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Parkinson’s Disease

First described in the 1800s, Parkinson’s Disease (PD) is a chronic, progressive and neurodegenerative disease that has a significant morbidity and mortality . PD is the second most common chronic neurodegenerative disease, after Alzheimer’s Disease, affecting to 2 per 1,000 adults at any given time and 1% of the population above 60 years . PD is among the neurological disorders which rank the highest as the cause of global disability (Collaborators, 2018). PD has been estimated to have doubled in prevalence from 1990 to 2015 due to an increasing proportion of elderly populations, longer disease durations and other environmental factors. PD is characterised by four cardinal symptoms: bradykinesia, rigidity, tremor and postural instability. The pathophysiology of PD is complex, but can be briefly summarised as the degeneration of dopaminergic neurons in the substantia nigra pars compacta, diminished production of striatal dopamine, and the formation of intracytoplasmic proteinaceous inclusions known as Lewy bodies .

Diagnosis of Parkinson’s Disease

The diagnosis of PD is a clinical one which was recently updated in 2015 by the Movement Disorder Society (MDS). The MDS PD diagnostic criteria are as follows: absence of absolute exclusion criteria (e.g. normal functional neuroimaging of presynaptic dopaminergic system), at least two supporting criteria (e.g. levodopa-induced dyskinesia, rest tremor of a limb, and presence of olfactory loss or cardiac sympathetic denervation) and no red flags (e.g. rapid progression of gait dysfunction or severe orthostatic hypotension) . Specifically, neuroimaging plays a role in the diagnosis of PD insofar as the presynaptic dopaminergic system is concerned. Indeed, a normally functioning presynaptic dopaminergic system is an absolute exclusion criterion for PD. This is because the hallmark of PD is that of the degeneration of dopaminergic neurons, leading to a lack of dopamine. Conventional magnetic resonance imaging (MRI) is used in the diagnostic workup to exclude subcortical vascular perturbations, secondary causes or parkinsonism, as well as to distinguish typical PD from atypical PD .

Functional Magnetic Resonance Imaging (fMRI)

Functional magnetic resonance imaging (fMRI) is a class of imaging modalities which was developed in order to delineate region-specific and time-dependent changes in cerebral metabolism . In other words, fMRI enables a visualisation of the working human brain. These alterations in cerebral metabolism can be due to changes in the state of cognition as they relate to certain tasks or unregulated processes (e.g. disease states) in the brain. In the case of the former, as the brain is functionally sub-specialised, certain tasks which are initiated by certain areas of the brain would result in an increase in the activity (rate of firing) of the involved neurons. The additional activity undertaken by these involved neurons requires additional metabolic substrates due to increased metabolic demand. In order to meet this metabolic demand, the haemodynamic flow of oxygenated blood to the regions of the brain that are involved in said tasks is enhanced. Blood oxygen level-dependent (BOLD) contrast imaging is typically used to map specific regions of the functioning brain to alterations in blood oxygen . Deoxygenated haemoglobin is a paramagnetic substance which causes the MR signal to be attenuated, in view of a high magnetic susceptibility. Conversely, oxygenated haemoglobin is a diamagnetic substance which enhances the MR signal due to its low magnetic susceptibility . fMRI has seen applications in various domains of neuroscience and medicine, such as clinical psychiatry, neurosurgery and behavioural science. fMRI is a popular imaging modality because it is non-invasive and does not necessitate the injection of radioactive isotopes or pharmacological agents, has a relatively low cost and has a modest spatial resolution . fMRI is extremely useful as a research tool in functional imaging, as well as in clinical practice for pre-operative planning.

FMRI Techniques and Methods in Parkinson’s Disease

Applications of fMRI in PD

As previously iterated, fMRI is capable of elucidating the functional activity in various brain networks reliably. fMRI has been utilised in order to understand the brain state of patients with PD; indeed, a recent study showed that the brin of PD patients have , as opposed to less densely connected and disparate brain states . One approach that has been used in fMRI as regards PD is the use of generative models. Generative models are computational models which derive how the observed fMRI data were generated, by leveraging pre-defined hypotheses regarding how the brain network was configured . The use of generative models in fMRI is termed ‘dynamic causal modelling’ (DCM) and allows for the comparison between different models of brain function within one group or between two groups. DCM has been used in PD to test how specific brain network interactions result in resting tremor and abnormal voluntary actions. Differences that are brought to light for certain models of brain function may be used to define and validate fMRI-based PD phenotypes or even support differential diagnoses for PD . Another approach that has been used in fMRI as regards PD is that of the extraction of biologically meaningful features from the imaging data. The resting state fMRI allows for the calculation of parameters which are indicative of the gradient of cortico-striatal connectivity across various regions . These gradients are useful to delineate as they reflect the underlying dopamine distribution in the brain and can be used to build nomograms for PD patients . These nomograms could be used not only to diagnose PD via imaging, but also to monitor the patient’s response to treatment which can be costly. As an extension of this application, the cost-effectiveness of PD treatment can also be derived by clinicians, thereby aiding in shared clinical decision making with the patient.

Benefits of using FMRI to better understand and treat Parkinson’s Disease

Diagnosing PD with fMRI

Various studies have demonstrated fMRI’s utility as a diagnostic tool. One study showed that PD patients demonstrated a spatial covariance pattern; this pattern was a combination of decreased neural activity in the striatum, middle frontal gyrus and occipital cortex, as well as an increased neural activity in the cerebellum, superior parietal lobule and temporal cortex . Based on this pattern alone, researchers were able to yield a 90% accuracy of a fMRI’s diagnosis accuracy in diagnosing PD of 90%. Although the diagnosis of PD is a clinical one and the MDS has updated their diagnostic criteria recently, there exist grey area patients who fulfil neither the criteria for clinically established PD, or clinically probably PD. Hence, fMRI may be a useful, cost-effective and safe diagnostic adjunct in these cases.

Diagnosing PD Beyond Cardinal Symptoms

Although PD is characterised by the four cardinal symptoms – bradykinesia, rigidity, tremor and postural instability, the disease extends beyond these to include other domains such as non-motor symptoms. These characteristics of PD cannot be solely attributed to basal ganglia dysfunction; instead, they are caused by neuronal circuit dysfunction. Hence, fMRI is useful in assessing this neural connectivity. fMRI may even be useful in detecting subclinical PD or early PD in which the cardinal symptoms have yet to manifest. As an example of this application, one recent study sought to examine the utility of fMRI in detecting non-motor symptoms in PD; specifically, the disturbed processing of emotions . Nineteen medicated PD patients were subjected to BOLD-fMRI and their valence and arousal were measured in response to positive, negative and neutral pictures. PD patients were shown to have attenuated putaminal activation and an enhanced activation in the right dorsomedial prefrontal cortex when compared to control subjects . These findings suggested a compensatory neural mechanism in PD patients during the processing of emotions which could have an impact upon current therapeutic strategies for depressive disorders in PD.

FMRI as a Biomarker for Parkinson’s Disease

Beyond its utility as a diagnostic tool or adjunct, fMRI can also serve as a biomarker for PD. Although PD is characterised mainly by motor symptoms, it is complicated by non-motor features such as mild cognitive impairment which progresses insidiously to culminate in advanced dementia. Currently, there are no reliable and reproducible biomarkers for cognitive decline in PD, as well as for determining the risk of progression to dementia. To that end, on-going studies are measuring anatomical and regional neural activation changes via resting state fMRI in PD patients in order to characterise neural network changes which can reliably predict the conversion of mild cognitive impairment in PD to dementia . The main limitation of using resting-state fMRI as a biomarker for PD is that of varied methods of fMRI ; studies which consistently adopt the same fMRI techniques would significantly value-add to the existing literature regarding fMRI’s potential as a PD biomarker.

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