Long-term prognostic value and clinical correlates of brain [¹⁸F]-FDG PET in patients with post-COVID-19 condition and neurocognitive disorders: a prospective cohort study

For millions of people worldwide, the acute phase of a viral infection has passed, yet the body refuses to return to normal. This lingering state, known as post-COVID-19 condition, brings a confusing array of symptoms that can persist for months or even years. Among the most debilitating are cognitive struggles: a fog that makes thinking difficult, a memory that feels unreliable, and a profound exhaustion that sleep does not fix. Doctors have long sought a way to see what is happening inside the brains of these patients. They needed a tool that could move beyond subjective reports of fatigue and show, with objective clarity, whether the brain itself was struggling. One such tool is a specialized imaging scan that tracks how much energy brain cells are using. When brain cells are active, they consume fuel; when they are sluggish or damaged, their fuel consumption drops. By mapping these energy levels, doctors can visualize areas where the brain is working less than it should.

A team of researchers in Nancy, France, decided to use this energy-mapping technique to answer a critical question: does the pattern of low energy in the brain predict how a patient will recover? They wondered if a scan taken early in the illness could serve as a crystal ball, telling doctors who would eventually feel better and who would remain disabled. To find out, they followed a group of seventy patients who had suffered from the virus and were experiencing ongoing cognitive problems. These individuals underwent brain scans that measured their cellular energy use. The researchers then tracked these patients for more than two years, watching how their symptoms changed over time. At the end of this long period, an expert panel reviewed each patient's condition, classifying them into three groups: those who had fully recovered, those who had improved but still faced significant challenges, and those whose condition had remained unchanged.

The study revealed a clear picture of what was happening in the brains of these patients, but it also delivered a surprising answer to the main question. When the researchers compared the patients' scans to those of healthy people, they found distinct areas where the brain was using significantly less energy. These "cold spots" appeared in the right side of the brain, specifically in the frontal and temporal regions, as well as in the parietal area and the cerebellum, which sits at the base of the skull. These findings confirmed that the brain was indeed affected, providing a biological signature for the cognitive struggles these patients described. The researchers also discovered that the severity of these energy drops was linked to how sick the patients had been initially. Those who had been hospitalized or infected with earlier versions of the virus showed deeper energy deficits than those who had been treated as outpatients or infected with newer variants.

However, when the team looked to see if these energy patterns could predict the future, the results were different. The scans taken at the beginning of the study did not match the final outcomes. Patients with severe energy drops in their scans were just as likely to recover fully as those with milder drops. Conversely, those with only slight metabolic changes were just as likely to remain disabled. Even when the researchers re-scanned a smaller group of patients a year later, the changes in their brain energy levels did not correlate with whether their symptoms had improved or worsened. The data showed that the brain's energy map, while a reliable indicator that something was wrong, could not forecast the trajectory of recovery.

This finding suggests that the path to recovery in post-viral conditions is far more complex than a simple measure of brain energy can explain. The fact that the scans did not predict the outcome implies that the factors driving long-term disability are not solely rooted in the visible, localized damage seen on these images. Instead, the persistence of symptoms likely involves a tangled mix of other mechanisms, such as immune system activity, psychological factors, and autonomic nervous system issues, which these scans cannot capture. While the imaging tool remains valuable for confirming that a patient's brain is involved and for ruling out other causes of their symptoms, it cannot yet be used to tell a patient exactly how their journey will unfold. The study concludes that managing these patients requires a broad, clinical approach that looks at the whole person, rather than relying on a single image to predict the future.