Radiomics for diagnosis and assessing brain diseases: an approach based on texture analysis on magnetic resonance imaging

Abstract

IIIn the third project, we evaluated the hippocampus MRI profile of Alzheimer's disease (AD) patients to identify the different stages of the disease. The current criteria for diagnosing AD require the presence of relevant cognitive deficits, so the underlying neuropathological damage is important by the time the diagnosis is made. With the purpose of establishing new biomarkers to detect AD in its early stages, we evaluated a set of 2D and 3D texture features extracted from MRI scans of the hippocampus of patients with advanced AD, early mild cognitive impairment and cognitive normality. Many 3D texture parameters resulted to be statistically significant to differentiate between AD patients and subjects from the other two populations. When combining these 3D parameters with machine learning techniques, high accuracy was obtained, thus suggesting that texture analysis could at least help identify the presence of AD.In the fourth project, we attempted to characterize the heterogeneity patterns of ischemic stroke in structural MRI. In brain MRI of older individuals, some pathological processes present similar imaging characteristics, like in the case of stroke lesions and white matter hyperintensities (WMH) of diverse natures, thus hindering the study of cerebrovascular diseases by means of imaging. Given that stroke effects are present not only in the affected region, but also in unaffected tissue, we investigated the feasibility of 3D texture features from WMH, normal-appearing white matter and subcortical structures to differentiate individuals who had a lacunar or cortical stroke visible on conventional brain MRI (T1-weighted, T2-weighted and FLAIR images) from subjects who did not. Texture features were not useful to differentiate between post-acute cortical and lacunar strokes, but promising results were achieved for discerning between patients presenting an old stroke and normal-ageing patients who never had a stroke. These results suggest that texture features may help in the detection of stroke lesions.This thesis presents four novel feasibility studies to help clinicians in the evaluation of different brain disorders by means of a radiomics approach based on texture analysis in conventional MRI. The results achieved highlight the potential of this practice for defining and characterizing brain lesions in a fast, reliable and non-invasive way. Abbreviations and Acronyms Brain and DiseasesAD Alzheimer's disease ADNI Alzheimer's Disease Neuroimaging Initiative BM brain metastasis CN cognitively normal, cognitive normality CNS central nervous system CSF cerebrospinal fluid EMCI early mild cognitive impairment GBM glioblastoma multiforme MCI mild cognitive impairment NAWM normal appearing white matter PNS peripheral nervous system SRS stereotactic radiosurgery SS subcortical structures SVD small vessel disease WBRT whole-brain radiotherapy WHO World Health Organization WMH white matter hyperintensities VIII Medical Imaging CAD computer-aided detection and diagnosis CT computed tomography FID free induction dec...