Applications of Ultrasound in the Resection of Brain Tumors

Efficacy of various extent of resection on survival rates of patients with pilocytic astrocytoma: based on a large population

Pilocytic astrocytoma (PA) is classified as a Grade I benign neuroglial tumor. The extent of surgical resection is a critical factor influencing the prognosis for patients with PA. In prior researches of PA, the extent of surgical resection is generally categorized into GTR, STR and biopsy. In some researches on brain tumor surgeries, the extent of resection also includes GTL. There is no existing research specifically comparing the efficacy of GTR versus GTL in PA treatment. In this study, the data we used are from the SEER database. We categorized the extent of resection into GTL, GTR, STL, STR, biopsy, and no surgery based on SEER classification of surgical procedures, to investigate the impact of extent of resection on PA patient survival. A multivariate logistic regression model was utilized to acquire odds ratios (OR) for different extent of resection. Survival outcomes across different extent of resection (GTL, GTR, STL, STR, biopsy, no surgery) were assessed using Kaplan-Meier survival curve analysis, with curve comparisons conducted via log-rank tests. The impact of various risk factors on survival was assessed using the Cox proportional hazards model. The hazard ratio (HR) was employed to quantify the influence of one or more factors on overall survival throughout the follow-up period. Multivariate Cox analysis revealed that age, tumor location, extent of resection, as well as the application of radiotherapy and chemotherapy, all significantly impacted prognosis. Compared to GTL, GTR did not significantly increase the risk of mortality (HR 1.17; 95% CI 0.73-1.86, p = 0.5). Furthermore, there was no statistically significant difference between the Kaplan-Meier survival curves of the two groups (p = 0.18). We employed propensity score matching (PSM) to balance the differences in baseline characteristics of patients receiving chemotherapy or radiotherapy. A total of 4429 patients were included in this study. Age, diagnosis period, race, tumor size, and tumor location as influential on the extent of resection. Age, tumor location, extent of resection, and application of radiotherapy and chemotherapy influenced the survival of PA patients. The Kaplan-Meier survival curves revealed that the long-term survival rate for GTR is slightly higher than that for GTL. The PSM analysis revealed that the application of radiotherapy and chemotherapy was associated with the reduction of overall survival in PA patients. In conclusion, there was no significant difference in survival between GTR and GTL, so GTR with less damage was preferred. The application of radiotherapy and chemotherapy can reduce overall survival of patients with PA.

Intraoperative visualization of cerebral aneurysms using navigated 3D-ultrasound power-Doppler angiography

BACKGROUND

The questions of whether the spatial resolution of navigated 3D-ultrasound (3D-US) power-Doppler angiography imaging rendered by existing 3D-US systems is sufficient for the intraoperative visualization of cerebral aneurysms, and in what percentage of cases, are largely unanswered. A study on this topic is lacking in the literature.

METHODS

From 2015 to 2022, we performed 86 surgeries on 83 aneurysm patients. Navigated 3D-US was used at the discretion of the operating neurosurgeons when available (i.e., not being used during parallel tumor surgeries). Twenty-five aneurysms (15 ruptured) were operated on using 3D-US; 22 aneurysms were located at the middle cerebral artery (MCA). Patient 3D-US power-Doppler angiography images and surgical reports were retrospectively reviewed to assess the intraoperative ultrasound visibility of aneurysms.

RESULTS

In 20 patients (80%) the aneurysms were successfully visualized. In five patients (20%), the aneurysms visualization was insufficient or absent. Nineteen of 22 aneurysms (86.4%) were visualized in the MCA aneurysm subgroup. We observed no association between aneurysm visibility and aneurysm size or the presence of subarachnoid hemorrhage. In the subgroup of MCA aneurysms, no association between aneurysm visibility and the presence of subarachnoid hemorrhage was found; a trend toward poor sonographic visibility of smaller aneurysms was observed (p = 0.09).

CONCLUSIONS

Our initial data show that intraoperative 3D-US power-Doppler angiography, rendered by current navigated 3D-US systems, clearly depicts the majority of aneurysms in the MCA aneurysm subgroup. However, future prospective studies performed on a higher number of aneurysms localized at various anatomic sites are needed to confirm our initial findings and determine their potential clinical relevance.

Neuronavigation Combined With Intraoperative Ultrasound and Intraoperative Magnetic Resonance Imaging Versus Neuronavigation Alone in Diffuse Glioma Surgery

OBJECTIVE

This study aimed to integrate intraoperative ultrasound and magnetic resonance imaging (IMRI) with neuronavigation (NN) to create a multimodal surgical protocol for diffuse gliomas. Clinical outcomes were compared to the standard NN-guided protocol.

METHODS

Adult patients with diffuse gliomas scheduled for gross total resection (GTR) were consecutively enrolled to undergo either NN-guided surgery (80 patients, July 2019-January 2022) or multimodal-integrated surgery (80 patients, February 2022-August 2023). The primary outcomes were the extent of resection (EOR) and GTR. Additional outcomes included operative time, blood loss, length of hospital stay, and patient survival.

RESULTS

GTR was achieved in 69% of patients who underwent multimodal-integrated surgery, compared to 43% of those who received NN-guided surgery (P = 0.002). Residual tumor was detected by IMRI in 53 patients (66%), and further GTR was achieved in 28 of these cases. The median EOR was 100% for the multimodal group and 95% for the NN-guided group (P = 0.001), while the median operative time was 8 hours versus 5 hours (P < 0.001). Neurological deficits, blood loss, and hospital stay durations were comparable between 2 groups. Multimodal-integrated surgery resulted in greater EOR and higher GTR rates in contrast-enhancing gliomas, gliomas in eloquent regions, and large gliomas (≥50 mm). GTR in glioblastomas and other contrast-enhancing gliomas contributed to improved overall survival.

CONCLUSIONS

Compared to standard NN-guided surgery, multimodal-integrated surgery using NN, IMRI, and intraoperative ultrasound significantly increased the EOR and GTR rates for diffuse gliomas.

Microscope integrated MHz optical coherence tomography system for neurosurgery: development and clinical in-vivo imaging

Neurosurgical interventions on the brain are impeded by the requirement to keep damages to healthy tissue at a minimum. A new contrast channel enhancing the visual separation of malign tissue should be created. A commercially available surgical microscope was modified with adaptation optics adapting the MHz speed optical coherence tomography (OCT) imaging system developed in our group. This required the design of a scanner optics and beam delivery system overcoming constraints posed by the mechanical and optical parameters of the microscope. High quality volumetric OCT C-scans with dense sample spacing can be acquired in-vivo as part of surgical procedures within seconds and are immediately available for post-processing.

Spectral analysis comparison of pushbroom and snapshot hyperspectral cameras for in vivo brain tissues and chromophore identification

Significance

Hyperspectral imaging sensors have rapidly advanced, aiding in tumor diagnostics for in vivo brain tumors. Linescan cameras effectively distinguish between pathological and healthy tissue, whereas snapshot cameras offer a potential alternative to reduce acquisition time.

Aim

Our research compares linescan and snapshot hyperspectral cameras for in vivo brain tissues and chromophore identification.

Approach

We compared a linescan pushbroom camera and a snapshot camera using images from 10 patients with various pathologies. Objective comparisons were made using unnormalized and normalized data for healthy and pathological tissues. We utilized the interquartile range (IQR) for the spectral angle mapping (SAM), the goodness-of-fit coefficient (GFC), and the root mean square error (RMSE) within the 659.95 to 951.42 nm range. In addition, we assessed the ability of both cameras to capture tissue chromophores by analyzing absorbance from reflectance information.

Results

The SAM metric indicates reduced dispersion and high similarity between cameras for pathological samples, with a 9.68% IQR for normalized data compared with 2.38% for unnormalized data. This pattern is consistent across GFC and RMSE metrics, regardless of tissue type. Moreover, both cameras could identify absorption peaks of certain chromophores. For instance, using the absorbance measurements of the linescan camera, we obtained SAM values below 0.235 for four peaks, regardless of the tissue and type of data under inspection. These peaks are one for cytochrome b in its oxidized form at λ = 422    nm , two forHbO 2 at λ = 542    nm and λ = 576    nm , and one for water at λ = 976    nm .

Conclusion

The spectral signatures of the cameras show more similarity with unnormalized data, likely due to snapshot sensor noise, resulting in noisier signatures post-normalization. Comparisons in this study suggest that snapshot cameras might be viable alternatives to linescan cameras for real-time brain tissue identification.

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.

Intraoperative ultrasound and magnetic resonance comparative analysis in brain tumor surgery: a valuable tool to flatten ultrasound's learning curve

BACKGROUND

Intraoperative ultrasound (IOUS) is a profitable tool for neurosurgical procedures' assistance, especially in neuro-oncology. It is a rapid, ergonomic and reproducible technique. However, its known handicap is a steep learning curve for neurosurgeons. Here, we describe an interesting postoperative analysis that provides extra feedback after surgery, accelerating the learning process.

METHOD

We conducted a descriptive retrospective unicenter study including patients operated from intra-axial brain tumors using neuronavigation (Curve, Brainlab) and IOUS (BK-5000, BK medical) guidance. All patients had preoperative Magnetic Resonance Imaging (MRI) prior to tumor resection. During surgery, 3D neuronavigated IOUS studies (n3DUS) were obtained through craniotomy N13C5 transducer's integration to the neuronavigation system. At least two n3DUS studies were obtained: prior to tumor resection and at the resection conclusion. A postoperative MRI was performed within 48 h. MRI and n3DUS studies were posteriorly fused and analyzed with Elements (Brainlab) planning software, permitting two comparative analyses: preoperative MRI compared to pre-resection n3DUS and postoperative MRI to post-resection n3DUS. Cases with incomplete MRI or n3DUS studies were withdrawn from the study.

RESULTS

From April 2022 to March 2024, 73 patients were operated assisted by IOUS. From them, 39 were included in the study. Analyses comparing preoperative MRI and pre-resection n3DUS showed great concordance of tumor volume (p < 0,001) between both modalities. Analysis comparing postoperative MRI and post-resection n3DUS also showed good concordance in residual tumor volume (RTV) in cases where gross total resection (GTR) was not achieved (p < 0,001). In two cases, RTV detected on MRI that was not detected intra-operatively with IOUS could be reviewed in detail to recheck its appearance.

CONCLUSIONS

Post-operative comparative analyses between IOUS and MRI is a valuable tool for novel ultrasound users, as it enhances the amount of feedback provided by cases and could accelerate the learning process, flattening this technique's learning curve.

Portable ultrasound-guided keyhole evacuation of intracerebral hemorrhage: a detailed case report highlighting technical nuances

Intracerebral hemorrhage (ICH) is a common neurosurgical emergency that is associated with high morbidity and mortality. Minimally invasive or endoscopic hematoma evacuation has emerged in recent years as a viable alternative to conventional large craniotomies. However, accurate trajectory planning and placement of the tubular retractor remains a challenge. We describe a novel technique for handheld portable ultrasound-guided minimally invasive endoscopic evacuation of supratentorial hematomas. A 64-year-old male diagnosed right hematoma (48.5 mL) at the basal ganglia was treated with emergent ultrasound-guided endoscopic transtubular evacuation through a small craniotomy. Ultrasound-guidance facilitated optimal placement of the tubular retractor into the long axis of the hematoma, and allowed for near-total evacuation, reducing iatrogenic tissue damage by mitigating the need for wanding or repositioning of the retractor. The emergence of a new generation of small portable phased array ultrasound probes with improved resolution and clarity has broadened ultrasound's clinical applications.

Navigated Intraoperative Ultrasound Offers Effective and Efficient Real-Time Analysis of Intracranial Tumor Resection and Brain Shift

BACKGROUND AND OBJECTIVES

Neuronavigation is a fundamental tool in the resection of intracranial tumors. However, it is limited by its calibration to preoperative neuroimaging, which loses accuracy intraoperatively after brain shift. Therefore, surgeons rely on anatomic landmarks or tools like intraoperative MRI to assess the extent of tumor resection (EOR) and update neuronavigation. Recent studies demonstrate that intraoperative ultrasound (iUS) provides point-of-care imaging without the cost or resource utilization of an intraoperative MRI, and advances in neuronavigation-guided iUS provide an opportunity for real-time imaging overlaid with neuronavigation to account for brain shift. We assessed the feasibility, efficacy, and benefits of navigated iUS to assess the EOR and restore stereotactic accuracy in neuronavigation after brain shift.

METHODS

This prospective single-center study included patients presenting with intracranial tumors (gliomas, metastasis) to an academic medical center. Navigated iUS images were acquired preresection, midresection, and postresection. The EOR was determined by the surgeon intraoperatively and compared with the postoperative MRI report by an independent neuroradiologist. Outcome measures included time to perform the iUS sweep, time to process ultrasound images, and EOR predicted by the surgeon intraoperatively compared with the postoperative MRI.

RESULTS

This study included 40 patients consisting of gliomas (n = 18 high-grade gliomas, n = 4 low-grade gliomas, n = 4 recurrent) and metastasis (n = 18). Navigated ultrasound sweeps were performed in all patients (n = 83) with a median time to perform of 5.5 seconds and a median image processing time of 29.9 seconds. There was 95% concordance between the surgeon's and neuroradiologist's determination of EOR using navigated iUS and postoperative MRI, respectively. The sensitivity was 100%, and the specificity was 94%.

CONCLUSION

Navigated iUS was successfully used for EOR determination in glioma and metastasis resection. Incorporating navigated iUS into the surgical workflow is safe and efficient and provides a real-time assessment of EOR while accounting for brain shift in intracranial tumor surgeries.

Improved quantification of tumor adhesion in meningiomas using MR elastography-based slip interface imaging

Meningiomas, the most prevalent primary benign intracranial tumors, often exhibit complicated levels of adhesion to adjacent normal tissues, significantly influencing resection and causing postoperative complications. Surgery remains the primary therapeutic approach, and when combined with adjuvant radiotherapy, it effectively controls residual tumors and reduces tumor recurrence when complete removal may cause a neurologic deficit. Previous studies have indicated that slip interface imaging (SII) techniques based on MR elastography (MRE) have promise as a method for sensitively determining the presence of tumor-brain adhesion. In this study, we developed and tested an improved algorithm for assessing tumor-brain adhesion, based on recognition of patterns in MRE-derived normalized octahedral shear strain (NOSS) images. The primary goal was to quantify the tumor interfaces at higher risk for adhesion, offering a precise and objective method to assess meningioma adhesions in 52 meningioma patients. We also investigated the predictive value of MRE-assessed tumor adhesion in meningioma recurrence. Our findings highlight the effectiveness of the improved SII technique in distinguishing the adhesion degrees, particularly complete adhesion. Statistical analysis revealed significant differences in adhesion percentages between complete and partial adherent tumors (p = 0.005), and complete and non-adherent tumors (p<0.001). The improved technique demonstrated superior discriminatory ability in identifying tumor adhesion patterns compared to the previously described algorithm, with an AUC of 0.86 vs. 0.72 for distinguishing complete adhesion from others (p = 0.037), and an AUC of 0.72 vs. 0.67 for non-adherent and others. Aggressive tumors exhibiting atypical features showed significantly higher adhesion percentages in recurrence group compared to non-recurrence group (p = 0.042). This study validates the efficacy of the improved SII technique in quantifying meningioma adhesions and demonstrates its potential to affect clinical decision-making. The reliability of the technique, coupled with potential to help predict meningioma recurrence, particularly in aggressive tumor subsets, highlights its promise in guiding treatment strategies.

Intraoperative Ultrasound: An Old but Ever New Technology for a More Personalized Approach to Brain Tumor Surgery

BACKGROUND

Although the use of transcranial ultrasound dates to the mid-20th century, the main purpose of this research work is to standardize its use in the resection of brain tumors. This is due to its wide availability, low cost, lack of contraindications, and absence of harmful effects for the patient and medical staff, along with the possibility of real-time verification of the complete resection of tumor lesions and minimization of vascular injuries or damage to adjacent structures.

METHODS

A retrospective study was conducted from June to December 2022. The study included eight patients (three men and five women) aged between 32 and 76 years. Histological examination revealed two high-grade gliomas, one low-grade glioma, and five metastatic lesions.

RESULTS

The low-grade glioma appeared as a homogeneously echogenic structure and easily distinguishable from brain parenchyma, whereas metastases and high-grade gliomas showed higher echogenicity, being identified as malignant lesions due to areas of low echogenicity necrosis and peritumoral edema identified as a hyperechogenic structure.

CONCLUSIONS

The use of intraoperative transcranial ultrasound constitutes an important tool for neurosurgeons during tumor resection. Although it is easy to use, intraoperative ultrasound requires a relatively short learning curve and a good understanding of the fundamentals of ultrasound. Its main advantage over neuronavigation is that it is not affected by the "brain shift" phenomenon that commonly occurs during tumor resection, since the ultrasound images are updated during surgery.

Enabling Navigation and Augmented Reality in the Sitting Position in Posterior Fossa Surgery Using Intraoperative Ultrasound

Despite its broad use in cranial and spinal surgery, navigation support and microscope-based augmented reality (AR) have not yet found their way into posterior fossa surgery in the sitting position. While this position offers surgical benefits, navigation accuracy and thereof the use of navigation itself seems limited. Intraoperative ultrasound (iUS) can be applied at any time during surgery, delivering real-time images that can be used for accuracy verification and navigation updates. Within this study, its applicability in the sitting position was assessed. Data from 15 patients with lesions within the posterior fossa who underwent magnetic resonance imaging (MRI)-based navigation-supported surgery in the sitting position were retrospectively analyzed using the standard reference array and new rigid image-based MRI-iUS co-registration. The navigation accuracy was evaluated based on the spatial overlap of the outlined lesions and the distance between the corresponding landmarks in both data sets, respectively. Image-based co-registration significantly improved (p < 0.001) the spatial overlap of the outlined lesion (0.42 ± 0.30 vs. 0.65 ± 0.23) and significantly reduced (p < 0.001) the distance between the corresponding landmarks (8.69 ± 6.23 mm vs. 3.19 ± 2.73 mm), allowing for the sufficient use of navigation and AR support. Navigated iUS can therefore serve as an easy-to-use tool to enable navigation support for posterior fossa surgery in the sitting position.

Optical Methods for Brain Tumor Detection: A Systematic Review

Background: In brain tumor surgery, maximal tumor resection is typically desired. This is complicated by infiltrative tumor cells which cannot be visually distinguished from healthy brain tissue. Optical methods are an emerging field that can potentially revolutionize brain tumor surgery through intraoperative differentiation between healthy and tumor tissues. Methods: This study aimed to systematically explore and summarize the existing literature on the use of Raman Spectroscopy (RS), Hyperspectral Imaging (HSI), Optical Coherence Tomography (OCT), and Diffuse Reflectance Spectroscopy (DRS) for brain tumor detection. MEDLINE, Embase, and Web of Science were searched for studies evaluating the accuracy of these systems for brain tumor detection. Outcome measures included accuracy, sensitivity, and specificity. Results: In total, 44 studies were included, covering a range of tumor types and technologies. Accuracy metrics in the studies ranged between 54 and 100% for RS, 69 and 99% for HSI, 82 and 99% for OCT, and 42 and 100% for DRS. Conclusions: This review provides insightful evidence on the use of optical methods in distinguishing tumor from healthy brain tissue.

Non-navigated 2D intraoperative ultrasound: An unsophisticated surgical tool to achieve high standards of care in glioma surgery

PURPOSE

In an era characterized by rapid progression in neurosurgical technologies, traditional tools such as the non-navigated two-dimensional intraoperative ultrasound (nn-2D-IOUS) risk being overshadowed. Against this backdrop, this study endeavors to provide a comprehensive assessment of the clinical efficacy and surgical relevance of nn-2D-IOUS, specifically in the context of glioma resections.

METHODS

This retrospective study undertaken at a single center evaluated 99 consecutive, non-selected patients diagnosed with both high-grade and low-grade gliomas. The primary objective was to assess the proficiency of nn-2D-IOUS in generating satisfactory image quality, identifying residual tumor tissue, and its influence on the extent of resection. To validate these results, early postoperative MRI data served as the reference standard.

RESULTS

The nn-2D-IOUS exhibited a high level of effectiveness, successfully generating good quality images in 79% of the patients evaluated. With a sensitivity rate of 68% and a perfect specificity of 100%, nn-2D-IOUS unequivocally demonstrated its utility in intraoperative residual tumor detection. Notably, when total tumor removal was the surgical objective, a resection exceeding 95% of the initial tumor volume was achieved in 86% of patients. Additionally, patients in whom residual tumor was not detected by nn-2D-IOUS, the mean volume of undetected tumor tissue was remarkably minimal, averaging at 0.29 cm3.

CONCLUSION

Our study supports nn-2D-IOUS's invaluable role in glioma surgery. The results highlight the utility of traditional technologies for enhanced surgical outcomes, even when compared to advanced alternatives. This is particularly relevant for resource-constrained settings and emphasizes optimizing existing tools for efficient patient care. NCT05873946 - 24/05/2023 - Retrospectively registered.

Survival Analysis of Patients Undergoing Intraoperative Contrast-enhanced Ultrasound in the Surgical Treatment of Malignant Glioma

OBJECTIVE

Complete resection of malignant gliomas is often challenging. Our previous study indicated that intraoperative contrast-enhanced ultrasound (ICEUS) could aid in the detection of residual tumor remnants and the total removal of brain lesions. This study aimed to investigate the survival rates of patients undergoing resection with or without the use of ICEUS and to assess the impact of ICEUS on the prognosis of patients with malignant glioma.

METHODS

A total of 64 patients diagnosed with malignant glioma (WHO grade HI and IV) who underwent surgery between 2012 and 2018 were included. Among them, 29 patients received ICEUS. The effects of ICEUS on overall survival (OS) and progression-free survival (PFS) of patients were evaluated. A quantitative analysis was performed to compare ICEUS parameters between gliomas and the surrounding tissues.

RESULTS

The ICEUS group showed better survival rates both in OS and PFS than the control group. The univariate analysis revealed that age, pathology and ICEUS were significant prognostic factors for PFS, with only age being a significant prognostic factor for OS. In multivariate analysis, age and ICEUS were significant prognostic factors for both OS and PFS. The quantitative analysis showed that the intensity and transit time of microbubbles reaching the tumors were significantly different from those of microbubbles reaching the surrounding tissue.

CONCLUSION

ICEUS facilitates the identification of residual tumors. Age and ICEUS are prognostic factors for malignant glioma surgery, and use of ICEUS offers a better prognosis for patients with malignant glioma.

Ultrasound-guided resection of cerebellar racemose neurocysticercosis: novel insights from a unique scenario

Racemose neurocysticercosis (RNC) is a malignant form of Taenia solium infection. It carries high mortality due to widespread intraparenchymal invasion, mass effect, and cyst rupture. Cerebellar RNC is unusual and constitutes a surgical challenge. Scarce applications of ultrasound (US) -guided resection have been reported for RNC of the posterior fossa. We report the case of a 66-year-old woman who presented with ataxia and dysmetria. Her past medical history was relevant for seizures and hydrocephalus secondary to neurocysticercosis. Because of the increasing cyst invasion and threatening mass effect in the posterior fossa, the patient underwent US-guided resection of lesions. Postoperative computed tomography (CT) demonstrated complete excision of cysts, and a 2-year follow-up magnetic resonance imaging (MRI) showed no recurrence. On neurological examination, the patient had persistent ataxia without new-onset neurological deficits. The present case study illustrates the feasibility and cost-effective approach of US-guided resection to provide enhanced operative visualization and achieve complete cyst resection.

Intraoperative computed tomography, navigated ultrasound, 5-amino-levulinic acid fluorescence and neuromonitoring in brain tumor surgery: overtreatment or useful tool combination?

BACKGROUND

Brain tumor surgery is routinely supported by several intraoperative techniques, such as fluorescence, brain mapping and neuronavigation, which are often used independently. Efficacy of navigation is limited by the brain-shift phenomenon, particularly in cases of large or deep-sited lesions. Intraoperative imaging was introduced also to update neuronavigation data, to try and solve the brain-shift phenomenon-related pitfalls and increase overall safety. Nevertheless, each intraoperative imaging modality has some intrinsic limitations and technical shortcomings, making its clinical use challenging. We used a multimodal intraoperative imaging protocol to update neuronavigation, based on the combination of intraoperative Ultrasound (i-US) and intraoperative Computed Tomography (i-CT) integrated with 5-ALA fluorescence and neuromonitoring-guided resection.

METHODS

This is a pilot study on 52 patients (29 men), including four children, with a mean age of 57.67 years, suffering from brain low- (N.=10) or high-grade (N.=34) glioma or metastasis (N.=8), prospectively and consecutively enrolled. They underwent 5-ALA fluorescence-guided microsurgical tumor resection and neuromonitoring was used in cases of lesions located in eloquent areas, according to preoperative clinical and neuroradiological features. Navigated B-mode ultrasound acquisition was carried out after dural opening to identify the lesion. After tumor resection, i-US was used to identify residual tumor. Following further tumor resection or in cases of unclear US images, post-contrast i-CT was performed to detect and localize small tumor remnants and to allow further correction for brain shift. A final i-US check was performed to verify the completeness of resection. Clinical evaluation was based on comparison of pre- and postoperative Karnofsky Performance Score (KPS) and assessment of overall survival (OS) and progression-free survival (PFS). Extent of tumor resection (EOTR) was evaluated by volumetric postoperative Magnetic Resonance performed within 48 h after surgery.

RESULTS

Forty-one of the 52 (78.8%) patients were alive and still under follow-up in December 2017. 5-ALA was strongly or vaguely positive in 45 cases (86.5%). Seven lesions (four low-grade glioma, one high-grade glioma, and two metastases) were not fluorescent. i-US visualized residual tumor after resection of all fluorescent or pathological tissue in 22 cases (42.3%). After i-US guided resection, i-CT documented the presence of further residual tumor in 11 cases (21.1%). Mean EOTR was 98.79% in the low-grade gliomas group, 99.84% in the high-grade gliomas group and 100% in the metastases group. KPS changed from 77.88, preoperatively, to 72.5, postoperatively. At the last follow-up, mean KPS was 84.23.

CONCLUSIONS

The combination of different intraoperative imaging modalities may increase brain tumor safety and extent of resection. In particular, i-US seems to be highly sensitive to detect residual tumors, but it may generate false positives due to artifacts. Conversely, i-CT is more specific to localize remnants, allowing a more reliable updating of navigation data.

Advances in Neuro-Oncological Imaging: An Update on Diagnostic Approach to Brain Tumors

This study delineates the pivotal role of imaging within the field of neurology, emphasizing its significance in the diagnosis, prognostication, and evaluation of treatment responses for central nervous system (CNS) tumors. A comprehensive understanding of both the capabilities and limitations inherent in emerging imaging technologies is imperative for delivering a heightened level of personalized care to individuals with neuro-oncological conditions. Ongoing research in neuro-oncological imaging endeavors to rectify some limitations of radiological modalities, aiming to augment accuracy and efficacy in the management of brain tumors. This review is dedicated to the comparison and critical examination of the latest advancements in diverse imaging modalities employed in neuro-oncology. The objective is to investigate their respective impacts on diagnosis, cancer staging, prognosis, and post-treatment monitoring. By providing a comprehensive analysis of these modalities, this review aims to contribute to the collective knowledge in the field, fostering an informed approach to neuro-oncological care. In conclusion, the outlook for neuro-oncological imaging appears promising, and sustained exploration in this domain is anticipated to yield further breakthroughs, ultimately enhancing outcomes for individuals grappling with CNS tumors.

Updates on Neuronavigation: Emerging tools for tumor resection

Multiple studies have been conducted to properly elucidate the various tools available to help enhance the resection of tumor tissue, aneurysms, and arteriovenous malformations (AVM). Diffusion tensor imaging (DTI) tractography is useful in providing a map of the tumor borders, allowing the optimal preservation of function and structure of specific regions of the brain. During neurosurgery, especially craniotomies, the possibility of the brain shifting due to swelling or gravity is high. Thus, tools for intraoperative imaging such as high-frequency linear array ultrasound transducers and doppler ultrasonography are utilized for high resolution images and detecting frequency shifts. 4D-digital subtraction angiography (DSA) is another technique used to create spatial resolutions and 3D maps for aneurysms. These similar techniques can also be utilized to assess the integrity of white matter in AVM. By implementing effective evaluation strategies, healthcare professionals can make informed decisions regarding treatment options, preventive measures, and long-term care plans tailored to individual patients.

Hyperspectral imaging benchmark based on machine learning for intraoperative brain tumour detection

Brain surgery is one of the most common and effective treatments for brain tumour. However, neurosurgeons face the challenge of determining the boundaries of the tumour to achieve maximum resection, while avoiding damage to normal tissue that may cause neurological sequelae to patients. Hyperspectral (HS) imaging (HSI) has shown remarkable results as a diagnostic tool for tumour detection in different medical applications. In this work, we demonstrate, with a robust k-fold cross-validation approach, that HSI combined with the proposed processing framework is a promising intraoperative tool for in-vivo identification and delineation of brain tumours, including both primary (high-grade and low-grade) and secondary tumours. Analysis of the in-vivo brain database, consisting of 61 HS images from 34 different patients, achieve a highest median macro F1-Score result of 70.2 ± 7.9% on the test set using both spectral and spatial information. Here, we provide a benchmark based on machine learning for further developments in the field of in-vivo brain tumour detection and delineation using hyperspectral imaging to be used as a real-time decision support tool during neurosurgical workflows.

Critical Assessment of Cancer Characterization and Margin Evaluation Techniques in Brain Malignancies: From Fast Biopsy to Intraoperative Flow Cytometry

Brain malignancies, given their intricate nature and location, present significant challenges in both diagnosis and treatment. This review critically assesses a range of diagnostic and surgical techniques that have emerged as transformative tools in brain malignancy management. Fast biopsy techniques, prioritizing rapid and minimally invasive tissue sampling, have revolutionized initial diagnostic stages. Intraoperative flow cytometry (iFC) offers real-time cellular analysis during surgeries, ensuring optimal tumor resection. The advent of intraoperative MRI (iMRI) has seamlessly integrated imaging into surgical procedures, providing dynamic feedback and preserving critical brain structures. Additionally, 5-aminolevulinic acid (5-ALA) has enhanced surgical precision by inducing fluorescence in tumor cells, aiding in their complete resection. Several other techniques have been developed in recent years, including intraoperative mass spectrometry methodologies. While each technique boasts unique strengths, they also present potential limitations. As technology and research continue to evolve, these methods are set to undergo further refinement. Collaborative global efforts will be pivotal in driving these advancements, promising a future of improved patient outcomes in brain malignancy management.

Deep learning for tumor margin identification in electromagnetic imaging

In this work, a novel method for tumor margin identification in electromagnetic imaging is proposed to optimize the tumor removal surgery. This capability will enable the visualization of the border of the cancerous tissue for the surgeon prior or during the excision surgery. To this end, the border between the normal and tumor parts needs to be identified. Therefore, the images need to be segmented into tumor and normal areas. We propose a deep learning technique which divides the electromagnetic images into two regions: tumor and normal, with high accuracy. We formulate deep learning from a perspective relevant to electromagnetic image reconstruction. A recurrent auto-encoder network architecture (termed here DeepTMI) is presented. The effectiveness of the algorithm is demonstrated by segmenting the reconstructed images of an experimental tissue-mimicking phantom. The structure similarity measure (SSIM) and mean-square-error (MSE) average of normalized reconstructed results by the DeepTMI method are about 0.94 and 0.04 respectively, while that average obtained from the conventional backpropagation (BP) method can hardly overcome 0.35 and 0.41 respectively.

A Review of Recent Advances in Brain Tumor Diagnosis Based on AI-Based Classification

Uncontrolled and fast cell proliferation is the cause of brain tumors. Early cancer detection is vitally important to save many lives. Brain tumors can be divided into several categories depending on the kind, place of origin, pace of development, and stage of progression; as a result, tumor classification is crucial for targeted therapy. Brain tumor segmentation aims to delineate accurately the areas of brain tumors. A specialist with a thorough understanding of brain illnesses is needed to manually identify the proper type of brain tumor. Additionally, processing many images takes time and is tiresome. Therefore, automatic segmentation and classification techniques are required to speed up and enhance the diagnosis of brain tumors. Tumors can be quickly and safely detected by brain scans using imaging modalities, including computed tomography (CT), magnetic resonance imaging (MRI), and others. Machine learning (ML) and artificial intelligence (AI) have shown promise in developing algorithms that aid in automatic classification and segmentation utilizing various imaging modalities. The right segmentation method must be used to precisely classify patients with brain tumors to enhance diagnosis and treatment. This review describes multiple types of brain tumors, publicly accessible datasets, enhancement methods, segmentation, feature extraction, classification, machine learning techniques, deep learning, and learning through a transfer to study brain tumors. In this study, we attempted to synthesize brain cancer imaging modalities with automatically computer-assisted methodologies for brain cancer characterization in ML and DL frameworks. Finding the current problems with the engineering methodologies currently in use and predicting a future paradigm are other goals of this article.

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.

Narrative Review of Multidisciplinary Management of Central Nervous Involvement in Patients with HER2-Positive Metastatic Breast Cancer: Focus on Elderly Patients

The tumor biology of human epidermal growth factor receptor 2 (HER2)-positive breast cancer (BC) promotes the development of central nervous system (CNS) metastases, with 25% of patients with HER2-positive BC developing CNS metastases. Furthermore, the incidence of HER2-positive BC brain metastases has increased in the last decades, likely because of the improved survival with targeted therapies and better detection methods. Brain metastases are detrimental to quality of life and survival and represent a challenging clinical problem, particularly in elderly women, who comprise a substantial proportion of patients diagnosed with BC and often have comorbidities or an age-related decline in organ function. Treatment options for patients with BC brain metastases include surgical resection, whole-brain radiation therapy, stereotactic radiosurgery, chemotherapy, and targeted agents. Ideally, local and systemic treatment decisions should be made by a multidisciplinary team, with input from several specialties, based on an individualized prognostic classification. In elderly patients with BC, additional age-associated conditions, such as geriatric syndromes or comorbidities, and the physiologic changes associated with aging, may impact their ability to tolerate cancer therapy and should be considered in the treatment decision-making process. This review describes the treatment options for elderly patients with HER2-positive BC and brain metastases, focusing on the importance of multidisciplinary management, the different points of view from the distinct disciplines, and the role of oncogeriatric and palliative care in this vulnerable patient group.

The accuracy and safety of intraoperative ultrasound-guided external ventricular drainage in intraventricular hemorrhage

Severe IVH often results in a poor outcome. Currently, EVD is a standard treatment for IVH, but there is little research to show whether using ultrasound to guide the catheter placement improves outcome. Patients with severe IVH who had iUS-guided EVD (the iUS-guided group) were enrolled retrospectively and compared with a group who had EVD performed without ultrasound guidance (the control group) from January 2016 to July 2022. Data were collected on accuracy of the catheter placement, complications and outcome at 3 months assessed by mRS. The accuracy of the EVD placement was classified as optimal placement, sub-optimal placement and misplacement according to the position of the catheter tip. The complications reported are catheter-related hemorrhage, intracranial infection and hydrocephalus. There were 105 cases enrolled, with 72 patients in the iUS-guided group having 131 catheters inserted and 33 patients in the group where ultrasound was not used with a total of 59 catheters. 116 (88.55%) were optimally placed, 12 (9.16%) sub-optimal and 3 (2.29%) misplaced in the iUS-guided group, while 25 (42.37%) were in optimally placed, 30 (50.85%) sub-optimal and 4(6.78%) misplaced in the control group. Accuracy of placement was highly significantly improved using ultrasound (P < 0.001). The operation time and the average catheterized time were longer in the iUS-guided group (P < 0.05), but the complication rates were no different between the groups. The mRS at three months was not significantly different between the two groups. Using iUS to place EVD catheters in patients with severe IVH is a safe technique delivering more accurate catheter placement without increasing the complication rate compared with freehand placement.

Headlight and loupe-based fluorescein detection system in brain tumor surgery: a first-in-human experience

Fluorescein is an agent that accumulates in areas of blood-brain barrier breakdown and is commonly used in neurosurgical oncology to assist with lesion localization and visualizing the extent of resection. It is considered to be cost-effective and has a favorable safety profile. Studies on the utilization of fluorescein demonstrate an improved extent of tumor resection and increased overall survival. Currently, fluorescein detection systems are all microscope based, leading to limitations such as decreased maneuverability, limited visualization of the entire operative field, and significant cost associated with obtaining and maintaining a neurosurgical operating microscope. Three consecutive craniotomy patients for tumor resection were included, and surgery was carried out under loupe fluorescence guidance using the ReVeal 450 System, and also a surgical microscope for comparison. Loupe-mounted fluorescence system enabled excellent visualization of fluorescence in all three cases. In this manuscript, we describe our experience with a loupe-mounted fluorescein detection system in three patients with malignant gliomas. We found that the loupe-mounted system offered excellent ability to visualize fluorescein fluorescence. Although loupe-mounted systems are not an alternative to surgical microscopes, they could be a useful surgical adjunct for superficial lesions and in low-middle income counties.

Advances in Focused Ultrasound for the Treatment of Brain Tumors

Employing the full arsenal of therapeutics to treat brain tumors is limited by the relative impermeability of the blood-brain and blood-tumor barriers. In physiologic states, the blood-brain barrier serves a protective role by passively and actively excluding neurotoxic compounds; however, this functionality limits the penetrance of therapeutics into the tumor microenvironment. Focused ultrasound technology provides a method for overcoming the blood-brain and blood-tumor barriers through ultrasound frequency to transiently permeabilize or disrupt these barriers. Concomitant delivery of therapeutics has allowed for previously impermeable agents to reach the tumor microenvironment. This review details the advances in focused ultrasound in both preclinical models and clinical studies, with a focus on its safety profile. We then turn towards future directions in focused ultrasound-mediated therapies for brain tumors.

Potential benefits of intraoperative ultrasound in neurosurgery

Computed tomography and magnetic resonance imaging are the most popular diagnostic tools to visualize intracranial pathology and help surgical planning in the neurosurgical practice. However, these preoperative techniques need to be supplemented with intraoperative methods, if the lesion size may increase or preoperative anatomy may change after the primary imaging due to rapid progression of the underlying intracranial disease. In such situations intraoperative ultrasound could be a valuable technique in real-time imaging of intracranial pathologic processes, real-time control of surgical procedure, assistance in drain or catheter placement, and real-time assessment of residual tumor or hematoma volume during neurosurgical interventions.

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.

A Systematic Review of Amino Acid PET Imaging in Adult-Type High-Grade Glioma Surgery: A Neurosurgeon's Perspective

Amino acid PET imaging has been used for a few years in the clinical and surgical management of gliomas with satisfactory results in diagnosis and grading for surgical and radiotherapy planning and to differentiate recurrences. Biological tumor volume (BTV) provides more meaningful information than standard MR imaging alone and often exceeds the boundary of the contrast-enhanced nodule seen in MRI. Since a gross total resection reflects the resection of the contrast-enhanced nodule and the majority of recurrences are at a tumor's margins, an integration of PET imaging during resection could increase PFS and OS. A systematic review of the literature searching for "PET" [All fields] AND "glioma" [All fields] AND "resection" [All fields] was performed in order to investigate the diffusion of integration of PET imaging in surgical practice. Integration in a neuronavigation system and intraoperative use of PET imaging in the primary diagnosis of adult high-grade gliomas were among the criteria for article selection. Only one study has satisfied the inclusion criteria, and a few more (13) have declared to use multimodal imaging techniques with the integration of PET imaging to intentionally perform a biopsy of the PET uptake area. Despite few pieces of evidence, targeting a biologically active area in addition to other tools, which can help intraoperatively the neurosurgeon to increase the amount of resected tumor, has the potential to provide incremental and complementary information in the management of brain gliomas. Since supramaximal resection based on the extent of MRI FLAIR hyperintensity resulted in an advantage in terms of PFS and OS, PET-based biological tumor volume, avoiding new neurological deficits, deserves further investigation.

The use of the sodium fluorescein and YELLOW 560 nm filter for the resection of pediatric posterior fossa lesions

PURPOSE

This study aimed to verify the feasibility, safety, and benefit of using fluorescein sodium (FL) and a YELLOW 560 nm filter in posterior fossa tumors in children.

METHODS

All cases of pediatric posterior fossa tumors that have undergone surgery using fluorescein (2018-2022) have been included and were examined retrospectively. In those cases where resection of the tumor was planned, a blinded neuroradiologist distinguished gross total resection and subtotal resection according to the postoperative MRI findings. The surgical report and medical files were reviewed regarding the intraoperative staining grade and adverse events. The grade of fluorescent staining of the targeted lesion was assessed as described in the surgical reports. The screening was conducted for any reference to the degree of fluorescent staining: "intense," "medium," "slight," and "no staining."

RESULTS

19 cases have been included. In 14 cases, a complete resection was initially intended. In 11 of these cases, a gross total resection could be achieved (78.6%). Staining was described as intense in most cases (58.8%). Except for yellow-colored urine, no side effects obviously related to FL were found throughout the observation period.

CONCLUSION

In combination with a specific filter, FL is a reliable, safe, and feasible tool in posterior fossa surgery in children.

Optimization of intraoperative ultrasound navigation during focal cortical dysplasia surgery: a case report

Intraoperative ultrasound (IUS) is known to be an effective method for neuronavigation during surgical treatment of intractable seizures caused by focal cortical dysplasia (FCD). However, the 2-dimensional (2D) IUS has poor image quality and low spatial resolution. We describe via a case report how Ultrasound integrated Brainlab (BL) – Navigation software was used to optimize 2D IUS and thereby reduce these challenges.

Case report: We present a case report of a 22-year-old female patient with a long-standing history of seizures. The patient was treated with more than two anti-epileptic drugs without any clinical efficacy. In 2022 she was diagnosed with temporal lobe FCD. We performed a temporal lobe lesionectomy using optimized IUS BL-Navigation that provided enhanced 3-dimensional (3D) images.

Discussion: The extent of resection of the underlying FCD lesion is a key factor in determining whether a patient achieves meaningful seizure freedom after surgery. While the 2D IUS offers admirable characteristics that have been used as an aid during surgery, it is our view that IUS enhanced 3D BL-Navigation offers better appreciation of FCD lesions and therefore improves the extent of resection.

Particle Swarm Optimization and Two-Way Fixed-Effects Analysis of Variance for Efficient Brain Tumor Segmentation

Simple Summary

Segmentation of brain tumor images from magnetic resonance imaging (MRI) is a challenging topic in medical image analysis. The brain tumor can take many shapes, and MRI images vary considerably in intensity, making lesion detection difficult for radiologists. This paper proposes a three-step approach to solving this problem: (1) pre-processing, based on morphological operations, is applied to remove the skull bone from the image; (2) the particle swarm optimization (PSO) algorithm, with a two-way fixed-effects analysis of variance (ANOVA)-based fitness function, is used to find the optimal block containing the brain lesion; (3) the K-means clustering algorithm is adopted, to classify the detected block as tumor or non-tumor. An extensive experimental analysis, including visual and statistical evaluations, was conducted, using two MRI databases: a private database provided by the Kouba imaging center—Algiers (KICA)—and the multimodal brain tumor segmentation challenge (BraTS) 2015 database. The results show that the proposed methodology achieved impressive performance, compared to several competing approaches.

Abstract

Segmentation of brain tumor images, to refine the detection and understanding of abnormal masses in the brain, is an important research topic in medical imaging. This paper proposes a new segmentation method, consisting of three main steps, to detect brain lesions using magnetic resonance imaging (MRI). In the first step, the parts of the image delineating the skull bone are removed, to exclude insignificant data. In the second step, which is the main contribution of this study, the particle swarm optimization (PSO) technique is applied, to detect the block that contains the brain lesions. The fitness function, used to determine the best block among all candidate blocks, is based on a two-way fixed-effects analysis of variance (ANOVA). In the last step of the algorithm, the K-means segmentation method is used in the lesion block, to classify it as a tumor or not. A thorough evaluation of the proposed algorithm was performed, using: (1) a private MRI database provided by the Kouba imaging center—Algiers (KICA); (2) the multimodal brain tumor segmentation challenge (BraTS) 2015 database. Estimates of the selected fitness function were first compared to those based on the sum-of-absolute-differences (SAD) dissimilarity criterion, to demonstrate the efficiency and robustness of the ANOVA. The performance of the optimized brain tumor segmentation algorithm was then compared to the results of several state-of-the-art techniques. The results obtained, by using the Dice coefficient, Jaccard distance, correlation coefficient, and root mean square error (RMSE) measurements, demonstrated the superiority of the proposed optimized segmentation algorithm over equivalent techniques.

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.

Navigated 3D ultrasound-guided resection of high-grade gliomas: A case series and review

Background:

The crux in high-grade glioma surgery remains maximizing resection without affecting eloquent brain areas. Toward this, a myriad of adjunct tools and techniques has been employed to enhance surgical safety and efficacy. Despite intraoperative MRI and advanced neuronavigational techniques, as well as augmented reality, to date, the only true real-time visualization tool remains the ultrasound (US). Neuroultrasonography is a cost-efficient imaging modality that offers instant, real-time information about the changing anatomical landscape intraoperatively. Recent advances in technology now allow for the integration of intraoperative US with neuronavigation.

Case Description:

In this report, we present the resection technique for three cases of high-grade gliomas (two glioblastomas and one anaplastic astrocytoma). The patient presented with a variable clinical spectrum. All three cases have been performed using the Brainlab^® neuronavigation system (BrainLAB, Munich, Germany) and the bk5000 US Machine^® (BK Medical, Analogic Corporation, Peabody, Massachusetts, USA).

Conclusion:

Gross total resection was achieved in all three cases. The use of 3D navigated US was a reliable adjunct surgical tool in achieving favorable resection outcomes in these patients.

Machine learning-enabled quantitative ultrasound techniques for tissue differentiation

PURPOSE

Quantitative ultrasound (QUS) infers properties about tissue microstructure from backscattered radio-frequency ultrasound data. This paper describes how to implement the most practical QUS parameters using an ultrasound research system for tissue differentiation.

METHODS

This study first validated chicken liver and gizzard muscle as suitable acoustic phantoms for human brain and brain tumour tissues via measurement of the speed of sound and acoustic attenuation. A total of thirteen QUS parameters were estimated from twelve samples, each using data obtained with a transducer with a frequency of 5-11 MHz. Spectral parameters, i.e., effective scatterer diameter and acoustic concentration, were calculated from the backscattered power spectrum of the tissue, and echo envelope statistics were estimated by modelling the scattering inside the tissue as a homodyned K-distribution, yielding the scatterer clustering parameter α and the structure parameter κ. Standard deviation and higher-order moments were calculated from the echogenicity value assigned in conventional B-mode images.

RESULTS

The k-nearest neighbours algorithm was used to combine those parameters, which achieved 94.5% accuracy and 0.933 F1-score.

CONCLUSION

We were able to generate classification parametric images in near-real-time speed as a potential diagnostic tool in the operating room for the possible use for human brain tissue characterisation.

Measurement of aspiration pressure in cannula brain tumour biopsy and its correlation with ultrasonographic elastography

BACKGROUND

Stereotactic brain biopsy is to perform the manual aspiration tissue biopsy using a cannula on a syringe under stereotactic guidance to provide histological confirmation. Excessive vacuum aspiration increases the risk of haemorrhage. Manual aspiration relies on the surgeon's experience while the minimum vacuum pressure is unknown.

OBJECTIVES

1. To assess the aspiration vacuum pressure range in cannula brain tumour biopsy; 2. To understand the correlation of ultrasound elastography data with the aspiration pressure.

METHODS

This prospective study has recruited 10 patients for stereotactic brain tumour biopsy. With the use of ultrasound elastography, strain ratio of the lesion was assessed in real time before biopsy. Vacuum aspiration pressures were recorded using a T-connector pressure sensor during the stereotactic biopsy.

RESULTS

A total of 11 biopsies were taken from 10 patients, including a bilateral biopsy for a patient with bifrontal lesions. The diagnostic yield was 100% in all the 10 patients with no symptomatic haemorrhage (but 2 subclinical haemorrhages in CT scan) nor infection. The vacuum pressures ranged from 40.34 to 65.61 kPa and the strain-ratio ranged from 0.405 to 2.74. Strain ratio of the lesion at the lower range required a lower range of aspiration pressure, whereas lesions of Strain ratio over 0.45 required a higher range of aspiration pressure.

CONCLUSION

A vacuum pressure of 40 to 66 kPas is safe and adequate for biopsy of various types of tumours with heterogenous elastographic characters. Ultrasonographic elastography may be a real-time guide for the minimum vacuum pressure required for biopsy.

Intraoperative integration of multimodal imaging to improve neuronavigation: a technical note

BACKGROUND

Brain shift may cause significant error in neuronavigation leading the surgeon to possible mistakes. Intraoperative MRI is the most reliable technique in brain tumor surgery. Unfortunately, it is highly expensive and time consuming and, at the moment, it is available only in few neurosurgical centers.

METHODS

In this case series the surgical workflow for brain tumor surgery is described where neuronavigation of pre-operative MRI, intraoperative CT scan and US as well as rigid and elastic image fusion between preoperative MRI and intraoperative US and CT, respectively, was applied to four brain tumor patients in order to compensate for surgical induced brain shift by using a commercially available software (Elements Image Fusion 4.0 with Virtual iMRI Cranial; Brainlab AG).

RESULTS

Three exemplificative cases demonstrated successful integration of different components of the described intraoperative surgical workflow. The data indicates that intraoperative navigation update is feasible by applying intraoperative 3D US and CT scanning as well as rigid and elastic image fusion applied depending on the degree of observed brain shift.

CONCLUSIONS

Integration of multiple intraoperative imaging techniques combined with rigid and elastic image fusion of preoperative MRI may reduce the risk of incorrect neuronavigation during brain tumor resection. Further studies are needed to confirm the present findings in a larger population.

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.

Application of Intraoperative Ultrasound Navigation in Neurosurgery

Effective intraoperative image navigation techniques are necessary in modern neurosurgery. In the last decade, intraoperative ultrasonography (iUS), a relatively inexpensive procedure, has gained widespread acceptance.

Navigated Intraoperative 3D Ultrasound in Glioblastoma Surgery: Analysis of Imaging Features and Impact on Extent of Resection

Background

Neuronavigation is routinely used in glioblastoma surgery, but its accuracy decreases during the operative procedure due to brain shift, which can be addressed utilizing intraoperative imaging. Intraoperative ultrasound (iUS) is widely available, offers excellent live imaging, and can be fully integrated into modern navigational systems. Here, we analyze the imaging features of navigated i3D US and its impact on the extent of resection (EOR) in glioblastoma surgery.

Methods

Datasets of 31 glioblastoma resection procedures were evaluated. Patient registration was established using intraoperative computed tomography (iCT). Pre-operative MRI (pre-MRI) and pre-resectional ultrasound (pre-US) datasets were compared regarding segmented tumor volume, spatial overlap (Dice coefficient), the Euclidean distance of the geometric center of gravity (CoG), and the Hausdorff distance. Post-resectional ultrasound (post-US) and post-operative MRI (post-MRI) tumor volumes were analyzed and categorized into subtotal resection (STR) or gross total resection (GTR) cases.

Results

The mean patient age was 59.3 ± 11.9 years. There was no significant difference in pre-resectional segmented tumor volumes (pre-MRI: 24.2 ± 22.3 cm³; pre-US: 24.0 ± 21.8 cm³). The Dice coefficient was 0.71 ± 0.21, the Euclidean distance of the CoG was 3.9 ± 3.0 mm, and the Hausdorff distance was 12.2 ± 6.9 mm. A total of 18 cases were categorized as GTR, 10 cases were concordantly classified as STR on MRI and ultrasound, and 3 cases had to be excluded from post-resectional analysis. In four cases, i3D US triggered further resection.

Conclusion

Navigated i3D US is reliably adjunct in a multimodal navigational setup for glioblastoma resection. Tumor segmentations revealed similar results in i3D US and MRI, demonstrating the capability of i3D US to delineate tumor boundaries. Additionally, i3D US has a positive influence on the EOR, allows live imaging, and depicts brain shift.

Multiparametric Intraoperative Ultrasound in Oncological Neurosurgery: A Pictorial Essay

Intraoperative ultrasound (ioUS) is increasingly used in current neurosurgical practice. This is mainly explained by its affordability, handiness, multimodal real-time nature, and overall by its image spatial and temporal resolution. Identification of lesion and potential residue, analysis of the vascularization pattern, and characterization of the nature of the mass are only some of the advantages that ioUS offers to guide safe and efficient tumor resection. Technological advances in ioUS allow to achieve both structural and functional imaging. B-mode provides high-resolution visualization of the lesion and of its boundaries and relationships. Pioneering modes, such as contrast-enhanced ultrasound (CEUS), ultrasensitive Doppler, and elastosonography, are tools with great potential in characterizing different functional aspects of the lesion in a qualitative and quantitative manner. As already happening for many organs and pathologies, the combined use of different US modalities offers new insights in a multiparametric fashion. In this study, we present the potential of our multiparametric approach for ioUS during neuro-oncological surgery. In this effort, we provide a pictorial essay focusing on the most frequent pathologies: low- and high-grade gliomas, meningiomas, and brain metastases.

Intelligent Ultra-Light Deep Learning Model for Multi-Class Brain Tumor Detection

The diagnosis and surgical resection using Magnetic Resonance (MR) images in brain tumors is a challenging task to minimize the neurological defects after surgery owing to the non-linear nature of the size, shape, and textural variation. Radiologists, clinical experts, and brain surgeons examine brain MRI scans using the available methods, which are tedious, error-prone, time-consuming, and still exhibit positional accuracy up to 2–3 mm, which is very high in the case of brain cells. In this context, we propose an automated Ultra-Light Brain Tumor Detection (UL-BTD) system based on a novel Ultra-Light Deep Learning Architecture (UL-DLA) for deep features, integrated with highly distinctive textural features, extracted by Gray Level Co-occurrence Matrix (GLCM). It forms a Hybrid Feature Space (HFS), which is used for tumor detection using Support Vector Machine (SVM), culminating in high prediction accuracy and optimum false negatives with limited network size to fit within the average GPU resources of a modern PC system. The objective of this study is to categorize multi-class publicly available MRI brain tumor datasets with a minimum time thus real-time tumor detection can be carried out without compromising accuracy. Our proposed framework includes a sensitivity analysis of image size, One-versus-All and One-versus-One coding schemes with stringent efforts to assess the complexity and reliability performance of the proposed system with K-fold cross-validation as a part of the evaluation protocol. The best generalization achieved using SVM has an average detection rate of 99.23% (99.18%, 98.86%, and 99.67%), and F-measure of 0.99 (0.99, 0.98, and 0.99) for (glioma, meningioma, and pituitary tumors), respectively. Our results have been found to improve the state-of-the-art (97.30%) by 2%, indicating that the system exhibits capability for translation in modern hospitals during real-time surgical brain applications. The method needs 11.69 ms with an accuracy of 99.23% compared to 15 ms achieved by the state-of-the-art to earlier to detect tumors on a test image without any dedicated hardware providing a route for a desktop application in brain surgery.

Intraoperative application of yellow fluorescence in resection of intramedullary spinal canal ependymoma

BACKGROUND

Spinal ependymoma is the most common intramedullary tumor in adults. This study was performed to evaluate whether intraoperative yellow fluorescence use enhances our ability to identify the tumor margin and residual tumor tissue in intramedullary spinal cord ependymoma resection. We also evaluated patients' clinical conditions at a 3-month follow-up.

METHODS

We retrospectively evaluated 56 patients with intramedullary ependymoma. Thirty minutes before anesthesia, the patients received intravenous sodium fluorescein injections. Tumor resection was performed under two illumination modes, traditional white light and yellow fluorescence, and the residual tumor tissue was detected. Magnetic resonance imaging was performed 3 months postoperatively to observe the tumor resection outcome and residual tumor tissue. The McCormick spinal cord function grade was evaluated preoperatively and 3 months postoperatively.

RESULTS

The total resection rate was 100.0% in all patients. Nine patients had no significant fluorescence imaging. After 3 months, patients with a spinal function grade of I to IV showed significant spinal function improvement. Magnetic resonance imaging showed no residual tumor tissue or recurrence.

CONCLUSION

Sodium fluorescein aids in total excision of intramedullary spinal cord ependymoma and intraoperative residual tumor tissue identification. At the 3-month follow-up, the patients' functional outcome in the fluorescein group was good.