Final Activity Report Summary - QBALLMOR (Q-ball Based Morphometry for Applications to Psychiatric Disorders) Besides carrying immense social stigma, mental diseases represent important burden on family members and society in general. The problem is multifaceted and it includes significant financial aspects. Early diagnosis could substantially improve the prognosis and could potentiate the mapping of primary targets in pathology, leading to better treatment solution. A number of magnetic resonance imaging (MRI) studies were performed to assess volumetric and morphological changes in brains of persons affected by schizophrenia and autism. However, the mechanisms of neuropathology of these diseases remain elusive. Disease specific markers have not been clearly identified, nor have been primary therapeutic targets established. Biomarkers that express disease hallmarks distinguishable from similar pathologies would assure reliable diagnosis (particularly in early stages of the disease, where the diagnosis is hindered due to resemblance of symptoms to those of other psychiatric or neurological diseases/disorders). They would also enable following disease progression, and would bring in the potential for defining primary therapeutic targets. There is, hence, a great need for new biomarkers and for the methods of sufficient sensitivity and accuracy to detect and classify these biomarkers. This project proposed an original morphometry method for non-invasive in vivo investigation of brain white matter (WM) at the microstructural level. The derived microstructural features may prove valuable disease specific biomarkers in schizophrenia and autism. As conventional MRI does not contain enough information for brain analysis at the microscopic scale, more advanced MRI modalities, like diffusion MRI (dMRI), need to be employed. Diffusion MRI measures signal dephasing due to random molecular motion (of water molecules, typically) inside tissues, where this motion implicitly encodes the geometry of the milieu. We based our approach on High Angular Resolution Diffusion Imaging (HARDI), that can model complex non-Gaussian displacement profiles of water molecules inside tissues. We also put forward the idea of the object-based analysis as opposed to point wise methods. Based on the hypotheses: there exist characteristic foci of brain WM modification; alterations in fibre bundles and connectivity may carry disease specific information on dysmaturation; and alterations in fibre bundles and connectivity are related to clinical symptoms and manifestations, we defined the primary project objective: Design of the HARDI-based, object-oriented WM morphometry method, in specifically constructed WM fibre bundle-dedicated coordinate systems. As the result of this objective, a novel WM morphometry was proposed, that employed for the first time HARDI-derived features in an object-based morphometry framework. The proposed method consists of a number of modules for which we introduced improvements and original approaches during the course of the project. Special care was taken to render the method applicable in clinical settings. Compared to the state-of-the-art, the main progress brought up by the novel method is to represent and exploit WM on a highly localised and highly detailed level. We validated the method on a smaller group of normal control subjects (NCs). The method is now being validated on a much larger database of NCs and is to be passed to the collaborating psychiatric unit that will deal with applications to cohorts of schizophrenic and autistic patients. The expert psychiatrists of the unit will correlate HARDI-derived features to disease specific clinical measures, and evaluate the suitability of the new biomarkers resulted from the proposed morphometry method. Finally, the work during this postdoctoral fellowship resulted in the number of publications in relevant peer-reviewed journal articles and conference proceedings, and presentations at international meetings.