Neurobiological support to the diagnosis of ADHD in stimulant-naïve adults: pattern recognition analyses of MRI data

OBJECTIVE

In adulthood, the diagnosis of attention-deficit/hyperactivity disorder (ADHD) has been subject of recent controversy. We searched for a neuroanatomical signature associated with ADHD spectrum symptoms in adults by applying, for the first time, machine learning-based pattern classification methods to structural MRI and diffusion tensor imaging (DTI) data obtained from stimulant-naïve adults with childhood-onset ADHD and healthy controls (HC).

METHOD

Sixty-seven ADHD patients and 66 HC underwent high-resolution T1-weighted and DTI acquisitions. A support vector machine (SVM) classifier with a non-linear kernel was applied on multimodal image features extracted on regions of interest placed across the whole brain.

RESULTS

The discrimination between a mixed-gender ADHD subgroup and individually matched HC (n = 58 each) yielded area-under-the-curve (AUC) and diagnostic accuracy (DA) values of up to 0.71% and 66% (P = 0.003) respectively. AUC and DA values increased to 0.74% and 74% (P = 0.0001) when analyses were restricted to males (52 ADHD vs. 44 HC).

CONCLUSION

Although not at the level of clinically definitive DA, the neuroanatomical signature identified herein may provide additional, objective information that could influence treatment decisions in adults with ADHD spectrum symptoms.

State-dependent microstructural white matter changes in drug-naïve patients with first-episode psychosis

BACKGROUND

Diffusion tensor imaging (DTI) studies have consistently shown white matter (WM) microstructural abnormalities in schizophrenia. Whether or not such alterations could vary depending on clinical status (i.e. acute psychosis v. remission) remains to be investigated.

METHODS

Twenty-five treatment-naïve first-episode psychosis (FEP) patients and 51 healthy-controls (HC) underwent MRI scanning at baseline. Twenty-one patients were re-scanned as soon as they achieved sustained remission of symptoms; 36 HC were also scanned twice. Rate-of-change maps of longitudinal DTI changes were calculated for in order to examine WM alterations associated with changes in clinical status. We conducted voxelwise analyses of fractional anisotropy (FA) and trace (TR) maps.

RESULTS

At baseline, FEP presented reductions of FA in comparison with HC [p < 0.05, false-discovery rate (FDR)-corrected] affecting fronto-limbic WM and associative, projective and commissural fasciculi. After symptom remission, patients showed FA increase over time (p < 0.001, uncorrected) in some of the above WM tracts, namely the right anterior thalamic radiation, right uncinate fasciculus/inferior fronto-occipital fasciculus, and left inferior fronto-occipital fasciculus/inferior longitudinal fasciculus. We also found significant correlations between reductions in PANSS scores and FA increases over time (p < 0.05, FDR-corrected).

CONCLUSIONS

WM changes affecting brain tracts critical to the integration of perceptual information, cognition and emotions are detectable soon after the onset of FEP and may partially reverse in direct relation to the remission of acute psychotic symptoms. Our findings reinforce the view that WM abnormalities in brain tracts are a key neurobiological feature of acute psychotic disorders, and recovery from such WM pathology can lead to amelioration of symptoms.