and the navigation accuracy.

OBJECTIVE

To evaluate the performance of an iCT-based fusion algorithm using clinical data.

METHODS

Ten patients with brain tumors were enrolled; preoperative MRI was acquired. The iCT was applied at the end of microsurgical resection. Elastic image fusion of the preoperative MRI to iCT data was performed by deformable fusion employing a biomechanical simulation based on a finite element model. Fusion accuracy was evaluated: the target registration error (TRE, mm) was measured for rigid and elastic fusion (Rf and Ef) and anatomical landmark pairs were divided into test and control structures according to distinct involvement by the brainshift. Intraoperative points describing the stereotactic position of the brain were also acquired and a qualitative evaluation of the adaptive morphing of the preoperative MRI was performed by 5 observers.

RESULTS

The mean TRE for control and test structures with Rf was 1.81 ± 1.52 and 5.53 ± 2.46 mm, respectively. No significant change was observed applying Ef to control structures; the test structures showed reduced TRE values of 3.34 ± 2.10 mm after Ef (P < .001). A 32% average gain (range 9%-54%) in accuracy of image registration was recorded. The morphed MRI showed robust matching with iCT scans and intraoperative stereotactic points.

CONCLUSIONS

The evaluated method increased the registration accuracy of preoperative MRI and iCT data. The iCT-based non-linear morphing of the preoperative MRI can potentially enhance the consistency of neuronavigation intraoperatively.

CT and MRI Image Fusion Error: An Analysis of Co-Registration Error Using Commercially Available Deep Brain Stimulation Surgical Planning Software

INTRODUCTION

During deep brain stimulation (DBS) surgery, computed tomography (CT) and magnetic resonance imaging (MRI) scans need to be co-registered or fused. Image fusion is associated with the error that can distort the location of anatomical structures. Co-registration in DBS surgery is usually performed automatically by proprietary software; the amount of error during this process is not well understood. Here, our goal is to quantify the error during automated image co-registration with FrameLink™, a commonly used software for DBS planning and clinical research.

METHODS

This is a single-center retrospective study at a quaternary care referral center, comparing CT and MR imaging co-registration for a consecutive series of patients over a 12-month period. We collected CT images and MRI scans for 22 patients with Parkinson's disease requiring placement of DBS. Anatomical landmarks were located on CT images and MRI scans using a novel image analysis algorithm that included a method for capturing the potential error inherent in the image standardization step of the analysis. The distance between the anatomical landmarks was measured, and the error was found by averaging the distances across all patients.

RESULTS

The average error during co-registration was 1.25 mm. This error was significantly larger than the error resulting from image standardization (0.19 mm) and was worse in the anterior-posterior direction.

CONCLUSIONS

The image fusion errors found in this analysis were nontrivial. Although the estimated error may be inflated, it is sig-nificant enough that users must be aware of this potential inaccuracy, and developers of proprietary software should provide details about the magnitude and direction of co-registration errors.

Regional-surface-based registration for image-guided neurosurgery: effects of scan modes on registration accuracy

PURPOSE

The conventional surface-based method only registers the facial zone with preoperative point cloud, resulting in low accuracy away from the facial area. Acquiring a point cloud of the entire head for registration can improve registration accuracy in all parts of the head. However, it takes a long time to collect a point cloud of the entire head. It may be more practical to selectively scan part of the head to ensure high registration accuracy in the surgical area of interest. In this study, we investigate the effects of different scan regions on registration errors in different target areas when using a surface-based registration method.

METHODS

We first evaluated the correlation between the laser scan resolution and registration accuracy to determine an appropriate scan resolution. Then, with the appropriate resolution, we explored the effects of scan modes on registration error in computer simulation experiments, phantom experiments and two clinical cases. The scan modes were designed based on different combinations of five zones of the head surface, i.e., the sphenoid-frontal zone, parietal zone, left temporal zone, right temporal zone and occipital zone. In the phantom experiment, a handheld scanner was used to acquire a point cloud of the head. A head model containing several tumors was designed, enabling us to calculate the target registration errors deep in the brain to evaluate the effect of regional-surface-based registration.

RESULT

The optimal scan modes for tumors located in the sphenoid-frontal, parietal and temporal areas are mode 4 (i.e., simultaneously scanning the sphenoid-frontal zone and the temporal zone), mode 4 and mode 6 (i.e., simultaneously scanning the sphenoid-frontal zone, the temporal zone and the parietal zone), respectively. For the tumor located in the occipital area, no modes were able to achieve reliable accuracy.

CONCLUSION

The results show that selecting an appropriate scan resolution and scan mode can achieve reliable accuracy for use in sphenoid-frontal, parietal and temporal area surgeries while effectively reducing the operation time.

Applications of Ultrasound in the Resection of Brain Tumors

Neurosurgery makes use of preoperative imaging to visualize pathology, inform surgical planning, and evaluate the safety of selected approaches. The utility of preoperative imaging for neuronavigation, however, is diminished by the well-characterized phenomenon of brain shift, in which the brain deforms intraoperatively as a result of craniotomy, swelling, gravity, tumor resection, cerebrospinal fluid (CSF) drainage, and many other factors. As such, there is a need for updated intraoperative information that accurately reflects intraoperative conditions. Since 1982, intraoperative ultrasound has allowed neurosurgeons to craft and update operative plans without ionizing radiation exposure or major workflow interruption. Continued evolution of ultrasound technology since its introduction has resulted in superior imaging quality, smaller probes, and more seamless integration with neuronavigation systems. Furthermore, the introduction of related imaging modalities, such as 3-dimensional ultrasound, contrast-enhanced ultrasound, high-frequency ultrasound, and ultrasound elastography, has dramatically expanded the options available to the neurosurgeon intraoperatively. In the context of these advances, we review the current state, potential, and challenges of intraoperative ultrasound for brain tumor resection. We begin by evaluating these ultrasound technologies and their relative advantages and disadvantages. We then review three specific applications of these ultrasound technologies to brain tumor resection: (1) intraoperative navigation, (2) assessment of extent of resection, and (3) brain shift monitoring and compensation. We conclude by identifying opportunities for future directions in the development of ultrasound technologies.