Periodic Reporting for period 4 - CDS-QUAMRI (A Clinical Decision Support system based on Quantitative multimodal brain MRI for personalized treatment in neurological and psychiatric disorders)
Período documentado: 2020-03-01 hasta 2021-02-28
Hence a clinical decision support system (CDS) enabling personalized diagnostics and treatment for neurological and psychiatric disorders is envisioned that is based on multimodal quantitative (QUA) magnetic resonance imaging (MRI) and multi-parametric
classification and shall be demonstrated for major depressive disorder (treatment response prediction) and multiple sclerosis (disease progression type prediction).
The second objective of the CDS QUAMRI project was to develop a prototype Clinical Decision support system using classifiers that discriminate different patient subgroups (treatment response, disease progression) using machine-learning based classification methods and multi-modal MRI data from patients with major depressive disorder as well as multiple sclerosis. At the end of the entire period duration it was demonstrated that anatomical, functional and metabolic MRI allow prediction of therapy response to electroconvulsive, ketamine and psycho therapy in patients with major depressive disorder. Furthermore, the correct assignment of patients to different disease progression types of multiple scleroses was possible based on a combination of anatomical, microstructural and metabolic MRI. Furthermore microstructural MRI shows strong predictive power for disability scores in multiple sclerosis patients. The data analysis and classification trials for both multiple sclerosis and major depressive disorder are going to be continued after the project end.
The envisioned Clinical Decision Support System has been successfully demonstrated for specific clinical decision making problems in patients with major depression and multiple sclerosis. It makes use of disease specific anatomical, microstructural, functional and metabolic MRI based surrogate markers to enable (1) the prediction of treatment response to electroconvulsive therapy, ketamine therapy and psychotherapy in major depressive disorder and (2) the distinction of different disease progression types in multiple sclerosis. In both patient groups it was also found that anatomical imaging data that are routinely acquired yield predictive power if a quantitative analysis is performed instead of the qualitative evaluation that is the current clinical standard. The demonstrated principles can be extended to a larger number of neurological and psychiatric disorders and disease specific clinical decision making problems in order to facilitate personalized treatment. A key outcome of this project is the need for clinical trials that provide large consistent multimodal MRI data sets acquired with standardized scan protocols on one hand and the move from qualitative to quantitative analysis of clinical MRI data on the other hand.