Imaging-based identification of a neurological disease or a neurological disorder

A system comprising:

• a memory that retains data and logic;
• and
• a processor functionally coupled to the memory and programmed by the logic to
• receive imaging data related to nervous tissue in at least one central nervous system (CNS) structure of a subject;
• extract from the imaging data a set of one or more values of a group of diffusion tensor metrics comprising tensor skewness asymmetry;
• and
• apply a multivariate classifier based at least on the group of diffusion tensor metrics comprising tensor skewness asymmetry to the set of one or more values;
• and
• in response to application of the multivariate classifier, yield a probability of the subject having a neurological disease or neurological disorder that affects the at least one CNS structure.

A method comprising:

• collecting diffusion tensor imaging (DTI) data for at least one of the superior temporal gyrus (STG) or the temporal stem (TS);
• based on the DTI data, extracting at least one value of at least one diffusion tensor metric in a group of diffusion tensor metrics comprising STG tensor skewness asymmetry, left STG fractional anisotropy, right temporal stem (TS) axial diffusivity, right TS radial diffusivity, right TS mean diffusivity, or STG axial diffusitivity;
• applying a multivariate classifier based at least on the group of diffusion tensor metrics to the at least one value of the at least one diffusion tensor metric in the group of diffusion tensor metrics;
• and
• in response to the applying act, yielding a first probability of the subject having at least one autism.