For the last 50 years, there have been very few novel drug treatments for psychiatric disorders. Although medications have been refined and patient dosing finessed, the molecular targets have broadly remained the same. Sadly, many of our existing treatments for the wide array of psychiatric disorders only work in roughly half the affected population; and those that do work often have limited duration of effect, undesired consequences and poor patient tolerability. Worse yet, many people with a mental health disorder go undiagnosed until the disease manifests with severe symptoms.
“Unlike many other medical conditions, there are no biopsies or tissue that we can directly access to gain a better biological insight of the patient’s mental health,” says Professor Steve Williams, founder and Head of the Department of Neuroimaging at the Centre for Neuroimaging Sciences, based at the Institute of Psychiatry, Psychology and Neuroscience (IoPPN) and Maudsley Hospital, King’s College London. “And that is where medical imaging can play a crucial role—to help provide that insight we need for a patient centric, personalized medicine approach to psychiatry.”
Although many mental health disorders have become less stigmatized in the last decade, with more people willing to seek treatment and society, at large, becoming more aware and accepting, the fact remains that mental illness comes with significant economic and societal burdens. A recent report estimated the global economic cost will be $16 trillion by 20301 and people with mental health disorders are more likely to be unemployed, be poor and be less productive at work. On average, they also have a life span that is 20 years shorter than the general population2.
“If we can identify patients at risk for a psychiatric disorder, prior to frank clinical symptoms, then we can be proactive and try to delay the onset or even prevent the occurrence with targeted early treatment,” Professor Williams adds.
For example, structural magnetic resonance imaging (MRI) can identify an early loss of tissue in the hippocampal region in Alzheimer’s Disease patients3. According to Professor Williams, patients with depression or schizophrenia who have undergone a similar neuro MRI exam may also present with reduced volumes in brain regions including the hippocampus and, in many cases, a scan is warranted to rule out an underlying organic, pathological cause for the symptoms.
There is hope, he adds, that medical imaging and specifically MRI can be used in the diagnostic work-up of patients suffering from a mental health disorder.
“For many psychiatric disorders it is not just a change in one focal region such as the hippocampus, rather, the complexion of the whole brain changes,” he explains. “If we can use
artificial intelligence to examine the vast array of neuroimaging data to identify what is different in the brains of patients at risk of developing schizophrenia, for example, and combine this information with genetics, lifestyle and family history, then potentially we can start to predict those who will develop this condition with a high degree of accuracy.”
While diffusion MR imaging is now widely used in the neuroimaging assessment of stroke patients to identify brain tissue at risk of infarction, the same technology can also be used to assess the structural integrity and connectivity of brain white matter. This technique may also end up being equally important in psychiatry, particularly in neurodevelopmental disorders such as attention-deficit/hyperactivity disorder (ADHD), schizophrenia and autism. Meta-analyses of the literature have reported several localized measures of white matter abnormality in these disorders, although it is not yet clear if these will be diagnostic or prognostic in the longer term. Further, prospective studies across a wider lifespan are warranted.
Dynamic fluctuations in brain networks can also be probed using resting-state functional MRI4 (rs-fMRI) which is a non-invasive method to detect synchronous regions of brain activity by virtue of localized changes in blood oxygenation. Recent rs-fMRI studies of depression have not only detected abnormal functional connectivity in frontostriatal and limbic brain networks but also predicted response to transcranial magnetic stimulation therapy in a specific subgroup of depressed patients based on their rs-fMRI network characteristics prior to treatment5.
“As we look to evaluate potential new treatments, one of the most promising MR sequences is 3D ASL [arterial spin labelling],” Professor Williams adds. “3D ASL allows us to non-invasively quantify the perfusion in every part of the brain. If we want to know whether a putative new drug has a central effect, we can measure if, when and how long the treatment modulates brain physiology.”
This information can also inform the route of administration, optimal dosing and even help to prioritize specific indications based on the pattern of perfusion change.
Imaging may also have an impact on treatment management. Understandably, a clinician will commonly prescribe a drug that runs the risk of fewer side effects rather than start with a more aggressive intervention. However, in psychiatry where the conditions are chronic and the time to achieve a measurable clinical response can be many months, this process may require years of different drug and dose iterations before a patient is on the right regimen.
“We are now investigating the potential of 18F-DOPA PET scans to see if they can help us stratify psychosis patients who don’t have a dopamine malfunction in the brain so we can get them on a different class of antipsychotic drug sooner,” explains Professor Williams.
Psychotherapy is another treatment where imaging can help with patient selection. While the side effects are minimal, it can be very expensive and labor intensive to administer. One might predict that the better the structural integrity and functional flexibility of the brain, the greater the mental capacity to respond to this type of treatment.
Yet, it’s not only new MR sequences or PET tracers that are enabling a broader utilization of imaging for a patient-centric diagnosis in psychiatry. “What is exciting and pioneering about MRI is that the manufacturers are now developing scanners that are quicker, quieter and quantitative,” Professor Williams explains. “With an acquisition technique that can make the sound of an MR scan as silent as a whisper, we can now perform scans during sleep or image the most anxious patients. This will be particularly useful in the study of migraine, tinnitus and autism where participants who are often hypersensitive to noise.”
1. Patel V, Saxena S, Lund C, et al. The Lancet Commission on global mental health and sustainable development. Lancet. 2018 Oct 27;392(10157):1553-1598.
2. Mental health problems costing Europe greatly. Organisation for Economic Co-operation and Development (OECD). Available at: https://www.oecd.org/newsroom/mental-health-problems-costing-europe-heavily.htm. Accessed on: July 29, 2019.
3. Frisoni GB, Fox NC, Jack Jr CR, Scheltens P, Thompson PM. The clinical use of structural MRI in Alzheimer disease. Nat Rev Neurol. 2010 Feb; 6(2): 67–77.
4. Preti MG, Bolton TAW, Van De Ville D. The dynamic functional connectome: State-of-the-art and perspectives. NeuroImage. 2017 Oct 15;160:41-54.
5. Drysdale AT, Grosenick L, Downar J, et al. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med. 2017 Jan;23(1):28-38.