Novel Brain Imaging System Quantifies THC-Related Impairment in Cannabis Users

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Researchers sought to evaluate the capability of a portable imaging system to effectively quantify THC impairment in cannabis users.

Functional near-infrared spectroscopy (fNIRS)-assessed prefrontal cortex (PFC) signaling changes were found to objectively categorize delta-9-tetrahydrocannabinol (THC) intoxication. These findings were published in Neuropsychopharmacology.

Use of THC impairs cognitive and psychomotor performance and has been associated with doubling the risk for fatal motor vehicle crashes. Despite its association with impaired driving, an evidence-based field sobriety assessment for THC has not been established. This study evaluated the potential for a portable imaging system to effectively quantify THC impairment in cannabis users.

Between 2017 and 2020, adults (N=169) aged 18-55 years who reported weekly or more cannabis use were recruited in the greater Boston area. Participants were randomized to receive oral dronabinol, a synthetic THC, or placebo on differing study days. The dronabinol dosage was determined by the participant’s cannabis usage up to a maximum of 80 mg. On the study visit, participants underwent urine drug screening to ensure they were free from intoxicating substances, they rated their level of intoxication at 20-minute intervals after drug ingestion, responded to a Drug Effects Questionnaire, underwent a physical examination, fNIRS, and an extended field sobriety test.

Participants were aged mean 25.2 (standard deviation [SD], 6.4) years, 50.9% were men, 67.5% were White, 56.2% were cannabis daily users, who began regular use at 19 (SD, 3.9) years of age.

There were 93 participants who self-rated themselves as intoxicated during the study compared with 96 as rated by the clinical consensus ratings (CCR). A total of 80 participants had concordant results with CCR and self-assessed intoxicated classification. The dose for the 80 participants with concordant results was 35.6±11.5 mg. Similarly, there were 57 participants with concordant ratings of not impaired and they had an average dose of 34.8±16.1 mg.

The participants who were impaired had greater subjective, physiologic, and cognitive effects compared with the participants who were not clearly impaired, despite no significant difference in the average THC dose received.

The field sobriety test classified 64.5% of participants as impaired following THC use and 21.6% impaired following placebo use. Among only field sobriety tests administered following THC use, the average dose for impaired individuals was 36.0 mg compared with 32.9 mg (P =.28) among participants classified as not impaired.

During a memory task, the fNIRS found increased oxygenated hemoglobin concentration in the PFC after THC intoxication compared with baseline or after placebo (P <.05).

Using fNIRS scan data with self-rated impairment, a machine learning approach classified impairment with an accuracy of 76.4%, positive predictive value of 69.8%, false positive rate of 10.0%, and an area under the receiver operating characteristic curve of 0.83.

The fNIRS approach may be limited in the field as optical detectors must be shielded from sunlight and certain movements, such as moving one’s eyebrows can cause motion artifacts in the assessment.

These data indicated that “impairment due to THC intoxication was associated with increased PFC activation on a simple memory task assessed with fNIRS. […] As we showed that there was no difference in THC dose between those who became impaired from those who did not following THC, it is likely that a brain- or behavior-based metric (eg, eye tracking or cognitive testing), rather than a per se blood or oral fluid limit of THC, is required to distinguish THC impairment from simple exposure.”

Disclosure: Multiple authors declared affiliations with industry. Please refer to the original article for a full list of disclosures.

Reference

Gilman JM, Schmitt WA, Potter K, et al. Identification of Δ9-tetrahydrocannabinol (THC) impairment using functional brain imaging. Neuropsychopharmacology. Published online January 8, 2022. doi:10.1038/s41386-021-01259-0