Quantitative Prediction of Individual Psychopathology in Trauma Survivors Using Resting-State fMRI

TY - JOUR

T1 - Quantitative Prediction of Individual Psychopathology in Trauma Survivors Using Resting-State fMRI

AU - Gong, Qiyong

AU - Li, Lingjiang

AU - Du, Mingying

AU - Pettersson-Yeo, William

AU - Crossley, Nicolas

AU - Yang, Xun

AU - Li, Jing

AU - Huang, Xiaoqi

AU - Mechelli, Andrea

PY - 2014/2

Y1 - 2014/2

N2 - Neuroimaging techniques hold the promise that they may one day aid the clinical assessment of individual psychiatric patients. However, the vast majority of studies published so far have been based on average differences between groups. This study employed a multivariate approach to examine the potential of resting-state functional magnetic resonance imaging (MRI) data for making accurate predictions about psychopathology in survivors of the 2008 Sichuan earthquake at an individual level. Resting-state functional MRI data was acquired for 121 survivors of the 2008 Sichuan earthquake each of whom was assessed for symptoms of post-traumatic stress disorder (PTSD) using the 17-item PTSD Checklist (PCL). Using a multivariate analytical method known as relevance vector regression (RVR), we examined the relationship between resting-state functional MRI data and symptom scores. We found that the use of RVR allowed quantitative prediction of clinical scores with statistically significant accuracy (correlation 0.32, P = 0.006; mean squared error = 176.88, P = 0.001). Accurate prediction was based on functional activation in a number of prefrontal, parietal, and occipital regions. This is the first evidence that neuroimaging techniques may inform the clinical assessment of trauma-exposed individuals by providing an accurate and objective quantitative estimation of psychopathology. Furthermore, the significant contribution of parietal and occipital regions to such estimation challenges the traditional view of PTSD as a disorder specific to the fronto-limbic network.

AB - Neuroimaging techniques hold the promise that they may one day aid the clinical assessment of individual psychiatric patients. However, the vast majority of studies published so far have been based on average differences between groups. This study employed a multivariate approach to examine the potential of resting-state functional magnetic resonance imaging (MRI) data for making accurate predictions about psychopathology in survivors of the 2008 Sichuan earthquake at an individual level. Resting-state functional MRI data was acquired for 121 survivors of the 2008 Sichuan earthquake each of whom was assessed for symptoms of post-traumatic stress disorder (PTSD) using the 17-item PTSD Checklist (PCL). Using a multivariate analytical method known as relevance vector regression (RVR), we examined the relationship between resting-state functional MRI data and symptom scores. We found that the use of RVR allowed quantitative prediction of clinical scores with statistically significant accuracy (correlation 0.32, P = 0.006; mean squared error = 176.88, P = 0.001). Accurate prediction was based on functional activation in a number of prefrontal, parietal, and occipital regions. This is the first evidence that neuroimaging techniques may inform the clinical assessment of trauma-exposed individuals by providing an accurate and objective quantitative estimation of psychopathology. Furthermore, the significant contribution of parietal and occipital regions to such estimation challenges the traditional view of PTSD as a disorder specific to the fronto-limbic network.

KW - trauma

KW - prediction

KW - post-traumatic stress disorder

KW - resting-state

KW - functional magnetic resonance imaging

KW - relevance vector regression

KW - POSTTRAUMATIC-STRESS-DISORDER

KW - PREFRONTAL CORTEX

KW - VECTOR MACHINE

KW - PTSD

KW - VOLUME

KW - BRAIN

KW - DEPERSONALIZATION

KW - AMYGDALA

KW - MRI

U2 - 10.1038/npp.2013.251

DO - 10.1038/npp.2013.251

M3 - Article

SN - 0893-133X

VL - 39

SP - 681

EP - 687

JO - Neuropsychopharmacology

JF - Neuropsychopharmacology

IS - 3

M1 - N/A

ER -