Detection of Δ9-Tetrahydrocannabinol Impairment Using Resting-State Functional Near-Infrared Spectroscopy: A Randomized Clinical Trial

TL;DR

A portable brain imaging tool called fNIRS can detect cannabis impairment more accurately and quickly than traditional roadside tests.

Contribution

This study shows that resting-state fNIRS outperforms field sobriety tests in detecting THC impairment with higher accuracy and fewer false positives.

Findings

Resting-state fNIRS achieved an ROC-AUC of 0.87 and accuracy of 0.90 in detecting THC impairment.

fNIRS had a significantly lower false-positive rate (0.05) compared to field sobriety tests (0.34).

fNIRS performed better in precision, accuracy, and ROC-AUC than traditional behavioral assessments.

Abstract

This crossover trial compares the accuracy of resting-state functional near-infrared spectroscopy vs standard field sobriety testing to detect ∆9-tetrahydrocannabinol (THC) impairment among adults who use cannabis.

Can a portable neuroimaging method (functional near-infrared spectroscopy [fNIRS]) improve detection of impairment due to ∆9-tetrahydrocannabinol (THC)–induced intoxication over current benchmark behavioral assessments?

In this crossover trial of 183 adults who received doses of THC and/or placebo, 6-minute fNIRS measurements of resting prefrontal cortex activity identified THC impairment with superior accuracy compared with 45-minute expanded field sobriety tests and with comparable accuracy to fNIRS measurements conducted during attention task performance.

These findings suggest that portable fNIRS neuroimaging provides more objective, accurate, and rapid detection of THC-induced impairment than conventional field sobriety methods, offering significant advantages for cannabis impairment detection in roadside, workplace, and research settings.

The primary psychoactive compound in cannabis, ∆9-tetrahydrocannabinol (THC) induces intoxication and functional impairment, raising safety concerns in driving. The traditional impairment detection method, behavioral field sobriety tests (FSTs), are subject to bias.

To determine whether resting-state functional near-infrared spectroscopy (fNIRS) can detect THC-related impairment with greater accuracy and a lower rate of false positives than FSTs.

This double-blind, randomized, crossover trial was conducted from January 2017 to January 2021 at a single site. Eligible participants were adults aged 18 to 55 years who used cannabis. Analyses were performed from November 2024 to November 2025.

Participants received a single oral dose of synthetic THC (range, 5-80 mg) intended to induce intoxication or placebo in separate visits.

fNIRS scans were acquired before and approximately 100 and 200 minutes after study drug administration to assess prefrontal cortex responses at rest and during a working memory task. Machine learning models trained on fNIRS data were then used to identify clinically determined THC-induced impairment. The primary outcome of this study was accuracy of THC-induced impairment classification using fNIRS data as compared with an FST. Model performance was quantified using false-positive rate, precision, recall, F1 score, and area under the receiver operating curve (ROC-AUC).

A total of 183 participants (mean [SD] age, 25.3 [6.3] years; 90 [49.2%] female) who used cannabis for a median (IQR) of 6.5 (4-7) days per week completed at least 1 study visit. fNIRS data collected during rest produced a classifier for impairment, with an ROC-AUC of 0.87 (95% CI, 0.83 to 0.91), accuracy of 0.90 (95% CI, 0.88 to 0.92), and false-positive rate of 0.05 (95% CI, 0.04 to 0.07), using clinical impairment assessment as ground truth. The FST showed an ROC-AUC of 0.75 (95% CI, 0.74 to 0.76), accuracy of 0.69 (95% CI, 0.67 to 0.71), and a false-positive rate of 0.34 (95% CI, 0.32 to 0.36). fNIRS performed significantly better than the FST in precision (difference = 0.23; 95% CI, 0.14 to 0.33; P < .001), accuracy (difference = 0.15; 95% CI, 0.10 to 0.19; P < .001), false-positive rate (difference = −0.25, 95% CI, −0.31 to −0.20; P < .001), and ROC-AUC (difference = 0.08; 95% CI, 0.01 to 0.14; P = .005).

In this crossover trial of THC vs placebo, THC intoxication produced prefrontal cortex activation patterns detectable with resting state fNIRS neuroimaging, producing a neural signature of THC-induced impairment that was superior to FSTs for individual-level impairment identification. These findings lay the groundwork for further exploration of fNIRS as a tool for detecting impairment.

ClinicalTrials.gov Identifier: NCT03655717

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