Brain Shift in Neuronavigation of Brain Tumors: An Updated Review of Intra-Operative Ultrasound Applications

[Progress in neurosurgical treatment of neurofibromatosis type 1]

Objective

To summarize the latest developments in neurosurgical treatments for neurofibromatosis type 1 (NF1) and explore therapeutic strategies to provide comprehensive treatment guidelines for clinicians.

Methods

The recent domestic and international literature and clinical cases in the field of NF1 were reviewed. The main types of neurological complications associated with NF1 and their treatments were thorough summarized and the future research directions in neurosurgery was analyzed.

Results

NF1 frequently results in complex and diverse lesions in the central and peripheral nervous systems, particularly low-grade gliomas in the brain and spinal canal and paraspinal neurofibromas. Treatment decisions should be made by a multidisciplinary team. Symptomatic plexiform neurofibromas and tumors with malignant imaging evidence require neurosurgical intervention. The goals of surgery include reducing tumor size, alleviating pain, and improving appearance. Postoperative functional rehabilitation exercises, long-term multidisciplinary follow-up, and psychosocial interventions are crucial for improving the quality of life for patients. Advanced imaging guidance systems and artificial intelligence technologies can help increase tumor resection rates and reduce recurrence.

Conclusion

Neurosurgical intervention is the primary treatment for symptomatic plexiform neurofibromas and malignant peripheral nerve sheath tumors when medical treatment is ineffective and the lesions progress rapidly. Preoperative multidisciplinary assessment, intraoperative electrophysiological monitoring, and advanced surgical assistance devices significantly enhance surgical efficacy and safety. Future research should continue to explore new surgical techniques and improve postoperative management strategies to achieve more precise and personalized treatment for NF1 patients.

Sensitivity of Frequency Domain Near Infrared Spectroscopy for Neurovascular Structure Detection in Biotissue Volume: Numerical Modeling Results

Through numerical modeling, it has been determined that near infrared spectroscopy with a frequency domain approach can detect neurovascular structures with diameters from 0.5 mm at source-detector distances of 5-8 mm, depending on optical parameters and technical implementation of the method. Among the five classical machine learning methods considered, quadratic discriminant analysis is the most effective for detection. Furthermore, it has been demonstrated that the use of a photomultiplier tube and the registration of both amplitude and phase signal components exhibit the highest sensitivity. Spectroscopy can rival modern ultrasound for detecting arterial vessels. A cross-shaped probe configuration improves sensitivity, and the ratio of reduced scattering coefficient values at different wavelengths is informative for blood-filled vessel detection. These findings are consistent with and significantly extend previous experimental in vivo and in situ studies and could be valuable for intraoperative diagnostic tasks, particularly in neurosurgery.

Navigated intraoperative ultrasound in pediatric brain tumors

PURPOSE

The aim of this study was to evaluate the diagnostic value and accuracy of navigated intraoperative ultrasound (iUS) in pediatric oncological neurosurgery as compared to intraoperative magnetic resonance imaging (iMRI).

METHODS

A total of 24 pediatric patients undergoing tumor debulking surgery with iUS, iMRI, and neuronavigation were included in this study. Prospective acquisition of iUS images was done at two time points during the surgical procedure: (1) before resection for tumor visualization and (2) after resection for residual tumor assessment. Dice similarity coefficients (DSC), Hausdorff distances 95th percentiles (HD95) and volume differences, sensitivity, and specificity were calculated for iUS segmentations as compared to iMRI.

RESULTS

A high correlation (R = 0.99) was found for volume estimation as measured on iUS and iMRI before resection. A good spatial accuracy was demonstrated with a median DSC of 0.72 (IQR 0.14) and a median HD95 percentile of 4.98 mm (IQR 2.22 mm). The assessment after resection demonstrated a sensitivity of 100% and a specificity of 84.6% for residual tumor detection with navigated iUS. A moderate accuracy was observed with a median DSC of 0.58 (IQR 0.27) and a median HD95 of 5.84 mm (IQR 4.04 mm) for residual tumor volumes.

CONCLUSION

We found that iUS measurements of tumor volume before resection correlate well with those obtained from preoperative MRI. The accuracy of residual tumor detection was reliable as compared to iMRI, indicating the suitability of iUS for directing the surgeon's attention to areas suspect for residual tumor. Therefore, iUS is considered as a valuable addition to the neurosurgical armamentarium.

TRIAL REGISTRATION NUMBER AND DATE

PMCLAB2023.476, February 12th 2024.

Learnable real-time inference of molecular composition from diffuse spectroscopy of brain tissue

Significance

Diffuse optical modalities such as broadband near-infrared spectroscopy (bNIRS) and hyperspectral imaging (HSI) represent a promising alternative for low-cost, non-invasive, and fast monitoring of living tissue. Particularly, the possibility of extracting the molecular composition of the tissue from the optical spectra deems the spectroscopy techniques as a unique diagnostic tool.

Aim

No established method exists to streamline the inference of the biochemical composition from the optical spectrum for real-time applications such as surgical monitoring. We analyze a machine learning technique for inference of changes in the molecular composition of brain tissue.

Approach

We propose modifications to the existing learnable methodology based on the Beer-Lambert law. We evaluate the method's applicability to linear and nonlinear formulations of this physical law. The approach is tested on data obtained from the bNIRS- and HSI-based monitoring of brain tissue.

Results

The results demonstrate that the proposed method enables real-time molecular composition inference while maintaining the accuracy of traditional methods. Preliminary findings show that Beer-Lambert law-based spectral unmixing allows contrasting brain anatomy semantics such as the vessel tree and tumor area.

Conclusion

We present a data-driven technique for inferring molecular composition change from diffuse spectroscopy of brain tissue, potentially enabling intra-operative monitoring.

Open access segmentations of intraoperative brain tumor ultrasound images

PURPOSE

Registration and segmentation of magnetic resonance (MR) and ultrasound (US) images could play an essential role in surgical planning and resectioning brain tumors. However, validating these techniques is challenging due to the scarcity of publicly accessible sources with high-quality ground truth information. To this end, we propose a unique set of segmentations (RESECT-SEG) of cerebral structures from the previously published RESECT dataset to encourage a more rigorous development and assessment of image-processing techniques for neurosurgery.

ACQUISITION AND VALIDATION METHODS

The RESECT database consists of MR and intraoperative US (iUS) images of 23 patients who underwent brain tumor resection surgeries. The proposed RESECT-SEG dataset contains segmentations of tumor tissues, sulci, falx cerebri, and resection cavity of the RESECT iUS images. Two highly experienced neurosurgeons validated the quality of the segmentations.

DATA FORMAT AND USAGE NOTES

Segmentations are provided in 3D NIFTI format in the OSF open-science platform: https://osf.io/jv8bk.

POTENTIAL APPLICATIONS

The proposed RESECT-SEG dataset includes segmentations of real-world clinical US brain images that could be used to develop and evaluate segmentation and registration methods. Eventually, this dataset could further improve the quality of image guidance in neurosurgery.

Neuronavigation in glioma resection: current applications, challenges, and clinical outcomes

Background

Glioma resection aims for maximal tumor removal while preserving neurological function. Neuronavigation systems (NS), with intraoperative imaging, have revolutionized this process through precise tumor localization and detailed anatomical navigation.

Objective

To assess the efficacy and breadth of neuronavigation and intraoperative imaging in glioma resections, identify operational challenges, and provide educational insights to medical students and non-neurosurgeons regarding their practical applications.

Methods

This systematic review analyzed studies from 2012 to 2023 on glioma patients undergoing surgical resection with neuronavigation, sourced from MEDLINE (PubMed), Embase, and Web of Science. A database-specific search strategy was employed, with independent reviewers screening for eligibility using Rayyan and extracting data using the Joanna Briggs Institute (JBI) tool.

Results

The integration of neuronavigation systems with intraoperative imaging modalities such as iMRI, iUS, and 5-ALA significantly enhances gross total resection (GTR) rates and extent of resection (EOR). While advanced technology improves surgical outcomes, it does not universally reduce operative times, and its impact on long-term survival varies. Combinations like NS + iMRI and NS + 5-ALA + iMRI achieve higher GTR rates compared to NS alone, indicating that advanced imaging adjuncts enhance tumor resection accuracy and success. The results underscore the multifaceted nature of successful surgical outcomes.

Conclusions

Integrating intraoperative imaging with neuronavigation improves glioma resection. Ongoing research is vital to refine technology, enhance accuracy, reduce costs, and improve training, considering various factors impacting patient survival.

Clinical application of intraoperative ultrasound superb microvascular imaging in brain tumors resections: contributing to the achievement of total tumoral resection

BACKGROUND

To investigate whether the intraoperative superb microvascular imaging(SMI) technique helps evaluate lesion boundaries compared with conventional grayscale ultrasound in brain tumor surgery and to explore factors that may be associated with complete radiographic resection.

METHODS

This study enrolled 57 consecutive brain tumor patients undergoing surgery. During the operation, B-mode and SMI ultrasound evaluated the boundaries of brain tumors. MRI before and within 48h after surgery was used as the gold standard to evaluate gross-total resection(GTR). The ultrasound findings and GTR results were analyzed to determine the imaging factors related to GTR.

RESULTS

A total of 57 patients were enrolled in the study, including 32 males and 25 females, with an average age of 53.4 ± 14.1 years old(range 19 ~ 80). According to the assessment criteria of MRI, before and within 48 h after the operation, 37(63.9%) cases were classified as GTR, and 20(35.1%) cases were classified as GTR. In comparing tumor interface definition between B-mode and SMI mode, SMI improved HGG boundary recognition in 5 cases(P = 0.033). The results showed that the tumor size ≥ 5 cm and unclear ultrasonic boundary were independent risk factors for nGTR (OR>1, P<0.05).

CONCLUSIONS

As an innovative intraoperative doppler technique in neurosurgery, SMI can effectively demarcate the tumor's boundary and help achieve GTR as much as possible.

Mass spectrometry for neurosurgery: Intraoperative support in decision-making

Ambient ionization mass spectrometry was proved to be a powerful tool for oncological surgery. Still, it remains a translational technique on the way from laboratory to clinic. Brain surgery is the most sensitive to resection accuracy field since the balance between completeness of resection and minimization of nerve fiber damage determines patient outcome and quality of life. In this review, we summarize efforts made to develop various intraoperative support techniques for oncological neurosurgery and discuss difficulties arising on the way to clinical implementation of mass spectrometry-guided brain surgery.

An 8 mm endoscopic histotripsy array with integrated high-resolution ultrasound imaging

An 8 mm diameter, image-guided, annular array histotripsy transducer was fabricated and characterized. The array was laser etched on a 5 MHz, 1-3 dice and fill, PZT-5H/epoxy composite with a 45 % volume fraction. Flexible PCBs were used to electrically connect to the array elements using wirebonds. The array was backed with a low acoustic impedance epoxy mixture. A 3.6 by 3.8 mm, 64-element, 30 MHz phased array imaging probe was positioned in the center hole, to co-align the imaging plane with the bubble cloud produced by the therapy array. A custom 16-channel high voltage pulse generator was used to test the annular array for focal lengths ranging from 3- to 8-mm. An aluminum lens-focussed transducer with a 7 mm focal length was fabricated using the same piezocomposite and backing material and tested along with the histotripsy array. Simulated results from COMSOL FEM models were compared to measured results for low voltage characterization of the array and lens-focussed transducer. The measured transmit sensitivity of the array ranged from 0.113 to 0.167 MPa/V, while the lens-focussed transducer was 0.192 MPa/V. Simulated values were 0.160 to 0.174 MPa/V and 0.169 MPa/V, respectively. The measured acoustic fields showed a significantly increased depth-of-field compared the lens-focussed transducer, while the beamwidths of the array focus were comparable to the lens. The measured cavitation voltage in water was between 254 V and 498 V depending on the focal length, and 336 V for the lens-focussed transducer. The array had a lower cavitation voltage than the lens-focussed transducer for a comparable operating depth. The histotripsy array was tested in a tissue phantom and an in vivo rat brain. It was used to produce an elongated lesion in the brain by electronically steering the focal length from 3- to 8-mm axially. Real time ultrasound imaging with a Doppler overlay was used to target the tissue and monitor ablation progress, and histology confirmed the targeted tissue was fully homogenized.

An Observational Comparative Study to Evaluate the Use of Image-Guided Surgery in the Management and Outcome of Supratentorial Intracranial Space-Occupying Lesions

Objectives

The objective of this article is to study the effect of neuronavigation on the outcome of surgery for supratentorial tumors, such as the extent of resection, size of craniotomy, and overall morbidity and mortality by comparing with conventional excision.

Methods

A total of 50 patients undergoing intracranial surgery for supratentorial space-occupying lesions from 2020 to 2022 were included in the study. One intervention group consisted of patients undergoing surgical resection of supratentorial tumors utilizing image guidance versus the control group, which consisted of patients undergoing surgical excision of supratentorial tumor excision without image guidance. Parameters used to compare the outcome were the extent of resection of the lesions, craniotomy size, and overall morbidity and mortality.

Results and Conclusion

There was no significant reduction in craniotomy size or prolongation of operative duration with the use of neuronavigation. There was no significant difference in postoperative hospital stay between the two groups. Neuronavigation-assisted cases did not show any significant reduction in the occurrence of postoperative neurological deficits or any reduction of overall morbidity and mortality.

Application accuracy of a frameless optical neuronavigation system as a guide for craniotomies in dogs

BACKGROUND

Optical neuronavigation systems using infrared light to create a virtual reality image of the brain allow the surgeon to track instruments in real time. Due to the high vulnerability of the brain, neurosurgical interventions must be performed with a high precision. The aim of the experimental cadaveric study was to determine the application accuracy of a frameless optical neuronavigation system as guide for craniotomies by determining the target point deviation of predefined target points at the skull surface in the area of access to the cerebrum, cerebellum and the pituitary fossa. On each of the five canine cadaver heads ten target points were marked in a preoperative computed tomography (CT) scan. These target points were found on the cadaver skulls using the optical neuronavigation system. Then a small drill hole (1.5 mm) was drilled at these points. Subsequently, another CT scan was made. Both CT data sets were fused into the neuronavigation software, and the actual target point coordinates were identified. The target point deviation was determined as the difference between the planned and drilled target point coordinates. The calculated deviation was compared between two observers.

RESULTS

The analysis of the target point accuracies of all dogs in both observers taken together showed a median target point deviation of 1.57 mm (range: 0.42 to 5.14 mm). No significant differences were found between the observers or the different areas of target regions.

CONCLUSION

The application accuracy of the described system is similar to the accuracy of other optical neuronavigation systems previously described in veterinary medicine, in which mean values of 1.79 to 4.3 mm and median target point deviations of 0.79 to 3.53 mm were determined.

Lightfield hyperspectral imaging in neuro-oncology surgery: an IDEAL 0 and 1 study

Introduction

Hyperspectral imaging (HSI) has shown promise in the field of intra-operative imaging and tissue differentiation as it carries the capability to provide real-time information invisible to the naked eye whilst remaining label free. Previous iterations of intra-operative HSI systems have shown limitations, either due to carrying a large footprint limiting ease of use within the confines of a neurosurgical theater environment, having a slow image acquisition time, or by compromising spatial/spectral resolution in favor of improvements to the surgical workflow. Lightfield hyperspectral imaging is a novel technique that has the potential to facilitate video rate image acquisition whilst maintaining a high spectral resolution. Our pre-clinical and first-in-human studies (IDEAL 0 and 1, respectively) demonstrate the necessary steps leading to the first in-vivo use of a real-time lightfield hyperspectral system in neuro-oncology surgery.

Methods

A lightfield hyperspectral camera (Cubert Ultris ×50) was integrated in a bespoke imaging system setup so that it could be safely adopted into the open neurosurgical workflow whilst maintaining sterility. Our system allowed the surgeon to capture in-vivo hyperspectral data (155 bands, 350-1,000 nm) at 1.5 Hz. Following successful implementation in a pre-clinical setup (IDEAL 0), our system was evaluated during brain tumor surgery in a single patient to remove a posterior fossa meningioma (IDEAL 1). Feedback from the theater team was analyzed and incorporated in a follow-up design aimed at implementing an IDEAL 2a study.

Results

Focusing on our IDEAL 1 study results, hyperspectral information was acquired from the cerebellum and associated meningioma with minimal disruption to the neurosurgical workflow. To the best of our knowledge, this is the first demonstration of HSI acquisition with 100+ spectral bands at a frame rate over 1Hz in surgery.

Discussion

This work demonstrated that a lightfield hyperspectral imaging system not only meets the design criteria and specifications outlined in an IDEAL-0 (pre-clinical) study, but also that it can translate into clinical practice as illustrated by a successful first in human study (IDEAL 1). This opens doors for further development and optimisation, given the increasing evidence that hyperspectral imaging can provide live, wide-field, and label-free intra-operative imaging and tissue differentiation.

Toward Estimating MRI-Ultrasound Registration Error in Image-Guided Neurosurgery

Image-guided neurosurgery allows surgeons to view their tools in relation to preoperatively acquired patient images and models. To continue using neuronavigation systems throughout operations, image registration between preoperative images [typically magnetic resonance imaging (MRI)] and intraoperative images (e.g., ultrasound) is common to account for brain shift (deformations of the brain during surgery). We implemented a method to estimate MRI-ultrasound registration errors, with the goal of enabling surgeons to quantitatively assess the performance of linear or nonlinear registrations. To the best of our knowledge, this is the first dense error estimating algorithm applied to multimodal image registrations. The algorithm is based on a previously proposed sliding-window convolutional neural network that operates on a voxelwise basis. To create training data where the true registration error is known, simulated ultrasound images were created from preoperative MRI images and artificially deformed. The model was evaluated on artificially deformed simulated ultrasound data and real ultrasound data with manually annotated landmark points. The model achieved a mean absolute error (MAE) of 0.977 ± 0.988 mm and a correlation of 0.8 ± 0.062 on the simulated ultrasound data, and an MAE of 2.24 ± 1.89 mm and a correlation of 0.246 on the real ultrasound data. We discuss concrete areas to improve the results on real ultrasound data. Our progress lays the foundation for future developments and ultimately implementation of clinical neuronavigation systems.

Intra-operative applications of augmented reality in glioma surgery: a systematic review

Background

Augmented reality (AR) is increasingly being explored in neurosurgical practice. By visualizing patient-specific, three-dimensional (3D) models in real time, surgeons can improve their spatial understanding of complex anatomy and pathology, thereby optimizing intra-operative navigation, localization, and resection. Here, we aimed to capture applications of AR in glioma surgery, their current status and future potential.

Methods

A systematic review of the literature was conducted. This adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. PubMed, Embase, and Scopus electronic databases were queried from inception to October 10, 2022. Leveraging the Population, Intervention, Comparison, Outcomes, and Study design (PICOS) framework, study eligibility was evaluated in the qualitative synthesis. Data regarding AR workflow, surgical application, and associated outcomes were then extracted. The quality of evidence was additionally examined, using hierarchical classes of evidence in neurosurgery.

Results

The search returned 77 articles. Forty were subject to title and abstract screening, while 25 proceeded to full text screening. Of these, 22 articles met eligibility criteria and were included in the final review. During abstraction, studies were classified as "development" or "intervention" based on primary aims. Overall, AR was qualitatively advantageous, due to enhanced visualization of gliomas and critical structures, frequently aiding in maximal safe resection. Non-rigid applications were also useful in disclosing and compensating for intra-operative brain shift. Irrespective, there was high variance in registration methods and measurements, which considerably impacted projection accuracy. Most studies were of low-level evidence, yielding heterogeneous results.

Conclusions

AR has increasing potential for glioma surgery, with capacity to positively influence the onco-functional balance. However, technical and design limitations are readily apparent. The field must consider the importance of consistency and replicability, as well as the level of evidence, to effectively converge on standard approaches that maximize patient benefit.

Assessing informative tract segmentation and nTMS for pre-operative planning

BACKGROUND

Deep learning-based (DL) methods are the best-performing methods for white matter tract segmentation in anatomically healthy subjects. However, tract annotations are variable or absent in clinical data and manual annotations are especially difficult in patients with tumors where normal anatomy may be distorted. Direct cortical and subcortical stimulation is the gold standard ground truth to determine the cortical and sub-cortical lo- cation of motor-eloquent areas intra-operatively. Nonetheless, this technique is invasive, prolongs the surgical procedure, and may cause patient fatigue. Navigated Transcranial Magnetic Stimulation (nTMS) has a well-established correlation to direct cortical stimulation for motor mapping and the added advantage of being able to be acquired pre-operatively.

NEW METHOD

In this work, we evaluate the feasibility of using nTMS motor responses as a method to assess corticospinal tract (CST) binary masks and estimated uncertainty generated by a DL-based tract segmentation in patients with diffuse gliomas.

RESULTS

Our results show CST binary masks have a high overlap coefficient (OC) with nTMS response masks. A strong negative correlation is found between estimated uncertainty and nTMS response mask distance to the CST binary mask.

COMPARISON WITH EXISTING METHODS

We compare our approach (UncSeg) with the state-of-the-art TractSeg in terms of OC between the CST binary masks and nTMS response masks.

CONCLUSIONS

In this study, we demonstrate that estimated uncertainty from UncSeg is a good measure of the agreement between the CST binary masks and nTMS response masks distance to the CST binary mask boundary.

Automatic rigid image Fusion of preoperative MR and intraoperative US acquired after craniotomy

BACKGROUND

Neuronavigation of preoperative MRI is limited by several errors. Intraoperative ultrasound (iUS) with navigated probes that provide automatic superposition of pre-operative MRI and iUS and three-dimensional iUS reconstruction may overcome some of these limitations. Aim of the present study is to verify the accuracy of an automatic MRI - iUS fusion algorithm to improve MR-based neuronavigation accuracy.

METHODS

An algorithm using Linear Correlation of Linear Combination (LC2)-based similarity metric has been retrospectively evaluated for twelve datasets acquired in patients with brain tumor. A series of landmarks were defined both in MRI and iUS scans. The Target Registration Error (TRE) was determined for each pair of landmarks before and after the automatic Rigid Image Fusion (RIF). The algorithm has been tested on two conditions of the initial image alignment: registration-based fusion (RBF), as given by the navigated ultrasound probe, and different simulated course alignments during convergence test.

RESULTS

Except for one case RIF was successfully applied in all patients considering the RBF as initial alignment. Here, mean TRE after RBF was significantly reduced from 4.03 (± 1.40) mm to (2.08 ± 0.96 mm) (p = 0.002), after RIF. For convergence test, the mean TRE value after initial perturbations was 8.82 (± 0.23) mm which has been reduced to a mean TRE of 2.64 (± 1.20) mm after RIF (p < 0.001).

CONCLUSIONS

The integration of an automatic image fusion method for co-registration of pre-operative MRI and iUS data may improve the accuracy in MR-based neuronavigation.

Effects of formalin fixation on polarimetric properties of brain tissue: fresh or fixed?

Significance

Imaging Mueller polarimetry (IMP) appears as a promising technique for real-time delineation of healthy and neoplastic tissue during neurosurgery. The training of machine learning algorithms used for the image post-processing requires large data sets typically derived from the measurements of formalin-fixed brain sections. However, the success of the transfer of such algorithms from fixed to fresh brain tissue depends on the degree of alterations of polarimetric properties induced by formalin fixation (FF).

Aim

Comprehensive studies were performed on the FF induced changes in fresh pig brain tissue polarimetric properties.

Approach

Polarimetric properties of pig brain were assessed in 30 coronal thick sections before and after FF using a wide-field IMP system. The width of the uncertainty region between gray and white matter was also estimated.

Results

The depolarization increased by 5% in gray matter and remained constant in white matter following FF, whereas the linear retardance decreased by 27% in gray matter and by 28% in white matter after FF. The visual contrast between gray and white matter and fiber tracking remained preserved after FF. Tissue shrinkage induced by FF did not have a significant effect on the uncertainty region width.

Conclusions

Similar polarimetric properties were observed in both fresh and fixed brain tissues, indicating a high potential for transfer learning.

Themes in neuronavigation research: A machine learning topic analysis

Objective

To understand trends in neuronavigation we employed machine learning methods to perform a broad literature review which would be impractical by manual inspection.

Methods

PubMed was queried for articles with "Neuronavigation" in any field from inception-2020. Articles were designated neuronavigation-focused (NF) if "Neuronavigation" was a major MeSH. The latent dirichlet allocation topic modeling technique was used to identify themes of NF research.

Results

There were 3896 articles of which 1727 (44%) were designated as NF. Between 1999-2009 and 2010-2020, the number of NF publications experienced 80% growth. Between 2009-2014 and 2015-2020, there was a 0.3% decline. Eleven themes covered 1367 (86%) NF articles. "Resection of Eloquent Lesions" comprised the highest number of articles (243), followed by "Accuracy and Registration" (242), "Patient Outcomes" (156), "Stimulation and Mapping" (126), "Planning and Visualization" (123), "Intraoperative Tools" (104), "Placement of Ventricular Catheters" (86), "Spine Surgery" (85), "New Systems" (80), "Guided Biopsies" (61), and "Surgical Approach" (61). All topics except for "Planning and Visualization", "Intraoperative Tools", and "New Systems" exhibited a monotonic positive trend. When analyzing subcategories, there were a greater number of clinical assessments or usage of existing neuronavigation systems (77%) rather than modification or development of new apparatuses (18%).

Conclusion

NF research appears to focus on the clinical assessment of neuronavigation and to a lesser extent on the development of new systems. Although neuronavigation has made significant strides, NF research output appears to have plateaued in the last decade.

Perilesional resection technique of glioblastoma: intraoperative ultrasound and histological findings of the resection borders in a single center experience

INTRODUCTION

The surgical goal in glioblastoma treatment is the maximal safe resection of the tumor. Currently the lack of consensus on surgical technique opens different approaches. This study describes the "perilesional technique" and its outcomes in terms of the extent of resection, progression free survival and overall survival.

METHODS

Patients included (n = 40) received a diagnosis of glioblastoma and underwent surgery using the perilesional dissection technique at "San Gerardo Hospital"between 2018 and 2021. The tumor core was progressively isolated using a circumferential movement, healthy brain margins were protected with Cottonoid patties in a "shingles on the roof" fashion, then the tumorwas removed en bloc. Intraoperative ultrasound (iOUS) was used and at least 1 bioptic sample of "healthy" margin of the resection was collected and analyzed. The extent of resection was quantified. Extent of surgical resection (EOR) and progression free survival (PFS)were safety endpoints of the procedure.

RESULTS

Thirty-four patients (85%) received a gross total resection(GTR) while 3 (7.5%) patients received a sub-total resection (STR), and 3 (7.5%) a partial resection (PR). The mean post-operative residual volume was 1.44 cm³ (range 0-15.9 cm³).During surgery, a total of 76 margins were collected: 51 (67.1%) were tumor free, 25 (32.9%) were infiltrated. The median PFS was 13.4 months, 15.3 in the GTR group and 9.6 months in the STR-PR group.

CONCLUSIONS

Perilesional resection is an efficient technique which aims to bring the surgeon to a safe environment, carefully reaching the "healthy" brain before removing the tumoren bloc. This technique can achieve excellent tumor margins, extent of resection, and preservation of apatient's functions.

Ultrasound-Oriented Surgical Planning ("UOSP") for Intracranial Lesions: A Systematic Integration to the Standard Preoperative Planning

OBJECTIVE

Intraoperative ultrasound (iUS) is a well-established technique whose aim is to provide real-time visualization of deep lesions during brain surgery. The lack of definition of anatomic semeiotics and the unusual direction of the insonation plane make interpretation and orientation challenging for the surgeon who newly approaches to such a tool. We propose a novel protocol to be applied during the surgical planning for intracranial lesions surgery, a so-called ultrasound-oriented surgical planning ("UOSP") protocol, and we provide a retrospective analysis of 21 patients who underwent surgery for an intracranial lesion in which UOSP was applied. To further enlighten different surgical orientation strategies and possible limitations given by the technique, we discuss 3 illustrative cases assigned to 3 categories ("basic," "intermediate," and "challenging" lesions) with progressively growing difficulty in anatomic orientation during a surgical procedure.

METHODS

A total of 21 patients operated between March 2021 and July 2021 and where the UOSP protocol was applied during surgical planning were evaluated retrospectively. The UOSP protocol was performed the days before the surgical intervention by the same surgical team.

RESULTS

The UOSP protocol was successfully applied in all 21 patients. In all cases, the preoperative imaging obtained during surgical planning corresponded to the images observed during the application of iUS.

CONCLUSIONS

The introduction of the UOSP protocol during the planification of the surgical intervention for an intracerebral lesion may serve as a key factor to overcome the actual limitations inherent to the iUS technique. Utilization of this protocol may facilitate wider use of iUS in neurosurgery.

Association between features of intraoperative ultrasound and magnetic resonance imaging in the diagnosis of dysembryoplastic neuroepithelial tumor

Background

To analyze the characteristics of images from intraoperative ultrasound (IoUS) and preoperative magnetic resonance imaging (MRI) and their relationship with pathological components of dysembryoplastic neuroepithelial tumor (DNT) and to discuss the role of IoUS in detecting tumor residues.

Methods

The clinical and image data of 24 patients with postoperative pathology-confirmed DNT were analyzed retrospectively. Baseline characteristics, imaging features, and intraoperative residues were recorded for further analysis. Cohen's kappa consistency evaluation was performed on the echo and signal characteristics of the lesions.

Results

Cohen's kappa coefficient between the echo and signal of the lesion was 0.832. The characteristics of IoUS were gyrus or mass hyperechoic solid nodules located under the cortex, insufficient blood flow signals, and clear boundaries, in addition to mixed cystic and solid echo nodules. The solid part of the lesion consisted of pathologically nodular specific glioneuronal element (SGE) or was combined with glial nodules and focal cortical dysplasia (FCD), which was characterized by a high echo or long T1 long T2 signal and uniform or uneven distribution. The cystic part consisted of a mucinous matrix, showing echoless or long T1 long T2 on fluid attenuated inversion recovery (FLAIR), which was higher than that in cerebrospinal fluid but lower than that in the cerebral cortex. The residual lesion discovered using IoUS was confirmed with postoperative MRI.

Conclusions

The IoUS characteristics of DNT are strongly consistent with MRI, and its imaging features are related to pathological components. IoUS can assist the operator to judge the mode and scope of tumor resection, detect residual tumor, and improve the rate of total tumor resection.

Incorporation of a Disposable ESI Emitter into Inline Cartridge Extraction Mass Spectrometry Improves Throughput and Spectra Stability

Rapid and reliable methods for detecting tumor margins are crucial for neuro-oncology. Several mass spectrometry-based methods have been recently proposed to address this problem. Inline Cartridge Extraction (ICE) demonstrates the potential for clinical application, based on ex-vivo analysis of dissected tissues, but requires time-consuming steps to avoid cross-contamination. In this work, a method of incorporating a disposable electrospray emitter into the ICE cartridge by PEEK sleeves melting is developed. It reduces total analysis time and improves throughput. The proposed setup also improves the robustness of the ICE molecular profiling as demonstrated with human glial tumor samples in that stability and reproducibility of the spectra were increased.

Intraoperative ultrasound in recurrent gliomas surgery: Impact on residual tumor volume and patient outcomes

Background

Reoperation may be beneficial for patients with recurrent gliomas. Minimizing the residual tumor volume (RTV) while ensuring the functionality of relevant structures is the goal of the reoperation of recurrent gliomas. Intraoperative ultrasound (IoUS) may be helpful for intraoperative tumor localization, intraoperative real-time imaging to guide surgical resection, and postoperative evaluation of the RTV in the reoperation for recurrent gliomas.

Objective

To assess the effect of real-time ioUS on minimizing RTV in recurrent glioma surgery compared to Non-ioUS.

Methods

We retrospectively analyzed the data from 92 patients who had recurrent glioma surgical resection: 45 were resected with ioUS guidance and 47 were resected without ioUS guidance. RTV, Karnofsky Performance Status (KPS) at 6 months after the operation, the number of recurrent patients, and the time to recurrence were evaluated.

Results

The average RTV in the ioUS group was significantly less than the Non-ioUS group (0.27 cm³ vs. 1.33 cm³, p = 0.0004). Patients in the ioUS group tended to have higher KPS scores at 6 months of follow-up after the operation than those in the Non-ioUS group (70.00 vs. 60.00, p = 0.0185). More patients in the Non-ioUS group experienced a recurrence than in the ioUS group (43 (91.49%) vs. 32 (71.11%), p = 0.0118). The ioUS group had a longer mean time to recurrence than the Non-ioUS group (7.9 vs. 6.3 months, p = 0.0013).

Conclusion

The use of ioUS-based real-time for resection of recurrent gliomas has been beneficial in terms of both RTV and postoperative outcomes, compared to the Non-ioUS group.

Nondestructive label-free detection of peritumoral white matter damage using cross-polarization optical coherence tomography

Introduction

To improve the quality of brain tumor resections, it is important to differentiate zones with myelinated fibers destruction from tumor tissue and normal white matter. Optical coherence tomography (OCT) is a promising tool for brain tissue visualization and in the present study, we demonstrate the ability of cross-polarization (CP) OCT to detect damaged white matter and differentiate it from normal and tumor tissues.

Materials and methods

The study was performed on 215 samples of brain tissue obtained from 57 patients with brain tumors. The analysis of the obtained OCT data included three stages: 1) visual analysis of structural OCT images; 2) quantitative assessment based on attenuation coefficients estimation in co- and cross-polarizations; 3) building of color-coded maps with subsequent visual analysis. The defining characteristics of structural CP OCT images and color-coded maps were determined for each studied tissue type, and then two classification tests were passed by 8 blinded respondents after a training.

Results

Visual assessment of structural CP OCT images allows detecting white matter areas with damaged myelinated fibers and differentiate them from normal white matter and tumor tissue. Attenuation coefficients also allow distinguishing all studied brain tissue types, while it was found that damage to myelinated fibers leads to a statistically significant decrease in the values of attenuation coefficients compared to normal white matter. Nevertheless, the use of color-coded optical maps looks more promising as it combines the objectivity of optical coefficient and clarity of the visual assessment, which leads to the increase of the diagnostic accuracy of the method compared to visual analysis of structural OCT images.

Conclusions

Alteration of myelinated fibers causes changes in the scattering properties of the white matter, which gets reflected in the nature of the received CP OCT signal. Visual assessment of structural CP OCT images and color-coded maps allows differentiating studied tissue types from each other, while usage of color-coded maps demonstrates higher diagnostic accuracy values in comparison with structural images (F-score = 0.85-0.86 and 0.81, respectively). Thus, the results of the study confirm the potential of using OCT as a neuronavigation tool during resections of brain tumors.

Augmented and virtual reality usage in awake craniotomy: a systematic review

Augmented and virtual reality (AR, VR) are becoming promising tools in neurosurgery. AR and VR can reduce challenges associated with conventional approaches via the simulation and mimicry of specific environments of choice for surgeons. Awake craniotomy (AC) enables the resection of lesions from eloquent brain areas while monitoring higher cortical and subcortical functions. Evidence suggests that both surgeons and patients benefit from the various applications of AR and VR in AC. This paper investigates the application of AR and VR in AC and assesses its prospective utility in neurosurgery. A systematic review of the literature was performed using PubMed, Scopus, and Web of Science databases in accordance with the PRISMA guidelines. Our search results yielded 220 articles. A total of six articles consisting of 118 patients have been included in this review. VR was used in four papers, and the other two used AR. Tumour was the most common pathology in 108 patients, followed by vascular lesions in eight patients. VR was used for intraoperative mapping of language, vision, and social cognition, while AR was incorporated in preoperative training of white matter dissection and intraoperative visualisation and navigation. Overall, patients and surgeons were satisfied with the applications of AR and VR in their cases. AR and VR can be safely incorporated during AC to supplement, augment, or even replace conventional approaches in neurosurgery. Future investigations are required to assess the feasibility of AR and VR in various phases of AC.

Intraoperative Evaluation of Brain-Tumor Microvascularization through MicroV IOUS: A Protocol for Image Acquisition and Analysis of Radiomic Features

Microvascular Doppler (MicroV) is a new-generation Doppler technique developed by Esaote (Esaote s.p.a., Genova, Italy), which is able to visualize small and low-flow vessels through a suppression of interfering signals. MicroV uses advanced filters that are able to differentiate tissue artifacts from low-speed blood flows; by exploiting the space-time coherence information, these filters can selectively suppress tissue components, preserving the signal coming from the microvascular flow. This technique is clinically applied to the study of the vascularization of parenchymatous lesions, often with better diagnostic accuracy than color/power Doppler techniques. The aim of this paper is to develop a reproducible protocol for the recording and collection of MicroV intraoperative ultrasound images by the use of a capable intraoperative ultrasound machine and post-processing aimed at evaluation of brain-tumor microvascularization through the analysis of radiomic features. The proposed protocol has been internally validated on eight patients and will be firstly applied to patients affected by WHO grade IV astrocytoma (glioblastoma-GBM) candidates for craniotomy and lesion removal. In a further stage, it will be generally applied to patients with primary or metastatic brain tumors. IOUS is performed before durotomy. Tumor microvascularization is evaluated using the MicroV Doppler technique and IOUS images are recorded, stored, and post-processed. IOUS images are remotely stored on the BraTIoUS database, which will promote international cooperation and multicentric analysis. Processed images and texture radiomic features are analyzed post-operatively using ImageJ, a free scientific image-analysis software based on the Sun-Java platform. Post-processing protocol is further described in-depth. The study of tumor microvascularization through advanced IOUS techniques such as MicroV could represent, in the future, a non-invasive and real-time method for intraoperative predictive evaluation of the tumor features. This evaluation could finally result in a deeper knowledge of brain-tumor behavior and in the on-going adaptation of the surgery with the improvement of surgical outcomes.

Full-course resection control strategy in glioma surgery using both intraoperative ultrasound and intraoperative MRI

Background

Intraoperative ultrasound(iUS) and intraoperative MRI (iMRI) are effective ways to perform resection control during glioma surgery. However, most published studies employed only one modality. Few studies have used both during surgery. How to combine these two techniques reasonably, and what advantages they could have for glioma surgery are still open questions.

Methods

We retrospectively reviewed a series of consecutive patients who underwent initial surgical treatment of supratentorial gliomas in our center. We utilized a full-course resection control strategy to combine iUS and iMRI: IUS for pre-resection assessment and intermediate resection control; iMRI for final resection control. The basic patient characteristics, surgical results, iMRI/iUS findings, and their impacts on surgical procedures were evaluated and reported.

Results

A total of 40 patients were included. The extent of resection was 95.43 ± 10.37%, and the gross total resection rate was 72.5%. The median residual tumor size was 6.39 cm3 (range 1.06–16.23 cm3). 5% (2/40) of patients had permanent neurological deficits after surgery. 17.5% (7/40) of patients received further resection after the first iMRI scan, resulting in four (10%) more patients achieving gross total resection. The number of iMRI scans per patient was 1.18 ± 0.38. The surgical time was 4.5 ± 3.6 hours. The pre-resection iUS scan revealed that an average of 3.8 borders of the tumor were beside sulci in 75% (30/40) patients. Intermediate resection control was utilized in 67.5% (27/40) of patients. In 37.5% (15/40) of patients, the surgical procedures were changed intraoperatively based on the iUS findings. Compared with iMRI, the sensitivity and specificity of iUS for residual tumors were 46% and 96%, respectively.

Conclusion

The full-course resection control strategy by combining iUS and iMRI could be successfully implemented with good surgical results in initial glioma surgeries. This strategy might stabilize resection control quality and provide the surgeon with more intraoperative information to tailor the surgical strategy. Compared with iMRI-assisted glioma surgery, this strategy might improve efficiency by reducing the number of iMRI scans and shortening surgery time.

Visualization, navigation, augmentation. The ever-changing perspective of the neurosurgeon

Introduction

The evolution of neurosurgery coincides with the evolution of visualization and navigation. Augmented reality technologies, with their ability to bring digital information into the real environment, have the potential to provide a new, revolutionary perspective to the neurosurgeon.

Research question

To provide an overview on the historical and technical aspects of visualization and navigation in neurosurgery, and to provide a systematic review on augmented reality (AR) applications in neurosurgery.

Material and methods

We provided an overview on the main historical milestones and technical features of visualization and navigation tools in neurosurgery. We systematically searched PubMed and Scopus databases for AR applications in neurosurgery and specifically discussed their relationship with current visualization and navigation systems, as well as main limitations.

Results

The evolution of visualization in neurosurgery is embodied by four magnification systems: surgical loupes, endoscope, surgical microscope and more recently the exoscope, each presenting independent features in terms of magnification capabilities, eye-hand coordination and the possibility to implement additional functions. In regard to navigation, two independent systems have been developed: the frame-based and the frame-less systems. The most frequent application setting for AR is brain surgery (71.6%), specifically neuro-oncology (36.2%) and microscope-based (29.2%), even though in the majority of cases AR applications presented their own visualization supports (66%).

Discussion and conclusions

The evolution of visualization and navigation in neurosurgery allowed for the development of more precise instruments; the development and clinical validation of AR applications, have the potential to be the next breakthrough, making surgeries safer, as well as improving surgical experience and reducing costs.

Novel rapid intraoperative qualitative tumor detection by a residual convolutional neural network using label-free stimulated Raman scattering microscopy

Determining the presence of tumor in biopsies and the decision-making during resections is often dependent on intraoperative rapid frozen-section histopathology. Recently, stimulated Raman scattering microscopy has been introduced to rapidly generate digital hematoxylin-and-eosin-stained-like images (stimulated Raman histology) for intraoperative analysis. To enable intraoperative prediction of tumor presence, we aimed to develop a new deep residual convolutional neural network in an automated pipeline and tested its validity. In a monocentric prospective clinical study with 94 patients undergoing biopsy, brain or spinal tumor resection, Stimulated Raman histology images of intraoperative tissue samples were obtained using a fiber-laser-based stimulated Raman scattering microscope. A residual network was established and trained in ResNetV50 to predict three classes for each image: (1) tumor, (2) non-tumor, and (3) low-quality. The residual network was validated on images obtained in three small random areas within the tissue samples and were blindly independently reviewed by a neuropathologist as ground truth. 402 images derived from 132 tissue samples were analyzed representing the entire spectrum of neurooncological surgery. The automated workflow took in a mean of 240 s per case, and the residual network correctly classified tumor (305/326), non-tumorous tissue (49/67), and low-quality (6/9) images with an inter-rater agreement of 89.6% (κ = 0.671). An excellent internal consistency was found among the random areas with 90.2% (Cα = 0.942) accuracy. In conclusion, the novel stimulated Raman histology-based residual network can reliably detect the microscopic presence of tumor and differentiate from non-tumorous brain tissue in resection and biopsy samples within 4 min and may pave a promising way for an alternative rapid intraoperative histopathological decision-making tool.

MRI-Based Risk Assessment for Incomplete Resection of Brain Metastases

Object

Recent studies demonstrated that gross total resection of brain metastases cannot always be achieved. Subtotal resection (STR) can result in an early recurrence and might affect patient survival. We initiated a prospective observational study to establish a MRI-based risk assessment for incomplete resection of brain metastases.

Methods

All patients in whom ≥1 brain metastasis was resected were prospectively included in this study (DRKS ID: DRKS00021224; Nov 2020 - Nov 2021). An interdisciplinary board of neurosurgeons and neuroradiologists evaluated the pre- and postoperative MRI (≤48h after surgery) for residual tumor. Extensive neuroradiological analyses were performed to identify risk factors for an unintended STR which were integrated into a regression tree analysis to determine the patients' individual risk for a STR.

Results

We included 150 patients (74 female; mean age: 61 years), in whom 165 brain metastases were resected. A STR was detected in 32 cases (19.4%) (median residual tumor volume: 1.36ml, median EOR_rel: 93.6%), of which 6 (3.6%) were intended STR (median residual tumor volume: 3.27ml, median EOR_rel: 67.3%) - mainly due to motor-eloquent location - and 26 (15.8%) were unintended STR (uSTR) (median residual tumor volume: 0.64ml, median EOR_rel: 94.7%). The following risk factors for an uSTR could be identified: subcortical metastasis ≥5mm distant from cortex, diffuse contrast agent enhancement, proximity to the ventricles, contact to falx/tentorium and non-transcortical approaches. Regression tree analysis revealed that the individual risk for an uSTR was mainly associated to the distance from the cortex (distance ≥5mm vs. <5mm: OR 8.0; 95%CI: 2.7 - 24.4) and the contrast agent patterns (diffuse vs. non-diffuse in those with distance ≥5mm: OR: 4.2; 95%CI: 1.3 - 13.7). The preoperative tumor volume was not substantially associated with the extent of resection.

Conclusions

Subcortical metastases ≥5mm distant from cortex with diffuse contrast agent enhancement showed the highest incidence of uSTR. The proposed MRI-based assessment allows estimation of the individual risk for uSTR and can help indicating intraoperative imaging.

A Dedicated Tool for Presurgical Mapping of Brain Tumors and Mixed-Reality Navigation During Neurosurgery

Brain tumor surgery requires a delicate tradeoff between complete removal of neoplastic tissue while minimizing loss of brain function. Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) have emerged as valuable tools for non-invasive assessment of human brain function and are now used to determine brain regions that should be spared to prevent functional impairment after surgery. However, image analysis requires different software packages, mainly developed for research purposes and often difficult to use in a clinical setting, preventing large-scale diffusion of presurgical mapping. We developed a specialized software able to implement an automatic analysis of multimodal MRI presurgical mapping in a single application and to transfer the results to the neuronavigator. Moreover, the imaging results are integrated in a commercially available wearable device using an optimized mixed-reality approach, automatically anchoring 3-dimensional holograms obtained from MRI with the physical head of the patient. This will allow the surgeon to virtually explore deeper tissue layers highlighting critical brain structures that need to be preserved, while retaining the natural oculo-manual coordination. The enhanced ergonomics of this procedure will significantly improve accuracy and safety of the surgery, with large expected benefits for health care systems and related industrial investors.

Photoacoustic-MR Image Registration Based on a Co-Sparse Analysis Model to Compensate for Brain Shift

Brain shift is an important obstacle to the application of image guidance during neurosurgical interventions. There has been a growing interest in intra-operative imaging to update the image-guided surgery systems. However, due to the innate limitations of the current imaging modalities, accurate brain shift compensation continues to be a challenging task. In this study, the application of intra-operative photoacoustic imaging and registration of the intra-operative photoacoustic with pre-operative MR images are proposed to compensate for brain deformation. Finding a satisfactory registration method is challenging due to the unpredictable nature of brain deformation. In this study, the co-sparse analysis model is proposed for photoacoustic-MR image registration, which can capture the interdependency of the two modalities. The proposed algorithm works based on the minimization of mapping transform via a pair of analysis operators that are learned by the alternating direction method of multipliers. The method was evaluated using an experimental phantom and ex vivo data obtained from a mouse brain. The results of the phantom data show about 63% improvement in target registration error in comparison with the commonly used normalized mutual information method. The results proved that intra-operative photoacoustic images could become a promising tool when the brain shift invalidates pre-operative MRI.

Intraoperative MR Imaging during Glioma Resection

One of the major issues in the surgical treatment of gliomas is the concern about maximizing the extent of resection while minimizing neurological impairment. Thus, surgical planning by carefully observing the relationship between the glioma infiltration area and eloquent area of the connecting fibers is crucial. Neurosurgeons usually detect an eloquent area by functional MRI and identify a connecting fiber by diffusion tensor imaging. However, during surgery, the accuracy of neuronavigation can be decreased due to brain shift, but the positional information may be updated by intraoperative MRI and the next steps can be planned accordingly. In addition, various intraoperative modalities may be used to guide surgery, including neurophysiological monitoring that provides real-time information (e.g., awake surgery, motor-evoked potentials, and sensory evoked potential); photodynamic diagnosis, which can identify high-grade glioma cells; and other imaging techniques that provide anatomical information during the surgery. In this review, we present the historical and current context of the intraoperative MRI and some related approaches for an audience active in the technical, clinical, and research areas of radiology, as well as mention important aspects regarding safety and types of devices.

Surgical advances in the management of brain metastases

As the epidemiological and clinical burden of brain metastases continues to grow, advances in neurosurgical care are imperative. From standard magnetic resonance imaging (MRI) sequences to functional neuroimaging, preoperative workups for metastatic disease allow high-resolution detection of lesions and at-risk structures, facilitating safe and effective surgical planning. Minimally invasive neurosurgical approaches, including keyhole craniotomies and tubular retractors, optimize the preservation of normal parenchyma without compromising extent of resection. Supramarginal surgery has pushed the boundaries of achieving complete removal of metastases without recurrence, especially in eloquent regions when paired with intraoperative neuromonitoring. Brachytherapy has highlighted the potential of locally delivering therapeutic agents to the resection cavity with high rates of local control. Neuronavigation has become a cornerstone of operative workflow, while intraoperative ultrasound (iUS) and intraoperative brain mapping generate real-time renderings of the brain unaffected by brain shift. Endoscopes, exoscopes, and fluorescent-guided surgery enable increasingly high-definition visualizations of metastatic lesions that were previously difficult to achieve. Pushed forward by these multidisciplinary innovations, neurosurgery has never been a safer, more effective treatment for patients with brain metastases.