Multimodal neuroimaging: Potential Biomarkers for response to AEDs?
Ana C. Coan1, MD; Fernando Cendes1, MD, PhD.
1Neuroimaging Laboratory, Department of Neurology, University of Campinas,
Campinas, SP, Brazil
Fernando Cendes, MD, PhD
Professor and Head, Department of Neurology,
University of Campinas, UNICAMP
Faculdade de Ciências Médicas
Campinas SP, Brazil, CEP 13083-970
Tel: +55 19 3521-8244
The author has no conflict of interest to disclose. We confirm that we have read the
Journal’s position on issues involved in ethical publication and affirm that this report is
consistent with those guidelines.
Neuroimaging techniques in epilepsy are widely used for definition of the epileptogenic
lesion and surgical decision. However, its application extends to the knowledge of
epileptic mechanisms and includes the identification of prognostic features that can help
our decisions for the appropriated type of treatment on an individual basis. Structural
neuroimaging may be able to identify patients more likely to respond to anti-epileptic
drug (AED) treatment and also patients who are better candidates for earlier surgical
treatment. In the last decades, quantitative analyses have also improved our knowledge
about epileptogenic lesions and networks as well as prognosis on seizure control,
cognitive outcome and comorbidities. New advanced neuroimaging techniques as
functional MRI and the development biotracers that could be associated with
inflammation and specific genetic patterns will add further knowledge in the field of
Key words: Antiepileptic drugs, Magnetic resonance imaging, functional imaging,
seizures, outcome, epileptogenic lesions, neuronal damage, biomarkers.
Supported by FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo),
At least 30% of patients with epilepsy will fail antiepileptic drug (AED) treatment
(Kwan & Brodie, 2000). For those, the best approach is surgical treatment with
resection of the epileptogenic zone. However, around 53% of patients who became
seizure free after surgery will have seizures relapse after a period of 10 years (de Tisi et
al., 2011). The early identification of patients who will not respond to AEDs or will fail
surgical treatment can save time and reduce morbidity. Neuroimaging techniques allow
non-invasive detection of subtle structural and functional brain abnormalities that may
be linked to better or worse response to AED or surgical treatments in these patients.
The field of neuroimaging has improved in the last decades and the use of these
techniques to define biomarkers of neurologic disease, including epilepsy, has grown
widely. The most commonly used neuroimaging method is structural MRI, but
functional images as functional MRI (fMRI) and positron emission tomography (PET)
have improved the searching for biomarkers. MRI quantification analysis has allowed
the identification of subtle structural abnormalities related, for example, to clinical
features as family history (Yasuda et al., 2010) and seizure recurrence after AED
withdrawal in patients who had been seizure free for at least two years (Cardoso et al.,
2006). Recently, refined brain imaging targeting abnormalities related to inflammation,
pharmacology and genetics are under development (Jones et al 2012).
It is classically known that only about 60% of individuals with epilepsy respond to the
first two AEDs and less than 4% will respond to further AED trials (Kwan & Brodie,
2000). Recent data have added the knowledge that while 59% of patients with epilepsies
will remain constantly seizure free with AEDs, 25% will never achieve seizure control
with medication, and a subgroup of 16% of patients will develop a relapse-remitting
pattern of response to AED (Brodie et al., 2012). For this last pattern of AED response,
surgical decision is usually delayed, enhancing the morbidity and higher risk of SUDEP
in these patients (Hesdorffer et al., 2011). Efforts must be made to the identification of
biomarkers that could allow the early detection of patients who will fail treatment.
Accordingly, a study in our center demonstrated that patients with pharmaco-resistant
and relapse-remitting mesial temporal lobe epilepsy (MTLE) have a similar pattern of
gray matter atrophy detected by voxel-based morphometry (VBM), and it was more
widespread than in AED responders (Bilevicius et al., 2010). These findings also
indicate that the brain damage and morbidity in patients with pharmacoresistant and
with relapse-remitting MTLE is similar and that surgical treatment should be readily
considered in patients with relapse-remitting seizure control. The authors concluded that
AED response in MTLE is multifactorial and appears to be related to the underlying
pattern of brain atrophy that extends beyond the hippocampus and age at seizure onset.
The question that remains is how one could precociously identify AED responders.
Another study from our center demonstrated that proton MR spectroscopy (MRS)
maybe a reliable biomarker to TLE patients who will respond to the first AED (Campos
et al., 2010). Reduced NAA/creatine ratio was found in hippocampi of patients who
failed the first AED trial but not in those who achieved seizure freedom indicating that
patients with TLE who respond well to the AED have significantly less evidence of
neuronal and axonal damage/dysfunction.
More appropriate biomarkers should be directed for specific types of epilepsies. The
majority of studies evaluate TLE patients and less is known about the possible markers
of treatment response of individuals with other localization-related epilepsies. Even in
studies with TLE associated with hippocampal sclerosis (HS), one must have in mind
that this is a syndrome rather than a specific disease. Refined analysis emphasizing the
possible different etiologies is the gold standard for the definition of accurate
biomarkers. For example, we were able to identify predictive factors of poor outcome in
a cohort of individuals with familial mesial TLE (FMTLE) after a mean follow-up of
7.6 years. In this study, the presence of hippocampal atrophy on MRI and interictal
epileptiform discharges (IEDs) were related to worse outcome (Morita et al., 2102).
Functional MRI (fMRI) has also helped to improve the knowledge about prognosis in
epilepsy. Moreover, by examining brain systems and their functional dynamics, fMRI
may be able to optimize the discovery of new drugs for neurological conditions,
including epilepsy, in the near future (Borsook, et al., 2006). The study of different
brain networks abnormalities in specific epilepsy groups and the association with AED
response is a rich field to be exploited by future researches. Also, the role of fMRI in
the prediction of surgical outcome in epilepsy has been investigated in some studies.
The use of IEDs triggered fMRI (EEG-fMRI), for example, can identify not only
hemodynamic abnormalities in the seizure onset zone of patients with epilepsy but it
also can detect abnormal networks that may have implications in surgical outcome.
EEG-fMRI has the advantage of relying on single-subject analysis what can be readily
used in the clinical setting for decisions for a specific patient. For example, we observed
with EEG-fMRI exams that the hemodynamic abnormalities related to temporal IEDs in
patients with non-lesional TLE is often localized in extra-temporal regions and it may
be diffuse (Coan et al., 2012). Other EEG-fMRI studies have demonstrated that the
concordance of IEDs triggered hemodynamic abnormalities with the localization of
surgical resection is associated to a better surgical outcome (Thornton et al., 2010;
Pharmacogenetics may be one additional variable in AED response. For example, there
is a strong association between carbamazepine-induced hypersensitivity reactions and
the leukocyte antigen HLA-B1502 in Han Chinese population (Chung et al., 2004) as
well as with the HLA‑A*3101 in Europeans (McCormack et al., 2011).We found an
association between pharmaco-resistance in MTLE patients and drug-transporter
(ABCC2) and drug-metabolism genes (CYP1A2 and CYP2E1) (Silva et al., 2010). In
addition, the ABCC2 expression was up-regulated in postoperative tissue samples of
patients with pharmaco-resistant MTLE (Silva et al., 2010).
Neuroimaging may help to clarify the relation of genotype and clinical characteristics
and treatment response. Fedi et al (2006), for example, using [11C]flumazenil PET,
demonstrated that patients with the GABRG2(R82Q) mutation express reduced GABAA
receptors and that the [11C]flumazenil binds mostly in the cingulate and insular cortices.
Onver the past decade, attention has been paid to the role of inflammation in the
epileptogenesis and seizure recurrence or epilepsy progression. Drugs with anti-
inflammatory mechanisms are promising targets to treat epilepsy. Preliminary data of a
Phase II trial indicate a possible beneficial effect in seizure reduction with VX-765, a
novel Interleukin-1β -Converting Enzyme/Caspase 1 inhibitor, which reduces the
production and release of IL-1 β (French et al., 2011). Neuroimaging have the potential
to be used in diagnosis and follow up of inflammatory abnormalities as shown by
studies in animal models. Filibian et al. (2012) demonstrated that proton MRS
measurements can be used to explore glia activation as a biomarker during
epileptogenesis and in the chronic epileptic phase in rat hippocampus. In another study
with rat lithium–pilocarpine model, Duffy et al. (2012) verified that vascular cell
adhesion molecule 1 antibody labeled iron oxide can be a potential targeted for MRI
contrast agent to image the inflammatory changes. The authors observed marked focal
hypointensities caused by contrast agent binding in vivo MRIs in the group of animals
with induced status epilepticus, particularly in the periventricular regions, hippocampus
and cerebral cortex. In humans, the use of neuroimaging techniques to demonstrate
neuroinflammation is still scarce, with few case reports. Butler et al. (2012) used
[C11]PK11195 PET, a marker of activated microglia, to visualize neuroinflammation in
a patient with focal cortical dysplasia. They observed an area of increased radiotracer
uptake in the right frontal lobe which was concordant to the identified seizure focus.
Neuroimaging biomarkers may also be used to evaluate progressive structural and
functional abnormalities in chronic epilepsies. There is extensive evidence that TLE-HS
is a progressive disorder and neuroimaging studies, especially MRI, have contributed to
this knowledge (Coan et al., 2009; Conz et al., 2011; Morita et al.,2012). For other types
of epilepsies, the evidence of disease progression is not so clear. Neuroimaging studies
with homogenous types of epilepsies can provide evidence of specific pattern and
intensity of progression what can propitiate more adequate clinical decisions and
perhaps the development of mechanisms to slow down this progression. We have
observed that progressive gray matter atrophy correlated with seizure frequency and
epilepsy duration in a VBM study of patients with MTLE and that the progressive
abnormalities were more pronounced in patients with seizure focus on the left side
(Coan et al., 2009). Progression of hippocampal atrophy defined by volume measures
was also detected in sporadic and familial MTLE, although in the familial group this
progression maybe slower, emphasizing that the underlying mechanism of
epileptogenesis play a role in the progressive burden of chronic epilepsy independent of
the seizure frequency (Conz et al., 2011; Morita et al., 2012).
Prediction of response to AEDs and surgical outcome are essential to improve treatment
for patients with epilepsy. Neuroimaging techniques, especially quantitative MRI, have
already helped to increase our knowledge about the differences of structural
abnormalities in diverse groups of patients and its relation to AED response. New
neuroimaging modalities will likely help in the development of better treatments for
seizures comorbidities in people with epilepsy. Imaging directed to investigate
inflammation and specific genetic patterns are under development and will help us to
learn more about the different epileptogenic mechanisms in humans.
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