A Picture of Sadness — Spotting Depression With Imaging
By Kathy Hardy
Radiology Today
Vol. 21 No. 5 P. 14

While outward symptoms of major depressive disorder—sadness, lack of motivation, and difficulty focusing, to name a few—may be easily recognizable, its clinical basis isn’t as easily detected. That’s changing, as researchers from several specialties, including neurology, neuroradiology, and the emerging field of psychoradiology, are looking at imaging to help spot depression in the brain and bring a more individualized approach to the diagnosis and treatment of this disorder.

Possible results of research in brain imaging include classifying different subtypes of depression and determining which treatment methods work best in each patient. This contrasts with a historically more generalized approach.

“Other areas of medicine, such as infectious disease and oncology, have evidence-based testing available to see what works for which conditions and for different patients,” says Helen S. Mayberg, MD, a professor of neurology, neurosurgery, psychiatry, and neuroscience at Icahn School of Medicine at Mount Sinai in New York. “With depression, treatment selection generally relies on trial and error for readily available treatments such as medication or psychotherapy, but what we need are clear biomarkers to guide treatment selection for individual patients so we can get a given person better fast and avoid treatments unlikely to work or cause side effects.”

This research has the potential to benefit a significant number of individuals. The World Health Organization, in 2017, identified more than 264 million people worldwide who are affected by depression. And depression takes different forms in different people. Mayberg says it comes down to identifying subtypes.

“Psychiatrists and physicians can diagnose depression, but despite ongoing research undeniably demonstrating that depression is a brain disorder, we don’t yet have brain scan methods that reliably diagnose or define subtypes in individual patients,” she says. “The variability of symptoms suggests that there should be ways to classify depression into such subtypes based on specific biological disturbances. We can tell what symptoms are dominant but, with reliable biomarkers, we might further help stratify treatment outcomes. The ultimate goal of a brain-based classification approach is to guide optimal treatment selection—a move toward true precision psychiatry.”

Neuroimaging and Depression Subtypes
A key tool in the effort to identify depression subtypes is neuroimaging using modalities such as CT, MRI, functional MRI (fMRI), and PET. One neuroimaging method involves examining traditional clinical subtypes for their neuroimaging correlates. Another approach has been to examine core features of depression using task-based studies, which analyze patterns of reactivity in the brain as the patient focuses on a specific cognitive or emotional stimulus.

With substantial variability in individual patient outcomes from major depressive disorder treatments, researchers see an even greater need to find ways to identify biomarkers that guide treatment selection. With biomarkers, not only can neuroimaging play a role in identifying depression subtypes, it has the potential to enable precision psychiatry—helping identify an individual’s possibility of remission or treatment failure with first-line treatment options.

Mayberg was the principal investigator of two studies testing the use of FDG-PET and resting-state fMRI to predict differential response and failure to cognitive behavioral therapy (CBT) or antidepressant medication in the treatment of adults with major depressive disorder. Glucose metabolism in the right anterior insula discriminated the two treatments, with remitters to medication and failures to CBT showing high activity, while remitters to CBT and failures to medication showed low activity. Similarly, in a second cohort of patients, the pattern of functional connectivity of resting-state fMRI also discriminated these two treatment response groups, suggesting the feasibility of imaging for precision treatment strategies for depression.

Mayberg notes that imaging has been an important method for investigating the neural basis of depression for many decades, with studies evolving in lockstep with the maturation of the field. Early studies of poststroke depression in the 1980s took advantage of CT scanning to localize lesions, which continues now with high-resolution structural MRI analyses. Early blood flow studies used low-resolution xenon or other radionuclide methods and matured to utilize positron tracers to chart blood flow, metabolism, and mapping as well as resting state and diffusion measures to characterize depression pathophysiology by recording functional and structural connectivity.

As neuroimaging techniques evolved and applications in brain imaging expanded, experts in the field developed psychoradiology, a subspecialty of radiology. Psychoradiology utilizes neuroimaging approaches to advance differential diagnoses and individualized patient care for psychiatric illnesses such as depression. The subspecialty includes a growing consortium of specialists from the fields of clinical psychology/neuropsychiatry and clinical imaging/radiology.

A leader in psychoradiology is Qiyong Gong, MD, PhD, a professor of radiology and director of the Huaxi Magnetic Resonance Research Center in the department of radiology at West China Hospital of Sichuan University, China. He and his team of researchers were the first to expand the field, which has roots as early as 1976 in looking for brain changes in CT scans of patients with schizophrenia.

“This field didn’t become mature until 2016, when my colleague, Dr. Su Lui, first formally described this term in Radiology,” Gong says. “And the term was only first mentioned in 2015, in a named lecture of the ISMRM [International Society for Magnetic Resonance in Medicine] annual conference in Toronto, Canada.”

Gong and his team’s pilot study on the association between clinical symptoms and cerebral gaps in psychiatric patients led to the psychoradiological hypothesis of mental disorders. This theory suggests that brain syndromes come from structural alteration, primarily due to the impact of impaired functional connectivity. Their continued work in this area, along with other researchers, is resulting in the identification of biomarkers that relate to specific psychiatric disorders, such as depression.

“By imaging a normal brain, we have the best opportunity to study our brain in vivo,” Gong says. “Once we have better understanding of the brain, we can then be in the best position to study the diseased brain. In particular, the correct understanding of the brain’s cognitive and behavioral function gives us the basis to understand the functional disorders in relation to psychiatric disorders.”

Compared with conventional radiology, where the radiologist makes a diagnosis mainly based on visible radiological signs, Gong says psychoradiologists rely more on analytical data.

“For psychoradiologists, biomarkers will most likely be identified based on the quantitative analysis of the quality imaging data acquired with the rigorously designed psychoradiological exam battery” he says. “In particular, the identified specific brain regions will, in turn, serve as the targets of treatment for interventional psychoradiologists.”

The Role of MRI
Gong says that while imaging modalities and radiological techniques have evolved significantly over the past 20 years, MR advancements that have benefited psychiatry the most are multimodal MR scans allowing the quantification of brain tissue at the structural, functional, and molecular levels. While early experience using brain scans in psychiatry with traditional visual image inspection failed to establish meaningful benefit to patient care, improved and novel image acquisition strategies and semiautomated quantitative image analysis approaches have established the clinical relevance of brain imaging studies of psychiatric patients.

“Using these advances, the field of psychoradiology has developed to utilize neuroimaging approaches to advance differential diagnosis and individualized patient care for common psychiatric illnesses analogous to neuroradiology for neurological diseases,” Gong says.

He adds that, although the technical capability of MRI is developing at a rapid pace, other modalities, such as PET, are complementary and can provide metabolic information that MRI is not yet capable of providing.

“However, MRI has no irradiation involved, in addition to its multimodal imaging capacity,” Gong says. “It is by far the main driver of the development of this radiology subspecialty.”

Interventional Psychoradiology
Gong points to Mayberg as a “pioneer” in image-guided psychiatric therapeutic intervention, or interventional psychoradiology. She is also known for her work in deep brain stimulation research. Deep brain stimulation is a procedure for treatment-resistant depression that involves placing electrodes deep in the brain and turning them on at an amplitude and frequency that disrupts activity between various brain regions.

“Deep brain stimulation is true image-guided therapy, driven by what the imaging shows,” Mayberg says. “Targeting where you place the stimulator, and specifically the part of the brain you’re attempting to activate, uses a combination of anatomical and functional neuroimaging methods.”

“In the future, with the technical advances such as the advent of MR-guided focused ultrasound,” Gong adds, “interventional psychoradiology may likely be revolutionized by moving from minimally invasive—or surgical—to completely noninvasive—nonsurgical—imaging-guided therapeutic procedures.”

Strength in Numbers
Mayberg, who along with Gong is an associate editor of the American Journal of Psychiatry, is also the founding director of Mount Sinai’s Nash Family Center for Advanced Circuit Therapeutics. Since 2018, the center has worked to advance surgical treatments for neuropsychiatric disorders through the development of neuroscience and neuroengineering innovations that correct brain circuit abnormalities. The center operates with a cross-disciplinary group of individuals from clinical fields including neurology, neurosurgery, and psychiatry, as well as experts from neuroscience, imaging, engineering, bioinformatics, neuro-engineering, and computational neuroscience, all with a goal of developing new circuit-based strategies and increasingly individualized treatments for patients with advanced neuropsychiatric disorders. Mayberg and Gong, who participated together in a panel discussion at RSNA 2019 on imaging as a diagnostic tool for depression, agree about the benefits of working with a multidisciplinary team in this area.

“The process of working with different related professionals is very interesting, enjoyable, stimulating, and inspiring” Gong says. “The benefits are obvious, because this allows the integration of the different expertise for addressing the specific clinical issue. Most importantly, such collaborations are mutually beneficial, and it certainly is creating a win-win situation.”

Gong is also the editor of a recent psychoradiology textbook approved by the Accreditation Council for Continuing Medical Education for practicing radiologists and radiology residents. As the current chair of the ISMRM Psychiatric MR Study Group, he is endeavoring to expand clinical translational value of MR psychiatric imaging by taking advantage of the disciplinary diversity of ISMRM members and, ultimately, improving care for psychiatric patients.

Gong expects psychoradiology to play a critical role in the clinical management of the diagnosis and treatment of patients with psychiatric illnesses. He says imaging will continue to serve as an important tool in the investigation of how the brain changes over time, how to identify different types of depression in the brain, and what treatment methods work best in individual patients.

“Imaging is at the forefront of how we conceptualize what goes wrong in the brain, even in the most complex behavioral disorders,” Mayberg says. “And imaging gives us evidence-based data for use in building models of how the brain works, which will lead to better diagnoses and better treatment.”

— Kathy Hardy is a freelance writer based in Phoenixville, Pennsylvania. She is a frequent contributor to Radiology Today.