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Project Objectives

A large number of neurological and psychiatric disorders lack objective criteria for primary diagnoses, early differential diagnosis with regard to subtypes in treatment response and disease progression or effective therapy monitoring resulting in a tremendous negative socio-economic impact. Scientific studies based on advanced MRI methods indicate that related patients show specific subtle changes in multiple MRI readouts that are only detectable by quantitative approaches. Existing tools for MRI data analysis are largely insufficient to maximise the use of advanced modality based, diverse and complex MRI data with deficiencies existing mainly in interoperability as well as data organisation, integration, analysis and exploitation in clinical decision making.


The overall goal of the CDS-QuaMRI project was to develop a clinical decision support system based on multimodal quantitative magnetic resonance imaging (QuaMRI) data. In one arm of the project a software framework was developed, and in another project arm classification routines were developed based on test datasets including QuaMRI data from patients with major depressive disorder (MDD) and Multiple Sclerosis (MS).


The project had two major objectives:
  1. Development of integrated multi-modal magnetic resonance imaging analysis software for 10 MRI modalities that makes advanced analysis algorithms and tools accessible to non-expert clinical users.
  2. Exploitation of machine-learning classification methods in combination with multimodal MRI for automated clinical decision support in major depression and multiple sclerosis.