A conceptual framework for the use of neuroimaging to study and predict pharmacoresistance in epilepsy

Clinical prediction models for treatment outcomes in newly diagnosed epilepsy: A systematic review

Up to 35% of individuals diagnosed with epilepsy continue to have seizures despite treatment, commonly referred to as drug-resistant epilepsy. Uncontrolled seizures can directly, or indirectly, negatively impact an individual's quality of life. To inform clinical management and life decisions, it is important to be able to predict the likelihood of seizure control. Those likely to achieve seizure control will be able to return sooner to their usual work and leisure activities and require less follow-up, whereas those with a poor prognosis will need more frequent clinical attendance and earlier consideration of epilepsy surgery. This is a systematic review aimed at identifying demographic, clinical, physiological (e.g., electroencephalographic), and imaging (e.g., magnetic resonance imaging) factors that may be predictive of treatment outcomes in patients with newly diagnosed epilepsy (NDE). MEDLINE and Embase were searched for prediction models of treatment outcomes in patients with NDE. Study characteristics were extracted and subjected to assessment of risk of bias (and applicability concerns) using the PROBAST (Prediction Model Risk of Bias Assessment Tool) tool. Baseline variables associated with treatment outcomes are reported as prognostic factors. After screening, 48 models were identified in 32 studies, which generally scored low for concerns of applicability, but universally scored high for susceptibility to bias. Outcomes reported fit broadly into four categories: drug resistance, short-term treatment response, seizure remission, and mortality. Prognostic factors were also heterogenous, but the predictors that were commonly significantly associated with outcomes were those related to seizure characteristics/types, epilepsy history, and age at onset. Antiseizure medication response was often included as a baseline variable, potentially obscuring other factor relationships at baseline. Currently, outcome prediction models for NDE demonstrate a high risk of bias. Model development could be improved with a stronger adherence to recommended TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) practices. Furthermore, we outline actionable changes to common practices that are intended to improve the overall quality of prediction model development in NDE.

Altered structural connectome in non-lesional newly diagnosed focal epilepsy: Relation to pharmacoresistance

Despite an expanding literature on brain alterations in patients with longstanding epilepsy, few neuroimaging studies investigate patients with newly diagnosed focal epilepsy (NDfE). Understanding brain network impairments at diagnosis is necessary to elucidate whether or not brain abnormalities are principally due to the chronicity of the disorder and to develop prognostic markers of treatment outcome. Most adults with NDfE do not have MRI-identifiable lesions and the reasons for seizure onset and refractoriness are unknown. We applied structural connectomics to T1-weighted and multi-shell diffusion MRI data with generalized q-sampling image reconstruction using Network Based Statistics (NBS). We scanned 27 patients within an average of 3.7 (SD = 2.9) months of diagnosis and anti-epileptic drug treatment outcomes were collected 24 months after diagnosis. Seven patients were excluded due to lesional NDfE and outcome data was available in 17 patients. Compared to 29 healthy controls, patients with non-lesional NDfE had connectomes with significantly decreased quantitative anisotropy in edges connecting right temporal, frontal and thalamic nodes and increased diffusivity in edges between bilateral temporal, frontal, occipital and parietal nodes. Compared to controls, patients with persistent seizures showed the largest effect size (|d|>=1) for decreased anisotropy in right parietal edges and increased diffusivity in edges between left thalamus and left parietal nodes. Compared to controls, patients who were rendered seizure-free showed the largest effect size for decreased anisotropy in the edge connecting the left thalamus and right temporal nodes and increased diffusivity in edges connecting right frontal nodes. As demonstrated by large effect sizes, connectomes with decreased anisotropy (edge between right frontal and left insular nodes) and increased diffusivity (edge between right thalamus and left parietal nodes) were found in patients with persistent seizures compared to patients who became seizure-free. Patients who had persistent seizures showed larger effect sizes in all network metrics than patients who became seizure-free when compared to each other and compared to controls. Furthermore, patients with focal-to-bilateral tonic-clonic seizures (FBTCS, N = 11) had decreased quantitative anisotropy in a bilateral network involving edges between temporal, parietal and frontal nodes with greater effect sizes than those of patients without FBTCS (N = 9). NBS findings between patients and controls indicated that structural network changes are not necessarily a consequence of longstanding refractory epilepsy and instead are present at the time of diagnosis. Computed effect sizes suggest that there may be structural network MRI-markers of future pharmacoresistance and seizure severity in patients with a new diagnosis of focal epilepsy.

Thalamohippocampal atrophy in focal epilepsy of unknown cause at the time of diagnosis

BACKGROUND AND PURPOSE

Patients with chronic focal epilepsy may have atrophy of brain structures important for the generation and maintenance of seizures. However, little research has been conducted in patients with newly diagnosed focal epilepsy (NDfE), despite it being a crucial point in time for understanding the underlying biology of the disorder. We aimed to determine whether patients with NDfE show evidence of volumetric abnormalities of subcortical structures.

METHODS

Eighty-two patients with NDfE and 40 healthy controls underwent magnetic resonance imaging scanning using a standard clinical protocol. Volume estimation of the left and right hippocampus, thalamus, caudate nucleus, putamen and cerebral hemisphere was performed for all participants and normalised to whole brain volume. Volumes lower than two standard deviations below the control mean were considered abnormal. Volumes were analysed with respect to patient clinical characteristics, including treatment outcome 12 months after diagnosis.

RESULTS

Volume of the left hippocampus (p_(FDR-corr)  = 0.04) and left (p_(FDR-corr)  = 0.002) and right (p_(FDR-corr)  = 0.04) thalamus was significantly smaller in patients relative to controls. Relative to the normal volume limits in controls, 11% patients had left hippocampal atrophy, 17% had left thalamic atrophy and 9% had right thalamic atrophy. We did not find evidence of a relationship between volumes and future seizure control or with other clinical characteristics of epilepsy.

CONCLUSIONS

Volumetric abnormalities of structures known to be important for the generation and maintenance of focal seizures are established at the time of epilepsy diagnosis and are not necessarily a result of the chronicity of the disorder.

Investigating imaging network markers of cognitive dysfunction and pharmacoresistance in newly diagnosed epilepsy: a protocol for an observational cohort study in the UK

INTRODUCTION

Epilepsy is one of the most common serious brain disorders, characterised by seizures that severely affect a person's quality of life and, frequently, their cognitive and mental health. Although most existing work has examined chronic epilepsy, newly diagnosed patients present a unique opportunity to understand the underlying biology of epilepsy and predict effective treatment pathways. The objective of this prospective cohort study is to examine whether cognitive dysfunction is associated with measurable brain architectural and connectivity impairments at diagnosis and whether the outcome of antiepileptic drug treatment can be predicted using these measures.

METHODS AND ANALYSIS

107 patients with newly diagnosed focal epilepsy from two National Health Service Trusts and 48 healthy controls (aged 16-65 years) will be recruited over a period of 30 months. Baseline assessments will include neuropsychological evaluation, structural and functional Magnetic Resonance Imaging (MRI), Electroencephalography (EEG), and a blood and saliva sample. Patients will be followed up every 6 months for a 24-month period to assess treatment outcomes. Connectivity- and network-based analyses of EEG and MRI data will be carried out and examined in relation to neuropsychological evaluation and patient treatment outcomes. Patient outcomes will also be investigated with respect to analysis of molecular isoforms of high mobility group box-1 from blood and saliva samples.

ETHICS AND DISSEMINATION

This study was approved by the North West, Liverpool East Research Ethics Committee (19/NW/0384) through the Integrated Research Application System (Project ID 260623). Health Research Authority (HRA) approval was provided on 22 August 2019. The project is sponsored by the UoL (UoL001449) and funded by a UK Medical Research Council (MRC) research grant (MR/S00355X/1). Findings will be presented at national and international meetings and conferences and published in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

IRAS Project ID 260623.

Resting-state functional brain networks in adults with a new diagnosis of focal epilepsy

OBJECTIVES

Newly diagnosed focal epilepsy (NDfE) is rarely studied, particularly using advanced neuroimaging techniques. Many patients with NDfE experience cognitive impairments, particularly with respect to memory, sustained attention, mental flexibility, and executive functioning. Cognitive impairments have been related to alterations in resting-state functional brain networks in patients with neurological disorders. In the present study, we investigated whether patients with NDfE had altered connectivity in large-scale functional networks using resting-state functional MRI.

METHODS

We recruited 27 adults with NDfE and 36 age- and sex-matched healthy controls. Resting-state functional MRI was analyzed using the Functional Connectivity Toolbox (CONN). We investigate reproducibly determined large-scale functional networks, including the default mode, salience, fronto-parietal attention, sensorimotor, and language networks using a seed-based approach. Network comparisons between patients and controls were thresholded using a FDR cluster-level correction approach.

RESULTS

We found no significant differences in functional connectivity between seeds within the default mode, salience, sensorimotor, and language networks and other regions of the brain between patients and controls. However, patients with NDfE had significantly reduced connectivity between intraparietal seeds within the fronto-parietal attention network and predominantly frontal and temporal cortical regions relative to controls; this finding was demonstrated including and excluding the patients with brain lesions. No common alteration in brain structure was observed in patients using voxel-based morphometry. Findings were not influenced by treatment outcome at 1 year.

CONCLUSIONS

Patients with focal epilepsy have brain functional connectivity alterations at diagnosis. Functional brain abnormalities are not necessarily a consequence of the chronicity of epilepsy and are present when seizures first emerge.

Progression of gray matter atrophy in seizure-free patients with temporal lobe epilepsy

OBJECTIVES

To investigate the presence and progression of gray matter (GM) reduction in seizure-free patients with temporal lobe epilepsy (TLE).

METHODS

We enrolled 39 consecutive TLE patients, seizure-free for at least 2 years--20 with magnetic resonance imaging (MRI) signs of hippocampal sclerosis (TLE-HS), 19 with normal MRI (TLE-NL), and 74 healthy controls. For longitudinal analysis, we included individuals who had a second MRI with minimum interval of 18 months: 21 patients (10 TLE-HS, 11 TLE-NL) and 11 controls. Three-dimensional (3D) T1 -weighted images acquired in 3 Tesla MRI were analyzed with voxel-based morphometry (VBM). The images of patients with right-sided interictal epileptogenic zone (EZ) were right-left flipped, as well as a comparable proportion of controls. Cross-sectional analysis: The patients' images from each group were compared to controls to investigate differences in GM volumes. Longitudinal analysis: The first and second images were compared in each group to look for decreased GM volume.

RESULTS

Cross-sectional analysis: Patients with TLE-HS had diffuse GM atrophy, including hippocampus and parahippocampal gyrus, insula, frontal, and occipital lobes ipsilateral to EZ, bilateral thalamus and contralateral orbitofrontal gyrus, and caudate. In contrast, TLE-NL group did not present significant differences compared to controls. Longitudinal analysis: TLE-HS presented progressive GM reduction in ipsilateral insula and occipital lobe, contralateral motor area, and bilateral temporal and frontal lobes. TLE-NL had GM progression in ipsilateral hypothalamus and parietal lobe, contralateral cerebellum, and bilateral temporal lobe. Controls did not show changes in GM volume between MRIs.

SIGNIFICANCE

Diffuse extrahippocampal GM atrophy is present in seizure-free patients with TLE-HS. In addition, there is progressive GM atrophy in patients with and without HS. These results demonstrate that not only ongoing seizures are involved in the progression of GM atrophy. An underlying pathologic mechanism could be responsible for progressive brain volume loss in TLE patients even in seizure-free periods.