A team of Italian researchers led by Alice Deruti, Anna Nigri, and colleagues at the Fondazione IRCCS Istituto Neurologico Carlo Besta in Milan has published what is among the most granular combined metabolic-and-network studies of chronic disorders of consciousness to date. Their cohort of 84 chronic patients who underwent FDG-PET included 47 in vegetative state/unresponsive wakefulness syndrome, 31 in minimally conscious state, and six who had emerged from minimally conscious state, equally distributed across traumatic, vascular, and anoxic etiologies. While FDG-PET alone is known to help distinguish vegetative from minimally conscious states, FDG-PET studies that cross-examine different etiologies and link metabolic activity to resting-state fMRI network structure have been limited. The study, published in Brain Communications in early 2026, addresses that gap by doing both simultaneously.
The metabolic signal separated the two main diagnostic groups cleanly and did so across every brain region examined. Patients in vegetative state/unresponsive wakefulness syndrome exhibited a significant decrease in metabolism compared to patients in minimally conscious state across all areas of interest. Standardized uptake values were calculated for 10 resting-state fMRI networks, the precuneus, and a whole-brain mask. Discrimination between the two groups was significant, with the highest area under the curve reaching 0.83 in the precuneus and 0.82 in the medial visual network, and area-under-the-curve values above 0.77 also in the lateral visual network, the default mode network, and the dorsal attention network. A subgroup of 68 patients also underwent resting-state fMRI, and the presence or absence of those networks corresponded with higher or lower metabolic levels, making the two modalities mutually reinforcing rather than redundant. Critically, eight cases of covert cortical processing were identified, and 68 patients also underwent resting-state fMRI; those covert-processing patients showed intermediate metabolic levels between the two principal diagnostic categories, a finding that complicates any clean binary view of the vegetative-versus-conscious divide.
The etiology analysis produced one of the study's most striking findings. The anoxic group displayed a severe decrease in metabolism compared to patients with traumatic and vascular etiologies, a result that aligns with prior understanding that cardiac-arrest-related brain injury tends to be diffuse rather than focal. Because hypoxic-ischaemic injury is typically diffuse, damage to a network of brain regions is likely involved in the resulting disorder of consciousness, a pattern that may explain why anoxic patients land at the bottom of the metabolic distribution regardless of their formal behavioral diagnosis. The clinical stakes behind all of this are considerable: the approximate rate of misdiagnosing a patient with at least minimal consciousness as unconscious on routine clinical examination is 40 percent, an alarming rate that may affect critical clinical decisions, lead to premature withdrawal of life-sustaining treatment, and restrict access to rehabilitation services.
Skeptics raise a legitimate access concern: FDG-PET requires a cyclotron-produced radiotracer, specialized scanners, and radiation exposure, meaning the combined protocol described here is unlikely to become a routine bedside tool in most hospitals any time soon. Researchers working on EEG-based and portable fMRI approaches argue that scalable alternatives must be developed in parallel, and that a single-center Italian cohort, however carefully assembled, cannot settle questions of generalizability across diverse health systems and patient populations. The study itself also cannot resolve the deeper philosophical question its data brush against: whether the metabolic floor of the anoxic vegetative group represents an absolute absence of experience or only an absence of the neural infrastructure that investigators currently know how to measure.
The practical upshot is plain: a PET scan and a half-hour of resting-state fMRI together tell a clinician more about whether the lights are on than any bedside behavior exam can, and for patients stuck in the diagnostic gray zone, that difference can determine whether care continues or stops.