3D intra-operative ultrasound and MR image guidance: pursuing an ultrasound-based management of brainshift to enhance neuronavigation

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.

Intraoperative AIRO mobile computer tomography in frameless stereotactic procedures

BACKGROUND

Multiple factors can affect the accuracy of neuronavigation, that is a relevant issue, particularly for frameless stereotactic procedures, where precision and optimal image-guidance is crucial for the surgical performance, workflow, and outcome.

OBJECTIVE

To investigate the impact of AIRO Mobile Computer Tomography in frameless stereotactic approaches.

METHODS

A retrospective study on 12 patients was performed. All the procedures were deployed using a frameless stereotactic technique, both for the collection of biopsy pathological specimens for diagnosis and insertion of drainage in the treatment of intracranial cystic lesions.

RESULTS

Twelve patients (eight males, four females) underwent the frameless stereotactic procedure. Mean age at surgery was 55 (±5 SE). The mean volume of the lesion was 23.85 cm³ (±3.13). Six diagnostic biopsies and six cyst drainages were performed. The mean trajectory length was 75.9 ± 11.8 mm. Three posterior fossa lesions (27%) were approached through a retro-sigmoidal burr-hole. A craniotomy for draining a haematoma was performed after detection with AIRO-CT. No permanent neurological dysfunction, in-hospital or 30-day mortality were recorded.

CONCLUSION

The AIRO-CT resulted feasible with a potential utility for stereotactic procedures. We showed how it could grant the efficacy of the stereotactic procedures reducing some technical and physical sources of inaccuracy, also enhancing safety and allowing prompt detection and management of intraoperative complications.

Raman Spectroscopy and Machine Learning for IDH Genotyping of Unprocessed Glioma Biopsies

Simple Summary

Isocitrate dehydrogenase (IDH) mutation is one of the most important prognostic markers in glioma tumors. Raman spectroscopy (RS) is an optical technique with great potential in intraoperative molecular diagnosis and surgical guidance. We analyzed RS’s ability to detect the IDH mutation onto unprocessed glioma biopsies. A total of 2073 Raman spectra were extracted from 38 tumor specimens. From the 103 Raman shifts screened, we identified 52 shifts (related to lipids, collagen, DNA and cholesterol/phospholipids) with the highest performance in the distinction of the two groups. We described 18 shifts never used before for IDH detection with RS in fresh or frozen samples. We were able to distinguish between IDH-mutated and IDH-wild-type tumors with an accuracy and precision of 87%. RS showed optimal accuracy and precision in discriminating IDH-mutated glioma from IDH-wild-type tumors ex-vivo onto fresh surgical specimens.

Abstract

Isocitrate dehydrogenase (IDH) mutational status is pivotal in the management of gliomas. Patients with IDH-mutated (IDH-MUT) tumors have a better prognosis and benefit more from extended surgical resection than IDH wild-type (IDH-WT). Raman spectroscopy (RS) is a minimally invasive optical technique with great potential for intraoperative diagnosis. We evaluated the RS’s ability to characterize the IDH mutational status onto unprocessed glioma biopsies. We extracted 2073 Raman spectra from thirty-eight unprocessed samples. The classification performance was assessed using the eXtreme Gradient Boosted trees (XGB) and Support Vector Machine with Radial Basis Function kernel (RBF-SVM). Measured Raman spectra displayed differences between IDH-MUT and IDH-WT tumor tissue. From the 103 Raman shifts screened as input features, the cross-validation loop identified 52 shifts with the highest performance in the distinction of the two groups. Raman analysis showed differences in spectral features of lipids, collagen, DNA and cholesterol/phospholipids. We were able to distinguish between IDH-MUT and IDH-WT tumors with an accuracy and precision of 87%. RS is a valuable and accurate tool for characterizing the mutational status of IDH mutation in unprocessed glioma samples. This study improves RS knowledge for future personalized surgical strategy or in situ target therapies for glioma tumors.

Augmented reality-assisted roadmaps during periventricular brain surgery

Visualizing major periventricular anatomical landmarks intraoperatively during brain tumor removal is a decisive measure toward preserving such structures and thus the patient's postoperative quality of life. The aim of this study was to describe potential standardized preoperative planning using standard landmarks and procedures and to demonstrate the feasibility of using augmented reality (AR) to assist in performing surgery according to these "roadmaps." The authors have depicted stepwise AR surgical roadmaps applied to periventricular brain surgery with the aim of preserving major cognitive function. In addition to the technological aspects, this study highlights the importance of using emerging technologies as potential tools to integrate information and to identify and visualize landmarks to be used during tumor removal.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Chinese Cerebrovascular Neurosurgery Society and Chinese Interventional & Hybrid Operation Society, of Chinese Stroke Association Clinical Practice Guidelines for Management of Brain Arteriovenous Malformations in Eloquent Areas

Aim: The aim of this guideline is to present current and comprehensive recommendations for the management of brain arteriovenous malformations (bAVMs) located in eloquent areas. Methods: An extended literature search on MEDLINE was performed between Jan 1970 and May 2020. Eloquence-related literature was further screened and interpreted in different subcategories of this guideline. The writing group discussed narrative text and recommendations through group meetings and online video conferences. Recommendations followed the Applying Classification of Recommendations and Level of Evidence proposed by the American Heart Association/American Stroke Association. Prerelease review of the draft guideline was performed by four expert peer reviewers and by the members of Chinese Stroke Association. Results: In total, 809 out of 2,493 publications were identified to be related to eloquent structure or neurological functions of bAVMs. Three-hundred and forty-one publications were comprehensively interpreted and cited by this guideline. Evidence-based guidelines were presented for the clinical evaluation and treatment of bAVMs with eloquence involved. Topics focused on neuroanatomy of activated eloquent structure, functional neuroimaging, neurological assessment, indication, and recommendations of different therapeutic managements. Fifty-nine recommendations were summarized, including 20 in Class I, 30 in Class IIa, 9 in Class IIb, and 2 in Class III. Conclusions: The management of eloquent bAVMs remains challenging. With the evolutionary understanding of eloquent areas, the guideline highlights the assessment of eloquent bAVMs, and a strategy for decision-making in the management of eloquent bAVMs.

Path Replanning for Orientation-Constrained Needle Steering

INTRODUCTION

Needle-based neurosurgical procedures require high accuracy in catheter positioning to achieve high clinical efficacy. Significant challenges for achieving accurate targeting are (i) tissue deformation (ii) clinical obstacles along the insertion path (iii) catheter control.

OBJECTIVE

We propose a novel path-replanner able to generate an obstacle-free and curvature bounded three-dimensional (3D) path at each time step during insertion, accounting for a constrained target pose and intraoperative anatomical deformation. Additionally, our solution is sufficiently fast to be used in a closed-loop system: needle tip tracking via electromagnetic sensors is used by the path-replanner to automatically guide the programmable bevel-tip needle (PBN) while surgical constraints on sensitive structures avoidance are met.

METHODS

The generated path is achieved by combining the "Bubble Bending" method for online path deformation and a 3D extension of a convex optimisation method for path smoothing.

RESULTS

Simulation results performed on a realistic dataset show that our replanning method can guide a PBN with bounded curvature to a predefined target pose with an average targeting error of 0.65  ± 0.46 mm in position and 3.25  ± 5.23 degrees in orientation under a deformable simulated environment. The proposed algorithm was also assessed in-vitro on a brain-like gelatin phantom, achieving a target error of 1.81  ± 0.51 mm in position and 5.9  ± 1.42 degrees in orientation.

CONCLUSION

The presented work assessed the performance of a new online steerable needle path-planner able to avoid anatomical obstacles while optimizing surgical criteria.

SIGNIFICANCE

This method is particularly suited for surgical procedures demanding high accuracy on the desired goal pose under tissue deformations and real-world inaccuracies.

Application of Multiparametric Intraoperative Ultrasound in Glioma Surgery

Gliomas are the most invasive and fatal primary malignancy of the central nervous system that have poor prognosis, with maximal safe resection representing the gold standard for surgical treatment. To achieve gross total resection (GTR), neurosurgery relies heavily on generating continuous, real-time, intraoperative glioma descriptions based on image guidance. Given the limitations of currently available equipment, developing a real-time image-guided resection technique that provides reliable functional and anatomical information during intraoperative settings is imperative. Nowadays, the application of intraoperative ultrasound (IOUS) has been shown to improve resection rates and maximize brain function preservation. IOUS, which presents an attractive option due to its low cost, minimal operational flow interruptions, and lack of radiation exposure, is able to provide real-time localization and accurate tumor size and shape descriptions while helping distinguish residual tumors and addressing brain shift. Moreover, the application of new advancements in ultrasound technology, such as contrast-enhanced ultrasound, three-dimensional ultrasound, navigable ultrasound, ultrasound elastography, and functional ultrasound, could help to achieve GTR during glioma surgery. The current review describes current advancements in ultrasound technology and evaluates the role and limitation of IOUS in glioma surgery.

Intraoperative Ultrasound Shear-Wave Elastography in Focal Cortical Dysplasia Surgery

Previous studies reported interest in intraoperative shear-wave elastography (SWE) guidance for brain-tumor and epilepsy surgeries. Focal cortical dysplasia (FCD) surgery is one of the most appropriate indications for using SWE guidance. The aim of this study was to evaluate the efficacy of ultrasound SWE techniques for the intraoperative detection of FCDs. We retrospectively analyzed data from 18 adult patients with drug-resistant epilepsy associated with FCD who had undergone SWE-guided surgery. Conventional B-mode images detected FCD in 2 patients (11.1%), while SWE detected FCD in 14 patients (77.8%). The stiffness ratios between MRI-positive and -negative cases were significantly different (3.6 ± 0.4 vs. 2.2 ± 0.6, respectively; p < 0.001). FCDs were significantly more frequently detected by interoperative SWE in women (OR 4.7, 95% CI (1.7–12.7); p = 0.004) and in patients in whom FCD was visible on magnetic resonance imaging (MRI; OR 2.3, 95% CI (1.3–4.3); p = 0.04). At 1 year after surgery and at last follow-up (mean = 21 months), seizure outcome was good (International League Against Epilepsy (ILAE) Class 1 or 2) in 72.2% and 55.6% of patients, respectively. Despite some limitations, our study highlighted the potential of SWE as an intraoperative tool to detect FCD. Future technical developments should allow for optimizing intraoperative surgical-cavity evaluation from the perspective of complete FCD resection. Interobserver reliability of SWE measurements should also be assessed by further studies.

Glioma biopsies Classification Using Raman Spectroscopy and Machine Learning Models on Fresh Tissue Samples

Identifying tumor cells infiltrating normal-appearing brain tissue is critical to achieve a total glioma resection. Raman spectroscopy (RS) is an optical technique with potential for real-time glioma detection. Most RS reports are based on formalin-fixed or frozen samples, with only a few studies deployed on fresh untreated tissue. We aimed to probe RS on untreated brain biopsies exploring novel Raman bands useful in distinguishing glioma and normal brain tissue. Sixty-three fresh tissue biopsies were analyzed within few minutes after resection. A total of 3450 spectra were collected, with 1377 labelled as Healthy and 2073 as Tumor. Machine learning methods were used to classify spectra compared to the histo-pathological standard. The algorithms extracted information from 60 different Raman peaks identified as the most representative among 135 peaks screened. We were able to distinguish between tumor and healthy brain tissue with accuracy and precision of 83% and 82%, respectively. We identified 19 new Raman shifts with known biological significance. Raman spectroscopy was effective and accurate in discriminating glioma tissue from healthy brain ex-vivo in fresh samples. This study added new spectroscopic data that can contribute to further develop Raman Spectroscopy as an intraoperative tool for in-vivo glioma detection.

High Grade Glioma Treatment in Elderly People: Is It Different Than in Younger Patients? Analysis of Surgical Management Guided by an Intraoperative Multimodal Approach and Its Impact on Clinical Outcome

OBJECTIVE

Age is considered a negative prognostic factor for High Grade Gliomas (HGGs) and many neurosurgeons remain skeptical about the benefits of aggressive treatment. New surgical and technological improvements may allow extended safe resection, with lower level of post-operative complications. This opportunity opens the unsolved question about the most appropriate HGG treatment in elderly patients. The aim of this study is to analyze if HGG maximal safe resection guided by an intraoperative multimodal imaging protocol coupled with neuromonitoring is associated with differences in outcome in elderly patients versus younger ones.

METHODS

We reviewed 100 patients, 53 (53%) males and 47 (47%) females, with median (IQR) age of 64 (57; 72) years. Eight patients were diagnosed with Anaplastic Astrocytoma (AA), 92 with Glioblastoma (GBM). Surgery was aimed to achieve safe maximal resection. An intraoperative multimodal imaging protocol, including neuronavigation, neurophysiological monitoring, 5-ALA fluorescence, 11C MET-PET, navigated i-US system and i-CT, was used, and its impact on EOTR and clinical outcome in elderly patients was analyzed. We divided patients in two groups according to their age: <65 and >65 years, and surgical and clinical results (EOTR, post-operative KPS, OS and PFS) were compared. Yet, to better understand age-related differences, the same patient cohort was also divided into <70 and >70 years and all the above data reanalyzed.

RESULTS

In the first cohort division, we did not found KPS difference over time and survival analysis did not show significant difference between the two groups (p = 0.36 for OS and p = 0.49 for PFS). Same results were obtained increasing the age cut-off for age up to 70 years (p = 0.52 for OS and p = 0.92 for PFS).

CONCLUSIONS

Our data demonstrate that there is not statistically significant difference in post-operative EOTR, KPS, OS, and PFS between younger and elderly patients treated with extensive tumor resection aided by a intraoperative multimodal protocol.

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

Neuronavigation using pre-operative imaging data for neurosurgical guidance is a ubiquitous tool for the planning and resection of oncologic brain disease. These systems are rendered unreliable when brain shift invalidates the patient-image registration. Our previous review in 2015, Brain shift in neuronavigation of brain tumours: A review offered a new taxonomy, classification system, and a historical perspective on the causes, measurement, and pre- and intra-operative compensation of this phenomenon. Here we present an updated review using the same taxonomy and framework, focused on the developments of intra-operative ultrasound-based brain shift research from 2015 to the present (2020). The review was performed using PubMed to identify articles since 2015 with the specific words and phrases: “Brain shift” AND “Ultrasound”. Since 2015, the rate of publication of intra-operative ultrasound based articles in the context of brain shift has increased from 2–3 per year to 8–10 per year. This efficient and low-cost technology and increasing comfort among clinicians and researchers have allowed unique avenues of development. Since 2015, there has been a trend towards more mathematical advancements in the field which is often validated on publicly available datasets from early intra-operative ultrasound research, and may not give a just representation to the intra-operative imaging landscape in modern image-guided neurosurgery. Focus on vessel-based registration and virtual and augmented reality paradigms have seen traction, offering new perspectives to overcome some of the different pitfalls of ultrasound based technologies. Unfortunately, clinical adaptation and evaluation has not seen as significant of a publication boost. Brain shift continues to be a highly prevalent pitfall in maintaining accuracy throughout oncologic neurosurgical intervention and continues to be an area of active research. Intra-operative ultrasound continues to show promise as an effective, efficient, and low-cost solution for intra-operative accuracy management. A major drawback of the current research landscape is that mathematical tool validation based on retrospective data outpaces prospective clinical evaluations decreasing the strength of the evidence. The need for newer and more publicly available clinical datasets will be instrumental in more reliable validation of these methods that reflect the modern intra-operative imaging in these procedures.

A Review on Advances in Intra-operative Imaging for Surgery and Therapy: Imagining the Operating Room of the Future

With the advent of Minimally Invasive Surgery (MIS), intra-operative imaging has become crucial for surgery and therapy guidance, allowing to partially compensate for the lack of information typical of MIS. This paper reviews the advancements in both classical (i.e. ultrasounds, X-ray, optical coherence tomography and magnetic resonance imaging) and more recent (i.e. multispectral, photoacoustic and Raman imaging) intra-operative imaging modalities. Each imaging modality was analyzed, focusing on benefits and disadvantages in terms of compatibility with the operating room, costs, acquisition time and image characteristics. Tables are included to summarize this information. New generation of hybrid surgical room and algorithms for real time/in room image processing were also investigated. Each imaging modality has its own (site- and procedure-specific) peculiarities in terms of spatial and temporal resolution, field of view and contrasted tissues. Besides the benefits that each technique offers for guidance, considerations about operators and patient risk, costs, and extra time required for surgical procedures have to be considered. The current trend is to equip surgical rooms with multimodal imaging systems, so as to integrate multiple information for real-time data extraction and computer-assisted processing. The future of surgery is to enhance surgeons eye to minimize intra- and after-surgery adverse events and provide surgeons with all possible support to objectify and optimize the care-delivery process.

The state-of-the-art in ultrasound-guided spine interventions

During the last two decades, intra-operative ultrasound (iUS) imaging has been employed for various surgical procedures of the spine, including spinal fusion and needle injections. Accurate and efficient registration of pre-operative computed tomography or magnetic resonance images with iUS images are key elements in the success of iUS-based spine navigation. While widely investigated in research, iUS-based spine navigation has not yet been established in the clinic. This is due to several factors including the lack of a standard methodology for the assessment of accuracy, robustness, reliability, and usability of the registration method. To address these issues, we present a systematic review of the state-of-the-art techniques for iUS-guided registration in spinal image-guided surgery (IGS). The review follows a new taxonomy based on the four steps involved in the surgical workflow that include pre-processing, registration initialization, estimation of the required patient to image transformation, and a visualization process. We provide a detailed analysis of the measurements in terms of accuracy, robustness, reliability, and usability that need to be met during the evaluation of a spinal IGS framework. Although this review is focused on spinal navigation, we expect similar evaluation criteria to be relevant for other IGS applications.

Automatic segmentation of brain tumor resections in intraoperative ultrasound images using U-Net

To compensate for the intraoperative brain tissue deformation, computer-assisted intervention methods have been used to register preoperative magnetic resonance images with intraoperative images. In order to model the deformation due to tissue resection, the resection cavity needs to be segmented in intraoperative images. We present an automatic method to segment the resection cavity in intraoperative ultrasound (iUS) images. We trained and evaluated two-dimensional (2-D) and three-dimensional (3-D) U-Net networks on two datasets of 37 and 13 cases that contain images acquired from different ultrasound systems. The best overall performing method was the 3-D network, which resulted in a 0.72 mean and 0.88 median Dice score over the whole dataset. The 2-D network also had good results with less computation time, with a median Dice score over 0.8. We also evaluated the sensitivity of network performance to training and testing with images from different ultrasound systems and image field of view. In this application, we found specialized networks to be more accurate for processing similar images than a general network trained with all the data. Overall, promising results were obtained for both datasets using specialized networks. This motivates further studies with additional clinical data, to enable training and validation of a clinically viable deep-learning model for automated delineation of the tumor resection cavity in iUS images.

Reliability of intraoperative ultrasound in detecting tumor residual after brain diffuse glioma surgery: a systematic review and meta-analysis

Intraoperative ultrasonography (iUS) is considered an accurate, safe, and cost-effective tool to estimate the extent of resection of both high-grade (HGG) and low-grade (DLGG) diffuse gliomas (DGs). However, it is currently missing an evidence-based assessment of iUS diagnostic accuracy in DGs surgery. The objective of review is to perform a systematic review and meta-analysis of the diagnostic performance of iUS in detecting tumor residue after DGs resection. A comprehensive literature search for studies published through October 2018 was performed according to PRISMA-DTA and STARD 2015 guidelines, using the following algorithm: ("ultrasound" OR "ultrasonography" OR "ultra-so*" OR "echo*" OR "eco*") AND ("brain" OR "nervous") AND ("tumor" OR "tumour" OR "lesion" OR "mass" OR "glio*" OR "GBM") AND ("surgery" OR "surgical" OR "microsurg*" OR "neurosurg*"). Pooled sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR-), and diagnostic odds ratio (DOR) of iUS in DGs were calculated. A subgroup analysis for HGGs and DLGGs was also conducted. Thirteen studies were included in the systematic review (665 DGs). Ten articles (409 DGs) were selected for the meta-analysis with the following results: sensitivity 72.2%, specificity 93.5%, LR- 0.29, LR+ 3, and DOR 9.67. Heterogeneity among studies was non-significant. Subgroup analysis demonstrates a better diagnostic performance of iUS for DLGGs compared with HGGs. iUS is an effective technique in assessing DGs resection. No significant differences are seen regarding iUS modality and transducer characteristics. Its diagnostic performance is higher in DLGGs than HGGs and could be worsened by previous treatments, surgical artifacts, and small tumor residue volumes.

Is supratotal resection achievable in low-grade gliomas? Feasibility, putative factors, safety, and functional outcome

OBJECTIVE

Surgery for low-grade gliomas (LGGs) aims to achieve maximal tumor removal and maintenance of patients' functional integrity. Because extent of resection is one of the factors affecting the natural history of LGGs, surgery could be extended further than total resection toward a supratotal resection, beyond tumor borders detectable on FLAIR imaging. Supratotal resection is highly debated, mainly due to a lack of evidence of its feasibility and safety. The authors explored the intraoperative feasibility of supratotal resection and its short- and long-term impact on functional integrity in a large cohort of patients. The role of some putative factors in the achievement of supratotal resection was also studied.

METHODS

Four hundred forty-nine patients with a presumptive radiological diagnosis of LGG consecutively admitted to the neurosurgical oncology service at the University of Milan over a 5-year period were enrolled. In all patients, a policy was adopted to perform surgery according to functional boundaries, aimed at achieving a supratotal resection whenever possible, without any patient or tumor a priori selection. Feasibility, general safety, and tumor or patient putative factors possibly affecting the achievement of a supratotal resection were analyzed. Postsurgical patient functional performance was evaluated in five cognitive domains (memory, language, praxis, executive functions, and fluid intelligence) using a detailed neuropsychological evaluation and quality of life (QOL) examination.

RESULTS

Total resection was feasible in 40.8% of patients, and supratotal resection in 32.3%. The achievement of a supratotal versus total resection was independent of age, sex, education, tumor volume, deep extension, location, handedness, appearance of tumor border, vicinity to eloquent sites, surgical mapping time, or surgical tools applied. Supratotal resection was associated with a long clinical history and histological grade II, suggesting that reshaping of brain networks occurred. Although a consistent amount of apparently MRI-normal brain was removed with this approach, the procedure was safe and did not carry additional risk to the patient, as demonstrated by detailed neuropsychological evaluation and QOL examination. This approach also improved seizure control.

CONCLUSIONS

Supratotal resection is feasible and safe in routine clinical practice. These results show that a long clinical history may be the main factor associated with its achievement.

Lower Grade Gliomas: Relationships Between Metabolic and Structural Imaging with Grading and Molecular Factors

BACKGROUND

Positron emission tomography (PET) is a valuable tool for the characterization of brain tumors in vivo. However, few studies have investigated the correlation between carbon-11-methionine (11C-METH) PET metrics and the clinical, radiological, histological, and molecular features of patients affected by lower grade gliomas (LGGs). The present observational study evaluated the relationships between 11C-METH PET metrics and structural magnetic resonance imaging (MRI) findings with the histomolecular biomarkers in patients with LGGs who were candidates for surgery.

METHODS

We enrolled 96 patients with pathologically proven LGG (51 men, 45 women; age 44.1 ± 13.7 years; 45 with grade II, 51 with grade III), who had been referred from March 2012 to January 2015 for tumor resection and had undergone preoperative 11C-METH PET. The semiquantitative metrics for 11C-METH PET included maximum standardized uptake value (SUVmax), SUV ratio to normal brain, and metabolic tumor burden (MTB). The PET semiquantitative metrics were analyzed and compared with the MRI features, histological diagnosis, isocitrate dehydrogenase-1/2 status, and 1p/19q codeletion.

RESULTS

Histological grade was associated with SUVmax (P = 0.002), SUV ratio (P = 0.011), and MTB (P = 0.001), with grade III lesions showing higher values. Among the nonenhancing lesions on MRI, SUVmax (P = 0.001), SUV ratio (P = 0.003) and MTB (P < 0.001) were significantly different statistically for grade II versus grade III. The MRI lesion volume correlated poorly with MTB (r² = 0.13). The SUVmax and SUV ratio were greater (P < 0.05) in isocitrate dehydrogenase-1/2 wild-type lesions, and the SUV ratio was associated with the presence of the 1p19q codeletion.

CONCLUSIONS

The 11C-METH PET metrics correlated significantly with histological grade and the molecular profile. Semiquantitative PET metrics can improve the preoperative evaluation of LGGs and thus support clinical decision-making.

Applications of Raman spectroscopy in cancer diagnosis

Novel approaches toward understanding the evolution of disease can lead to the discovery of biomarkers that will enable better management of disease progression and improve prognostic evaluation. Raman spectroscopy is a promising investigative and diagnostic tool that can assist in uncovering the molecular basis of disease and provide objective, quantifiable molecular information for diagnosis and treatment evaluation. This technique probes molecular vibrations/rotations associated with chemical bonds in a sample to obtain information on molecular structure, composition, and intermolecular interactions. Raman scattering occurs when light interacts with a molecular vibration/rotation and a change in polarizability takes place during molecular motion. This results in light being scattered at an optical frequency shifted (up or down) from the incident light. By monitoring the intensity profile of the inelastically scattered light as a function of frequency, the unique spectroscopic fingerprint of a tissue sample is obtained. Since each sample has a unique composition, the spectroscopic profile arising from Raman-active functional groups of nucleic acids, proteins, lipids, and carbohydrates allows for the evaluation, characterization, and discrimination of tissue type. This review provides an overview of the theory of Raman spectroscopy, instrumentation used for measurement, and variation of Raman spectroscopic techniques for clinical applications in cancer, including detection of brain, ovarian, breast, prostate, and pancreatic cancers and circulating tumor cells.

Using the variogram for vector outlier screening: application to feature-based image registration

PURPOSE

Matching points that are derived from features or landmarks in image data is a key step in some medical imaging applications. Since most robust point matching algorithms claim to be able to deal with outliers, users may place high confidence in the matching result and use it without further examination. However, for tasks such as feature-based registration in image-guided neurosurgery, even a few mismatches, in the form of invalid displacement vectors, could cause serious consequences. As a result, having an effective tool by which operators can manually screen all matches for outliers could substantially benefit the outcome of those applications.

METHODS

We introduce a novel variogram-based outlier screening method for vectors. The variogram is a powerful geostatistical tool for characterizing the spatial dependence of stochastic processes. Since the spatial correlation of invalid displacement vectors, which are considered as vector outliers, tends to behave differently than normal displacement vectors, they can be efficiently identified on the variogram.

RESULTS

We validate the proposed method on 9 sets of clinically acquired ultrasound data. In the experiment, potential outliers are flagged on the variogram by one operator and further evaluated by 8 experienced medical imaging researchers. The matching quality of those potential outliers is approximately 1.5 lower, on a scale from 1 (bad) to 5 (good), than valid displacement vectors.

CONCLUSION

The variogram is a simple yet informative tool. While being used extensively in geostatistical analysis, it has not received enough attention in the medical imaging field. We believe there is a good deal of potential for clinically applying the proposed outlier screening method. By way of this paper, we also expect researchers to find variogram useful in other medical applications that involve motion vectors analyses.

SUPRA: open-source software-defined ultrasound processing for real-time applications : A 2D and 3D pipeline from beamforming to B-mode

PURPOSE

Research in ultrasound imaging is limited in reproducibility by two factors: First, many existing ultrasound pipelines are protected by intellectual property, rendering exchange of code difficult. Second, most pipelines are implemented in special hardware, resulting in limited flexibility of implemented processing steps on such platforms.

METHODS

With SUPRA, we propose an open-source pipeline for fully software-defined ultrasound processing for real-time applications to alleviate these problems. Covering all steps from beamforming to output of B-mode images, SUPRA can help improve the reproducibility of results and make modifications to the image acquisition mode accessible to the research community. We evaluate the pipeline qualitatively, quantitatively, and regarding its run time.

RESULTS

The pipeline shows image quality comparable to a clinical system and backed by point spread function measurements a comparable resolution. Including all processing stages of a usual ultrasound pipeline, the run-time analysis shows that it can be executed in 2D and 3D on consumer GPUs in real time.

CONCLUSIONS

Our software ultrasound pipeline opens up the research in image acquisition. Given access to ultrasound data from early stages (raw channel data, radiofrequency data), it simplifies the development in imaging. Furthermore, it tackles the reproducibility of research results, as code can be shared easily and even be executed without dedicated ultrasound hardware.

Experimental study of sector and linear array ultrasound accuracy and the influence of navigated 3D-reconstruction as compared to MRI in a brain tumor model

PURPOSE

Currently, intraoperative ultrasound in brain tumor surgery is a rapidly propagating option in imaging technology. We examined the accuracy and resolution limits of different ultrasound probes and the influence of 3D-reconstruction in a phantom and compared these results to MRI in an intraoperative setting (iMRI).

METHODS

An agarose gel phantom with predefined gel targets was examined with iMRI, a sector (SUS) and a linear (LUS) array probe with two-dimensional images. Additionally, 3D-reconstructed sweeps in perpendicular directions were made of every target with both probes, resulting in 392 measurements. Statistical calculations were performed, and comparative boxplots were generated.

RESULTS

Every measurement of iMRI and LUS was more precise than SUS, while there was no apparent difference in height of iMRI and 3D-reconstructed LUS. Measurements with 3D-reconstructed LUS were always more accurate than in 2D-LUS, while 3D-reconstruction of SUS showed nearly no differences to 2D-SUS in some measurements. We found correlations of 3D-reconstructed SUS and LUS length and width measurements with 2D results in the same image orientation.

CONCLUSIONS

LUS provides an accuracy and resolution comparable to iMRI, while SUS is less exact than LUS and iMRI. 3D-reconstruction showed the potential to distinctly improve accuracy and resolution of ultrasound images, although there is a strong correlation with the sweep direction during data acquisition.

Patient-specific model-based segmentation of brain tumors in 3D intraoperative ultrasound images

PURPOSE

Intraoperative ultrasound (iUS) imaging is commonly used to support brain tumor operation. The tumor segmentation in the iUS images is a difficult task and still under improvement because of the low signal-to-noise ratio. The success of automatic methods is also limited due to the high noise sensibility. Therefore, an alternative brain tumor segmentation method in 3D-iUS data using a tumor model obtained from magnetic resonance (MR) data for local MR-iUS registration is presented in this paper. The aim is to enhance the visualization of the brain tumor contours in iUS.

METHODS

A multistep approach is proposed. First, a region of interest (ROI) based on the specific patient tumor model is defined. Second, hyperechogenic structures, mainly tumor tissues, are extracted from the ROI of both modalities by using automatic thresholding techniques. Third, the registration is performed over the extracted binary sub-volumes using a similarity measure based on gradient values, and rigid and affine transformations. Finally, the tumor model is aligned with the 3D-iUS data, and its contours are represented.

RESULTS

Experiments were successfully conducted on a dataset of 33 patients. The method was evaluated by comparing the tumor segmentation with expert manual delineations using two binary metrics: contour mean distance and Dice index. The proposed segmentation method using local and binary registration was compared with two grayscale-based approaches. The outcomes showed that our approach reached better results in terms of computational time and accuracy than the comparative methods.

CONCLUSION

The proposed approach requires limited interaction and reduced computation time, making it relevant for intraoperative use. Experimental results and evaluations were performed offline. The developed tool could be useful for brain tumor resection supporting neurosurgeons to improve tumor border visualization in the iUS volumes.

Functional MRI for Surgery of Gliomas

PURPOSE OF REVIEW

Advanced neuroimaging techniques such as functional MRI (fMRI) and diffusion MR tractography have been increasingly used at every stage of the surgical management of brain gliomas, as a means to improve tumor resection while preserving brain functions. This review provides an overview of the last advancements in the field of functional MRI techniques, with a particular focus on their current clinical use and reliability in the preoperative and intraoperative setting, as well as their future perspectives for personalized multimodal management of patients with gliomas.

RECENT FINDINGS

fMRI and diffusion MR tractography give relevant insights on the anatomo-functional organization of eloquent cortical areas and subcortical connections near or inside a tumor. Task-based fMRI and diffusion tensor imaging (DTI) tractography have proven to be valid and highly sensitive tools for localizing the distinct eloquent cortical and subcortical areas before surgery in glioma patients; they also show good accuracy when compared with intraoperative stimulation mapping data. Resting-state fMRI functional connectivity as well as new advanced HARDI (high angular resolution diffusion imaging) tractography methods are improving and reshaping the role of functional MRI for surgery of gliomas, with potential benefit for personalized treatment strategies. Noninvasive functional MRI techniques may offer the opportunity to perform a multimodal assessment in brain tumors, to be integrated with intraoperative mapping and clinical data for improving surgical management and oncological and functional outcome in patients affected by gliomas.