Brain Morphometry: Suicide

Diffusion tensor imaging studies on subjects with suicidal thoughts and behaviors: A descriptive literature review

OBJECTIVE

Globally, suicide represents the second leading cause of death in young people aged 15-29 years for both sexes, after traffic accidents. Suicide occurs not only in high-income countries, in high-income countries but it is a global phenomenon in all regions of the world and it represents a serious public health problem.

METHOD

This review was conducted on studies focused on white matter alterations in people who have attempted or thought about suicide. We searched PubMed and Scopus databases and screened references of included studies and reviewed articles for additional citations. From the initial 21 publications, we included only 12 studies that met search criteria and described the association between white matter alterations and suicide.

RESULTS

White matter alterations in suicidal behaviors were found in the prefrontal cortex, orbitofrontal cortex, internal capsule, corpus callosum, and default mode networks, which are critical cerebral areas involved in emotion processing and regulation, decision-making, executive functions, and empathy.

CONCLUSIONS

White matter alteration in cerebral areas involving high cognitive process and emotional regulation to confer a heightened vulnerability for suicidal behavior. Suicide is a complex process ranging from suicidal ideation to planning, attempting, or committing suicide. The identification of abnormalities in underlying neural circuitry may help delineate the neurobiological basis for suicide risk.

Classifying suicidal behavior with resting-state functional connectivity and structural neuroimaging

OBJECTIVE

About 80% of patients who commit suicide do not report suicidal ideation the last time they speak to their mental health provider, highlighting the need to identify biomarkers of suicidal behavior. Our goal is to identify suicidal behavior neural biomarkers to classify suicidal psychiatric inpatients.

METHODS

Eighty percent of our sample [suicidal (n = 63) and non-suicidal psychiatric inpatients (n = 65)] was used to determine significant differences in structural and resting-state functional connectivity measures throughout the brain. These measures were used in a random forest classification model on 80% of the sample for training the model.

RESULTS

The model built on 80% of the patients had sensitivity = 79.4% and specificity = 72.3%. This model was tested on an independent sample (20%; n = 32) with sensitivity = 81.3% and specificity = 75.0% for confirming the generalizability of the model. Altered resting-state functional connectivity features from frontal and middle temporal regions, as well as the amygdala, parahippocampus, putamen, and vermis were found to generalize best.

CONCLUSION

This work demonstrates neuroimaging (an unbiased biomarker) can be used to classify suicidal behavior in psychiatric inpatients without observing any clinical features.