Media.Player

Pupillary predictor of treatment outcome for affective disorders

Detailed Technology Description

None

*Abstract

BackgroundThe current best treatments for affective disorders work for 40-60% of participants to whom they are given, leading to increased time to successful intervention and associated negative consequences such as patient deaths as well as wasted resources. Earlier research found that brain scans (fMRI) can help identify patients that respond well to cognitive therapy. The cost of such a test is too expensive to be performed regularly by psychiatric clinicians. Also in a recent study it was found that patients who exhibited larger and more sustained pupil dilation while performing these tasks had more difficulty responding to cognitive therapy than the other patients.TechnologyThe subject invention is a technique that uses pupillary responses to predict response to treatment for affective disorders. Pupillary responses can be extracted from any sufficiently detailed image of the eye, including webcam pictures. Using standard capture of eye images in response to stimuli, this technique can discriminate likelihood of outcomes to best-practices treatment for affective disorders.Application* Predicting remission likelihood in Cognitive Therapy for depression.Advantages* Quick* Easy* Inexpensive (vs. brain scans via fMRI)* Non-invasive* Administered by a minimally trained clinician* Can be remotely administered (telemedicine). * High discrimination for remission likelihood in initial trials.Stage of Development* Mechanisms validated via fMRI* Developed and tested successfully.

*Principal Investigator

Name: Greg Siegle, Associate Professor of Psychiatry

Department: Med-Psychiatry

Country/Region

USA