A new hope for resistant Obsessive-Compulsive Disorder – innovative strategies for outcome prediction and treatment
Obsessive-compulsive disorder (OCD) is a chronic, debilitating disease that affects 2-3% of individuals worldwide. This psychiatric disorder is characterized by the presence of obsessions – intrusive and repetitive thoughts, images or impulses that generate intense anxiety – and/or compulsions – mental or motor acts that are repetitive in nature and are triggered in response to obsessions to relieve anxiety. (…) Effective treatments for OCD include cognitive-behavioral therapy and selective serotonin reuptake inhibitors (SSRIs). However, approximately 50% of patients are treatment-resistant to conventional treatments, highlighting the need of new therapeutic approaches. In this project, we intend to use state-of-the-art neuroimaging tools using a multimodal approach to better characterize brain function and structure in OCD and to identify possible predictors for treatment outcomes. We will establish data-driven associations between brain activation and structure and treatment response (pharmacological or psychotherapeutic) which are critical to provide personalized care. (…) Growing evidence has pointed out the putative efficacy of dopaminergic modulation in the treatment of OCD. (…) Having this into account, we intend to develop an D2/D3 intervention to decrease OCD severity and improve quality of life in patients that do not respond to first-line treatments, in combination with multimodal neuroimaging outcomes. Our results may thus contribute to establishing dopaminergic agonists as an important alternative tool in the treatment of OCD, particularly among treatment-resistant patients.
Luso-American Development Foundation (FLAD)
Main Project Outcomes
S. Queirós, “Right ventricular segmentation in multi-view cardiac MRI using a unified U-net model”, in E. Puyol Antón et al. (eds) Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. STACOM 2021. Lecture Notes in Computer Science, vol 13131, pp. 287-295, Springer, Cham, 2022.
“Best Paper Award in the M&Ms-2 Challenge”, by M&Ms2 Challenge organizers and the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society.
Main Project Outcomes