| Title: | Radiomics for improved antidepressant treatment selection |
| Lead Institution: | Amsterdam UMC Research BV |
| Principal investigator: | Professor Liesbeth Reneman |
Application 60646
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
About
For treatment of major depression, there are multiple antidepressant drugs available. However, finding the right antidepressant drug for the right patient can take a long time. In fact, after one year, only half of the patients have found an effective drug. In the absence of a better selection method, treating physicians take a trial-and-error approach: start with a specific treatment, take 6-12 weeks to observe efficacy, if symptoms are not efficiently reduced, slowly reduce dosage minimizing withdrawal symptoms, start a new treatment and repeat the cycle. In this project we want to shorten this trial and error time, by investigating whether a combination of brain MRI characteristics from UK biobank, such as hippocampal volume, combined with advanced image analysis approaches and clinical input can predict which patients will not-respond, or will respond to the antidepressant medications. The outcome of this study (an algorithm) will subsequently be applied to a new study at our home institute, to make sure the algorithm works well. In doing so, this project will have great medical (reduction of side-effects of ineffective medications) as well as economic benefits (shorter treatment durations) for society.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 19250 | Normative amygdala fMRI response during emotional processing as a trait of depressive symptoms in the UK Biobank | Jerke J. van den Berg (+4) | 2025 | Psychological Medicine |
Enabling scientific discoveries that improve human health