Personalized fMRI delineates functional regions preserved within brain tumors

Efficacy and Safety of High-Dose TBS on Poststroke Upper Extremity Motor Impairment: A Randomized Controlled Trial

BACKGROUND

Upper extremity (UE) motor function impairment is a major poststroke complication whose recovery remains one of the most challenging tasks in neurological rehabilitation. This study examined the efficacy and safety of the personalized neuroimaging-guided high-dose theta-burst stimulation (TBS) for poststroke UE motor function recovery.

METHODS

Patients after stroke with UE motor impairment from a China rehabilitation center were randomly assigned to receive high-dose intermittent TBS (iTBS) to ipsilesional UE sensorimotor network, continuous TBS (cTBS) to contralesional UE sensorimotor network, or sham stimulation, along with conventional therapy for 3 weeks. The primary outcome was the score changes on the Fugl-Meyer assessment-UE from baseline to 1 and 3 weeks. The secondary outcomes included the response rate on Fugl-Meyer assessment-UE scores posttreatment (≥9-point improvement) and score changes in multidimensional scales measuring UE, lower extremity, and activities and participation.

RESULTS

From June 2021 to June 2022, 45 participants were randomized and 43 were analyzed. The iTBS and continuous TBS groups showed significantly greater improvement in Fugl-Meyer assessment-UE (mean improvement, iTBS: 10.73 points; continuous TBS: 10.79 points) than the sham group (2.43 points) and exhibited significantly greater response rates on Fugl-Meyer assessment-UE (iTBS, 60.0%; continuous TBS, 64.3%) than the sham group (0.0%). The active groups consistently exhibited superior improvement on the other 2 UE assessments at week 3. However, only the iTBS group showed greater efficacy on 1 lower extremity assessment than the sham group at week 3. Both active groups showed significant improvements in activities and participation assessments.

CONCLUSIONS

The study provides evidence for the efficacy and safety of high-dose TBS in facilitating poststroke UE rehabilitation.

REGISTRATION

URL: www.chictr.org.cn; Unique identifier: ChiCTR2100047340.

Predictors of cognition after glioma surgery: connectotomy, structure-function phenotype, plasticity

Determining preoperatively the maximal extent of resection that would preserve cognitive functions is the core challenge of brain tumour surgery. Over the past decade, the methodological framework to achieve this goal has been thoroughly renewed: the population-level topographically-focused voxel-based lesion-symptom mapping has been progressively overshadowed by machine learning (ML) algorithmics, in which the problem is framed as predicting cognitive outcomes in a patient-specific manner from a typically large set of variables. However, the choice of these predictors is of utmost importance, as they should be both informative and parsimonious. In this perspective, we first introduce the concept of connectotomy: instead of parameterizing resection topography through the status (intact/resected) of a huge number of voxels (or parcels) paving the whole brain in the Cartesian 3D-space, the connectotomy models the resection in the connectivity space, by computing a handful number of networks disconnection indices, measuring how the structural connectivity sustaining each network of interest was hit by the resection. This connectivity-informed reduction of dimensionality is a necessary step for efficiently implementing ML tools, given the relatively small number of patient-examples in available training datasets. We further argue that two other major sources of interindividual variability must be considered to improve the accuracy with which outcomes are predicted: the underlying structure-function phenotype and neuroplasticity, for which we provide an in-depth review and propose new ways of determining relevant predictors. We finally discuss the benefits of our approach for precision surgery of glioma.

The promise of precision functional mapping for neuroimaging in psychiatry

Precision functional mapping (PFM) is a neuroimaging approach to reliably estimate metrics of brain function from individual people via the collection of large amounts of fMRI data (hours per person). This method has revealed much about the inter-individual variation of functional brain networks. While standard group-level studies, in which we average brain measures across groups of people, are important in understanding the generalizable neural underpinnings of neuropsychiatric disorders, many disorders are heterogeneous in nature. This heterogeneity often complicates clinical care, leading to patient uncertainty when considering prognosis or treatment options. We posit that PFM methods may help streamline clinical care in the future, fast-tracking the choice of personalized treatment that is most compatible with the individual. In this review, we provide a history of PFM studies, foundational results highlighting the benefits of PFM methods in the pursuit of an advanced understanding of individual differences in functional network organization, and possible avenues where PFM can contribute to clinical translation of neuroimaging research results in the way of personalized treatment in psychiatry.

Predicting brain age using Tri-UNet and various MRI scale features

In the process of human aging, significant age-related changes occur in brain tissue. To assist individuals in assessing the degree of brain aging, screening for disease risks, and further diagnosing age-related diseases, it is crucial to develop an accurate method for predicting brain age. This paper proposes a multi-scale feature fusion method called Tri-UNet based on the U-Net network structure, as well as a brain region information fusion method based on multi-channel input networks. These methods address the issue of insufficient image feature learning in brain neuroimaging data. They can effectively utilize features at different scales of MRI and fully leverage feature information from different regions of the brain. In the end, experiments were conducted on the Cam-CAN dataset, resulting in a minimum Mean Absolute Error (MAE) of 7.46. The results demonstrate that this method provides a new approach to feature learning at different scales in brain age prediction tasks, contributing to the advancement of the field and holding significance for practical applications in the context of elderly education.

Functional connectome through the human life span

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimer's disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.

Personalised functional imaging-guided multitarget continuous theta burst stimulation for post-stroke aphasia: study protocol for a randomised controlled trial

INTRODUCTION

Continuous theta burst stimulation (cTBS), a form of repetitive transcranial magnetic stimulation (rTMS), targeting the language network in the right hemisphere of post-stroke aphasia (PSA) patients shows promising results in clinical trials. However, existing PSA studies have focused on single-target rTMS, leaving unexplored the potential benefits of multitarget brain stimulation. Consequently, there is a need for a randomised clinical trial aimed to evaluate the efficacy and safety of cTBS targeting on multiple critical nodes in the language network for PSA.

METHODS AND ANALYSIS

This is a prospective, multicentre, double-blind, two-arm parallel-group, sham-controlled randomised trial. The study will include a total of 60 participants who will be randomly assigned in a 1:1 ratio to either the active cTBS group or the sham cTBS group. Using precision resting-state functional MRI for each participant, we will map personalised language networks and design personalised targets in the inferior frontal gyrus, superior temporal gyrus and superior frontal gyrus. Participants will undergo a 3-week cTBS intervention targeting the three personalised targets, coupled with speech and language therapy. The primary outcome is the change in the Western Aphasia Battery-Revised aphasia quotient score among participants after a 3-week treatment. Secondary outcomes include Boston Diagnostic Aphasia Examination severity ratings, Token Test and the Chinese-version of the Stroke and Aphasia Quality of Life Scale 39-generic version.

ETHICS AND DISSEMINATION

The study has been approved by the ethics committees of Affiliated Hospital of Hebei University, Hebei General Hospital and Affiliated Hospital of Chengde Medical University. The findings of this study will be reported in peer-reviewed scientific journals.

TRIAL REGISTRATION NUMBER

The study has been registered on ClinicalTrials.gov (NCT05957445).

Verbal memory network mapping in individual patients predicts postoperative functional impairments

Verbal memory decline is a significant concern following temporal lobe surgeries in patients with epilepsy, emphasizing the need for precision presurgical verbal memory mapping to optimize functional outcomes. However, the inter-individual variability in functional networks and brain function-structural dissociations pose challenges when relying solely on group-level atlases or anatomical landmarks for surgical guidance. Here, we aimed to develop and validate a personalized functional mapping technique for verbal memory using precision resting-state functional MRI (rs-fMRI) and neurosurgery. A total of 38 patients with refractory epilepsy scheduled for surgical interventions were enrolled and 28 patients were analyzed in the study. Baseline 30-min rs-fMRI scanning, verbal memory and language assessments were collected for each patient before surgery. Personalized verbal memory networks (PVMN) were delineated based on preoperative rs-fMRI data for each patient. The accuracy of PVMN was assessed by comparing post-operative functional impairments and the overlapping extent between PVMN and surgical lesions. A total of 14 out of 28 patients experienced clinically meaningful declines in verbal memory after surgery. The personalized network and the group-level atlas exhibited 100% and 75.0% accuracy in predicting postoperative verbal memory declines, respectively. Moreover, six patients with extra-temporal lesions that overlapped with PVMN showed selective impairments in verbal memory. Furthermore, the lesioned ratio of the personalized network rather than the group-level atlas was significantly correlated with postoperative declines in verbal memory (personalized networks: r = -0.39, p = .038; group-level atlas: r = -0.19, p = .332). In conclusion, our personalized functional mapping technique, using precision rs-fMRI, offers valuable insights into individual variability in the verbal memory network and holds promise in precision verbal memory network mapping in individuals.

Tumour-infiltrated cortex participates in large-scale cognitive circuits

The extent to which tumour-infiltrated brain tissue contributes to cognitive function remains unclear. We tested the hypothesis that cortical tissue infiltrated by diffuse gliomas participates in large-scale cognitive circuits using a unique combination of intracranial electrocorticography (ECoG) and resting-state functional magnetic resonance (fMRI) imaging in four patients. We also assessed the relationship between functional connectivity with tumour-infiltrated tissue and long-term cognitive outcomes in a larger, overlapping cohort of 17 patients. We observed significant task-related high gamma (70-250 Hz) power modulations in tumour-infiltrated cortex in response to increased cognitive effort (i.e., switch counting compared to simple counting), implying preserved functionality of neoplastic tissue for complex tasks probing executive function. We found that tumour locations corresponding to task-responsive electrodes exhibited functional connectivity patterns that significantly co-localised with canonical brain networks implicated in executive function. Specifically, we discovered that tumour-infiltrated cortex with larger task-related high gamma power modulations tended to be more functionally connected to the dorsal attention network (DAN). Finally, we demonstrated that tumour-DAN connectivity is evident across a larger cohort of patients with gliomas and that it relates to long-term postsurgical outcomes in goal-directed attention. Overall, this study contributes convergent fMRI-ECoG evidence that tumour-infiltrated cortex participates in large-scale neurocognitive circuits that support executive function in health. These findings underscore the potential clinical utility of mapping large-scale connectivity of tumour-infiltrated tissue in the care of patients with diffuse gliomas.

Shared and malignancy-specific functional plasticity of dynamic brain properties for patients with left frontal glioma

The time-varying brain activity may parallel the disease progression of cerebral glioma. Assessment of brain dynamics would better characterize the pathological profile of glioma and the relevant functional remodeling. This study aims to investigate the dynamic properties of functional networks based on sliding-window approach for patients with left frontal glioma. The generalized functional plasticity due to glioma was characterized by reduced dynamic amplitude of low-frequency fluctuation of somatosensory networks, reduced dynamic functional connectivity between homotopic regions mainly involving dorsal attention network and subcortical nuclei, and enhanced subcortical dynamic functional connectivity. Malignancy-specific functional remodeling featured a chaotic modification of dynamic amplitude of low-frequency fluctuation and dynamic functional connectivity for low-grade gliomas, and attenuated dynamic functional connectivity of the intrahemispheric cortico-subcortical connections and reduced dynamic amplitude of low-frequency fluctuation of the bilateral caudate for high-grade gliomas. Network dynamic activity was clustered into four distinct configuration states. The occurrence and dwell time of the weakly connected state were reduced in patients' brains. Support vector machine model combined with predictive dynamic features achieved an averaged accuracy of 87.9% in distinguishing low- and high-grade gliomas. In conclusion, dynamic network properties are highly predictive of the malignant grade of gliomas, thus could serve as new biomarkers for disease characterization.

The involvement of brain regions associated with lower KPS and shorter survival time predicts a poor prognosis in glioma

Background

Isocitrate dehydrogenase-wildtype glioblastoma (IDH-wildtype GBM) and IDH-mutant astrocytoma have distinct biological behaviors and clinical outcomes. The location of brain tumors is closely associated not only with clinical symptoms and prognosis but also with key molecular alterations such as IDH. Therefore, we hypothesize that the key brain regions influencing the prognosis of glioblastoma and astrocytoma are likely to differ. This study aims to (1) identify specific regions that are associated with the Karnofsky Performance Scale (KPS) or overall survival (OS) in IDH-wildtype GBM and IDH-mutant astrocytoma and (2) test whether the involvement of these regions could act as a prognostic indicator.

Methods

A total of 111 patients with IDH-wildtype GBM and 78 patients with IDH-mutant astrocytoma from the Cancer Imaging Archive database were included in the study. Voxel-based lesion-symptom mapping (VLSM) was used to identify key brain areas for lower KPS and shorter OS. Next, we analyzed the structural and cognitive dysfunction associated with these regions. The survival analysis was carried out using Kaplan-Meier survival curves. Another 72 GBM patients and 48 astrocytoma patients from Harbin Medical University Cancer Hospital were used as a validation cohort.

Results

Tumors located in the insular cortex, parahippocampal gyrus, and middle and superior temporal gyrus of the left hemisphere tended to lead to lower KPS and shorter OS in IDH-wildtype GBM. The regions that were significantly correlated with lower KPS in IDH-mutant astrocytoma included the subcallosal cortex and cingulate gyrus. These regions were associated with diverse structural and cognitive impairments. The involvement of these regions was an independent predictor for shorter survival in both GBM and astrocytoma.

Conclusion

This study identified the specific regions that were significantly associated with OS or KPS in glioma. The results may help neurosurgeons evaluate patient survival before surgery and understand the pathogenic mechanisms of glioma in depth.

Personalized functional imaging-guided rTMS on the superior frontal gyrus for post-stroke aphasia: A randomized sham-controlled trial

BACKGROUND

Aphasia affects approximately one-third of stroke patients and yet its rehabilitation outcomes are often unsatisfactory. More effective strategies are needed to promote recovery.

OBJECTIVE

We aimed to examine the efficacy and safety of the theta-burst stimulation (TBS) on the language area in the superior frontal gyrus (SFG) localized by personalized functional imaging, in facilitating post-stroke aphasia recovery.

METHODS

This randomized sham-controlled trial uses a parallel design (intermittent TBS [iTBS] in ipsilesional hemisphere vs. continuous TBS [cTBS] in contralesional hemisphere vs. sham group). Participants had aphasia symptoms resulting from their first stroke in the left hemisphere at least one month prior. Participants received three-week speech-language therapy coupled with either active or sham stimulation applied to the left or right SFG. The primary outcome was the change in Western Aphasia Battery-Revised (WAB-R) aphasia quotient after the three-week treatment. The secondary outcome was WAB-R aphasia quotient improvement after one week of treatment.

RESULTS

Ninety-seven patients were screened between January 2021 and January 2022, 45 of whom were randomized and 44 received intervention (15 in each active group, 14 in sham). Both iTBS (estimated difference = 14.75, p < 0.001) and cTBS (estimated difference = 13.43, p < 0.001) groups showed significantly greater improvement than sham stimulation after the 3-week intervention and immediately after one week of treatment (p's < 0.001). The adverse events observed were similar across groups. A seizure was recorded three days after the termination of the treatment in the iTBS group.

CONCLUSION

The stimulation showed high efficacy and SFG is a promising stimulation target for post-stroke language recovery.

Alteration of default mode network: association with executive dysfunction in frontal glioma patients

OBJECTIVE

Patients with frontal gliomas often experience executive dysfunction (EF-D) before surgery, and the changes in brain plasticity underlying this effect remain obscure. In this study, the authors aimed to assess whole-brain structural and functional alterations by using structural MRI and resting-state functional MRI (rs-fMRI) in frontal glioma patients with or without EF-D.

METHODS

Fifty-seven patients with frontal gliomas were admitted prospectively to the authors' institution and assigned to one of two groups: 1) the normal executive function (EF-N) group and 2) the EF-D group, based on patient results for the Trail Making Test, Part B and Stroop Color-Word Test, Part C. Twenty-nine baseline-matched healthy controls were also recruited. All participants underwent multimodal MRI examination. Cortical surface thickness, surface-based resting-state activity (fractional amplitude of low-frequency fluctuation [fALFF] and regional homogeneity [ReHo]), and edge-based network functional connectivity (FC) were measured with FreeSurfer and fMRIPrep. The correlation between altered MRI parameters and executive function (EF) was assessed using Pearson correlation and receiver operating characteristic (ROC) analysis.

RESULTS

Demographic characteristics (sex, age, and education level) and clinical characteristics (location, volume, grade of tumor, and preoperative epilepsy) were not significantly different between the groups, but the Karnofsky Performance Scale score was worse in the EF-D group. There was no significant difference in cortical surface thickness between the EF-D and EF-N groups. In both low-grade and high-grade glioma patients the fALFF value (permutation test + threshold-free cluster enhancement, p value after family-wise error correction < 0.05) and ReHo value (t-test, p < 0.001) of the left precuneus cortex in the EF-D group were greater than those in the EF-N group, which were negatively correlated with EF (p < 0.05) and enabled prediction of EF (area under the ROC curve 0.826 for fALFF and 0.855 for ReHo, p < 0.001). Compared with the EF-N group, the FCs between the default mode network (DMN) from DMN node to DMN node (DMN-DMN) and from the DMN to the central executive network (DMN-CEN) in the EF-D group were increased significantly (network-based statistics corrected p < 0.05) and negatively correlated with EF (Pearson correlation, p < 0.05).

CONCLUSIONS

Apart from local disruption, the abnormally activated DMN in the resting state is related to EF-D in frontal glioma patients. DMN activity should be considered during preoperative planning and postoperative neurorehabilitation for frontal glioma patients to preserve EF. Clinical trial registration no.: NCT03087838 (ClinicalTrials.gov).

Abnormal metabolic connectivity in default mode network of right temporal lobe epilepsy

Aims

Temporal lobe epilepsy (TLE) is a common neurological disorder associated with the dysfunction of the default mode network (DMN). Metabolic connectivity measured by 18F-fluorodeoxyglucose Positron Emission Computed Tomography (18F-FDG PET) has been widely used to assess cumulative energy consumption and provide valuable insights into the pathophysiology of TLE. However, the metabolic connectivity mechanism of DMN in TLE is far from fully elucidated. The present study investigated the metabolic connectivity mechanism of DMN in TLE using 18F-FDG PET.

Method

Participants included 40 TLE patients and 41 health controls (HC) who were age- and gender-matched. A weighted undirected metabolic network of each group was constructed based on 14 primary volumes of interest (VOIs) in the DMN, in which Pearson's correlation coefficients between each pair-wise of the VOIs were calculated in an inter-subject manner. Graph theoretic analysis was then performed to analyze both global (global efficiency and the characteristic path length) and regional (nodal efficiency and degree centrality) network properties.

Results

Metabolic connectivity in DMN showed that regionally networks changed in the TLE group, including bilateral posterior cingulate gyrus, right inferior parietal gyrus, right angular gyrus, and left precuneus. Besides, significantly decreased (P < 0.05, FDR corrected) metabolic connections of DMN in the TLE group were revealed, containing bilateral hippocampus, bilateral posterior cingulate gyrus, bilateral angular gyrus, right medial of superior frontal gyrus, and left inferior parietal gyrus.

Conclusion

Taken together, the present study demonstrated the abnormal metabolic connectivity in DMN of TLE, which might provide further insights into the understanding the dysfunction mechanism and promote the treatment for TLE patients.

Task-Based and Resting-State Functional MRI in Observing Eloquent Cerebral Areas Personalized for Epilepsy and Surgical Oncology Patients: A Review of the Current Evidence

Functional magnetic resonance imaging (fMRI) is among the newest techniques of advanced neuroimaging that offer the opportunity for neuroradiologists, neurophysiologists, neuro-oncologists, and neurosurgeons to pre-operatively plan and manage different types of brain lesions. Furthermore, it plays a fundamental role in the personalized evaluation of patients with brain tumors or patients with an epileptic focus for preoperative planning. While the implementation of task-based fMRI has increased in recent years, the existing resources and evidence related to this technique are limited. We have, therefore, conducted a comprehensive review of the available resources to compile a detailed resource for physicians who specialize in managing patients with brain tumors and seizure disorders. This review contributes to the existing literature because it highlights the lack of studies on fMRI and its precise role and applicability in observing eloquent cerebral areas in surgical oncology and epilepsy patients, which we believe is underreported. Taking these considerations into account would help to better understand the role of this advanced neuroimaging technique and, ultimately, improve patient life expectancy and quality of life.

Fast cortical surface reconstruction from MRI using deep learning

Reconstructing cortical surfaces from structural magnetic resonance imaging (MRI) is a prerequisite for surface-based functional and anatomical image analyses. Conventional algorithms for cortical surface reconstruction are computationally inefficient and typically take several hours for each subject, causing a bottleneck in applications when a fast turnaround time is needed. To address this challenge, we propose a fast cortical surface reconstruction (FastCSR) pipeline by leveraging deep machine learning. We trained our model to learn an implicit representation of the cortical surface in volumetric space, termed the “level set representation”. A fast volumetric topology correction method and a topology-preserving surface mesh extraction procedure were employed to reconstruct the cortical surface based on the level set representation. Using 1-mm isotropic T1-weighted images, the FastCSR pipeline was able to reconstruct a subject’s cortical surfaces within 5 min with comparable surface quality, which is approximately 47 times faster than the traditional FreeSurfer pipeline. The advantage of FastCSR becomes even more apparent when processing high-resolution images. Importantly, the model demonstrated good generalizability in previously unseen data and showed high test–retest reliability in cortical morphometrics and anatomical parcellations. Finally, FastCSR was robust to images with compromised quality or with distortions caused by lesions. This fast and robust pipeline for cortical surface reconstruction may facilitate large-scale neuroimaging studies and has potential in clinical applications wherein brain images may be compromised.