Brain Qualitative and Quantitative Radiological Biomarker Association with Cognitive Impairment and Dementia. Summary of the Doctoral Thesis
Bibliographic record
Abstract
Demographic changes in the population and timely diagnosis and treatment of neurodegenerative diseases are among the major challenges in Europe and the world in the 21st century. Within the framework of the dissertation, the possibilities of magnetic resonance (MR) examination are explored in analysing study participants with cognitive impairments. The aim of the study is to determine the relationship between qualitative and quantitative brain biomarkers and cognitive function in patients with cognitive impairments. The literature review section of the study examines the concept of cognitive impairment and dementia, commonly used cognitive tests, describes commonly used qualitative visual assessment scales, and evaluates the use of quantitative biomarkers in the diagnosis of cognitive impairments. The material section evaluates demographic indicators of participants, divides participants into groups, and evaluates differences between participant groups. In total, 81 participants were analysed, of which 24 had no cognitive impairment and 57 had various degrees of cognitive impairments assessed by the Montreal Cognitive Assessment (MoCA) scale. The methods section evaluates the application of statistical methods, including the Mann-Whitney U test, Kruskal-Wallis H test, post-hoc analysis, p-value correction after Bonferroni, Spearman correlation, principal component analysis. Results indicate that certain brain radiological biomarkers are associated with cognitive function outcomes, including both qualitative assessment scales and quantitative volume, cortical thickness, and white-matter fibre characteristic values. These identified relationships serve as the basis for further research on the use of quantitative radiological biomarkers in the diagnosis of cognitive impairment and to identify patients in the future who are at higher risk. In conclusion, the hypotheses that were defined during the work are confirmed – in the case of cognitive impairment and dementia, structural changes occur in the brain, which can be detected in MR images by performing a qualitative and quantitative analysis of brain structures, and cognitive impairment is associated with specific changes in the quantitative measures of the brain MR. Overall, MR examination can not only rule out large pathologies but also provide more extensive and detailed information on anatomical and structural changes in the brain that are essential for the diagnosis, control, and evaluation of interventions for cognitive impairment in the long term. 3.2 Clinical Medicine; Sub-Sector – Roentgenology and Radiology. Keywords: brain, radiological biomarkers, cognitive functions, dementia, magnetic resonance imaging. This research has been developed with financing from the European Social Fund and the Latvian state budget within the project No. 8.2.2.0/20/I/004 “Support for involving doctoral students in scientific research and studies” at Rīga Stradiņš University.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".