Reliability of Functional Magnetic Resonance Imaging in Patients with Brain Tumors: A Critical Review and Meta-Analysis

A deep learning model for the localization and extraction of brain tumors from MR images using YOLOv7 and grab cut algorithm

Introduction

Brain tumors are a common disease that affects millions of people worldwide. Considering the severity of brain tumors (BT), it is important to diagnose the disease in its early stages. With advancements in the diagnostic process, Magnetic Resonance Imaging (MRI) has been extensively used in disease detection. However, the accurate identification of BT is a complex task, and conventional techniques are not sufficiently robust to localize and extract tumors in MRI images. Therefore, in this study, we used a deep learning model combined with a segmentation algorithm to localize and extract tumors from MR images.

Method

This paper presents a Deep Learning (DL)-based You Look Only Once (YOLOv7) model in combination with the Grab Cut algorithm to extract the foreground of the tumor image to enhance the detection process. YOLOv7 is used to localize the tumor region, and the Grab Cut algorithm is used to extract the tumor from the localized region.

Results

The performance of the YOLOv7 model with and without the Grab Cut algorithm is evaluated. The results show that the proposed approach outperforms other techniques, such as hybrid CNN-SVM, YOLOv5, and YOLOv6, in terms of accuracy, precision, recall, specificity, and F1 score.

Discussion

Our results show that the proposed technique achieves a high dice score between tumor-extracted images and ground truth images. The findings show that the performance of the YOLOv7 model is improved by the inclusion of the Grab Cut algorithm compared to the performance of the model without the algorithm.

Intraoperative identification of functional brain areas with RGB imaging using statistical parametric mapping: Simulation and clinical studies

Complementary technique to preoperative fMRI and electrical brain stimulation (EBS) for glioma resection could improve dramatically the surgical procedure and patient care. Intraoperative RGB optical imaging is a technique for localizing functional areas of the human cerebral cortex that can be used during neurosurgical procedures. However, it still lacks robustness to be used with neurosurgical microscopes as a clinical standard. In particular, a robust quantification of biomarkers of brain functionality is needed to assist neurosurgeons. We propose a methodology to evaluate and optimize intraoperative identification of brain functional areas by RGB imaging. This consist in a numerical 3D brain model based on Monte Carlo simulations to evaluate intraoperative optical setups for identifying functional brain areas. We also adapted fMRI Statistical Parametric Mapping technique to identify functional brain areas in RGB videos acquired for 12 patients. Simulation and experimental results were consistent and showed that the intraoperative identification of functional brain areas is possible with RGB imaging using deoxygenated hemoglobin contrast. Optical functional identifications were consistent with those provided by EBS and preoperative fMRI. We also demonstrated that a halogen lighting may be particularity adapted for functional optical imaging. We showed that an RGB camera combined with a quantitative modeling of brain hemodynamics biomarkers can evaluate in a robust way the functional areas during neurosurgery and serve as a tool of choice to complement EBS and fMRI.

Maximal safe resection of diffuse lower grade gliomas primarily within central lobe using cortical/subcortical direct electrical stimulation under awake craniotomy

Background

Diffuse lower-grade glioma (DLGG) in the central lobe is a challenge for safe resection procedures. To improve the extent of resection and reduce the risk of postoperative neurological deficits, we performed an awake craniotomy with cortical-subcortical direct electrical stimulation (DES) mapping for patients with DLGG located primarily within the central lobe. We investigated the outcomes of cortical-subcortical brain mapping using DES in an awake craniotomy for central lobe DLGG resection.

Methods

We performed a retrospective analysis of clinical data of a cohort of consecutively treated patients from February 2017 to August 2021 with diffuse lower-grade gliomas located primarily within the central lobe. All patients underwent awake craniotomy with DES for cortical and subcortical mapping of eloquent brain areas, neuronavigation, and/or ultrasound to identify tumor location. Tumors were removed according to functional boundaries. Maximum safe tumor resection was the surgical objective for all patients.

Results

Thirteen patients underwent 15 awake craniotomies with intraoperative mapping of eloquent cortices and subcortical fibers using DES. Maximum safe tumor resection was achieved according to functional boundaries in all patients. The pre-operative tumor volumes ranged from 4.3 cm³ to 137.3 cm³ (median 19.2 cm³). The mean extent of tumor resection was 94.6%, with eight cases (53.3%) achieving total resection, four (26.7%) subtotal and three (20.0%) partial. The mean tumor residue was 1.2 cm³. All patients experienced early postoperative neurological deficits or worsening conditions. Three patients (20.0%) experienced late postoperative neurological deficits at the 3-month follow-up, including one moderate and two mild neurological deficits. None of the patients experienced late onset severe neurological impairments post-operatively. Ten patients with 12 tumor resections (80.0%) had resumed activities of daily living at the 3-month follow-up. Among 14 patients with pre-operative epilepsy, 12 (85.7%) were seizure-free after treatment with antiepileptic drugs 7 days after surgery up to the last follow-up.

Conclusions

DLGG located primarily in the central lobe deemed inoperable can be safely resected using awake craniotomy with intraoperative DES without severe permanent neurological sequelae. Patients experienced an improved quality of life in terms of seizure control.

Simultaneous electroencephalography-functional magnetic resonance imaging for assessment of human brain function

Electroencephalography (EEG) and functional Magnetic Resonance Imaging (MRI) have long been used as tools to examine brain activity. Since both methods are very sensitive to changes of synaptic activity, simultaneous recording of EEG and fMRI can provide both high temporal and spatial resolution. Therefore, the two modalities are now integrated into a hybrid tool, EEG-fMRI, which encapsulates the useful properties of the two. Among other benefits, EEG-fMRI can contribute to a better understanding of brain connectivity and networks. This review lays its focus on the methodologies applied in performing EEG-fMRI studies, namely techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. We will investigate simultaneous resting-state and task-based EEG-fMRI studies and discuss their clinical and technological perspectives. Moreover, it is established that the brain regions affected by a task-based neural activity might not be limited to the regions in which they have been initiated. Advanced methods can help reveal the regions responsible for or affected by a developed neural network. Therefore, we have also looked into studies related to characterization of structure and dynamics of brain networks. The reviewed literature suggests that EEG-fMRI can provide valuable complementary information about brain neural networks and functions.

What Can Resting-State fMRI Data Analysis Explain about the Functional Brain Connectivity in Glioma Patients?

Resting-state functional MRI has been increasingly implemented in imaging protocols for the study of functional connectivity in glioma patients as a sequence able to capture the activity of brain networks and to investigate their properties without requiring the patients’ cooperation. The present review aims at describing the most recent results obtained through the analysis of resting-state fMRI data in different contexts of interest for brain gliomas: the identification and localization of functional networks, the characterization of altered functional connectivity, and the evaluation of functional plasticity in relation to the resection of the glioma. An analysis of the literature showed that significant and promising results could be achieved through this technique in all the aspects under investigation. Nevertheless, there is room for improvement, especially in terms of stability and generalizability of the outcomes. Further research should be conducted on homogeneous samples of glioma patients and at fixed time points to reduce the considerable variability in the results obtained across and within studies. Future works should also aim at establishing robust metrics for the assessment of the disruption of functional connectivity and its recovery at the single-subject level.

Functional Approaches to the Surgery of Brain Gliomas

In the surgery of gliomas, recent years have witnessed unprecedented theoretical and technical development, which extensively increased indication to surgery. On one hand, it has been solidly demonstrated the impact of gross total resection on life expectancy. On the other hand, the paradigm shift from classical cortical localization of brain function towards connectomics caused by the resurgence of awake surgery and the advent of tractography has permitted safer surgeries focused on subcortical white matter tracts preservation and allowed for surgical resections within regions, such as Broca's area or the primary motor cortex, which were previously deemed inoperable. Furthermore, new asleep electrophysiological techniques have been developed whenever awake surgery is not an option, such as operating in situations of poor compliance (including paediatric patients) or pre-existing neurological deficits. One such strategy is the use of intraoperative neurophysiological monitoring (IONM), enabling the identification and preservation of functionally defined, but anatomically ambiguous, cortico-subcortical structures through mapping and monitoring techniques. These advances tie in with novel challenges, specifically risk prediction and the impact of neuroplasticity, the indication for tumour resection beyond visible borders, or supratotal resection, and most of all, a reappraisal of the importance of the right hemisphere from early psychosurgery to mapping and preservation of social behaviour, executive control, and decision making.Here we review current advances and future perspectives in a functional approach to glioma surgery.

Current and Future Challenges of Functional MRI and Diffusion Tractography in the Surgical Setting: From Eloquent Brain Mapping to Neural Plasticity

Decades ago, Spetzler (1986) and Sawaya (1998) provided a rough brain segmentation of the eloquent areas of the brain, aimed to help surgical decisions in cases of vascular malformations and tumors, respectively. Currently in clinical use, their criteria are in need of revision. Defining functions (eg, sensorimotor, language and visual) that should be preserved during surgery seems a straightforward task. In practice, locating the specific areas that could cause a permanent vs transient deficit is not an easy task. This is particularly true for the associative cortex and cognitive domains such as language. The old model, with Broca's and Wernicke's areas at the forefront, has been superseded by a dual-stream model of parallel language processing; named ventral and dorsal pathways. This complicated network of cortical hubs and subcortical white matter pathways needing preservation during surgery is a work in progress. Preserving not only cortical regions but most importantly preserving the connections, or white matter fiber bundles, of core regions in the brain is the new paradigm. For instance, the arcuate fascicululs and inferior fronto-occipital fasciculus are key components of the dorsal and ventral language pathways, respectively; and their damage result in permanent language deficits. Interestedly, the damage of the temporal portions of these bundles -where there is a crossroad with other multiple bundles-, appears to be more important (permanent) than the damage of the frontal portions - where plasticity and contralateral activation could help. Although intraoperative direct cortical and subcortical stimulation have contributed largely, advanced MR techniques such as functional MRI (fMRI) and diffusion tractography (DT), are at the epi-center of our current understanding. Nevertheless, these techniques posse important challenges: such as neurovascular uncoupling or venous bias on fMRI; and appropriate anatomical validation or accurate representation of crossing fibers on DT. These limitations should be well understood and taken into account in clinical practice. Unifying multidisciplinary research and clinical efforts is desirable, so these techniques could contribute more efficiently not only to locate eloquent areas but to improve outcomes and our understanding of neural plasticity. Finally, although there are constant anatomical and functional regions at the individual level, there is a known variability at the inter-individual level. This concept should strengthen the importance of a personalized approach when evaluating these regions on fMRI and DT. It should strengthen the importance of personalized treatments as well, aimed to meet tailored needs and expectations.

Structural and Functional Imaging in Glioma Management

The goal of glioma surgery is maximal safe resection in order to provide optimal tumor control and survival benefit to the patient. There are multiple imaging modalities beyond traditional contrast-enhanced magnetic resonance imaging (MRI) that have been incorporated into the preoperative workup of patients presenting with gliomas. The aim of these imaging modalities is to identify cortical and subcortical areas of eloquence, and their relationship to the lesion. In this article, multiple modalities are described with an emphasis on the underlying technology, clinical utilization, advantages, and disadvantages of each. functional MRI and its role in identifying hemispheric dominance and areas of language and motor are discussed. The nuances of magnetoencephalography and transcranial magnetic stimulation in localization of eloquent cortex are examined, as well as the role of diffusion tensor imaging in defining normal white matter tracts in glioma surgery. Lastly, we highlight the role of stimulated Raman spectroscopy in intraoperative histopathological diagnosis of tissue to guide tumor resection. Tumors may shift the normal arrangement of functional anatomy in the brain; thus, utilization of multiple modalities may be helpful in operative planning and patient counseling for successful surgery.

Feasibility, Contrast Sensitivity and Network Specificity of Language fMRI in Presurgical Evaluation for Epilepsy and Brain Tumor Surgery

Language fMRI has become an integral part of the planning process in brain surgery. However, fMRI may suffer from confounding factors both on the patient side, as well as on the provider side. In this study, we investigate how patient-related confounds affect the ability of the patient to perform language fMRI tasks (feasibility), the task sensitivity from an image contrast point of view, and the anatomical specificity of expressive and receptive language fMRI protocols. 104 patients were referred for language fMRI in the context of presurgical procedures for epilepsy and brain tumor surgery. Four tasks were used: (1) a verbal fluency (VF) task to map vocabulary use, (2) a semantic description (SD) task to map sentence formation/semantic integration skills, (3) a reading comprehension (RC) task and (4) a listening comprehension (LC) task. Feasibility was excellent in the LC task (100%), but in the acceptable to mediocre range for the rest of the tasks (SD: 87.50%, RC: 85.57%, VF: 67.30%). Feasibility was significantly confounded by age (p = 0.020) and education level (p = 0.003) in VF, by education level (p = 0.004) and lesion laterality (p = 0.019) in SD and by age (p = 0.001), lesion laterality (p = 0.007) and lesion severity (p = 0.048) in RC. All tasks were comparable regarding sensitivity in generating statistically significant image contrast (VF: 90.00%, SD: 92.30%, RC: 93.25%, LC: 88.46%). The lobe of the lesion (p = 0.005) and the age (p = 0.009) confounded contrast sensitivity in the VF and SD tasks respectively. Both VF and LC tasks demonstrated unilateral lateralization of posterior language areas; only the LC task showed unilateral lateralization of anterior language areas. Our study highlights the effects of patient-related confounding factors on language fMRI and proposes LC as the most feasible, less confounded, and efficiently lateralizing task in the clinical presurgical context.

Good neighbors, bad neighbors: the frequent network neighborhood mapping of the hippocampus enlightens several structural factors of the human intelligence on a 414-subject cohort

The human connectome has become the very frequent subject of study of brain-scientists, psychologists and imaging experts in the last decade. With diffusion magnetic resonance imaging techniques, united with advanced data processing algorithms, today we are able to compute braingraphs with several hundred, anatomically identified nodes and thousands of edges, corresponding to the anatomical connections of the brain. The analysis of these graphs without refined mathematical tools is hopeless. These tools need to address the high error rate of the MRI processing workflow, and need to find structural causes or at least correlations of psychological properties and cerebral connections. Until now, structural connectomics was only rarely able of identifying such causes or correlations. In the present work we study the frequent neighbor sets of the most deeply investigated brain area, the hippocampus. By applying the Frequent Network Neighborhood mapping method, we identified frequent neighbor-sets of the hippocampus, which may influence numerous psychological parameters, including intelligence-related ones. We have found "Good Neighbor" sets, which correlate with better test results and also "Bad Neighbor" sets, which correlate with worse test results. Our study utilizes the braingraphs, computed from the imaging data of the Human Connectome Project's 414 subjects, each with 463 anatomically identified nodes.

Pediatric Functional Neuroimaging: Practical Tips and Pearls

OBJECTIVE. Functional MRI (fMRI) is clinically used for localization of eloquent cortex before surgical intervention, most commonly motor and language function in patients with tumors or epilepsy. In the pediatric population, special considerations for fMRI relate to limited examination tolerance, small head size, developing anatomy and physiology, and diverse potential abnormalities. In this article, we will highlight pearls and pitfalls of clinical pediatric fMRI including blood oxygenation level-dependent imaging principles, patient preparation, study acquisition, data postprocessing, and examination interpretation. CONCLUSION. Clinical fMRI is indicated for presurgical localization of eloquent cortex in patients with tumors, epilepsy, or other neurologic conditions and requires a solid understanding of technical considerations and data processing. In children, special approaches are needed for patient preparation as well as study design, acquisition, and interpretation. Radiologists should be cognizant of developmental neuroanatomy, causes of neuropathology, and capacity for neuroplasticity in the pediatric population.

Limitations of functional neuroimaging for patient selection and surgical planning in glioma surgery

The optimal surgical management of gliomas requires a balance between surgical cytoreduction and preservation of neurological function. Preoperative functional neuroimaging, such as functional MRI (fMRI) and diffusion tensor imaging (DTI), has emerged as a possible tool to inform patient selection and surgical planning. However, evidence that preoperative fMRI or DTI improves extent of resection, limits neurological morbidity, and broadens surgical indications in classically eloquent areas is lacking. In this review, the authors describe facets of functional neuroimaging techniques that may limit their impact on neurosurgical oncology and critically evaluate the evidence supporting fMRI and DTI for patient selection and operative planning in glioma surgery. The authors also propose alternative applications for functional neuroimaging in the care of glioma patients.

Simultaneous EEG-fMRI for Functional Neurological Assessment

The increasing incidence of neurodegenerative and psychiatric diseases requires increasingly sophisticated tools for their diagnosis and monitoring. Clinical assessment takes advantage of objective parameters extracted by electroencephalogram and magnetic resonance imaging (MRI) among others, to support clinical management of neurological diseases. The complementarity of these two tools can be now emphasized by the possibility of integrating the two technologies in a hybrid solution, allowing simultaneous acquisition of the two signals by the novel EEG-fMRI technology. This review will focus on simultaneous EEG-fMRI technology and related early studies, dealing about issues related to the acquisition and processing of simultaneous signals, and including critical discussion about clinical and technological perspectives.