Mapping the brain: AI-driven radiomic approaches to mental disorders

Area of Science:

• Neuroscience
• Medical Imaging
• Artificial Intelligence

Background:

• Mental health conditions affect millions globally, posing significant healthcare challenges.
• Abnormalities in brain structure and neural connections are linked to mental disorders.
• Current diagnostic methods often lack precision and timeliness.

Purpose of the Study:

• To review the current applications of radiomics and AI in diagnosing mental disorders using neuroimaging.
• To identify critical radiomic features and associated brain regions for various DSM-5 categorized disorders.
• To explore the potential of these technologies for personalized treatment and improved patient outcomes.

Main Methods:

• Systematic review of radiomics-based studies utilizing neuroimaging and AI.
• Analysis of quantitative features extracted from brain scans.
• Identification of algorithms and methodologies employed in radiomics research for mental health.

Main Results:

• Radiomic features show promise in improving diagnostic accuracy for disorders like schizophrenia, PTSD, and depression.
• Specific brain regions and radiomic signatures are associated with different mental health conditions.
• AI and radiomics can aid in predicting treatment response.

Conclusions:

• Radiomics and AI offer powerful tools for the precise diagnosis of mental health conditions.
• These technologies can identify significant biomarkers for early detection and personalized treatment.
• Further research is needed to overcome limitations and fully realize the potential of radiomics in mental healthcare.