Brain Imaging May Pinpoint Optimal Treatment for Depression

Brain imaging may accurately pinpoint whether medication or psychotherapy is the optimal treatment for achieving remission in patients with major depression, independently of patients’ preferences with regard to treatment, new research shows.

Using functional magnetic resonance imaging (fMRI), investigators at Emory University School of Medicine in Atlanta, Georgia, found that the degree of functional connectivity between the subcallosal cingulate cortex (SCC) and three other key brain regions identified the best treatment for an individual patient.

In contrast, researchers found that patients who received their preferred treatment were not more likely to achieve remission, although they were more likely to complete the trial.

“All depressions are not equal, and like different types of cancer, different types of depression will require specific treatments. Using these scans, we may be able to match a patient to the treatment that is most likely to help them, while avoiding treatments unlikely to provide benefit,” principal investigator Helen Mayberg, MD, said in a release.

The study results were published online March 24 in two articles in the American Journal of Psychiatry.

Patient Preference Not Predictive

The authors note that in the absence of useful treatment predictors for major depression, current treatment guidelines recommend that patient preference for either psychotherapy or medication be considered when deciding on the initial treatment.

The goal of the Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) study, said Dr Mayberg, “is to use biomarkers to more precisely to predict who will respond to which intervention.

“This contributes to the model of precision medicine, which applies equally to psychiatry as to other areas of medicine, and is so important in today’s political and scientific climate,” Dr Mayberg told Medscape Medical News.

To examine whether patient preference is indeed predictive of clinical outcome, the investigators studied 344 treatment-naive adult patients who had major depression, as defined by a total score on the Hamilton Depression Rating Scale (HAM-D) of ≥18 at screening and ≥15 at baseline visit.

After screening and during the week prior to randomization, resting-state fMRIs were obtained. After the trial ended, the scans were analyzed to see whether they predicted treatment outcome.

At study outset, participants were asked whether they preferred cognitive-behavioral therapy (CBT) or medication, or whether they had a preference. They were then randomly allocated to received escitalopram (Lexapro, Forest Laboratories), 10-20 mg/day (n = 114), duloxetine (Cymbalta, Lilly) 30-60 mg per day (n = 115), or 16 individual sessions of CBT (n = 115).

The researchers report an estimated mean total improvement of 10.9 points on the HAM-D in the intent-to-treat sample. This result did not differ significantly across the three groups.

The mean reduction in HAM-D score among patients who completed therapy and the change over time likewise did not differ across the treatment groups, and there was no significant difference in remission rates between treatment arms, either in the last observation carried forward or in preprotocol samples.

Of the 66% of patients who expressed a preference, 35.5% preferred CBT, and 30.5% preferred medication. In contrast to white non-Hispanic patients, almost half of black patients (47.5%) preferred CBT, and only a fifth of Hispanic patients preferred medication.

The completion rate was significantly higher among those matched, vs those mismatched, to their preferred treatment (82.2% vs 67.8%, respectively, χ = 6.19, df = 1, = .013). However, the strength of treatment preference did not significantly affect remission rates.

“Although being matched to one’s preference did increase the chance of completing treatment, it did not improve outcomes,” said Dr Mayberg.

“Significant” Clinical Implications

The second study examined the relationship between the functional connectivity of the SCC and surrounding pathways and the differential response of patients to CBT and medication using fMRI imaging.

In this trial, the researchers examined neuroimaging results of 122 patients drawn from the PReDICT study. The patients had completed 12 weeks of randomized treatment with either CBT or antidepressant medication.

Of these, 58 achieved remission (CBT: n = 17; medication: n = 41), and 24 patients experienced treatment failure (CBT: n = 10; medication: n = 14). Forty patients had intermediate outcomes (CBT: n = 10; medication: n = 30).

The researchers found that both medication and CBT were associated with the degree of resting-state functional connectivity between the areas of the brain that are involved in mood regulation — that is, the SCC and the left frontal operculum (incorporating Broadmann area [BA] 47 in the ventrolateral prefrontal cortex and anterior insula); the left ventromedial prefrontal cortex (BA10); and the dorsal midbrain.

Summed SCC functional connectivity scores were applied to these three regions. The researchers found that negative connectivity scores were associated with remission in patients treated with medication, as well as with treatment failure with CBT. Positive connectivity scores were associated with remission in treatment with CBT and treatment failure with medication.

This summed value, when applied to all patients, provided “reasonable measures of internal validity (72% – 78% for remission, 75% – 89% for treatment failure), which exceeded the value of any clinical measure,” the authors note.

“We took outcomes and forced the brain to tell us that it could identify two types, those who respond to CBT, and those who respond to medication,” said Dr Mayberg.

The clinical implications are significant, she said.

“When a patient presents with depression, the first-line treatment is often a drug. When that patient returns with inadequate response, the drug is likely switched or augmented with another drug. Although it is common to have treatment failure with one drug and success with another, it is still a trial-and-error approach.”

Instead, “perhaps the failure of a drug does not imply that the patient should start another drug. Perhaps the patient should try CBT before trying another drug.”

Precision Psychiatry

Commenting on the findings for Medscape Medical News, Conor Liston, MD, PhD, assistant professor of neuroscience and psychiatry, Weill Cornell Brain and Mind Research Institute, New York City, who was not involved in the research, called the findings “remarkable.”

“Dr Mayberg and her colleagues have done seminal work identifying the SCC in the brain as a potential predictor of who will and who will not remit differentially to CBT vs medication. This study suggests that the SCC measures can be used to predict the likelihood of responding to one over the other,” he said.

He emphasized that the findings need to be replicated to see whether they can be generalized to other fMRI scanners, given the fact that “there can be strong scanner-related differences in functional connectivity assessments.”

But the results are promising.

“Although not everyone who is depressed will require a brain scan, you can certainly imagine that in clinically challenging decision-making situations, having an objective biomarker could be very useful,” he said.

Dr Mayberg agreed. “When a patient has pneumonia or an infection, the choice of antibiotic is based on whether it is gram negative or gram positive. The type of cancer a patient has informs the treatment choice. Depression is not a second-class illness to cancer or other conditions, and its treatment should likewise be based on biomarkers.”

The studies were supported by grants from the National Institutes of Health. Eli Lilly and Forest Laboratories donated the study medications, escitalopram and duloxetine, respectively, but were otherwise uninvolved in the study design, data collection, data analysis, or interpretation of findings. Full listings of the authors’ relationships with industry are provided in the original articles.

Am J Psychiatry. Published online March 24, 2017. 

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