RPS 1611 - Functional MRI and diffusion tensor imaging

Purpose:

Stroke is one of the main causes of disability in adults. Resting-state functional magnetic resonance imaging (rs-fMRI) is able to map functional-anatomic networks by analysing spontaneously correlated low-frequency activity fluctuations across the brain. However, the role of rs-fMRI to predict the functional outcome after acute stroke remains unclear. We aimed to evaluate the impact of rs-fMRI at 72h after stroke symptoms onset to predict the functional outcome at 1-year follow-up.

Methods and materials:

35 reperfused stroke patients (12 female, age: 68±14 years, 3-day national institutes of health stroke scale (NIHSS) score: 6±5) were consecutively scanned 72 hours after symptom onset. A modified Rankin scale (mRS) was used to evaluate functional outcome at 90 days (patients with good functional outcome, mRS ≤2; poor outcome, mRS>2). Image pre-processing included motion and slice-timing correction, outliers’ detection, brain tissue segmentation, MNI space normalisation, smoothing, and band-pass filtering to remove undesired components. Region-of-interest analyses were performed to calculate the correlation coefficients for every pairwise region and a weighted general linear model was used to discover significative differences (p<0.05 FWE) between groups.

Results:

Patients with good outcome presented higher intra-network connectivity, while patients with poor outcome showed lower inter-network connectivity. To predict the 1-year functional outcome after a stroke, the 3-day NIHSS score was the most relevant predictor. An accuracy of 74.3% was obtained through a discriminant model using only clinical scores. Adding anatomical networks increased accuracy to 88.6%, 97.1% (including functional networks), and 100% (with clinical and imaging variables).

Conclusion:

These results show the relevance of rs-fMRI in the acute phase to predict the long-term functional outcome in stroke patients.

Limitations:

The sample size.

Ethics committee approval

n/a

Funding:

No funding was received for this work.

Purpose:

Medication-overuse headache (MOH) is a psychiatric comorbidity associated with chronic migraine. As machine learning is capable of identifying subtle disease patterns on a single subject level, we sought to determine the differences between MOH patients from healthy controls by using a machine learning classifier on resting-state functional MRIs (rs-fMRI).

Methods and materials:

34 patients with MOH and 41 age and sex-matched healthy controls were recruited. Smooth mean regional homogeneity (smReHo) was obtained via DPARSFA. Support vector machine (SVMs) algorithms based on PRoNTo toolbox were used to explore the utility for smReHo in the differentiation of patients and controls individually. Finally, Pearson's correlation between the MOH patients and clinical measurement was investigated.

Results:

The balanced accuracy of the correct classification of MOH and controls was 72.03% for smReHo (p<0.001 during 1,000 permutation testing). Areas contributing to classification accuracy mainly included in right Heschl's gyrus (3.23%), left temporal pole, and right inferior temporal gyrus. The direct comparison showed that MOH patients had significantly decreased smReHo activation in the right Heschl's gyrus (p<0.05, FDR corrected), which was corresponding to the highest weight area by machine learning classifier. A negative correlation was observed between the duration of medication intake and smReHo activation in the right Heschl's gyrus (r=-0.433, p<0.05).

Conclusion:

With machine learning computational analyses, our study was able to diagnose MOH patients on a single subject level by demonstrating decreased regional function in MOH patients, notably involving the right Heschl's gyrus, suggesting the right Heschl's gyrus might play an important role in the pathogenesis of MOH.

Limitations:

Studies with larger samples may be required for further verification.

Ethics committee approval

n/a

Funding:

No funding was received for this work.

Purpose:

The reorganisation of language is common in epilepsy patients and a relevant factor in surgical therapy. The non-invasive gold standard in presurgical evaluation is language fMRI. fMRI network analysis could reveal subtle changes in language network architecture so far invisible with standard analyses and thus provide relevant additional information. We aimed to investigate the reorganisation processes of language networks in surgical patients with temporal lobe epilepsy (TLE) using standard fMRI activation and recent network analysis.

Methods and materials:

Task-based language fMRIs were performed on 28 TLE patients (16 right/12 left) before and after surgery, and on 22 healthy controls. FMRI activation analysis, a derived laterality index, and functional connectivity of global and language networks were used to investigate language architecture. Naming, semantic, and phonematic verbal fluency were correlated with imaging parameters.

Results:

Both left and right TLE were associated with widespread language network alterations, particularly ipsilesional, before, and more pronounced after surgery. Preoperatively, mesiotemporal connectivity was decreased in left TLE, while postoperatively bihemispheric changes with a shift to more atypical language laterality (especially frontal) occurred. In right TLE, right intrahemispheric frontotemporal functional connectivity was attenuated before and further decreased after surgery, while those patients with stronger connectivity scored worse in semantic verbal fluency. Better postoperative naming ability was generally accompanied by stronger interhemispheric frontal connectivity. In all cases, network analysis revealed more widespread alterations than activation analysis.

Conclusion:

The reorganisation of language function is a visualisable phenomenon in left and right TLE, both before and after surgery. Functional connectivity analysis reveals more widespread network changes than fMRI activation analysis and may offer a more comprehensive view on language architecture. Some connectivity measures may serve as biomarkers for language performance.

Limitations:

n/a

Ethics committee approval

n/a

Funding:

No funding was received for this work.

Purpose:

Functional connectivity abnormalities, such as default mode network (DMN), have been reported previously in trigeminal neuralgia (TN) of which chronic pain is a common symptom. However, little is known about the dynamic functional connectivity (dFC) in patients with TN.

Methods and materials:

29 patients with TN were enrolled in this study and underwent rest-functional MRI scanning along with 24 age-, sex-, and education-matched healthy control (HC) subjects. A sliding-window approach was used to study the dFC based on the GIFT (group ICA of fMRI toolbox).

Results:

The functional networks were arranged into DMN, auditory network (AUD), visual network (VIS), and ventral attention network (VAN). Dynamic analysis suggested 4 distinct connectivity ‘states’ across the entire group (state I for 24%, state II for 16%, state III for 35%, and state IV for 25%) and a larger proportion of state III and a smaller proportion of state IV were observed compared with HC group (p=0.0000 and p=0.0058, respectively). Furthermore, the TN group showed decreased connections between networks (DMN-VIS, AUD-VIS, and VIS-VAN). Our analyses showed that increased dwell time in the state IV was associated with the presence of pain in TN.

Conclusion:

Our study indicates that chronic pain in TN is characterised by altered temporal properties in dynamic connectivity. Further studies on dynamic functional connectivity could help to better understand the progressive dysfunction of networks in TN.

Limitations:

Correlation analysis is in progress.

Ethics committee approval

n/a

Funding:

No funding was received for this work.

Purpose:

Diffuse low-grade gliomas (DLGG) have a slow infiltrating character, allowing for simultaneous plasticity and maintaining the patients’ functional capacity. Here we addressed whether and how anatomical disconnection following left-hemispheric DLGG growth and resection interferes with resting-state connectivity, specifically in relation to language.

Methods and materials:

39 native French persons with a left DLGG were included and underwent awake surgical resection of the tumour. The anatomical disconnectivity risk following the DLGG volume and the resection, and the functional connectivity of resting-state fMRI images in relation to language, were evaluated prior to and three months after surgery. Resting-state connectivity patterns were compared with 19 healthy controls. Language was assessed with a picture-naming task.

Results:

Adaptive plasticity was observed in regions around the tumour/cavitas area, with increased connectivity of the left and right inferior parietal lobule with the left inferior temporal gyrus. Picture naming was surprisingly not dependent on the connectivity of the language network, but of the connectivity of regions know to be involved in semantics, in which their specific role could be explained in the light of the broader resting-state network they took part in. Also, the recruitment of the frontoparietal attention network was observed.

Conclusion:

A whole-brain approach with specific clinical data input is required for meaningful resting-state analysis in case of lesions. Pre-surgical local plasticity and functional compensation by increased task-directed attention allow a relative high level of performance maintenance after DLGG resection.

Limitations:

All participants underwent intensive speech-language rehabilitation post-surgery, which might have trained and strengthened attentional resources. The compensational strategy might thus have been learned.

Ethics committee approval

The study received local ethical committee’s approval. Participants gave informed consent.

Funding:

LabEx NUMEV (n° AN-10-LABX-20) and CHU Montpellier (AOI n° 2010-A01313-36).

Purpose:

There have been accumulating studies demonstrating thalamic related structural, functional, and metabolic abnormalities in minimal hepatic encephalopathy (MHE). We conducted the first study to investigate thalamic-related structural connectivity alterations in MHE.

Methods and materials:

Diffusion based probabilistic tractography was used to determine the structural connection between the thalamus and the cortical/subcortical regions in 22 cirrhotic patients with MHE, 30 cirrhotic patients without MHE (NHE), and 30 healthy controls. DTI (diffusion tensor imaging) measurements of these thalamic connections, including connectivity strength (CS), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), were calculated and compared across three groups. Neuropsychological assessment was performed as well. The correlation analysis was conducted to investigate the relationship between neuropsychological performance and the measurements about thalamic connections. Machine-learning classification analysis was performed to estimate whether diffusion measurements can distinguish MHE from NHE.

Results:

The probabilistic tractography revealed thalamic structural connection, which was disturbed in cirrhotic patients (reflected by decreased CS/FA and increased MD/AD/RD). Abnormal thalamic connection primarily involved the prefrontal cortex, sensorimotor cortex, parietal cortex, medial temporal cortex, hippocampus, and striatum. Thalamic connectivity abnormalities deteriorated from NHE to MHE and correlated with patients’ impaired neuropsychological performance. The relatively high classification accuracy was obtained using CS as a discriminating index.

Conclusion:

Our results demonstrated the altered thalamic structural connectivity with both cortical and subcortical regions in MHE. The disturbed thalamic connectivity may underlie the mechanism about cognitive deficits in MHE and can serve as biomarker for the diagnosis of MHE and monitoring disease progression.

Limitations:

The cross-sectional design.

Ethics committee approval

The Research Ethics Committee of Fujian Medical University Union Hospital, China.

Each subject provided a written informed consent.

Funding:

The National Natural Science Foundation of China (No.81501450).

Purpose:

Constant stimulation of the nervous system is one of the most popular ways to activate neural networks in order to activate the brain and initiate neuroplasticity processes. The purpose of the study was to evaluate the impact of translingual neurostimulation of the brain to balance, coordination of movement, and the ability to form new motor skills in children with cerebral palsy in the late residual stage.

Methods and materials:

This study involved 6 children with cerebral palsy, a form of spastic diplegia. Patients had intact intellect and no seizures in anamnesis. All children received standard treatment, including massage, medical-gymnastics with simulators, 10 daily sessions of physical therapy and neurostimulation of the brain (using a device for electrotactile stimulation called PoNS (portable neurostimulator)).

Patients underwent functional MRI of the brain before the start of, and at the end of, the course of treatment. The research was carried out using movement functional paradigms for each extremity (both feet and hands) and an active “count” paradigm for patients who could perform the task for the count and depending on clinical status, and passive movement or sensory paradigms were performed for those who could not. Postprocessing was carried out using the software package SPM 12.

Results:

All patients noted decreased muscle tone and improved balance and coordination functions after neurostimulation. According to obtained fMRI data, patients who underwent translingual neurostimulation showed increased activation in the right-hand motor area and activation in the foot motor area in response to the stimuli.

Conclusion:

Translingual neurostimulation is innovative in the field of neurostimulation, non-invasive, and safe and easy to use. fMRI active paradigms, with proper and high-quality implementation, is an auxiliary method for the objective control of treatment efficiency.

Limitations:

n/a

Ethics committee approval

n/a

Funding:

No funding was received for this work.

Purpose:

Magnetic resonance imaging (MRI) is the gold-standard imaging tool for compressive spinal cord myelopathy (CSCM). Diffusion tensor imaging (DTI), especially fibre-tracking or tractography (DTT), has been considered superior to routine MRI in predicting prognosis and urgency of decompression. This study aims to evaluate DTT as an advanced dimension of MRI in patients with CSCM in predicting the necessity of decompression management.

Methods and materials:

12 patients with clinical signs of CSCM underwent conventional MRI and DTI examination with a high-resolution matrix on a 1.5T magnet system. 3D-colour-coded maps were obtained in the sagittal and coronal planes. The presence or absence of parenchymal signal alteration and change in colour-code of the neural fibre tracts in the spinal cord, in addition to the integrity and homogeneous thickness of the fibre tracts on DTT, was evaluated.

A near-homogeneous blue colour in the spinal cord and cauda equina was considered normal in our study, with the blue colour representing diffusion in the craniocaudal direction. Alteration in colour, thickness, and integrity, especially at the level of compression on T2W images, was considered significant.

Results:

Out of 12 patients, 9 had signs of CSCM secondary to infective spondylodiskitis, 1 secondary to a disk protrusion, 1 secondary to a disk extrusion, and 1 secondary to the metastatic collapse of the vertebra.

In 8/12 patients with no spinal cord parenchymal signal alteration on T2W images, DTT revealed significant alteration in the colour-code both at and above the level of compression, signifying altered diffusion.

Conclusion:

DTT is a more sensitive indicator of spinal cord compression than conventional MRI by revealing colour alterations, thinning and loss of integrity of spinal nerve fibre tracts, and providing an easy and fast tool to predict the need for surgical decompression.

Limitations:

n/a

Ethics committee approval

n/a

Funding:

No funding was received for this work.

Purpose:

Our retrospective study investigates whether a correlation exists between functional language lateralisation using fMRI and structural lateralisation using diffusion data of language tracts in controls and tumour patients.

Methods and materials:

15 controls and 61 patients were included and underwent structural, functional, and diffusion imaging on 3T MRI. Subjects performed verbal fluency and verb generation language fMRI tasks, and a laterality index (LI) was calculated using data from the cerebral hemisphere and the contralateral cerebellar hemisphere. The diffusion tracts included the long fibres of the arcuate fasciculus, anterior and posterior short fibres of the arcuate fasciculus, uncinate fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, and frontal aslant tract. An asymmetry index (AI) for each fibre pair was calculated using the tract volume derived from single tensor (ST) and spherical deconvolution (SD) diffusion data, as well as using the hindrance modulated orientational anisotropy (HMOA) derived from the SD method. A linear regression analysis between fMRI LI and DTI AI was performed.

Results:

In all subjects, there was no significant correlation between fMRI LI and DTI AI for any of the tracts.

Conclusion:

Our results do not justify replacing fMRI with tractography in the assessment of language lateralisation. The discordant results between ST- and SD-based asymmetry indices indicate that the structural lateralisation is less robust than the functional one.

Limitations:

The predominately left-sided tumour distribution is due to the retrospective design, as included patients had all been selected clinically for presurgical assessment. The number of right-handed, left-handed, and ambidextrous subjects was not balanced. Disrupted or infiltrated fibres were excluded.

Ethics committee approval

The National Hospital for Neurology and Neurosurgery and Institute of Neurology Joint Research Ethics Committee approval was obtained.

Funding:

No funding was received for this work.