Clinical utility of BOLD fMRI in preoperative work-up of epilepsy

Clinical applications of magnetic resonance imaging based functional and structural connectivity

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

Translating state-of-the-art brain magnetic resonance imaging (MRI) techniques into clinical practice: multimodal MRI differentiates dementia subtypes in a traditional clinical setting

BACKGROUND

This study sought to validate the clinical utility of multimodal magnetic resonance imaging (MRI) techniques in the assessment of neurodegenerative disorders. We intended to demonstrate that advanced neuroimaging techniques commonly used in research can effectively be employed in clinical practice to accurately differentiate heathy aging and dementia subtypes.

METHODS

Twenty patients with dementia of the Alzheimer's type (DAT) and 18 patients with Parkinson's disease dementia (PDD) were identified using gold-standard techniques. Twenty-three healthy, age and sex matched control participants were also recruited. All participants underwent multimodal MRI including T1 structural, diffusion tensor imaging (DTI), arterial spin labeling (ASL), and magnetic resonance spectroscopy (MRS). MRI modalities were evaluated by trained neuroimaging readers and were separately assessed using cross-validated, iterative discriminant function analyses with subsequent feature reduction techniques. In this way, each modality was evaluated for its ability to differentiate patients with dementia from healthy controls as well as to differentiate dementia subtypes.

RESULTS

Following individual and group feature reduction, each of the multimodal MRI metrics except MRS successfully differentiated healthy aging from dementia and also demonstrated distinct dementia subtypes. Using the following ten metrics, excellent separation (95.5% accuracy, 92.3% sensitivity; 100.0% specificity) was achieved between healthy aging and neurodegenerative conditions: volume of the left frontal pole, left occipital pole, right posterior superior temporal gyrus, left posterior cingulate gyrus, right planum temporale; perfusion of the left hippocampus and left occipital lobe; fractional anisotropy (FA) of the forceps major and bilateral anterior thalamic radiation. Using volume of the left frontal pole, right posterior superior temporal gyrus, left posterior cingulate gyrus, perfusion of the left hippocampus and left occipital lobe; FA of the forceps major and bilateral anterior thalamic radiation, neurodegenerative subtypes were accurately differentiated as well (87.8% accuracy, 95.2% sensitivity; 85.0% specificity).

CONCLUSIONS

Regional volumetrics, DTI metrics, and ASL successfully differentiated dementia patients from controls with sufficient sensitivity to differentiate dementia subtypes. Similarly, feature reduction results suggest that advanced analyses can meaningfully identify brain regions with the most positive predictive value and discriminant validity. Together, these advanced neuroimaging techniques can contribute significantly to diagnosis and treatment planning for individual patients.

Outcomes of tumour related epilepsy in a specialised epilepsy surgery unit

INTRODUCTION

Seizures are an important cause of morbidity in patients with low grade gliomas with approximately 40% of cases drug resistant. The pathogenesis is quite complex and poorly understood. The treatment aims vary between almost purely epilepsy considerations and those that are primarily oncologic.

AIM

To determine whether patients who present with seizures and are found to have a low grade glioma have better outcomes when managed through a specialized epilepsy unit compared to the general neurosurgical service.

METHODS

A review of the prospectively collected database was performed over a 10 year period to identify 48 adult patients who present with a seizure and were subsequently found to have a low grade glioma. These patients were analysed with respect to management through the specialized epilepsy service or the general neurosurgical service. The primary outcome was Engel classification between the two groups. Secondary outcomes included recurrence, postoperative deficits, delay to surgery, histology, grade and extent of resection.

OUTCOMES

The patients managed through the epilepsy service had significantly higher rate of favourable Engel outcomes (I and II) compared to the general neurosurgery service (OR: 13.2, 95% CI: 1.239-140.679; P = 0.033). The epilepsy surgery group patients had a significantly higher delay to surgery (P < 0.001). The patients in the epilepsy service had a significantly higher resection ratio compared to the general neurosurgery service (73% vs 127%, P = 0.014). Rates of recurrence were not different between the two groups.

CONCLUSION

Patients with tumour related epilepsy who undergo an intensive presurgical evaluation may obtain better seizure related outcomes.